There is a growing emphasis on ecological connectivity in planning for effective biodiversity conservation and building ecosystem resilience. A major part of this is to counteract the negative impacts of habitat fragmentation (reduction in are and increase in isolation). This is a spatial dataset consisting of maps of habitat networks originally developed by Countryside Council for Wales (CCW) in collaboration with Forestry Commission Wales and Forest Research using a functional networks approach, and now managed and progressively developed by NRW. Patches of habitat and other intervening habitats through which many of their species are able to move are mapped as habitat networks. Networks have been mapped for habitats including woodland, unimproved grassland, calcareous grassland,
marshy grassland, heathland, fens and bogs; in most cases these are divided into upland and lowland versions and in some cases networks that support the highest quality areas of habitat have been selected out as priority layers. Results are available for the whole of Wales as GIS layers and include three levels of habitat networks; core networks (areas within which species that require extensive habitat and disperse poorly are able to move), focal networks (areas within which species tolerant of smaller habitat patches and with greater dispersal ability are able to move), and local networks (areas within species that can persist within small habitat patches and have very limited dispersal abilities can move). Purpose of data capture was to allow the scope and range of potential networks t
o be rapidly explored. Predicted habitat networks can be used to guide large-scale planning for nature conservation, provide insight into how the landscape is likely to be functioning and prioritise action to improve the connectivity and viability of protected sites. Layers are arranged in two folders: Level 1, containing all outputs across Wales, and Level 2 which are selected, priority networks, within which action may be targeted to enhance functional networks of the best habitat areas.