Abstract
Knowledge of the spatial distribution and habitat associations of species in relation to the environment is essential for their management and conservation. Habitat suitability models are useful in quantifying species-environment relationships and predicting species distribution patterns. Little is known, however, about the stability and performance of habitat suitability models when projected into new areas (spatial transferability) and how this can inform resource management. The aims of this study were to model habitat suitability of Norway lobster (Nephrops norvegicus) in five fished areas of the Northeast Atlantic (Aran ground, Irish Sea, Celtic Sea, Scotland Inshore and Fladen ground), and to test for spatial transferability of habitat models among multiple regions. Nephrops burrow density was modelled using generalised additive models (GAMs) with predictors selected from four environmental variables (depth, slope, sediment and rugosity). Models were evaluated and tested for spatial transferability among areas. The optimum models (lowest AICc) for different areas always included depth and sediment as predictors. Burrow densities were generally greater at depth and in finer sediments, but relationships for individual areas were sometimes more complex. Aside from an inclusion of depth and sediment, the optimum models differed between fished areas. When it came to tests of spatial transferability, however, most of the models were able to predict Nephrops density in other areas. Furthermore, transferability was not dependent on use of the optimum models since competing models were also able to achieve a similar level of transferability to new areas. A degree of decoupling between model ‘fitting’ performance and spatial transferability supports the use of simpler models when extrapolating habitat suitability maps to different areas. Differences in the form and performance of models from different areas may supply further information on the processes shaping species’ distributions. Spatial transferability of habitat models can be used to support fishery management when the information is scarce but caution needs to be applied when making inference and a multi-area transferability analysis is preferable to bilateral comparisons between areas.
Highlights
Species distribution models (SDMs), called habitat models, habitat preference, habitat suitability or habitat distribution models, are empirically-defined models relating field observations to environmental variables, with the aim of quantifying species-environment relationships and predicting species occurrence and/ or density at unsurveyed locations [1,2]
Rugosity was found to be a predictor of Nephrops habitat suitability in the Irish Sea, Scotland inshore waters and Fladen ground models
Slope was included in the best model for the Celtic Sea, Scotland inshore waters and Fladen ground (Table 3; Fig. 4)
Summary
Species distribution models (SDMs), called habitat models, habitat preference, habitat suitability or habitat distribution models, are empirically-defined models relating field observations (e.g. presence-only, presence-absence or abundance only) to environmental variables, with the aim of quantifying species-environment relationships and predicting species occurrence and/ or density at unsurveyed locations [1,2]. The application of such models has become an important tool to address issues in ecology, biogeography, conservation planning and more recently in climate change research [3,4,5]. The model is fitted on the training data and its performance is evaluated on the testing data [2,6]
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