Professor Jim Harris Department of Natural SER Europe...
Transcript of Professor Jim Harris Department of Natural SER Europe...
The role of soil microbiology in restoration
Professor Jim HarrisDepartment of Natural Resources
SER EuropeSummer School
September 2007
The MillenniumEcosystem Assessment
The Millennium Ecosystem Assessment
• 60% of world ecosystem services have been degraded
• Of 24 evaluated ecosystem types, 15 are being damaged
• About a quarter of the Earth's land surface is now cultivated.
Soil-dependentecosystem services
OverburdenOverburdenSubSub --soilsoilTopsoilTopsoil
Nine attributes of a restored ecosystem
1. Reference ecosystem, characteristic assemblages
2. Indigenous species, some exceptions 3. Functional groups present or available
4. Physical environment appropriate
5. Ecosystem functions normally for successional stage6. Landscape integration, biotic and abiotic interactions
7. Potential threats eliminated8. Resilience and integrity
9. Self-sustaining
Criteria for ecological indicators
• Easily measured• Sensitive
• Respond predictably to stress• Anticipatory• Allow for adaptive management intervention
• Integrative• Have known responses to stress, disturbances
and time• Low variability in response
Derived from Dale and Beyeler 2001
A QUICK PRIMER ON LIFE IN EARTH
SERVICES PROVIDED BY SOILS
• Primary productivity• food and fibre production
• diverse habitats
• Environmental services
• filtering
• buffering
• transforming
• Biological habitat and biodiversity reserve
• Platform functions
• Landscape and heritage
• Source of raw materials
THE SOIL HABITAT
5 cm 5 mm
SOIL BIOMASS
• Handful of arable soil(c. 200g)…..
• .…approximately0.5 g of fresh biomass (mainly ‘microbial’)
5 t ha-1
equivalent to 100 sheep per hectare
grassland – 20 times greater = 2000 sheep per hectare
DISTRIBUTION WITHIN SOIL PROFILE
POPLAR PLANTATION (2-YEARS OLD)
0
5
10
15
20
25
30
35
0 - 25 25 - 60 60 -100
Depth (cm)
t ha
-1
TOTAL C
0
50
100
150
200
250
300
0 - 25 25 - 60 60 -100Depth (cm)
MIC
RO
BE
, kg
/ ha
0
200
400
600
800
1000
1200
1400
RO
OT
, kg
/ ha
Fungal CBacterial CRoot C
BIOLOGICAL C
(Horwath , 1993, adapted from Paul and Clark, 1996)
SOIL BIODIVERSITY
µm
cm
mm
MAMMALS
PROTOZOANEMATODES
INSECTSARACHNIDSMOLLUSCSWORMS
BACTERIAFUNGIALGAE
SOILBIOMASS
PLANT ROOTS
TENS OF THOUSANDS spp.
HUNDREDS
HUNDREDS
FEW
TENS
20 µm50 µm
10-100 µm
0.1 - 2 mm
2-20 mm
MAP OF Armillaria bulbosa in Michigan forest
CLONE A
CLONE B
N
100 m
CLONE A
CLONE B
N
100 m
CLONE A
CLONE B
N
100 m
CLONE A
CLONE B
N
100 m
BlueWhale
ARBUSCULAR MYCORRHIZAE
NEMATODE-TRAPPING FUNGI
Arthrobotrys anchonia
EXAMPLE OF SOIL FOOD WEB IN ARABLE SOIL
de Ruiter, Moore et al. 1993; Journal of Applied Ecology 30, 95-106
What can we measure?
•Size•Composition •Activity
Community Size andGross Activity
0
200
400
600
800
1000
1200
1400
0 50 100 150 200 250
Time (Years)
Mic
robi
al B
iom
ass-
C (µ
g/g)
BareVegetated
Change in BiomassChange in Biomass--C with timeC with time
(redrawn from Insam and Domsch, 1989)
Microbial Community Size and Activity
Scatterplot (Spreadsheet2 in Tom Hill data 3v*12c)
Dune 5 yr
Dune 17 yrDune 30 yr
Dune 50 yrDune 80 yr
Dune 100 yr
56 104 177 239 277
Biomass-C
-50
0
50
100
150
200
250
300
350
400
450
500
DH
A
Adapted from Hill, 1995
1000 metres
Location of Sutton Courtenay landfill site.
