Western United States Research Articles

Detections of Rabbit Hemorrhagic Disease Virus 2 (RHDV2) Following the 2020 Outbreak in Wild Lagomorphs across the Western United States.

Rabbit hemorrhagic disease virus 2 (RHDV2) is a highly infectious, often fatal viral disease that affects both domestic and wild lagomorph species. In the United States (U.S.), the virus first was detected in wild lagomorph populations in the southwest in March 2020 and has continued to be detected in native North American lagomorph species over several years. The susceptibility of host species and exact mechanisms of environmental transmission across the U.S. landscape remain poorly understood. Our study aims to increase the understanding of RHDV2 in wild lagomorph populations by providing a history of detection. We present and summarize results from all RHDV2-suspect wild lagomorph morbidity and mortality samples submitted for diagnostic testing in the U.S. from March 2020 to March 2024. Samples were submitted from 916 wild lagomorphs across eight native North American species in 14 western states, of which 313 (34.2%) tested positive by RHDV2 RT-qPCR. Detections of RHDV2 in pygmy rabbits (Brachylagus idahoensis) and riparian brush rabbits (Sylvilagus bachmani riparius) suggest that the risk to threatened and endangered species warrants more attention. Continuing to investigate wild lagomorph morbidity and mortality events and tracking RHDV2 detections over time can help inform on disease epidemiology and wild lagomorph population trends.

Shifts in elevational distributions of montane birds in an arid ecosystem

Montane species are generally predicted to respond to climate change via upslope movement. Elevational range shifts of birds rarely have been examined in arid regions. Here, we examine shifts in the elevational distributions of breeding birds from two regions of the Great Basin, a desert in the western USA, over 10 to 20 years. We collected data annually from 2001 to 2020, a relatively long and consistent time series that is uncommon in research on distributional shifts. We used single‐species occupancy models of 32 bird species to examine shifts along the full elevational gradient (1650–3200 m a.s.l.) and within the lowest and highest edges (25%) of the gradient. We then conducted simulations to test whether population stochasticity could confound inferences about shifts. We examined whether temperature, precipitation, and primary productivity (normalized difference vegetation index) were associated with occupancy and shifts. The elevational distributions of 23 species shifted, and simulations indicated that shifts in the distributions of 18 species were unlikely to be stochastic. The majority of shifts in the western Great Basin were downslope, whereas those in the central Great Basin were upslope. More shifts occurred at the edges of the elevational gradient than along the full gradient. Elevational shifts lacked a consistent climate‐response signal, but those of some species appeared to follow changes in primary productivity. We found regional differences in elevational shifts and climate associations, and our work suggests that these desert bird populations may be relatively resilient to climate change.

Colorado Tick Fever in the United States, 2013-2022.

Colorado tick fever (CTF) virus is an arbovirus maintained in an enzootic cycle between Rocky Mountain wood ticks (Dermacentor andersoni) and rodent species in the western United States. Individuals with CTF typically present with symptoms including fever, headache, myalgia, and lethargy, with a biphasic illness frequently occurring. We reviewed data on CTF cases reported to the national U.S. arboviral disease surveillance system and identified through testing at the CDC to characterize the epidemiology of CTF from 2013-2022. During this period, 148 CTF cases were identified, all likely infected in an endemic area in one of six states (Montana, Wyoming, Oregon, Colorado, Utah, Idaho). A median of 11 cases (range: 5-37) were identified per year, with an average annual national incidence of 0.04 cases per million population. The median age of cases was 55 years (range: 1-84 years), and 96 (65%) were male. Most (n = 145; 98%) cases acquired infection from April through July. The hospitalization rate was 16% (16 of 102 cases with data), and no deaths were reported. These findings substantiate the continued circulation of CTF virus in the western United States, highlighting the importance of implementing approaches to ensure CTF awareness for medical providers and providing education on tick bite prevention strategies for residents and visitors to risk areas.

A Systematic Review of the Distribution and Prevalence of Viruses Detected in the Peromyscus maniculatus Species Complex (Rodentia: Cricetidae).

