57 research outputs found

    Confronting the challenges of whale avoidance by large vessels to reduce collision risk: A quantitative approach

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    Disturbance of wildlife by human transportation infrastructure is ubiquitous. This type of human-wildlife conflict has the potential to negatively impact wildlife population growth rates, especially for at-risk species like large whales. While many whale populations are rebounding as a result of a moratorium on commercial whaling, increasing ship traffic constitutes a significant threat to whale conservation efforts in the form of ship-whale collisions (“ship strikes”). Ship strike avoidance is difficult because vessel operators can only see whales when they are breaking the surface of the water, or “available for detection,” and even then, they will only see them a fraction of the time (the “perception process”). We investigated the ability of ship operators to detect and actively avoid whales by quantifying two processes: the ability of vessel operators to ascertain the direction of travel of whales (Chapter 2), and the varying detection challenges faced by vessel operators as whales move through the “strike zone” (Chapter 3). In Chapter 2, we modeled the ability of vessel operators to congruously determine whale direction of travel as a function of ship-to-whale distance and the number of surfacings in a bout. We found that the probability of making a congruous DT assignment increased as surfacing bout length increased and as ship-to-whale distance decreased. We also modeled the time it took vessel operators to make a DT assignment after the first sighting of a whale, and found that the probability of making a DT assignment was around 0.5 after three minutes had passed. In Chapter 3, we modeled the probabilities of whales entering and exiting the upper portion of the water column where they are at risk of ship strike (the “strike zone”), as well as the availability probability. We found that whales are present and undetected in the strike zone far more frequently than they are available for detection, which has important consequences for ship strike avoidance protocols and regulations

    Confronting the Challenge of Whale Detection from Large Vessels

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    As a result of a moratorium on commercial whaling, most populations of large whales are increasing across the globe. However, concurrent growth in shipping means that lethal ship-whale collisions constitute a significant threat to whale conservation efforts. This study investigates the ability of ship operators to detect and avoid whales by quantifying the predictability of whale surfacing behaviors, which are the cues used to determine whale presence. Whale avoidance is challenging because whales spend most of their time underwater and thus unavailable to be detected (the “availability process”), but must be detected at sufficiently large distances (the “detection process”) to enact an effective avoidance maneuver.  We quantified one of the main characteristics of whale behavior that governs detectability – time breaking the surface – to create a novel model of whale surfacing patterns around ships while accounting for the detection process. We then estimated the frequency with which cues go undetected (i.e. whales break the surface but ship operators are unaware of them), as well as the frequency with which whales are present but unavailable for detection (i.e. below the surface of the water). This work will enable the prediction of close ship-whale encounters given different combinations of detected and/or missed cues at varying ship speeds. It will support ship operators’ avoidance efforts by quantifying the availability and detection processes in a way that facilitates the development of whale avoidance protocols

    Serum Iron Level is Associated with Time to Antibiotics in Cystic Fibrosis

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    Background: Serum levels of hepcidin‐25, a peptide hormone that reduces blood iron content, are elevated when patients with cystic fibrosis (CF) develop pulmonary exacerbation (PEx). Because hepcidin‐25 is unavailable as a clinical laboratory test, we questioned whether a one‐time serum iron level was associated with the subsequent number of days until PEx, as defined by the need to receive systemic antibiotics (ABX) for health deterioration. Methods: Clinical, biochemical, and microbiological parameters were simultaneously checked in 54 adults with CF. Charts were reviewed to determine when they first experienced a PEx after these parameters were assessed. Time to ABX was compared in subgroups with and without specific attributes. Multivariate linear regression was used to identify parameters that significantly explained variation in time to ABX. Results: In univariate analyses, time to ABX was significantly shorter in subjects with Aspergillus‐positive sputum cultures and CF‐related diabetes. Multivariate linear regression models demonstrated that shorter time to ABX was associated with younger age, lower serum iron level, and Aspergillus sputum culture positivity. Conclusions: Serum iron, age, and Aspergillus sputum culture positivity are factors associated with shorter time to subsequent PEx in CF adults

    Smoking is associated with the concurrent presence of multiple autoantibodies in rheumatoid arthritis rather than with anti-citrullinated protein antibodies per se:a multicenter cohort study

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    BACKGROUND: The contribution of smoking to rheumatoid arthritis (RA) is hypothesized to be mediated through formation of anti-citrullinated protein antibodies (ACPA). In RA, however, autoantibodies such as ACPA, rheumatoid factor (RF), and anti-carbamylated protein antibodies (anti-CarP) often occur together, and it is thus unclear whether smoking is specifically associated with some autoantibodies rather than others. We therefore investigated whether smoking is only associated with ACPA or with the presence of multiple RA-related autoantibodies. METHODS: A population-based Japanese cohort (n = 9575) was used to investigate the association of smoking with RF and anti-cyclic citrullinated peptide antibodies (anti-CCP2) in individuals without RA. Furthermore, RA patients fulfilling the 1987 criteria from three early arthritis cohorts from the Netherlands (n = 678), the United Kingdom (n = 761), and Sweden (n = 795) were used. Data on smoking, RF, anti-CCP2, and anti-CarP were available. A total score of autoantibodies was calculated, and odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated by logistic regression. RESULTS: In the population-based non-RA cohort, no association was found between smoking and one autoantibody (RF or anti-CCP2), but smoking was associated with double-autoantibody positivity (OR 2.95, 95% CI 1.32-6.58). In RA patients, there was no association between smoking and the presence of one autoantibody (OR 0.99, 95% CI 0.78-1.26), but smoking was associated with double-autoantibody positivity (OR 1.32, 95% CI 1.04-1.68) and triple-autoantibody positivity (OR 2.05, 95% CI 1.53-2.73). CONCLUSIONS: Smoking is associated with the concurrent presence of multiple RA-associated autoantibodies rather than just ACPA. This indicates that smoking is a risk factor for breaking tolerance to multiple autoantigens in RA

