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At least 217 records · Page 12Linked to original sources
USGS2009

Adaptation of farming practices could buffer effects of climate change on northern prairie wetlands

Wetlands of the Prairie Pothole Region of North America are vulnerable to climate change. Adaptation of farming practices to mitigate adverse impacts of climate change on wetland water levels is a potential watershed management option. We chose a modeling approach (WETSIM 3.2) to examine the effects of changes in climate and watershed cover on the water levels of a semi-permanent wetland in eastern South Dakota. Land-use practices simulated were unmanaged grassland, grassland managed with moderately heavy grazing, and cultivated crops. Climate scenarios were developed by adjusting the historical climate in combinations of 2??C and 4??C air temperature and ??10% precipitation. For these climate change scenarios, simulations of land use that produced water levels equal to or greater than unmanaged grassland under historical climate were judged to have mitigative potential against a drier climate. Water levels in wetlands surrounded by managed grasslands were significantly greater than those surrounded by unmanaged grassland. Management reduced both the proportion of years the wetland went dry and the frequency of dry periods, producing the most dynamic vegetation cycle for this modeled wetland. Both cultivated crops and managed grassland achieved water levels that were equal or greater than unmanaged grassland under historical climate for the 2??C rise in air temperature, and the 2??C rise plus 10% increase in precipitation scenarios. Managed grassland also produced water levels that were equal or greater than unmanaged grassland under historical climate for the 4??C rise plus 10% increase in precipitation scenario. Although these modeling results stand as hypotheses, they indicate that amelioration potential exists for a change in climate up to an increase of 2??C or 4??C with a concomitant 10% increase in precipitation. Few empirical data exist to verify the results of such land-use simulations; however, adaptation of farming practices is one possible mitigation avenue available for prairie wetlands. ?? 2009, The Society of Wetland Scientists.

Wetlands↗
USGS2015

Climate-smart management of biodiversity

Determining where biodiversity is likely to be most vulnerable to climate change and methods to reduce that vulnerability are necessary first steps to incorporate climate change into biodiversity management plans. Here, we use a spatial climate change vulnerability assessment to (1) map the potential vulnerability of terrestrial biodiversity to climate change in the northeastern United States and (2) provide guidance on how and where management actions for biodiversity could provide long-term benefits under climate change (i.e., climate-smart management considerations). Our model suggests that biodiversity will be most vulnerable in Delaware, Maryland, and the District of Columbia due to the combination of high climate change velocity, high landscape resistance, and high topoclimate homogeneity. Biodiversity is predicted to be least vulnerable in Vermont, Maine, and New Hampshire because large portions of these states have low landscape resistance, low climate change velocity, and low topoclimate homogeneity. Our spatial climate-smart management considerations suggest that: (1) high topoclimate diversity could moderate the effects of climate change across 50% of the region; (2) decreasing local landscape resistance in conjunction with other management actions could increase the benefit of those actions across 17% of the region; and (3) management actions across 24% of the region could provide long-term benefits by promoting short-term population persistence that provides a source population capable of moving in the future. The guidance and framework we provide here should allow conservation organizations to incorporate our climate-smart management considerations into management plans without drastically changing their approach to biodiversity conservation.

Ecosphere↗
USGS2010

Water-the Nation's Fundamental Climate Issue A White Paper on the U.S. Geological Survey Role and Capabilities

