Matches in Nanopublications for { ?s <http://schema.org/description> ?o ?g. }
- c8bd3371-151b-4650-9cb5-a64e40adf506 description "## Objective The FAIR2Adapt is a multidisciplinary project geared towards transforming data into actionable knowledge to shape climate adaptation strategies. By leveraging and collaborating with EOSC, we fully tap into the EOSC's wide range of services, the FAIR Implementation Framework Catalogue of Resources, and align with the EOSC interoperability framework. We adopt FAIR Digital Objects (FDOs) by using RO-Crate and nanopublications as key implementation tools. We use semantic bridging strategies, such as the I-ADOPT framework, and tailored FDO services to build a collaborative, user-friendly FAIR and open data sharing framework. Rich case studies will co-develop FAIR Supporting Resources in alignment with the FAIRification framework and demonstrate the impact of FAIR and open data sharing on climate change adaptation, and strategically support the EU Mission’s objective of enhancing climate resilience in European regions and communities. Through transfer cases and collaboration with other initiatives, FAIR2Adapt extends its reach to additional contexts, showcasing its scalability, sustainability and applicability beyond the project’s completion. A significant aspect of the FAIR2Adapt project is stakeholder engagement and capacity-building activities, which will be instrumental in raising awareness and devising customised solutions. By transforming data into flexible, practical, and resilient climate adaptation strategies, FAIR2Adapt constructs a scalable and extensible model for data sharing that can be adapted to multiple climate adaptation scenarios. The impact of FAIR2Adapt will span across scientific advancement, economic resilience, social-environmental wellbeing, and responsive policy development, fostering multidisciplinary cooperation, enhancing trust in science, and stimulating a climate-smart economy. Ultimately, FAIR2Adapt intends to build a more resilient, inclusive and knowledge-based society capable of efficiently tackling the challenges of climate change." assertion.
- c8bd3371-151b-4650-9cb5-a64e40adf506 description "## Objective The FAIR2Adapt is a multidisciplinary project geared towards transforming data into actionable knowledge to shape climate adaptation strategies. By leveraging and collaborating with EOSC, we fully tap into the EOSC's wide range of services, the FAIR Implementation Framework Catalogue of Resources, and align with the EOSC interoperability framework. We adopt FAIR Digital Objects (FDOs) by using RO-Crate and nanopublications as key implementation tools. We use semantic bridging strategies, such as the I-ADOPT framework, and tailored FDO services to build a collaborative, user-friendly FAIR and open data sharing framework. Rich case studies will co-develop FAIR Supporting Resources in alignment with the FAIRification framework and demonstrate the impact of FAIR and open data sharing on climate change adaptation, and strategically support the EU Mission’s objective of enhancing climate resilience in European regions and communities. Through transfer cases and collaboration with other initiatives, FAIR2Adapt extends its reach to additional contexts, showcasing its scalability, sustainability and applicability beyond the project’s completion. A significant aspect of the FAIR2Adapt project is stakeholder engagement and capacity-building activities, which will be instrumental in raising awareness and devising customised solutions. By transforming data into flexible, practical, and resilient climate adaptation strategies, FAIR2Adapt constructs a scalable and extensible model for data sharing that can be adapted to multiple climate adaptation scenarios. The impact of FAIR2Adapt will span across scientific advancement, economic resilience, social-environmental wellbeing, and responsive policy development, fostering multidisciplinary cooperation, enhancing trust in science, and stimulating a climate-smart economy. Ultimately, FAIR2Adapt intends to build a more resilient, inclusive and knowledge-based society capable of efficiently tackling the challenges of climate change." assertion.
- b622e76a-d3ec-48f4-985c-1ca5e1e68318 description "This folder contains information about the FAIR2Adapt Case Studies" assertion.
- b622e76a-d3ec-48f4-985c-1ca5e1e68318 description "This folder contains information about the FAIR2Adapt Case Studies" assertion.
- ea15c5d0-eba3-4711-ac8a-cd28f46c5273 description "Folder containing the FAIR2Adapt Project Deliverables." assertion.
- ea15c5d0-eba3-4711-ac8a-cd28f46c5273 description "Folder containing the FAIR2Adapt Project Deliverables." assertion.
