Abstract (from  http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0111669): Projected climate change at a regional level is expected to shift vegetation habitat distributions over the next century. For the sub-alpine species whitebark pine (Pinus albicaulis), warming temperatures may indirectly result in loss of suitable bioclimatic habitat, reducing its distribution within its historic range. This research focuses on understanding the patterns of spatiotemporal variability for future projected P.albicaulis suitable habitat in the Greater Yellowstone Area (GYA) through a bioclimatic envelope approach. Since intermodel variability from General Circulation Models (GCMs) lead to differing predictions regarding the magnitude and direction of modeled suitable habitat area, nine bias-corrected statistically down-scaled GCMs were utilized to understand the uncertainty associated with modeled projections. P.albicaulis was modeled using a Random Forests algorithm for the 1980-2010 climate period and showed strong presence/absence separations by summer maximum temperatures and springtime snowpack. Patterns of projected habitat change by the end of the century suggested a constant decrease in suitable climate area from the 2010 baseline for both Representative Concentration Pathways (RCPs) 8.5 and 4.5 climate forcing scenarios. Percent suitable climate area estimates ranged from 2-29% and 0.04-10% by 2099 for RCP 8.5 and 4.5 respectively. Habitat projections between GCMs displayed a decrease of variability over the 2010-2099 time period related to consistent warming above the 1910-2010 temperature normal after 2070 for all GCMs. A decreasing pattern of projected P.albicaulis suitable habitat area change was consistent across GCMs, despite strong differences in magnitude. Future ecological research in species distribution modeling should consider a full suite of GCM projections in the analysis to reduce extreme range contractions/expansions predictions. The results suggest that restoration strageties such as planting of seedlings and controlling competing vegetation may be necessary to maintain P.albicaulis in the GYA under the more extreme future climate scenarios. This publication was developed as part of the project,  Informing Implementation of the Greater Yellowstone Coordinating Committee’s (GYCC) Whitebark Pine (WBP) Strategy Based on Climate Sciences, Ecological Forecasting, and Valuation of WBP-Related Ecosystem Services.

Many semi-arid plant communities in western North America are dominated by big sagebrush. These ecosystems are being reduced in extent and quality due to economic development, invasive species, and climate change. These pervasive modifications have generated concern about the long-term viability of sagebrush habitat and sagebrush-obligate wildlife species (notably greater sage-grouse), highlighting the need for better understanding of the future big sagebrush distribution, particularly at the species' range margins. These leading and trailing edges of potential climate-driven sagebrush distribution shifts are likely to be areas most sensitive to climate change. We used a process-based regeneration model for big sagebrush, which simulates potential germination and seedling survival in response to climatic and edaphic conditions and tested expectations about current and future regeneration responses at trailing and leading edges that were previously identified using traditional species distribution models. Our results confirmed expectations of increased probability of regeneration at the leading edge and decreased probability of regeneration at the trailing edge below current levels. Our simulations indicated that soil water dynamics at the leading edge became more similar to the typical seasonal ecohydrological conditions observed within the current range of big sagebrush ecosystems. At the trailing edge, an increased winter and spring dryness represented a departure from conditions typically supportive of big sagebrush. Our results highlighted that minimum and maximum daily temperatures as well as soil water recharge and summer dry periods are important constraints for big sagebrush regeneration. Overall, our results confirmed previous predictions, i.e., we see consistent changes in areas identified as trailing and leading edges; however, we also identified potential local refugia within the trailing edge, mostly at sites at higher elevation. Decreasing regeneration probability at the trailing edge underscores the Schlaepfer et al. Future regeneration potential of big sagebrush potential futility of efforts to preserve and/or restore big sagebrush in these areas. Conversely, increasing regeneration probability at the leading edge suggest a growing potential for conflicts in management goals between maintaining existing grasslands by preventing sagebrush expansion versus accepting a shift in plant community composition to sagebrush dominance.