The North American Deermouse, Peromyscus maniculatus, is one of the most widespread and abundant mammals on the continent. It is of public health interest as a known host of several viruses that are transmissible to humans and can cause illness, including the acute respiratory disease Hantavirus Pulmonary Syndrome (HPS). However, recent taxonomic studies indicate that P. maniculatus is a complex of multiple species, raising questions about how to identify and interpret three decades of hantavirus monitoring data. We conducted a systematic review investigating the prevalence and spatial distribution of viral taxa detected in wild populations allocated to P. maniculatus. From the 46 relevant studies published from 2000 to 2022, we extracted and analyzed spatial occurrence data to calculate weighted populational prevalences for hantaviruses. We found that detection efforts have been concentrated in the Western United States and Mexico with a focus on the spread of Sin Nombre virus, the primary causative agent of HPS. There are significant gaps in the existing literature both geographically and in regard to the types of hantaviruses being sampled. These results are significantly impacted by a recent taxonomic split of P. maniculatus into four species, which results in the relabeling of 92% of hantavirus observations. Considering the uncertain, and likely multiple, phylogenetic histories of these viral hosts should be a key emphasis of future modeling efforts.

Green Infrastructure Microbial Community Response to Simulated Pulse Precipitation Events in the Semi-Arid Western United States

Processes driving nutrient retention in stormwater green infrastructure (SGI) are not well quantified in water-limited biomes. We examined the role of plant diversity and physiochemistry as drivers of microbial community physiology and soil N dynamics post precipitation pulses in a semi-arid region experiencing drought. We conducted our study in bioswales receiving experimental water additions and a montane meadow intercepting natural rainfall. Pulses of water generally elevated soil moisture and pH, stimulated ecoenzyme activity (EEA), and increased the concentration of organic matter, proteins, and N pools in both bioswale and meadow soils. Microbial community growth was static, and N assimilation into biomass was limited across pulse events. Unvegetated plots had greater soil moisture than vegetated plots at the bioswale site, yet we detected no clear effect of plant diversity on microbial C:N ratios, EEAs, organic matter content, and N pools. Differences in soil N concentrations in bioswales and the meadow were most directly correlated to changes in organic matter content mediated by ecoenzyme expression and the balance of C, N, and P resources available to microbial communities. Our results add to growing evidence that SGI ecological function is largely comparable to neighboring natural vegetated systems, particularly when soil media and water availability are similar.

Isotopic evaluation of the National Water Model reveals missing agricultural irrigation contributions to streamflow across the western United States.

The National Water Model (NWM) provides critical analyses and projections of streamflow that support water management decisions. However, the NWM performs poorly in lower-elevation rivers of the western United States (US). The accuracy of the NWM depends on the fidelity of the model inputs and the representation and calibration of model processes and water sources. To evaluate the NWM performance in the western US, we compared observations of river water isotope ratios ( and expressed in notation) to NWM-flux-estimated (model) river reach isotope ratios. The modeled estimates were calculated from long-term (2000-2019) mean summer (June, July, and August) NWM hydrologic fluxes and gridded isotope ratios using a mass balance approach. The observational dataset comprised 4503 in-stream water isotope observations in 877 reaches across 5 basins. A simple regression between observed and modeled isotope ratios explained 57.9 % ( ) and 67.1 % ( ) of variance, although observations were 0.5 ‰ ( ) and 4.8 ‰ ( ) higher, on average, than mass balance estimates. The unexplained variance suggest that the NWM does not include all relevant water fluxes to rivers. To infer possible missing water fluxes, we evaluated patterns in observation-model differences using ( ) and ( ). We detected evidence of evaporation in observations but not model estimates (negative and positive ) at lower-elevation, higher-stream-order, arid sites. The catchment actual-evaporation-to-precipitation ratio, the fraction of streamflow estimated to be derived from agricultural irrigation, and whether a site was reservoir-affected were all significant predictors of in a linear mixed-effects model, with up to 15.2 % of variance explained by fixed effects. This finding is supported by seasonal patterns, groundwater levels, and isotope ratios, and it suggests the importance of including irrigation return flows to rivers, especially in lower-elevation, higher-stream-order, arid rivers of the western US.

