The sagebrush ecosystem is home to diverse wildlife, including big-game and Greater sage-grouse. Historic and contemporary land-uses, large wildfires, exotic plant invasion, and woodland expansion all represent threats to this multiple-use landscape. Efforts of federal and state agencies and private landowners across the landscape are focused on restoration and maintenance of conditions that support wildlife, livestock, energy development, and many other uses. However, this semi-arid landscape presents challenges for management due to highly variable patterns in growing conditions that lead to differences in plant composition, fuel accumulation, and vegetation recovery. Much of this variability is created by soil and climate conditions. Because of their fundamental effects on plant growth, soil and climate patterns can be used to predict plant growth and regeneration. This information can then help managers understand the long-term persistence of ecosystems, resilience after wildfires and habitat treatments, and the potential for invasive weeds such as cheatgrass to spread.   This project focuses on better understanding the resistance and resilience of the sagebrush landscape to habitat change. The resistance of an ecosystem refers to how well it can maintain its processes when subjected to stress, such as a drought or wildfire, while the resilience of an ecosystem refers to how well it can recover from a stressor or adapt to changing conditions. To do this, researchers will characterize future variability in the soil environment and the sensitivity of growing conditions to potential future changes in temperature and precipitation. Instead of broadly classified climate regions, researchers will model a continuous surface of grid cells using the soil and climate conditions unique to each location. This enables the development of estimates of soil temperature and moisture across a large landscape that take into account both local and landscape-scale conditions. Researchers will also incorporate scenarios of potential future changes in temperature and precipitation, to assess the implications of these changes for habitat conditions, restoration outcomes, and fuel profiles. A better understanding of the patterns of plant production, resistance of the sagebrush ecosystem to invasion by non-native plants, and resilience of the ecosystem following wildfires can inform habitat management activities, such as restoration and reclamation.

Changing climate conditions can make water management planning and drought preparedness decisions more complicated than ever before.  Federal and State natural resource managers can no longer rely solely on historical trends as a baseline and thus are in need of science that is relevant to their specific needs to inform important planning decisions. Questions remain, however, regarding the most effective and efficient methods for extending scientific knowledge and products into management and decision-making. This project analyzed two unique cases of water management to better understand how science can be translated into resource management actions and decision-making, focusing particularly on how the context of how drought influences ecosystems. In particular, this project sought to understand (1) the characteristics that make science actionable and useful for water resource management and drought preparedness, and (2) the ideal types of scientific knowledge or science products that facilitate the use of science in management and decision making. The first case study focused on beaver mimicry, an emerging nature-based solution that increases the presence of wood and woody debris in rivers and streams to mimic the actions of beavers. This technique has been rapidly adopted by natural resource managers as a way to restore riparian areas, reconnect incised streams with their floodplains, increase groundwater infiltration, and slow surface water flow so that more water is available later in the year during hotter and drier months (Pollock and others 2015). The second case study focused on an established research program, Colorado Dust on Snow, that provides water managers with scientific information explaining how the movement of dust particles from the Colorado Plateau influences hydrology and the timing and intensity of snow melt and water runoff into critical water sources. This program has support from – and is being used by – several water conservation districts in Colorado. Understanding how scientific knowledge translates into action and decision-making in these cases is useful to strengthen knowledge of actionable science for drought management. The project team gathered qualitative data through stakeholder conversations and conducted an extensive literature review. In the case of beaver mimicry, the research identified perceived benefits of and barriers to using beaver mimicry structures and considered how these differ between managers and scientists. The dust on snow case results focused on how and why dust monitoring information is used. Findings from these efforts were also incorporated into a broader Intermountain West Drought Social Science Synthesis effort to determine and assess commonalities and differences among socio-ecological aspects of drought adaptation and planning.

Abstract (from Frontiers in Ecology and Evolution): Tallgrass prairie ecosystems in North America are heavily degraded and require effective restoration strategies if prairie specialist taxa are to be preserved. One common management tool used to restore grassland is the application of a seed-mix of native prairie plant species. While this technique is effective in the short-term, it is critical that species' resilience to changing climate be evaluated when designing these mixes. By utilizing species distribution models (SDMs), species' bioclimatic envelopes–and thus the geographic area suitable for them–can be quantified and predicted under various future climate regimes, and current seed-mixes may be modified to include more climate resilient species or exclude more affected species. We evaluated climate response on plant functional groups to examine the generalizability of climate response among species of particular functional groups. We selected 14 prairie species representing the functional groups of cool-season and warm-season grasses, forbs, and legumes and we modeled their responses under both a moderate and more extreme predicted future. Our functional group “composite maps” show that warm-season grasses, forbs, and legumes responded similarly to other species within their functional group, while cool-season grasses showed less inter-species concordance. The value of functional group as a rough method for evaluating climate-resilience is therefore supported, but candidate cool-season grass species will require more individualized attention. This result suggests that seed-mix designers may be able to use species with more occurrence records to generate functional group-level predictions to assess the climate response of species for which there are prohibitively few occurrence records for modeling.

