Andrew S. Maurer, Tomo Eguchi, Garrett E. Lemons, Robin A. LeRoux, Erin L. LaCasella, Calandra N. Turner Tomaszewicz, Megan E. Hanna, Jessica Curran, Bryant Chesney, Sheila V. Madrak, Jeffrey A. Seminoff
{"title":"Resource selection by a megaomnivore in a marine foraging habitat","authors":"Andrew S. Maurer, Tomo Eguchi, Garrett E. Lemons, Robin A. LeRoux, Erin L. LaCasella, Calandra N. Turner Tomaszewicz, Megan E. Hanna, Jessica Curran, Bryant Chesney, Sheila V. Madrak, Jeffrey A. Seminoff","doi":"10.1002/ece3.70132","DOIUrl":null,"url":null,"abstract":"<p>Habitat-based approaches to animal conservation are bolstered by an understanding of resource selection, that is, use of resources (i.e., habitat features) relative to their availability in the environment. Quantifying resource selection is especially valuable when data characterizing animal space use are limited, as is often the case with mobile and/or cryptic species. Documenting associations with habitat features can better inform management in space in time, while also revealing key insight into movement ecology and behavior. Here, we evaluate resource selection by a megaomnivore whose highly mobile nature within marine habitats has resulted in an incomplete understanding of drivers of space use. We used satellite telemetry to track 29 green turtles (<i>Chelonia mydas</i>) from an eastern Pacific foraging aggregation in San Diego Bay, California, USA during 2013–2023. Tracking produced 5023 Fastloc-GPS points which we used to model selection for local environmental resources relative to their availability. We employed logistic models to evaluate associations with seagrass, bathymetry, and water temperatures, implementing a framework that additionally allowed us to explore the roles of season, diel period, and turtle body size. Our methods demonstrate an approach for down-weighting observations according to assumed telemetry error and autocorrelation. Results from fine-scale resource selection models provide evidence that green turtles in San Diego Bay select for eelgrass meadows (<i>Zostera marina</i>), particularly during the warmest months of the year, but the strength of this selection changes from day to night. We additionally found day–night shifts in depth and temperature selection that changed with turtle body size and season. We discuss these findings in the context of diel patterns in resting and foraging behavior in addition to seasonal changes in thermally sensitive metabolic rates. Our study documents resource associations and provides quantitative information for the management of sea turtle foraging populations and their habitats. We offer key insight into habitat use by green turtles in the eastern Pacific at a pivotal time when multiple indicators point to population growth and expansion within the region.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ece3.70132","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ece3.70132","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
Habitat-based approaches to animal conservation are bolstered by an understanding of resource selection, that is, use of resources (i.e., habitat features) relative to their availability in the environment. Quantifying resource selection is especially valuable when data characterizing animal space use are limited, as is often the case with mobile and/or cryptic species. Documenting associations with habitat features can better inform management in space in time, while also revealing key insight into movement ecology and behavior. Here, we evaluate resource selection by a megaomnivore whose highly mobile nature within marine habitats has resulted in an incomplete understanding of drivers of space use. We used satellite telemetry to track 29 green turtles (Chelonia mydas) from an eastern Pacific foraging aggregation in San Diego Bay, California, USA during 2013–2023. Tracking produced 5023 Fastloc-GPS points which we used to model selection for local environmental resources relative to their availability. We employed logistic models to evaluate associations with seagrass, bathymetry, and water temperatures, implementing a framework that additionally allowed us to explore the roles of season, diel period, and turtle body size. Our methods demonstrate an approach for down-weighting observations according to assumed telemetry error and autocorrelation. Results from fine-scale resource selection models provide evidence that green turtles in San Diego Bay select for eelgrass meadows (Zostera marina), particularly during the warmest months of the year, but the strength of this selection changes from day to night. We additionally found day–night shifts in depth and temperature selection that changed with turtle body size and season. We discuss these findings in the context of diel patterns in resting and foraging behavior in addition to seasonal changes in thermally sensitive metabolic rates. Our study documents resource associations and provides quantitative information for the management of sea turtle foraging populations and their habitats. We offer key insight into habitat use by green turtles in the eastern Pacific at a pivotal time when multiple indicators point to population growth and expansion within the region.