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USGS2024

The impact of future changes in climate on breeding waterfowl pairs in the US Prairie Pothole Region

Millions of small (< 10 ha) waterbodies embedded in grassland and agroecosystems in midcontinental North America provide breeding habitat to an estimated 50–80% of North America’s migratory ducks. Tens of millions of dollars are invested annually to conserve and enhance upland and wetland habitats for breeding ducks by prioritizing locations predicted to have high densities of breeding pairs under average precipitation conditions. An implicit assumption of this approach is that the distribution of breeding habitat remains relatively static. Climate change is an identified risk to this strategy. To assess this assumption and plan for potential forthcoming conditions, we estimated changes in potential breeding duck pairs under different climate scenarios by combining results of 1) a mechanistic hydrology model that simulates ecosystem processes for a subset of wetlands distributed across the U.S. Prairie Pothole Region (USPPR); 2) four downscaled climate model projections at mid- and late-century time horizons; and 3) U.S. Fish and Wildlife Service multi-decadal datasets and predictive breeding waterfowl pair statistical models. We conducted virtual and in-person informational sessions with partners to inform them on the best practices of using downscaled global circulation models and approaches for climate scenario planning. This close coordination led to a joint presentation at a monthly North Central Climate Adaptation Science Center seminar. We are also co-developing simulated wetland- waterfowl responses under different climate futures for wetlands. Information from these robust predictions of waterfowl habitat and settling patterns in this region provides land-management agencies insights in prioritizing current conservation actions given uncertainty. In addition, understanding how many breeding pairs the USPPR might support in coming decades will likely influence overall breeding population sizes and sustainable harvest objectives across North America.

Iowa, Minnesota, Nebraska, North Dakota, South Dak↗

USGS2024

Best practices for incorporating climate change science into Department of the Interior analyses, consultations, and decision making

The purpose of this document is to provide technical guidance, practical application examples, and resource lists for those who conduct, manage, and/or interpret technical workflows within the Department of the Interior. This document is intended to support implementation of Department of the Interior policy 526 DM 1 and establish best practices for using climate change science to inform analysis, consultation, and decision making. The Earth’s climate is an interconnected system that distributes energy, heat, and water around the planet. Due to human-driven increases in long-lived greenhouse gases, the Earth’s climate is now changing. For Departmental decision-making purposes, assuming a static, unchanging baseline climate is no longer consistent with current knowledge about the climate system. There are uncertainties about future climate and how resources or assets (RoAs) will respond to new conditions. To depict the possibilities, the global climate science community develops scenarios and models to explore how future climate may respond to socioeconomic and technological development in the world. Principles for informing policy development, planning and decisions, and regulatory processes using climate change science must: 1) consider the effects of future climate change, 2) characterize the risks, and 3) characterize the uncertainties. Best practices include: Use multiple scenarios to assess risks from a range of plausible societal pathways. When constraints prevent the use of multiple scenarios or if decision makers are risk averse, ensure that the chosen scenario considers higher risk outcomes. This is particularly important for large investments or irreversible decisions and reduces the chances of overconfident decision making. Use multiple climate models within each scenario to account for the range of outcomes due to model uncertainty. Do not rely solely on a single model or an ensemble average. Use relevant climate data . Use a time-period for model projections of the future climate change consistent with the relevant timeframe of the policy, action, or decision being considered. Historical observations are useful for understanding past conditions and climate trends for the next several years, but not beyond the next decade. Consult with climate data and modeling experts to assess which data and model resources are most appropriate for any given application. Clearly describe key analysis uncertainties (including with any climate observations, models, and scenarios used), and how they were addressed in the analysis and/or decision process. This ensures transparency and learning among analysts and decision makers.

Report↗

USGS2017

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.

