MEPS 683:221-226 (2022)  -  DOI: https://doi.org/10.3354/meps13949

ABSTRACT: Habitat suitability models have been used for decades to develop spatially explicit predictions of landscape capacity to support populations of target species. As high-resolution remote sensing data are increasingly included in habitat suitability models that inform spatial conservation and restoration decisions, it is essential to validate model predictions with independent, quantitative data collected over sustained time frames. Here, we used data collected from 12 reefs over a 14 yr sampling period to validate a recently developed physical habitat suitability model for intertidal oyster reefs in coastal Virginia, USA. The model used intertidal elevation, water residence time, and fetch to predict the likelihood of suitable conditions for eastern oysters Crassostrea virginica across a coastal landscape, and remotely sensed elevation was the most restrictive parameter in the model. Model validation revealed that adult oyster biomass was on average 1.5 times greater on oyster reefs located in predicted ‘suitable’ habitat relative to reefs located in predicted ‘less suitable’ habitat over the 14 yr sampling period. By validating this model with long-term population data, we highlight the importance of elevation as a driver of sustained intertidal oyster success. These findings extend the validation of habitat suitability models by quantitatively supporting the inclusion of remotely sensed data in habitat suitability models for intertidal species. Our results suggest that future oyster restoration and aquaculture projects could enhance oyster biomass by using habitat suitability models to select optimal site locations.

KEY WORDS: Eastern oyster · Crassostrea virginica · Elevation · LiDAR · Habitat suitability model · Oyster restoration · Remote sensing

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Cite this article as: Smith RS, Hogan S, Tedford KN, Lusk B, Reidenbach MA, Castorani MCN (2022) Long-term data reveal greater intertidal oyster biomass in predicted suitable habitat. Mar Ecol Prog Ser 683:221-226. https://doi.org/10.3354/meps13949 Export citation Share:    Facebook - - linkedIn