- ebc45cf8-9658-4cdd-93a5-0be5d451df73 description "Folder with all the events we contributed/participated during the FAIR2Adapt project." assertion.
- ebc45cf8-9658-4cdd-93a5-0be5d451df73 description "Folder with all the events we contributed/participated during the FAIR2Adapt project." assertion.
- f1f9f1b9-d73c-42af-b13e-8e9ea415bda8 description "Folder containing files related to the FAIR2Adapt Visual Identify (logos, colors, etc.)" assertion.
- f1f9f1b9-d73c-42af-b13e-8e9ea415bda8 description "Folder containing files related to the FAIR2Adapt Visual Identify (logos, colors, etc.)" assertion.
- fd3fcc3c-cbac-411f-82f6-65b458f4f595 description "Folder containing the FAIR2Adapt meetings (agenda, minutes, etc.)" assertion.
- fd3fcc3c-cbac-411f-82f6-65b458f4f595 description "Folder containing the FAIR2Adapt meetings (agenda, minutes, etc.)" assertion.
- ea3ac578-ab0a-47c8-a10a-9d06678a9450 description "Research Object containing information about the RiOMar Case Study of the FAIR2Adapt project." assertion.
- ea3ac578-ab0a-47c8-a10a-9d06678a9450 description "Research Object containing information about the RiOMar Case Study of the FAIR2Adapt project." assertion.
- Agenda%20Kick-off%20Fair2Adapt.pdf description "This document contains the agenda of the FAIR2Adapt kick-off meeting." assertion.
- Agenda%20Kick-off%20Fair2Adapt.pdf description "This document contains the agenda of the FAIR2Adapt kick-off meeting." assertion.
- Minutes-FAIR2Adapt-kick-off.pdf description "Minutes from the FAIR2Adapt Kick-Off Meeting" assertion.
- Minutes-FAIR2Adapt-kick-off.pdf description "Minutes from the FAIR2Adapt Kick-Off Meeting" assertion.
- 15337227 description "Presentation given at EGU'25 at the Session ITS3.11/ERE6.3 entitled "Advancing Environmental Science through Integrated Research Infrastructures"." assertion.
- 15337227 description "Presentation given at EGU'25 at the Session ITS3.11/ERE6.3 entitled "Advancing Environmental Science through Integrated Research Infrastructures"." assertion.
- RIOMAR-2024-2030 description "# The French Project RIOMar (River-dominated Ocean Margins) The French project **RIOMar** (River-dominated Ocean Margins), a winner of the *"Ocean & Climate" Priority Research Program*, focuses on an in-depth study of the environment in five major coastal areas of mainland France influenced by rivers. Its objective is to provide scientifically grounded solutions to maintain or restore sustainable ecosystems in regions particularly affected by climate change and anthropogenic inputs transported and deposited by rivers. --- ## Scientifically Grounded Solutions to Mitigate Risks to Vulnerable Coastal Ecosystems Coastal areas are crucial for humanity, especially those dominated by rivers flowing into the ocean. Their future evolution poses a significant challenge, as it is estimated that **80% of the global population will live within 40 kilometers of the coast by 2030**. At the intersection of land and sea, **estuaries, lagoons, and deltas** experience daily interactions between freshwater and marine waters. The major estuaries of France (*Seine, Loire, and Gironde*) and the Rhône delta are just a few examples of these "transitional" environments along the French coastline. Currently, the **885 coastal municipalities of mainland France** account for over **10% of the population**. According to recent estimates (*source: Ministry of Ecological Transition*), an additional **4.5 million inhabitants** are expected to settle in these regions by 2040. In such conditions, the **coastal ocean environment** in these areas will become increasingly vulnerable to various combined human and climate-induced stressors: - Warming - Acidification - Eutrophication* - Hypoxia* - Contamination - Extreme events Simulating their evolution under the combined influence of **anthropogenic pressure and climate change** is a major challenge. The number of unknown and often unpredictable parameters is considerable. Addressing this requires a **comprehensive approach**, grounded in the **multidisciplinary analysis** of the numerous environmental factors affecting these coastal zones. The knowledge generated will enable the **co-construction of scientifically based solutions** with environmental managers for the **sustainable development** of coastal areas. --- ## An Original, Multidisciplinary, and Innovative Integrated Approach Spanning **six years (2022-2028)**, the RIOMar (*River-dominated Ocean Margins*) project aims to tackle all these challenges. Scientific studies within the project focus on five major coastal areas in mainland France influenced by large rivers: - The Seine - The Loire - The Gironde - The Rhône - The Charente Various scenarios for future evolution will be explored in collaboration with numerous stakeholders from these regions. **Relevant indicators** will be developed, in consultation with environmental managers, to propose **tailored and sustainable solutions** for public policies. --- ### Glossary - **Eutrophication**: The excessive enrichment of water with nutrients, leading to algal blooms and oxygen depletion. - **Hypoxia**: Low oxygen levels in water, threatening aquatic life." assertion.