Sonoran Desert↗

USGS2006

Forecasting selenium discharges to the San Francisco Bay-Delta Estuary: Ecological effects of a proposed San Luis Drain extension

Selenium discharges to the San Francisco Bay-Delta Estuary (Bay-Delta) could change significantly if federal and state agencies (1) approve an extension of the San Luis Drain to convey agricultural drainage from the western San Joaquin Valley to the North Bay (Suisun Bay, Carquinez Strait, and San Pablo Bay); (2) allow changes in flow patterns of the lower San Joaquin River and Bay-Delta while using an existing portion of the San Luis Drain to convey agricultural drainage to a tributary of the San Joaquin River; or (3) revise selenium criteria for the protection of aquatic life or issue criteria for the protection of wildlife. Understanding the biotransfer of selenium is essential to evaluating effects of selenium on Bay-Delta ecosystems. Confusion about selenium threats to fish and wildlife stem from (1) monitoring programs that do not address specific protocols necessary for an element that bioaccumulates; and (2) failure to consider the full complexity of the processes that result in selenium toxicity. Past studies show that predators are more at risk from selenium contamination than their prey, making it difficult to use traditional methods to predict risk from environmental concentrations alone. This report presents an approach to conceptualize and model the fate and effects of selenium under various load scenarios from the San Joaquin Valley. For each potential load, progressive forecasts show resulting (1) water-column concentration; (2) speciation; (3) transformation to particulate form; (4) particulate concentration; (5) bioaccumulation by invertebrates; (6) trophic transfer to predators; and (7) effects on those predators. Enough is known to establish a first-order understanding of relevant conditions, biological response, and ecological risks should selenium be discharged directly into the North Bay through a conveyance such as a proposed extension of the San Luis Drain. The approach presented here, the Bay-Delta selenium model, determines the mass, fate, and effects of selenium released to the Bay-Delta through use of (1) historical land-use, drainage, alluvial-fill, and runoff databases; (2) existing knowledge concerning biogeochemical reactions and physiological parameters of selenium (e.g., speciation, partitioning between dissolved and particulate forms, and bivalve assimilation efficiency); and (3) site-specific data mainly from 1986 to 1996 for clams and bottom-feeding fish and birds. Selenium load scenarios consider effluents from North Bay oil refineries and discharges of agricultural drainage from the San Joaquin Valley to enable calculation of (a) a composite freshwater endmember selenium concentration at the head of the estuary; and (b) a selenium concentration at a selected seawater location (Carquinez Strait) as a foundation for modeling. Analysis of selenium effects also takes into account the mode of conveyance for agricultural drainage (i.e., the San Luis Drain or San Joaquin River); and flows of the Sacramento River and San Joaquin River on a seasonal or monthly basis. Load scenarios for San Joaquin Valley mirror predictions made since 1955 of a worsening salt (and by inference, selenium) build-up exacerbated by an arid climate and massive irrigation. The reservoir of selenium in the San Joaquin Valley is sufficient to provide loading at an annual rate of approximately 42,500 pounds of selenium to a Bay-Delta disposal point for 63 to 304 years at the lower range of projections presented here, even if influx of selenium from the California Coast Ranges could be curtailed. Disposal of wastewaters on an annual basis outside of the San Joaquin Valley may slow the degradation of valley resources, but drainage alone cannot alleviate the salt and selenium build-up in the San Joaquin Valley, at least within a century. Load scenarios also show the different proportions of selenium loading to the Bay-Delta. Oil refinery loads from 1986 to 1992 ranged from 8.5 to 20 pounds of selenium per day; with treatment