Jones, Faith
- Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences
- University of British Columbia
Research article2024Peer reviewed
Morales-Castilla, Ignacio; Davies, T. J.; Legault, Geoffrey; Buonaiuto, D. M.; Chamberlain, Catherine J.; Ettinger, Ailene K.; Garner, Mira; Jones, Faith A. M.; Loughnan, Deirdre; Pearse, William D.; Sodhi, Darwin S.; Wolkovich, E. M.
The ability to adapt to climate change requires accurate ecological forecasting. Current forecasts, however, have failed to capture important variability in biological responses, especially across species. Here we present a new method using Bayesian hierarchical phylogenetic models and show that species-level differences are larger than the average differences between cues. Applying our method to phenological experiments manipulating temperature and day length we show an underlying phylogenetic structure in plant phenological responses to temperature cues, whereas responses to photoperiod appear weaker, more uniform across species and less phylogenetically constrained. We thus illustrate how a focus on certain clades can bias prediction, but that predictions may be improved by integrating information on phylogeny to better estimate species-level responses. Our approach provides an advance in ecological forecasting, with implications for predicting the impacts of climate change and other anthropogenic forces on ecosystems.The authors demonstrate that integrating phenology data with evolutionary relationships can improve predictions of change. They show how including phylogenetic structure in plant responses to temperature produces better estimates and reveals markedly different responses across species.
Nature Climate Change
2024, volume: 14, number: 9, pages: 989–995
Publisher: NATURE PORTFOLIO
Ecology
Climate Science
https://res.slu.se/id/publ/131360