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At least 289 records · Page 16Linked to original sources
USGS2013

The Borderlands and climate change: Chapter 10 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science

The prediction of global climate change in response to both natural forces and human activity is one of the defining issues of our times. The unprecedented observational capacity of modern earth-orbiting satellites coupled with the development of robust computational representations (models) of the Earth’s weather and climate systems afford us the opportunity to observe and investigate how these systems work now, how they have worked in the past, and how they will work in the future when forced in specific ways. In the most recent report on global climate change by the Intergovernmental Panel on Climate Change (IPCC; Solomon and others, 2007), analyses using multiple climate models support recent observations that the Earth’s climate is changing in response to a combination of natural and human-induced causes. These changes will be significant in the United States–Mexican border region, where the process of climate change affects all of the Borderlands challenge themes discussed in the preceding chapters. The dual possibilities of both significantly-changed climate and increasing variability in climate make it challenging to take full measure of the potential effects because the Borderlands already experience a high degree of interannual variability and climatological extremes.

United States-Mexico Borderlands↗
USGS1978

Climate variation and its effects on our land and water : Part B, Current research by the Geological Survey

To better coordinate information being generated by the U.S. Geological Survey, a workshop was convened near Denver, Colo., on December 7-9, 1976, to exchange ideas about research that is oriented toward climate, climate variation, and the effects of climate on the Nation 's land and water resources. This is the first circular of a three-part report resulting from that workshop. Hydrologic records provide information to the earth scientist about the responses of ground water, surface water, and glaciers to climatic change; geologic sequences provide evidence of earth-surface water, and glaciers to climatic change; geologic sequences provide evidence of earth-surface responses to climatic change; biological records yield information about the effects of climatic change on the Earth 's biota; archeological records tell us where and how man was able to live under changing climatic conditions; and historical records allow the specific effects of short-term changes in climate to be accurately documented. The interrelation between present and past geologic environments, various methods of study , and the span of time over which the results can be applied are shown in a table. (Woodard-USGS)

Circular↗
USGS2010

Climate change and wildlife health: direct and indirect effects

Climate change will have significant effects on the health of wildlife, domestic animals, and humans, according to scientists. The Intergovernmental Panel on Climate Change projects that unprecedented rates of climate change will result in increasing average global temperatures; rising sea levels; changing global precipitation patterns, including increasing amounts and variability; and increasing midcontinental summer drought (Intergovernmental Panel on Climate Change, 2007). Increasing temperatures, combined with changes in rainfall and humidity, may have significant impacts on wildlife, domestic animal, and human health and diseases. When combined with expanding human populations, these changes could increase demand on limited water resources, lead to more habitat destruction, and provide yet more opportunities for infectious diseases to cross from one species to another. Awareness has been growing in recent years about zoonotic diseases— that is, diseases that are transmissible between animals and humans, such as Lyme disease and West Nile virus. The rise of such diseases results from closer relationships among wildlife, domestic animals, and people, allowing more contact with diseased animals, organisms that carry and transmit a disease from one animal to another (vectors), and people. Disease vectors include insects, such as mosquitoes, and arachnids, such as ticks. Thus, it is impossible to separate the effects of global warming on wildlife from its effects on the health of domestic animals or people. Climate change, habitat destruction and urbanization, the introduction of exotic and invasive species, and pollution—all affect ecosystem and human health. Climate change can also be viewed within the context of other physical and climate cycles, such as the El Niño Southern Oscillation (El Niño), the North Atlantic Oscillation, and cycles in solar radiation that have profound effects on the Earth’s climate. The effects of climate change on wildlife disease are summarized in several areas of scientific study discussed briefly below: geographic range and distribution of wildlife diseases, plant and animal phenology (Walther and others, 2002), and patterns of wildlife disease, community and ecosystem composition, and habitat degradation.

