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At least 37 records · Page 2Linked to original sources

Watershed-scale response to climate change through the twenty-first century for selected basins across the United States

The hydrologic response of different climate-change emission scenarios for the twenty-first century were evaluated in 14 basins from different hydroclimatic regions across the United States using the Precipitation-Runoff Modeling System (PRMS), a process-based, distributed-parameter watershed model. This study involves four major steps: 1) setup and calibration of the PRMS model in 14 basins across the United States by local U.S. Geological Survey personnel; 2) statistical downscaling of the World Climate Research Programme’s Coupled Model Intercomparison Project phase 3 climate-change emission scenarios to create PRMS input files that reflect these emission scenarios; 3) run PRMS for the climate-change emission scenarios for the 14 basins; and 4) evaluation of the PRMS output. This paper presents an overview of this project, details of the methodology, results from the 14 basin simulations, and interpretation of these results. A key finding is that the hydrological response of the different geographical regions of the United States to potential climate change may be very different, depending on the dominant physical processes of that particular region. Also considered is the tremendous amount of uncertainty present in the climate emission scenarios and how this uncertainty propagates through the hydrologic simulations. This paper concludes with a discussion of the lessons learned and potential for future work.

Earth Interactions↗

Stream classification of the Apalachicola-Chattahoochee-Flint River System to support modeling of aquatic habitat response to climate change

A stream classification and associated datasets were developed for the Apalachicola-Chattahoochee-Flint River Basin to support biological modeling of species response to climate change in the southeastern United States. The U.S. Geological Survey and the Department of the Interior’s National Climate Change and Wildlife Science Center established the Southeast Regional Assessment Project (SERAP) which used downscaled general circulation models to develop landscape-scale assessments of climate change and subsequent effects on land cover, ecosystems, and priority species in the southeastern United States. The SERAP aquatic and hydrologic dynamics modeling efforts involve multiscale watershed hydrology, stream-temperature, and fish-occupancy models, which all are based on the same stream network. Models were developed for the Apalachicola-Chattahoochee-Flint River Basin and subbasins in Alabama, Florida, and Georgia, and for the Upper Roanoke River Basin in Virginia. The stream network was used as the spatial scheme through which information was shared across the various models within SERAP. Because these models operate at different scales, coordinated pair versions of the network were delineated, characterized, and parameterized for coarse- and fine-scale hydrologic and biologic modeling. The stream network used for the SERAP aquatic models was extracted from a 30-meter (m) scale digital elevation model (DEM) using standard topographic analysis of flow accumulation. At the finer scale, reaches were delineated to represent lengths of stream channel with fairly homogenous physical characteristics (mean reach length = 350 m). Every reach in the network is designated with geomorphic attributes including upstream drainage basin area, channel gradient, channel width, valley width, Strahler and Shreve stream order, stream power, and measures of stream confinement. The reach network was aggregated from tributary junction to tributary junction to define segments for the benefit of hydrological, soil erosion, and coarser ecological modeling. Reach attributes are summarized for each segment. In six subbasins segments are assigned additional attributes about barriers (usually impoundments) to fish migration and stream isolation. Segments in the six sub-basins are also attributed with percent urban area for the watershed upstream from the stream segment for each decade from 2010–2100 from models of urban growth. On a broader scale, for application in a coarse-scale species-response model, the stream-network information is aggregated and summarized by 256 drainage subbasins (Hydrologic Response Units) used for watershed hydrologic and stream-temperature models. A model of soil erodibility based on the Revised Universal Soil Loss Equation also was developed at this scale to parameterize a model to evaluate stream condition. The reach-scale network was classified using multivariate clustering based on modeled channel width, valley width, and mean reach gradient as variables. The resulting classification consists of a 6-cluster and a 12-cluster classification for every reach in the Apalachicola-Chattahoochee-Flint Basin. We present an example of the utility of the classification that was tested using the occurrence of two species of darters and two species of minnows in the Apalachicola-Chattahoochee-Flint River Basin, the blackbanded darter and Halloween darter, and the bluestripe shiner and blacktail shiner.

