Importance of scale in seascape habitat suitability modeling: Predicting species distributions in changing ecosystems
- 1Department of Marine Sciences University of Georgia Athens Georgia USA
- 2Present address: Department of Earth and Environment, Institute of Environment Florida International University Miami Florida USA
Abstract
Habitat suitability models (HSMs) use landscape metrics to describe patterns in species distributions, quantify the success of habitat restoration, and model species responses to change. Within a particular level of organization, the spatial scale of effect at which habitat is integrated and incorporated into HSMs can influence model performance. However, scale optimization can be time consuming and requires high‐quality data across spatial scales. As such, it is not widely applied in suitability models and is particularly rare in marine studies. In coastal and marine landscapes, or seascapes, rapidly changing seascape metrics and environmental contexts can disrupt known species‐seascape relationships and complicate evaluations of habitat quality. Studying the effect of scale on species suitability models in these systems allows for greater predictive power and better understanding of the multiscale processes that drive species distributions. We use quantitative species abundance from a Louisiana Gulf coast estuary along with both drone and satellite‐derived habitat data to model species‐habitat relationships across a range of measurement scales. Using this approach, we identify optimal measurement scales for population‐level HSMs for Penaeus setiferus (white shrimp) and Callinectes sapidus (blue crabs) and identify key species‐habitat relationships. Within the range of scales considered (20–600‐m radius), blue crab HSMs had the highest predictive power at 150 m. White shrimp showed high predictive power at both 120 m and 300 m in drone and satellite‐based analyses, respectively. Our models show that white shrimp have a positive association with Avicennia germinans (black mangroves), a range‐expanding foundation species rapidly encroaching onto the Spartina alterniflora marshes in Louisiana. This approach generates predictive HSMs for two key fisheries species on the Louisiana coast and helps define their relationship to ongoing changes in their habitat. Future seascape suitability studies should test across spatial scales to optimize the predictive power of their models.
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BibTeX
@article{leavitt2026importance,
title = {{Importance of scale in seascape habitat suitability modeling: Predicting species distributions in changing ecosystems}},
author = {Herbert Leavitt and Alexander Thomas and James A. Nelson},
journal = {Ecological Applications},
year = {2026},
month = nov,
doi = {10.1002/eap.70318},
url = {https://doi.org/10.1002/eap.70318},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Importance of scale in seascape habitat suitability modeling: Predicting species distributions in changing ecosystems
AU - Herbert Leavitt
AU - Alexander Thomas
AU - James A. Nelson
PY - 2026
DA - 2026/11/04
JO - Ecological Applications
DO - 10.1002/eap.70318
UR - https://doi.org/10.1002/eap.70318
AB - Habitat suitability models (HSMs) use landscape metrics to describe patterns in species distributions, quantify the success of habitat restoration, and model species responses to change. Within a particular level of organization, the spatial scale of effect at which habitat is integrated and incorporated into HSMs can influence model performance. However, scale optimization can be time consuming and requires high‐quality data across spatial scales. As such, it is not widely applied in suitability models and is particularly rare in marine studies. In coastal and marine landscapes, or seascapes, rapidly changing seascape metrics and environmental contexts can disrupt known species‐seascape relationships and complicate evaluations of habitat quality. Studying the effect of scale on species suitability models in these systems allows for greater predictive power and better understanding of the multiscale processes that drive species distributions. We use quantitative species abundance from a Louisiana Gulf coast estuary along with both drone and satellite‐derived habitat data to model species‐habitat relationships across a range of measurement scales. Using this approach, we identify optimal measurement scales for population‐level HSMs for Penaeus setiferus (white shrimp) and Callinectes sapidus (blue crabs) and identify key species‐habitat relationships. Within the range of scales considered (20–600‐m radius), blue crab HSMs had the highest predictive power at 150 m. White shrimp showed high predictive power at both 120 m and 300 m in drone and satellite‐based analyses, respectively. Our models show that white shrimp have a positive association with Avicennia germinans (black mangroves), a range‐expanding foundation species rapidly encroaching onto the Spartina alterniflora marshes in Louisiana. This approach generates predictive HSMs for two key fisheries species on the Louisiana coast and helps define their relationship to ongoing changes in their habitat. Future seascape suitability studies should test across spatial scales to optimize the predictive power of their models.
SN - 1051-0761
ER -