Integrating spatial multi-criteria evaluation and expert knowledge for GIS-based habitat suitability modelling

GIS data processing and spatial analysis, together with modern decision analysis techniques, were used in this study to improve habitat suitability evaluation over large areas. Both empirical evaluation models and models based on expert knowledge can be applied in this approach. The habitat requirements of species were described as map layers within GIS so that each map layer represented one criterion. GIS was used as the platform in managing, combining and displaying the criterion data and also as a tool for producing new data, especially by utilising spatial analysis functions. Criterion standardisation, weighting and combining were accomplished by means of multi-criteria evaluation (MCE) methods, the theoretical background being based on the multi-attribute utility theory (MAUT). By using continuous priority and sub-priority functions in the evaluation, no classification of continuous attributes was needed and also non-linear relationships between habitat suitability and the attributes could be considered. Sensitivity analysis was applied to consider the temporal factor in the analysis and to find out the effect of different criteria weights on the spatial pattern of the suitability index. Changing the weights of permanent and time-changeable habitat factors shifted the location of optimal habitats for the species. In the long run, permanent factors such as soil properties define the habitat potential, which is important to take into consideration; e.g. in forest management planning and species conservation. The method is illustrated by a case study in which habitat suitability maps were produced for an old-forest polypore, Skeletocutis odora.