0
200
400
600
800
1000
1200
R4 R13G R20G R35 CON
Field
Mic
rob
ial
Bio
mas
s,
g.g
dry
so
il
Microbial Biomass results from each sample area. The bars show standard error (n=3).
50 100 150 200 250 300 350 400 450 500 550
ATP
0
100
200
300
400
500
600
>2m
m a
gg s
tab
(g/k
g)11 Years
6 years
5 years6 years
Compacted
6 yearswaterlogged
CHARACTERISING BIODIVERSITY
GENOTYPIC
• fundamental information – the blueprint
FUNCTIONAL• processes – the working engine
PHENOTYPIC• expressed information – the parts
CHARACTERISING BIODIVERSITY
GENOTYPIC
• fundamental information – the blueprint
Environmental Sample
Purification
Polymerase chain reaction
Diversity measures :SequencingDGGE, TGGE, ARDRA-RFLP,G+C contents,Disassociation-reassociation curves
Enumeration:Real time PCR,Probes, G+C contents
Activities:Real time PCR-mRNA
ExtractionActivities:Microscopy•Reporter genes•STARFISH
Enumeration:Probes
BROAD-SCALE GENETIC ANALYSIS
• %G+C profiling of soil community DNA in UK upland grasslands
-5
-4
-3
-2
-1
0
1
2
3
4
5
-6 -4 -2 0 2 4 6 8
CV1
CV
2
Unimproved
Semi-improved
Improved
-5
-4
-3
-2
-1
0
1
2
3
4
5
-6 -4 -2 0 2 4 6 8
CV1
CV
2
Unimproved
Semi-improved
Improved
Unimproved
Semi-improved
Improved
CHARACTERISING BIODIVERSITY
PHENOTYPIC• expressed information – the parts
Microbe
Cell MembraneCell Membrane
PHOSPHOLIPID FATTY ACIDS
PLFA Profile from a mixed woodlandPLFA Profile from a mixed woodland
PLFA profiles: Microbial groupsPLFA profiles: Microbial groups
PLFA PHENOTYPIC PROFILING
• Appropriateness in context of biodiversity ?• relationship to taxonomy is rather loose• relationship to environmental context is
apparently quite high• are number of PLFA’s a measure of ‘diversity’
0.0
0.2
0.4
0.6
0.8
1.0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Community 1
Community 2
Pro
port
ion
Abbots Hall Farm EssexAbbots Hall Farm Essex
SSOO
FF
FrFrYY
-5
-4
-3
-2
-1
0
1
2
3
-7 -5 -3 -1 1 3 5
SaltmarshFarmlandFarmland (former marsh)Restored Marsh (1995 flood)Restored Marsh (2002)
SaltmarshSaltmarsh
FarmlandFarmland
Reclaimed Farmland (300yr)Reclaimed Farmland (300yr)
20022002 RestorationRestoration
1995 Restoration1995 Restoration
CHARACTERISING BIODIVERSITY
FUNCTIONAL
• processes – the working engine
FUNCTIONAL PROFILING
• High-throughput systems:• enzyme profiling
• fluorimetric systems (umbelliferones, MUF)
• substrate utilisation profiling
Carbon is the currency of the soil economy
Multiple Substrate Induced Respiration
96-channel respirometers:
RABIT MicroRespTM
MSIR OUTPUT: RATE CURVES
CTA
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
MNL
0
20
40
60
80
100
0 5 10 1 5 20
ERY
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
GLT
0
20
40
60
80
100
0 5 10 1 5 20
PHN
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
QNA
0
20
40
60
80
100
0 5 10 1 5 20
URE
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
MGL
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
BSA
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
CLB
0
20
40
60
80
100
0 5 10 15 20
CDX
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
GLC
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 2 0
MLA
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
MNS
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
GLA
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
GLY
0
20
40
60
80
100
0 5 10 15 20
ARG
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
A SC
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 2 0
A SP
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
GLM
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
HST
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
LY S
0
20
