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Resolving the biodiversity paradox.

James S Clark1, Mike Dietze, Sukhendu Chakraborty

  • 1Nicholas School of the Environment, Duke University, Durham, NC 27708, USA. jimclark@duke.edu

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|June 28, 2007
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Summary

High-dimensional differences among species, quantified by random individual and temporal effects (RITES), explain ecological community stability. This resolves the biodiversity paradox, contrasting with traditional low-dimensional tradeoffs and neutral models.

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Area of Science:

  • Ecology
  • Theoretical Ecology
  • Biodiversity Science

Background:

  • The biodiversity paradox highlights the conflict between mathematical predictions of species differences for coexistence and observed ecological stability.
  • Existing explanations include low-dimensional tradeoffs (e.g., colonization-competition, resource competition) and neutral theory, which assumes species differences are irrelevant.

Purpose of the Study:

  • To demonstrate that neither low-dimensional tradeoffs nor neutrality adequately resolve the biodiversity paradox.
  • To propose and support a high-dimensional framework for understanding species coexistence and ecological stability.

Main Methods:

  • Critically evaluate traditional low-dimensional tradeoff and neutral models, focusing on their interpretation of stochasticity.
  • Apply new hierarchical modeling techniques to infer high-dimensional species differences using random individual and temporal effects (RITES).

Main Results:

  • Traditional models fail to predict coexistence due to misinterpretation of stochasticity and insufficient dimensionality.
  • RITES reveal substantial high-dimensional variation among species, representing unobserved differences crucial for coexistence.
  • High-dimensional coexistence provides a more robust explanation than low-dimensional tradeoffs or neutral assumptions.

Conclusions:

  • The biodiversity paradox is best explained by high-dimensional species differences, not simple tradeoffs or neutrality.
  • RITES offer a powerful method for quantifying these complex differences and understanding community stability.
  • This framework reconciles theoretical predictions with empirical observations of diverse and stable ecosystems.