GNSS Geodesy Quantifies Water‐Storage Gains and Drought Improvements in California Spurred by Atmospheric Rivers

AbstractAtmospheric rivers (ARs) deliver significant and essential precipitation to the western United States (US) with consequential interannual variability. The intensity and frequency of ARs strongly influence reservoir levels, mountain snowpack, and groundwater recharge, which are key drivers of water‐resource availability and natural hazards. Between October 2022 and April 2023, western states experienced exceptionally heavy precipitation from several families of powerful ARs. Using observations of surface‐loading deformation from Global Navigation Satellite Systems, we find that terrestrial water‐storage gains exceeded 100% of normal within vital California watersheds. Independent water‐storage solutions derived from different data‐analysis and inversion methods provide an important measure of precision. The sustained storage increases, which we show are closely associated with ARs at daily‐to‐weekly timescales, alleviated both meteorological and hydrological drought conditions in the region, with a lag in hydrological‐drought improvements. Quantifying water‐storage recovery associated with extreme precipitation after drought advances understanding of an increasingly variable hydrologic cycle.

How Much Does Land–Atmosphere Coupling Influence Summertime Temperature Variability in the Western United States?

Abstract Interannual fluctuations in average summertime temperatures across the western United States are captured by a leading empirical orthogonal function that explains over 50% of the total observed variance. In this paper, we explain the origins of this pattern of interannual temperature variability by examining soil moisture–temperature coupling that acts across seasons in observations and climate models. We find that a characteristic pattern of coupled temperature–soil moisture climate variability accounts for 34% of the total observed variance in summertime temperature across the region. This pattern is reproduced in state-of-the-art global climate models, where experiments that eliminate soil moisture variability reduce summertime average temperature variance by a factor of 3 on average. We use an idealized model of the coupled atmospheric boundary layer and underlying land surface to demonstrate that feedbacks between soil moisture, boundary layer relative humidity, and precipitation can explain the observed relations between springtime soil moisture and summertime temperature. Our results suggest that antecedent soil moisture conditions and subsequent land–atmosphere interactions play an important role in interannual summertime temperature variability in the western United States; soil moisture variations cause distal temperature anomalies and impart predictability at time scales longer than one season. Our results indicate that 40% of the observed warming trend across the western United States since 1981 has been driven by wintertime precipitation trends in the U.S. southwest. Significance Statement Year-to-year fluctuations in summertime temperatures have a large impact on drought, wildfire, and extreme heat across the Western United States. We find strong evidence that soil moisture deficits in the preceding spring may be the primary driver of higher-than-average summer temperatures in this region. Our results suggest that memory in the water cycle may lead to greater predictability in the climate system from season to season and that trends in southwest precipitation have exerted a considerable influence on observed warming over the past 40 years.

Deep Learning of a 200-Member Ensemble with a Limited Historical Training to Improve the Prediction of Extreme Precipitation Events

Abstract This study introduces a deep learning (DL) scheme to generate reliable and skillful probabilistic quantitative precipitation forecasts (PQPFs) in a postprocessing framework. Enhanced machine learning model architecture and training mechanisms are proposed to improve the reliability and skill of PQPFs while permitting computationally efficient model fitting using a short training dataset. The methodology is applied to postprocessing of 24-h accumulated PQPFs from an ensemble forecast system recently introduced by the Center for Western Weather and Water Extremes (CW3E) and for lead times from 1 to 6 days. The ensemble system was designed based on a high-resolution version of the Weather Research and Forecasting (WRF) Model, named West-WRF, to produce a 200-member ensemble in near–real time (NRT) over the western United States during the boreal cool seasons to support Forecast-Informdayed Reservoir Operations (FIRO) and studies of prediction of heavy-to-extreme events. Postprocessed PQPFs are compared with those from the raw West-WRF ensemble, the operational Global Ensemble Forecast System version 12 (GEFSv12), and the ensemble from the European Centre for Medium-Range Weather Forecasts (ECMWF). As an additional baseline, we provide PQPF verification metrics from a recently developed neural network postprocessing scheme. The results demonstrate that the skill of postprocessed forecasts significantly outperforms PQPFs and deterministic forecasts from raw ensembles and the recently developed algorithm. The resulting PQPFs broadly improve upon the reliability and skill of baselines in predicting heavy-to-extreme precipitation (e.g., >75 mm) across all lead times while maintaining the spatial structure of the high-resolution raw ensemble.

