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USGS2018

Climate change science and modeling

This chapter provides a brief background on climate change science, climate simulation models, and models that project the impacts of changes in climate on tree species and ecosystems. Throughout the chapter, boxes list resources for more information on each topic. A more detailed scientific review of climate change science, trends, and modeling can be found in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (IPCC 2014), and the Fourth National Climate Assessment (U.S. Global Climate Research Program [USGCRP] 2017).

Delaware, Maryland, New Jersey, New York, Pennsylv↗

USGS2024

Climate-resource scenarios to inform climate change adaptation in Wrangell-St. Elias National Park and Preserve: Summary of 2021 climate change scenario planning

This report illustrates use of scenario planning as a climate change adaptation tool supporting Wrangell-St. Elias National Park and Preserve’s Resource Stewardship Strategy. The primary objective of scenario planning is to help resource managers and scientists make management and planning decisions informed by assessments of critical future uncertainties. This report outlines a process that synthesized future climate projections into three distinct but plausible and relevant climate summaries for the focal area and used them to develop climate-resource scenarios through participatory scenario planning. Initial steps identified the priority resource management topics and the corresponding related climate uncertainties. Next, local climate summaries were used to develop divergent climate futures: those that describe the broadest possible range of plausible conditions while capturing relevant uncertainty. The final phase further developed the climate futures and their resource implications. These participatory scenario planning exercises occurred virtually in fall (August–November) 2021. The climate-resource scenarios informed adaptation strategies in conjunction with the park’s Resource Stewardship Strategy development. The scope and complexity of this effort is unique but elements from the scenarios and resource implications have broad applicability to other large, protected areas in Alaska and Northwest Canada.

Alaska↗

USGS2009

Forecasting the combined effects of urbanization and climate change on stream ecosystems: from impacts to management options

Streams collect runoff, heat, and sediment from their watersheds, making them highly vulnerable to anthropogenic disturbances such as urbanization and climate change. Forecasting the effects of these disturbances using process-based models is critical to identifying the form and magnitude of likely impacts. Here, we integrate a new biotic model with four previously developed physical models (downscaled climate projections, stream hydrology, geomorphology, and water temperature) to predict how stream fish growth and reproduction will most probably respond to shifts in climate and urbanization over the next several decades. The biotic submodel couples dynamics in fish populations and habitat suitability to predict fish assemblage composition, based on readily available biotic information (preferences for habitat, temperature, and food, and characteristics of spawning) and day-to-day variability in stream conditions. We illustrate the model using Piedmont headwater streams in the Chesapeake Bay watershed of the USA, projecting ten scenarios: Baseline (low urbanization; no on-going construction; and present-day climate); one Urbanization scenario (higher impervious surface, lower forest cover, significant construction activity); four future climate change scenarios [Hadley CM3 and Parallel Climate Models under medium-high (A2) and medium-low (B2) emissions scenarios]; and the same four climate change scenarios plus Urbanization. Urbanization alone depressed growth or reproduction of 8 of 39 species, while climate change alone depressed 22 to 29 species. Almost every recreationally important species (i.e. trouts, basses, sunfishes) and six of the ten currently most common species were predicted to be significantly stressed. The combined effect of climate change and urbanization on adult growth was sometimes large compared to the effect of either stressor alone. Thus, the model predicts considerable change in fish assemblage composition, including loss of diversity. Synthesis and applications . The interaction of climate change and urban growth may entail significant reconfiguring of headwater streams, including a loss of ecosystem structure and services, which will be more costly than climate change alone. On local scales, stakeholders cannot control climate drivers but they can mitigate stream impacts via careful land use. Therefore, to conserve stream ecosystems, we recommend that proactive measures be taken to insure against species loss or severe population declines. Delays will inevitably exacerbate the impacts of both climate change and urbanization on headwater systems.

