Managing microbially-mediated nitrogen cycling to
decrease risk of loss
from semi-arid rainfed agricultural soils
Louise Marjorie Fisk
Bachelor of Science (Technology), University of Waikato
This thesis is presented for the degree of
Doctor of Philosophy
(Soil Science and Plant Nutrition)
of The University of Western Australia
School of Earth and Environment, Faculty of Science
2015
ii
iii
Abstract
More efficient management of nitrogen (N) in agricultural soils is vital to maximise
food supply and minimise losses of N to the environment. Nitrification is a key pathway
of detrimental N loss, as nitrate and gaseous nitrous oxide are produced. In semi-arid
soils, N cycling and nitrification is not well understood during summer fallow, an
important period for N loss, as most research has instead focussed on N fertiliser
management during the growing season. In order to better understand and manage N
cycling in cropped semi-arid soils, this thesis investigated factors contributing to risk of
N loss, as well as possible solutions to decrease the risk of loss. The close link between
soil N and carbon (C) cycling suggested that solutions might be found through
management of soil organic matter. Soil was used from a long-term field site in the
northern grainbelt of Western Australia with a range of crop residue and tillage
treatments (no tillage; no tillage with burnt stubble; tillage; tillage plus additional crop
residue inputs; and tillage plus crop residues run-down) that altered soil organic matter
content since 2003, allowing examination of N transformation pathways without
confounding effects of differing soil types or climate.
Firstly, steady-state N transformations and risk of N loss (defined as gross nitrification:
immobilisation ratio) were examined, in response to a range of soil temperatures, root
exudate C and field treatment (tilled soil and tilled soil plus crop residues), using 15N
isotopic pool dilution and turnover of 14C-labelled substrates. Tilled soil plus crop
residues had 76% more total C than tilled soil. Root exudates were effective at
decreasing risk of N loss by stimulating microbial N immobilisation over nitrification.
Abstract
iv
In comparison, management of N loss through additional crop residue inputs was
unlikely to be effective, as increased soil organic matter enhanced the supply of both C
and N substrates and N cycling overall. At temperatures above 30 °C, net N
mineralisation was associated with decreased microbial C use efficiency, likely
contributing to increases in inorganic N pools during summer fallow.
Seasonal variation in ammonia-oxidising microorganisms and their relationships to
other soil biogeochemical properties (microbial biomass C, dissolved organic C,
ammonium, nitrate and potentially mineralisable N) were then investigated in all five
field treatments that were sampled on ten occasions over a two year period. Bacterial
and archaeal amoA gene abundances were measured by quantitative real-time
polymerase chain reaction at these time points. Ammonia-oxidising bacteria regulated
nitrification in the surface of this soil rather than ammonia-oxidising archaea.
Collaborative research supported this conclusion: abundance of ammonia-oxidising
bacteria was greater in surface soil (0–10 cm) than in subsoil (10–90 cm) and was
correlated to gross nitrification, while abundance of ammonia-oxidising archaea was
greater in subsoil than in surface soil and had no relationship to gross nitrification.
Growth of ammonia-oxidising bacteria was correlated to increased nitrate pools during
summer fallow, potentially increasing the risk of N loss by leaching in the first rains of
the following growing season.
A nitrification inhibitor, nitrapyrin, was evaluated for its ability to control nitrification
of N released from soil organic matter mineralisation at high soil temperature (20 and
40 °C), in tilled soil or tilled soil plus crop residues. The soil was wet-up from dry and
subsequently either held at optimal water content, or allowed to dry. Nitrapyrin
Abstract
v
successfully inhibited nitrification by 86% at 40 °C, illustrating the potential to decrease
risk of N loss outside the cropping period.
The thesis findings highlight that risk of N loss from this semi-arid rainfed agricultural
soil is primarily related to variation in rainfall, temperature, supply of C and N
substrates (especially in relation to crop rhizodeposition or lack thereof during fallow
periods), and abundance of ammonia-oxidising bacteria. Ammonia-oxidising archaea
were not important regulators of nitrification. Further investigation is required to find
other methods of controlling the risk of N loss from semi-arid rainfed agricultural soils,
including whether nitrapyrin is effective at inhibiting nitrification under field conditions
during summer fallow. Nevertheless, the findings of this thesis imply that there are
limited options for management of N loss during summer in the current annual cropping
system, due to the predominant influence of climate on N cycling and lack of plants at
the time of maximum inorganic N production.
vi
For Robbie
We did not come to remain whole.
We came to lose our leaves like the trees,
The trees that are broken
And start again, drawing up on great roots
Robert Bly
vii
Acknowledgements
“Data, things are only impossible until they’re not.”
Captain Jean-Luc Picard, Star Trek Next Generation 1.17
They say that doing a PhD is 10% intelligence and 90% persistence, but I would say
that somewhere in there at least half depends on other people’s kindness and support. I
gratefully thank my supervisors, Prof. Dan Murphy, Assoc. Prof. Louise Barton and Dr
Linda Maccarone. I appreciate collaboration from Prof. Davey Jones and Dr Helen
Glanville of Bangor University, Wales. Thank you to Yoshi Sawada, Richard Bowles,
Ian Waite, Chris Swain, Hazel Gaza, Xiaodi Li, Michael Smirk and Darryl Roberts for
laboratory and field assistance, Laura Firth and Marty Firth for statistical advice, and
members of the Soil Biology and Molecular Ecology Group and Soil Science admin
staff for thoughts and support.
Special thanks to the UWA Graduate Education Officers, particularly Krystyna Haq, for
skills and inspiration. And finally, thank you to my Australian friends and family for
perspective, encouragement and sanity: Jane, Jane, Linda and Ken, Bel, Scott, Glenn,
Stuart, Heath, Malin, Katrina, Emielda, Georgie, Rupy, Nian, Bede, Andy, Tony, Dan,
Stuart, Leon, Steve, Grace, Andy, Kikki and Jack.
This research was part of the Grains Research and Development Corporation’s Soil
Biology Initiative II (UWA00139) and was also funded by the Australian Research
Council and the Australian Government. Financial support for my candidature was
Acknowledgements
viii
provided by an Australian Postgraduate Award, The University of Western Australia,
and the School of Earth and Environment, UWA. Greg Wells and Dow AgroSciences
donated a sample of nitrapyrin and CSIRO provided rainfall and temperature data. This
research was made possible by the support of the Liebe Group, who manage the Long-
Term Soil Biology Trial site.
ix
Statement of Candidate Contribution
In accordance with The University of Western Australia’s regulations regarding
Research Higher Degrees, this thesis is presented as a series of journal papers, some of
which have been co-authored. The bibliographic details of the papers and where they
appear in the thesis are outlined below, with the contribution of the candidate and co-
authors in parentheses.
(i) Fisk, L.M. (70%), Barton, L. (10%), Jones, D.L. (5%), Glanville, H.C. (5%) &
Murphy, D.V. (10%), 2015. Root exudate carbon mitigates nitrogen loss in a semi-arid
soil. Soil Biology & Biochemistry, 88, 380-389. doi:10.1016/j.soilbio.2015.06.011
Appears as Chapter 3.
(ii) Fisk, L.M. (70%), Barton, L. (10%), Maccarone, L.D. (10%) & Murphy, D.V.
(10%). Seasonal dynamics of ammonia-oxidising bacteria but not archaea influence risk
of nitrogen loss in a semi-arid agricultural soil. Manuscript in preparation.
Appears as Chapter 4.
(iii) Fisk, L.M. (60%), Maccarone, L.D. (20%), Barton, L. (10%), & Murphy, D.V.
(10%), 2015. Nitrapyrin decreased nitrification of nitrogen released from soil organic
matter but not amoA gene abundance at high soil temperature. Soil Biology &
Biochemistry, 88, 214-223. doi:10.1016/j.soilbio.2015.05.029
Appears as Chapter 5.
Statement of Candidate Contribution
x
(iv) Banning, N.C. (30%), Maccarone, L.D. (30%), Fisk, L.M. (10%) & Murphy, D.V.
(30%), 2015. Ammonia-oxidising bacteria not archaea dominate nitrification activity in
semi-arid agricultural soil. Scientific Reports, 5. doi:10.1038/srep11146
Appears as Appendix A.
We hereby declare that all authors have granted permission to the candidate (Louise
Fisk) to use the results presented in these publications.
Candidate
Signature _________________________________________ Date _______________
Name ________________________________
Coordinating Supervisor
Signature _________________________________________ Date _______________
Name ________________________________
xi
Table of Contents
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .vii
Statement of candidate contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xvii
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxi
Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxiii
Chapter 1.
Introduction 1.1. Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1
1.2. Research gaps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3
1.3. This work: Objectives and outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6
Chapter 2.
Nitrogen loss from semi-arid rainfed agricultural soils 2.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11
2.2. Rainfed arable agriculture in semi-arid regions . . . . . . . . . . . . . . . . . . . . . . . . . . .12
2.3. Rainfed arable agriculture in the semi-arid region of south-western Australia . . .14
2.4. Soil nitrogen cycle and environmentally detrimental loss . . . . . . . . . . . . . . .16
2.4.1. The soil nitrogen cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .16
2.4.2. Nitrate in semi-arid soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19
2.4.3. Nitrous oxide emissions from semi-arid soils . . . . . . . . . . . . . . . . . . . . .20
2.4.4. Tools to predict the risk of nitrogen loss . . . . . . . . . . . . . . . . . . . . .26
2.5. Factors controlling risk of nitrogen loss through microbially-mediated soil
nitrogen transformations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27
2.5.1. Soil water and wetting-drying cycles . . . . . . . . . . . . . . . . . . . . . . . . . . .29
2.5.2. Soil temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33
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xii
2.5.3. Availability of carbon and nitrogen substrates . . . . . . . . . . . . . . . . . . . . .35
2.5.4. Soil pH and liming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .38
2.5.5. Relationships between plants and nitrogen cycling microorganisms . . .40
2.6. Molecular ecology of nitrifiers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .42
2.6.1. Ammonia-oxidising bacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .42
2.6.2. Ammonia-oxidising archaea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43
2.6.3. Niche differentiation between ammonia-oxidising bacteria and archaea
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .45
2.6.4. Nitrite-oxidising bacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .46
2.6.5. Heterotrophic nitrification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .47
2.7. Approaches to limiting nitrogen losses from semi-arid soils . . . . . . . . . . . . . . .48
2.7.1. Nitrification inhibitors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .50
2.7.2. Nitrapyrin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .51
2.8. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55
Chapter 3.
Root exudate carbon was more effective than soil organic carbon at
decreasing the risk of nitrogen loss in a semi-arid soil 3.1. Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .57
3.2. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .59
3.3. Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61
3.3.1. Study site and field soil collection . . . . . . . . . . . . . . . . . . . . . . . . . . .61
3.3.2. Laboratory experimental design . . . . . . . . . . . . . . . . . . . . . . . . . . .63
3.3.3. Peptide and amino acid turnover . . . . . . . . . . . . . . . . . . . . . . . . . . .65
3.3.4. Modelling 14C dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .66
3.3.5. Gross N transformation rates and inorganic N . . . . . . . . . . . . . . . . . . . . .67
3.3.6. Modelling N transformation rates . . . . . . . . . . . . . . . . . . . . . . . . . . .70
3.3.7. Nitrous oxide analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70
3.3.8. Statistical analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70
3.4. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .71
3.4.1. Soil organic matter turnover (N supply) . . . . . . . . . . . . . . . . . . . . .71
3.4.2. Nitrogen transformation rates and inorganic N pools . . . . . . . . . . . . . . .73
3.4.3. Fate of inorganic N . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .77
3.5. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .78
Table of Contents
xiii
3.5.1. Sources of soil organic C to decrease the risk of N loss . . . . . . . . .78
3.5.2. Inorganic N accumulates at high soil temperature . . . . . . . . . . . . . . .80
3.5.3. Differences between amino acid and peptide turnover . . . . . . . . . . . . . . .81
3.5.4. Implications for semi-arid environments . . . . . . . . . . . . . . . . . . . . .82
3.6. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .83
Chapter 4.
Seasonal dynamics of ammonia-oxidising bacteria but not archaea
influence risk of nitrogen loss in a semi-arid agricultural soil 4.1. Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .85
4.2. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .87
4.3. Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .90
4.3.1. Study site and soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .90
4.3.2. Experimental design and soil collection . . . . . . . . . . . . . . . . . . . . .93
4.3.3. Microbial biomass C and dissolved organic C . . . . . . . . . . . . . . . . . . . . .94
4.3.4. Inorganic N analysis and potentially mineralisable N . . . . . . . . . . . . . . .95
4.3.5. Nucleic acid extraction and qPCR . . . . . . . . . . . . . . . . . . . . . . . . . . .95
4.3.6. Statistical analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .97
4.4. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .98
4.4.1. Environmental conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .98
4.4.2. Microbial biomass C and dissolved organic C . . . . . . . . . . . . . . . . . . . . .98
4.4.3. Inorganic N and potentially mineralisable N . . . . . . . . . . . . . . . . . . . .100
4.4.4. Ammonia oxidiser gene abundance . . . . . . . . . . . . . . . . . . . . . . . . . .102
4.4.5. Relationships between bacterial amoA gene abundance and other
variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .103
4.5. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .108
4.6. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .113
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Chapter 5.
Nitrapyrin decreased nitrification of nitrogen released from soil organic
matter but not amoA gene abundance at high soil temperature 5.1. Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .115
5.2. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .117
5.3. Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .120
5.3.1. Soil and soil collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .120
5.3.2. Laboratory experimental design . . . . . . . . . . . . . . . . . . . . . . . . . .121
5.3.3. Gross N transformation rates and inorganic N analysis . . . . . . . .122
5.3.4. Calculation of gross N transformation rates . . . . . . . . . . . . . . . . . . . .124
5.3.5. Nucleic acid extraction and qPCR . . . . . . . . . . . . . . . . . . . . . . . . . .124
5.3.6. Statistical analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .125
5.4. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .126
5.4.1. Recovery of 15N . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .126
5.4.2. Water-filled pore space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .127
5.4.3. Labelled ammonium and nitrate-N . . . . . . . . . . . . . . . . . . . . . . . . . .127
5.4.4. Unlabelled inorganic N . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .130
5.4.5. Gross N transformation rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .133
5.4.6. Bacterial and archaeal amoA gene abundance . . . . . . . . . . . . . . . . . . . .135
5.5. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .136
5.6. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .140
Chapter 6.
General discussion 6.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .141
6.2. Contributing factors to variation in risk of nitrogen loss from semi-arid
rainfed agricultural soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .142
6.2.1. Variation in rainfall and temperature . . . . . . . . . . . . . . . . . . . . . . . . . .142
6.2.2. Root exudate carbon inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .144
6.2.3. The importance of surface soil layers . . . . . . . . . . . . . . . . . . . . . . . . . .147
6.3. Management of semi-arid soils to decrease risk of nitrogen loss outside the
growing season . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .150
6.3.1. Crop residue inputs and increased soil organic matter . . . . . . . . . . . . . .150
6.3.2. Nitrapyrin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .151
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6.4. Future research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .153
6.4.1. Further unravelling the interactions between ammonia oxidisers and
N loss . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .153
6.4.2. Field application of nitrapyrin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .158
6.4.3. Other methods to manage risk of nitrogen loss . . . . . . . . . . . . . .160
6.5. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .162
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .167
Appendices Appendix A. Ammonia-oxidising bacteria not archaea dominate nitrification
activity in semi-arid agricultural soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .201
Supplementary information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .222
Appendix B. Data not shown in Chapter 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .225
Appendix C. Data not shown in Chapter 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .227
Appendix D. Data not shown in Chapter 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .229
Appendix E. Publications arising from this thesis . . . . . . . . . . . . . . . . . . . . . . . . . .231
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xvii
List of Figures
Chapter 2.
2.1. Arid regions of the world . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12 2.2. World distribution of Mediterranean-type climates . . . . . . . . . . . . . . . . . . . . .13 2.3. A simplified soil nitrogen cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17 2.4. Conceptual nutrient release from high quality (High Q), low quality (Low Q)
and a mixture of organic materials in relation to plant uptake . . . . . . . . .50
2.5. Structure of nitrapyrin, 2-chloro-6-(trichloromethyl)-pyridine . . . . . . . . .52
Chapter 3.
3.1. Daily maximum and minimum soil temperatures at 5 cm depth and daily
rainfall for 2011 at the research site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .62
3.2. Influence of temperature on microbial carbon use efficiencies of (a) 14C-
labelled peptides without root exudates; (b) 14C-labelled peptides with root
exudates; (c) 14C-labelled amino acids without root exudates; and (d) 14C-
labelled amino acids with root exudates . . . . . . . . . . . . . . . . . . . . . . . . . . .72
3.3. Influence of temperature on half-lives of pool a1 of (a) 14C-labelled peptides
without root exudates; (b) 14C-labelled peptides with root exudates; (c) 14C-
labelled amino acids without root exudates; and (d) 14C-labelled amino acids
with root exudates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .73 3.4. Influence of temperature after seven days of incubation on (a) gross N
mineralisation without root exudates; (b) gross N mineralisation with root
exudates; and influence of temperature over seven days of incubation on (c)
net N mineralisation without root exudates and (d) net N mineralisation with
root exudates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .75
List of Figures
xviii
3.5. Influence of temperature on (a) gross nitrification without root exudates; (b)
gross nitrification with root exudates; (c) gross N immobilisation without root
exudates; (d) gross N immobilisation with root exudates; (e) N:I ratio without
root exudates; and (f) N:I ratio with root exudates . . . . . . . . . . . . . . . . . . . . .76 3.6. Influence of temperature after seven days of incubation on (a) NH4
+-N; and
(b) NO3--N . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .77
3.7. Influence of temperature on (a) N2O flux over 24 h; and (b) N2O 15N
enrichment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .78
Chapter 4.
4.1. (a) Daily rainfall (bar graph, left y-axis) and daily soil minimum and
maximum temperature at 5 cm depth (line graph, right y-axis) measured at
the study site. (b) Soil water content at time of sample collection . . . . . . . . .91 4.2. Change in (a) microbial biomass carbon; and (b) dissolved organic carbon
through time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .99
4.3. Change in (a) total inorganic nitrogen; (b) NH4+-N; (c) NO3
--N; and (d)
potentially mineralisable nitrogen through time . . . . . . . . . . . . . . . . . . . .101 4.4. Change in bacterial amoA gene abundance (AOB) through time . . . . . . . .102 4.5. Significant linear regression relationships between logged bacterial amoA
gene abundance (logAOB) and (a) logged dissolved organic carbon
(logDOC); (b) logged microbial biomass carbon (logMBC); and (c) square
root transformed nitrate concentration (sqrtNO3-) . . . . . . . . . . . . . . . . . . . .105
4.6. Principal component analysis biplot of principal components 1 (PC1) and 2
(PC2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .106
Chapter 5.
5.1. Change in total recovery of 15N (% of applied 15N) through time from soil
applied with (a) 15N-labelled NH4+ and (b) 15N-labelled NO3
- . . . . . . . .128 5.2. Change in water-filled pore space (% WFPS) through time (a) at 20 °C; and
(b) at 40 °C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .128
List of Figures
xix
5.3. Change in 15N-labelled nitrate (NO3-) above natural abundance through time
with added 15(NH4)2SO4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .129 5.4. Change in unlabelled inorganic N through time at 40 °C . . . . . . . . . . . . . .131 5.5. Change in unlabelled inorganic N through time at 20 °C . . . . . . . . . . . . . .132 5.6. Change in gross N mineralisation and nitrification rates through time . .134 5.7. Change in bacterial amoA gene abundance (AOB) through time . . . . . . . .136
List of Figures
xx
xxi
List of Tables
Chapter 1.
1.1. Research aims and hypotheses addressed in each thesis chapter . . . . . . . . . .8
Chapter 2.
2.1. Nitrate leaching rates observed in semi-arid climates with winter dominant
rainfall . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22 2.2. Nitrous oxide emissions observed in semi-arid climates with winter dominant
rainfall . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24 2.3. Common agricultural nitrification inhibitors . . . . . . . . . . . . . . . . . . . . . . . . . . .51
Chapter 3.
3.1. Properties of field trial soils (0–10 cm depth) collected eight years after soil
organic carbon management treatments were imposed . . . . . . . . . . . . . . .64
Chapter 4.
4.1. Properties of field organic matter treatments (0–10 cm depth) at start of
present study, seven years after treatments were imposed . . . . . . . . . . . . . . .92
4.2. Linear regression results for response of logged bacterial amoA gene
abundance to each soil and environmental variable separately . . . . . . . .104
4.3. Eigenvector loadings of principal components 1–6 . . . . . . . . . . . . . . . . . . . .107 4.4. Loadings matrix (eigenvectors) for principal components 1–6. . . . . . . . .108
List of Tables
xxii
Chapter 5.
5.1. Properties of field soils (0–10 cm depth), collected nine years after soil
organic matter (OM) treatments were imposed . . . . . . . . . . . . . . . . . . . .121
Chapter 6.
6.1. Specific thesis questions as set out in Chapter 1, the chapter in which each
question was answered, related hypotheses and answers . . . . . . . . . . . . . .164
xxiii
Abbreviations
ANOVA analysis of variance
AMO ammonia monooxygenase
AOA ammonia-oxidising archaea
AOB ammonia-oxidising bacteria
BSA bovine serum albumin
C carbon
CARD-FISH catalysed reporter deposition-fluorescent in situ hybridisation
CO2 carbon dioxide
DCD dicyandiamide
DGGE denaturing gradient gel electrophoresis
DMPP 3, 4-dimethylpyrazole phosphate
DNA deoxyribonucleic acid
DNRA dissimilatory nitrate reduction to ammonium
DOC dissolved organic carbon
DRY soil wet-up to 45% water-filled pore space from dry, then subsequently
allowed to dry (laboratory treatment)
EC electrical conductivity
FISH fluorescent in situ hybridisation
HAO hydroxylamine oxidoreductase
HNO nitroxyl
IRMS isotope ratio mass spectrometer
KNO3 potassium nitrate
K2SO4 potassium sulphate
LFOM light fraction organic matter
LMWOM low molecular weight organic matter
MBC microbial biomass carbon
MIT mineralisation-immobilisation turnover
mRNA messenger ribonucleic acid
N nitrogen
Abbreviations
xxiv
N2 dinitrogen gas
NanoSIMS nano-scale secondary ion mass spectrometry
NaOH sodium hydroxide
NH3 ammonia
NH4+ ammonium
(NH4)2SO4 ammonium sulphate
N:I ratio ratio of gross nitrification to gross nitrogen immobilisation
NO nitric oxide
N2O nitrous oxide
NO2- nitrite
NO3- nitrate
NOB nitrite-oxidising bacteria
No RE no synthetic root exudates (laboratory treatment)
NXR nitrite oxidoreductase
OM organic matter
OWC soil wet-up to 45% water-filled pore space from dry, then subsequently
held at optimal water content (45% water-filled pore space) (laboratory
treatment)
PC1 principal component 1
PC2 principal component 2
PCA principal component analysis
PCR polymerase chain reaction
P/Etp ratio of precipitation to potential evapotranspiration
PMN potentially mineralisable nitrogen
qPCR quantitative real-time polymerase chain reaction
+RE plus synthetic root exudates (laboratory treatment)
RNA ribonucleic acid
rRNA ribosomal ribonucleic acid
SEM standard error of the mean
SIP stable isotope probing
SOC soil organic carbon
TukeyHSD Tukey’s honest significant difference test
WFPS water-filled pore space
1
Chapter 1.
Introduction
1.1. Background
Present-day agriculture is experiencing unprecedented pressure to provide food for the
growing global population, without degradation of the environment. Anthropogenic
harnessing of the nitrogen (N) cycle, largely for food production, annually converts
around 210 million tonnes of N from the atmosphere into reactive N forms, or half of
the total estimated N fixation by all biogeochemical processes combined (Fowler et al.,
2013; Rockström et al., 2009). This reactive N is also a major source of environmental
pollution, contributing to problems ranging from eutrophication and acidification to
global warming (Gruber and Galloway, 2008). Efficient management of N in agriculture
is therefore essential for sustainable food production while minimising harmful effects
on the environment. The central relationship that determines whether N is helpful or
harmful is ‘synchrony’: how well N supply in soil matches crop N demand (Crews and
Peoples, 2005). Nitrogen supply from fertiliser application or organic matter (OM)
mineralisation that does not match either the timing or amount of crop N demand can
accumulate in soil and has potential to be lost.
Environmentally detrimental N losses from semi-arid rainfed agricultural soils occur
primarily by nitrate (NO3-) leaching or gaseous N emissions such as nitrous oxide (N2O)
Ch. 1: Introduction
2
and nitric oxide (NO). Other losses that may occur include soil erosion by water or wind
and ammonia (NH3) volatilisation, although this is not usually a major loss pathway
from acidic soil (Ryan et al., 2009). Nitrate leaching negatively impacts groundwater
and surface water by encouraging growth of algae and causing eutrophication,
acidification and decreased water quality (Di and Cameron, 2002; Peoples et al., 2004).
Nitrous oxide and NO are also detrimental to the environment because N2O is a
greenhouse gas that contributes to global warming and depletion of stratospheric ozone,
while NO is highly reactive in the troposphere, causing acid rain and forming ozone
(Galbally et al., 2008; Peoples et al., 2004). Nitrate leaching, N2O and NO emissions are
a consequence of nitrification either directly or indirectly: directly, because nitrification
is the pathway whereby inorganic ammonium (NH4+) is converted to NO3
-, with N2O
and NO sometimes formed as a by-product; and indirectly, because N2O and NO can
also be formed during denitrification, when NO3- is further converted to dinitrogen gas
(N2; Medinets et al., 2015; Wrage et al., 2001). Microbially-mediated nitrification
therefore plays a key role in N loss processes, and can be considered as the ‘gatekeeper’
between internal soil cycling and external N loss (Schimel et al., 2005).
Management of N in rainfed agricultural soils of semi-arid regions presents particular
challenges. Rainfed agriculture relies on natural rainfall patterns to provide water to
crops without irrigation. In semi-arid regions, annual precipitation is only 20–50% of
potential evapotranspiration and is highly variable between seasons and years, which
makes rainfed crop production inherently risky and uncertain (Harrington and Tow,
2011; UNESCO, 1979). Nutrient cycling and biological activity in semi-arid soils is
governed by pulses in soil water availability due to sporadic rainfall events, and
microbial activity can be particularly intense when temperatures are elevated (Austin et
al., 2004; Belnap et al., 2005; Noy-Meir, 1973). Emerging research indicates that N
Ch. 1: Introduction
3
cycling in water-limited soil behaves differently to when moisture is plentiful and
predictable (Collins et al., 2008). For example, N2O emissions worldwide are
predominantly in response to N fertiliser applications (Reay et al., 2012), but a large
proportion of N2O and NO emissions in semi-arid regions are due to wetting of hot, dry
soil, as occurs during summer and autumn fallow (Galbally et al., 2008). In addition,
microbial biomass, net N mineralisation and potential nitrification and denitrification
rates were greater in a semi-arid Californian shrubland soil during the dry summer than
during the winter growing season (Parker and Schimel, 2011). Plant productivity is
often more limited by lack of water than is microbial activity, so crop uptake is often
uncoupled from N supply by OM mineralisation (Angus, 2001; Collins et al., 2008).
This asynchrony is particularly pronounced in rainfed annual cropping systems: most
crop plants are only present for 12–16 weeks, and take up N in large amounts for only
about three to four weeks of this period (Olson and Kurtz, 1982; Robertson, 1997).
Maximum crop N uptake though can be very rapid, at approximately 4 kg N ha-1 day-1
for wheat during the grand period of vegetative growth (Olson and Kurtz, 1982).
However, OM mineralisation still occurs outside the cropping period: gross N
mineralisation rates can be as high as 6.8 kg N ha-1 in the 24 hours after wetting of dry
soil (Murphy et al., 1998b). This inorganic N that is produced outside the growing
season does not match the timing of crop N demand, so is at risk of loss.
1.2. Research Gaps
The challenge is to find management practices that can reduce the risk of N loss outside
the growing season in semi-arid soils. This might be achieved by management of
microbial N transformations to decrease N supply or prevent nitrification, or to capture
excess NO3- before it is lost (Crews and Peoples, 2005). In order to find techniques for
Ch. 1: Introduction
4
preventing N loss from semi-arid soils, we need to better understand the influence of
different environmental and biogeochemical factors on N transformation rates and
microbial populations. These factors include soil water and temperature, carbon (C) and
N substrate availability and soil pH (Booth et al., 2005; Sahrawat, 2008).
Variation in populations of ammonia-oxidising bacteria (AOB) and archaea (AOA) is
likely a factor regulating risk of N loss in soil. Ammonia oxidation is the first, limiting
step of nitrification, and is carried out by AOA and AOB that convert ammonia (in
equilibrium with NH4+) to nitrite (NO2
-; Hatzenpichler, 2012; Kowalchuk and Stephen,
2001). The key enzyme of ammonia oxidation in bacteria is ammonia monooxygenase
(AMO), the active site of which is coded for by the amoA gene (Kowalchuk and
Stephen, 2001). Chemolithoautotrophic bacteria were thought to be the sole organisms
carrying out ammonia oxidation, until the discovery of homologous gene sequences for
amoA in marine Crenarchaeota (Treusch et al., 2005; Venter et al., 2004). Since then
AOA have been found to be ubiquitous in marine, freshwater and terrestrial
environments and have been placed in the newly-described archaeal phylum,
Thaumarchaeota (Brochier-Armanet et al., 2008; Pester et al., 2011). Relative
abundances of AOA and AOB vary widely between soils in different environments, as
does evidence for their contributions to nitrifying activity (for example Adair and
Schwartz, 2008; Di et al., 2009; Gubry-Rangin et al., 2010; Jia and Conrad, 2009).
Niche specialisation and differentiation between these two groups of microorganisms
however has not been clearly defined, despite the ongoing search for regulating factors
(that might include soil pH or NH4+ availability; Prosser and Nicol, 2012). Nor is it well
understood what factors regulate seasonal variation in AOA and AOB abundances and
activity, particularly in semi-arid environments (Adair and Schwartz, 2008; Sher et al.,
Ch. 1: Introduction
5
2013). These factors that regulate ammonia-oxidising microorganisms may have
consequent effects on nitrification rates and risk N loss.
One way to capture excess inorganic N is to stimulate microbial N immobilisation by
increasing C availability in soil. Soil N cycling is tightly coupled to C cycling, as a
direct result of living organisms requiring both of these elements to build biomass at a
molecular level (Sterner and Elser, 2002). The majority of nitrifiers in agricultural soils
are considered to be autotrophs, which use inorganic N substrates from soil to generate
energy but fix their own C from carbon dioxide (CO2; De Boer and Kowalchuk, 2001;
Kurakov et al., 2001). Mineralising and immobilising microorganisms on the other hand
are heterotrophs: they need organic C from soil as an energy source. Soil OM and C
availability is generally low in semi-arid soils, due to low plant productivity, soil loss by
erosion, low rainfall and elevated temperatures (Archibold, 1995; Jenny, 1941; Ryan,
2011). Carbon in soil can be altered by long-term agricultural practices such as tillage
and OM inputs, or by short-term C inputs from plant root exudates (Dick, 1992; Jones
et al., 2004a). However, the impact of increased C availability on risk of N loss in semi-
arid agricultural soils has not been fully investigated.
Nitrification inhibitors also have potential to control the risk of N loss in semi-arid
agricultural soils. These chemicals inhibit nitrification, often by deactivating one of the
enzymes involved (McCarty, 1999). Nitrification inhibitors such as nitrapyrin have been
used successfully for many years to decrease nitrification and N loss of applied
fertiliser, particularly in cooler climates (Slangen and Kerkhoff, 1984; Wolt, 2004).
However, the applicability of nitrification inhibitors under semi-arid conditions has not
been investigated, particularly for the purpose of controlling nitrification of NH4+
Ch. 1: Introduction
6
released by OM decomposition at elevated temperatures (as occurs during summer
fallow).
In summary, management of N cycling in semi-arid rainfed agricultural soils presents a
challenge, as asynchrony of N supply is inherent in the water-limited environment.
Mineralisation of OM and crop residues outside the growing season is a major source of
inorganic N, at a time of minimal plant uptake. Therefore, tools to decrease the risk of N
loss need to be identified for this period, and might be discovered through an increased
understanding of N cycling and microbial population dynamics.
1.3. This Work: Objectives and Outline
The objective of this thesis is to gain a better understanding of N cycling in semi-arid
rainfed agricultural soils, through investigating the factors contributing to variation in
risk of N loss, and possible management solutions to decrease the risk of N loss.
In order to address this objective, this research specifically aimed to answer the
following questions:
1. What environmental and biochemical factors contribute to temporal variation in
risk of N loss? (Chapters 3 and 4)
2. How do total soil C and root exudate C affect N cycling and risk of loss? (Chapter
3)
3. How do ammonia-oxidising populations vary with season, depth and agricultural
management? (Chapters 4 and 5, Appendix A)
4. How are ammonia-oxidising populations related to other soil environmental and
biochemical factors? (Chapters 4, Appendix A)
Ch. 1: Introduction
7
5. Does increasing soil total C through additional crop residue inputs decrease the risk
of N loss? (Chapter 3)
6. Does the nitrification inhibitor nitrapyrin decrease risk of loss of NH4+ produced by
OM mineralisation under temperature and water availability conditions that may
occur during summer? (Chapter 5)
Overarching hypotheses for this thesis in relation to the aims listed above are:
1. Temporal variation in risk of N loss in semi-arid rainfed agricultural soil is related
to water availability (rainfall and soil water content) soil temperature and soil C
availability (total soil organic C and labile root exudate C).
2. Increasing total soil organic C and root exudate C will increase soil C availability
and enable heterotrophic microorganisms to compete more successfully over
autotrophic nitrifiers, thus increasing N immobilisation and decreasing the risk of N
loss.
3. Ammonia-oxidising population abundance (both AOA and AOB) will be greater
during the winter growing season than during summer fallow; will decrease with
depth as N substrates diminish; will be enhanced by additional crop residue inputs
and no tillage; but will be decreased by tillage and stubble burning.
4. Ammonia-oxidising population abundance will be positively related to rainfall, soil
water content, microbial biomass C (MBC) and NO3- concentrations, negatively
related to soil temperature, dissolved organic C (DOC) and total soil C but not
related to NH4+ concentrations.
5. Increasing total soil C through additional crop residue inputs will decrease the risk
of N loss.
6. The nitrification inhibitor nitrapyrin will decrease risk of loss of NH4+ produced by
OM mineralisation under conditions that may occur during summer.
Tabl
e 1.
1. R
esea
rch
aim
s and
hyp
othe
ses a
ddre
ssed
in e
ach
thes
is ch
apte
r.
The
sis C
hapt
er a
nd T
itle
Res
earc
h A
ims
Hyp
othe
ses
Cha
pter
3.
Roo
t exu
date
car
bon
was
mor
e ef
fect
ive
than
soil
orga
nic
carb
on a
t dec
reas
ing
the
risk
of n
itrog
en lo
ss in
a se
mi-a
rid so
il.
To u
nder
stand
how
diff
eren
t sou
rces
of C
alte
r N tr
ansf
orm
atio
ns in
arab
le se
mi-a
rid so
il.
Spec
ifica
lly, h
ow to
tal s
oil o
rgan
ic C
ver
sus r
oot e
xuda
te C
affe
cted
:
N
dec
ompo
sitio
n pa
thw
ays;
and
th
e su
bseq
uent
fate
of N
and
risk
of N
loss
as d
efin
ed b
y th
e
nitri
ficat
ion
to im
mob
ilisa
tion
(N:I
) rat
io,
unde
r con
ditio
ns re
flect
ive
of b
oth
sum
mer
and
win
ter c
ondi
tions
in
sem
i-arid
soils
.
Incr
easin
g so
il C
ava
ilabi
lity
(bot
h to
tal s
oil o
rgan
ic C
and
root
exud
ate
C) w
ill d
ecre
ase
the
pote
ntia
l for
N lo
ss (i
.e.
decr
ease
the
N:I
ratio
), es
peci
ally
at t
empe
ratu
res g
reat
er
than
30
°C.
Cha
pter
4.
Seas
onal
dyn
amic
s of a
mm
onia
-oxi
disin
g
bact
eria
but
not
arc
haea
influ
ence
risk
of
nitro
gen
loss
in a
sem
i-arid
agr
icul
tura
l
soil.
To im
prov
e un
ders
tand
ing
of te
mpo
ral p
opul
atio
n dy
nam
ics o
f
amm
onia
oxi
dise
rs so
as t
o be
tter u
nder
stand
N lo
ss m
echa
nism
s in
sem
i-arid
env
ironm
ents
dom
inat
ed b
y w
inte
r rai
nfal
l. Sp
ecifi
cally
:
ho
w so
il O
M c
onte
nt a
ffect
s am
mon
ia o
xidi
ser a
bund
ance
;
if
incr
ease
d so
il O
M m
odifi
es se
ason
al v
aria
tion
in a
mm
onia
oxid
iser
abu
ndan
ce; a
nd
w
hich
soil
envi
ronm
enta
l and
bio
chem
ical
fact
ors r
egul
ate
the
rela
tive
abun
danc
e of
AO
B an
d A
OA
.
Am
mon
ia-o
xidi
sing
bact
eria
will
dom
inat
e ov
er A
OA
in th
e
surf
ace
soil
thro
ugho
ut th
e ye
ar.
Incr
ease
d so
il O
M c
onte
nt w
ill in
crea
se a
mm
onia
oxi
dise
r
abun
danc
e.
Seas
onal
var
iatio
n in
am
mon
ia o
xidi
ser a
bund
ance
will
be
rela
ted
to ra
infa
ll, so
il w
ater
con
tent
, tem
pera
ture
and
NO
3-
conc
entra
tions
but
not
to N
H4+ c
once
ntra
tions
.
Tabl
e 1.
1. c
ontin
ued
on n
ext p
age.
Tabl
e 1.
1. R
esea
rch
aim
s and
hyp
othe
ses a
ddre
ssed
in e
ach
thes
is ch
apte
r (c
ontin
ued)
. T
hesi
s Cha
pter
and
Titl
e R
esea
rch
Aim
s H
ypot
hese
s C
hapt
er 5
.
Nitr
apyr
in d
ecre
ased
nitr
ifica
tion
of
nitro
gen
rele
ased
from
soil
orga
nic
mat
ter
but n
ot a
moA
gen
e ab
unda
nce
at h
igh
soil
tem
pera
ture
.
To e
xam
ine
the
pote
ntia
l of t
he n
itrifi
catio
n in
hibi
tor n
itrap
yrin
to
cont
rol n
itrifi
catio
n at
ele
vate
d so
il te
mpe
ratu
re in
resp
onse
to a
sim
ulat
ed ra
infa
ll w
ettin
g an
d dr
ying
eve
nt. S
peci
fical
ly:
w
heth
er n
itrap
yrin
dec
reas
ed g
ross
nitr
ifica
tion
rate
s
with
out a
lterin
g ot
her N
tran
sfor
mat
ion
rate
s at 2
0 an
d 40
°C;
w
heth
er in
crea
sed
soil
OM
con
tent
dim
inish
es th
e ab
ility
of
nitra
pyrin
to in
hibi
t nitr
ifica
tion
at e
leva
ted
tem
pera
ture
;
w
heth
er d
ecre
asin
g w
ater
con
tent
with
tim
e (a
s occ
urs w
hen
soil
drie
s afte
r a su
mm
er ra
infa
ll ev
ent)
incr
ease
s the
abi
lity
of n
itrap
yrin
to in
hibi
t nitr
ifica
tion
com
pare
d to
whe
n so
il
wat
er c
onte
nt is
opt
imal
; and
if po
pula
tions
of A
OB
or A
OA
are
con
sequ
ently
affe
cted
.
Nitr
apyr
in w
ill m
ore
effe
ctiv
ely
inhi
bit n
itrifi
catio
n at
elev
ated
tem
pera
ture
s in
a lo
w O
M so
il co
mpa
red
to w
here
addi
tiona
l cro
p re
sidu
e in
puts
have
incr
ease
d so
il O
M.
Nitr
apyr
in w
ill b
e m
ore
effe
ctiv
e as
soil
drie
s and
nitr
ifica
tion
activ
ity d
ecre
ases
.
