Drivers of arthropod biodiversity in an urban ecosystem.

Our world is becoming increasingly urbanized with a growing human population concentrated around cities. The expansion of urban areas has important consequences for biodiversity, yet the abiotic drivers of biodiversity in urban ecosystems have not been well characterized for the most diverse group of animals on the planet, arthropods. Given their great diversity, comparatively small home ranges, and ability to disperse, arthropods make an excellent model for studying which factors can most accurately predict urban biodiversity. We assessed the effects of (i) topography (distance to natural areas and to ocean) (ii) abiotic factors (mean annual temperature and diurnal range), and (iii) anthropogenic drivers (land value and amount of impervious surface) on the occurrence of six arthropod groups represented in Malaise trap collections run by the BioSCAN project across the Greater Los Angeles Area. We found striking heterogeneity in responses to all factors both within and between taxonomic groups. Diurnal temperature range had a consistently negative effect on occupancy but this effect was only significant in Phoridae. Anthropogenic drivers had mixed though mostly insignificant effects, as some groups and species were most diverse in highly urbanized areas, while other groups showed suppressed diversity. Only Phoridae was significantly affected by land value, where most species were more likely to occur in areas with lower land value. Los Angeles can support high regional arthropod diversity, but spatial community composition is highly dependent on the taxonomic group.

Cardiovascular Disease Risk Factors Predict the Development and Numbers of Common Musculoskeletal Disorders in a Prospective Cohort.

OBJECTIVE: The aim of the study is to assess risk of common musculoskeletal disorders (MSDs) based on cardiovascular disease (CVD) risk scores. METHODS: Data from a 9-year prospective cohort of 1224 workers in three states were analyzed. Baseline data included questionnaires, structured interviews, physical examinations, anthropometric measurements, nerve conduction studies, and individualized measurement of job physical factors. Monthly follow-ups were conducted. Framingham risk scores were calculated. A priori case definitions were constructed for carpal tunnel syndrome, lateral epicondylopathy, medial epicondylopathy, and rotator cuff tendinopathy. RESULTS: Adjusted RRs for one or more MSDs increased to 3.90 (95% confidence interval, 2.20-6.90) among those with 10-year cardiovascular disease risk scores greater than 15% and 17.4 (95% confidence interval, 3.85-78.62) among those with more than 4 disorders. CONCLUSIONS: Cardiovascular disease factors are strongly associated with the subsequent development of common MSDs. Risks among those with multiple MSDs are considerably stronger.

Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds.

Species sensitivity to forest fragmentation varies latitudinally, peaking in the tropics. A prominent explanation for this pattern is that historical landscape disturbance at higher latitudes has removed fragmentation-sensitive species or promoted the evolution of more resilient survivors. However, it is unclear whether this so-called extinction filter is the dominant driver of geographic variation in fragmentation sensitivity, particularly because climatic factors may also cause latitudinal gradients in dispersal ability, a key trait mediating sensitivity to habitat fragmentation. Here we combine field survey data with a morphological proxy for avian dispersal ability (hand-wing index) to assess responses to forest fragmentation in 1,034 bird species worldwide. We find that fragmentation sensitivity is strongly predicted by dispersal limitation and that other factors-latitude, body mass and historical disturbance events-have relatively limited explanatory power after accounting for species differences in dispersal. We also show that variation in dispersal ability is only weakly predicted by historical disturbance and more strongly associated with intra-annual temperature fluctuations (seasonality). Our results suggest that climatic factors play a dominant role in driving global variation in the impacts of forest fragmentation, emphasizing the need for more nuanced environmental policies that take into account local context and associated species traits.

Working Alone and/or in Remote Locations: Opportunities to Prevent the Risk of Fatality From Cardiovascular Events in Oil and Gas Extraction Workers.

OBJECTIVE: The aim of the study is to explore personal and work factors related to fatal cardiac events among oil and gas extraction (OGE) workers. METHODS: The National Institute for Occupational Safety and Health Fatalities in Oil and Gas Extraction database was reviewed to identify fatal cardiac events among OGE workers from 2014 through 2019. A case series design was used to review case files, provide descriptive statistics, and summarize the findings. RESULTS: There were 75 fatalities identified, including 55 (73%) with sufficient information for review. Of the 55 workers, 18 (33%) worked alone. Thirty-six fatal cardiac events (66%) were unwitnessed by a coworker. Toxicology findings suggested some possible exposures to hydrogen sulfide or hydrocarbon gases or vapors. Missing data were common. CONCLUSIONS: This study identified the need for cardiovascular disease prevention and treatment, emergency preparedness, lone worker programs, medical screening, and enhanced exposure control in the OGE industry.

