Evidence map›Paper›PMID 24552834›Full record

ArticleProceedings. Biological sciences2014

Genetic connectivity for two bear species at wildlife crossing structures in Banff National Park.

Michael A Sawaya, Steven T Kalinowski, Anthony P Clevenger

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

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  10. The ecology of human-carnivore coexistence.Proceedings of the National Academy of Sciences of the United States of America · 2020
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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.

Michael A SawayaWestern Transportation Institute, Montana State University, , Bozeman, MT 59717, USA, Department of Ecology, Montana State University, , Bozeman, MT 59717, USA.
Steven T Kalinowski
Anthony P Clevenger

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Roads can fragment and isolate wildlife populations, which will eventually decrease genetic diversity within populations. Wildlife crossing structures may counteract these impacts, but most crossings are relatively new, and there is little evidence that they facilitate gene flow. We conducted a three-year research project in Banff National Park, Alberta, to evaluate the effectiveness of wildlife crossings to provide genetic connectivity. Our main objective was to determine how the Trans-Canada Highway and crossing structures along it affect gene flow in grizzly (Ursus arctos) and black bears (Ursus americanus). We compared genetic data generated from wildlife crossings with data collected from greater bear populations. We detected a genetic discontinuity at the highway in grizzly bears but not in black bears. We assigned grizzly bears that used crossings to populations north and south of the highway, providing evidence of bidirectional gene flow and genetic admixture. Parentage tests showed that 47% of black bears and 27% of grizzly bears that used crossings successfully bred, including multiple males and females of both species. Differentiating between dispersal and gene flow is difficult, but we documented gene flow by showing migration, reproduction and genetic admixture. We conclude that wildlife crossings allow sufficient gene flow to prevent genetic isolation.

Indexed as

EcosystemGene FlowHoming BehaviorSexual Behavior, AnimalAlbertaAnimalsBreedingCanadaConservation of Natural ResourcesFemaleGenetic VariationMaleUrsidaeconnectivityfragmentationgene flowroadursidwildlife crossing structure

Identifiers

PMID24552834
PMCPMC4027379

What OpenQuestion holds

Textmetadata
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.