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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. [ABSTRACT FROM AUTHOR]

Seafood is an essential source of protein for more than 3 billion people worldwide, yet bycatch of threatened species in capture fisheries remains a major impediment to fisheries sustainability. Management measures designed to reduce bycatch often result in significant economic losses and even fisheries closures. Static spatial management approaches can also be rendered ineffective by environmental variability and climate change, as productive habitats shift and introduce new interactions between human activities and protected species. We introduce a new multispecies and dynamic approach that uses daily satellite data to track ocean features and aligns scales of management, species movement, and fisheries. To accomplish this, we create species distribution models for one target species and three bycatch-sensitive species using both satellite telemetry and fisheries observer data. We then integrate species-specific probabilities of occurrence into a single predictive surface, weighing the contribution of each species by management concern. We find that dynamic closures could be 2 to 10 times smaller than existing static closures while still providing adequate protection of endangered nontarget species. Our results highlight the opportunity to implement near real-time management strategies that would both support economically viable fisheries and meet mandated conservation objectives in the face of changing ocean conditions. With recent advances in eco-informatics, dynamic management provides a new climate-ready approach to support sustainable fisheries.

GLO:KQE/01jan21:mms12757-gra-0001.jpg PHOTO (COLOR): . gl B Thomas F. Norris1965-2020 b Our friend and colleague, Thomas F. Norris, passed away peacefully in San Diego, California, on September 9, 2020, after a 7-month battle with pancreatic cancer. 13 Norris, T., Martin, S. W., Yack, T. M., Thomas, L., & Oswald, J. (2011). 17 Norris, T., Yack, T. M., Martin, S., Oswald, J. N., Cummins, A. J., & Thomas, L. (2010b). [Extracted from the article]