and cleanup, loads decreased to 3.0 pounds of selenium per day in 1999. In contrast, San Joaquin Valley agricultural drainage loads disposed of in a San Luis Drain extension could range from 45 to 117 pounds of selenium per day across a set of historical and future conditions. Components of this valley-wide load include five source subareas (i.e., Grassland, Westlands, Tulare, Kern, and Northern) defined by water and drainage management. Loads vary per subarea mainly because of proximity of the subarea to geologic sources of selenium and irrigation history. Loads from the Sacramento River, depending on flow conditions, range from 0.8 to 10 pounds of selenium per day. Loads from the San Joaquin River vary depending on restoration and flow conditions, which are considered. A consistent picture of ecological risk emerges under modeled selenium discharges from a proposed San Luis Drain extension. The threat to the estuary is greatest during low flow seasons and critically dry years. Where selenium undergoes reactions typical of low flow or longer residence time, highly problematic bioaccumulation in prey (food) is forecast. Surf scoter, greater and lesser scaup, and white sturgeon appear to be most at risk because these Bay-Delta predators feed on deposit and filter-feeding bivalves. Recent findings add Sacramento splittail and Dungeness crab to that list. During the low flow season of critically dry years, forecasted selenium concentrations in water, particulate matter, prey (diet), and predator tissue exceed guidelines with a high certainty of producing adverse effects under the most likely load scenario from a proposed San Luis Drain extension. High flows afford some protection under certain conditions in modeled San Joaquin River scenarios. However, meeting a combined goal of releasing a specific load during maximum flows and keeping selenium concentrations in the river below a certain objective to protect against bioaccumulation may not always be attainable. Management of the San Joaquin River on a constant concentration basis also could create problematic bioaccumulation during a wet year, especially during the low flow season, because high flows translate to high loads that are not always offset by seasonal river inflows. Prior to refinery cleanup, selenium contamination was sufficient to threaten reproduction in key species within the Bay-Delta ecosystems and human health advisories were posted based on selenium concentrations in tissues of diving ducks. During this time, selenium concentrations in the Bay-Delta were well below the most stringent recommended water quality criterion [1 microgram per liter (1 µg/L)]. Enhanced biogeochemical transformations to bioavailable particulate selenium and efficient bioaccumulation by bivalves characterized the system. If these biogeochemical conditions continue to prevail and agricultural selenium sources replace or exceed refinery sources, ecological forecasts suggest the risk of adverse effects will be difficult to eliminate under an out-of-valley resolution to the selenium problem. The Bay-Delta selenium model presented here is a systematic approach for conducting forecasts of the ecological effects from selenium on aquatic food webs. It is a new tool that links and models the major processes leading from loads through consumer organisms to predators. It also is a feasible approach for site-specific analysis and could provide a framework for developing new protective selenium foodweb guidelines and predator criteria. Model components that help ensure understanding ecosystems and the basis of environmental protection are (1) contaminant concentrations and speciation in sources, such as particulate material, that most influence bioavailability; (2) bioaccumulation models that calculate concentrations in diet, specifically in bivalves of the Bay-Delta that act as sensitive indicators of selenium contamination; (3) food-web type that determines what animals are threatened and when; and (4) multiple media concentrations (water, particulate material, and tissue of prey and predators) that, in-combination, determine risk or hazard.

