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Research data keyboard_double_arrow_right Dataset 2024Embargo end date: 06 Nov 2024 United KingdomPublisher:University of Strathclyde Authors: Downie, Dillon;Dataset including raw Photoluminescence (PL) spectral data, UV-vis Absorbance (ABS) spectral data, Photoluminescence quantum yield (PLQY) data and calculations, and the average Suprapartice (SP) size data.
University of Strath... arrow_drop_down University of Strathclyde KnowledgeBase DatasetsDataset . 2024License: CC BYData sources: DataciteAll Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.15129/5825535a-ab05-4678-8102-fe957bdf7943&type=result"></script>'); --> </script>
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more_vert University of Strath... arrow_drop_down University of Strathclyde KnowledgeBase DatasetsDataset . 2024License: CC BYData sources: DataciteAll Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.15129/5825535a-ab05-4678-8102-fe957bdf7943&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019Embargo end date: 05 Feb 2022Publisher:Zenodo Authors: Aguirre Gutierrez, Jesus; Malhi, Yadvinder;Maps created and resulting data from analysis in changes in community weighted mean of traits. The raw trait data and forest census data used are available from their sources in www.gem.tropicalforests.ox.ac.uk and ForestPlots.net.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Publisher:Mendeley Data Geiger, Katja; Rivera, Antonella; Aguión, Alba; Barbier, Marine; Cruz, Teresa; Fandiño, Susana; García-Flórez, Lucía; Macho, Gonzalo; Neves, Francisco; Penteado, Nélia; Peón Torre, Paloma; Thiébaut, Eric; Vázquez, Elsa; Acuña, José Luis;Survey data used in a perception study of stalked barnacle harvesters on the effectiveness of fisheries management practices in Spain, Portugal and France. Harvesters from the following six regions along the Atlantic Arc participated: Morbihan in Brittany (France), Asturias-East, Asturias-West and Galicia (Spain), the Reserva Natural das Berlengas (RNB; Portugal) and the Parque Natural do Sudoeste Alentejano e Costa Vicentina (PNSACV; Portugal). We administered 184 surveys from October 2019 to September 2020 and each region was treated as an independent population. The data includes: general demographic data (Region, Age, Gender, Level of Education, Main income source, Years of Experience); perception data of the effectiveness of the currently implemented management strategies in each region (coded: e_name_of_strategy – using Likert Scale with scores ranging from 1 = completely ineffective to 5 = very effective); data of the willingness for change of the currently implemented management (Yes, No, NA); and data of harvesters’ perceptions regarding the most important strategy to achieve sustainability in the fishery. Because the surveys were conducted both before and during the Covid-19 pandemic (the column Covid indicates whether the data was collected before or during the pandemic), we had to make adjustments in our data collection methods. We provided the following options for survey completion (see the Recollection_of_data column): by hand in a written format, online, or via an oral interview conducted with the assistance of a scientist per telephone. Our results indicate that the majority of harvesters in the regions in Portugal and France were willing to make changes to current management strategies, reflecting their awareness of the need for improvement. Based on the AIC model selection analysis results, the model with the single variable region explained 83% of the cumulative model weight. The variable region was the best predictor of the trends in management strategy preferences, and presented a highly significant goodness-of-fit result (p<0.001), suggesting that regional differences play a significant role in shaping these preferences. No clear trend emerged regarding a single "optimal" management strategy preferred by harvesters across regions. Harvesters in less developed co-management systems favored general input and output restrictions and expressed a desire for greater involvement in co-management processes. Conversely, harvesters in highly developed co-management systems with Territorial User Rights for Fishers (TURFs) preferred the most restrictive and spatially explicit management strategies, such as implementing harvest bans and establishing marine reserves. Our findings emphasise that management strategies do not only need to be tailored to each region's particular practices, needs, and characteristics, but that resource users’ readiness for specific strategies also needs to be considered.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017 United States, KazakhstanAll Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=r3ba4f6876af::23a296426e0d937e5e07345ec2da3ab7&type=result"></script>'); --> </script>
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017 1W, Kazakhstan, United States, United StatesAll Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=r3ba4f6876af::1e24f2cddfbdf709d9addc04c16348f3&type=result"></script>'); --> </script>
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Publisher:Biological and Chemical Oceanography Data Management Office (BCO-DMO) Dam, Hans G.; Baumann, Hannes; Finiguerra, Michael; Pespeni, Melissa; Brennan, Reid;These data include population fitness measurements collected for Acartia hudsonica during multigenerational exposure to ocean warming (OW), ocean acidification (OA), and combined ocean warming and acidification (OWA) including a benign ambient condition temperature and CO2 control (AM).