Journal of Applied Ecology↗

USGS2015

Targeting climate diversity in conservation planning to build resilience to climate change

Climate change is raising challenging concerns for systematic conservation planning. Are methods based on the current spatial patterns of biodiversity effective given long-term climate change? Some conservation scientists argue that planning should focus on protecting the abiotic diversity in the landscape, which drives patterns of biological diversity, rather than focusing on the distribution of focal species, which shift in response to climate change. Climate is one important abiotic driver of biodiversity patterns, as different climates host different biological communities and genetic pools. We propose conservation networks that capture the full range of climatic diversity in a region will improve the resilience of biotic communities to climate change compared to networks that do not. In this study we used historical and future hydro-climate projections from the high resolution Basin Characterization Model to explore the utility of directly targeting climatic diversity in planning. Using the spatial planning tool, Marxan, we designed conservation networks to capture the diversity of climate types, at the regional and sub-regional scale, and compared them to networks we designed to capture the diversity of vegetation types. By focusing on the Conservation Lands Network (CLN) of the San Francisco Bay Area as a real-world case study, we compared the potential resilience of networks by examining two factors: the range of climate space captured, and climatic stability to 18 future climates, reflecting different emission scenarios and global climate models. We found that the climate-based network planned at the sub-regional scale captured a greater range of climate space and showed higher climatic stability than the vegetation and regional based-networks. At the same time, differences among network scenarios are small relative to the variance in climate stability across global climate models. Across different projected futures, topographically heterogeneous areas consistently show greater climate stability than homogenous areas. The analysis suggests that utilizing high-resolution climate and hydrological data in conservation planning improves the likely resilience of biodiversity to climate change. We used these analyses to suggest new conservation priorities for the San Francisco Bay Area.

Ecosphere↗

USGS2011

On the Hydrologic Adjustment of Climate-Model Projections: The Potential Pitfall of Potential Evapotranspiration

Hydrologic models often are applied to adjust projections of hydroclimatic change that come from climate models. Such adjustment includes climate-bias correction, spatial refinement ("downscaling"), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climate models and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median -11%) caused by the hydrologic model’s apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen–Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors’ findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climate-change impacts on water.

Earth Interactions↗

USGS2015

Accounting for multiple climate components when estimating climate change exposure and velocity

The effect of anthropogenic climate change on organisms will likely be related to climate change exposure and velocity at local and regional scales. However, common methods to estimate climate change exposure and velocity ignore important components of climate that are known to affect the ecology and evolution of organisms. We develop a novel index of climate change (climate overlap) that simultaneously estimates changes in the means, variation and correlation between multiple weather variables. Specifically, we estimate the overlap between multivariate normal probability distributions representing historical and current or projected future climates. We provide methods for estimating the statistical significance of climate overlap values and methods to estimate velocity using climate overlap. We show that climates have changed significantly across 80% of the continental United States in the last 32 years and that much of this change is due to changes in the variation and correlation between weather variables (two statistics that are rarely incorporated into climate change studies). We also show that projected future temperatures are predicted to be locally novel (<1·5% overlap) across most of the global land surface and that exposure is likely to be highest in areas with low historical climate variation. Last, we show that accounting for changes in the variation and correlation between multiple weather variables can dramatically affect velocity estimates; mean velocity estimates in the continental United States were between 3·1 and 19·0 km yr −1 when estimated using climate overlap compared to 1·4 km yr −1 when estimated using traditional methods. Our results suggest that accounting for changes in the means, variation and correlation between multiple weather variables can dramatically affect estimates of climate change exposure and velocity. These climate components are known to affect the ecology and evolution of organisms, but are ignored by most measures of climate change. We conclude with a set of future directions and recommend future work to determine which measures of climate change exposure and velocity are most related to biological responses to climate change.

Methods in Ecology and Evolution↗

USGS2022

An introduction to current climate projections and their use in climate impacts research

Using climate projections to evaluate future climate impacts and their associated risks requires a background knowledge of the nature of climate change, use of climate models to develop future projections, and knowledge of how to address climate scenario uncertainty. This chapter provides an overview of climate and climate change, some of the foundational climate science that underlies current climate change assessments, and a brief introduction to climate models and climate scenario uncertainty. Global projections of temperature and precipitation changes from the recent Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6) and a brief comparison to the prior assessment (AR5) are provided. The main sources of uncertainty in these projections include climate variability, climate model differences and treatment of scientific knowledge gaps, and greenhouse gas (GHG) emissions. When projections are downscaled to local resolution, downscaling is an additional source of uncertainty. These uncertainties can be incorporated in assessments of climate impacts by choosing a range of scenarios that directly address the sources of uncertainty. Evaluating the likelihood of a given climate impact on animal health or management strategies requires consideration of the main sources of climate projection uncertainties. Adaptation requires consideration of global-to-regional contexts of climate changes and impacts, but also adaptive capacity.

