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There is a growing need for accurate and interpretable maps that describe the spatial extent and suitability of flatfish habitats. A common approach to developing such maps is to construct spatially explicit habitat models from fisheries-independent survey data. As the entire range of factors that define fish habitats can never be fully quantified, habitat models are invariably built from a small subset of factors, which typically consist of physical seabed and water column characteristics. If important physical and biological habitat features have not been measured, conventional modelling techniques may underestimate habitat use and quality. We present a spatial modelling technique capable of estimating the maximum extent and suitability of flatfish habitats, i.e. the potential or upper limits of the habitat, using juvenile sole (Solea solea L.) in the Dover Strait as an example. To develop the models, juvenile sole catch densities and environmental habitat data were first acquired and assembled within a Geographical Information System (GIS). Regression quantiles were then estimated for models of change in juvenile sole catch density according to changes in a number of habitat variables. Finally, spatial models were constructed within a GIS by combining the quantile regression models with digital maps of the environmental variables. The use of regression quantiles allowed linear model parameters to be estimated near to the upper bounds of the sole-habitat relationships, thereby providing estimates of the limiting effects of the habitat. In turn, the habitat map built from the upper regression quantiles provided robust estimates of the maximum spatial extent and suitability of sole nursery grounds in the Dover Strait region, as confirmed by model tests using independent data. Habitat maps developed using this approach may be desirable from a species conservation perspective, as the likelihood of underestimating the extent and quality of the habitat is reduced. |
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