Evidence map›Paper›PMID 42834575›Full record

ArticleEcological applications : a publication of the Ecological Society of America2026

Application of close-kin mark-recapture to an American black bear population using harvest samples.

Anthony Sévêque, Robert C Lonsinger, Lisette P Waits, Kristin E Brzeski, Sarah L Mayhew, D Cody Norton, Caitlin N Ott-Conn, Tyler R Petroelje, Anaïs K Tallon, Maya Weissman and 1 more

Abstract read
In one paragraph

Article in Ecological applications : a publication of the Ecological Society of America, 2026. 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. Application of close-kin mark-recapture to an American black bear population using harvest samples.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

11 authors.

Anthony SévêqueDepartment of Wildlife, Fisheries and Aquaculture, Forest and Wildlife Research Center, Mississippi State University, Mississippi State, Mississippi, USA.ORCID https://orcid.org/0000-0003-4363-4137
Robert C LonsingerU.S. Geological Survey, Oklahoma Cooperative Fish and Wildlife Research Unit, Oklahoma State University, Stillwater, Oklahoma, USA.ORCID https://orcid.org/0000-0002-1040-7299
Lisette P WaitsDepartment of Fish and Wildlife Resources, University of Idaho, Moscow, Idaho, USA.
Kristin E BrzeskiCollege of Forest Resources and Environment Science, Michigan Technological University, Houghton, Michigan, USA.
Sarah L MayhewWildlife Division, Michigan Department of Natural Resources, Lansing, Michigan, USA.
D Cody NortonWildlife Division, Michigan Department of Natural Resources, Marquette, Michigan, USA.
Caitlin N Ott-ConnWildlife Division, Michigan Department of Natural Resources, Marquette, Michigan, USA.
Tyler R PetroeljeWildlife Division, Michigan Department of Natural Resources, Marquette, Michigan, USA.ORCID https://orcid.org/0000-0003-4957-6732
Anaïs K TallonAnimal GenoPhenomics, Agroscope, Posieux, Switzerland.
Maya WeissmanCollege of Forest Resources and Environment Science, Michigan Technological University, Houghton, Michigan, USA.
Dana J MorinDepartment of Wildlife, Fisheries and Aquaculture, Forest and Wildlife Research Center, Mississippi State University, Mississippi State, Mississippi, USA.ORCID https://orcid.org/0000-0002-5612-3259

Funding

Federal Aid in Wildlife Restoration Act, U.S. Fish and Wildlife Service W-155-RNational Institute of Food and Agriculture 1020959National Institute of Food and Agriculture 7008167
6 · The paper itself

Abstract

Close-kin mark-recapture (CKMR) offers a promising alternative to traditional mark-recapture methods for estimating wildlife population parameters. CKMR estimates demographic parameters by identifying genetic relationships between individuals, effectively "recapturing" parental genotypes through their offspring's genetic profiles. One key advantage of CKMR over traditional methods is the ability to estimate abundance without recapture, facilitating the use of lethally collected biological samples. Here, we present an application of CKMR to a terrestrial species using samples collected from harvested individuals. We analyzed genetic data from 1767 American black bears (Ursus americanus) harvested over two consecutive years in Michigan's Upper Peninsula. Using Genotyping-in-Thousands by sequencing (GT-seq), we identified parent-offspring pairs and developed sex-specific models tailored to black bear reproductive biology and management strategies. Female population estimates aligned with our expectations, based on prior knowledge of the population. In contrast, male population estimates deviated from expectations, potentially due to an unmodeled combination of factors pertaining to male reproductive biology and sampling bias. Our study not only demonstrates the viability of using harvest-based CKMR for monitoring of terrestrial wildlife populations, but also highlights the need for careful model specification. By providing a novel method to estimate demographic parameters and population size, CKMR using harvest samples can inform management decisions and harvest quotas. This approach leverages existing management practices involving collection of genetic samples, such as mandatory harvest registrations and health monitoring programs. Our findings contribute to the growing body of CKMR applications and expand its use to terrestrial species management.

Indexed as

Conservation of Natural ResourcesUrsidaeAnimalsFemaleMaleMichiganabundance estimationAmerican black bearclose‐kin mark–recapturegeneticsharvestkinshipterrestrial species

Identifiers

PMID42834575
PMCPMC13639227

What OpenQuestion holds

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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.