Since 2014, the High Plains Regional Climate Center, along with several partners, has worked with the Eastern Shoshone and Northern Arapaho tribes of the Wind River Indian Reservation in western Wyoming. The reservation is located in an arid, mountainous region that is prone to water resource issues. Through input from numerous workshops, webinars, and calls with tribal representatives, the HPRCC created a series of quarterly climate summaries to help the tribes make better informed on-reservation water management decisions. This Decision Dashboard is complementary to the summaries, allowing for more real-time monitoring of climate and drought conditions. This work was funded by the North Central CSC, through the project "The Wind River Indian Reservation’s Vulnerability to the Impacts of Drought and the Development of Decision Tools to Support Drought Preparedness".

The Colorado office of the Bureau of Land Management (BLM), which administers 8.4 million acres of Colorado’s surface acres, and more than 29 million acres of sub‐surface mineral estate, has been charged with developing a climate adaptation strategy for BLM lands within the state. The assessments presented herein present a statewide perspective on the potential future influences of a changing climate on species and ecosystems of particular importance to the BLM, with the goal of facilitating development of the best possible climate adaptation strategies to meet future conditions. The Colorado Natural Heritage Program conducted climate change vulnerability assessments of plant and animal species, and terrestrial and freshwater ecosystems (“targets”) within a time frame of mid‐21st century. Our assessments 1) evaluate the potential impact of future climate conditions on both species and ecosystems by identifying the degree of change expected between current and future climate conditions within the Colorado range of the target, and 2) address the potential impact of non‐climate factors that can affect the resilience of the target to climate change, or which are likely to have a greater impact due to climate change. Climate change vulnerability assessments are not an end unto themselves, but are intended to help BLM managers identify areas where action may mitigate the effects of climate change, recognize potential novel conditions that may require additional analysis, and characterize uncertainties inherent in the process.

We worked with managers in two focal areas to plan for the uncertain future by integrating quantitative climate change scenarios and simulation modeling into scenario planning exercises. In our central North Dakota focal area, centered on Knife River Indian Villages National Historic Site, managers are concerned about how changes in flood severity and growing conditions for native and invasive plants may affect archaeological resources and cultural landscapes associated with the Knife and Missouri Rivers. Climate projections and hydrological modeling based on those projections indicate plausible changes in spring and summer soil moisture ranging from a 7 percent decrease to a 13 percent increase and maximum winter snowpack (important for spring flooding) changes ranging from a 13 percent decrease to a 47 percent increase. Facilitated discussions among managers and scientists exploring the implications of these different climate scenarios for resource management revealed potential conflicts between protecting archeological sites and fostering riparian cottonwood forests. The discussions also indicated the need to prioritize archeological sites for excavation or protection and culturally important plant species for intensive management attention. In our southwestern South Dakota focal area, centered on Badlands National Park, managers are concerned about how changing climate will affect vegetation production, wildlife populations, and erosion of fossils, archeological artifacts, and roads. Climate scenarios explored by managers and scientists in this focal area ranged from a 13 percent decrease to a 33 percent increase in spring precipitation, which is critical to plant growth in the northern Great Plains region, and a slight decrease to a near doubling of intense rain events. Facilitated discussions in this focal area concluded that greater effort should be put into preparing for emergency protection, excavation, and preservation of exposed fossils or artifacts and revealed substantial opportunities for different agencies to learn from each other and cooperate on common management goals. Follow up quantitative simulation modeling of grassland dynamics helped quantify the degree of change expected in vegetation production under the wide range of climate scenarios and suggested that (a) low grazing rates could be adversely affecting vegetation composition in the national park and (b) understanding of the management practices needed to maintain desired vegetation conditions is incomplete.

