The effects of climate change on the natural resources protected by Parks will likely be substantial, but geographically variable, due to local variation in climate trajectories and differences among ecosystems in their vulnerability to climate change. The projections of general circulation models (GCMs) indicate the possible magnitude and direction of future climate change for a region, but the utility of these projections for more local scales, those of individual National Park Service (NPS) units, are more uncertain because the coarse-scale GCMs lack much of the topographic detail that alters local climates. In addition, complex, interacting effects of temperature, precipitation, atmospheric CO2 concentrations, fire, and herbivores on the vegetation that is the foundational natural resource of many NPS units present challenges in assessing the effects of projected future climates on plant and animal assemblages managed by the NPS. In spring 2009, Wind Cave National Park (WICA) served as a case study in a workshop assessing the use of scenario planning as a tool for park management planning in the face of rapidly changing climate. One outcome of the workshop was the recognized need for quantitative models to better understand the range of possible vegetation changes under different future climates and management decisions. This report addresses this need; it describes our adaptation of a dynamic global vegetation model (DGVM) to WICA vegetation and the resulting projections of future vegetation under three future climate scenarios and 11 management scenarios determined by Park natural resource managers. Wind Cave National Park lies along a narrow transition zone between the ponderosa pine (Pinus ponderosa) forests of the Black Hills and the mixed grass prairie that once extended with few interruptions over the lower, gentler terrain, subject to warmer, drier climate to the east and south of the Park. The location and character of this transition is strongly influenced by fire frequency and intensity (Brown and Sieg 1999). Furthermore, the mixed grass prairie occupies a broader transition zone between eastern tallgrass prairie and the shortgrass prairie of the western Great Plains. The dominance of species characteristic of these two prairie types varies with soil moisture availability, evaporative demand, and recent grazing history (Cogan et al. 1999). In addition, Wind Cave lies near the midpoint of a long gradient of C3 (cool season) grass dominance to the north and C4 (warm season) grass dominance to the south. The ecotonal position of WICA may make it particularly sensitive to climate change. For example, small changes in fire frequency and/or intensity and the vigor of trees vs. grass could dramatically shift the proportions of these two lifeforms. The Park hydrology is also sensitive to changes in the balance between infiltration of precipitation and evapotranspiration, as on average, only a small fraction of annual precipitation reaches the deeper soil layers that feed permanent streamflow. The resources at risk at Wind Cave NP include the Cave itself, as well as small backcountry caves, a genetically important bison herd, and other prairie species including the black-tailed prairie dog and endangered black-footed ferrets. All of these resources will be directly affected by climate change impacts on vegetation and hydrology. Natural resource management challenges at WICA are substantial, diverse, and intertwined. Aboveground, the park has been recognized as exemplary for its high quality vegetation (Marriot et al. 1999), though the park is relatively small for the diversity of vegetation types and species that it supports. Even without a changing climate, maintaining the integrity of the plant communities is complicated by the park’s legislated responsibility to maintain viable populations of bison, elk and pronghorn. In addition, the federally endangered black-footed ferret was recently re-introduced to the park. This species requires large extents of prairie dog towns for prey and habitat. Prairie dogs impact vegetation by constant clipping, grazing and soil disturbance, thereby affecting plant composition and productivity. Moreover, naturally high interannual climate variability and the strong influence of precipitation on grass productivity in this region combine to yield high interannual variability in the amount of forage available for the wildlife that the park is tasked to maintain. Finally, fire, which is now primarily controlled by WICA and NPS Northern Great Plains fire management programs, is intertwined with all other natural resource issues at WICA, as it can impact prairie dog colony and forest expansion, ungulate foraging behavior, invasive plant species, and hydrological processes. Although not capable of capturing all of these complexities, dynamic vegetation models do provide a means for quantitatively projecting vegetation futures in future climates under plausible fire and grazing regimes. Our work uses the DGVM MC1 to simulate the effects of future climate projections and management practices on the vegetation of WICA. MC1 is designed to project potential vegetation as influenced by natural processes and hence is appropriate for national parks, where conservation of native biota and ecosystems is of great importance. Since the initial application of MC1 to a small portion of WICA (Bachelet et al. 2000), the model has been altered to improve model performance with the inclusion of dynamic fire. Applying this improved version to WICA required substantial recalibration, during which we have made a number of improvements to MC1 that will be incorporated as permanent changes. In this report we document these changes and our calibration procedure following a brief overview of the model. We compare the projections of current vegetation to the current state of the park and present projections of vegetation dynamics under future climates downscaled from three GCMs selected to represent the existing range in available GCM projections. In doing so, we examine the consequences of different management options regarding fire and grazing, major aspects of biotic management at Wind Cave.