40
60
80
100
0 5 10 15 20
SER
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
MAL
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 2 0
PNT
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
STC
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
SNC
0
2 0
4 0
6 0
8 0
10 0
0 5 10 15 20
TWN
0
20
40
60
80
100
0 5 10 15 20
WA T XYL
0
2 0
4 0
6 0
8 0
10 0
0 2 4 6 8 10 12 14 16 18
KBA
0
2 0
4 0
6 0
8 0
10 0
0 2 4 6 8 10 12 14 16 18
KGA
0
20
40
60
80
100
0 2 4 6 8 10 12 14 16 18
Subtract respiration from water controls
FUNCTIONAL PROFILING:FUNCTIONAL PROFILING:Multiple substrate SIRMultiple substrate SIR
� Effect of agricultural management regimes
So
urc
e: D
ege
ns &
Ha
rris
19
97: S
oil
Bio
lBio
chem
29
:13
09
-132
0
-1
-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-1.2 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4
PC1
PC
2
Continuous pastureArable2y pasture leyReseeded pasture
MONITORING: TRAINING LOADS
• BIOLOGICAL STATUS OF SOILS• microbes provide sensitive indicator• Approach pioneered in USA
EFFECT OF MILITARY TRAFFICKING UPON SOIL MICROBIAL BIOMASS
0
5
10
15
20
25
30
35
40
45
Reference Light Moderate Heavy Remediated
PLF
A p
mol
g-1
So
urc
e: P
ea
cock
et a
l. (2
001
) E
colo
gic
al In
dic
ato
rs 1
:11
3-1
21
TRAINING LOAD
BIO
MA
SS
EFFECT OF MILITARY TRAFFICKING UPON SOIL MICROBIAL BIOMASS
0
5
10
15
20
25
30
35
40
45
Reference Light Moderate Heavy Remediated
PLF
A p
mol
g-1
So
urc
e: P
ea
cock
et a
l. (2
001
) E
colo
gic
al In
dic
ato
rs 1
:11
3-1
21
TRAINING LOAD
BIO
MA
SS
Salisbury Plain Training Area
BACKGROUND
• Covering approx. 14,000 ha, ATE SP has by far the largest extent of chalk grassland in the UK, and indeed, in north-west Europe
• Chalk grassland is one of the most ecologically diverse wildlife habitats to be found in Britain
• Site of Special Scientific Interest (SSSI) and Special Protection Area (SPA) for birds
• Historical and current land-use of SPTA have resulted in landscapes and wildlife almost unique in the UK
EFFECT OF DISTURBANCE UPON SOIL COMMUNITIES
• Cranfield University Development Project• Case study @ Salisbury Plain
• SOILS SAMPLED FROM FIVE CATEGORIES [March 04]
Arable field (cereal)X
SevereE
HeavyD
MediumC
LightB
NoneA
DISTURBANCE CATEGORYCODE
PROPERTIES MEASURED
• How much is life is there ?• microbial biomass
• Who is there ?• community structure
• Soil chemical properties
SAMPLING LOCATIONS
E D C
BA
X
A
B
C
E
D
MICROBIAL BIOMASS
DISTURBANCE CATEGORY
µg
C g
dry
soi
l-1
0
250
500
750
1000
A B C D E X
ANALYSIS OF MULTI-VARIATE DATA
• Principal component analysis• reduces large data sets to a few numbers
(Principal Components, PCs) that essentially capture the same information as is contained within the full data set
• quantify the extent to which the PCs ‘represent’the entire data set
• identify which of the properties are most responsible for discriminating between samples
E
D
C
B
A
-3
-2
-1
0
1
2
3
4
5
-6 -4 -2 0 2 4 6
PC1 (55%)
PC
2 (1
7%)
PRINCIPAL COMPONENT ANALYSIS
X
A
B
X
D
E
C
PLOT OF FIRST THREE PRINCIPAL COMPONENTS
Discrimination mainly due to one
PLFA
A
B
X
D
E
C
PLOT OF FIRST THREE PRINCIPAL COMPONENTS
Discrimination mainly due to one
PLFA
FUNGAL:BACTERIAL RATIO
DISTURBANCE CATEGORY
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
A B C D E X
“STRESS” RATIO
DISTURBANCE CATEGORY
0.4
0.6
0.8
A B C D E X
SALISBURY PLAIN CASE STUDY
• Training load influences microbial biomass in a consistent manner
• greater disturbance � smaller biomass
• Microbial community structure shows distinct trajectory in relation to training load
• relatively few PLFAs lead to discrimination
• Sample site C – why different ?
