ABSTRACT

Sea turtle species observed nesting at the US Naval Station at Guantanamo Bay, Cuba (GTMO) include greens (Chelonia mydas) and hawksbills (Eretmochelys imbricata), both of which are classified as endangered by the World Conservation Union (IUCN). As Cuba and its neighbors continue to develop their coasts, all efforts should be made to preserve this important nesting refuge. Habitat suitability index models are one tool with which managers can generate hypotheses and experiment with management options. This study used an observational dataset of nests and measured habitat variables to develop habitat suitability index models in a geographic information system. The first objective was to compare the performance of 3 different habitat model-building approaches in order to determine which technique, if any, provides reliable information on sea turtle nesting habitat preferences. A habitat suitability index score for each beach zone was computed using 1) suitability indices with expert weights, 2) unscaled environmental variables with regression-based weights, and 3) a combination of suitability indices with regression-based weights. The second objective was to use the models to lend insight into important environmental descriptors of suitable sea turtle habitat for GTMO. All models predicted moderately well with 40% prediction rates, even though they assigned different weights to the variables. Moderate model performance may be attributed to low samples sizes and/or nest site fidelity that is unrelated to environmental factors. Overall, differences between empirical and expert model results reflect a shift from a regional (Caribbean) to a local scale of analysis (GTMO). However, in all models, compaction of the substrate was almost twice as influential as the other variables, indicating that the looser the sand, the more suitable the habitat. Conservation implications and suggestions for future research are discussed.

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