Electrifying New York City Ride-Hailing fleets: An examination of the need for public fast charging.

This report assesses the scale of public fast charging needed to electrify approximately 20,000 vehicles across the yellow cab and for-hire segments in New York City. The analysis considers real-world trip data in conjunction with driver home locations, overnight charging access rates, driver schedules, and more. Outcomes indicate that the existing charging network in New York City is not adequate even in the most optimistic scenario; 1,054 150-kW ports are required when 15% of drivers have access to overnight charging, whereas 367 150-kW ports are needed when 100% of drivers have access. Results also indicate that although charging is demanded in areas nearby high trip demand, fast charging ports are also demanded in areas near driver residences as a supplement for home charging in scenarios with limited overnight charging access. These findings motivate investment into both overnight charging and public fast charging to meet the charging demands of ride-hailing fleets.

Vertical stratification of insect abundance and species richness in an Amazonian tropical forest.

Tropical forests are among the most biodiverse biomes on the planet. Nevertheless, quantifying the abundance and species richness within megadiverse groups is a significant challenge. We designed a study to address this challenge by documenting the variability of the insect fauna across a vertical canopy gradient in a Central Amazonian tropical forest. Insects were sampled over two weeks using 6-m Gressitt-style Malaise traps set at five heights (0 m-32 m-8 m intervals) on a metal tower in a tropical forest north of Manaus, Brazil. The traps contained 37,778 specimens of 18 orders of insects. Using simulation approaches and nonparametric analyses, we interpreted the abundance and richness of insects along this gradient. Diptera, Hymenoptera, and Coleoptera had their greatest abundance at the ground level, whereas Lepidoptera and Hemiptera were more abundant in the upper levels of the canopy. We identified species of 38 of the 56 families of Diptera, finding that 527 out of 856 species (61.6%) were not sampled at the ground level. Mycetophilidae, Tipulidae, and Phoridae were significantly more diverse and/or abundant at the ground level, while Tachinidae, Dolichopodidae, and Lauxaniidae were more diverse or abundant at upper levels. Our study suggests the need for a careful discussion of strategies of tropical forest conservation based on a much more complete understanding of the three-dimensional distribution of its insect diversity.

SMAP-HydroBlocks, a 30-m satellite-based soil moisture dataset for the conterminous US.

Soil moisture plays a key role in controlling land-atmosphere interactions, with implications for water resources, agriculture, climate, and ecosystem dynamics. Although soil moisture varies strongly across the landscape, current monitoring capabilities are limited to coarse-scale satellite retrievals and a few regional in-situ networks. Here, we introduce SMAP-HydroBlocks (SMAP-HB), a high-resolution satellite-based surface soil moisture dataset at an unprecedented 30-m resolution (2015-2019) across the conterminous United States. SMAP-HB was produced by using a scalable cluster-based merging scheme that combines high-resolution land surface modeling, radiative transfer modeling, machine learning, SMAP satellite microwave data, and in-situ observations. We evaluated the resulting dataset over 1,192 observational sites. SMAP-HB performed substantially better than the current state-of-the-art SMAP products, showing a median temporal correlation of 0.73 ± 0.13 and a median Kling-Gupta Efficiency of 0.52 ± 0.20. The largest benefit of SMAP-HB is, however, the high spatial detail and improved representation of the soil moisture spatial variability and spatial accuracy with respect to SMAP products. The SMAP-HB dataset is available via zenodo and at https://waterai.earth/smaphb .

Improving Delivery of Care through Standardized Monitoring in Children with Eosinophilic Esophagitis.

INTRODUCTION: Eosinophilic esophagitis (EoE) is a chronic, antigen-driven disorder for which endoscopic monitoring and multidisciplinary care are recommended to achieve histologic remission. The EoE team at our large academic center developed a quality improvement (QI) initiative aimed to reduce variability in monitoring. This QI project focused on completing 3 process metrics within 6 months of diagnosis: (1) outpatient follow-up with a gastroenterologist; (2) referral to an allergist; and (3) Follow-up esophagogastroduodenoscopy (EGD). METHODS: In January 2015, our QI team developed a registry of newly diagnosed EoE patients and maintained ongoing, weekly tracking of the process measures. Interventions to increase the completion of the process metrics included educational sessions, proactive reminders to providers, and targeted communications with patient families. Missed opportunities were evaluated by more in-depth chart review and categorized as provider- or patient-driven. RESULTS: We tracked 6-month process metrics from 2015 through 2018. During this interval, follow-up visit rates in GI improved from 77% to 86%, and the percentage of referrals placed to allergy increased from 65% to 77%. The percentage of patients completing a repeat EGD improved from 33% to 61%. Among patients without a repeated EGD, nearly 70% of those missed opportunities were provider-driven. CONCLUSIONS: In patients newly diagnosed with EoE, QI interventions, including patient registry development, implementation of a local standard of care, and creating a patient tracking system, improved adherence with national EoE monitoring guidelines.

