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A road map for integrating eco-evolutionary processes into biodiversity models.

Wilfried Thuiller1, Tamara Münkemüller, Sébastien Lavergne

  • 1Laboratoire d'Ecologie Alpine, UMR CNRS 5553, Université J. Fourier, Grenoble I, BP 53, Grenoble Cedex 9, 38041, France. wilfried.thuiller@ujf-grenoble.fr

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Summary

Biodiversity models need to integrate ecological and evolutionary processes for accurate future distribution predictions. This study proposes a novel eco-evolutionary modelling framework to improve reliability and understanding of species dynamics.

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Area of Science:

  • Ecology and evolutionary biology
  • Biodiversity modeling
  • Ecological forecasting

Background:

  • Current biodiversity models often fail to incorporate crucial ecological and evolutionary processes.
  • This limitation hinders accurate predictions of species ranges and community structures.
  • There is a growing demand for reliable projections of future biodiversity distribution.

Purpose of the Study:

  • To review essential eco-evolutionary processes for biodiversity distribution modeling.
  • To identify limitations in current modeling approaches.
  • To propose an integrated modeling framework for improved predictions.

Main Methods:

  • Review of key eco-evolutionary processes and their interactions.
  • Identification of theoretical, quantitative, and data-related gaps in current modeling.
  • Development of a novel integrated species distribution model based on metapopulation theory.

Main Results:

  • Existing biodiversity models lack integration of key eco-evolutionary dynamics.
  • A strong theoretical foundation is crucial for developing tractable and reliable models.
  • A new model integrating abiotic constraints, dispersal, biotic interactions, and evolution is presented.

Conclusions:

  • An integrated eco-evolutionary modeling framework is essential for reliable biodiversity projections.
  • The proposed model offers a more comprehensive approach to understanding species distribution under environmental change.
  • Further research and model development are encouraged to advance the field.