Search USGS⌕ Search

SEARCH · Search USGS

Results for “Climate”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23Linked to original sources
USGS2019

Identifying credible and diverse GCMs for regional climate change studies—case study: Northeastern United States

Climate data obtained from global climate models (GCMs) form the basis of most studies of regional climate change and its impacts. Using the northeastern US as a test case, we develop a framework to systematically sub-select reliable models for use in climate change studies in the region. We retain 14 of 36 CMIP5 GCMs that (a) have satisfactory historical performance, and (b) provide diverse climate scenarios consistent with uncertainties in the multi-model ensemble (MME). The historical performance is evaluated for a wide variety of standard and process metrics including large-scale atmospheric circulation features that drive regional climate variability. Model performance is then used in conjunction with the assessment of diversity and redundancy in model projections to eliminate models without underrepresenting the uncertainty in the MME. Overall, the models show significant variations in their performance across metrics and seasons with none emerging as the best model. This combined with a lack of a strong relationship between model biases and future projections together highlight the importance of maintaining diversity in projections for risk assessment. The summer mean precipitation projections, in particular, are uncertain but also have considerable redundancy in their spatial patterns within the ensemble, which we use effectively to eliminate models. The better performing models in the retained set do suggest a potential to narrow the ranges in temperature and precipitation projections. But any further refinement should be based on a detailed analysis of the physical processes that drive regional climate variability and extremes to avoid providing overconfident projections.

Connecticut, Maine, Massachusetts, New Hampshire, ↗
USGS2020

Seasonality of biological and physical systems as indicators of climatic variation and change

Evidence-based responses to climate change by society require operational and sustained information including biophysical indicator systems that provide up-to-date measures of trends and patterns against historical baselines. Two key components linking anthropogenic climate change to impacts on socio-ecological systems are the periodic inter- and intra-annual variations in physical climate systems (seasonality) and in plant and animal life cycles (phenology). We describe a set of national indicators that reflect sub-seasonal to seasonal drivers and responses of terrestrial physical and biological systems to climate change and variability at the national scale. Proposed indicators and metrics include seasonality of surface climate conditions (e.g., frost and freeze dates and durations), seasonality of freeze/thaw in freshwater systems (e.g., timing of stream runoff and durations of lake/river ice), seasonality in ecosystem disturbances (e.g., wildfire season timing and duration), seasonality in vegetated land surfaces (e.g., green-up and brown-down of landscapes), and seasonality of organismal life-history stages (e.g., timings of bird migration). Recommended indicators have strong linkages to variable and changing climates, include abiotic and biotic responses and feedback mechanisms, and are sufficiently simple to facilitate communication to broad audiences and stakeholders interested in understanding and adapting to climate change.

Climatic Change↗
USGS2022

Climate change alters aging patterns of reservoir aquatic habitats

Two slow-moving developments are threatening reservoir aquatic habitats globally: aging and climate change. These events are projected to transform reservoir aquatic habitats in various and often unpredictable ways. Aging affects in-lake habitats directly, whereas climate change affects both in-lake and off-lake conditions. Climate change is expected to accelerate and, in some instances, possibly decelerate aging. Aging can be indexed as functional age, an index that signals the position of a reservoir along its lifespan relying on in-lake descriptors of aquatic habitat. Using existing habitat datasets and climate projections, we developed semi-quantitative predictions about the effect of climate change on reservoir functional age in the USA. Driven by increased warming, functional age was predicted to increase latitudinally from south to north with no obvious longitudinal gradient. Functional age also changed with precipitation, increasing latitudinally from south to north and longitudinally in the east and west but decreasing in the central USA. Our projections are tentative because of the uncertain nature of reservoir aging and climate change sciences, as well as the inexactness of available data and models. We review general strategies suitable for systematically dealing with the unpredictable and constantly changing conditions expected to occur this century as reservoirs certainly continue to get older, within the scope of uncertain climate change projections.

