DataSheet_2_Using marine mammal necropsy data in animal health surveillance: the case of the harbor porpoise in the Southern North Sea.docx
Rapid changes of marine ecosystems resulting from human activities and climate change, and the subsequent reported rise of infectious diseases in marine mammals, highlight the urgency for timely detection of unusual health events negatively affecting populations. Studies reporting pathological findi...
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ftfrontimediafig:oai:figshare.com:article/24997385 2024-02-11T10:06:47+01:00 DataSheet_2_Using marine mammal necropsy data in animal health surveillance: the case of the harbor porpoise in the Southern North Sea.docx Lonneke L. IJsseldijk Jan van den Broek Marja J. L. Kik Mardik F. Leopold Elisa Bravo Rebolledo Andrea Gröne Hans Heesterbeek 2024-01-15T04:17:59Z https://doi.org/10.3389/fmars.2023.1306294.s002 https://figshare.com/articles/dataset/DataSheet_2_Using_marine_mammal_necropsy_data_in_animal_health_surveillance_the_case_of_the_harbor_porpoise_in_the_Southern_North_Sea_docx/24997385 unknown doi:10.3389/fmars.2023.1306294.s002 https://figshare.com/articles/dataset/DataSheet_2_Using_marine_mammal_necropsy_data_in_animal_health_surveillance_the_case_of_the_harbor_porpoise_in_the_Southern_North_Sea_docx/24997385 CC BY 4.0 Oceanography Marine Biology Marine Geoscience Biological Oceanography Chemical Oceanography Physical Oceanography Marine Engineering cetacean post-mortem investigation animal health surveillance supervised classification methods unsupervised classification methods causes of death Dataset 2024 ftfrontimediafig https://doi.org/10.3389/fmars.2023.1306294.s002 2024-01-18T00:14:33Z Rapid changes of marine ecosystems resulting from human activities and climate change, and the subsequent reported rise of infectious diseases in marine mammals, highlight the urgency for timely detection of unusual health events negatively affecting populations. Studies reporting pathological findings in the commonly stranded harbor porpoise (Phocoena phocoena) on North Atlantic coastlines are essential to describe new and emerging causes of mortality. However, such studies often cannot be used as long-term health surveillance tools due to analytical limitations. We tested 31 variables gained from stranding-, necropsy-, dietary- and marine debris data from 405 harbor porpoises using applied supervised and unsupervised machine learning techniques to explore and analyze this large dataset. We classified and cross-correlated the variables and characterized the importance of the different variables for accurately predicting cause-of-death categories, to allow trend assessment for good conservation decision. The variable ‘age class’ seemed most influential in determining cause-of-death categories, and it became apparent that juveniles died more often due to acute causes, including bycatch, grey-seal-predation and other trauma, while adults of infectious diseases. Neonates were found in summer, and mostly without prey in their stomach and more often stranded alive. The variables assigned as part of the external examination of carcasses, such as imprints from nets and lesions induced by predators, as well as nutritional condition were most important for predicting cause-of-death categories, with a model prediction accuracy of 75%. Future porpoise monitoring, and in particular the assessment of temporal trends, should predominantly focus on influential variables as determined in this study. Pathogen- and contaminant assessment data was not available for all cases, but would be an important step to further complete the dataset. This could be vital for drawing population-inferences and thus for long-term harbor porpoise ... Dataset North Atlantic Phocoena phocoena Frontiers: Figshare |
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Open Polar |
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Frontiers: Figshare |
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ftfrontimediafig |
language |
unknown |
topic |
Oceanography Marine Biology Marine Geoscience Biological Oceanography Chemical Oceanography Physical Oceanography Marine Engineering cetacean post-mortem investigation animal health surveillance supervised classification methods unsupervised classification methods causes of death |
spellingShingle |
