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  • Authors: 3rd World Seabird Conference 2021; Power, Andrew;

    Abstract: The Northern Gannet Morus bossanus is an avian sentinel; the largest breeding seabird in Ireland and an obligate piscivore. Gannet eggs were collected from two island colonies off the east coast of Ireland, approximately 150km from each other, in locations with divergent history of industrialization (n = 10-20). Levels of potentially harmful contaminants including Polychlorinated biphenyls (PCBs), Polybrominated diphenyl ethers (PBDEs), Organochlorine pesticides (OCs), heavy metals and mercury were measured and differences of contaminant concentrations between different colonies compared. This is the first such study of contaminant levels in Gannet, or in any seabird egg in Ireland. Stable isotopes of carbon (d13C) and nitrogen (d15N) were measured in each egg to understand the influence of diet in contaminant levels detected. Significantly higher levels of PCBs, PBDEs and mercury were detected near Dublin (Ireland's industrialized capital city and location of its largest port) compared to Wexford. No differences were observed in levels of OCs and heavy metals between the two colonies. Stable isotope analysis demonstrated that Gannets in both locations occupy the same dietary niche excluding a difference in diet as the driver of differing contaminant levels in the two feeding areas. Though Gannets travel significant distances when foraging for food (~200km) tracking studies have shown that Gannets colonies maintain exclusive feeding areas with little overlap between neighbouring colonies. Differences between colonies within the feeding range of Gannets can therefore be detected despite Gannet's high dispersal ability. These results are in concurrence with elevated levels of contaminants in lower trophic level organisms that have been found in Dublin Bay compared to the rest of Ireland, indicating potential for Gannets as a higher trophic level indicator - though variability in their diet, including feeding on fishing discard, may lead to unacceptable levels of variability for an indicator species. Authors: Andrew Power��, Philip White��, Brendan McHugh��, Sinead Murphy��, Simon Berrow��, Moira Schlingermann��, Stephen Newton��, Linda O'Hea��, Brian Boyle��, Marissa Tannian��, Denis Crowley��, Evin McGovern��, Ian O'Connor�� ��Galway Mayo Institute of Technology, ��Marine Institute, ��BirdWatch Ireland

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    Authors: Richard, Benoit; Dupouey, Jean-Luc; Corcket, Emmanuel; Alard, Didier; +29 Authors

    Datasets for the paper Richard, B. et al. The climatic debt is growing in the understory of temperate forests: stand characteristics matter. Global Ecology and Biogeography. The files provided here contain the data for CTI and contributing factors in lags used in analyses.

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    ZENODO
    Dataset . 2021
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    ZENODO
    Dataset . 2021
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    Smithsonian figshare
    Dataset . 2021
    License: CC BY
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
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      ZENODO
      Dataset . 2021
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      Smithsonian figshare
      Dataset . 2021
      License: CC BY
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    Authors: Segovia-Martin, Jose;