Knowing your limits: Patterns and drivers of nutrient limitation and nutrient–chlorophyll relationships in US lakes

AbstractAlthough understanding nutrient limitation of primary productivity in lakes is among the oldest research priorities in limnology, there have been few broad‐scale studies of the characteristics of phosphorus (P)‐, nitrogen (N)‐, and co‐limited lakes and their environmental context. By analyzing 3342 US lakes with concurrent P, N, and chlorophyll a (Chl a) samples, we showed that US lakes are predominantly co‐limited (43%) or P‐limited (41%). Majorities of lakes were P‐limited in the Northeast, Upper Midwest, and Southeast, and co‐limitation was most prevalent in the interior and western United States. N‐limitation (16%) was more prevalent than P‐limitation in the Great Basin and Central Plains. Nutrient limitation was related to lake, watershed, and regional variables, including Chl a concentration, watershed soil, and wet nitrate deposition. N and P concentrations interactively affected nutrient–chlorophyll relationships, which differed by nutrient limitation. Our study demonstrates the value of considering P, N, and environmental context in nutrient limitation and nutrient–chlorophyll relationships.

Potency–Magnitude Scaling Relations and a Unified Earthquake Catalog for the Western United States

Abstract Quantifying the size of earthquakes is a foundational task in seismology, and over the years several magnitude scales have been developed. Of these, only scales based on seismic moment or potency can properly characterize changes in event size without saturation. Here, we develop empirical potency–magnitude scaling relations for earthquakes in the western United States, allowing us to translate instrumental magnitude estimates into uniform measures of earthquake size. We use synthetic waveforms to validate the observed scaling relations and to provide additional insight into the differences between instrumental and physics-based magnitude scales. Each earthquake in our catalog is assigned a clustering designation distinguishing mainshocks from triggered seismicity, along with a potency-based magnitude estimate that is comparable to moment magnitude and that can be easily converted into other magnitude scales as needed. The developed catalog and associated scaling relations have broad applications for fundamental and applied studies of earthquake processes and hazards.

Oil and gas development influences potential for dust emission from the Upper Colorado River Basin, USA

AbstractWind erosion and dust emission from drylands have large consequences for ecosystem function and human health. Wind erosion is naturally reduced by soil crusting and sheltering by non‐erodible roughness elements such as plants. Land uses that reduce surface roughness and disturb the soil surface can dramatically increase dust emission. Extraction of oil and gas is a common and growing land use in the western United States (US) that removes vegetation and other roughness elements for construction of well pads and unpaved access roads, resulting in thousands of small (1–4 ha), discrete patches of unprotected soil. Here, we use a satellite albedo‐based model to assess the effect of oil/gas activity on surface roughness in the Uinta‐Piceance Basin, an area of the Upper Colorado River Basin (UCRB) with dense oil and natural gas development and modelled how the change in surface roughness could impact aeolian sediment flux and dust emission. We also investigated how regional drought influences the response of surface roughness to well pads and access roads. Oil/gas activity reduced surface roughness and increased modelled aeolian sediment flux at the landscape scale across much of the study region, resulting in a modest increase of 10 139 kg of dust per year, which is small relative to dust loads from a single regional dust event observed in the region, but downwind impact could be significant. The magnitude of surface roughness reductions by oil/gas activity was generally consistent among land cover types. However, in parts of the basin that had high cover of annual forbs and grasses, oil/gas activity was associated with larger surface roughness and smaller potential dust emission. Drought decreased surface roughness across disturbed and undisturbed sites, but there was no interactive effect of oil/gas activity and drought on surface roughness. These results suggest that oil/gas activity may increase sediment fluxes and likely contributes to dust emission from landscapes in the UCRB. Understanding how drought and land use change contribute to dust emissions will benefit mitigation of undesirable impacts of wind erosion and dust transport.

Forest Carbon Storage in the Western United States: Distribution, Drivers, and Trends

Forest Carbon Storage in the Western United States: Distribution, Drivers, and Trends

Brazilian Peppertree: Watch Out for This Lesser-Known Relative of Poison Ivy.