    Increased ice flow in Western Palmer Land linked to ocean melting

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    A decrease in the mass and volume of Western Palmer Land has raised the prospect that ice speed has increased in this marine-based sector of Antarctica. To assess this possibility, we measure ice velocity over 25 years using satellite imagery and an optimized modeling approach. More than 30 unnamed outlet glaciers drain the 800 km coastline of Western Palmer Land at speeds ranging from 0.5 to 2.5 m/d, interspersed with near-stagnant ice. Between 1992 and 2015, most of the outlet glaciers sped up by 0.2 to 0.3 m/d, leading to a 13% increase in ice flow and a 15 km3/yr increase in ice discharge across the sector as a whole. Speedup is greatest where glaciers are grounded more than 300 m below sea level, consistent with a loss of buttressing caused by ice shelf thinning in a region of shoaling warm circumpolar water

    Extensive Genomic Variation within Clonal Complexes of Neisseria meningitidis

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    Meningococcal disease is a widely distributed complex disease affecting all age categories. It can cause severe meningitis and septicemia, especially in unvaccinated infants and young children. The causative agent, Neisseria meningitidis (Nm), can be phenotypically and genetically differentiated into serogroups and sequence types (STs) and has a highly dynamic population structure. To obtain a deeper understanding of the epidemiology of Nm, we sequenced seven Nm genomes. Large-scale genomic analysis was conducted with these 7 Nm genomes, 27 additional Nm genomes from GenBank, and 4 other Neisseria genomes. We observed extensive homologous recombination in all gene functional categories among different Nm genomes. Homologous recombination is so frequent that it has resulted in numerous chimeric open reading frames, including genes in the capsule biosynthesis cluster and loci targeted by commercial vaccines. Our results reveal that, despite widespread use, evolutionary relationships inferred from the standard seven-gene multilocus sequence typing (MLST) method could not predict virulence gene content or strain phenotype. In fact, up to 28% of the virulence-associated genes could differ between strains of identical STs. Consistent with previous studies, we found that allelic recombination is also associated with alterations in antibiotic susceptibility. Overall, these findings emphasize the extensive genomic plasticity of Nm and the limitations of standard molecular methods to quantify this genotypic and phenotypic diversity

    Mass balance of the Greenland Ice Sheet from 1992 to 2018

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    In recent decades, the Greenland Ice Sheet has been a major contributor to global sea-level rise1,2, and it is expected to be so in the future3. Although increases in glacier flow4–6 and surface melting7–9 have been driven by oceanic10–12 and atmospheric13,14 warming, the degree and trajectory of today’s imbalance remain uncertain. Here we compare and combine 26 individual satellite measurements of changes in the ice sheet’s volume, flow and gravitational potential to produce a reconciled estimate of its mass balance. Although the ice sheet was close to a state of balance in the 1990s, annual losses have risen since then, peaking at 335 ± 62 billion tonnes per year in 2011. In all, Greenland lost 3,800 ± 339 billion tonnes of ice between 1992 and 2018, causing the mean sea level to rise by 10.6 ± 0.9 millimetres. Using three regional climate models, we show that reduced surface mass balance has driven 1,971 ± 555 billion tonnes (52%) of the ice loss owing to increased meltwater runoff. The remaining 1,827 ± 538 billion tonnes (48%) of ice loss was due to increased glacier discharge, which rose from 41 ± 37 billion tonnes per year in the 1990s to 87 ± 25 billion tonnes per year since then. Between 2013 and 2017, the total rate of ice loss slowed to 217 ± 32 billion tonnes per year, on average, as atmospheric circulation favoured cooler conditions15 and as ocean temperatures fell at the terminus of Jakobshavn IsbrĂŠ16. Cumulative ice losses from Greenland as a whole have been close to the IPCC’s predicted rates for their high-end climate warming scenario17, which forecast an additional 50 to 120 millimetres of global sea-level rise by 2100 when compared to their central estimate

    The James Webb Space Telescope Mission

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    Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least 4m4m. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the 6.5m6.5m James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

    GrassPlot - a database of multi-scale plant diversity in Palaearctic grasslands

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    GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001;... 1,000 m(2)) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database " sPlot". Its main aim is to facilitate studies on the scale-and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board

    TRY plant trait database – enhanced coverage and open access

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    Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
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