Meiofauna Community in Soft Sediments at TAG and Snake Pit Hydrothermal Vent Fields

Spedicato, Adriana; Sánchez, Nuria; Pastor, Lucie; Menot, Lénaïck; Zeppilli, Daniela

doi:10.3389/fmars.2020.00200

Cited by 8 publications

(6 citation statements)

References 53 publications

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“…Recently, however, Cruz et al (2022) referred to a general similarity between the Broken Spur fauna and that encountered elsewhere on the MAR. As reported by Boschen-Rose and Colaco (2021), as few as 9 benthic megafaunal Gebruk and Mironov, 2006;Flint, 2007;Ivanenko et al, 2011;Tchesunov, 2015;Zeppilli et al, 2015;Sarrazin et al, 2015;Zeppilli et al, 2019;Spedicato et al, 2020); +, taxon recorded; -, taxon not recorded.…”

Section: Mega-and Nektobenthosmentioning

confidence: 64%

“…The soft sediment-covered areas away from active venting support fairly abundant meiobenthic communities compared with abundances found in other deep-sea environments. Abundances at the TAG and Snake Pit hydrothermal vent fields are 11-35 and 72-86 ind/10cm 2 respectively (Spedicato et al, 2020).…”

Section: Abundance and Biomassmentioning

confidence: 94%

“…Gollner et al, 2010;Zeppilli et al, 2018, and references therein). There have been few meiobenthos-focused studies in the MAR in general (Zekely et al, 2006;Flint, 2007;Ivanenko et al, 2011;Cuvelier et al, 2014;Sarrazin et al, 2015;Tchesunov, 2015;Zeppilli et al, 2015;Plum et al, 2017;Spedicato et al, 2020). However, information can be extracted by taking a broader view of MAR benthic communities, notably from the work of Galkin (2006) and Gebruk and Mironov (2006).…”

Section: Meiobenthosmentioning

confidence: 99%

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Benthic biology in the Polish exploration contract area of the Mid-Atlantic Ridge: The knowns and the unknowns. A review

Radziejewska

Błażewicz²,

Włodarska‐Kowalczuk³

et al. 2022

Front. Mar. Sci.

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In February 2018, the Government of Poland and the International Seabed Authority signed a 15-year contract for exploration of polymetallic sulfide deposits on a section of the Mid-Atlantic Ridge extending between the Hayes, Atlantic and Kane transform faults (32°45.378’ N, 39°57.760’ W to 26°14.411’ N, 44°18.008’ W). The contractor is obliged to collect data on the contract area environment and its ecosystem components. In this context, it is important that the contractor establishes a sound starting point which further baseline investigations can be referred to. Such a starting point involves assessment of currently held information and, most importantly, knowledge gaps on the ecosystem components in the area of exploration (and of potential future exploitation). Of major importance here is the knowledge on benthic communities, as it is the benthos that will be most affected by any human intervention in the area of interest. Based on available published evidence, we have reviewed the present state of knowledge on benthic communities in the Polish exploration contract area (PECA). In the process, we have identified important knowledge gaps that will need to be addressed during exploration surveys. These include, but are not limited to, the distribution and structure of benthic communities throughout the contract area, the spatial and temporal variability of those communities, possible differences between communities inhabiting active and inactive vent fields, connectivity issues and the recovery potential. Special consideration should be given to Lost City, a geologically and ecologically unique hydrothermal field which has been a focus of international research and an important conservation target.

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Section: Mega-and Nektobenthosmentioning

confidence: 64%

Section: Abundance and Biomassmentioning

confidence: 94%

Section: Meiobenthosmentioning

confidence: 99%

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Benthic biology in the Polish exploration contract area of the Mid-Atlantic Ridge: The knowns and the unknowns. A review

Radziejewska

Błażewicz²,

Włodarska‐Kowalczuk³

et al. 2022

Front. Mar. Sci.

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“…Despite their ecological importance, the lack of reliable identification tools at lower taxonomical levels hampers ecological, molecular, and conservation studies ( Macheriotou et al, 2019 ; Ridall & Ingels, 2021 ; Pantó et al, 2021 ). As a result, nematodes are often identified at the genus level rather than the species level ( Miljutin et al, 2010 ; Sandulli, Semprucci & Balsamo, 2014 ; Brannock et al, 2017 ; Spedicato et al, 2020 ). The use of ML techniques in nematode identification is still limited.…”

Section: Introductionmentioning

confidence: 99%

Machine learning algorithms accurately identify free-living marine nematode species