California↗

USGS2025

Simulation of the impacts of projected climate change on groundwater resources in the urban, semiarid Yucaipa Valley watershed, southern California using an integrated hydrologic model

Managing water resources in semiarid watersheds is challenging due to limited supply and uncertain future climate conditions. This paper examines the impact of future climate changes on an urban watershed in southern California using an integrated hydrologic model. GSFLOW modeling software is used to simulate the nonlinear relationships between climate trends and precipitation partitioning into ET, runoff, and subsurface storage. Four global circulation models (GCMs), each with two greenhouse-gas scenarios, RCP45 and RCP85 are used to project future climate conditions. GCMs include the CanESM2, CNRM-CM5, HadGEM2-ES, and MIROC5 models. The model's simulated hydrologic conditions are compared with historical data to assess changes in water budgets and groundwater supply. Results indicate decreased groundwater storage in most scenarios due to increased natural evapotranspiration, vegetation consumptive use, and streamflow out of the watershed. Only scenarios with substantially increased future precipitation show increased groundwater storage. The study also highlights increased future aridity despite the rise in precipitation and large precipitation events forecast by GCMs, which increase the risk of urban floods and decrease stream leakage and water available to vegetation.

California↗

USGS2018

Extinction risk and conservation options for Maui Parrotbill, an endangered Hawaiian honeycreeper

Extinction rates for island birds around the world have been historically high. For forest passerines, the Hawaiian archipelago has suffered some of the highest extinction rates and reintroduction is a conservation tool that can be used to prevent the extinction of some of the remaining endangered species. Population viability analyses can be used to assess risks to vulnerable populations and evaluate the relative benefits of conservation strategies. Here we present a population viability analysis to assess the long-term viability for Maui parrotbill(s) (Kiwikiu) Pseudonestor xanthophrys, a federally endangered passerine on the Hawaiian island of Maui. Contrary to indications from population monitoring, our results indicate Maui parrotbills may be unlikely to persist beyond 25 years. Our modeling suggests female mortality as a primary factor driving this decline. To evaluate and compare management options involving captive rearing and translocation strategies we made a female-only stage-structured, meta-population simulation model. Due to the low reproductive potential of Maui parrotbills in captivity, the number of individuals (~ 20% of the global population) needed to source a reintroduction solely from captive reared birds is unrealistic. A reintroduction strategy that incorporates a minimal contribution from captivity and instead translocates mostly wild individuals was found to be the most feasible management option. Habitat is being restored on leeward east Maui, which may provide more favorable climate and habitat conditions and promote increased reproductive output. Our model provides managers with benchmarks for fecundity and survival needed to ensure reintroduction success, and highlights the importance of establishing a new population in potentially favorable habitat to ensure long-term persistence.

Journal of Fish and Wildlife Management↗

USGS2020

Wildfire risk and hazardous fuel reduction treatments along the US-Mexico border: A review of the science (1985-2019)

The ecosystems along the border between the United States and Mexico are at increasing risk to wildfire due to interactions among climate, land-use, and fuel loads. A wide range of fuel treatments have been implemented to mitigate wildfire and its threats to valued resources, yet we have little information about treatment effectiveness. To fill critical knowledge gaps, we reviewed wildfire risk and fuel treatment studies that were conducted near the US-Mexico border and published in the peer-reviewed literature between 1986 and 2019. The number of studies has grown during this time in warm desert to forest ecosystems on primarily federal lands. The most common study topics included fire effects on native species, the role of invasive species and woody encroachment on wildfire risk, historical fire regimes, and remote sensing and modeling to study wildfire risk across the landscape. A majority of fuel treatment studies focused on prescribed burns, and fuel treatments collectively had mixed effects on mitigating future wildfire risk and threats to ecosystems depending on vegetation and fire characteristics. The diversity of ecosystems and land ownership along the US-Mexico border present unique challenges for understanding and managing wildfire risk, and also create opportunities for collaboration and cross-site studies to promote knowledge across broad environmental gradients.

Arizona, California, New Mexico, Texas↗

USGS2019

The evolving threat of rapid Ohia death (ROD) to Hawaii’s native ecosystems and rare plant species

