First Three-dimensional Quantification of Planktic Food Chain lower levels (Copepods) for the Ross Sea region Marine Protected Area (RSRMPA), Antarctica: Using FAIR-inspired legacy data with Machine Learning, and Open Source GIS
This dataset is relative to the paper entitled: "First Three-dimensional Quantification of Planktic Food Chain lower levels (Copepods) for the Ross Sea region Marine Protected Area (RSRMPA), Antarctica: Using FAIR-inspired legacy data with Machine Learning, and Open Source GIS" publishing...
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Online Access: | https://doi.org/10.5281/zenodo.6389676 |
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ftzenodo:oai:zenodo.org:6389676 2024-09-15T17:44:21+00:00 First Three-dimensional Quantification of Planktic Food Chain lower levels (Copepods) for the Ross Sea region Marine Protected Area (RSRMPA), Antarctica: Using FAIR-inspired legacy data with Machine Learning, and Open Source GIS Marco Grillo Falk Huettmann Letterio Guglielmo Stefano Schiaparelli 2022-03-29 https://doi.org/10.5281/zenodo.6389676 eng eng Zenodo https://doi.org/10.5281/zenodo.6389675 https://doi.org/10.5281/zenodo.6389676 oai:zenodo.org:6389676 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode Machine learning Antarctic copepods Species Distribution Models (SDMs) Ross Sea Open Source FAIR data info:eu-repo/semantics/other 2022 ftzenodo https://doi.org/10.5281/zenodo.638967610.5281/zenodo.6389675 2024-07-27T07:39:32Z This dataset is relative to the paper entitled: "First Three-dimensional Quantification of Planktic Food Chain lower levels (Copepods) for the Ross Sea region Marine Protected Area (RSRMPA), Antarctica: Using FAIR-inspired legacy data with Machine Learning, and Open Source GIS" publishing in journal Diversity (MPDI). Abstract: Zooplankton is a fundamental group in all aquatic ecosystems located the base of the food chain. It forms a link between the lower trophic levels with secondary consumers and shows marked fluctuations of populations with environmental change, especially reacting to heating and water acidification. At sea copepod crustaceans account for app. 70% in abundance of zooplankton and are a target of monitoring activities in key areas such as the Southern Ocean. In this study we have used FAIR-inspired legacy data (dating back to the ‘80s) collected in the Ross Sea by the Italian National Antarctic Program in GBIF.org. Together with other open-access GIS data sources and tools it allows generating, for the first time, three-dimensional predictive distribution maps for twenty-six copepod species. These predictive maps were obtained by applying machine learning techniques to grey literature data, which were visualized in open-source GIS platforms. In a Species Distribution Modeling (SDM) frameworkwe used machine learning with three types of algorithms (TreeNet, RandomForest and Ensemble) to analyze the presence and absence of copepods at different areas and depth classes in function of environmental descriptors obtained from the Polar Macroscope Layers present in Quantartica. The models allow for the first time to map-predict the food chain in quantitative terms showing the relative index of occurrence (RIO) and identified the presence for each copepod species analyzed in the Ross Sea. Our results show marked geographical preferences that vary with species and trophic strategy. This study demonstrates that machine learning is a successful method in accurately predicting Antarctic copepod presence, ... Other/Unknown Material Antarc* Antarctic Antarctica Ross Sea Southern Ocean Copepods Zenodo |
institution |
Open Polar |
collection |
Zenodo |
op_collection_id |
ftzenodo |
language |
English |
topic |
Machine learning Antarctic copepods Species Distribution Models (SDMs) Ross Sea Open Source FAIR data |
spellingShingle |
Machine learning Antarctic copepods Species Distribution Models (SDMs) Ross Sea Open Source FAIR data Marco Grillo Falk Huettmann Letterio Guglielmo Stefano Schiaparelli First Three-dimensional Quantification of Planktic Food Chain lower levels (Copepods) for the Ross Sea region Marine Protected Area (RSRMPA), Antarctica: Using FAIR-inspired legacy data with Machine Learning, and Open Source GIS |
topic_facet |
Machine learning Antarctic copepods Species Distribution Models (SDMs) Ross Sea Open Source FAIR data |