Fact Sheet↗
USGS2011

Dynamically downscaled climate simulations over North America: Methods, evaluation, and supporting documentation for users

We have completed an array of high-resolution simulations of present and future climate over Western North America (WNA) and Eastern North America (ENA) by dynamically downscaling global climate simulations using a regional climate model, RegCM3. The simulations are intended to provide long time series of internally consistent surface and atmospheric variables for use in climate-related research. In addition to providing high-resolution weather and climate data for the past, present, and future, we have developed an integrated data flow and methodology for processing, summarizing, viewing, and delivering the climate datasets to a wide range of potential users. Our simulations were run over 50- and 15-kilometer model grids in an attempt to capture more of the climatic detail associated with processes such as topographic forcing than can be captured by general circulation models (GCMs). The simulations were run using output from four GCMs. All simulations span the present (for example, 1968-1999), common periods of the future (2040-2069), and two simulations continuously cover 2010-2099. The trace gas concentrations in our simulations were the same as those of the GCMs: the IPCC 20th century time series for 1968-1999 and the A2 time series for simulations of the future. We demonstrate that RegCM3 is capable of producing present day annual and seasonal climatologies of air temperature and precipitation that are in good agreement with observations. Important features of the high-resolution climatology of temperature, precipitation, snow water equivalent (SWE), and soil moisture are consistently reproduced in all model runs over WNA and ENA. The simulations provide a potential range of future climate change for selected decades and display common patterns of the direction and magnitude of changes. As expected, there are some model to model differences that limit interpretability and give rise to uncertainties. Here, we provide background information about the GCMs and the RegCM3, a basic evaluation of the model output and examples of simulated future climate. We also provide information needed to access the web applications for visualizing and downloading the data, and give complete metadata that describe the variables in the datasets.

Open-File Report↗
USGS2014

Downscaled climate projections for the Southeast United States: evaluation and use for ecological applications

Climate change is likely to have many effects on natural ecosystems in the Southeast U.S. The National Climate Assessment Southeast Technical Report (SETR) indicates that natural ecosystems in the Southeast are likely to be affected by warming temperatures, ocean acidification, sea-level rise, and changes in rainfall and evapotranspiration. To better assess these how climate changes could affect multiple sectors, including ecosystems, climatologists have created several downscaled climate projections (or downscaled datasets) that contain information from the global climate models (GCMs) translated to regional or local scales. The process of creating these downscaled datasets, known as downscaling, can be carried out using a broad range of statistical or numerical modeling techniques. The rapid proliferation of techniques that can be used for downscaling and the number of downscaled datasets produced in recent years present many challenges for scientists and decisionmakers in assessing the impact or vulnerability of a given species or ecosystem to climate change. Given the number of available downscaled datasets, how do these model outputs compare to each other? Which variables are available, and are certain downscaled datasets more appropriate for assessing vulnerability of a particular species? Given the desire to use these datasets for impact and vulnerability assessments and the lack of comparison between these datasets, the goal of this report is to synthesize the information available in these downscaled datasets and provide guidance to scientists and natural resource managers with specific interests in ecological modeling and conservation planning related to climate change in the Southeast U.S. This report enables the Southeast Climate Science Center (SECSC) to address an important strategic goal of providing scientific information and guidance that will enable resource managers and other participants in Landscape Conservation Cooperatives to make science-based climate change adaptation decisions.

Open-File Report↗
USGS2020

Climate change Is likely to alter future wolf - moose - forest interactions at Isle Royale National Park, United States

We evaluated how climate change and variable rates of moose browsing intensity, as they relate to wolf predation, might affect the forests of Isle Royale National Park, Michigan, United States by conducting a modeling experiment. The experiment consisted of contrasting three different scenarios of wolf management and with a static (current conditions) and changing climate (high emissions). Our results indicate that the interactive effects of wolf predation and climate change are likely to be temporally variable and dependent on biogeographic and forest successional processes. During the first 50 years of 120-year simulations, when the effects of climate change were less impactful, higher simulated rates of predation by wolves reduced moose population densities, resulting in greater forest biomass and higher carrying capacities for moose. However, over the longer term, early successional and highly palatable aspen and birch forests transitioned to late successional spruce and fir forests, regardless of climate or predation intensity. After 50 years, the effects of climate change and predation were driven by effects on balsam fir, a late successional conifer species that is fed on by moose. High-intensity predation of moose allowed balsam fir to persist over the long term but only under the static climate scenario. The climate change scenario caused a reduction in balsam fir and the other boreal species that moose currently feed on, and the few temperate species found on this isolated island were unable to compensate for such reductions, causing strong declines in total forest biomass. The direct effects of moose population management via reintroduction of wolves may become increasingly ineffective as the climate continues to warm because the productivity of boreal plant species may not be sufficient to support a moose population, and the isolation of the island from mainland temperate tree species may reduce the likelihood of compensatory species migrations.

