Western United States Research Articles

Excess Fatal Overdoses in the United States During the COVID-19 Pandemic by Geography and Substance Type: March 2020-August 2021.

Objectives. To assess heterogeneity in pandemic-period excess fatal overdoses in the United States, by location (state, county) and substance type. Methods. We used seasonal autoregressive integrated moving average (SARIMA) models to estimate counterfactual death counts in the scenario that no pandemic had occurred. Such estimates were subtracted from actual death counts to assess the magnitude of pandemic-period excess mortality between March 2020 and August 2021. Results. Nationwide, we estimated 25 668 (95% prediction interval [PI] = 2811, 48 524) excess overdose deaths. Specifically, 17 of 47 states and 197 of 592 counties analyzed had statistically significant excess overdose-related mortality. West Virginia, Louisiana, Tennessee, Kentucky, and New Mexico had the highest rates (20-37 per 100 000). Nationally, there were 5.7 (95% PI = 1.0, 10.4), 3.1 (95% PI = 2.1, 4.2), and 1.4 (95% PI = 0.5, 2.4) excess deaths per 100 000 involving synthetic opioids, psychostimulants, and alcohol, respectively. Conclusions. The steep increase in overdose-related mortality affected primarily the southern and western United States. We identified synthetic opioids and psychostimulants as the main contributors. Public Health Implications. Characterizing overdose-related excess mortality across locations and substance types is critical for optimal allocation of public health resources. (Am J Public Health. 2024;114(6):599-609. https://doi.org/10.2105/AJPH.2024.307618).

Center-Pivot Maintenance Trends in the Western United States

Center-Pivot Maintenance Trends in the Western United States

Breaking barriers for cancer clinical trials: A multi-tiered interventional approach to boost racial and ethnic minority participation in early-phase studies.

TPS1639 Background: Racial and ethnic minority populations are underrepresented in cancer clinical trials. The USC Norris Comprehensive Cancer Center (USC NCCC) has multiple clinical trial recruitment sites, including the Los Angeles General Medical Center (LAG), the largest safety-net hospital in the western USA. LAG partners with USC to provide cancer care to the underserved minority population of LAC, including clinical trials. As a result, between 2015-2022 a total of 120 LAG patients were accrued to phase I clinical trials; enrolled subjects were 66% Hispanic, 21% Asian, 4% Black, and 9% other. An interventional study was designed to further enhance the referral and participation of racial and ethnic minority patients from other Los Angeles County (LAC) safety-net facilities. The study is funded by the Stand up to Cancer Diversity in Early Development Clinical Trials Research Grants Program. Methods: This interventional study has 3 specific aims. First, to identify barriers to referral for minority and underserved patients: Qualitative interviews will be conducted with key stakeholders in the LAC safety net system which will uncover barriers to referring minority and underserved patients. A screening tool developed by the NCI to characterize barriers will be used. Second, to implement a multi-component program to enhance the referral of patients to early-phase clinical trials. The intervention addresses system-level, provider-level, and patient-level factors to improve the process, with a demonstration site compared to a non-demonstration site. Key features include a streamlined referral process for healthcare professionals with a singular centrally operated email managed by a specialized facilitator, weekly meetings to assign trials to prospective patients, and facilitation of approval and scheduling for referrals. We will educate providers regarding trials and exchange feedback on the referral process. We will extend resources to patients to assist with financial and transportation limitations. We will compare change in referral and enrollment rates at baseline and after the intervention for both the demonstration site and non-demonstration site. Third, to explore the impact of remotely conducted clinical trials: A clinical trial (NCT05340309) administers study drug subcutaneously and uses telemedicine visits, wearable sensors, and a smartphone app for monitoring. This pilot trial will be analyzed to determine the model’s impact on barriers to enrollment. The above interventions may provide a model that can be adapted in other healthcare delivery settings to optimize referral and enrollment of racial and ethnic minorities.

Human‐modified habitats imperil ornamented dragonflies less than their non‐ornamented counterparts at local, regional, and continental scales

AbstractBiologists have long wondered how sexual ornamentation influences a species' risk of extinction. Because the evolution of condition‐dependent ornamentation can reduce intersexual conflict and accelerate the fixation of advantageous alleles, some theory predicts that ornamented taxa can be buffered against extinction in novel and/or stressful environments. Nevertheless, evidence from the wild remains limited. Here, we show that ornamented dragonflies are less vulnerable to extinction across multiple spatial scales. Population‐occupancy models across the Western United States reveal that ornamented species have become more common relative to non‐ornamented species over >100 years. Phylogenetic analyses indicate that ornamented species exhibit lower continent‐wide extinction risk than non‐ornamented species. Finally, spatial analyses of local dragonfly assemblages suggest that ornamented species possess advantages over non‐ornamented taxa at living in habitats that have been converted to farms and cities. Together, these findings suggest that ornamented taxa are buffered against contemporary extinction at local, regional, and continental scales.

