Evidence map›Paper›PMID 31807930›Full record

ArticleEnvironmental monitoring and assessment2019

PelagiCam: a novel underwater imaging system with computer vision for semi-automated monitoring of mobile marine fauna at offshore structures.

Emma V Sheehan, Danielle Bridger, Sarah J Nancollas, Simon J Pittman

Abstract read
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In one paragraph

Article in Environmental monitoring and assessment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Conservation physiology · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Emma V SheehanSchool of Biological and Marine Sciences, University of Plymouth, Drakes Circus, Plymouth, PL4 8AA, UK.ORCID https://orcid.org/0000-0002-1066-8237
Danielle BridgerSchool of Biological and Marine Sciences, University of Plymouth, Drakes Circus, Plymouth, PL4 8AA, UK.
Sarah J NancollasSchool of Biological and Marine Sciences, University of Plymouth, Drakes Circus, Plymouth, PL4 8AA, UK.
Simon J PittmanSchool of Biological and Marine Sciences, University of Plymouth, Drakes Circus, Plymouth, PL4 8AA, UK.ORCID https://orcid.org/0000-0002-4113-6970

Funding

Offshore Shellfish Ltd NA
6 · The paper itself

Abstract

Engineered structures in the open ocean are becoming more frequent with the expansion of the marine renewable energy industry and offshore marine aquaculture. Floating engineered structures function as artificial patch reefs providing novel and relatively stable habitat structure not otherwise available in the pelagic water column. The enhanced physical structure can increase local biodiversity and benefit fisheries yet can also facilitate the spread of invasive species. Clear evidence of any ecological consequences will inform the design and placement of structures to either minimise negative impacts or enhance ecosystem restoration. The development of rapid, cost-effective and reliable remote underwater monitoring methods is crucial to supporting evidence-based decision-making by planning authorities and developers when assessing environmental risks and benefits of offshore structures. A novel, un-baited midwater video system, PelagiCam, with motion-detection software (MotionMeerkat) for semi-automated monitoring of mobile marine fauna, was developed and tested on the UK's largest offshore rope-cultured mussel farm in Lyme Bay, southwest England. PelagiCam recorded Atlantic horse mackerel (Trachurus trachurus), garfish (Belone belone) and two species of jellyfish (Chrysaora hysoscella and Rhizostoma pulmo) in open water close to the floating farm structure. The software successfully distinguished video frames where fishes were present versus absent. The PelagiCam system provides a cost-effective remote monitoring tool to streamline biological data acquisition in impact assessments of offshore floating structures. With the rise of sophisticated artificial intelligence for object recognition, the integration of computer vision techniques should receive more attention in marine ecology and has great potential to revolutionise marine biological monitoring.

Indexed as

EcosystemVideo RecordingAnimalsAquacultureAquatic OrganismsBiodiversityComputersEnglandEnvironmental MonitoringFishesMarine Biologyaquacultureecosystem functionMonitoringmotion detectionmussel farmpelagicvideo analysis

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.