    These data are part of a data portal that accompanies the special issue ‘Climate change adaptation needs a science of culture,’ published in Philosophical Transactions of the Royal Society B in 2023. To access the data portal, please visit: https://doi.org/10.5061/dryad.bnzs7h4h4. This code represents a computational model investigating the dynamics of coupled and decoupled resource use and efficiency gains. It can be used to simulate the effects of exploration-exploitation strategies on efficiency, consumption and sustainability, considering different levels of direct and indirect rebound effects. The model simulates a population of agents who make decisions on whether to explore or exploit a natural resource. These agents become more efficient over time based on their chosen strategy, affecting resource consumption. Different scenarios are considered, including various rebound effects, which influence how efficiency gains impact resource use. The key elements of the model include agents' uncertainty about the efficiency of their actions, the operationalization of efficiency as a reward, and the calculation of resource consumption based on efficiency gains and rebound effects. The model provides insights into how agents' decisions and resource use evolve over time under different conditions. This computational framework offers a valuable tool for exploring the complex dynamics of resource consumption and management in the face of environmental challenges. It can be applied to gain a deeper understanding of the Jevons Paradox and its implications for sustainable resource use. This computational model simulates the dynamics of exploration and exploitation strategies within a population of agents. These agents make decisions on whether to explore new solutions or exploit existing ones, with a focus on maximizing efficiency. The model employs a N-armed bandit problem approach, where agents select actions to maximize efficiency gains. Efficiency is operationalized as a reward, and agents use sample means to estimate expected efficiency. A balance between exploration and exploitation is maintained through a probability-based algorithm. The code also encompasses resource domains, representing different resources and their dynamics, along with computations of resource consumption, existing resources, and sustainability indices. The simulations consider various parameter combinations to examine the model's behavior. Overall, the code serves as a tool for studying the interplay between exploration, exploitation, efficiency, and resource consumption within a population of agents across different scenarios, making it valuable for investigating the effects of rebound effects on resource consumption and sustainability. The simulations run a comprehensive set of parameter combinations to explore the model's behavior thoroughly. # Code from: Efficiency traps beyond the climate crisis: Exploration-exploitation tradeoffs and rebound effects. Python scripts to run the model, as described in: Segovia-Martin J, Creutzig F, Winters J. 2023 Efficiency traps beyond the climate crisis: exploration–exploitation tradeoffs and rebound effects. Phil. Trans. R. Soc. B 378: 20220405. https://doi.org/10.1098/rstb.2022.0405 The code and supplementary materials are all freely accessible at the following link: [https://github.com/School-of-Collective-Intelligence/Jevons-Paradox-and-Cultural-Evolution](https://github.com/School-of-Collective-Intelligence/Jevons-Paradox-and-Cultural-Evolution) The simulator can be accessed via the following links: [https://jevons-collectiveintelligence.pythonanywhere.com/](https://jevons-collectiveintelligence.pythonanywhere.com/) or [https://jsegoviamartin.pythonanywhere.com/](https://jsegoviamartin.pythonanywhere.com/) The DOI of this Dryad repository: [https://doi.org/10.5061/dryad.qjq2bvqnk](https://doi.org/10.5061/dryad.qjq2bvqnk) ##

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    ZENODO
    Dataset . 2023
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    DRYAD
    Dataset . 2023
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      ZENODO
      Dataset . 2023
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      DRYAD
      Dataset . 2023
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    Authors: Ziehn, Tilo; Dix, Martin; Mackallah, Chloe; Chamberlain, Matthew; +4 Authors

    Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.DAMIP.CSIRO.ACCESS-ESM1-5.hist-nat' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The Australian Community Climate and Earth System Simulator Earth System Model Version 1.5 climate model, released in 2019, includes the following components: aerosol: CLASSIC (v1.0), atmos: HadGAM2 (r1.1, N96; 192 x 145 longitude/latitude; 38 levels; top level 39255 m), land: CABLE2.4, ocean: ACCESS-OM2 (MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m), ocnBgchem: WOMBAT (same grid as ocean), seaIce: CICE4.1 (same grid as ocean). The model was run by the Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia (CSIRO) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.

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    World Data Center for Climate
    Dataset . 2023
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    World Data Center for Climate
    Dataset . 2023
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    Data sources: Datacite
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    World Data Center for Climate
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      World Data Center for Climate
      Dataset . 2023
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      Data sources: Datacite
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      World Data Center for Climate
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      World Data Center for Climate
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Lefevre, Dominique; Libes, Maurice; Mallarino, Didier; Bernardet, Karim; +1 Authors

    EMSO-Western Ligurian Site (European Multidisciplinary See floor Observatory and water column, Western Ligurian Site) is a second generation permanent submarine observatory deployed offshore of Toulon, France, as a follow up of the pioneering ANTARES neutrino telescope located nearby. This submarine network is part of KM3NeT (https://www.km3net.org/) which has a modular topology designed to connect up to 120 neutrino detection units, i.e. ten times more than ANTARES. The Earth and Sea Science (ESS) instrumentation connected to KM3NeT is based on two complementary components: an Instrumented Interface Module (MII) and an autonomous mooring line (ALBATROSS). The Module Interface Instrumented "MII" was deployed in May 2019 and cabled to the MEUST Node#1. Node#1 is cabled to the shore via the KM3NeT cable. The MII provides data for temperature, conductivity/salinity, pressure, particles proxy (deduced from beam attenuation measured with a CSTAR transmissiometer). The MII collects data through an acoustic link from the instrumented mooring line ALBATROSS (https://doi.org/10.17882/74513) deployed at a distance of 2-3 kilometers. These data are being transferred daily for near real time visualisation.