Michigan↗
USGS2019

Simulating land cover change impacts on groundwater recharge under selected climate projections, Maui, Hawaiʻi

This project developed an integrated land cover/hydrological modeling framework using remote sensing and geographic information systems (GIS) data, stakeholder input, climate information and projections, and empirical data to estimate future groundwater recharge on the Island of Maui, Hawaiʻi, USA. End-of-century mean annual groundwater recharge was estimated under four future land cover scenarios: Future 1 (conservation-focused), Future 2 (status-quo), Future 3 (development-focused), and Future 4 (balanced conservation and development), and two downscaled climate projections: a coupled model intercomparison project (CMIP) phase 5 (CMIP5) representative concentration pathway (RCP) 8.5 “dry climate” future and a CMIP3 A1B “wet climate” future. Results were compared to recharge estimated using the 2017 baseline land cover to understand how changing land management and climate could influence groundwater recharge. Estimated recharge increased island-wide under all future land cover and climate combinations and was dominated by specific land cover transitions. For the dry future climate, recharge for land cover Futures 1 to 4 increased by 12%, 0.7%, 0.01%, and 11% relative to 2017 land cover conditions, respectively. Corresponding increases under the wet future climate were 10%, 0.9%, 0.6%, and 9.3%. Conversion from fallow/grassland to diversified agriculture increased irrigation, and therefore recharge. Above the cloud zone (610 m), conversion from grassland to native or alien forest led to increased fog interception, which increased recharge. The greatest changes to recharge occurred in Futures 1 and 4 in areas where irrigation increased, and where forest expanded within the cloud zone. Furthermore, new future urban expansion is currently slated for coastal areas that are already water-stressed and had low recharge projections. This study demonstrated that a spatially-explicit scenario planning process and modeling framework can communicate the possible consequences and tradeoffs of land cover change under a changing climate, and the outputs from this study serve as relevant tools for landscape-level management and interventions.

Hawaii↗
USGS2019

Synergistic interaction of climate and land-use drivers alter the function of North American, Prairie-pothole Wetlands

Prairie-pothole wetlands provide the critical habitat necessary for supporting North American migratory waterfowl populations. However, climate and land-use change threaten the sustainability of these wetland ecosystems. Very few experiments and analyses have been designed to investigate the relative impacts of climate and land-use change drivers, as well as the antagonistic or synergistic interactions among these drivers on ecosystem processes. Prairie-pothole wetland water budgets are highly dependent on atmospheric inputs and especially surface runoff, which makes them especially susceptible to changes in climate and land use. Here, we present the history of prairie-pothole climate and land-use change research and address the following research questions: 1) What are the relative effects of climate and land-use change on the sustainability of prairie-pothole wetlands? and 2) Do the effects of climate and land-use change interact differently under different climatic conditions? To address these research questions, we modeled 25 wetland basins (1949–2018) and measured the response of the lowest wetland in the watershed to wetland drainage and climate variability. We found that during an extremely wet period (1993–2000) wetland drainage decreased the time at which the lowest wetland reached its spill point by four years, resulting in 10 times the amount of water spilling out of the watershed towards local stream networks. By quantifying the relative effects of both climate and land-use drivers on wetland ecosystems our findings can help managers cope with uncertainties about flooding risks and provide insight into how to manage wetlands to restore functionality

Sustainability↗
USGS2022

A framework for ensemble modelling of climate change impacts on lakes worldwide: The ISIMIP lake sector.

Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5 ∘ × 0.5 ∘ global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.

