Dissecting impacts of phenological shifts for performance across biological scales
Although phenological shifts in response to climate are often assumed to benefit species’ performance and viability, phenology’s role in allowing population persistence and mediating species-level responses in the face of climate change remain unclear. Here, we develop a framework to understand when...
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Veröffentlicht in: | Trends in ecology & evolution (Amsterdam) 2022-02, Vol.37 (2), p.147-157 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Although phenological shifts in response to climate are often assumed to benefit species’ performance and viability, phenology’s role in allowing population persistence and mediating species-level responses in the face of climate change remain unclear. Here, we develop a framework to understand when and why phenological shifts at three biological scales will influence performance: individuals, populations, and macroecological patterns. Specifically, we highlight three underexplored assumptions: (i) individual variability in phenology does not affect population fitness; (ii) population growth rates are sensitive to vital rates affected by phenology; and (iii) phenology mediates species-level responses to climate change including patterns of extinction, invasion, and range shifts. We outline promising methods for understanding how phenological shifts will influence performance within and across biological scales.
Phenological shifts are commonly assumed to benefit performance of individuals, populations, and species, but few studies have linked phenological shifts to performance across biological scales despite the relevance for conservation.Doing so will require investigating several key understudied mechanisms in the phenology literature: the effect of shifting phenological variance among individuals, the demographic consequences of phenology for population persistence, and the role of phenology in driving species’ extirpation or expansion.Future studies should use individual-based data, demographic models, and comparative approaches that leverage long-term demographic and phenological datasets paired with relevant experimental manipulations. |
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ISSN: | 0169-5347 1872-8383 |
DOI: | 10.1016/j.tree.2021.10.004 |