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    https://dx.doi.org/10.17882/75...
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    SEANOE
    Dataset . 2023
    License: CC BY
    Data sources: SEANOE
    B2FIND
    Dataset . 2022
    Data sources: B2FIND
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      https://dx.doi.org/10.17882/75...
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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      SEANOE
      Dataset . 2023
      License: CC BY
      Data sources: SEANOE
      B2FIND
      Dataset . 2022
      Data sources: B2FIND
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  • Authors: Higgs, Carl; Liu, Shiqin; Boeing, Geoff; Arundel, Jonathan; +8 Authors

    Output data prepared for analysis of 25 diverse global cities by the Global Healthy and Sustainable City-Indicator Collaboration study, published in The Lancet Global Health Series on urban design, transport, and health. 2022. https://www.thelancet.com/series/urban-design-2022 Boeing, G. et al. (2022) ‘Using open data and open-source software to develop spatial indicators of urban design and transport features for achieving healthy and sustainable cities’, The Lancet Global Health, 10(6), pp. e907–e918. Available at: https://doi.org/10.1016/S2214-109X(22)00072-9. Data outputs were generated through use of the global-indicators software tool, designed for this study and available from: https://github.com/global-healthy-liveable-cities/global-indicators Further detail on the methods used is provided in the following publication: Liu, S., Higgs, C., Arundel, J., Boeing, G., Cerdera, N., Moctezuma, D., Cerin, E., Adlakha, D., Lowe, M. and Giles-Corti, B. (2021), A Generalized Framework for Measuring Pedestrian Accessibility around the World Using Open Data. Geogr Anal. https://doi.org/10.1111/gean.12290 The study made use of OpenStreetMap, Global Human Settlements and custom data, and is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/

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    Authors: Alon, Asaf; Cohen, Shabtai; Burlett, Regis; Hochberg, Uri; +6 Authors

    Survival and growth of woody species in the Mediterranean are mainly restricted by water availability. We tested the hypothesis that Mediterranean species acclimate their xylem vulnerability and osmotic potential along a precipitation gradient. We studied five predominant co-occurring Mediterranean species; Quercus calliprinos, Pistacia palaestina, Pistacia lentiscus, Rhamnus lycioides, and Phillyrea latifolia, over two summers at three sites. The driest of the sites is the distribution edge for all the five species. We measured key hydraulic and osmotic traits related to drought resistance, including resistance to embolism (Ψ50) and the seasonal dynamics of water and osmotic potentials. The leaf water potentials (Ψ1) of all species declined significantly along the summer, reaching significantly lower Ψl at the end of summer in the drier sites. Surprisingly, we did not find plasticity along the drought gradient in Ψ50 or osmotic potentials. This resulted in much narrower hydraulic safety margins (HSM) in the drier sites, where some species experienced significant embolism. Our analysis indicates that reduction in HSM to null values put Mediterranean species in embolism risk as they approach their hydraulic limit near the geographic dry edge of their distribution. The PLC curves and resistance to embolism were measured using the Cavitron. The pre-dawn and midday water potentials were measured using a pressure bomb. The C13 was measured with a 13C cavity ring-down analyzer. The osmotic potential was measured using an osmometer. All methods are described in Alon et al., Acclimation limits for embolism resistance and osmotic adjustment accompany the geographic dry edge of Mediterranean species. 2023. Functional Ecology Excel

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    ZENODO
    Dataset . 2023
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2023
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC 0
      Data sources: ZENODO
      DRYAD
      Dataset . 2023
      License: CC 0
      Data sources: Datacite
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    Authors: Behzad Rismanchi; Lu Aye; Sheikh Khaleduzzaman Shah;

    This dataset includes data from the validation of double U-tube borehole and seasonal solar thermal energy storage system TRNSYS models. The simulated transient temperatures at various points of the systems were compared with the measured ones. To quantify the agreement between each simulated and measured temperature of interest, mean bias error (MBE), root mean square error (RMSE) and correlation coefficient (CC) were applied.