continental United States↗
USGS2023

Indicators of the effects of climate change on freshwater ecosystems

Freshwater ecosystems, including lakes, streams, and wetlands, are responsive to climate change and other natural and anthropogenic stresses. These ecosystems are frequently hydrologically and ecologically connected with one another and their surrounding landscapes, thereby integrating changes throughout their watersheds. The responses of any given freshwater ecosystem to climate change depend on the magnitude of climate forcing, interactions with other anthropogenic and natural changes, and the characteristics of the ecosystem itself. Therefore, the magnitude and manner in which freshwater ecosystems respond to climate change are difficult to predict a priori. We present a conceptual model to elucidate how freshwater ecosystems are altered by climate change. We identify eleven indicators that describe the response of freshwater ecosystems to climate change, discuss their potential value and limitations, and describe supporting measurements. Indicators are organized in three interrelated categories: hydrologic, water quality, and ecosystem structure and function. The indicators are supported by data sets with a wide range of temporal and spatial coverage, and they inform important scientific and management needs. Together, these indicators improve the understanding and management of the effects of climate change on freshwater ecosystems.

Climate Change↗
USGS2012

Ground water and climate change

As the world's largest distributed store of fresh water, ground water plays a central part in sustaining ecosystems and enabling human adaptation to climate variability and change. The strategic importance of ground water for global water and food security will probably intensify under climate change as more frequent and intense climate extremes (droughts and floods) increase variability in precipitation, soil moisture and surface water. Here we critically review recent research assessing the impacts of climate on ground water through natural and human-induced processes as well as through groundwater-driven feedbacks on the climate system. Furthermore, we examine the possible opportunities and challenges of using and sustaining groundwater resources in climate adaptation strategies, and highlight the lack of groundwater observations, which, at present, limits our understanding of the dynamic relationship between ground water and climate.

Nature Climate Change↗
USGS2020

Evaluation of Arctic warming in mid-Pliocene climate simulations

Palaeoclimate simulations improve our understanding of the climate, inform us about the performance of climate models in a different climate scenario, and help to identify robust features of the climate system. Here, we analyse Arctic warming in an ensemble of 16 simulations of the mid-Pliocene Warm Period (mPWP), derived from the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2). The PlioMIP2 ensemble simulates Arctic (60–90 ∘ N) annual mean surface air temperature (SAT) increases of 3.7 to 11.6 ∘ C compared to the pre-industrial period, with a multi-model mean (MMM) increase of 7.2 ∘ C. The Arctic warming amplification ratio relative to global SAT anomalies in the ensemble ranges from 1.8 to 3.1 (MMM is 2.3). Sea ice extent anomalies range from −3.0 to - 10.4 × 10 6 "> − 10.4 × 10 6 km 2 , with a MMM anomaly of - 5.6 × 10 6 "> − 5.6 × 10 6 km 2 , which constitutes a decrease of 53 % compared to the pre-industrial period. The majority (11 out of 16) of models simulate summer sea-ice-free conditions ( ≤ 1 × 10 6 "> ≤ 1 × 10 6 km 2 ) in their mPWP simulation. The ensemble tends to underestimate SAT in the Arctic when compared to available reconstructions, although the degree of underestimation varies strongly between the simulations. The simulations with the highest Arctic SAT anomalies tend to match the proxy dataset in its current form better. The ensemble shows some agreement with reconstructions of sea ice, particularly with regard to seasonal sea ice. Large uncertainties limit the confidence that can be placed in the findings and the compatibility of the different proxy datasets. We show that while reducing uncertainties in the reconstructions could decrease the SAT data–model discord substantially, further improvements are likely to be found in enhanced boundary conditions or model physics. Lastly, we compare the Arctic warming in the mPWP to projections of future Arctic warming and find that the PlioMIP2 ensemble simulates greater Arctic amplification than CMIP5 future climate simulations and an increase instead of a decrease in Atlantic Meridional Overturning Circulation (AMOC) strength compared to pre-industrial period. The results highlight the importance of slow feedbacks in equilibrium climate simulations, and that caution must be taken when using simulations of the mPWP as an analogue for future climate change.