Effects of telemetry collars on two free-roaming feral equid species.

There are two species of free-roaming feral equids in North America: horses (Equus caballus) and donkeys or "burros" (E. asinus). Both species were introduced as domestic animals to North America in the early 1500s and currently inhabit rangelands across the western United States, Canada, and all continents except Antarctica. Despite their global distribution, little is known about their fine scale spatial ecology. Contemporary research tools to assess space use include global positioning system (GPS) tracking collars, but older models were problematic due to stiff collar belting causing poor fit. We tested modern designs of GPS collars on n = 105 horses and n = 60 burros for 4 years in five populations (3 horse, 2 burro) across the western United States, to assess whether collars posed welfare risks to horses or burros. We found no difference in survival of collared versus uncollared mares and jennies, and no difference in survival of their foals. In 4036 of 4307 observations for horses (93.7%) and 2115 of 2258 observations for burros (93.6%), collars were observed symmetrical, maintaining proper fit on the neck. Fur effects from collars (sweaty neck, indented fur, broken fur) were seen in 3% of horse observations and 25% of burro observations. Superficial effects (chafes and marks on skin surface) were seen in 2% of horse observations and 11% of burro observations; no severe effects from collars were seen. Body condition was not affected by collars; mean body condition of collared horses was 4.70 ± 0.54 (mean ± s.d) and 4.71 ± 0.65 for collared burros. Behavior results indicated minimal effects; collared horses stood slightly more than uncollared, and collared burros stood and foraged more in one population, but not in the other. For 6.3% of observations of horses and 6.4% of observations of burros, we found an effect of time wearing a collar on the cumulative sum of fur effects which increased over time (burros: rs = 0.87, P = <0.0001; horses: rs = 0.31, P = 0.002). Burros also showed an increase over time in the number of superficial effects, but horses did not. Collars occasionally moved into the wrong position, shifting forward over the ears; we observed this on 19 horses and 1 burro. Of those, most collars went over the ears in summer (n = 12). All collars were equipped with a remote release mechanism as well as a timed-release mechanism for redundancy, thus removed when observed in wrong position to avoid rubbing or discomfort. Our finding of no consequential physical effects in 98% of horse observations, and 89% of burro observations suggests the consequences of collars on free-roaming equid welfare and survival is biologically insignificant, although collars should be monitored regularly and continue to be equipped with a remote release mechanism to remove a collar if needed. With frequent welfare-driven, visual monitoring, collaring of free-roaming equids can be a safe and useful tool to increase our understanding of their spatial ecology, demography, habitat use, behavior, and interactions with other wildlife.

‘Mind the Gap’—reforestation needs vs. reforestation capacity in the western United States

Tree establishment following severe or stand-replacing disturbance is critical for achieving U.S. climate change mitigation goals and for maintaining the co-benefits of intact forest ecosystems. In many contexts, natural post-fire tree regeneration is sufficient to maintain forest cover and associated ecosystem services, but increasingly the pattern and scale of disturbance exceeds ecological thresholds and active reforestation may be warranted. Our capacity to plant trees, however, is not keeping pace with reforestation needs. This shortfall is uniquely apparent in the western U.S., where wildfire size and severity have increased in recent decades and long-term divestment in the reforestation supply chain has limited our ability to respond to existing needs. Here we present an analysis of key facets of both the supply and demand side of reforestation in the western U.S. and address six questions: (1) What is the current backlog of potential reforestation needs driven by high-severity wildfire?; (2) How will increasing wildfire activity through the end of the century affect potential reforestation needs?; (3) What is our capacity to meet current and future reforestation needs?; (4) How can we scale the reforestation supply chain to meet current and future demands?; (5) What approaches to reforestation can promote forest resilience to climate change and wildfire?; and (6) Where are opportunities emerging from recent policy initiatives, innovative public-private partnerships, and natural capital markets for scaling reforestation? Between 1984 and 2000, annual tree planting capacity met post-fire needs but cumulatively over the last two decades (2000 to 2021) it has fallen short of fire-driven needs by an estimated 1.5 million ha (ca. 3.8 million ac). We anticipate this gap will increase 2 to 3 fold by 2050. Scaling up reforestation efforts to close this gap will require increased investment across all facets of the reforestation supply chain, public-private partnerships, and novel approaches to reforestation that increase the resilience of western forests to drought and wildfire. We highlight emerging opportunities from recent policy initiatives and conservation finance for expanding reforestation efforts.