Alabama, Florida, Georgia, Virginia↗

Western Mountain Initiative: predicting ecosystem responses to climate change

Mountain ecosystems of the western United States provide irreplaceable goods and services such as water, timber, biodiversity, and recreational opportunities, but their responses to climatic changes are complex and not well understood. The Western Mountain Initiative (WMI), a collaboration between USGS and U.S. Forest Service scientists, catalyzes assessment and synthesis of the effects of disturbance and climate change across western mountain areas, focusing on national parks and surrounding national forests. The WMI takes an ecosystem approach to science, integrating research across science disciplines at scales ranging from field studies to global trends.

Fact Sheet↗

Demographic responses to climate change in a threatened Arctic species

The Arctic is undergoing rapid and accelerating change in response to global warming, altering biodiversity patterns, and ecosystem function across the region. For Arctic endemic species, our understanding of the consequences of such change remains limited. Spectacled eiders ( Somateria fischeri ), a large Arctic sea duck, use remote regions in the Bering Sea, Arctic Russia, and Alaska throughout the annual cycle making it difficult to conduct comprehensive surveys or demographic studies. Listed as Threatened under the U.S. Endangered Species Act, understanding the species response to climate change is critical for effective conservation policy and planning. Here, we developed an integrated population model to describe spectacled eider population dynamics using capture–mark–recapture, breeding population survey, nest survey, and environmental data collected between 1992 and 2014. Our intent was to estimate abundance, population growth, and demographic rates, and quantify how changes in the environment influenced population dynamics. Abundance of spectacled eiders breeding in western Alaska has increased since listing in 1993 and responded more strongly to annual variation in first-year survival than adult survival or productivity. We found both adult survival and nest success were highest in years following intermediate sea ice conditions during the wintering period, and both demographic rates declined when sea ice conditions were above or below average. In recent years, sea ice extent has reached new record lows and has remained below average throughout the winter for multiple years in a row. Sea ice persistence is expected to further decline in the Bering Sea. Our results indicate spectacled eiders may be vulnerable to climate change and the increasingly variable sea ice conditions throughout their wintering range with potentially deleterious effects on population dynamics. Importantly, we identified that different demographic rates responded similarly to changes in sea ice conditions, emphasizing the need for integrated analyses to understand population dynamics.

Ecology and Evolution↗

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured inter-annual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including above-ground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.

Global Change Biology↗

Persistence and diversification of the Holarctic shrew, Sorex tundrensis (Family Soricidae), in response to climate change

Environmental processes govern demography, species movements, community turnover and diversification and yet in many respects these dynamics are still poorly understood at high latitudes. We investigate the combined effects of climate change and geography through time for a widespread Holarctic shrew, Sorex tundrensis . We include a comprehensive suite of closely related outgroup taxa and three independent loci to explore phylogeographic structure and historical demography. We then explore the implications of these findings for other members of boreal communities. The tundra shrew and its sister species, the Tien Shan shrew ( Sorex asper ), exhibit strong geographic population structure across Siberia and into Beringia illustrating local centres of endemism that correspond to Late Pleistocene refugia. Ecological niche predictions for both current and historical distributions indicate a model of persistence through time despite dramatic climate change. Species tree estimation under a coalescent process suggests that isolation between populations has been maintained across timeframes deeper than the periodicity of Pleistocene glacial cycling. That some species such as the tundra shrew have a history of persistence largely independent of changing climate, whereas other boreal species shifted their ranges in response to climate change, highlights the dynamic processes of community assembly at high latitudes.