- RIOMAR-2024-2030 description "# The French Project RIOMar (River-dominated Ocean Margins) The French project **RIOMar** (River-dominated Ocean Margins), a winner of the *"Ocean & Climate" Priority Research Program*, focuses on an in-depth study of the environment in five major coastal areas of mainland France influenced by rivers. Its objective is to provide scientifically grounded solutions to maintain or restore sustainable ecosystems in regions particularly affected by climate change and anthropogenic inputs transported and deposited by rivers. --- ## Scientifically Grounded Solutions to Mitigate Risks to Vulnerable Coastal Ecosystems Coastal areas are crucial for humanity, especially those dominated by rivers flowing into the ocean. Their future evolution poses a significant challenge, as it is estimated that **80% of the global population will live within 40 kilometers of the coast by 2030**. At the intersection of land and sea, **estuaries, lagoons, and deltas** experience daily interactions between freshwater and marine waters. The major estuaries of France (*Seine, Loire, and Gironde*) and the Rhône delta are just a few examples of these "transitional" environments along the French coastline. Currently, the **885 coastal municipalities of mainland France** account for over **10% of the population**. According to recent estimates (*source: Ministry of Ecological Transition*), an additional **4.5 million inhabitants** are expected to settle in these regions by 2040. In such conditions, the **coastal ocean environment** in these areas will become increasingly vulnerable to various combined human and climate-induced stressors: - Warming - Acidification - Eutrophication* - Hypoxia* - Contamination - Extreme events Simulating their evolution under the combined influence of **anthropogenic pressure and climate change** is a major challenge. The number of unknown and often unpredictable parameters is considerable. Addressing this requires a **comprehensive approach**, grounded in the **multidisciplinary analysis** of the numerous environmental factors affecting these coastal zones. The knowledge generated will enable the **co-construction of scientifically based solutions** with environmental managers for the **sustainable development** of coastal areas. --- ## An Original, Multidisciplinary, and Innovative Integrated Approach Spanning **six years (2022-2028)**, the RIOMar (*River-dominated Ocean Margins*) project aims to tackle all these challenges. Scientific studies within the project focus on five major coastal areas in mainland France influenced by large rivers: - The Seine - The Loire - The Gironde - The Rhône - The Charente Various scenarios for future evolution will be explored in collaboration with numerous stakeholders from these regions. **Relevant indicators** will be developed, in consultation with environmental managers, to propose **tailored and sustainable solutions** for public policies. --- ### Glossary - **Eutrophication**: The excessive enrichment of water with nutrients, leading to algal blooms and oxygen depletion. - **Hypoxia**: Low oxygen levels in water, threatening aquatic life." assertion.
- visualize-riomar.html description "This is the rendered Jupyter notebook to Visualize RiOMAR dggs-transformed data with xddgs and lonboard" assertion.
- visualize-riomar.html description "This is the rendered Jupyter notebook to Visualize RiOMAR dggs-transformed data with xddgs and lonboard" assertion.
- Riomar_RO.html description "This is a rendered Jupyter notebook showing how to create a RO-Crate (using the Python API rocrate) for archiving the RiOMar dataset into the NIRD archive. The metadata used for the creation of the RO-Crate correspond to what is needed when archiving in the NIRD archive (Norwegian Research Data Archive)." assertion.
- Riomar_RO.html description "This is a rendered Jupyter notebook showing how to create a RO-Crate (using the Python API rocrate) for archiving the RiOMar dataset into the NIRD archive. The metadata used for the creation of the RO-Crate correspond to what is needed when archiving in the NIRD archive (Norwegian Research Data Archive)." assertion.
