A WATERSHED APPROACH TO ECOSYSTEM MONITORING IN DENALI NATIONAL PARK AND PRESERVE, ALASKA 1

• Published in: JAWRA Journal of the American Water Resources Association
• Main Authors: Thorsteinson, Lyman K., Taylor, Dale L.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 1997
• Subjects: Earth-Surface Processes; Water Science and Technology; Ecology; Arctic; Rock Creek; Climate change; Subarctic; Alaska
• Online Access: http://dx.doi.org/10.1111/j.1752-1688.1997.tb04106.x; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1752-1688.1997.tb04106.x; https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1752-1688.1997.tb04106.x

ABSTRACT: The National Park Service and the National Biological Service initiated research in Denali National Park and Preserve, a 2.4 million‐hectare park in southcentral Alaska, to develop ecological monitoring protocols for national parks in the Arctic/Subarctic biogeographic area. We are focusing pilot studies on design questions, on scaling issues and regionalization, ecosystem structure and function, indicator selection and evaluation, and monitoring technologies. Rock Creek, a headwater stream near Denali headquarters, is the ecological scale for initial testing of a watershed ecosystem approach. Our conceptual model embraces principles of the hydrological cycle, hypotheses of global climate change, and biological interactions of organisms occupying intermediate, but poorly studied, positions in Alaskan food webs. The field approach includes hydrological and depositional considerations and a suite of integrated measures linking key aquatic and terrestrial biota, environmental variables, or defined ecological processes, in order to establish ecological conditions and detect, track, and understand mechanisms of environmental change. Our sampling activities include corresponding measures of physical, chemical, and biological attributes in four Rock Creek habitats believed characteristic of the greater system diversity of Denali. This paper gives examples of data sets, program integration and scaling, and research needs.