Science produced by the National and Regional Climate Adaptation Science Center (CASC) network must ideally be scientifically sound, relevant to a management decision, fair and respectful of stakeholders’ divergent values, and produced through a process of iterative collaboration between scientists and managers. However, research that aims to produce usable knowledge and collaborative approaches that boost usability are not common in academia or federal research programs. As a result, neither the process of creating such research nor the impacts to stakeholders are well understood or well documented. This lack of attention to the processes and impacts of collaborative scientist-stakeholder knowledge production also limits our ability to evaluate research outcomes beyond standard academic metrics such as number of peer reviewed journal publications, conference presentations, or students trained.   CASC-funded researchers have previously proposed a cohort of 45 indicators for evaluating the co-production of climate knowledge by conducting a review of the academic literature, examining metrics used by other agencies to evaluate usable science, and compiling insights from experienced researchers and managers. While this research has resulted in a rich set of data, constraints on resources, such as time and funding, have limited the team to working with a small sample of case study projects from the Southwest and Northwest CASCs.   This project will address the issue of scalability in evaluation, both in terms of number of projects evaluated and number of stakeholders targeted. An evaluation approach that encompasses a center’s full portfolio of projects will better enable the intercomparison of funding choices and co-production approaches. This evaluation will focus on completed projects from the North Central and South Central CASCs. Researchers will distribute a survey to targeted stakeholders in order to learn more about their interactions with project teams and their use of specific products. Results from this project will inform decisions made by the CASC network about future projects in order to ensure good stewardship of federal funds.

Grasslands in the northern Great Plains are important ecosystems that support local economies, tribal communities, livestock grazing, diverse plant and animal communities, and large-scale migrations of big game ungulates, grassland birds, and waterfowl. Climate change and variability impact how people and animals live on and interact with grasslands, and can bring more frequent droughts, fires, or new plant species that make managing these landscapes challenging. Understanding how climate change and variability will impact grassland ecosystems and their management in the 21st century first requires a synthesis of what is known across all of these scales and a gap analysis to identify key areas of focus for future research. Researchers will address this need by conducting a series of synthesis efforts to (1) identify and describe known management questions and information needs of stakeholders related to grasslands; (2) assess the state-of-the-science on climate change and variability in the northern Great Plains region; and (3) describe ecological responses to climate variability and change across the grasslands, including tipping points, changing fire patterns, spreading invasive species, changing species distributions, habitat fragmentation, and other changes in ecological communities. This project supports resource managers by providing them with the scientific information needed to make best-practice management decisions about northern Great Plains grasslands and will foster relationships with the conservation and management organizations that will utilize this science to make decisions about public lands.

The North Central Climate Adaptation Science Center (NC CASC) partnered with the Wildlife Conservation Society (WCS) and Conservation Science Partners, Inc. (CSP) to systematically identify information gaps that, if addressed, would support management decisions for key species, habitats, or other issues within the North Central region (Montana, Wyoming, Colorado, North Dakota, South Dakota, Nebraska, Kansas). In particular, we were interested in the intersection between 1) high-priority species or habitats that are 2) the subject of a planned decision, and for which 3) climate information would aid decision-making for state and federal agencies. In Spring of 2018, we interviewed state fish and wildlife managers to learn about high-priority species, habitats, and issues within the North Central region. As described in this report, the interviews generated a wealth of information about state agency priorities, and topics for which state managers think more climate change information would be useful.

Although drought is a natural part of climate across the north-central United States, how drought is experienced and responded to is the result of complex biophysical and social processes. Climate change assessments indicate drought impacts will likely worsen in the future, which will further challenge decision-making. Here, a drought management decision typology is empirically developed from synthesis of three in-depth case studies using a modified grounded-theory approach. The typology highlights 1) the entity or entities involved, 2) management sectors, 3) decision types, 4) spatial and temporal scale(s) of decision-making, and 5) barriers that inhibit decision-making. Findings indicate similarities in decision types and barriers across cases. Changes in operations, practices, or behaviors; information and technology; and legal or policy changes were the most common decision types, while commonly cited barriers were institutional constraints, fragmented decision-making, and limited personnel and financial resources. Yet barriers and responses also differed within and between sectors and jurisdictions. Several barriers inhibited anticipatory, regional, and interagency drought response, such as limited institutional support, competing mandates, limited resources, lack of usable information, limits to interagency fund transfers, and historical context and distrust among entities. Findings underscore the importance of documenting nuanced decision-making in local places and broader generalizations in decision-making across scales. This contributes to the goal of developing drought science that is actionable for decision-making.