Hydrologic models are used throughout the world to forecast and simulate streamflow, inform water management, municipal planning, and ecosystem conservation, and investigate potential effects of climate and land-use change on hydrology. The USGS Modeling of Watershed Systems (MoWS) group is currently developing the infrastructure for a National Hydrologic Model (NHM) to support coordinated, comprehensive, and consistent hydrologic model development and application. The NHM is expected to provide internally consistent estimates of total water availability, water sources, and streamflow timing, and measures of uncertainty around these estimates, for the entire United States. VisTrails, a scientific workflow and provenance management system (www.vistrails.org), could be used to facilitate consistent, organized, reproducible data management, analysis, and visualization for the NHM. A VisTrails system for the USGS Monthly Water Balance model (MWB) and/or the USGS Precipitation-Runoff Modeling System (PRMS) would be widely used in the NHM effort as well as by numerous agencies and researchers for individual model applications. Project Researchers worked with North Central Climate Science Center (NC CSC) staff to develop a VisTrails system for MWB, as a first step in developing a more complex VisTrails system for PRMS. The resulting VisTrails system for MWB has facilitated consistent, organized, and reproducible model calibration and simulations for monthly streamflow projections by research hydrologists and managers nationwide.

The goal of this project was to inform implementation of the Greater Yellowstone Coordinating Committee (GYCC) Whitebark Pine (WBP) subcommittee’s “WBP Strategy” based on climate science and ecological forecasting. Project objectives were to: 1. Forecast ecosystem processes and WBP habitat suitability across the Greater Yellowstone Area (GYA) under alternative IPCC future scenarios; 2. Improve understanding of possible response to future climate by analyzing WBP/climate relationships in past millennia; 3. Develop WBP management alternatives; 4. Evaluate the alternatives under IPCC future scenarios in terms of WBP goals, ecosystem services, and costs of implementation; and 5. Draw recommendations for implementation of the GYCC WBP strategy that consider uncertainty. Recommendations were derived in a scenario planning workshop based on both the results and uncertainty in the results. These recommendations are expected to thus be immediately acted upon by the GYA management community and the approach and methods are readily applicable to the several other tree species that are undergoing die-offs under changing climate. 

The Prairie Pothole Region spans parts of North and South Dakota, Minnesota, Montana, Iowa and south-central Canada and contains millions of wetlands that provide habitat for breeding and migrating birds. Because it is the continent’s most important breeding area for waterfowl, conservation and management largely focuses on protecting habitat for nesting ducks. However, other wetland-dependent birds also rely on this region, and it is important to understand the degree to which habitat conserved for ducks provides habitat for other species, and how the quality of this habitat will be affected by climate change. Project researchers tested whether waterfowl are effective representatives, or surrogates, for other wetland-dependent birds by predicting how climate change will affect habitat suitability for waterfowl and other species. The team also considered how climate change is likely to affect land-use patterns and agricultural conversion risk, and used these predictions to identify areas of the landscape where both waterfowl and other species were expected to have suitable habitat in the future. This research was intended to help managers efficiently direct their resources towards conserving areas that will provide habitat to a broad suite of species.

Southwestern Colorado is already experiencing the effects of climate change in the form of larger and more severe wildfires, prolonged drought, and earlier snowmelt. Climate scientists expect the region to experience more summer heat waves, longer-lasting and more frequent droughts, and decreased river flow in the future. These changes will ultimately impact local communities and challenge natural resource managers in allocating water under unpredictable drought conditions, preserving forests in the face of changing fire regimes, and managing threatened species under shifting ecological conditions.   In light of the wide-ranging potential impacts of climate change in the region, this project sought to help decision-makers develop strategies to reduce climate change impacts on people and nature. Scientists, land managers, and local communities worked together to identify actions that can be taken to reduce the negative impacts of climate change. Known as “adaptation strategies”, these actions are an essential component of effective planning under shifting climate conditions. To facilitate the planning process, researchers aimed to provide information on the vulnerability of ecosystems, model plausible future climate conditions, and identify the social contexts in which adaptation decisions are made.   The project focused on the San Juan and upper Gunnison river basins of southwestern Colorado, though the goal was to develop an adaptation toolkit that can be applied to other landscapes. By identifying appropriate adaptation actions, this project was designed to help improve the resilience of local communities and ecosystems in the face of an uncertain future. Learn more about how this project is progressing in its second phase: Building Social and Ecological Resilience to Climate Change in Southwestern Colorado: Phase 2

Through its Foundational Science Area (FSA) activities, the North Central Climate Science Center (CSC) aims to provide relevant and usable climate information to decision-makers and natural resource managers, so that they can better manage their natural and cultural resources under climate change. Research to meet this objective was implemented in 2013 through three FSAs: (1) Understanding and quantifying drivers of regional climate changes; (2) connecting climate drivers to management targets; and (3) characterizing adaptive capacity of stakeholder communities and informing management options. FSA 1 focused on developing targeted climate information for the North Central region, such as changes in air temperature and evapotranspiration. Through FSA 2, this climate data was used to help resource managers identify the vulnerability of conservation targets, such as particular plant or animal populations, to changing conditions. Finally, FSA 3 focused on identifying how various climate changes have already affected management practices, with the goal of understanding the ability of managers to implement adaptation and mitigation strategies in repsonse to changing conditions.   These areas of research contribute to the development of a coordinated and integrated approach to the management of the North Central region’s natural and cultural resources, utilizing the best possible understanding of past, present, and future climate. The knowledge gained from this research was also used by the North Central CSC to provide expertise and consultation on the services and tools being developed by the CSC, to ensure that the CSC’s research and tools are both relevant and useable to resource managers throughout the region.   

