Search Results (88)

This study delves into the necessity for gender-affirming practices, particularly focusing on the underrepresented transgender and non-binary communities in California’s Central Valley. Despite the recognized standards by the World Professional Association for Transgender Health (WPATH) for best practices in mental health care, adequately trained professionals in this region remains a notable scarcity. The paper highlights the heightened risks these communities face, including discrimination and mental health challenges, underscoring the critical need for compassionate and competent care. The research aims to bridge the gap in education and training for practitioners on gender diversity and improve mental health services for transgender and non-binary individuals. Through thematic analysis of individual interviews, the study captures the experiences of gender diverse individuals with behavioral health care, emphasizing the importance of gender-affirming care, the dangers of pathologizing gender diversity, and the adverse impacts of gatekeeping and conversion therapy. Conclusively, the study advocates for an informed consent model for medical transitions, as per WPATH guidelines, and calls for a shift towards intersectional, inclusive practices. It stresses the need for ongoing education, policy reform, and advocacy to ensure equitable, affirming mental health care for gender diverse populations. Full article

Wintertime cold air pools (CAPs) are common across the Western United States and result in cold, dense air trapped in valley basins. The CAPs are characterized by a stable atmospheric boundary layer, leading to cold air and low wind speeds. While CAP formation occurs nightly, the CAP conditions can persist into daytime and often last for multiple days (i.e., persistent cold air pool or PCAP), resulting in poor air quality in populated areas. The presence and strength of CAPs can be calculated using data from radiosondes, surface weather stations at varying elevations, and indirectly through air pollution monitors. Because vertical profile data are often limited to twice daily radiosondes, and are spatially sparse, numerical models can be a useful substitute. This work uses the European Centre for Medium-Range Weather Forecasts (ECMWFs) Reanalysis v5 (ERA) atmospheric reanalysis to provide data to classify wintertime CAP events without radiosonde observations. An automated CAP classification method using ERA outputs is evaluated using afternoon radiosonde observations in six cities (Salt Lake City, Utah; Reno, Nevada; Boise, Idaho; Denver, Colorado; Las Vegas, Nevada; Medford, and Oregon). Using this CAP determination method, days with CAP events are analyzed in 13 locations, 6 with radiosonde observations and 7 without, including the Central valley of California. The CAP classification method is evaluated at these 13 locations across the Western US over the study period of 2000–2022. The results show that the ERA model performs similarly to the radiosonde observations when used to identify CAP events. Therefore, ERA can be used to provide a reasonable estimate of CAP conditions when radiosonde data are unavailable. Providing consistent CAP classifications across space and time are necessary for regional scale CAP studies, such as human health effects modeling over large spatial and temporal scales. Full article

To mitigate the impact of north–south strip errors inherent in Gravity Recovery and Climate Experiment (GRACE) spherical harmonic coefficient solutions, this research develops a state-space model to generate a more robust solution. The efficacy of the state-space model is demonstrated by comparing its performance with that of conventional filtering methods and hydrological modeling schemes. The method is subsequently applied to estimate the GRACE Groundwater Drought Index in the California Central Valley basin, a region significantly affected by drought during the GRACE observation period. This analysis quantifies the severity of droughts and floods while investigating the direct influences of precipitation, runoff, evaporation, and anthropogenic activities. By incorporating the El Niño–Southern Oscillation (ENSO) and the Pacific Decadal Oscillation, the study offers a detailed causal analysis and proposes a novel methodology for water resource management and disaster early warning. The results indicate that a moderate-duration flood event in 2006 resulted in a recharge of 19.81 km³ of water resources in the California Central Valley basin, whereas prolonged droughts in 2008 and 2013, lasting over 15 months, led to groundwater depletion of 41.53 km³ and 91.45 km³, respectively. Precipitation and runoff are identified as the primary determinants of local drought and flood conditions. The occurrence of ENSO events correlates with sustained precipitation variations over the subsequent 2–3 months, resulting in corresponding changes in groundwater storage. Full article

The Central Valley of California provides critical wintering habitat for Sandhill Cranes (Antigone canadensis), which rely on wetlands, grasslands, and grain crops to meet their energetic needs. However, temporary row crops that support Sandhill Cranes and other wintering birds are ostensibly being replaced by permanent woody crops, which offer little value for wetland and grassland-dependent species. To better understand how landcover changes may be affecting habitat availability for these wintering cranes, we analyzed landcover trends within priority crane wintering areas from 2008 to 2023. We employed a mixed-methods approach that allowed us to describe both linear and non-linear trends over time and across regions. Our findings indicate a significant decrease in landcover types suitable as crane habitat over the 16-year period ($\tau$ = −0.90, p < 0.001), with an average annual decline of approximately −1.15 ± 0.21% (B± 95% CI). The best-fit trendline showed that habitat suitability in priority wintering areas decreased from over 81% in 2008 to under 65% in 2023. Specifically, grasslands, rice fields, and alfalfa acreage declined across priority wintering areas, while woody landcover—including orchards, vineyards, and riparian forest breaks—increased significantly ($\tau$ = 0.88, p < 0.001; B = 1.14 ± 0.20%). These landscape-level changes may constrain the regional carrying capacity for Sandhill Cranes and reduce their overall resilience. Full article

