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• W4383500685 abstract "Abstract Species distribution models (SDMs) have been central for documenting the relationship between species’ geographic ranges and environmental conditions for more than two decades. However, the vast majority of SDMs rarely consider functional traits, such as phenology, which strongly affect species’ demography and fitness. Using >120,000 herbarium specimens representing 360 plant species across the eastern United States, we developed a novel “phenology-informed” SDM that integrates dynamic phenological responses to changing climates. Compared to standard SDMs based only on abiotic variables, our phenology-informed SDMs forecast significantly lower species habitat loss and less species turnover within communities under climate change. These results suggest that phenotypic plasticity or local adaptation in phenology may help many species adjust their ecological niches and persist in their habitats during periods of rapid environmental change. By modeling historical data that link phenology, climate, and species distributions, our findings reveal how species’ reproductive phenology mediates their geographic distributions along environmental gradients and affects regional biodiversity patterns in the face of future climate change. More importantly, our newly developed model also circumvents the need for mechanistic models that explicitly link traits to occurrences for each species, thus better facilitating the deployment of trait-based SDMs across unprecedented spatial and taxonomic scales." @default.
• W4383500685 created "2023-07-08" @default.
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• W4383500685 date "2023-07-07" @default.
• W4383500685 modified "2023-10-18" @default.
• W4383500685 title "Phenologically-informed species distribution models (SDMs) forecast less species loss and turnover versus standard SDMs" @default.
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• W4383500685 doi "https://doi.org/10.1101/2023.07.05.547862" @default.
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