Evidence map›Paper›PMID 35045110›Full record

ArticlePloS one2022

Evaluating the effectiveness of drones for quantifying invasive upside-down jellyfish (Cassiopea sp.) in Lake Macquarie, Australia.

Claire E Rowe, Will F Figueira, Brendan P Kelaher, Anna Giles, Lea T Mamo, Shane T Ahyong, Stephen J Keable

Abstract read
In one paragraph

Article in PloS one, 2022. 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. Identification ofPeerJ · 2025
    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

7 authors.

Claire E RoweSchool of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-5205-7629
Will F FigueiraSchool of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0001-9472-8710
Brendan P KelaherNational Marine Science Centre, Southern Cross University, Lismore, New South Wales, Australia.
Anna GilesNational Marine Science Centre, Southern Cross University, Lismore, New South Wales, Australia.
Lea T MamoNational Marine Science Centre, Southern Cross University, Lismore, New South Wales, Australia.
Shane T AhyongMarine Invertebrates, Australian Museum Research Institute, Sydney, New South Wales, Australia.
Stephen J KeableMarine Invertebrates, Australian Museum Research Institute, Sydney, New South Wales, Australia.ORCID 0000-0002-1754-6750

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Upside-down jellyfish (Cassiopea sp.) are mostly sedentary, benthic jellyfish that have invaded estuarine ecosystems around the world. Monitoring the spread of this invasive jellyfish must contend with high spatial and temporal variability in abundance of individuals, especially around their invasion front. Here, we evaluated the utility of drones to survey invasive Cassiopea in a coastal lake on the east coast of Australia. To assess the efficacy of a drone-based methodology, we compared the densities and counts of Cassiopea from drone observations to conventional boat-based observations and evaluated cost and time efficiency of these methods. We showed that there was no significant difference in Cassiopea density measured by drones compared to boat-based methods along the same transects. However, abundance estimates of Cassiopea derived from scaling-up transect densities were over-inflated by 319% for drones and 178% for boats, compared to drone-based counts of the whole site. Although conventional boat-based survey techniques were cost-efficient in the short-term, we recommend doing whole-of-site counts using drones. This is because it provides a time-saving and precise technique for long-term monitoring of the spatio-temporally dynamic invasion front of Cassiopea in coastal lakes and other sheltered marine habitats with relatively clear water.

Indexed as

AnimalsAnimals, WildAustraliaBehavior, AnimalEcosystemEnvironmental MonitoringIntroduced SpeciesLakesScyphozoaUnmanned Aerial DevicesWaterWater

Identifiers

PMID35045110
PMCPMC8769344

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.