Systemic immunological responses are dependent on sex and ovarian hormone presence following acute inhaled woodsmoke exposure

BackgroundRural regions of the western United States have experienced a noticeable surge in both the frequency and severity of acute wildfire events, which brings significant challenges to both public safety and environmental conservation efforts, with impacts felt globally. Identifying factors contributing to immune dysfunction, including endocrinological phenotypes, is essential to understanding how hormones may influence toxicological susceptibility.MethodsThis exploratory study utilized male and female C57BL/6 mice as in vivo models to investigate distinct responses to acute woodsmoke (WS) exposure with a focus on sex-based differences. In a second set of investigations, two groups were established within the female mouse cohort. In one group, mice experienced ovariectomy (OVX) to simulate an ovarian hormone-deficient state similar to surgical menopause, while the other group received Sham surgery as controls, to investigate the mechanistic role of ovarian hormone presence in driving immune dysregulation following acute WS exposure. Each experimental cohort followed a consecutive 2-day protocol with daily 4-h exposure intervals under two conditions: control HEPA-filtered air (FA) and acute WS to simulate an acute wildfire episode.ResultsMetals analysis of WS particulate matter (PM) revealed significantly increased levels of 63Cu, 182W, 208Pb, and 238U, compared to filtered air (FA) controls, providing insights into the specific metal components most impacted by the changing dynamics of wildfire occurrences in the region. Male and female mice exhibited diverse patterns in lung mRNA cytokine expression following WS exposure, with males showing downregulation and females displaying upregulation, notably for IL-1β, TNF-α, CXCL-1, CCL-5, TGF-β, and IL-6. After acute WS exposure, there were notable differences in the responses of macrophages, neutrophils, and bronchoalveolar lavage (BAL) cytokines IL-10, IL-6, IL-1β, and TNF-α. Significant diverse alterations were observed in BAL cytokines, specifically IL-1β, IL-10, IL-6, and TNF-α, as well as in the populations of immune cells, such as macrophages and polymorphonuclear leukocytes, in both Sham and OVX mice, following acute WS exposure. These findings elucidated the profound influence of hormonal changes on inflammatory outcomes, delineating substantial sex-related differences in immune activation and revealing altered immune responses in OVX mice due to ovarian hormone deficiency. In addition, the flow cytometry analysis highlighted the complex interaction between OVX surgery, acute WS exposure, and their collective impact on immune cell populations within the hematopoietic bone marrow niche.ConclusionsIn summary, both male and female mice, alongside females subjected to OVX and those who had sham surgery, exhibit significant variations in the expression of proinflammatory cytokines, chemokines, lung mRNA gene expression, and related functional networks linked to signaling pathways. These differences potentially act as mediators of sex-specific and hormonal influences in the systemic inflammatory response to acute WS exposure during a wildfire event. Understanding the regulatory roles of genes expressed differentially under environmental stressors holds considerable implications, aiding in identifying sex-specific therapeutic targets for addressing acute lung inflammation and injury.

Illuminating Snow Droughts: The Future of Western United States Snowpack in the SPEAR Large Ensemble

AbstractSeasonal snowpack in the Western United States (WUS) is vital for meeting summer hydrological demands, reducing the intensity and frequency of wildfires, and supporting snow‐tourism economies. While the frequency and severity of snow droughts (SD), that is, anomalously low snowpacks, are expected to increase under continued global warming, the uncertainty from internal climate variability remains challenging to quantify with observations alone. Using a 30‐member large ensemble from a state‐of‐the‐art global climate model, the Seamless System for Prediction and EArth System Research (SPEAR), and an observations‐based data set, we find WUS SD changes are already significant. By 2100, SPEAR projects SDs to be nearly 9 times more frequent under shared socioeconomic pathway 5‐8.5 (SSP5‐8.5) and 5 times more frequent under SSP2‐4.5, compared to a 1921–2011 average. By investigating the influence of the two primary drivers of SD, temperature and precipitation amount, we find the average WUS SD will become warmer and wetter. To assess how these changes affect future summer water availability, we track late winter and spring snowpack across WUS watersheds, finding differences in the onset time of a “no‐snow” threshold between regions and large internal variability within the ensemble that are both on the order of decades. We attribute the inter‐regional variability to differences in the regions' mean winter temperature and the intra‐regional variability to irreducible internal climate variability which is not well‐explained by temperature variations alone. Despite strong scenario forcing, internal climate variability will continue to drive variations in SD and no‐snow conditions through 2100.