Brazilian peppertree (Schinus terebinthifolia), a member of the Anacardiaceae family, has invaded territory throughout the world, including the southeastern and western United States. Similar to fellow family members poison ivy and poison oak, Brazilian peppertree causes allergic contact dermatitis (ACD) in susceptible individuals. As this pest increases its range, dermatologists living in endemic areas should familiarize themselves with Brazilian peppertree, its effects on the skin, and how to treat any associated ACD.

Tree species explain only half of explained spatial variability in plant water sensitivity.

Spatiotemporal patterns of plant water uptake, loss, and storage exert a first-order control on photosynthesis and evapotranspiration. Many studies of plant responses to water stress have focused on differences between species because of their different stomatal closure, xylem conductance, and root traits. However, several other ecohydrological factors are also relevant, including soil hydraulics, topographically driven redistribution of water, plant adaptation to local climatic variations, and changes in vegetation density. Here, we seek to understand the relative importance of the dominant species for regional-scale variations in woody plant responses to water stress. We map plant water sensitivity (PWS) based on the response of remotely sensed live fuel moisture content to variations in hydrometeorology using an auto-regressive model. Live fuel moisture content dynamics are informative of PWS because they directly reflect vegetation water content and therefore patterns of plant water uptake and evapotranspiration. The PWS is studied using 21,455 wooded locations containing U.S. Forest Service Forest Inventory and Analysis plots across the western United States, where species cover is known and where a single species is locally dominant. Using a species-specific mean PWS value explains 23% of observed PWS variability. By contrast, a random forest driven by mean vegetation density, mean climate, soil properties, and topographic descriptors explains 43% of observed PWS variability. Thus, the dominant species explains only 53% (23% compared to 43%) of explainable variations in PWS. Mean climate and mean NDVI also exert significant influence on PWS. Our results suggest that studies of differences between species should explicitly consider the environments (climate, soil, topography) in which observations for each species are made, and whether those environments are representative of the entire species range.

Beet curly top virus affects vector biology: the first transcriptome analysis of the beet leafhopper.

Curly top disease, caused by beet curly top virus (BCTV), is among the most serious viral diseases affecting sugar beets in western USA. The virus is exclusively transmitted by the beet leafhopper (BLH, Circulifer tenellus) in a circulative and non-propagative manner. Despite the growing knowledge on virus-vector interactions, our understanding of the molecular interactions between BCTV and BLH is hampered by limited information regarding the virus impact on the vector and the lack of genomic and transcriptomic resources for BLH. This study unveils the significant impact of BCTV on both the performance and transcriptome response of BLHs. Viruliferous BLHs had higher fecundity than non-viruliferous counterparts, which was evident by upregulation of differentially expressed transcripts (DETs) associated with development, viability and fertility of germline and embryos in viruliferous insects. Conversely, most DETs associated with muscle movement and locomotor activities were downregulated in viruliferous insects, implying potential behavioural modifications by BCTV. Additionally, a great proportion of DETs related to innate immunity and detoxification were upregulated in viruliferous insects. Viral infection also induced notable alterations in primary metabolisms, including energy metabolism, namely glucosidases, lipid digestion and transport, and protein degradation, along with other cellular functions, particularly in chromatin remodelling and DNA repair. This study represents the first comprehensive transcriptome analysis for BLH. The presented findings provide new insights into the multifaceted effects of viral infection on various biological processes in BLH, offering a foundation for future investigations into the complex virus-vector relationship and potential management strategies for curly top disease.

