Modeling lake ecosystem change within coupled human-natural systems to improve water resources management

Lake ecosystems are sentinels of change in a landscape, integrating upstream terrestrial and aquatic effects of climate and land use drivers. Climate and land use change is mediated by socio-cultural and economic processes, resulting in complex responses in lake ecosystems as a part of coupled natural human (CNH) systems. I used multiple approaches within a CNH framework to better understand the effects of climate and land use on freshwater-human interactions. I first conducted a literature synthesis and found that slow processes (e.g., cultural change) are underrepresented in CNH-freshwater models relative to fast processes (e.g., daily decision-making), though both fast and slow processes are key to assessing decadal trajectories of change. I then examined the interaction of fast and slow variables in lakes through two ecosystem modeling assessments. I used a process-based model to assess drivers of annual chlorophyll-a concentration, a metric of phytoplankton biomass, over three decades in a low-nutrient lake and found that increases in summer median versus maximum chlorophyll-a are related to rising air temperatures and external phosphorus load, respectively. I also conducted a single-year study in the same lake to examine variability in site-specific gross primary production (GPP) and respiration (R), two fast-changing variables that serve as robust indicators of slowly-changing trophic state. I found that higher rates of near-shore GPP and R were partially due to stream-related variables, providing insight into how inflowing streams connect to in-lake processes. These two ecosystem assessment studies indicate fast-changing response variables can be indicative of specific slow-changing variables: annual maximum versus median chlorophyll-a can be used to assess differing impacts from climate and land use change, and estimation of GPP and R near inflow streams integrate sub-catchment drivers. Finally, I evaluated the effectiveness of an online model visualization relating current land use decisions, a fast process, to future water quality outcomes, a slow process, and found that the visualization was effective in altering property owner beliefs and intended behavior related to applying lawn fertilizer and installing waterfront buffers. Collectively, this work advances our understanding of how fast and slow variables interact to improve assessments of changes in CNH-lake systems.