Sea turtles are key species in many coastal ecosystems worldwide, particularly coral reef and seagrass habitats. Yet, six of seven species are endangered. Their nests, which incubate in beach sand and rely on specific climatic conditions for egg viability, face significant threats from inundation, for example through wave runup. This paper examines a method to rapidly predict wave runup in low-data coral reef environments, and the implications thereof on the inundation of sea turtle nests. The study uses two metamodels, BEWARE-2 and HyCReWW, to predict wave runup at Ras Baridi, Saudi Arabia, a key nesting site of the Red Sea green turtle population. The models were used to analyze runup events and inundation durations and provide a first estimate of a safe nesting elevation. Despite data limitations, the study provides valuable insights for coastal managers to protect sea turtle nests, suggesting that a 5-year return period runup elevation could serve as a threshold for nest relocation. However, the findings also highlight the importance of more accurate hydrodynamic predictions and the need for in-situ data to validate models and improve conservation strategies.

Climate change and human activity pose increasing challenges to endangered sea turtles, which are key species in many marine ecosystems worldwide. Among these challenges are the flooding and erosion of nesting beaches. In this perspective, we argue that existing methods and tools from coastal science and management hold significant, yet underused, potential for sea turtle conservation. We introduce a stepwise framework for integrating sea turtle ecology and coastal management to address these coastal threats. The framework follows an Observe–Understand–Predict–Intervene cycle and links ecological thresholds, coastal processes, and management interventions across scales, from Regional Management Units (RMUs) to individual beaches. We illustrate how state-of-the-art monitoring, modeling, and nature-based solutions (NBS) can be embedded within this framework to inform when and how to intervene. Increased in-situ data collection and interdisciplinary collaboration will be critical to apply and refine this approach, thereby enhancing the long-term resilience of nesting habitats.

Climate change and human activity threaten sea turtle nesting beaches through increased flooding and erosion. Understanding the environmental characteristics that enable nesting can aid to preserve and expand these habitats. While numerous local studies exist, a comprehensive global analysis of environmental influences on the distribution of sea turtle nesting habitats remains largely unexplored. Here, we relate the distribution of global sea turtle nesting to 22 coastal indicators, spanning hydrodynamic, atmospheric, geophysical, habitat, and human processes. Using state-of-the-art global datasets and a novel 50-km-resolution hexagonal coastline grid (Coastgons), we employ machine learning to identify spatially homogeneous patterns in the indicators and correlate these to the occurrence of nesting grounds. Our findings suggest sea surface temperature, tidal range, extreme surges, and proximity to coral and seagrass habitats significantly influence global nesting distribution. Low tidal ranges and low extreme surges appear to be particularly favorable for individual species, likely due to reduced nest flooding. Other indicators, previously reported as influential (e.g., precipitation and wind speed), were not as important in our global-scale analysis. Finally, we identify new, potentially suitable nesting regions for each species. On average, 23 % of global coastal regions between - 39 ^∘ and 48 ^∘ latitude could be suitable for nesting, while only 7 % is currently used by turtles, showing that the realized niche is significantly smaller than the fundamental niche, and that there is potential for sea turtles to expand their nesting habitat. Our results help identify suitable nesting conditions, quantify potential hazards to global nesting habitats, and lay a foundation for nature-based solutions to preserve and potentially expand these habitats.