Incorporating responses of traits to changing climates into species distribution models: a path forward
Conventional species distribution models (SDMs) typically consider only abiotic factors, thus overlooking critical biotic dimensions, including traits that play an important role in determining species' distributions in changing environments. Process-based trait SDMs explicitly incorporate traits and have been applied to SDMs. However, their parameterization can be complex and require data that are unavailable for most species. Recently developed hierarchical trait-based SDMs use widely available data and facilitate the incorporation of traits into SDMs at broad temporal, spatial, and taxonomic scales. However, despite their promise, existing hierarchical trait-based SDMs fail to accommodate changing trait spaces under different climate conditions. Here, we provide a new, simplified framework for hierarchical trait-based SDMs that integrates individuals' trait responses into forecasts of species range shifts in response to ongoing climate changes. We further briefly discuss the issue of non-independence among species in hierarchical trait-based SDMs. This work will contribute to an improved understanding of how traits affect species distributions along environmental and temporal gradients and facilitate the application of trait-based SDMs at large scales under future climate change.
Authors
- Shijia Peng (ORCID: https://orcid.org/0000-0002-3510-119X)
- Aaron M. Ellison (ORCID: https://orcid.org/0000-0003-4151-6081)
- Charles C. Davis (ORCID: https://orcid.org/0000-0001-8747-1101)
Institutions
- Harvard University (US)
- Harvard University Press (US)
- University of Oxford (GB)
- Evolutionary Genomics (United States) (US)
- Skyre (United States) (US)
Publication Details
- Journal
- New Phytologist
- Published
- 2025-07-26
- DOI
- https://doi.org/10.1111/nph.70402
- Citations
- 1
- Primary Topic
- Species Distribution and Climate Change
- Type
- article
- Field-Weighted Citation Impact
- 1.84
Funders
- National Science Foundation