Of all the potential threats posed by climatic variability and change, those associated with water resources are arguably the most consequential for both society and the environment (Waggoner, 1990). Climatic effects on agriculture, aquatic ecosystems, energy, and industry are strongly influenced by climatic effects on water. Thus, understanding changes in the distribution, quantity and quality of, and demand for water in response to climate variability and change is essential to planning for and adapting to future climatic conditions. A central role of the U.S. Geological Survey (USGS) with respect to climate is to document environmental changes currently underway and to develop improved capabilities to predict future changes. Indeed, a centerpiece of the USGS role is a new Climate Effects Network of monitoring sites. Measuring the climatic effects on water is an essential component of such a network (along with corresponding effects on terrestrial ecosystems). The USGS needs to be unambiguous in communicating with its customers and stakeholders, and with officials at the Department of the Interior, that although modeling future impacts of climate change is important, there is no more critical role for the USGS in climate change science than that of measuring and describing the changes that are currently underway. One of the best statements of that mission comes from a short paper by Ralph Keeling (2008) that describes the inspiration and the challenges faced by David Keeling in operating the all-important Mauna Loa Observatory over a period of more than four decades. Ralph Keeling stated: 'The only way to figure out what is happening to our planet is to measure it, and this means tracking changes decade after decade and poring over the records.' There are three key ideas that are important to the USGS in the above-mentioned sentence. First, to understand what is happening requires measurement. While models are a tool for learning and testing our understanding, they are not a substitute for observations. The second key idea is that measurement needs to be done over a period of many decades. When viewing hydrologic records over time scales of a few years to a few decades, trends commonly appear. However, when viewed in the context of many decades to centuries, these short-term trends are recognized as being part of much longer term oscillations. Thus, while we might want to initiate monitoring of important aspects of our natural resources, the data that will prove to be most useful in the next few years are those records that already have long-term continuity. USGS streamflow and groundwater level data are excellent examples of such long-term records. These measured data span many decades, follow standard protocols for collection and quality assurance, and are stored in a database that provides access to the full period of record. The third point from the Keeling quote relates to the notion of ?poring over the records.? Important trends will not generally jump off the computer screen at us. Thoughtful analyses are required to get past a number of important but confounding influences in the record, such as the role of seasonal variation, changes in water management, or influences of quasi-periodic phenomena, such as El Ni?o-Southern Oscillation (ENSO) or the Pacific Decadal Oscillation (PDO). No organization is better situated to pore over the records than the USGS because USGS scientists know the data, quality-assure the data, understand the factors that influence the data, and have the ancillary information on the watersheds within which the data are collected. To fulfill the USGS role in understanding climatic variability and change, we need to continually improve and strengthen two of our key capabilities: (1) preserving continuity of long-term water data collection and (2) analyzing and interpreting water data to determine how the Nation's water resources are changing. Understanding change in water resources

Circular↗
USGS2014

Tribal engagement strategy of the South Central Climate Science Center, 2014

The South Central Climate Science Center was established by the U.S. Department of the Interior in 2012 to increase understanding of climate change and coordinate an effective response to climate-change effects on Native American tribes and natural and cultural resources that the Department manages. The eight regional Climate Science Centers of the U.S. Department of the Interior work closely with natural-resource management agencies, university researchers, and others such as tribes and private landowners on climate-change issues. The relatively large number of Native Americans in the south central United States and their special knowledge of changing ecosystems make working with tribes and tribal members on climate-change issues particularly important in this part of the Nation. This circular describes priorities of the South Central Climate Science Center and provides information about resources available from Climate Science Centers and partner agencies regarding climate change. The circular also describes how this Climate Science Center, tribes and tribal members, and others can collaborate to minimize potential harmful effects of climate change on human society and our surrounding ecosystems.

Louisiana, New Mexico, Oklahoma, Texas↗
USGS2014

Projecting climate effects on birds and reptiles of the Southwestern United States