Milkweed and floral resource availability for monarch butterflies (Danaus plexippus) in the United States

The global decline of pollinators, particularly insects, underscores the importance of enhanced monitoring of their populations and habitats. However, monitoring some pollinator habitat is challenging due to widespread species distributions and shifts in habitat requirements through seasons and life stages. The monarch butterfly (Danaus plexippus), a migratory insect pollinator that breeds widely throughout North America, presents a unique case study for testing a sampling framework to overcome these challenges. Monarchs exhibit discrete resource needs across life stages (e.g., larval requirement for milkweed, adult requirement for floral nectar), utilizing many land use types across their extensive geographic range during breeding and migration seasons. The Integrated Monarch Monitoring Program (IMMP) uses a standardized protocol with a generalized random tessellation stratified (GRTS) sampling design to gather spatially balanced and ecologically representative information on monarch habitats within the United States. The IMMP is applicable to various land use types and habitats used by breeding monarchs and may be extended to sites outside of the GRTS design to collect data on non-random sites of interest, such as legacy or conservation sites. Additionally, the IMMP’s modular design and publicly available training allows for broad participation, including involvement from community scientists. Here, we summarize habitat metrics (milkweed and floral resources) across 1,233 sites covering much of the monarch’s breeding range. We examine variation in milkweed density and floral resource availability on probabilistic (random) and non-probabilistic (convenience) samples and among land use types (site types). Additionally, we assess resource availability within core geographies for monarch breeding and migration, specifically within the U.S. Fish and Wildlife Service’s Monarch Conservation Units (western, northern, and southern United States). Milkweed density, floral frequency, and floral richness were higher on non-random sites and in the North region. Among site types, milkweed density was highest on Rights-of-Way and Unclassified Grassland, while floral frequency was lowest on Rights-of-Way. The IMMP represents the first field-based habitat monitoring program of this scale for monarchs, yielding a robust dataset on monarchs and their habitats across their breeding range and offering a framework for surveying the habitat of insect species with diverse habitat requirements or widespread distributions.

Parallel SnowModel (v1.0): a parallel implementation of a distributed snow-evolution modeling system (SnowModel)

Abstract. SnowModel, a spatially distributed snow-evolution modeling system, was parallelized using Coarray Fortran for high-performance computing architectures to allow high-resolution (1 m to hundreds of meters) simulations over large regional- to continental-scale domains. In the parallel algorithm, the model domain was split into smaller rectangular sub-domains that are distributed over multiple processor cores using one-dimensional decomposition. All the memory allocations from the original code were reduced to the size of the local sub-domains, allowing each core to perform fewer computations and requiring less memory for each process. Most of the subroutines in SnowModel were simple to parallelize; however, there were certain physical processes, including blowing snow redistribution and components within the solar radiation and wind models, that required non-trivial parallelization using halo-exchange patterns. To validate the parallel algorithm and assess parallel scaling characteristics, high-resolution (100 m grid) simulations were performed over several western United States domains and over the contiguous United States (CONUS) for a year. The CONUS scaling experiment had approximately 70 % parallel efficiency; runtime decreased by a factor of 1.9 running on 1800 cores relative to 648 cores (the minimum number of cores that could be used to run such a large domain because of memory and time limitations). CONUS 100 m simulations were performed for 21 years (2000–2021) using 46 238 and 28 260 grid cells in the x and y dimensions, respectively. Each year was simulated using 1800 cores and took approximately 5 h to run.

