Soil microbial responses to climate perturbations Sarah E. Evans Kellogg Biological Station Michigan State University

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1 Soil microbial responses to climate perturbations Sarah E. Evans Kellogg Biological Station Michigan State University

2 The soil environment Harsh environment, many abiotic stressors Highly diverse, many unknown species Frequent passive and host associated dispersal Changes in microbial function influence soil services and biogeochemical cycling

3 Moisture stress: what do we know? Long term exposure to moisture stress alters composition Filter We also know: Many tolerance strategies, costs are elusive Indirect effects important Fungi often more resistant Variability matters

4 Exposure to extreme rainfall patterns alters composition Can we go beyond this? Konza Biological Station rainfall manipulations Soils were exposed to greater moisture fluctuation for 10 years

5 Clustering taxa by life history strategy revealed ecological adaptation No exposure to extremes Long-term exposure to extremes Lab exposure to stress Tolerant Tolerant Opportunistic Sensitive Opportunistic Taxa (1 each row) Sensitive Extreme pulses Extreme pulses Evans and Wallenstein, Ecology Letters, 2014

6 Introduction of new (tolerant) taxa was important for shift 75% were different spp Previously exposed to moisture pulses 25% overlap Control Of those taxa present in both control and manipulated plots, 82% of taxa changed strategy Evans and Wallenstein, Ecology Letters, 2014

7 Evolutionary and ecological response to perturbation Change strategy Depends on: Plasticity, evolution, trait lability Community filtering Depends on: Dispersal rate, colonization, regional species Evans and Wallenstein, Ecology Letters, 2014

8 Simulating effects of dispersal rate on communities DEMENT trait based model Allison et al. 2012, Ecology Letters Individual taxa are assigned a suite of traits Taxa filtered by fitness/traits in environment Varied passive dispersal rate Taxa abundance Time Time Time

9 Model showed: dispersal greatly affects species composition and Low dispersal traits Higher stochasticity in composition, likely due to drift Reached less optimal trait values High dispersal Stronger environmental selection No swamping at very high rates Higher functional potential for many traits Evans et al ISMEJ, Evans et al. in prep Density Density Km_Lignin Km_Lignin

10 Does dispersal play a role in adaptation to drought?

11 Experimental design Collect precipitation Filter-sterilize Re-add water to intact cores

12 Experimental design Receive sterile rain Receive rain with microbes 25% of ambient rain re-added Ambient 2nd factor: Drought

13 High variation in composition of air/rain Aug 2 Rain communities Nov Feb 16 NMDS Soil communities Feb 16 Feb 16 Oct Jan 16 Nov Dec Jan 16Nov Oct Oct Aug Aug Oct Aug Nov Dec Oct Aug Aug Aug Sep Sep Sep Jan 16 Aug Sep NMDS1 Nov Composition predictors: Date: p > 0.1 Precip type: p > 0.1 Most abundant phyla Proteobacteria Acidobacteria Actinobacteria Verrucomicrobia Bacteroidetes Cyanobacteria Firmicutes

14 Don t see a large signature of rain microbes in soil On average, rain indicator species made up about 5% of abundance of soil communities Some treatments had higher rain microbes Drought > ambient Sterilized soil > non sterilized Clay > sand No difference in sterile rain and nonsterile rain!

15 Yet, dispersal treatment significantly affected composition: 0.2 Time Filter NMDS Dispersal treatment Rain Sterile rain Drought treatment Reduced Ambient NMDS1

16 Is there evidence that rain helped introduce more tolerant taxa? Functional diversity a a a b Rain Trt: p=0.07 Disp Trt: p=0.008 Interaction p=0.85 Reduced Ambient Reduced Ambient Sterile rain Nonsterile rain

17 Summing up: perturbation x dispersal Passive colonizers play a role in maintaining soil diversity More nuanced than supplying rain microbes Dispersal alters the effect of drought, but no strong evidence it aids in adaptation

18 Next steps: scaling up Coastal fog disperses novel microbes into the hyperarid Namib Desert, Namibia

19 Cross cutting needs Use of assembly and ecological theory to get more predictive Composition alone still insufficient for understanding response to perturbation Dispersal rate can significantly alter compositional patterns we are observing Need to integrate dispersal into our understanding of microbial resilience

20 Acknowledgements Collaborators and assistance Kevin Dougherty, Will West, MSU (rain dispersal) Steve Allison, Jen Martiny at UC Irvine (modeling) Kathy and Peter Jacobson, Grinnell College (Namib) Funding sources DOE Nat l Inst for Climate Change Research (NICCR) NSF Math/Bio Postdoctoral Fellowship in Biology Kellogg Biological Station, Michigan State Univ National Geographic Society

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22 Start End Lignin enzyme potential Environment 1 (mild) Environment 2 (harsh) Density Density Density K Li i Km_Lignin K Li i K Li i Km_Lignin Low dispersal High dispersal Low dispersal High dispersal Density Density Density Density Km_Lignin Km_Lignin Density

23 Abundance 3e+05 2e+05 1e+05 Abundant Phyla in rain Proteobacteria Acidobacteria Actinobacteria Verrucomicrobia Bacteroidetes Cyanobacteria Firmicutes 0e+00 Feb Jan Dec Nov Oct Sept Aug

24 And function NMDS Rain Sterile rain Reduced Ambient Functional profiles and diversity of control communities (no dispersal limitation or drought) were distinct from all other communities.

25 And changed compositional response to drought: Time 0 Mean distance drought-ambient Filter NMDS2 0.0 Rain Sterile rain -0.1 Dispersal treatment Rain Sterile rain Drought treatment Reduced Ambient NMDS1

26 Rain Sterile rain Mean distance drought-ambient

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