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Selecting ecological models using multi-objective optimization

May 14, 2019

Choices in ecological research and natural resource management require balancing multiple, often competing objectives. Examples include maximizing species persistence in a wildlife conservation context, while minimizing cost, or balancing opposing stakeholder objectives when managing wildlife populations. Multiple-objective optimization (MOO) provides a unifying framework for solving multiple objective problems. Model selection is a critical component of ecological inference and prediction and requires balancing the competing objectives of model fit and model complexity. The tradeoff between model fit and model complexity provides a basis for describing the model-selection problem within the MOO framework. We discuss MOO and two strategies for solving the MOO problem; modeling preferences pre-optimization and post-optimization. Most conventional model selection methods can be formulated as solutions of MOO problems via specification of pre-optimization preferences. We reconcile model selection within the MOO framework. We also consider model selection using post-optimization specification of preferences. That is, by first identifying Pareto optimal solutions, and then selecting among them. We demonstrate concepts with an ecological application of model selection using avian species richness data in the continental United States.

    Publication Year 2019
    Title Selecting ecological models using multi-objective optimization
    DOI 10.1016/j.ecolmodel.2019.04.012
    Authors Perry J. Williams, William L. Kendall, Mevin Hooten
    Publication Type Article
    Publication Subtype Journal Article
    Series Title Ecological Modelling
    Index ID 70215205
    Record Source USGS Publications Warehouse
    USGS Organization Coop Res Unit Seattle