Michael Arsenault, Antóin M. O’Sullivan, Jae Ogilvie, Carole-Anne Gillis, Tommi Linnansaari & R. Allen Curry (2022) Remote sensing framework details riverscape connectivity fragmentation and fish passability in a forested landscape, Journal of Ecohydraulics, DOI: 10.1080/24705357.2022.2040388April 6, 2022
Fragmentation of stream networks from anthropogenic structures such as road culverts can affect the health of a catchment by negatively affecting the ecosystem’s biota, their movements, abundance, and species richness. We present a framework using publicly available LiDAR and orthophotography to locate and identify road crossings, i.e. the most prolific of barriers in forested landscapes, and evaluate fragmentation and passability at the landscape scale. Coupling the LiDAR stream network and private road network in the 3,223 km2 study area, we identified 1,052 stream crossings of which, 32% were culverts and 12% of the total stream network was potentially inaccessible due to these culverts. We correctly identified the type of stream-road crossings at >90% of any stream order and at 100% at Orders >2. The 10 culverts restricting the most stream kilometers, restricted >34% of the potential stream habitats for four species of fish, a result that provides the resource management with a first assessment for effective improvement of connectivity across this landscape. With this framework, managers equipped with appropriate imagery can create a stream crossing database with minimal funding, create an inventory of instream barriers, and prioritize removals at a landscape-scale, thus providing an effective assessment and decision-making tool for their habitat restoration efforts.
Keywords: culvert, LiDAR, remote sensing, stream connectivity