Nitr
apyr
in w
ill d
ecre
ase
amoA
gen
e ab
unda
nce
by in
hibi
ting
amm
onia
mon
ooxy
gena
se a
nd th
us d
imin
ishin
g th
e ab
ility
of
amm
onia
-oxi
disin
g m
icro
orga
nism
s to
obta
in e
nerg
y an
d to
grow
.
Ch. 1: Introduction
10
The study was conducted using soil collected from a study site established in 2003 with
a range of crop residue and tillage treatments. The research site provided a unique
opportunity to examine the effects of various treatments on the medium-term changes
(approximately 10 years) in soil OM and C, and consequent effects on N cycling and
soil biological communities and functioning, without confounding effects of soil type
and climate.
This thesis is set out as a series of experimental papers in order to answer the specific
aims (Chapters 3–5). As these chapters are either under review or are in preparation for
publication as stand alone journal articles, minor repetition exists in the introductions
and methods. Specific aims addressed in each chapter are set out in Table 1.1. A general
discussion of the overall findings follows the experimental chapters, and all references
may be found in the section following Chapter 6 at the end of the thesis.
11
Chapter 2.
Nitrogen Loss from Semi-Arid Rainfed Agricultural
Soils
2.1. Introduction
This review provides an overview of nitrogen (N) cycling and factors contributing to the
risk of N loss in semi-arid soils, particularly those which experience winter-dominant
rainfall and hot, dry summers. The review will begin by defining and describing the
particular environment and land use of the soils relevant to this thesis, including the
challenges of rainfed cropping in relation to limited water availability in these areas
worldwide and in south-western Australia. Following this is a general overview of soil
N cycling, and environmentally detrimental N loss with a specific emphasis on
microbially-mediated N transformations in semi-arid soils. A focus is then given to the
molecular ecology of nitrifiers, the microorganisms that regulate the key loss pathway
of nitrification. Finally, approaches are considered that have potential to limit N losses
from semi-arid soils, particularly nitrification inhibitors.
Ch. 2: Literature Review
12
2.2. Rainfed Arable Agriculture in Semi-Arid Regions
Semi-arid and arid regions cover approximately a third of the Earth’s surface
(Archibold, 1995) and 54% of the global agricultural area (Fig. 2.1; The World Bank,
2008). When combined with hyper-arid deserts and dry sub-humid land, these regions
support two billion people, so are considerably important for world food production
(United Nations, 2011). Semi-arid regions can be described under the climate
classification of the United Nations Educational, Scientific and Cultural Organization
(UNESCO, 1979), extended from Meigs (1953), which defines climate by the ratio of
annual precipitation to potential evapotranspiration (P/Etp). The P/Etp of semi-arid
regions ranges from 0.20–0.50, or precipitation that is only 20–50% of potential
evapotranspiration (UNESCO, 1979). The UNESCO classification further subdivides
climate regions on the basis of mean temperature of the coldest and warmest months of
the year, number of dry months with less than 20 mm precipitation, and the
precipitation regime (i.e. season of dominant rainfall; UNESCO, 1977).
Figure 2.1. Arid regions of the world. From Dregne (1983), redrawn from UNESCO
(1977).
Ch. 2: Literature Review
13
Of particular interest to this thesis are semi-arid regions with winter-dominant rainfall
and hot, dry summers, some of which are also known as a Mediterranean-type climate
(Cs in the Köppen-Geiger classification; Peel et al., 2007). These regions occur between
30–45° latitude on the western side of continents, and around the Mediterranean basin
(Fig. 2.2; Harrington and Tow, 2011). As rainfall is concentrated in winter, it is
ecologically more significant compared to summer rainfall, because potential
evapotranspiration is comparatively low in winter and more rainfall is actually available
for plant growth (UNESCO, 1979).
Figure 2.2. World distribution of Mediterranean-type climates. From Ochoa-Hueso
et al. (2011).
Rainfed agriculture (i.e. agriculture without irrigation) in semi-arid regions is generally
possible for certain crops, though harvests and yields are irregular and agriculture is
intrinsically risky due to high variability in annual rainfall and the possibility of
prolonged dry periods during the cropping season (Harrington and Tow, 2011; Stewart
and Koohafkan, 2004; UNESCO, 1979). Crops that are grown in Mediterranean-type
climates range from cereals such as wheat and barley; tree crops such as olives; pulses
Ch. 2: Literature Review
14
like lentils and chickpeas; and oilseed crops such as canola (Harrington and Tow, 2011).
The type of crops grown and degree of agricultural intensity and productivity depend on
the amount of annual rainfall, the degree of development of the region and population
pressure for food (Harrington and Tow, 2011).
Bowden (1979) defines four unique keys that need to be considered for agricultural
development in semi-arid lands, two of which are particularly important for
Mediterranean-type areas. These are that 1): precipitation and temperature will not be
the same in amount, range, extremes or averages between growing seasons, meaning
that each year cultivation of crops must be adjusted accordingly; and 2): crop
production is highly unpredictable and must be managed and planned differently each
growing season. The highly variable nature of rainfall and soil water availability means
that use efficiency of nutrients, such as N, is also highly variable, being related to
changes in soil organic matter (OM) mineralisation and nutrient immobilisation (Ryan,
2011). For example, wheat yields in a four-year study in northern Syria were more
dependent on seasonal rainfall than crop rotation, N fertiliser application or soil fertility
(Pala et al., 1996).
2.3. Rainfed Arable Agriculture in the Semi-Arid Region of South-
Western Australia
In Australia, almost the entire continental area is occupied by semi-arid and arid
climates, radiating gradually out from a substantial area of aridity in the interior to a
non-arid coastal fringe (Meigs, 1953; UNESCO, 1979). Seasonal precipitation in south-
western Australia is dominated by winter rainfall, with a marked summer dry period of
four to seven months, typical of a Mediterranean-type climate (Aschmann, 1973). In the
Ch. 2: Literature Review
15
summer there are however occasional rainfall events, often linked with tropical
cyclones from the north-west (UNESCO, 1979).
Arable agriculture in south-western Australia is almost exclusively concentrated in the
semi-arid, winter rainfall dominated climate band known locally as the wheatbelt or
grainbelt. This area produces a significant amount of Australia’s crops: over the past
five years, the state of Western Australia has produced on average 32% of Australia’s
total winter crop yield, though depending on rainfall this proportion can range from 19–
39% (ABARES, 2014). The main winter crops grown in this region are wheat, barley,
canola and lupins (ABARES, 2014). During summer, lack of rainfall and soil water
availability limits plant growth, so most agricultural soils are left fallow.
Common arable agricultural practice in south-western Australia is no-tillage, which has
no soil disturbance other than at seeding (Roper et al., 2010). At this time, either disk
seeding without any soil throw or seeding with a knife point (5–20% disturbance) is
used (Roper et al., 2010). No-tillage usually avoids inversion and affects only the
surface 5–10 cm (Murphy et al., 2011). Compared to soil that has been rotary tilled, no-
tillage tends to have greater soil total carbon (C), light fraction OM (LFOM), dissolved
OM, microbial biomass C (MBC) and N pools and rates of C and N cycling in surface
soil than in subsurface soil due to decreased soil disturbance and mixing (Cookson et
al., 2008). Nitrogen fertiliser additions are generally low (20–100 kg N ha-1 y-1) and
targeted according to expected growing season rainfall. As a consequence, at times
more than half of N supply to crops in this environment results from mineralisation of
OM and previous crop or pasture residues (Angus, 2001).
Ch. 2: Literature Review
16
Arable soils in south-western Australia are derived from highly weathered landscapes,
so the majority have coarse-textured surface soils, and are low in OM and nutrients
(Cookson et al., 2006a; McArthur, 2004; Tennant et al., 1992). Most microbial biomass
and N cycling occur in the surface 10 cm of soil and as such, changes in temperature
and rainfall have a direct effect on the microbially active surface layer (Murphy et al.,
1998a). Water availability primarily affects the timing of microbial activity, but the
magnitudes of biological processes, such as N cycle fluxes, are mostly affected by soil
temperature and texture (Cookson et al., 2006a).
2.4. Soil Nitrogen Cycle and Environmentally Detrimental Loss
2.4.1. The soil nitrogen cycle
Nitrogen cycles through a variety of inorganic and organic pools in soil, mediated by
soil microorganisms that use N for energy and growth (Fig. 2.3). The largest pool of N
in soil (greater than 90%) is the OM pool, which contains many complex forms of plant
and microbial detritus, ranging from easily decomposable and microbially available
compounds to resistant compounds (Focht and Martin, 1979). Easily decomposable
compounds include amino acids, simple sugars and organic acids, which can by broken
down by decomposers within hours to days (Behera and Wagner, 1974). Resistant N
compounds such as lignins and waxes can take months or years to decompose (Haider
et al., 1967). The majority of soil OM is a large, inactive pool that has a constant decay
rate. There is also a small, active pool of soil OM, the decay rate of which can be
influenced by the quality of plant detritus inputs (i.e. C:N ratio and chemical
constituents; Knops et al., 2002).
Ch. 2: Literature Review
17
Figure 2.3. A simplified soil nitrogen cycle. Dashed red arrows show pathways of
environmentally detrimental loss. Open blue arrows show agricultural organic and
inorganic N additions. Adapted from Schimel and Bennett (2004). Abbreviations: NH4+:
ammonium; NO2-: nitrite; NO3
-: nitrate; N2O: nitrous oxide; NO: nitric oxide; N2:
dinitrogen gas.
Heterotrophic microorganisms break down soil OM in order to gain energy, C, N and
other nutrients (Robertson and Groffman, 2006). Nitrogen mineralisation occurs when
excess N is released as ammonium (NH4+) during breakdown of OM. Microorganisms
synthesise extracellular enzymes to depolymerise insoluble macromolecular OM,
producing dissolved organic N-containing compounds such as amino acids and short
chains of amino acids known as oligopeptides (Schimel et al., 2005). Many
microorganisms and plants are able to directly take up and use these simple low
molecular weight OM (LMWOM) compounds (Farrell et al., 2013; Näsholm et al.,
1998). Competition for these LMWOM compounds and their subsequent breakdown is
Ch. 2: Literature Review
18
considered to be the key limiting step in the supply of N to subsequent soil N cycle
processes (Hill et al., 2012; Jones et al., 2004b; Schimel and Bennett, 2004).
Nitrification is the production of nitrate (NO3-) by the further transformation of NH4
+ to
nitrite (NO2-) and then NO3
-. Most nitrification in agricultural soils is considered to be
carried out by autotrophic microorganisms, which use nitrification in order to gain
energy as well as the building blocks for new biomass, and do not require C for
production of energy (De Boer and Kowalchuk, 2001). The molecular ecology of
nitrifiers is discussed further in Section 2.6. Nitrate can be further transformed to
dinitrogen gas (N2) by denitrification (Robertson and Groffman, 2006), or can be turned
back into NH4+ by nitrate ammonification, also known as dissimilatory nitrate reduction
to ammonium (DNRA; Giles et al., 2012). Although DNRA can be a significant NO3-
consumption pathway in some forest and rice paddy soils (Rütting et al., 2008; Templer
et al., 2008; Yin et al., 2002), DNRA is favoured by very reduced and C rich
environments, generally occurs in anaerobic conditions, and rates are expected to be
greatest in soil with high OM contents in humid temperate regions (Giles et al., 2012;
Medinets et al., 2015; Rütting et al., 2011). The soils of interest for this thesis have very
low OM contents and are well-drained, rarely becoming anaerobic, so DNRA is not
considered further in this thesis as an important N cycle process.
Inorganic forms of N (NH4+ and NO3
-) may be taken up again by soil microorganisms
and incorporated into biomass. This process is N immobilisation, and is the pathway by
which N can be retained in soil, as N becomes part of the soil OM pool again.
Nitrification on the other hand is the main pathway for environmentally detrimental
losses of N from soil, as the greenhouse gas nitrous oxide (N2O) can be formed during
Ch. 2: Literature Review
19
nitrification and denitrification, and NO3- is highly mobile in groundwater or runoff
(Cameron et al., 2013; Robertson and Groffman, 2006).
Nitrogen may also be lost from soil by volatilisation of ammonia (NH3) from the
surface. Ammonium exists in soil in equilibrium with ammonia gas, and when soil pH
is high (as in calcareous soils or temporarily after urea fertiliser application), ammonia
production is favoured (Cameron et al., 2013). Ammonia in the atmosphere can be
deposited back onto the Earth’s surface, either in rainfall or attached to particulate
matter, contributing to acidification and eutrophication (Peoples et al., 2004). Ammonia
volatilisation is not considered an important N loss process in this thesis however,
because the agricultural soils of interest in the study region of south-western Australia
have predominantly acidic pH (or near neutral where lime has been applied).
2.4.2. Nitrate in semi-arid soils
Nitrate is a negatively charged ionic form of inorganic N, and as a consequence of
repellence by the positive charge of cation exchange sites in most soils, NO3- is easily
leached through drainage of soil water (McLaren and Cameron, 1996). This loss of N
can be detrimental to the environment by stimulating growth of unwanted
microorganisms and plants in receiving water bodies and thus causing eutrophication
(Smith and Schindler, 2009).
Nitrate leaching rates vary with soil type, season and climate, and are often greatest in
seasons when plant uptake of NO3- is low and soil drainage is occurring, and when
precipitation is greater than evapotranspiration and the water storage capacity of soil
(Kurtz, 1980). In semi-arid climates with winter dominant rainfall, this often occurs in
late summer and autumn, when winter crops are not yet established and taking up NO3-
Ch. 2: Literature Review
20
and the first rains of the growing season cause drainage. In a sand soil from south-
western Australia that was cropped to wheat, 68% of total NO3- leached during the
growing season occurred in the first two rainfall events of autumn (Anderson et al.,
1998). Similarly, in a silty clay loam soil from Navarra, Spain, 65–80% of total N
leached occurred in the first three months of crop development (Arregui and Quemada,
2006). Soils that are conducive to water movement, such as those with poor structure
and coarse textures that promote preferential flow through macropores, are also more
susceptible to leaching losses (Cameron et al., 2013).
Few studies have measured NO3- leaching rates from soils in semi-arid climates.
Leaching rates that have been observed show that in general, native ecosystems have
very low leaching rates (less than 1 kg N ha-1 y-1), but leaching rates from cropped soils
can be significant (Table 2.1). One Australian soil leached up to 59 kg NO3--N ha-1 in
one growing season (Anderson et al., 1998), while a Spanish soil had leaching rates
greater than 75 kg NO3--N ha-1 (Arregui and Quemada, 2006).
2.4.3. Nitrous oxide emissions from semi-arid soils
Nitrous oxide is a potent greenhouse gas with 298 times the 100-year global warming
potential of carbon dioxide (CO2; Myhre et al., 2013). Nitrous oxide can be produced
from soil during nitrification by ammonia oxidisers, and during denitrification by both
denitrifiers and some ammonia-oxidising bacteria (AOB) that are also able to denitrify
(Fig. 2.3; Kool et al., 2011). Ammonia-oxidising archaea (AOA) have also been
observed to produce N2O (Löscher et al., 2012; Rasche et al., 2011; Santoro et al., 2011;
Stieglmeier et al., 2014), possibly originating from chemical reactions of intermediates
in the ammonia oxidation process, rather than through nitrifier denitrification like AOB
(Hatzenpichler, 2012). Nitrate ammonification (DNRA) can additionally form N2O as a
Ch. 2: Literature Review
21
by-product, but is unlikely to be an important source of N2O in the semi-arid soils of
interest in this thesis as DNRA generally occurs under anaerobic conditions in soils
with high C content (Giles et al., 2012; Medinets et al., 2015; Rütting et al., 2011).
Agricultural sources are estimated to contribute about 60% of global anthropogenic N2O
emissions, directly from soil and from animal production (Ciais et al., 2013).
A significant proportion of N2O emissions from semi-arid soils can be produced by
wetting of dry soil when inorganic N is available (Aguilera et al., 2013). This is in
contrast to most N2O emissions from temperate soils, which appear to be in response to
N fertiliser additions (Galbally et al., 2008; Mummey et al., 1994). For example, in
south-west Australian agricultural soils, over half of annual N2O fluxes can be in
response to summer and autumn rainfall events (Barton et al., 2008; Barton et al.,
2013b). Typical N loss rates as N2O emissions are however an order of magnitude lower
on average than in irrigated semi-arid systems (Aguilera et al., 2013), where measured
annual fluxes can range from 0.08–0.69 kg N2O-N ha-1 (Table 2.2). These low
emissions in rainfed semi-arid soils compared to irrigated systems or more humid
climates may be due to typically low N fertiliser application rates, and crop growth
during the coolest season when N2O fluxes are limited by temperature (Aguilera et al.,
2013). Low temperatures below 10–12 °C can even be associated with negative N2O
fluxes (Meijide et al., 2009).
Tabl
e 2.
1: N
itrat
e le
achi
ng r
ates
obs
erve
d in
sem
i-ari
d cl
imat
es w
ith w
inte
r do
min
ant r
ainf
all.
Loc
atio
n L
and
use
Mea
n an
nual
rain
fall
(mm
) St
udy
leng
th
N a
pplic
atio
n (k
g
N h
a-1 y
-1)
Nitr
ate
leac
hing
(kg
NO
3- -N h
a-1)
Ref
eren
ce
Moo
ra, W
este
rn A
ustra
lia,
Aus
tralia
Cro
pped
[lup
in (L
upin
us
angu
stifo
lius)
, whe
at (T
ritic
um
aest
ivum
)] an
d pa
stur
e
[sub
terr
anea
n cl
over
(Tri
foliu
m
subt
erra
neum
)] ro
tatio
ns
460
98, 1
26, 5
9 da
ys
(3 g
row
ing
seas
ons)
0
2–59
#
And
erso
n et
al.
(199
8)
Dev
il C
anyo
n, S
an
Bern
ardi
no M
ount
ains
,
Cal
iforn
ia, U
SA
Fore
st (m
ixed
con
ifers
), gr
adin
g
to sh
rubl
and
(cha
parr
al)
610
4 ye
ars
0 3.
6-11
.6 §
Fenn
and
Pot
h (1
999)
NE
San
Die
go C
ount
y,
Cal
iforn
ia, U
SA
Shru
blan
d (c
hapa
rral
), po
st fi
re
530
3 ye
ars
0,
50
0.00
2–12
2.6,
‡
1.3–
130.
0
Vou
rlitis
et a
l. (2
009)
Nav
arra
, Spa
in
Cro
pped
[whe
at, b
arle
y (H
orde
um
vulg
are)
, rap
esee
d (B
rass
ica
napu
s) ro
tatio
n]
347–
492
(gro
win
g
seas
on ra
infa
ll)
120,
164
, 143
day
s
(3 g
row
ing
seas
ons)
0–13
5 5.
6–78
†
Arr
egui
and
Q
uem
ada
(200
6)
Mon
tsen
y M
ount
ains
,
Cat
alon
ia, S
pain
Fore
st [h
olm
oak
(Que
rcus
ilex
)] 90
1 10
yea
rs
0 0.
05 ¶
A
vila
et a
l. (2
002)
# M
ost f
rom
lupi
n-w
heat
rota
tion,
leas
t fro
m p
astu
re-p
astu
re, v
arie
d w
ith y
early
rain
fall.
§ 19
95-1
998
expo
rt fr
om e
ntire
cat
chm
ent,
dow
nstre
am o
f N sa
tura
ted
fore
st.
‡ H
igh
year
ly v
aria
tion
with
rain
fall.
† V
aria
tion
mai
nly
due
to d
rain
age
and
soil
min
eral
N c
onte
nt.
¶
10 y
ear a
vera
ge o
f tot
al N
exp
ort a
t cat
chm
ent o
utle
t.
Ta
ble
2.1.
con
tinue
d on
nex
t pag
e.
Tabl
e 2.
1. N
itrat
e le
achi
ng r
ates
obs
erve
d in
sem
i-ari
d cl
imat
es w
ith w
inte
r do
min
ant r
ainf
all (
cont
inue
d).
Loc
atio
n L
and
use
Mea
n an
nual
rain
fall
(mm
) St
udy
leng
th
N a
pplic
atio
n
(kg
N h
a-1 y
-1)
Nitr
ate
leac
hing
(kg
NO
3- -N h
a-1)
Ref
eren
ce
Mon
tsen
y M
ount
ains
,
Cat
alon
ia, S
pain
Fore
st (h
olm
oak
and
ald
er)
1258
1
year
0
0.7
◊ Bu
tturin
i and
Sa
bate
r (20
02)
Cat
alon
ia, S
pain
M
ainl
y fo
rest
[cor
k oa
k (Q
uerc
us
sube
r) a
nd p
ine]
, <10
%
agric
ultu
ral f
ield
s
613
3 ye
ars
0 0.
1–0.
4 ◊
Bern
al e
t al.
(200
2)
◊ St
ream
exp
ort
Tabl
e 2.
2: N
itrou
s oxi
de e
mis
sions
obs
erve
d in
sem
i-ari
d cl
imat
es w
ith w
inte
r do
min
ant r
ainf
all.
Loc
atio
n L
and
use
Rai
nfal
l (m
m)
Stud
y le
ngth
N a
pplic
atio
n ra
te
(kg
N h
a-1 y
-1)
N2O
em
issi
ons
(kg
N2O
-N h
a-1)
Ref
eren
ce
Cun
derd
in, W
este
rn
Aus
tralia
, Aus
tralia
Cro
pped
[whe
at (T
ritic
um a
estiv
um)]
368
# 1
year
0,
100
0.
09 –
0.1
1 Ba
rton
et a
l. (2
008)
Cun
derd
in, W
este
rn
Aus
tralia
, Aus
tralia
Cro
pped
[can
ola
(Bra
ssic
a na
pus)
] 36
7 #
1 ye
ar
0, 7
5 0.
08–0
.13
Barto
n et
al.
(201
0)
Cun
derd
in, W
este
rn
Aus
tralia
, Aus
tralia
Cro
pped
[nar
row
-leaf
ed lu
pin
(Lup
inus
angu
stifo
lius)
]
365
# 1
year
0
§ 0.
13
Barto
n et
al.
(201
1)
Won
gan
Hill
s, W
este
rn
Aus
tralia
, Aus
tralia
Cro
pped
(lup
in–w
heat
; whe
at–w
heat
rota
tions
)
374
# 2
year
s 0,
20
(lupi
n–w
heat
rota
tion)
,
75, 5
0 (w
heat
–whe
at
rota
tion)
0.04
–0.0
7 ‡
Barto
n et
al.
(201
3b)
Arb
uckl
e, C
alifo
rnia
,
USA
Cov
er c
rop
(legu
min
ous m
ix) b
etw
een
vine
yard
row
s (Vi
tis v
inife
ra)
42.7
(mea
sure
d
Mar
ch–O
ctob
er)
195
days
5
† 0.
07–0
.11
¶ G
arla
nd e
t al.
(201
1)
# M
ean
annu
al ra
infa
ll.
§
Lupi
n is
a g
rain
-legu
me:
no
ferti
liser
.
‡ Li
min
g de
crea
sed
N2O
em
issi
ons o
ver t
wo
year
s in
whe
at–w
heat
but
not
in lu
pin–
whe
at ro
tatio
n.
† N
ferti
liser
app
lied
once
dur
ing
study
per
iod.
¶ N
2O e
mis
sion
s are
cum
ulat
ive
for t
he g
row
ing
seas
on, c
onve
ntio
nal t
ill a
nd n
o-til
l tre
atm
ents.
Ta
ble
2.2.
con
tinue
d on
nex
t pag
e.
Tabl
e 2.
2: N
itrou
s oxi
de e
mis
sions
obs
erve
d in
sem
i-ari
d cl
imat
es w
ith w
inte
r do
min
ant r
ainf
all (
cont
inue
d).
Loc
atio
n L
and
use
Rai
nfal
l (m
m)
Stud
y le
ngth
N a
pplic
atio
n ra
te
(kg
N h
a-1 y
-1)
N2O
em
issi
ons
(kg
N2O
-N h
a-1)
Ref
eren
ce
Mon
tere
y C
ount
y,
Cal
iforn
ia, U
SA
Cov
er c
rop
[Trio
s 102
(Trit
ical
e x
Trio
seca
le) o
r Mer
ced
Rye
(Sec
ale
cere
ale)
] or c
ultiv
ated
soil
betw
een
vine
yard
row
s
460
(for w
inte
r
2005
–200
6)
1 ye
ar
0 0.
47–0
.69
Stee
nwer
th a
nd
Belin
a (2
008)
Alc
alá
de H
enar
es,
Mad
rid, S
pain
Cro
pped
[bar
ley
(Hor
deum
vul
gare
)] 43
0 13
2 da
ys (c
rop
perio
d), 3
7 da
ys
(aut
umn
fallo
w)
125
0.20
–0.3
7 ◊
Mei
jide
et a
l. (2
009)
◊ C
umul
ativ
e N
2O e
mis
sion
s for
cro
p pe
riod
(Jan
uary
–Jun
e) a
nd fi
rst r
ain
even
ts o
f aut
umn
(Oct
ober
–Nov
embe
r).
Ch. 2: Literature Review
26
2.4.4. Tools to predict the risk of nitrogen loss
Experimental methods to determine actual N loss rates are often time and labour
intensive, expensive, and result in data that are not suitable for generalisation or
prediction (Buczko et al., 2010). In order to effectively manage agricultural N and
reduce N losses from soil, some method of assessing and predicting the risk and
magnitude of N losses from soil is necessary. Various N loss indicators have been used,
ranging from simple qualitative or semi-quantitative indicators such as N balances (for
example Buczko et al., 2010; Wick et al., 2012), to complex models based on a
combination of physical N transport mechanisms and N sources, which require a lot of
input data and expertise to operate (for example Delgado et al., 2008).
One tool to that can be utilised to understand the risk of N loss is the gross nitrification
to N immobilisation ratio (N:I ratio), which describes the balance between the pathway
of N loss (nitrification) and the pathway of microbial N retention (immobilisation). The
N:I ratio was first used as an indicator of N saturation and the likely fate of NO3- in
forest soils (Aber, 1992), and was used to describe the competition for NH4+ between
heterotrophic immobilising microorganisms and nitrifiers (Tietema and Wessel, 1992).
The N:I ratio has been positively correlated to leaching losses in arable and grassland
soils from temperate, humid climates of the United Kingdom and New Zealand
(Stockdale et al., 2002), but has not been examined in relation to N2O loss. The ratio has
also been compared between grassland and forested sites in a cold temperate
environment in central Canada, to suggest the risk of N loss through NO3- leaching and
N2O emissions (Cheng et al., 2012). There are few studies however that have used the
N:I ratio in semi-arid soils. In one Western Australian red earth, the N:I ratio showed an
increased risk of N loss at low (5 °C) and high temperatures (30 and 40 °C; Hoyle et al.,
2006), due to limitation of N immobilisation at these temperatures. It is unknown
Ch. 2: Literature Review
27
whether the N:I ratio has a similar pattern in other semi-arid soils and under different
soil conditions.
2.5. Factors Controlling Risk of Nitrogen Loss through Microbially-
Mediated Soil Nitrogen Transformations
Variation in microbially-mediated N transformations affects the risk of N loss in semi-
arid soils through increased N loss processes such as nitrification or gaseous N
production. Generally this variation and biological activity in semi-arid soils is
controlled mainly by environmental factors of water availability and temperature (Hoyle
and Murphy, 2011; Noy-Meir, 1973). Other factors also modify microbial N cycling
and the risk of N loss such as availability of C and N substrates, soil pH, and the
relationships between microorganisms and plants (Booth et al., 2005; Sahrawat, 2008).
The factors that control the risk of N loss in soil vary spatially and with time. All soils,
by their nature, are highly spatially variable, on scales from the microscopic to the
landscape (Ettema and Wardle, 2002). For example, at the field scale, distance between
crop rows affects soil processes and functioning (Ettema and Wardle, 2002). At finer
scales, microsites provide differing degrees of substrate, water and oxygen availability,
and can protect bacteria from predation (Ettema and Wardle, 2002; Grundmann and
Debouzie, 2000; Ranjard and Richaume, 2001). Soil organisms need to locate and
access C, oxygen and nutrients within the heterogeneous soil environment, which has
differing degrees and scales of connectivity (Young et al., 1998). Spatial heterogeneity
provides high microhabitat diversity, and with limited active dispersal of most soil
microorganisms, communities are characterised by low species resource specialisation
but high species richness (Ettema and Wardle, 2002). Different microbial communities
may exist in N-rich versus N-poor microsites. In microsites that are nutrient-rich,
Ch. 2: Literature Review
28
microorganisms generally mineralise N, while in nutrient poor microsites
microorganisms immobilise N, leading to intense N cycling between these microsites
with different nutrient availabilities (Schimel and Bennett, 2004; Schimel and
Hättenschwiler, 2007). This suggests that net N mineralisation measured on bulk soil is
not always a good indication of the supply of N that is at risk of loss, as N can be
translocated from high to low regions of availability and the connections (or lack
thereof) between these microsites will determine if inorganic N accumulates.
Temporal variation in the risk of N loss is also apparent on a variety of scales, from
minute to minute variations, through seasonal cycles, to annual and decadal changes.
This is especially important in semi-arid soils, where biological processes are limited by
water availability, linked to rainfall that also varies greatly with season and from year-
to-year (Harrington and Tow, 2011; Noy-Meir, 1973). For example, temporal variation
in N substrate availability is often high in semi-arid soils, with seasonal shifts in the
relative dominance of dissolved organic N and inorganic N and consequent shifts in risk
of N loss (Delgado-Baquerizo et al., 2011). In regions with winter dominant rainfall,
soil inorganic N pools are often greatest during and after summer dry periods, which
suggests that production of NH4+ and NO3
- continues to occur during seasons which are
limiting to plant growth (Delgado-Baquerizo et al., 2011; Jackson et al., 1988). The
increase in availability of N substrates for nitrification may increase the potential for N
loss, especially when there is limited plant N uptake such as during summer fallow.
This is shown by maximum NO3- leaching rates at the end of summer and in the early
growing season (Anderson et al., 1998; Avila et al., 2002).
Ch. 2: Literature Review
29
2.5.1. Soil water and wetting-drying cycles
Abiotic factors of water content and soil temperature are the main controls on rates of N
cycling in semi-arid regions (Farrell et al., 2013; Hoyle and Murphy, 2011; Jones et al.,
2009; Noy-Meir, 1973). A common feature of semi-arid climates is the presence of
wetting and drying cycles in soil (Austin et al., 2004). Variations in rainfall and soil
water availability cause water pulses in the soil, which may occur over the long term in
areas with seasonally dominant rainfall and over shorter periods as wetting-drying
cycles due to individual rainfall events (Austin et al., 2004).
Microbial communities in semi-arid regions are likely adapted to the seasonal extremes
of water stress that are normal for these environments (Cookson et al., 2006a; Halverson
et al., 2000; Placella et al., 2012). Bacterial communities from these climates have
phenotypes that are both thermo- and drought-tolerant (Curiel Yuste et al., 2014).
Surprisingly, potential nitrification rates during the dry season of some semi-arid soils
can be greater than in the wet season, suggesting that the size of the ammonia-oxidising
community is also larger in the dry season, and potential for N loss is also greater
(Parker and Schimel, 2011; Sullivan et al., 2012). Microbial biomass in a semi-arid
Californian soil was also higher in the dry season than the wet, which may be because
microbial death rates are lower, as predators such as protozoa are more drought-
sensitive and reliant on hydrological connections to move about (Parker and Schimel,
2011). Maintaining the potential for metabolic activity during the dry season may be a
strategy by microbes to compete more successfully against plants for resources during
rainfall pulses (Sullivan et al., 2012). This also suggests that even though soil water
availability may be limiting for the majority of the time during dry seasons, there is still
potential for N loss at these times.
Ch. 2: Literature Review
30
Soil microorganisms are faced with different challenges depending on whether soil is
drying or whether dry soil is rewet. Water films between and on soil particles decrease
and become less connected as soil dries, restricting the mobility of microorganisms that
live in water, decreasing diffusion of soluble substrates and decreasing hydrological
connectivity between different N cycle processes (Schimel et al., 2007). Decreased
movement of predators may decrease bacterial death rates, causing an apparent increase
in microbial activity (Parker and Schimel, 2011). Increased concentration of substrates
as water films contract can also stimulate microbial growth, though if the soil remains
dry and water films don’t expand again, the substrates can become depleted, causing a
drop in microbial growth after the initial increase (Schimel et al., 2007). Inorganic N
may accumulate as NH4+ when microsites of N mineralisation are not connected to
microsites of NH4+ consumption. This was shown in a semi-arid Californian soil where
the dominant N form in summer was NH4+ (Parker and Schimel, 2011).
Increases in NH4+ during drought may cause some observed differences between AOA
and AOB in their resilience to drying-rewetting stress. The abundance and community
composition of AOA appears to be less resilient to drying-rewetting stress than AOB,
possibly linked to the decreased tolerance of AOA to high NH4+ concentrations (Thion
and Prosser, 2014). Ammonia-oxidising bacteria also react more quickly to rewetting,
increasing their transcriptional activity slightly faster than AOA (within one hour
compared to nine hours; Placella and Firestone, 2013).
As soil dries, microbial activity and biomass decrease as soil microorganisms dehydrate
and either adapt to drought stress or induce survival mechanisms (Borken and Matzner,
2009). In liquid culture, mechanisms that allow microorganisms to remain active during
desiccation include accumulating solutes to maintain osmotic balance between
Ch. 2: Literature Review
31
intracellular and extracellular water potentials, and changing the structure and
composition of their cell walls to resist loss of internal cell water (Schimel et al., 2007).
In the more complex soil environment however, microbial adaption to desiccation
appears to be different: microorganisms instead become dormant (Boot et al., 2013;
Kakumanu et al., 2013). This drought avoidance is likely due to C and N substrates
becoming limiting as diffusion decreases in drying soils, so microorganisms are unable
to access the resources they need to synthesise extra osmolytes (Boot et al., 2013;
Kakumanu et al., 2013). Furthermore, in environments with plants, labile C inputs to
soil from root exudates can decrease by up to 80% when soil dries, as plants decrease
their allocation of C to belowground biomass (Gorissen et al., 2004). This may affect
the availability of C to heterotrophic microorganisms, which may increase the potential
for N loss if immobilisation decreases to a greater degree than to nitrification.
When soil is wetted, microorganisms need to rapidly equilibrate to the increased water
potential, which can cause even more stress than the microorganisms experienced on
soil drying (Schimel et al., 2007). If microorganisms are unable to adjust to the
increased water potential, they can die and lyse, contributing as substrate to the initial
pulse of mineralisation often observed on wetting of dry soil (Schimel et al., 2007).
Depending on the organism, up to 26% of cell amino acids, 21% of low molecular
weight sugars (Halverson et al., 2000) and 20–70% of viable MBC (Kieft et al., 1987)
can be released on rewetting. This released C and N however is rapidly reassimilated by
microorganisms in many soils for energy and growth, so after wetting microbial
biomass can recover to the same size as in permanently moist soil, or even increase
(Bottner, 1985; Lundquist et al., 1999).
Ch. 2: Literature Review
32
Wetting of dry soil has rapid short-term effects on microbial activity and C and N
cycling. Microbial activity, including N mineralisation increases within minutes to
hours after wetting (Lee et al., 2004; Murphy et al., 1998b; Sponseller, 2007). Easily
decomposable organic substrates are accumulated or exposed during the dry period,
then when dry soils are wetted these organic substrates are immediately mineralised,
causing a pulse in microbial activity, observable as a large CO2 pulse known as the
Birch effect (Jarvis et al., 2007; Kieft et al., 1987). In some soils, the substrate for the
observed N mineralisation increase can come from non-microbial organic N (Appel,
1998). Wetting of dry soil also increases the connections between water films, allowing
increased diffusion of substrates and mobility of microorganisms to access those
substrates (Borken and Matzner, 2009). Increased N mineralisation and hydrological
connectivity of microsites also increases substrate availability to microbially-mediated
N transformations such as nitrification and denitrification, leading to an increased risk
of N loss.
High water contents present different challenges for microorganisms. At high water
contents, soil oxygen is decreased and anaerobic conditions develop. Oxygen diffusion
in soil becomes limited when water-filled pore space (WFPS) is greater than 90%
(Wesseling and van Wijk, 1957). Under these conditions, aerobic microorganisms that
require oxygen as an electron acceptor for energy production may become limited, such
as autotrophic nitrifying bacteria, which may decrease risk of N loss through
nitrification. However, microorganisms that are facultative aerobes may change their
metabolism when anaerobic conditions develop, and anaerobic organisms may become
active, changing the products of N cycling. For example, denitrifiers may become more
active, or more N2O may be produced by nitrifier denitrification and denitrification
(Wrage et al., 2001).
Ch. 2: Literature Review
33
2.5.2. Soil temperature
Fluctuations in temperature diurnally and with season are strong drivers of change in N
transformation rates (Frederick, 1956; Sabey et al., 1956). Microbial growth rates,
biological process rates and enzyme catalysis rates increase with increasing temperature
up to an optimum, above which they decline (Johnson et al., 1974). The pattern of
change with temperature of microbial activity is due to an intrinsic property of enzymes:
the negative change in heat capacity between the ground state of an enzyme and the
transition state of the enzyme as it facilitates the transformation of substrates into
products (Hobbs et al., 2013). Optimum temperatures for microorganisms vary
depending on their native climate. For example, optimum temperatures for nitrification
have been measured as 25 °C for cool temperate soils in Iowa (Sabey et al., 1956) and
35 °C for an Australian tropical soil (Myers, 1975).
Temperature has intrinsic and extrinsic effects on microorganisms and N cycling.
Intrinsic effects act directly on metabolic processes, while extrinsic effects are due to
environmental constraints such as changes in diffusion rates and solubility of substrates
(Davidson and Janssens, 2006). With decreasing temperature below the optimum, cell
membranes become less fluid, which decreases the efficiency of transport proteins and
enzymes located in the membrane, thus decreasing the affinity of the microorganism for
substrates which are taken up by active transport processes (Beney and Gervais, 2001;
Nedwell, 1999). Microorganisms are able to adapt to decreasing temperatures to a
certain degree, by inducing cold shock proteins, or by changing the structure of their
membranes to increase the amount of unsaturated lipids and decrease the proportion of
branched chain lipids, which helps to maintain membrane fluidity to lower temperatures
(Russell, 1990). Diffusion rates of substrates and oxygen also decrease with decreasing
temperatures (Schimel et al., 2007). Microbial growth may become limited once
Ch. 2: Literature Review
34
microorganisms have used the resources in their immediate environment and if
diffusion rates are too low to replace those resources (Schimel et al., 2007).
At temperatures above optimum, microorganisms can become constrained by
irreversible protein denaturation, the physiological cost of inducing survival
mechanisms by diverting C and energy to maintenance requirements, cell lysis and
death (Corkrey et al., 2012; Johnson et al., 1974; Schimel et al., 2007). Increases in the
optimum temperature of enzymes without compromising their rate of reaction require
increases in enzyme rigidity, in order to increase the change in heat capacity for
catalysis and to provide enzyme stability at high temperatures (Hobbs et al., 2013).
Microorganisms can also acclimate to increasing temperature by increasing the
proportion of saturated and long-chain fatty acids in membrane lipids, in order to
maintain constant membrane fluidity, to decrease leakiness of the membrane and to
maintain substrate transport mechanisms (Sinensky, 1974).
Some N cycling processes may be more sensitive to temperature than others, causing
disconnections between N cycling processes that may in turn increase the risk of N loss.
Uncoupling of N mineralisation-immobilisation turnover (MIT) and increased risk of N
loss has been observed at high temperatures in semi-arid soils (above 30 °C; Hoyle et
al., 2006; Luxhøi et al., 2008), when gross N immobilisation rates were limited more
than gross N mineralisation and nitrification rates. The limitation of immobilisation at
high temperatures may be due to increased soil respiration and microbial biomass
rapidly assimilating labile C, leading to a C substrate limitation (Cookson et al., 2007).
Uncoupling of MIT has also been observed in temperate soils from Denmark at low
temperatures (below 5 °C), where limitation of immobilisation was attributed to down-
Ch. 2: Literature Review
35
regulation of microbial growth and thus NH4+ consumption (Andersen and Jensen,
2001).
