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Spatiotemporal drivers of energy expenditure in a coastal marine fish
Authors:Email author" target="_blank">Jacob?W?BrownscombeEmail author  Steven?J?Cooke  Andy?J?Danylchuk
Institution:1.Fish Ecology and Conservation Physiology Laboratory, Ottawa-Carleton Institute for Biology,Carleton University,Ottawa,Canada;2.Department of Environmental Conservation,University of Massachusetts Amherst,Amherst,USA
Abstract:Animal behavior and energy expenditure often vary significantly across the landscape, and quantifying energy expenditure over space and time provides mechanistic insight into ecological dynamics. Yet, spatiotemporal variability in energy expenditure has rarely been explored in fully aquatic species such as fish. Our objective was to quantify spatially explicit energy expenditure for a tropical marine teleost fish, bonefish (Albula vulpes), to examine how bonefish energetics vary across landscape features and temporal factors. Using a swim tunnel respirometer, we calibrated acoustic accelerometer transmitters implanted in bonefish to estimate their metabolic rates and energy expenditure, and applied this technology in situ using a fine-scale telemetry system on a heterogeneous reef flat in Puerto Rico. Bonefish energy expenditure varied most among habitats, with significant interactions between habitat and temporal factors (i.e., diel period, tide state, season). The energy expenditure was generally highest in shallow water habitats (i.e., seagrass and reef crest). Variation in activity levels was the main driver of these differences in energy expenditure, which in shallow, nearshore habitats is likely related to foraging. Bonefish moderate energy expenditure across seasonal fluctuations in temperature, by selectively using shallow nearshore habitats at moderate water temperatures that correspond with their scope for activity. Quantifying how animals expend energy in association with environmental and ecological factors can provide important insight into behavioral ecology, with implications for bioenergetics models.
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