description |
This dataset is relative to the paper entitled: "First Three-dimensional Quantification of Planktic Food Chain lower levels (Copepods) for the Ross Sea region Marine Protected Area (RSRMPA), Antarctica: Using FAIR-inspired legacy data with Machine Learning, and Open Source GIS" publishing in journal Diversity (MPDI). Abstract: Zooplankton is a fundamental group in all aquatic ecosystems located the base of the food chain. It forms a link between the lower trophic levels with secondary consumers and shows marked fluctuations of populations with environmental change, especially reacting to heating and water acidification. At sea copepod crustaceans account for app. 70% in abundance of zooplankton and are a target of monitoring activities in key areas such as the Southern Ocean. In this study we have used FAIR-inspired legacy data (dating back to the ‘80s) collected in the Ross Sea by the Italian National Antarctic Program in GBIF.org. Together with other open-access GIS data sources and tools it allows generating, for the first time, three-dimensional predictive distribution maps for twenty-six copepod species. These predictive maps were obtained by applying machine learning techniques to grey literature data, which were visualized in open-source GIS platforms. In a Species Distribution Modeling (SDM) frameworkwe used machine learning with three types of algorithms (TreeNet, RandomForest and Ensemble) to analyze the presence and absence of copepods at different areas and depth classes in function of environmental descriptors obtained from the Polar Macroscope Layers present in Quantartica. The models allow for the first time to map-predict the food chain in quantitative terms showing the relative index of occurrence (RIO) and identified the presence for each copepod species analyzed in the Ross Sea. Our results show marked geographical preferences that vary with species and trophic strategy. This study demonstrates that machine learning is a successful method in accurately predicting Antarctic copepod presence, ... |
format |
Other/Unknown Material |
author |
Marco Grillo Falk Huettmann Letterio Guglielmo Stefano Schiaparelli |
author_facet |
Marco Grillo Falk Huettmann Letterio Guglielmo Stefano Schiaparelli |
author_sort |
Marco Grillo |
title |
First Three-dimensional Quantification of Planktic Food Chain lower levels (Copepods) for the Ross Sea region Marine Protected Area (RSRMPA), Antarctica: Using FAIR-inspired legacy data with Machine Learning, and Open Source GIS |
title_short |
First Three-dimensional Quantification of Planktic Food Chain lower levels (Copepods) for the Ross Sea region Marine Protected Area (RSRMPA), Antarctica: Using FAIR-inspired legacy data with Machine Learning, and Open Source GIS |
title_full |
First Three-dimensional Quantification of Planktic Food Chain lower levels (Copepods) for the Ross Sea region Marine Protected Area (RSRMPA), Antarctica: Using FAIR-inspired legacy data with Machine Learning, and Open Source GIS |
title_fullStr |
First Three-dimensional Quantification of Planktic Food Chain lower levels (Copepods) for the Ross Sea region Marine Protected Area (RSRMPA), Antarctica: Using FAIR-inspired legacy data with Machine Learning, and Open Source GIS |
title_full_unstemmed |
First Three-dimensional Quantification of Planktic Food Chain lower levels (Copepods) for the Ross Sea region Marine Protected Area (RSRMPA), Antarctica: Using FAIR-inspired legacy data with Machine Learning, and Open Source GIS |
title_sort |
first three-dimensional quantification of planktic food chain lower levels (copepods) for the ross sea region marine protected area (rsrmpa), antarctica: using fair-inspired legacy data with machine learning, and open source gis |
publisher |
Zenodo |
publishDate |
2022 |
url |
https://doi.org/10.5281/zenodo.6389676 |
genre |
Antarc* Antarctic Antarctica Ross Sea Southern Ocean Copepods |
genre_facet |
Antarc* Antarctic Antarctica Ross Sea Southern Ocean Copepods |
op_relation |
https://doi.org/10.5281/zenodo.6389675 https://doi.org/10.5281/zenodo.6389676 oai:zenodo.org:6389676 |
op_rights |
info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode |
op_doi |
https://doi.org/10.5281/zenodo.638967610.5281/zenodo.6389675 |
_version_ |
1810491820485902336 |