Evidence map›Paper›PMID 36604526›Full record

ArticleScientific reports2023

Sampling environmental DNA from trees and soil to detect cryptic arboreal mammals.

Michael C Allen, Robert Kwait, Anthony Vastano, Alex Kisurin, Isabelle Zoccolo, Benjamin D Jaffe, Jordan C Angle, Brooke Maslo, Julie L Lockwood

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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  11. Passive Sampling of Urban Runoff Solids to Capture Environmental DNA for the Detection of Rodents in Urban Spaces.Water environment research : a research publication of the Water Environment Federation · 2025
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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

9 authors.

Michael C AllenEcology, Evolution and Natural Resources, Rutgers University, 14 College Farm Road, New Brunswick, NJ, 08901, USA. michael.allen@rutgers.edu.
Robert KwaitEcology, Evolution and Natural Resources, Rutgers University, 14 College Farm Road, New Brunswick, NJ, 08901, USA.
Anthony VastanoEcology, Evolution and Natural Resources, Rutgers University, 14 College Farm Road, New Brunswick, NJ, 08901, USA.
Alex KisurinEcology, Evolution and Natural Resources, Rutgers University, 14 College Farm Road, New Brunswick, NJ, 08901, USA.
Isabelle ZoccoloEcology, Evolution and Natural Resources, Rutgers University, 14 College Farm Road, New Brunswick, NJ, 08901, USA.
Benjamin D JaffeExxonMobil Biomedical Sciences Inc, Annandale, NJ, USA.
Jordan C AngleExxonMobil Upstream Research Company, Spring, TX, USA.
Brooke MasloEcology, Evolution and Natural Resources, Rutgers University, 14 College Farm Road, New Brunswick, NJ, 08901, USA.
Julie L LockwoodEcology, Evolution and Natural Resources, Rutgers University, 14 College Farm Road, New Brunswick, NJ, 08901, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Environmental DNA (eDNA) approaches to monitoring biodiversity in terrestrial environments have largely focused on sampling water bodies, potentially limiting the geographic and taxonomic scope of eDNA investigations. We assessed the performance of two strictly terrestrial eDNA sampling approaches to detect arboreal mammals, a guild with many threatened and poorly studied taxa worldwide, within two central New Jersey (USA) woodlands. We evaluated species detected with metabarcoding using two eDNA collection methods (tree bark vs. soil sampling), and compared the performance of two detection methods (qPCR vs. metabarcoding) within a single species. Our survey, which included 94 sampling events at 21 trees, detected 16 species of mammals, representing over 60% of the diversity expected in the area. More DNA was found for the 8 arboreal versus 8 non-arboreal species detected (mean: 2466 vs. 289 reads/sample). Soil samples revealed a generally similar composition, but a lower diversity, of mammal species. Detection rates for big brown bat were 3.4 × higher for qPCR over metabarcoding, illustrating the enhanced sensitivity of single-species approaches. Our results suggest that sampling eDNA from on and around trees could serve as a useful new monitoring tool for cryptic arboreal mammal communities globally.

Indexed as

ChiropteraDNA, EnvironmentalAnimalsBiodiversityDNA Barcoding, TaxonomicEnvironmental MonitoringMammalsSoilTreesDNA, EnvironmentalSoil

Identifiers

PMID36604526
PMCPMC9814459

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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.