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The effects of synthetic nitrogen fertilizer on the biodiversity of soil microbial communities Biederman T and Heidenreich G
Introduction
The practices of conventional agriculture impact the soil in a number of ways. The term
conventional is used to refer to agriculture which uses synthetic products such as fertilizers and
also transgenic technology to increase yields and become more profitable as a result (Pimental et
al. 2005). The different forms of conventional farming practices such as tilling the soil, and
applying synthetic fertilizer and pesticides onto the soil, can impact the symbiotic relationship
between crops and soil microorganisms, but are done in order to increase crop growth (Liphadzi
et al. 2005). As discussed by van der Heijden et al. (2008), the symbiotic relationship between
plants and microorganisms has been found to be important for maintaining and increasing
longterm plant productivity.
Historically, animal manure was the primary way to introduce additional nitrogen to the
soil. Microbial enzymes convert the nitrogen within the manure from ammonium, into the usable
form, nitrate, a process called nitrification, and thereby improve yields (Zhen et al. 2014).
Microbial nitrification is especially important for Zea mays because as a grass, it relies on soil
bacteria to convert nitrogen fertilizers into useable forms for the plant (Santi et al. 2013). Zhen
(2014) indicated that the application of urea, a common synthetic nitrogen fertilizer, decreased
soil microbial presence when compared to nitrogen in the form of manure. Farmers apply
different forms of synthetic nitrogen fertilizers onto their fields in the hope of increasing annual
yields, without having a complete understanding of how their synthetic fertilizers are affecting
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the soil microbial community, possibly affecting their soil’s longterm health and fertility
(Mrkovacki et al. 2012 and Zhen et al 2014).
The usage of different forms of synthetic nitrogen and its impact on soil microbial
community biodiversity in a production field setting has not been extensively researched. Soil
microbial diversity is determined through measuring the enzymatic activity of microbes when
placed in solution onto different substrates, such as in a BIOLOG Ecoplate (Liphadzi et al.
2005). BIOLOG Ecoplates measure microbial presence via a reduction reaction within the
substrate initiated by enzymatic activity, causing a color change that can be measured via optical
density readings. A change in total microbial enzymatic activity is an indirect way to measure
change in microbial diversity (van Heerden et al. 2001).
Shen et al. (2010) conducted a study that indicated that when granular urea is applied at
high rates, there was a negative impact on soil microbial enzyme activity. However, few studies
examined the impact of knifed anhydrous ammonia effect on soil microbial diversity It was
hypothesized that there would be a difference in soil microbial biodiversity when granular urea
and anhydrous ammonia are compared to a control. It was predicted that granular urea would
have an overall negative impact on the soil microbial biodiversity when compared to the control.
Methods
Study site
Our project was situated on a 2.2 hectares (ha) corn field in Northwestern Illinois at 42°
24' 33"N, 89° 58' 36.0624"W. The soil is an Oxford silt loam with approximately 150 cm of
topsoil. The field was planted on May 1, 2015 with the Pioneer 0495 AMX, a RoundUp Ready®
hybrid, at 91,400 seeds per hectare. The field was divided into three equal nitrogen treatment
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strips, with each strip divided into three sampling blocks, running the width of the field (Figure
1). Treatment on the southern strip was granular urea (U), the central strip had no fertilizer
(control, C), and the northern strip received knifed anhydrous ammonia (A). The granular urea
was applied at a rate of 440 kg ha1, and the anhydrous ammonia was applied at a rate of 250 kg
ha1 so that there would be 200 kg ha1 of available nitrogen in the soil. The nitrogen was applied
on April 28, 2015.
Figure 1. Field layout. Three treatment strips with divisions of granular urea fertilizer (U), knifed anhydrous ammonia fertilizer (A), and the control strip (C) along with the sampling locations represented by the circles on the map.
Soil collection
Samples were collected on three separate dates: May 2, July 22, and September 6, 2015.
In each of the block of the grid, RTK® GPS was used to place flags in the sampling locations.
Each of these flags remained in the same place throughout the project so samples would be taken
from the from the exact same locations each time. A soil corer was utilized to take soil samples
approximately 15 cm below the soil’s surface from within the grid pattern (Figure 1). The May
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sampling occurred 24 hours postplanting. . The samples taken in July and September were
taken at the same depth, but the crop’s roots had grown large enough to create a
microenvironment, called the rhizosphere, just under the soil surface. In Zea mays, the
rhizosphere has the greatest amount of plantmicroorganism interaction (Santi et al. 2013). The
samples were again taken at a depth of 15 cm in the rhizosphere on each date, placed in zipped
bags, and then placed in a cooler for transport back to the lab for analysis. In between each
sampling location, the soil corer was sanitized with 70% ethanol. This procedure was repeated
each time the field was visited for sampling.