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2018Publisher:Zenodo Funded by:EC | REINVENTEC| REINVENTHansen, Teis; Keaney, Monica; Bulkeley, Harriet A.; Cooper, Mark; Mölter, Helena; Nielsen, Hjalti; Pietzner, Katja; Sonesson, Ludwig B.; Stripple, Johannes; S.I. Aan Den Toorn; Tziva, Maria; Tönjes, Annika; Vallentin, Daniel; Van-Veelen, Bregje;This database includes more than 100 decarbonisation innovations in Paper, Plastic, Steel and Meat & Dairy sectors, across their value chains, as well as in Finance. For each innovation there is a description, information about its contribution to decarbonisation, actors and collaborators involved, sources of funding, drivers, (co)benefits and disadvantages. More information on the method for selecting innovations for the database is available here. The database was created as part of REINVENT – a Horizon 2020 research project funded by the European Commission (grant agreement 730053). REINVENT involves five research institutions from four countries: Lund University (Sweden), Durham University (United Kingdom), Wuppertal Institute (Germany), PBL Netherlands Environmental Assessment Agency (the Netherlands) and Utrecht University (the Netherlands). More information can be found on our website: www.reinvent-project.eu.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Embargo end date: 13 Apr 2022Publisher:Dryad Gao, Guang; Beardall, John; Jin, Peng; Gao, Lin; Xie, Shuyu; Gao, Kunshan;The atmosphere concentration of CO2 is steadily increasing and causing climate change. To achieve the Paris 1.5 or 2 oC target, negative emissions technologies must be deployed in addition to reducing carbon emissions. The ocean is a large carbon sink but the potential of marine primary producers to contribute to carbon neutrality remains unclear. Here we review the alterations to carbon capture and sequestration of marine primary producers (including traditional ‘blue carbon’ plants, microalgae, and macroalgae) in the Anthropocene, and, for the first time, assess and compare the potential of various marine primary producers to carbon neutrality and climate change mitigation via biogeoengineering approaches. The contributions of marine primary producers to carbon sequestration have been decreasing in the Anthropocene due to the decrease in biomass driven by direct anthropogenic activities and climate change. The potential of blue carbon plants (mangroves, saltmarshes, and seagrasses) is limited by the available areas for their revegetation. Microalgae appear to have a large potential due to their ubiquity but how to enhance their carbon sequestration efficiency is very complex and uncertain. On the other hand, macroalgae can play an essential role in mitigating climate change through extensive offshore cultivation due to higher carbon sequestration capacity and substantial available areas. This approach seems both technically and economically feasible due to the development of offshore aquaculture and a well-established market for macroalgal products. Synthesis and applications: This paper provides new insights and suggests promising directions for utilizing marine primary producers to achieve the Paris temperature target. We propose that macroalgae cultivation can play an essential role in attaining carbon neutrality and climate change mitigation, although its ecological impacts need to be assessed further. To calculate the parameters presented in Table 1, the relevant keywords "mangroves, salt marshes, macroalgae, microalgae, global area, net primary productivity, CO2 sequestration" were searched through the ISI Web of Science and Google Scholar in July 2021. Recent data published after 2010 were collected and used since area and productivity of plants change with decade. For data with limited availability, such as net primary productivity (NPP) of seagrasses and global area and NPP of wild macroalgae, data collection was extended back to 1980. Total NPP and CO2 sequestration for mangroves, salt marshes, seagrasses and wild macroalgae were obtained by the multiplication of area and NPP/CO2 sequestration density and subjected to error propagation analysis. Data were expressed as means ± standard error.