Molecular Ecology↗

On the brink of change: Plant responses to climate on the Colorado Plateau

The intensification of aridity due to anthropogenic climate change in the southwestern U.S. is likely to have a large impact on the growth and survival of plant species that may already be vulnerable to water stress. To make accurate predictions of plant responses to climate change, it is essential to determine the long‐term dynamics of plant species associated with past climate conditions. Here we show how the plant species and functional types across a wide range of environmental conditions in Colorado Plateau national parks have changed with climate variability over the last twenty years. During this time, regional mean annual temperature increased by 0.18°C per year from 1989–1995, 0.06°C per year from 1995–2003, declined by 0.14°C from 2003–2008, and there was high interannual variability in precipitation. Non‐metric multidimensional scaling of plant species at long‐term monitoring sites indicated five distinct plant communities. In many of the communities, canopy cover of perennial plants was sensitive to mean annual temperature occurring in the previous year, whereas canopy cover of annual plants responded to cool season precipitation. In the perennial grasslands, there was an overall decline of C 3 perennial grasses, no change of C 4 perennial grasses, and an increase of shrubs with increasing temperature. In the shrublands, shrubs generally showed no change or slightly increased with increasing temperature. However, certain shrub species declined where soil and physical characteristics of a site limited water availability. In the higher elevation woodlands, Juniperus osteosperma and shrub canopy cover increased with increasing temperature, while Pinus edulis at the highest elevation sites was unresponsive to interannual temperature variability. These results from well‐protected national parks highlight the importance of temperature to plant responses in a water‐limited region and suggest that projected increases in aridity are likely to promote grass loss and shrub expansion on the Colorado Plateau.

Utah↗

Modeled ecohydrological responses to climate change at seven small watersheds in the northeastern United States

A cross-site analysis was conducted on seven diverse, forested watersheds in the northeastern United States to evaluate hydrological responses (evapotranspiration, soil moisture, seasonal and annual streamflow, and water stress) to projections of future climate. We used output from four atmosphere–ocean general circulation models (AOGCMs; CCSM4, HadGEM2-CC, MIROC5, and MRI-CGCM3) included in Phase 5 of the Coupled Model Intercomparison Project, coupled with two Representative Concentration Pathways (RCP 8.5 and 4.5). The coarse resolution AOGCMs outputs were statistically downscaled using an asynchronous regional regression model to provide finer resolution future climate projections as inputs to the deterministic dynamic ecosystem model PnET-BGC. Simulation results indicated that projected warmer temperatures and longer growing seasons in the northeastern United States are anticipated to increase evapotranspiration across all sites, although invoking CO 2 effects on vegetation (growth enhancement and increases in water use efficiency (WUE)) diminish this response. The model showed enhanced evapotranspiration resulted in drier growing season conditions across all sites and all scenarios in the future. Spruce-fir conifer forests have a lower optimum temperature for photosynthesis, making them more susceptible to temperature stress than more tolerant hardwood species, potentially giving hardwoods a competitive advantage in the future. However, some hardwood forests are projected to experience seasonal water stress, despite anticipated increases in precipitation, due to the higher temperatures, earlier loss of snow packs, longer growing seasons, and associated water deficits. Considering future CO 2 effects on WUE in the model alleviated water stress across all sites. Modeled streamflow responses were highly variable, with some sites showing significant increases in annual water yield, while others showed decreases. This variability in streamflow responses poses a challenge to water resource management in the northeastern United States. Our analyses suggest that dominant vegetation type and soil type are important attributes in determining future hydrological responses to climate change.

