Predicting trends in humpback whale (Megaptera novaeangliae) abundance using citizen science

The Great Whale Count (GWC) is an annual citizen science event that monitors changes in humpback whale (Megaptera novaeangliae) sightings in Maui County during the breeding season. The study includes 15 years of observations (1995–1996 and 1999–2011) with over 11 000 whale sightings. We provide a cr...

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Main Authors: Tonachella, N., Nastasi, A., Kaufman, G., Maldini, D., Rankin, R.W.
Format: Article in Journal/Newspaper
Language:English
Published: Surrey Beatty & Sons 2012
Subjects:
Online Access:https://researchrepository.murdoch.edu.au/id/eprint/30323/
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author Tonachella, N.
Nastasi, A.
Kaufman, G.
Maldini, D.
Rankin, R.W.
author_facet Tonachella, N.
Nastasi, A.
Kaufman, G.
Maldini, D.
Rankin, R.W.
author_sort Tonachella, N.
collection Murdoch University Research Portal
description The Great Whale Count (GWC) is an annual citizen science event that monitors changes in humpback whale (Megaptera novaeangliae) sightings in Maui County during the breeding season. The study includes 15 years of observations (1995–1996 and 1999–2011) with over 11 000 whale sightings. We provide a critical examination of the utility of the citizen science data given the challenges of observer-, site- and year-specific biases in counts, as well as an immeasurable and imperfect detection process. We estimate an annual increase of 5.16% per year (±2.76%), which closely resembles earlier trend estimates for Hawai’i. We demonstrate how uncertainty estimates in citizen science data can be strongly influenced by sampling processes, especially observer effects. Although such effects are now widely recognized in ecological studies, citizen science data often predate the mainstreaming of sampling protocols which measure and adjust for imperfect detectability. Here, we propose random effect models to minimize such effects in lieu of detectability techniques, and urge citizen science programs to adapt their protocols to handle observer processes at the planning and data collection stage.
format Article in Journal/Newspaper
genre Humpback Whale
Megaptera novaeangliae
genre_facet Humpback Whale
Megaptera novaeangliae
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institution Open Polar
language English
op_collection_id ftmurdochuniv
op_relation https://researchrepository.murdoch.edu.au/id/eprint/30323/
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op_source Tonachella, N., Nastasi, A., Kaufman, G., Maldini, D. and Rankin, R.W. <https://researchrepository.murdoch.edu.au/view/author/Rankin, Robert.html> (2012) Predicting trends in humpback whale (Megaptera novaeangliae) abundance using citizen science. Pacific Conservation Biology, 18 (4). pp. 297-309.
publishDate 2012
publisher Surrey Beatty & Sons
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spelling ftmurdochuniv:oai:researchrepository.murdoch.edu.au:30323 2025-01-16T22:20:17+00:00 Predicting trends in humpback whale (Megaptera novaeangliae) abundance using citizen science Tonachella, N. Nastasi, A. Kaufman, G. Maldini, D. Rankin, R.W. 2012 https://researchrepository.murdoch.edu.au/id/eprint/30323/ eng eng Surrey Beatty & Sons https://researchrepository.murdoch.edu.au/id/eprint/30323/ full_text_status:none Tonachella, N., Nastasi, A., Kaufman, G., Maldini, D. and Rankin, R.W. <https://researchrepository.murdoch.edu.au/view/author/Rankin, Robert.html> (2012) Predicting trends in humpback whale (Megaptera novaeangliae) abundance using citizen science. Pacific Conservation Biology, 18 (4). pp. 297-309. Journal Article 2012 ftmurdochuniv 2020-01-05T18:56:01Z The Great Whale Count (GWC) is an annual citizen science event that monitors changes in humpback whale (Megaptera novaeangliae) sightings in Maui County during the breeding season. The study includes 15 years of observations (1995–1996 and 1999–2011) with over 11 000 whale sightings. We provide a critical examination of the utility of the citizen science data given the challenges of observer-, site- and year-specific biases in counts, as well as an immeasurable and imperfect detection process. We estimate an annual increase of 5.16% per year (±2.76%), which closely resembles earlier trend estimates for Hawai’i. We demonstrate how uncertainty estimates in citizen science data can be strongly influenced by sampling processes, especially observer effects. Although such effects are now widely recognized in ecological studies, citizen science data often predate the mainstreaming of sampling protocols which measure and adjust for imperfect detectability. Here, we propose random effect models to minimize such effects in lieu of detectability techniques, and urge citizen science programs to adapt their protocols to handle observer processes at the planning and data collection stage. Article in Journal/Newspaper Humpback Whale Megaptera novaeangliae Murdoch University Research Portal
spellingShingle Tonachella, N.
Nastasi, A.
Kaufman, G.
Maldini, D.
Rankin, R.W.
Predicting trends in humpback whale (Megaptera novaeangliae) abundance using citizen science
title Predicting trends in humpback whale (Megaptera novaeangliae) abundance using citizen science
title_full Predicting trends in humpback whale (Megaptera novaeangliae) abundance using citizen science
title_fullStr Predicting trends in humpback whale (Megaptera novaeangliae) abundance using citizen science
title_full_unstemmed Predicting trends in humpback whale (Megaptera novaeangliae) abundance using citizen science
title_short Predicting trends in humpback whale (Megaptera novaeangliae) abundance using citizen science
title_sort predicting trends in humpback whale (megaptera novaeangliae) abundance using citizen science
url https://researchrepository.murdoch.edu.au/id/eprint/30323/