Identifying Large Ecological Networks with Spatial Conservation Prioritization Methods to Benefit Regional Land-use Planning

Abstract

The current biodiversity crisis is a major environmental problem to be solved. Land-use planning should respond to the near-ubiquitous decline in habitats and their ecological quality, which derives from e.g. urban expansion and natural resource use. Connectivity is one crucial thing to consider in biodiversity-friendly land-use planning. In human-modified landscapes, it is important to identify and preserve not only the remaining small sites of high biodiversity value, but also the larger-scale mosaics of good-quality sites.

Spatial conservation prioritization is a group of methods that has been successfully used to steer resource-efficient conservation. Complementarity-based prioritization methods have been used to identify places that enable maximal biodiversity retention, i.e. to locate places that are "critical" for conservation. Connectivity has often been used as a factor to increase sites´ value if they are located next to similar areas (e.g. forest patches close to other ones) or e.g. protected areas, but not to identify large agglomerations of good-quality sites per se. A strict focus on small "critical" sites might lead to a neglect of general ecological quality in land-use planning, especially in fragmented landscapes.

We used a spatial conservation prioritization software called Zonation to identify regional-scale ecological networks in the Uusimaa region (Southern Finland, 9,600 km2) which is a heavily human-dominated landscape with extensive urban areas (e.g. the Finnish capital region), as well as intensive agriculture and forestry. We had 59 GIS layers describing different biotopes (forest quality, peatlands, etc.) and species (rare species observations, deer densities, regionally important bird areas, etc.) as input features for Zonation analysis. Focusing not only on the prioritization result ("the critical sites") but also to the relative density of the input features ("the overall diversity") allowed us to identify large ecological networks that emerge from the surrounding landscape, form well-connected mosaics of ecologically good-quality environments, and harbor a great portion of the regional biodiversity. Furthermore, we used the corridor building function of Zonation to identify ecological corridors between valuable nature sites inside and between the large networks. We then compared the identified networks and corridors to modelled urban growth in Uusimaa to identify future conflict areas between urban expansion and nature conservation. The results are used in the ongoing Uusimaa Regional Plan 2050 initiative.