Data from: Projected distributions of Southern Ocean albatrosses, petrels and fisheries as a consequence of climatic change ...
Given the major ongoing influence of environmental change on the oceans, there is a need to understand and predict the future distributions of marine species in order to plan appropriate mitigation to conserve vulnerable species and ecosystems. In this study we use tracking data from seven large sea...
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Online Access: | https://dx.doi.org/10.5061/dryad.b4217 https://datadryad.org/stash/dataset/doi:10.5061/dryad.b4217 |
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ftdatacite:10.5061/dryad.b4217 2024-02-04T10:00:00+01:00 Data from: Projected distributions of Southern Ocean albatrosses, petrels and fisheries as a consequence of climatic change ... Krüger, Lucas Ramos, J. A. Xavier, J. C. Grémillet, D. González-Solís, J. Petry, M. V. Phillips, R. A. Wanless, R. M. Paiva, V. H. 2017 https://dx.doi.org/10.5061/dryad.b4217 https://datadryad.org/stash/dataset/doi:10.5061/dryad.b4217 en eng Dryad https://dx.doi.org/10.1111/ecog.02590 Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode cc0-1.0 Representative Concentration Pathways Thalassarche melanophris Macronectes giganteus Geographic Information System Diomedea dabbenena Diomedea exulans Procellaria aequinoctialis Thalassarche chrysostoma Macronectes halli Dataset dataset 2017 ftdatacite https://doi.org/10.5061/dryad.b421710.1111/ecog.02590 2024-01-05T04:39:59Z Given the major ongoing influence of environmental change on the oceans, there is a need to understand and predict the future distributions of marine species in order to plan appropriate mitigation to conserve vulnerable species and ecosystems. In this study we use tracking data from seven large seabird species of the Southern Ocean (Black-browed Albatross Thalassarche melanophris, Grey-headed Albatross T. chrysostoma, Northern Giant Petrel Macronectes halli, Southern Giant Petrel M. giganteus, Tristan Albatross Diomedea dabbenena Wandering Albatross D. exulans and White-chinned Petrel Procellaria aequinoctialis , and on fishing effort in two types of fisheries (characterised by low or high-bycatch rates), to model the associations with environmental variables (bathymetry, chlorophyll-a concentration, sea surface temperature and wind speed) through ensemble Species Distribution Models. We then project these distributions according to four climate change scenarios built by the Intergovernmental Panel for ... : Data for Krüger et al. 2017 DOI: 10.1111/ecog.02590The zip file contains eight folders, one with the environmental data used for modelling (Sea Surface Temperature SST, Chlorophyll CHLOR, Wind Speed WIND, Sea Ice Cover ICE, Bathymetry BATH) and their projections for each representative concentration pathways (RCPs) for 2050 and 2100. One folder with the distribution of fisheries types in .csv (geographic coordinate system, WGS84) and geotiff images for the species and fisheries distribution models (files with the name pred) and projections for each scenario. Also the scripts used for SDMs and GWPCA are presented in the file.kruger_ecog02590.zip ... Dataset Diomedea exulans Giant Petrel Macronectes giganteus Sea ice Southern Ocean Wandering Albatross DataCite Metadata Store (German National Library of Science and Technology) Giganteus ENVELOPE(62.500,62.500,-67.567,-67.567) Southern Ocean Tristan ENVELOPE(140.900,140.900,-66.735,-66.735) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
Representative Concentration Pathways Thalassarche melanophris Macronectes giganteus Geographic Information System Diomedea dabbenena Diomedea exulans Procellaria aequinoctialis Thalassarche chrysostoma Macronectes halli |
spellingShingle |
Representative Concentration Pathways Thalassarche melanophris Macronectes giganteus Geographic Information System Diomedea dabbenena Diomedea exulans Procellaria aequinoctialis Thalassarche chrysostoma Macronectes halli Krüger, Lucas Ramos, J. A. Xavier, J. C. Grémillet, D. González-Solís, J. Petry, M. V. Phillips, R. A. Wanless, R. M. Paiva, V. H. Data from: Projected distributions of Southern Ocean albatrosses, petrels and fisheries as a consequence of climatic change ... |