Satellite Flood Inundation Assessment and Forecast Using SMAP and Landsat.

The capability and synergistic use of multisource satellite observations for flood monitoring and forecasts is crucial for improving disaster preparedness and mitigation. Here, surface fractional water cover (FW) retrievals derived from Soil Moisture Active Passive (SMAP) L-band (1.4 GHz) brightness temperatures were used for flood assessment over southeast Africa during the Cyclone Idai event. We then focused on five subcatchments of the Pungwe basin and developed a machine learning based approach with the support of Google Earth Engine for daily (24-h) forecasting of FW and 30-m inundation downscaling and mapping. The Classification and Regression Trees model was selected and trained using retrievals derived from SMAP and Landsat coupled with rainfall forecasts from the NOAA Global Forecast System. Independent validation showed that FW predictions over randomly selected dates are highly correlated (R = 0.87) with the Landsat observations. The forecast results captured the flood temporal dynamics from the Idai event; and the associated 30-m downscaling results showed inundation spatial patterns consistent with independent satellite synthetic aperture radar observations. The data-driven approach provides new capacity for flood monitoring and forecasts leveraging synergistic satellite observations and big data analysis, which is particularly valuable for data sparse regions.

Impact of remote prenatal education on program participation and breastfeeding of women in rural and remote Indigenous communities.

BACKGROUND: First Nations (FN) women have a higher risk of diabetes than non-FN women in Canada. Prenatal education and breastfeeding may reduce the risk of diabetes in mothers and offspring. The rates of breastfeeding initiation and participation in the prenatal program are low in FN communities. METHODS: A prenatal educational website, social media-assisted prenatal chat groups and community support teams were developed in three rural or remote FN communities in Manitoba. The rates of participation of pregnant women in prenatal programs and breastfeeding initiation were compared before and after the start of the remote prenatal education program within 2014-2017. FINDINGS: The participation rate of FN pregnant women in rural or remote communities in the prenatal program and breastfeeding initiation during 1-year after the start of the community-based remote prenatal education program were significantly increased compared to that during 1-year before the start of the program (54% versus 36% for the participation rate, 50% versus 34% for breastfeeding initiation, p < 0·001). Availability of high-speed Wi-Fi and/or postpartum supporting team were associated with favorite study outcomes. Positive feedback on the remote prenatal education was received from participants. INTERPRETATION: The findings suggest that remote prenatal education is feasible and effective for improving the breastfeeding rate and engaging pregnant women to participate in the prenatal program in rural or remote FN communities. The remote prenatal education remained active during COVID-19 in the participating communities, which suggests an advantage to expand remote prenatal education in other Indigenous communities. FUNDING: Canadian Institutes of Health Research, the Lawson Foundation and University of Manitoba.

A new vector-based global river network dataset accounting for variable drainage density.

Spatial variability of river network drainage density (Dd) is a key feature of river systems, yet few existing global hydrography datasets have properly accounted for it. Here, we present a new vector-based global hydrography that reasonably estimates the spatial variability of Dd worldwide. It is built by delineating channels from the latest 90-m Multi-Error-Removed Improved Terrain (MERIT) digital elevation model and flow direction/accumulation. A machine learning approach is developed to estimate Dd based on the global watershed-level climatic, topographic, hydrologic, and geologic conditions, where relationships between hydroclimate factors and Dd are trained using the high-quality National Hydrography Dataset Plus (NHDPlusV2) data. By benchmarking our dataset against HydroSHEDS and several regional hydrography datasets, we show the new river flowlines are in much better agreement with Landsat-derived centerlines, and improved Dd patterns of river networks (totaling ~75 million kilometers in length) are obtained. Basins and estimates of intermittent stream fraction are also delineated to support water resources management. This new dataset (MERIT Hydro-Vector) should enable full global modeling of river system processes at fine spatial resolutions.