Pinyon-juniper woodlands are a major part of western landscapes and are valued for recreational use, cultural resources, watershed protection, and wildlife habitats. These woodlands have been identified by several stakeholders, including natural resource management entities, federal and state agencies, and numerous tribal nations, as important ecosystems that are currently threatened by land treatments, changes in disturbance regimes such as drought and fire, and widespread tree mortality. Currently there exist competing objectives for the management of these systems, including the desire to preserve pinyon-juniper viability as climate conditions continue to shift, as well as the need to track these systems to ensure their ranges do not expand into historically non-forested areas. The Southern Rockies Landscape Conservation Cooperative (SRLCC), which considers pinyon-juniper woodlands among their focal resources, recently conducted vulnerability assessments of these woodlands in the four corners and upper Rio Grande landscapes. In a series of workshops to discuss these assessments, stakeholders identified the need for synthesizing regional knowledge of pinyon-juniper woodland structure and dynamics, which can differ dramatically due to the geographically broad distribution of this ecosystem.   The goal of this project is to synthesize the state of the science on pinyon-juniper woodland ecosystems by examining previous research and management practices to identify what is known and what remains to be studied. To do this, researchers are compiling published, peer-reviewed, scientific manuscripts and agency reports on the structure, function, and management of pinyon-juniper ecosystems into a comprehensive database. Unpublished material from land managers who work with pinyon-juniper systems, libraries at the US Forest Service, USGS, and other agencies will also be incorporated. The end product will be a state of the science report evaluating the influence current management decisions and climatic conditions have on possible adaptation strategies for pinyon-juniper woodlands.

Species distribution models (SDMs) are commonly used to assess potential climate change impacts on biodiversity, but several critical methodological decisions are often made arbitrarily. We compare variability arising from these decisions to the uncertainty in future climate change itself. We also test whether certain choices offer improved skill for extrapolating to a changed climate and whether internal cross-validation skill indicates extrapolative skill. We compared projected vulnerability for 29 wetland-dependent bird species breeding in the climatically dynamic Prairie Pothole Region, USA. For each species we built 1,080 SDMs to represent a unique combination of: future climate, class of climate covariates, collinearity level, and thresholding procedure. We examined the variation in projected vulnerability attributed to each uncertainty source. To assess extrapolation skill under a changed climate, we compared model predictions with observations from historic drought years. Uncertainty in projected vulnerability was substantial, and the largest source was that of future climate change. Large uncertainty was also attributed to climate covariate class with hydrological covariates projecting half the range loss of bioclimatic covariates or other summaries of temperature and precipitation. We found that choices based on performance in cross-validation improved skill in extrapolation. Qualitative rankings were also highly uncertain. Given uncertainty in projected vulnerability and resulting uncertainty in rankings used for conservation prioritization, a number of considerations appear critical for using bioclimatic SDMs to inform climate change mitigation strategies. Our results emphasize explicitly selecting climate summaries that most closely represent processes likely to underlie ecological response to climate change. For example, hydrological covariates projected substantially reduced vulnerability, highlighting the importance of considering whether water availability may be a more proximal driver than precipitation. However, because cross-validation results were correlated with extrapolation results, the use of cross-validation performance metrics to guide modeling choices where knowledge is limited was supported.

The Liaison Project increased communications between the North Central Climate Science Center (NC CSC), other USGS Science Centers and potential collaborators including active members of the four Landscape Conservation Cooperatives (LCC) included in the NC CSC area. The project was initiated with listening sessions to determine partners’ interest in liaising with the NC CSC, and USGS liaison proposals were selected based on demonstrated ability to continue and initiate relationships with state, federal, tribal, university and other partners. Increased communications has resulted in activities to co-produce knowledge to support management decisions that are impacted by climate.

The Evaporative Demand Drought Index (EDDI) is an experimental drought monitoring and early warning guidance tool. It examines how anomalous the atmospheric evaporative demand (E0; also known as "the thirst of the atmosphere") is for a given location and across a time period of interest. EDDI is multi-scalar, meaning that this period—or "timescale"—can vary to capture drying dynamics that themselves operate at different timescales; we generate EDDI at 1-week through 12-month timescales. This webpage offers a frequently updated assessment of current conditions across CONUS, southern parts of Canada, and northern parts of Mexico; a tool to generate historical time series of EDDI for a user-selected region; introductions to the EDDI team; and a list of resources for users to explore EDDI and its applications further.