We modeled the current and future breeding ranges of seven bird and five reptile species in the Southwestern United States with sets of landscape, biotic (plant), and climatic global circulation model (GCM) variables. For modeling purposes, we used PRISM data to characterize the climate of the Western United States between 1980 and 2009 (baseline for birds) and between 1940 and 2009 (baseline for reptiles). In contrast, we used a pre-selected set of GCMs that are known to be good predictors of southwestern climate (five individual and one ensemble GCM), for the A1B emission scenario, to characterize future climatic conditions in three time periods (2010–39; 2040–69; and, 2070–99). Our modeling approach relied on conceptual models for each target species to inform selection of candidate explanatory variables and to interpret the ecological meaning of developed probabilistic distribution models. We employed logistic regression and maximum entropy modeling techniques to create a set of probabilistic models for each target species. We considered climatic, landscape, and plant variables when developing and testing our probabilistic models. Climatic variables included the maximum and minimum mean monthly and seasonal temperature and precipitation for three time periods. Landscape features included terrain ruggedness and insolation. We also considered plant species distributions as candidate explanatory variables where prior ecological knowledge implicated a strong association between a plant and animal species. Projected changes in range varied widely among species, from major losses to major gains. Breeding bird ranges exhibited greater expansions and contractions than did reptile species. We project range losses for Williamson’s sapsucker and pygmy nuthatch of a magnitude that could move these two species close to extinction within the next century. Although both species currently have a relatively limited distribution, they can be locally common, and neither are presently considered candidates for prospective endangerment. We project range losses of over 40 percent, from its current extent of occurrence, for the plateau striped whiptail, Arizona black rattlesnake, and common lesser earless lizard. Currently, these reptile species are thought to be common or at least locally abundant throughout their ranges. The total contribution of plants in each distribution model was very small, but models that contained at least one plant always outperformed models with only physical variables (climatic or landscape). The magnitude of change in projected range increased further into the future, especially when a plant was in the model. Among bird species, those that had the strongest association with a landscape feature during the breeding season, such as terrain ruggedness and insolation, exhibited the smallest contractions in projected breeding range in the future. In contrast, bird species that had weak associations with landscape features, but strong climatic associations, suffered the greatest breeding range contractions. Thus, landscape effects appeared to buffer some of the negative effects of climate change for some species. Among bird species, magnitude of change in projected breeding range was positively related to the annual average temperature of their baseline distribution, thus species with the warmest breeding ranges exhibited the greatest changes in future breeding ranges. This pattern was not evident for reptiles, but might exist if additional species were included in the model. Our results provide managers with a series of projected range maps that will enable scientists, concerned citizens, and wildlife managers to identify what the potential effects of climate change will be on bird and reptile distributions in the Western United States. We hope that our results can be used in proactive ways to mitigate some of the potential effects of climate change on selected species.

Colorado Plateau;Sonoran Desert↗
USGS2013

Simulation of climate-change effects on streamflow, lake water budgets, and stream temperature using GSFLOW and SNTEMP, Trout Lake Watershed, Wisconsin

Although groundwater and surface water are considered a single resource, historically hydrologic simulations have not accounted for feedback loops between the groundwater system and other hydrologic processes. These feedbacks include timing and rates of evapotranspiration, surface runoff, soil-zone flow, and interactions with the groundwater system. Simulations that iteratively couple the surface-water and groundwater systems, however, are characterized by long run times and calibration challenges. In this study, calibrated, uncoupled transient surface-water and steady-state groundwater models were used to construct one coupled transient groundwater/surface-water model for the Trout Lake Watershed in north-central Wisconsin, USA. The computer code GSFLOW (Ground-water/Surface-water FLOW) was used to simulate the coupled hydrologic system; a surface-water model represented hydrologic processes in the atmosphere, at land surface, and within the soil-zone, and a groundwater-flow model represented the unsaturated zone, saturated zone, stream, and lake budgets. The coupled GSFLOW model was calibrated by using heads, streamflows, lake levels, actual evapotranspiration rates, solar radiation, and snowpack measurements collected during water years 1998–2007; calibration was performed by using advanced features present in the PEST parameter estimation software suite. Simulated streamflows from the calibrated GSFLOW model and other basin characteristics were used as input to the one-dimensional SNTEMP (Stream-Network TEMPerature) model to simulate daily stream temperature in selected tributaries in the watershed. The temperature model was calibrated to high-resolution stream temperature time-series data measured in 2002. The calibrated GSFLOW and SNTEMP models were then used to simulate effects of potential climate change for the period extending to the year 2100. An ensemble of climate models and emission scenarios was evaluated. Downscaled climate drivers for the period 2010–2100 showed increases in maximum and minimum temperature over the scenario period. Scenarios of future precipitation did not show a monotonic trend like temperature. Uncertainty in the climate drivers increased over time for both temperature and precipitation. Separate calibration of the uncoupled groundwater and surface-water models did not provide a representative initial parameter set for coupled model calibration. A sequentially linked calibration, in which the uncoupled models were linked by means of utility software, provided a starting parameter set suitable for coupled model calibration. Even with sequentially linked calibration, however, transmissivity of the lower part of the aquifer required further adjustment during coupled model calibration to attain reasonable parameter values for evaporation rates off a small seepage lake (a lake with no appreciable surface-water outlets) with a long history of study. The resulting coupled model was well calibrated to most types of observed time-series data used for calibration. Daily stream temperatures measured during 2002 were successfully simulated with SNTEMP; the model fit was acceptable for a range of groundwater inflow rates into the streams. Forecasts of potential climate change scenarios showed growing season length increasing by weeks, and both potential and actual evapotranspiration rates increasing appreciably, in response to increasing air temperature. Simulated actual evapotranspiration rates increased less than simulated potential evapotranspiration rates as a result of water limitation in the root zone during the summer high-evapotranspiration period. The hydrologic-system response to climate change was characterized by a reduction in the importance of the snow-melt pulse and an increase in the importance of fall and winter groundwater recharge. The less dynamic hydrologic regime is likely to result in drier soil conditions in rainfed wetlands and uplands, in contrast to less drying in groundwater-fed systems. Seepage lakes showed larger forecast stage declines related to climate change than did drainage lakes (lakes with outlet streams). Seepage lakes higher in the watershed (nearer to groundwater divides) had less groundwater inflow and thus had larger forecast declines in lake stage; however, ground-water inflow to seepage lakes in general tended to increase as a fraction of the lake budgets with lake-stage decline because inward hydraulic gradients increased. Drainage lakes were characterized by less simulated stage decline as reductions in outlet streamflow of set losses to other water flows. Net groundwater inflow tended to decrease in drainage lakes over the scenario period. Simulated stream temperatures increased appreciably with climate change. The estimated increase in annual average temperature ranged from approximately 1 to 2 degrees Celsius by 2100 in the stream characterized by a high groundwater inflow rate and 2 to 3 degrees Celsius in the stream with a lower rate. The climate drivers used for the climate-change scenarios had appreciable variation between the General Circulation Model and emission scenario selected; this uncertainty was reflected in hydrologic flow and temperature model results. Thus, as with all forecasts of this type, the results are best considered to approximate potential outcomes of climate change.

