Evidence map›Paper›PMID 36950367›Full record

ArticleEcology and evolution2023

Novel frontier in wildlife monitoring: Identification of small rodent species from fecal pellets using near-infrared reflectance spectroscopy (NIRS).

Maria W Tuomi, Francisco J A Murguzur, Katrine S Hoset, Eeva M Soininen, Eero J Vesterinen, Tove Aa Utsi, Sissel Kaino, Kari Anne Bråthen

Open access · goldFull text read
In one paragraph

Article in Ecology and evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 21% of its field
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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
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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

8 authors at 4 institutions in 3 countries.

Maria W TuomiDepartment of Arctic and Marine Biology UiT The Arctic University of Norway Tromsø Norway.ORCID https://orcid.org/0000-0002-7154-5177
Francisco J A MurguzurDepartment of Arctic and Marine Biology UiT The Arctic University of Norway Tromsø Norway.ORCID https://orcid.org/0000-0002-1435-5190
Katrine S HosetSection of Ecology Department of Biology University of Turku Turku Finland.ORCID https://orcid.org/0000-0002-1371-012X
Eeva M SoininenDepartment of Arctic and Marine Biology UiT The Arctic University of Norway Tromsø Norway.ORCID https://orcid.org/0000-0003-4280-8350
Eero J VesterinenDepartment of Ecology Swedish University of Agricultural Sciences Uppsala Sweden.ORCID https://orcid.org/0000-0003-3665-5802
Tove Aa UtsiDepartment of Arctic and Marine Biology UiT The Arctic University of Norway Alta Norway.ORCID https://orcid.org/0000-0003-0776-2369
Sissel KainoDepartment of Arctic and Marine Biology UiT The Arctic University of Norway Tromsø Norway.
Kari Anne BråthenDepartment of Arctic and Marine Biology UiT The Arctic University of Norway Tromsø Norway.ORCID https://orcid.org/0000-0003-0942-1074
UiT The Arctic University of Norway · NOUniversity of Turku · FICentre for Arctic Gas Hydrate, Environment and Climate · NOUniversity of Helsinki · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Small rodents are prevalent and functionally important across the world's biomes, making their monitoring salient for ecosystem management, conservation, forestry, and agriculture. There is a growing need for cost-effective and noninvasive methods for large-scale, intensive sampling. Fecal pellet counts readily provide relative abundance indices, and given suitable analytical methods, feces could also allow for the determination of multiple ecological and physiological variables, including community composition. In this context, we developed calibration models for rodent taxonomic determination using fecal near-infrared reflectance spectroscopy (fNIRS). Our results demonstrate fNIRS as an accurate and robust method for predicting genus and species identity of five coexisting subarctic microtine rodent species. We show that sample exposure to weathering increases the method's accuracy, indicating its suitability for samples collected from the field. Diet was not a major determinant of species prediction accuracy in our samples, as diet exhibited large variation and overlap between species. fNIRS could also be applied across regions, as calibration models including samples from two regions provided a good prediction accuracy for both regions. We show fNIRS as a fast and cost-efficient high-throughput method for rodent taxonomic determination, with the potential for cross-regional calibrations and the use on field-collected samples. Importantly, appeal lies in the versatility of fNIRS. In addition to rodent population censuses, fNIRS can provide information on demography, fecal nutrients, stress hormones, and even disease. Given the development of such calibration models, fNIRS analytics could complement novel genetic methods and greatly support ecosystem- and interaction-based approaches to monitoring.

Indexed as

abundance indexdietDNA metabarcodingfield methodmultispecies communitynoninvasive samplingtundra

Identifiers

PMID36950367
PMCPMC10024998
OpenAlexW4327858987

What OpenQuestion holds

Textfull text, public
LicenceCC BY
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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.