Modeling Eastern Russian High Arctic Geese (Anser fabalis, A. albifrons) during moult and brood rearing in the ‘New Digital Arctic’
Abstract Many polar species and habitats are now affected by man-made global climate change and underlying infrastructure. These anthropogenic forces have resulted in clear implications and many significant changes in the arctic, leading to the emergence of new climate, habitats and other issues inc...
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ftdoajarticles:oai:doaj.org/article:fb9b7afd8ee64f3fb75d3e4305e024da 2023-05-15T13:30:09+02:00 Modeling Eastern Russian High Arctic Geese (Anser fabalis, A. albifrons) during moult and brood rearing in the ‘New Digital Arctic’ Diana Solovyeva Inga Bysykatova-Harmey Sergey L. Vartanyan Alexander Kondratyev Falk Huettmann 2021-11-01T00:00:00Z https://doi.org/10.1038/s41598-021-01595-7 https://doaj.org/article/fb9b7afd8ee64f3fb75d3e4305e024da EN eng Nature Portfolio https://doi.org/10.1038/s41598-021-01595-7 https://doaj.org/toc/2045-2322 doi:10.1038/s41598-021-01595-7 2045-2322 https://doaj.org/article/fb9b7afd8ee64f3fb75d3e4305e024da Scientific Reports, Vol 11, Iss 1, Pp 1-13 (2021) Medicine R Science Q article 2021 ftdoajarticles https://doi.org/10.1038/s41598-021-01595-7 2022-12-31T11:29:03Z Abstract Many polar species and habitats are now affected by man-made global climate change and underlying infrastructure. These anthropogenic forces have resulted in clear implications and many significant changes in the arctic, leading to the emergence of new climate, habitats and other issues including digital online infrastructure representing a ‘New Artic’. Arctic grazers, like Eastern Russian migratory populations of Tundra Bean Goose Anser fabalis and Greater White-fronted Goose A. albifrons, are representative examples and they are affected along the entire flyway in East Asia, namely China, Japan and Korea. Here we present the best publicly-available long-term (24 years) digitized geographic information system (GIS) data for the breeding study area (East Yakutia and Chukotka) and its habitats with ISO-compliant metadata. Further, we used seven publicly available compiled Open Access GIS predictor layers to predict the distribution for these two species within the tundra habitats. Using BIG DATA we are able to improve on the ecological niche prediction inference for both species by focusing for the first time specifically on biological relevant population cohorts: post-breeding moulting non-breeders, as well as post-breeding parent birds with broods. To assure inference with certainty, we assessed it with 4 lines of evidence including alternative best-available open access field data from GBIF.org as well as occurrence data compiled from the literature. Despite incomplete data, we found a good model accuracy in support of our evidence for a robust inference of the species distributions. Our predictions indicate a strong publicly best-available relative index of occurrence (RIO). These results are based on the quantified ecological niche showing more realistic gradual occurrence patterns but which are not fully in agreement with the current strictly applied parsimonious flyway and species delineations. While our predictions are to be improved further, e.g. when synergetic data are made freely available, ... Article in Journal/Newspaper Anser fabalis Arctic Chukotka Climate change Tundra Yakutia Directory of Open Access Journals: DOAJ Articles Arctic Scientific Reports 11 1 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
Medicine R Science Q |
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Medicine R Science Q Diana Solovyeva Inga Bysykatova-Harmey Sergey L. Vartanyan Alexander Kondratyev Falk Huettmann Modeling Eastern Russian High Arctic Geese (Anser fabalis, A. albifrons) during moult and brood rearing in the ‘New Digital Arctic’ |
topic_facet |
Medicine R Science Q |
description |
Abstract Many polar species and habitats are now affected by man-made global climate change and underlying infrastructure. These anthropogenic forces have resulted in clear implications and many significant changes in the arctic, leading to the emergence of new climate, habitats and other issues including digital online infrastructure representing a ‘New Artic’. Arctic grazers, like Eastern Russian migratory populations of Tundra Bean Goose Anser fabalis and Greater White-fronted Goose A. albifrons, are representative examples and they are affected along the entire flyway in East Asia, namely China, Japan and Korea. Here we present the best publicly-available long-term (24 years) digitized geographic information system (GIS) data for the breeding study area (East Yakutia and Chukotka) and its habitats with ISO-compliant metadata. Further, we used seven publicly available compiled Open Access GIS predictor layers to predict the distribution for these two species within the tundra habitats. Using BIG DATA we are able to improve on the ecological niche prediction inference for both species by focusing for the first time specifically on biological relevant population cohorts: post-breeding moulting non-breeders, as well as post-breeding parent birds with broods. To assure inference with certainty, we assessed it with 4 lines of evidence including alternative best-available open access field data from GBIF.org as well as occurrence data compiled from the literature. Despite incomplete data, we found a good model accuracy in support of our evidence for a robust inference of the species distributions. Our predictions indicate a strong publicly best-available relative index of occurrence (RIO). These results are based on the quantified ecological niche showing more realistic gradual occurrence patterns but which are not fully in agreement with the current strictly applied parsimonious flyway and species delineations. While our predictions are to be improved further, e.g. when synergetic data are made freely available, ... |
format |
Article in Journal/Newspaper |
author |
Diana Solovyeva Inga Bysykatova-Harmey Sergey L. Vartanyan Alexander Kondratyev Falk Huettmann |
author_facet |
Diana Solovyeva Inga Bysykatova-Harmey Sergey L. Vartanyan Alexander Kondratyev Falk Huettmann |
author_sort |
Diana Solovyeva |
title |
Modeling Eastern Russian High Arctic Geese (Anser fabalis, A. albifrons) during moult and brood rearing in the ‘New Digital Arctic’ |
title_short |
Modeling Eastern Russian High Arctic Geese (Anser fabalis, A. albifrons) during moult and brood rearing in the ‘New Digital Arctic’ |
title_full |
Modeling Eastern Russian High Arctic Geese (Anser fabalis, A. albifrons) during moult and brood rearing in the ‘New Digital Arctic’ |
title_fullStr |
Modeling Eastern Russian High Arctic Geese (Anser fabalis, A. albifrons) during moult and brood rearing in the ‘New Digital Arctic’ |
title_full_unstemmed |
Modeling Eastern Russian High Arctic Geese (Anser fabalis, A. albifrons) during moult and brood rearing in the ‘New Digital Arctic’ |
title_sort |
modeling eastern russian high arctic geese (anser fabalis, a. albifrons) during moult and brood rearing in the ‘new digital arctic’ |
publisher |
Nature Portfolio |
publishDate |
2021 |
url |
https://doi.org/10.1038/s41598-021-01595-7 https://doaj.org/article/fb9b7afd8ee64f3fb75d3e4305e024da |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Anser fabalis Arctic Chukotka Climate change Tundra Yakutia |
genre_facet |
Anser fabalis Arctic Chukotka Climate change Tundra Yakutia |
op_source |
Scientific Reports, Vol 11, Iss 1, Pp 1-13 (2021) |
op_relation |
https://doi.org/10.1038/s41598-021-01595-7 https://doaj.org/toc/2045-2322 doi:10.1038/s41598-021-01595-7 2045-2322 https://doaj.org/article/fb9b7afd8ee64f3fb75d3e4305e024da |
op_doi |
https://doi.org/10.1038/s41598-021-01595-7 |
container_title |
Scientific Reports |
container_volume |
11 |
container_issue |
1 |
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1766005734749765632 |