2.5.3. Availability of carbon and nitrogen substrates
Availability of C and N substrates are a major factor affecting rates of N cycling and
risk of N loss in semi-arid soils, as N cycling microorganisms require both C and N to
grow. The availability of N substrates may depend on production of those substrates by
previous N transformation processes, or on competition for the same N substrate
between diverse N cycling organisms. In the case of nitrification, autotrophic nitrifiers
require NH4+, so the rate at which N mineralisation produces NH4
+ affects subsequent
nitrification rates (Booth et al., 2005; Murphy et al., 2003). In addition, nitrifiers and
heterotrophic N immobilisers compete for NH4+ substrate. Autotrophic nitrifiers
generally have low specific growth rates and yields due to the low energy gain from
ammonia or nitrite oxidation, and use of most of that energy to fix CO2, so are
considered to be inefficient compared to heterotrophic microorganisms (Prosser, 1989).
Soil C availability may therefore regulate N loss processes through influencing the
competition between heterotrophic N immobilisers and autotrophic nitrifiers for NH4+.
Autotrophs fix their own C from CO2, while heterotrophs must assimilate organic
compounds for C and energy (Madigan and Martinko, 2006). Heterotrophs are generally
more active when soil C availability is high, when their higher specific growth rates
allow them to compete more successfully for NH4+ against nitrifiers. If heterotrophic
immobilisers are limited by factors such as decreased C availability, nitrifiers can
compete more effectively for NH4+ substrate, and the risk of N loss is greater (Booth et
al., 2005; Hart et al., 1994). Available or labile C is often present in the form of low
molecular weight, simple compounds, such as sugars and amino acids, obtained from
Ch. 2: Literature Review
36
plant rhizodeposits and during microbial breakdown of plant residues and other soil OM
(Haynes, 2005). Available C can increase N immobilisation markedly and thus may
increase retention of N in soil (Gibbs and Barraclough, 1998). For example, inorganic N
availability and net N mineralisation was decreased after eight years of additions of
sugar (labile C) and/or sawdust (more recalcitrant C) to soil of a semi-arid shortgrass
steppe (Burke et al., 2013).
Carbon availability can also stimulate the N loss process of denitrification, which
reduces NO3- to gaseous forms (NO and N2O). The microorganisms that carry out
denitrification are predominantly heterotrophic, so depend on an organic C source
(Wrage et al., 2001). The product ratio of N2O:N2 as well as denitrification rates are
influenced by labile C: when availability of easily decomposable C substrates is high in
soil, the proportion of N2O emitted during denitrification compared to N2 decreases
compared to when there is a C limitation (Azam et al., 2002; Weier et al., 1993).
Niche differentiation between AOA and AOB may be determined by ammonia substrate
availability. Ammonia-oxidising bacteria can be limited by lack of ammonia substrate,
but stimulated by NH4+ additions, while AOA with their high affinity for ammonia
often are found to dominate in environments with low substrate concentrations
(Daebeler et al., 2015; Di et al., 2010; Di et al., 2009; Pratscher et al., 2011).
Agricultural management practices that change the availability of C and N substrates by
altering soil OM content or C and N inputs can consequently change the risk of N loss.
In semi-arid soils this is particularly important, as soil OM content is usually low
compared to soil in more humid climates due to less precipitation, greater temperatures,
low plant productivity and continual soil loss by erosion (Archibold, 1995; Jenny, 1941;
Ch. 2: Literature Review
37
Ryan, 2011). Management practices that change C and N inputs and soil OM content
include addition of crop residues or other OM such as manure, additions of N fertiliser,
incorporation of surface residues and tillage, stubble burning, and growing legumes in
rotation.
Addition of chemical N fertilisers is the simplest way to provide N to semi-arid soils
that are deficient in N in order to support annual crop yields (Henderson, 1979).
However, N fertiliser additions in excess of plant demand or at times that are not
matched to plant growth can accumulate inorganic N in soil where it is at risk of loss
(Cameron et al., 2013). Accumulated N is susceptible to leaching, depending on the
amount and intensity of corresponding rainfall (Rasmussen and Collins, 1991). Loss of
N can be decreased by improving fertiliser management in order to match soil N supply
to crop demand, for example by applying the proper rate of N, split applications and
placement of fertiliser where uptake is most active (Meisinger and Delgado, 2002;
Murphy et al., 2004).
Tillage can decrease total C and N availability in soil by increasing oxidation and loss
of OM. Tillage is used for controlling weeds, preparing the physical condition of soil to
allow easy seedling establishment, improve water infiltration or to incorporate surface
residues or fertilisers (Henderson, 1979). However, loss of OM can also be significant,
depending on factors such as the intensity and duration of tillage, climate, crop and soil
type (Heenan et al., 1995; Murphy et al., 2011; Rasmussen and Collins, 1991). Greater
soil disturbance and soil-residue contact due to higher degrees of tillage can also
increase net inorganic N supply in semi-arid soils, with a consequent increase in risk of
N loss (Hoyle and Murphy, 2011). In addition to these effects, tillage redistributes
Ch. 2: Literature Review
38
LFOM-C, dissolved organic C (DOC) and microbial biomass to soil locations and
depths that may not be so favourable for microbial activity (Roper et al., 2010).
Burning of crop stubble left over after harvest can also cause decreases in C and N
substrate availability and direct N losses. Burning of stubble is used to control weeds
and crop diseases (Rasmussen and Rohde, 1988), but can also affect belowground
microbial processes and N cycling in semi-arid soils by decreasing microbial biomass,
soil OM, total C and N, mineralisable N and gross N mineralisation rates (Biederbeck et
al., 1980; Hoyle et al., 2006; Rasmussen et al., 1980). High temperature burning can
also cause sizeable losses of N through volatilisation (Murphy et al., 2011).
Legumes can alter availability of N in soil and risk of N loss through several pathways.
The symbiotic association of legume crops with root-nodulating bacteria provides fixed
N to the growing crop, which consequently uses less inorganic soil N. More inorganic N
then remains in soil where it may be available for subsequent crops, or if it is not
immobilised by microorganisms it can be at risk of loss (Gupta et al., 2011).
Additionally, legume crop residues have a low C:N ratio compared to cereal residues, so
if retained after harvest and incorporated into soil, these N-rich residues can stimulate N
mineralisation as they decompose, which may also be at risk of loss if not taken up by
subsequent crops (Crews and Peoples, 2005).
2.5.4. Soil pH and liming
Soil pH affects N transformations and risk of N loss primarily through its influence on
nitrification and the equilibrium that naturally occurs between NH4+ and ammonia
(NH3) in soil. Mineralisation, NH4+ consumption and inorganic N assimilation are
generally considered to be unaffected by soil pH (Booth et al., 2005). Free ammonia,
Ch. 2: Literature Review
39
not NH4+, is the substrate for ammonia oxidation, and the equilibrium between
ammonia and NH4+ is pH dependent. Each unit decrease in pH decreases the amount of
ammonia substrate by one order of magnitude (Prosser, 1989). Nitrifiers have strategies
to overcome this ammonia limitation at low pH that do allow nitrification to occur, such
as active transport of substrates, containing ammonia monooxygenase (AMO) enzymes
with high affinities for ammonia, hydrolysis of urea, carrying out heterotrophic
nitrification, making use of microsites with more neutral pH, forming biofilms by cells
attaching to surfaces and producing protective substances (Levy-Booth et al., 2014;
Prosser, 1989). Low pH is in fact the only consistent differentiating factor between
bacterial and archaeal ammonia oxidisers (Prosser and Nicol, 2012). Archaeal AMO has
an affinity for ammonia that is three to four orders of magnitude greater than bacterial
AMO (Martens-Habbena et al., 2009), allowing AOA to be more prevalent and active
than AOB at soil pH below 5.5 (Prosser and Nicol, 2012). Nitrite oxidisers on the other
hand are restricted under acid conditions due to chemical decomposition of nitrite,
which forms an equilibrium with toxic nitrous acid (Norton, 2008; Prosser, 1989).
Nitrifiers face other challenges as soil becomes more basic. As pH increases, ammonia
substrate becomes increasingly available, until pH is above the optimum for that
organism, and the advantages of increased substrate is balanced by the extra energy that
cells require to maintain their internal pH, and growth will become constrained (Prosser,
1989). As pH increases, increased ammonia also has the potential to be lost from soil by
volatilisation (Francis et al., 2008).
The effect of soil pH management on the risk of N loss is complex. Some authors have
reported that raising soil pH, for example by liming, increases nitrification rates (for
example Islam et al., 2006; Kemmitt et al., 2006), which in turn can increase N loss
Ch. 2: Literature Review
40
through increased NO3- pools and as N2O emissions. This may be either directly from
nitrification (Billore et al., 1996; Goodroad and Keeney, 1984), or indirectly by
increasing N substrates for denitrification if soil water content is high (Clough et al.,
2004). However, raising soil pH can also decrease N losses from N2O emissions during
nitrification, by increasing activity of nitrite oxidisers and limiting the conversion of
nitrite to N2O (Clough et al., 2004; Feng et al., 2003). This was demonstrated in a semi-
arid soil, where increasing pH by liming decreased N2O emissions due to nitrification
compared to more acid soil (Barton et al., 2013a).
2.5.5. Relationships between plants and nitrogen cycling microorganisms
Plants predominantly affect N cycling by influencing inputs and losses of N. Plant are
both a source of N, via symbiotic associations with N fixing microorganisms, and a sink
for N, by utilising inorganic N (and thus decreasing the amount of NO3- that is available
for leaching) (Knops et al., 2002). Although plants and microorganisms might be
expected to compete for N substrates, there is in fact a temporal niche separation
between them: in the short-term microorganisms outcompete roots for N, but as
microorganisms turn over very quickly and have high C respiration losses, in the long
term N is released by microorganisms which plants are subsequently able to take up
(Jones et al., 2013; Kuzyakov and Xu, 2013). The temporal niche separation of N
uptake between microorganisms and plants suggests that microorganisms actually
cooperate rather than compete with plants, especially in soils that are N-limited.
Microorganisms store excess inorganic N and prevent N losses by leaching, helping to
maintain ecosystem stability (Kuzyakov and Xu, 2013). Plant uptake of N also
decreases the amount of N that is at risk of loss: leaching of dissolved inorganic N can
be significantly elevated in soil without roots (Lajtha et al., 2005). Agricultural systems
however often create conditions where there is a disconnect between plants and
Ch. 2: Literature Review
41
microbes, so microbes become C limited and unable to immobilise excess inorganic N,
and N losses may be high (Kuzyakov and Xu, 2013). For example, in Mediterranean-
type semi-arid climates, N mineralisation occurs both in the winter growing season and
the summer non-growing season. In the winter mineralised N is more likely to be taken
up by the crop or immobilised, while in the summer mineralised N is more likely to
accumulate or be at risk of loss through leaching or gaseous N emission (Gupta et al.,
2011).
Plants also influence N cycling by regulating C inputs through rhizodeposits and root
turnover, which consequently control microbial activity and N immobilisation (Knops
et al., 2002). During the growing season, crop plant roots extend and occupy new soil
volume, during which the roots release rhizodeposits. Plants may lose 1–30% of
photosynthetically fixed C through their roots as they grow through the soil (Whipps,
1990), though basal root exudation in unstressed conditions is likely to be only 3–5% of
photosynthesised C (Dilkes et al., 2004; Jones et al., 2004a). These rhizodeposits are of
various compositions including amino acids, organic acids, sugars, polysaccharides and
phytohormones (Meharg, 1994), but most are low molecular weight solutes that are
readily available to microorganisms (Jones et al., 2004a). Within hours or days,
microorganisms utilise these available C sources for growth and maintenance
respiration. Microorganisms also use the available C to produce extracellular enzymes
that mineralise soil OM, in order to obtain N, then on microbial death, the N that was
immobilised from soil OM can be released as NH4+ and become available to plants
(Kuzyakov and Xu, 2013), or the dead microorganisms become part of soil OM again to
close the microbial N loop (Knops et al., 2002).
Ch. 2: Literature Review
42
2.6. Molecular Ecology of Nitrifiers
The microorganisms that carry out nitrification, the conversion of NH4
+ to NO3-, were
originally identified as obligately aerobic chemolithoautotrophic bacteria (Lees, 1955).
Autotrophic nitrifiers use this conversion of N to produce energy as well as new
biomass, and compete for NH4+ with heterotrophic immobilising organisms, which use
N to construct biomass, but require organic C for energy production (Booth et al.,
2005). There are two steps of autotrophic nitrification: oxidation of ammonia to nitrite,
followed by oxidation of nitrite to NO3-, carried out respectively by ammonia oxidisers
(both AOB, such as the genera Nitrosomonas and AOA) and nitrite oxidisers (such as
Nitrobacter (Lees, 1955; Monteiro et al., 2014). Ammonia oxidation is the key limiting
step in nitrification, as nitrite oxidation is reliant on nitrite produced by ammonia
oxidation (Kowalchuk and Stephen, 2001). In the past 10 years, with the advent of
metagenomic techniques and identification of the functional gene amoA involved in
ammonia oxidation, it has been recognised that archaea are also capable of ammonia
oxidation and are ubiquitous in soil, marine, sediment and geothermal environments
around the world, and in a variety of climates from humid to semi-arid (Schleper and
Nicol, 2010).
2.6.1. Ammonia-oxidising bacteria
Autotrophic bacterial ammonia oxidisers belong to at least two different phylogenetic
groups, the beta-subclass of the Proteobacteria, including the Nitrosomonas and
Nitrosospira genera and Nitrosococcus mobilis, and the gamma-subclass of
Proteobacteria, including the rest of the Nitrosococcus genus (Purkhold et al., 2000).
Ammonia oxidation in bacteria involves the oxidation of ammonia to an intermediate,
hydroxylamine, catalysed by the AMO enzyme (Kowalchuk and Stephen, 2001). Two
electrons are required, which are generated by the further oxidation of hydroxylamine to
Ch. 2: Literature Review
43
nitrite by the hydroxylamine oxidoreductase enzyme (HAO). Ammonia monooxygenase
has three subunits, coded for by the amoA, amoB and amoC genes (Nicol and Schleper,
2006). Ammonia-oxidising bacteria from the Betaproteobacteria have two or three
copies of the amo operon, while those from the Gammaproteobacteria contain a single
copy (Norton et al., 2002). Quantification of gene copy numbers in soil therefore is not
a direct count of the number of ammonia-oxidising microorganisms.
There is evidence that AMO in the Betaproteobacteria evolved to oxidise ammonia
specifically, while AMO in the Gammaproteobacteria evolved for both ammonia and
methane oxidation (Hooper et al., 1997). In addition, AOB in the gamma-subclass
appear to be more closely related to methane oxidisers in the same subclass than to
ammonia oxidisers in the beta-subclass (Holmes et al., 1995). The ability of AMO of
bacteria in the gamma-subclass to oxidise both ammonia and methane seems to be an
adaptation to incorporate C into cell biomass from methane, methanol or carbon
monoxide, for example when CO2 is limiting to C fixation (Jones and Morita, 1983;
Ward, 1987).
2.6.2. Ammonia-oxidising archaea
Archaeal ammonia oxidisers in soil belong to the phylum Thaumarchaeota, a new
archaeal phylum that was recognised after the discovery of AOA (Brochier-Armanet et
al., 2008; Spang et al., 2010). In many soils, AOA appear to be more abundant than
AOB (Leininger et al., 2006), and may be the reason why nitrification is so prevalent
even when NH4+ concentrations are below the predicted affinity threshold for AOB
(Monteiro et al., 2014).
Ch. 2: Literature Review
44
The ammonia oxidation pathway in AOA may differ fundamentally from AOB.
Evidence for this includes: archaeal amoA sequences are shorter than and only show
about 40% similarity with bacterial amoA sequences (Nicol and Schleper, 2006); there
seems to be no equivalent of the HAO complex or cytochrome c proteins as found in
AOB (Hallam et al., 2006; Walker et al., 2010); and AOA seem to produce energy via a
copper-containing electron transfer system, as opposed to the iron-containing electron
transfer system of AOB (Hallam et al., 2006; Walker et al., 2010). Ammonia oxidation
by AOA therefore either produces an intermediate other than hydroxylamine (as in
AOB), or uses fundamentally different enzymes to produce hydroxylamine and nitrite
(Schleper and Nicol, 2010; Walker et al., 2010). Nitroxyl (HNO) has been hypothesised
as an alternative intermediate (Walker et al., 2010). However, the marine AOA
Nitrosopumilus maritimus was recently shown to produce and consume hydroxylamine
during ammonia oxidation, so AOA likely use novel uncharacterised enzymes to
catalyse ammonia oxidation (Vajrala et al., 2013). One similarity to the
Gammaproteobacteria however is that at least one AOA (Nitrosopumilus maritimus) has
only one copy of amoA in its genome (Walker et al., 2010).
Carbon fixation pathways of AOB and AOA also appear to differ. The C fixation
pathway of AOB uses ribulose biphosphate carboxylase/oxygenase in the Calvin-
Bassham-Benson Cycle. On the other hand, genome sequences suggest that AOA can
utilise acetyl coenzyme A in a modified 3-hydroxypropionate cycle, and also have
components of an oxidative tricarboxylic acid cycle, which could allow AOA to utilise
organic C and grow mixotrophically (Hallam et al., 2006; Walker et al., 2010).
Ch. 2: Literature Review
45
2.6.3. Niche differentiation between ammonia-oxidising bacteria and archaea
Research is currently focussing on finding distinguishing characteristics between AOA
and AOB, specifically with regard to niche specialisation (their adaptation to abiotic and
biotic soil characteristics) and niche differentiation (their resource utilisation patterns;
Hu et al., 2014; Prosser and Nicol, 2012; Yao et al., 2013). This is because both AOB
and AOA are abundant in soil, but their relative abundances vary between regions and
often from site to site. Possible causes that have been proposed include ammonia
concentration and source (Di et al., 2010; Jia and Conrad, 2009), the ability to grow
both autotrophically and heterotrophically (Karlsson et al., 2012; Kelly et al., 2011) and
different pH sensitivities (Bru et al., 2011; Gubry-Rangin et al., 2011). Except for pH,
where acid soils with pH <5.5 are dominated by AOA, none of these factors appear to
be the sole reason for niche specialisation or differentiation between AOA and AOB,
with both bacteria and archaea having enough physiological diversity to grow under all
conditions (Prosser and Nicol, 2012).
In semi-arid regions, as in other environments, both AOB and AOA are widespread, but
the ratio of AOA:AOB can vary widely even in the same continent (Adair and
Schwartz, 2008; O’Sullivan et al., 2013). For example, in semi-arid soils from south-
eastern Australia, archaea tend to dominate the ammonia-oxidising populations, while
in south-western Australia, abundances of AOA and AOB tend to be comparable
(O’Sullivan et al., 2013). Factors that regulate the relative abundance of AOA and AOB
in semi-arid soil may include season of sampling, precipitation, temperature, soil water
content, soil OM content and C:N ratio, however there are few studies that have tested
regulating factors in semi-arid soil, or even described temporal variation in relative
abundances of ammonia oxidisers (Adair and Schwartz, 2008; O’Sullivan et al., 2013;
Sher et al., 2013). Further research also needs to examine the proportion of nitrification
Ch. 2: Literature Review
46
activity that can be attributed to each of these groups of ammonia-oxidising
microorganisms, as growth rates and gene abundances may not reflect actual process
rates.
2.6.4. Nitrite-oxidising bacteria
The second step of nitrification is oxidation of nitrite to NO3-, which is carried out by
nitrite-oxidising bacteria (NOB) and involves nitrite oxidoreductase (NXR) as the main
enzyme (Prosser, 1989). The presence and diversity of NOB are more difficult to
determine using molecular techniques than ammonia-oxidising microorganisms, as
NOB belong to several phylogenetic groups (Ehrich et al., 1995; Teske et al., 1994).
Advances have been made by the design of a polymerase chain reaction (PCR)
cloning/sequencing approach (Poly et al., 2008) and denaturing gradient gel
electrophoresis (DGGE) fingerprint-type approach (Wertz et al., 2008) utilising newly
designed primers for the functional gene nxrA, which encodes the beta-subunit of NXR.
However, there are important differences between the nxrA gene sequences of different
groups of NOB. For example, the primers designed for these studies were able to target
Nitrobacter and Nitrococcus strains, but were not successful for Nitrospira (Wertz et
al., 2008). In addition, there is strong evidence that NOB have multiple copies of the
nxrA gene with different sequences in their genomes, which makes it complicated to
interpret NOB taxonomy and diversity in environmental samples (Poly et al., 2008;
Wertz et al., 2008).
Nitrite-oxidising bacteria may be less drought-tolerant than AOB, so may respond more
slowly than ammonia oxidisers to changes in water availability. This was shown by
nitrite accumulation after the first rains following the dry season in a semi-arid soil
(Gelfand and Yakir, 2008).
Ch. 2: Literature Review
47
2.6.5. Heterotrophic nitrification
Some heterotrophic microorganisms are also able to oxidise ammonia to nitrite
including certain bacteria (e.g. Thiosphaera pantotropha) and fungi (e.g. Aspergillus
flavus) (De Boer and Kowalchuk, 2001; Lees, 1955). Growth of heterotrophic nitrifying
bacteria and fungi never occurs on ammonia alone: heterotrophic nitrification does not
produce energy or cell growth for the microorganism, but may have the function of
being an electron sink (Hooper et al., 1997; Killham, 1990; Robertson and Kuenen,
1990). Heterotrophic nitrifiers can use both organic and inorganic N sources (De Boer
and Kowalchuk, 2001; Zhang et al., 2014), and many are able to denitrify
simultaneously, where nitrite produced is reduced to N2 (De Boer and Kowalchuk,
2001; Robertson and Kuenen, 1990). This combined nitrification-denitrification may be
utilised to maintain high growth rates when oxygen respiration capacity is limited
(Blagodatsky et al., 2006; Stouthamer et al., 1997). Other heterotrophic nitrifiers may
use ammonia oxidation to produce N-oxides in order to inhibit the growth of competing
microorganisms (Honda et al., 1998). Fungal heterotrophic nitrification is by a different
pathway again, as a side effect of cell lysis and lignin degradation when hydroxyl
radicals react with N compounds (De Boer and Kowalchuk, 2001).
Heterotrophic nitrifiers likely use diverse ammonia-oxidising enzymes, that differ from
those of autotrophic bacterial nitrifiers. Certain species such as Thiosphaera
pantotropha have AMO and HAO enzymes like AOB, so the substrates, intermediates
and products of heterotrophic nitrification are similar to autotrophic ammonia oxidation
(Moir et al., 1996). However, the genes that encode AMO and HAO in T. pantotropha
and also in another heterotrophic nitrifier, Methylocystis capsulatus, are not
homologous to those in AOB (Hooper et al., 1997). Instead of HAO, T. pantotropha
uses another protein with iron-sulphur centres to catalyse the reaction of hydroxylamine
Ch. 2: Literature Review
48
to nitrite, while M. capsulatus may use an enzyme similar to cytochrome P-460 of
Nitrosomonas for this reaction (Hooper et al., 1997; Zahn et al., 1994).
Heterotrophic nitrification may be an important source of NO3- and N2O under certain
conditions. These conditions include under native vegetation where organic N is readily
available but there is little NH4+, or in soils with high organic C concentrations and low
pH (Cai et al., 2010; Kurakov et al., 2001; Müller et al., 2014). For example, in some
forest soils, 33–46% of NO3- can be produced by heterotrophic nitrification (Kurakov et
al., 2001). Aerobic heterotrophic nitrification can produce more N2O per cell than
autotrophic nitrification, so may be a significant source of N2O in some soils (Anderson
et al., 1993; Papen et al., 1989). For example, as much as 38% of N2O emissions were
due to heterotrophic nitrification in a black arable soil with high soil organic C content
(Cai et al., 2010). Generally though, heterotrophic nitrification is considered to be
unimportant in most agricultural soils (Barraclough and Puri, 1995; De Boer and
Kowalchuk, 2001; Kurakov et al., 2001).
2.7. Approaches to Limiting Nitrogen Losses from Semi-Arid Soils
Management techniques to limit detrimental N losses due to NO3
- leaching and N2O
emissions from semi-arid soils require a good understanding of the biogeochemistry and
dynamics of the N cycle (Delgado, 2002; Meisinger and Delgado, 2002). There are two
approaches to decrease NO3- leaching: manage the leachate volume and manage the
amount of NO3- in soil (Meisinger and Delgado, 2002). In rainfed cropping systems,
management of leachate volume is difficult because the main source is precipitation, so
effective management needs to focus on managing nitrification and NO3- in soil and
synchronising plant uptake with soil NO3- production. This is also expected to decrease
Ch. 2: Literature Review
49
other N losses such as N2O emissions that are in response to nitrification and
denitrification.
Increasing crop N use efficiency during the growing season might be achieved by
matching N supply to crop demand (a concept known as synchrony), by applying
fertiliser N only when crops can rapidly utilise it and in amounts that are not in excess
of expected crop yields (Meisinger and Delgado, 2002; Murphy et al., 2004). Synchrony
also takes into account N release from organic additions, and particularly in tropical
cropping systems, a lot of research has been invested in understanding how organic
materials of differing qualities show different patterns of nutrient release, and how these
patterns are modified by mixing materials of different qualities, to replace or decrease
the amount of inorganic N fertiliser (reviewed in Palm et al., 2001). Although high
quality plant materials such as legume residues have similar patterns of N availability to
and may be applied as a direct substitute for inorganic fertilisers, N release from no
single organic material can match crop N demand (Palm et al., 2001). Mineralisation of
a mixture of high and low quality plant residues generally has a pattern that is the
weighted average of the individual patterns of the two types of residue, rather than
having a period of delayed rapid N release to match plant demand (Fig. 2.4).
Matching N supply to crop demand minimises N substrates available for nitrifying
microorganisms, so that N is taken up rapidly by crop plants and is no longer available
for loss. This can be achieved by on-site monitoring of soil and plant N, and fertiliser
management techniques such as split applications, banding or deep placement and foliar
applications (Meisinger and Delgado, 2002; Subbarao et al., 2006). Other approaches to
managing soil NO3- and nitrification in semi-arid soils include having a cover crop to
take up N when soil would usually be bare, use of organic fertilisers, promoting N
Ch. 2: Literature Review
50
immobilisation through additions of low-quality organic residues, improving the
precision of N application and application of nitrification inhibitors (Aguilera et al.,
2013; Meisinger and Delgado, 2002).
Figure 2.4. Conceptual nutrient release from high quality (High Q), low quality
(low Q) and a mixture of organic materials in relation to plant uptake. From Palm
et al. (2001).
2.7.1. Nitrification inhibitors
Nitrification inhibitors have been effective tools for many years to decrease nitrification
and keep fertiliser N in soil where it is accessible by crop plants, decreasing loss of N to
the environment (Wolt, 2000). Nitrification inhibitors are chemical compounds that
inhibit some part of the nitrification process (Slangen and Kerkhoff, 1984). Many
nitrification inhibitors act on AMO, the enzyme that catalyses the first step of
nitrification (McCarty, 1999). The exact mechanism differs depending on the
nitrification inhibitor, and may include acting as a substrate for AMO, thus blocking the
enzyme’s active sites and temporarily making the enzyme ineffective; reacting with
AMO and changing its configuration, thus permanently deactivating it; and creating
products that bind to other parts of the cell and inhibit normal cell metabolism
(McCarty, 1999).
Ch. 2: Literature Review
51
Table 2.3. Common agricultural nitrification inhibitors (Hauck, 1980; Subbarao et
al., 2006). Common name/
Abbreviation Chemical Formula Application method
Nitrapyrin, N-serve 2-chloro-6-(trichloromethyl)-
pyridine
Injection into soil with anhydrous ammonia,
liquid fertilisers, solid fertiliser coatings
DCD dicyandiamide Mixing with solid N fertilisers, e.g. urea
DMPP 3, 4-dimethyl pyrazole phosphate Mixing with solid N fertilisers, e.g. urea
AM 2-amino-4-chloro-6-methyl
pyrimidine
Solid N fertiliser coatings
Many chemical compounds inhibit some part of the nitrification process, whether
ammonia oxidation, hydroxylamine oxidation or nitrite oxidation. These compounds
range from general inhibitors such as pesticides, herbicides and fungicides to specific
inhibitors (Hauck, 1980). Some natural compounds produced by plants (biological
nitrification inhibitors) also inhibit nitrification, such as neem seed and oil-extracted
cake, which is produced by the Indian lilac tree (Azadirachta indica; Sharma and
Prasad, 1995). Some of the chemical nitrification inhibitors which are marketed for
agricultural use are listed in Table 2.3.
2.7.2. Nitrapyrin
Nitrapyrin, or 2-chloro-6-(trichloromethyl)-pyridine, has most potential for use in semi-
arid agricultural soils because out of the three most well-known commercial nitrification
inhibitors (nitrapyrin, DCD and DMPP; Subbarao et al., 2006), nitrapyrin was the most
effective inhibitor of nitrification at 25 °C and above (Ali et al., 2008; Chen et al.,
2010). Nitrapyrin is a heterocyclic N compound, with a chlorine atom and a
trichloromethyl group substituted on either side of the ring N (Fig. 2.5; McCarty, 1999).
Properties of nitrapyrin include that it is volatile, insoluble in water, but soluble in
Ch. 2: Literature Review
52
solvents such as xylene (McCarty, 1999; Slangen and Kerkhoff, 1984). Nitrapyrin has
been formulated for application with liquid fertilisers, anhydrous ammonia and as as a
solid coating on fertilisers (Nelson and Huber, 1980). The volatility of nitrapyrin
however means that it is necessary to immediately incorporate it into the soil and
surface application is not recommended (Nelson and Huber, 1980; Wolt, 2000).
Figure 2.5. Structure of nitrapyrin, 2-chloro-6-(trichloromethyl)-pyridine. Adapted
from McCarty (1999).
The mechanism by which nitrapyrin inhibits nitrification is not completely understood.
However, evidence indicates that nitrapyrin is involved with AMO (Campbell and
Aleem, 1965a; Vannelli and Hooper, 1992). Nitrapyrin is an alternative substrate for
AMO, the active site of which specifically binds and orients the aromatic ring of
nitrapyrin and forces the trichloromethyl group into the enzyme’s oxygen binding site
(Hooper et al., 1997). The trichloromethyl group of nitrapyrin is then likely reduced
instead of oxygen, producing 6-chloropicolinic acid (Vannelli and Hooper, 1992).
Nitrapyrin is only a weak substrate of AMO however, so the binding of nitrapyrin to
AMO doesn't entirely explain how nitrapyrin can so strongly inhibit nitrification
(McCarty, 1999). Inhibition of ammonia oxidation might also be partly accounted for
by the product, 6-chloropicolinic acid, which binds indiscriminately to membrane
proteins and could inhibit other membrane processes (Vannelli and Hooper, 1992). In
Ch. 2: Literature Review
53
addition, nitrapyrin also appears to block electron transfer from ammonia to oxygen at
the cytochrome oxidase site involved in ammonia oxidation, by binding or chelating the
copper component of the cytochrome oxidase (Campbell and Aleem, 1965a). Nitrapyrin
has little effect on the hydroxylamine-oxidising enzyme systems or nitrite oxidation (the
subsequent steps of nitrification) compared to the ammonia-oxidising enzymes, even at
high concentrations (Campbell and Aleem, 1965a, b).
Nitrapyrin has varying effects on other biological N transformations in soil. Nitrapyrin
has no effect on microbial activity in general as measured by CO2 production, but may
inhibit N mineralisation, though only when applied in high concentrations of 20 µg g-1
(Laskowski et al., 1975; Malhi and Nyborg, 1983). Nitrapyrin has been reported to
either have no effect on N immobilisation, or to stimulate N immobilisation due to a
longer retention time of NH4+ (Aulakh and Rennie, 1984; Osiname et al., 1983).
Nitrapyrin applied with NH4+ can also stimulate heterotrophic bacterial growth
(Kangatharalingam and Priscu, 1993). Nitrapyrin can however decrease rates of N
transformations that are reliant on nitrification, such as fixation of nitrite into OM, N2O
emissions, and other gaseous N emissions (Aulakh et al., 1984; Azhar et al., 1986a;
Azhar et al., 1986b; Bremner and Blackmer, 1978; Chen et al., 2010; Smith and Chalk,
1980).
The persistence of nitrapyrin in soil after application and its subsequent bioactivity is
regulated by soil properties such as temperature, pH and OM content. Increasing
temperature decreases the effectiveness of nitrapyrin by increasing the rate of microbial
degradation of nitrapyrin, and likely increasing the recovery rate of surviving nitrifying
microorganisms (Goring, 1962). Nitrapyrin can, however, be effective at inhibiting
nitrification at soil temperatures at 25–35 °C, and also decreased N2O emissions by 96–
Ch. 2: Literature Review
54
98% at 25 °C following applications of urea (Ali et al., 2008; Chen et al., 2010). With
increasing soil pH, nitrifiers are more susceptible to nitrapyrin, but surviving
microorganisms are able to recover more quickly, so overall more nitrapyrin is required
to effectively block ammonia oxidation (Goring, 1962; Hendrickson and Keeney, 1979).
Soil OM can absorb nitrapyrin, making it unavailable for inhibition, and also stimulates
the microorganisms that degrade nitrapyrin by providing an energy source (Goring,
1962; Lewis and Stefanson, 1975).
In semi-arid soils specifically, as in soils from other climates, the factors which
determine the persistence and bioactivity of nitrapyrin are those described above:
temperature, soil OM content, pH (Goring, 1962). This is demonstrated by the original
experiments describing nitrapyrin, which used a range of soils including 17 from
California, a region with a semi-arid Mediterranean-type climate (Goring, 1962). Under
cooler conditions of the winter growing season, nitrapyrin appears to be effective at
inhibiting nitrification in the field. For example, nitrapyrin decreased nitrification of
NH4+ fertilisers applied to several fallow Californian soils in the field during the winter
growing season, increasing recovery of fertiliser NH4+ by up to 77% after 21 weeks
depending on the concentration of nitrapyrin (Turner et al., 1962). Addition of
nitrapyrin to NH4+ fertilisers for irrigated cotton, sweet corn and sugar beets in
California also increased yields by up to 32%, depending on soil type and concentration
of inhibitor (Swezey and Turner, 1962).
The effectiveness of nitrapyrin at inhibiting nitrification outside the growing season has
not been investigated. For example, it is unclear if nitrapyrin can inhibit nitrification
during summer fallow when rain events encourage OM decomposition and production
of inorganic N, and when soil temperatures are elevated (above 25 °C). Although
Ch. 2: Literature Review
55
nitrapyrin has been evaluated in a semi-arid soil during the summer, the soil was not
fallow and nitrapyrin was used for the purpose of retaining N fertiliser (Ali et al., 2008).
Nitrapyrin was only effective at elevated soil temperatures (35 °C) when applied at rates
greater than that normally recommended for temperate environments (i.e. >0.25–0.50
mg kg-1, or 0.56–1.12 kg ha-1; Ali et al., 2008). For example applying nitrapyrin
retained 50% of applied NH4+ in soil after 4 weeks when applied at 8.32 µg g-1, and
retained 88% of applied NH4+ after 12 weeks at 52 µg g-1 (Ali et al., 2008). This
suggests that nitrapyrin has the potential to inhibit nitrification at the elevated
temperatures experienced by soil during summer fallow in semi-arid climates.
2.8. Conclusions
The factors that ultimately influence the risk of N loss in semi-arid agricultural soils are
varied and complex. This review has described the effects of soil water, temperature, C
and N substrate availability, pH and the relationships that exist between plants and
microorganisms. Many questions remain to be answered however with regards to
interacting soil and environmental conditions on soil N supply pathways and internal
soil N cycling, especially during the hot and dry summer fallow. With the advent of
molecular techniques, new insights are being gained into the role of microorganisms in
N loss processes, particularly the influence of the relative abundances and community
structure of AOA and AOB on nitrification. What is not yet clear is what factors
influence the relative importance of AOA and AOB on nitrification rates, their seasonal
dynamics and how they can be managed to prevent N loss. The greatest risk of N loss in
semi-arid rainfed agricultural soils of south-west Australia appears to be in response to
production of inorganic N outside the growing season. Manipulation of microbially-
mediated N transformation rates to decrease the risk of loss may be possible by
Ch. 2: Literature Review
56
managing C and N substrate availabilities, or by directly controlling nitrification using a
nitrification inhibitor. However, as will be explored in this thesis, it remains to be seen
whether management of risk of N loss is possible outside the growing season.
57
Chapter 3.
Root exudate carbon was more effective than soil
organic carbon at decreasing the risk of nitrogen
loss in a semi-arid soil
3.1. Abstract
The need for increased food production to support the growing global population
requires more efficient nutrient management and prevention of nitrogen (N) losses from
both applied fertiliser and organic matter (OM) decomposition. This is particularly
important in semi-arid rainfed cropped soils, where soil water and temperature are the
dominant drivers of N cycling rather than agricultural management. Here we used 14C
and 15N techniques to examine how peptide/amino acid turnover, gross and net N
transformation rates and nitrous oxide emissions responded to changes in both total and
root exudate soil organic C (SOC) pools. Soil was collected from a semi-arid rainfed
field trial with one winter crop per year followed by a summer fallow period, where
additions of straw/chaff over 10 years increased total SOC by 76% (Tilled soil
compared to Tilled+OM soil). These soils were incubated with or without synthetic root
exudate mixture to account for both sources of SOC available to microorganisms in soil.
Laboratory experimental conditions reflected soil temperatures ranging from winter
cropping (5 °C) to summer fallow (50 °C). Increased total SOC did not decrease the risk
Ch. 3: N Loss and Carbon
58
of N loss as defined by the nitrification:immobilisation (N:I) ratio at most temperatures,
so was not an effective management tool to control N losses. In comparison, root
exudate addition decreased the risk of N loss at all temperatures and for both field trial
treatments. Increased net N mineralisation and decreased microbial C use efficiency at
temperatures greater than 30 °C resulted in significant ammonium accumulation.
Microbial decomposers appeared to use amino acid-C for growth but peptide-C for
energy production. Findings indicate that the greatest risk of N loss in these semi-arid
soils will occur during the start of growing season rains, due to inorganic N
accumulation over summer fallow when there are high soil temperatures, occasional
significant rainfall events and no release of root exudates from growing plants. While
most attempts to manipulate the soil N cycle have occurred during the winter cropping
period, our findings highlight the need to manage N supply during summer fallow if we
are to minimise losses to the environment from semi-arid soils.
Ch. 3: N Loss and Carbon
59
3.2. Introduction
Concerns regarding food security, low fertiliser use efficiencies and the need to
decrease greenhouse gas emissions necessitate the development of more sustainable
agricultural systems. Semi-arid and arid regions cover approximately half of the global
agricultural area (The World Bank, 2008) and are thus of major importance to food
production and associated nutrient management. Sustainable agriculture in semi-arid
regions presents unique challenges, especially in rainfed cropping systems, where
rainfall and temperature are the main drivers of microbial activity and cycling of
nutrients such as nitrogen (N; Hoyle and Murphy, 2011; Noy-Meir, 1973). Semi-arid
regions in the Southern Hemisphere have experienced a drying trend since the 1970s
predominantly at the start of the grain-growing season (April and May; Cai et al., 2012).
Although there has been a reported 15% decrease in heavy winter rainfall between 1950
and 2003 (Nicholls, 2010), summer rainfall events that occur outside of the period of
crop and annual pasture growth are increasing (Alexander et al., 2007). More summer
rainfall is expected to increase soil organic matter (OM) decomposition and N supply at
a time when there is limited or no plant N uptake (Austin et al., 2004; Murphy et al.,
1998b). Nitrogen supply in excess of microbial demand results in N release, which is at
risk of loss to the environment if nitrified.
Nitrogen losses are undesirable, potentially limiting crop yield and having detrimental
off-site environmental impacts [e.g. N leaching and emissions of nitrous oxide (N2O)].