Climate of the Past↗
USGS2017

Matching seed to site by climate similarity: techniques to prioritize plant materials development and use in restoration

Land management agencies are increasing the use of native plant materials for vegetation treatments to restore ecosystem function and maintain natural ecological integrity. This shift toward the use of natives has highlighted a need to increase the diversity of materials available. A key problem is agreeing on how many, and which, new accessions should be developed. Here we describe new methods that address this problem. Our methods use climate data to calculate a climate similarity index between two points in a defined extent. This index can be used to predict relative performance of available accessions at a target site. In addition, the index can be used in combination with standard cluster analysis algorithms to quantify and maximize climate coverage (mean climate similarity), given a modeled range extent and a specified number of accessions. We demonstrate the utility of this latter feature by applying it to the extents of 11 western North American species with proven or potential use in restoration. First, a species-specific seed transfer map can be readily generated for a species by predicting performance for accessions currently available; this map can be readily updated to accommodate new accessions. Next, the increase in climate coverage achieved by adding successive accessions can be explored, yielding information that managers can use to balance ecological and economic considerations in determining how many accessions to develop. This approach identifies sampling sites, referred to as climate centers, which contribute unique, complementary, climate coverage to accessions on hand, thus providing explicit sampling guidance for both germplasm preservation and research. We examine how these and other features of our approach add to existing methods used to guide plant materials development and use. Finally, we discuss how these new methods provide a framework that could be used to coordinate native plant materials development, evaluation, and use across agencies, regions, and research groups.

Ecological Applications↗
USGS2019

Partitioning global change: Assessing the relative importance of changes in climate and land cover for changes in avian distribution

Understanding the relative impact of climate change and land cover change on changes in avian distribution has implications for the future course of avian distributions and appropriate management strategies. Due to the dynamic nature of climate change, our goal was to investigate the processes that shape species distributions, rather than the current distributional patterns. To this end, we analyzed changes in the distribution of Eastern Wood Pewees (Contopus virens) and Red-eyed Vireos (Vireo olivaceus) from 1997 to 2012 using Breeding Bird Survey data and dynamic correlated-detection occupancy models. We estimated the local colonization and extinction rates of these species in relation to changes in climate (hours of extreme temperature) and changes in land cover (amount of nesting habitat). We fit six nested models to partition the deviance explained by spatial and temporal components of land cover and climate. We isolated the temporal components of environmental variables because this is the essence of global change. For both species, model fit was significantly improved when we modeled vital rates as a function of spatial variation in climate and land cover. Model fit only improved insignificantly when we added temporal variation in climate and land cover to the model. Temporal variation in climate explained more deviance than temporal variation in land cover, although both combined only explained 20% (Eastern Wood Pewee) and 6% (Red-eyed Vireo) of temporal variation in vital rates. Our results showing a significant correlation between initial occupancy and environmental covariates are consistent with biological expectation and previous studies. Our results estimating a weak correlation between vital rates and temporal changes in covariates indicate that we have yet to identify the most relevant components of global change changing the distributions of these species and, more significantly, that spatially significant covariates are not necessarily driving temporal shifts in avian distributions.

Ecology and Evolution↗
USGS2019

Spatial patterns of meadow sensitivities to interannual climate variability in the Sierra Nevada

Conservation of montane meadows is a high priority for land and water managers given their critical role in buffering the effects of climate variability and their vulnerability to increasing temperatures and evaporative demands. Recent advances in cloud computing have provided new opportunities to examine ecological responses to climate variability over the past few decades, and at large spatial scales. In this study we characterized the sensitivities (magnitude and direction of the slope) of meadow vegetation responses to interannual variations in climate. We calculated sensitivity as the regression slope between a 35-year (1985-2016) time series of Landsat-derived vegetation indices characterizing late-season vegetation vigor and water balance variables from the Basin Characterization Model. We identified April 1 snowpack as the climate variable the majority of meadows were most sensitive to. We assessed how vegetation sensitivities to snowpack varied with hydrogeomorphic context (e.g., climate, geology, soils, watershed geometry and land cover) across the Sierra Nevada mountain range using factor analysis to reduce the dimensionality of the hydrogeomorphic data, and multiple linear regression to model sensitivity responses. We found that meadow sensitivities to snowpack varied with long-term average meadow climate, indicators of watershed subsurface water storage capacity, and indicators of meadow vegetation composition. Alpine and sub-alpine meadows with high average annual precipitation, but limited catchment subsurface storage exhibited the largest sensitivities. Our results provide a novel regional perspective on spatial patterns of meadow sensitivities to climate variability and the landscape-scale hydrogeomorphic factors that influence late-season water availability in meadow ecosystems in the Sierra Nevada.

