Optimising sampling of fish assemblages on intertidal reefs using remote underwater video.

Katherine R Erickson, Ana B Bugnot, Will F Figueira

Abstract read

In one paragraph

Article in PeerJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

1 citing paper in PubMed.

Patch design principles for oyster reef restoration: Lessons from fish habitat use in natural remnant systems.Ecological applications : a publication of the Ecological Society of America · 2026
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

3 authors.

Katherine R EricksonCentre for Marine Science and Innovation, University of New South Wales, Sydney, NSW, Australia.ORCID 0000-0001-7363-5865

Ana B BugnotSchool of Life and Environmental Sciences, University of Sydney, Sydney, NSW, Australia.

Will F FigueiraSchool of Life and Environmental Sciences, University of Sydney, Sydney, NSW, Australia.ORCID 0000-0001-9472-8710

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Assessing fish assemblages in subtidal and intertidal habitats is challenging due to the structural complexity of many of these systems. Trapping and collecting are regarded as optimal ways to sample these assemblages, but this method is costly and destructive, so researchers also use video techniques. Underwater visual census and baited remote underwater video stations are commonly used to characterise fish communities in these systems. More passive techniques such as remote underwater video (RUV) may be more appropriate for behavioural studies, or for comparing proximal habitats where the broad attraction caused by bait plumes could be an issue. However, data processing for RUVs can be time consuming and create processing bottlenecks. Methods: Here, we identified the optimal subsampling method to assess fish assemblages on intertidal oyster reefs using RUV footage and bootstrapping techniques. We quantified how video subsampling effort and method (systematic Results: Results suggest that MaxN

Indexed as

Coral ReefsFishesAnimalsCensusesEcosystemCryptic fishIntertidal reefSampling effortUnbaited underwater camera

Identifiers

PMID37250718

DOI10.7717/peerj.15426

PMCPMC10211360

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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.