Wisconsin↗
USGS2015

Historical and projected climate (1901–2050) and hydrologic response of karst aquifers, and species vulnerability in south-central Texas and western South Dakota

Two karst aquifers, the Edwards aquifer in the Balcones Escarpment region of south-central Texas and the Madison aquifer in the Black Hills of western South Dakota, were evaluated for hydrologic response to projected climate change through 2050. Edwards aquifer sites include Barton Springs, the Bexar County Index Well, and Comal Springs. Madison aquifer sites include Spearfish Creek and Rhoads Fork Spring. Climate projections at sites were based on output from the Community Climate System Model of global climate, linked to the Weather Research and Forecasting (WRF) model of regional climate. The WRF model output was bias adjusted to match means for 1981–2010 from records at weather stations near Madison and Edwards aquifer sites, including Boerne, Texas, and Custer and Lead, South Dakota. Hydrologic response at spring and well sites was based on the Rainfall-Response Aquifer and Watershed Flow (RRAWFLOW) model. The WRF model climate projections for 2011–50 indicate a significant upward trend in annual air temperature for all three weather stations and a significant downward trend in annual precipitation for the Boerne weather station. Annual springflow simulated by the RRAWFLOW model had a significant downward trend for Edwards aquifer sites and no trend for Madison aquifer sites. Flora and fauna that rely on springflow from Edwards and Madison aquifer sites were assessed for vulnerability to projected climate change on the basis of the Climate Change Vulnerability Index (CCVI). The CCVI is determined by the exposure of a species to climate, the sensitivity of the species, and the ability of the species to cope with climate change. Sixteen species associated with springs and groundwater were assessed in the Balcones Escarpment region. The Barton Springs salamander ( Eurycea sosorum ) was scored as highly vulnerable with moderate confidence. Nine species—three salamanders, a fountain darter ( Etheostoma fonticola ), three insects, and two amphipods—were scored as moderately vulnerable. The remaining six species—four vascular plants, the Barton cavesnail ( Stygopyrgus bartonensis ), and a cave shrimp—were scored as not vulnerable/presumed stable (not vulnerable and evidence does not support change in abundance or range of the species). Vulnerability of eight species associated with streams that receive springflow from the Madison aquifer in the Black Hills was assessed. Of these, the American dipper ( Cinclus mexicanus ) and the lesser yellow lady’s slipper ( Cypripedium parviflorum ) were scored as moderately vulernable with high confidence. The dwarf scouringrush ( Equisetum scirpoides ) and autumn willow ( Salix serissima ) were also scored as moderately vulnerable with moderate to low confidence, respectively. Other species were assessed as not vulnerable/presumed stable or not vulnerable/increase likely (not vulnerable and evidence supporting an increase in abundance or range of the species). Lower vulnerability scores for the Black Hills species in comparison to the Balcones Escarpment species reflect lower endemicity, higher projected springflow than in the historical period, and high thermal tolerance of many of the species for the Black Hills. Importantly, climate change vulnerability scores differed substantially for Edwards aquifer species when RRAWFLOW model projections were included, resulting in increased vulnerability scores for 12 of the 16 species.

