Can microbial functional traits predict the response and resilience of decomposition to global change?

1
Can microbial functional traits predict the
response and resilience of decomposition to
global change?

• Steve Allison
• UC Irvine
• Ecology and Evolutionary Biology
• Earth System Science
• allisons_at_uci.edu

2
Project goals

• Determine how microbial taxa respond to reduced
  precipitation and increased N
• Determine the distribution of enzyme genes among
  taxa
• Predict enzyme function and litter decomp based
  on first two goals
• Test if microbial communities are resilient to
  environmental change

3
Project design
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Plot
Litter origin
A
Ambient
A
N
A
N
Nitrogen experiment
Nitrogen enriched
A
N
A
N
Precip reduced
Mic. comm. origin
A
P
A Ambient
Precip experiment
N Nitrogen enriched
A
P
P Precip reduced
B
inoculation
2012
2013
composition samples
2011
additional samples
June
June
Feb
Feb
Dec
Feb
Dec
Dec
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Allison lab responsibilities

• Litter mass remaining
• Fungal and bacterial counts
• Microscopy (fungi), flow cytometer (bacteria)
• Extracellular enzyme activities
• Litterbag and plot-level
• Litter chemistry
• nIR, C/N analysis
• Decomposition model

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Litter mass remaining Drought

• Microbes from reduced water leave more mass
  remaining (6-12 months)
• Less mass loss in reduced water plots (6 months)

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Litter mass remaining N addition

• Significant plot by litter interactions that
  differ at 6 vs. 12 months

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Fungal counts Drought

• More fungi in reduced water plots (3-6 months)
• Significant and contradictory microbial origin
  effects

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Bacterial counts Drought

• Strong negative effects of reduced water
  microbial origin effect disappears by 6 months

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Bacterial counts N addition

• Positive effect of N in litter origin at 6 months

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Enzymes Drought

• Higher activities of all hydrolytic enzymes
  except LAP

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Enzymes N addition

• Higher LAP in fertilized litter other effects
  are weak

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Initial litter chemistry

• Similar for litter from control and added N plots
• Litter from reduced water plots has more lignin,
  protein, labile compounds less cellulose and
  hemicellulose
• Some differences are maintained after 3 months

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Litter chemistry Drought

• 3-6 months relatively more labile constituents
  remaining in reduced water plots

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Litter chemistry N addition

• Greater lignin loss in litter from N plots (6
  months)

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Data summary

• Reduced water effects generally stronger than N
  effects
• Direct effects of plot on decomposition generally
  stronger than indirect effects on plants and
  microbes
• Reduced water favors fungi over bacteria, slows
  decomposition, and allows enzymes and labile
  substrates to accumulate

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Project goal model integration

• Incorporate disturbance responses and gene
  distributions into a model
• Predict response of litter decomposition to
  treatments
• Validate model with reciprocal transplant results

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Approaches to modeling decomposition
Exponential decay (Olson 1963)
Schimel and Weintraub (2003)
Moorhead and Sinsabaugh (2006) Guild
decomposition model (functional groups)
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What is a trait-based model?

• Organisms are represented explicitly (biomass,
  physiology, etc.)
• Each taxon possesses a specific set of trait
  values
• Trait values can be randomly chosen and/or
  empirically derived
• Community composition
• is an emergent property

www.brooklyn.cuny.edu
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Represented traits

• Extracellular enzymes and uptake proteins
• Gene presence/absence
• Vmax, Km
• Specificity
• Production and maintenance costs
• Carbon use efficiency
• Cellular stoichiometry
• Dispersal distance

www-news.uchicago.edu
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Model structure
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Example question and application

• Under what conditions are generalist versus
  specialist strategies favored?
• Generalist broad range of enzymes produced

Specialist
Generalist
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Model set-up

• 100 taxa, 100 x 100 grid
• Taxa may possess 0 to 20 enzymes
• 12 chemical substrates (approximates fresh
  litter)
• Each degraded by at least 1 enzyme

Enzymes
Substrates
1 20
1 0 1 0
0 0 0
100 1 0 0
1 12
1 0 2.5 0
0 0 1.2
20 1.7 0 0
Vmax values
Taxa
Enzymes
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Model set-up

• Equivalent uptake across taxa
• Could also implement uptake matrices

Transporters
Monomers
1 20
1 0 1 0
0 0 0
100 1 0 0
1 14
1 0 2.5 0
0 0 1.2
20 1.7 0 0
Vmax values
Taxa
Transporters
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Model experiments

• Simulate leaf litter decomposition (no inputs)
• Test effect of tradeoffs in enzyme traits
• Increase litter N or lignin
• Model validation with Hawaiian litter

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Model results

• Taxa vary in density over time (succession)

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Model results

• Should be selection to link uptake with enzymes

Enzymes and uptake correlated
No correlation
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Model results

• Species interactions are present but vary by
  taxon and model conditions

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Model validation

• Fits are better for decomposition than enzymes

R2 0.35 P lt 0.001
R2 0.81 P lt 0.001 Slope 1.70.2
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Model summary

• Enzyme genes and uptake proteins should be
  correlated
• Species interactions may be important
• Empirical and genomic data can tell us about
  tradeoffs, trait correlations, and trait
  distributions

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Thank you!

• NSF ATB, DOE BER, audience