Evidence map›Paper›PMID 42007277›Full record

ArticleEcology and evolution2026

Community Science: Big Insights From Small Mammal Data.

Marion Sherbourne, Meghan Ward, Meagan Stager, Shelby Cohen, Lucy van Haaften, Thomas Burgess, Bryan Hughes, Jeff Bowman

Abstract read
In one paragraph

Article in Ecology and evolution, 2026. 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

8 authors.

Marion SherbourneEnvironmental and Life Sciences Graduate Program Trent University Peterborough Ontario Canada.ORCID https://orcid.org/0009-0005-8047-4832
Meghan WardEnvironmental and Life Sciences Graduate Program Trent University Peterborough Ontario Canada.ORCID https://orcid.org/0000-0002-4189-2653
Meagan StagerEnvironmental and Life Sciences Graduate Program Trent University Peterborough Ontario Canada.ORCID https://orcid.org/0009-0004-0890-9013
Shelby CohenEnvironmental and Life Sciences Graduate Program Trent University Peterborough Ontario Canada.ORCID https://orcid.org/0009-0008-9087-8058
Lucy van HaaftenBiology Graduate Program Acadia University Wolfville Nova Scotia Canada.ORCID https://orcid.org/0009-0007-6137-4427
Thomas BurgessEnvironmental and Life Sciences Graduate Program Trent University Peterborough Ontario Canada.ORCID https://orcid.org/0009-0004-5558-4469
Bryan HughesEnvironmental and Life Sciences Graduate Program Trent University Peterborough Ontario Canada.ORCID https://orcid.org/0000-0003-4331-7203
Jeff BowmanEnvironmental and Life Sciences Graduate Program Trent University Peterborough Ontario Canada.ORCID https://orcid.org/0000-0002-1892-4469

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biodiversity surveys can be costly and labor-intensive; therefore, community science databases serve as a practical resource to support survey goals. Community science datasets may be a valuable tool for easily identifiable species. In contrast, cryptic or hard-to-identify species may appear less frequently in community science datasets. We investigated the reliability of community science datasets for evaluating the distribution and abundance of small mammals in Ontario, Canada. We selected eight focal species, categorized by historical abundance and ease of identification. We ran a community outreach event from May to August 2025 to promote the contribution of species records as a tool for scientific research. We collected data directly from iNaturalist, the Global Biodiversity Information Facility (GBIF), and records provided directly to us by community members. We counted observations of each focal species before and after our outreach campaign to assess the effectiveness of community outreach for small mammals. Our campaign did not increase the number of iNaturalist submissions of our focal species compared to previous time windows of a similar duration. Furthermore, few observations were obtained for rare or confusible species, whereas most were of abundant, non-confusible species. The lack of abundant new iNaturalist records in response to our campaign may reflect a broader gap in photographic evidence to support the identification of rare small-mammal species. Despite the low number of new iNaturalist records, the combined datasets dramatically increased the total number of records. Our study highlights the limitations of using community science repositories to monitor rare and confusible species. Integrating other community sources alongside iNaturalist yielded the most robust dataset. We encourage small-mammal researchers and enthusiasts to submit photographs of rare or confusing species to community science repositories and to validate submitted photographs. We also suggest establishing a verification process to include community science records without pictures.

Indexed as

abundantcitizen sciencecrypticenigmaticiNaturalistrare

Identifiers

PMID42007277
PMCPMC13090111

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.