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USGS2013

An integrated model of environmental effects on growth, carbohydrate balance, and mortality of Pinus ponderosa forests in the southern Rocky Mountains

Climate-induced tree mortality is an increasing concern for forest managers around the world. We used a coupled hydrologic and ecosystem carbon cycling model to assess temperature and precipitation impacts on productivity and survival of ponderosa pine ( Pinus ponderosa ). Model predictions were evaluated using observations of productivity and survival for three ponderosa pine stands located across an 800 m elevation gradient in the southern Rocky Mountains, USA, during a 10-year period that ended in a severe drought and extensive tree mortality at the lowest elevation site. We demonstrate the utility of a relatively simple representation of declines in non-structural carbohydrate (NSC) as an approach for estimating patterns of ponderosa pine vulnerability to drought and the likelihood of survival along an elevation gradient. We assess the sensitivity of simulated net primary production, NSC storage dynamics, and mortality to site climate and soil characteristics as well as uncertainty in the allocation of carbon to the NSC pool. For a fairly wide set of assumptions, the model estimates captured elevational gradients and temporal patterns in growth and biomass. Model results that best predict mortality risk also yield productivity, leaf area, and biomass estimates that are qualitatively consistent with observations across the sites. Using this constrained set of parameters, we found that productivity and likelihood of survival were equally dependent on elevation-driven variation in temperature and precipitation. Our results demonstrate the potential for a coupled hydrology-ecosystem carbon cycling model that includes a simple model of NSC dynamics to predict drought-related mortality. Given that increases in temperature and in the frequency and severity of drought are predicted for a broad range of ponderosa pine and other western North America conifer forest habitats, the model potentially has broad utility for assessing ecosystem vulnerabilities.

Jemez Mountains, Rocky Mountains↗

USGS2015

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

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

Colorado, Wyoming↗

USGS2021

Climate change implications for the conservation of amphibians in tropical environments.

The U.S. Fish and Wildlife Service and the Puerto Rico Department of Natural and Environmental Resources want to develop a plan of actions to protect 12 species of coqui frogs (Eleutherodactylus spp.) that are currently considered at risk of being considered threatened or endangered, requiring additional protections under the Endangered Species Act. Actions center on two possible adaptation strategies: a) translocations to suitable, unoccupied habitat, and b) identifying climate-resilient habitats to ensure the persistence of species. Knowledge required to implement these strategies includes understanding how microhabitat and microclimatic factors – the local environmental conditions around individual frogs influence their occupancy (distribution), abundance, and reproduction; these were estimated by focusing on four representative species (E. wightmanae, E. brittoni, E. antillensis, and E. coqui). The abundance of all species but E. antillensis was positively and strongly influenced by moisture levels. As expected, E. antillensis exhibited an opposite relationship. Similarly, the reproductive activity of E. coqui was influenced by higher relative humidity and the presence of a chorus of other individuals. We found that our four focal species were not affected (e.g., abundance, reproduction) by the passing of hurricane Maria in September 2017, possibly because fallen debris creates conditions of increased food and shelter. Our findings help to assess habitat suitability, potential climate refuges, and inform timing for managed translocations.

Final Report↗

USGS2013

Fragmentation and thermal risks from climate change interact to affect persistence of native trout in the Colorado River basin

Impending changes in climate will interact with other stressors to threaten aquatic ecosystems and their biota. Native Colorado River cutthroat trout (CRCT; Oncorhynchus clarkii pleuriticus ) are now relegated to 309 isolated high-elevation ( > 1700 m) headwater stream fragments in the Upper Colorado River Basin, owing to past nonnative trout invasions and habitat loss. Predicted changes in climate (i.e., temperature and precipitation) and resulting changes in stochastic physical disturbances (i.e., wildfire, debris flow, and channel drying and freezing) could further threaten the remaining CRCT populations. We developed an empirical model to predict stream temperatures at the fragment scale from downscaled climate projections along with geomorphic and landscape variables. We coupled these spatially explicit predictions of stream temperature with a Bayesian Network (BN) model that integrates stochastic risks from fragmentation to project persistence of CRCT populations across the upper Colorado River basin to 2040 and 2080. Overall, none of the populations are at risk from acute mortality resulting from high temperatures during the warmest summer period. In contrast, only 37% of populations have a greater than or equal to 90% chance of persistence for 70 years (similar to the typical benchmark for conservation), primarily owing to fragmentation. Populations in short stream fragments < 7 km long, and those at the lowest elevations, are at the highest risk of extirpation. Therefore, interactions of stochastic disturbances with fragmentation are projected to be greater threats than warming for CRCT populations. The reason for this paradox is that past nonnative trout invasions and habitat loss have restricted most CRCT populations to high-elevation stream fragments that are buffered from the potential consequences of warming, but at risk of extirpation from stochastic events. The greatest conservation need is for management to increase fragment lengths to forestall these risks.