This study presents a comprehensive review and comparative analysis of traditional machine learning (ML) and deep learning (DL) models for land cover classification in agricultural remote sensing. We evaluate the reported successes, trade-offs, and performance metrics of ML and DL models across diverse agricultural contexts. Building on this foundation, we apply both model types to the specific case of almond crop field identification in California’s Central Valley using Landsat data. DL models, including U-Net, MANet, and DeepLabv3+, achieve high accuracy rates of 97.3% to 97.5%, yet our findings demonstrate that conventional ML models—such as Decision Tree, K-Nearest Neighbor, and Random Forest—can reach comparable accuracies of 96.6% to 96.8%. Importantly, the ML models were developed using data from a single year, while DL models required extensive training data spanning 2008 to 2022. Our results highlight that traditional ML models offer robust classification performance with substantially lower computational demands, making them especially valuable in resource-constrained settings. This paper underscores the need for a balanced approach in model selection—one that weighs accuracy alongside efficiency. The findings contribute actionable insights for agricultural land cover mapping and inform ongoing model development in the geospatial sciences. Full article

Bovine mastitis is a significant disease affecting dairy cattle worldwide, impacting milk quality and farm profitability. Understanding pathogen distribution is crucial for effective disease management. This study analyzed 319,634 individual cow milk samples submitted to the UC Davis Milk Quality Laboratory between 2009 and 2023 to assess pathogen prevalence, seasonal variations, and long-term trends. Routine microbiological cultures identified major and minor mastitis pathogens, with additional testing for Mycoplasma spp. Statistical analyses evaluated annual and seasonal trends in bacterial isolation rates. Results indicated that environmental pathogens, particularly non-aureus staphylococci and coliforms, were most frequently isolated, while contagious pathogens (Staphylococcus aureus, Streptococcus agalactiae, and Mycoplasma spp.) were less prevalent. Seasonal trends revealed higher contamination rates in Winter and increased no-growth samples in Summer. The study also observed a decline in sample submissions in recent years, possibly reflecting evolving dairy management practices. These findings provide a comprehensive perspective on mastitis pathogen dynamics in California’s Central Valley, supporting improved milk quality control measures and tailored mastitis prevention strategies. Full article

Research on access to healthcare for transgender populations in California remains mostly focused on the major city centers, leaving out many rural and poorer areas of the state. Understanding the barriers to gender-affirming healthcare in a largely rural, agricultural, and low-income area is critical in creating effective policies and programs to address significant gaps in transgender healthcare. This is especially true in regions like Fresno County, which sits within the heart of the Central Valley of California, that are mostly rural and agricultural. This study conducted a community health assessment using a mixed-methods approach, focusing on transgender communities’ experience of accessing healthcare and gender-affirming healthcare in Fresno County and on the various existing barriers and critical needs. The study reveals the critical deficits in accessing gender-affirming healthcare in Fresno County, especially regarding doctors providing gender-affirming care, as well as the larger implications this has on the health and well-being of transgender individuals living in the Central Valley. Full article

In 2020, California banned the sale and agricultural use of chlorpyrifos, an organophosphate pesticide (OP) associated with neurotoxicity and other adverse health outcomes. We primarily assessed changes in chlorpyrifos associated with this policy and secondarily explored how other OP exposures changed. The participants were from California’s Central Valley, 18 years or older, and English- or Spanish-speaking. The surveys and urine samples were collected pre-ban (December 2020) and post-ban (February–April 2022). The urine samples were analyzed for a chlorpyrifos-specific metabolite (TCPy), six dialkyl phosphates (DEP, DMTP, DETP, DMDTP, DMP, DEDTP), and total DE and DM. The pre- and post-ban metabolite concentrations were compared via Wilcoxon signed-rank tests and natural log-transformed paired differences in linear mixed effects regression, adjusted for covariates. Forty-nine participants had repeated biomarker data. The mean age of the study population was 46.8 years (SD: 16), 61% female, 67% Spanish-speaking, 100% Hispanic/Latino(a), and 47% had less than a high school education. Six urinary metabolites (TCPy, DEP, DMP, DMTP, total DE and total DM) had sufficient variation for further analysis, while DMDTP, DEDTP, and DETP were undetected. The paired differences in adjusted models showed statistically significant increases in TCPy and DMP associated with the policy change (e.g., TCPy estimated ratio of geometric means: 4.53 (95% CI 2.66, 7.69)) Reductions in metabolites of chlorpyrifos exposure were not observed following California’s chlorpyrifos ban, suggesting ongoing exposure to chlorpyrifos from other sources. Full article