Global Change Biology↗

Responding to ecological transformation in Capitol Reef National Park, Utah—Employee perspectives from pilot interviews from the Cross-Park Resist-Assist-Direct Project

Executive Summary Climate change is causing a range of changes that can affect the natural, cultural, and built resources of the Nation’s protected areas and affect opportunities to visit and recreate in these spaces. Changes in temperature and precipitation patterns also affect species and habitats, leading to ecological transformation. This report describes findings from pilot research conducted in Capitol Reef National Park, Utah (hereinafter referred to as “Capitol Reef” or “the Park”) as part of a larger interagency study of how National Park Service (NPS) staff are considering management of transforming ecosystems. Semi-structured interviews were used to assess how Capitol Reef employees (n=9) understand the challenge of ecological transformation, including their perceptions of how climate change is affecting the Park’s natural and cultural resources, the multiple timeframes over which employees respond to climate change impacts, and their awareness and understanding of ecological transformation and the Resist-Accept-Direct (RAD) framework, which was developed to address ecological transformation, that is, ecosystems changing in response to changes in climate conditions (Schuurman and others, 2020, 2022). The interviews also solicited employee perceptions about constraints and enabling factors that allow Capitol Reef to effectively respond to ecological transformation. The report uses a conceptual framework that has been used by the National Park Service Climate Change Response Program (Clifford and others, 2022) to structure the reporting of the data about constraints and enabling factors, with sections describing the role of factors internal to an individual employee (culture, worldviews, and understanding of an ecological system) and contextual factors external to an individual (institutional context, social feasibility and scientific uncertainty as influenced by available scientific information). Participating Capitol Reef staff perceived the most pressing climate impacts in the Park as increasing air temperatures, aridity, and flash floods, which are impacting natural and cultural resources, public safety, and infrastructure. Staff mostly agreed on what the future landscape (approximately 50 years into the future) may look like at Capitol Reef in terms of changes in vegetation and future temperature and precipitation conditions. However, staff had more divergent views or were uncertain about how specific species will adapt to future conditions (for example, how endemic plants might shift their ranges) and are grappling with which management strategies to take at which times. Staff also had differing opinions about how much data is needed to prompt action. Interviewees agreed that leadership in the Park had made climate change a priority and created a climate-attuned culture among staff. Participating employees described the park culture at Capitol Reef as collaborative, with frequent communication and work across divisions, which, as an example, shapes responses to flash floods and other events (for example, working across divisions on search and rescue, or repairing fencing that is washed out by storms). This collaborative, climate-attuned culture may help Capitol Reef in future problem-solving as it grapples with how to respond to climate change and ecological transformation in the Park.

Utah↗

Nitrogen and carbon soil dynamics in response to climate change in a high-elevation ecosystem in the Rocky Mountains, U.S.A.

We have implemented a long-term snow-fence experiment at the Niwot Ridge Long-Term Ecological Research (NWT) site in the Colorado Front Range of the Rocky Mountains, U.S.A., to assess the effects of climate change on alpine ecology and biogeochemical cycles. The responses of carbon (C) and nitrogen (N) dynamics in high-elevation mountains to changes in climate are investigated by manipulating the length and duration of snow cover with the 2.6 × 60 m snow fence, providing a proxy for climate change. Results from the first year of operation in 1994 showed that the period of continuous snow cover was increased by 90 d. The deeper and earlier snowpack behind the fence insulated soils from winter air temperatures, resulting in a 9°C increase in annual minimum temperature at the soil surface. The extended period of snow cover resulted in subnivial microbial activity playing a major role in annual C and N cycling. The amount of C mineralized under the snow as measured by CO 2 production was 22 g m -2 in 1993 and 35 g m -2 in 1994, accounting for 20% of annual net primary above-ground production before construction of the snow fence in 1993 and 31% after to snow fence was constructed in 1994. In a similar fashion, maximum subnivial N 2 O flux increased 3-fold behind the snow fence, from 75 μg N m -2 d -1 in 1993 to 250 μg N m -2 d -1 in 1994. The amount of N lost from denitrification was greater than the annual atmospheric input of N in snowfall. Surface litter decomposition studies show that there was a significant increase in the litter mass loss under deep and early snow, with no significant change under medium and little snow conditions. Changes in climate that result in differences in snow duration, depth, and extent may therefore produce large changes in the C and N soil dynamics of alpine ecosystems.

