A decision support tool for assessing cumulative effects on an Arctic migratory tundra caribou population

• Published in: Ecology and Society
• Main Authors: Don Russell, Anne Gunn, Robert White
• Format: Article in Journal/Newspaper
• Language: English
• Published: Resilience Alliance 2021
• Subjects: arctic national wildlife refuge; caribou; climate; cumulative effects; hydrocarbon; impact assessment; mitigation; modeling; porcupine caribou; Biology (General); QH301-705.5; Ecology; QH540-549.5; Arctic; Tundra
• Online Access: https://doi.org/10.5751/ES-12105-260104; https://doaj.org/article/07e0562638914821b88058965e800d34

As large migratory caribou herds decline globally and regional climate trends point to a warmer future, there is a need and a legislative requirement to ensure impacts of industrial development are fully assessed, particularly with respect to cumulative effects. In this paper we use a current proposal, the potential leasing of the 1002 lands on the Alaskan Arctic coastal plain of the Arctic National Wildlife Refuge for hydrocarbon development, to project the potential cumulative effects on the international Porcupine Caribou Herd. Using the caribou cumulative effects model, an existing decision support tool, we evaluate six alternative development scenarios for the 1002 lands, ranging from no leasing to full leasing with standard mitigation conditions. Compared to the no leasing option, at the current population size (218,000 caribou), our analysis projected that the likelihood of a herd decline over a 10-year period would increase from 3% to 19% depending on the leasing scenarios analyzed. This compares to an increased probability of decline from 11% to 26% if the starting population was 100,000, indicative of population estimates in the early 1970s. Our approach accomplishes one of the main steps in a comprehensive cumulative effects assessment, namely the quantification of past, present, and foreseeable future projects on a valued ecosystem component, the Porcupine Caribou Herd. We suggest the testing of underlining assumptions and refinements of the model required to more fully estimate the impacts of development. The use of transparent, quantitative decision support tools in assessing industrial development impacts on Arctic wildlife becomes more critical as climatic changes to Arctic landscapes accelerate.