The TopoWx ('Topography Weather') dataset contains historical 30-arcsec resolution (~800-m) interpolations of daily minimum and maximum topoclimatic air temperature for the conterminous U.S. Using both DEM-based variables and MODIS land skin temperature as predictors of air temperature, interpolation procedures include moving window regression kriging and geographically weighted regression. To avoid artificial climate trends, all input station data are homogenized using the GHCN/USHCN Pairwise Homogenization Algorithm (http://www.ncdc.noaa.gov/oa/climate/research/ushcn/#phas). The interpolation model is open source and information on obtaining model code can be found at http://www.ntsg.umt.edu/project/TopoWx. The following data are available in this archive: 1948-2014 daily minimum and maximum temperature, and 1981-2010 monthly normals for minimum and maximum temperature with corresponding uncertainty (kriging prediction error). Ongoing annual updates will regenerate the entire dataset incorporating both new observations and model enhancements. This will result in a continuously improved dataset. However, different versions of TopoWx will be incompatible. For instance, data from the original 1948-2012 version should not be mixed with data from the new 1948-2014 version.

Abstract (from http://journal.frontiersin.org/article/10.3389/fpls.2014.00785/abstract): Fire is a key ecological process affecting vegetation dynamics and land cover. The characteristic frequency, size, and intensity of fire are driven by interactions between top-down climate-driven and bottom-up fuel-related processes. Disentangling climatic from non-climatic drivers of past fire regimes is a grand challenge in Earth systems science, and a topic where both paleoecology and ecological modeling have made substantial contributions. In this manuscript, we (1) review the use of sedimentary charcoal as a fire proxy and the methods used in charcoal-based fire history reconstructions; (2) identify existing techniques for paleoecological modeling; and (3) evaluate opportunities for coupling of paleoecological and ecological modeling approaches to better understand the causes and consequences of past, present, and future fire activity.

Abstract (from http://onlinelibrary.wiley.com/doi/10.1002/2014GL062803/abstract): Observations from the main mountain climate station network in the western United States (U.S.) suggest that higher elevations are warming faster than lower elevations. This has led to the assumption that elevation-dependent warming is prevalent throughout the region with impacts to water resources and ecosystem services. Here we critically evaluate this network's temperature observations and show that extreme warming observed at higher elevations is the result of systematic artifacts and not climatic conditions. With artifacts removed, the network's 1991–2012 minimum temperature trend decreases from +1.16°C decade−1 to +0.106°C decade−1 and is statistically indistinguishable from lower elevation trends. Moreover, longer-term widely used gridded climate products propagate the spurious temperature trend, thereby amplifying 1981–2012 western U.S. elevation-dependent warming by +217 to +562%. In the context of a warming climate, this artificial amplification of mountain climate trends has likely compromised our ability to accurately attribute climate change impacts across the mountainous western U.S.

The U.S. Northern Rocky Mountains support a large number of native wildlife species, and survival of these populations depends on connected landscapes to support current migration and dispersal, as well as future shifts in species’ ranges. However, habitat fragmentation and loss threaten these connections. Land and wildlife managers across the U.S. are faced with decisions focused on reducing risks, like those from habitat fragmentation, to wildlife, ecosystems, and landscapes. Establishing connections between natural landscapes is a frequently recommended strategy for these managers to help wildlife adapt to changing conditions. Working in partnership with state and federal resource managers and private land trusts, this project sought to 1) understand how future climate change may alter habitat composition of landscapes that are expected to serve as important connections for wildlife, 2) understand how wildlife species of concern are expected to respond to changing conditions, 3) develop strategies to help stakeholders manage public and private lands in ways that allow wildlife to continue to move in response to changing conditions, and 4) explore how well existing management plans and conservation efforts are expected to support crucial connections for wildlife under climate change.   