- pangeo-riomar.html description "This is the rendered Jupyter notebook showing how to regrid a sample of RiOMar data into DGGS (Healpix)." assertion.
- pangeo-riomar.html description "This is the rendered Jupyter notebook showing how to regrid a sample of RiOMar data into DGGS (Healpix)." assertion.
- pangeo-riomar_resize_datarmor.html description "Read a netCDF original dataset from RiOMar and select a few timestep to save it in Zarr. This is the rendered Jupyter nobteook." assertion.
- pangeo-riomar_resize_datarmor.html description "Read a netCDF original dataset from RiOMar and select a few timestep to save it in Zarr. This is the rendered Jupyter nobteook." assertion.
- riomar_plots-datatree_multiresoplot.html description "This is the rendered Jupyter Notebook that uses Datatree (Xarray) to examplify how to create a multi-resolution dataset with DGGS (different resolution)." assertion.
- riomar_plots-datatree_multiresoplot.html description "This is the rendered Jupyter Notebook that uses Datatree (Xarray) to examplify how to create a multi-resolution dataset with DGGS (different resolution)." assertion.
- virtualizarr_riomar_kerchunk.html description "This is the rendered Jupyter notebook that shows how to use Virtualizarr with Kerchunk to create a RiOMar datasets with all the necessary files required for a full RiOMar data analysis." assertion.
- virtualizarr_riomar_kerchunk.html description "This is the rendered Jupyter notebook that shows how to use Virtualizarr with Kerchunk to create a RiOMar datasets with all the necessary files required for a full RiOMar data analysis." assertion.
- RiOMar2DGGS.png description "This image shows how a RiOMar dataset can be visualized with xdggs (that uses lonboard)." assertion.
- RiOMar2DGGS.png description "This image shows how a RiOMar dataset can be visualized with xdggs (that uses lonboard)." assertion.
- a0007726-0f5b-4ccb-a160-f350d669805e description "## RiOMar Case Study This [FAIR2Adapt](http://fair2adapt-eosc.eu) case study is led by IFREMER and builds on the outcomes of the RiOMar Project - Coastal Water Quality Anticipation to manage coastal zone ecosystem responses for biodiversity conservation. The RiOMar project’s data is high-resolution and complex to manipulate. To effectively support climate adaptation strategies and plans, it is crucial to maintain the high-resolution quality while enabling efficient data fusion with diverse datasets. ## Event The Hack4RiOMar workathon brought together six motivated participants in person, collaborating to advance the FAIR2Adapt RiOMar Case Study—the first workshop in our series of FAIR2Adapt case studies. We extend our gratitude 👏 to the external experts who participated at their own expense, bringing their expertise to tackle challenges and drive progress. ## Funding FAIR2Adapt project (101188256) is funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the Agency. Neither the European Union nor the granting authority can be held responsible for them." assertion.
- a0007726-0f5b-4ccb-a160-f350d669805e description "## RiOMar Case Study This [FAIR2Adapt](http://fair2adapt-eosc.eu) case study is led by IFREMER and builds on the outcomes of the RiOMar Project - Coastal Water Quality Anticipation to manage coastal zone ecosystem responses for biodiversity conservation. The RiOMar project’s data is high-resolution and complex to manipulate. To effectively support climate adaptation strategies and plans, it is crucial to maintain the high-resolution quality while enabling efficient data fusion with diverse datasets. ## Event The Hack4RiOMar workathon brought together six motivated participants in person, collaborating to advance the FAIR2Adapt RiOMar Case Study—the first workshop in our series of FAIR2Adapt case studies. We extend our gratitude 👏 to the external experts who participated at their own expense, bringing their expertise to tackle challenges and drive progress. ## Funding FAIR2Adapt project (101188256) is funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the Agency. Neither the European Union nor the granting authority can be held responsible for them." assertion.
- 561c6d89-9cff-4033-af0e-e474ef0f1070 description "Agenda and minutes from the first workshop for the Biscayan RiOMar Case Study (Hack4RiOMar event)." assertion.
- 561c6d89-9cff-4033-af0e-e474ef0f1070 description "Agenda and minutes from the first workshop for the Biscayan RiOMar Case Study (Hack4RiOMar event)." assertion.
