Katrina E. Bennett

Predicting Chronic Climate-Driven Disturbances and Their Mitigation

Society increasingly demands the stable provision of ecosystem resources to support our population. Resource risks from climate-driven disturbances, including drought, heat, insect outbreaks, and wildfire, are growing as a chronic state of disequilibrium results from increasing temperatures and a greater frequency of extreme events. This confluence of increased demand and risk may soon reach critical thresholds. We explain here why extreme chronic disequilibrium of ecosystem function is likely to increase dramatically across the globe, creating no-analog conditions that challenge adaptation. We also present novel mechanistic theory that combines models for disturbance mortality and metabolic scaling to link size-dependent plant mortality to changes in ecosystem stocks and fluxes. Efforts must anticipate and model chronic ecosystem disequilibrium to properly prepare for resilience planning.

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

The Colorado River basin is a fundamentally important river for society, ecology and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model. We combine global sensitivity analysis with a space-filling Latin Hypercube sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach. We find that snow-dominated regions are much more sensitive to uncertainties in VIC parameters. Although baseflow and runoff changes respond to parameters used in previous sensitivity studies, we discover new key parameter sensitivities. For instance, changes in runoff and evapotranspiration are sensitive to albedo, while changes in snow water equivalent are sensitive to canopy fraction and Leaf Area Index (LAI) in the VIC model. It is critical for improved modeling to narrow uncertainty in these parameters through improved observations and field studies. This is important because LAI and albedo are anticipated to change under future climate and narrowing uncertainty is paramount to advance our application of models such as VIC for water resource management.

Using MODIS estimates of fractional snow cover extent to improvestreamflow forecasts in Interior Alaska

1International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, Alaska, 99775 U.S.A. 5 2Water and Environmental Research Center, University of Alaska Fairbanks, Fairbanks, Alaska, 99775 U.S.A. 3Current affiliation, Earth and Environmental Sciences, Los Alamos National Lab, Los Alamos, NM, 87545, U.S.A 4Alaska Pacific River Forecast Center, Anchorage, Alaska, 99502 U.S.A. 5AMEC Environment and Infrastructure, Boulder, Colorado, 80302 U.S.A. 10