Management practices that mitigate N losses therefore need to be developed. Losses of
N are particularly difficult to mitigate when they are not in response to N fertiliser
additions, but originate from soil OM decomposition. The timing of inorganic N release
from soil OM decomposition is difficult to change (Hoyle and Murphy, 2011) as
Ch. 3: N Loss and Carbon
60
peptide and amino acid turnover is primarily regulated by water and temperature
(Farrell et al., 2013; Jones et al., 2009). Instead management options are more likely to
succeed when targeting the subsequent fate of the released inorganic N. Nitrification is
the key pathway for N loss, as nitrate (NO3-) is susceptible to leaching, and the
greenhouse gas N2O may be produced during and after nitrification (Wrage et al.,
2001). One way to decrease potential N loss is by increasing microbial N
immobilisation and thus decreasing the amount of inorganic N that is available for
nitrification and loss (Crews and Peoples, 2005). The nitrification to immobilisation
ratio, or N:I ratio, represents the balance between the N loss and retention pathways
(Aber, 1992; Tietema and Wessel, 1992). This index has been correlated with NO3-
leaching losses in temperate grassland and arable soils (Stockdale et al., 2002), but little
is known about the behaviour of the N:I ratio in cropped soils from other climates.
Increased microbial N immobilisation and decreased potential for N loss could be
achieved through manipulation of soil carbon (C) availability. Soil organic C (SOC) and
N cycles are inextricably linked: both N mineralisation and immobilisation pathways
are mediated by heterotrophic microorganisms, which require C from organic sources
for growth and production of energy. When heterotrophic immobilisers are limited by C
compared to N, net production of inorganic N occurs, which is then at risk of
nitrification and subsequent loss (Barraclough, 1997). The majority of our
understanding about soil C and N cycling processes has been gained through research in
temperate and humid environments, but N cycling appears to behave unexpectedly in
semi-arid regions, particularly in warm and dry seasons (Parker and Schimel, 2011;
Sullivan et al., 2012). For example, in Californian grassland soil, net N mineralisation
rates and nitrification potentials are greater during the warm dry summer than during the
cooler, wetter winter, resulting in greater ammonium (NH4+) pools in the summer
Ch. 3: N Loss and Carbon
61
(Parker and Schimel, 2011). In addition, in south-western Australian soils, heterotrophic
N immobilisation becomes constrained at temperatures greater than 30 °C, and
mineralisation–immobilisation turnover becomes decoupled, resulting in the
accumulation of inorganic N (Hoyle et al., 2006; Luxhøi et al., 2008). This
mineralisation-immobilisation turnover decoupling at elevated temperatures was
hypothesised to be due to C substrate limitation, caused by microorganisms consuming
available C faster than C could be replaced by diffusion from nearby soil microsites
(Hoyle et al., 2006). We hypothesised therefore that increasing soil C availability will
decrease the potential of N loss (i.e. decrease the N:I ratio), especially at elevated
temperatures as occur during summer in some semi-arid soils.
Soil organic C content and availability may be changed by agricultural management
practices that build or remove C. These practices include tillage and OM inputs over the
longer term (Dick, 1992; Liu et al., 2014), or shorter term rhizosphere processes such as
inputs of labile C from root exudates and mycorrhiza (Jones et al., 2004a; Kaiser et al.,
2015). The objective of this research was to understand how different sources of C alter
N transformations in arable semi-arid soil. Specifically, we investigated how total SOC
versus root exudate C affected (a) N decomposition pathways; and (b) the subsequent
fate of N and risk of N loss as defined by the N:I ratio, under conditions reflective of
both summer and winter conditions in semi-arid soils.
3.3. Methods
3.3.1. Study site and field soil collection
Soil was collected from a field research site approximately 221 km north-northeast of
Perth in the agricultural production zone (wheatbelt) of Western Australia (30.00° S,
Ch. 3: N Loss and Carbon
62
116.33° E). The soil is a sand (92% sand, 2% silt, 6% clay) and classified as a Basic
Regolithic Yellow-Orthic Tenosol (Australian soil classification; Isbell, 2002), or a
Haplic Arenosol (IUSS Working Group WRB, 2007). The area has a semi-arid climate
with cool, wet winters and hot, dry summers (Fig. 3.1). At the weather monitoring
station closest to the study site (Dalwallinu, 30.28° S, 116.67° E) the historical mean
annual rainfall is 288 mm and mean monthly temperatures range from 5.8 to 35.3 °C
(1997–2013 data; Commonwealth of Australia Bureau of Meteorology,
http://www.bom.gov.au/climate/data). Soil temperatures at 5 cm depth at the research
site ranged from 6.2–45.6 °C (2008–2012).
Figure 3.1. Daily maximum and minimum soil temperatures at 5 cm depth and
daily rainfall for 2011 at the research site.
The field site consisted of two SOC management treatments: (i) tilled soil (control;
using offset disks before seeding to 10 cm depth and seeded with knife point tines to 10
cm depth; “Tilled”), and (ii) tilled soil plus OM additions (“Tilled+OM”) of 20 t ha-1 of
barley straw, canola chaff and oaten chaff in 2003, 2006 and 2010 respectively. This
represented an additional input to soil of 27 t C ha-1, of which 7.9 t C ha-1 was retained
Ch. 3: N Loss and Carbon
63
as SOC (i.e. microbial C use efficiency of 29%). This equated to 76% more SOC in
Tilled+OM soil than in Tilled soil (Table 3.1). Treatment plots (80 m by 10 m) were
randomly allocated to three replicate blocks when the experimental site was established
(2003), and have since been planted to an annual crop each winter (lupin-wheat-wheat
rotation).
Soil was collected (Ap horizon; 0–10 cm) from each of the three replicate field
treatments in May 2011 while the soil was dry (0.012 g H2O g -1 dry soil) and before
winter rain commenced. A composite soil sample of 18 cores (7 cm diameter, 10 cm
depth) was collected from each treatment plot in a zigzag sampling pattern, sieved (<2
mm) and stored at 4 °C until further analysis. Each field replicate (n = 3) was kept
separate for use in the laboratory experimental design.
3.3.2. Laboratory experimental design
The laboratory experiment consisted of soil collected from the two field trial SOC
treatments (Tilled and Tilled+OM) as described above, by three field replicates. Sub-
samples from each replicate bag of soil received one of the laboratory synthetic root
exudate treatments [plus root exudates (+RE) or no root exudates (No RE)], by four
laboratory incubation temperatures for low molecular weight OM (LMWOM) turnover
(5, 15, 30 and 50 °C) or seven temperatures for the other N transformation rate
measurements (5, 10, 15, 20, 30, 40 and 50 °C). The synthetic root exudate solution was
used to simulate conditions when plants are present in the soil. The mixture consisted of
D-glucose (6.75 mM); D-fructose and D-sucrose (1.35 mM each); succinic acid, citric
acid, L-malic acid and fumaric acid (675 µM each); and glycine, L-leucine, L-alanine,
L-valine, L-serine, L-glutamic acid, L-aspartic acid, L-lysine, L-arginine, and L-
phenylalanine (135 µM each). This solution delivered 50 µg C g-1 dry soil (C:N ratio of
Ch. 3: N Loss and Carbon
64
38:1) in 250 µL for LMWOM turnover (added to 5 g soil) or 1 mL for all other N
transformation measurements (added to 20 g soil).
Table 3.1. Properties of field trial soils (0–10 cm depth) collected eight years after
soil organic carbon treatments were imposed. Values represent means ±SEM (n = 3).
Abbreviations: LFOM: light fraction organic matter; DOC: dissolved organic carbon;
MBC: microbial biomass carbon. Tilled Tilled+OM
Soil pHCaCl2 # 6.17 ± 0.19 6.30 ± 0.11
Total carbon (%) § 0.76 ± 0.08 1.36 ± 0.21*
Total nitrogen (%) § 0.07 ± 0.00 0.11 ± 0.02
Soil C:N ratio 11.2 ± 0.6 12.3 ± 0.3
LFOM carbon (mg C g-1) §‡ 0.91 ± 0.13 2.04 ± 0.39
LFOM nitrogen (mg N g-1) §‡ 0.05 ± 0.01 0.12 ± 0.03
LFOM C:N ratio 17.0 ± 0.23 16.6 ± 0.45
DOC (µg C g-1) † 120.4 ± 3.8 236.0 ± 26.3*
MBC (µg C g-1) ¶ 118.4 ± 17.3 218.9 ± 43.7
* +OM soil significantly different from No OM soil at P < 0.05.
# Soil pH measured in 0.01 M CaCl2 with a 1:5 soil:extract ratio.
§ Total C, total N, LFOM C and LFOM N determined by dry combustion of finely ground air-dry soil or
LFOM using an Elementar Vario MACRO CNS elemental analyser (Hanau, Germany).
‡ Light fraction organic matter recovered by density separation with deionised water (1.05 g cm-3).
† Dissolved organic C was extracted using 0.5 M K2SO4 (20 g soil to 80 mL extract) and analysed using
an OI Analytical Aurora 1030 Wet Oxidation TOC Analyzer (College Station, TX, USA).
¶ Microbial biomass C determined by fumigation–extraction (Brookes et al., 1985), analysed for
oxidisable C as described for DOC, and then a kEC factor of 0.45 used to convert the oxidisable C ‘flush’
into MB-C (Wu et al., 1990).
Soil was pre-incubated for 7 d at the specified temperatures to pre-condition the soil
microorganisms, as microbial community structure and function differ with incubation
temperature (Cookson et al., 2007). On day 1 and day 4 (during pre-incubation) and on
day 8 (coinciding with 14C or 15N application; see sections below) the synthetic root
exudate mixture, or an equivalent amount of deionised water (≤18.2 MΩ), was added to
the soil. In total the +RE treatment received 100 µg C g-1 dry soil and 2.64 µg N g-1 dry
soil prior to measurement of LMWOM turnover and N transformation rates. This was
Ch. 3: N Loss and Carbon
65
equivalent to the mass of C contained in the microbial biomass of the Tilled soil (Table
3.1) and was thus sufficient to ensure no C limitation to the microbial population during
incubation.
3.3.3. Peptide and amino acid turnover
Mineralisation of LMWOM substrates was examined by determining 14C-labelled
peptide and amino acid turnover. Five grams of soil was placed in 50 mL polypropylene
vials and pre-incubated for 7 d, with 125 µL of either synthetic root exudate mixture or
deionised water added to the soil on days 1 and 4 as described above. To determine the
rate of 14CO2 evolution after pre-incubation, 250 µL of the synthetic root exudate
mixture (another 50 µg C g-1 dry soil and 1.32 µg N g-1 dry soil) or deionised water was
spiked with either 14C-labelled peptide (L-trialanine, ~1.5 mM, 0.28 kBq, 0.008 µCi,
American Radiochemicals Inc., USA) or 14C-labelled amino acids (~3 mM, 0.27 kBq,
0.007 µCi, American Radiochemicals Inc., USA) and added to the surface of the soil on
day 8. The amino acids were an equimolar mixture of 0.2 mM 14C-labelled L-amino
acids (alanine, arginine, aspartic acid, glutamic acid, glycine, histidine, isoleucine,
leucine, lysine, phenylalanine, proline, serine, threonine, tyrosine, valine).
To capture evolved 14CO2, a 1 M sodium hydroxide (NaOH; 1 mL) trap was placed
inside each polypropylene vial and suspended above the soil and the vial hermetically
sealed. 14CO2 evolution was monitored by replacing the NaOH trap after 0.5, 1, 2, 4, 8,
10, 24, 48, 120, 144 and 168 h. The 14C content of the 1 M NaOH traps was determined
by adding Scintisafe 3® scintillation cocktail (Fisher Scientific, Loughborough, UK) and
the 14C content was subsequently measured using a Wallac 1404 liquid scintillation
counter (Wallac EG&G, Milton Keynes, UK).
Ch. 3: N Loss and Carbon
66
3.3.4. Modelling 14C dynamics
Mineralisation of LMWOM was modelled from the amount of 14C substrate remaining
in the soil using SigmaPlot 12.3 (Systat Software Inc., San Jose, CA) and confirmed
with R version 2.15.2 (R Foundation for Statistical Computing, Vienna, Austria). For
the majority of treatments a double first-order exponential decay model was fitted to the
data to represent a biphasic pattern of mineralisation:
f = ( exp–k1t) ( exp–k2t) (Eqn 3.1)
where f is the amount of 14C remaining in the soil, and describe the size of the
each mineralisation pool, and correspond to the respective rate constants for each
mineralisation phase, and t is time. The first rapid phase described by is considered
to reflect 14CO2 efflux as substrates are immediately used for catabolic processes (i.e.
respiration; Boddy et al., 2007). The remaining 14C-substrate is considered to be
immobilised in the microbial biomass via anabolic processes. The second, slower
mineralisation phase is attributed to the use of this C temporarily immobilised in
the biomass (i.e. storage-C; Boddy et al., 2007; Farrar et al., 2012).
For some treatments at 5 and 50 °C a simpler first-order exponential model with
asymptote fitted the data better:
(Eqn 3.2)
where the asymptote value describes a pool that is unavailable for microbial
mineralisation (recalcitrant C), describes the size of a single, very slowly
mineralisable pool (labile C) with k representing the exponential decay constant for this
pool.
The substrate half-life for the first mineralisation pool ( and for double and single
exponential decay models respectively) was calculated using the following equation:
Ch. 3: N Loss and Carbon
67
(Eqn 3.3)
To calculate the proportion of C immobilised by the microbial biomass, we calculated
the microbial C use efficiency as follows (Manzoni et al., 2012; Sinsabaugh et al.,
2013):
(Eqn 3.4)
where is the amount of C immobilised by the microbial biomass (i.e. difference
between total 14C input minus 14CO2 evolved), and accounts for C lost through
respiration (14CO2 evolved).
For data where a single exponential decay equation was used, the following equation
was used.
(Eqn 3.5)
where is the amount of recalcitrant C and accounts for C lost through respiration
(14CO2 evolved). Since the amount of C immobilised by the microbial biomass was
determined by difference (i.e. total 14C input minus 14CO2 evolved) this could include
substrate in the microbial biomass as well as any 14C substrate remaining in the soil at
the end of the incubation period. However, residual 14C substrate is considered to be
negligible as 14C substrates such as amino acids and oligopeptides are rapidly
immobilised by the microbial biomass leaving less than a few percent of the total in
solution after a few hours (Farrell et al., 2013). In addition, transfer of 14C to humified
soil OM would be insignificant over the time courses represented in these experiments.
3.3.5. Gross N transformation rates and inorganic N
Gross N transformation rates were determined by 15N isotopic pool dilution (Kirkham
and Bartholomew, 1954). The bulk soil samples were adjusted to 45% water-filled pore
Ch. 3: N Loss and Carbon
68
space (WFPS), mixed, left to equilibrate overnight at 4 °C, and then 20 g of soil was
packed into 120 mL vials to a bulk density of 1.4 g cm-3. Subsamples of each treatment
combination were then pre-incubated for 7 d at temperatures representative of field soil
conditions (5, 10, 15, 20, 30, 40 and 50 °C). Each vial was placed inside an airtight
glass jar fitted with gas septum ports in the lids to enable headspace gas analysis. Water
(10 mL) was added to the jars (but not in contact with the soil) to maintain humidity and
thus minimise soil drying. The jars were vented every 24 h to maintain an aerobic
environment. On days 1 and 4, 0.5 mL of either synthetic root exudate solution or
deionised water (≤18.2 MΩ) was added to subsample vials, for a total of 50 µg C g-1 dry
soil and 1.32 µg N g-1 dry soil during pre-incubation.
After pre-incubation, 1 mL of 15N-enriched (60 atom %) ammonium sulphate
[(15NH4)2SO4] was applied as multiple droplets to each vial of soil to obtain a
concentration of 5 µg N g-1 dry soil. The +RE treatment also received a second
application of synthetic root exudates (50 µg C g-1 dry soil and 1.32 µg N g-1 dry soil) in
the same 1 mL aliquot as the (15NH4)2SO4. The 1 mL aliquot increased the soil water
content to approximately 60% WFPS: below the WFPS at which nitrification becomes
limited by oxygen exchange in soils from this study region (Gleeson et al., 2010), and at
the upper limit of soil WFPS observed in the field (Barton et al., 2011; Barton et al.,
2013b). The vials were incubated inside airtight jars at the temperatures described above
until they were extracted. Two extraction times were selected based on a previous 15N
isotopic pool dilution study by Hoyle et al. (2006) in a similar semi-arid soil: T0 = 4–6 h
and T1 = 24 h after 15N addition. At each of these times, subsamples were shaken with
80 mL of 0.5 M potassium sulphate (K2SO4) for 30 min then filtered through Whatman
No. 42 filter paper using Buchner funnels under vacuum. The extracts were kept frozen
until further analysis for inorganic N concentration and 15N enrichment.
Ch. 3: N Loss and Carbon
69
Ammonium and NO3- concentrations in soil extracts were determined by colorimetric
analysis using the modified Berthelot reaction for NH4+ (Krom, 1980; Searle, 1984) and
the hydrazinium reduction method for NO3- (Kamphake et al., 1967; Kempers and Luft,
1988) on a Skalar San Plus auto-analyser (Skalar Inc., Breda, The Netherlands). Net N
mineralisation and net nitrification rates over the 7 d pre-incubation were calculated
from the difference between NH4+ and NO3
- concentrations before and after pre-
incubation.
The soil extracts were prepared for 15N/14N isotope ratio analysis using a modified
diffusion method (Brooks et al., 1989; Sørensen and Jensen, 1991). The NH4+ and NO3
-
within the extracts was, in a two-stage process, trapped on separate acidified diffusion
disks as ammonia (NH3). The disks were subsequently analysed for %N and 15N/14N
isotope ratio by the UC Davis Stable Isotope Facility, using an Elementar Vario EL
Cube elemental analyser (Elementar Analysensysteme GmbH, Hanau, Germany)
interfaced to a PDZ Europa 20-20 isotope ratio mass spectrometer (IRMS; Sercon,
Cheshire, UK). For further details see the UC Davis website
(http://stableisotopefacility.ucdavis.edu/).
Any residual inorganic N remaining in the soil after extraction was removed by filtering
with a further 80 mL of 0.5 M K2SO4 and then two subsequent 80 mL volumes of
deionised water. The washed soil was dried at 70 °C, ground to a fine powder, and
analysed for %N and 15N/14N isotope ratio as described above. Total recovery of applied
15N after 24 h from the NH4+, NO3
- and residual soil pools was on average 98% (data
not shown).
Ch. 3: N Loss and Carbon
70
3.3.6. Modelling N transformation rates
The numerical model FLUAZ (Mary et al., 1998) was used to simulate gross N
transformation rates. The lowest mean weighted errors were obtained when
mineralisation and nitrification were modelled using zero-order kinetics, immobilisation
using first-order kinetics and we assumed no denitrification. Denitrification was set to
zero in the model as measured N2O fluxes were low (see Results section 3.4.3) and a
sensitivity analysis indicated no influence of these low N2O fluxes on modelled gross N
transformation rates. The model was unable to simulate gross N cycling rates at 40 and
50 °C in some of the soils due to a convergence problem between the fitted parameters,
which may be linked to observed rapid dilution of 15N enrichment of the NH4+ pool
prior to T0 at elevated temperatures.
3.3.7. Nitrous oxide analysis
Nitrous oxide fluxes were determined by collecting headspace gas samples (15 mL)
from all treatment jars 24 h after 15N was added (i.e. before soil extraction). Three
replicate samples of the background concentration of N2O in air were also taken prior to
closing the jars. Samples were stored in 12 mL Labco Exetainers under positive
pressure before analysis for concentration and 15N atom % of N2O by the UC Davis
Stable Isotope Facility using a ThermoFinnigan GasBench + PreCon trace gas
concentration system interfaced to a ThermoScientific Delta V Plus IRMS (Bremen,
Germany). For further details see the UC Davis website (http://
stableisotopefacility.ucdavis.edu/).
3.3.8 Statistical analysis
Analysis of variance (ANOVA) with associated TukeyHSD post hoc tests were carried
out using R version 3.1.0 (R Foundation for Statistical Computing, Vienna, Austria) to
Ch. 3: N Loss and Carbon
71
determine if there were significant differences between the soil properties of the SOC
treatments. A mixed model, PROC MIXED from SAS version 9 (SAS Institute Inc.,
Cary, NC, USA) was used to determine significant effects of SOC treatment, addition of
synthetic root exudates and temperature on 14C-labelled LMWOM substrate half-lives,
microbial C use efficiencies, inorganic N, net N cycling rates, N2O flux and 15N2O
enrichment. Gross N transformation rates were compared using the 95% confidence
intervals generated by the FLUAZ model.
3.4. Results
3.4.1. Soil organic matter turnover (N supply)
Peptide mineralisation data was best represented by a double first-order exponential
decay model (r2 = 0.9904 ± 0.0024), except for soil incubated at 50 °C and +RE soil
incubated at 5 ºC. A single-order exponential decay model with asymptote (r2 = 0.9733
± 0.0052) was fitted to the exceptions. Amino acid mineralisation data was also best
described by a double first-order exponential decay model (r2 = 0.9974 ± 0.0003).
Total SOC treatment had no significant effect on the microbial C use efficiencies of
peptides (mean of 42.8% at 5–30 °C) or amino acids (mean of 70.8% at 5–30 °C) except
at 50 °C where Tilled+OM soil was greater than Tilled soil (P<0.0001; Fig. 3.2).
Addition of synthetic root exudates (+RE) decreased peptide C use efficiencies at 5 and
50 °C by a mean of 14% (P<0.05), but increased peptide C use efficiencies at 30 °C by
a mean of 20% (P<0.0001; Fig. 3.2a–b). Root exudates also decreased amino acid C use
efficiencies at 50 °C by a mean of 14% (P<0.0001), but not at other temperatures
(P>0.05; Fig. 3.2c–d). Across all treatments, C use efficiencies were about half at 50 °C
compared to 30 °C (P<0.0001).
Ch. 3: N Loss and Carbon
72
Both total SOC and root exudate treatments had minimal effect on peptide and amino
acid turnover between 15 and 30 °C (Fig. 3.3a–d). However at 5 °C, the half-lives of
both peptides and amino acids significantly decreased in the Tilled+OM treatment
(P<0.05; Fig. 3.3a–d). Addition of synthetic root exudates (+RE) only increased amino
acid half-lives at 5 °C (P<0.01; Fig. 3.3c–d).
Figure 3.2. Influence of temperature on microbial carbon use efficiencies of (a) 14C-labelled peptides without root exudates; (b) 14C-labelled peptides with root
exudates; (c) 14C-labelled amino acids without root exudates; and (d) 14C-labelled
amino acids with root exudates. Error bars are ±SEM (n = 3), and may be smaller than
the symbols. Legend is the same for all panels. Legend abbreviation: OM: organic
matter.
Ch. 3: N Loss and Carbon
73
Figure 3.3. Influence of temperature on half-lives of pool a1 of (a) 14C-labelled
peptides without root exudates; (b) 14C-labelled peptides with root exudates; (c) 14C-labelled amino acids without root exudates; and (d) 14C-labelled amino acids
with root exudates. Error bars are ±SEM (n = 3), and may be smaller than the symbols.
Legend is the same for all panels. Legend abbreviation: OM: organic matter.
3.4.2. Nitrogen transformation rates and inorganic N pools
Gross N transformation rates increased linearly to 30 °C, at which point gross N
mineralisation, nitrification and immobilisation rates averaged across both RE
treatments were 2-, 2.2- and 2.8-fold greater in Tilled+OM than Tilled soil, respectively
(Fig. 3.4a–b, 3.5a–d). In addition, net N mineralisation rates showed a significant
increase from 30–50 °C; Tilled+OM soil (maximum 6.3 µg N g-1 d-1) was greater than
Tilled soil (maximum 2.5 µg N g-1 d-1; P<0.001; Fig. 3.4c–d). Net N mineralisation
rates were negligible from 5–20 °C (0.02 µg N g-1 d-1) with no treatment effect (Fig.
3.4c–d). Microbial demand for NH4+ by nitrifiers (Fig. 3.5a–b) and immobilisers (Fig.
Ch. 3: N Loss and Carbon
74
3.5c–d) decreased above 30 °C. As a consequence the NH4+-N pool size rapidly
increased from 3.2 µg N g-1 at 30 °C to 60.5 µg N g-1 in Tilled+OM soil and 24.9 µg N
g-1 in Tilled soil at 50 °C (Tilled+OM and Tilled soils were significantly different at
P<0.001; Fig. 3.6a).
Addition of synthetic root exudates caused a small increase in gross N mineralisation
(P<0.05; Fig. 3.4a–b), but had no effect on net N mineralisation (P=0.06; Fig. 3.4c–d).
Addition of synthetic root exudates caused a small decrease in gross nitrification at
some temperatures in both the Tilled and Tilled+OM soils (P<0.05; Fig. 3.5a–b). In
contrast root exudates caused on average a 3.9-fold increase in gross N immobilisation
from 5–30 °C in both SOC treatments (P<0.05; Fig. 3.5c–d).
Addition of synthetic root exudates slightly but significantly decreased NH4+ pool size
by a mean of 1.2 µg N g-1 (P<0.0001; combined root exudate treatments are shown in
Fig. 3.6a). Nitrate pool size in the Tilled+OM soil was approximately twice as large at
all temperatures compared to the Tilled soil (P<0.0001; combined root exudate
treatments are shown in Fig. 3.6b). Addition of synthetic root exudates had no effect on
NO3- pool size (P=0.22).
Net nitrification in the Tilled+OM soil was only greater than Tilled soil at 30 °C
(P<0.0001; data not shown). Addition of synthetic root exudates had no effect on net
nitrification rates (P=0.18). Net nitrification rates increased with increasing temperature
to a maximum at 30–40 °C then decreased substantially at 50 °C (P<0.001).
Ch. 3: N Loss and Carbon
75
Figure 3.4. Influence of temperature after seven days of incubation on (a) gross N
mineralisation without root exudates; (b) gross N mineralisation with root
exudates; and influence of temperature over seven days of incubation on (c) net N
mineralisation without root exudates; and (d) net N mineralisation with root
exudates. Error bars for gross N mineralisation are 95% confidence intervals derived
from the FLUAZ model, and for net N mineralisation are ±SEM (n = 3), and may be
smaller than the symbols. Legend is the same for all panels. Legend abbreviation: OM:
organic matter.
Ch. 3: N Loss and Carbon
76
Figure 3.5. Influence of temperature on (a) gross nitrification without root
exudates; (b) gross nitrification with root exudates; (c) gross N immobilisation
without root exudates; (d) gross N immobilisation with root exudates; (e) N:I ratio
without root exudates; and (f) N:I ratio with root exudates. The dashed line at 1.0 in
(e) and (f) represents the N:I ratio at which nitrification and N immobilisation rates are
equal. Error bars are 95% confidence intervals derived from the FLUAZ model, and
may be smaller than the symbols. Legend is the same for all panels. Legend
abbreviation: OM: organic matter.
Ch. 3: N Loss and Carbon
77
Figure 3.6. Influence of temperature after seven days of incubation on (a) NH4+-N;
and (b) NO3--N. Synthetic root exudate treatments were combined in the figure
presented, as root exudates had no effect on NO3--N (P>0.05) and the effect of root
exudates on NH4+-N was small compared to the effects of soil organic carbon treatment
and temperature. Error bars are ±SEM (n = 6), and may be smaller than the symbols.
Legend is the same for all panels. Legend abbreviation: OM: organic matter.
3.4.3. Fate of inorganic N
Addition of synthetic root exudates decreased the N:I ratio to a greater extent and at a
wider range of temperatures than increased total SOC (Fig. 3.5e–f). Addition of
synthetic root exudates significantly decreased the N:I ratio over the temperature range
5–30 °C for the Tilled soil and between 10–30 °C for the Tilled+OM soil (P<0.05). The
N:I ratio was <1 in the presence of synthetic root exudates at all temperatures (i.e. gross
N immobilisation was greater than gross nitrification; Fig. 3.5f). In contrast, the N:I
ratio was >1 for treatments from 10–30 °C without synthetic root exudates (Fig. 3.5e).
Increased total SOC in soil without synthetic root exudates decreased the N:I ratio at
temperatures from 10–30 °C (P<0.05; Fig. 3.5e). However, total SOC additions in the
presence of root exudates slightly increased the N:I ratio but only at 15 °C (P<0.05; Fig.
3.5f).
Ch. 3: N Loss and Carbon
78
Figure 3.7. Influence of temperature on (a) N2O flux over 24 h; and (b) N2O 15N
enrichment. Root exudate treatments were combined as they had no effect on N2O flux
(P>0.05) and had a small effect on 15N2O enrichment compared to soil organic carbon
and temperature treatments. Error bars are ±SEM (n = 6), and may be smaller than the
symbols. Legend is the same for both panels. Legend abbreviation: OM: organic matter.
Nitrous oxide fluxes after the 7 d incubation period were low with maximum N2O flux
at 40 °C (mean of 0.005 µg N g-1 d-1; combined root exudate treatments are shown in
Fig. 3.7a). Soil organic C treatment and addition of synthetic root exudates had no effect
on N2O flux (P=0.13; Fig. 3.7a). The 15N enrichment range of N2O (0.3–4.9 atom %;
combined root exudate treatments are shown in Fig. 3.7b) was the same as the 15N
enrichment range of the NO3- pool 24 h after 15N addition (0.4–4.3 atom %) but lower
than that of the NH4+ pool (3.0–54.2 atom %); this suggests that denitrification or nitrate
ammonification was the source of N2O.
3.5. Discussion
3.5.1. Sources of soil organic C to decrease the risk of N loss
Inputs of labile C to soil as synthetic root exudates decreased the risk of N loss to a
greater extent than long-term inputs of plant residues that increased total soil OM. Root
exudate C decreased the risk of N loss by stimulating microbial N immobilisation (on
Ch. 3: N Loss and Carbon
79
average by 3.9-fold), and by slightly decreasing nitrification. By contrast, addition of
plant residues increased both immobilisation and nitrification (on average by 2.7- and
2.8-fold respectively), but had no effect on the ratio between these two competing
pathways for inorganic NH4+. Nitrification is often the principal process controlling
inorganic N consumption in semi-arid soils due to C limitation of the heterotrophic
microbial population (Hoyle et al., 2006). Root exudate C appeared to remove C
limitation of microbial heterotrophs, allowing them to compete more successfully for
NH4+. Our findings are consistent with others who have found that labile C additions
from rhizodeposition stimulate microbial N immobilisation, thus retaining N in soil
(Clarholm, 1985; Qian et al., 1997).
Addition of crop residues to soil increased both inorganic N supply and N loss pathways
and thus did not decrease the risk of N loss. Crop residue inputs increased total SOC,
dissolved organic C (DOC) and LFOM-C by 1.8-, 2.0- and 2.2-fold respectively over
eight years of treatment. Both DOC and LFOM are indicators of available C in soil, as
these soil OM fractions are transient, turn over rapidly and are microbial substrates
(Haynes, 2005; Janzen et al., 1992). Even though there was more DOC and LFOM in
the soil with crop residue inputs (Tilled+OM), overall the risk of N loss was not
decreased, and instead crop residue additions up-regulated the entire soil N cycle. This
suggests that the greater pool of soil OM from crop residue inputs did not solely
increase C availability to heterotrophic microorganisms, but also increased N supply
through mineralisation, and thus had little effect on the balance between subsequent
NH4+ retention and loss pathways. Our results are consistent with other studies with
long-term increases in soil OM due to crop residue inputs, which generally increase
microbial biomass, C and N contents and nutrient cycling (reviewed in Kumar and Goh,
2000). This is however in contrast to short-term additions of plant residues to soil, after
Ch. 3: N Loss and Carbon
80
which net N immobilisation and decreased inorganic N pools are often observed (for
example Geisseler et al., 2012; Janzen and Kucey, 1988). Increasing total soil OM
through long-term additions of crop residue was not an effective management tool to
decrease N losses in this semi-arid environment.
3.5.2. Inorganic N accumulates at high soil temperature
Considerable NH4+ accumulation at soil temperatures representative of summer
conditions was a result of decreased microbial C use efficiency coinciding with
increased net N mineralisation. This NH4+ build-up was consistent with mineralisation-
immobilisation turnover decoupling observed by Hoyle et al. (2006) and Luxhøi et al.
(2008) at temperatures greater than 30 °C in similar semi-arid soils, while greater net N
mineralisation has also been observed during hot, dry summer months compared to the
cooler growing season in a Californian semi-arid grassland ecosystem (Parker and
Schimel, 2011). The two main pathways of NH4+ production in soil are either by direct
assimilation of LMWOM molecules into microbial biomass and subsequent release of
N that is not required (Jones et al., 2013), or by mineralisation of organic N to NH4+ by
extracellular enzymes (Geisseler et al., 2010). Which pathway is dominant in soil
depends on regulation of microbial enzyme production for N uptake of LMWOM or
NH4+, which in turn is hypothesised to depend on the main forms and relative
availabilities of N and C in soil (Geisseler et al., 2010). Our results suggest that at
elevated temperatures both C and N from LMWOM are less able to be incorporated into
microbial biomass, so more NH4+ is released into the soil mineral N pool, whether due
to extracellular or intracellular breakdown of LMWOM.
The mechanism for decreased microbial C use efficiency at soil temperatures greater
than 30 °C in this semi-arid soil is likely related to a shift in the balance between
Ch. 3: N Loss and Carbon
81
microbial growth and respiration compared to lower temperatures. Microbial respiration
is inherently more sensitive to temperature increases than microbial growth (Allison et
al., 2010; Steinweg et al., 2008; Wetterstedt and Ågren, 2011), due to the increasing
physiological costs of respiration and heat survival mechanisms (Schimel et al., 2007).
Therefore at elevated temperatures microbes respire a larger proportion of any C they
assimilate compared to C allocated to growth. In addition, increased C cycling and
microbial metabolism at elevated temperatures can deplete readily accessible labile
substrates, requiring microorganisms to use substrates of lesser quality, and which also
lowers microbial C use efficiency (Manzoni et al., 2012; Sinsabaugh et al., 2013). In the
present study, C cycling appears to be tightly linked to N cycling, as decreased
microbial C use efficiency and assimilation of C at elevated soil temperatures is
associated with NH4+ release and thus decreased assimilation of N.
3.5.3. Differences between amino acid and peptide turnover
Measurement of peptide and amino acid turnover suggested that these LMWOM
molecules were used in differing ways by microbial decomposers in this semi-arid soil.
Peptides turned over more rapidly than amino acids, as has been previously observed in
a range of microorganisms and climates (Farrell et al., 2013; Matthews and Payne,
1980). Interestingly, we also observed that in this semi-arid soil peptide-C appeared to
be utilised for production of energy (more C was allocated to respiration), while amino
acid-C was utilised for building biomass. Peptides and amino acids are taken up actively
(i.e. using energy) by separate transport systems (Payne and Smith, 1994). Peptides may
be preferentially used for energy production over amino acids because active uptake of
one peptide molecule requires less energy than if the constituent amino acids were taken
up separately, and peptides provide more C and N per molecule than amino acids
(Farrell et al., 2013; Matthews and Payne, 1980). On the other hand, amino acids can be
Ch. 3: N Loss and Carbon
82
directly used for biosynthesis of proteins, but peptides must be hydrolysed before their
constituent amino acids can be used for protein synthesis or as sources of C and N after
further breakdown (Anraku, 1980; Payne, 1980). If the patterns of N turnover of these
substrates follow C turnover, peptides may be the primary source of inorganic N after
catabolism and release of peptide-C through respiration. Amino acid-N may instead be
immobilised into microbial biomass concurrently with amino acid-C.
3.5.4. Implications for semi-arid environments
Effective management practices to decrease the risk of N loss in semi-arid soils still
need to be found. The greatest risk of N loss in this arable semi-arid soil likely occurs
from inorganic N that accumulates due to OM decomposition over summer. These
inorganic N pools are then at risk of loss by NO3- leaching during rain events that mark
the beginning of the cooler growing season (Anderson et al., 1998; Arregui and
Quemada, 2006). Risk of N loss by N2O emissions in this semi-arid soil is also likely
greatest during summer fallow: N2O emissions under steady-state water conditions in
the present study were at a maximum between 30 and 40 °C, and up to half of annual
N2O emissions in the field can be in response to summer and autumn rainfall events
(Barton et al., 2008; Barton et al., 2013b; Mummey et al., 1997).
Tools that decrease the risk of N loss may work by controlling N supply, increasing
plant N demand, or by immobilising excess inorganic N in microbial or plant biomass
(Crews and Peoples, 2005). Control of N supply in these rainfed semi-arid agricultural
soils is difficult, because the majority of inorganic N availability (up to 80% of plant N
uptake in wheat) is derived from microbial decomposition of crop residues and soil OM
(Angus, 2001; Fillery, 2001), and OM decomposition is more reliant on changes in soil
water availability and temperature than agricultural management practices (Hoyle and
Ch. 3: N Loss and Carbon
83
Murphy, 2011). In the present study, increasing soil OM through long-term crop residue
inputs was not effective at decreasing the risk of N loss, because although microbial
immobilisation was increased, N supply and nitrification were also increased. The
present study however highlighted the importance of root exudates for increasing
microbial N immobilisation. Mitigation of N loss in these semi-arid soils therefore
could involve increasing the extent and duration of actively growing plant roots,
especially during late summer and early autumn. This might be achieved by
incorporation of perennials into the current annual cropping system (Crews and Peoples,
2005), or summer crops. Root growth may also be increased in the early growing season
by managing soil constraints that restrict root growth (e.g. sub-soil acidity, compaction
layers) and by selective breeding for traits such as increased root branching and early
growth vigour, which also increases root NO3- capture (Dunbabin et al., 2003; Hoad et
al., 2001; Lynch, 1995).
3.6. Conclusions
Our ability to manipulate N transformation rates and decrease the risk of N loss from
semi-arid soils will depend greatly on the C source (which is associated with the
presence or absence of root exudates), and the time of year (as high soil temperature can
cause potential disconnect in mineralisation–immobilisation turnover). Root exudate C
was more effective than long-term increased plant residue inputs at decreasing the risk
of N loss, by increasing the potential for heterotrophic microbial immobilisation relative
to nitrification. In contrast, addition of plant residues to soil increased both N supply
and N loss pathways. Therefore the greatest risk of N loss in this arable semi-arid soil
occurs from soil inorganic N that accumulates over summer. This accumulation is in
response to high net N mineralisation rates after occasional rainfall events, coupled with
Ch. 3: N Loss and Carbon
84
low microbial C use efficiency at elevated soil temperatures, and limitations to active
plant growth. Potential loss of this accumulated inorganic N is subsequently greatest
following opening rains in autumn prior to crop establishment, when drainage begins
and soil temperatures cool allowing nitrification to occur. However, management
practices to mitigate this risk of N loss still need to be found.
85
Chapter 4.
Seasonal dynamics of ammonia-oxidising bacteria
but not archaea influence risk of nitrogen loss in a
semi-arid agricultural soil
4.1. Abstract
Nitrification, a key pathway of nitrogen (N) loss from soil, is regulated by ammonia-
oxidising bacteria (AOB) and archaea (AOA). Niche differentiation and seasonal
dynamics of these two groups of microorganisms may be influenced by both
environmental and soil characteristics (e.g. substrate availability, soil pH). However,
what regulates AOB and AOA in semi-arid soils is not well understood. Here the
seasonal dynamics of ammonia oxidiser gene abundances were examined in relation to
soil biogeochemical properties in a cropped semi-arid soil subjected to long-term (since
2003) tillage and crop residue management treatments. AOB regulated ammonia
oxidation in the surface soil, as AOA were undetected, potentially due to agricultural
modification of ammonium availability or soil pH. Seasonal variation in AOB was
related to dissolved organic carbon, microbial biomass carbon and nitrate concentrations
but not to ammonium concentrations, rainfall, soil water content, or temperature. Crop
residue inputs enhanced AOB abundance independent of any seasonal variation.
Increased AOB abundance during summer fallow coincided with increased soil nitrate
Ch. 4: Seasonal Dynamics
86
pools. Consequently, the growth of the AOB population likely contributes to increased
risk of N loss at the start of the following growing season.
Ch. 4: Seasonal Dynamics
87
4.2. Introduction
Nitrification plays a key role in nitrogen (N) loss processes, as the gatekeeper between
internal soil cycling and external N loss (Schimel et al., 2005). Ammonia oxidation, the
limiting step of nitrification, is regulated by bacterial and archaeal ammonia oxidisers,
which convert ammonia (in equilibrium with ammonium, NH4+) to nitrite
(Hatzenpichler, 2012; Kowalchuk and Stephen, 2001). Ammonia-oxidising bacteria
(AOB) belong to the beta- and gamma-subclasses of Proteobacteria while ammonia-
oxidising archaea (AOA) belong to the phylum Thaumarchaeota (Rotthauwe et al.,
1997; Spang et al., 2010). Both AOA and AOB express functionally similar genes for
the primary enzyme catalysing ammonia oxidation, ammonia monooxygenase
(Rotthauwe et al., 1997; Schleper and Nicol, 2010). However, bacterial and archaeal
ammonia oxidisers differ in their genetics, physiologies and metabolic processes, so are
likely to differ in their adaptations to abiotic and biotic soil conditions (niche
specialisation) and utilisation of resources (niche differentiation; Prosser and Nicol,
2012).
