Evidence map›Paper›PMID 41136510›Full record

ArticleScientific reports2025

Monitoring juvenile sicklefin lemon shark Negaprion acutidens in remote marine nurseries using unmanned aerial vehicles (UAVs).

Chia-Yun Joanne Li, Chin-Ti Lin, Keryea Soong

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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
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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

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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

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

3 authors.

Chia-Yun Joanne LiCoastal and Offshore Resources Research Center, Fisheries Research Institute, Ministry of Agriculture, Kaohsiung, 80672, Taiwan. iwy5422@gmail.com.
Chin-Ti LinDepartment of Oceanography, National Sun Yat-sen University, Kaohsiung, 804201, Taiwan.
Keryea SoongDepartment of Oceanography, National Sun Yat-sen University, Kaohsiung, 804201, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding spatial and demographic patterns in threatened coastal sharks is essential for effective conservation, yet remote reef systems remain understudied due to logistical constraints. We used dual unmanned aerial vehicles (UAVs) to monitor juvenile Negaprion acutidens around Dongsha Atoll, a no-take marine reserve in the northern South China Sea. Thirteen synchronized UAV surveys were conducted during summer and winter, covering 20 locations categorized into three zones representing different levels of human impact. We quantified seasonal variation in shark abundance, body size, spatial distribution, and environmental drivers using Generalized Linear Mixed Models (GLMMs). Results revealed stable overall abundance but strong fine-scale shifts between summer and winter. Northeastern sites showed sharp declines in shark sightings during winter, likely due to monsoonal exposure, while sheltered southern zones supported increased winter presence. Neonates were concentrated in lagoon habitats, whereas larger individuals occurred farther offshore and in seagrass areas, indicating ontogenetic habitat expansion. Human impact shaped demographic structure: low-impact areas hosted more and larger sharks, while smaller individuals and nearshore aggregation dominated high-impact zones. These findings confirm Dongsha's role as a critical nursery habitat for N. acutidens and highlight the utility of UAV surveys for capturing spatiotemporal ecological patterns in remote ecosystems. By integrating UAV monitoring with conservation planning, managers can prioritize seasonal protection of nursery zones and respond adaptively to climate and anthropogenic pressures.

Indexed as

Environmental MonitoringSharksUnmanned Aerial DevicesAnimalsChinaConservation of Natural ResourcesEcosystemHumansRemote Sensing TechnologySeasonsAnthropogenic disturbanceDongsha atollDrone surveyNegaprion acutidensSpatial ecologyUAV

Identifiers

PMID41136510
PMCPMC12552443

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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.