Assessment of a non-invasive approach to pregnancy diagnosis in gray whales through drone-based photogrammetry and faecal hormone analysis
Funding: This project was supported by the NOAA National Marine Fisheries Service Office of Science and Technology, the Office of Naval Research Marine Mammals and Biology Program (no. N00014-20-1-2760), the Oregon State University Marine Mammal Institute and Oregon Sea Grant. Knowledge of baleen wh...
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Online Access: | http://hdl.handle.net/10023/28000 https://doi.org/10.1098/rsos.230452 |
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ftstandrewserep:oai:research-repository.st-andrews.ac.uk:10023/28000 2023-08-27T04:08:38+02:00 Assessment of a non-invasive approach to pregnancy diagnosis in gray whales through drone-based photogrammetry and faecal hormone analysis Fernandez Ajó, Alejandro Pirotta, Enrico Bierlich, K. C. Hildebrand, Lisa Bird, Clara N. Hunt, Kathleen E. Buck, C. Loren New, Leslie Dillon, Danielle Torres, Leigh G. University of St Andrews. School of Biology 2023-07-21T11:30:09Z 21 application/pdf http://hdl.handle.net/10023/28000 https://doi.org/10.1098/rsos.230452 eng eng Royal Society Open Science Fernandez Ajó , A , Pirotta , E , Bierlich , K C , Hildebrand , L , Bird , C N , Hunt , K E , Buck , C L , New , L , Dillon , D & Torres , L G 2023 , ' Assessment of a non-invasive approach to pregnancy diagnosis in gray whales through drone-based photogrammetry and faecal hormone analysis ' , Royal Society Open Science , vol. 10 , no. 7 , 230452 . https://doi.org/10.1098/rsos.230452 2054-5703 PURE: 290891218 PURE UUID: cb70c056-f611-432d-9cc5-ff67b7b843bc ORCID: /0000-0003-3541-3676/work/139156467 http://hdl.handle.net/10023/28000 https://doi.org/10.1098/rsos.230452 Copyright © 2023 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. Gray whale Progesterone Drone-based photogrammetry Enzyme immunoassay Pregnancy QL Zoology DAS MCC QL Journal article 2023 ftstandrewserep https://doi.org/10.1098/rsos.230452 2023-08-10T22:29:36Z Funding: This project was supported by the NOAA National Marine Fisheries Service Office of Science and Technology, the Office of Naval Research Marine Mammals and Biology Program (no. N00014-20-1-2760), the Oregon State University Marine Mammal Institute and Oregon Sea Grant. Knowledge of baleen whales’ reproductive physiology is limited and requires long-term individual-based studies and innovative tools. We used 6 years of individual-level data on the Pacific Coast Feeding Group gray whales to evaluate the utility of faecal progesterone immunoassays and drone-based photogrammetry for pregnancy diagnosis. We explored the variability in faecal progesterone metabolites and body morphology relative to observed reproductive status and estimated the pregnancy probability for mature females of unknown reproductive status using normal mixture models. Individual females had higher faecal progesterone concentrations when pregnant than when presumed nonpregnant. Yet, at the population level, high overlap and variability in progesterone metabolite concentrations occurred between pregnant and non-pregnant groups, limiting this metric for accurate pregnancy diagnosis in gray whales. Alternatively, body width at 50% of the total body length (W50) correctly discriminated pregnant from non-pregnant females at individual and population levels, with high accuracy. Application of the model using W50 metric to mature females of unknown pregnancy status identified eight additional pregnancies with high confidence. Our findings highlight the utility of drone-based photogrammetry to non-invasively diagnose pregnancy in this group of gray whales, and the potential for improved data on reproductive rates for population management of baleen whales generally. Publisher PDF Peer reviewed Article in Journal/Newspaper baleen whales University of St Andrews: Digital Research Repository Pacific Royal Society Open Science 10 7 |
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Open Polar |
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University of St Andrews: Digital Research Repository |
op_collection_id |
ftstandrewserep |
language |
English |
topic |
Gray whale Progesterone Drone-based photogrammetry Enzyme immunoassay Pregnancy QL Zoology DAS MCC QL |
spellingShingle |
Gray whale Progesterone Drone-based photogrammetry Enzyme immunoassay Pregnancy QL Zoology DAS MCC QL Fernandez Ajó, Alejandro Pirotta, Enrico Bierlich, K. C. Hildebrand, Lisa Bird, Clara N. Hunt, Kathleen E. Buck, C. Loren New, Leslie Dillon, Danielle Torres, Leigh G. Assessment of a non-invasive approach to pregnancy diagnosis in gray whales through drone-based photogrammetry and faecal hormone analysis |
