Since 1930, the University of Michigan has maintained the Edwin S. George Reserve (ESGR) for the purposes of providing research and education opportunities in the natural sciences and preserving the native flora and fauna. The ESGR is a 525-hectare (ca. 1300 acre) fenced preserve located in Livingston County, Michigan (about 25 miles Northwest of Ann Arbor), which was presented to the University as a gift by Edwin S. George in 1930. The ESGR is characterized by a rugged moraine and basin topography supporting a rich fauna and flora (species lists). The ESGR is administered by the Department of Ecology and Evolutionary Biology at the University of Michigan.

A permutation test and spatial cross-validation approach to assess models of interspecific competition between trees

TitleA permutation test and spatial cross-validation approach to assess models of interspecific competition between trees
Publication TypeJournal Article
Year of Publication2020
AuthorsAllen D, Kim AY
Secondary AuthorsYang J
JournalPLOS ONE
Volume15213416921642797121352939174044823311127
Issue324122113112758519843117104112
Paginatione0229930
Date PublishedNov-03-2020
Abstract

Measuring species-specific competitive interactions is key to understanding plant communities. Repeat censused large forest dynamics plots offer an ideal setting to measure these interactions by estimating the species-specific competitive effect on neighboring tree growth. Estimating these interaction values can be difficult, however, because the number of them grows with the square of the number of species. Furthermore, confidence in the estimates can be overestimated if any spatial structure of model errors is not considered. Here we measured these interactions in a forest dynamics plot in a transitional oak-hickory forest. We analytically fit Bayesian linear regression models of annual tree radial growth as a function of that tree’s species, its size, and its neighboring trees. We then compared these models to test whether the identity of a tree’s neighbors matters and if so at what level: based on trait grouping, based on phylogenetic family, or based on species. We used a spatial cross-validation scheme to better estimate model errors while avoiding potentially over-fitting our models. Since our model is analytically solvable we can rapidly evaluate it, which allows our proposed cross-validation scheme to be computationally feasible. We found that the identity of the focal and competitor trees mattered for competitive interactions, but surprisingly, identity mattered at the family rather than species-level.

URLhttps://dx.plos.org/10.1371/journal.pone.0229930
DOI10.1371/journal.pone.022993010.1371
Short TitlePLoS ONE
Related research sites: