Science Inventory

Predictive Model of Lake Photic Zone Temperature Across the Conterminous United States

Citation:

Kreakie, B., S. Shivers, Jeff Hollister, AND W. Milstead. Predictive Model of Lake Photic Zone Temperature Across the Conterminous United States. Frontiers in Environmental Science. Frontiers, Lausanne, Switzerland, 9:707874, (2021). https://doi.org/10.3389/fenvs.2021.707874

Impact/Purpose:

As the average global air temperature on Earth increases (0.15-0.20 °C per decade since 1975), surface temperatures of lakes are also increasing globally (0.34 °C per decade from 1985 to 2009). The influence of this increased temperature touches all biotic and abiotic components of lentic ecosystems. For example, warming lakes are related to a disruption in trophic linkages between phytoplankton and zooplankton, increased cyanobacteria bloom frequency and toxicity, and altered stratification patterns. Because of the ecological significance, it is important to understand how lake temperatures have changed and to predict how it will change in the future across a large spatial extent. This work presents a simple yet robust method to predict lake near-surface temperatures for the conterminous US.

Description:

As the average global air temperature increases, lake surface temperatures are also increasing globally. The influence of this increased temperature is known to impact lake ecosystems across local to broad scales. Warming lake temperature is linked to disruptions in trophic linkages, changes in thermal stratification, and cyanobacteria bloom dynamics. Thus, comprehending broad trends in lake temperature is important to understanding the changing ecology of lakes and the potential human health impacts of these changes. To help address this, we developed a simple yet robust random forest model of lake photic zone temperature using the 2007 and 2012 United States Environmental Protection Agency’s National Lakes Assessment data for the conterminous United States. The final model has a root mean square error of 1.48°C and an adjusted R2 of 0.88; the final model included 2,282 total samples. The sampling date, that day’s average ambient air temperature and longitude are the most important variables impacting the final model’s accuracy. The final model also included 30-days average temperature, elevation, latitude, lake area, and lake shoreline length. Given the importance of temperature to a lake ecosystem, this model can be a valuable tool for researchers and lake resource managers. Daily predicted lake photic zone temperature for all lakes in the conterminous US can now be estimated based on basic ambient temperature and location information.