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Setting an evolutionary trap: could the hider strategy be maladaptive for white-tailed deer?

M. Colter Chitwood; Marcus A. Lashley; Christopher E. Moorman; Christopher S. DePerno
Journal of Ethology · Vol. 35, Issue 3 · pp. 251-257 · 2017

Abstract

An evolutionary trap occurs when an organism makes a formerly adaptive decision that now results in a maladaptive outcome. Such traps can be induced by anthropogenic environmental changes, with nonnative species introductions being a leading cause. The recent establishment of coyotes ( Canis latrans ) into the southeastern USA has the potential to change white-tailed deer ( Odocoileus virginianus ) population dynamics through direct predation and behavioral adaptation. We used movement rate and bedsite characteristics of radiocollared neonates to evaluate their antipredator strategies in the context of novel predation risk in a structurally homogeneous, fire-maintained ecosystem. Neonate bedsites had greater plant cover values compared with random sites ( t = 30.136; p < 0.001), indicating bedsite selection was consistent with the hider strategy used to avoid predation. We determined selection gradients of coyote predation on neonate movement rate and plant cover and diversity at bedsites during the first 10 days of life. Interestingly, neonates that moved less and bedded in denser cover were more likely to be depredated by coyotes, meaning that greater neonate movement rate and bedsites located in less dense cover were favored by natural selection. These results are counter to expected antipredator strategies in white-tailed deer and exemplify how an adaptive response could be maladaptive in novel contexts.

Bibliographic Information

JournalJournal of Ethology
PublisherSpringer
Publication Date2017-09-01
Publication Year2017
Volume35
Issue3
Pages251-257
Document TypeJournal Article
Print ISSN0289-0771
eISSN1439-5444
DOI10.1007/s10164-017-0514-z

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NARA Access Coverage1983-01-01~Current
Journal Homepagehttps://www.springer.com/journal/10164
Publisher PageOpen Publisher Page
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