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    Mendeley Data
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    B2FIND
    Dataset . 2021
    Data sources: B2FIND
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      Mendeley Data
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      B2FIND
      Dataset . 2021
      Data sources: B2FIND
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    Authors: Zaake, Paul; Paul, Birthe K.; Marshall, Karen; Notenbaert, An; +4 Authors

    There is limited attention to impacts of climate change on pigs in Uganda by stakeholders, despite the potential vulnerability of pigs to climate change. Pigs are sensitive to heat-stress, as they do not have functioning sweat glands as other livestock species do, and have small lungs which reduces their ability to disseminate heat by panting. The objectives of the study were to i) determine the heat-stress status in pigs, ii) analyze factors influencing heat-stress, and iii) explore the heat-stress adaptation options in Lira District, Uganda. Lira was selected because of presence of both rural & urban areas and expected heat stress throughout the year in the district. The data including household demographics, management systems, age, color, breeds, body/skin temperature, rectal temperature and others were collected from 104 households and 259 pigs during the hot months in Ojwina and Barr sub-counties- Lira district. We collected data on adaptation options during the four gender disaggregated focus group discussions. Weather data was collected during the time of administering the questionnaire, and it was complemented with data from Ngetta Meteorological Station, Lira. STATA, 14

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    Harvard Dataverse
    Dataset . 2020
    Data sources: Datacite
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    Research@WUR
    Dataset . 2020
    Data sources: Research@WUR
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      Harvard Dataverse
      Dataset . 2020
      Data sources: Datacite
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      Research@WUR
      Dataset . 2020
      Data sources: Research@WUR
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    Authors: Viviroli, Daniel; Kummu, Matti; Meybeck, Michel; Kallio, Marko; +1 Authors

    Water resources index W quantifies the potential dependence of the world's lowland areas on water resources originating in mountain areas upstream. The data cover the timeframe from the 1960s (1961–1970) to the 2040s (2041–2050) in decadal steps. Data for projections from the 2010s onwards are available for three scenario pathways (SSP1-RCP4.5, SSP2-RCP6.0, SSP3-RCP6.0) and show median results from 5 CMIP5 GCMs (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1‑M). The files are GeoTIFF formatted and in a regular raster of 5’×5’ (arc minutes in WGS 1984 coordinate system) The values of W can be classified using the following ranges: W ≤ -2 → Essential but vastly insufficient -2 < W < -1 → Essential but insufficient -1 ≤ W < 0 → Essential and sufficient W = 0 → No surplus from mountains 0 < W ≤ 1 → Supportive 1 < W < 2 → Minor W ≥ 2 → Negligible The values of W are rounded to four decimal places and limited to a range of -1110 to 9998. Values falling outside of that range are set to the nearest limit. he following flag values apply to W: -5555 indicates that there is no water balance surplus from the mountain area upstream, but a lowland water balance surplus; -6666 indicates that there is no water balance surplus from the mountain area upstream, and a lowland water balance deficit. Mountain areas and oceans are NODATA, large ice shields are omitted (Greenland: NODATA, Antarctica: not covered in extent). Mountain areas provide disproportionally high runoff in many parts of the world, and here we quantify for the first time their importance for water resources and food production from the viewpoint of the lowland areas downstream. The dataset maps the degree to which lowland areas potentially depend on runoff contributions from mountain areas (39% of land mass) between the 1960s and the 2040s.

