ArticleEcology and evolution2026
Community Science: Big Insights From Small Mammal Data.
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.
What it found
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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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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.