Forest Connectivity Regions of Canada Using Circuit Theory and Image Analysis.
Ecological processes are increasingly well understood over smaller areas, yet information regarding interconnections and the hierarchical nature of ecosystems remains less studied and understood. Information on connectivity over large areas with high resolution source information provides for both local detail and regional context. The emerging capacity to apply circuit theory to create maps of omnidirectional connectivity provides an opportunity for improved and quantitative depictions of forest connectivity, supporting the formation and testing of hypotheses about the density of animal movement, ecosystem structure, and related links to natural and anthropogenic forces. In this research, our goal was to delineate regions where connectivity regimes are similar across the boreal region of Canada using new quantitative analyses for characterizing connectivity over large areas (e.g., millions of hectares). Utilizing the Earth Observation for Sustainable Development of forests (EOSD) circa 2000 Landsat-derived land-cover map, we created and analyzed a national-scale map of omnidirectional forest connectivity at 25m resolution over 10000 tiles of 625 km2 each, spanning the forested regions of Canada. Using image recognition software to detect corridors, pinch points, and barriers to movements at multiple spatial scales in each tile, we developed a simple measure of the structural complexity of connectivity patterns in omnidirectional connectivity maps. We then mapped the Circuitscape resistance distance measure and used it in conjunction with the complexity data to study connectivity characteristics in each forested ecozone. Ecozone boundaries masked substantial systematic patterns in connectivity characteristics that are uncovered using a new classification of connectivity patterns that revealed six clear groups of forest connectivity patterns found in Canada. The resulting maps allow exploration of omnidirectional forest connectivity patterns at full resolution while permitting quantitative analyses of connectivity over broad areas, informing modeling, planning and monitoring efforts.
Department of Natural Resource Sciences and McGill School of Environment, McGill University, Montreal, QC, Canada.
David
D
Pelletier
Département de Mathématiques, Collège Montmorency, Laval, QC, Canada.
Marc-Élie
MÉ
Lapointe
Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, Victoria, BC, Canada.
Michael A
MA
Wulder
Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, Victoria, BC, Canada.
Joanne C
JC
White
Department of Natural Resource Sciences and McGill School of Environment, McGill University, Montreal, QC, Canada.
Jeffrey A
JA
Cardille
D002170:Canada; D003198:Computer Simulation; D003247:Conservation of Natural Resources; D004463:Ecology; D017753:Ecosystem; D004784:Environmental Monitoring; D065928:Forests; D062305:Geographic Mapping; D007091:Image Processing, Computer-Assisted; D011156:Population Density; D014197:Trees