Abstract B001: Urinary bladder cancer incidence and mortality in the United States: 20-year trends and initial impact of the COVID-19 pandemic

Abstract Introduction: We examined nationwide trends in urinary bladder cancer incidence and mortality focusing on 1999-2019. A separate analysis of data from 2020 revealed how these rates were affected by the onset of the COVID-19 pandemic. Methods: State-specific bladder cancer (in situ and invasive) incidence and mortality rates were ascertained from the United States (US) Centers for Disease Control and Prevention (CDC) Wide-ranging Online Data for Epidemiologic Research (WONDER) database for 1999-2020 overall and according to age, gender, and geographic region. All rates were age-adjusted to the 2000 US Census population, except age-specific rates. We used Joinpoint software to calculate the 20-year average annual percent change and annual percent change for specific periods identified by data-driven joinpoint placement with 95% confidence intervals (CI). Results: In 2019, the US bladder cancer incidence rate was 18.8 (CI, 18.6 to 18.9) cases per 100,000. Bladder cancer incidence decreased 0.9% annually (CI, 0.8 to 1.0% decrease) during 1999-2019, with a 3.3% annual decrease (CI, 2.5 to 4.1% decrease) during 2016-2019 specifically. Among men, the 20-year annual decrease was 1.1% (CI, 1.0 to 1.1% decrease), with a 3.8% annual decrease (CI, 2.8 to 4.6% decrease) during 2017-2019 specifically. Among women, the 20-year annual decrease was 1.0% (CI, 0.9 to 1.2% decrease), with a 2.6% annual decrease (CI, 1.7 to 4.2% decrease) during 2016-2019 specifically. Largest annual decreases in incidence rates were seen among 55-59-year-olds (1.8%, CI, 1.6 to 2.0% decrease), and in the western US (2.3%, CI, 2.0 to 2.6% decrease). Conversely, some southern states showed an increase in incidence. In Tennessee, there was a 20-year annual increase of 1.2% (CI, 0.9 to 1.6% increase). In 2019, the US bladder cancer mortality rate was 4.1 (CI, 4.0 to 4.2) deaths per 100,000. Bladder cancer mortality decreased 0.4% annually (CI, 0.2 to 0.5% decrease) during 1999-2019, with a 2.5% annual decrease (CI, 1.3 to 4.7% decrease) during 2016-2019 specifically. Mortality rate trends were generally similar among men and women (0.4% and 0.7% decrease annually, respectively). Largest annual decreases in mortality rates were seen among 50-54-year-olds (1.5%, CI, 0.6 to 2.4% decrease) and in the northeast US (0.8%, CI, 0.7 to 1.0% decrease). Reflecting the initial impact of the COVID-19 pandemic, bladder cancer incidence decreased by 8.6% (CI, 7.7 to 9.6% decrease) and bladder cancer mortality decreased by 2.7% (CI, 0.6 to 4.8% decrease) comparing 2020 with 2019. Conclusions: After decades remaining relatively constant, bladder cancer incidence and mortality rates in the US began to decrease around 2016-2017. This trend was less apparent in the southern part of the country, where incidence trended upward in some states. As evident for other common cancers, bladder cancer incidence rates decreased sharply during the first year of the COVID-19 pandemic. Forthcoming data for 2021-2024 will provide a clearer picture of the magnitude of this disruption and the possibility of a rebound. Citation Format: Grace B. Gallant, Hugo Pomares-Millan, Judy R. Rees, Margaret R. Karagas, Michael N. Passarelli. Urinary bladder cancer incidence and mortality in the United States: 20-year trends and initial impact of the COVID-19 pandemic [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(10_Suppl):Abstract nr B001.

Quantifying marine larval dispersal to assess MPA network connectivity and inform future national and transboundary planning efforts

A marine protected area (MPA) network of multiple reserves can protect biodiversity across space, but to be effective, network configuration should support dispersal among MPAs as well as spillover to unprotected habitats. The ability of MPAs to function as an interacting network of populations connected by dispersal, however, is difficult to estimate at broad spatial scales, and therefore, connectivity is often not integrated in MPA design. Here, we simulate passive larval dispersal using a biophysical model to estimate potential transboundary network connectivity of MPAs in western Canada and United States. Drift time was varied to represent generic functional groups of nearshore species with planktonic larvae and sedentary adult stages. We found that MPAs potentially act as an interacting network and meet connectivity design criteria for nearshore invertebrate species, many MPAs (65%–90%) possibly exchange individuals, and a third of larvae from MPAs (25%–32%) source areas of the unprotected coast. This analysis provides a first approximation of multispecies connectivity to inform ongoing transboundary MPA design, and it can be used as a foundation for future model development.