Lab work
Once at the lab, the samples were placed in cold storage at 4°C. While the samples were
in cold storage, a solution of 1X PBS buffer solution with magnesium chloride was prepared
from a 5X stock solution. A stock 1X PBS solution volume of 99 mL was pipetted into 9
sterilized Erlenmeyer flasks. One gram of soil was put into each flask. The flasks were then
agitated to suspend the soil in the solution, removing the microbes from the soil particles.
Separation of the soil particles from the microbes was done to ensure optical density readings
would be accounting only for microbial enzymatic activity. Once the soil was suspended, the
flasks were placed in the cold room for 24 hours to settle. Once the solutions had settled, 110 μL
of the solution was pipetted into each well of the BIOLOG Ecoplates using a BIOLOG 8well
micropipetter.
BIOLOG Ecoplates consisted of 96 wells with 31 different substrates in triplicate. The
three remaining wells were water controls. If microbes were present and aerobically respiring,
the well underwent a color change due to respiration initiating a reduction of the tetrazolium dye.
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As greater amounts of the tetrazolium dye was reduced, leading to a color change within the
wells from clear to deeper shades of purple, Deeper shades of purple registered higher optical
densities which indicated increased enzymatic activity as seen in Appendix 1. Enzymatic activity
serves as an indirect measurement of microbial biodiversity based upon number of substrates
used (van Heerden et al. 2001). The BIOLOG plates were placed in a 27° incubator for 24 hours
before the first BIOLOG readings. The BIOLOG readings were taken using a BIOLOG reader to
determine light absorbance readings. The plates were incubated for an additional 24 hours before
taking the second readings. This procedure was repeated for each sampling date. In summation,
there were 9 BIOLOG Ecoplates per sampling date, one plate for each sampling location, for a
total of 27 plates across the three sampling dates.
The BIOLOG plate reader would calculate light absorbance readings based on the
amount of light absorbed by the control wells, which contained only water in the substrate.
Positive readings and marginal readings were determined by the computer program according to
the reading from the control wells. Light absorbance readings that registered as positive were
recorded as scoring a 1 on the spreadsheet, and readings that scored marginally positives were
assigned a 0.5 value. Readings that were not positive or marginal positives were assigned values
of 0. The total score per plate was tabulated and recorded for analysis.
Data analysis
The data from the 48 hour readings were compiled into one spreadsheet as total number
of positive absorbancies by taking the sum of total positive and marginal absorbancies per
BIOLOG plate. The Friedman Test is a nonparametric test, similar to ANOVA, in which more
than two groups can be compared. The Friedman test detects differences in treatments across
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multiple sampling dates within each block (Sokal and Rohlf 1995). A Friedman’s Test was used
to determine if there were statistical differences in the number of positive absorbance readings
between the three treatments separated by sampling date (Appendix 1 and 2).
Results
Treatment
Ammonia
Urea Control
Sampling Dates
1 51.6 ± 2.02
51.0 ± 7.76
53.5 ± 4.09
2 37.3 ± 2.61
38.0 ± 4.75
42.3 ± 9.61
3 56.3 ± 4.37
44.2 ± 3.65
51.0 ± 3.61
Table 1. Total score of positive and marginal readings for each sampling site and date.
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Figure 2ac. Total number of substrate usage positives for each sampling site and date.
Due to the fact that some of the replicates within a date were significantly different the data
could not be used as replication in the statistical analyses.
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Discussion
There were no significant differences between the treatments, etc. From our calculated
pvalue of 0.422692, it can be concluded that there is no significant difference in the results from
the samplings. This does not support the hypothesis that there would be a difference in the
treatments when compared to the control. It also does not support the prediction that there would
be a decrease in microbial biodiversity and presence in the granular urea strip of the plot. The
data collected showed that, despite claims made by Shen et al. (2010), there was no significant
impact on the soil communities in relation to the type of fertilizer used. The study conducted by
Shen et al. (2010) examined the effects of different application rates of granular urea to soils,
whereas this study only examined the effects of one rate of granular urea. The rate at which our
urea was applied was with recommendations from agronomists who supplied the fertilizer to us
and in the middle of the urea rates of Shen et al. (2010). The recommended rate was based on
plant needs and resource conservation to aid in runoff prevention and nitrate loss. Granular urea
had the lowest overall BIOLOG score of the two treatments and the control. This could be
attributed to inert or inactive ingredients in the granules of urea. These particles could have a
negative impact on the soil microbiome in comparison to the other two treatments.