Geoscientific Model Development↗
USGS2024

Incorporating climate change into restoration decisions: Perspectives from dam removal practitioners

Incorporating climate change into conservation and restoration decisions is increasingly important for natural resource managers and restoration practitioners to effectively address the underlying drivers of ecosystem change. Small dam removal is an example of a restoration tool that may offer multiple socioeconomic and ecological benefits in streams, including promoting climate resilience. With the pace of dam removals increasing, practitioners and researchers are well-poised to incorporate climate change into future dam removal decisions. Therefore, we surveyed dam removal practitioners across 14 states in the eastern United States to understand current practices of small dam removals, factors driving restoration decisions, and how climate change knowledge is incorporated into these decisions. We also aimed to identify barriers to and opportunities for knowledge exchange between practitioners and researchers. Of the 100 respondents, most (79%) consider climate change in their dam removal decisions to some extent. Despite this, many reported a lack of clear, relevant, and accessible data linking small dam removal to climate resilience benefits. Dam removal practitioners also indicated that they most often rely on climate change information garnered from conversations with colleagues, rather than from scientific research products. These results suggest that the co-production of relevant, salient research questions and readily accessible and interpretable research products (e.g., technical summaries, open access articles) may encourage practitioners to incorporate climate change science more consistently and efficiently into dam removal decisions. These findings may also translate to other stream restoration efforts to inform knowledge exchange and improve restoration outcomes in a changing climate.

Connecticut, Delaware, Kentucky, Maine, Maryland, ↗
USGS2012

Modeling responses of large-river fish populations to global climate change through downscaling and incorporation of predictive uncertainty

Climate change operates over a broad range of spatial and temporal scales. Understanding its effects on ecosystems requires multi-scale models. For understanding effects on fish populations of riverine ecosystems, climate predicted by coarse-resolution Global Climate Models must be downscaled to Regional Climate Models to watersheds to river hydrology to population response. An additional challenge is quantifying sources of uncertainty given the highly nonlinear nature of interactions between climate variables and community level processes. We present a modeling approach for understanding and accomodating uncertainty by applying multi-scale climate models and a hierarchical Bayesian modeling framework to Midwest fish population dynamics and by linking models for system components together by formal rules of probability. The proposed hierarchical modeling approach will account for sources of uncertainty in forecasts of community or population response. The goal is to evaluate the potential distributional changes in an ecological system, given distributional changes implied by a series of linked climate and system models under various emissions/use scenarios. This understanding will aid evaluation of management options for coping with global climate change. In our initial analyses, we found that predicted pallid sturgeon population responses were dependent on the climate scenario considered.

Missouri River↗
USGS2011

Adapting to climate change at Olympic National Forest and Olympic National Park

Climate change presents a major challenge to natural resource managers both because of the magnitude of potential effects of climate change on ecosystem structure, processes, and function, and because of the uncertainty associated with those potential ecological effects. Concrete ways to adapt to climate change are needed to help natural resource managers take the first steps to incorporate climate change into management and take advantage of opportunities to counteract the negative effects of climate change. We began a climate change adaptation case study at Olympic National Forest (ONF) in partnership with Olympic National Park (ONP) to determine how to adapt management of federal lands on the Olympic Peninsula, Washington, to climate change. The case study began in the summer of 2008 and continued for 1½ years. The case study process involved science-based sensitivity assessments, review of management activities and constraints, and adaptation workshops in each of four focus areas (hydrology and roads, fish, vegetation, and wildlife). The process produced adaptation options for ONF and ONP, and illustrated the utility of place-based vulnerability assessment and science-management workshops in adapting to climate change. The case study process provides an example for other national forests, national parks, and natural resource agencies of how federal land management units can collaborate in the initial stages of climate change adaptation. Many of the ideas generated through this process can potentially be applied in other locations and in other agencies

Washington↗
USGS2014

Disentangling the effects of climate and landscape change on bird population trends in the western U.S. and Canada

Changes in climate are often assumed result in changes to species’ ranges, with potential impacts on natural system functioning and ecosystem services. ‘Climate envelope models’, which rely on correlations between climate and species distributions, have been used to predict the future of biodiversity under these assumptions. However, other factors including land-cover, dispersal ability and interspecific competition and facilitation may play an important role in driving species distributions and population trends either alone or in combination with climate. In an ongoing project, we used long-term data on bird distributions and abundance to develop climate envelope and land-use models for 161 species in order to provide a multi-species test of the degree to which climate envelope versus land-use models are useful in predicting species distributions and population trends of birds in forest ecosystems of the western U.S. and Canada. Our results suggest that models describing associations between climatic variables and abundance patterns can be used for some species to predict changes through time, and that changes in climate have already driven shifts in the geographic patterns of abundance of bird populations in western North America. For other species, models using land-use variables including raw remote-sensing variables may provide the best predictions for abundance change. The results of this research showing the reliability of models across multiple species will aid managers in understanding which species are most vulnerable to changes from climate, land-use change and their interaction.

