Predicting the Sensitivity of Boreal Lake Ecosystems to Climate Change

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BACKGROUND AND OBJECTIVES In order to predict lake sensitivity to climate change it is important to model the physical driver (lake thermal structure) and measure the ecological response (algal community change). Predicting the propensity of a lake to stratify during the summer growing season has been widely studied in Minnesota (Gorham and Boyce, 1989; Fang and Stefan, 1997). Large spatial surveys show that maximum lake depth and lake surface area are key parameters that determine whether a lake will stratify or not (Gorham and Boyce, 1989; Jacobson et al., 2010). Furthermore, recently developed physical lake models are now able to accurately describe lake thermal structure and dissolved oxygen conditions using meteorological and contemporary lake data (Stefan et al., 1998). Hind-casting these lake thermal models is therefore possible using measured historical weather data as we are currently doing for a pilot study of several GLKN lakes. Ultimately, resolving how boreal lakes respond to changes in thermal structure is a key step towards modifying management strategies to protect aquatic resources and informing public use to sustain public appreciation in a changing climate. Isle Royale was stablished as a park in 1931. Its inland lakes have been and are iconic features and key natural resources. These ecosystems provide important habitat for fish and waterfowl, including loons. They also provide popular recreational opportunities, including fishing, swimming, boating, and prime camping. Given the high value of these systems, the Water Resources Management Plan (Crane et al. 2006) lists monitoring of ISRO inland lakes as a high priority issue in this International Biosphere Reserve. The objective of this Agreement is to assess the sensitivity of boreal lakes to climate change based on the long-term changes in algal communities (the base of the aquatic food chain). The relative sensitivity of lakes along a gradient of lake stratification will provide a semi-empirical scale to predict which lakes will be most susceptible to changes in algal communities in the future. We will use a combination of contemporary limnological monitoring, ecosystem modeling, and lake sediment records from eight lake ecosystems along a gradient of size (lake area and depth).

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