Identification of distinct movement patterns in Pacific leatherback turtle populations influenced by ocean conditions

Interactions with fisheries are believed to be a major cause of mortality for adult leatherback turtles (Dermochelys coriacea), which is of particular concern in the Pacific Ocean, where they have been rapidly declining. In order to identify where these interactions are occurring and how they may be reduced, it is essential first to understand the movements and behavior of leatherback turtles. There are two regional nesting populations in the East Pacific (EP) and West Pacific (WP), comprising multiple nesting sites. We synthesized tracking data from the two populations and compared their movement patterns. A switching state-space model was applied to 135 Argos satellite tracks to account for observation error, and to distinguish between migratory and area-restricted search behaviors. The tracking data, from the largest leatherback data set ever assembled, indicated that there was a high degree of spatial segregation between EP and WP leatherbacks. Area-restricted search behavior mainly occurred in the southeast Pacific for the EP leatherbacks, whereas the WP leatherbacks had several different search areas in the California Current, central North Pacific, South China Sea, off eastern Indonesia, and off southeastern Australia. We also extracted remotely sensed oceanographic data and applied a generalized linear mixed model to determine if leatherbacks exhibited different behavior in relation to environmental variables. For the WP population, the probability of area-restricted search behavior was positively correlated with chlorophyll-a concentration. This response was less strong in the EP population, but these turtles had a higher probability of search behavior where there was greater Ekman upwelling, which may increase the transport of nutrients and consequently prey availability. These divergent responses to oceanographic conditions have implications for leatherback vulnerability to fisheries interactions and to the effects of climate change. The occurrence of leatherback turtles within both coastal and pelagic areas means they have a high risk of exposure to many different fisheries, which may be very distant from their nesting sites. The EP leatherbacks have more limited foraging grounds than the WP leatherbacks, which could make them more susceptible to any temperature or prey changes that occur in response to climate change.     

Incorporating multidimensional behavior into a risk management tool for a critically endangered and migratory species

Conservation of migratory species exhibiting wide-ranging and multidimensional behaviors is challenged by management efforts that only utilize horizontal movements or produce static spatial–temporal products. For the deep-diving, critically endangered eastern Pacific leatherback turtle, tools that predict where turtles have high risks of fisheries interactions are urgently needed to prevent further population decline. We incorporated horizontal–vertical movement model results with spatial–temporal kernel density estimates and threat data (gear-specific fishing) to develop monthly maps of spatial risk. Specifically, we applied multistate hidden Markov models to a biotelemetry data set (n = 28 leatherback tracks, 2004–2007). Tracks with dive information were used to characterize turtle behavior as belonging to 1 of 3 states (transiting, residential with mixed diving, and residential with deep diving). Recent fishing effort data from Global Fishing Watch were integrated with predicted behaviors and monthly space-use estimates to create maps of relative risk of turtle–fisheries interactions. Drifting (pelagic) longline fishing gear had the highest average monthly fishing effort in the study region, and risk indices showed this gear to also have the greatest potential for high-risk interactions with turtles in a residential, deep-diving behavioral state. Monthly relative risk surfaces for all gears and behaviors were added to South Pacific TurtleWatch (SPTW) ( https://www.upwell.org/sptw ), a dynamic management tool for this leatherback population. These modifications will refine SPTW's capability to provide important predictions of potential high-risk bycatch areas for turtles undertaking specific behaviors. Our results demonstrate how multidimensional movement data, spatial–temporal density estimates, and threat data can be used to create a unique conservation tool. These methods serve as a framework for incorporating behavior into similar tools for other aquatic, aerial, and terrestrial taxa with multidimensional movement behaviors.