Niche specialisation and differentiation between AOA and AOB are not yet clearly
defined, but may be regulated by factors including soil pH, NH4+ supply, or relative
ability to carry out mixotrophic or heterotrophic growth (Prosser and Nicol, 2012). Low
soil pH is the only consistent differentiating factor between AOA and AOB: at pH < 5.5
acidophilic AOA appear to be the dominant ammonia-oxidising microorganisms,
particularly of the phylogenetic cluster associated with Nitrosotalea devanaterra
(Gubry-Rangin et al., 2011; Lehtovirta-Morley et al., 2011). Conditions of low NH4+
supply may allow AOA to dominate over AOB, as AOA have greater substrate affinity
for NH4+ than AOB, and are more sensitive than AOB to inhibition by high
concentrations of NH4+ (Di et al., 2010; Martens-Habbena et al., 2009). This may be
Ch. 4: Seasonal Dynamics
88
important in agricultural soils to which NH4+-based fertilisers are applied, selecting for
AOB populations to the detriment of AOA (Jia and Conrad, 2009; Pratscher et al.,
2011). However, some AOA seem to be tolerant to high NH4+ concentrations
(Verhamme et al., 2011), and the source of NH4+ may be important: ammonia oxidation
by archaea has been associated with mineralisation of organic N but not addition of
inorganic N sources (Levičnik-Höfferle et al., 2012; Stopnišek et al., 2010). The
metabolism of AOA is still in the early stages of investigation, but it has been suggested
that both AOB and AOA may have the ability to grow mixotrophically or
heterotrophically [i.e. are able to use organic sources of carbon (C)] (Sayavedra-Soto
and Arp, 2011; Schmidt, 2009; Walker et al., 2010). This ability may provide the
organism with a competitive advantage over obligate autotrophic ammonia oxidisers for
C assimilation or energy production under certain soil conditions such as increased C
availability.
Factors that regulate differentiation in populations between niches and sites are often
different from factors that regulate temporal fluctuations of populations at one site
(Wardle, 1998). Factors that have been proposed as regulating temporal ammonia
oxidiser gene abundance include climate and seasonal differences (e.g. temperature and
rainfall), soil organic matter (OM), and changes in NH4+ availability due to N fertiliser
additions and periods of soil OM mineralisation (Adair and Schwartz, 2008; Sher et al.,
2013; Taylor et al., 2012). Taylor et al. (2012) speculated that increases of AOA amoA
abundance (but not AOB) in spring of a fallow Oregon agricultural soil was due to their
utilisation of another energy-generating metabolism besides ammonia oxidation (i.e.
heterotrophy or mixotrophy), and that increased AOB amoA gene abundance in cropped
soil at the same site was in response to N fertiliser increasing NH4+ availability. Low
NH4+ availability due to low soil water content causing low mineralisation rates in
Ch. 4: Seasonal Dynamics
89
summer was hypothesised as the cause of greater AOA abundance than AOB in a semi-
arid soil in Israel, while AOB may have also been more limited by elevated temperature
than AOA: in winter AOB shifted to greater dominance than AOA in the same soil
(Sher et al., 2013). However, there appears to be no consistent effect of season on
abundance of AOB or AOA in semi-arid soils.
Drylands, including semi-arid and arid regions, are important for agriculture,
comprising one third of the world’s agriculturally productive lands, and supporting
nearly half of the global population (Harrison and Pearce, 2000; Reynolds et al., 2007).
Semi-arid agricultural soils in the grain-growing region of south-western Australia are
generally acidic, sandy, low in soil OM content, and are annually exposed to soil
temperatures greater than 40 °C during summer (Barton et al., 2013b; McArthur, 2004).
Soil NH4+ concentrations are usually less than 5 µg N g-1 dry soil except for short
periods when NH4+-based fertilisers are applied to agricultural soil during the winter
growing season (Barton et al., 2008; Barton et al., 2013b; Cookson et al., 2006b).
Archaeal ammonia oxidisers would be expected to have greater abundance than AOB in
these soils, due to their better resistance to elevated temperatures, low pH and low NH4+
availability. Studies of surface soils in this region however have shown that AOB are
similar to or more abundant than AOA (Appendix A; Gleeson et al., 2010; O’Sullivan et
al., 2013). As these studies sampled soil at one point in time, it is not yet clear whether
this dominance of AOB occurs across all seasons, and how AOB and AOA populations
vary dynamically with time in response to soil and environmental conditions.
The overall objective of this study therefore was to improve understanding of temporal
population dynamics of ammonia oxidisers so as to better understand N loss
mechanisms in semi-arid environments dominated by winter rainfall. Specifically: (i)
Ch. 4: Seasonal Dynamics
90
how soil OM content affects ammonia oxidiser abundance; (ii) if increased soil OM
modifies seasonal variation in ammonia oxidiser abundance; and (iii) which soil,
environmental and biochemical factors regulate the abundances of AOB and AOA were
investigated during a two year field-based study. We hypothesised that AOB will
dominate over AOA in the surface soil throughout the year, and that increased soil OM
will increase ammonia oxidiser abundance. We also hypothesised that ammonia
oxidiser abundance will be related to rainfall, soil water content, temperature and NO3-
concentrations but not to NH4+ concentrations.
4.3. Methods
4.3.1. Study site and soil
Temporal variation of ammonia-oxidising populations was examined at a field research
site with arable management treatments that aims to alter soil OM concentrations
without the confounding effects of climate and soil type. The study site is located in the
northern grainbelt of Western Australia at Buntine (30.00° S, 116.33° E), with a
Mediterranean-type semi-arid climate of cool, wet winters and hot, dry summers. Mean
annual rainfall is 285 mm and mean monthly temperatures range from 5.8–35.3 °C
[1997–2014 data, from a weather station closest to the study site at Dalwallinu (30.28°
S, 116.67° E); Commonwealth of Australia Bureau of Meteorology,
http://www.bom.gov.au/climate/data]. Rainfall and soil temperature data was collected
at the site (Fig. 4.1a) using a Tipping Bucket Raingauge Model TB4 (Hydrological
Services, Liverpool, NSW, Australia) and CS Model 107 Temperature Probes
(Campbell Scientific, Logan, Utah, USA). The soil is a sand (92% sand, 2% silt, 6%
clay), classified as a Basic Regolithic Yellow-Orthic Tenosol (Australian Soil
Ch. 4: Seasonal Dynamics
91
Classification; Isbell, 2002) or a Haplic Arenosol (FAO World Reference Base for Soil
Resources; IUSS Working Group WRB, 2007).
Figure 4.1. (a) Daily rainfall (bar graph, left y-axis) and daily soil minimum and
maximum temperature at 5 cm depth (line graph, right y-axis) measured at the
study site. (b) Soil water content at time of sample collection. Dashed arrows
indicate date of seeding (wheat, Triticum aestivum) and solid arrows indicate date of
harvest. Error bars are ±SEM (n = 3). Legend abbreviations: OM: organic matter; RD:
Run-Down.
Tabl
e 4.
1. P
rope
rtie
s of f
ield
org
anic
mat
ter
trea
tmen
ts (0
–10
cm d
epth
) at s
tart
of p
rese
nt st
udy,
seve
n ye
ars a
fter
trea
tmen
ts w
ere
impo
sed.
Val
ues a
re ±
SEM
(n =
3).
Org
anic
mat
ter t
reat
men
ts w
ith th
e sa
me
lette
r are
not
sign
ifica
ntly
diff
eren
t (P>
0.05
). A
bbre
viat
ion:
OM
: org
anic
mat
ter.
N
o T
ill
No
Till
B
urnt
Stu
bble
T
illed
T
illed
+OM
T
illed
+OM
R
un-D
own
Bulk
den
sity
(g c
m-3
) #
1.5
8 ±
0.04
ab
1.6
0 ±
0.01
ab
1.63
± 0
.03b
1.42
± 0
.05a
1.40
± 0
.08a
pH (C
aCl 2)
§
6.1
± 0.
1a 6.
2 ±
0.1a
6.2
± 0.
2a 6.
2 ±
0.2a
6.3
± 0.
0a
EC (d
S m
-1) ‡
0
.09
± 0.
008a
0.1
0 ±
0.00
4a 0
.08
± 0.
004a
0.1
7 ±
0.01
8b 0
.17
± 0.
013b
Tota
l car
bon
(%) †
0.
94 ±
0.0
2a 1
.05
± 0.
03ab
0.
91 ±
0.0
2a 1
.22
± 0.
15ab
1.
38 ±
0.0
7b
Tota
l nitr
ogen
(%) †
0
.09
± 0.
001a
0.
10 ±
0.0
03ac
0
.09
± 0.
002a
0.
12 ±
0.0
10bc
0
.13
± 0.
004b
C:N
ratio
11
.0 ±
0.3
0a 11
.0 ±
0.0
6a 10
.5 ±
0.0
5a 10
.1 ±
0.3
9a 10
.9 ±
0.2
6a
# Bu
lk d
ensit
y de
term
ined
usin
g th
e in
tact
cor
e m
etho
d w
ith 3
cor
es o
f 7.3
5 cm
dia
met
er b
y 10
cm
dep
th (C
ress
wel
l and
Ham
ilton
, 200
2).
§ pH
was
det
erm
ined
on
air-
dry
soil
in 0
.01M
CaC
l 2 w
ith a
1:5
soil:
extra
ct ra
tio, a
fter s
haki
ng fo
r 1 h
, and
whi
le st
irrin
g th
e so
il su
spen
sion
(Ray
men
t and
Lyo
ns, 2
011)
.
‡ El
ectri
cal c
ondu
ctiv
ity w
as d
eter
min
ed o
n ai
r-dr
y so
il in
wat
er w
ith a
1:5
soil:
wat
er ra
tio (R
aym
ent a
nd L
yons
, 201
1).
† To
tal c
arbo
n an
d ni
troge
n w
ere
dete
rmin
ed b
y hi
gh-te
mpe
ratu
re c
ombu
stio
n of
fin
ely
grou
nd a
ir-dr
y so
il us
ing
an E
lem
enta
r V
ario
MA
CRO
CN
S el
emen
tal a
naly
ser
(Han
au,
Ger
man
y; R
aym
ent a
nd L
yons
, 201
1).
Ch. 4: Seasonal Dynamics
93
4.3.2. Experimental design and soil collection
The site had a three-year rotation of lupin (Lupinus angustifolius) – wheat (Triticum
aestivum) – wheat since 2003, with one rainfed crop each winter. A randomised block
design was employed, with three blocks of five OM field treatment plots (80 m by 10
m). The five OM treatments were: (i) no tillage with full stubble retention, seeded with
knife point tines to 15 cm depth (No Till); (ii) no tillage with burnt stubble (Burnt); (iii)
soil tilled with offset disks to 10 cm depth prior to seeding (Tilled); (iv) tilled soil
loaded with additional OM (Tilled+OM); and (v) Tilled+OM Run-Down, where
additional OM was applied between 2003–2006 and then ceased. Organic matter was
applied at 20 t ha-1 to both Tilled+OM and Tilled+OM Run-Down plots in 2003 (barley
straw) and 2006 (canola chaff), and to Tilled+OM plots in 2010 (oat chaff). Organic
matter was applied after each lupin crop, before seeding of wheat. At the time of the
present study, seven years after commencement of the trial, soil organic carbon (SOC)
contents ranged from 0.91% in the Tilled soil to 1.38% in the Tilled+OM Run-Down
soil, while total N contents ranged from 0.09% in the Tilled soil to 0.13% in the
Tilled+OM Run-Down soil (Table 4.1).
Two crops of winter wheat were grown and harvested during the present study. The site
was fertilised at rates depending on expected growing season rainfall and projected
potential yields (1.5–2.5 t ha-1 in 2010, 3–4 t ha-1 in 2011), as is standard practice in this
region. In 2010, 60 kg ha-1 granular fertiliser (NPKS – 10.2:12.0:11.2:6.0; N as
ammonium sulphate and monoammonium phosphate) was applied at seeding (28th
May), and 40 L ha-1 of liquid fertiliser (NPKS – 32.0:0:0:0; N as urea and ammonium
nitrate) was applied at crop emergence (12th July), for a total of 23.0 kg N ha-1 y-1. In
2011, 60 kg ha-1 solid and 20 L ha-1 liquid fertiliser were applied at seeding (1st June;
NPKS and N form as above), and 50 L ha-1 liquid fertiliser was applied at emergence
Ch. 4: Seasonal Dynamics
94
(26th July) for a total of 35.7 kg N ha-1 y-1. Harvest in 2010 was on 16th November, and
in 2011 was on 14th November.
Soil was collected (0–10 cm depth) on ten occasions from each plot between May 2010
and November 2011. Within each plot, 25 cores (5.3 cm diameter x 10 cm depth) were
sampled using a zigzag pattern at least 1 m from the plot boundary. Subsamples of soil
from each plot were frozen for DNA analysis of AOA and AOB on return from the
field. Remaining soil was sieved to <2 mm and stored field-moist at 4 °C until further
analysis. Soils were analysed for gravimetric soil water content and inorganic N at field
moisture content. Soils collected during the period when the soil is field dry (i.e. on 19 th
Nov 2010, 1st Dec 2010 and 2nd May 2011) were first wet-up to 45% water holding
capacity, then pre-incubated for 7 d at 25 °C before analysis for microbial biomass C
(MBC), dissolved organic C (DOC) and potentially mineralisable N (PMN). On the
other sampling dates there was no need to first wet-up the soil.
4.3.3. Microbial biomass C and dissolved organic C
Microbial biomass C was measured using the chloroform fumigation–extraction method
(Brookes et al., 1985). Fresh soil (10 g) was fumigated with chloroform (containing low
levels of the stabilising agent amylene) under vacuum in the dark for 24 h at 25 °C.
Fumigated samples, with replicate non-fumigated samples, were then extracted by
shaking for 1 hr with 40 mL of 0.5 M potassium sulphate (K2SO4). Filtered extracts
(Whatman No. 42) were frozen until further analysis. Fumigated and non-fumigated
extracts were analysed using an OI Analytical Aurora 1030 Wet Oxidation TOC
Analyser (College Station, TX, USA) for non-purgeable organic C. Dissolved organic C
values were determined using the results from non-fumigated extracts. Microbial
Ch. 4: Seasonal Dynamics
95
biomass C was calculated from the difference between fumigated and non-fumigated
organic C, divided by a kEC factor of 0.45 (Wu et al., 1990).
4.3.4. Inorganic N analysis and potentially mineralisable N
Inorganic N was extracted from 20 g soil by shaking for 1 h with 80 mL of 0.5 M
K2SO4. Filtered extract solutions (Whatman No. 42) were kept frozen until colorimetric
analysis on a Skalar San Plus auto-analyser (Breda, The Netherlands), using the
modified Berthelot reaction for NH4+ (Krom, 1980) and the hydrazinium reduction
method for nitrate (NO3-; Kamphake et al., 1967).
Potentially mineralisable N was determined by anaerobic incubation (Keeney and
Bremner, 1966; Waring and Bremner, 1964). Fresh soil (20 g) was incubated in 80 mL
of deionised water for 7 d at 40 °C. Potassium sulphate was added (6.97 g) to adjust the
soil solution to 0.5 M K2SO4, then samples were shaken for 1 h. Replicate 20 g samples
of non-incubated soil in 80 mL of 0.5 M K2SO4 were also shaken. Incubated and non-
incubated samples were filtered (Whatman No. 42) then frozen until further analysis.
Samples were analysed for NH4+ on an autoanalyser, as described above.
4.3.5. Nucleic acid extraction and qPCR
DNA was extracted from 700 mg subsamples of field-moist soil (Griffiths et al., 2000)
and stored at -40 °C until further analysis. The functional genes encoding bacterial and
archaeal ammonia monooxygenase (amoA) were determined by quantitative real-time
polymerase chain reaction (qPCR). Bacterial amoA primers were amoA-1F, with primer
sequence of 5ʹ-GGGGTTTCTACTGGTGGT-3ʹ, and amoA-2R, with primer sequence
of 5ʹ-CCCCTCKGSAAAGCCTTCTTC-3ʹ (K = G or T, S = G or C), amplifying a
fragment length of 491 bp (Rotthauwe et al., 1997). Bacterial amoA gene abundance
Ch. 4: Seasonal Dynamics
96
was quantified using an ABI 7500 Fast qPCR machine (Applied Biosystems, Carlsbad,
CA, USA). Each 20 µL qPCR reaction contained 10 µL of Power SYBR® Green PCR
Master Mix (Applied Biosystems, Warrington, UK), 0.2 µL each of the specific forward
and reverse primers at 10 µM, 2 µL of bovine serum albumin at 5 mg mL-1 (Ambion®
UltraPure BSA, Carlsbad, CA, USA), 2 µL of template DNA and 5.6 µL of water.
Thermocycling conditions were: 95 °C for 10 min; then 40 cycles of 94 °C for 60 s, 56
°C for 60 s, 72 °C for 60 s and 78 °C for 60 s; followed by a melt curve. Fluorescence
data was collected at the 78 °C stage.
Archaeal amoA primers were Arch-amoAF (5ʹ-STAATGGTCTGGCTTAGACG-3ʹ)
and Arch-amoAR (5ʹ-GCGGCCATCCATCTGTATGT-3ʹ) amplifying a fragment
length of 635 bp (Francis et al., 2005). Archaeal amoA gene abundance was quantified
using an Applied Biosystems ViiA™ 7 (Carlsbad, CA, USA). Each 10 µL qPCR
reaction contained 5 µL of Power SYBR® Green PCR Master Mix (Applied
Biosystems, Warrington, UK), 0.1 µL each of the specific forward and reverse primers
at 10 µM, 1 µL of BSA, 1 µL of template DNA and 2.8 µL of water. Thermocycling
conditions were: 94°C for 10 min; then 40 cycles of 94°C for 1 min, 52°C for 1 min,
72°C for 1 min and 78°C for 1 min; followed by a melt curve. Fluorescence data was
collected at the 78°C stage.
Standard templates used to determine gene copy numbers in the qPCR reactions were
cloned plasmids, as described in Barton et al. (2013a). Samples were tested over a series
of dilutions to determine if there was inhibition, and further analysis was completed
using the dilution that produced the highest copy number. Samples were replicated
three times in each qPCR run. Standard curves generated in each reaction were linear
over four orders of magnitude for AOB (103–106 gene copies) and six orders of
Ch. 4: Seasonal Dynamics
97
magnitude for AOA (103–108 gene copies) with r2 values greater than 0.98.
Amplification efficiencies ranged from 79–111%.
4.3.6. Statistical analysis
Statistical differences between OM treatments for the basic soil properties were
determined using analysis of variance (ANOVA) with associated TukeyHSD post hoc
tests in R version 3.1.0 (R Foundation for Statistical Computing, Vienna, Austria).
Bacterial amoA gene abundance was initially log transformed before all statistical
analyses. Statistical significances of OM treatment with time for each soil property were
evaluated using PROC MIXED in SAS version 9.3 (SAS Institute Inc., Cary, NC,
USA), as replication was at the highest level (i.e. field plot). For this analysis, NH4+,
PMN, MBC and DOC were also log transformed, while total inorganic N, NO3- and
AOB abundance were square root transformed to ensure homoscedasticity.
Backwards multiple linear regression was carried out also using PROC MIXED, for
response of logged AOB abundance to: cumulative rainfall and mean daily maximum
and minimum soil temperatures at 5 cm depth in the 30 days prior to collection;
gravimetric soil water content at collection; logged NH4+, PMN, MBC and DOC values;
and square-root total inorganic N and NO3- values. Random effects of field block and
field block interacting with OM treatment were included in the model. The best
regression model was evaluated by minimising the Akaike Information Criteria
(Akaike, 1981).
Principal component analysis (PCA) was carried out using prcomp in R version 3.1.0
with scaled and centred data of logged AOB abundance, cumulative rainfall and mean
daily minimum and maximum soil temperature at 5 cm depth in the 30 days prior to soil
Ch. 4: Seasonal Dynamics
98
collection, soil water content at collection, MBC, DOC, total inorganic N, NH4+, NO3
-
and PMN.
4.4. Results
4.4.1. Environmental conditions
Daily rainfall over the study period ranged from 0–25.2 mm, while daily soil
temperature at 5 cm depth ranged from 6.6–42.7 °C (Fig. 4.1a). Growing season rainfall
(April–October) was greater in 2011 (283 mm) than in 2010 (144 mm). Daily minimum
soil temperature at 5 cm depth ranged from 6.6 °C in July 2011 to 30.4 °C in January
2011 (Fig. 4.1a). Daily maximum soil temperature at 5 cm depth ranged from 9.2 °C in
August 2010 to 41.7 °C in January 2011 (Fig. 4.1a).
Soil water content at time of soil collection followed a similar pattern to rainfall,
increasing during the winter growing season (May–November) and at a minimum
during summer (mean <0.01 g g-1; October 2010–May 2011; Fig. 4.1b). Mean
maximum soil water content at sampling was greater in 2011 (0.09 g g-1 in August) than
in 2010 (0.05 g g-1 in July–August; P<0.0001). Tilled+OM soil had greater soil water
content than the other OM treatments on two occasions in winter (July 2010, August
2011; P<0.01), and greater soil water content than the No Till, Burnt and Tilled soils on
one occasion in late spring (November 2011; P<0.05; Fig. 4.1b).
4.4.2. Microbial biomass C and dissolved organic C
Mean MBC ranged from 46–489 µg C g-1 (Fig. 4.2a). Microbial biomass C followed
similar patterns with time in all OM treatments, but the Tilled+OM soil had
significantly greater MBC than the other OM treatments (P<0.05), except in June 2011
Ch. 4: Seasonal Dynamics
99
(winter). Microbial biomass C was at a maximum during the winter in 2010 and at a
minimum in summer (i.e. December 2010).
Figure 4.2. Change in (a) microbial biomass carbon; and (b) dissolved organic
carbon through time. Error bars are ±SEM (n = 3). Legend is the same for both panels.
Legend abbreviations: OM: organic matter; RD: Run-Down.
Mean DOC ranged from 60–217 µg C g-1 (Fig. 4.2b). Dissolved organic C in No Till,
Burnt and Tilled soils were not different (P>0.05). Dissolved organic C in Tilled+OM
soil however was greater than No Till, Burnt and Tilled soils at all sampling times
(P<0.01), and was greater than Tilled+OM Run-Down from July–December in 2010
(mid-winter to mid-summer), and from September–December in 2011 (spring to mid-
Ch. 4: Seasonal Dynamics
100
summer; P<0.01). Dissolved organic C was at a maximum in December 2010 (summer)
and at a minimum in August 2011 (winter, mid-growing season).
4.4.3. Inorganic N and potentially mineralisable N
Mean NH4+ concentrations ranged from <1–13 µg N g-1 (Fig. 4.3b), while mean NO3
-
concentrations were greater than NH4+, and ranged from <1–44 µg N g-1 (Fig. 4.3c).
Mean NH4+ in No Till, Burnt and Tilled soils peaked in winter (July 2010 and 2011),
coinciding with N fertiliser inputs. Surprisingly, NH4+ concentrations in the Tilled+OM
soil did respond to N fertiliser inputs in July 2011. However, NH4+ concentrations in
Tilled+OM soil were greater than the other OM treatments during summer (October
2010–May 2011; P<0.05). Nitrate increased over summer (October 2010–May 2011;
P<0.0001) in response to a series of rainfall events, peaking at the start of each growing
season, and then declining to a minimum by the end of winter (around September;
P<0.0001). Mean NO3- concentrations over time in Tilled+OM soil and Tilled+OM Run
Down were greater than the other OM treatments (P<0.001), and patterns in NO3- over
time were the same irrespective of treatment. Total inorganic N (NH4+ + NO3
-) ranged
from means of 2–48 µg N g-1, and was dominated by NO3- (mean of 69 %; Fig. 4.3a).
Mean PMN ranged from 10–98 µg N g-1 (Fig. 4.3d). Potentially mineralisable N in
Tilled+OM soil peaked in August 2010 (late winter), approximately three months after
OM additions to this treatment, and remained greater than the other OM treatments until
December 2010 (summer; P<0.05). Mean PMN in No Till, Burnt, Tilled and
Tilled+OM Run-Down soils did not change from October 2010–November 2011
(P>0.05).
Ch. 4: Seasonal Dynamics
101
Figure 4.3. Change in (a) total inorganic nitrogen; (b) NH4+-N; (c) NO3
--N; and (d)
potentially mineralisable nitrogen through time. Arrows indicate dates of N fertiliser
application. Error bars are ±SEM (n = 3). Legend is the same for all panels. Legend
abbreviations: OM: organic matter; RD: Run-Down. Note difference in y-axis scale
between panels.
Ch. 4: Seasonal Dynamics
102
Figure 4.4. Change in bacterial amoA gene abundance (AOB) through time. Error
bars are ±SEM (n = 3). Note log scale of y-axis. Legend abbreviations: OM: organic
matter; RD: Run-Down.
4.4.4. Ammonia oxidiser gene abundance
Archaeal amoA gene abundance was below detection limits for 96% of samples (144
out of 150 samples; data not shown). Detected archaeal amoA gene abundances ranged
from 1.16 x 105–3.25 x 107 gene copies g-1 dry soil.
Bacterial amoA gene abundance ranged from 2.35 x 107–1.11 x 109 gene copies g-1 dry
soil (Fig. 4.4), and was detected in all samples. Bacterial amoA gene abundance
generally decreased from the middle to the end of each growing season and was at a
minimum in spring to early summer. Bacterial amoA gene abundance increased over
summer to a maximum at the start of the growing season (May 2011). Tilled+OM soil
had greater bacterial amoA gene abundance than the other OM treatments (P<0.05), and
Tilled+OM Run-Down had greater bacterial amoA gene abundance than Burnt and
Tilled soils (P<0.05), but was not different from No Till soil (P>0.05). Patterns in
bacterial amoA gene abundance due to OM treatments were independent of sampling
date (OM treatment by sampling date interaction P>0.05).
Ch. 4: Seasonal Dynamics
103
4.4.5. Relationships between bacterial amoA gene abundance and other variables
Linear regressions between bacterial amoA gene abundance and each variable
separately provided models with the lowest Akaike Information Criteria. Bacterial
amoA gene abundance had significant positive relationships with NO3-, MBC and DOC
(P<0.01), but no relationship with cumulative rainfall, mean daily maximum or
minimum soil temperature in the 30 days prior to sampling, soil water content at
collection, NH4+ or PMN (P>0.05; Table 4.2; Fig. 4.5). The potential relationship
between AOB and each significantly correlated variable was calculated by multiplying
the coefficient by the maximum value measured for that variable. Variables with linear
regression coefficients in order of greatest to least correlation to AOB were DOC,
MBC, total inorganic N and NO3-. Maximum measured DOC (216.7 µg C g-1) however
would only be related to an increase in bacterial amoA gene abundance of 538 ± 8 gene
copies g-1, while maximum measured NO3- (43.8 µg N g-1) would be related to an
increase in bacterial amoA gene abundance of 28 ± 2 gene copies g-1.
Principal component analysis required six principal components to explain greater than
90% of the variance in soil biochemical and environmental properties (Table 4.3).
Principal component 1 (PC1) explained 36.4% of total variance in the data (Table 4.3),
and separated most strongly cumulative 30-day rainfall and soil water content at
collection (positive loadings) from 30-day mean minimum and maximum soil
temperatures (most strongly negative loadings; Fig. 4.6; Table 4.4). Otherwise, PC1
separated MBC, NH4+, NO3
-, PMN and logged AOB gene abundance (with loadings
near zero) from DOC, which had a slightly negative loading. Principal component 2
(PC2) explained 22.3% of total variance in the data (Table 4.3), and separated 30-day
mean minimum and maximum soil temperatures, cumulative 30-day rainfall and soil
water content at collection (positive or near zero loadings) from MBC, DOC, NO3-,
Ch. 4: Seasonal Dynamics
104
PMN and logged AOB gene abundance (most strongly negative loadings; Fig. 4.6;
Table 4.4).
Samples from the same sample collection date were grouped across the biplot of PC1
and PC2, roughly in line with PC1 as rainfall, soil water content and soil temperature
varied (Fig. 4.6). Samples from the Tilled+OM soil, and Tilled+OM Run-Down to a
lesser extent, had greater scatter across the biplot in line with PC2, compared to the No
Till, Burnt and Tilled soils, which were grouped towards positive scores of PC2.
Table 4.2. Linear regression results for response of logged bacterial amoA gene
abundance to each soil and environmental variable separately. Regression
coefficients are only reported for significant relationships. Abbreviations: sqrt: square
root transformed; log: log transformed; DOC: dissolved organic carbon; MBC:
microbial biomass carbon; Rainfall: cumulative rainfall of 30 days prior to sampling;
Max. Temp: mean daily maximum soil temperature at 5 cm depth during 30 days prior
to sampling; Min Temp: mean daily minimum soil temperature at 5 cm depth during 30
days prior to sampling; Soil Water: soil water content at time of collection; PMN:
potentially mineralisable nitrogen.
Predictor
Significance
level Coefficient
Standard
error of
coefficient Intercept
Standard
error of
intercept
log DOC P=0.0029 1.1690 0.3858 5.8534 0.7836
log MBC P=0.0012 0.7440 0.2256 6.6650 0.4751
sqrt NO3- P<0.0001 0.2180 0.0266 7.5275 0.0959
Rainfall P=0.9690
Max. Temp. P=0.5436
Min. Temp. P=0.8774
Soil Water P=0.1417
log NH4+ P=0.3633
log PMN P=0.7610
Ch. 4: Seasonal Dynamics
105
Figure 4.5. Significant linear regression relationships between logged bacterial
amoA gene abundance (logAOB) and (a) logged dissolved organic carbon
(logDOC); (b) logged microbial biomass carbon (logMBC); and (c) square root
transformed nitrate concentration (sqrtNO3-).
Ch. 4: Seasonal Dynamics
106
Figure 4.6. Principal component analysis biplot of principal components 1 (PC1)
and 2 (PC2). Abbreviations: logAOB: logged bacteria amoA gene abundance; Rf:
rainfall; Tmax and Tmin: mean daily maximum and minimum soil temperature at 5 cm
depth respectively, Wa: soil water content at collection, MBC: microbial biomass
carbon, DOC: dissolved organic carbon, NH4: ammonium, NO3: nitrate, PMN:
potentially mineralisable nitrogen, OM: organic matter; RD: Run-Down. Symbol
colours represent field organic matter treatments and symbol shapes represent sampling
date.
Tabl
e 4.
3. E
igen
vect
or lo
adin
gs o
f pri
ncip
al c
ompo
nent
s 1–6
.
PC
1 PC
2 PC
3 PC
4 PC
5 PC
6
Stan
dard
dev
iatio
n 1.
9086
1.
4933
1.
1831
0.
9747
0.
8023
0.
6193
Var
ianc
e (e
igen
valu
e)
3.64
28
2.22
98
1.39
98
0.95
00
0.64
37
0.44
73
Prop
ortio
n of
var
ianc
e 0.
3643
0.
2230
0.
1400
0.
0950
0.
0644
0.
0447
Cum
ulat
ive
prop
ortio
n of
var
ianc
e 0.
3643
0.
5873
0.
7272
0.
8223
0.
8866
0.
9313
Ch. 4: Seasonal Dynamics
108
Table 4.4. Loadings matrix (eigenvectors) for principal components 1–6.
Abbreviations: Rainfall: cumulative rainfall of 30 days prior to soil collection; Water:
soil water content at collection; Min. Temp. and Max. Temp: mean daily minimum and
maximum soil temperature at 5 cm depth of 30 days prior to soil collection; MBC:
microbial biomass carbon; DOC: dissolved organic carbon; PMN: potentially
mineralisable nitrogen; log AOB: logged bacterial amoA gene abundance. PC1 PC2 PC3 PC4 PC5 PC6
Rainfall 0.4113 0.0203 0.1119 -0.3201 -0.3437 -0.2311
Water 0.4882 -0.0813 0.0337 0.0731 -0.0796 -0.2072
Min. Temp. -0.4778 0.1972 -0.0120 -0.0306 -0.2070 -0.0803
Max. Temp. -0.4709 0.2078 0.0693 -0.0335 -0.1947 -0.0429
MBC -0.0409 -0.4864 0.3002 -0.0846 0.5695 0.2874
DOC -0.3398 -0.4062 0.2305 0.0899 -0.0609 -0.2257
NH4+ 0.0529 -0.2250 -0.4530 0.7184 -0.2123 0.2411
NO3- -0.1359 -0.4051 -0.4754 -0.1341 0.1372 -0.6772
PMN 0.0025 -0.4055 0.5129 0.1785 -0.5219 -0.0455
log AOB -0.0647 -0.3607 -0.3792 -0.5559 -0.3611 0.4929
4.5. Discussion
Ammonia-oxidising bacteria rather than AOA appear to regulate nitrification processes
in the surface layer of this semi-arid agricultural soil across both the hot and dry
summer fallow and the cool and wet winter cropped seasons. This agrees with other
studies from this region (Appendix A; Gleeson et al., 2010; O’Sullivan et al., 2013) but
is in contrast to other semi-arid environments and agricultural soils, which have found
that AOA are often dominant to AOB (Adair and Schwartz, 2008; Leininger et al.,
2006; O’Sullivan et al., 2013; Zhang et al., 2012). Here, we speculate that AOA were
not detectable in the topsoil as a consequence of soil properties that have been modified
by agricultural practices, particularly NH4+ availability. Archaeal ammonia oxidisers
were present in the subsoil of the same soil as the present study (mean maximum 2.1 x
105 gene copies g-1 dry soil in 60–90 cm layer; Appendix A), and also in the surface
Ch. 4: Seasonal Dynamics
109
layer of the adjacent native bushland (2.60 x 104 gene copies g-1 dry soil using the same
archaeal amoA gene primers; L. Maccarone, pers. comm.). This agricultural soil has
annual additions of inorganic N fertiliser, which increases NH4+ availability in the
surface layers and may have inhibited AOA, as has been attributed in other soils (Di et
al., 2010; Di et al., 2009; Pratscher et al., 2011; Shen et al., 2011). Archaeal ammonia
oxidisers have greater substrate affinity for ammonia than AOB so may prefer low
ammonia environments, and AOA are more sensitive to high concentrations of
ammonia than AOB (Di et al., 2010; Martens-Habbena et al., 2009). Bacterial ammonia
oxidisers therefore may dominate in soils as in the present study that are regularly
fertilised (Prosser and Nicol, 2012). Other factors regulating AOA and AOB
abundances however cannot be ruled out. Collaborative work that examined ammonia
oxidiser gene abundances with depth in the same soil as the present study found AOB
abundance was positively and AOA abundance was negatively correlated with soil pH
and soil OM (Appendix A). Archaeal ammonia oxidisers tend to dominate over AOB in
soils with low (acidic) pH (He et al., 2012; Hu et al., 2013), but the surface soil
examined in the present study has a pH close to neutral (Table 4.1). Agricultural
modification of soil pH by additions of lime may therefore have combined with N
fertiliser and crop residue additions to increase soil pH and substrate availability,
creating conditions that have allowed AOB to compete more successfully in the surface
soil.
The poor relationship between bacterial amoA gene abundance and rainfall, soil
temperature, soil water content at collection was unexpected. Seasonal variation in AOB
abundance instead was related to DOC, MBC and NO3- concentrations, but as
hypothesised, not to NH4+ concentrations. Other authors have observed that climate
effects such as rainfall, soil water content and temperature are more important than
Ch. 4: Seasonal Dynamics
110
agricultural management effects on soil and microbial processes in semi-arid soils
(Hoyle and Murphy, 2011; Noy-Meir, 1973). A positive correlation has also been
reported between AOB and soil water content (adjusted R2 of multiple regression model
including OM and NO3- = 0.53; Sher et al., 2013). The lack of a relationship between
AOB abundance and environmental conditions in the present study might be explained
by the disconnect between longer-term population dynamics and shorter-term
environmental events. Although directly influenced by environmental conditions such
as soil water and temperature, abundances of functional genes are less dynamic than
many environmental and edaphic characteristics, so functional gene abundances likely
reflect the longer-term variation of those characteristics (Petersen et al., 2012).
Although there was no linear correlation between AOB and climate characteristics, the
PCA showed that variation in all the data was partly explained by rainfall, soil water
content and temperature and clearly grouped by sampling date (Fig. 4.6; PC1 in Table
4.4). The absence of a correlation between AOB abundance and NH4+ concentration
was expected because soil NH4+ concentrations are not a good indication of NH4
+
substrate availability or activity of ammonia oxidisers (Prosser and Nicol, 2012). Nitrate
dominates inorganic N pools in semi-arid soil from this region, indicating active
nitrification and rapid depletion of NH4+ pools (Fig. 4.3; Barton et al., 2008; Barton et
al., 2013b; Cookson et al., 2006b). Alternatively, heterotrophic nitrifiers may be
important in this soil, producing NO3- from organic N sources, which may also explain
the correlation between DOC and AOB abundance. Modelling of gross N
transformation rates in another Australian semi-arid soil suggested that greater than
50% of nitrification could be explained by heterotrophic nitrification (Cookson et al.,
2006b). From culture studies there is evidence for mixotrophic and heterotrophic
growth in AOB, including the ability to take up low molecular weight organic
compounds, the presence of genes encoding organotrophic metabolic pathways and
Ch. 4: Seasonal Dynamics
111
anaerobic growth on organic compounds (Sayavedra-Soto and Arp, 2011; Schmidt,
2009; Walker et al., 2010). These findings suggest that seasonal dynamics of AOB
populations are not yet well understood, but are due to many interacting factors that will
consequently influence risk of N loss through the production of NO3-.
Crop residue inputs may have positively but indirectly influenced bacterial amoA gene
abundance (irrespective of the time of year) due to the enhanced supply of either C or N
substrates. The effect of soil OM content on AOB in other semi-arid soils varies from
these observations. For example, bacterial amoA gene abundance in summer and winter
over six years in a semi-arid shrubland soil was negatively correlated with soil OM
(Sher et al., 2013). This negative correlation would be expected to occur if soil OM
stimulates heterotrophic microorganisms to compete more successfully for NH4+,
decreasing N substrate availability and thus growth of autotrophic ammonia oxidisers.
The positive effect of increased soil OM pools on AOB abundance in the present study
could be attributed to the associated increases in N supply to autotrophic ammonia
oxidisers, or greater DOC pools (and presumably dissolved organic N), which would
also directly stimulate heterotrophic ammonia oxidisers. Previous work on the same soil
showed additional crop residue inputs increased gross N mineralisation, immobilisation
as well as nitrification rates (Chapter 3), suggesting that increased soil OM stimulates
both heterotrophic and autotrophic microbial populations.
Bacterial ammonia oxidiser growth during summer fallow is likely an important factor
determining increases in soil NO3- pools and consequently risk of N loss in this semi-
arid soil. Soil NO3- pools are a balance of inputs and outputs. Nitrate inputs into the
surface soil (0–10cm) appear to continue as summer progresses (Fig. 4.3), as also
observed in similar semi-arid soils in response to summer rainfall events, which
Ch. 4: Seasonal Dynamics
112
stimulate N mineralisation (Barton et al., 2008; Barton et al., 2013b; Murphy et al.,
1998b). In contrast to inputs, outputs of NO3- in this region are likely to be low during
summer fallow, with plant uptake minimal or non-existent due to the absence of plants,
and it is not until the start of the growing season rains that any significant deep drainage
and NO3- leaching occurs (Anderson et al., 1998). Correlation of bacterial amoA gene
abundance and NO3- pool size suggests that increases in NO3
- during summer are not
due merely to N mineralisation flushes and lack of inorganic N uptake, but also due to
growth of the AOB population, strongly coupled to activity of nitrite-oxidising bacteria.