- isprs-archives-XLVIII-4-W12-2024-75-2024 description "## Abstract Traditional map projections introduce distortions, especially for global data. Discrete Global Grid Systems (DGGS) offer an alternative by dividing the Earth into equal-area grid cells at different resolutions. This paper describes xdggs, a new Xarray extension that simplifies working with DGGS. Xdggs provides a unified API for various DGGS libraries and integrates seamlessly with the Pangeo ecosystem through extending the widely used Xarray library to use the DGGS-specific cell identifiers as an index. This development makes DGGS more accessible and will lead to facilitating data analysis on a planetary scale. Xdggs aims to provide a user-friendly API that hides the implementation complexities of different DGGS libraries. And because it integrates seamlessly with Xarray, a popular tool for geospatial data analysis, xdggs promotes FAIR data practices by simplifying data access and interoperability and can become a valuable tool for geospatial scientists and application developers working with global datasets. ## How to cite Kmoch, A., Bovy, B., Magin, J., Abernathey, R., Coca-Castro, A., Strobl, P., Fouilloux, A., Loos, D., Uuemaa, E., Chan, W. T., Delouis, J.-M., and Odaka, T.: XDGGS: A community-developed Xarray package to support planetary DGGS data cube computations, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4/W12-2024, 75–80, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-75-2024, 2024." assertion.
- isprs-archives-XLVIII-4-W12-2024-75-2024 description "## Abstract Traditional map projections introduce distortions, especially for global data. Discrete Global Grid Systems (DGGS) offer an alternative by dividing the Earth into equal-area grid cells at different resolutions. This paper describes xdggs, a new Xarray extension that simplifies working with DGGS. Xdggs provides a unified API for various DGGS libraries and integrates seamlessly with the Pangeo ecosystem through extending the widely used Xarray library to use the DGGS-specific cell identifiers as an index. This development makes DGGS more accessible and will lead to facilitating data analysis on a planetary scale. Xdggs aims to provide a user-friendly API that hides the implementation complexities of different DGGS libraries. And because it integrates seamlessly with Xarray, a popular tool for geospatial data analysis, xdggs promotes FAIR data practices by simplifying data access and interoperability and can become a valuable tool for geospatial scientists and application developers working with global datasets. ## How to cite Kmoch, A., Bovy, B., Magin, J., Abernathey, R., Coca-Castro, A., Strobl, P., Fouilloux, A., Loos, D., Uuemaa, E., Chan, W. T., Delouis, J.-M., and Odaka, T.: XDGGS: A community-developed Xarray package to support planetary DGGS data cube computations, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4/W12-2024, 75–80, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-75-2024, 2024." assertion.
- requirements.txt description "Python requirements.txt for running the Jupyter Notebooks." assertion.
- requirements.txt description "Python requirements.txt for running the Jupyter Notebooks." assertion.
- Riomar_RO.ipynb description "In this notebook, we will learn how to create a simple RO-Crate from the RiOMar data. We will then identify any missing metadata that needs to be added to the original dataset’s metadata." assertion.
- Riomar_RO.ipynb description "In this notebook, we will learn how to create a simple RO-Crate from the RiOMar data. We will then identify any missing metadata that needs to be added to the original dataset’s metadata." assertion.
- pangeo-riomar.ipynb description "The goal is to regrid a sample of RiOMar data into DGGS (Healpix)." assertion.
- pangeo-riomar.ipynb description "The goal is to regrid a sample of RiOMar data into DGGS (Healpix)." assertion.
- pangeo-riomar_resize_datarmor.ipynb description "The goal is to create a smaller RiOMar dataset to test regridding to Healpix on Pangeo EOSC." assertion.
- pangeo-riomar_resize_datarmor.ipynb description "The goal is to create a smaller RiOMar dataset to test regridding to Healpix on Pangeo EOSC." assertion.
- riomar_plots-datatree_multiresoplot.ipynb description "The use of multiscale Zarr in combination with the Discrete Global Grid System (DGGS) for Earth Observation aims to enhance the efficiency and scalability of storing, accessing, and analyzing large geospatial datasets. Multiscale Zarr allows for efficient compression and chunking of data, enabling rapid access to high-resolution imagery and other spatial datasets. When integrated with DGGS, which provides a hierarchical, cell-based representation of the Earth’s surface, this approach facilitates seamless multi-resolution analysis, improves interoperability, and supports advanced geospatial processing and visualization, ultimately enabling more effective monitoring and understanding of environmental changes." assertion.
