Scholarship & Research
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Item Evaluating the importance of wolverine habitat predictors using a machine learning method(Oxford University Press, 2021-12) Carroll, Kathleen A.; Hansen, Andrew J.; Inman, Robert M.; Lawrence, Rick L.In the conterminous United States, wolverines (Gulo gulo) occupy semi-isolated patches of subalpine habitats at naturally low densities. Determining how to model wolverine habitat, particularly across multiple scales, can contribute greatly to wolverine conservation efforts. We used the machine-learning algorithm random forest to determine how a novel analysis approach compared to the existing literature for future wolverine conservation efforts. We also determined how well a small suite of variables explained wolverine habitat use patterns at the second- and third-order selection scale by sex. We found that the importance of habitat covariates differed slightly by sex and selection scales. Snow water equivalent, distance to high-elevation talus, and latitude-adjusted elevation were the driving selective forces for wolverines across the Greater Yellowstone Ecosystem at both selection orders but performed better at the second order. Overall, our results indicate that wolverine habitat selection is, in large part, broadly explained by high-elevation structural features, and this confirms existing data. Our results suggest that for third-order analyses, additional fine-scale habitat data are necessary.Item Putting Climate Adaptation on the Map: Developing Spatial Management Strategies for Whitebark Pine in the Greater Yellowstone Ecosystem(2018-06) Ireland, Kathryn B.; Hansen, Andrew J.; Keane, Robert E.; Legg, Kristin L.; Gump, Robert L.Natural resource managers face the need to develop strategies to adapt to projected future climates. Few existing climate adaptation frameworks prescribe where to place management actions to be most effective under anticipated future climate conditions. We developed an approach to spatially allocate climate adaptation actions and applied the method to whitebark pine (WBP; Pinus albicaulis) in the Greater Yellowstone Ecosystem (GYE). WBP is expected to be vulnerable to climate-mediated shifts in suitable habitat, pests, pathogens, and fire. We spatially prioritized management actions aimed at mitigating climate impacts to WBP under two management strategies: (1) current management and (2) climate-informed management. The current strategy reflected management actions permissible under existing policy and access constraints. Our goal was to understand how consideration of climate might alter the placement of management actions, so the climate-informed strategies did not include these constraints. The spatial distribution of actions differed among the current and climate-informed management strategies, with 33–60% more wilderness area prioritized for action under climate-informed management. High priority areas for implementing management actions include the 1–8% of the GYE where current and climate-informed management agreed, since this is where actions are most likely to be successful in the long-term and where current management permits implementation. Areas where climate-informed strategies agreed with one another but not with current management (6–22% of the GYE) are potential locations for experimental testing of management actions. Our method for spatial climate adaptation planning is applicable to any species for which information regarding climate vulnerability and climate-mediated risk factors is available.Item Which tree species and biome types are most vulnerable to climate change in the US Northern Rocky Mountains?(2015-02) Hansen, Andrew J.; Phillips, Linda B.The goal of this study was to assess components of vulnerability of tree species and biome types to projected future climate within the Great Northern Landscape Conservation Cooperative (GNLCC) in the US Northern Rockies and the ecosystems surrounding Glacier and Yellowstone/Grand Teton National Parks. We drew on the results of five published studies and analyzed current and projected future climate suitability for 11 tree species and 8 biome types under two IPCC emissions scenarios. We assessed components of vulnerability based on four metrics of current and projected future climate suitability. Results for biome types indicated largely a shift from climates suitable for alpine and subalpine conifer to climates suitable for desert scrub and grassland types. Results from the four studies of tree species indicated substantial loss of area of climate suitability for the four subalpine species by 2100. This was especially true for Whitebark pine (Pinus albicaulis). Suitable climate for this species dropped from just over 20% of the study area in the reference period to 0.5–7.0% by 2070–2100 under the A2 scenario. The studies agreed in projecting expansion of climate suitability for some montane tree species but disagreed on expansion of climate suitability of west-side mesic tree species to eastside locations such as Yellowstone National park. Importantly, the rankings of tree species vulnerability were similar among studies, scenarios, and geographic areas and indicated highest vulnerability for Whitebark pine and Mountain hemlock (Tsuga mertensiana). The results should help federal managers in the GNLCC prioritize tree species for climate adaptation strategies. Moreover, our methods for using published data as a basis for climate vulnerability assessment can be applied within other LCCs across the US and other management units internationally.