Identifying Black Corals and Octocorals From Deep-Sea Imagery for Ecological Assessments: Trade-Offs Between Morphology and Taxonomy

An increased reliance on imagery as the source of biodiversity data from the deep sea has stimulated many recent advances in image annotation and data management. The form of image-derived data is determined by the way faunal units are classified and should align with the needs of the ecological stu...

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Autores principales: Candice B. Untiedt, Alan Williams, Franziska Althaus, Phil Alderslade, Malcolm R. Clark
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Lenguaje:EN
Publicado: Frontiers Media S.A. 2021
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spelling oai:doaj.org-article:e808dad67a07484aa0373e657dd7c5ec2021-11-16T07:28:02ZIdentifying Black Corals and Octocorals From Deep-Sea Imagery for Ecological Assessments: Trade-Offs Between Morphology and Taxonomy2296-774510.3389/fmars.2021.722839https://doaj.org/article/e808dad67a07484aa0373e657dd7c5ec2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fmars.2021.722839/fullhttps://doaj.org/toc/2296-7745An increased reliance on imagery as the source of biodiversity data from the deep sea has stimulated many recent advances in image annotation and data management. The form of image-derived data is determined by the way faunal units are classified and should align with the needs of the ecological study to which it is applied. Some applications may require only low-resolution biodiversity data, which is easier and cheaper to generate, whereas others will require well-resolved biodiversity measures, which require a larger investment in annotation methods. We assessed these trade-offs using a dataset of 5 939 images and physical collections of black and octocorals taken during surveys from a seamount area in the southwest Pacific Ocean. Coral diversity was greatly underestimated in images: only 55 black and octocoral ‘phototaxa’ (best-possible identifications) were consistently distinguishable out of a known 210 species in the region (26%). Patterns of assemblage composition were compared between the phototaxa and a standardized Australian classification scheme (“CATAMI”) that uses morphotypes to classify taxa. Results were similar in many respects, but the identities of dominant, and detection of rare but locally abundant, coral entities were achieved only when annotation was at phototaxon resolution, and when faunal densities were recorded. A case study of data from 4 seamounts compared three additional classification schemes. Only the two with highest resolution – phototaxon and a combined phototaxon-morphological scheme – were able to distinguish black and octocoral communities on unimpacted vs. impacted seamounts. We conclude that image annotation schemes need to be fit-for-purpose. Morphological schemes such as CATAMI may perform well and are most easily standardized for cross-study data sharing, but high resolution (and more costly) annotation schemes are likely necessary for some ecological and management-based applications including biodiversity inventory, change detection (monitoring) – and to develop automated annotation using machine learning.Candice B. UntiedtCandice B. UntiedtAlan WilliamsFranziska AlthausPhil AldersladeMalcolm R. ClarkFrontiers Media S.A.articlebenthic habitatsseamountsvulnerable marine ecosystemsbiodiversitytowed cameramorphospeciesScienceQGeneral. Including nature conservation, geographical distributionQH1-199.5ENFrontiers in Marine Science, Vol 8 (2021)
institution DOAJ
collection DOAJ
language EN
topic benthic habitats
seamounts
vulnerable marine ecosystems
biodiversity
towed camera
morphospecies
Science
Q
General. Including nature conservation, geographical distribution
QH1-199.5
spellingShingle benthic habitats
seamounts
vulnerable marine ecosystems
biodiversity
towed camera
morphospecies
Science
Q
General. Including nature conservation, geographical distribution
QH1-199.5
Candice B. Untiedt
Candice B. Untiedt
Alan Williams
Franziska Althaus
Phil Alderslade
Malcolm R. Clark
Identifying Black Corals and Octocorals From Deep-Sea Imagery for Ecological Assessments: Trade-Offs Between Morphology and Taxonomy
description An increased reliance on imagery as the source of biodiversity data from the deep sea has stimulated many recent advances in image annotation and data management. The form of image-derived data is determined by the way faunal units are classified and should align with the needs of the ecological study to which it is applied. Some applications may require only low-resolution biodiversity data, which is easier and cheaper to generate, whereas others will require well-resolved biodiversity measures, which require a larger investment in annotation methods. We assessed these trade-offs using a dataset of 5 939 images and physical collections of black and octocorals taken during surveys from a seamount area in the southwest Pacific Ocean. Coral diversity was greatly underestimated in images: only 55 black and octocoral ‘phototaxa’ (best-possible identifications) were consistently distinguishable out of a known 210 species in the region (26%). Patterns of assemblage composition were compared between the phototaxa and a standardized Australian classification scheme (“CATAMI”) that uses morphotypes to classify taxa. Results were similar in many respects, but the identities of dominant, and detection of rare but locally abundant, coral entities were achieved only when annotation was at phototaxon resolution, and when faunal densities were recorded. A case study of data from 4 seamounts compared three additional classification schemes. Only the two with highest resolution – phototaxon and a combined phototaxon-morphological scheme – were able to distinguish black and octocoral communities on unimpacted vs. impacted seamounts. We conclude that image annotation schemes need to be fit-for-purpose. Morphological schemes such as CATAMI may perform well and are most easily standardized for cross-study data sharing, but high resolution (and more costly) annotation schemes are likely necessary for some ecological and management-based applications including biodiversity inventory, change detection (monitoring) – and to develop automated annotation using machine learning.
format article
author Candice B. Untiedt
Candice B. Untiedt
Alan Williams
Franziska Althaus
Phil Alderslade
Malcolm R. Clark
author_facet Candice B. Untiedt
Candice B. Untiedt
Alan Williams
Franziska Althaus
Phil Alderslade
Malcolm R. Clark
author_sort Candice B. Untiedt
title Identifying Black Corals and Octocorals From Deep-Sea Imagery for Ecological Assessments: Trade-Offs Between Morphology and Taxonomy
title_short Identifying Black Corals and Octocorals From Deep-Sea Imagery for Ecological Assessments: Trade-Offs Between Morphology and Taxonomy
title_full Identifying Black Corals and Octocorals From Deep-Sea Imagery for Ecological Assessments: Trade-Offs Between Morphology and Taxonomy
title_fullStr Identifying Black Corals and Octocorals From Deep-Sea Imagery for Ecological Assessments: Trade-Offs Between Morphology and Taxonomy
title_full_unstemmed Identifying Black Corals and Octocorals From Deep-Sea Imagery for Ecological Assessments: Trade-Offs Between Morphology and Taxonomy
title_sort identifying black corals and octocorals from deep-sea imagery for ecological assessments: trade-offs between morphology and taxonomy
publisher Frontiers Media S.A.
publishDate 2021
url https://doaj.org/article/e808dad67a07484aa0373e657dd7c5ec
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