Freshwater lakes integrate the cumulative impact of upstream human activities on water quality. Thus, early warning indicators (EWIs) of ecosystem change in lakes may be used to understand the impact of catchment environmental changes. EWIs have been used to retroactively assess observed regime shifts and to reverse algal blooms in lakes, but they have not been widely used to date to inform real-world management decisions. Here, we explored the use of EWIs in water quality management by addressing the questions: 1) How are land use and climate change interacting to affect water quality in an oligotrophic lake over three decades? and 2) Can we use EWIs to manage water quality in a real-world oligotrophic lake? We used historical data on Lake Sunapee, New Hampshire (USA), collected primarily by committed citizen scientists, to calibrate a lake ecosystem simulation model run at an hourly time step for three decades. We then tested for EWIs in the model output using a suite of statistical metrics, including breakpoint analysis, rolling standard deviation, and autocorrelation. We assessed land cover change with Landsat imagery in conjunction with historical data on sub-catchment nutrient loads. These data were used to develop spatially-explicit nutrient loading model scenarios for predicting future changes in lake water quality and their association with changes in land use.
Results/Conclusions
Both land use and climate are important drivers of changing water quality in Lake Sunapee, where land use changes best explain decadal trends, and interannual differences in precipitation and temperature best explain within-year patterns. Historical data for 1986 – 2016 demonstrate small, yet statistically significant changes in gross primary production and respiration, while Secchi depth and chlorophyll a have not yet exhibited change. The Landsat analysis demonstrated spatially variable land cover change from 1985 to present across the catchment, with tributary sub-catchment exhibiting everything from negligible forest cover change to loss of approximately 30% of forest cover. The Landsat analysis and simulated lake response to nutrient loading provide a suite of alternative scenarios as a tool to assist management. Model simulations predict that increased conversion of forest cover to impervious surface in some sub-catchments may rapidly accelerate the onset of EWI alarms within the next several years. Overall, our study demonstrates the feasibility of informing on-the-ground management with modeling scenarios developed using data streams from heterogeneous sources and highlights the importance of including data collected by citizen scientists.