Greater sage‐grouse chick mortality risk relative to livestock grazing management, environmental factors, and morphometric measurements

AbstractGreater sage‐grouse (Centrocercus urophasianus; sage‐grouse) populations in the western United States have declined, necessitating conservation efforts. The United States Department of Agriculture Natural Resources Conservation Service and livestock producers implemented the Sage Grouse Initiative (SGI) to improve sage‐grouse habitat using regional‐specific management actions such as rotational grazing. We assessed the effect of SGI grazing management, the influence of brood female and chick morphometric traits, and multiple environmental and anthropogenic disturbance factors on chick mortality risk in a sage‐grouse population in central Montana, USA, from 2011–2019. We used a Kaplan‐Meier survival function to evaluate chick survival, Cox proportional hazards models to evaluate chick mortality risk as a function of brood female and chick morphometric traits, and the Andersen‐Gill formulation of the Cox proportional hazards model to assess the effects of time‐dependent habitat characteristics on chick mortality risk. Survival to 45 days post‐hatch for 510 chicks varied annually from 0.26 ± 0.07 (SE) to 0.69 ± 0.07. The 45‐day survival rate for all years combined was 0.51 ± 0.03. Chick mortality risk was not affected by changes in livestock grazing management implemented through the SGI grazing program. Brood female age and body condition, sex of chicks, vegetation, and anthropogenic variables were also unassociated with chick mortality risk. There were small protective effects of chick mass adjusted for age and mean minimum monthly temperature; greater chick mass and lower monthly temperatures correlated with reduced mortality risk. Overall, our study suggests the SGI grazing program does not confer additional benefits to sage‐grouse chicks beyond existing grazing practices. Incentivizing grazing practices that adhere to fundamental principles of rangeland ecology and maintain intact rangelands may be more effective than specific prescribed grazing systems for sage‐grouse conservation in this region.

Assessing Justice, Equity, Diversity, and Inclusion Best Practices for Test Item Writing at a Physician Assistant Program: A Retrospective Analysis

Introduction Outcomes for specific racial and ethnic groups during the COVID-19 pandemic and the widespread protests demanding racial justice in 2020 renewed a focus on health equity practices and bias in medical education. Routine inclusion of sociodemographic identifiers such as sex/gender, age, race, and/or ethnicity in test items risks perpetuation of implicit bias and race-based practices in medical education. Methods A retrospective review was conducted of test items in a pathophysiology course series at an academic medical center in the Western United States. Sociodemographic identifiers in multiple choice test items were reviewed to determine clinical relevance. Results Of 795 test items, 475 referred to sociodemographic information (gender, race/ethnicity, age, sexual orientation) and in only 27.5% of questions, this inclusion was clinically relevant (131/475). Discussion Current evidence suggests that routine inclusion of sociodemographic information in test items infrequently supports the clinical diagnosis and perpetuates implicit bias and race-based practices in medical education. Thoughtful inclusion of sociodemographic information in assessment offers an opportunity to address sociostructural determinants of health.

How three-dimensional forest structure regulates the amount and timing of snowmelt across a climatic gradient of snow persistence

Across the western United States, forests are changing rapidly, with uncertain impacts on snowmelt water resources. Snow partitioning is controlled by forest effects on interception, radiation, and sublimation. Yet, models often lack snow measurements with sufficiently high spatial and temporal resolution across gradients of forest structure to accurately represent these fine-scale processes. Here, we utilize four Snowtography stations in Arizona, in the lower Colorado River Basin, with daily measurements over 3–5 years at ~110 positions distributed across gradients of forest structure resulting from wildfires and mechanical thinning. We combine Snowtography with lidar snapshots of forest and snow to train a high-resolution snow model and run it for 6 years to quantify how forest structure regulates snowpack and snowmelt. These study sites represent a climate gradient from lower/warmer ephemeral snowpack (~2,100 m asl) to higher/colder seasonal snowpack (~2,800 m asl). Forest cover reduced snowpack and snowmelt through canopy sublimation. Forest advanced snowmelt timing at lower/warmer sites but delayed it at higher/colder sites. Within canopy gaps, shaded cool edges had the greatest peak snow water equivalent (SWE). Surprisingly, sunny/warm gap edges produced more snowmelt than cool edges, because high radiation melted snow quickly, reducing exposure to sublimation. Therefore, peak SWE is not an ideal proxy for snowmelt volume from ephemeral snowpacks, which are becoming more prevalent due to warming. The results imply that forest management can influence the amount and timing of snowmelt, and that there may be decision trade-offs between enhancing forest resilience through delayed snowmelt and maximizing snowmelt volumes for downstream water resources.

