Colorado mountains
From Long-Term Data to Understanding: Toward a Predictive Ecology
2015 LTER ASM Estes Park, CO - August 30 - September 2, 2015

Quantifying the magnitude and predictability of community changes: a new framework for studying and a meta-analysis of community responses to global change drivers

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Meghan Avolio
KimberlyJ La Pierre
Forest Isbell
Emily Grman
Gregory R Houseman
David S Johnson
Kevin R Wilcox
Sally E Koerner

Global change drivers can have drastic effects on plant community composition, with consequences for ecosystem function. Ecologists have been tasked with predicting the trajectory and magnitude of community responses to these altered environmental conditions. The methods typically employed in ecological studies focus on mean differences in richness and composition in response to resource manipulations, thus masking the inherent complexity of many ecological systems. Yet variability among replicates within a treatment can be informative for the trajectory and predictability of community responses to global change drivers. For example, when replicates converge, there is high predictability for both community and ecosystem responses. Alternatively, replicate communities that diverge may more difficult to predict, even though divergence could result from either stochastic or deterministic processes. Here we present a new framework for studying community responses to global change drivers, and then use our framework to understand community changes with a meta-analysis of 81 studies in herbaceous systems. All studies manipulated at least one resource (water, light, carbon, nutrients) and tracked total community changes for at least three years. We found the shift in community composition treatments relative to the controls increased with the duration of the experiment and was stronger when multiple global change drivers were simultaneously manipulated (e.g., combined N and CO2 additions) than when one driver was manipulated alone. In addition to shifts in community composition between treatments, replicate plots within treatments were also observed to vary in community composition. The dispersion among replicates within treatments varied widely relative to the control plots, with some treatments resulting in plant community convergence, others resulting in divergence, and some showing no change in dispersion among replicates. Finally, experiments where the plant community shifted with experimental treatments exhibited corresponding shifts in ANPP; further, the predictability of ANPP increased when replicate plant communities converged in response to treatments and decreased when they diverged. Overall, our results illustrate the importance of examining both changes in mean and variance in community composition when examining ecosystem responses to global change.