Book chapter↗

USGS2017

Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics

Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics—changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly sensitive to climate extremes during periods of high stem density following major regeneration events when average inter-tree competition was high. Results suggest the resistance and resilience of forest growth to climate extremes can be increased through management steps such as thinning to reduce competition during early stages of stand development and small-group selection harvests to maintain forest structures characteristic of older, mature stands.

Minnesota, Wisconsin↗

USGS2017

Designing ecological climate change impact assessments to reflect key climatic drivers

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.

Global Change Biology↗

USGS2005

Ground-water/surface-water responses to global climate simulations, Santa Clara-Calleguas basin, Ventura County, California, 1950-93

Climate variations can play an important, if not always crucial, role in successful conjunctive management of ground water and surface water resources. This will require accurate accounting of the links between variations in climate, recharge, and withdrawal from the resource systems, accurate projection or predictions of the climate variations, and accurate simulation of the responses of the resource systems. To assess linkages and predictability of climate influences on conjunctive management, global climate model (GCM) simulated precipitation rates were used to estimate inflows and outflows from a regional ground water model (RGWM) of the coastal aquifers of the Santa Clara-Calleguas Basin at Ventura, California, for 1950 to 1993. Interannual to interdecadal time scales of the El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) climate variations are imparted to simulated precipitation variations in the Southern California area and are realistically imparted to the simulated ground water level variations through the climate-driven recharge (and discharge) variations. For example, the simulated average ground water level response at a key observation well in the basin to ENSO variations of tropical Pacific sea surface temperatures is 1.2 m/°C, compared to 0.9 m/°C in observations. This close agreement shows that the GCM-RGWM combination can translate global scale climate variations into realistic local ground water responses. Probability distributions of simulated ground water level excursions above a local water level threshold for potential seawater intrusion compare well to the corresponding distributions from observations and historical RGWM simulations, demonstrating the combination's potential usefulness for water management and planning. Thus the GCM-RGWM combination could be used for planning purposes and — when the GCM forecast skills are adequate — for near term predictions.

California↗

USGS2024

Existing evidence on the effects of climate variability and climate change on ungulates in North America: A systematic map

Background Climate is an important driver of ungulate life-histories, population dynamics, and migratory behaviors. Climate conditions can directly impact ungulates via changes in the costs of thermoregulation and locomotion, or indirectly, via changes in habitat and forage availability, predation, and species interactions. Many studies have documented the effects of climate variability and climate change on North America’s ungulates, recording impacts to population demographics, physiology, foraging behavior, migratory patterns, and more. However, ungulate responses are not uniform and vary by species and geography. Here, we present a systematic map describing the abundance and distribution of evidence on the effects of climate variability and climate change on native ungulates in North America. Methods We searched for all evidence documenting or projecting how climate variability and climate change affect the 15 ungulate species native to the U.S., Canada, Mexico, and Greenland. We searched Web of Science, Scopus, and the websites of 62 wildlife management agencies to identify relevant academic and grey literature. We screened English-language documents for inclusion at both the title and abstract and full-text levels. Data from all articles that passed full-text review were extracted and coded in a database. We identified knowledge clusters and gaps related to the species, locations, climate variables, and outcome variables measured in the literature. Review findings We identified a total of 674 relevant articles published from 1947 until September 2020. Caribou ( Rangifer tarandus ), elk ( Cervus canadensis ), and white-tailed deer ( Odocoileus virginianus ) were the most frequently studied species. Geographically, more research has been conducted in the western U.S. and western Canada, though a notable concentration of research is also located in the Great Lakes region. Nearly 75% more articles examined the effects of precipitation on ungulates compared to temperature, with variables related to snow being the most commonly measured climate variables. Most studies examined the effects of climate on ungulate population demographics, habitat and forage, and physiology and condition, with far fewer examining the effects on disturbances, migratory behavior, and seasonal range and corridor habitat. Conclusions The effects of climate change, and its interactions with stressors such as land-use change, predation, and disease, is of increasing concern to wildlife managers. With its broad scope, this systematic map can help ungulate managers identify relevant climate impacts and prepare for future changes to the populations they manage. Decisions regarding population control measures, supplemental feeding, translocation, and the application of habitat treatments are just some of the management decisions that can be informed by an improved understanding of climate impacts. This systematic map also identified several gaps in the literature that would benefit from additional research, including climate effects on ungulate migratory patterns, on species that are relatively understudied yet known to be sensitive to changes in climate, such as pronghorn ( Antilocapra americana ) and mountain goats ( Oreamnos americanus ), and on ungulates in the eastern U.S. and Mexico.