Upper Colorado River Basin↗

USGS2020

Population and habitat analyses for greater sage-grouse (Centrocercus urophasianus) in the bi-state distinct population segment—2018 update

Executive Summary The Bi-State Distinct Population Segment (Bi-State DPS) of greater sage-grouse ( Centrocercus urophasianus , hereinafter “sage-grouse”) represents a genetically distinct and geographically isolated population that straddles the border between Nevada and California. The primary threat to these sage-grouse populations is the expansion of single-leaf pinyon ( Pinus monophylla ) and Utah juniper ( Juniperus osteosperma ) into sagebrush ecosystems, which fragments and reduces population connectivity and survival. Other important threats include low water availability during brood-rearing, particularly during drought, and increased predation by common ravens ( Corvus corax ), a generalist predator often associated with anthropogenic resource subsidies. Although the Bi-State DPS occurs at high elevations relative to sage-grouse range-wide, changes in historical wildfire cycles and the conversion of native shrubs to invasive annual grasslands still threaten these populations. The Bi-State DPS has undergone multiple federal status assessments and associated litigation. For example, in October of 2013, the Bi-State DPS was proposed for listing as threatened under the Endangered Species Act of 1973 by the U.S. Fish and Wildlife Service (USFWS), then withdrawn in April 2015. The withdrawal decision was challenged, and in May 2018, a Federal district court ordered the withdrawal decision to be vacated, and USFWS was required to re-open the October 2013 listing evaluation. In response, the U.S. Geological Survey (USGS), with State and Federal collaborators, embarked on a multipronged analysis to provide current and best available science regarding population status of sage-grouse within the Bi-State DPS. Using data from a long-term monitoring program, we carried out four analytical study objectives, and here, we provide preliminary results of these analyses. First, we used integrated population modeling (IPM) to predict annual population abundance and annual finite rate of population change for the Bi-State DPS, as a whole, and for each subpopulation between 1995 and 2018. Because sage-grouse exhibit population cycles (periodic increases and decreases in abundance across approximately 6- to 10-year wavelengths), we estimated trends across three nested temporal scales that represent one (11 years), two (18 years), and three (24 years) complete population cycles. These estimates of relatively long-term averaged population change account for temporal (that is, interannual) variation. Our model predicted population abundance for the Bi-State DPS during 2018 at 3,305 individuals (2,247–4,683), with the majority occupying Bodie Hills and Long Valley. The model also predicted cyclic dynamics in abundance through time with evidence of 24-year population growth and slight trends of decline over the past 18 years. Specifically, across the Bi-State DPS as a whole, we estimated annual average at 0.99, 0.99, and 1.02 over the one, two, and three population cycles, which equated to a 10.5 percent, 16.6 percent decrease, and 60.0 percent increase in abundance over the 11-, 18-, and 24-year cycles. Estimated abundance in 2018 had not reached numbers lower than those predicted during 1995. However, we found spatial variation in population trends across the three cycles. Bodie Hills subpopulation comprised the greatest (1,521) and exhibited average annual greater than 1.0 across all periods resulting in average annual increases of 7 percent. This relatively large subpopulation has grown 5 times larger than what was predicted in 1995 while experiencing cyclical dynamics within that period. Conversely, other smaller subpopulations within the Bi-State DPS exhibited average annual equal to or less than 1.0 resulting in estimated 10-year risks of extirpation ranging from 2.0 to 76.1 percent. In general, evidence of decline among smaller subpopulations was greatest for the most recent period (2008–18) compared to a period that encompassed three full population cycles (24-year). This difference coincides with an intense period of drought that began in 2012. For comparative purposes as part of this first objective, we conducted a similar analysis for populations of sage-grouse within Nevada and California but outside the Bi-State DPS. We developed a region-wide and distance-weighted IPM using lek count from Nevada Department of Wildlife (NDOW) and California Department of Fish and Wildlife (CDFW) databases and with telemetry data collected by USGS across 12 sage-grouse subpopulations. Our models predicted similar patterns in population cycling outside the Bi-State DPS but with much stronger evidence of long-term declines across 24 years. Specifically, median averaged across each year of the 11-, 18-, and 24-year periods resulted in average annual values of 0.94, 0.97, and 0.99, respectively. These values equate to 41.0 percent, 38.5 percent, and 21.3 percent declines over the corresponding periods. Second, we used lek