ArticlePeerJ2020
The influence of bait on remote underwater video observations in shallow-water coastal environments associated with the North-Eastern Atlantic.
Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Cameras or Divers? How Baited Remote Underwater Videos and 'Long Swims' Underwater Visual Census Complement Each Other on Coral Reefs.Ecology and evolution · 2026Article
- Application of spatially robust stereo-BRUV sampling for quantifying fish assemblages in UK marine protected areas.Ecological applications : a publication of the Ecological Society of America · 2025Article
- More but Smaller: Marine Heatwaves Exacerbate Size Truncation in Overfished Fish Communities in the Skagerrak.Ecology and evolution · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of baited remote underwater video (BRUV) for examining and monitoring marine biodiversity in temperate marine environments is rapidly growing, however many aspects of their effectiveness relies on assumptions based on studies from the Southern Hemisphere. The addition of bait to underwater camera systems acts as a stimulus for attracting individuals towards the camera field of view, however knowledge of the effectiveness of different bait types in northern temperate climbs is limited, particularly in dynamic coastal environments. Studies in the Southern Hemisphere indicate that oily baits are most effective whilst bait volume and weight do not impact BRUV effectiveness to any great degree. The present study assesses the influence of four bait types (mackerel, squid, crab and no bait (control)) on the relative abundance, taxonomic diversity and faunal assemblage composition at two independent locations within the North-Eastern Atlantic region; Swansea Bay, UK and Ria Formosa Lagoon, Portugal. Two different bait quantities (50 g and 350 g) were further trialled in Swansea Bay. Overall, patterns showed that baited deployments recorded statistically higher values of relative abundance and taxonomic diversity when compared to un-baited deployments in Swansea Bay but not in Ria Formosa Lagoon. No statistical evidence singled out one bait type as best performing for attracting higher abundances and taxonomic diversity in both locations. Faunal assemblage composition was however found to differ with bait type in Swansea Bay, with mackerel and squid attracting higher abundances of scavenging species compared to the crab and control treatments. With the exception of squid, bait quantity had minimal influence on bait attractiveness. It is recommended for consistency that a minimum of 50 g of cheap, oily fish such as mackerel is used as bait for BRUV deployments in shallow dynamic coastal environments in the North-Eastern Atlantic Region.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.