DECISION TREE ANALYSIS
• Formulate model using decision tree
• Which are key drivers that discriminate between samples ?
• Showed significance of
• microbial biomass
• certain key PLFA compounds
• Predict to 93% accuracy to which disturbance level a soil sample corresponds
Putting it all together
3D Scatterplot (Spreadsheet1 in Workbook3 4v*12c)
Floodmeadow 1
Restored Grass 5 yr
Floodmeadow 2
Restored Woodland 1
Rough Grassland
Restored Grass 10 yr
Restored Woodland 2
Breckland
Woodland 1
Chalk Grassland
Woodland 2Woodland 3
3D Scatterplot (Spreadsheet1 in Workbook3 4v*12c)
Floodmeadow 1
Restored Grass 5 yr
Floodmeadow 2
Restored Woodland 1
Rough Grassland
Restored Grass 10 yr
Restored Woodland 2
Breckland
Woodland 1
Chalk Grassland
Woodland 2Woodland 3
3D Scatterplot (Spreadsheet1 in Workbook3 4v*12c)
Floodmeadow 1
Restored Grass 5 yr
Floodmeadow 2
Restored Woodland 1
Rough Grassland
Restored Grass 10 yr
Restored Woodland 2
Breckland
Woodland 1
Chalk Grassland
Woodland 2Woodland 3
SOIL MICROBIAL PROPERTIES AS ECOLOGICAL INDICATORSSOIL MICROBIAL PROPERTIES AS ECOLOGICAL INDICATORS
TOTAL TOTAL BIOMASSBIOMASS
Community Community compositioncomposition
GROSS ACTIVITYGROSS ACTIVITY
Late Grass
Mid Grass
5 Year Restored
Early Grass
Scrub
Stored Soil
Pioneer
Forest
Bare
COMMUNITY TRAJECTORIESCOMMUNITY TRAJECTORIES……
TOTAL TOTAL BIOMASSBIOMASS
GROSS ACTIVITYGROSS ACTIVITY
Late Grass
Mid Grass
5 Year Restored
Early Grass
Scrub
Stored Soil
Pioneer
Forest
Bare
Community Community compositioncomposition
CONCLUSIONS: BIOLOGICAL STATUS OF SOILS
• Microbes provide sensitive indicator of ecological status / ecosystem health
• assessment of degree of disturbance• assessment of current status in relation to
management of degraded and restored ecosystems
• quantify where the system ‘is’ and where it is ‘going’
• Restoration context• assess potential for restoration and status of such
management (target setting)
Facilitators or Followers?
• Facilitation by modifying soil conditions• Facilitation by symbionts• Inhibition by symbionts• Facilitation by pathogens and herbivores
• Inhibition by pathogens and herbivores• Maintenance of stability in late-successional
assemblages
Principal research gaps
• How much genotypic and functional diversity is required to facilitate plant community function?
• What community players, other than symbionts, are essential for facilitation or inhibition?
• Do shifts from bacterial to fungal dominated communities result in ecosystem stability?
• A large scale survey of restoration and reference sites
• What are the feedbacks between the soil biological community and soil structural formation and stability?
Nine attributes of a restored ecosystem
1. Reference ecosystem, characteristic assemblages
2. Indigenous species, some exceptions 3. Functional groups present or available
4. Physical environment appropriate
5. Ecosystem functions normally for successional stage6. Landscape integration, biotic and abiotic interactions
7. Potential threats eliminated8. Resilience and integrity
9. Self-sustaining
Nine attributes of a restored ecosystem
1. Reference ecosystem, characteristic assemblages
2. Indigenous species, some exceptions 3. Functional groups present or available
4. Physical environment appropriate
5. Ecosystem functions normally for successional stage6. Landscape integration, biotic and abiotic interactions
7. Potential threats eliminated8. Resilience and integrity
9. Self-sustaining
Conclusions
• The soil biological community is a a key component of the soil ecosystem, crucial in supplying ecosystem goods and services
• Understanding it is critical to provide successful outcomes in restoration programmes
• It may be use to indicate objectively the progress, or lack of it, in such programmes