Climate change can have strong effects on aquatic ecosystems, including disrupting nutrient cycling and mediating processes that affect primary production. Past studies have been conducted mostly on individual or small groups of ecosystems, making it challenging to predict how future climate change will affect water quality at broad scales. We used a subcontinental-scale database to address three objectives: (1) identify which climate metrics best predict lake water quality, (2) examine whether climate influences different nutrient and productivity measures similarly, and (3) quantify the potential effects of a changing climate on lakes. We used climate data to predict lake water quality in similar to 11,000 north temperate lakes across 17 U.S. states. We developed a novel machine learning method that jointly models different measures of water quality using 48 climate metrics and accounts for properties inherent in macroscale data (e.g., spatial autocorrelation). Our results suggest that climate metrics related to winter precipitation and summer temperature were strong predictors of lake nutrients and productivity. However, we found variation in the magnitude and direction of the relationship between climate and water quality. We predict that a likely future climate change scenario of warmer summer temperatures will lead to increased nutrient concentrations and algal biomass across lakes (median similar to 3%-9% increase), whereas increased winter precipitation will have highly variable effects. Our results emphasize the importance of heterogeneity in the response of individual ecosystems to climate and are a caution to extrapolating relationships across space.
1.Univ Wisconsin, Ctr Limnol, Madison, WI 53706 USA 2.Univ Wyoming, Dept Zool & Physiol, Laramie, WY 82071 USA 3.Michigan State Univ, Dept Comp Sci & Engn, E Lansing, MI 48824 USA 4.US Geol Survey, Upper Midwest Water Sci Ctr, Middleton, WI USA 5.Univ Montreal, Dept Sci Biol, Montreal, PQ, Canada 6.GRIL, Montreal, PQ, Canada 7.Michigan State Univ, Dept Fisheries & Wildlife, E Lansing, MI 48824 USA 8.Michigan State Univ, Lyman Briggs Coll, E Lansing, MI 48824 USA 9.US EPA, Natl Res Council, Corvallis, OR USA 10.Penn State Univ, US Geol Survey, Penn Cooperat Fish & Wildlife Unit, University Pk, PA 16802 USA
Recommended Citation:
Collins, S. M.,Yuan, S.,Tan, P. N.,et al. Winter Precipitation and Summer Temperature Predict Lake water Quality at Macroscales[J]. WATER RESOURCES RESEARCH,2019-01-01,55(4):2708-2721