Sea Turtle Nesting Species Distribution Modeling

This research involves a suite of projects leveraging a 22-year dataset of sea turtle nesting activity from Escambia County, Florida to examine spatial patterns and environmental controls on nesting behavior.

Together, these projects link spatial statistics, geomorphology, and long-term ecological data to better understand sea turtle nesting behavior and support habitat conservation and coastal management in dynamic beach–dune environments.

Projects:

Spatial-Temporal Analysis

A core component of this project applies geospatial cluster analysis to identify persistent nesting hotspots and evaluate how nesting distributions vary across developed and undeveloped coastlines. These patterns are further explored through time-series analyses to assess interannual variability and longer-term trends in nesting activity.

  • Space–Time Mapping and Identification of Sea Turtle Nesting Clusters on Pensacola Beach and Gulf Islands National Seashore, Florida

    • Published (2026). Southeastern Geographer, 66 (2), 152-180.
    • Sea turtle nesting behavior along Florida’s western panhandle remains poorly characterized despite its ecological importance and management relevance. We analyzed twenty-two years (1998–2020) of nesting data from Santa Rosa Island and Perdido Key to quantify spatial and temporal clustering in a low-density region (average 1.7 nests/km). Using Optimized Hot Spot Analysis (OHSA), Emerging Hot Spot Analysis (EHSA), and a three-dimensional Space–Time Cube (STC) in ArcGIS Pro, we detected statistically significant spatial clusters and temporal transitions in nesting. OHSA revealed three persistent hotspots—in central Perdido Key, eastern Pensacola Beach near Portofino, and Opal Beach—and four cold spots associated with developed or disturbed beaches. EHSA and STC showed early cold spots (2000–2012) aligning with major disturbances (the 2004–2005 hurricanes and the 2010 Deepwater Horizon oil spill), followed by widespread, persistent hotspots after 2012 as geomorphic conditions stabilized and nesting abundance increased. Collectively, these analyses indicate that nesting is strongly non-random, with persistent high-use areas distributed across the region. Patterns are shaped by beach morphology, disturbance history, development pressure, and changes in nesting population size. Integrating multi-temporal spatial analyses provides a scalable framework for monitoring coastal habitat recovery and guiding adaptive management of vulnerable sea turtle nesting environments.

  • Time-Series Analysis

Presence–Pseudo-Absence

Another major focus quantifies the influence of beach and dune geomorphology on nest-site selection. By integrating high-resolution topographic data with both presence and pseudo-absence nesting data, this work evaluates how physical landscape characteristics shape nesting probability at fine spatial scales. A complementary effort expands this framework by incorporating nested data structures that include both successful nests and false crawls, providing additional insight into the decision-making process underlying nesting attempts.

  • Modeling Sea Turtle Nesting Probability: Evaluating Loggerhead Nest Site Selection Using Presence–Pseudo-Absence Data.

    • In Review (2026). Ecosphere
    • Sea turtle nesting populations face growing threats from climate change, sea-level rise, and coastal development. Understanding how beach morphology influences nest-site selection is essential for effective conservation planning. This study examines loggerhead (Caretta caretta) nesting preferences on Santa Rosa Island and Perdido Key, Florida-an underutilized nesting region-using high-resolution LiDAR data from 2016 and 2020. Nest locations were paired with an equal number of pseudo-absence points, and five morphological variables were extracted: beach slope, foreshore slope, dune height, nest elevation, and nest distance from the mean higher high-water line. Logistic regression models (adjusted and unadjusted) identified nest elevation as the only variable consistently associated with nest presence, particularly in 2016. In contrast, elevation was not significant in 2020, highlighting annual variability in nesting cues. No other individual variable were significant across both years. Paired interaction analyses revealed a statistically significant and strong positive relationship between nest elevation and dune height, indicating that taller dunes increased the likelihood of nesting at higher elevations. Nest distance also significantly interacted with both dune height and beach slope, with inland nesting patterns more pronounced on steeper beaches and in areas with taller dunes. However, the positive effect of dune height weakened as beach slope increased, suggesting a trade-off between slope steepness and dune accessibility. Foreshore slope showed no meaningful direct or interactive effects. These findings highlight the complex and interrelated influences of beach morphology on nesting behavior, suggesting that loggerheads are flexible nesters across a range of physical settings but selectively respond to elevation-especially when paired with protective dune features. Conservation strategies that preserve or restore elevated nesting zones and dune structures may improve nesting success and enhance resilience in low-density nesting areas like the Florida Panhandle.

  • Multi-Ratio Presence–Pseudo-Absence AnLysis of Sea Turtle Nesting Site Selection

  • Simulation of Nesting Probability Based on Multi-Ratio Presence–Pseudo-Absence Data