Climate change is poised to alter natural systems, the frequency of extreme weather, and human health and livelihoods. In order to effectively prepare for and respond to these challenges in the north-central region of the U.S., people must have the knowledge and tools to develop plans and adaptation strategies. The objective of this project was to build stakeholders’ capacity to respond to climate change in the north-central U.S., filling in gaps not covered by other projects in the region. During the course of this project, researchers focused on three major activities:   Tribal Capacity Building: Researchers provided tribal colleges and universities with mini-grants to develop student projects to document climate-related changes in weather and culturally or traditionally significant plants. These efforts, carried out in collaboration with other organizations, contributed to building the Indigenous Geography Phenology Network, a locally grounded, national network for documenting the impacts of climate change on plants and animals. Researchers also helped the Intertribal Council On Utility Policy determine how climate science could be integrated into management decisions in the resource-rich Missouri River Basin.   Climate Training for Resource Managers: Researchers offered two climate change vulnerability assessment courses – one in Jackson, Wyoming and another in La Crosse, Wisconsin – designed to build the knowledge and skills of resource managers. Additional trainings on climate-smart conservation are being planned.   PhenoCam Deployment: Researchers co-supported the deployment of PhenoCams (streaming cameras) in locations throughout Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, and Wyoming. Observations collected by the PhenoCams will help scientists track seasonal changes across the region and better understand how climate impacts living things.

Large shifts in species ranges have been predicted under future climate scenarios based primarily on niche-based species distribution models. However, the mechanisms that would cause such shifts are uncertain. Natural and anthropogenic fires have shaped the distributions of many plant species, but their effects have seldom been included in future projections of species ranges. Here, we examine how the combination of climate and fire influence historical and future distributions of the ponderosa pine–prairie ecotone at the edge of the Black Hills in South Dakota, USA, as simulated by MC1, a dynamic global vegetation model that includes the effects of fire, climate, and atmospheric CO2 concentration on vegetation dynamics. For this purpose, we parameterized MC1 for ponderosa pine in the Black Hills, designating the revised model as MC1-WCNP. Results show that fire frequency, as affected by humidity and temperature, is central to the simulation of historical prairies in the warmer lowlands versus woodlands in the cooler, moister highlands. Based on three downscaled general circulation model climate projections for the 21st century, we simulate greater frequencies of natural fire throughout the area due to substantial warming and, for two of the climate projections, lower relative humidity. However, established ponderosa pine forests are relatively fire resistant, and areas that were initially wooded remained so over the 21st century for most of our future climate x fire management scenarios. This result contrasts with projections for ponderosa pine based on climatic niches, which suggest that its suitable habitat in the Black Hills will be greatly diminished by the middle of the 21st century. We hypothesize that the differences between the future predictions from these two approaches are due in part to the inclusion of fire effects in MC1, and we highlight the importance of accounting for fire as managed by humans in assessing both historical species distributions and future climate change effects.

An important component in the fields of ecology and conservation biology is understanding the environmental conditions and geographic areas that are suitable for a given species to inhabit. A common tool in determining such areas is species distribution modeling which uses computer algorithms to determine the spatial distribution of organisms. Most commonly the correlative relationships between the organism and environmental variables are the primary consideration. The data requirements for this type of modeling consist of known presence and possibly absence locations of the species as well as the values of environmental or climatic covariates thought to define the species habitat suitability at these locations. These covariate data are generally extracted from remotely sensed imagery, interpolated/gridded historical climate data, or downscaled climate model output. Traditionally, ecologists and biologists have constructed species distribution models using workflows and data that reside primarily on their local workstations or networks. This workflow is becoming challenging as scientists increasingly try to use these modeling techniques to inform management decisions under different climate change scenarios. This challenge stems from the fact that remote sensing products, gridded historical climate, and downscaled climate models are not only increasing in spatial and temporal resolution but proliferating as well. Any rigorous assessment of uncertainty requires a computationally intensive sensitivity analysis accounting for various sources of uncertainty. The scientists fitting these models generally do not have the background in computer science required to take advantage of recent advances in web-service based data acquisition, remote high-powered data processing, or scientific workflow systems. Ecologists in the field of modeling are in need of a tractable platform that abstracts the inherent computational complexity required to incorporate the burgeoning field of coupled climate and ecological response modeling. In this paper we describe the computational challenges in species distribution modeling and solutions using scientific workflow systems. We focus on the Software for Assisted Species Modeling (SAHM) a package within VisTrails, an open-source scientific workflow system.