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Embargo end date: 16 Jan 2024Publisher:Dryad Authors: Pérez-Navarro, María Ángeles;This repository contains a series of .csv files developed for the study titled "Plant canopies promote climatic disequilibrium in Mediterranean recruit communities", authored by: Perez-Navarro MA, Lloret F, Molina-Venegas R, Alcántara JM and Verdú M. The author of these files is Perez-Navarro MA. These files are used to characterize species niches, estimate climatic disequilibrium for recruit communities growing under plant canopies and open spaces, and conduct statistical analyses. Variables description of each table is compiled in the METADATA.txt file. Please visit Github readme () to correctly place these files in the folder tree and check for the corresponding scripts where they are required. Please notice that although alternative approaches were calibrated to estimate species niche (accordingly producing multiple niche, distances and disequilibrium dataframes), only niche centroid calibrated discarding 95 percentile of lowest niche density was used for paper results and figures. Also, in case of univariate analyses only bio01, bio06 and bio12 were used in analyses, though species niche and further niche and community estimations were obtained for all 19 variables. This is version 2 (v2) and include extra intermediate .csv required to run all the R scripts included in the abovementioned Github repository. NAs or empty cells present in the .csv files of this repository means no data and do not contribute to the analyses. Visit METADATA.txt file for variables description. These data are under CC0 license. It is possible to share, copy and redistribute the material in any medium or format, and adapt, remix, transform, and build upon the material for any purpose. Studies using R scripts or any data files from these study should cite the abovementioned paper (Perez-Navarro MA, Lloret F, Molina-Venegas R, Alcantara JM, Verdu M. (2024). Plant canopies promote climatic disequilibrium in Mediterranean recruit communities). Please contact m.angeles582@gmail.com in case of having doubts or problems with the existing files and scripts. Current rates of climate change are exceeding the capacity of many plant species to track climate, thus leading communities to be in disequilibrium with climatic conditions. Plant canopies can contribute to this disequilibrium by buffering macro-climatic conditions and sheltering poorly adapted species to the oncoming climate, particularly in their recruitment stages. Here we analyze differences in climatic disequilibrium between understory and open ground woody plant recruits in 28 localities, covering more than 100,000 m2, across an elevation range embedding temperature and aridity gradients in the southern Iberian Peninsula. This study demonstrates higher climatic disequilibrium under canopies compared with open ground, supporting that plant canopies would affect future community climatic lags by allowing the recruitment of less arid-adapted species in warm and dry conditions, but also it endorse that canopies could favor warm-adapted species in extremely cold environments as mountain tops, thus pre-adapting communities living in these habitats to climate change.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019Publisher:The Smithsonian Institution Authors: Paton, Steve;doi: 10.25573/data.10059476.v9 , 10.25573/data.10059476.v35 , 10.25573/data.10059476.v24 , 10.25573/data.10059476.v22 , 10.25573/data.10059476.v26 , 10.25573/data.10059476.v1 , 10.25573/data.10059476.v25 , 10.25573/data.10059476.v38 , 10.25573/data.10059476.v34 , 10.25573/data.10059476.v31 , 10.25573/data.10059476.v12 , 10.25573/data.10059476.v14 , 10.25573/data.10059476.v23 , 10.25573/data.10059476.v21 , 10.25573/data.10059476.v28 , 10.25573/data.10059476.v17 , 10.25573/data.10059476.v11 , 10.25573/data.10059476.v20 , 10.25573/data.10059476.v27 , 10.25573/data.10059476.v7 , 10.25573/data.10059476.v13 , 10.25573/data.10059476.v10 , 10.25573/data.10059476.v2 , 10.25573/data.10059476.v8 , 10.25573/data.10059476.v3 , 10.25573/data.10059476.v37 , 10.25573/data.10059476.v16 , 10.25573/data.10059476.v33 , 10.25573/data.10059476.v5 , 10.25573/data.10059476.v32 , 10.25573/data.10059476.v6 , 10.25573/data.10059476.v15 , 10.25573/data.10059476.v18 , 10.25573/data.10059476.v4 , 10.25573/data.10059476.v19 , 10.25573/data.10059476.v36 , 10.25573/data.10059476