Hawai‘i’s most widespread native tree, ‘ōhi‘a lehua ( Metrosideros polymorpha ), has been dying across large areas of Hawai‘i Island mainly due to two fungal pathogens ( Ceratocystis lukuohia and Ceratocystis huliohia ) that cause a disease collectively known as Rapid ‘Ōhi‘a Death (ROD). Here we examine patterns of positive detections of C. lukuohia as it has been linked to the larger mortality events across Hawai‘i Island. Our analysis compares the environmental range of C. lukuohia and its spread over time through the known climatic range and distribution of ‘ōhi‘a. Analyses show this fungal pathogen generally encompassed the core, but not the extremes of the climatic range of ‘ōhi‘a. We further modeled the potential distribution of C. lukuohia across the Hawaiian Archipelago to estimate the risk of ROD to other islands. Given the potential for C. lukuohia to alter the structure of ‘ōhi‘a dominated forests, we used our projected potential distribution of C. lukuohia to assess the risk of ROD to threatened and endangered plant species across Hawai‘i. Many native plants are likely vulnerable to these types of large ‘ōhi‘a mortality events: of 234 endangered native plant species considered, 147 (62.8%) have more than half of their range within current and expanding C. lukuohia suitable areas. We also found evidence that protecting habitat by fencing out introduced feral ungulates reduces the prevalence of the disease likely by reducing physical damage caused by these animals to ‘ōhi‘a trees, a precondition for Ceratocystis infection. Given the ongoing spread of C. lukuohia , we developed a dynamic web portal to host our results online, where models and analyses are updated with new lab-confirmed detections to provide managers with a useful tool to help monitor and assess the risk of C. lukuohia as it continues to spread.

Hawaii↗

USGS2015

Modelling regional land change scenarios to assess land abandonment and reforestation dynamics in the Pyrenees (France)

Over the last decades and centuries, European mountain landscapes have experienced substantial transformations. Natural and anthropogenic LULC changes (land use and land cover changes), especially agro-pastoral activities, have directly influenced the spatial organization and composition of European mountain landscapes. For the past sixty years, natural reforestation has been occurring due to a decline in both agricultural production activities and rural population. Stakeholders, to better anticipate future changes, need spatially and temporally explicit models to identify areas at risk of land change and possible abandonment. This paper presents an integrated approach combining forecasting scenarios and a LULC changes simulation model to assess where LULC changes may occur in the Pyrenees Mountains, based on historical LULC trends and a range of future socio-economic drivers. The proposed methodology considers local specificities of the Pyrenean valleys, sub-regional climate and topographical properties, and regional economic policies. Results indicate that some regions are projected to face strong abandonment, regardless of the scenario conditions. Overall, high rates of change are associated with administrative regions where land productivity is highly dependent on socio-economic drivers and climatic and environmental conditions limit intensive (agricultural and/or pastoral) production and profitability. The combination of the results for the four scenarios allows assessments of where encroachment (e.g. colonization by shrublands) and reforestation are the most probable. This assessment intends to provide insight into the potential future development of the Pyrenees to help identify areas that are the most sensitive to change and to guide decision makers to help their management decisions.

Journal of Mountain Science↗

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↗

USGS2017

Cross-scale assessment of potential habitat shifts in a rapidly changing climate

We assessed the ability of climatic, environmental, and anthropogenic variables to predict areas of high-risk for plant invasion and consider the relative importance and contribution of these predictor variables by considering two spatial scales in a region of rapidly changing climate. We created predictive distribution models, using Maxent, for three highly invasive plant species (Canada thistle, white sweetclover, and reed canarygrass) in Alaska at both a regional scale and a local scale. Regional scale models encompassed southern coastal Alaska and were developed from topographic and climatic data at a 2 km (1.2 mi) spatial resolution. Models were applied to future climate (2030). Local scale models were spatially nested within the regional area; these models incorporated physiographic and anthropogenic variables at a 30 m (98.4 ft) resolution. Regional and local models performed well (AUC values > 0.7), with the exception of one species at each spatial scale. Regional models predict an increase in area of suitable habitat for all species by 2030 with a general shift to higher elevation areas; however, the distribution of each species was driven by different climate and topographical variables. In contrast local models indicate that distance to right-of-ways and elevation are associated with habitat suitability for all three species at this spatial level. Combining results from regional models, capturing long-term distribution, and local models, capturing near-term establishment and distribution, offers a new and effective tool for highlighting at-risk areas and provides insight on how variables acting at different scales contribute to suitability predictions. The combinations also provides easy comparison, highlighting agreement between the two scales, where long-term distribution factors predict suitability while near-term do not and vice versa.

Alaska↗

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↗