8 research outputs found

    Blood concentrations of 50 elements in Eagle owl (Bubo bubo) at different contamination scenarios and related effects on plasma vitamin levels

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    Some metals and metalloids (e.g. Pb, Hg, Cd and As) are well-known for their bioaccumulation capacity and their toxic effects on birds, but concerns on other minor elements and rare earth elements (ME and REE) are growing due to their intensive use in modern technology and potential toxicity. Vitamins and carotenoids play essential roles in nestling growth and proper development, and are known to be affected by the metals classically considered as toxic. However, we are unaware of any attempts to evaluate the exposure to 50 elements and related effects in plasma vitamins and carotenoids in raptor species. The main goals of this study are: (i) to assess the exposure to 50 elements (i.e. classic toxic elements, trace elements, REE and ME) in nestling Eagle owls (Bubo bubo) inhabiting three differently polluted environments (mining, industrial and control areas) in southeastern Spain, and (ii) to evaluate how element exposure affects plasma vitamin and carotenoid levels, hematocrit and body measurements (mass and wing length) of the individuals. Our results show that local contamination in the mining area contributes to increased blood concentrations of Pb, As and Tl in nestlings, while diet differences between control and mining/industrial areas may account for the different levels of Mn, Zn, and Sr in blood, and lutein in plasma. Plasma tocopherol levels were increased in the mining-impacted environment, which may be a mechanism of protection to prevent toxic element-related oxidative stress. Plasma α-tocopherol was enhanced by 20% at blood Pb concentrations ≄8 ng/ml, and nestlings exhibited up to 56% increase in α-tocopherol levels when blood Pb concentrations reached 170 ng/ml. Tocopherol seems to be a sensitive biomarker under an exposure to certain toxic elements (e.g. Pb, As, Tl).</p

    Connecting the data landscape of long-term ecological studies: The SPI-Birds data hub

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    The integration and synthesis of the data in different areas of science is drastically slowed and hindered by a lack of standards and networking programmes. Long-term studies of individually marked animals are not an exception. These studies are especially important as instrumental for understanding evolutionary and ecological processes in the wild. Furthermore, their number and global distribution provides a unique opportunity to assess the generality of patterns and to address broad-scale global issues (e.g. climate change). To solve data integration issues and enable a new scale of ecological and evolutionary research based on long-term studies of birds, we have created the SPI-Birds Network and Database (www.spibirds.org)\u2014a large-scale initiative that connects data from, and researchers working on, studies of wild populations of individually recognizable (usually ringed) birds. Within year and a half since the establishment, SPI-Birds has recruited over 120 members, and currently hosts data on almost 1.5 million individual birds collected in 80 populations over 2,000 cumulative years, and counting. SPI-Birds acts as a data hub and a catalogue of studied populations. It prevents data loss, secures easy data finding, use and integration and thus facilitates collaboration and synthesis. We provide community-derived data and meta-data standards and improve data integrity guided by the principles of Findable, Accessible, Interoperable and Reusable (FAIR), and aligned with the existing metadata languages (e.g. ecological meta-data language). The encouraging community involvement stems from SPI-Bird's decentralized approach: research groups retain full control over data use and their way of data management, while SPI-Birds creates tailored pipelines to convert each unique data format into a standard format. We outline the lessons learned, so that other communities (e.g. those working on other taxa) can adapt our successful model. Creating community-specific hubs (such as ours, COMADRE for animal demography, etc.) will aid much-needed large-scale ecological data integration

    Connecting the data landscape of long-term ecological studies : The SPI-Birds data hub

    Get PDF
    The integration and synthesis of the data in different areas of science is drastically slowed and hindered by a lack of standards and networking programmes. Long-term studies of individually marked animals are not an exception. These studies are especially important as instrumental for understanding evolutionary and ecological processes in the wild. Furthermore, their number and global distribution provides a unique opportunity to assess the generality of patterns and to address broad-scale global issues (e.g. climate change). To solve data integration issues and enable a new scale of ecological and evolutionary research based on long-term studies of birds, we have created the SPI-Birds Network and Database ()-a large-scale initiative that connects data from, and researchers working on, studies of wild populations of individually recognizable (usually ringed) birds. Within year and a half since the establishment, SPI-Birds has recruited over 120 members, and currently hosts data on almost 1.5 million individual birds collected in 80 populations over 2,000 cumulative years, and counting. SPI-Birds acts as a data hub and a catalogue of studied populations. It prevents data loss, secures easy data finding, use and integration and thus facilitates collaboration and synthesis. We provide community-derived data and meta-data standards and improve data integrity guided by the principles of Findable, Accessible, Interoperable and Reusable (FAIR), and aligned with the existing metadata languages (e.g. ecological meta-data language). The encouraging community involvement stems from SPI-Bird's decentralized approach: research groups retain full control over data use and their way of data management, while SPI-Birds creates tailored pipelines to convert each unique data format into a standard format. We outline the lessons learned, so that other communities (e.g. those working on other taxa) can adapt our successful model. Creating community-specific hubs (such as ours, COMADRE for animal demography, etc.) will aid much-needed large-scale ecological data integration.Peer reviewe
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