26 research outputs found

    Flowering resources distract pollinators from crops: Model predictions from landscape simulations

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    Enhancing floral resources is a widely accepted strategy for supporting wild bees and promoting crop pollination. Planning effective enhancements can be informed with pollination service models, but these models should capture the behavioural and spatial dynamics of service-providing organisms. Model predictions, and hence management recommendations, are likely to be sensitive to these dynamics. We used two established models of pollinator foraging to investigate whether habitat enhancement improves crop visitation; whether this effect is influenced by pollinator foraging distance and landscape pattern; and whether behavioural detail improves model predictions. The more detailed central place foraging model better predicted variation in bee visitation observed between habitat types, because it includes optimized trade-offs between patch quality and distance. Both models performed well when predicting visitation rates across broader scales. Using real agricultural landscapes and simulating habitat enhancements, we show that additional floral resources can have diverging effects on predicted crop visitation. When only co-flowering resources were added, optimally foraging bees concentrated in enhancements to the detriment of crop pollination. For both models, adding nesting resources increased crop visitation. Finally, the marginal effect of enhancements was greater in simple landscapes. Synthesis and applications. Model results help to identify the conditions under which habitat enhancements are most likely to increase pollination services in agriculture. Three design principles for pollinator habitat enhancement emerge: (a) enhancing only flowers can diminish services by distracting pollinators away from crops, (b) providing nesting resources is more likely to increase bee populations and crop visitation and (c) the benefit of enhancements will be greatest in landscapes that do not already contain abundant habitat

    Finishing the euchromatic sequence of the human genome

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    The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

    Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

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    Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

    Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

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    IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

    Cropland heterogeneity drives frequency and intensity of pesticide use

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    Agricultural landscapes across the planet have replaced natural habitat with crop production that is less diverse at field and landscape scales. Loss of cropland heterogeneity can increase pest colonization rates and decrease predation rates, thereby exacerbating pest pressure and leading to increased use of pesticides. Linking landscape pattern, crop pest pressure, and pesticide use is emerging as critical step for understanding the benefits, and potential trade-offs, of diversified agriculture. We advance this work by exploring how cropland heterogeneity drives pesticide use, and whether this effect is modified by pesticide class (i.e. fungicide, herbicide or insecticide). We focus on a diverse growing region, California's Central Valley, and use spatial auto-regressive models to test for consistent class-based differences in the relationship between pesticide use and cropland heterogeneity (i.e. mean field size and landscape-level crop diversity). We find reduced pesticide use, in terms of both frequency and intensity of application, in diversified, spatially-heterogenous landscapes. Additionally, we see (a) more consistent responses of fungicides and insecticides to landscape pattern, (b) pesticide use increases as cropland becomes more homogenous with respect to crop identity, and (c) this effect is more consistent for perennial crops than annual crops. The modifying influence of pesticide class is largely consistent with expectations from ecological theory. Our results support increasing focus on whether enhancing the heterogeneity of the crop mosaic itself can benefit biodiversity, ecosystem services, and human well-being

    Global relationships between crop diversity and nutritional stability

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    Nutritional stability – a food system’s capacity to provide sufficient nutrients despite disturbance – is an important, yet challenging to measure outcome of diversified agriculture. Using 55 years of data across 184 countries, we assemble 22,000 bipartite crop-nutrient networks to quantify nutritional stability by simulating crop and nutrient loss in a country, and assess its relationship to crop diversity across regions, over time and between imports versus in country production. We find a positive, saturating relationship between crop diversity and nutritional stability across countries, but also show that over time nutritional stability remained stagnant or decreased in all regions except Asia. These results are attributable to diminishing returns on crop diversity, with recent gains in crop diversity among crops with fewer nutrients, or with nutrients already in a country’s food system. Finally, imports are positively associated with crop diversity and nutritional stability, indicating that many countries’ nutritional stability is market exposed

    Ecological traits interact with landscape context to determine bees' pesticide risk

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    Widespread contamination of ecosystems with pesticides threatens non-target organisms. However, the extent to which life-history traits affect pesticide exposure and resulting risk in different landscape contexts remains poorly understood. We address this for bees across an agricultural land-use gradient based on pesticide assays of pollen and nectar collected by Apis mellifera, Bombus terrestris and Osmia bicornis, representing extensive, intermediate and limited foraging traits. We found that extensive foragers (A. mellifera) experienced the highest pesticide risk-additive toxicity-weighted concentrations. However, only intermediate (B. terrestris) and limited foragers (O. bicornis) responded to landscape context-experiencing lower pesticide risk with less agricultural land. Pesticide risk correlated among bee species and between food sources and was greatest in A. mellifera-collected pollen-useful information for future postapproval pesticide monitoring. We provide foraging trait- and landscape-dependent information on the occurrence, concentration and identity of pesticides that bees encounter to estimate pesticide risk, which is necessary for more realistic risk assessment and essential information for tracking policy goals to reduce pesticide risk

    Mapping connectivity and conservation opportunity on agricultural lands across the conterminous United States

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    Depending on management practices, agricultural lands can either pose substantial barriers to species movement or can support landscape connectivity by linking areas of high-quality habitat. Balancing connectivity and sustainable food production on agricultural lands is critical to conservation in the conterminous United States (CONUS) where agriculture makes up close to half of total land area. However, limited guidance exists on where to target conservation resources to maximize benefits for native species and food security. To quantify the potential contribution of agricultural lands to the movement of organisms, we developed a novel method for estimating agricultural management intensity (based on remotely sensed temporal variation in vegetation cover) and incorporated these estimates into a CONUS-wide model of ecological flow connectivity. We combined our connectivity results with data on the productivity, versatility, and resilience of agricultural lands (PVR) to identify conservation opportunities that support both biodiversity and food production. The highest levels of connectivity on agricultural lands occurred on relatively unmodified rangelands and on cropland and pasture surrounded by large amounts of natural land cover. Mapping connectivity and PVR across CONUS revealed 10.2 Mha of agricultural lands (2.7 %) with high value for both connectivity and food production, as well as large amounts of agricultural land (>140 Mha in total) with high value for either cultivation or supporting biodiversity. Drawing on these findings, we provide recommendations on the types of conservation approaches most suitable for a given agricultural system and link these recommendations to specific government incentive programs
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