Final Report↗
USGS2016

Resource management and operations in central North Dakota: Climate change scenario planning workshop summary November 12-13, 2015, Bismarck, ND

The Scaling Climate Change Adaptation in the Northern Great Plains through Regional Climate Summaries and Local Qualitative-Quantitative Scenario Planning Workshops project synthesizes climate data into 3-5 distinct but plausible climate summaries for the northern Great Plains region; crafts quantitative summaries of these climate futures for two focal areas; and applies these local summaries by developing climate-resource-management scenarios through participatory workshops and, where possible, simulation models. The two focal areas are central North Dakota and southwest South Dakota (Figure 1). The primary objective of this project is to help resource managers and scientists in a focal area use scenario planning to make management and planning decisions based on assessments of critical future uncertainties. This report summarizes project work for public and tribal lands in the central North Dakota focal area, with an emphasis on Knife River Indian Villages National Historic Site. The report explains scenario planning as an adaptation tool in general, then describes how it was applied to the central North Dakota focal area in three phases. Priority resource management and climate uncertainties were identified in the orientation phase. Local climate summaries for relevant, divergent, and challenging climate scenarios were developed in the second phase. In the final phase, a two-day scenario planning workshop held November 12-13, 2015 in Bismarck, ND, featured scenario development and implications, testing management decisions, and methods for operationalizing scenario planning outcomes.

Natural Resource Report↗
USGS2016

Resource management and operations in southwest South Dakota: Climate change scenario planning workshop summary January 20-21, 2016, Rapid City, SD

The Scaling Climate Change Adaptation in the Northern Great Plains through Regional Climate Summaries and Local Qualitative-Quantitative Scenario Planning Workshops project synthesizes climate data into 3-5 distinct but plausible climate summaries for the northern Great Plains region; crafts quantitative summaries of these climate futures for two focal areas; and applies these local summaries by developing climate-resource-management scenarios through participatory workshops and, where possible, simulation models. The two focal areas are central North Dakota and southwest South Dakota (Figure 1). The primary objective of this project is to help resource managers and scientists in a focal area use scenario planning to make management and planning decisions based on assessments of critical future uncertainties. This report summarizes project work for public and tribal lands in the southwest South Dakota grasslands focal area, with an emphasis on Badlands National Park and Buffalo Gap National Grassland. The report explains scenario planning as an adaptation tool in general, then describes how it was applied to the focal area in three phases. Priority resource management and climate uncertainties were identified in the orientation phase. Local climate summaries for relevant, divergent, and challenging climate scenarios were developed in the second phase. In the final phase, a two-day scenario planning workshop held January 20-21, 2016 in Rapid City, South Dakota, featured scenario development and implications, testing management decisions, and methods for operationalizing scenario planning outcomes.

Natural Resource Report↗
USGS2020

Effects of climate change on plague exposure pathways and resulting disease dynamics