Colorado↗

A model integrating longshore and cross-shore processes for predicting long-term shoreline response to climate change

We present a shoreline change model for coastal hazard assessment and management planning. The model, CoSMoS-COAST (Coastal One-line Assimilated Simulation Tool), is a transect-based, one-line model that predicts short-term and long-term shoreline response to climate change in the 21 st century. The proposed model represents a novel, modular synthesis of process-based models of coastline evolution due to longshore and cross-shore transport by waves and sea-level rise. Additionally, the model uses an extended Kalman filter for data assimilation of historical shoreline positions to improve estimates of model parameters and thereby improve confidence in long-term predictions. We apply CoSMoS-COAST to simulate sandy shoreline evolution along 500 km of coastline in Southern California, which hosts complex mixtures of beach settings variably backed by dunes, bluffs, cliffs, estuaries, river mouths, and urban infrastructure, providing applicability of the model to virtually any coastal setting. Aided by data assimilation, the model is able to reproduce the observed signal of seasonal shoreline change for the hindcast period of 1995-2010, showing excellent agreement between modeled and observed beach states. The skill of the model during the hindcast period improves confidence in the model's predictive capability when applied to the forecast period (2010-2100) driven by GCM-projected wave and sea-level conditions. Predictions of shoreline change with limited human intervention indicate that 31% to 67% of Southern California beaches may become completely eroded by 2100 under sea-level rise scenarios of 0.93 to 2.0 m.

California↗

Examining the mechanisms of species responses to climate change: Are there biological thresholds?

Climate-change-driven shifts in distribution and abundance have been documented in many species. However, in order to better predict species responses, managers are seeking to understand the mechanisms that are driving these changes, including any thresholds that might soon be crossed. Leveraging the research that has already been supported by the Northeast Climate Adaptation Science Center and its partners, this project used the latest modeling techniques combined with robust field data to examine the impact of specific climate variables, land use change, and species interactions on the future distribution and abundance of species of conservation concern. Moreover, this project documented biological thresholds related to climate variability and change for critical species in the Northeastern and Midwestern U.S. Specifically, our objectives were to identify the primary drivers (climate change vs. urban growth) of species distribution changes in the Northeast; examine the nature of species landscape capability change over time to identify potential thresholds; determine how changing temperatures and snowpack characteristics will drive species interactions; analyze the sensitivity of tree and bird responses to the magnitude, variability, periodicity, and seasonality of temperature and precipitation under climate change in the eastern U.S.; and identify how discrete climate triggers such as extreme events will correlate with known biological thresholds. Major outcomes included 1) refining the understanding of the mechanisms that drive projected changes in the distribution of vulnerable populations; and 2) improving how these results are conveyed to stakeholders by identifying understandable responses in the form of thresholds.

Connecticut, Delaware, Illinois, Indiana, Iowa, Ke↗

Assessing coastal wetland carbon and mineral accumulation response to changing climate, Cape Espenberg, Alaska

The Arctic is experiencing warming and ecological shifts due to climate change and the compounding effects of polar amplification. Arctic Alaskan coastal marsh environments, such as the Cape Espenberg barrier beach system, offer an opportunity to determine the carbon cycle response to changing climate by examining sediment records that have been preserved through time as shoreline-parallel, linear geometry prograding geomorphic features. This study determines the carbon and mineral accumulation trends in marsh environments at Cape Espenberg for both paleo (~776 CE to 1850 CE) and modern (post-1850 CE) time frames. A comprehensive physical and chemical dataset, including radioisotope (137Cs, 210Pb, 14C), stable isotope (δ13C), element concentration (%C, %N, C:N), and dry bulk density, has been built for several sediment cores. Results indicate that carbon and mineral accumulation rates have increased from paleo to modern times, potentially because of better growing and preservation conditions for organic matter in a modern climate. Paleoclimate trends in the Medieval Climate Anomaly (MCA) and warm periods interspersed within the Little Ice Age (LIA) also correlate with greater contributions of wetland organic matter, as evidenced by lighter δ13C values. Cold climate periods within the LIA correlate with increased aquatic organic matter sourcing and heavier δ13C values, with some spikes of wetland sources interspersed throughout the LIA. Future temperatures are predicted to rise with global climate change, which may continue to expand carbon stores in Arctic coastal wetland sediments. This has been observed in the swale environments at Cape Espenberg, where increasingly favourable growing and soil-preservation conditions (i.e. wet/anoxic soils and lower salinity to limit organic material decay, higher temperatures to promote growth) are increasing the carbon storage within Arctic coastal carbon reservoirs.