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    ZENODO
    Dataset . 2020
    Data sources: ZENODO
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    ZENODO
    Dataset . 2020
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2020
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2020
      Data sources: ZENODO
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      ZENODO
      Dataset . 2020
      License: CC 0
      Data sources: ZENODO
      DRYAD
      Dataset . 2020
      License: CC 0
      Data sources: Datacite
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  • Authors: 3rd World Seabird Conference 2021; Power, Andrew;

    Abstract: The Northern Gannet Morus bossanus is an avian sentinel; the largest breeding seabird in Ireland and an obligate piscivore. Gannet eggs were collected from two island colonies off the east coast of Ireland, approximately 150km from each other, in locations with divergent history of industrialization (n = 10-20). Levels of potentially harmful contaminants including Polychlorinated biphenyls (PCBs), Polybrominated diphenyl ethers (PBDEs), Organochlorine pesticides (OCs), heavy metals and mercury were measured and differences of contaminant concentrations between different colonies compared. This is the first such study of contaminant levels in Gannet, or in any seabird egg in Ireland. Stable isotopes of carbon (d13C) and nitrogen (d15N) were measured in each egg to understand the influence of diet in contaminant levels detected. Significantly higher levels of PCBs, PBDEs and mercury were detected near Dublin (Ireland's industrialized capital city and location of its largest port) compared to Wexford. No differences were observed in levels of OCs and heavy metals between the two colonies. Stable isotope analysis demonstrated that Gannets in both locations occupy the same dietary niche excluding a difference in diet as the driver of differing contaminant levels in the two feeding areas. Though Gannets travel significant distances when foraging for food (~200km) tracking studies have shown that Gannets colonies maintain exclusive feeding areas with little overlap between neighbouring colonies. Differences between colonies within the feeding range of Gannets can therefore be detected despite Gannet's high dispersal ability. These results are in concurrence with elevated levels of contaminants in lower trophic level organisms that have been found in Dublin Bay compared to the rest of Ireland, indicating potential for Gannets as a higher trophic level indicator - though variability in their diet, including feeding on fishing discard, may lead to unacceptable levels of variability for an indicator species. Authors: Andrew Power��, Philip White��, Brendan McHugh��, Sinead Murphy��, Simon Berrow��, Moira Schlingermann��, Stephen Newton��, Linda O'Hea��, Brian Boyle��, Marissa Tannian��, Denis Crowley��, Evin McGovern��, Ian O'Connor�� ��Galway Mayo Institute of Technology, ��Marine Institute, ��BirdWatch Ireland

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    Authors: Richard, Benoit; Dupouey, Jean-Luc; Corcket, Emmanuel; Alard, Didier; +29 Authors

    Datasets for the paper Richard, B. et al. The climatic debt is growing in the understory of temperate forests: stand characteristics matter. Global Ecology and Biogeography. The files provided here contain the data for CTI and contributing factors in lags used in analyses.

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    Dataset . 2021
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    Dataset . 2021
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    Dataset . 2021
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    Dataset . 2021
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    ZENODO
    Dataset . 2021
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    ZENODO
    Dataset . 2021
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    ZENODO
    Dataset . 2021
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    Dataset . 2021
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    Dataset . 2021
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    Smithsonian figshare
    Dataset . 2021
    License: CC BY
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      Dataset . 2021
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      Dataset . 2021
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      Dataset . 2021
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      Data sources: Datacite
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      Dataset . 2021
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      Dataset . 2021
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      Data sources: Datacite
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      Dataset . 2021
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      Smithsonian figshare
      Dataset . 2021
      License: CC BY
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Segovia-Martin, Jose;