Environmental Evidence↗

USGS2012

Impacts of climate change on biodiversity, ecosystems, and ecosystem services: technical input to the 2013 National Climate Assessment

Ecosystems, and the biodiversity and services they support, are intrinsically dependent on climate. During the twentieth century, climate change has had documented impacts on ecological systems, and impacts are expected to increase as climate change continues and perhaps even accelerates. This technical input to the National Climate Assessment synthesizes our scientific understanding of the way climate change is affecting biodiversity, ecosystems, ecosystem services, and what strategies might be employed to decrease current and future risks. Building on past assessments of how climate change and other stressors are affecting ecosystems in the United States and around the world, we approach the subject from several different perspectives. First, we review the observed and projected impacts on biodiversity, with a focus on genes, species, and assemblages of species. Next, we examine how climate change is affecting ecosystem structural elements—such as biomass, architecture, and heterogeneity—and functions—specifically, as related to the fluxes of energy and matter. People experience climate change impacts on biodiversity and ecosystems as changes in ecosystem services; people depend on ecosystems for resources that are harvested, their role in regulating the movement of materials and disturbances, and their recreational, cultural, and aesthetic value. Thus, we review newly emerging research to determine how human activities and a changing climate are likely to alter the delivery of these ecosystem services. This technical input also examines two cross-cutting topics. First, we recognize that climate change is happening against the backdrop of a wide range of other environmental and anthropogenic stressors, many of which have caused dramatic ecosystem degradation already. This broader range of stressors interacts with climate change, and complicates our abilities to predict and manage the impacts on biodiversity, ecosystems, and the services they support. The second cross-cutting topic is the rapidly advancing field of climate adaptation, where there has been significant progress in developing the conceptual framework, planning approaches, and strategies for safeguarding biodiversity and other ecological resources. At the same time, ecosystem-based adaptation is becoming more prominent as a way to utilize ecosystem services to help human systems adapt to climate change. In this summary, we present key findings of the technical input, focusing on themes that can be found throughout the report. Thus, this summary takes a more integrated look at the question of how climate change is affecting our ecological resources, the implications for humans, and possible response strategies. This integrated approach better reflects the impacts of climate in the real world, where changes in ecosystem structure or function will alter the viability of different species and the efficacy of ecosystem services. Likewise, adaptation to climate change will simultaneously address a range of conservation goals. Case studies are used to illustrate this complete picture throughout the report; a snapshot of one case study, 2011 Las Conchas, New Mexico Fire , is included in this summary.

Report↗

USGS2017

At a global scale, do climate change threatened species also face a greater number of non-climatic threats?

