Modeling the emergence of migratory corridors and foraging hot spots of the green sea turtle

Abstract

Environmental factors shape the spatial distribution and dynamics of populations. Understanding how these factors interact with movement behavior is critical for efficient conservation, in particular for migratory species. Adult female green sea turtles, Chelonia mydas, migrate between foraging and nesting sites that are generally separated by thousands of kilometers. As an emblematic endangered species, green turtles have been intensively studied, with a focus on nesting, migration, and foraging. Nevertheless, few attempts integrated these behaviors and their trade‐offs by considering the spatial configurations of foraging and nesting grounds as well as environmental heterogeneity like oceanic currents and food distribution. We developed an individual‐based model to investigate the impact of local environmental conditions on emerging migratory corridors and reproductive output and to thereby identify conservation priority sites. The model integrates movement, nesting, and foraging behavior. Despite being largely conceptual, the model captured realistic movement patterns which confirm field studies. The spatial distribution of migratory corridors and foraging hot spots was mostly constrained by features of the regional landscape, such as nesting site locations, distribution of feeding patches, and oceanic currents. These constraints also explained the mixing patterns in regional forager communities. By implementing alternative decision strategies of the turtles, we found that foraging site fidelity and nesting investment, two characteristics of green turtles' biology, are favorable strategies under unpredictable environmental conditions affecting their habitats. Based on our results, we propose specific guidelines for the regional conservation of green turtles as well as future research suggestions advancing spatial ecology of sea turtles. Being implemented in an easy to learn open‐source software, our model can coevolve with the collection and analysis of new data on energy budget and movement into a generic tool for sea turtle research and conservation. Our modeling approach could also be useful for supporting the conservation of other migratory marine animals.

Movements of Juvenile Green Turtles (Chelonia mydas) in the Nearshore Waters of the Northwestern Gulf of Mexico

“…For sea turtles, space-time analysis may lend itself most useful when applied to long-term datasets for nesting females and impacts of anthropogenic and environmental alterations to nesting beaches, as well as numerous other applications. For example, areas of hot spot clustering at nesting beaches have been documented across numerous sea turtle species (Foley et al, 2013;Baudouin et al, 2015;Dawson et al, 2017;Dalleau et al, 2019;Evans et al, 2019). Hot spot analysis identifies these areas as locations of peak activity, but space-time analysis allows for resource and conservation managers to identify specific timing of these events in relation to their location.…”

“…Juvenile sea turtles' strong fidelity to foraging areas can be used to identify critical habitat important to the health and survival of these populations. Hot spot analyses have been used to assess the density of sea turtles in a given area and to measure the extent of their location interactions across a wide range of habitats and species (Mitchell, 2005;Lucchetti et al, 2017;Dalleau et al, 2019;Evans et al, 2019). Kernel density estimation (KDE) has become a popular mapping technique as it depicts hot spots as smooth contours and provides reasonable visual representations in core (50%) and home range (95%) use areas (Seaman and Powell, 1996;Chainey et al, 2008;Hart et al, 2012;Coleman et al, 2017).…”

Seascape Genetics and the Spatial Ecology of Juvenile Green Turtles

“…Passive dispersion modeling of hatchlings from Europa indicates that water flow is expulsed from the South Mozambique Channel into (1) the Agulhas Current, and then to the South Atlantic, and (2) into the Agulhas Return Current, flowing back in the Indian Ocean along the Subtropical Convergence in cold waters (<15 • C); [71] (Appendix A; Figure A1). Hatchlings may then experience only a few potential foraging sites in the south of Madagascar and Mozambique, the Indian South African coast and Europa, all known to be foraging grounds for the green turtle [72], and then return preferentially to the few foraging grounds they have visited. Even if we expect high mortality due to cold water at dispersal, it is likely that the dispersal of green turtles may be driven by both passive drifting and active swimming to avoid such cold water, as shown by Gaspar and Lalire [31] and Lalire and Gaspar [5] for the leatherback turtle.…”

Inter-Nesting Movements, Migratory Pathways, and Resident Foraging Areas of Green Sea Turtles (Chelonia mydas) Satellite-Tagged in Southwest Florida

“…However, there can be a great deal of plasticity in each phase of this process, including migration strategy (Godley et al, 2002;Blumenthal et al, 2006;Seminoff et al, 2008;Baudouin et al, 2015;Hays et al, 2020), the extent of movement during the inter-nesting period (Hays et al, 1999); the number of days between nesting events, and foraging behavior (Hatase et al, 2006), with variability documented even within a single nesting beach. Currents (Chambault et al, 2015), learned behavior (Scott et al, 2014), water temperature (Godley et al, 2002;Hays et al, 2002;Santos et al, 2015), predator avoidance (Mettler et al, 2020), resource availability (Dalleau et al, 2019), and diel cycles (Hays et al, 1999) have been proposed to influence such behaviors.…”