count data in a state-space modeling framework to compare trends in population abundance across different spatial scales (that is, leks versus Bi-State DPS). This hierarchical framework allowed us to disentangle declines associated with climate conditions as opposed to other local level factors that might signal the need for management intervention. Specifically, we identified 7 leks that were both declining and recently decoupled from larger spatial scale trends, typically governed by climatic conditions (referred to as soft or hard signals). The goal of this analysis was to provide an early warning system that might have implications for conservation actions at local scales. Third, we developed phenological (spring, summer–fall, and winter) and reproductive life stage (nesting, early brood-rearing, and late-brood rearing) based resource selection functions using various environmental covariates. We report rankings of variable importance for each season and life stage, developed maps of habitat selection indices (HSI), binned categories representing low, moderate, and high classes of quality (where any category greater than or equal to low indicated selected habitat) for each phenological season and life stage, and produced composite maps by selected phenological and reproductive stage to estimate annual habitat. Fourth, we used for each lek within the Bi-State DPS to carry out a spatial analysis that quantified substantial changes in the distribution of occupied habitat across long- (24-year) and short- (11-year) term periods. Owing to differences among available datasets, the long-term analysis primarily reflected spatial shifts among subpopulations comprising the majority of the Bi-State DPS (that is, Bodie Hills and Long Valley) while the short-term analysis also quantified changes among subpopulations along the periphery. Over long and short-term periods, the overall distribution of occupied habitat (as measured by 99 percent utilization distributions intersecting any quantified habitat) was reduced by 20,573 ha and 55,492 ha, respectively. Occupied core areas (as measured by 50 percent utilization distributions intersecting any quantified habitat) over long-term periods were solely located in Bodie Hills and Long Valley. Although nearly all subpopulations experienced contractions in occupied overall and core distribution, Bodie Hills experienced spatial expansion that occurred with concomitant spatial contraction at Long Valley over both periods. Subpopulations at the northern (Pine Nuts), central (Sagehen) and southern (White-Mountains) extents of the Bi-State DPS also experienced spatial contraction over the short-term period. These findings, coupled with those of population trends, indicate long-term patterns in redistribution of sage-grouse from Long Valley and peripheral subpopulations to Bodie Hills. That is, sage-grouse subpopulations at the periphery are declining while the largest population at the core is increasing, which could have meaningful impacts on overall metapopulation persistence. We provide evidence for loss of occupied habitat (reduced distribution) given local extirpation of subpopulations. Fifth, we calculated percentages of selected phenological, life stage, and annual habitat that each subpopulation contributed to the Bi-State DPS. We then intersected these maps with a composite estimate of occupied habitat from the fourth objective and calculated percentages of selected habitat likely occupied by sage-grouse that each subpopulation contributed to the Bi-State DPS. These values provide evidence for loss of occupied habitat and subsequent reductions in spatial distribution given reductions in abundance and, in some cases, extirpation of leks within subpopulations. Lastly, we carried out an initial in-depth analysis of selection for irrigated pastures and wet meadows during the brood-rearing stage for the Long Valley subpopulation. We chose this subpopulation because it represents a population core, representing 26.5 percent of total sage-grouse within the Bi-State DPS, and has exhibited long-term declines in abundance and distribution. This subpopulation is highly sensitive to precipitation and other factors that influence water availability. Models predicted higher use of the interior portions of irrigated pastures and wet meadows during late brood-rearing period, which represented a potentially risky use of habitat that was exacerbated during periods of low moisture (for example, drought, reduced water delivery, or both). Sage-grouse typically used edges of riparian areas and pastures, largely because the interior of these mesic areas consisted of considerably less overhead concealment cover (for example, shrubs) that likely resulted in a higher risk of mortality. We found that a lack of water delivery to pastures in the form of overwinter precipitation or diversion ditches increased the movements of sage-grouse to the interior of pastures. Although further investigation of water delivery impacts on chick survival are warrented, our initial findings regarding resource selection may explain recent declines in population growth at Long Valley.

