Evidence map›Paper›PMID 41917382›Full record

ArticleScientific reports2026

Observing abilities of satellite-tagged sea turtles: comparison of reconstructed temperature profiles with ocean model data in the Adriatic and Ionian Seas.

Daniele Piazzolla, Simone Bonamano, Carla Cherubini, Viviana Piermattei, Marco Marcelli, Giacomo Marzano, Francesco De Franco, Emanuela Clementi, Ivan Federico, Giovanni Coppini and 1 more

Abstract readComparative Study
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.

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1 · What the graph read from it

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.

2 · The registry

The trial behind it

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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

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Daniele PiazzollaCMCC Foundation - Euro-Mediterranean Center on Climate Change, Lecce, Italy.
Simone BonamanoCMCC Foundation - Euro-Mediterranean Center on Climate Change, Lecce, Italy.
Carla CherubiniCMCC Foundation - Euro-Mediterranean Center on Climate Change, Lecce, Italy.
Viviana PiermatteiCMCC Foundation - Euro-Mediterranean Center on Climate Change, Lecce, Italy.
Marco MarcelliCMCC Foundation - Euro-Mediterranean Center on Climate Change, Lecce, Italy.
Giacomo MarzanoConsorzio di gestione di Torre Guaceto, Carovigno, Brindisi, Italy.
Francesco De FrancoConsorzio di gestione di Torre Guaceto, Carovigno, Brindisi, Italy.
Emanuela ClementiCMCC Foundation - Euro-Mediterranean Center on Climate Change, Lecce, Italy.
Ivan FedericoCMCC Foundation - Euro-Mediterranean Center on Climate Change, Lecce, Italy.
Giovanni CoppiniCMCC Foundation - Euro-Mediterranean Center on Climate Change, Lecce, Italy.
Rosalia MagliettaCMCC Foundation - Euro-Mediterranean Center on Climate Change, Lecce, Italy. rosalia.maglietta@cnr.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In situ and satellite-based oceanographic data are essential to understanding marine dynamics. In this study, we explore the ability of seawater temperature profiles along the water column, reconstructed from data collected by satellite-tagged loggerhead sea turtles, to capture ocean thermal structures. Temperature and depth data collected by seven loggerhead turtles (Caretta caretta) equipped with satellite tags in the Adriatic and northern Ionian Seas were compared with Copernicus Marine model products. Discrepancies between observed and CMEMS MedFS data primarily occur at intermediate (15 to 50 m) and greater depths (50 to 100 m), especially during summer and winter seasons, when stratification and limited deep-water observations reduce accuracy. These differences were most pronounced in dynamically complex areas such as the Western Adriatic Coastal Current (WACC) region and in the northern and middle Adriatic Seas, where fine-scale coastal processes and intense winter cooling challenge the resolution of both the CMEMS MedFS data and the animal-borne sensors. Although limited in sample size, the dataset offers a valuable opportunity to evaluate the additional observational insights provided by animal-borne sensors in challenging oceanographic environments, emphasizing the complementary role of turtle-borne observations within existing monitoring networks.

Indexed as

TemperatureTurtlesAnimalsOceanographyOceans and SeasSeasonsSeawaterAnimal-borne sensorsC. carettanumerical modelssatellite tagsea turtlesstatistical models

Identifiers

PMID41917382
PMCPMC13181045

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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.