Machine learning allows for large-scale habitat prediction of a wide-ranging carnivore across diverse ecoregions

ContextResource selection functions are powerful tools for predicting habitat selection of animals. Recently, machine-learning methods such as random forest have gained popularity for predicting habitat selection due to their flexibility and strong predictive performance.ObjectivesWe tested two methods for predicting continental-scale, second-order habitat selection of a wide-ranging large carnivore, the mountain lion (Puma concolor), to support continent-wide conservation management, including estimating abundance, and to predict habitat suitability for recolonizing or reintroduced animals.MethodsWe compared a generalized linear model (GLM) and a random forest model using GPS location data from 476 individuals across 20 study sites in the western USA and Canada and remotely-sensed landscape data. We internally validated models and examined their ability to correctly classify used and available points by calculating area under the receiver operating characteristics (AUC). We performed leave-one-out (LOO) out-of-sample tests of predictive strength on both models.ResultsBoth models suggested that mountain lions select for steeper slopes, areas closer to water, and with higher normalized difference vegetation index (NDVI), and against variables associated with human impact. The random forest model (AUC = 0.94) demonstrated that mountain lion habitat can be accurately predicted at continental scales, outperforming the traditional GLM model (AUC = 0.68). Our LOO validation provided similar results (x̄ = 0.93 for the random forest and x̄ = 0.65 for the GLM).ConclusionsWe found that the added flexibility of the random forest model provided deeper insights into how individual covariates impacted habitat selection across diverse ecosystems. Our LOO analyses suggested that our model can predict mountain lion habitat selection in unoccupied areas or where local data are unavailable. Our model thus provides a tool to support discussions and analyses relevant to continent-wide mountain lion conservation and management including estimating metapopulation abundance.

Multi‐locus sequence typing indicates multiple strains of Mycoplasma in desert bighorn sheep and aoudad in Texas

AbstractEpizootic events of pneumonia, presumably caused by Mycoplasma ovipneumoniae, in bighorn sheep (Ovis canadensis) have been observed in the western United States and Canada. Until recently, it was thought that populations of Mexican (O. c. mexicana) and Nelson's (O. c. nelsoni) desert bighorn sheep in Texas, USA, had not been exposed to Mycoplasma. Evidence of disease and potential population decline from outbreaks of M. ovipneumoniae are now known from several populations across the Trans‐Pecos Ecoregion with documented instances of pneumonia and bluetongue in desert bighorn sheep from the Van Horn Mountains and Black Gap Wildlife Management Area. These disease events, especially those in 2019–2021, may be a result of increasing populations of aoudad (Ammotragus lervia), an introduced and invasive ungulate, in the region. With large population sizes and similar movement patterns as desert bighorn sheep, aoudad potentially are the reservoirs for bacterial and viral diseases, such as pneumonia and bluetongue, and are possibly contributing to the decline of desert bighorn sheep. Herein, we optimized the multi‐locus sequence typing (MLST) with modifications in the Taq polymerase and annealing temperatures to determine the genetic identity of Mycoplasma strains or species within the nasal passages of desert bighorn sheep and aoudad in the Trans‐Pecos Ecoregion of Texas. Four loci (small ribosomal unit, 16S; 16S‐23S intergenic spacer region, IGS; RNA polymerase B, rpoB; gyrase B, gyrB) were characterized using MLST. Based on results from the modified MLST technique, we identified 9 desert bighorn sheep and 5 aoudad with M. ovipneumoniae, 9 aoudad with bacterial sequences genetically similar to M. conjunctivae, and 10 aoudad with bacterial sequences genetically similar M. hyopneumoniae. Of these, 9 aoudad possessed bacterial sequences genetically similar to both M. conjunctivae and M. hyopneumoniae. Among the 4 diagnostic loci, genetic divergence of M. ovipneumoniae ranged from 0.00–0.90% among desert bighorn sheep and aoudad. Future sampling efforts of seemingly asymptomatic aoudad, and asymptomatic, visibly sick, or deceased desert bighorn sheep, are important to monitor the spread of disease in desert bighorn sheep populations across mountain ranges in western Texas. It is imperative that aoudad removal plans are implemented to reduce and eliminate current infections and putative transmission of M. ovipneumoniae, prevent future disease outbreaks of pneumonia, and ultimately conserve desert bighorn sheep for future generations.