Alaska↗

Predicted range shifts of non‐native grasses in response to climate change are influenced by photosynthetic pathway: A case study in the Hawaiian Islands

Aim Grasses comprise three main photosynthetic pathway variants (C 3 -BOP, C 3 -PACMAD and C 4 -PACMAD hereafter referred to as C 4 ). We sought to confirm climate niche differences among these photosynthetic pathway variants and assessed whether predicted non-native grass range shift patterns with climate change differ among photosynthetic pathway variants. Location Hawaiian Islands. Methods We used a species distribution modelling (SDM) approach that uses global occurrence records to inform local SDM based on local (Hawaiian Islands) occurrences. We compared climate niches and projected climate-driven range shifts, assuming moderate climate change (RCP 4.5, end of century), among 22 non-native grasses representing C 3 -BOP, C 3 -PACMAD and C 4 photosynthetic pathway variants. Results C 4 grasses exhibited the warmest temperature niches on average, but did not differ substantially in rainfall niche versus C 3 -BOP grasses. C 3 -PACMAD species averaged high suitability across a broad range of temperatures and rainfall conditions, except extreme aridity. In response to projected climate change, C 4 grasses had projected range increases. C 3 -BOP grasses typically responded with net range decreases, while C 3 -PACMAD grasses had variable range responses. However, patterns were contingent on elevation: for instance, the projected expansion of C 4 grasses was generally limited to elevations below 2000 m, with the largest increases in areas up to ~750 m. Areas of greatest reduction for C 3 -BOP and C 3 -PACMAD were projected at 750–1900 m and 100–1100 m elevation, respectively. Above 2000 m, range increases were projected for both C 3 grass variants. Main Conclusions Our projections suggest that non-native C 4 grasses pose the greatest risk for increasing spread and impacts under RCP 4.5, while certain C 3 -PACMAD grasses may endanger valuable high-elevation habitats. Photosynthetic pathway may be a useful component of weed risk assessment to evaluate how species may respond to climate change as similar range response patterns may be expected for other non-native grasses in other tropical and subtropical regions.

Hawaii↗

Vegetation response to climate change in Alaska: examples from the fossil record

Preface: This report was presented as an invited paper at the Fish & Wildlife Service Climate Forum held in Anchorage, Alaska on February 21-23, 2007. The purpose of the talk was to provide some examples of past climate changes that appear to have caused significant responses in Alaskan vegetation. These examples are based on interpretations of dated fossil assemblages (pollen, spores and plant macrofossils) collected and interpreted by U.S. Geological Survey and collaborating scientists from other scientific organizations during the past several decades.

Alaska↗

Identification of storm events and contiguous coastal sections for deterministic modeling of extreme coastal flood events in response to climate change