    These data are part of a data portal that accompanies the special issue ‘Climate change adaptation needs a science of culture,’ published in Philosophical Transactions of the Royal Society B in 2023. To access the data portal, please visit: https://doi.org/10.5061/dryad.bnzs7h4h4. This code represents a computational model investigating the dynamics of coupled and decoupled resource use and efficiency gains. It can be used to simulate the effects of exploration-exploitation strategies on efficiency, consumption and sustainability, considering different levels of direct and indirect rebound effects. The model simulates a population of agents who make decisions on whether to explore or exploit a natural resource. These agents become more efficient over time based on their chosen strategy, affecting resource consumption. Different scenarios are considered, including various rebound effects, which influence how efficiency gains impact resource use. The key elements of the model include agents' uncertainty about the efficiency of their actions, the operationalization of efficiency as a reward, and the calculation of resource consumption based on efficiency gains and rebound effects. The model provides insights into how agents' decisions and resource use evolve over time under different conditions. This computational framework offers a valuable tool for exploring the complex dynamics of resource consumption and management in the face of environmental challenges. It can be applied to gain a deeper understanding of the Jevons Paradox and its implications for sustainable resource use. This computational model simulates the dynamics of exploration and exploitation strategies within a population of agents. These agents make decisions on whether to explore new solutions or exploit existing ones, with a focus on maximizing efficiency. The model employs a N-armed bandit problem approach, where agents select actions to maximize efficiency gains. Efficiency is operationalized as a reward, and agents use sample means to estimate expected efficiency. A balance between exploration and exploitation is maintained through a probability-based algorithm. The code also encompasses resource domains, representing different resources and their dynamics, along with computations of resource consumption, existing resources, and sustainability indices. The simulations consider various parameter combinations to examine the model's behavior. Overall, the code serves as a tool for studying the interplay between exploration, exploitation, efficiency, and resource consumption within a population of agents across different scenarios, making it valuable for investigating the effects of rebound effects on resource consumption and sustainability. The simulations run a comprehensive set of parameter combinations to explore the model's behavior thoroughly. # Code from: Efficiency traps beyond the climate crisis: Exploration-exploitation tradeoffs and rebound effects. Python scripts to run the model, as described in: Segovia-Martin J, Creutzig F, Winters J. 2023 Efficiency traps beyond the climate crisis: exploration–exploitation tradeoffs and rebound effects. Phil. Trans. R. Soc. B 378: 20220405. https://doi.org/10.1098/rstb.2022.0405 The code and supplementary materials are all freely accessible at the following link: [https://github.com/School-of-Collective-Intelligence/Jevons-Paradox-and-Cultural-Evolution](https://github.com/School-of-Collective-Intelligence/Jevons-Paradox-and-Cultural-Evolution) The simulator can be accessed via the following links: [https://jevons-collectiveintelligence.pythonanywhere.com/](https://jevons-collectiveintelligence.pythonanywhere.com/) or [https://jsegoviamartin.pythonanywhere.com/](https://jsegoviamartin.pythonanywhere.com/) The DOI of this Dryad repository: [https://doi.org/10.5061/dryad.qjq2bvqnk](https://doi.org/10.5061/dryad.qjq2bvqnk) ##

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    ZENODO
    Dataset . 2023
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    DRYAD
    Dataset . 2023
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      ZENODO
      Dataset . 2023
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      Dataset . 2023
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    Authors: Ziehn, Tilo; Dix, Martin; Mackallah, Chloe; Chamberlain, Matthew; +4 Authors

    Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.DAMIP.CSIRO.ACCESS-ESM1-5.hist-nat' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The Australian Community Climate and Earth System Simulator Earth System Model Version 1.5 climate model, released in 2019, includes the following components: aerosol: CLASSIC (v1.0), atmos: HadGAM2 (r1.1, N96; 192 x 145 longitude/latitude; 38 levels; top level 39255 m), land: CABLE2.4, ocean: ACCESS-OM2 (MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m), ocnBgchem: WOMBAT (same grid as ocean), seaIce: CICE4.1 (same grid as ocean). The model was run by the Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia (CSIRO) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.

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    World Data Center for Climate
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    World Data Center for Climate
    Dataset . 2023
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    Data sources: Datacite
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    World Data Center for Climate
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      World Data Center for Climate
      Dataset . 2023
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      World Data Center for Climate
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      World Data Center for Climate
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Lefevre, Dominique; Libes, Maurice; Mallarino, Didier; Bernardet, Karim; +1 Authors

    EMSO-Western Ligurian Site (European Multidisciplinary See floor Observatory and water column, Western Ligurian Site) is a second generation permanent submarine observatory deployed offshore of Toulon, France, as a follow up of the pioneering ANTARES neutrino telescope located nearby. This submarine network is part of KM3NeT (https://www.km3net.org/) which has a modular topology designed to connect up to 120 neutrino detection units, i.e. ten times more than ANTARES. The Earth and Sea Science (ESS) instrumentation connected to KM3NeT is based on two complementary components: an Instrumented Interface Module (MII) and an autonomous mooring line (ALBATROSS). The Module Interface Instrumented "MII" was deployed in May 2019 and cabled to the MEUST Node#1. Node#1 is cabled to the shore via the KM3NeT cable. The MII provides data for temperature, conductivity/salinity, pressure, particles proxy (deduced from beam attenuation measured with a CSTAR transmissiometer). The MII collects data through an acoustic link from the instrumented mooring line ALBATROSS (https://doi.org/10.17882/74513) deployed at a distance of 2-3 kilometers. These data are being transferred daily for near real time visualisation.

