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Thresholds can be used to interpret environmental data in a way that is easily communicated and useful for decision making purposes. However, thresholds are often developed for specific data products and time periods, changing findings when the same threshold is applied to datasets or periods with different characteristics. Here, we test the impact of different spatial discretizations of snow on annual estimates of wolverine habitat in the Colorado Rocky Mountains, defined using a snow water equivalent (SWE) threshold (0.20 m) and threshold date (15 May) from previous habitat assessments. Annual wolverine habitable area (WHA) was thresholded from a 36-year (1985 - 2020) snow reanalysis at three different spatial discretizations: 1) 480 m grid cells, 2) 90 m grid cells, and 3) 480 m grid cells with implicit representations of subgrid snow spatial heterogeneity. Relative to the 480 m grid cells, 90 m grid cells resolved shallower snow deposits on slopes between 3050 and 3350 m elevation, decreasing WHA by 10%, on average. In years with warmer and/or drier winters, grid cells with subgrid representations of snow heterogeneity increased the prevalence of 15 May snow deposits that exceeded the 0.20 m SWE threshold, even within grid cells where mean SWE was less than the threshold. These simulations increased WHA by upwards of 30% in low snow years, as compared to simulations without subgrid snow heterogeneity. Despite WHA sensitivity to different snow spatial discretizations, WHA was controlled more by annual variations in winter precipitation and temperature. However, small changes to the SWE threshold (± 0.07 m) and threshold date (± 2 weeks) also affected WHA by as much as 82%. Across these threshold ranges, WHA was approximately 18% more sensitive to the SWE threshold than the threshold date. However, the sensitivity to the threshold date was larger in years with late spring snowfall, when WHA depended greatly on whether the date SWE was thresholded was before, during, or after spring snow accumulation. Our results demonstrate that snow thresholds are useful but may not always provide a complete picture of the annual variability in snow-adapted wildlife habitat. Studies thresholding spatiotemporal datasets could be improved by including 1) information about the fidelity of thresholds across multiple spatial discretizations, and 2) uncertainties related to ranges of realistic thresholds. [ABSTRACT FROM AUTHOR]

Future reduction in mountain snowpack due to anthropogenic climate change poses a threat to many snow‐adapted species worldwide. Mountain topography exerts a strong control on snowpack not only due to elevation but also through the effect of slope and aspect on the surface energy balance. We develop high‐resolution projections of snowpack in order to provide improved, physically based estimates of the spatial distribution of future snowpack to inform species conservation efforts for the wolverine (Gulo gulo) in two study areas in the Rocky Mountains: one in Montana with known den sites and one in Colorado with recent wolverine activity and potential for reintroduction. Here we assess springtime snowpack loss in actual and potential denning areas under five future climate scenarios for the mid‐21st century. Snowpack in April and May is likely to persist into the mid‐21st century in the upper half of current denning elevations in all but the warmest future climate scenario, while large declines are projected for the lower half of the denning elevations. We gain new insight into the influence of topographical aspect on future snowpack and quantify the potential for enhanced snow persistence on north and east facing slopes under future scenarios that is only revealed in simulations where terrain slopes are resolved. Plain Language Summary: Climate change and its effect on snow are a threat to high mountain ecosystems and species worldwide. The future of mountain snowpack is complex, with multiple drivers, and with a strong elevation dependence. What has received much less attention is the dependence on topographical aspect—how will the snowpack on north facing versus south facing slopes respond differently under climate change. In this paper we develop snow projections motivated by a conservation issue for the wolverine: the future of the springtime snowpack at elevations of observed and potential wolverine denning for two study areas in the Rocky Mountains by the mid‐21st century. While there is significant snowpack loss in the lower half of denning elevations, the upper denning elevations retain springtime snowpack, supporting conservation actions through midcentury in these regions. Key Points: Early spring snowpack declines sharply in the lower half of wolverine den elevations studied but persists through midcentury higher upSpringtime snowpack is less affected by climate change on north and east facing slopes leading to potential for climate refugiaHigh‐resolution modeling that resolves topographical aspect may provide useful information to support conservation decisions [ABSTRACT FROM AUTHOR]

Recently-developed Holocene lake-level reconstructions from the Rocky Mountains offer a quantitative target for testing the skill of state-of-the-art climate system models in simulating hydroclimate change. Here, we use a combination of hydrologic models of catchment streamflow, lake energy balance, and lake water balance to simulate lake level at Little Windy Hill Pond (LWH) in the Medicine Bow Range of Wyoming for a period of severe drought during the mid-Holocene (MH; approximately 6000 years ago). Using Coupled Model Intercomparison Project (CMIP5) output to drive our hydrologic models, we find that none of our simulations reproduce the significantly lowered lake levels at LWH during the MH. Rather, simulated hydroclimate changes for the MH are modest (< 10% reductions in precipitation and streamflow and generally 10–30% increases in lake evaporation), and LWH lake-level changes are buffered by the large volume of snowmelt runoff that the lake receives. Only when winter precipitation is approximately halved in sensitivity experiments do water inputs to the lake become small enough that lake level can be significantly drawn down by year-over-year negative water balances. Possible explanations for the model-data mismatch could lie in the realism of our hydrological modeling framework or in the accuracy of the CMIP5 output, the latter having important implications for projections of future drying in western North America. [ABSTRACT FROM AUTHOR]

Summary Since 2002, the headwaters of the Colorado River and nearby basins have experienced extensive changes in land cover at sub-annual timescales. Widespread tree mortality from bark beetle infestation has taken place across a range of forest types, elevation, and latitude. Extent and severity of forest structure alteration have been observed through a combination of aerial survey, satellite remote-sensing, and in situ measurements. Additional perturbations have resulted from deposition of dust from regional dry-land sources on mountain snowpacks that strongly alter the snow surface albedo, driving earlier and faster snowmelt runoff. One challenge facing past studies of these forms of disturbance is the relatively small magnitude of the disturbance signals within the larger climatic signal. The combined impacts of forest disturbance and dust-on-snow are explored within a hydrologic modeling framework. We drive the Distributed Hydrology Soil and Vegetation Model (DHSVM) with observed meteorological data, time-varying maps of leaf area index and forest properties to emulate bark beetle impacts, and parameterizations of snow albedo based on observations of dust forcing. Results from beetle-killed canopy alteration suggest slightly greater snow accumulation as a result of less interception and reduced canopy sublimation and evapotranspiration, contributing to overall increases in annual water yield between 8% and 13%. However, understory regeneration roughly halves the changes in water yield. A purely observation-based estimate of runoff coefficient change with cumulative forest mortality shows comparable sensitivities to simulated results; however, positive water yield changes are not statistically significant ( p ⩽ 0.05). The primary hydrologic impact of dust-on-snow forcing is an increased rate of snowmelt associated with more extreme dust deposition, producing earlier peak streamflow rates on the order of 1–3 weeks. Simulations of combined bark beetle and dust-on-snow produced little compounding effects, due to the relatively exclusive nature of their impacts. Potential changes in water yield and peak streamflow timing have important implications for regional water management decisions. [ABSTRACT FROM AUTHOR]