Journal
ECOLOGY LETTERS
Volume 23, Issue 4, Pages 588-597Publisher
WILEY
DOI: 10.1111/ele.13459
Keywords
Bayesian population model; carry-over effects; demography; factor-analytic models; seasonal structured population models; viability
Categories
Funding
- ERC [33785]
- Swiss National Science Foundation [31003A_182286]
- Spanish Ministry of Economy and Competitiveness Juan de la Cierva-Formacion grant [FJCI-2017-32893]
- National Geographic Society [8140-06]
- UCLA Faculty Senate
- UCLA Division of Life Sciences
- RMBL research fellowship
- National Science Foundation [IDBR-0754247, DEB-1119660, 1557130, DBI 0242960, 0731346, 1226713]
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Natural populations are exposed to seasonal variation in environmental factors that simultaneously affect several demographic rates (survival, development and reproduction). The resulting covariation in these rates determines population dynamics, but accounting for its numerous biotic and abiotic drivers is a significant challenge. Here, we use a factor-analytic approach to capture partially unobserved drivers of seasonal population dynamics. We use 40 years of individual-based demography from yellow-bellied marmots (Marmota flaviventer) to fit and project population models that account for seasonal demographic covariation using a latent variable. We show that this latent variable, by producing positive covariation among winter demographic rates, depicts a measure of environmental quality. Simultaneously, negative responses of winter survival and reproductive-status change to declining environmental quality result in a higher risk of population quasi-extinction, regardless of summer demography where recruitment takes place. We demonstrate how complex environmental processes can be summarized to understand population persistence in seasonal environments.
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