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Contrasting predictions of

Contrasting predictions of. experimental and observational. studies of the response of plant. communities to changing precipitation. Brody Sandel 1 , Leah J. Goldstein 2 , Nathan Kraft 1 , Jordan  Okie 3 , Michal Shuldman 1 , David D. Ackerly 1 , Elsa Cleland 4 and  Katharine N. Suding 2

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Contrasting predictions of

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  1. Contrasting predictions of experimental and observational studies of the response of plant communities to changing precipitation Brody Sandel1 , Leah J. Goldstein2, Nathan Kraft1, Jordan  Okie3, Michal Shuldman1, David D. Ackerly1, Elsa Cleland4 and  Katharine N. Suding2 (1)Department of Integrative Biology, UC Berkeley, Berkeley, CA (2)Ecology and Evolutionary Biology, UC Irvine, Irvine, CA (3)Department of Biology, University of New Mexico, Albuquerque, NM (4)Ecology, Behavior & Evolution Section, UC San Diego, La Jolla, CA

  2. Introduction Plant responses to climate change • How will the composition of plant assemblages respond to climate change? • Precipitation change Weltzin et al. 2003, Bioscience. • Plant functional traits Suding et al. 2008, Glob. Change Biol. • Experimental/observational Rustad 2006, Plant Ecol.

  3. Introduction Traits and climate change • Traits vary with climate • Can they predict response to changing climate? N:P Wright et al. 2005, Glob. Ecol. Biogeogr. Reich and Oleksyn 2004, PNAS

  4. Introduction Traits and climate change • Advantages of trait-based predictions • Mechanistic interpretations • Allows syntheses • Predictions are generalizable

  5. Introduction Experimental and observational • Similar predictions? • Direction and magnitude of effect • Shifts in functional trait composition are the bases for comparison

  6. Introduction Similar predictions? Mean trait value Mean trait value Control + Precip Precipitation

  7. Introduction Similar predictions? • Direction Mean trait value Mean trait value Control + Precip Precipitation

  8. Introduction Similar predictions? • Direction • Magnitude • ∆TE =? ∆TO ∆TE ∆TO Mean trait value Mean trait value Equivalent to experiment Control + Precip Precipitation

  9. Introduction Similar predictions? • Combining results • Same direction, different magnitude • (My a priori expectation) Observational gradient T C T Experimental studies Mean trait value C T C Precipitation

  10. Methods Methods overview • Experimental water additions • Natural precipitation gradient • Match species lists to trait databases • Calculate plot mean trait values • Test for effects of increased water • Compare experimental and observational outcomes • Direction • Magnitude

  11. Methods Experimental data • Four water addition experiments • Konza LTER (1991-2005) Knapp et al. 2001, Ecosystems. • Shortgrass Steppe LTER (2000) • Sevilleta LTER (2004-2006) Baez et al. In prep. • Jasper Ridge Global Change Experiment (1999-2002) Zavaleta et al. 2003, Ecol. Monogr. • Between 10% and 190% (mean 50%) precip. increases • Plant community composition data • Grasslands or mixed grass-shrublands • 219 species total

  12. Methods Observational data • VegBank (vegbank.org) • 21,566 plots from across the country • Plant assemblage of all plots • 7813 species total • Used PRISM climate data to obtain 30-year mean precipitation values

  13. Methods Traits • Matched species lists to trait databases • USDA Plants • Kew Gardens Seed Information Database • Glopnet leaf traits Wright et al. 2004. Nature. • More leaf traits Tjoelker et al. 2005, New Phyt.; Reich and Oleksyn 2004, PNAS. • Height Cleland et al. 2008. Ecology.

  14. Methods Traits

  15. Methods Analyses • Abundance-weighted trait means for each plot • Percentage cover by a group • All analyses performed on these plot-level values • Experimental • ANOVA using last year of each study • Observational • Aggregated cells at 1 x 1 degree resolution • Linear regression

  16. Results Seed size example log(Seed mass (mg)) log(Precip (mm))

  17. Results Seed size example log(Seed mass (mg)) log(Precip (mm))

  18. Results Seed size example log(Seed mass (mg)) log(Precip (mm))

  19. Results Seed size example log(Seed mass (mg)) log(Precip (mm))

  20. Results Seed size example log(Seed mass (mg)) log(Precip (mm))

  21. Treatment effect log(Seed mass (mg)) per log(Precip (mm)) Results Seed size example Slopes of line segments through time Year

  22. Results Summary of all traits † indicates a significant site by treatment interaction

  23. Results Summary of all traits † indicates a significant site by treatment interaction

  24. Results Summary of all traits † indicates a significant site by treatment interaction

  25. Results How will communities change? • Experimental studies • Tall, long-lived forbs with short leaf lifespans, high leaf N concentrations, high specific leaf area, and small seeds • Observational analysis • Long-lived woody species with long leaf lifespans, low leaf N concentrations and photosynthetic capacity, and large seeds

  26. Discussion Why the mismatch? • One is right, the other wrong • Experimental artifacts • Unmeasured covariates • The different responses may reflect a real, two-phased response to climate change

  27. Discussion A two-phase model • Response to climate change may occur over distinct phases • Why two phases? • Why might the responses in each phase differ? • What determines the time scale of the phases?

  28. Discussion Two phases • Premise – Abundance changes happen more quickly than species gain and loss • Phase 1 – Changes in local species abundance • Phase 2 – Changes in species pool • Calculating plot trait values not weighted by abundance revealed fewer treatment effects • Abundance shifts were critical in experiments

  29. Discussion Two phases Increased water Phase 1 – Abundance changes Time Phase 2 – Species pool changes

  30. Discussion Phase differences • Why might the trait responses differ in the two phases? • Changing interactions among species • Shifts in the limiting resource • The traits of local species that increase are not the same as those of immigrating species

  31. Discussion Phase differences Increasing species are able to take advantage of increased resource availability (tall, high leaf N, short-lived leaves, small seeds) Increased water Taller stature - light limitation Species must cope with low light environment (woody, low leaf N, long-lived leaves, large seeds) Time

  32. Discussion Time scales • Little evidence for phase 2 in the experiments • No convergence through time towards observational results • No treatment affect on species-time relationships KNZ JRG SEV

  33. Discussion Time scales • What determines the length of phase 1? • Spatial extent of climate change • Life histories of local species (annual/perennial) • At least decades in this case • Lengthened by experimental limitations

  34. Discussion Main messages • Traits useful predictors • Mismatch between experimental and observational results • Could be due to different time scales captured by these two types of study • Use the appropriate data to predict for a given time scale

  35. Acknowledgments • NCEAS, and the coordinators and participants in the distributed graduate seminar • William Lauenroth • Alan Knapp • William Pockman • Erika Zavaleta • Funding – • NSF grant to NCEAS (EF-0553768) • UC Santa Barbara • LTER network office for cross-site research • NSF LTER program (DEB0218210, BSR 88-11906, DEB9411976, DEB0080529, DEB0217774, DEB0217631) • David and Lucile Packard Foundation • Morgan Family Foundation • Jasper Ridge Biological Preserve • The many VegBank contributors • Ian Wright and Peter Reich (Glopnet)

  36. Discussion A two-phase model

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