Host adaptation to novel pathogen introduction: Predicting conditions that promote evolutionary rescue
Novel pathogen introduction can have drastic consequences for naive host populations, and outcomes can be difficult to predict. Evolutionary rescue (ER) provides a foundation for understanding whether hosts are driven to extinction or survive via adaptation. Currently, patterns of host population dy...
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Veröffentlicht in: | Ecology letters 2021-10, Vol.24 (10), p.2238-2255 |
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Sprache: | eng |
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Zusammenfassung: | Novel pathogen introduction can have drastic consequences for naive host populations, and outcomes can be difficult to predict. Evolutionary rescue (ER) provides a foundation for understanding whether hosts are driven to extinction or survive via adaptation. Currently, patterns of host population dynamics alongside evidence of adaptation are used to infer ER. However, the gap between established ER theory and complexity inherent in natural systems makes interpreting empirical patterns difficult because they can be confounded with ecological drivers of survival under current theory. To bridge this gap, we expand ER theory to include biological selective agents, such as pathogens. We find birth processes to be more important than previously theorised in determining ER potential. We employ a novel framework evaluating ER potential within natural systems and gain ability to identify system characteristics that make ER possible. Identifying these characteristics allows a shift from retrospective observation to a predictive mindset, and our findings suggest that ER occurrence may be more limited than previously thought. We use the plague system of Yersinia pestis infecting Cynomys ludovicianus (black‐tailed prairie dogs) and Spermophilus beecheyi (California ground squirrels) as a case study.
Evolutionary rescue (ER) provides a foundation for understanding whether hosts are driven to extinction or survive via adaptation when novel pathogens are introduced. We extend ER theory to include biological selective agents using a novel framework for evaluating ER in complex natural systems. Our framework identifies conditions under which ER can occur, and gives insight into how limited ER may be in natural host–pathogen systems. |
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ISSN: | 1461-023X 1461-0248 |
DOI: | 10.1111/ele.13845 |