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.

The Software for Assisted Habitat Modeling (SAHM) has been created to both expedite habitat modeling and help maintain a record of the various input data, pre- and post-processing steps and modeling options incorporated in the construction of a species distribution model through the established workflow management and visualization VisTrails software. This paper provides an overview of the VisTrails:SAHM software including a link to the open source code, a table detailing the current SAHM modules, and a simple example modeling an invasive weed species in Rocky Mountain National Park, USA. 

Abstract (from http://www.esajournals.org/doi/abs/10.1890/13-0905.1):  Many protected areas may not be adequately safeguarding biodiversity from human activities on surrounding lands and global change. The magnitude of such change agents and the sensitivity of ecosystems to these agents vary among protected areas. Thus, there is a need to assess vulnerability across networks of protected areas to determine those most at risk and to lay the basis for developing effective adaptation strategies. We conducted an assessment of exposure of U.S. National Parks to climate and land use change and consequences for vegetation communities. We first defined park protected-area centered ecosystems (PACEs) based on ecological principles. We then drew on existing land use, invasive species, climate, and biome data sets and models to quantify exposure of PACEs from 1900 through 2100. Most PACEs experienced substantial change over the 20th century (>740% average increase in housing density since 1940, 13% of vascular plants are presently nonnative, temperature increase of 1°C/100 yr since 1895 in 80% of PACEs), and projections suggest that many of these trends will continue at similar or increasingly greater rates (255% increase in housing density by 2100, temperature increase of 2.5° - 4.5°C/100 yr, 30% of PACE areas may lose their current biomes by 2030). In the coming century, housing densities are projected to increase in PACEs at about 82% of the rate of since 1940. The rate of climate warming in the coming century is projected to be 2.5 - 5.8 times higher than that measured in the past century. Underlying these averages, exposure of individual park PACEs to change agents differ in important ways. For example, parks such as Great Smoky Mountains exhibit high land use and low climate exposure, others such as Great Sand Dunes exhibit low land use and high climate exposure, and a few such as Point Reyes exhibit high exposure on both axes. The cumulative and synergistic effects of such changes in land use, invasives, and climate are expected to dramatically impact ecosystem function and biodiversity in national parks. These results are foundational to developing effective adaptation strategies and suggest policies to better safeguard parks under broad-scale environmental change.