California, Nevada↗

USGS2022

Simulating burn severity maps at 30 meters in two forested regions in California

Climate change is altering wildfire behavior and vegetation regimes in California’s forested ecosystems. Present day fires are seeing an increase in high burn severity area and high severity patch size. The ability to predict future burn severity patterns would support better policy and land management decisions. Here we demonstrate a methodology to first, statistically estimate individual burn severity classes at 30 meters and second, cluster and smooth high severity patches onto a landscape. Our goal here was not to exactly replicate observed burn severity maps, but rather to utilize observed maps as one realization of a random process dependent on climate, topography, fire weather, and fuels, to inform creation of additional realizations through our simulation technique. We developed two sets of empirical models with two different vegetation datasets to test if coarse vegetation could accurately model for burn severity. While visual acuity can be used to assess the performance of our simulation process, we also employ the Ripley’s K function to compare spatial point processes at different scales to test if the simulation is capturing an appropriate amount of clustering. We utilize FRAGSTATS to obtain high severity patch metrics to test the contiguity of our high severity simulation. Ripley’s K function helped identify the number of clustering iterations and FRAGSTATS showed how different focal window sizes affected our ability to cluster high severity patches. High severity patch simulations was comparable between the coarse and fine resolution vegetation datasets. Improving our ability to simulate burn severity will help advance our understanding of the potential influence of land and fuels management on ecosystem-level response variables that are important for decision-makers. Simulated burn severity maps can support managing habitat and estimating risks of habitat loss, protecting infrastructure and homes, improving future wildfire emissions projections, and better mapping and planning for fuels treatment scenarios.

California↗

USGS2013

Threatened and endangered subspecies with vulnerable ecological traits Also have high susceptibility to sea level rise and habitat fragmentation

The presence of multiple interacting threats to biodiversity and the increasing rate of species extinction make it critical to prioritize management efforts on species and communities that maximize conservation success. We implemented a multi-step approach that coupled vulnerability assessments evaluating threats to Florida taxa such as climate change, sea-level rise, and habitat fragmentation with in-depth literature surveys of taxon-specific ecological traits. The vulnerability, adaptive capacity, and ecological traits of 12 threatened and endangered subspecies were compared to non-listed subspecies of the same parent species. Overall, the threatened and endangered subspecies showed high vulnerability and low adaptive capacity, in particular to sea level rise and habitat fragmentation. They also exhibited larger home ranges and greater dispersal limitation compared to non-endangered subspecies, which may inhibit their ability to track changing climate in fragmented landscapes. There was evidence for lower reproductive capacity in some of the threatened or endangered taxa, but not for most. Taxa located in the Florida Keys or in other low coastal areas were most vulnerable to sea level rise, and also showed low levels of adaptive capacity, indicating they may have a lower probability of conservation success. Our analysis of at-risk subspecies and closely related non-endangered subspecies demonstrates that ecological traits help to explain observed differences in vulnerability and adaptive capacity. This study points to the importance of assessing the relative contributions of multiple threats and evaluating conservation value at the species (or subspecies) level when resources are limited and several factors affect conservation success.

PLoS ONE↗

USGS2014

Vulnerability of breeding waterbirds to climate change in the Prairie Pothole Region, U.S.A.

The Prairie Pothole Region (PPR) of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs). We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971–2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981–2000 and projected future distributions to climate scenarios for 2040–2049. Species were projected to, on average, lose almost half their current habitat (-46%). However, individual species projections varied widely, from +8% (Upland Sandpiper) to -100% (Wilson's Snipe). Variable importance ranks indicated that land cover (wetland and upland) variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts.