Anhydrous ammonia has been found to be highly toxic in the application zone of the soil,
but not as toxic in adjacent soil locations. Smiley et al. (1970) conducted research using
anhydrous ammonia as a fungicide in wheat. Their research found that the fungus fusaria began
to decline in density as the proximity to the anhydrous ammonia decreased. This can be related
to soil microorganisms as well. If the soil sampling were to have occurred in the middle of the
ammonia application line, there is the potential that there would have been a significant decrease
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in soil microbial presence. Due to the results of the anhydrous ammonia BIOLOG score and the
control BIOLOG score being so close, it can be concluded that the ammonia line was
approximately 40 cm away from the sampling location, reducing ammonia’s impact on the
microbes.
Zhen et al. (2014) studied the impacts of granular urea on soil microbial communities
compared to cattle manure compost. Their study found that the granular urea plots had a lower
level of microbial biodiversity than the plots with cattle manure compost added. This result is
unsurprising, however, due to the fact that within manure is remnants of the cattle’s microbiome,
a collection of microbes, primarily bacteria, that is not common to the soil rhizosphere (Parham
et al. 2003). In addition to adding composted manure, Zhen et al. (2014) compared the difference
in microbial presence in composted manure fertilizer plus bacterial fertilizer to urea with
bacterial fertilizer added. The same result was found, the manure had a higher level of soil
bacteria and biodiversity in comparison to the urea. When urea is added at high concentrations, it
was found to have a negative impact on the soil. Comparing this to higher concentrations of
composted manure does not, however draw a fair comparison. Adding more microbes as manure
does and comparing it to a synthetic fertilizer that has no microbial properties does not yield
results conducive to making fertilizer recommendations.
This study aimed to determine the impact that two different types of synthetic nitrogen
fertilizers had on the soil microbial community. The results were inconclusive in that there was
no significant difference in the microbial presence in the anhydrous ammonia or the granular
urea plot. This leads to the conclusion that there is no negative impact on the soil microbial
community when either anhydrous ammonia or granular urea are used as fertilizers on
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conventional farms. This does not, however, determine the longterm impacts on the soil. Further
research with multiyear trials would need to be conducted to determine the longterm impacts
on soil communities.
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Literature Cited
BIOLOG Inc. 2015. BIOLOG EcoPlate. BIOLOG Inc. Hayward(CA). [cited 1 December 2015]. http://www.biolog.com/pdf/milit/00A_012_EcoPlate_Sell_Sheet.pdf van Heerden J, Ehlers MM, Cloete TE. 2001. BIOLOG for the determination of microbial diversity in activated sludge systems. Water Science Technology. 43(1):8390. van der Heijden MGA, Bardgett RD, van Straalen NM. 2008. The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. Ecology Letters. 11: 296–310. Liphadzi KB, AlKhatib K, Bensch CN, Stahlman PW, Dille JA, Todd T, Rice CW, Horak MJ, Head G. 2005. Soil microbial and nematode communities as affected by glyphosate and tillage practices in a glyphosateresistant cropping system. Weed Science. 53:536545. Mrkovacki N, Dalovic I, Jockovic D. 2012. Dynamics of the number of microorganisms and dehydrogenase activity in the rhizosphere of maize in longterm monoculture. Agricultural Science. 44(2):192197. Parham A, Deng SP, Da HN, Sun HY, Raun WR. 2003. Longterm cattle manure application in soil. II. Effect on soil microbial populations and community structure. Biology and Fertility of Soils. 38(4): 209215. Pimentel D, Hepperly P, Seidel R, Hanson J, Douds D 2005. Environmental, energetic, and economic comparisons of organic and conventional farming systems. BioScience. 55(7): 573582. Santi C, Bogusz D, Franche F. 2013. Biological nitrogen fixation in nonlegume plants. Annals of Botany. 1:125. Shen W, Lin X, Shi W, Min J, Gao N, Zhang H, Yin R, He X. 2010. Higher rates of nitrogen fertilization decrease soil enzyme activities, microbial functional diversity and nitrification capacity in a Chinese polytunnel greenhouse vegetable land. Plant Soil. 337:137150. Smiley RW, Cook RJ, Papendick RI. 1970. Anhydrous ammonia as a soil fungicide against fusarium and fungicidal activity in the ammonia retention zone. Phytopathology. 60(1): 12271232 Sokal RR and Rohlf FJ. 1995. Biometry. Third Edition. New York (NY): W.H. Freeman and Company. 440441.
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Wagg C, Jansa J, Schmid B, van der Heijden MGA. 2011. Belowground biodiversity effects of plant symbionts support aboveground productivity. Ecology Letters. 14: 10011009. Zhen Z, Liu H, Wang N, Guo L, Meng J, Ding N, Wu G, Jiang G. 2014. Effects of Manure Compost Application on soil microbial community diversity and soil microenvironments in a temperate cropland in China. PLoS ONE. 9(10):113.
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Appendix
Figure A.1: BIOLOG Ecoplate after 24 hour incubation
Figure A.2: BIOLOG Ecoplate Substrate Map (BIOLOG Inc. 2015)