Sierra Nevada↗
USGS2017

Climate changes and wildfire alter vegetation of Yellowstone National Park, but forest cover persists

We present landscape simulation results contrasting effects of changing climates on forest vegetation and fire regimes in Yellowstone National Park, USA, by mid-21st century. We simulated potential changes to fire dynamics and forest characteristics under three future climate projections representing a range of potential future conditions using the FireBGCv2 model. Under the future climate scenarios with moderate warming (>2°C) and moderate increases in precipitation (3–5%), model simulations resulted in 1.2–4.2 times more burned area, decreases in forest cover (10–44%), and reductions in basal area (14–60%). In these same scenarios, lodgepole pine ( Pinus contorta ) decreased in basal area (18–41%), while Douglas-fir ( Pseudotsuga menziesii ) basal area increased (21–58%). Conversely, mild warming (<2°C) coupled with greater increases in precipitation (12–13%) suggested an increase in forest cover and basal area by mid-century, with spruce and subalpine fir increasing in abundance. Overall, we found changes in forest tree species compositions were caused by the climate-mediated changes in fire regime (56–315% increase in annual area burned). Simulated changes in forest composition and fire regime under warming climates portray a landscape that shifts from lodgepole pine to Douglas-fir caused by the interaction between the magnitude and seasonality of future climate changes, by climate-induced changes in the frequency and intensity of wildfires, and by tree species response.

Wyoming↗
USGS2018

STEPWAT2: An individual‐based model for exploring the impact of climate and disturbance on dryland plant communities

The combination of climate change and altered disturbance regimes is directly and indirectly affecting plant communities by mediating competitive interactions, resulting in shifts in species composition and abundance. Dryland plant communities, defined by low soil water availability and highly variable climatic regimes, are particularly vulnerable to climatic changes that exceed their historical range of variability. Individual‐based simulation models can be important tools to quantify the impacts of climate change, altered disturbance regimes, and their interaction on demographic and community‐level responses because they represent competitive interactions between individuals and individual responses to fluctuating environmental conditions. Here, we introduce STEPWAT2, an individual plant‐based simulation model for exploring the joint influence of climate change and disturbance regimes on dryland ecohydrology and plant community composition. STEPWAT2 utilizes a process‐based soil water model (SOILWAT2) to simulate available soil water in multiple soil layers, which plant individuals compete for based on the temporal matching of water and active root distributions with depth. This representation of resource utilization makes STEPWAT2 particularly useful for understanding how changes in soil moisture and altered disturbance regimes will concurrently impact demographic and community‐level responses in drylands. Our goals are threefold: (1) to describe the core modules and functions within STEPWAT2 (model description), (2) to validate STEPWAT2 model output using field data from big sagebrush plant communities (model validation), and (3) to highlight the usefulness of STEPWAT2 as a modeling framework for examining the impacts of climate change and disturbance regimes on dryland plant communities under future conditions (model application). To address goals 2 and 3, we focus on 15 sites that span the spatial extent of big sagebrush plant communities in the western United States. For goal 3, we quantify how climate change, fire, and grazing can interact to influence plant functional type biomass and composition. We use big sagebrush‐dominated plant communities to demonstrate the functionality of STEPWAT2, as these communities are among the most widespread dryland ecosystems in North America.

Ecosphere↗
USGS2025

Ecological thresholds and transformations due to climate change: The role of abiotic stress

An ecological threshold is the point at which a comparatively small environmental change triggers an abrupt and disproportionately large ecological response. In the face of accelerating climate change, there is concern that abrupt ecosystem transformations will become more widespread as critical ecological thresholds are crossed. There has been ongoing debate, however, regarding the prevalence of ecological thresholds across the natural world. While ecological thresholds are ubiquitous in some ecosystems, thresholds have been difficult to detect in others. Some studies have even concluded that threshold responses are uncommon in the natural world and overly emphasized in the ecological literature. As ecologists who work in ecosystems chronically exposed to high abiotic stress, we consider ecological thresholds and ecosystem transformations to be critical concepts that can greatly advance understanding of ecological responses to climate change and inform ecosystem management. But quantifying ecological thresholds can be challenging, if not impossible, without data that are strategically collected for that purpose. Here, we present a conceptual framework built upon linkages between abiotic stress, climate-driven ecological threshold responses, and the risk of ecosystem transformation. We also present a simple approach for quantifying ecological thresholds across abiotic stress gradients. We hypothesize that climate-driven threshold responses are especially influential in ecosystems chronically exposed to high abiotic stress, where autotroph diversity is low and foundation species play a prominent ecological role. Abiotic conditions in these environments are often near physiological tolerance limits of foundation species, which means that small abiotic changes can trigger landscape-level ecological transformations. Conversely, the alleviation of stress near thresholds can allow foundation species to thrive and spread into previously inhospitable locations. We provide examples of this climate-driven threshold behavior from four high-stress environments: coastal wetlands, coral reefs, drylands, and alpine ecosystems. Our overarching aim in this review is to clarify the strong relationships between abiotic stress, climate-driven ecological thresholds, and the risk of ecosystem transformation under climate change.