Minnesota, North Dakota, South Dakota↗

USGS2017

Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions

Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages from January 1, 1884 through January 9, 2014 provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February, estimating outcomes 5-11 months ahead of their occurrence. Few drought prediction methods exploit temporal links among streamflows. We find MLLR modeling of drought streamflow probabilities exploits the explanatory power of temporally linked water flows. MLLR models with strong correct classification rates were produced for streams throughout the U.S. One ad hoc test of correct prediction rates of September 2013 hydrological droughts exceeded 90% correct classification. Some of the best-performing models coincide with areas of high concern including the West, the Midwest, Texas, the Southeast, and the Mid-Atlantic. Using hydrological drought MLLR probability estimates in a water management context can inform understanding of drought streamflow conditions, provide warning of future drought conditions, and aid water management decision making.

Journal of the American Water Resources Associatio↗

USGS2023

Ammonia and aquatic ecosystems – A review of global sources, biogeochemical cycling, and effects on fish

The purpose of this review is to better understand the full life cycle and influence of ammonia from an aquatic biology perspective. While ammonia has toxic properties in water and air, it also plays a central role in the biogeochemical nitrogen (N) cycle and regulates mechanisms of normal and abnormal fish physiology. Additionally, as the second most synthesized chemical on Earth, ammonia contributes economic value to many sectors, particularly fertilizers, energy storage, explosives, refrigerants, and plastics. But, with so many uses, industrial N 2 -fixation effectively doubles natural reactive N concentrations in the environment. The consequence is global, with excess fixed nitrogen driving degradation of soils, water, and air; intensifying eutrophication, biodiversity loss, and climate change; and creating health risks for humans, wildlife, and fisheries. Thus, the need for ammonia research in aquatic systems is growing. In response, we prepared this review to better understand the complexities and connectedness of environmental ammonia. Even the term “ammonia” has multiple meanings. So, we have clarified the nomenclature, identified units of measurement, and summarized methods to measure ammonia in water. We then discuss ammonia in the context of the N-cycle, review its role in fish physiology and mechanisms of toxicity, and integrate the effects of human N-fixation, which continuously expands ammonia's sources and uses. Ammonia is being developed as a carbon-free energy carrier with potential to increase reactive nitrogen in the environment. With this in mind, we review the global impacts of excess reactive nitrogen and consider the current monitoring and regulatory frameworks for ammonia. The presented synthesis illustrates the complex and interactive dynamics of ammonia as a plant nutrient, energy molecule, feedstock, waste product, contaminant, N-cycle participant, regulator of animal physiology, toxicant, and agent of environmental change. Few molecules are as influential as ammonia in the management and resilience of Earth's resources.

Science of the Total Environment↗

USGS2014

Potential future land use threats to California's protected areas

Increasing pressures from land use coupled with future changes in climate will present unique challenges for California’s protected areas. We assessed the potential for future land use conversion on land surrounding existing protected areas in California’s twelve ecoregions, utilizing annual, spatially explicit (250 m) scenario projections of land use for 2006–2100 based on the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios to examine future changes in development, agriculture, and logging. We calculated a conversion threat index (CTI) for each unprotected pixel, combining land use conversion potential with proximity to protected area boundaries, in order to identify ecoregions and protected areas at greatest potential risk of proximal land conversion. Our results indicate that California’s Coast Range ecoregion had the highest CTI with competition for extractive logging placing the greatest demand on land in close proximity to existing protected areas. For more permanent land use conversions into agriculture and developed uses, our CTI results indicate that protected areas in the Central California Valley and Oak Woodlands are most vulnerable. Overall, the Eastern Cascades, Central California Valley, and Oak Woodlands ecoregions had the lowest areal percent of protected lands and highest conversion threat values. With limited resources and time, rapid, landscape-level analysis of potential land use threats can help quickly identify areas with higher conversion probability of future land use and potential changes to both habitat and potential ecosystem reserves. Given the broad range of future uncertainties, LULC projections are a useful tool allowing land managers to visualize alternative landscape futures, improve planning, and optimize management practices.

