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Harvard Forest Symposium Abstract 2018

  • Title: Evaluating the link between metacommunity stability and environmental variability across trophic groups represented at LTER sites
  • Primary Author: Sydne Record (Bryn Mawr College)
  • Abstract:

    Metacommunity ecology emphasizes both the local and regional scale factors that shape community structure. Metacommunity dynamics and stability in response to environmental variability may depend on key parameters, such as dispersal, niche differentiation, and habitat heterogeneity. However, it remains uncertain whether these parameters can confer stability over long time scales or across ecosystem types. We used NSF Long-Term Ecological Research (LTER) datasets to synthesize general relationships between metacommunity parameters and stability across a wide range of ecosystems and over long temporal scales. We characterized the links between metacommunity variability and environmental fluctuations by calculating summary statistics (e.g., alpha, beta, and gamma diversity) to describe variability in each time series, including coefficient of variation (CV) for univariate time series of aggregate metrics, and measures such as beta diversity to characterize compositional variation. We then explored how the magnitude of variability in metacommunity metrics was related to environmental variability across LTER data sets. Functions used to calculate local and regional measures of metacommunity and environmental stability along with derived data products created during this synthesis effort will be released as a package for the R statistical environment.

    We have collected, formatted, and pre-processed twenty-one metacommunity time series data sets representing thirteen LTER sites across a variety of ecosystem types, including forests, deserts, freshwater, and marine systems. Thirteen taxa are represented in the data sets, including plants, invertebrates, fish, mammals, birds, and reptiles. Environmental variables include factors such as water availability (e.g., precipitation in terrestrial habitats), wave action (marine habitats), and mean annual temperature. Qualitatively, we observed a decrease in variation in biodiversity with increased environmental variability, both at local and regional scales. Preliminary results also suggest environmental factors and measures of biodiversity were more variable at marine LTER sites than terrestrial LTER sites. This pattern was apparent both at local (e.g., mean alpha diversity) and regional (gamma diversity) scales. Variability in biodiversity at local and regional scales varied among trophic groups at each site, but there was no consistent pattern across LTER sites or ecosystem types. These results suggest that our long held notions of what confers stability may not be applicable across all ecosystem types, which is useful information for ecosystem managers dealing with globally changing ecosystems.

    This work is part of the LTER Metacommunity Synthesis Working Group at NCEAS and includes contributions from Nicole M. Voelker (Geography & Environmental Systems, University of Maryland, Baltimore County, Baltimore, MD), Eric R. Sokol (NEON and INSTAAR, University of Colorado, Boulder, CO), Nathan I. Wisnoski (Department of Biology, Indiana University, Bloomington, IN), Christopher M. Swan (Geography and Environmental Systems, University of Maryland, Baltimore County, Baltimore, MD), Thomas Lamy (Université de Montréal, Montreal, QC, Canada; Marine Science Institute, University of California, Santa Barbara, Santa Barbara, CA), Max C.N. Castorani (Marine Science Institute, University of California, Santa Barbara), Luca Marazzi (Southeast Environmental Research Center (SERC), Florida International University, Miami, FL) Aldo Compagnoni (Ecology and Evolutionary Biology, Rice University, Houston, TX), Jesse R. Blanchard (Earth and Environment, Florida International University, Miami, FL), Riley Andrade (School of Geographical Sciences and Urban Planning, Arizona State University), and Nina K. Lany (Dartmouth College, Hanover, NH; Department of Forestry, and Ecology, Evolutionary Biology and Behavior Program, Michigan State University).


  • Research Category: Ecological Informatics and Modelling; Biodiversity Studies