Fossil fuel and agriculture have increased atmospheric concentrations of the greenhouse gases carbon dioxide and methane, which have caused global air temperature to increase by almost 1- degree Celsius. In the absence of climate mitigation, over the next century human-driven climate change is expected to increase temperatures from pre-industrial levels by more than 2-degrees. Understanding the consequences of climate change on ecosystems and the services they provide are critical for guiding land management activities that aim to improve resiliency and to prevent species losses. Here we evaluated how sagebrush ecosystems in the Western United States respond to climate change by using multiple climate projections and ecosystem modeling approaches to assess uncertainty and to identify future areas of field and experimental research. We find that in the absence of changes in fire, invasive species, and habitat loss, that sagebrush is tolerant of both low moisture levels and high air temperatures, and that climate change will impact the southern extent of its range most significantly. Process-based models, which consider the effects of carbon dioxide on leaf photosynthesis and water exchange show potential increases in the growth of sagebrush into the 21st century. Compared to field observations, there is a need to further constrain how sagebrush allocates carbon to roots, stems and foliage, and how these processes respond to water limitation. Agreement between modeling approaches that sagebrush is tolerant to higher air temperatures suggests that land managers should consider enhancing resilience of these systems through fire and invasive species management strategies.

The purpose of this project was to estimate and map the probability that grassland converts to cropland in the northern plains and prairie region given potential climate change. This region provides critical breeding and migratory habitat for waterfowl and other wetland-dependent species, and is also a highly productive agricultural region. Generally, the regional effects projected by climate models are increasing temperatures and more variable precipitation, which could provide incentives for private landowners to convert native and managed grassland to intensive cropland. Conversion of grassland to cropland can result in habitat loss for dependent species and the degradation of a range of ecosystem services. If climate change alters the spatial distribution of both agricultural land use and suitable habitat, land managers and conservationists may need to alter efforts to offset the negative consequences of combined climate and land-use change on habitats and dependent species. The land-use change projections associated with this report provide information for such management efforts.

In the previous first phase of the Impacts and Vulnerability project, we made substantial progress in assessing climate and land use change impacts across the NCCASC domain. These include: quantifying the rates of land use change in greater wildland ecosystems (GWEs), determining the extent of fragmentation in major ecosystems across GWEs, assessing climate change impacts on public, private, and tribal lands within GWEs, evaluating evaporative demands across hydroclimatic gradients of eight ecoregions across north central U.S., and predicting forest ecosystem responses to climate change. We found that rates of climate and land use change varied across the Great Plains and Rocky Mountains, as did the responses of ecosystems to these changes. We also identified the major locations highly impacted by these changes that call for crafting locally relevant adaptation strategies to cope with these changes. This second phase of the project (FY’17) aimed to generate coproduction of knowledge with a wide range of stakeholders to support decision making for the management and conservation of affected areas. During this FY’17 phase of the project, we worked with various user groups to evaluate potential land use and climate impacts and adaptation strategies for the most affected areas and ecosystem types identified by our previous work. Specifically, we focused on forest and shrubland vegetation and habitat of a selected wildlife species (Gulo gulo) in the Rocky Mountains and Washington Cascade regions. We also designed and produced resource briefs on land use and climate change assessments of selected areas and ecosystem types to provide information to coordinated management. Thirdly, we conducted series of webinars and workshops with federal, private, and NGO stakeholders to draw on all of the science results (e.g., from species distribution models, state and transition models, and mechanistic models) to identify and evaluate vegetation climate adaptation strategies for the Custer Gallatin National Forest Plan Revision that are robust under climate uncertainty.     

Historical and projected suitable habitat of 14 tree and shrub species a under CCSM4 GCMs from 2000 to 2099 was predicted to assess projected climate change impacts in forest communities of North Central U.S. We obtained presence/absence record of each species from Forest Inventory and Analysis (FIA) data. required ata. Historical tme period ranges from 1971 to 2000, and projected time period ranges from 2071 to 2100. Random Forest was used to project historical and future suitable habitat of all species across West U.S. using the Biomod2 software programmed in R environment. We adopted a climate change scenarios generated from the experiments conducted under fifth assessment of Coupled Model Intercomparison Project (CMIP5) for the Intergovernmental Panel on Climate Change. Selected climate change scenarios include high representative concentrative pathway (RCP8.5).