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    https://dx.doi.org/10.17882/75...
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    SEANOE
    Dataset . 2023
    License: CC BY
    Data sources: SEANOE
    B2FIND
    Dataset . 2022
    Data sources: B2FIND
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      https://dx.doi.org/10.17882/75...
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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      SEANOE
      Dataset . 2023
      License: CC BY
      Data sources: SEANOE
      B2FIND
      Dataset . 2022
      Data sources: B2FIND
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  • Authors: Higgs, Carl; Liu, Shiqin; Boeing, Geoff; Arundel, Jonathan; +8 Authors

    Output data prepared for analysis of 25 diverse global cities by the Global Healthy and Sustainable City-Indicator Collaboration study, published in The Lancet Global Health Series on urban design, transport, and health. 2022. https://www.thelancet.com/series/urban-design-2022 Boeing, G. et al. (2022) ‘Using open data and open-source software to develop spatial indicators of urban design and transport features for achieving healthy and sustainable cities’, The Lancet Global Health, 10(6), pp. e907–e918. Available at: https://doi.org/10.1016/S2214-109X(22)00072-9. Data outputs were generated through use of the global-indicators software tool, designed for this study and available from: https://github.com/global-healthy-liveable-cities/global-indicators Further detail on the methods used is provided in the following publication: Liu, S., Higgs, C., Arundel, J., Boeing, G., Cerdera, N., Moctezuma, D., Cerin, E., Adlakha, D., Lowe, M. and Giles-Corti, B. (2021), A Generalized Framework for Measuring Pedestrian Accessibility around the World Using Open Data. Geogr Anal. https://doi.org/10.1111/gean.12290 The study made use of OpenStreetMap, Global Human Settlements and custom data, and is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/

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    Authors: Alon, Asaf; Cohen, Shabtai; Burlett, Regis; Hochberg, Uri; +6 Authors

    Survival and growth of woody species in the Mediterranean are mainly restricted by water availability. We tested the hypothesis that Mediterranean species acclimate their xylem vulnerability and osmotic potential along a precipitation gradient. We studied five predominant co-occurring Mediterranean species; Quercus calliprinos, Pistacia palaestina, Pistacia lentiscus, Rhamnus lycioides, and Phillyrea latifolia, over two summers at three sites. The driest of the sites is the distribution edge for all the five species. We measured key hydraulic and osmotic traits related to drought resistance, including resistance to embolism (Ψ50) and the seasonal dynamics of water and osmotic potentials. The leaf water potentials (Ψ1) of all species declined significantly along the summer, reaching significantly lower Ψl at the end of summer in the drier sites. Surprisingly, we did not find plasticity along the drought gradient in Ψ50 or osmotic potentials. This resulted in much narrower hydraulic safety margins (HSM) in the drier sites, where some species experienced significant embolism. Our analysis indicates that reduction in HSM to null values put Mediterranean species in embolism risk as they approach their hydraulic limit near the geographic dry edge of their distribution. The PLC curves and resistance to embolism were measured using the Cavitron. The pre-dawn and midday water potentials were measured using a pressure bomb. The C13 was measured with a 13C cavity ring-down analyzer. The osmotic potential was measured using an osmometer. All methods are described in Alon et al., Acclimation limits for embolism resistance and osmotic adjustment accompany the geographic dry edge of Mediterranean species. 2023. Functional Ecology Excel

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    ZENODO
    Dataset . 2023
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2023
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC 0
      Data sources: ZENODO
      DRYAD
      Dataset . 2023
      License: CC 0
      Data sources: Datacite
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    Authors: Behzad Rismanchi; Lu Aye; Sheikh Khaleduzzaman Shah;

    This dataset includes data from the validation of double U-tube borehole and seasonal solar thermal energy storage system TRNSYS models. The simulated transient temperatures at various points of the systems were compared with the measured ones. To quantify the agreement between each simulated and measured temperature of interest, mean bias error (MBE), root mean square error (RMSE) and correlation coefficient (CC) were applied.