Bacterial amoA gene abundance was less in summer than in winter in another semi-arid
soil from Israel, which was attributed to the sensitivity of AOB to high temperatures, at
that site ranging from 23–35 °C in summer (Sher et al., 2013). By contrast, bacterial
amoA gene abundance in the present study continued to increase over summer, even
though soil temperatures exceeded 40 °C (Fig. 4.1a). This may be because AOB were
sampled more often, so finer scale population dynamics could be observed in this soil.
An alternative explanation is that AOB in the present study region have adapted to
periods of high temperature and low water availability, allowing them to survive then
continue to grow when conditions become favourable, even if only briefly due to
transient water pulses from summer rainfall events.
Predicted changes in climate for this region are likely to exacerbate the effects of AOB
population dynamics and NO3- production, particularly during summer fallow. Since the
1970s, mean annual rainfall in Southern Hemisphere semi-arid regions has been
decreasing, especially during autumn and winter at the start of the growing season (Cai
et al., 2012; Nicholls, 2010). Summer rainfall events however are increasing (Alexander
et al., 2007), which will likely enhance inorganic N supply through OM decomposition
when there is no plant N uptake from fallow soil (Austin et al., 2004; Murphy et al.,
Ch. 4: Seasonal Dynamics
113
1998b). This inorganic N is then at risk of loss if it is in excess of microbial demand and
is nitrified. With continuing climate change in this semi-arid region, it is likely to
become increasingly challenging to manage undesirable losses of N from soil.
4.6. Conclusions
Seasonal variation of bacterial amoA gene abundance in this soil is likely a factor
contributing to NO3- production and risk of N loss, especially as summer fallow
progresses. Archaea however are unlikely to be influential drivers of ammonia
oxidation as archaeal amoA gene abundances were predominantly below detection
limits in the surface layers, possibly due to N fertilisers enhancing soil N substrate
supply. Increased soil OM levels by additional crop residue inputs positively influenced
bacterial amoA gene abundances, but did not modify seasonal variation in ammonia
oxidiser abundance. As expected, bacterial amoA gene abundance was not related to
NH4+ concentration, but surprisingly was also not related to soil water content, 30-day
rainfall or mean soil temperature. Bacterial amoA gene abundance was related to DOC,
MBC, and NO3- suggesting that ammonia oxidiser populations are either regulated by
longer-term changes in climate and substrate supply, or that heterotrophic nitrification
may be important in this semi-arid soil.
Ch. 4: Seasonal Dynamics
114
115
Chapter 5.
Nitrapyrin decreased nitrification of nitrogen
released from soil organic matter but not amoA
gene abundance at high soil temperature
5.1. Abstract
Water pulses have a significant impact on nitrogen (N) cycling, making management of
N challenging in agricultural soils that are exposed to episodic rainfall. In hot, dry
environments, wetting of dry soil during summer fallow causes a rapid flush of organic
matter mineralisation and subsequent nitrification, which may lead to N loss via nitrous
oxide emission and nitrate leaching. Here we examined the potential for the nitrification
inhibitor nitrapyrin to decrease gross nitrification at elevated temperature in soils with
contrasting soil organic matter contents, and the consequent effects on ammonia
oxidiser populations. Soil was collected during summer fallow while dry (water content
0.01 g g-1 soil) from a research site with two management treatments (tilled soil and
tilled soil with long-term additional crop residues) by three field replicates. The field
dry soil (0–10 cm) was wet with or without nitrapyrin, and incubated (20 or 40 °C) at
either constant soil water content or allowed to dry (to simulate summer drying after a
rainfall event). Gross N transformation rates and inorganic N pools sizes were
determined on six occasions during the 14 day incubation. Bacterial and archaeal amoA
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116
gene abundance was determined on days 0, 1, 7 and 14. Nitrapyrin increased
ammonium retention and decreased gross nitrification rates even with soil drying at 40
°C. Nitrification was likely driven by bacterial ammonia oxidisers, as the archaeal amoA
gene was below detection in the surface soil layer. Bacterial ammonia oxidiser gene
abundances were not affected by nitrapyrin, despite the decrease in nitrifier activity.
Increased soil organic matter from long-term additional crop residues diminished the
effectiveness of nitrapyrin. The present study highlights the potential for nitrapyrin to
decrease nitrification and the risk of N loss due to mineralisation of soil organic matter
under summer fallow conditions.
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5.2. Introduction
Regions where water-limited soils occur at high temperatures include those with semi-
arid, arid and Mediterranean-type climates, which are widely used for agricultural
production. Most agricultural mitigation strategies for nitrogen (N) loss are targeted
towards increasing N fertiliser use efficiency, through for example, matching spatial and
temporal N supply to crop N demand during the growing season (Meisinger and
Delgado, 2002; Murphy et al., 2004). A large proportion of N losses in water-limited
soils however can be in response to biochemical processes that occur during the dry,
non-growing season (Anderson et al., 1998; Austin et al., 2004; Barton et al., 2008;
Mummey et al., 1997). Management of these losses are challenging, as they occur in
response to episodic rainfall events, rather than agricultural management practices.
After summer rainfall in semi-arid environments, microorganisms rapidly become
active, resulting in a flush of soil organic matter (OM) mineralisation that increases
inorganic N availability (Austin et al., 2004; Murphy et al., 1998b). Production of
inorganic N is particularly detrimental in fallow soil, as plant uptake is non-existent and
nitrate (NO3-) is at risk of loss by leaching during subsequent rainfall and drainage
events (Anderson et al., 1998; Arregui and Quemada, 2006). In addition, up to half of
annual emissions of the greenhouse gases nitric oxide (NO) and nitrous oxide (N2O) can
occur when hot, dry soil is wetted (Barton et al., 2008; Barton et al., 2013b; Galbally et
al., 2008).
One strategy that decreases the potential for N loss is the use of a nitrification inhibitor.
These chemicals control nitrification, the key pathway for N loss, often by binding or
otherwise deactivating one of the enzymes involved (Slangen and Kerkhoff, 1984).
Generally, the effectiveness of nitrification inhibitors decreases with increasing
temperature, due to increasing microbial degradation, stimulation of microbial activity
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118
and loss of volatile chemicals (Slangen and Kerkhoff, 1984). Nitrapyrin (2-chloro-6-
(trichloromethyl)-pyridine) has been successfully used for many years to decrease
nitrification and N loss from applied fertiliser where N inputs are high (45–338 kg N ha-
1; Wolt, 2004), and has been effective at soil temperatures as high as 25–35 °C (Ali et
al., 2008; Chen et al., 2010). These studies have investigated the effectiveness of
nitrapyrin in the presence of N fertiliser, however it is not clear if nitrapyrin inhibits
nitrification due to N released from soil OM mineralisation.
The effectiveness of nitrapyrin at decreasing nitrification in soil depends on a number of
interacting factors besides soil temperature (Slangen and Kerkhoff, 1984). Soil OM both
absorbs nitrapyrin and provides an energy source for the microorganisms which degrade
nitrapyrin, decreasing the ability of nitrapyrin to inhibit nitrification (Goring, 1962;
Lewis and Stefanson, 1975). Semi-arid soils often have low OM contents due to the
seasonally dry climate, low plant productivity and continual soil loss by erosion
(Archibold, 1995; Ryan, 2011). We expected that nitrapyrin would more effectively
inhibit nitrification at elevated temperatures in a low OM soil compared to where
additional crop residue inputs have increased soil OM. There is a paucity of research
about the effect of soil wetting and drying events on the effectiveness of nitrapyrin,
however some research suggests that nitrification inhibitors can be more effective when
either low or high water content limits the activity of nitrifying organisms (Keeney,
1986). We therefore hypothesised that nitrapyrin would be more effective as soil dried
and nitrification activity decreased.
The mechanism by which nitrapyrin inhibits nitrification is thought to involve ammonia
monooxygenase (AMO), the main enzyme involved in ammonia oxidation (Vannelli
and Hooper, 1992). Nitrapyrin is a substrate for AMO, producing 6-chloropicolinic acid
Ch. 5: Nitrapyrin at High Temperature
119
which then binds indiscriminately to other membrane proteins, the suggested
mechanism for inactivation of ammonia oxidation (Vannelli and Hooper, 1992).
Nitrapyrin does not inhibit hydroxylamine oxidation or nitrite oxidation (the steps in
nitrification following ammonia oxidation) except at extremely high concentrations
(80–175 ppm; Campbell and Aleem, 1965a, b). The subunit of AMO contains the
enzyme’s active site and is encoded by the amoA gene, which has homologous gene
sequences in both ammonia-oxidising bacteria (AOB) and archaea (AOA; Nicol and
Schleper, 2006). We therefore hypothesised that inhibition of AMO by nitrapyrin would
diminish the ability of ammonia-oxidising microorganisms to obtain energy and to
grow, thus decreasing amoA gene abundance. Few studies have examined the effect of
nitrapyrin on ammonia oxidiser populations, and findings have been contradictory (Cui
et al., 2013; Lehtovirta-Morley et al., 2013; Shen et al., 2013). Further research is
necessary to unravel the many interacting factors that control effectiveness of nitrapyrin
at inhibiting ammonia-oxidising microorganisms and nitrification.
Consequently, we examined the potential of the nitrification inhibitor nitrapyrin to
control nitrification at elevated soil temperature in response to a simulated rainfall
wetting and drying event. Specifically, we determined (i) whether nitrapyrin decreased
gross nitrification rates without altering other N transformation rates at 20 and 40 °C;
(ii) whether increased soil OM content diminishes the ability of nitrapyrin to inhibit
nitrification at elevated temperature; (iii) whether decreasing water content with time
(as occurs when soil dries after a summer rainfall event) increases the ability of
nitrapyrin to inhibit nitrification compared to when soil water content is optimal; and
(iv) if populations of AOA or AOB are consequently affected.
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120
5.3. Methods
5.3.1. Soil and soil collection
Soil was collected from the Liebe Group’s Soil Biology Trial (30.00° S, 116.33° E), in
the northern wheatbelt of Western Australia, approximately 221 km north-northeast of
Perth. This research site was established in 2003 with a three year lupin-wheat-wheat
rotation and a range of field management treatments to create a range of soil OM
contents. Each treatment has three field replicate plots that are 80 m long and 10 m
wide. Two treatments with contrasting OM contents were selected for the present study:
tilled soil (‘Tilled’), and tilled soil loaded with additional OM (‘Tilled+OM’). The
Tilled soil was tilled to 10–15 cm depth annually using offset discs before seeding, and
seeded with knife point tines to 15 cm depth. Tilled+OM soil had 20 t ha-1 barley,
canola, oat and oat chaff tilled into the soil in 2003, 2006, 2010 and 2012 respectively,
using the same tillage method described for the Tilled soil. This represented an
additional 36 t C ha-1, of which 7.0 t C ha-1 was retained as extra soil organic carbon
(SOC) in the Tilled+OM soil nine years after trial establishment (i.e. 64% more SOC in
Tilled+OM than in Tilled soil; Table 5.1).
The region has a semi-arid climate, with hot, dry summers and cool, wet winters (when
cropping occurs). Based on 15 years of climate data (1997–2014) the area has a mean
annual rainfall of 284.9 mm, mean monthly temperatures ranging from 5.8–35.3 °C and
actual temperatures ranging from -1.0–46.9 °C (Commonwealth of Australia Bureau of
Meteorology, http://www.bom.gov.au/climate/data). At the research site, soil
temperatures (5 cm depth) ranged from 6.2–45.6 °C (2008–2012). Soil at the site is a
deep sand (92% sand, 2% silt, 6% clay) and classified as a Basic Regolithic Yellow-
Orthic Tenosol (Australian soil classification; Isbell, 2002), or a Haplic Arenosol
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121
(World Reference Base for Soil Resources; IUSS Working Group WRB, 2007).
Selected soil chemical and biological properties are listed in Table 5.1.
Soil was sampled in late summer (27 March 2012), prior to the first rains of the
autumn/winter growing season. At this time, the soil was fallow and naturally air-dry
(field soil water content of 0.01 g g-1 soil). Rain had last fallen in mid-summer (3
February 2012), 52 days prior to soil sampling, and over those 52 days, daily maximum
soil temperatures at 5 cm depth ranged from 26–39 °C. A composite sample (40 cores,
each 7 cm diameter by 10 cm depth) were taken from each replicate field plot in a
zigzag sampling pattern. Samples were sieved (<2 mm) and stored without further
drying at room temperature until further analysis.
Table 5.1. Properties of field soils (0–10 cm depth), collected nine years after soil
organic matter (OM) treatments were imposed. Values are means ±SEM (n = 3). Tilled soil Tilled+OM soil
Soil pHCaCl2 # 6.15 ± 0.18 6.23 ± 0.13
Total carbon (%) § 0.78 ± 0.03 1.31 ± 0.07**
Total carbon (t ha-1) 10.83 ± 0.55 17.78 ± 1.10**
Total nitrogen (%) § 0.06 ± 0.00 0.10 ± 0.01**
Soil C:N ratio 12.9 ± 0.2 12.9 ± 0.2
Ammonium-N (µg g-1) 2.25 ± 0.45 1.76 ± 0.57
Nitrate-N (µg g-1) 20.47 ± 1.05 31.83 ± 2.49
Bacterial amoA (gene copies g-1) 2.08 x 107 ± 4.22 x 106 2.01 x 107 ± 6.65 x 106
Archaeal amoA (gene copies g-1) <1 x 103 <1 x 103
**Tilled+OM soil is significantly different from Tilled soil at P<0.01.
#Soil pH measured in 0.01 M CaCl2 with a 1:5 soil:extract ratio
§Total C, and total N determined by dry combustion of finely ground soil using an Elementar Vario
MACRO CNS elemental analyser (Hanau, Germany).
5.3.2. Laboratory experimental design
The laboratory experimental design was two nitrification inhibitor treatments (with or
without nitrapyrin), two incubation temperatures (20 and 40 °C), two soils of differing
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OM contents (Tilled and Tilled+OM soil) by three field replicates, and two soil water
regimes (OWC and DRY; explained below). The nitrification inhibitor used was
nitrapyrin (2-chloro-6-(trichloromethyl)-pyridine) at 9 µg active ingredient g-1 dry soil.
The soil water regimes were: simulated rainfall event to optimum soil water content that
was held at optimum over the course of the experiment (OWC); and a simulated rainfall
event to optimum soil water content with subsequent drying (DRY). The optimal soil
water content chosen was 45% water-filled pore space (WFPS), as (i) this is the WFPS
that occurs following a common summer rainfall event for this region of 15 mm; (ii)
measured field soil water content in this region rarely exceeds 45% WFPS (Barton et
al., 2011; Barton et al., 2008; Barton et al., 2013b); and (iii) because at this WFPS
neither mineralisation nor nitrification are constrained in this soil type (Gleeson et al.,
2010).
5.3.3. Gross N transformation rates and inorganic N analysis
15N isotopic pool dilution was used to calculate gross N cycling transformation rates.
Paired treatments of 15N were either 15N enriched (60 atom%) ammonium sulphate
[(NH4)2SO4] + potassium nitrate (KNO3) at natural abundance, or (NH4)2SO4 at natural
abundance + 15N enriched (60 atom%) KNO3. Both (NH4)2SO4 and KNO3 were applied
at 5 µg N g-1. In total, four solutions were prepared for application to the samples:
(15NH4)2SO4 + KNO3; (NH4)2SO4 + K15NO3; (15NH4)2SO4 + KNO3 + nitrapyrin; and
(NH4)2SO4 + K15NO3 + nitrapyrin. Each of the four 15N solutions were then added to
separate subsamples of soil, which were mixed well and then packed into 120 mL vials
to 10 cm depth and to the bulk density at the research site (1.4 g cm-3 bulk density).
Optimal water content vials were sealed inside 500 mL glass jars with 5 mL of water at
the bottom, to minimise evaporation. These jars were aerated every 24 hours to prevent
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anaerobic conditions developing. DRY vials were incubated without lids. Samples were
incubated at either 20 or 40 °C for up to 14 days.
Soils were extracted on six occasions during the incubation: 2–4 hours after 15N
addition, and at 1, 3, 7, 10 and 14 days. At each of these sampling times, soil was mixed
and then a subsample (ca. 20 g) was snap-frozen in liquid N, and then stored at -80 °C
for subsequent DNA analysis (see below). Another subsample of soil (ca. 30 g) was
used to determine gravimetric soil water content. Water-filled pore space was calculated
by dividing volumetric water content by total porosity, where volumetric water content
is gravimetric water content multiplied by bulk density (1.4 g cm-3), and total porosity is
[1 – (bulk density / particle density)] × 100, using measured particle density for each
field soil replicate (Linn and Doran, 1984).
A further subsample (20.0 g) was extracted with 80 mL of 0.5 M potassium sulphate
(K2SO4) for 30 minutes in an end-over-end shaker, then filtered through Whatman No.
42 filter paper. The extracts were kept frozen at -20 °C until further analysis for
inorganic N. Using Buchner funnels under vacuum, the inorganic N remaining in soil
solution was removed by a second extraction with 80 mL of 0.5 M K2SO4 followed by
two extractions with 80 mL of MilliQ water. The remaining washed soil was dried at 70
°C and ground to a fine powder, then analysed for 15N atom% and total N using a
continuous flow system, consisting of a SERCON 20-22 Stable Isotope Ratio Mass
Spectrometer (IRMS) connected with an Automated Nitrogen Carbon analyser (Sercon,
Crewe, UK).
Inorganic N concentrations of the extracts were determined by colorimetric analysis on
a Skalar San Plus auto-analyser (Skalar Inc., Breda, The Netherlands), using the
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124
modified Berthelot reaction for ammonium-N (NH4+-N; Krom, 1980) and the
hydrazinium reduction method for NO3--N (Kamphake et al., 1967). The extracts from
each sampling time were prepared for IRMS 15N/14N isotope ratio analysis using a
modified diffusion method (Brooks et al., 1989; Sørensen and Jensen, 1991). The
extract NH4+ and NO3
- was trapped on separate acidified diffusion disc, and the discs
were analysed by IRMS as described above.
5.3.4. Calculation of gross N transformation rates
The analytical equations of Kirkham and Bartholomew (1954) were used to calculate
gross N mineralisation and nitrification rates between each sampling time point (i.e.
days 1–3, days 3–7, days 7–10, and days 10–14).
5.3.5. Nucleic acid extraction and qPCR
DNA was extracted from 800 mg sub-samples of soil immediately after wet-up and
from days 1, 7 and 14 of the incubation. The DNA PowerSoil® Kit (MoBio) was used
following the manufacturer’s instructions with one exception: the DNA was eluted in 50
µL of the final solution. DNA was stored at -40 °C prior to further analysis.
Bacterial and archaeal amoA genes were quantified by quantitative real-time
polymerase chain reaction (qPCR; Applied Biosystems ViiA™ 7) using GoTaq® qPCR
System (Promega Corp.). For bacterial amoA gene quantification, primers used were
amoA-1F (5ʹ-GGGGTTTCTACTGGTGGT-3ʹ) and amoA-2R (5ʹ-CCCCTCKGSAAA
GCCTTCTTC-3ʹ) with fragment length of 491 bp (Rotthauwe et al., 1997). Each 20 µL
qPCR reaction contained 10 µL of SYBR Green GoTaq® qPCR 2 × Master Mix
(Promega Corp.), 0.2 µL of each forward and reverse primer at a concentration of 10
µM, 2 µL bovine serum albumin (Ambion® UltraPure™ BSA, 5mg mL-1), 2 µL of
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template DNA and 5.6 µL of water. Cycling conditions were: 94 °C for 10 min, then 40
cycles of: 94 °C for 30 sec, 56 °C for 30 sec, 72 °C for 30 sec and 78 °C for 30 sec,
followed by a melt curve. Fluorescence data was collected at the 78 °C stage.
For archaeal amoA gene quantification, primers used were Arch-amoAF (5ʹ-
STAATGGTCTGGCTTAGACG-3ʹ) and Arch-amoAR (5ʹ-GCGGCCATCCATCT
GTATGT-3ʹ) with fragment length of 635 bp (Francis et al., 2005). Each 10 µL qPCR
reaction contained 5 µL of SYBR Green GoTaq® qPCR 2 × Master Mix (Promega
Corp.), 0.1 µL of each forward and reverse primer at a concentration of 10 µM, 1 µL
BSA, 1 µL of template DNA and 2.8 µL of water. Cycling conditions were: 94 °C for
10 min, then 40 cycles of: 94 °C for 1 min, 52 °C for 1 min, 72 °C for 1 min and 78 °C
for 1 min, followed by a melt curve. Fluorescence data was collected at the 78 °C stage.
Each standard and sample was replicated three times during each qPCR run. Templates
for determining gene copy numbers in the qPCR reactions were cloned plasmids as
described in Barton et al. (2013a). The standard curves generated were linear over four
orders of magnitude (103–106 gene copies) for AOB and over six orders of magnitude
for AOA (103–108 gene copies) with r2 values greater than 0.98. Amplification
efficiencies ranged from 83–98% and a dilution series determined if there was any
inhibition in the samples. The lower detection limit was 103 gene copies in 1 µL
template.
5.3.6. Statistical analysis
Statistical differences between the field soil properties of the soil OM management
treatments were examined using analysis of variance (ANOVA) with associated
TukeyHSD post hoc tests in R version 3.1.0 (R Foundation for Statistical Computing,
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126
Vienna, Austria). Statistical significances of nitrapyrin, soil OM management,
temperature, and water regime treatments on WFPS, labelled NH4+ and NO3
-, gross N
transformation rates and amoA gene abundance with time were evaluated using a mixed
model, PROC MIXED in SAS version 9.3 (SAS Institute Inc., Cary, NC, USA).
Ammonia oxidiser amoA gene abundance data was log10 transformed before all
analyses. Time was a significant factor for all variables, so each time point was
analysed separately to better clarify statistical relationships between treatments. R
version 3.1.0 was used to run linear regressions of gross N transformation rates, against
ammonia oxidiser amoA gene abundance at the end of the period over which each rate
was calculated.
5.4. Results
5.4.1. Recovery of 15N
Two hours after 15NH4+ application, mean recovery of 15N was 33% at 20 °C and 93%
at 40 °C (combined inhibitor, soil and water regime treatments are shown in Fig. 5.1a).
Recovery of applied 15NH4+ at 20 °C increased to day 7, after which mean 15N recovery
was stable at 74%. The low recovery of 15N two hours after 15NH4+ application at 20 °C
was not due to nitrification, as there was no appearance of 15NO3-. Due to this low
recovery of 15NH4+ at two hours, gross N mineralisation rates from 2 hr–day 1 were not
calculated. Mean recovery of applied 15NO3- at both temperatures and all time points
was approximately constant at 80% (combined inhibitor, soil and water regime
treatments are shown in Fig. 5.1b). In all treatments where 15NO3- was applied, no
remineralisation through to 15NH4+ was detected.
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127
5.4.2. Water-filled pore space
Water-filled pore space in the OWC samples was maintained between 41–45%
throughout the incubation (combined inhibitor treatments are shown in Fig. 5.2). Water-
filled pore space in DRY samples decreased with time, from a mean of 43% to a
minimum on day 14. Minimum mean WFPS in DRY samples was less in Tilled soil
than in Tilled+OM soil [10 and 15% respectively at 20 °C (Fig. 5.2a); and 1 and 5% at
40 °C respectively (Fig. 5.2b); P<0.0001].
5.4.3. Labelled ammonium and nitrate-N
After 15NH4+ application, nitrapyrin maintained labelled NH4
+ pools approximately
constant from day 3 at 40 °C, in contrast to labelled NH4+ pools without nitrapyrin
which generally decreased with time, and were less than in the presence of nitrapyrin
from day 3 until day 14 (P<0.0001; data not shown). Nitrapyrin was more effective at
retaining labelled NH4+ in soil without additional OM at 40 °C, and in soil held at
OWC. Labelled NH4+ in Tilled+OM soil with nitrapyrin was less than in Tilled soil with
nitrapyrin on all days of incubation (P<0.05), and labelled NH4+ in DRY soil with
nitrapyrin was less than in OWC soil with nitrapyrin from day 1 onwards (P<0.0001).
Labelled NH4+ at 20 °C followed the same general pattern as at 40 °C but on average
was 27% of 40 °C labelled NH4+ (data not shown).
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128
Figure 5.1. Change in total recovery of 15N (% of applied 15N) through time from
soil applied with (a) 15N-labelled NH4+ and (b) 15N-labelled NO3
-. Error bars are
±SEM (n = 24) and may be smaller than the symbols. Legend is the same for both
panels.
Figure 5.2. Change in water-filled pore space (% WFPS) through time (a) at 20 °C;
and (b) at 40 °C. Error bars are ±SEM (n = 12) and are smaller than the symbols.
Legend is the same for both panels. Legend abbreviations: OWC: samples held at
optimal water content (45% WFPS); DRY: samples wet-up to 45% WFPS then allowed
to dry; OM: organic matter.
Ch. 5: Nitrapyrin at High Temperature
129
Figure 5.3. Change in 15N-labelled nitrate (NO3-) above natural abundance through
time with added 15(NH4)2SO4. (a) at 20 °C in soil held at optimal water content (45%
WFPS); (b) at 20 °C in soil wet-up to 45% WFPS then allowed to dry; (c) at 40 °C in
soil held at optimal water content; and (d) at 40 °C in soil wet-up then allowed to dry.
Error bars are ±SEM (n = 3). Legend is the same for all panels. Legend abbreviation:
OM: organic matter.
After 15NH4+ application, nitrapyrin kept labelled NO3
- pools constant at 0.1 µg 15N g-1
from days 1–14 at 40 °C, in contrast to labelled NO3- pools without nitrapyrin, which
generally increased with time (Fig. 5.3c–d). There was no difference in labelled NO3-
pools between Tilled and Tilled+OM soils or between OWC and DRY samples in the
presence of nitrapyrin at 40 °C (P<0.05; Fig. 5.3c–d). Without nitrapyrin however,
labelled NO3- pools in Tilled soil were greater than in Tilled+OM soil from days 1–14
at 40 °C (P<0.0001; Fig. 5.3c–d). Labelled NO3- at 20 °C generally followed a similar
pattern and magnitude as at 40 °C (Fig. 5.3a–b).
Ch. 5: Nitrapyrin at High Temperature
130
5.4.4. Unlabelled inorganic N
Unlabelled NH4+ pools at 40 °C were greater in the presence of nitrapyrin than without
from days 7–14 (P<0.0001; Fig. 5.4a–b). Ammonium pools increased to a greater extent
in the presence of nitrapyrin in Tilled+OM soil than in Tilled soil at 40 °C. Nitrapyrin
retained more NH4+ in OWC samples than in DRY samples at 40 °C (P<0.001).
Nitrapyrin had a similar effect on NH4+ in soil incubated at 20 °C, but NH4
+ pools were
on average 40% of NH4+ pools at 40 °C (Fig. 5.5a–b).
Nitrapyrin kept unlabelled NO3- pools at 40 °C approximately stable in DRY soil, while
NO3- pools decreased with time at OWC (Fig. 5.4c–d). Without nitrapyrin, NO3
- pools
generally increased with time to levels greater than in soil with nitrapyrin on days 10–
14 at OWC (P<0.0001) and on days 7–14 in DRY soil (P<0.01). Tilled+OM soil had
greater NO3- than Tilled soil in DRY samples from days 1–10 (P<0.05), but at OWC,
there was no difference in NO3- between OM treatments after 2 hr (P<0.05). Nitrate
changes with time at 20 °C were more related to OM treatment than nitrapyrin (Fig.
5.5c–d). At OWC and 20 °C, NO3- pools in Tilled+OM soil were greater than Tilled soil
until day 10, and nitrapyrin decreased the NO3- pool size in both OM treatments on days
10–14 (P<0.05; Fig. 5.5c). Nitrate in DRY soil at 20 °C remained generally constant in
all treatments from days 3–14 (Fig. 5.5d).
Total inorganic N at 40 °C generally increased with time, and nitrapyrin had no effect in
DRY soil (P>0.05; Fig. 5.4e–f). At OWC however, total inorganic N was greater in the
presence of nitrapyrin in Tilled+OM soil (P<0.05) but not in Tilled soil at 40 °C
(P>0.05; Fig. 5.4e). Total inorganic N in Tilled+OM soil was generally greater than
Tilled soil at 40 °C. Total inorganic N at 20 °C was not affected by nitrapyrin, and
Ch. 5: Nitrapyrin at High Temperature
131
followed similar patterns with time and OM treatment as that observed in the NO3-
traces at 40 °C (Fig. 5.5e–f).
Figure 5.4. Change in unlabelled inorganic N through time at 40 °C. (a) NH4+-N in
soil held at optimal water content (45% WFPS); (b) NH4+-N in soil wet-up (to 45%
WFPS) then allowed to dry; (c) NO3--N in soil held at optimal water content; (d) NO3
--
N in soil wet-up then allowed to dry; (e) total inorganic N in soil held at optimal water
content; and (f) total inorganic N in soil wet-up then allowed to dry. Error bars are
±SEM (n = 6). Legend is the same for all panels. Legend abbreviation: OM: organic
matter.
Ch. 5: Nitrapyrin at High Temperature
132
Figure 5.5. Change in unlabelled inorganic N through time at 20 °C. (a) NH4+-N in
soil held at optimal water content (45% WFPS); (b) NH4+-N in soil wet-up (to 45%
WFPS) then allowed to dry; (c) NO3--N in soil held at optimal water content; (d) NO3
--
N in soil wet-up then allowed to dry; (e) total inorganic N in soil held at optimal water
content; and (f) total inorganic N in soil wet-up then allowed to dry. Error bars are
±SEM (n = 6). Legend is the same for all panels. Legend abbreviation: OM: organic
matter.
Ch. 5: Nitrapyrin at High Temperature
133
5.4.5. Gross N transformation rates
Mean gross nitrification rates at 40 °C ranged from 0–3.3 µg N g-1 d-1 (Fig. 5.6g–h).
Addition of nitrapyrin decreased gross nitrification at 40 °C in DRY samples between
days 1–7, and in OWC samples between days 1–3, and again between days 7–10
(P<0.05). During these time periods at 40 °C, nitrapyrin inhibited nitrification by a
mean of 86%. At 20 °C between days 1–3, nitrapyrin decreased gross nitrification in
DRY Tilled soil and OWC Tilled+OM soil (P<0.05; Fig. 5.6e–f). Furthermore, addition
of nitrapyrin decreased gross nitrification at 20 °C in DRY samples between days 3–7
(P<0.0001) and in OWC samples between days 7–14 (P<0.001; Fig. 5.6e–f). For these
samples at 20 °C, nitrapyrin inhibited nitrification by a mean of 62%. There was no
consistent effect of OM treatment, experimental water regime, or incubation
temperature on gross nitrification rates.
Gross N mineralisation rates at 40 °C generally decreased with time, and means ranged
from 0.1–7.1 µg N g-1 d-1 (Fig. 5.6c–d). Nitrapyrin had no consistent effect on gross N
mineralisation rates at either 20 or 40 °C (P>0.05). Tilled+OM soil had greater gross N
mineralisation rates than Tilled soil between 2 h and day 3 at 40 °C (P<0.05). Optimal
water content samples had greater gross N mineralisation than DRY samples between
days 3–14 at 40 °C (P<0.05). In general, gross N mineralisation at 20 °C was half of
gross N mineralisation at 40 °C, and followed a similar pattern over the incubation
period (Fig. 5.6a–b).
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134
Figure 5.6. Change in gross N mineralisation and nitrification rates through time.
Gross N mineralisation (a) at 20 °C in soil held at optimal water content (45% WFPS);
(b) at 20 °C in soil wet-up (to 45% WFPS) then allowed to dry; (c) at 40 °C in soil held
at optimal water content; and (d) at 40 °C in soil wet-up then allowed to dry. Gross
nitrification (e) at 20 °C in soil held at optimal water content; (f) at 20 °C in soil wet-up
then allowed to dry; (g) at 40 °C in soil held at optimal water content; and (h) at 40 °C
in soil wet-up then allowed to dry. Points shown are at the middle of the time period
over which the rates were calculated (1–3 days; 3–7 days; 7–10 days; and 10–14 days).
Error bars are ±SEM (n = 3). Legend is the same for all panels. Legend abbreviation:
OM: organic matter. Note the different y-axis scales of (c) and (d).
Ch. 5: Nitrapyrin at High Temperature
135
5.4.6. Bacterial and archaeal amoA gene abundance
Archaeal amoA gene abundance was below detection limits in the majority of samples,
and followed no pattern when detected (mean across all treatments: 3.30 x 104 gene
copies g-1 dry soil). Mean bacterial amoA gene abundance at 40 °C ranged from below
detection limits to 3.71 x 107 gene copies g-1 dry soil (Fig. 5.7c–d). Wetting of dry soil
at 40 °C immediately decreased bacterial amoA gene abundance between time zero and
day 1 in all 40 °C samples (P<0.0001; Fig. 5.7c–d) but gene abundance recovered to
similar levels as the original soil by day 14. Addition of nitrapyrin at 40 °C decreased
AOB gene abundance only in the DRY Tilled soil on day 7 (P<0.05; Fig. 5.7d).
Mean AOB gene abundance at 20 °C ranged from 4.32 x 105–7.28 x 107 gene copies g-1
dry soil (Fig. 5.7a–b). Wetting of dry soil at 20 °C decreased bacterial amoA gene
abundance between time zero and day 1 in DRY samples (P<0.0001) but not in OWC
samples (P>0.05; Fig. 5.7a–b). Addition of nitrapyrin at 20 °C decreased AOB gene
abundance only on day 7, in the Tilled soil for both OWC and DRY water regimes, and
in the DRY Tilled+OM soil (P<0.05; Fig. 5.7a–b). Otherwise there was no consistent
effect of experimental water regime or OM treatment on AOB gene abundance at 20 or
40 °C.
Bacterial amoA gene abundance had no relationship with gross nitrification (P>0.05),
but had a statistically significant negative relationship with gross N mineralisation
(P<0.05; data not shown). Adjusted R-squared values for this relationship however was
only 0.11, and the coefficient estimate was -0.052.
Ch. 5: Nitrapyrin at High Temperature
136
Figure 5.7. Change in bacterial amoA gene abundance (AOB) through time. (a) at
20 °C in soil held at optimal water content (45% WFPS); (b) at 20 °C in soil wet-up (to
45% WFPS) then allowed to dry; (c) at 40 °C in soil held at optimal water content; and
(d) at 40 °C in soil wet-up then allowed to dry. Error bars are ±SEM (n = 3). Legend is
the same for both panels. Legend abbreviation: OM: organic matter.
5.5. Discussion
Nitrapyrin has potential to decrease nitrification and thus the risk of N loss under
elevated soil temperatures. Despite the fact that nitrapyrin is reported to become less
effective at inhibiting nitrification with increasing temperature, the present study
indicates that nitrapyrin was still able to inhibit nitrification at elevated temperatures in
this semi-arid soil, without affecting other N transformation rates. Other studies have
found that nitrapyrin can decrease nitrification at temperatures from 25–35 °C (Ali et
al., 2008; Chen et al., 2010). Most research to date has focussed on effectiveness of
Ch. 5: Nitrapyrin at High Temperature
137
nitrapyrin at decreasing nitrification of NH4+-based fertilisers when applied during the
cropping season (for example Chen et al., 1994; Wolt, 2004). When nitrapyrin is
applied with a N source (such as N fertiliser), there is a more noticeable retention of
applied inorganic N due to the higher NH4+ concentration (for example Tu, 1973). Our
findings however extend the use of nitrapyrin to control nitrification of OM mineralised
outside the cropping season during summer fallow, with soil temperatures up to 40 °C.
Ammonia oxidiser gene abundance did not change in response to nitrapyrin, despite
decreased gross nitrification rates and therefore ammonia oxidiser function. Function
and population size were also disconnected as the AOB gene abundance had no
correlation to N transformation rates. This is in contrast to our expectations that
nitrapyrin would decrease ammonia oxidiser gene abundance, by diminishing energy
production and potential for growth. Few studies have examined the effect of nitrapyrin
on ammonia oxidiser gene abundance, and there is no clear evidence whether nitrapyrin
affects AOA or AOB to a greater extent. Nitrapyrin decreased both growth and activity
of the AOA Nitrosotalea devanaterra in liquid culture and soil (Lehtovirta-Morley et
al., 2013), while nitrapyrin had weak inhibitory effects on nitrification and AOB but not
AOA gene abundance in three Chinese soils (Cui et al., 2013). Nitrapyrin inhibited
production of nitrite by the AOA Ca. Nitrososphaera viennensis but had only a weak
inhibitory effect on production of nitrite by the AOB Nitrosospira multiformis in culture
(Shen et al., 2013). Evidently, different strains and communities of ammonia oxidisers
are influenced by nitrapyrin to differing degrees, likely also depending on
environmental and experimental conditions. Here we attributed nitrification to AOB, as
we were unable to detect AOA in the surface soil layer. Although AOB gene abundance
was not affected by nitrapyrin, an effect on gross nitrification was still observed. Our
Ch. 5: Nitrapyrin at High Temperature
138
results illustrate the need for further study to understand the complexities of ammonia
oxidiser sensitivities to nitrapyrin.
Organic matter additions to this soil decreased the effectiveness of nitrapyrin, observed
as a diminished retention of labelled NH4+. This was as expected, as nitrapyrin adsorbs
onto OM, decreasing its ability to inhibit ammonia oxidation (Goring, 1962). Organic
matter also increases soil microbial activity and provides carbon and N substrates for
microorganisms which degrade nitrapyrin (Goring, 1962). Recently there has been
much interest in building soil OM particularly for the purpose of sequestering C to
decrease atmospheric carbon dioxide levels and mitigate climate change (Powlson et al.,
2011; Viscarra Rossel et al., 2014). Our results suggest that although nitrapyrin could be
effective under summer conditions, these responses are likely to be greatest in low OM
soils. Increasing soil OM, for example through crop residue additions as was done here,
will have complex consequences on N cycling and our ability to manage N losses by the
use of nitrapyrin.
Bacterial amoA gene abundance notably declined due to initial wet-up of dry soil, but
was not affected by whether soil was subsequently held at optimal water content or
allowed to dry. Rapid increases in soil water potential, as occur when rain falls on dry
soil, place soil microorganisms under greater stress than they experience as soil dries
(Schimel et al., 2007). If microorganisms are unable to adjust to the increasing water
potential, they may release intracellular solutes, lyse and die (Halverson et al., 2000;
Kieft et al., 1987). Recent evidence from in situ microbial communities suggests that
soil microorganisms do not accumulate osmolytes as they dry (which might allow them
to remain active; Boot et al., 2013), but instead the best strategy for survival is drought
avoidance by dormancy until reactivation by a wetting event (Manzoni et al., 2014).
Ch. 5: Nitrapyrin at High Temperature
139
Although we expected that microbial communities in this soil would be adapted to and
able to cope with the climate (i.e. sporadic wetting events during the summer when soil
is dry), a proportion of the AOB population appears not to be able to adjust rapidly
enough to the increased water potential on soil rewetting, causing lysis and death. This
is in contrast to the heterotrophic N mineralisers and immobilisers, which showed
maximum activity during the first 24 h after wet-up. By day 14 however, bacterial
amoA gene abundance in all treatments had recovered to the similar levels as in pre-wet
soils. This follows a similar pattern to that observed in another semi-arid soil, where
bacterial amoA gene abundance 72 h after wetting was the same or less than in pre-wet
soil (Placella and Firestone, 2013).
Low recovery of 15NH4+ within two hours of application at 20 °C was attributed to rapid
bacterial uptake. Uptake was followed by slow release of 15NH4+ back into the soil
environment presumably once cells were saturated with N. This effect has been
previously observed by Jones et al. (2013) using high-resolution nano-scale secondary
ion mass spectrometry (NanoSIMS) stable isotope imaging: metabolically active
bacterial cells in the rhizosphere of wheat plants accumulated and became saturated
with 15NH4+ within 30 minutes of application of low levels of 15NH4
+ (3 mM). In the
present study we were not able to measure this bacterial 15NH4+ uptake due to the
relatively enormous size of the organic N pool (307–1048 µg N g-1) compared to the
amount of applied 15N (5 µg N g-1 at 60 atom%), and thus detected it as diminished 15N
recovery. Rapid bacterial uptake of applied 15NH4+ was not observed at 40 °C, which
we attribute to limitation of immobilisation at elevated temperatures: in a similar semi-
arid soil, Hoyle et al. (2006) noted that N immobilisation was restricted at temperatures
greater than 30 °C, likely due to C substrate limitation. Our results imply that 15N
isotopic pool dilution may not be a useful tool to measure short-term rates (i.e. over the
Ch. 5: Nitrapyrin at High Temperature
140
initial 24 hours) of N transformations in N-limited soils, as these measurements appear
to be confounded by rapid immediate bacterial uptake and release of 15NH4+
independent of soil OM mineralisation.
