Evidence map›Paper›PMID 41545621›Full record

ArticleScientific reports2026

Ensuring reliable cave temperature data for climate change research.

Alice Cimenti, Lorenzo Cresi, Marco Isaia, Elena Piano, Anna Piquet, Giuseppe Nicolosi, Stefano Mammola, Antonella Senese, Fiorella Acquaotta

Abstract read
In one paragraph

Article in Scientific reports, 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

9 authors.

Alice Cimenti *Dipartimento di Scienze della Terra, Università degli Studi di Torino, Torino, Italy.ORCID http://orcid.org/0009-0006-8789-2567
Lorenzo Cresi *Department of Environmental Science and Policy (ESP), Università degli Studi di Milano, Via Celoria 10, Milano, 20133, Italy. lorenzo.cresi@unimi.it.ORCID http://orcid.org/0009-0008-7244-1960
Marco IsaiaDipartimento di Scienze della Vita e Biologia dei Sistemi, University of Torino, Torino, Italia.ORCID http://orcid.org/0000-0001-5434-2127
Elena PianoDipartimento di Scienze della Vita e Biologia dei Sistemi, University of Torino, Torino, Italia.ORCID http://orcid.org/0000-0002-4685-7240
Anna PiquetDipartimento di Scienze della Terra, Università degli Studi di Torino, Torino, Italy.ORCID http://orcid.org/0009-0000-5093-2971
Giuseppe NicolosiDepartment of Biological, Geological and Environmental Sciences, University of Catania, Catania, Italy.ORCID http://orcid.org/0000-0002-6360-7171
Stefano MammolaNational Biodiversity Future Center, Palermo, Italy.ORCID http://orcid.org/0000-0002-4471-9055
Antonella Senese *Department of Environmental Science and Policy (ESP), Università degli Studi di Milano, Via Celoria 10, Milano, 20133, Italy.ORCID http://orcid.org/0000-0001-7190-3272
Fiorella Acquaotta *Dipartimento di Scienze della Terra, Università degli Studi di Torino, Torino, Italy.ORCID http://orcid.org/0000-0002-9498-3313

Funding

NextGenerationEU 2022MJSYF8
6 · The paper itself

Abstract

Caves are unique natural laboratories for studying climate change and its ecological impacts. However, analyzing air temperature in these environments is challenging due to stable microclimatic conditions and high humidity. Collecting reliable data requires dedicated devices and protocols. We developed a standardized quality control procedure-Cave Air Temperature Quality Control (CAT-QC)-to assess the reliability of temperature data collected inside caves. The protocol consists of four main steps: (i) assessing data completeness; (ii) identifying physically implausible values; (iii) detecting statistical outliers using three progressively sensitive methods; and (iv) conducting a final manual check. We tested CAT-QC on a dataset from 19 caves in the Piedmont region (Northwest Italy), recorded with iButton devices. The protocol effectively identified gaps, absurd values, and abrupt temperature changes, many of which were due to human interference or sensor issues. Data flagged through CAT-QC can be further reviewed to address biases and rerun through the process if needed. Designed for broad applicability, CAT-QC is dynamic and can be tailored to local series characteristics, making it suitable for diverse subterranean environments. This tool provides a robust framework for ensuring data quality and comparability in cave climate studies, supporting research and conservation efforts in the context of climate change.

Indexed as

Air temperatureClimate changeLong-term monitoringQuality controlSubterranean ecosystem

Identifiers

PMID41545621
PMCPMC12858822

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.