Modelling semi-aquatic vertebrates’ distribution at the drainage basin scale: The case of the otter Lutra lutra in Italy

Abstract

Modelling habitat suitability of semi-aquatic vertebrates for large scale conservation purposes is a particularly challenging task, due to the fine-scale linearity of riverine habitats, and to the ecological continuum represented by the riparian and the aquatic ecosystems, on one side, and by a river and its tributaries, on the other. We advocate that habitat suitability models (HSMs) should represent the fine-scale complexity of the riparian and aquatic ecosystems at the drainage basin scale, which is the most relevant spatial unit for planning conservation strategies for semi-aquatic vertebrates. Hence, we developed a 3-step GIS-based modelling approach, and applied it to otter Lutra lutra in Italy to illustrate its potential applications for designing a nation-wide conservation strategy. First, we built a deductive HSM (resolution: 1:250,000, grain: 100 m × 100 m) of the riparian (100 m buffer around each river bank) and of the back-riparian (500 m buffer) areas along rivers. After, we created a synthetic index S i summarising this information within the cells of a 5 km × 5 km grid superimposed to the whole country, thus obtaining a nation-wide overview of habitat suitability. Both HSM and S i were validated by using data on otter distribution, by performing a sensitivity analysis. Finally, we scaled-up the information provided by S i to obtain a suitability index within each drainage basin ( S b ). By overlapping a layer representing the basins occupied by otters to S b we obtained an effective tool to identify basins to be prioritised for the conservation and expansion of existing populations, for rejoining isolated sub-populations, and for habitat restoration. The methodology developed here helps filling the gap between the urgent conservation needs of semi-aquatic species, and the inadequacy of traditional modelling approaches for species inhabiting one of the world's most endangered ecosystems.