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Integration of remote sensing and spatial conservation prioritization approaches for aiding large-area, multi-jurisdictional biodiversity conservation in Canada’s boreal forest

University of British Columbia

Remote sensing is an important complementary data source to enable cost effective monitoring and mapping of biodiversity indicators over large extents in a consistent and repeatable manner. As such, remote sensing is capable of supporting the information needs of modern biodiversity conservation efforts. However, a number of critical challenges and opportunities deserve greater attention. The aim of this research is to advance the use of remote sensing and other geospatial techniques for large-area, multi-jurisdictional conservation of Canada’s boreal forest. Outcomes of this dissertation contributed to progress in each of four research themes: (i) assessing biodiversity across broad areas, (ii) identifying areas of high conservation priority (iii) evaluating the efficacy of current and hypothetical reserve networks, and (iv) incorporating future vegetation variability in conservation planning. The overall research findings indicate the tremendous capacity of the Canadian boreal forest to provide suitable areas for conservation investment and demonstrate the usefulness of these coarse-scale approaches for guiding ongoing research aimed at boreal conservation planning. Key findings included: (a) Reserves that were restricted to only intact forest landscapes were less flexible and efficient (more costly), (b) Reserves using accessibility (distance from road and human settlement) as a cost surrogate were able to satisfy a range of conservation targets and compactness levels while remaining remote from human influence, (c) Reserves (≥1000 km2; <10000 km2) were relatively less variable, (d) Climate change impacts (estimated vegetation productivity variability) greatly influences the cost of reserve networks and the amount of area required to meet conservation targets, (e) Conservation of more sites spread across locations with higher variable vegetation probability values, yet low cost (wilderness areas), proved most efficient, and (f) Reserve networks optimized under “current” or “least change (B1)” conditions are unlikely to maintain their current representative targets in 2080

Text

2015-04-20

Attribution-NonCommercial-NoDerivs 2.5 Canada

http://hdl.handle.net/2429/52903

Forestry

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/2.5/ca/