Modelling riparian forest distribution and composition to entire river networks

Aim: Developing a methodology to map the distribution of riparian forests to entire river networks and determining the main environmental factors controlling their spatial patterns. Location: Cantabrian region, northern Spain. Methods: We mapped the riparian forests at a physiognomic and phytosociological level by delimiting riparian zones and generating vegetation distribution models based on remote sensing data (Landsat 8 OLI and LiDAR PNOA). We built virtual watersheds to define a spatial framework where the catchment environmental information can be specified for each river reach, in combination with the vegetation map. In order to determine the drivers that play a significant role in the observed spatial patterns in riparian forests, based on our data sets we modelled interactions between environmental information and riparian vegetation by using the Random Forest algorithm. Results: The modelling results obtained reliably reproduced the variation of riparian forest structure and composition across Cantabrian watersheds. The produced maps were highly accurate, with a more than 70% overall accuracy for forest occurrence. A clear differentiation between Eurosiberian (habitats 91E0 and 9160) and Mediterranean (92E0) riparian forests was shown on both sides of the mountain range. Topography and land use were the main drivers defining the distribution of riparian forest as a physiognomic unit. In turn, altitude, climate and percentage of pasture were the most relevant factors determining their composition (phytosociological approach). Conclusions: Our study confirms that anthropic control ultimately defines the distribution of vegetation in the riparian area at a regional to local scale. Human disturbances constrain the extension of forest patches across their potential distribution defined by topoclimatic boundaries, which establish a clear limit between Mediterranean and Eurosiberian biogeographical regions. Riparian forests were mapped using an approach based on remote sensing. We saw how their potential distribution is defined by the existence of a biogeographic gradient in which climate is the principal factor. However, anthropic uses constrain their current distribution in these areas. Our modelling framework provides useful information that could be translated into indicators for the EU’s Water Framework Directive and Habitats Directive.