4.5 Article

Effects of conditionally expressed phenotypes and environment on amphibian dispersal in nature

期刊

OIKOS
卷 127, 期 8, 页码 1142-1151

出版社

WILEY
DOI: 10.1111/oik.05276

关键词

dispersal; complex life cycles; Ambystoma annulatum; condition-dependent; exploration; PIT telemetry

类别

资金

  1. Dept of Defense [SERDP RC-2155]
  2. Univ. of Missouri Research Council [URC-13-087]
  3. National Science Foundation [DEB-0943941]
  4. Life Sciences Fellowship

向作者/读者索取更多资源

Individuals vary greatly in the distance they disperse, and in doing so, strongly affect ecological and evolutionary processes. Dispersal, when viewed as a component of phenotype, can be affected independently or jointly by environment. However, among taxa with complex life cycles that occupy different habitats over ontogeny, the effects of environment on dispersal and the interaction between environment and phenotype remains poorly understood. Here, we conducted a field experiment to measure how dispersal distance was affected by phenotype, environment experienced before and after metamorphosis, and their interaction. We manipulated the environment encountered by a pond-breeding salamander Ambystoma annulatum during the aquatic larval stage and again as dispersing terrestrial juveniles. After assaying juvenile phenotype (exploration behavior, body condition, and morphology), we then measured the initial distance dispersed by juveniles. The distance moved by dispersing salamanders was affected by attributes of both larval and juvenile habitat, with salamanders that encountered low quality habitat in either life stage moving the farthest. However, we did not find support for an interactive effect of phenotype and environment affecting the distance moved by dispersers. Interestingly, exploration behavior explained the distance moved by philopatric animals but not dispersing ones. Our findings indicate that the environment experienced before metamorphosis can affect juvenile dispersal behavior, and demonstrates the need to consider dispersal in species with complex life cycles to understand the coupling between local and regional population dynamics.

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