doi: 10.25573/data.10059476.v9 , 10.25573/data.10059476.v35 , 10.25573/data.10059476.v24 , 10.25573/data.10059476.v22 , 10.25573/data.10059476.v26 , 10.25573/data.10059476.v1 , 10.25573/data.10059476.v25 , 10.25573/data.10059476.v38 , 10.25573/data.10059476.v34 , 10.25573/data.10059476.v31 , 10.25573/data.10059476.v12 , 10.25573/data.10059476.v14 , 10.25573/data.10059476.v23 , 10.25573/data.10059476.v21 , 10.25573/data.10059476.v28 , 10.25573/data.10059476.v17 , 10.25573/data.10059476.v11 , 10.25573/data.10059476.v20 , 10.25573/data.10059476.v27 , 10.25573/data.10059476.v7 , 10.25573/data.10059476.v13 , 10.25573/data.10059476.v10 , 10.25573/data.10059476.v2 , 10.25573/data.10059476.v8 , 10.25573/data.10059476.v3 , 10.25573/data.10059476.v37 , 10.25573/data.10059476.v16 , 10.25573/data.10059476.v33 , 10.25573/data.10059476.v5 , 10.25573/data.10059476.v32 , 10.25573/data.10059476.v6 , 10.25573/data.10059476.v15 , 10.25573/data.10059476.v18 , 10.25573/data.10059476.v4 , 10.25573/data.10059476.v19 , 10.25573/data.10059476.v36 , 10.25573/data.10059476
Monthly and daily summary from the Fortuna Station (Centro de Investigaciones Jorge L. Arauz)Location: 8° 43.340'N, 82° 14.241'WParameters: air temperature, wind speed and direction, precipitation, solar radiation (pyranometer)Located in the highlands of the Chiriqui Province, in western Panama.There are three sensor locations: north clearing, south clearing, and a 15m tower.
https://dx.doi.org/1... arrow_drop_down Smithsonian figshareDataset . 2019License: CC BYData sources: Bielefeld Academic Search Engine (BASE)All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.25573/data.10059476.v9&type=result"></script>'); --> </script>
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Research data keyboard_double_arrow_right Dataset 2024Embargo end date: 06 Nov 2024 United KingdomPublisher:University of Strathclyde Authors: Downie, Dillon;Dataset including raw Photoluminescence (PL) spectral data, UV-vis Absorbance (ABS) spectral data, Photoluminescence quantum yield (PLQY) data and calculations, and the average Suprapartice (SP) size data.
University of Strath... arrow_drop_down University of Strathclyde KnowledgeBase DatasetsDataset . 2024License: CC BYData sources: DataciteAll Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.15129/5825535a-ab05-4678-8102-fe957bdf7943&type=result"></script>'); --> </script>
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more_vert University of Strath... arrow_drop_down University of Strathclyde KnowledgeBase DatasetsDataset . 2024License: CC BYData sources: DataciteAll Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.15129/5825535a-ab05-4678-8102-fe957bdf7943&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019Embargo end date: 05 Feb 2022Publisher:Zenodo Authors: Aguirre Gutierrez, Jesus; Malhi, Yadvinder;Maps created and resulting data from analysis in changes in community weighted mean of traits. The raw trait data and forest census data used are available from their sources in www.gem.tropicalforests.ox.ac.uk and ForestPlots.net.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Publisher:Mendeley Data Geiger, Katja; Rivera, Antonella; Aguión, Alba; Barbier, Marine; Cruz, Teresa; Fandiño, Susana; García-Flórez, Lucía; Macho, Gonzalo; Neves, Francisco; Penteado, Nélia; Peón Torre, Paloma; Thiébaut, Eric; Vázquez, Elsa; Acuña, José Luis;Survey data used in a perception study of stalked barnacle harvesters on the effectiveness of fisheries management practices in Spain, Portugal and France. Harvesters from the following six regions along the Atlantic Arc participated: Morbihan in Brittany (France), Asturias-East, Asturias-West and Galicia (Spain), the Reserva Natural das Berlengas (RNB; Portugal) and the Parque Natural do Sudoeste Alentejano e Costa Vicentina (PNSACV; Portugal). We administered 184 surveys from October 2019 to September 2020 and each region was treated as an independent population. The data includes: general demographic data (Region, Age, Gender, Level of Education, Main income source, Years of Experience); perception data of the effectiveness of the currently implemented management strategies in each region (coded: e_name_of_strategy – using Likert Scale with scores ranging from 1 = completely ineffective to 5 = very effective); data of the willingness for change of the currently implemented management (Yes, No, NA); and data of harvesters’ perceptions regarding the most important strategy to achieve sustainability in the fishery. Because the surveys were conducted both before and during the Covid-19 pandemic (the column Covid indicates whether the data was collected before or during the pandemic), we had