Abstract (from OxfordAcademic): The whitebark pine (Pinus albicaulis Engelm.) tree species faces precipitously declining populations in many locations. It is a keystone species found primarily in high-elevation forests across the Western US. The species is an early responder to climate change and qualifies for endangered species protection. We use contingent valuation to estimate the public’s willingness to pay for management of the whitebark pine species. In contrast, previous work centres on valuing broader aspects of forest ecosystems or threats to multiple tree species. While only approximately half of the survey respondents have seen whitebark pine, the mean willingness to pay for whitebark pine management is $135 per household. When aggregated across all households from the three sampled states, willingness to pay totals $163 million. This information is valuable to forest managers who must make difficult decisions in times of resource constraints and climate change.

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.

Prairies were once widespread across North America, but are now one of the most endangered and least protected ecosystems in the world. Agriculture and residential development have reduced once extensive prairies into a patchwork of remnant prairies and “surrogate” grasslands (e.g., hayfields, planted pastures). Grassland ecosystems and many grassland-dependent birds are also particularly vulnerable to rapid shifts in climate and associated changes in drought and extreme weather.   The Central Flyway is a vast bird migration route that comprises more than half of the continental U.S., and extends from Central America to Canada, and harbors the greatest diversity of grassland birds in North America. Throughout this region, numerous agencies and organizations are entrusted with the management of grassland ecosystems and the species that depend on them in landscapes extensively altered by human activities. Today, they face the additional challenge of managing these ecosystems in the face of a rapidly changing climate.   The goal of this project is to synthesize the vulnerability of grassland ecosystems to climate change across the Central Flyway, with an emphasis on grassland-dependent migratory birds. Researchers will synthesize the state of the science, including providing a robust assessment of how climate variables directly and indirectly (via land use change) affect grassland habitats and migratory bird populations. Researchers will also review current and future adaptation strategies for the conservation of grassland ecosystems and grassland-dependent birds. This effort will result in a synthesis of key management strategies and future research needs related to the conservation of migratory grassland bird populations in the Central Flyway in the face of climate change.

Abstract (from ScienceDirect): Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbon fluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle, we must also be able to understand and model its effects on dryland vegetation. Dynamic Global Vegetation Models (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduce seasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to both total productivity and competitive interactions with other plants, errors in how process-based models represent phenology hinder our ability to predict climate change impacts. This may be particularly problematic in dryland ecosystems where many species have developed a complex phenology in response to seasonal variability in both moisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure of existing phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) and gross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized model parameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, we modified the model to include a semi-deciduous phenology type and added flexibility to the representation of grass phenology. While optimizing parameters reduced model bias, the largest gains in model performance were associated with the development of our new representation of phenology. This modified model was able to better capture seasonal patterns of both leaf area index (R2 = 0.75) and gross primary productivity (R2 = 0.84), though its ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new model also resulted in a more realistic outcome of modeled competition between grass and shrubs. These findings demonstrate the importance of improving how DGVMs represent phenology in order to accurately forecast climate change impacts in dryland ecosystems.

Abstract (from Diversity and Distributions):  Aim Surrogate species can provide an efficient mechanism for biodiversity conservation if they encompass the needs or indicate the status of a broader set of species. When species that are the focus of ongoing management efforts act as effective surrogates for other species, these incidental surrogacy benefits lead to additional efficiency. Assessing surrogate relationships often relies on grouping species by distributional patterns or by species traits, but there are few approaches for integrating outputs from multiple methods into summaries of surrogate relationships that can inform decision‐making. Location Prairie Pothole Region of the United States. Methods We evaluated how well five upland‐nesting waterfowl species that are a focus of management may act as surrogates for other wetland‐dependent birds. We grouped species by their patterns of relative abundance at multiple scales and by different sets of traits, and evaluated whether empirical validation could effectively select among the resulting species groupings. We used an ensemble approach to integrate the different estimated relationships among species and visualized the ensemble as a network diagram. Results Estimated relationships among species were sensitive to methodological decisions, with qualitatively different relationships arising from different approaches. An ensemble provided an effective tool for integrating across different estimates and highlighted the Sora (Porzana carolina), American Avocet (Recurvirostra Americana) and Black Tern (Chlidonias niger) as the non‐waterfowl species expected to show the strongest incidental surrogacy relationships with the waterfowl that are the focus of ongoing management. Main conclusions An ensemble approach integrated multiple estimates of surrogate relationship strength among species and allowed for intuitive visualizations within a network. By accounting for methodological uncertainty while providing a simple continuous metric of surrogacy, our approach is amenable to both further validation and integration into decision‐making.