South Dakota, Texas↗
USGS2020

Genetic and environmental indicators of climate change vulnerability for desert bighorn sheep

Assessments of organisms’ vulnerability to potential climatic shifts are increasingly common. Such assessments are often conducted at the species level and focused primarily on the magnitude of anticipated climate change (i.e., climate exposure). However, wildlife management would benefit from population-level assessments that also incorporate measures of local or regional potential for organismal adaptation to change. Estimates of genetic diversity, gene flow, and landscape connectivity can address this need and complement climate exposure estimates to establish management priorities at broad to local scales. We provide an example of this holistic approach for desert bighorn sheep ( Ovis canadensis nelsoni ) within and surrounding lands administered by the U.S. National Park Service. We used genetic and environmental data from 62 populations across the southwestern U.S. to delineate genetic structure, evaluate relationships between genetic diversity and isolation, and estimate relative climate vulnerability for populations as a function of five variables associated with species’ responses to climate change: genetic diversity, genetic isolation, geographic isolation, forward climate velocity within a population’s habitat patch (a measure of geographic movement rate required for an organism to maintain constant climate conditions), and maximum elevation within the habitat patch (a measure of current climate stress, as lower maximum elevation is associated with higher temperature, lower precipitation, and lower population persistence). Genetic structure analyses revealed a high-level division between populations in southeastern Utah and populations in the remainder of the study area, which were further differentiated into four lower-level genetic clusters. Genetic diversity decreased with population isolation, whereas genetic differentiation increased, but these patterns were stronger for native populations than for translocated populations. Populations exhibited large variation in predicted vulnerability across the study area with respect to all variables, but native populations occupying relatively intact landscapes, such as Death Valley and Grand Canyon national parks, had the lowest overall vulnerability. These results provide local and regional context for conservation and management decisions regarding bighorn populations in a changing climate. Our study further demonstrates how assessments combining multiple factors could allow a more integrated response, such as increasing efforts to maintain connectivity and thus potential for adaptation in areas experiencing rapid climate change.

Arizona, California, Nevada, Utah↗
USGS2016

Climate change and future fire regimes: Examples from California

Climate and weather have long been noted as playing key roles in wildfire activity, and global warming is expected to exacerbate fire impacts on natural and urban ecosystems. Predicting future fire regimes requires an understanding of how temperature and precipitation interact to control fire activity. Inevitably this requires historical analyses that relate annual burning to climate variation. Fuel structure plays a critical role in determining which climatic parameters are most influential on fire activity, and here, by focusing on the diversity of ecosystems in California, we illustrate some principles that need to be recognized in predicting future fire regimes. Spatial scale of analysis is important in that large heterogeneous landscapes may not fully capture accurate relationships between climate and fires. Within climatically homogeneous subregions, montane forested landscapes show strong relationships between annual fluctuations in temperature and precipitation with area burned; however, this is strongly seasonal dependent; e.g., winter temperatures have very little or no effect but spring and summer temperatures are critical. Climate models that predict future seasonal temperature changes are needed to improve fire regime projections. Climate does not appear to be a major determinant of fire activity on all landscapes. Lower elevations and lower latitudes show little or no increase in fire activity with hotter and drier conditions. On these landscapes climate is not usually limiting to fires but these vegetation types are ignition-limited. Moreover, because they are closely juxtaposed with human habitations, fire regimes are more strongly controlled by other direct anthropogenic impacts. Predicting future fire regimes is not rocket science; it is far more complicated than that. Climate change is not relevant to some landscapes, but where climate is relevant, the relationship will change due to direct climate effects on vegetation trajectories, as well as by feedback processes of fire effects on vegetation distribution, plus policy changes in how we manage ecosystems.

