The chapters of this book have delved into the timely and important topic of science and management of wildland ecosystems in the face of climate and land use change. The period of the book’s development (2011–2015) was one of rapid advancement in science, policy, agency infrastructure, and understanding of climate change adaptation (chaps. 2, 3, and 13). During this period, evidence of climate change and its consequences was ever more apparent. This was the warmest five-year period on record (http://www.ncdc.noaa.gov). Extreme climate events, such as droughts in California, Amazonia, and Australia, caused fundamental changes in allocating water to people and managing human risk from fire. Evidence of the ecological impacts of climate change became pervasive, including forest die-offs in many parts of the world and massive bleaching of coral ecosystems.

Grassland loss has been extensive worldwide, endangering the associated biodiversity and human well-being that are both dependent on these ecosystems. Ecologists have developed approaches to restore grassland communities and many have been successful, particularly where soils are rich, precipitation is abundant, and seeds of native plant species can be obtained. However, climate change adds a new filter needed in planning grassland restoration efforts. Potential responses of species to future climate conditions must also be considered in planning for long-term resilience. We demonstrate this methodology using a site-specific model and a maximum entropy approach to predict changes in habitat suitability for 33 grassland plant species in the tallgrass prairie region of the U.S. using the Intergovernmental Panel on Climate Change scenarios A1B and A2. The A1B scenario predicts an increase in temperature from 1.4 to 6.4°C, whereas the A2 scenario predicts temperature increases from 2 to 5.4°C and much greater CO2 emissions than the A1B scenario. Both scenarios predict these changes to occur by the year 2100. Model projections for 2040 under the A1B scenario predict that all but three modeled species will lose ~90% of their suitable habitat. Then by 2080, all species except for one will lose ~90% of their suitable habitat. Models run using the A2 scenario predict declines in habitat for just four species by 2040, but models predict that by 2080, habitat suitability will decline for all species. The A2 scenario appears based on our results to be the less severe climate change scenario for our species. Our results demonstrate that many common species, including grasses, forbs, and shrubs, are sensitive to climate change. Thus, grassland restoration alternatives should be evaluated based upon the long-term viability in the context of climate change projections and risk of plant species loss.

Evaporative demand (E0) both drives and responds to droughts based on interactions across the land surface-atmosphere interface, and can be exploited to signal agricultural, hydrologic, and ecological droughts. In this chapter, we argue that using a fully physically based measure of E0 moves the drought community toward a more complete understanding of drought processes that will enhance its abilities with regard to early warning and drought monitoring in the present day and drought-risk assessment under future climate change scenarios. We examine regional characteristics in E0 and their behavior during droughts in the recent historical period across different hydroclimates. We review physical mechanisms driving extremes in E0 and how climate change could influence their behavior in both driving and responding to extreme droughts in the 21st century. Finally, we discuss plant physiological responses under elevated atmospheric CO2 and their consequences for drought and heat stress on plants.

This paper describes the motivation for the creation of the Vulnerability, Impacts, Adaptation and Climate Services (VIACS) Advisory Board for the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), its initial activities, and its plans to serve as a bridge between climate change applications experts and climate modelers. The climate change application community comprises researchers and other specialists who use climate information (alongside socioeconomic and other environmental information) to analyze vulnerability, impacts, and adaptation of natural systems and society in relation to past, ongoing, and projected future climate change. Much of this activity is directed toward the co-development of information needed by decision-makers for managing projected risks. CMIP6 provides a unique opportunity to facilitate a two-way dialog between climate modelers and VIACS experts who are looking to apply CMIP6 results for a wide array of research and climate services objectives. The VIACS Advisory Board convenes leaders of major impact sectors, international programs, and climate services to solicit community feedback that increases the applications relevance of the CMIP6-Endorsed Model Intercomparison Projects (MIPs). As an illustration of its potential, the VIACS community provided CMIP6 leadership with a list of prioritized climate model variables and MIP experiments of the greatest interest to the climate model applications community, indicating the applicability and societal relevance of climate model simulation outputs. The VIACS Advisory Board also recommended an impacts version of Obs4MIPs and indicated user needs for the gridding and processing of model output.

