Soil Biodiversity
What can it tell us
about the state of the
environment?
Professor Jim Harris
Challenges
• Global climate change
• Sea level rise
• Agricultural intensification
• Food and water security
• Loss of biodiversity
Soil biology is essential
to ecosystem structure
and function
• Organic matter decomposition and nutrient
cycling – and therefore in regulating plant
productivity and community dynamics (Wardle et
al, 2004; Van der Heijden et al, 2008);
• Soil structural generation (Feeney et al, 2006);
• Successional processes “crossing barriers”
(Kardol et al 2009)
• Plant diversity, ecosystem variability, and
productivity (Van der Heijden et al 1998)
HOW MUCH IS
THERE ? •SOIL BIOMASS
• handful of arable soil
(c. 200g)
• approximately
0.5 g of fresh biomass
(mainly ‘microbial’)
• Over 10,000 species
per gram
(conservative
estimate)
5 tonnes per hectare –
equivalent to 100 sheep
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 h
a-1
TOTAL C
0
50
100
150
200
250
300
0 - 25 25 - 60 60 -100
Depth (cm)
MIC
RO
BE
, k
g /
ha
0
200
400
600
800
1000
1200
1400
RO
OT
, k
g /
ha
Fungal C
Bacterial C
Root C
BIOLOGICAL C
(Horwath, 1993, adapted from Paul and Clark, 1996)
SOIL BIODIVERSITY
µm
cm
mm
SOIL
BIOMASS
MAMMALS
PROTOZOA
NEMATODES
INSECTS
ARACHNIDS
MOLLUSCS
WORMS
BACTERIA
FUNGI
ALGAE
PLANT ROOTS
MAMMALS
PROTOZOA
NEMATODES
INSECTS
ARACHNIDS
MOLLUSCS
WORMS
BACTERIA
FUNGI
PLANT ROOTS
100,000,000,000
50,000 m
100,000
10,000
5000
0.001
500 m
# INDIVIDUALS
10,000
100
100
0.001
10
# SPECIES
SOIL BIODIVERSITY
20 µm
MAP OF Armillaria bulbosa in Michigan forest
CLONE A
CLONE B
N
100 m
CLONE A
CLONE B
N
100 m
MAP OF Armillaria bulbosa in Michigan forest
Blue
Whale
Here
Plant
shoots
Plant
roots
Organic
matter
Plant
Feeding
nematodes
Mycorrhizae
Saprophytic
fungi
Bacteria
Mesostigmatid
mites
Fungal feeding
nematodes
Bacterial feeding
nematodes
Flagellates
Amoebae
Ciliates
Fungal
Feeding mites
Predatory
Nematodes
Soil biota – Data rich
How might we measure this?
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
CHARACTERISING THE SOIL BIOTA
FUNCTIONAL
• processes – the working engine
PHENOTYPIC
• expressed information – the parts
STRUCTURAL
• the physical organisation – the engine
GENOTYPIC
• fundamental information – the blueprint
SIZE
• how much is there?
0 200 400 600 800 1000 1200 1400
0-5
5-10
10-15
15-20
20-25
25-30
Depth (cm)
DHA g/kg/d
Cut 5 Year
Grazed 5 Year
Cut 10 Year
Grazed 10 Year
Wet Reference
Dry Reference
Microbial activity decreases with depth
Soil ecosystem maturity
‘As microbial communities develop during succession from r-dominated (principally bacterial) to K-dominated (principally fungal) communities, they become more thermodynamically efficient, manifest as producing less waste heat per unit added glucose per unit biomass.’
Harris Science 2009
Fungal:Bacterial Ratio
Microbial
Biomass
in
Soil bulk
phase
Raw substrate/degraded site
Pioneer/
Immature
system
Late grassland
Scrub
Forest
Normal
successional
trajectory
Restoration
shortcut
Harris, Science (2009)
COMMUNITY TRAJECTORIES…
TOTAL
BIOMASS
FUNGAL
BIOMASS
GROSS ACTIVITY
Late Grass
Mid Grass
5 Year Restored
Early Grass
Scrub
Stored Soil
Pioneer
Forest
Bare
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
COMMUNITY TRAJECTORIES…
TOTAL
BIOMASS
FUNGAL
BIOMASS
GROSS ACTIVITY
Late Grass
Mid Grass
5 Year Restored
Early Grass
Scrub
Stored Soil
Pioneer
Forest
Bare
But just “more of everything” does
not necessarily mean “better”
Examples
Phenotypic profiling
Phospholipid fatty acid (PLFA) profiling
The Analytical Process
Forest Soil Sample Extraction Partition
Fractionation Analysis
GC/GC-MS
Derivatization
(methanolysis)
+ CH3OHOH
OR'
+ H2OO
OCH3
R'
PLFA Profile from a mixed woodland
PLFA PROFILES
• Provide phenotypic ‘fingerprint’
of soil community structure
• Studies consistently show there
are distinct profiles associated
with:
– ecosystems
– vegetation types
– environmental factors (pollutants)
– management effects (cropping
system, tillage, type and rate of
substrate input)
PLFA TYPE
AMOUNT
Abbots Hall Farm Essex
Abbots’ Hall – High Tide
Abbots Hall Farm Essex
S
O
F
Fr
Y
-5
-4
-3
-2
-1
0
1
2
3
-7 -5 -3 -1 1 3 5
Saltmarsh
Farmland
Farmland (former marsh)
Restored Marsh (1995 flood)
Restored Marsh (2002)
Saltmarsh
Farmland
Reclaimed Farmland (300yr)
2002 Restoration
1995 Restoration
Canonical Analysis of
Principal Co-ordinates of
Multiplex-TRFs on six
sampling dates (numbers)
for four restoration sites
(coloured)
Canonical Analysis of
Principal Co-ordinates of
ITS-fungal TRFs on six
sampling dates (numbers)
for four restoration sites
(coloured)
Restored
Stuck
Recovering
Can we measure anything which doesn’t
involve having to measure partitioning
between different biological groups?