Oceanography Marine Biology Marine Geoscience Biological Oceanography Chemical Oceanography Physical Oceanography Marine Engineering cetacean post-mortem investigation animal health surveillance supervised classification methods unsupervised classification methods causes of death Lonneke L. IJsseldijk Jan van den Broek Marja J. L. Kik Mardik F. Leopold Elisa Bravo Rebolledo Andrea Gröne Hans Heesterbeek DataSheet_2_Using marine mammal necropsy data in animal health surveillance: the case of the harbor porpoise in the Southern North Sea.docx |
topic_facet |
Oceanography Marine Biology Marine Geoscience Biological Oceanography Chemical Oceanography Physical Oceanography Marine Engineering cetacean post-mortem investigation animal health surveillance supervised classification methods unsupervised classification methods causes of death |
description |
Rapid changes of marine ecosystems resulting from human activities and climate change, and the subsequent reported rise of infectious diseases in marine mammals, highlight the urgency for timely detection of unusual health events negatively affecting populations. Studies reporting pathological findings in the commonly stranded harbor porpoise (Phocoena phocoena) on North Atlantic coastlines are essential to describe new and emerging causes of mortality. However, such studies often cannot be used as long-term health surveillance tools due to analytical limitations. We tested 31 variables gained from stranding-, necropsy-, dietary- and marine debris data from 405 harbor porpoises using applied supervised and unsupervised machine learning techniques to explore and analyze this large dataset. We classified and cross-correlated the variables and characterized the importance of the different variables for accurately predicting cause-of-death categories, to allow trend assessment for good conservation decision. The variable ‘age class’ seemed most influential in determining cause-of-death categories, and it became apparent that juveniles died more often due to acute causes, including bycatch, grey-seal-predation and other trauma, while adults of infectious diseases. Neonates were found in summer, and mostly without prey in their stomach and more often stranded alive. The variables assigned as part of the external examination of carcasses, such as imprints from nets and lesions induced by predators, as well as nutritional condition were most important for predicting cause-of-death categories, with a model prediction accuracy of 75%. Future porpoise monitoring, and in particular the assessment of temporal trends, should predominantly focus on influential variables as determined in this study. Pathogen- and contaminant assessment data was not available for all cases, but would be an important step to further complete the dataset. This could be vital for drawing population-inferences and thus for long-term harbor porpoise ... |
format |
Dataset |
author |
Lonneke L. IJsseldijk Jan van den Broek Marja J. L. Kik Mardik F. Leopold Elisa Bravo Rebolledo Andrea Gröne Hans Heesterbeek |
author_facet |
Lonneke L. IJsseldijk Jan van den Broek Marja J. L. Kik Mardik F. Leopold Elisa Bravo Rebolledo Andrea Gröne Hans Heesterbeek |
author_sort |
Lonneke L. IJsseldijk |
title |
DataSheet_2_Using marine mammal necropsy data in animal health surveillance: the case of the harbor porpoise in the Southern North Sea.docx |
title_short |
DataSheet_2_Using marine mammal necropsy data in animal health surveillance: the case of the harbor porpoise in the Southern North Sea.docx |
title_full |
DataSheet_2_Using marine mammal necropsy data in animal health surveillance: the case of the harbor porpoise in the Southern North Sea.docx |
title_fullStr |
DataSheet_2_Using marine mammal necropsy data in animal health surveillance: the case of the harbor porpoise in the Southern North Sea.docx |
title_full_unstemmed |
DataSheet_2_Using marine mammal necropsy data in animal health surveillance: the case of the harbor porpoise in the Southern North Sea.docx |
title_sort |
datasheet_2_using marine mammal necropsy data in animal health surveillance: the case of the harbor porpoise in the southern north sea.docx |
publishDate |
2024 |
url |
https://doi.org/10.3389/fmars.2023.1306294.s002 https://figshare.com/articles/dataset/DataSheet_2_Using_marine_mammal_necropsy_data_in_animal_health_surveillance_the_case_of_the_harbor_porpoise_in_the_Southern_North_Sea_docx/24997385 |
genre |
North Atlantic Phocoena phocoena |
genre_facet |
North Atlantic Phocoena phocoena |
op_relation |
doi:10.3389/fmars.2023.1306294.s002 https://figshare.com/articles/dataset/DataSheet_2_Using_marine_mammal_necropsy_data_in_animal_health_surveillance_the_case_of_the_harbor_porpoise_in_the_Southern_North_Sea_docx/24997385 |
op_rights |
CC BY 4.0 |
op_doi |
https://doi.org/10.3389/fmars.2023.1306294.s002 |
_version_ |
1790604736477528064 |