2026/05/01 by Jaime Restrepo, Dina Nisthar, Wei Khang Heng +10 · 1 voice
Environmental Science · #Avian ecology and behavior #Turtle Biology and Conservation #Wildlife Ecology and Conservation
paper · doi:10.1111/ddi.70196
openalex created_date 2025/10/10 · openalex publication_date 2026/05/01 · openalex updated_date 2026/07/28
ABSTRACT Aim Green turtles are a widely distributed and highly migratory species; despite extensive data on their movement, there is no species‐specific global synthesis on the subject. Based on three decades of published literature and building on previous global analyses, we developed a global network model of migratory connectivity for green turtles to better understand their spatial biology. Location Global. Time Period 1990–2022. Major Taxa Studied Green Sea Turtle ( Chelonia mydas ). Methods We conducted a structured literature review extracting georeferenced information on the movement of green turtles from 1990 to 2022, aggregating this information into a single connectivity model, defining nodes of connectivity. We evaluated connectivity routes from nesting areas to foraging sites for each RMU, identifying trajectories moving outside and across the boundaries of these areas. Results We found a total of 113 sources informing migratory connectivity globally. We identified 474 sites, representing locations where green turtles were observed (124 being nesting sites). Migratory connections, derived from both long‐term (≥ 1 year) and short‐term (< 12 months) tracking data, ranged from resident turtles that never left their nesting sites to rookeries connected to as many as 20 different locations, some over 5000 km apart. This long‐distance connectivity exposes populations to threats across disparate locations. Most connections traversed national jurisdictions, including crossing different Regional Management Units. Main Conclusions We compiled the largest available dataset describing movement of green turtles worldwide and present the most comprehensive global model of their migratory connectivity. This model provides ecological insights into regional differences in life histories, identifies geographic and demographic gaps in sampling, and provides baseline information on connectivity to support transboundary management of green turtle populations. The study reiterates the need for larger collaborative efforts to aggregate knowledge beyond local jurisdictions, to inform and align effective management measures to protect this historically threatened species.