SENSITIVITY OF LONG-TERM ECOLOGICAL DATA: AN ANALYSIS OF THE EFFECTS OF REDUCED SAMPLING FREQUENCY ON WATER QUALITY TRENDS IN A MOUNTAIN WATERSHED

Long-term ecological data are critical for understanding ecosystem responses to climate change and are stronger drivers of environmental policy and resource management than short-term studies. Such datasets are especially important for high-elevation systems, where warming is amplified and lakes are coupled with the cryosphere, yet these datasets are costly to maintain. As both ecosystems and monitoring programs face growing threats, there is a need to establish and maintain long-term monitoring programs that minimize costs while maximizing captured variation and abilities to make ecological inferences. Using a 30+ year aquatic biogeochemical record from the Loch Vale watershed in Rocky Mountain National Park, we evaluate how reduced sampling frequency affects trends and variability in long-term data. We statistically subsampled the historical weekly time series to fortnightly and monthly frequencies and assessed changes in estimated trends in major cations and in distributions and variability of nitrate fluxes annually and during snowmelt, baseflow, and winter. Preliminary results show that estimated trends in solutes indicative of weathering are largely preserved when sampling frequency is reduced, though inference strength can weaken. In contrast, nitrate concentrations and N flux estimates are sensitive to statistical downsampling, especially during hydrologically variable periods. These results highlight the need to collect long-term data at frequencies aligned with research goals and to guide adaptation of monitoring programs for personnel maintaining these datasets.

Presentation Preference: Standard Oral (12 Minutes)

Primary Presenter: Adeline Kelly, University of Colorado (adelinekelly04@gmail.com)

Authors:

Adeline Kelly, University of Colorado  (adeline.kelly@colorado.edu)

Jill Baron, Colorado State University, U.S. Geological Survey  (Jill.baron@colostate.edu)

Isabella Oleksy, University of Colorado  (Isabella.Oleksy@colorado.edu)