Abstract

With the development of new geographic information system (GIS) tools and powerful statistical methods, predictive habitat and species models are becoming an important tool in protected areas management and spatial planning. Such models enable predict species’ distributions based on the species-environment relationships. Benthic vegetation has an essential role in providing spawning ground, feeding and nursery areas for many commercially important fish species (e.g. Baltic herring, perch, pike) in the northern Baltic Sea. Bladder wrack (Fucus vesiculosus), eelgrass (Zostera marina) and Charophytes are among the most important habitat forming plants in the area. These taxa are listed in the The European Union Habitat Directive. The available information on the species is very scattered and up to date we lack reliable information on the distribution of the species. In this paper we present a case study about the modelling of important fish habitats in the Northern Baltic Sea using generalized regression analysis and spatial prediction (GRASP). GRASP is a general method for making spatial predictions of response variables using point surveys of the response variables and spatial coverages of predictor variables. The probability maps of occurrence of Fucus vesiculosus, Zostera marina and Charophytes were modelled in a shallow coastal area of the Northern Baltic Sea. The following GIS layers of environmental predictor variables were used: depth, seabed slope (different resolutions), seabed sediment type and salinity. Model validations showed more than 75% accuracy in predicting the occurrence of the key phytobenthic species indicating that GRASP modelling is an adequate tool for species’ predictions.

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