topic_facet |
Representative Concentration Pathways Thalassarche melanophris Macronectes giganteus Geographic Information System Diomedea dabbenena Diomedea exulans Procellaria aequinoctialis Thalassarche chrysostoma Macronectes halli |
description |
Given the major ongoing influence of environmental change on the oceans, there is a need to understand and predict the future distributions of marine species in order to plan appropriate mitigation to conserve vulnerable species and ecosystems. In this study we use tracking data from seven large seabird species of the Southern Ocean (Black-browed Albatross Thalassarche melanophris, Grey-headed Albatross T. chrysostoma, Northern Giant Petrel Macronectes halli, Southern Giant Petrel M. giganteus, Tristan Albatross Diomedea dabbenena Wandering Albatross D. exulans and White-chinned Petrel Procellaria aequinoctialis , and on fishing effort in two types of fisheries (characterised by low or high-bycatch rates), to model the associations with environmental variables (bathymetry, chlorophyll-a concentration, sea surface temperature and wind speed) through ensemble Species Distribution Models. We then project these distributions according to four climate change scenarios built by the Intergovernmental Panel for ... : Data for Krüger et al. 2017 DOI: 10.1111/ecog.02590The zip file contains eight folders, one with the environmental data used for modelling (Sea Surface Temperature SST, Chlorophyll CHLOR, Wind Speed WIND, Sea Ice Cover ICE, Bathymetry BATH) and their projections for each representative concentration pathways (RCPs) for 2050 and 2100. One folder with the distribution of fisheries types in .csv (geographic coordinate system, WGS84) and geotiff images for the species and fisheries distribution models (files with the name pred) and projections for each scenario. Also the scripts used for SDMs and GWPCA are presented in the file.kruger_ecog02590.zip ... |
format |
Dataset |
author |
Krüger, Lucas Ramos, J. A. Xavier, J. C. Grémillet, D. González-Solís, J. Petry, M. V. Phillips, R. A. Wanless, R. M. Paiva, V. H. |
author_facet |
Krüger, Lucas Ramos, J. A. Xavier, J. C. Grémillet, D. González-Solís, J. Petry, M. V. Phillips, R. A. Wanless, R. M. Paiva, V. H. |
author_sort |
Krüger, Lucas |
title |
Data from: Projected distributions of Southern Ocean albatrosses, petrels and fisheries as a consequence of climatic change ... |
title_short |
Data from: Projected distributions of Southern Ocean albatrosses, petrels and fisheries as a consequence of climatic change ... |
title_full |
Data from: Projected distributions of Southern Ocean albatrosses, petrels and fisheries as a consequence of climatic change ... |
title_fullStr |
Data from: Projected distributions of Southern Ocean albatrosses, petrels and fisheries as a consequence of climatic change ... |
title_full_unstemmed |
Data from: Projected distributions of Southern Ocean albatrosses, petrels and fisheries as a consequence of climatic change ... |
title_sort |
data from: projected distributions of southern ocean albatrosses, petrels and fisheries as a consequence of climatic change ... |
publisher |
Dryad |
publishDate |
2017 |
url |
https://dx.doi.org/10.5061/dryad.b4217 https://datadryad.org/stash/dataset/doi:10.5061/dryad.b4217 |
long_lat |
ENVELOPE(62.500,62.500,-67.567,-67.567) ENVELOPE(140.900,140.900,-66.735,-66.735) |
geographic |
Giganteus Southern Ocean Tristan |
geographic_facet |
Giganteus Southern Ocean Tristan |
genre |
Diomedea exulans Giant Petrel Macronectes giganteus Sea ice Southern Ocean Wandering Albatross |
genre_facet |
Diomedea exulans Giant Petrel Macronectes giganteus Sea ice Southern Ocean Wandering Albatross |
op_relation |
https://dx.doi.org/10.1111/ecog.02590 |
op_rights |
Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode cc0-1.0 |
op_doi |
https://doi.org/10.5061/dryad.b421710.1111/ecog.02590 |
_version_ |
1789965081331630080 |