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Good modelling practice in ecology, the hierarchical Bayesian perspective

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  • White, Philip A.
  • Gelfand, Alan E.
  • Frye, Henry
  • Silander, John A.

Abstract

Ecological modelling often involves addressing challenges such as dependence in responses, e.g., spatial and/or temporal correlation, heterogeneity of variance, and hierarchical structures inherent in ecological processes and data. A constant challenge is the inadequacy of the data to well address the questions of interest. What is observable may not be sufficiently informative. What has been observed may not have been well designed. Carefully conceived modelling can take us to improved inference compared with adopting standard inference tools like basic regression and analysis of variance. Hierarchical modelling techniques provide a powerful framework for capturing these complexities by explicitly modelling the multi-level structure of ecological systems.

Suggested Citation

  • White, Philip A. & Gelfand, Alan E. & Frye, Henry & Silander, John A., 2024. "Good modelling practice in ecology, the hierarchical Bayesian perspective," Ecological Modelling, Elsevier, vol. 496(C).
    • Handle: RePEc:eee:ecomod:v:496:y:2024:i:c:s0304380024002357
    DOI: 10.1016/j.ecolmodel.2024.110847
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