Outstanding Challenges in the Transferability of Ecological Models
- PMID: 30166069
- DOI: 10.1016/j.tree.2018.08.001
Outstanding Challenges in the Transferability of Ecological Models
Abstract
Predictive models are central to many scientific disciplines and vital for informing management in a rapidly changing world. However, limited understanding of the accuracy and precision of models transferred to novel conditions (their 'transferability') undermines confidence in their predictions. Here, 50 experts identified priority knowledge gaps which, if filled, will most improve model transfers. These are summarized into six technical and six fundamental challenges, which underlie the combined need to intensify research on the determinants of ecological predictability, including species traits and data quality, and develop best practices for transferring models. Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions.
Keywords: Predictive modeling; extrapolation; generality; habitat models; model transfers; species distribution models; uncertainty.
Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.
Comment in
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Transferability of Mechanistic Ecological Models Is About Emergence.Trends Ecol Evol. 2019 Jun;34(6):487-488. doi: 10.1016/j.tree.2019.01.010. Epub 2019 Feb 19. Trends Ecol Evol. 2019. PMID: 30795841 No abstract available.
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Better Model Transfers Require Knowledge of Mechanisms.Trends Ecol Evol. 2019 Jun;34(6):489-490. doi: 10.1016/j.tree.2019.04.006. Epub 2019 May 2. Trends Ecol Evol. 2019. PMID: 31054858 No abstract available.
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