Ecosphere↗
USGS2016

Mangrove expansion and contraction at a poleward range limit: Climate extremes and land-ocean temperature gradients

Within the context of climate change, there is a pressing need to better understand the ecological implications of changes in the frequency and intensity of climate extremes. Along subtropical coasts, less frequent and warmer freeze events are expected to permit freeze-sensitive mangrove forests to expand poleward and displace freeze-tolerant salt marshes. Here, our aim was to better understand the drivers of poleward mangrove migration by quantifying spatiotemporal patterns in mangrove range expansion and contraction across land-ocean temperature gradients. Our work was conducted in a freeze-sensitive mangrove-marsh transition zone that spans a land-ocean temperature gradient in one of the world's most wetland-rich regions (Mississippi River Deltaic Plain; Louisiana, USA). We used historical air temperature data (1893-2014), alternative future climate scenarios, and coastal wetland coverage data (1978-2011) to investigate spatiotemporal fluctuations and climate-wetland linkages. Our analyses indicate that changes in mangrove coverage have been controlled primarily by extreme freeze events (i.e., air temperatures below a threshold zone of -6.3 to -7.6 °C). We expect that in the past 121 years, mangrove range expansion and contraction has occurred across land-ocean temperature gradients. Mangrove resistance, resilience, and dominance were all highest in areas closer to the ocean where temperature extremes were buffered by large expanses of water and saturated soil. Under climate change, these areas will likely serve as local hotspots for mangrove dispersal, growth, range expansion, and displacement of salt marsh. Collectively, our results show that the frequency and intensity of freeze events across land-ocean temperature gradients greatly influences spatiotemporal patterns of range expansion and contraction of freeze-sensitive mangroves. We expect that, along subtropical coasts, similar processes govern the distribution and abundance of other freeze-sensitive organisms. In broad terms, our findings can be used to better understand and anticipate the ecological effects of changing winter climate extremes, especially within the transition zone between tropical and temperate climates.

Louisiana↗
USGS2017

Climate change may restrict dryland forest regeneration in the 21st century

The persistence and geographic expansion of dryland forests in the 21st century will be influenced by how climate change supports the demographic processes associated with tree regeneration. Yet, the way that climate change may alter regeneration is unclear. We developed a quantitative framework that estimates forest regeneration potential (RP) as a function of key environmental conditions for ponderosa pine, a key dryland forest species. We integrated meteorological data and climate projections for 47 ponderosa pine forest sites across the western United States, and evaluated RP using an ecosystem water balance model. Our primary goal was to contrast conditions supporting regeneration among historical, mid-21st century and late-21st century time frames. Future climatic conditions supported 50% higher RP in 2020–2059 relative to 1910–2014. As temperatures increased more substantially in 2060–2099, seedling survival decreased, RP declined by 50%, and the frequency of years with very low RP increased from 25% to 58%. Thus, climate change may initially support higher RP and increase the likelihood of successful regeneration events, yet will ultimately reduce average RP and the frequency of years with moderate climate support of regeneration. Our results suggest that climate change alone may begin to restrict the persistence and expansion of dryland forests by limiting seedling survival in the late 21st century.

Ecology↗
USGS2013

Climate change and watershed mercury export: a multiple projection and model analysis

Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling.