The San Joaquin Valley (SJV) of California is one of the world’s most productive agricultural regions. Reliance on groundwater has led to some of the greatest rates of human-induced land subsidence in the world in the 20th century, as well as more recently. The United States Geological Survey (USGS) has recently developed an integrated surface–subsurface hydrologic model, the Central Valley Hydrologic Model 2 (CVHM2), that represents the major components of the hydrologic system of California’s Central Valley. In this study, CVHM2 was applied as a decision support tool while simulating various management strategies to mitigate the land subsidence caused by the extraction of groundwater. CVHM2 was extended through to 2073 and applied to simulate management scenarios in terms of three primary drivers and their impact on subsidence along the Delta–Mendota Canal (DMC), a critical piece of infrastructure in the western SJV. The drivers considered were agricultural water demands, managed aquifer recharge (MAR), and changes in future climate. The results show that future subsidence is most sensitive to water demands, second most sensitive to future changes in climate, and relatively insensitive to MAR when it is applied as a surface application in the western SJV. However, we demonstrate via proof-of-concept scenarios that the MAR is capable of arresting subsidence when implemented via injection below the Corcoran Clay Member of the Tulare Formation instead of as a surface application. We also examine the uncertainty that is the result of climate variability and how to use the tool to identify the most appropriate strategies to constrain future subsidence to acceptable levels. Full article

The endangered San Joaquin kit fox (SJKF) (Vulpes macrotis mutica), which is endemic to the San Joaquin Valley in California, has lost most of its natural habitat due to urban sprawl and change in land use over time. Many studies have been conducted to restore and protect the remaining habitat, involving presence/absence surveys prior to urban development using camera monitoring, tracking dogs, tracking plates, spotlighting, and trapping. While these traditional methods work well, they can be invasive, expensive, labor-intensive, and require permits to perform. In our study, we used a non-invasive method based on DNA extraction from scat collected in the environment, followed by a diagnostic Polymerase Chain Reaction (PCR)-based approach on mitochondrial DNA fragments and investigated the presence of the SJKF on four case study sites that shared a high SJKF habitat suitability index but are under the threat of development. We found that the diagnostic PCR was able to accurately differentiate between different canids present at the sites, in a time- and cost-effective manner. Including this non-invasive method in the Department of Fish and Wildlife’s standardized recommendations for survey methods would help to improve future environmental assessments for SJKF populations in the Central Valley of California. Full article

The potential of terminating cover crops with a roller-crimper is of increasing interest. A two-year (2020/21 and 2021/22) study was conducted in Fresno, CA, USA. Five cover crop treatments (rye (Secale cereale L.) alone, ultra-high diversity mix, multiplex cover crop mix, fava bean (Vicia faba L.) + phacelia (Phacelia tanacetifolia Benth.), and rye + field pea (Pisum sativum L.) + purple vetch (Vicia americana Muhl. Ex Willd.)) were planted in November, roller-crimped in April, and silage maize (Zea mays L.) was strip-till planted in the residue in May. Cover crop kill, soil cover by residue, weed cover, amount of organic residue, and silage maize yield were recorded. The roller-crimper resulted in 95 to 100% kill of the cover crops. Soil cover at maize canopy closure (mid-July) was approximately 90% in the rye plots while it was 30 to 70% in the other treatments. The fava bean + phacelia cover crop disintegrated the most rapidly. Weed cover was <5% in all the treatments until maize canopy closure. The cover crops added 6.7 to 14 MT ha⁻¹ of residue. Maize silage yield was similar across the treatments. Therefore, in this study, cover crops were successfully terminated by the roller-crimper, allowing successful strip-till establishment and production of silage maize. Full article

