Ecosphere (Oct 2022)

Using local and regional trait hypervolumes to study the effects of environmental factors on community assembly

  • Wei Mao,
  • Zhibin Sun,
  • Elisabeth J. Forrestel,
  • Robert Griffin‐Nolan,
  • Anping Chen,
  • Melinda D. Smith

DOI
https://doi.org/10.1002/ecs2.4253
Journal volume & issue
Vol. 13, no. 10
pp. n/a – n/a

Abstract

Read online

Abstract Determining how local and environmental conditions affect community assembly processes is critical to understanding and preserving ecosystem functions. A combination of plant traits is required to capture the broad spectrum of strategies that species employ to respond to varying environmental conditions. The trait hypervolume (i.e., n‐dimensional trait space) accurately describes such multi‐trait characteristics. Here we use hypervolume mismatch metric, defined as the difference between the observed trait hypervolume and the trait hypervolume inferred from local and/or regional species pools, to investigate plant community assembly. Our method suggests plant traits should be categorized a priori to quantify trait hypervolumes associated with environmental variation (i.e., resource utilization strategies). Using the plant trait data from North American and South African grassland communities, this hypervolume mismatch metric can be applied to different categories of traits and scales, thus providing new insights into community assembly processes. For example, the trait hypervolumes calculated from physiological traits (e.g., mean stomatal length, stomatal pore index, and mean stomatal density) were highly correlated with regional environmental factors. By contrast, local species pool factors explained a greater proportion of variation in hypervolumes estimated from leaf stoichiometric traits (e.g., leaf nitrogen [N] content, leaf carbon [C] content, and leaf C/N ratio). Therefore, this hypervolume mismatch framework can accurately identify the separate impacts of regional versus local species pools on community assembly across environmental gradients.

Keywords