The conversion of grassland to cropland in the Dakotas could imperil wildlife such as nesting waterfowl and contribute to the degradation of water quality in the Mississippi River watershed. However, high crop prices in recent years have contributed to a high rate of grassland to cropland conversion on private lands. In addition to these economic factors, changes in climate could exacerbate the challenge of protecting grasslands, as conditions may become more amenable to row crop production.   The goal of this project was to work with grassland conservation managers to better target the use of funds allocated toward incentivizing grassland preservation in the Dakotas. Researchers identified the vulnerability of crop production to climate change, assessed the likelihood of grassland conversion to cropping, and calculated the costs of protecting grasslands under different future economic and climate scenarios.   Working with land conservation managers, researchers aimed to use these results to identify land parcels where grassland conservation investments would be most effective. For example, researchers aimed to develop a land conversion choice calculator that will compare long-run expected returns from different land uses under alternative climate and economic scenarios. By developing tools such as the land conversion choice calculator, this project is designed to help inform a critical component of grassland conservation – deciding which parcels to target for protection.  

The Wind River Indian Reservation in west-central Wyoming is home to the Eastern Shoshone and Northern Arapaho tribes, who reside near and depend on water from the streams that feed into the Wind River. In recent years, however, the region has experienced frequent severe droughts, which have impacted tribal livelihoods and cultural activities.   Scientists with the North Central Climate Science Center at Colorado State University, the National Drought Mitigation Center at the University of Nebraska-Lincoln, and several other university and agency partners are working closely with tribal water managers to assess how drought affects the reservation, integrating social, ecological, and hydro-climatological sciences with local knowledge. The findings were intended to help inform the creation of a climate monitoring system and drought management plan, which are being supported with additional technical and financial support from the High Plains Regional Climate Center and NOAA’s National Integrated Drought Information System. The drought plan integrated climate science with hydrologic, social, and ecological vulnerabilities and risks, and identify response capacities and strategies to support the Tribal Water Code and related resources management. Ultimately, the plan was designed to help the tribes ensure that agricultural and other societal needs are met during times of drought.   As part of the project, tribal water managers and the public were engaged in educational activities related to water resources and drought preparedness through joint activities with Wyoming Experimental Program to Stimulate Competitive Research to build the tribes’ ability to respond to future drought. Additionally, the Western Water Assessment at the University of Colorado-Boulder and the project team evaluated team processes and outputs to document “lessons learned” from the collaborative process to support the transfer of knowledge to other tribes and non-tribal entities in the region and beyond.

One of the biggest challenges facing resource managers today is not knowing exactly when, where, and how climate change effects will unfold. While models can be used to predict the types of impacts that climate change might have on a landscape, uncertainty remains surrounding factors such as how quickly changes will occur and how specific resources will respond.   In order to plan for this uncertain future, managers have begun to use a tool known as scenario planning. In this approach, a subset of global climate model projections are selected that represent a range of plausible future climate scenarios for a particular area. Through a series of facilitated workshops, managers can then explore different management options under each scenario, enabling them to be proactive in the face of uncertainty. However, selecting and synthesizing climate information for scenario planning requires significant time and skills, and it can be difficult to predict exactly how resources might respond to a combination of climate, management actions, and other factors.   Therefore, the goals of this project were to develop a process for creating regional climate summaries that can also be used for local scenario planning, and to pilot an approach for enhancing scenario planning through simulation modeling. Researchers drew on global climate model projections to develop several climate summaries for the northern Great Plains region. The summaries are expected to be used for local-scale climate adaptation planning efforts for Badlands National Park (South Dakota) and Knife River Indian Villages National Historical Site (North Dakota) and surrounding federal and tribal lands. A final step was to develop a simulation model for the South Dakota site to help managers address the “what if” questions regarding how management actions might affect focal resources under the different scenarios.   Not only is this project meant to improve climate adaptation efforts in the northern Great Plains region, but it is also expected to result in a new, integrative approach for identifying how climate change might affect key resources of management concern at a local-scale and what actions can be taken to protect these resources – a method that could be applied to management units across the country.