PELD - ABRS | Avaliação e monitoramento dos recifes de Abrolhos
Citation
Leão de Moura R, Menegassi del Favero J, D’Ornellas Teixeira C (2022). PELD - ABRS | Avaliação e monitoramento dos recifes de Abrolhos. Version 1.4. Sistema de Informação sobre a Biodiversidade Brasileira - SiBBr. Occurrence dataset https://doi.org/10.15468/mhrm29 accessed via GBIF.org on 2024-12-12.Description
Relative annual coverage (percentage) of the different benthic groups presents in the Abrolhos Archipelago, starting in 2006.Sampling Description
Study Extent
Monitored sites include five reefs in the Abrolhos Archipelago, a set of small volcanic islands ~55 km off the coast and within the Marine National Park. Data has been acquired since 2006, mostly during the Austral summer.Sampling
We used fixed photo-quadrats demarcated with metal pins that are periodically replaced. Each benthic sampling unit is composed of a mosaic of 15 high resolution photos and covering ~70 cm2. Each sampling site has 10 sampling units. During the period monitored, some years and/or locations were not sampled due to logistical and funding constrains. Images were annotated semi-automatically with the deep neural network provided by the CoralNet platform*. Relative cover was estimated from the identification of benthic organisms below 30 random points distributed in each image (one photo-quadrat = a mosaic of 15 high resolution close-up images). Organisms were identified at nine broad taxonomic or functional groups and categorized either as slower-growing longer-lived reef builders [corals, crustose calcareous algae (CCA) and hydrocorals] or their faster-growing shorter-lived antagonists [(frondose macroalgae, turf, benthic cyanobacteria mats (BCM), zoanthids, sponges and “other organisms” (OO)]. * Beijbom O, Edmunds PJ, Roelfsema C, Smith J, Kline DI, Neal BP, et al. Towards automated annotation of benthic survey images: variability of human experts and operational modes of automation. PLoSOne. 2015; 10(7): e0130312. https://doi.org/10.1371/journal.pone.0130312 PMID: 26154157Quality Control
We used an 80% confidence threshold (label accuracy: 95.4%, functional group accuracy: 96.9%, fraction above threshold: 53%) for the semi-automatic annotation carried out with the deep neural network of the CoralNet platform.Method steps
- Benthic sampling is described in Teixeira et al. (2021).
Taxonomic Coverages
Coral reefs organisms were identified at the lower taxa possible (species or genus)
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Agariciarank: genus
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Favia gravidarank: species
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Madracis decactisrank: species
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Meandrina braziliensisrank: species
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Milleporarank: genus
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Millepora nitidarank: species
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Montastrea cavernosarank: species
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Mussismilia braziliensisrank: species
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Mussismilia harttirank: species
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Mussismilia hispidarank: species
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Mussismilia leptophyllarank: species
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Poritesrank: genus
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Scolymia wellsirank: species
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Siderastrearank: genus
Zoanthids includes Palythoa caribaeorum and Zoanthus spp.
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Zoanthariarank: order
Crustose Calcareous Algae (CCA)
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CCArank: unranked
Benthic cyanobacteria mats
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Cyanobacteriarank: phylum
Includes all encrusting sponges
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Encrusting spongerank: unranked
Includes all species of macroalgae
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Macroalgaerank: unranked
Includes all massive sponges
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Massive spongerank: unranked
Includes octocorals, bryozoans, ascidians, polychaetes, anemones
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Other organismsrank: unranked
Includes all boring sponges
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Perforating spongerank: unranked
Includes sediment and dead organisms
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Substrate/Deadrank: unranked
Turf
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Turfrank: unranked
Geographic Coverages
Data sampled in Abrolhos Marine National Park, Bahia, Brazil
Bibliographic Citations
Contacts
Rodrigo Leão de Mouraoriginator
position: Professor
Universidade Federal do Rio de Janeiro
BR
email: moura.uesc@gmail.com
userId: http://orcid.org/0000-0002-5597-6196
Jana Menegassi del Favero
originator
position: Post doctoral researcher
Universidade Federal do Rio de Janeiro
BR
userId: http://lattes.cnpq.br/0896371656987762
Carolina D’Ornellas Teixeira
originator
position: Technician
Universidade Federal do Rio de Janeiro
Jana Menegassi del Favero
metadata author
position: Post doctoral researcher
Universidade Federal do Rio de Janeiro
BR
email: delfaverojana@gmail.com
userId: http://lattes.cnpq.br/0896371656987762
Carolina D’Ornellas Teixeira
metadata author
position: Technician
Universidade Federal do Rio de Janeiro
Rodrigo Leão de Moura
user
position: Professor
Universidade Federal do Rio de Janeiro
BR
email: moura.uesc@gmail.com
userId: http://orcid.org/0000-0002-5597-6196
Rodrigo Leão de Moura
administrative point of contact
position: Professor
Universidade Federal do Rio de Janeiro
BR
email: moura.uesc@gmail.com
userId: http://orcid.org/0000-0002-5597-6196