Sorghum cultivars, particularly those used for forage and biomass, present significant potential as drought-resistant crops suitable for animal feed and biofuel production. This study evaluated 59 sorghum hybrids over five years (2019–2023) across three University of California research farm locations in the Central Valley: Kearney REC (KARE), West Side REC (WSREC), and Davis. The primary aim was to identify genotypes that exhibit high yield and stability across diverse environments in California, which is crucial for meeting the state’s significant feed needs associated with dairy operations and animal production. The evaluation focused on biomass yields, forage quality traits such as Relative Feed Quality (RFQ) and milk yield per ton (milk/ton), and biofuel-relevant chemical compositions like Neutral Detergent Fiber (NDF) and starch. A multi-trait stability index was employed to pinpoint superior genotypes that combine high yield with desirable quality traits. Results indicated significant genotypic, environmental, and genotype-by-environment (GxE) interaction effects for all traits except fat and water-soluble sugars. Eight hybrids were notable for maintaining high and stable biomass yields across different locations. Additionally, high fat and starch content were found to correlate with improved milk/ton potential, while lower fiber content (ADF, NDF) was associated with enhanced RFQ. Specifically, nine hybrids were identified as optimal for dairy forage due to their combination of high yield, RFQ, and milk/ton. Furthermore, distinct hybrids were identified for first-generation (starch-based) and second-generation (NDF-based) biofuel strategies. Three hybrids stood out as having desirable traits for both feed and biofuel applications, underscoring their versatility. This study highlights the utility of a multi-trait stability index in selecting superior sorghum genotypes for specific trait combinations. The identified candidates for forage and biofuel use, especially the multipurpose varieties, offer valuable insights that can aid growers and industry stakeholders in developing more sustainable and versatile sorghum production systems in California. Findings from this study contribute significantly to the development of more resilient sorghum production systems. By identifying hybrids that excel in both yield and quality across various environments, this research supports future cropping decisions aimed at enhancing water use efficiency and drought resilience in sorghum cultivation. These advancements are crucial for maintaining competitive dairy operations and advancing biofuel production in the face of climate change-induced challenges. Full article

Coccidioidomycosis is a disease caused by soil fungi of the genus Coccidioides, divided genetically into Coccidioides immitis (California isolates) and Coccidioides posadasii (isolates outside California). Coccidioidomycosis is transmitted through the inhalation of fungal spores, arthroconidia, which can cause disease in susceptible mammalian hosts, including humans. Coccidioidomycosis is endemic to the western part of the United States of America, including the central valley of California, Arizona, New Mexico, and parts of western Texas. Cases have been reported in other regions in different states, and endemic pockets are present in these states. The incidence of reported cases of coccidioidomycosis has notably increased since it became reportable in 1995. Clinically, the infection ranges from asymptomatic to fatal disease due to pneumonia or disseminated states. The recognition of coccidioidomycosis can be challenging, as it frequently mimics bacterial community-acquired pneumonia. The diagnosis of coccidioidomycosis is frequently dependent on serologic testing, the results of which can take several days or longer to obtain. Coccidioidomycosis continues to present challenges for clinicians, and suspected cases can be easily missed. The challenges of coccidioidomycosis disease, from presentation to diagnosis to treatment, remain a hurdle for clinicians, and further research is needed to address these challenges. Full article

Variations in species distribution, population structure, and behavior can provide a portfolio effect that buffers populations against rapid environmental change. Although diversity has been identified as a goal for effective resource management and genetic and demographic tools have been developed, life history remains challenging to quantify. In this study, we demonstrate a novel metric of life history diversity using telemetry data from migratory fish. Here, we examined diversity in the outmigration behavior of juvenile Chinook salmon (Oncorhynchus tshawytscha) released in the Sacramento River, California, between 2007 and 2017. In this synthesis, we examined a wide variety of landscape and demographic drivers at high resolution by incorporating many individual telemetry studies, with variability in release location by year, environmental conditions, and all runs of salmon that are present in the watershed. When years were grouped by shared hydrologic conditions, variation in travel time was significantly higher in wet years. Further, our model showed a negative effect of warm temperatures at low flows on the variation in migration movements. This suggests that enhanced hydrologic connectivity increases the variation in migration time, a representation of habitat complexity and biocomplexity, despite the degraded state of this watershed and the weakened state of these populations. Variation in migration behavior could buffer species from current and future environmental changes, such as climate effects on precipitation and temperature. Hence, behavioral metrics generated from telemetry studies can be used to understand life history diversity and the potential effects of environmental fluctuations. Full article

Changing weather patterns have already put pressure on cropping systems around the globe. Projected increases in mean temperatures and variance in precipitation will likely affect the profitability of current cropping patterns, leading to shifts in which crops are grown in a given location. The pressure on water resources in a location, in terms of both water quantity and water quality, will also change with the types of crops grown. While the southeastern United States is projected to become warmer under each of the representative concentration pathways, it is also projected to become somewhat wetter. California’s Central Valley, where much of the fresh produce in the US is grown, will likely continue to suffer significant and extended droughts. The southeastern US is a prime candidate for expanding fresh produce production in response to reduced yields in the west. This paper explores the consequences on water withdrawals and water quality of shifting from row crop to vegetable production in the southeastern US. The water quality consequences are based on changes in pesticide products and application rates. The water quantity consequences are based on crop water needs. The methodology used here can be applied to other production systems around the world. Identifying the water quality and quantity implications of shifting cropping patterns is critical to the long-term sustainability of water resources. Full article