For many species the threats of climate change occur in a context of multiple existing threats. Given the current focus of global change ecology in identifying and understanding species vulnerable to climate change, we performed a global analysis to characterize the multi-threat context for species threatened by climate change. Utilizing 30,053 species from the International Union for Conservation of Nature’s (IUCN) Red List of Threatened Species, we sought to evaluate if species threatened by climate change are more likely threatened by a greater number of non-climatic threats than species not threatened by climate change. Our results show that species threatened by climate change are generally impacted by 21% more non-climatic threats than species not threatened by climate change. Across all species, this pattern is related to IUCN risk status, where endangered species threatened by climate change face 33% more non-climatic threats than endangered species not threatened by climate change. With the clear challenges of assessing current and projected impacts of climate change on species and ecosystems, research often requires reductionist approaches that result in downplaying this multi-threat context. This cautionary note bears relevance beyond climate change threatened species as we also found other (but not all) anthropogenic threats are also similarly associated with more threats. Our findings serve as a reminder that ecological research should seriously consider these potential threat interactions, especially for species under elevated conservation concern.

Global Ecology and Conservation↗

USGS2001

Comparison of post-fire seedling establishment between scrub communities in mediterranean and non-mediterranean climate ecosystems

I Both fire regimes and the conditions under which fires occur vary widely. Abiotic conditions (such as climate) in combination with fire season, frequency and intensity could influence vegetation responses to fire. A variety of adaptations facilitate post-fire recruitment in mediterranean climate ecosystems, but responses of other communities are less well known. We evaluated the importance of climate by comparing sites with mediterranean and subtropical climates. 2 We used paired burned and mature sites in chamise chaparral, mixed chaparral and coastal sage scrub (California), and rosemary scrub, sand pine scrub and sand-hill (Florida), to test whether (i) patterns of pre-fire and post-fire seedling recruitment are more similar between communities within a region than between regions, and (ii) post-fire stimulation of seedling establishment is greater in regions with marked fire-induced contrasts in abiotic site characteristics. 3 Post-fire seedling densities were more similar among sites within climatic regions than between regions. Both seedling densities and proportions of species represented by seedlings after fires were generally higher in California. 4 The only site characteristic showing a pre-fire-post-fire contrast was percentage open canopy, and the effect was greater in California than in Florida. Soil properties were unaffected by fire. 5 Mediterranean climate ecosystems in other regions have nutrient-poor soils similar to our subtropical Florida sites, but show post-fire seedling recruitment patterns more similar to the nutrient-rich sites in California. Climate therefore appears to play a more major role than soil characteristics.

Journal of Ecology↗

USGS2014

Assessing effects of variation in global climate data sets on spatial predictions from climate envelope models

Climate change poses new challenges for natural resource managers. Predictive modeling of species–environment relationships using climate envelope models can enhance our understanding of climate change effects on biodiversity, assist in assessment of invasion risk by exotic organisms, and inform life-history understanding of individual species. While increasing interest has focused on the role of uncertainty in future conditions on model predictions, models also may be sensitive to the initial conditions on which they are trained. Although climate envelope models are usually trained using data on contemporary climate, we lack systematic comparisons of model performance and predictions across alternative climate data sets available for model training. Here, we seek to fill that gap by comparing variability in predictions between two contemporary climate data sets to variability in spatial predictions among three alternative projections of future climate. Overall, correlations between monthly temperature and precipitation variables were very high for both contemporary and future data. Model performance varied across algorithms, but not between two alternative contemporary climate data sets. Spatial predictions varied more among alternative general-circulation models describing future climate conditions than between contemporary climate data sets. However, we did find that climate envelope models with low Cohen's kappa scores made more discrepant spatial predictions between climate data sets for the contemporary period than did models with high Cohen's kappa scores. We suggest conservation planners evaluate multiple performance metrics and be aware of the importance of differences in initial conditions for spatial predictions from climate envelope models.

Journal of Fish and Wildlife Management↗

USGS2015

High and dry: high elevations disproportionately exposed to regional climate change in Mediterranean-climate landscapes