Introduction and Objectives: Sylvatic plague, a zoonotic flea-borne disease, caused by the bacterium Yersinia pestis , is relevant to the Department of Defense (DOD), because prairie dogs and other susceptible rodents are present on military installations in several western states. Arthropod-borne diseases, like plague, are thought to be particularly sensitive to local climate conditions. Expected changes in temperature and humidity over the next several decades will likely increase the geographical expansion of plague outbreaks in wildlife. Through a combination of field and laboratory work, along with data-driven modeling, we evaluated the potential effects of climate change on plague exposure pathways in prairie dogs and associated rodents to provide guidance to DOD partners regarding the potential for future outbreaks. Briefly, our specific objectives were to determine the relation between local climate conditions and the prevalence of plague and other pathogens while assessing the ecological roles of specific rodent hosts and vector species in plague dynamics, evaluate flea intensity on rodent hosts and in burrows in relation to local climate conditions, and develop models to predict the effects of climate change on plague dynamics. Technical Approach: Using data and samples collected during a large field study on the effectiveness of vaccination to manage plague in prairie dogs, we assessed rodent/flea assemblages, pathogen prevalence in fleas, and determined how local climate conditions influence flea development rates and relative abundance. Live animals (prairie dogs and some small rodents) were trapped to collect fleas and other samples on 46 prairie dog plots in 6 western states, many sites near DOD lands. At seven additional locations on a latitudinal gradient, fleas were collected from burrows several times per year to assess seasonality and effects of local climate conditions on flea abundance. These data were then used to develop predictive models that could be used to test specific hypotheses. Results: We determined that flea developmental rates, on-host flea abundance, species composition of the flea community, and burrow temperatures varied across a latitudinal gradient. Rodent and flea community composition and abundance differed geographically and were highly specialized. Flea-switching between prairie dogs and short-lived rodents was rare. Flea development rates, on-host flea abundance, and burrow temperatures increased with increasing ambient temperature. Although relative humidity can affect flea development, burrow humidity was uniformly high (~85%) across sampling sites and seasons. A large increase in the number of fleas found on a prairie dog colony, coupled with a greater number of infested burrows, could have substantial effects on plague dynamics in the western United States as the climate warms. In addition to affecting flea load, climate change may also influence body condition of prairie dogs by reducing the amount of forage. This may result in animals being more tolerant of high flea loads (less engaged in grooming behavior) and more vulnerable to disease.

Arizona, Montana, South Dakota, Texas, Utah, Wyomi↗
USGS2015

Regional modeling of large wildfires under current and potential future climates in Colorado and Wyoming, USA

Regional analysis of large wildfire potential given climate change scenarios is crucial to understanding areas most at risk in the future, yet wildfire models are not often developed and tested at this spatial scale. We fit three historical climate suitability models for large wildfires (i.e. ≥ 400 ha) in Colorado andWyoming using topography and decadal climate averages corresponding to wildfire occurrence at the same temporal scale. The historical models classified points of known large wildfire occurrence with high accuracies. Using a novel approach in wildfire modeling, we applied the historical models to independent climate and wildfire datasets, and the resulting sensitivities were 0.75, 0.81, and 0.83 for Maxent, Generalized Linear, and Multivariate Adaptive Regression Splines, respectively. We projected the historic models into future climate space using data from 15 global circulation models and two representative concentration pathway scenarios. Maps from these geospatial analyses can be used to evaluate the changing spatial distribution of climate suitability of large wildfires in these states. April relative humidity was the most important covariate in all models, providing insight to the climate space of large wildfires in this region. These methods incorporate monthly and seasonal climate averages at a spatial resolution relevant to land management (i.e. 1 km2) and provide a tool that can be modified for other regions of North America, or adapted for other parts of the world.

Colorado, Wyoming↗
USGS2021

Divergent, plausible, and relevant climate futures for near- and long-term resource planning

Scenario planning has emerged as a widely used planning process for resource management in situations of consequential, irreducible uncertainty. Because it explicitly incorporates uncertainty, scenario planning is regularly employed in climate change adaptation. An early and essential step in developing scenarios is identifying “climate futures”—descriptions of the physical attributes of plausible future climates that could occur at a specific place and time. Divergent climate futures that describe the broadest possible range of plausible conditions support information needs of decision makers, including understanding the spectrum of potential resource responses to climate change, developing strategies robust to that range, avoiding highly consequential surprises, and averting maladaptation. Here, we discuss three approaches for generating climate futures: a Representative Concentration Pathway (RCP)-ensemble, a quadrant-average, and an individual-projection approach. All are designed to capture relevant uncertainty, but they differ in utility for different applications, complexity, and effort required to implement. Using an application from Big Bend National Park as an example of numerous similar efforts to develop climate futures for National Park Service applications over the past decade, we compare these approaches, focusing on their ability to capture among-projection divergence during early-, mid-, and late-twenty-first century periods to align with near-, mid-, and long-term planning efforts. The quadrant-average approach and especially the individual-projection approach captured a broader range of plausible future conditions than the RCP-ensemble approach, particularly in the near term. Therefore, the individual-projection approach supports decision makers seeking to understand the broadest potential characterization of future conditions. We discuss tradeoffs associated with different climate future approaches and highlight suitable applications.

Climatic Change↗