to make adjustments in our data collection methods. We provided the following options for survey completion (see the Recollection_of_data column): by hand in a written format, online, or via an oral interview conducted with the assistance of a scientist per telephone. Our results indicate that the majority of harvesters in the regions in Portugal and France were willing to make changes to current management strategies, reflecting their awareness of the need for improvement. Based on the AIC model selection analysis results, the model with the single variable region explained 83% of the cumulative model weight. The variable region was the best predictor of the trends in management strategy preferences, and presented a highly significant goodness-of-fit result (p<0.001), suggesting that regional differences play a significant role in shaping these preferences. No clear trend emerged regarding a single "optimal" management strategy preferred by harvesters across regions. Harvesters in less developed co-management systems favored general input and output restrictions and expressed a desire for greater involvement in co-management processes. Conversely, harvesters in highly developed co-management systems with Territorial User Rights for Fishers (TURFs) preferred the most restrictive and spatially explicit management strategies, such as implementing harvest bans and establishing marine reserves. Our findings emphasise that management strategies do not only need to be tailored to each region's particular practices, needs, and characteristics, but that resource users’ readiness for specific strategies also needs to be considered.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017 United States, KazakhstanAll Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=r3ba4f6876af::23a296426e0d937e5e07345ec2da3ab7&type=result"></script>'); --> </script>
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017 1W, Kazakhstan, United States, United StatesAll Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=r3ba4f6876af::1e24f2cddfbdf709d9addc04c16348f3&type=result"></script>'); --> </script>
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Publisher:Biological and Chemical Oceanography Data Management Office (BCO-DMO) Dam, Hans G.; Baumann, Hannes; Finiguerra, Michael; Pespeni, Melissa; Brennan, Reid;These data include population fitness measurements collected for Acartia hudsonica during multigenerational exposure to ocean warming (OW), ocean acidification (OA), and combined ocean warming and acidification (OWA) including a benign ambient condition temperature and CO2 control (AM).
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2018Publisher:Zenodo Funded by:EC | REINVENTEC| REINVENTHansen, Teis; Keaney, Monica; Bulkeley, Harriet A.; Cooper, Mark; Mölter, Helena; Nielsen, Hjalti; Pietzner, Katja; Sonesson, Ludwig B.; Stripple, Johannes; S.I. Aan Den Toorn; Tziva, Maria; Tönjes, Annika; Vallentin, Daniel; Van-Veelen, Bregje;This database includes more than 100 decarbonisation innovations in Paper, Plastic, Steel and Meat & Dairy sectors, across their value chains, as well as in Finance. For each innovation there is a description, information about its contribution to decarbonisation, actors and collaborators involved, sources of funding, drivers, (co)benefits and disadvantages. More information on the method for selecting innovations for the database is available here. The database was created as part of REINVENT – a Horizon 2020 research project funded by the European Commission (grant agreement 730053). REINVENT involves five research institutions from four countries: Lund University (Sweden), Durham University (United Kingdom), Wuppertal Institute (Germany), PBL Netherlands Environmental Assessment Agency (the Netherlands) and Utrecht University (the Netherlands). More information can be found on our website: www.reinvent-project.eu.