California↗

USGS2024

Dynamic modeling of coastal compound flooding hazards due to tides, extratropical storms, waves, and sea-level rise: A case study in the Salish Sea, Washington (USA)

The Puget Sound Coastal Storm Modeling System (PS-CoSMoS) is a tool designed to dynamically downscale future climate scenarios (i.e., projected changes in wind and pressure fields and temperature) to compute regional water levels, waves, and compound flooding over large geographic areas (100 s of kilometers) at high spatial resolutions (1 m) pertinent to coastal hazard assessments and planning. This research focuses on advancing robust and computationally efficient approaches to resolving the coastal compound flooding components for complex, estuary environments and their application to the Puget Sound region of Washington State (USA) and the greater Salish Sea. The modeling system provides coastal planners with projections of storm hazards and flood exposure for recurring flood events, spanning the annual to 1-percent annual chance of flooding, necessary to manage public safety and the prioritization and cost-efficient protection of critical infrastructure and valued ecosystems. The tool is applied and validated for Whatcom County, Washington, and includes a cross-shore profile model (XBeach) and overland flooding model (SFINCS) and is nested in a regional tide–surge model and wave model. Despite uncertainties in boundary conditions, hindcast simulations performed with the coupled model system accurately identified areas that were flooded during a recent storm in 2018. Flood hazards and risks are expected to increase exponentially as the sea level rises in the study area of 210 km of shoreline. With 1 m of sea-level rise, annual flood extents are projected to increase from 13 to 33 km 2 (5 and 13% of low-lying Whatcom County) and flood risk (defined in USD) is projected to increase fifteenfold (from 14 to USD 206 million). PS-CoSMoS, like its prior iteration in California (CoSMoS), provides valuable coastal hazard projections to help communities plan for the impacts of sea-level rise and storms.

Washington↗

USGS2023

Flood-frequency analysis in the Midwest: Addressing potential nonstationarity of annual peak-flow records

Flood-frequency analysis is essential in numerous water-resource management applications, including critical structure design and flood-plain mapping. A basic assumption within Bulletin 17C [1], the standardized guidelines for conducting flood-frequency analysis, is that basins without major hydrologic alterations, such as regulation or urbanization, exhibit stationary statistical properties of the distribution of annual peak streamflow. That is, the mean, variance, and skew are constant over time and the peak-flow record is a representative sample of the population of future floods [1]. In recent decades, better understanding of long-term climatic persistence and concerns about climate and land-use change have caused the assumption of stationarity in peak-flow records to be reexamined [2, 3, 4, 5]. Under nonstationary conditions, the long-term distributional properties (mean, variance, and/or skew) of peak-flow series change one or more times, either gradually or abruptly. Nonstationarities may be attributed to one source, but are often a result of a mixture of drivers, making detection and attribution of nonstationarities challenging [6, 7, 8]. Failure to incorporate observed trends and abrupt changes into flood-frequency analysis may result in a poor representation of the true flood risk. Bulletin 17C currently offers no guidance on how to account for nonstationarities when estimating floods and acknowledges the benefit additional flood frequency studies that incorporate changing climate or basin characteristics into the analysis would provide[1].

Midwest↗

USGS2011

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32 000 km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC_RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC_RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC_RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction.

Journal of Flood Risk Management↗

USGS2019

Adaptive variation, including local adaptation, requires decades to become evident in common gardens

Population‐level adaptation to spatial variation in factors such as climate and soils is critical for climate‐vulnerability assessments, restoration seeding, and other ecological applications in species management, and the underlying information is typically based on common‐garden studies that are short duration. Here, we show >20 yr were required for adaptive differences to emerge among 13 populations of a widespread shrub (sagebrush, Artemisia tridentata ssp wyomingensis ) collected from around the western United States and planted into common gardens. Additionally, >10 yr were required for greater survival of local populations, that is, local adaptation, to become evident. Variation in survival was best explained by the combination of populations’ home ecoregion combined with grouping of minimum temperature and aridity. Additional reductions in survival were explained by ungrouped (i.e., continuous) measures of garden‐to‐population‐origin separation in geographic distance (5% decrease in survival per 100 km increase in separation; R 2 = 0.22) and especially in minimum temperature in younger plants (−4% per + °C difference, R 2 = 0.56 vs. 0.29 in the 14th vs. 27th post‐planting years, respectively). Longer‐term common garden studies are needed. While we await them, uncertainty in adaptive variation resulting from short‐term observations could be quantitatively estimated and reported with seed‐transfer guidelines to reduce risks of introducing maladapted provenances in restoration.