This dataset represents the area in the Greater Yellowstone Ecosystem prioritized for different whitebark pine(Pinus albicaulis) management activities, summarized by climate suitability zones. This data was developed for use in a landscape simulation modeling study aimed at evaluating how well alternative management strategies maintain whitebark pine populations under historical climate and future climate conditions. For the study, we developed three spatial management alternatives for whitebark pine in the Greater Yellowstone Ecosystem representing no active management, current management, and climate-informed management. These management alternatives were implemented in the simulaton model FireBGCv2 under historical climate and three future climate change scenarios - the HadGEM-ES, CESM1-CAM5, and CNRM-CM5 Global Circulation Models under the RCP 8.5 emissions scenario. We worked with the Greater Yellowstone Coordinating Committee's (GYCC) Whitebark Pine Subcommittee to develop this spatial representation of their current management strategy. The treatments mapped represent a set of the treatments recommended in the GYCC Whitebark Pine 2011 Strategy document and include planting blister-rust resistant whitebark pine seedlings, competition removal thinning, wildland fire use and prescribed fire, and protection from mountain pine beetles using verbenone and carbaryl. We used historical and future projections of climate suitability based on species distribution models for whitebark pine (Chang et al. 2014) to map zones of core, deteriorating, and future whitebark pine habitat. Core zones were those areas that are currently suitable for whitebark and remain suitable in the future. Deteriorating zones were where the climatic conditions for whitebark pine are expected to decline. Future zones were areas that are projected to become newly suitable for whitebark pine. We then overlaid our climate zones for whitebark pine with similar projections of future climate suitability for all of whitebark pine’s competitors - Engelmann spruce, subalpine fir, lodgepole pine, and Douglas-fir (Piekielek et al. 2015. We discussed the different combinations of climate suitability zones (core, deteriorating, future) and potential future level of competition (low or high) from other species with the GYCC Whitebark Pine Subcommittee to determine which management activities should be prioritized within each management zone. The result is a map of management zones where different activities are prioritized to meet the goal of maintaining whitebark pine populations. This was used to determine which treatments would be implemented spatially during the simulation modeling, dependent upon additional criteria related to simulated stand-level conditions. In this dataset, we used the resulting map of spatially prioritized management activities to summarize the area prioritized for each management activity that fell within Core, Deteriorating, and Future climate suitability zones

This dataset represents the area in the Greater Yellowstone Ecosystem prioritized for different whitebark pine(Pinus albicaulis) management activities, summarized by land classes. This data was developed for use in a landscape simulation modeling study aimed at evaluating how well alternative management strategies maintain whitebark pine populations under historical climate and future climate conditions. For the study, we developed three spatial management alternatives for whitebark pine in the Greater Yellowstone Ecosystem representing no active management, current management, and climate-informed management. These management alternatives were implemented in the simulaton model FireBGCv2 under historical climate and three future climate change scenarios - the HadGEM-ES, CESM1-CAM5, and CNRM-CM5 Global Circulation Models under the RCP 8.5 emissions scenario. We worked with the Greater Yellowstone Coordinating Committee's (GYCC) Whitebark Pine Subcommittee to develop this spatial representation of their current management strategy. The treatments mapped represent a set of the treatments recommended in the GYCC Whitebark Pine 2011 Strategy document and include planting blister-rust resistant whitebark pine seedlings, competition removal thinning, wildland fire use and prescribed fire, and protection from mountain pine beetles using verbenone and carbaryl. We used historical and future projections of climate suitability based on species distribution models for whitebark pine (Chang et al. 2014) to map zones of core, deteriorating, and future whitebark pine habitat. Core zones were those areas that are currently suitable for whitebark and remain suitable in the future. Deteriorating zones were where the climatic conditions for whitebark pine are expected to decline. Future zones were areas that are projected to become newly suitable for whitebark pine. We then overlaid our climate zones for whitebark pine with similar projections of future climate suitability for all of whitebark pine’s competitors - Engelmann spruce, subalpine fir, lodgepole pine, and Douglas-fir (Piekielek et al. 2015. We discussed the different combinations of climate suitability zones (core, deteriorating, future) and potential future level of competition (low or high) from other species with the GYCC Whitebark Pine Subcommittee to determine which management activities should be prioritized within each management zone. The result is a map of management zones where different activities are prioritized to meet the goal of maintaining whitebark pine populations. This was used to determine which treatments would be implemented spatially during the simulation modeling, dependent upon additional criteria related to simulated stand-level conditions. In this dataset, we used the resulting map of spatially prioritized management activities to summarize the area prioritized for each management activity that fell within different land classifications (mutliple use forests, National Park Service lands, Wilderness lands, and non-federal lands).