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Embargo end date: 13 Apr 2022Publisher:Dryad Gao, Guang; Beardall, John; Jin, Peng; Gao, Lin; Xie, Shuyu; Gao, Kunshan;The atmosphere concentration of CO2 is steadily increasing and causing climate change. To achieve the Paris 1.5 or 2 oC target, negative emissions technologies must be deployed in addition to reducing carbon emissions. The ocean is a large carbon sink but the potential of marine primary producers to contribute to carbon neutrality remains unclear. Here we review the alterations to carbon capture and sequestration of marine primary producers (including traditional ‘blue carbon’ plants, microalgae, and macroalgae) in the Anthropocene, and, for the first time, assess and compare the potential of various marine primary producers to carbon neutrality and climate change mitigation via biogeoengineering approaches. The contributions of marine primary producers to carbon sequestration have been decreasing in the Anthropocene due to the decrease in biomass driven by direct anthropogenic activities and climate change. The potential of blue carbon plants (mangroves, saltmarshes, and seagrasses) is limited by the available areas for their revegetation. Microalgae appear to have a large potential due to their ubiquity but how to enhance their carbon sequestration efficiency is very complex and uncertain. On the other hand, macroalgae can play an essential role in mitigating climate change through extensive offshore cultivation due to higher carbon sequestration capacity and substantial available areas. This approach seems both technically and economically feasible due to the development of offshore aquaculture and a well-established market for macroalgal products. Synthesis and applications: This paper provides new insights and suggests promising directions for utilizing marine primary producers to achieve the Paris temperature target. We propose that macroalgae cultivation can play an essential role in attaining carbon neutrality and climate change mitigation, although its ecological impacts need to be assessed further. To calculate the parameters presented in Table 1, the relevant keywords "mangroves, salt marshes, macroalgae, microalgae, global area, net primary productivity, CO2 sequestration" were searched through the ISI Web of Science and Google Scholar in July 2021. Recent data published after 2010 were collected and used since area and productivity of plants change with decade. For data with limited availability, such as net primary productivity (NPP) of seagrasses and global area and NPP of wild macroalgae, data collection was extended back to 1980. Total NPP and CO2 sequestration for mangroves, salt marshes, seagrasses and wild macroalgae were obtained by the multiplication of area and NPP/CO2 sequestration density and subjected to error propagation analysis. Data were expressed as means ± standard error.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Embargo end date: 16 Jan 2024Publisher:Dryad Authors: Pérez-Navarro, María Ángeles;This repository contains a series of .csv files developed for the study titled "Plant canopies promote climatic disequilibrium in Mediterranean recruit communities", authored by: Perez-Navarro MA, Lloret F, Molina-Venegas R, Alcántara JM and Verdú M. The author of these files is Perez-Navarro MA. These files are used to characterize species niches, estimate climatic disequilibrium for recruit communities growing under plant canopies and open spaces, and conduct statistical analyses. Variables description of each table is compiled in the METADATA.txt file. Please visit Github readme () to correctly place these files in the folder tree and check for the corresponding scripts where they are required. Please notice that although alternative approaches were calibrated to estimate species niche (accordingly producing multiple niche, distances and disequilibrium dataframes), only niche centroid calibrated discarding 95 percentile of lowest niche density was used for paper results and figures. Also, in case of univariate analyses only bio01, bio06 and bio12 were used in analyses, though species niche and further niche and community estimations were obtained for all 19 variables. This is version 2 (v2) and include extra intermediate .csv required to run all the R scripts included in the abovementioned Github repository. NAs or empty cells present in the .csv files of this repository means no data and do not contribute to the analyses. Visit METADATA.txt file for variables description. These data are under CC0 license. It is possible to share, copy and redistribute the material in any medium or format, and adapt, remix, transform, and build upon the material for any purpose. Studies using R scripts or any data files from these study should cite the abovementioned paper (Perez-Navarro MA, Lloret F, Molina-Venegas R, Alcantara JM, Verdu M. (2024). Plant canopies promote climatic disequilibrium in Mediterranean recruit