Evidence map›Paper›PMID 37284929›Full record

ArticleAnimal cognition2023

Assessment of predation risk through conspecific cues by anuran larvae.

Carlos Caballero-Díaz, Rosa Arribas, Nuria Polo-Cavia

Abstract read
In one paragraph

Article in Animal cognition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Carlos Caballero-DíazDepartment of Biology, Universidad Autónoma de Madrid, Ciudad Universitaria de Cantoblanco, 28049, Madrid, Spain.
Rosa ArribasDepartment of Biology, Universidad Autónoma de Madrid, Ciudad Universitaria de Cantoblanco, 28049, Madrid, Spain.
Nuria Polo-CaviaDepartment of Biology, Universidad Autónoma de Madrid, Ciudad Universitaria de Cantoblanco, 28049, Madrid, Spain. nuria.polo@uam.es.ORCID http://orcid.org/0000-0003-4258-0210

Funding

Ministerio de Ciencia, Innovación y Universidades CGL2015-68670-R
6 · The paper itself

Abstract

Accurate assessment of predation risk is critical for prey survival during predator-prey interactions. Prey can assess predation risk by the presence of cues dropped by predators themselves, but they can also gather information about risk level through cues released by other prey, avoiding the hazard of being in close proximity to predators. In this study, we examine the ability of anuran larvae (Pelobates cultripes) to detect predation risk indirectly when they are in contact with conspecifics that have been recently exposed to chemical stimuli from natural predators (larvae of aquatic beetles). In a first experiment, we confirmed that larvae exposed to predator cues exhibited innate defensive behavior, indicating that they perceived the risk of predation and, thus, could potentially act as risk indicators for naïve conspecifics. In a second experiment, we observed that unexposed larvae paired with a startled conspecific adjusted their antipredator behavior, presumably by mirroring conspecifics' behavior and/or using chemical cues from their partners as a risk information source. This cognitive ability of tadpoles to assess predation risk through conspecific cues might play an important role in their interaction with predators, facilitating the early detection of potential threats to elicit appropriate antipredator responses and increase the chances of survival.

Indexed as

CuesPredatory BehaviorAnimalsAnuraLarvaAntipredator behaviorDisturbance cuesLarval amphibiansPelobates cultripesRisk assessmentSocial learning

Identifiers

PMID37284929
PMCPMC10344842

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.