Geoscience Canada↗
USGS2004

Simulated hydrologic responses to climate variations and change in the Merced, Carson, and American River basins, Sierra Nevada, California, 1900-2099

Hydrologic responses of river basins in the Sierra Nevada of California to historical and future climate variations and changes are assessed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-yr period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th century until about 1975 when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st century with an attendant +2.5 °C warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. The various projected trends in the business-as-usual simulations become readily visible despite realistic simulated natural climatic and hydrologic variability by about 2025. In contrast to these changes that are mostly associated with streamflow timing, long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. A control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995 yields climate and streamflow timing conditions much like the 1980s and 1990s throughout its duration. The availability of continuous climate-change projection outputs and careful design of initial conditions and control experiments, like those utilized here, promise to improve the quality and usability of future climate-change impact assessments.

Climatic Change↗
USGS2019

Not so normal normals: Species distribution model results are sensitive to choice of climate normals and model type

Species distribution models have many applications in conservation and ecology, and climate data are frequently a key driver of these models. Often, correlative modeling approaches are developed with readily available climate data; however, the impacts of the choice of climate normals is rarely considered. Here, we produced species distribution models for five disparate species using four different modeling algorithms and compared results between two different, but overlapping, climate normals time periods. Although the correlation structure among climate predictors did not change between the time periods, model results were sensitive to both baseline climate period and model method, even with model parameters specifically tuned to a species. Each species and each model type had at least one difference in variable retention or relative ranking with the change in climate time period. Pairwise comparisons of spatial predictions were also different, ranging from a low of 1.6% for climate period differences to a high of 25% for algorithm differences. While uncertainty from model algorithm selection is recognized as an important source of uncertainty, the impact of climate period is not commonly assessed. These uncertainties may affect conservation decisions, especially when projecting to future climates, and should be evaluated during model development.

Climate↗
USGS2024

Declining ecological resilience and invasion resistance under climate change in the sagebrush region, United States

In water-limited dryland ecosystems of the Western United States, climate change is intensifying the impacts of heat, drought, and wildfire. Disturbances often lead to increased abundance of invasive species, in part, because dryland restoration and rehabilitation are inhibited by limited moisture and infrequent plant recruitment events. Information on ecological resilience to disturbance (recovery potential) and resistance to invasive species can aid in addressing these challenges by informing long-term restoration and conservation planning. Here, we quantified the impacts of projected future climate on ecological resilience and invasion resistance (R&R) in the sagebrush region using novel algorithms based on ecologically relevant and climate-sensitive predictors of climate and ecological drought. We used a process-based ecohydrological model to project these predictor variables and resulting R&R indicators for two future climate scenarios and 20 climate models. Results suggested widespread future R&R decreases (24%–34% of the 1.16 million km 2 study area) that are generally consistent among climate models. Variables related to rising temperatures were most strongly linked to decreases in R&R indicators. New continuous R&R indices quantified responses to climate change; particularly useful for areas without projected change in the R&R category but where R&R still may decrease, for example, some of the areas with a historically low R&R category. Additionally, we found that areas currently characterized as having high sagebrush ecological integrity had the largest areal percentage with expected declines in R&R in the future, suggesting continuing declines in sagebrush ecosystems. One limitation of these R&R projections was relatively novel future climatic conditions in particularly hot and dry areas that were underrepresented in the training data. Including more data from these areas in future updates could further improve the reliability of the projections. Overall, these projected future declines in R&R highlight a growing challenge for natural resource managers in the region, and the resulting spatially explicit datasets provide information that can improve long-term risk assessments, prioritizations, and climate adaptation efforts.

western United States↗
USGS2017

Assessing the potential of translocating vulnerable forest birds by searching for novel and enduring climatic ranges