5.6. Conclusions
It is difficult to manage N losses during summer fallow when dry soils can experience
elevated temperatures and wetting events. The nitrification inhibitor nitrapyrin has the
potential to retain mineralised NH4+ that is released from these wetting events in this
semi-arid soil. However increasing soil OM through long-term crop residue additions
may make nitrapyrin less effective. Although ammonia oxidiser activity was diminished
by nitrapyrin, and ammonia oxidation was attributed to AOB, bacterial amoA gene
abundances were not affected by the inhibitor. Instead, AOB populations were most
affected by wet-up of dry soil, suggesting that these microbial communities are driven
mainly by changes in environmental conditions rather than management practices per
se. Further research needs to be conducted to evaluate whether nitrapyrin can be
effective under field conditions, and whether this is an economic solution to potential N
losses over summer fallow.
141
Chapter 6.
General Discussion
6.1. Introduction
The objective of this thesis was to gain a better understanding of how to manage
microbially-mediated nitrogen (N) cycling in order to prevent N loss from semi-arid
rainfed cropped soils. The objective was achieved in two ways: by investigating factors
contributing to variability in risk of N loss; and by investigating possible management
solutions to decrease the risk of N loss. This general discussion will bring together the
main findings from the three preceding research chapters, and will also make reference
to my collaborative research that is contained in Appendix A. The main findings of this
thesis will be critically assessed and put in context with what is already known about
semi-arid rainfed agricultural soils, and finally opportunities for future research will be
suggested.
Ch. 6: Discussion
142
6.2. Contributing Factors to Variation in Risk of Nitrogen Loss from
Semi-Arid Rainfed Agricultural Soils
6.2.1. Variation in rainfall and temperature
Seasonal variation in rainfall and temperature are of primary importance determining
patterns of risk of N loss from semi-arid rainfed agricultural soils. This is due to several
interacting factors: microbial production of inorganic and gaseous N in response to
rainfall and elevated temperatures, seasonality of N removal and carbon (C) inputs to
soil by annual crop plants, and the effect of timing and size of rainfall events on deep
drainage and potential nitrate (NO3-) leaching.
Production of inorganic N during summer fallow in response to rainfall and elevated
temperatures in this semi-arid soil is a key factor determining risk of N loss. Increasing
inorganic N pools appear to be partly a consequence of net microbial N mineralisation
at soil temperatures above 30 °C, which was associated with low microbial C use
efficiency (Chapter 3). This suggests that decomposing microorganisms are less
efficient at converting C from low molecular weight organic matter (LMWOM)
substrates into biomass, and respire more at elevated temperatures. Decreased microbial
C use efficiency also decreases demand for N, promoting N mineralisation when the N
content of LMWOM substrates is high enough to meet microbial requirements (Austin
et al., 2004). The mechanism for lowered microbial C use efficiency is likely linked to
the increased physiological costs of maintaining respiration at elevated temperatures
and inducing heat avoidance and survival mechanisms (Schimel et al., 2007). Increased
net N mineralisation and accumulation of inorganic N at elevated soil temperature has
also been observed in other semi-arid agricultural soils (Hoyle et al., 2006; Luxhøi et
al., 2008) and in annual grassland ecosystems (Jackson et al., 1988; Parker and Schimel,
2011). This accumulated inorganic N will be at risk of loss by NO3- leaching depending
Ch. 6: Discussion
143
on the timing and size of rainfall events, and particularly at the start of the winter
growing season when deep drainage below the crop rooting zone begins (Anderson et
al., 1998; Arregui and Quemada, 2006). Risk of N loss is also exacerbated when
seasonality of plant N uptake and available C inputs (almost exclusively occurring
during the winter growing season in this annual cropping system) does not match
seasonality of N supply from organic matter (OM) decomposition (taking place year-
round; Knops et al., 2002).
Nitrification of this mineralised N was also active during summer fallow, as shown by
low soil ammonium (NH4+) concentrations and the accumulation of NO3
- in response to
rainfall as the season progressed (Chapter 4). Increasing abundance of bacterial
ammonia oxidisers (AOB) during summer fallow was also linked to increasing soil
NO3- pools. Communities of N cycling microorganisms in this semi-arid soil are
therefore likely to be acclimated to drought and wetting events, which they generally
experience every year during summer. In fact, amoA transcripts have been observed in
semi-arid soils even when soil is dry (1–5% gravimetric water content), and AOB can
increase amoA transcription within one hour of soil wetting (Placella and Firestone,
2013). Potential nitrification rates in semi-arid soils can also be greater in dry seasons
than in wet seasons (Parker and Schimel, 2011; Sullivan et al., 2012). Adaptation of
microbial communities to drought and rewetting stress has been observed in other
environments (de Vries et al., 2012; Evans and Wallenstein, 2012; Peralta et al., 2013).
For example, potential nitrification rates in humid continental upland soils were not
affected by drought, while potential nitrification rates in adjacent non-acclimated
wetland soils decreased (Peralta et al., 2013). All of these lines of evidence suggest that
dry seasons in semi-arid soils are critical periods for understanding annual variation in
N cycling and risk of N loss.
Ch. 6: Discussion
144
6.2.2. Root exudate carbon inputs
Actively growing plant roots are highly important for decreasing risk of N loss, by
supplying available C to retain N in the microbial N loop and prevent production of
excess inorganic N. Both crop residue OM and root exudate inputs were expected to
increase C availability in soil, allowing heterotrophic microorganisms to compete more
effectively for NH4+, thus decreasing activity of nitrifying microorganisms and
decreasing the risk of N loss. The findings supported this hypothesis only in the case of
root exudate inputs (Chapter 3). Crop residue inputs did not change the risk of N loss, as
gross nitrification rates were enhanced along with N immobilisation rates (Fig. 3.5).
This occurred despite crop residue inputs resulting in significantly greater levels of light
fraction organic matter C (LFOM-C) and dissolved organic C (DOC), which have been
used as indicators of available C (Haynes, 2005; Janzen et al., 1992). In contrast, root
exudates increased heterotrophic microbial N immobilisation relative to nitrification, so
overall the risk of N loss decreased.
These findings fit with plant detritus decomposition theory. Current understanding of
decomposition is that litter or residue quality is less important for soil C and N
availability than soil characteristics such as microbial community composition
(Delgado-Baquerizo et al., 2015). The majority of N from plant litter (in this case crop
residues) becomes incorporated into soil OM during decomposition, which represents a
bottleneck between plant N and the soil N cycle. Release of N from soil OM is
subsequently regulated by microbial mineralisers, the majority of N being incorporated
into microbial biomass and returned to the soil OM pool upon death (Knops et al.,
2002). This is termed the microbial N loop, and is evidenced by much greater gross than
net N mineralisation rates, in this semi-arid soil at soil temperatures between 10 and 30
°C (Fig. 3.4). In fact, gross nitrification rates can also be much greater than net
Ch. 6: Discussion
145
nitrification rates, and in natural ecosystems are linked to high NH4+ and NO3
-
consumption rates, indicating tight internal soil N cycling (Stark and Hart, 1997;
Verchot et al., 2001).
The microbial N loop is regulated by recent inputs of microbially available C supplied
by plant rhizodeposits, such as root exudates and root turnover, which stimulate
microbial N immobilisation. This was clearly observed in the present study (Chapter 3),
where addition of synthetic root exudates resulted in gross N immobilisation rates
greater than nitrification rates, and an N:I ratio (gross nitrification to N immobilisation
ratio; an indicator of risk of N loss) less than one (Fig. 3.5). Stimulation of N
immobilisation by available C has also been observed in nutrient-deficient Arctic soils
with additions of glucose (Schmidt et al., 1997). In terms of the effect of available C on
actual N losses, one study in a Spanish semi-arid soil showed that available C in the
form of glucose decreased nitrous oxide (N2O) emissions by 23% and nitric oxide (NO)
emissions by 71% at 40% water-filled pore space (WFPS), when high rates of fertiliser
N were also added (200 kg N ha-1) but not low rates of N (50 kg N ha-1; Sánchez-Martín
et al., 2008). The authors hypothesised that the reductions were due to labile C
favouring complete denitrification over nitrifier denitrification, but equally the
reductions in gaseous N loss may have been due to increased microbial N
immobilisation (Sánchez-Martín et al., 2008). The authors did not consider that their
NH4+ and NO3
--N measurements indicated decreased net N mineralisation and
nitrification rates (and therefore increased immobilisation) in the presence of glucose
compared to without glucose for both rates of N fertiliser addition at 40% WFPS
(Sánchez-Martín et al., 2008). These findings suggest that risk of N loss in semi-arid
agricultural soils might be managed by increasing the time of influence of root growth
and root exudate C inputs, to enhance N retention in soil.
Ch. 6: Discussion
146
The effects of C inputs from plant roots will vary spatially over small scales
(centimetres to micrometres) and interact with N availability and hydrological
connectivity to influence risk of N loss. This study was conducted in the laboratory, so
root exudates could be applied homogenously to the samples, allowing the
quantification of gross N transformation rates from the soil as a whole. In the field
however, inputs of available C from root exudates will not be evenly distributed
throughout the bulk soil, and microsites will vary in both C and N availability. Carbon
flow from crop roots is highly complex and varies spatially and temporally along the
plant root. Rates of exudation are generally greater at the tips of roots than in mature
roots, though passive diffusion occurs along the entire length of the root (Hoffland et
al., 1989; McDougall and Rovira, 1970). The composition and quantity of rhizodeposits
also are influenced by a range of other factors such as plant species, developmental and
nutrient status, and environmental conditions (Jones et al., 2004a). Release of
rhizodeposits gives rise to zones of stimulated microbial activity that have different
characteristics to bulk soil, on the surface of roots (the rhizoplane), within roots (the
endorhizosphere) or outside roots (the ectorhizosphere; Lynch and Whipps, 1990).
Microscale variation in C availability will also interact with microscale variation in N
availability to produce sites where N is mineralised and sites where N is immobilised
(Schimel and Bennett, 2004). In addition, the laboratory incubation (Chapter 3) was
carried out at optimal water content, so microsites of differing C and N availabilities in
the samples would have been well connected. As soil water content varies in the field
with wetting and drying events, the hydrological connections between microsites will
also vary. Diffusion of substrates from sites of production to sites of consumption is
limited when microsites are not well connected, so those substrates can accumulate
(Parker and Schimel, 2011). The hydrological connections between spatially
Ch. 6: Discussion
147
heterogeneous microsites needs to be taken into account when inferring the effect of
varying management on accumulation of inorganic N and subsequent risk of N loss.
6.2.3. The importance of surface soil layers
The surface 10 cm of this semi-arid agricultural soil is where N transformation rates are
greatest, where most AOB are found, and where most N that is at risk of loss is
produced, particularly N2O and NO3-. Gross nitrification rates (actual and potential)
decrease with depth, and AOB amoA gene abundances that are correlated with
nitrification rates are also highest in the surface soil (Appendix A). Other researchers
have additionally shown that 70–88% of gross N mineralisation, 46–57% of NH4+
consumption and 55% of microbial biomass in the 50 cm soil profile occurs in the top
10 cm (Murphy et al., 1998a). The surface layer of soil in this water-limited
environment is where rainfall first increases soil water availability, where crop residue
and OM inputs are greatest, and where temperature fluctuations are most extreme.
Minimal or no-tillage are common agricultural practices in south-west Australian semi-
arid soils, so soils are generally highly stratified, without the deep mixing of tillage or
mouldboard ploughing (Roper et al., 2010). Subsoil layers are buffered by the overlying
soil from extremes in temperature, drying by evaporation and rewetting by rainfall.
Bacterial ammonia oxidisers dominate over archaeal ammonia oxidisers (AOA) in the
surface layer of this semi-arid soil, controlling nitrification and production of NO3- that
is at risk of loss. It is important to distinguish between nitrification carried out by AOB
or AOA because the differing physiologies and ecological functions of these ammonia
oxidisers likely influence how they respond to management practices, such as addition
of nitrification inhibitors, and their roles in production of environmentally detrimental
N2O, NO3- (Di et al., 2009; Prosser and Nicol, 2008). Both AOA and AOB were
Ch. 6: Discussion
148
expected to have greatest abundance in the surface soil compared to subsoil of this
semi-arid soil, because this is where most N mineralisation occurs and therefore where
most substrate for ammonia oxidisers would be found. This hypothesis was supported in
the case of AOB (Chapters 4 and 5, Appendix A), but not for AOA. Ammonia-
oxidising archaea were instead greater in the subsoil (10–90 cm) compared to the
surface layer (Appendix A). Bacterial ammonia oxidisers may dominate over AOA in
the surface layers due to the long-term effects of agricultural practices such as N
fertiliser application on these agricultural soils: in adjacent native bushland to the
present study site, AOA abundances in the surface soil were measured as approximately
an order of magnitude higher than in the agricultural soil. In some cases, AOB appear to
dominate in abundance or in activity over AOA when soil NH4+ levels are high, while
AOA prefer low nutrient conditions and can be inhibited by high NH4+ fertilisation (Di
et al., 2010; Di et al., 2009; Jia and Conrad, 2009; Pratscher et al., 2011; Shen et al.,
2011). Archaeal ammonia oxidisers may compete more effectively over AOB when soil
NH4+ levels are low due to their greater affinity for NH4
+ and their greater sensitivity to
inhibition by high NH4+ (Martens-Habbena et al., 2009; Prosser and Nicol, 2012). These
studies suggest that AOB dominate in this semi-arid agricultural soil as a consequence
of N fertiliser application and increased ammonia substrate availability, so it is more
important to understand AOB regulation of nitrification than that of AOA in order to
manage the risk of N loss in this environment.
Archaea do not appear to be important regulators of the risk of N loss through ammonia
oxidation, even in the subsoil where AOA were detected in greatest numbers. Total
archaeal populations that were detected in the surface layers predominantly appear not
to possess the ability to oxidise ammonia (Appendix A). Archaeal ammonia oxidisers
that were detected in the subsoil were negatively correlated to gross nitrification rates
Ch. 6: Discussion
149
(Appendix A). Therefore, in spite of possessing the amoA gene, these AOA appear to be
either not transcribing amoA, not producing the ammonia monooxygenase enzyme
(AMO) or not utilising ammonia oxidation for energy production and metabolism.
Instead these AOA may be using some form of heterotrophic or mixotrophic
metabolism. Other studies have provided evidence of heterotrophic and mixotrophic
growth by AOA, due to the presence of genes encoding transporters for organic C
compounds, and by enhanced growth rates when organic C compounds are added to
pure culture (Tourna et al., 2011; Walker et al., 2010). In addition, Thaumarchaeotes in
waste water treatment plants appear not to be restricted to chemolithoautotrophic
metabolism despite expressing the amoA gene (Mußmann et al., 2011). Mußmann et al.
(2011) suggested that these amoA-encoding Thaumarchaeota instead are heterotrophs,
gaining energy and C from an unknown organic compound. It is possible that instead of
carrying out chemolithoautotrophic ammonia oxidation, AOA detected in the subsoil
layers of the semi-arid soil in the present study are using heterotrophic or mixotrophic
metabolism, and therefore are not important producers of NO3- and do not need to be
taken into account when considering management of risk of N loss.
Although AOB were found to dominate over AOA in the surface of this semi-arid soil,
this may not be applicable to other semi-arid soils. Niche specialisation and
differentiation between AOA and AOB has not yet been adequately described, with the
possible exception of a consistent dominance of AOA at very low soil pH (pH <5.5;
Prosser and Nicol, 2012). In addition, communities of ammonia-oxidising
microorganisms vary between biogeographical regions, possibly due to differences in
current and historical environmental conditions and dispersal limitations (Fierer et al.,
2009; Pester et al., 2012). Western Australia has been geologically isolated and stable
for millions of years (McKenzie et al., 2004), so it is likely that unique microbial
Ch. 6: Discussion
150
communities have evolved here. The relative importance of AOA and AOB to
nitrification and risk of N loss varies between different soil types, environments and
regions (for example Adair and Schwartz, 2008; Di et al., 2009; Gubry-Rangin et al.,
2010; Jia and Conrad, 2009; Taylor et al., 2010), and the findings of AOB dominance in
this semi-arid agricultural soil should be applied to other semi-arid soils with caution.
6.3. Management of Semi-Arid Soils to Decrease Risk of Nitrogen Loss
Outside the Growing Season
The greatest risk of N loss in semi-arid rainfed agricultural soils with winter-dominant
rainfall is in response to inorganic N production during infrequent summer rainfall
events when soil is fallow, and during the first rains of the growing season before crop
establishment (see section 2.4.2 and 2.5 in Chapter 2). Management solutions therefore
are required for these periods of the year, to decrease the risk of N loss and improve the
synchrony of N supply to crops. This research evaluated two approaches to achieve
these objectives, through increasing soil OM by crop residue additions, or by
application of the nitrification inhibitor nitrapyrin.
6.3.1. Crop residue inputs and increased soil organic matter
Increased soil OM from additional crop residue inputs was not an effective management
tool to decrease risk of N loss and improve synchrony of N supply to crops. Greater soil
OM was hypothesised to increase C availability to heterotrophic N immobilising
microorganisms and thus limit autotrophic nitrifiers through competition for NH4+
substrate. This was expected because soil with OM inputs had measured increases in
LFOM-C and DOC, which are microbial substrates with rapid turnover rates and have
been used as indicators of soil available C (Haynes, 2005; Janzen et al., 1992). This
Ch. 6: Discussion
151
hypothesis was not supported by the findings, because increased soil OM stimulated
gross N mineralisation and nitrification as well as immobilisation, so the balance
between N retention and N loss pathways was unchanged (Chapter 3, Fig. 3.5). In fact,
it is likely that with increased total amounts of N cycling through soil, more N will be
available for loss processes such as N2O emissions and NO3- leaching. Nitrate
concentrations in soil with crop residue inputs were greater across all seasons than in
soil without these additional OM inputs, but particularly at the end of summer fallow
when there is greatest risk of loss by leaching (Fig. 4.3). In the short term, the high C:N
ratio of crop residues compared to soil OM tends to cause net N immobilisation and
decreased inorganic N concentrations (for example Geisseler et al., 2012; Janzen and
Kucey, 1988). Over the long term however, increased nutrient cycling and C and N
contents are similarly observed in other studies where crop residue inputs have been
used to increase soil OM (reviewed in Kumar and Goh, 2000). Manipulating total soil
OM pools in this semi-arid agricultural soil therefore is not an effective method to
manage the risk of N loss.
6.3.2. Nitrapyrin
Nitrapyrin has potential to decrease risk of N loss and improve synchrony of N supply
to crops by retaining mineralised N in soil as NH4+ during summer fallow. Nitrapyrin
typically performs better in cooler climates and becomes less effective as soil
temperature increases, due to increased volatilisation losses, microbial activity and more
rapid microbial degradation (Goring, 1962; Slangen and Kerkhoff, 1984; Wolt, 2004).
Nonetheless, in this semi-arid soil nitrapyrin was able to inhibit nitrification at 20 and
40 °C. Other researchers have found nitrapyrin to be effective at inhibiting nitrification
at temperatures between 25 and 35 °C (Ali et al., 2008; Bundy and Bremner, 1973;
Ch. 6: Discussion
152
Chen et al., 2010), though Ali et al. (2008) questioned the economic viability of
applying nitrapyrin at rates high enough to have beneficial effects on crop yields.
Nitrapyrin may have been effective at elevated temperatures in this semi-arid soil
because of the low soil OM content (0.8–1.3% total C). Soil OM is reported to decrease
the effectiveness of nitrapyrin by providing substrates for and stimulating the activity of
microorganisms that degrade nitrapyrin, and by absorbing nitrapyrin (Goring, 1962;
Lewis and Stefanson, 1975). Increased OM content in this semi-arid soil due to crop
residue inputs also decreased the observed effectiveness of nitrapyrin (Chapter 5).
However, some of the previous studies that reported decreased effectiveness at elevated
temperatures were carried out on soils with even lower OM contents to the present
study (0.8% OM, Goring, 1962; 1.7% OM, Tu, 1973). Other interacting soil and
environmental factors therefore may be involved, and further work is needed to better
understand these factors and whether nitrapyrin would be effective in other soil types in
the grainbelt of south-western Australia.
The findings of the present study showed for the first time that the ability of nitrapyrin
to inhibit nitrification at elevated temperatures was combined with the ability to control
nitrification of NH4+ released from OM mineralisation. Previous research has been
focussed on using nitrapyrin to prevent loss of applied NH4+-based fertiliser during the
growing season, and the effectiveness of nitrapyrin at retaining inorganic N is more
noticeable when the inhibitor is applied with a large N source (for example Tu, 1973).
Most laboratory based studies have applied nitrapyrin with N sources [for example
Chen et al. (2010) applied nitrapyrin with 715 µg urea-N g-1, similar to fertiliser
applications of 80 kg N ha-1]. In semi-arid rainfed cropping systems with winter-
dominant rainfall, a significant proportion of N at risk of loss is a consequence of OM
Ch. 6: Discussion
153
mineralisation during summer fallow, instead of N fertiliser applied during the growing
season. The present study shows that nitrapyrin may also be able to control
transformations of this mineralised N during summer.
6.4. Future Research
6.4.1. Further unravelling the interactions between ammonia oxidisers and N loss
This thesis has highlighted several key areas where further research is needed.
Development of clone libraries and design of primers specifically for AOA present in
south-west Australian soils will make us more confident that lack of detection is a real
effect and that we are not missing novel AOA species. In Chapters 4 and 5, AOA were
not detected in the surface soils of the sandy agricultural site, and in collaborative
research (Appendix A) they were detected in very low abundances in the 0–10 cm layer
(means ranging from 0–1.8 x 103 gene copies g-1 dry soil). These low abundances and
lack of detection could be because either the primers did not detect AOA that were
present, or AOA were simply not there. From the best evidence available (detection of
AOA with the same primers in subsoil and an adjacent native bushland soil), it was
concluded that AOA were not present, so were unimportant for nitrification (Chapter 4,
Appendix A). In order to be sure of this however, primers need to be specifically
designed for this region. The primers used here, amoA-1F and amoA-1R have been
extensively used to measure archaeal amoA gene abundance in acidic agricultural soils
and in semi-arid environments elsewhere (Adair and Schwartz, 2008; Delgado-
Baquerizo et al., 2013; O’Sullivan et al., 2013; Sher et al., 2013; Zhang et al., 2012), but
were designed from archaeal amoA gene sequences from the Sargasso Sea and soil from
Germany (Francis et al., 2005). Diverse biogeographical regions have communities of
ammonia-oxidising microorganisms that are distinctly different (Fierer et al., 2009;
Ch. 6: Discussion
154
Pester et al., 2012), and Western Australia is a unique environment that has been
geographically isolated, deeply weathered and stable for millions of years (McKenzie et
al., 2004). Therefore the possibility that AOA in this region are genetically divergent
from those in other parts of the world cannot be dismissed. Characterisation of the
genetic diversity of native AOA populations and design of appropriate amoA primers
will facilitate a better understanding of ammonia oxidiser regulation of nitrification and
N loss in this region.
The interactions between ammonia oxidisers and N loss in the semi-arid agricultural
soils of south-western Australia may be further unravelled by applying other methods
and technologies besides detection of amoA gene abundances. These methods include
detecting ribonucleic acid (RNA) transcripts, metagenomics and metatranscriptomics,
and the use of radioactive tracers, stable isotope probes and fluorescent markers.
Detection of amoA messenger RNA (mRNA) transcripts allows tracking of genes that
are being actively expressed in response to short-term treatment effects (for example
Gubry-Rangin et al., 2010; Placella and Firestone, 2013). This is in contrast to detection
of amoA gene abundance (i.e. population growth and decline), changes of which take
longer to occur. In addition, presence of amoA genes in the microbial population is also
not enough to determine whether those ammonia oxidisers are in fact active regulators
of nitrification: the genes may not be expressed, or the gene transcripts or enzymes
might be inactivated (Di et al., 2009; Mußmann et al., 2011).
Metagenomics characterises all genes present in a sample, providing information about
the potential functions of the microbial community, while metatranscriptomics
characterise all transcripts of mRNA in order to describe what the microbial community
is actually doing (Carvalhais et al., 2012; Prosser, 2015). These techniques are best used
Ch. 6: Discussion
155
for investigating spatial and temporal dynamics of the whole microbial community in
response to environmental changes (Prosser, 2015). In this soil the use of metagenomics
and metatranscriptomics would give a clearer idea of the functional groups or
phylotypes that are driving N loss processes of N2O and NO3- production, in response to
triggers such as wetting and drying events due to summer and autumn rainfall that may
resuscitate different N cycling microorganisms from dormancy at different speeds.
These techniques may also identify processes that have not previously been associated
with N loss processes in this environment, such as nitrate ammonification or
heterotrophic nitrification.
Two methods that use radioactive tracers are fluorescence in situ hybridisation (FISH)
combined with microautoradiography (Lee et al., 1999) and the isotope array
(Adamczyk et al., 2003). Combining FISH with microautoradiography allows
identification of fluorescent and radioactive cells that are metabolising a radiolabelled
substrate (Lee et al., 1999). An example of how FISH-microautoradiography has been
used is to show that AOB in a waste water treatment plant are active autotrophic
ammonia oxidisers, but archaea able to encode AMO did not have autotrophic
metabolism, despite having the genes to carry out ammonia oxidation (Mußmann et al.,
2011). In order to target mRNA that is expressed in low amounts, catalysed reporter
deposition can also be combined with FISH (CARD-FISH) to increase the signal
intensities of fluorescence labels (Pernthaler and Amann, 2004; Speel et al., 1999).
Pratscher et al. (2011) used CARD-FISH to visually investigate expression of AOA
amoA mRNA simultaneously with archaeal 16S rRNA, to show a high abundance of
AOA relative to the total archaeal population in an agricultural soil. The isotope array
similarly tracks the incorporation of a radiolabelled substrate into rRNA, and allows
Ch. 6: Discussion
156
high-throughput screening and the ability to apply many probes in parallel (Adamczyk
et al., 2003).
Stable isotopes may be used for more direct measurement of ammonia oxidisers by
nano-scale stable isotope mass spectrometry (NanoSIMS) and stable isotope probing
(SIP). NanoSIMS allows high resolution (submicron length scales) imaging of stable
isotopic ratios and elemental mapping, so isotopic tracers can be used to follow
individual cells of microorganisms that have assimilated stable isotopic tracers (Clode et
al., 2009; Lechene et al., 2007; Wagner, 2009). Stable isotope probing allows the
identification of cellular components, such as DNA or RNA, of microorganisms which
have assimilated a substrate labelled with a stable isotope such as 13C, and are
subsequently using the labelled substrate for growth or transcription (Dumont and
Murrell, 2005). Stable isotope probing can be used to demonstrate ammonia oxidation,
assuming it is coupled to autotrophic carbon dioxide (CO2) fixation, and has been used
to show the importance of AOA over AOB for ammonia oxidation in agricultural soils
(Pratscher et al., 2011; Zhang et al., 2012).
Applying these technologies to south-west Australian semi-arid soils, in combination
with specific AOA primers for this region, may answer outstanding questions about
factors regulating ammonia-oxidising populations and activity. These questions include:
whether agricultural practices have changed the relative dominance of AOA and AOB;
what the response of AOB activity is to changing management practices; and how AOB
populations and activity can be managed to decrease growth and production of NO3-
during summer fallow.
Ch. 6: Discussion
157
The possibility of heterotrophic nitrification needs further investigation as an important
pathway of NO3- production and risk of N loss in this semi-arid agricultural soil. The
findings in Chapter 4 raised this possibility, either through heterotrophic or mixotrophic
growth of AOB, or heterotrophic nitrification by other microorganisms. This was due to
a lack of correlation between AOB amoA gene abundance and soil NH4+ content, but a
correlation between AOB and DOC (Table 4.2). Modelling of N cycling in a similar
Western Australian semi-arid soil suggested that approximately 50% of nitrification
could be explained by heterotrophic nitrification, in that case production of NO3-
directly from organic N (Cookson et al., 2006b). There is also evidence from cultures
that AOB are able to assimilate LMWOM compounds and have genes coding for
organotrophic metabolisms (Sayavedra-Soto and Arp, 2011; Schmidt, 2009; Walker et
al., 2010).
Specific investigations need to be carried out in this semi-arid soil to quantify the
relative importance of heterotrophic nitrification compared to autotrophic nitrification.
Quantifying heterotrophic nitrification may be difficult by enumeration using specific
metabolites or molecular methods, due to the diverse metabolic activities that can be
coupled to nitrification and the polyphyletic nature of heterotrophic bacteria (De Boer
and Kowalchuk, 2001). Molecular targets developed for functional genes encoding
enzymes of specific groups of heterotrophic nitrifiers also may not fully reveal the role
of those detected nitrifiers in soil N transformations, as those enzymes can catalyse a
variety of other reactions (De Boer and Kowalchuk, 2001). However, a combination of
methods may allow investigation of heterotrophic nitrification compared to autotrophic
nitrification, including selective inhibition of autotrophic nitrifiers (for example by
acetylene; Persson and Wirén, 1995), use of 15N tracers or isotopic pool dilution (for
example Islam et al., 2007; Pedersen et al., 1999), removal of CO2 from soil atmosphere
Ch. 6: Discussion
158
(since autotrophs are reliant on CO2 for C fixation while heterotrophs incorporate C
from organic compounds) (for example De Boer et al., 1991) and measurement of
fixation of labelled CO2 into cell biomass (for example Kreitinger et al., 1985).
Management techniques that are targeted at decreasing autotrophic nitrification, or
stimulating heterotrophic activity at the expense of autotrophs, may not be effective at
decreasing the risk of N loss if heterotrophic nitrification accounts for a significant
proportion of total nitrification.
6.4.2. Field application of nitrapyrin
Nitrapyrin has potential to decrease risk of N loss during summer fallow in semi-arid
soils by minimising conversion of mineralised NH4+ to NO3
-, but needs to be tested
under field conditions. Several issues are still unclear, as follows.
How to target nitrapyrin application to prevent nitrification in response to
sporadic summer rainfall events (the time when significant production of
inorganic N can occur).
What rate, method and timing of nitrapyrin application should be used.
If nitrapyrin is equally effective in other soil types besides the sandy soil used in
the present study, particularly with differing OM contents.
If manipulating inorganic N forms (i.e. retaining NH4+ and preventing NO3
-
production) influences crop growth and yields in the following growing season.
If nitrapyrin is economically viable for land managers to use, considering the
extra cost and labour required against any potential yield and environmental
benefits.
Ch. 6: Discussion
159
Effectiveness of nitrapyrin in the field will depend on a variety of interacting factors.
The present study was conducted under laboratory conditions, which allow homogenous
application of nitrapyrin to soil samples, and losses by volatilisation are easy to control
in closed incubation vessels. In the field, the rate, method, and timing of application all
affect how persistent and effective nitrapyrin is at inhibiting nitrification, by influencing
loss rates of nitrapyrin (by volatilisation and leaching) and through the interaction
between nitrapyrin and environmental and soil variables such as nitrifying microbial
populations, substrates for nitrification, and soil OM content (Keeney, 1980). Under
certain conditions, for example with alkaline soils and fertiliser broadcast onto the soil
surface, nitrification inhibitors may in fact increase N losses by enhancing ammonia
volatilisation from NH4+-based fertilisers (Arregui and Quemada, 2006).
The costs and effort of nitrapyrin application for land managers also need to be
balanced with the potential benefits for farm profitability (through increased crop yields
or decreased N fertiliser application), and environmental benefits (through decreased
N2O emissions and NO3- leaching). Nitrification inhibitors, particularly in the Midwest
Cornbelt of the USA are often used as an insurance policy against N loss and thus
making yield responses to applied fertiliser more probable, although annual variability
in crop, environment and management factors creates uncertainty in the realisation of
these economic benefits from year to year (Nelson and Huber, 1980; Wolt, 2004). In the
rainfed annual cropping systems of semi-arid south-western Australia, annual yields are
particularly reliant on the timing and amount of rainfall, and N fertiliser additions are
generally low and targeted to expected growing season rainfall. In this region, economic
benefits of applying nitrapyrin may therefore be difficult to quantify at the farm scale,
although environmental benefits of decreased N loss to the environment may be seen
over broader scales of time and space.
Ch. 6: Discussion
160
6.4.3. Other methods to manage risk of nitrogen loss
Other effective approaches need to be found to manage the risk of N loss and
asynchrony of N supply to crops. Due to the dominating influence on N cycling of
seasonal changes in soil water availability and temperature, the nature of annual rainfed
agriculture, and since most inorganic N at risk of loss is produced outside the cropping
period in these regions, finding options for managing risk of N loss will likely prove
difficult. Methods that may have potential to decrease risk of N loss include
management of OM mineralisation by understanding and manipulating the
mineralisation gene cascades, and increasing the duration and extent of the active
rhizosphere to provide available C to microbial N immobilisers and recapture any
mineralised N.
Managing OM mineralisation during summer fallow may be possible by disconnecting
the flow from breakdown of high molecular weight OM to NH4+ production. This
mineralisation cascade can be monitored by a series of genes that encode fungal and
bacterial enzymes for OM and cellulose decomposition and soil organic N release (Bach
et al., 2001; Edwards et al., 2008; Kellner et al., 2007). Evidence suggests that sandy
soils cannot stabilise extracellular proteolytic enzymes, so breakdown of proteins is
reliant on continued transcription of the genes encoding these enzymes (Fuka et al.,
2008). A significant proportion of semi-arid south-western Australia has coarse-textured
surface soils (McArthur, 2004; Schoknecht, 2002), so if production of extracellular
proteolytic enzymes could be inhibited, then OM mineralisation in these soils might be
controlled. Chemicals that have been found to inhibit protease and peptidase activities,
and may have potential for OM mineralisation control include flavonoids, biflavones in
root exudates, plant hormones and tannins (Vranova et al., 2013). Besides inhibition of
these enzymes, investigation of the influence of agricultural management and soil
Ch. 6: Discussion
161
factors (such as timing and method of tillage) on N decomposition and mineralisation
functional gene abundances may highlight ways to manage mineralisation, especially
during summer fallow.
The importance of an active rhizosphere to supply easily available C to microbial N
immobilisers, as emphasised in the present study (Chapter 3), suggests that increasing
the extent and duration of plant root growth may decrease the risk of N loss. Annual
farming systems in rainfed, winter rainfall dominant semi-arid regions have limited
potential for increasing root growth, due to the dependence of plant growth on natural
patterns of water availability. Selection for crop varieties with traits such as early
growth vigour and increased root branching may increase rhizodeposition in the early
growing season, as will management of soil constraints that restrict root growth, such as
compaction and subsoil acidity (Dunbabin et al., 2003; Hoad et al., 2001; Lynch, 1995).
The asynchrony of N supply and crop N demand, exacerbated by asynchrony of
available C supply from plant roots, might also be mitigated by planting summer crops
or by integration of perennial species into the annual cropping system. Short duration
drought tolerant summer crops such as millet (a C4 grass) and cowpea (a tropical
legume) are currently being trialled by the Western Australian No-Tillage Farmers
Association (WANTFA, 2014). These are sown late in winter and may be used as a
cover crop or harvested if there has been enough summer rainfall. Besides decreasing N
losses, hypothesised benefits of these summer crops include decreasing summer weeds
(and the cost of spraying), and improving non-wetting soils by increasing water
infiltration pathways through root growth. There are concerns though about whether
these summer crops might use water and nutrients that normally accumulate over
summer, to the detriment of the following winter crop (WANTFA, 2014).
Ch. 6: Discussion
162
There are several ways that perennials might be integrated into the annual cropping
system. These include alley cropping, where annual crops are planted between rows of
perennial shrubs or trees; by intercropping or companion cropping, where cereals are
oversown into perennial pastures such as lucerne (alfalfa); or by perennial cropping, for
example utilising nut or seed producing trees (Abdel Magid et al., 1991; Crews and
Peoples, 2004; Crews and Peoples, 2005). Development of perennial grain crops has
also been suggested, but will require long-term investment in breeding programmes
before these are feasible (Cox et al., 2002). The balance between perennial and annual
crops however needs to be carefully managed to avoid competition for water and
nutrients between annuals and perennials which can lead to decreased yields, especially
in dry years (Angus et al., 2000).
6.5. Conclusions
This thesis makes several contributions to the current understanding of N cycling and
loss in semi-arid rainfed agricultural soils, particularly those with winter-dominant
rainfall. Variation in the risk of N loss from these soils is predominantly related to
seasonal variation in rainfall and temperature, and supply of microbially available C
inputs from root exudates. Ammonia-oxidising bacteria regulate nitrification in the
surface of the semi-arid soils examined in this study, and production of NO3- during
summer fallow is linked to increases in AOB abundance, likely in response to rainfall
events. Although AOA were detected in the subsoil, they were negatively correlated to
gross nitrification rates, suggesting that these microorganisms are not dependent on
autotrophic ammonia oxidation, and are not important regulators of risk of N loss in this
environment.
Ch. 6: Discussion
163
Management of the risk of N loss is not likely to be effective by building soil OM
content through crop residue inputs, as increased C and N substrates supplied by
residues tended to stimulate N transformation rates overall. However, the nitrification
inhibitor, nitrapyrin, has potential to retain mineralised N in soil at elevated soil
temperatures during summer fallow, although this needs to be evaluated under field
conditions along with other methods of controlling the risk of N loss.
This thesis set out to gain a better understanding of microbially-mediated N cycling, in
order to manage risk of N loss from semi-arid rainfed agricultural soils (specific
questions, hypotheses and their answers are set out in Table 6.1). Taken together, the
findings of this thesis suggest that annual cropping systems in semi-arid regions restrict
options for management of N loss, particularly during summer fallow. This is due to the
prevailing influence of variation in rainfall and temperature on risk of N loss, and
production of inorganic N outside the cropping period. Management to decrease risk of
N loss therefore might need to involve changes in the annual cropping system, such as
including more perennials or crops during summer to decrease accumulation of
inorganic N at this time.
Tabl
e 6.
1. S
peci
fic th
esis
ques
tions
as s
et o
ut in
Cha
pter
1, t
he c
hapt
er in
whi
ch e
ach
ques
tion
was
ans
wer
ed, r
elat
ed h
ypot
hese
s and
ans
wer
s.
The
sis Q
uest
ion
Cha
pter
H
ypot
hese
s A
nsw
er to
Que
stio
n
Wha
t env
ironm
enta
l and
bio
chem
ical
fact
ors c
ontri
bute
to te
mpo
ral v
aria
tion
in
risk
of N
loss
?
Cha
pter
s 3
and
4
Wat
er a
vaila
bilit
y (r
ainf
all a
nd so
il w
ater
cont
ent),
soil
tem
pera
ture
, C
avai
labi
lity
(tota
l soi
l C a
nd ro
ot e
xuda
te C
).
Rain
fall,
soil
tem
pera
ture
, roo
t exu
date
C.
How
do
tota
l soi
l C a
nd ro
ot e
xuda
te C
affe
ct N
cyc
ling
and
risk
of lo
ss?
Cha
pter
3
Incr
easin
g to
tal s
oil C
and
root
exu
date
C
will
dec
reas
e ris
k of
N lo
ss b
y in
crea
sing
N im
mob
ilisa
tion.
Tota
l soi
l C in
crea
ses N
cyc
ling
over
all b
ut d
oes n
ot c
hang
e th
e ris
k of
N
loss
. Roo
t exu
date
C st
imul
ates
N im
mob
ilisa
tion
over
nitr
ifica
tion
so
decr
ease
s ris
k of
N lo
ss.
How
do
amm
onia
-oxi
disin
g po
pula
tions
vary
with
dep
th, s
easo
n an
d ag
ricul
tura
l
man
agem
ent?
Cha
pter
s 4
and
5,
App
endi
x A
AO
A a
nd A
OB
will
dec
reas
e w
ith d
epth
as N
subs
trate
s dim
inish
.
