Climate controls the variables (light, temperature, hydrology) that drive the ecology of lakes and streams. However, local conditions can strongly ‘filter’ the effects of climate on ecosystem processes, creating variable responses across space and time. Mountains combine spatially compressed environmental gradients with highly heterogeneous topography, providing a natural template to explore variation in lake responses to climate at multiple spatial scales.
In many mountain regions, lake temperature is strongly associated with snow cover and snowmelt inputs, however, lake and catchment features should mediate this relationship. I am applying a mechanistic perspective to a regional-scale analysis of thermal regimes and ice cover in lakes across the mountains of California, in order to develop predictive models of lake-climate interactions. With the help of a stellar field crew, I installed sub-surface, high frequency instrument arrays in a unique network of remote lakes spanning the Sierra Nevada and Klamath mountains; these arrays are currently measuring water temperature, light, oxygen, and conductivity throughout the water column. Long-term data from Emerald Lake (Sequoia National Park) and Castle Lake (Klamath mountains) will supplement this spatially distributed sensor data and allow me to test hypotheses about how climate variation and physical landscape features influence ecological processes in lakes, such as ecosystem metabolism, carbon cycling, and community composition of zooplankton.