Influences of environmental and individual-level covariates on movement behaviour in American lobster Homarus americanus

Cassandra A. Konecny,David Cote,Jeremy Broome, Jean-Marc Nicolas,Paul M. Regular,Adam M. Cook, Fatemeh Hatefi

MARINE ECOLOGY PROGRESS SERIES(2024)

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摘要
Movements reflect important activities and life history events for animals, and therefore understanding what influences movement in organisms is increasingly important as climate change alters environmental conditions at unprecedented rates. This has relevance for predicting the effects of climate change on fitness and interpreting stock status of species such as American lobster Homarus americanus, whose catchability is behaviourally mediated. We analysed movement tracks from tagged lobsters in a natural environment over short (10 d, n = 37) and long timescales (up to 7 mo, n = 16), applying hidden Markov models to investigate the influence of individual-level and environmental covariates on movement patterns. We classified movement tracks to identify behavioural states through time and compared the distribution of states across habitats to understand how movement may relate to bottom composition. In the short-term analysis, we found evidence for 3 behavioural states: Sheltered, Exploratory, and Transit. In the long-term analysis, we found evidence of Sheltered and Exploratory states, but the Transit state was absent. Movement parameters varied across temperature, with higher velocities and more tortuous movements at higher temperatures. Our results demonstrate that lobsters spend most of their time Sheltered, with state probabilities being altered by diel period, time since release, sex, carapace length, temperature, and tide trend. Further, mobile states were typically observed in areas of low algal cover. Our results underscore the importance of environmental and individual-level factors in understanding lobster movement and suggest that such factors could obscure population depletion if not accounted for in a warming environment.
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关键词
Hidden Markov models,Telemetry,Habitat,Temperature,Diel cycle,Tagging effects
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