The Coexistence of Carpal Tunnel Syndrome in Workers With Trigger Digit.

Background: The objective of this study was to investigate the prevalence of carpal tunnel syndrome (CTS) in workers with trigger digit. There are few cross-sectional studies that assess this relationship. Methods: A baseline examination of 1216 workers from 17 diverse manufacturing facilities was conducted. Worker demographics, medical history, and symptoms of trigger digit were assessed. Age, sex, and body mass index were obtained. Biomechanical factors were individually measured using the Strain Index (SI). Prevalence was assessed with univariate and multivariate logistic regression. Results: Unadjusted prevalence of trigger digit was 12.0%, and among those workers, there was an unadjusted CTS prevalence of 26.7%. The adjusted multivariate model found an odds ratio (OR) of CTS of 1.56 (95% confidence interval [CI], 1.03-2.36) among the workers with trigger digit. The ORs of CTS for SI (OR = 1.53 [95% CI, 1.04-2.23]), age (OR = 1.03 [95% CI, 1.01-1.04]), and current smoking (OR = 1.76 [95% CI, 1.12-2.75]) were also significant. Sex and diabetes were not statistically significant covariates. Conclusion: The prevalence of CTS is higher among workers with trigger digit.

PPDIST, global 0.1° daily and 3-hourly precipitation probability distribution climatologies for 1979-2018.

We introduce the Precipitation Probability DISTribution (PPDIST) dataset, a collection of global high-resolution (0.1°) observation-based climatologies (1979-2018) of the occurrence and peak intensity of precipitation (P) at daily and 3-hourly time-scales. The climatologies were produced using neural networks trained with daily P observations from 93,138 gauges and hourly P observations (resampled to 3-hourly) from 11,881 gauges worldwide. Mean validation coefficient of determination (R2) values ranged from 0.76 to 0.80 for the daily P occurrence indices, and from 0.44 to 0.84 for the daily peak P intensity indices. The neural networks performed significantly better than current state-of-the-art reanalysis (ERA5) and satellite (IMERG) products for all P indices. Using a 0.1 mm 3 h-1 threshold, P was estimated to occur 12.2%, 7.4%, and 14.3% of the time, on average, over the global, land, and ocean domains, respectively. The highest P intensities were found over parts of Central America, India, and Southeast Asia, along the western equatorial coast of Africa, and in the intertropical convergence zone. The PPDIST dataset is available via www.gloh2o.org/ppdist .

What can we learn from wildlife sightings during the COVID-19 global shutdown?

During the worldwide shutdown in response to the COVID-19 pandemic, many reports emerged of urban wildlife sightings. While these images garnered public interest and declarations of wildlife reclaiming cities, it is unclear whether wildlife truly reoccupied urban areas or whether there were simply increased detections of urban wildlife during this time. Here, we detail key questions and needs for monitoring wildlife during the COVID-19 shutdown and then link these with future needs and actions with the intent of improving conservation within urban ecosystems. We discuss the tools ecologists and conservation scientists can use to safely and effectively study urban wildlife during the shutdown. With a coordinated, multicity effort, researchers and community scientists can rigorously investigate the responses of wildlife to changes in human activities, which can help us address long-standing questions in urban ecology, inspire conservation of wildlife, and inform the design of sustainable cities.

Publisher Correction: Present and future Köppen-Geiger climate classification maps at 1-km resolution.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Metabolic Syndrome in Commercial Truck Drivers: Prevalence, Associated Factors, and Comparison With the General Population.

INTRODUCTION: Commercial motor vehicle drivers, such as truck drivers, experience unique health, lifestyle, and occupational challenges directly associated with their profession. METHODS: All participants in this multistate cross-sectional study completed questionnaire measurements. Participants were categorized with metabolic syndrome (MetS) if they had at least three of the five modified criteria used in the joint scientific statement on metabolic syndrome. RESULTS: Overall MetS prevalence was 52.4% (n = 428) of the 817 participants. Prevalence of MetS criteria were waist circumference (n = 634, 77.0%), low HDL cholesterol (n = 580, 71.0%), elevated triglycerides (n = 552, 67.6%), elevated blood pressure (n = 175, 21.2%), and elevated hemoglobin A1c (n = 97, 11.9%). Truck drivers were 2.7 times more likely to have MetS compared to the general working population. CONCLUSION: Truck drivers in the United States have a high prevalence of MetS compared to the general working population.

The importance of street trees to urban avifauna.

