Regional and hierarchical perspectives of thermal regimes in subarctic, Alaskan lakes

1. We examined 60 clear, stained and glacial lakes in Alaska to quantify the relative importance of climate setting, morphometry, transparency, and lake typology influences on various thermal characteristics including duration of growing season, water temperature, mixing depth (MD) and heat content. We used analysis of variance (ANOVA) to test for differences in thermal characteristics in association with lake type and employed simple and multiple regression techniques to determine functional relationships between variables. 2. Latitude accounted for 60% of the total variance in length of growing season. Although the date of maximum heat content was consistent among lake types, stained lakes had longer growing seasons compared with clear and glacially turbid lakes. 3. Maximum water temperatures were approximately 3 degreesC higher in stained lakes and 3 degreesC lower in glacial lakes compared with clear lakes. Mean water column temperature was significantly lower in glacial lakes (5.9 degreesC) compared with clear lakes (7.4 degreesC), but there eras no statistical difference between clear and stained lakes (7.2 degreesC) or between stained and glacial lakes. Maximum surface temperatures were positively related (r(2) = 0.51) to colour (humic stain), but negatively related (r(2) = 0.40) to inorganic turbidity (glacial silt). 4. Only about half of the lakes in our data set underwent summer stratification. None of the glacial lakes developed a distinct thermocline, but stained lakes had shallower MDs (mean 8 m) than clear lakes (mean 12 m). Thus, the MD to total depth ratio for glacial lakes was unity compared with mean values of 0.66 for clear lakes and 0.34 for stained lakes. Fetch explained a significant fraction (51%) of the total variance in MD. Considering all lakes, MD was inversely related to transparency (Secchi depth). In contrast, considering only stratified clear and stained lakes, MD was positively related to Secchi depth (SD), the fraction of the total variance explained was 23%. The sign of the slope was dependent on the mixture of lake types. 5. Despite significant (ANOVA) differences in water temperatures, growing season, and MDs among the three lake types, there were no statistical differences in the summer heat budget associated with lake type. In addition, heat budgets were poorly correlated with lake area, depth and volume. In contrast, mean water column temperature was strongly and inversely related (r(2) = 0.77) to mean depth. 6. Potential explanations for the similarity in summer heat budget among lake types and weak correlation with morphometry were attributed to different patterns in vertical heat distribution associated with lake typology (colour and turbidity) differences. 7. Multiple linear regression including climatic (latitude and altitude), morphometric, and lake typology (colour and turbidity) factors demonstrated a hierarchical (climate-morphometry-typology) regulation of growing season characteristics, water temperatures, stratification and heat retention. A regional and hierarchical framework for lake thermal characteristics adds to our understanding of potential responses to climatic change and may be important for regional management objectives for fisheries.