High-dimensional coexistence based on individual variation: A synthesis of evidence

James S. Clark, David Bell, Chengjin Chu, Benoit Courbaud, Michael Dietze, Michelle Hersh, Janneke Hillerislambers, Inés Ibáñez, Shannon Ladeau, Sean McMahon, Jessica Metcalf, Jacqueline Mohan, Emily Moran, Luke Pangle, Scott Pearson, Carl Salk, Zehao Shen, Denis Valle, Peter Wyckoff

Research output: Contribution to journalArticlepeer-review

133 Scopus citations


High biodiversity of forests is not predicted by traditional models, and evidence for trade-offs those models require is limited. High-dimensional regulation (e.g., N factors to regulate N species) has long been recognized as a possible alternative explanation, but it has not be been seriously pursued, because only a few limiting resources are evident for trees, and analysis of multiple interactions is challenging. We develop a hierarchical model that allows us to synthesize data from long-term, experimental, data sets with processes that control growth, maturation, fecundity, and survival. We allow for uncertainty at all stages and variation among 26 000 individuals and over time, including 268 000 tree years, for dozens of tree species. We estimate population-level parameters that apply at the species level and the interactions among latent states, i.e., the demographic rates for each individual, every year. The former show that the traditional trade-offs used to explain diversity are not present. Demographic rates overlap among species, and they do not show trends consistent with maintenance of diversity by simple mechanisms (negative correlations and limiting similarity). However, estimates of latent states at the level of individuals and years demonstrate that species partition environmental variation. Correlations between responses to variation in time are high for individuals of the same species, but not for individuals of different species. We demonstrate that these relationships are pervasive, providing strong evidence that high-dimensional regulation is critical for biodiversity regulation.

Original languageEnglish (US)
Pages (from-to)569-608
Number of pages40
JournalEcological Monographs
Issue number4
StatePublished - Nov 2010
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics


  • Bayesian analysis
  • Biodiversity
  • Coexistence
  • Competition
  • Forest dynamics
  • Hierarchical models


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