Retrospective Demonstrations of an Integrated Team Approach to Fire Warnings for Western United States Wildfire Disasters

Retrospective Demonstrations of an Integrated Team Approach to Fire Warnings for Western United States Wildfire Disasters

Goal Setting, Movement Behaviors, and Perceived Health during an Online Health Coaching Intervention

The purpose of this study was to examine the associations of goal setting, movement behaviors, and health perceptions in young adults after an online health coaching intervention. Participants were young adults from a university within the western United States (N=257; 57.2% female). Participants met with health coaches in an online setting for one hour and goals were set for two behavior areas. Physical activity (PA), sitting time, sleep, and perceptions of general health and emotional wellbeing (health perceptions) were collected at baseline and at 2- and 4-weeks after the coaching session. Mediation analyses determined the associations of the health coaching session with goal setting on self-reported general health and emotional wellbeing and the indirect associations of each movement behavior. No movement behavior positively mediated the associations between the health coaching session and any of the health perception outcomes, although PA, sitting time, and weeknight sleep at 2-weeks associated with general health at 4-weeks (b=0.17–0.39, p<0.01) and associated with emotional wellbeing at 4-weeks (b=0.16–0.21, p<0.01). Emotional wellbeing mediated the associations of the health coaching session on general health (IE=0.19, p<0.001) and general health mediated the association of the health coaching session on emotional wellbeing (IE=0.09, p<0.001). Movement behaviors correlated with self-reported general health and emotional wellbeing, but no positive mediating associations were observed. Emotional wellbeing mediated the associations of the health coaching session on general health and vice-versa, suggesting a bidirectional association between the two health perceptions.

Application of Normalized Radar Backscatter and Hyperspectral Data to Augment Rangeland Vegetation Fractional Classification

Rangeland ecosystems in the western United States are vulnerable to climate change, fire, and anthropogenic disturbances, yet classification of rangeland areas remains difficult due to frequently sparse vegetation canopies that increase the influence of soils and senesced vegetation, the overall abundance of senesced vegetation, heterogeneity of life forms, and limited ground-based data. The Rangeland Condition Monitoring Assessment and Projection (RCMAP) project provides fractional vegetation cover maps across western North America using Landsat imagery and artificial intelligence from 1985 to 2023 at yearly time-steps. The objectives of this case study are to apply hyperspectral data from several new data streams, including Sentinel Synthetic Aperture Radar (SAR) and Earth Surface Mineral Dust Source Investigation (EMIT), to the RCMAP model. We run a series of five tests (Landsat-base model, base + SAR, base + EMIT, base + SAR + EMIT, and base + Landsat NEXT [LNEXT] synthesized from EMIT) over a difficult-to-classify region centered in southwest Montana, USA. Our testing results indicate a clear accuracy benefit of adding SAR and EMIT data to the RCMAP model, with a 7.5% and 29% relative increase in independent accuracy (R2), respectively. The ability of SAR data to observe vegetation height allows for more accurate classification of vegetation types, whereas EMIT’s continuous characterization of the spectral response boosts discriminatory power relative to multispectral data. Our spectral profile analysis reveals the enhanced classification power with EMIT is related to both the improved spectral resolution and representation of the entire domain as compared to legacy Landsat. One key finding is that legacy Landsat bands largely miss portions of the electromagnetic spectrum where separation among important rangeland targets exists, namely in the 900–1250 nm and 1500–1780 nm range. Synthesized LNEXT data include these gaps, but the reduced spectral resolution compared to EMIT results in an intermediate 18% increase in accuracy relative to the base run. Here, we show the promise of enhanced classification accuracy using EMIT data, and to a smaller extent, SAR.

Family Support in Transgender and Gender-Diverse Young Adults Seeking Telehealth for Hormone Therapy.

Background: Family support (FS) is a key social determinant of health for transgender and gender-diverse (TGD) young adults. We examined the association between FS and health outcomes in young adults seeking gender-affirming hormone therapy (GAHT) from a US telehealth service. Methods: Cross-sectional data from TGD young adults ages 18-24 (n = 7,740) who provided demographic information and information on FS at intake were analyzed. Relationships between FS, geography, insurance status, rates of depression, and smoking status were examined. Results: Less than half of respondents reported having FS. Patients with FS reported lower rates of depression and higher incidence of previous gender-affirming medical care (e.g., hormone therapy, surgeries), had lower rates of being uninsured, and were more likely to reside in the Northeast or WesternUnited States. Young adults assigned female at birth had higher rates of FS. Conclusion: FS may mitigate mental health disparities in TGD young adults including rates of depression. FS and insurance status are closely related in a geographically diverse population seeking telehealth services. The finding underscores the importance of FS as a social determinant of health and the unique characteristics of patients seeking telehealth services.