2020 ESA Annual Meeting (August 3 - 6)

OOS 19 Abstract - Causal inference to infer relationships between biodiversity-productivity in observational data

Tuesday, August 4, 2020: 3:30 PM
Laura Dee1, Paul Ferraro2, Chris Severen3, Eric W. Seabloom4, Elizabeth T. Borer4, Ashley L. Asmus5, Michel Loreau6, Jarrett E. K. Byrnes7, Kimberly Komatsu8, Akira S. Mori9 and The NutNet Consorteum10, (1)Department of Ecology and Evolutionary Biology, University of Colorado-Boulder, Boulder, CO, (2)Carey Business School and Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, (3)Philadelphia Federal Reserve, Philadelphia, PA, (4)Ecology, Evolution, and Behavior, University of Minnesota, Saint Paul, MN, (5)Department of Ecology, Evolution and Behavior, University of Minnesota, St Paul, MN, (6)Theoretical and Experimental Ecology Station (CNRS), Moulis, France, (7)Department of Biology, University of Massachusetts Boston, Boston, MA, (8)Smithsonian Environmental Research Center, Edgewater, MD, (9)Yokohama National University, Yokohama, Japan, (10)Nutrient Network (www.nutnet.org)
Background/Question/Methods

Through decades of experimental and observational research, ecologists have sought to understand how changes in biodiversity affect ecosystem productivity. While most small-scale experiments report positive effects, evidence from non-experimental settings is mixed. These conflicting results reflect challenges in developing empirical designs that permit credible, generalizable causal inferences from ecological systems. These challenges can, however, be overcome through recent advances in data and methods. To estimate how changes in species richness affect productivity, we leverage multi-site, longitudinal data from over 1200 unmanipulated plots in 43 grassland ecosystems around the world, and apply methods from public health and economics specifically designed for inferring causality from observational data.

Results/Conclusions

We find that losses in species richness cause productivity to increase: a 10% decline in richness leads to a 2.4% increase in productivity We find that losses in species richness cause productivity to increase: a 10% decline in richness leads to a 2.4% increase in productivity (i.e., an effect size of -.24 of biodiversity on productivity with a 95% CI of [-0.397, -0.083]). This result cannot be explained by observable or unobservable confounding factors but could be explained by plausible ecological mechanisms and the types of biodiversity changes happening in the Anthropocene as non-native species invade new areas and rare species are preferentially lost from ecosystems. As new sources of longitudinal ecological data become available, our methods can be applied more broadly to improve causal inferences about ecological relationships from observational data.

DISCLAIMER: The views expressed in this paper are solely those of the authors and do not necessarily reflect those of the Federal Reserve Bank of Philadelphia or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.