Because climate and land use strongly affect ecosystems and the services that they provide to society, understanding of both individual factors and their interactions is integral for developing effective environmental management and policy. Cross-scale interactions, wherein a factor at one scale interacts with a factor at another scale, are of particular interest, given their complexity and lack of study. The main goal of this research is to develop tools to measure and understand how climate and land use, by themselves and as interacting factors, affect lake ecosystems across scales of time and space, even as these factors are themselves, changing. Lakes are unique study systems to address questions of cross-scale interactions; for example, agricultural land use in a surrounding lake watershed can interact with the climate of the region in which the lake is located, leading to situations where lakes in different climatic zones may respond differently to similar surrounding environmental inputs, such as nutrient inputs from agricultural land use in their watersheds. This project will identify and measure the most important cross-scale interactions that control lake nutrients and water quality and will be guided by a landscape limnology conceptual framework. A collaborative team from three universities will collect a large dataset on lakes, nutrients, and watersheds, including over 5,000 lake ecosystems in 11 U.S. states spanning up to 30 years. Several new and innovative statistical modeling approaches will be used to detect and model cross-scale interactions, including Bayesian hierarchical modeling (a statistical method for learning and modeling complex relationships in data).
Identifying the conditions or the environments prone to cross-scale interactions is needed to forecast, manage, and restore ecosystems, such as lakes, responding to change operating at local to regional scales. The research framework, design, and analysis of this work provide an innovative approach that has the potential change the conduct of research on large-scale, living systems, beyond the lakes under study. Additionally, because commonly-measured lake water quality variables used in water resource policy will be used in this analysis, results from this project will directly inform state and federal agencies responsible for lake and water management. Finally, several undergraduate, graduate, and post-doctoral researchers will be trained as a result, helping to foster a new generation of biologists with skills in tackling broad-scaled research and policy problems.
