Using GIS tools to identify conservation hot spots in large boreal lakes

Abstract

Balancing the growing demands of human population and sustainable use of natural resources is a great challenge for humankind and the target of several international environmental conventions. Water Framework Directive (WFD) of the European Union aims at perceiving ecosystem services provided by aquatic ecosystems, while EU Habitats Directive (HD) along with the Natura 2000 network is to ensure the long-term survival of valuable habitats in aquatic as well as terrestrial environments. Both WFD and HD treat boreal lakes as large entities. In large lake systems, the assessment of lake bodies’ ecological and conservation status is determined over tens or even hundreds of square kilometres and the interpretation is often based on a few scattered field observations. Variation in ecological communities within lake bodies has received less attention, though detailed information on the spatial structuring of the communities and conservation values would improve the reliability of the ecological and conservation assessment of the habitats and promote more effective land use practices. Here, we present the first results of GIS-modelling based on intensive surveys of diversity of lake habitats in Freshwater LIFE IP project. The target lake, Southern Konnevesi, is an oligotrophic clear-water lake of HD habitat type “Oligotrophic waters containing very few minerals of sandy plains (Littorelletalia uniflorae)” defined by characteristic submerged vegetation. We use maximum entropy modelling with environmental variables describing geomorphological variation on different scales to show how water depth, slope of the littoral zone, wind exposure and sediment type explain the distribution of littoral vegetation zones, i.e. different life-forms of aquatic vegetation (helophytes, nymphaeids, isoetids and elodeids). The variability of littoral vegetation zones corresponds to habitat diversity. We use the presence of isoetids restricted to the genuses Isoetes, Littorella and Lobelia as an indicator of high conservation value for a site. Further, local anthropogenic stressors will be included in the model to evaluate the risk of human land use practices on the submerged vegetation with high conservation value. As the most influential environmental variable defining the distribution of aquatic vegetation is water depth, a good bathymetry model is needed in order to produce reliable predictions about the distribution of underwater biodiversity in new locations. Availability of detailed GIS data describing lakebeds will pose challenges for the transferability of underwater habitat distribution models. However, increasing interest of citizens in using remote sensing equipment such as high-quality sonars by fishers will likely enhance the availability of such data in the future.