Ecological Applications↗

USGS2021

Climate impacts on source contributions and evaporation to flow in the Snake River Basin using surface water isoscapes (δ2H and δ18O)

Rising global temperatures are expected to decrease the precipitation amount that falls as snow, causing greater risk of water scarcity, groundwater overdraft, and fire in areas that rely on mountain snowpack for their water supply. Streamflow in large river basins varies with the amount, timing, and type of precipitation, evapotranspiration, and drainage properties of watersheds; however, these controls vary in time and space making it difficult to identify the areas contributing most to flow and when. In this study, we separate the evaporative influences from source values of water isotopes from the Snake River Basin in the western United States (US) to relate source area to flow dynamics. We developed isoscapes (δ 2 H and δ 18 O) for the basin and found that isotopic composition of surface water in small watersheds is primarily controlled by longitude, latitude, and elevation. To examine temporal variability in source contributions to flow, we present a six-year record of Snake River water isotopes from King Hill, Idaho after removing evaporative influences. During periods of low flow, source water values were isotopically lighter indicating a larger contribution to flow from surface waters in the highest elevation, eastern portion of the basin. River evaporation increases were evident during summer likely reflecting climate, changing water availability, and management strategies within the basin. Our findings present a potential tool for identifying critical portions of basins contributing to river flow as climate fluctuations alter flow dynamics. This tool can be applied in other continental-interior basins where evaporation may obscure source water isotopic signatures.

Idaho, Montana, Oregon, Wyoming↗

USGS2012

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

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

Report↗

USGS2020

North Atlantic right whale (Eubalaena glacialis) scenario planning summary report

Scenario planning provides a structured framework that can be used in strategic planning to help manage risk and prioritize actions (Schwartz 1996; Peterson et al. 2003). By providing a mechanism to communicate about complex situations, scenario planning encourages “out-of-the-box” thinking to help groups assess the impacts of plausible future scenarios on a target or resource. The outcomes from scenario planning can be used to improve management decisions, highlight data gaps, and/or identify future science priorities (Star et al. 2015; Borggaard et al. 2019). The application of scenario planning by resource management organizations (e.g., Borggaard et al. 2019; Runyon et al. 2020; Star et al. 2015) and the urgency surrounding the recovery of the critically endangered North Atlantic right whale (Eubalaena glacialis), led to a 2018 NOAA Fisheries scenario planning initiative for the species. In addition to complementing the many management and conservation efforts already underway, this initiative was designed to address the uncertainties around future anthropogenic and environmental changes and how these uncertainties may impact species recovery. We used a scenario planning framework to explore plausible future conditions for North Atlantic right whales and to develop possible options to address those conditions and improve recovery. Specific objectives were to: 1) better understand the challenges of right whale management in a changing climate; 2) identify potential research activities and recovery needs across the species’ range; 3) increase coordination and collaboration related to recovery efforts; and 4) explore how scenario planning can be used to support decisions. Using projected changes in ocean conditions coupled with anthropogenic stressors, we built four plausible future scenarios for right whales. These scenarios helped identify priority research and management actions that NOAA Fisheries and our partners can undertake to improve right whale recovery. We identified priority actions related to science, management, and partnerships including, but not limited to, 1) research on shifting spatial and temporal distributions of right whales and prey in a changing climate; 2) development of technology to further reduce impacts from human activities; 3) continuation of ongoing management efforts related to vessel traffic and fishing; and 4) continued maintenance of existing and development of new partnerships (e.g., industry engagement in problem solving). This scenario planning exercise helped prioritize North Atlantic right whale management and science needs in light of changing ocean conditions and anthropogenic impacts. It can also serve as a reference for how NOAA Fisheries and its partners can better prepare for multiple plausible futures while complementing other on-going initiatives. Priorities identified here can be considered in conjunction with implementation and monitoring actions such as with the Atlantic Large Whale Take Reduction Team (ALWTRT) and/or regional Right Whale U.S. Implementation Teams. The framework can also be repeated and improved upon as additional information becomes available to support future exercises.

Technical Memorandum↗