Street trees are public resources planted in a municipality's right-of-way and are a considerable component of urban forests throughout the world. Street trees provide numerous benefits to people. However, many metropolitan areas have a poor understanding of the value of street trees to wildlife, which presents a gap in our knowledge of conservation in urban ecosystems. Greater Los Angeles (LA) is a global city harboring one of the most diverse and extensive urban forests on the planet. The vast majority of the urban forest is nonnative in geographic origin, planted throughout LA following the influx of irrigated water in the early 1900s. In addition to its extensive urban forest, LA is home to a high diversity of birds, which utilize the metropolis throughout the annual cycle. The cover of the urban forest, and likely street trees, varies dramatically across a socioeconomic gradient. However, it is unknown how this variability influences avian communities. To understand the importance of street trees to urban avifauna, we documented foraging behavior by birds on native and nonnative street trees across a socioeconomic gradient throughout LA. Affluent communities harbored a unique composition of street trees, including denser and larger trees than lower-income communities, which in turn, attracted nearly five times the density of feeding birds. Foraging birds strongly preferred two native street-tree species as feeding substrates, the coast live oak (Quercus agrifolia) and the California sycamore (Platanus racemosa), and a handful of nonnative tree species, including the Chinese elm (Ulmus parvifolia), the carrotwood (Cupaniopsis anacardioides), and the southern live oak (Quercus virginiana), in greater proportion than their availability throughout the cityscape (two to three times their availability). Eighty-three percent of street-tree species (n = 108, total) were used in a lower proportion than their availability by feeding birds, and nearly all were nonnative in origin. Our findings highlight the positive influence of street trees on urban avifauna. In particular, our results suggest that improved street-tree management in lower-income communities would likely positively benefit birds. Further, our study provides support for the high value of native street-tree species and select nonnative species as important habitat for feeding birds.

Effect of Structural Uncertainty in Passive Microwave Soil Moisture Retrieval Algorithm.

Passive microwave sensors use a radiative transfer model (RTM) to retrieve soil moisture (SM) using brightness temperatures (TB) at low microwave frequencies. Vegetation optical depth (VOD) is a key input to the RTM. Retrieval algorithms can analytically invert the RTM using dual-polarized TB measurements to retrieve the VOD and SM concurrently. Algorithms in this regard typically use the τ-ω types of models, which consist of two third-order polynomial equations and, thus, can have multiple solutions. Through this work, we find that uncertainty occurs due to the structural indeterminacy that is inherent in all τ-ω types of models in passive microwave SM retrieval algorithms. In the process, a new analytical solution for concurrent VOD and SM retrieval is presented, along with two widely used existing analytical solutions. All three solutions are applied to a fixed framework of RTM to retrieve VOD and SM on a global scale, using X-band Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) TB data. Results indicate that, with structural uncertainty, there ensues a noticeable impact on the VOD and SM retrievals. In an era where the sensitivity of retrieval algorithms is still being researched, we believe the structural indeterminacy of RTM identified here would contribute to uncertainty in the soil moisture retrievals.

Support for the habitat amount hypothesis from a global synthesis of species density studies.

Decades of research suggest that species richness depends on spatial characteristics of habitat patches, especially their size and isolation. In contrast, the habitat amount hypothesis predicts that (1) species richness in plots of fixed size (species density) is more strongly and positively related to the amount of habitat around the plot than to patch size or isolation; (2) habitat amount better predicts species density than patch size and isolation combined, (3) there is no effect of habitat fragmentation per se on species density and (4) patch size and isolation effects do not become stronger with declining habitat amount. Data on eight taxonomic groups from 35 studies around the world support these predictions. Conserving species density requires minimising habitat loss, irrespective of the configuration of the patches in which that habitat is contained.

Extinction filters mediate the global effects of habitat fragmentation on animals.

Habitat loss is the primary driver of biodiversity decline worldwide, but the effects of fragmentation (the spatial arrangement of remaining habitat) are debated. We tested the hypothesis that forest fragmentation sensitivity-affected by avoidance of habitat edges-should be driven by historical exposure to, and therefore species' evolutionary responses to disturbance. Using a database containing 73 datasets collected worldwide (encompassing 4489 animal species), we found that the proportion of fragmentation-sensitive species was nearly three times as high in regions with low rates of historical disturbance compared with regions with high rates of disturbance (i.e., fires, glaciation, hurricanes, and deforestation). These disturbances coincide with a latitudinal gradient in which sensitivity increases sixfold at low versus high latitudes. We conclude that conservation efforts to limit edges created by fragmentation will be most important in the world's tropical forests.