Hawaiian forest birds are imperiled, with fewer than half the original >40 species remaining extant. Recent studies document ongoing rapid population decline and pro- ject complete climate-based range losses for the critically endangered Kaua’i endemics ‘akeke’e (Loxops caeruleirostris) and ‘akikiki (Oreomystis bairdi) by end-of-century due to projected warming. Climate change facilitates the upward expansion of avian malaria into native high elevation forests where disease was historically absent. While intensi- fied conservation efforts attempt to safeguard these species and their habitats, the magnitude of potential loss and the urgency of this situation require all conservation options to be seriously considered. One option for Kaua’i endemics is translocation to islands with higher elevation habitats. We explored the feasibility of interisland translocation by projecting baseline and future climate-based ranges of ‘akeke’e and ‘akikiki across the Hawaiian archipelago. For islands where compatible climates for these spe- cies were projected to endure through end-of-century, an additional climatic niche overlap analysis compares the spatial overlap between Kaua’i endemics and current native species on prospective destination islands. Suitable climate-based ranges exist on Maui and Hawai’i for these Kaua’i endemics that offer climatically distinct areas compared to niche distributions of destination island endemics. While we recognize that any decision to translocate birds will include assessing numerous additional social, political, and biological factors, our focus on locations of enduring and ecologically compatible climate-based ranges represents the first step to evaluate this potential conservation option. Our approach considering baseline and future distributions of species with climatic niche overlap metrics to identify undesirable range overlap provides a method that can be utilized for other climate-vulnerable species with disjointed compatible environments beyond their native range.

Hawaii↗
USGS2015

Incorporating climate change projections into riparian restoration planning and design

Climate change and associated changes in streamflow may alter riparian habitats substantially in coming decades. Riparian restoration provides opportunities to respond proactively to projected climate change effects, increase riparian ecosystem resilience to climate change, and simultaneously address effects of both climate change and other human disturbances. However, climate change may alter which restoration methods are most effective and which restoration goals can be achieved. Incorporating climate change into riparian restoration planning and design is critical to long-term restoration of desired community composition and ecosystem services. In this review, we discuss and provide examples of how climate change might be incorporated into restoration planning at the key stages of assessing the project context, establishing restoration goals and design criteria, evaluating design alternatives, and monitoring restoration outcomes. Restoration planners have access to numerous tools to predict future climate, streamflow, and riparian ecology at restoration sites. Planners can use those predictions to assess which species or ecosystem services will be most vulnerable under future conditions, and which sites will be most suitable for restoration. To accommodate future climate and streamflow change, planners may need to adjust methods for planting, invasive species control, channel and floodplain reconstruction, and water management. Given the considerable uncertainty in future climate and streamflow projections, riparian ecological responses, and effects on restoration outcomes, planners will need to consider multiple potential future scenarios, implement a variety of restoration methods, design projects with flexibility to adjust to future conditions, and plan to respond adaptively to unexpected change.

Ecohydrology↗
USGS2017

Erosion of refugia in the Sierra Nevada meadows network with climate change

Climate refugia management has been proposed as a climate adaptation strategy in the face of global change. Key to this strategy is identification of these areas as well as an understanding of how they are connected on the landscape. Focusing on meadows of the Sierra Nevada in California, we examined multiple factors affecting connectivity using circuit theory, and determined how patches have been and are expected to be affected by climate change. Connectivity surfaces varied depending upon the underlying hypothesis, although meadow area and elevation were important features for higher connectivity. Climate refugia that would promote population persistence were identified from downscaled climate layers, based on locations with minimal climatic change from historical conditions. This approach was agnostic to specific species, yielding a broad perspective about changes and localized habitats. Connectivity was not a consistent predictor of refugial status in the 20th century, but expected future climate refugia tended to have higher connectivity than those that recently deviated from historical conditions. Climate change is projected to reduce the number of refugial meadows on a variety of climate axes, resulting in a sparser network of potential refugia across elevations. Our approach provides a straightforward method that can be used as a tool to prioritize places for climate adaptation.

California↗
USGS2024

Using life history traits to assess climate change vulnerability in understudied species