communities). Please contact m.angeles582@gmail.com in case of having doubts or problems with the existing files and scripts. Current rates of climate change are exceeding the capacity of many plant species to track climate, thus leading communities to be in disequilibrium with climatic conditions. Plant canopies can contribute to this disequilibrium by buffering macro-climatic conditions and sheltering poorly adapted species to the oncoming climate, particularly in their recruitment stages. Here we analyze differences in climatic disequilibrium between understory and open ground woody plant recruits in 28 localities, covering more than 100,000 m2, across an elevation range embedding temperature and aridity gradients in the southern Iberian Peninsula. This study demonstrates higher climatic disequilibrium under canopies compared with open ground, supporting that plant canopies would affect future community climatic lags by allowing the recruitment of less arid-adapted species in warm and dry conditions, but also it endorse that canopies could favor warm-adapted species in extremely cold environments as mountain tops, thus pre-adapting communities living in these habitats to climate change.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019Publisher:The Smithsonian Institution Authors: Paton, Steve;doi: 10.25573/data.10059476.v9 , 10.25573/data.10059476.v35 , 10.25573/data.10059476.v24 , 10.25573/data.10059476.v22 , 10.25573/data.10059476.v26 , 10.25573/data.10059476.v1 , 10.25573/data.10059476.v25 , 10.25573/data.10059476.v38 , 10.25573/data.10059476.v34 , 10.25573/data.10059476.v31 , 10.25573/data.10059476.v12 , 10.25573/data.10059476.v14 , 10.25573/data.10059476.v23 , 10.25573/data.10059476.v21 , 10.25573/data.10059476.v28 , 10.25573/data.10059476.v17 , 10.25573/data.10059476.v11 , 10.25573/data.10059476.v20 , 10.25573/data.10059476.v27 , 10.25573/data.10059476.v7 , 10.25573/data.10059476.v13 , 10.25573/data.10059476.v10 , 10.25573/data.10059476.v2 , 10.25573/data.10059476.v8 , 10.25573/data.10059476.v3 , 10.25573/data.10059476.v37 , 10.25573/data.10059476.v16 , 10.25573/data.10059476.v33 , 10.25573/data.10059476.v5 , 10.25573/data.10059476.v32 , 10.25573/data.10059476.v6 , 10.25573/data.10059476.v15 , 10.25573/data.10059476.v18 , 10.25573/data.10059476.v4 , 10.25573/data.10059476.v19 , 10.25573/data.10059476.v36 , 10.25573/data.10059476
doi: 10.25573/data.10059476.v9 , 10.25573/data.10059476.v35 , 10.25573/data.10059476.v24 , 10.25573/data.10059476.v22 , 10.25573/data.10059476.v26 , 10.25573/data.10059476.v1 , 10.25573/data.10059476.v25 , 10.25573/data.10059476.v38 , 10.25573/data.10059476.v34 , 10.25573/data.10059476.v31 , 10.25573/data.10059476.v12 , 10.25573/data.10059476.v14 , 10.25573/data.10059476.v23 , 10.25573/data.10059476.v21 , 10.25573/data.10059476.v28 , 10.25573/data.10059476.v17 , 10.25573/data.10059476.v11 , 10.25573/data.10059476.v20 , 10.25573/data.10059476.v27 , 10.25573/data.10059476.v7 , 10.25573/data.10059476.v13 , 10.25573/data.10059476.v10 , 10.25573/data.10059476.v2 , 10.25573/data.10059476.v8 , 10.25573/data.10059476.v3 , 10.25573/data.10059476.v37 , 10.25573/data.10059476.v16 , 10.25573/data.10059476.v33 , 10.25573/data.10059476.v5 , 10.25573/data.10059476.v32 , 10.25573/data.10059476.v6 , 10.25573/data.10059476.v15 , 10.25573/data.10059476.v18 , 10.25573/data.10059476.v4 , 10.25573/data.10059476.v19 , 10.25573/data.10059476.v36 , 10.25573/data.10059476
Monthly and daily summary from the Fortuna Station (Centro de Investigaciones Jorge L. Arauz)Location: 8° 43.340'N, 82° 14.241'WParameters: air temperature, wind speed and direction, precipitation, solar radiation (pyranometer)Located in the highlands of the Chiriqui Province, in western Panama.There are three sensor locations: north clearing, south clearing, and a 15m tower.
https://dx.doi.org/1... arrow_drop_down Smithsonian figshareDataset . 2019License: CC BYData sources: Bielefeld Academic Search Engine (BASE)All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.25573/data.10059476.v9&type=result"></script>'); --> </script>
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more_vert https://dx.doi.org/1... arrow_drop_down Smithsonian figshareDataset . 2019License: CC BYData sources: Bielefeld Academic Search Engine (BASE)All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.25573/data.10059476.v9&type=result"></script>'); --> </script>
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