Evidence map›Paper›PMID 40130007›Full record

ArticleEcology and evolution2025

Identification of Individual Texas Horned Lizards (

Daniella Biffi, Mary R Tucker, Alexis Ackel, Dean A Williams

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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Daniella BiffiAndrews Institute for Research in Mathematics & Science Education Texas Christian University Fort Worth Texas USA.ORCID https://orcid.org/0000-0001-6437-9855
Mary R TuckerDepartment of Biology Texas Christian University Fort Worth Texas USA.ORCID https://orcid.org/0000-0002-4893-449X
Alexis AckelDepartment of Biology Texas Christian University Fort Worth Texas USA.
Dean A WilliamsDepartment of Biology Texas Christian University Fort Worth Texas USA.ORCID https://orcid.org/0000-0002-9001-6019

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying individuals within a species is vital for monitoring population dynamics and determining appropriate conservation efforts. Traditional methods for marking individual lizards include toe-clipping, branding, tattooing, and passive integrated transponder (PIT) tags. However, some of these methods can potentially cause stress, affect performance and survival, and raise concerns about the ethical treatment of animals. We conducted a long-term study on the urban ecology of Texas horned lizards living in two small towns in south Texas, USA. Our study was in the unique position of possessing a dataset of individuals that were PIT tagged, genotyped, and photographed, which allowed us to validate genotyping and natural markings for individual identification. We calculated our genotyping error rate by comparing genotypes of recaptured individuals identified by PIT tags. Our mean error rate per allele was 0.0016, our mean error rate per multilocus genotype was 0.032, and we had high power to identify individuals. We used HotSpotter software to match photographs of individuals identified by PIT tags and genotyping. HotSpotter successfully matched photographs of the same individual 94% of the time. This could be increased to almost 100% by looking at the top 10 picture matches by eye to validate the matching. Additionally, individual spot patterns were unique and stable across years. Using pictures of ventral spots is an easy way to identify individuals, avoids potential rare infection or mortality, and is inexpensive relative to PIT tags and genotyping.

Indexed as

individual identificationmicrosatellitesnatural markingsprobability of identity

Identifiers

PMID40130007
PMCPMC11932728

What OpenQuestion holds

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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.