- riomar_plots-datatree_multiresoplot.ipynb description "The use of multiscale Zarr in combination with the Discrete Global Grid System (DGGS) for Earth Observation aims to enhance the efficiency and scalability of storing, accessing, and analyzing large geospatial datasets. Multiscale Zarr allows for efficient compression and chunking of data, enabling rapid access to high-resolution imagery and other spatial datasets. When integrated with DGGS, which provides a hierarchical, cell-based representation of the Earth’s surface, this approach facilitates seamless multi-resolution analysis, improves interoperability, and supports advanced geospatial processing and visualization, ultimately enabling more effective monitoring and understanding of environmental changes." assertion.
- virtualizarr_riomar_kerchunk.ipynb description "The goal is to create a virtualzarr for all RiOMar data using Kerchunk (since Icechunk does not work at the moment on Pangeo-EOSC or for data on datamor (https access)." assertion.
- virtualizarr_riomar_kerchunk.ipynb description "The goal is to create a virtualzarr for all RiOMar data using Kerchunk (since Icechunk does not work at the moment on Pangeo-EOSC or for data on datamor (https access)." assertion.
- visualize-riomar..ipynb description "## Purpose The goal is to visualize the DGGS transformed RiOMar data with xdggs and lonboard. ## Description In this notebook, we will: - Open DGGS RiOMar dataset - Visualize it using a colorblind-friendly colormap" assertion.
- visualize-riomar..ipynb description "## Purpose The goal is to visualize the DGGS transformed RiOMar data with xdggs and lonboard. ## Description In this notebook, we will: - Open DGGS RiOMar dataset - Visualize it using a colorblind-friendly colormap" assertion.
- croco_grd.nc description "This is the grid of the Croco model used to generate RiOMar data." assertion.
- croco_grd.nc description "This is the grid of the Croco model used to generate RiOMar data." assertion.
- GAMAR_1h_inst_Y2006M01.nc description "Raw RiOMar dataset generated by the Croco RiOMar numerical model. It corresponds to one month of simulation (January 2006)." assertion.
- GAMAR_1h_inst_Y2006M01.nc description "Raw RiOMar dataset generated by the Croco RiOMar numerical model. It corresponds to one month of simulation (January 2006)." assertion.
- small.zarr description "Small Zarr file generated from the original RiOMar data by selecting a few timestep to reduce the total size and make it easier to write Jupyter notebook examplifying the transformation from the original grid to DGGS Healpix grid." assertion.
- small.zarr description "Small Zarr file generated from the original RiOMar data by selecting a few timestep to reduce the total size and make it easier to write Jupyter notebook examplifying the transformation from the original grid to DGGS Healpix grid." assertion.
- small_healpix.zarr description "A sample dataset in DGGS Level 12 Healpix" assertion.
- small_healpix.zarr description "A sample dataset in DGGS Level 12 Healpix" assertion.
- small_healpix_13.zarr description "A sample dataset in DGGS Level 13 Healpix" assertion.
- small_healpix_13.zarr description "A sample dataset in DGGS Level 13 Healpix" assertion.
- small_healpix_14.zarr description "A sample dataset in DGGS Level 14 Healpix" assertion.
- small_healpix_14.zarr description "A sample dataset in DGGS Level 14 Healpix" assertion.
- 9ed8167f-1789-4eb4-ba9e-3a74f25c53e8 description "This study tested whether human body orientation can influence the behavior of bull sharks by examining sharks’ approach distances from a person positioned vertically or horizontally in the water. Results showed that bull sharks, Carcharhinus leucas, kept a significantly greater distance when the test subject was standing in chest-deep water with his head above water versus lying on the ocean floor. Furthermore, larger bull sharks in the immediate area withdrew when the subject entered the water" assertion.
- 9ed8167f-1789-4eb4-ba9e-3a74f25c53e8 description "This study tested whether human body orientation can influence the behavior of bull sharks by examining sharks’ approach distances from a person positioned vertically or horizontally in the water. Results showed that bull sharks, Carcharhinus leucas, kept a significantly greater distance when the test subject was standing in chest-deep water with his head above water versus lying on the ocean floor. Furthermore, larger bull sharks in the immediate area withdrew when the subject entered the water" assertion.