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    Mendeley Data
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    B2FIND
    Dataset . 2021
    Data sources: B2FIND
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      Mendeley Data
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      B2FIND
      Dataset . 2021
      Data sources: B2FIND
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    Authors: Zaake, Paul; Paul, Birthe K.; Marshall, Karen; Notenbaert, An; +4 Authors

    There is limited attention to impacts of climate change on pigs in Uganda by stakeholders, despite the potential vulnerability of pigs to climate change. Pigs are sensitive to heat-stress, as they do not have functioning sweat glands as other livestock species do, and have small lungs which reduces their ability to disseminate heat by panting. The objectives of the study were to i) determine the heat-stress status in pigs, ii) analyze factors influencing heat-stress, and iii) explore the heat-stress adaptation options in Lira District, Uganda. Lira was selected because of presence of both rural & urban areas and expected heat stress throughout the year in the district. The data including household demographics, management systems, age, color, breeds, body/skin temperature, rectal temperature and others were collected from 104 households and 259 pigs during the hot months in Ojwina and Barr sub-counties- Lira district. We collected data on adaptation options during the four gender disaggregated focus group discussions. Weather data was collected during the time of administering the questionnaire, and it was complemented with data from Ngetta Meteorological Station, Lira. STATA, 14

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    Harvard Dataverse
    Dataset . 2020
    Data sources: Datacite
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    Research@WUR
    Dataset . 2020
    Data sources: Research@WUR
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      Harvard Dataverse
      Dataset . 2020
      Data sources: Datacite
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      Research@WUR
      Dataset . 2020
      Data sources: Research@WUR
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    Authors: Viviroli, Daniel; Kummu, Matti; Meybeck, Michel; Kallio, Marko; +1 Authors

    Water resources index W quantifies the potential dependence of the world's lowland areas on water resources originating in mountain areas upstream. The data cover the timeframe from the 1960s (1961–1970) to the 2040s (2041–2050) in decadal steps. Data for projections from the 2010s onwards are available for three scenario pathways (SSP1-RCP4.5, SSP2-RCP6.0, SSP3-RCP6.0) and show median results from 5 CMIP5 GCMs (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1‑M). The files are GeoTIFF formatted and in a regular raster of 5’×5’ (arc minutes in WGS 1984 coordinate system) The values of W can be classified using the following ranges: W ≤ -2 → Essential but vastly insufficient -2 < W < -1 → Essential but insufficient -1 ≤ W < 0 → Essential and sufficient W = 0 → No surplus from mountains 0 < W ≤ 1 → Supportive 1 < W < 2 → Minor W ≥ 2 → Negligible The values of W are rounded to four decimal places and limited to a range of -1110 to 9998. Values falling outside of that range are set to the nearest limit. he following flag values apply to W: -5555 indicates that there is no water balance surplus from the mountain area upstream, but a lowland water balance surplus; -6666 indicates that there is no water balance surplus from the mountain area upstream, and a lowland water balance deficit. Mountain areas and oceans are NODATA, large ice shields are omitted (Greenland: NODATA, Antarctica: not covered in extent). Mountain areas provide disproportionally high runoff in many parts of the world, and here we quantify for the first time their importance for water resources and food production from the viewpoint of the lowland areas downstream. The dataset maps the degree to which lowland areas potentially depend on runoff contributions from mountain areas (39% of land mass) between the 1960s and the 2040s.

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    ZENODO
    Dataset . 2020
    Data sources: ZENODO
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    ZENODO
    Dataset . 2020
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2020
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2020
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2020
      License: CC 0
      Data sources: ZENODO
      DRYAD
      Dataset . 2020
      License: CC 0
      Data sources: Datacite
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