Deterministic dynamical modeling of future climate conditions and associated hazards, such as flooding, can be computationally-expensive if century-long time-series of waves, sea level variations, and overland flow patterns are simulated. To alleviate some of the computational costs, local impacts of individual coastal storms can be explored by first identifying particular events or scenarios of interest and dynamically modeling those events in detail. In this study, an efficient approach to selecting storm events for subsequent deterministic detailed modeling of coastal flooding is presented. The approach identifies locally relevant scenarios derived from regional datasets spanning long time-periods and covering large geographic areas. This is done by identifying storm events from global climate models using a robust, yet computationally simple approach for calculating total water level proxies at the shore, assuming a linear superposition of the important processes contributing to the overall total water level. Clustering of the total water level time-series is used to define coherent coastal cells where similar return period water level extrema occur in response to region-wide storms. Results show that the more severe but rare coastal flood events (e.g., the 100-year (yr) event) typically occur from the same storm across the region, but that a number of different storms are responsible for the less severe but more frequent local extreme water levels (e.g., the 1-yr event). This new ‘storm selection’ approach is applied to the Southern California Bight, a region of varying shoreline orientations that is subject to wave refraction across complex bathymetry, and shadowing, focusing, diffraction, and dissipation of wave energy by islands. Results indicate that wave runup dominates total water level extremes at this study site, highlighting the importance of downscaling global-scale models to nearshore waves when seeking accurate projections of local coastal hazards in response to climate change.

California↗

Combining past and contemporary species occurrences with ordinal species distribution modeling to investigate responses to climate change

Many organisms leave evidence of their former occurrence, such as scat, abandoned burrows, middens, ancient eDNA or fossils, which indicate areas from which a species has since disappeared. However, combining this evidence with contemporary occurrences within a single modeling framework remains challenging. Traditional binary species-distribution modeling reduces occurrence to two temporally coarse states (present/absent), so thus cannot leverage the information inherent in temporal sequences of evidence of past occurrence. In contrast, ordinal modeling can use the natural time-varying order of states (e.g. never occupied versus previously occupied versus currently occupied) to provide greater insights into range shifts. We demonstrate the power of ordinal modeling for identifying the major influences of biogeographic and climatic variables on current and past occupancy of the American pika Ochotona princeps , a climate-sensitive mammal. Sampling over five years across the species' southernmost, warm-edge range limit, we tested the effects of these variables at 570 habitat patches where occurrence was classified either as binary or ordinal. The two analyses produced different top models and predictors – ordinal modeling highlighted chronic cold as the most-important predictor of occurrence, whereas binary modeling indicated primacy of average summer-long temperatures. Colder wintertime temperatures were associated in ordinal models with higher likelihood of occurrence, which we hypothesize reflect longer retention of insulative and meltwater-provisioning snowpacks. Our binary results mirrored those of other past pika investigations employing binary analysis, wherein warmer temperatures decrease likelihood of occurrence. Because both ordinal- and binary-analysis top models included climatic and biogeographic factors, results constitute important considerations for climate-adaptation planning. Cross-time evidences of species occurrences remain underutilized for assessing responses to climate change. Compared to multi-state occupancy modeling, which presumes all states occur in the same time period, ordinal models enable use of historical evidence of species' occurrence to identify factors driving species' distributions more finely across time.

New Mexico↗

Integrated watershed-scale response to climate change for selected basins across the United States

A study by the U.S. Geological Survey (USGS) evaluated the hydrologic response to different projected carbon emission scenarios of the 21st century using a hydrologic simulation model. This study involved five major steps: (1) setup, calibrate and evaluated the Precipitation Runoff Modeling System (PRMS) model in 14 basins across the United States by local USGS personnel; (2) acquire selected simulated carbon emission scenarios from the World Climate Research Programme's Coupled Model Intercomparison Project; (3) statistical downscaling of these scenarios to create PRMS input files which reflect the future climatic conditions of these scenarios; (4) generate PRMS projections for the carbon emission scenarios for the 14 basins; and (5) analyze the modeled hydrologic response. This report presents an overview of this study, details of the methodology, results from the 14 basin simulations, and interpretation of these results. A key finding is that the hydrological response of the different geographical regions of the United States to potential climate change may be different, depending on the dominant physical processes of that particular region. Also considered is the tremendous amount of uncertainty present in the carbon emission scenarios and how this uncertainty propagates through the hydrologic simulations.

Scientific Investigations Report↗