Constraints on Mechanical Fuel Reduction Treatments in United States Forest Service Wildfire Crisis Strategy Priority Landscapes

Abstract The USDA Forest Service recently launched a Wildfire Crisis Strategy outlining objectives to safeguard communities and other values at risk by substantially increasing the pace and scale of fuel reduction treatment. This analysis quantified layered operational constraints to mechanical fuel reduction treatments, including existing vegetation, protected areas, steep slopes, and administrative boundaries in twenty-one prioritized landscapes. Results suggest that achieving the objective to treat 20%–40% of high-risk area is unlikely in most landscapes under a business-as-usual approach to mechanical fuel reduction treatments. Increased investment in steep-slope systems and expanded road access opens sufficient acreage to meet treatment objectives in eighteen of twenty-one priority landscapes. Achieving treatment objectives in the remaining three landscapes will require both increased investment to overcome physical constraints and navigating administrative complexities within reserved land allocations to implement fuels treatments at the pace and scale needed to moderate fire risk to communities. Study Implications: Legal, operational, and administrative factors have hindered the implementation of proposed wildland fire risk reduction management actions. Investing in steep-slope systems, expanding use of temporary roads, and revising administrative rules to allow for appropriately tailored mechanical thinning in special conservation areas are possible ways to meet fuel reduction treatment objectives of the USDA Forest Service Wildfire Crisis Strategy in twenty-one landscapes across the western United States. Broadening the land base available for mechanical treatment allows for flexibility to develop treatment plans that optimize across the multiple dimensions of effective landscape-scale fuel treatment design and restore fire as a key ecosystem process.

A time-to-event analysis for temperature dependence of seed germination in four conifers: Ecological niche and environmental gradients

Seed germination is a vital process in the plant life cycle. It directly influences seedling establishment and subsequently determines population persistence and species distribution. Germination is highly sensitive to climatic conditions, and germination traits may vary among species and populations within the same species. This study aims to improve our understanding of intraspecific and interspecific variation in temperature dependence of seed germination and how this variation relates to the environment where seeds were collected. We focused on four conifer species (Pinus contorta, Picea engelmannii, Pinus ponderosa, and Pseudotsuga menziesii) and seeds collected at 20 sites spanning the elevation range of each species in the Western United States. We conducted seed germination tests at temperatures from 5 to 40°C in 5°C intervals and tracked germination for 30 days. We used the log-logistic time-to-event model and Gaussian function to fit germination data and analyze their temperature dependence. The climate variables at the seed-collecting sites were summarized by long-term normals (1971–2000) covering most seed-collection years. Climate variables were correlated and thus were combined via Principal Component Analysis (PCA) into several uncorrelated principal components (PC scores) that describe climate at the seed collection sites. The estimated optimal temperature (To), shape coefficient (b), and maximum value at optimal temperature (GPmax) of germination percentages and median germination rates (GR50) were then fit to linear models to determine whether they varied with species identity and the climate-derived PC scores. Results showed that seed germination traits from different species exhibit climate gradients that are correlated with their ecological niche. However, seeds from different elevations within the same species had variable germination traits irrespective of environmental gradients. We also found that variation in germination was more significant near upper and lower temperature limits. Including inter- and intra-specific temperature dependence of seed germination would improve predictions of population dynamics and range shifts under climate warming and could inform forest management, seed transfer, and assisted migration practices.

The Dolan Fire of Central Coastal California: Burn Severity Estimates from Remote Sensing and Associations with Environmental Factors

In 2020, wildfires scarred over 4,000,000 hectares in the western United States, devastating urban populations and ecosystems alike. The significant impact that wildfires have on plants, animals, and human environments makes wildfire adaptation, management, and mitigation strategies a critical task. This study uses satellite imagery from Landsat to calculate burn severity and map the fire progression for the Dolan Fire of central Coastal California which occurred in August 2020. Several environmental factors, such as temperature, humidity, fuel type, topography, surface conditions, and wind velocity, are known to affect wildfire spread and burn severity. The aim of this study is the investigation of the relationship between these environmental factors, estimates of burn severity, and fire spread patterns. Burn severity is calculated and classified using the Difference in Normalized Burn Ratio (dNBR) before being displayed as a time series of maps. The Dolan Fire had a moderate severity burn with an average dNBR of 0.292. The ignition site location, when paired with the patterns of fire spread, is consistent with wind speed and direction data, suggesting fire movement to the southeast of the fire ignition site. Patterns of increased burn severity are compared with both topography (slope and aspect) and fuel type. Locations that were found to be more susceptible to high burn severity featured Long Needle Timber Litter and Mature Timber fuels, intermediate slope angles between 15 and 35°, and north- and east-facing slopes. This study has implications for the future predictive modeling of wildfires that may serve to develop wildfire mitigation strategies, manage climate change impacts, and protect human lives.