Bot
h A
OA
and
AO
B w
ill b
e gr
eate
r
durin
g th
e w
inte
r gro
win
g se
ason
than
durin
g su
mm
er fa
llow
.
AO
A a
nd A
OB
will
be
enha
nced
by
crop
resi
due
inpu
ts a
nd n
o til
lage
, but
will
be
decr
ease
d by
tilla
ge a
nd st
ubbl
e bu
rnin
g.
AO
A a
re lo
w to
non
-exi
sten
t in
surf
ace
soils
(0–1
0 cm
) but
incr
ease
with
dept
h.
AO
B ar
e m
ore
abun
dant
than
AO
A in
surf
ace
soils
, and
dec
reas
e w
ith
dept
h.
AO
B in
crea
se in
abu
ndan
ce in
surf
ace
soils
ove
r sum
mer
fallo
w, a
nd
decr
ease
ove
r the
win
ter g
row
ing
seas
on.
AO
B ab
unda
nce
is g
reat
er in
tille
d so
il w
ith a
dditi
onal
cro
p re
sidu
e
inpu
ts th
an in
soil
with
no
tilla
ge, b
urnt
stub
ble
or ti
llage
with
out c
rop
resi
due
inpu
ts.
Tabl
e 6.
1. c
ontin
ued
on n
ext p
age.
Tabl
e 6.
1. S
peci
fic th
esis
ques
tions
as s
et o
ut in
Cha
pter
1, t
he c
hapt
er in
whi
ch e
ach
ques
tion
was
ans
wer
ed, r
elat
ed h
ypot
hese
s and
ans
wer
s
(con
tinue
d).
The
sis Q
uest
ion
Cha
pter
H
ypot
hese
s A
nsw
er to
Que
stio
n
How
are
am
mon
ia-o
xidi
sing
popu
latio
ns
rela
ted
to o
ther
soil
envi
ronm
enta
l and
bioc
hem
ical
fact
ors?
Cha
pter
4,
App
endi
x A
AO
A a
nd A
OB
abun
danc
e w
ill b
e
posi
tivel
y re
late
d to
rain
fall,
soil
wat
er
cont
ent,
MBC
and
NO
3- con
cent
ratio
ns;
nega
tivel
y re
late
d to
soil
tem
pera
ture
,
DO
C a
nd to
tal s
oil C
;
but n
ot re
late
d to
NH
4+ con
cent
ratio
ns.
AO
B ab
unda
nce
in su
rfac
e so
il w
as p
ositi
vely
rela
ted
to so
il N
O3-
conc
entra
tions
, mic
robi
al b
iom
ass C
and
DO
C.
AO
B ab
unda
nce
in su
rfac
e so
il w
as n
ot re
late
d to
soil
NH
4+
conc
entra
tions
, pot
entia
lly m
iner
alis
able
N, w
ater
con
tent
at t
ime
of
colle
ctio
n, so
il te
mpe
ratu
re o
r rai
nfal
l ove
r the
pre
viou
s 30
days
bef
ore
colle
ctio
n.
AO
B ab
unda
nce
with
dep
th w
as p
ositi
vely
rela
ted
to to
tal s
oil C
.
AO
A a
bund
ance
with
dep
th w
as n
egat
ivel
y re
late
d to
tota
l soi
l C.
Doe
s inc
reas
ing
soil
tota
l C th
roug
h
addi
tiona
l cro
p re
sidu
e in
puts
decr
ease
the
risk
of N
loss
?
Cha
pter
3
Yes
. N
o.
Doe
s the
nitr
ifica
tion
inhi
bito
r nitr
apyr
in
decr
ease
risk
of l
oss o
f NH
4+ pro
duce
d by
OM
min
eral
isat
ion
unde
r tem
pera
ture
and
wat
er a
vaila
bilit
y co
nditi
ons t
hat m
ay o
ccur
durin
g su
mm
er?
Cha
pter
5
Yes
. Y
es.
Ch. 6: Discussion
166
167
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201
Appendix A.
Ammonia-oxidising bacteria not archaea dominate
nitrification activity in semi-arid agricultural soil
(With Supplementary Information)
App. A: Ammonia Oxidisers with Depth
202
Ammonia-oxidising bacteria not archaea dominate nitrification
activity in semi-arid agricultural soil
Natasha C. Banning, Linda D. Maccarone, Louise M. Fisk and Daniel V. Murphy*
Soil Biology and Molecular Ecology Group, School of Earth and Environment, Institute
of Agriculture, The University of Western Australia, Crawley, WA 6009, Australia.
* Corresponding author: [email protected]
Ammonia-oxidising archaea (AOA) and bacteria (AOB) are responsible for the rate
limiting step in nitrification; a key nitrogen (N) loss pathway in agricultural systems.
Dominance of AOA relative to AOB in the amoA soil gene pool has been reported in
many ecosystems globally, although their relative contributions to nitrification act ivity
are less clear. Here we examined the distribution of AOA and AOB with depth in semi-
arid agricultural soils in which soil organic matter content or pH had been altered, and
related their distribution to gross nitrification rates. Soil depth had a significant effect on
gene abundances, irrespective of management history. Contrary to reports of AOA
dominance in soils elsewhere, AOA gene copy numbers were four-fold lower than AOB
in the surface (0–10 cm). AOA gene abundance increased with depth while AOB
decreased, and sub-soil abundances were approximately equal (10–90 cm). The depth
profile of total archaea did not mirror that of AOA, indicating the likely presence of
archaea without nitrification capacity in the surface. Gross nitrification rates declined
significantly with depth and were positively correlated to AOB but negatively correlated
to AOA gene abundances. We conclude that AOB are the dominant population
regulating nitrification in these semi-arid soils.
App. A: Ammonia Oxidisers with Depth
203
Introduction
Nitrification, the microbially-mediated process which converts ammonia to nitrate
(through nitrite), is the major pathway by which nitrogen (N) can be lost from terrestrial
ecosystems. The autotrophic ammonia-oxidising bacteria (AOB), which produce the
key functional enzyme ammonia monooxygenase (AMO), have historically been
thought solely responsible for most ammonia oxidation, the rate limiting step in
nitrification, in terrestrial and aquatic ecosystems. This changed following the discovery
of intact amoA genes in mesophilic Crenarchaeota, members of the domain Archaea1.
Ammonia-oxidising archaea (AOA) have since been shown to numerically dominate
AOB in several European agricultural and pristine soils2 and subsequently elsewhere3,4.
More recent phylogenetic analyses have placed the AOA in the new phylum
Thaumarchaeota5.
In soils globally, the availability of inorganic nitrogen (ammonium and nitrate)
is important to plant nutrition and can regulate net primary productivity. In agricultural
soils, nitrogen loss (facilitated by nitrification) can be substantial, decreasing the
efficiency of nitrogen fertilizer use at huge economic cost6. Furthermore, nitrogen loss
through nitrate leaching contributes to groundwater pollution and the conversion of
nitrate to nitrous oxide (N2O) via denitrification pathways contributes to soil greenhouse
gas emissions7. One major question yet to be answered is to what extent AOA are
important in the nitrification process.
The presence of an amoA gene, transcript or protein is not sufficient to infer in
situ ammonia oxidization activity5. Consequently, there is considerable uncertainty
regarding the relative contributions of AOB and AOA to soil nitrification. Recently,
there has been evidence that AOA functionally dominate in acidic soils (with pH <
5.5)8. Elsewhere, AOB have been shown to dominate nitrification activity, even where
they were numerically less dominant than AOA9-11.
App. A: Ammonia Oxidisers with Depth
204
The relative importance of AOA vs. AOB to nitrification in semi-arid
agricultural soils also remains unclear. Semi-arid and arid lands constitute one-third of
the global land area and are widely used for agricultural production7. In the semi-arid
south western Australian grain-belt AOA have been found to be either similar to or less
abundant than AOB, in surface soil horizons12,13. The region typically has acidic sandy
soils with low organic matter content, where inorganic nitrogen fertilizers are required
for crop production. As two of the main drivers thought to provide a competitive niche
for AOA over AOB are a low soil pH14,15 and low substrate (i.e. ammonia)
availability16, the low abundance of AOA in earlier studies was unexpected17. However,
it has also been hypothesized that nitrogen supply through inorganic fertilizer
application, as opposed to an organic nitrogen supply pathway, may favour AOB
activity in agricultural soils5,18.
The impact of nitrogen fertilizer application as well as other agricultural
practices (e.g. liming, organic matter amendment, tillage) is predominantly in the soil
surface horizon and it has not been investigated whether the higher relative abundance
of AOB persists below the surface soil layer or if the surface dominance of AOB is
management induced. Soils exhibit strong environmental gradients with depth and little
is known more widely about the distribution of AOA and AOB abundance and function
down the soil profile. In many terrestrial ecosystems, microbial biomass and activity
declines with increasing depth19,20. However, studies have found AOA abundance either
stays relatively constant with soil depth or even increases with soil depth (this was
observed in an analysis of total archaeal abundance in which most of the population was
identified as Thaumarchaeota)20, while AOB abundance generally declines2,10.
As such, the aims of this study were to i) quantify the distribution of AOA and
AOB in the profile of semi-arid soils, ii) examine the relationship between gross
App. A: Ammonia Oxidisers with Depth
205
nitrification rates and amoA gene abundance of AOA and AOB, and iii) determine the
influence of soil pH and soil organic matter on AOA and AOB populations.
Results and Discussion
Irrespective of agricultural management, there were distinct depth profiles of both AOA
and AOB populations. AOB populations were significantly higher (P<0.001) in the
surface layer (0–10 cm) compared to the sub-soil (10–90cm; Fig. 1a). This was
consistent with the depth distribution of total bacterial population (Fig. 1b) and was
expected given depth gradients in soil organic matter, nutrients and aeration. In contrast
the AOA population was low in the surface layer but of similar magnitude to AOB
below 10 cm (Fig. 1a). The low AOA population in the surface was not mirrored by the
total archaeal population which varied little with depth (Fig. 1b). This suggests that in
the surface soil horizon at all sites there is either (i) a population of AOA that is not
detected with the primers used in this study or (ii) a large population of non-ammonia-
oxidising archaea, such as the Euryarchaeota (which includes methanogens) or group
1.1c Thaumarchaea which have been found in many acidic soils but have no known link
to amoA phylogeny8,21.
App. A: Ammonia Oxidisers with Depth
206
Fig. 1. Abundance of bacterial and archaeal amoA genes (a) and bacterial and archaeal
16S rRNA genes (b) in Western Australian semi-arid agricultural soils. Data points
represent means of three soil cores (per soil layer) collected from trial sites where soil
pH (-lime versus +lime) or soil organic matter (-OM versus +OM) had been historically
altered. Error bars represent ± 1SE. The mean of all treatments combined at each depth
are shown by the dashed line (archaea) or solid line (bacteria). Note: gene copy numbers
are plotted on a log10 scale.
The primers used in this study, developed by Francis et al.22 for use in the
marine environment, have been widely used for qPCR determination of AOA
abundance in acidic agricultural soils12,13,15,23 and elsewhere24,25. The primers amplify a
near full-length amoA gene product (635 bp) and thus in silico primer analysis is limited
by the availability of full-length amoA sequences. Nonetheless, a limited in silico
analysis of all available archaeal amoA sequences (n = 15; as published previously26)
covering the primer target regions (with the exception of the first three bases of the
0
10
20
30
40
50
60
70
80
90
1E+2 1E+4 1E+6 1E+8 1E+10
De
pth
mid
-po
int (
cm)
amoA gene copies g dry soil -1
AOA
AOB
0
10
20
30
40
50
60
70
80
90
1E+2 1E+4 1E+6 1E+8 1E+10
16S rRNA gene copies g dry soil -1
Archaea
Bacteria
102 104 106 108 1010 102 104 106 108 1010
(a) (b)
App. A: Ammonia Oxidisers with Depth
207
forward primer which was only covered by the soil fosmid clone 54d91), revealed
between 0 and 2 mismatches with the forward primer and between 0 and 3 mismatches
with the reverse primer. However, the majority of the mismatches were with AOA
associated with, or isolated from, non-soil environments (marine, estuarine, hot spring
or the sponge symbiont Cenarchaeum symbiosum). There were no mismatches with
either primer for the sandy soil fosmid clone 54d91 or the two Nitrososphaera
sequences (belonging to “group 1.1b” which have been shown to be the dominant AOA
in many soils21,26. Furthermore, none of the mismatches that were present were in the
five bases at the 3’ end of the forward primer or the 5’ end of the reverse primer, the
regions where target-primer matches are the most important for successful PCR
amplification27. Thus, there was no evidence of AOA amplification being restricted by
primer coverage limitations. However, geographic location on the continental scale has
been purported to effect soil AOA population structure26 and it cannot be ruled out that
these deeply weathered, ancient and geographically isolated Western Australian soils28
harbor novel AOA not detected by the current primers.
Nonetheless, we hypothesize that annual applications of inorganic nitrogen (20–
100 kg N ha-1) have favoured AOB over AOA. Previous studies have indicated that
AOA may have a competitive advantage at low ammonia concentrations due to their
higher substrate affinity29 or possibly due to higher sensitivity to growth inhibition at
high ammonia concentrations16. Activity of soil AOA is generally detected below 15 µg
NH4+-N per g soil5, although this is not always the case30. The measured ammonium
concentrations in this study were all low (< 1 µg NH4+-N per g soil) at the time of
sampling, and declined with depth. However, soil was collected in summer prior to
cropping and this does not reflect the historical annual applications of urea and
inorganic ammonium-based fertilizers, which may have contributed to the numerical
dominance of AOB.
App. A: Ammonia Oxidisers with Depth
208
A subsequent investigation of archaeal amoA gene abundance in the surface 0–
10 cm of native remnant bushland adjacent to each of the agricultural trial sites and on
the same soil type measured mean archaeal amoA gene abundances of 2.6x104 and
1.4x104 gene copies per g of soil at Buntine and Wongan Hills, respectively. This is
approximately an order of magnitude higher than AOA abundance in the 0–10 cm
depths of the agricultural soils, irrespective of treatment, potentially indicating a decline
in AOA with agricultural management. A study of Scottish soils has previously
provided evidence of a land use relationship with ammonia oxidiser communities with
an increase in abundance of AOB in the agricultural ecosystems compared to the natural
ecosystems surveyed, although AOA were always numerically more dominant18.
Examination of the relationship between changing AOB and AOA abundance
with depth and two purported drivers of niche specialization between ammonia
oxidisers, soil pH and substrate availability (as indicated by soil organic matter content),
revealed significant positive correlations between these factors and AOB abundance and
negative correlations with AOA abundance (Fig. 2b,d). This suggests that AOA are
better competitors in the more acidic, organic matter depleted soil conditions at depth
which is in agreement with trends observed elsewhere8 and in physiological studies with
the limited number of AOA in cultivation to date16. However, other variables such as
water, oxygen and temperature, will also exhibit gradients with soil depth and may also
play a role in regulating population abundances to depth.
In addition to the trends with depth this study also examined the effect of direct
manipulation of soil pH through liming and indirect manipulation of substrate
availability through organic amendment on ammonia oxidiser population abundance.
The depth profiles demonstrate that, as expected, the influence of these agricultural
practices was predominantly in the surface 10 cm (Fig. 2a,c). Increases in soil pH
through liming (to near-neutral pH) did not alter total bacterial or archaeal abundances
App. A: Ammonia Oxidisers with Depth
209
(16S rRNA gene copies), nor did it influence the uniformly low AOA abundance.
However, the increased pH had a positive effect on AOB abundance in the surface 0–20
cm layer (Supplementary Fig. S1). This is in agreement with a study of acidic tea
orchard soils in China which reported evidence of pH exerting a greater influence on
AOB abundance than AOA abundance31.
Increases in total organic carbon in response to the addition of extra plant
residues (+OM treatment) were mirrored by increases in total nitrogen and nitrate and
did not alter the soil pH. This suggests that, although the ammonium pool size remained
low (< 1 µg NH4+-N per g soil), the assumption that organic amendment increases
substrate (ammonia) availability holds. The abundance of 16S rRNA and amoA genes
from both bacteria and archaea was found to decrease in the surface layer in the +OM
treatment (Supplementary Fig. S1). This was surprising as the addition of extra organic
carbon and nutrients was expected to increase the size of the prokaryotic community in
general. However, gross nitrification rates were still higher in the surface soils of the
+OM treatment (Fig. 3a), suggesting a more active ammonia-oxidising community.
Although total carbon levels were the same in the sub-soil in the OM trial, all measured
populations were generally more abundant below 15 cm in the +OM treatment. It is
possible this was due to downward movement of dissolved and particulate organic
matter. This pool is known to provide a major energy source for microorganisms and
has been quantified to contribute as much as 42–49% of gross nitrification activity in a
similar agricultural soil32.
App. A: Ammonia Oxidisers with Depth
210
Fig. 2. Depth profiles (0–90 cm) of soil carbon (a) and pH (c) in Western Australian
agricultural soils collected from trial sites where soil pH (-lime versus +lime) or soil
organic matter (-OM versus +OM) had been historically altered and the correlation of
soil carbon and pH with bacterial and archaeal amoA gene abundance (b and d). Error
bars represent ± 1SE. Trendlines show a log-linear fit (all regressions significant at P <
0.001). Soil pH was determined in a 1:5 (w/w) soil suspension in 0.01 M CaCl2. Note:
gene copy numbers are plotted on a log10 scale.
R² = 0.46
R² = 0.621E+2
1E+3
1E+4
1E+5
1E+6
1E+7
1E+8
0.0 0.5 1.0 1.5 2.0 2.5
Log 1
0a
mo
Age
ne
co
pie
s g
dry
so
il -1
Soil C (%)
AOB
AOA
R² = 0.28
R² = 0.19
1E+2
1E+3
1E+4
1E+5
1E+6
1E+7
1E+8
3.0 4.0 5.0 6.0 7.0 8.0
Log 1
0a
mo
Age
ne
co
pie
s g
dry
so
il -1
Soil pH (CaCl2)
AOB
AOA
0
10
20
30
40
50
60
70
80
90
0 0.5 1 1.5 2 2.5
De
pth
mid
-po
int (
cm)
Soil C (%)
+lime
-lime
-OM
+OM
0
10
20
30
40
50
60
70
80
90
3 4 5 6 7 8
De
pth
mid
-po
int (
cm)
Soil pH (CaCl2)
+lime
-lime
-OM
+OM
(a) (b)
(c) (d)
102
103
104
105
106
107
108
102
103
104
105
106
107
108
App. A: Ammonia Oxidisers with Depth
211
Fig. 3. Depth profiles (0–30 cm) of actual (a) and potential (c) gross nitrification rates in
Western Australian agricultural soils collected from trial sites where soil pH (-lime
versus +lime) or soil organic matter (-OM versus +OM) had been historically altered
and the correlation of nitrification rates with bacterial and archaeal amoA gene
abundance (b and d). Error bars represent ± 1SE. Trendlines show a log-linear fit (all
regressions were significant at P <0.001 for all except actual nitrification-logAOB
where P = 0.003). Note: gene copy numbers are plotted on a log10 scale.
R² = 0.33 R² = 0.14
0
1
2
3
4
5
1E+2 1E+3 1E+4 1E+5 1E+6 1E+7 1E+8
Act
ual
gro
ss n
itri
fica
tio
n (
mg
N k
g-1d
-1)
Log amoA gene copies g dry soil-1
AOAAOB
0
5
10
15
20
25
30
0 1 2 3 4 5
De
pth
mid
-po
int (
cm)
Actual gross nitrification (mg N kg-1 d-1)
+lime
-lime
-OM
+OM
0
5
10
15
20
25
30
0 1 2 3 4 5
De
pth
mid
-po
int (
cm)
Potential gross nitrification (mg N kg-1 d-1)
+lime
-lime
-OM
+OM
R² = 0.44 R² = 0.28
0
1
2
3
4
5
1E+2 1E+3 1E+4 1E+5 1E+6 1E+7 1E+8
Po
ten
tial
gro
ss n
itri
fica
tio
n (
mg
N k
g-1d
-1)
Log amoA gene copies g dry soil-1
AOAAOB
(a) (b)
(c) (d)
102 104 106 108103 105 107
102 104 106 108103 105 107
App. A: Ammonia Oxidisers with Depth
212
In this study, 15N isotopic pool dilution was used to determine actual (no
ammonium addition) and potential (with ammonium addition) nitrification rates at in
situ pH values. Correlations between the abundance of ammonia oxidiser populations
and potential nitrification rates have been observed previously31,33. However, analyses
using potential nitrification assays34 are limited by the need to add substrate
(ammonium) and the use of incubation conditions adjusted to a neutral pH which may
inhibit species intolerant of those conditions16. The abundance of AOB was found to
positively correlate to both actual (P=0.003) and potential (P<0.001) gross nitrification
rates while AOA abundance was negatively correlated (P<0.001; Fig 3b, d). Gross
nitrification rates declined significantly with depth (P<0.001) at both sites (Fig 3a,c)
and declined significantly with liming treatment (P<0.001; actual nitrification rate and
P<0.05; potential nitrification rate). The addition of organic matter had no significant
effect on gross nitrification rates (P=0.109; actual nitrification rate and P=0.365;
potential nitrification rate). Our findings indicate that AOB are most likely responsible
for soil nitrification and is supported by previous studies on similar soil types within
this region13,17.
We conclude that AOB is the primary driver of nitrification in these semi-arid
agricultural soils. This is supported by (i) the niche separation of AOA and AOB
populations in these semi-arid agricultural soils with AOB populations dominant in the
surface, (ii) AOB abundance was positively correlated with gross nitrification rates
while AOA was negatively correlated and (iii) indication of a large proportion of the
archaeal population in the surface layer not having amoA genes, while this is where the
majority of nitrification occurs.
App. A: Ammonia Oxidisers with Depth
213
Methods
Soil collection. Soil was collected from two field trials on semi-arid agricultural soil
within the central grain growing region of Western Australia: an organic matter trial at
Buntine (30o 55’ S, 116o 21’ E) and a liming trial at Wongan Hills (30° 51’ S, 116° 44’
E). The region has a semi-arid climate, with hot, dry summers and cool, wet winters
(when cropping occurs).
At Buntine mean annual rainfall is 285 mm, mean monthly temperatures range
from 5.8–35.3 °C and actual temperatures range from -1.0–46.9 °C (calculated from 15
years of data, 1997–2014, Australian Bureau of Meteorology35). At the research site,
soil temperatures (5 cm depth) ranged from 6–46 °C (2008–2012). Soil at the site is a
deep sand (92% sand, 2% silt, 6% clay) and classified as a Basic Regolithic Yellow-
Orthic Tenosol (Australian soil classification36), or a Haplic Arenosol (World Reference
Base classification37). Soil organic matter (OM) treatments at Buntine were sampled
from plots (10 m × 18 m) that were either tilled only (-OM) or tilled with the addition of
extra plant residues (+OM) that had been surface applied at rate of 20 t ha-1 in 2003,
2006, 2010 and 2012 (12 days prior to sampling). This represented an additional 36 t ha-
1, of which 7.0 t of C ha-1 was retained as extra soil organic carbon in the +OM
treatment nine years after trial establishment (i.e. 64% more soil organic carbon in the
+OM treatments compared to the -OM treatments). Tillage was by means of offset disks
to 10 cm depth prior to seeding. Lime was applied to both treatments to maintain a
surface pH > 5.5 to prevent sub-soil acidification in accordance with regional
guidelines38.
At Wongan Hills, mean annual rainfall is 374 mm, with mean daily temperatures
ranging from 11.7 °C–25.3 °C (calculated from 30 years of data, 1981–2010, Australian
Bureau of Meteorology35). The soil at the experimental site is also a free-draining sand
classified as an Acidic Ferric Yellow-Orthic Tenosol (Australian soil classification36).
App. A: Ammonia Oxidisers with Depth
214
Soil pH treatments at Wongan Hills were sampled from plots (1 m × 4 m) that had
either been limed (+lime; 3.5 t ha-1 in March 2009) or not limed (-lime). Three years
after trial establishment the soil pH (CaCl2; 0–10 cm) was 4.4 in -lime and 5.5 in +lime
treatments.
Soil was collected in March (summer) of 2012, prior to crop establishment.
Three soil cores were collected from each replicate plot (n = 3) of each treatment. Soil
from the three soil cores were combined to produce one sample per field plot at each of
the following depth intervals (in cm): 0–2.5, 2.5–5, 5–7.5, 7.5–10, 10–20, 20–30, 30–60
and 60–90. Sub-samples for DNA extraction were frozen immediately upon collection
in a portable freezer and transferred to -20 °C within 1 h.
Nucleic acid extraction and qPCR. For each soil sample, DNA was extracted from
duplicate 800 mg sub-samples using UltraClean™ DNA Isolation Kit (MoBio
Laboratories Inc., Carlsbad, CA, USA). Cell lysis was performed using a Mini Bead
beater (BioSpec products, Inc., USA) at 2500 rpm for 2 minutes. Duplicate DNA
extractions were combined to give a total extract volume of 100 µl.
Functional genes, archaeal and bacterial amoA as well as archaeal and bacterial
16S rRNA genes were quantified using a 7500FAST qPCR machine (Applied
Biosystems, Life Technologies, USA). Each 20 µl qPCR reaction contained 10 µl of
Power SYBR® Green PCR Master Mix (Applied Biosystems), 0.2 µl of the specific
forward and reverse primer at a concentration of 10 µM, 2 µL BSA (Ambion Ultrapure
BSA; 5 mg ml -1), 2 µl of template DNA (8–115 ng) and 5.6 µL of water. DNA extracts
were tested over a series of dilutions to determine if there was inhibition and the
dilution which produced the highest copy number was used for further analysis. Primers
and thermal cycling conditions for both bacterial (primers amoA-1F and amoA-2R) and
archaeal (primers Arch-amoAF and Arch-amoAR) amoA genes were as described
App. A: Ammonia Oxidisers with Depth
215
previously13. Archaeal 16S rRNA gene primers Parch519F
(CAGCMGCCGCGGTAA39) and Arch915R ( GTGCTCCCCCGCCAATTCCT40)
were used with the following thermal cycling conditions: 94 °C for 5 min then 40 cycles
of 94 °C for 30 sec, 63 °C for 40 sec and 72 °C for 40 sec. Bacterial 16S rRNA gene
primers Eub338 (ACTCCTACGGGAGGCAGCAG41) and Eub518 (
ATTACCGCGGCTGCTGG42) were used with the following thermal cycling
conditions: 94 °C for 5 min then 40 cycles of 95 °C for 60 sec, 53 °C for 60 sec and 72
°C for 90 sec.
Melting curves were generated for each qPCR run and fluorescence data was
collected at temperatures above the Tm of the primers but below that of the target (78
°C for both amoA genes, 72 °C for archaeal and 75 °C for bacterial 16S rRNA genes) to
verify product specificity. Each qPCR reaction was run in triplicate. Standard curves
were generated using dilutions of linearized cloned plasmids. Template amplified with
each primer pair described above, was cloned with the P-GEM T-easy system
(Promega, USA), plasmid DNA extracted and inserts sequenced using Big Dye
Terminator chemistry (Australian Genome Research Facility, Western Australia) to
confirm correct length and identity. The standard curve gene sequences were as
described previously13. Standard curves generated in each reaction were linear over four
orders of magnitude (104 to 107 gene copies) with r2 values greater than 0.99.
Efficiencies for all quantification reactions were 80–100 %.
Gross nitrification. Gross nitrification rates were determined by 15N isotopic pool
dilution (see Murphy et al.43 for theory and methodological considerations) in soil
adjusted to 45 % water filled pore space and incubated at 25 °C. Subsamples of soil (20
g dry weight equivalent) were packed into 120 ml vials at a bulk density of 1.4 g cm-3.
To determine actual nitrification rates, 1 ml of 15N enriched (60 atom % excess) KNO3
App. A: Ammonia Oxidisers with Depth
216
was applied as multiple droplets to the vials to obtain a concentration of 5 µg N g -1 soil.
Potential nitrification rates were determined in separate vials by adding 1 ml of 15N
enriched (60 atom % excess) KNO3 (5 µg N g-1 soil) and (NH4)2SO4 at natural
abundance (5 µg N g-1 soil). The vials were incubated with the lids closed to avoid
water loss and aerated every 24 h. Extractions occurred 2 h and 96 h after 15N addition
with 80 ml of 0.5 M K2SO4 for 1 h on an end-over-end shaker, allowed to settle for 30
min and then filtered through Whatman No. 42 filter paper. Soil extracts were prepared
for 15N/14N isotope ratio analysis using a modified diffusion method 44,45 with
subsequent isotope ratio analysis (SERCON 20-22 mass spectrometer connected with
an Automated Nitrogen Carbon Analyzer; Sercon, UK). Gross nitrification was
calculated using the equation by Kirkham and Bartholomew46.
Statistical analyses. All data were statistically analyzed using mixed model Restricted
Maximum Likelihood (REML) repeated measures analysis using GenStat v14.047.
Skewed data was corrected by transforming to the natural logarithm prior to analysis.
AOB data could not be normalized by natural log transformation so was transformed by
log10 prior to analysis. A significance level of 5 % was used for all analysis and the
Power model (City block metric) was used allowing for variance heterogeneity.
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Acknowledgements
This research was funded by the Australian Research Council (ARC), the Australian
Grains Research and Development Corporation’s Soil Biology Initiative II
(UWA00139), and The University of Western Australia. D.V.M. is the recipient of an
ARC Future Fellowship (FT110100246). L.M.F. is supported by an Australian
Postgraduate Award and University of Western Australia Safety Net Top-Up Award.
We are grateful to Hazel Gaza for laboratory assistance and to Deirdre Gleeson and Lori
App. A: Ammonia Oxidisers with Depth
221
Phillips for useful discussions. We thank the Liebe Group and Department of
Agriculture and Food Western Australia for maintaining field trials.
Author contributions
D.V.M. and N.C.B conceived the research and obtained funding. L.D.M., L.M.F. and
D.V.M designed the experiment. L.D.M and L.M.F. carried out the experiment. N.C.B
and D.V.M led the manuscript preparation with substantial inputs on data interpretation
from L.D.M. and L.M.F. All authors have reviewed the manuscript before submission.
Competing financial interests
The authors declare no competing financial interests.
Am
mon
ia o
xidi
sing
bac
teri
a no
t arc
haea
dom
inat
e ni
trifi
catio
n ac
tivity
in se
mi-a
rid
agri
cultu
ral s
oil
Nat
asha
C. B
anni
ng, L
inda
D. M
acca
rone
, Lou
ise M
. Fisk
and
Dan
iel V
. Mur
phy*
Soil
Bio
logy
and
Mol
ecul
ar E
colo
gy G
roup
, Sch
ool o
f Ear
th a
nd E
nviro
nmen
t, In
stitu
te o
f Agr
icul
ture
, The
Uni
vers
ity o
f Wes
tern
Aus
tralia
, Cra
wle
y,
WA
600
9, A
ustra
lia.
* C
orre
spon
ding
aut
hor:
dani
el.m
urph
y@uw
a.ed
u.au
Supp
lem
enta
ry In
form
atio
n
Supp
lem
enta
ry F
ig. S
1. A
bund
ance
of b
acte
rial 1
6S rR
NA g
enes
(a,f)
, bac
teria
l am
oA g
enes
(b,g
), ar
chae
al 1
6S rR
NA g
enes
(c,h
) and
arc
haea
l am
oA
gene
s (d,
i) in
soil
core
s (0-
90 c
m d
epth
) fro
m tw
o W
este
rn A
ustra
lian
agric
ultu
ral f
ield
tria
ls w
ith tr
eatm
ents
+ o
r – o
rgan
ic m
atte
r (O
M; t
op ro
w) a
nd
+ or
– li
me
(bot
tom
row
). Tr
eatm
ent e
ffect
s on
soil
C (e
) and
soil
pH (j
) are
show
n fo
r the
OM
and
lim
ing
trial
site
s, re
spec
tivel
y. N
ote:
gen
e co
py
num
bers
are
plo
tted
on a
log 1
0 sc
ale.
0
10
20
30
40
50
60
70
80
901
E+2
1E+
41
E+6
1E+
81
E+1
0
+lim
e
-lim
e
1E+
21
E+4
1E+
61
E+8
1E+
10
+lim
e
-lim
e
1E+
21
E+4
1E+
61
E+8
1E+
10
+lim
e
-lim
e
1E+
21
E+4
1E+
61
E+8
1E+
10
+lim
e
-lim
e
2.0
4.0
6.0
8.0
+lim
e
-lim
e
1E+
21
E+4
1E+
61
E+8
1E+
10
+O
M
-OM
1E+
21
E+4
1E+
61
E+8
1E+
10
+O
M
-OM
1E+
21
E+4
1E+
61
E+8
1E+
10
+O
M
-OM
0 10
20
30
40
50
60
70
80
901
E+2
1E+
41
E+6
1E+
81
E+1
0
+O
M
-OM
0.0
1.0
2.0
3.0
-OM
+O
M
Depth mid-point (cm) Depth mid-point (cm)G
en
e c
op
ies
g d
ry s
oil-1
Tota
l C (
%)
Ge
ne
co
pie
s g
dry
so
il-1So
il p
H
a. B
acte
ria
b. A
OB
c. A
rch
aea
d. A
OA
e. S
oil
carb
on
f. B
acte
ria
g. A
OB
h. A
rch
aea
i. A
OA
j. So
il p
H (
CaC
l 2)
10
21
04
10
61
08
10
10
10
21
04
10
61
08
10
10
10
21
04
10
61
08
10
10
10
21
04
10
61
08
10
10
10
21
04
10
61
08
10
10
10
21
04
10
61
08
10
10
10
21
04
10
61
08
10
10
10
21
04
10
61
08
10
10
225
Appendix B.
Data not shown in Chapter 3
Figure B.1. Influence of temperature over 7 d of incubation on net nitrification
rates (a) without root exudates; and (b) with root exudates. Error bars are ±SEM (n
= 3), and may be smaller than the symbols. Legend is the same for both panels. Legend
abbreviation: OM: organic matter.
App. B: Data Not Shown Ch. 3
226
Figure B.2. Total recovery of applied 15N from the NH4+, NO3
- and residual soil
pools, calculated by FLUAZ as percentage of 15N at T0 (4–6 h) that was recovered
at T1 (24 h), (a) without root exudates; and (b) with root exudates. Legend is the
same for both panels. Legend abbreviation: OM: organic matter.
227
Appendix C.
Data not shown in Chapter 4
Table C.1. Archaeal amoA gene abundance (gene copies g-1 dry soil). Actual values
are reported. Numbers in parentheses indicate number of replicates in which archaeal
amoA genes were detected. Abbreviations: ND: not detected; OM: organic matter.
Date No Till
No Till
Burnt Stubble Tilled Tilled+OM
Tilled+OM
Run-Down
18 May 2010 ND ND ND ND ND
21 Jul 2010 6.58 x 105 (1) ND ND ND ND
23 Aug 2010 1.16 x 105 (1) ND ND ND ND
19 Oct 2010 ND ND ND ND ND
1 Dec 2010 2.09 x 105 (1) ND ND ND ND
2 May 2011 ND ND ND ND ND
20 Jun 2011 2.95 x 107 (1) ND ND ND 3.25 x 107 (1)
1 Aug 2011 ND ND ND ND ND
19 Sep 2011 ND ND ND ND ND
15 Nov 2011 2.39 x 107 (1) ND ND ND ND
App. C: Data Not Shown Ch. 4
228
229
Appendix D.
Data Not Shown in Chapter 5
Figure D.1. Change in 15N-labelled ammonium (NH4+) above natural abundance
through time with added 15(NH4)2SO4. (a) at 20 °C in soil held at optimal water
content (45% WFPS); (b) at 20 °C in soil wet-up to 45% WFPS then allowed to dry; (c)
at 40 °C in soil held at optimal water content; and (d) at 40 °C in soil wet-up then
allowed to dry. Error bars are ±SEM (n = 3). Legend is the same for all panels. Legend
abbreviation: OM: organic matter.
App. D: Data Not Shown Ch. 5
230
Table D.1. Linear regression results for response of logged bacterial amoA gene
abundance to gross N transformation rates. Regression coefficients are only reported
for the significant relationship. Abbreviations: Min: gross N mineralisation; Nitr: gross
nitrification.
Predictor
Significance
level Coefficient
Standard
error of
coefficient Intercept
Standard
error of
intercept
Adjusted
R2
Min. P<0.0001 -0.0524 0.0128 6.7409 0.0765 0.1111
Nitr. P=0.3435
231
Appendix E.
Publications arising from this thesis
Peer-Reviewed Journal Articles
Fisk, L.M., Barton, L., Jones, D.L., Glanville, H.C. & Murphy, D.V., 2015. Root
exudate carbon mitigates nitrogen loss in a semi-arid soil. Soil Biology & Biochemistry,
88, 380-389. doi:10.1016/j.soilbio.2015.06.011
Appears as Chapter 3.
Fisk, L.M., Maccarone, L.D., Barton, L. & Murphy, D.V., 2015. Nitrapyrin decreased
nitrification of nitrogen released from soil organic matter but not amoA gene abundance
at high soil temperature. Soil Biology & Biochemistry, 88, 214-223.
doi:10.1016/j.soilbio.2015.05.029
Appears as Chapter 5.
Banning, N.C., Maccarone, L.D., Fisk, L.M. & Murphy, D.V, 2015. Ammonia-
oxidising bacteria not archaea dominate nitrification activity in semi-arid agricultural
soil. Scientific Reports, 5. doi:10.1038/srep11146
Appears as Appendix A.
App. E: Publications Arising
232
Fisk, L.M., Barton, L., Maccarone, L.D. & Murphy, D.V. Seasonal dynamics of
ammonia-oxidising bacteria but not archaea influence risk of nitrogen loss in a semi-
arid agricultural soil. Manuscript in preparation.
Appears as Chapter 4.
Conference papers
Fisk, L.M., Murphy, D.V. & Barton, L., 2012. The effect of temperature and organic
carbon availability on the relative rates of microbial nitrogen immobilisation and
nitrification in a semi-arid soil, In: Burkitt, L.L., Sparrow, L.A. (Eds.), 5th Joint
Australian and New Zealand Soil Science Conference: Soil solutions for diverse
landscapes. Australian Society of Soil Science Inc., Hobart. (Oral presentation)
*awarded best oral presentation by a researcher under 35 years old
Maccarone, L., Fisk, L., Barton, L., Gleeson, D. & Murphy, D., 2012. Is there niche
separation of archaeal and bacterial nitrifying populations in semi-arid soil? In: Burkitt,
L.L., Sparrow, L.A. (Eds.), 5th Joint Australian and New Zealand Soil Science
Conference: Soil solutions for diverse landscapes. Australian Society of Soil Science
Inc., Hobart. (Poster presentation).
Fisk, L., Maccarone, L., Barton, L. & Murphy, D., 2013. Effectiveness of the
nitrification inhibitor nitrapyrin at reducing the risk of nitrogen loss in semi-arid soil.
Earth and Environment Postgraduate Symposium, The University of Western Australia,
Fremantle, Western Australia, 7th November, 2013. (Oral Presentation).
Fisk, L. M., Barton, L., Jones, D. L., Glanville, H. C. & Murphy, D. V., 2014. Root or
residues: Do carbon additions decrease the risk of nitrogen loss in semi-arid cropping
App. E: Publications Arising
233
soils? In: Crop Nutrition Symposium, Murdoch University, Murdoch, Western
Australia, 9th June 2014, p. 7. (Oral presentation)
Fisk, L., 2014. Roots or residues: Do carbon additions decrease the risk of nitrogen loss
in semi-arid cropping soils? The UWA Institute of Agriculture Postgraduate Showcase
2014: Frontiers in Agriculture, Crawley, Western Australia, 5th June, 2014. (Oral
Presentation)
Reports
Maccarone, L., Fisk, L., Sawada, Y., Barton, L., Gleeson, D. & Murphy, D., 2012.
Determining nitrogen cycling dynamics in semi-arid soil. Liebe Grower Group Trial
Report.
Murphy, D.V., Fisk, L., Kaiser, C., Maccarone, L., Jones, D., Kilburn, M., Clode, P.,
Banning, N., Gleeson, D., Phillips, L., Stockdale, E. & Barton, L., 2014. Harnessing the
nitrogen cycle through novel solutions, UWA00139. Final report for Soil Biology
Initiative II, The University of Western Australia and Grains Research & Development
Corporation.
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