Context Predicting climate-driven species’ range shifts depends substantially on species’ exposure to climate change. Mountain landscapes contain a wide range of topoclimates and soil characteristics that are thought to mediate range shifts and buffer species’ exposure. Quantifying fine-scale patterns of exposure across mountainous terrain is a key step in understanding vulnerability of species to regional climate change. Objectives We demonstrated a transferable, flexible approach for mapping climate change exposure in a moisture-limited, mountainous California landscape across 4 climate change projections under phase 5 of the Coupled Model Intercomparison Project (CMIP5) for mid-(2040–2069) and end-of-century (2070–2099). Methods We produced a 149-year dataset (1951–2099) of modeled climatic water deficit (CWD), which is strongly associated with plant distributions, at 30-m resolution to map climate change exposure in the Tehachapi Mountains, California, USA. We defined climate change exposure in terms of departure from the 1951–1980 mean and historical range of variability in CWD in individual years and 3-year moving windows. Results Climate change exposure was generally greatest at high elevations across all future projections, though we encountered moderate topographic buffering on poleward-facing slopes. Historically dry lowlands demonstrated the least exposure to climate change. Conclusions In moisture-limited, Mediterranean-climate landscapes, high elevations may experience the greatest exposure to climate change in the 21st century. High elevation species may thus be especially vulnerable to continued climate change as habitats shrink and historically energy-limited locations become increasingly moisture-limited in the future.

Landscape Ecology↗

USGS2012

Modeling plant species distributions under future climates: how fine scale do climate projections need to be?

Recent studies suggest that species distribution models (SDMs) based on fine‐scale climate data may provide markedly different estimates of climate‐change impacts than coarse‐scale models. However, these studies disagree in their conclusions of how scale influences projected species distributions. In rugged terrain, coarse‐scale climate grids may not capture topographically controlled climate variation at the scale that constitutes microhabitat or refugia for some species. Although finer scale data are therefore considered to better reflect climatic conditions experienced by species, there have been few formal analyses of how modeled distributions differ with scale. We modeled distributions for 52 plant species endemic to the California Floristic Province of different life forms and range sizes under recent and future climate across a 2000‐fold range of spatial scales (0.008–16 km 2 ). We produced unique current and future climate datasets by separately downscaling 4 km climate models to three finer resolutions based on 800, 270, and 90 m digital elevation models and deriving bioclimatic predictors from them. As climate‐data resolution became coarser, SDMs predicted larger habitat area with diminishing spatial congruence between fine‐ and coarse‐scale predictions. These trends were most pronounced at the coarsest resolutions and depended on climate scenario and species' range size. On average, SDMs projected onto 4 km climate data predicted 42% more stable habitat (the amount of spatial overlap between predicted current and future climatically suitable habitat) compared with 800 m data. We found only modest agreement between areas predicted to be stable by 90 m models generalized to 4 km grids compared with areas classified as stable based on 4 km models, suggesting that some climate refugia captured at finer scales may be missed using coarser scale data. These differences in projected locations of habitat change may have more serious implications than net habitat area when predictive maps form the basis of conservation decision making.

California↗

USGS2014

Predicted changes in climatic niche and climate refugia of conservation priority salamander species in the northeastern United States

Global climate change represents one of the most extensive and pervasive threats to wildlife populations. Amphibians, specifically salamanders, are particularly susceptible to the effects of changing climates due to their restrictive physiological requirements and low vagility; however, little is known about which landscapes and species are vulnerable to climate change. Our study objectives included, (1) evaluating species-specific predictions (based on 2050 climate projections) and vulnerabilities to climate change and (2) using collective species responses to identify areas of climate refugia for conservation priority salamanders in the northeastern United States. All evaluated salamander species were projected to lose a portion of their climatic niche. Averaged projected losses ranged from 3%–100% for individual species, with the Cow Knob Salamander ( Plethodon punctatus ), Cheat Mountain Salamander ( Plethodon nettingi ), Shenandoah Mountain Salamander ( Plethodon virginia ), Mabee’s Salamander ( Ambystoma mabeei ), and Streamside Salamander ( Ambystoma barbouri ) predicted to lose at least 97% of their landscape-scale climatic niche. The Western Allegheny Plateau was predicted to lose the greatest salamander climate refugia richness ( i.e. , number of species with a climatically-suitable niche in a landscape patch), whereas the Central Appalachians provided refugia for the greatest number of species during current and projected climate scenarios. Our results can be used to identify species and landscapes that are likely to be further affected by climate change and potentially resilient habitats that will provide consistent climatic conditions in the face of environmental change.

Forests↗