Evidence map›Paper›PMID 41383211›Full record

ArticleEcology and evolution2025

Statistically Classified Marine Epifaunal Bioregions on the Southern Benguela Margin, South Africa.

Donia Wozniak, Lara Atkinson, Natasha Karenyi

Abstract read
In one paragraph

Article in Ecology and evolution, 2025. 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.

  1. 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.

Donia WozniakDepartment of Biological Sciences University of Cape Town Cape Town South Africa.
Lara AtkinsonDepartment of Biological Sciences University of Cape Town Cape Town South Africa.
Natasha KarenyiDepartment of Biological Sciences University of Cape Town Cape Town South Africa.ORCID https://orcid.org/0000-0002-2992-4528

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Marine bioregional maps often underpin effective management and conservation planning. Bioregional maps determined by statistical models can predict the most probable bioregion at unsampled locations and have many advantages over expert-derived approaches, such as including measures of uncertainty. Here, we aim to statistically determine and map marine epifaunal bioregions on the Southern Benguela margin of South Africa, including their associated spatial uncertainty, utilising survey collected abundance data (70-800 m). Regions of Common Profile (RCP) models were implemented using the 'ecomix' R package to model and map bioregions of epifaunal assemblages and their environment. Epifaunal abundance data from 46 species collected across 325 sites by research trawl surveys between 2017 and 2020, were used to inform bioregions. Environmental predictors were bottom dissolved oxygen and temperature measured in situ and slope derived from bathymetry. Five bioregions were identified. Two well-defined depth breaks at ~150 m and ~400-500 m separated the mid shelf from the outer shelf and the outer shelf from the upper slope, respectively. The mid shelf and upper slope bioregions were associated with the highest estimated certainty, responding strongly to low oxygen concentration and low temperature, respectively. Outer shelf bioregions had the highest species richness, were dominated by the hermit crab

Indexed as

assemblagesbioregionalizationbioregionsdata‐drivenecosystem classification and mappingenvironmental driversmarine epifaunaregions of common profileSouth AfricaSouthern Benguela

Identifiers

PMID41383211
PMCPMC12690162

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Registered trials

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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.