- 4810 description "" assertion.
- 4810 description "" assertion.
- 1514325d-4838-4b09-a7a4-4b37167f8583 description "This is test of DMP creation." assertion.
- 1514325d-4838-4b09-a7a4-4b37167f8583 description "This is test of DMP creation." assertion.
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- 226e3b85-3dd9-4e57-aff9-24957b346fe3 description "Vestibulum ante ipsum primis in faucibus orci luctus et ultrices posuere cubilia curae; Etiam eleifend suscipit erat sed vulputate. Nulla scelerisque accumsan nulla sed congue. Quisque tempus ante et ligula aliquam elementum. Aliquam consequat varius mi sit amet rhoncus. Aenean in cursus mauris. Aenean consequat erat nisl. Vivamus scelerisque fermentum fermentum. Duis dignissim pellentesque odio, eget tincidunt diam aliquam lacinia. Pellentesque ut purus pharetra, porttitor mi vitae, pulvinar est. Pellentesque mollis nibh tristique tincidunt imperdiet. Nunc pharetra porta tincidunt. Integer consectetur lectus nec quam dictum, et interdum ligula aliquet. Pellentesque habitant morbi tristique senectus et netus et malesuada fames ac turpis egestas. Sed a accumsan turpis. Praesent rutrum fermentum nibh." assertion.
- dc0b871b-7a72-47c0-b20e-aa3e0d7a48c0 description "Lorem ipsum dolor sit amet, consectetur adipiscing elit. Cras vitae erat nec nisi molestie molestie vitae ut nulla. Nullam volutpat, augue eu pellentesque tempus, turpis arcu ultrices lectus, aliquet facilisis nunc est sit amet sem. Quisque id dapibus justo, ac tristique nisl. Integer ac enim viverra, lobortis neque nec, accumsan sapien. Aliquam in arcu sit amet ex placerat blandit. Aliquam a posuere odio. Donec vitae lacinia purus." assertion.
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- fsad087 description "Large-scale electronic tagging is a very powerful tool to study how fish movements and migrations shape the internal dynamics of populations. This knowledge, crucial for improving fishery management, was still limited for the European seabass, whose stocks in the Northeast Atlantic have declined drastically over the last decade. To better understand the species ecology and the spatio-temporal structure of the population, we tagged seabass in the North Sea, the English Channel, and the Bay of Biscay, from 2014 to 2016. Out of 1220 deployed DSTs, 482 have been recovered by November 2022. Approximately half of them included a period of potential spawning migration. Reconstructed trajectories confirmed seabass to be a partial migratory species, as individuals exhibited either long-distance migrations or residence. Most migrants exhibited fidelity to summer feeding areas and winter spawning areas. Our dataset enriches the knowledge of seabass biological traits (e.g. temperature and depth ranges, vulnerability to predation and fishing). Our results suggest a spatial structure of the Atlantic population that differs from the stock structure currently considered for assessment and management. The consequences should be explored at both the European level and by regional managers involved in conservation outcomes." assertion.
- fsad087 description "Large-scale electronic tagging is a very powerful tool to study how fish movements and migrations shape the internal dynamics of populations. This knowledge, crucial for improving fishery management, was still limited for the European seabass, whose stocks in the Northeast Atlantic have declined drastically over the last decade. To better understand the species ecology and the spatio-temporal structure of the population, we tagged seabass in the North Sea, the English Channel, and the Bay of Biscay, from 2014 to 2016. Out of 1220 deployed DSTs, 482 have been recovered by November 2022. Approximately half of them included a period of potential spawning migration. Reconstructed trajectories confirmed seabass to be a partial migratory species, as individuals exhibited either long-distance migrations or residence. Most migrants exhibited fidelity to summer feeding areas and winter spawning areas. Our dataset enriches the knowledge of seabass biological traits (e.g. temperature and depth ranges, vulnerability to predation and fishing). Our results suggest a spatial structure of the Atlantic population that differs from the stock structure currently considered for assessment and management. The consequences should be explored at both the European level and by regional managers involved in conservation outcomes." assertion.