Climate change is a primary threat to biodiversity, but for many species, we still lack information required to assess their relative vulnerability to changes. Climate change vulnerability assessment (CCVA) is a widely used technique to rank relative vulnerability to climate change based on species characteristics, such as their distributions, habitat associations, environmental tolerances, and life-history traits. However, for species that we expect are vulnerable to climate change yet are understudied, like many amphibians, we often lack information required to construct CCVAs using existing methods. We used the CCVA framework to construct trait-based models based on life history theory, using empirical evidence of traits and distributions that reflected sensitivity of amphibians to environmental perturbation. We performed CCVAs for amphibians in 7 states in the north-central USA, focusing on 31 aquatic-breeding species listed as species of greatest conservation need by at least 1 state. Because detailed information on habitat requirements is unavailable for most amphibian species, we used species distributions and information on traits expected to influence vulnerability to a drying climate (e.g., clutch size and habitat breadth). We scored species vulnerability based on changes projected for mid-century (2040−2069) from 2 climate models representing “least-dry” and “most-dry” scenarios for the region. Species characteristics useful for discriminating vulnerability in our models included small range size, small clutch size, inflexible diel activity patterns, and smaller habitat breadth. When projected climate scenarios included a mix of drier and wetter conditions in the future, the exposure of a species to drying conditions was most important to relative rankings. When the scenario was universally drier, species characteristics were more important to relative rankings. Using information typically available even for understudied species and a range of climate projections, our results highlight the potential of using life history traits as indicators of relative climate vulnerability. The commonalities we identified provide a framework that can be used to assess other understudied species threatened by climate change.

Colorado, Kansas, Montana, Nebraska, North Dakota,↗
USGS2005

Flow regime alterations under changing climate in two river basins: Implications for freshwater ecosystems

We examined impacts of future climate scenarios on flow regimes and how predicted changes might affect river ecosystems. We examined two case studies: Cle Elum River, Washington, and Chattahoochee-Apalachicola River Basin, Georgia and Florida. These rivers had available downscaled global circulation model (GCM) data and allowed us to analyse the effects of future climate scenarios on rivers with (1) different hydrographs, (2) high future water demands, and (3) a river-floodplain system. We compared observed flow regimes to those predicted under future climate scenarios to describe the extent and type of changes predicted to occur. Daily stream flow under future climate scenarios was created by either statistically downscaling GCMs (Cle Elum) or creating a regression model between climatological parameters predicted from GCMs and stream flow (Chattahoochee-Apalachicola). Flow regimes were examined for changes from current conditions with respect to ecologically relevant features including the magnitude and timing of minimum and maximum flows. The Cle Elum's hydrograph under future climate scenarios showed a dramatic shift in the timing of peak flows and lower low flow of a longer duration. These changes could mean higher summer water temperatures, lower summer dissolved oxygen, and reduced survival of larval fishes. The Chattahoochee-Apalachicola basin is heavily impacted by dams and water withdrawals for human consumption; therefore, we made comparisons between pre-large dam conditions, current conditions, current conditions with future demand, and future climate scenarios with future demand to separate climate change effects and other anthropogenic impacts. Dam construction, future climate, and future demand decreased the flow variability of the river. In addition, minimum flows were lower under future climate scenarios. These changes could decrease the connectivity of the channel and the floodplain, decrease habitat availability, and potentially lower the ability of the river to assimilate wastewater treatment plant effluent. Our study illustrates the types of changes that river ecosystems might experience under future climates. Copyright ?? 2005 John Wiley & Sons, Ltd.

River Research and Applications↗
USGS2015

Impacts of climate change on land-use and wetland productivity in the Prairie Pothole Region of North America

Wetland productivity in the Prairie Pothole Region (PPR) of North America is closely linked to climate. A warmer and drier climate, as predicted, will negatively affect the productivity of PPR wetlands and the services they provide. The effect of climate change on wetland productivity, however, will not only depend on natural processes (e.g., evapotranspiration), but also on human responses. Agricultural land use, the predominant use in the PPR, is unlikely to remain static as climate change affects crop yields and prices. Land use in uplands surrounding wetlands will further affect wetland water budgets and hence wetland productivity. The net impact of climate change on wetland productivity will therefore depend on both the direct effects of climate change on wetlands and the indirect effects on upland land use. We examine the effect of climate change and land-use response on semipermanent wetland productivity by combining an economic model of agricultural land-use change with an ecological model of wetland dynamics. Our results suggest that the climate change scenarios evaluated are likely to have profound effects on land use in the North and South Dakota PPR, with wheat displacing other crops and pasture. The combined pressure of land-use and climate change significantly reduces wetland productivity. In a climate scenario with a +4 °C increase in temperature, our model predicts that almost the entire region may lack the wetland productivity necessary to support wetland-dependent species.

North Dakota, South Dakota↗