Brito de Jesus,

Vieira,

Gheller

et al. 2023

PeerJ

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Background Identifying species, particularly small metazoans, remains a daunting challenge and the phylum Nematoda is no exception. Typically, nematode species are differentiated based on morphometry and the presence or absence of certain characters. However, recent advances in artificial intelligence, particularly machine learning (ML) algorithms, offer promising solutions for automating species identification, mostly in taxonomically complex groups. By training ML models with extensive datasets of accurately identified specimens, the models can learn to recognize patterns in nematodes’ morphological and morphometric features. This enables them to make precise identifications of newly encountered individuals. Implementing ML algorithms can improve the speed and accuracy of species identification and allow researchers to efficiently process vast amounts of data. Furthermore, it empowers non-taxonomists to make reliable identifications. The objective of this study is to evaluate the performance of ML algorithms in identifying species of free-living marine nematodes, focusing on two well-known genera: Acantholaimus Allgén, 1933 and Sabatieria Rouville, 1903. Methods A total of 40 species of Acantholaimus and 60 species of Sabatieria were considered. The measurements and identifications were obtained from the original publications of species for both genera, this compilation included information regarding the presence or absence of specific characters, as well as morphometric data. To assess the performance of the species identification four ML algorithms were employed: Random Forest (RF), Stochastic Gradient Boosting (SGBoost), Support Vector Machine (SVM) with both linear and radial kernels, and K-nearest neighbor (KNN) algorithms. Results For both genera, the random forest (RF) algorithm demonstrated the highest accuracy in correctly classifying specimens into their respective species, achieving an accuracy rate of 93% for Acantholaimus and 100% for Sabatieria, only a single individual from Acantholaimus of the test data was misclassified. Conclusion These results highlight the overall effectiveness of ML algorithms in species identification. Moreover, it demonstrates that the identification of marine nematodes can be automated, optimizing biodiversity and ecological studies, as well as turning species identification more accessible, efficient, and scalable. Ultimately it will contribute to our understanding and conservation of biodiversity.

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“…Benthic species composition in sediments surroundings Rainbow is different compared to control deep-sea sediments and highly influenced by the vent plume's fall out (Klunder et al, 2020). Nematode community composition in sediments in the surroundings of Snake Pit and TAG vent fields on the Mid-Atlantic Ridge is hypothesized to be influenced by geochemical setting and food availability (Spedicato et al, 2020). A study in the northern West-Pacific, suggested that the effect of in situ derived organic matter as a food source near vents may be limited to at most several 100 m away from the venting area (Nomaki et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Influence of Chemoautotrophic Organic Carbon on Sediment and Its Infauna in the Vicinity of the Rainbow Vent Field

et al. 2022

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Hydrothermal vents have been recognised as isolated islands of productivity in the deep sea, but very little is known about the transport and export of chemoautotrophic produced organic carbon to vent surrounding habitats. Here, we investigate vent carbon export and its influence on benthic food webs in sediments at the Rainbow (RB) vent field at the Mid Atlantic Ridge in ~2200 m water depth. Two sites were considered along the dispersal direction of the RB vent plume for sample collection: the close vicinity at about ~30-100 m (“near-vent”); and at 4 km distance (“off-vent”) to the nearest venting area. At both sites, box corers were used to sample sediments and their fauna. A turbidity sensor mounted on a CTD/Rosette provided data on the presence of a vent fluid plume in the water column. Niskin bottles were used to sample suspended particulate organic matter (SPOM) from the plume, as well as from surface waters at 75 m depth. SPOM, sediments and fauna were analysed for nitrogen and carbon stable isotopes. Carbon derived from in situ chemoautotrophy, characterised by depleted δ13C, was taken up by infauna close to the venting area as the main nutrition source, while fauna at the off-vent site showed less depleted δ13C with a signature more typical for photosynthetic- derived material. Nematodes were the most abundant faunal taxon. Their abundance and biomass were variable and not different at the two studied sites. In situ derived organic matter was traced back in the food web in the close vicinity of the venting area. The connectivity of vent and non-vent habitats should be taken appropriately into account when designing future spatial management plans with regard to deep-seabed mining at hydrothermal vents.

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Meiofauna Community in Soft Sediments at TAG and Snake Pit Hydrothermal Vent Fields

Cited by 8 publications

References 53 publications

Benthic biology in the Polish exploration contract area of the Mid-Atlantic Ridge: The knowns and the unknowns. A review

Benthic biology in the Polish exploration contract area of the Mid-Atlantic Ridge: The knowns and the unknowns. A review

Machine learning algorithms accurately identify free-living marine nematode species

Influence of Chemoautotrophic Organic Carbon on Sediment and Its Infauna in the Vicinity of the Rainbow Vent Field

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