Topological Analysis and the Impact of Ecological Anomalies on Sea Turtle Hatching Success

Sea turtle hatching success is influenced by a complex combination of environmental, biological, and anthropogenic factors, making it essential to understand its dynamics for effective conservation planning. This study utilizes Ball Mapper, a topological data analysis (TDA) tool, alongside the Isolation Forest anomaly detection algorithm to investigate 10 years (2013–2023) of high-dimensional ecological data from a coastal sea turtle nesting site. The dataset includes monthly records of hatch rates, predator activity, fungal presence, and flooding events. The Ball Mapper topological graphs revealed consistent seasonal trends, with April, May, and June exhibiting the highest hatching success across years. Meanwhile, months like January and February showed consistently lower outcomes and shared structural similarities in the data topology. Isolation Forest identified months with extreme ecological stressors as anomalies; however, months such as May and June 2016 still achieved high hatching success, suggesting that the presence of some predators may have also played a role in natural biocontrol. The TDA and anomaly-based approaches provided a better understanding of the complex relationships driving hatching success, uncovering patterns not easily detected by conventional methods. By visualizing temporal and ecological variation in hatching outcomes, the research supports data-driven strategies to enhance sea turtle conservation in the face of increasing environmental variability and ecological pressure.