Evidence map›Paper›PMID 30135455›Full record

ArticleScientific reports2018

Examining the viability of dorsal fin pigmentation for individual identification of poorly-marked delphinids.

M D M Pawley, K E Hupman, K A Stockin, A Gilman

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
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

2 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. 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 at 1 institution in 1 country.

M D M PawleyInstitute of Natural and Mathematical Sciences, Massey University, Auckland, 0745, New Zealand. M.pawley@massey.ac.nz.
K E HupmanInstitute of Natural and Mathematical Sciences, Massey University, Auckland, 0745, New Zealand.
K A StockinInstitute of Natural and Mathematical Sciences, Massey University, Auckland, 0745, New Zealand.
A GilmanInstitute of Natural and Mathematical Sciences, Massey University, Auckland, 0745, New Zealand. a.gilman@massey.ac.nz.
Massey University · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dolphin photo-identification has traditionally relied only on distinctive markings on the dorsal fin-this is problematic for delphinids whose populations exhibit a low mark ratio. We used common dolphins (genus Delphinus) as a model species to assess the viability of using pigmentation for photo-identification. Using a photo-identification catalogue of 169 adult individuals collected between 2002 and 2013, we extracted features that quantified pigmentation in a manner that was robust to lighting artefacts and dorsal fin orientation. We determined the proportion of individuals which exhibited pigmentation and examined temporal stability by (i) visually examining individuals and (ii) testing for seriation. We found 88-91% of images could be manually matched to the correct individual in the catalogue based on pigmentation patterns alone. A linear discriminant analysis classifier correctly identified the correct individual 77% of the time. We found 95% common dolphins exhibited distinctive pigmentation-all of which were temporarily stable. Our work challenges the current thinking that pigmentation is an unreliable feature for delphinid photo-identification and suggests that this feature could be applied to common dolphins and other poorly-marked delphinids.

Indexed as

Animal FinsAnimal Identification SystemsAnimalsDolphinsPigmentationSkin Pigmentation

Identifiers

PMID30135455
PMCPMC6105684
OpenAlexW2885924094

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.