There is a steady increase in the application of Habitat Suitability Models (HSM) in marine conservation and sustainable ecosystem management. These models predict if the habitat is suitable for a species to occur and allow predicting the spatial distribution of species. HSM are a cost effective technique, because fewer samples are needed to spatially explicit assess the ecological status of a region. Up until now very few modellers have used these models for simulating management scenarios. The main aim of this research is to provide examples how HSM can be used practically in marine conservation management as simulation tools.
A HSM was developed for the bivalve species Macoma balthica using samples collected on the Belgian part of the North Sea. The model was validated on an independent validation set, there by assessing model generalisation and transferability. The modelling technique used was quantile regression because this technique applies the ecological theory of limiting factors, in this way the potential distribution of a species can be modelled more effectively. Other methods are more sensitive to missing variables, variable interactions or stochastic variance. The density of the species was modelled for the whole region on a full cover scale, which allowed a spatially explicit stock assessment. Bootstrap resampling was used to produce replicas of the model, which provided confidence intervals of the modelled predictions.
In a simulation exercise the effect of induced habitat changes on the distribution of the species were assessed. Several marine management scenarios where simulated: a change in the sediment grain size (effect of dredging dumping), a change in bathymetry (dredging dumping, climate change), and change in current velocity (climate change). The local change in the amount of suitable habitat as well as the overall sum of suitable habitat were assessed. The change in the total stock of the species due to the induced changes was measured by means of a spatially explicit stock assessment.