254 research outputs found

    18F-FDG-PET/CT in diagnosis of Q fever endocarditis

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    info:eu-repo/semantics/publishedVersio

    Model-Derived Dispersal Pathways from Multiple Source Populations Explain Variability of Invertebrate Larval Supply

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    Background: Predicting the spatial and temporal patterns of marine larval dispersal and supply is a challenging task due to the small size of the larvae and the variability of oceanographic processes. Addressing this problem requires the use of novel approaches capable of capturing the inherent variability in the mechanisms involved. Methodology/Principal Findings: In this study we test whether dispersal and connectivity patterns generated from a biophysical model of larval dispersal of the crab Carcinus maenas, along the west coast of the Iberian Peninsula, can predict the highly variable daily pattern of wind-driven larval supply to an estuary observed during the peak reproductive season (March–June) in 2006 and 2007. Cross-correlations between observed and predicted supply were significant (p,0.05) and strong, ranging from 0.34 to 0.81 at time lags of 26 to+5 d. Importantly, the model correctly predicted observed cross-shelf distributions (Pearson r = 0.82, p,0.001, and r = 0.79, p,0.01, in 2006 and 2007) and indicated that all supply events were comprised of larvae that had been retained within the inner shelf; larvae transported to the outer shelf and beyond never recruited. Estimated average dispersal distances ranged from 57 to 198 km and were only marginally affected by mortality. Conclusions/Significance: The high degree of predicted demographic connectivity over relatively large geographic scales is consistent with the lack of genetic structuring in C. maenas along the Iberian Peninsula. These findings indicate that the dynamic nature of larval dispersal can be captured by mechanistic biophysical models, which can be used to provid

    Expansion of oxygen minimum zones may reduce available habitat for tropical pelagic fishes

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    Climate model predictions1, 2 and observations3, 4 reveal regional declines in oceanic dissolved oxygen, which are probably influenced by global warming5. Studies indicate ongoing dissolved oxygen depletion and vertical expansion of the oxygen minimum zone (OMZ) in the tropical northeast Atlantic Ocean6, 7. OMZ shoaling may restrict the usable habitat of billfishes and tunas to a narrow surface layer8, 9. We report a decrease in the upper ocean layer exceeding 3.5 ml l−1 dissolved oxygen at a rate of ≤1 m yr−1 in the tropical northeast Atlantic (0–25° N, 12–30° W), amounting to an annual habitat loss of ~5.95×1013 m3, or 15% for the period 1960–2010. Habitat compression and associated potential habitat loss was validated using electronic tagging data from 47 blue marlin. This phenomenon increases vulnerability to surface fishing gear for billfishes and tunas8, 9, and may be associated with a 10–50% worldwide decline of pelagic predator diversity10. Further expansion of the Atlantic OMZ along with overfishing may threaten the sustainability of these valuable pelagic fisheries and marine ecosystems

    Contribution of Alaskan glaciers to sea level rise derived from satellite imagery

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    International audienceOver the last 50 years, retreating glaciers and ice caps (GIC) contributed 0.5 mm/yr to sea level rises (SLR), and one third is believed to originate from ice masses bordering the Gulf of Alaska. However, these estimates of ice wastage in Alaska are based on methods that measure a limited number of glaciers and extrapolate the results to estimate ice loss for the many thousands of others. How these methods capture the complex pattern of decadal elevation changes at the scale of individual glacier and mountain range is unclear. Here, combining a comprehensive glacier inventory with elevation changes derived from sequential digital elevation models (DEMs), we found that, between 1962 and 2006, Alaskan glaciers lost 41.9 ± 8.6 km**3/yr water equivalent (w.e.) and contributed 0.12±0.02 mm/yr to SLR. Our ice loss is 34% lower than previous estimates. Reasons for our lower values include the higher spatial resolution of our glacier inventory and the reduction of ice thinning under debris and at the glacier margins which were not resolved in earlier work. Estimates of mass loss from GIC in other mountain regions could be subject to similar revisions
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