Scenario planning is a useful tool for identifying key vulnerabilities of ecological systems to changing climates, informed by the potential outcomes for a set of divergent, plausible, and relevant climate scenarios. We evaluated potential vulnerabilities of grassland communities to changing climate in the Southern Great Plains (SGP) and the Landscape Conservation Design pilot area (LCD) for the U.S. Fish and Wildlife Service, Science Applications Program, Great Plains Landscape Conservation Cooperative. Four climate scenarios (warm-dry, warm-wet, hot-dry, and hot-wet) from atmospheric-ocean general circulation models were selected to represent a suite of plausible future climatic conditions. For each scenario, and for contemporary climatic conditions, we predicted the spatial patterns of relative productivity for indicator grass species using statistical models of relative above-ground net primary productivity (hereafter, productivity) based on temperature, precipitation, and soil texture (percent sand, silt, or clay). Two indicator grass species were selected to represent each of four focal grassland communities: semi-desert grasslands, shortgrass prairie, mixed-grass prairie, and tallgrass prairie. Changes in spatial patterning of bioclimatic conditions conducive for each indicator species as predicted for each climate scenario relative to current land use were used to evaluate potential vulnerability and conservation opportunities for grassland communities. Specifically, the following questions were addressed for each focal grassland community: (1) Where is the productivity of each species predicted to increase, decrease, or remain stable relative to estimated contemporary productivity for the SGP and LCD pilot area, (2) where is the productivity of the two indicator species for each community predicted to increase, decrease, or remain stable, (3) which grassland communities are most vulnerable to changes in composition and vertical structure, (4) how do current land-use patterns contribute to potential vulnerabilities of grassland communities for the climate scenarios evaluated, and (5) how can managers use the vulnerabilities identified to evaluate conservation opportunities in the SGP and LCD? Current land-use patterns, in combination with the potential effects of a changing climate, pose greater risks to mixed-grass and tallgrass prairies of the SGP compared to semi-desert grasslands and shortgrass prairie. For most climate scenarios evaluated, bioclimatic conditions conducive to the taller species were predicted to contract within some or all the current distribution of mixed-grass and tallgrass prairies within the SGP. An increase in precipitation, however, could potentially ameliorate the negative effects of increasing temperatures as evidenced by higher productivity for the hot-wet scenario compared to the other scenarios for the most vulnerable species. Compounding their greater vulnerability to increasing temperatures coupled with decreasing precipitation, the mixed-grass and tallgrass prairies have been greatly fragmented and converted, primarily by agriculture. In contrast, the climate scenarios evaluated are generally conducive to stable or increasing productivity of indicator species for semi-desert grasslands and shortgrass prairie. In addition, conversion and fragmentation of semi-desert grasslands and shortgrass prairie were relatively low. These results suggest that the synergistic effects of land use and changing climatic conditions could have the greatest effects on the composition and structure of mixed-grass and tallgrass prairies in the SGP.

The Great Plains Grassland Summit: Challenges and Opportunities from North to South was held April 10-11, 2018 in Denver, Colorado to provide syntheses of information about key grassland topics of interest in the Great Plains; networking and learning channels for managers, researchers, and stakeholders; and working sessions for sharing ideas about challenges and future research and management opportunities. The summit was convened to better understand stressors and resource demands throughout the Great Plains and how to manage them, and to discuss methods for improved collaboration among natural resource managers, scientists, and stakeholders. Over 200 stakeholders, who collectively were affiliated with all of the Great Plains States, attended the summit. Attendees included university researchers, government scientists, and individuals affiliated with Federal and State agencies, tribes, the private sector, and nongovernmental organizations. Plenary speakers provided syntheses of current knowledge on key topics to help stage working sessions on working lands, native wildlife and biological diversity, native plants and pollinators, invasive species, wildland and prescribed fire, energy development, and weather, water, and climate. The summit steering committee designed a suite of questions that were asked of participants in each working session. This report is a digest of the input from those who attended the seven working sessions and responded to the structured questions.

To characterize eruption activity of the iconic Old Faithful Geyser in Yellowstone National Park over past centuries, we obtained 41 new radiocarbon dates of mineralized wood preserved in the mound of silica that precipitated from erupted waters. Trees do not grow on active geyser mounds, implying that trees grew on the Old Faithful Geyser mound during a protracted period of eruption quiescence. Rooted stumps and root crowns located on higher parts of the mound are evidence that at the time of tree growth, the geyser mound closely resembled its current appearance. The range of calibrated radiocarbon dates (1233–1362 CE) is coincident with a series of severe multidecadal regional droughts toward the end of the Medieval Climate Anomaly, prior to the onset of the Little Ice Age. Climate models project increasingly severe droughts by mid‐21st century, suggesting that geyser eruptions could become less frequent or completely cease.

In recent decades, Rocky Mountain accumulated snowpack levels have experienced rapid declines, yet long-term records of snowpack prior to the installation of snowpack observation stations in the early and mid 20th century are limited. To date, a small number of tree-ring based reconstructions of April 1 Snow Water Equivalent (SWE) in the northern Rocky Mountains have extended modern records of snowpack variability to ~1200 C.E. Carbonate isotope lake sediment records, provide an opportunity to further extend tree-ring based reconstructions through the Holocene, providing a millennial-scale temporal record that allows for an evaluation of multi-scale drivers of snowpack variability, from internal climate dynamics to orbital-scale forcings. Here we present a ~2200 year preliminary reconstruction of northern Rockies snowpack based on d18O measurements of sediment carbonates collected from Foy Lake, Montana. We explore the statistical calibration of lake sediment d18O to an annually resolved snowpack reconstruction from tree rings, and develop an approach to assess and quantify potential sources of error in this reconstruction approach. The sediment-based snowpack reconstruction shows strong low-frequency variability in snowpack over the last two millennia with few snow droughts approaching the magnitude of recent snowpack declines. Given the growing availability of high-resolution, carbonate-rich lake sediment records, such reconstructions could help improve our understanding of how snowpack conditions varied under previous climatic events (mid-Holocene climate optimum ca. 9-6 ka), providing critical insights for anticipating future snowpack conditions.