An expert-based approach to invertebrate conservation: Identification of priority areas in central-eastern Alps

The private and public agencies for nature protection often ask land managers to implement biodiversity conservation plans. Invertebrates constitute a substantial proportion of terrestrial and freshwater biodiversity and are critical to ecosystem functions. However, their inclusion in conservation planning and management is under represented, particularly in the Alps. In this paper we propose a new methodological solution and challenge for the identification of priority areas based on the integration of three approaches: invertebrate multi-taxa based; expert-based; and, GIS-based. The Trentino Province (eastern Italian Alps), was investigated as a case study. The first methodological step was to select a panel of nineteen experts which played a strategic role in the suggestion of 229 species, endangered or of mandatory conservation interest. The second step was to find objective criteria for species prioritisation. These criteria, crossed with the experts taxonomical and ecological knowledge resulted in a list of 70 focal invertebrate species. The third step was to integrate with the GIS-based approach data layers from the habitat requirements of each of the 70 focal species to generate potential spatial-distributional maps. Potential distribution maps gave information about the sites (priority areas) in which the highest number of focal species could concentrate, thus suggesting where to focus future monitoring efforts. Several priority areas resulted outside the protected ones. Alluvial forest and hop-hornbeam woods were the habitats with the highest number of focal species, and thus they represent the habitats of major conservation interest and concern, because they are usually small, fragmented, and near urbanised areas located in the bottom of the valleys. The relatively simple processes involved in species and potential habitat distribution proposed in this paper can be conducted with a minimal amount of data, making it an attractive tool when time and funds are in short supply.