South Carolina↗
USGS2021

Climate change effects on North American fish and fisheries to inform adaptation strategies

Climate change is a global persistent threat to fish and fish habitats throughout North America. Climate-induced modification of environmental regimes, including changes in streamflow, water temperature, salinity, storm surges, and habitat connectivity can change fish physiology, disrupt spawning cues, cause fish extinctions and invasions, and alter fish community structure. Reducing greenhouse emissions remains the primary mechanism to slow the pace of climate change, but local and regional management agencies and stakeholders have developed an arsenal of adaptation strategies to help partially mitigate the effects of climate change on fish. We summarize common stressors posed by climate change in North America, including (1) increased water temperature, (2) changes in precipitation, (3) sea level rise, and (4) ocean acidification, and present potential adaptation strategies that fishery professionals may apply to help vulnerable fish and fisheries cope with a changing climate. Although our adaptation strategies are primarily from North America, they have broader geographic applicability to fish and aquatic biota in other jurisdictions. These strategies provide opportunities for managers to mitigate the effects of climate change on fish and fish habitat while needed global policies to reduce greenhouse gas emissions emerge, which may offer more lasting solutions.

Fisheries Magazine↗
USGS2013

Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation

Climate models may be limited in their inferential use if they cannot be locally validated or do not account for spatial uncertainty. Much of the focus has gone into determining which interpolation method is best suited for creating gridded climate surfaces, which often a covariate such as elevation (Digital Elevation Model, DEM) is used to improve the interpolation accuracy. One key area where little research has addressed is in determining which covariate best improves the accuracy in the interpolation. In this study, a comprehensive evaluation was carried out in determining which covariates were most suitable for interpolating climatic variables (e.g. precipitation, mean temperature, minimum temperature, and maximum temperature). We compiled data for each climate variable from 1950 to 1999 from approximately 500 weather stations across the Western United States (32° to 49° latitude and −124.7° to −112.9° longitude). In addition, we examined the uncertainty of the interpolated climate surface. Specifically, Thin Plate Spline (TPS) was used as the interpolation method since it is one of the most popular interpolation techniques to generate climate surfaces. We considered several covariates, including DEM, slope, distance to coast (Euclidean distance), aspect, solar potential, radar, and two Normalized Difference Vegetation Index (NDVI) products derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). A tenfold cross-validation was applied to determine the uncertainty of the interpolation based on each covariate. In general, the leading covariate for precipitation was radar, while DEM was the leading covariate for maximum, mean, and minimum temperatures. A comparison to other products such as PRISM and WorldClim showed strong agreement across large geographic areas but climate surfaces generated in this study (ClimSurf) had greater variability at high elevation regions, such as in the Sierra Nevada Mountains.

International Journal of Climatology↗
USGS2022

Dispersal limitations increase vulnerability under climate change for reptiles and amphibians in the southwestern United States

Species conservation plans frequently rely on information that spans political and administrative boundaries, especially when predictions are needed of future habitat under climate change; however, most species conservation plans and their requisite predictions of future habitat are often limited in geographical scope. Moreover, dispersal constraints for species of concern are not often incorporated into distribution models, which can result in overly optimistic predictions of future habitat. We used a standard modeling approach across a suite of 23 taxa of amphibians and reptiles in the North American deserts (560,024 km 2 across 13 ecoregions) to assess impacts of climate change on habitat and combined landscape population dispersal simulations with species distribution modeling to reduce the risk of predicting future habitat in areas that are not available to species given their dispersal abilities. We used 3 general circulation models and 2 representative concentration pathways (RCPs) to represent multiple scenarios of future habitat potential and assess which study species may be most vulnerable to changes forecasted under each climate scenario. Amphibians were the most vulnerable taxa, but the most vulnerable species tended to be those with the lowest dispersal ability rather than those with the most specialized niches. Under the most optimistic climate scenario considered (RCP 2.6; a stringent scenario requiring declining emissions from 2020 to near zero emissions by 2100), 76% of the study area may experience a loss of >20% of the species examined, while up to 87% of the species currently present may be lost in some areas under the most pessimistic climate scenario (RCP 8.5; a scenario wherein greenhouse gases continue to increase through 2100 based on trajectories from the mid-century). Most areas with high losses were concentrated in the Arizona and New Mexico Plateau ecoregion, the Edwards Plateau in Texas, and the Southwestern Tablelands in New Mexico and Texas, USA. Under the most pessimistic climate scenario, all species are predicted to lose some existing habitat, with an average of 34% loss of extant habitat across all species. Even under the most optimistic scenario, we detected an average loss of 24% of extant habitat across all species, suggesting that changing climates may influence the ranges of reptiles and amphibians in the Southwest.

Arizona, California, Nevada, New Mexico, Texas, Ut↗