Mapping queen snapper (Etelis oculatus) suitable habitat in Puerto Rico using ensemble species distribution modeling
Katherine E Overly1,2, Vincent Lecours2,3
1Technical and Engineering Support Alliance, National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Southeast Fisheries Science Center, Panama City, Florida, United States of America.
Plos One
|February 26, 2024
Summary
This study used ensemble species distribution modeling to map queen snapper (Etelis oculatus) habitats in Puerto Rico. The models accurately predict queen snapper distribution, identifying key bathymetric features crucial for essential fish habitat.
Area of Science:
- Marine Ecology
- Fisheries Management
- Geospatial Analysis
Background:
- Queen snapper (Etelis oculatus) is a commercially important species in Puerto Rico, yet data-deficient regarding its population dynamics and habitat.
- Expanding fishing into deeper waters necessitates identifying essential fish habitats (EFH) for deep-sea species like queen snapper.
- Accurate distribution data is critical for effective management and conservation of queen snapper in the U.S. Caribbean.
Purpose of the Study:
- To predict the distribution of queen snapper along the coast of Puerto Rico using ensemble species distribution modeling (ESDM).
- To identify key environmental predictors, particularly bathymetry, influencing queen snapper habitat suitability.
- To provide a foundation for long-term monitoring programs and the determination of EFH for queen snapper.
Main Methods:
- Utilized occurrence data and terrain attributes from bathymetric datasets at varying resolutions (30 m and 8 m).
- Developed regional species distribution models using seven algorithms, then combined the best-performing models into ESDMs.
- Evaluated model performance using AUC and Kappa statistics, achieving 'excellent' predictive capability and 'substantial agreement'.
Main Results:
- All ESDMs demonstrated excellent predictive capability (AUC > 0.8) and substantial agreement (Kappa > 0.7).
- Bathymetry was consistently a top predictor of suitable queen snapper habitat across different spatial resolutions.
- Positive detections were localized around significant bathymetric features such as seamounts and ridges, indicating regional distribution patterns.
Conclusions:
- ESDM is a powerful tool for predicting the distribution of data-deficient deep-sea species like queen snapper.
- Bathymetric features are critical determinants of queen snapper habitat, guiding future EFH identification.
- The study provides essential spatial data to inform fisheries management and conservation efforts for queen snapper in Puerto Rico.