FUNCTIONAL PROFILING
MEASUREMENT OF PROCESSES
• Example: carbon transformations
– C utilisation profiling
• simultaneously determine the ability of soil
community to utilise a range of substrates of
varying composition and properties
0
1
2
3
4
5
6
7
8
9
10
1 3 5 7 9
11
13
15
17
19
21
23
Compound type
Utilisa
tio
n
0
1
2
3
4
5
6
7
8
9
10
1 3 5 7 9
11
13
15
17
19
21
23
Compound type
Utilisa
tio
nA B
Multiple
Substrate
Induced
Respiration
MicroResp™ is a unique microtitre-plate based respiration system
which allows 96 whole soil, sediment, biological tissue or water
samples to be analysed simultaneously.
Community-Level Physiological Profiles (CLPP),
www.microresp.com
MicroResp™
SIR Response Profile for IGER Pasture
Polymers Water
Respiration response
(µg CO2-C g-1 soil)
0
200
400
600
800
1000
Aromatics
Amino Acids Alcohols
Carboxylic acids Sugars
Amines Amides
SIR Response Profile for Lake Pasture
12
48
±83
11
70
±102
14
83
±42
Respiration response
(µg CO2-C g-1 soil)
0
200
400
600
800
1000
Aromatics
Amino Acids Alcohols
Carboxylic acids Sugars
Amines Amides
Water Polymers
Odum’s Ecosystem Attributes
• Community energetics • Community structure • Life-History • Nutrient cycling • Selection Pressure • Overall homeostasis
Contrast of non-equilibrium vs equilibrium
Nonequilibrium • Biotic decoupling • Species independence • Unsaturated • Abiotic limitation • Density independence • Opportunism • Large stochastic effects • Loose patterns
Equilibrium • Biotic coupling • Competition • Saturated • Resource limitation • Density dependence • Optimality • Few stochastic effects • Tight patterns
redrawn from Wiens 1984
Inefficient? Efficient?
TAM AIR
Harris et al 2012
Examples of heat output – samples from Fors
Heat signatures at A) 2 days, B) 6 days, C) 16 days & D) 36 days
+ Glucose
Water
Metabolism + Waste heat
Biomass
Increasing stress
Long-Term Soil Organic Matter Experiment
Inorganic input regimes
• Calcium nitrate • Ammonium sulphate
Organic input regimes
• Straw + calcium nitrate • Farmyard manure • Sewage sludge
x
Started in 1956
• How effectively energy is used?
• How much input energy is converted into biomass
and how much is lost as heat?
Where: ηeff = thermodynamic efficiency; Qgluc = heat production of glucose
amended sample (J g-1 soil); Qcontrol = heat production of unamended soil (J
g-1 soil); ΔHgluc = the enthalpy change for complete combustion of glucose
The higher this number the more efficient
the system is.
Harris et al 2012
Another Index:
Substrate Induced Heat Production = Total Heat Output/Soil Biomass
SIHP – the lower this number the higher the efficiency is.
Substrate Induced Heat Production index
Harris et al 2012
Metabolism + Waste heat
Biomass
Mature Immature
SIHP
Thermodynamic
efficiency
Successional age/ecosystem maturity
What might we find?
Map showing the location of the Morteratsch Valley in S.E. Switzerland (Google maps), with sample sites displayed as yellow markers on a semi-transparent Google EarthTM overlay of Burga’s (1999) moraine sequence map
A post-glacial successional gradient
Examples of samples sites from; A) site B, 2011 moraine, B) site 5, 2006 moraine, C) site 7, 1960 moraine, and D) site 12, 1857 moraine
Change in SIHP with age of site
In summary
We can tell us:
• If the microbiota is under stress
• The structural and functional aspects of the biotic
community following a trajectory that matches an
appropriate reference (or control) ecosystem
And another
thing……
Effect of mycorrhizal diversity on plant diversity
and productivity
“Red Queen”
Hypothesis
Pathogens favour rare
genotypes by putting
their resources into
attacking common
genotypes, thereby
enhancing non-native
over native vegetation
Inderjit and van der Putten (2010)
Microbial controls on
vegetation
composition
Direct effects include:
• native soil communities (including soil
pathogens) which resist invasion (Nijjer et al.
2007);
• native soil biota that can create positive
feedback (e.g. Callaway et al. 2004); and ,
• complete or partial release from enemies, such
as fungi or viruses (e.g. Keane and Crawley,
2002; Knevel et.al 2004).
In other words…
…microbes facilitate invasion
and novelty in ecosystems by
providing an irreversible
threshold
In conclusion
• Soil function is driven by biology
• Soil contains high levels of biodiversity
• This biodiversity is exquisitely sensitive to
environmental conditions and land use
• This data richness makes soil biology an ideal
indicator of function, status and change
• Soil biodiversity is being recognised as a critical
control on plant community assemblage and
therefore ecosystem structure and function
Thank you!