topic_facet |
Gray whale Progesterone Drone-based photogrammetry Enzyme immunoassay Pregnancy QL Zoology DAS MCC QL |
description |
Funding: This project was supported by the NOAA National Marine Fisheries Service Office of Science and Technology, the Office of Naval Research Marine Mammals and Biology Program (no. N00014-20-1-2760), the Oregon State University Marine Mammal Institute and Oregon Sea Grant. Knowledge of baleen whales’ reproductive physiology is limited and requires long-term individual-based studies and innovative tools. We used 6 years of individual-level data on the Pacific Coast Feeding Group gray whales to evaluate the utility of faecal progesterone immunoassays and drone-based photogrammetry for pregnancy diagnosis. We explored the variability in faecal progesterone metabolites and body morphology relative to observed reproductive status and estimated the pregnancy probability for mature females of unknown reproductive status using normal mixture models. Individual females had higher faecal progesterone concentrations when pregnant than when presumed nonpregnant. Yet, at the population level, high overlap and variability in progesterone metabolite concentrations occurred between pregnant and non-pregnant groups, limiting this metric for accurate pregnancy diagnosis in gray whales. Alternatively, body width at 50% of the total body length (W50) correctly discriminated pregnant from non-pregnant females at individual and population levels, with high accuracy. Application of the model using W50 metric to mature females of unknown pregnancy status identified eight additional pregnancies with high confidence. Our findings highlight the utility of drone-based photogrammetry to non-invasively diagnose pregnancy in this group of gray whales, and the potential for improved data on reproductive rates for population management of baleen whales generally. Publisher PDF Peer reviewed |
author2 |
University of St Andrews. School of Biology |
format |
Article in Journal/Newspaper |
author |
Fernandez Ajó, Alejandro Pirotta, Enrico Bierlich, K. C. Hildebrand, Lisa Bird, Clara N. Hunt, Kathleen E. Buck, C. Loren New, Leslie Dillon, Danielle Torres, Leigh G. |
author_facet |
Fernandez Ajó, Alejandro Pirotta, Enrico Bierlich, K. C. Hildebrand, Lisa Bird, Clara N. Hunt, Kathleen E. Buck, C. Loren New, Leslie Dillon, Danielle Torres, Leigh G. |
author_sort |
Fernandez Ajó, Alejandro |
title |
Assessment of a non-invasive approach to pregnancy diagnosis in gray whales through drone-based photogrammetry and faecal hormone analysis |
title_short |
Assessment of a non-invasive approach to pregnancy diagnosis in gray whales through drone-based photogrammetry and faecal hormone analysis |
title_full |
Assessment of a non-invasive approach to pregnancy diagnosis in gray whales through drone-based photogrammetry and faecal hormone analysis |
title_fullStr |
Assessment of a non-invasive approach to pregnancy diagnosis in gray whales through drone-based photogrammetry and faecal hormone analysis |
title_full_unstemmed |
Assessment of a non-invasive approach to pregnancy diagnosis in gray whales through drone-based photogrammetry and faecal hormone analysis |
title_sort |
assessment of a non-invasive approach to pregnancy diagnosis in gray whales through drone-based photogrammetry and faecal hormone analysis |
publishDate |
2023 |
url |
http://hdl.handle.net/10023/28000 https://doi.org/10.1098/rsos.230452 |
geographic |
Pacific |
geographic_facet |
Pacific |
genre |
baleen whales |
genre_facet |
baleen whales |
op_relation |
Royal Society Open Science Fernandez Ajó , A , Pirotta , E , Bierlich , K C , Hildebrand , L , Bird , C N , Hunt , K E , Buck , C L , New , L , Dillon , D & Torres , L G 2023 , ' Assessment of a non-invasive approach to pregnancy diagnosis in gray whales through drone-based photogrammetry and faecal hormone analysis ' , Royal Society Open Science , vol. 10 , no. 7 , 230452 . https://doi.org/10.1098/rsos.230452 2054-5703 PURE: 290891218 PURE UUID: cb70c056-f611-432d-9cc5-ff67b7b843bc ORCID: /0000-0003-3541-3676/work/139156467 http://hdl.handle.net/10023/28000 https://doi.org/10.1098/rsos.230452 |
op_rights |
Copyright © 2023 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
op_doi |
https://doi.org/10.1098/rsos.230452 |
container_title |
Royal Society Open Science |
container_volume |
10 |
container_issue |
7 |
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1775349483603755008 |