Evidence map›Paper›PMID 40353826›Full record

ArticleJournal of phycology2025

Assessment of the spatial distribution of Chondria tumulosa, a nuisance macroalga at Manawai in Papahānaumokuākea Marine National Monument using high-resolution satellite imagery.

Leiana Beyer, Tomoaki Miura, Kaʻuaʻoa Fraiola, Heather L Spalding, Taylor M Williams, Jonathan Martinez, Randall K Kosaki, Keolohilani H Lopes

Abstract read
In one paragraph

Article in Journal of phycology, 2025. 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

8 authors.

Leiana BeyerDepartment of Natural Resources and Environmental Management, University of Hawai'i at Mānoa, Honolulu, Hawaii, USA.ORCID 0000-0002-1935-5800
Tomoaki MiuraDepartment of Natural Resources and Environmental Management, University of Hawai'i at Mānoa, Honolulu, Hawaii, USA.ORCID 0000-0002-0882-3568
Kaʻuaʻoa FraiolaUnited States Geological Survey, Honolulu, Hawaii, USA.ORCID 0000-0003-3215-6651
Heather L SpaldingDepartment of Biology, College of Charleston, Charleston, South Carolina, USA.ORCID 0000-0003-3800-4990
Taylor M WilliamsDepartment of Biology, College of Charleston, Charleston, South Carolina, USA.
Jonathan MartinezUnited States Fish and Wildlife Service, Albuquerque, New Mexico, USA.
Randall K KosakiNational Oceanic and Atmospheric Administration, Honolulu, Hawaii, USA.ORCID 0000-0003-1363-5702
Keolohilani H LopesDepartment of Natural Resources and Environmental Management, University of Hawai'i at Mānoa, Honolulu, Hawaii, USA.ORCID 0000-0001-6116-0655

Funding

National Fish and Wildlife FoundationNational Oceanic and Atmospheric AdministrationU.S. Fish and Wildlife Service F21AC01611
6 · The paper itself

Abstract

In 2019, a red macroalgal species, Chondria tumulosa, was discovered overgrowing native coral and algal species and changing the benthic communities of Manawai (Pearl and Hermes Atoll) in Papahānaumokuākea Marine National Monument (PMNM). The main objective of this study was to assess the spatial distribution of C. tumulosa across the forereef and backreef of Manawai using satellite remote sensing. WorldView-2 and -3 commercial high-resolution satellite images were obtained for a 12-year period from 2010 to 2021, from which, time-series animations were created. Previous studies reported that C. tumulosa appeared as distinctively dark features in satellite imagery with the first evidence of C. tumulosa in 2015. Thus, the animations were visually inspected to identify dark patches that became visible around the time of discovery and persisted in subsequent years. Field survey data of C. tumulosa cover collected in 2019-2021 were used to gain confidence in the identification of dark patches. Using those dark features as a reference and a support vector machine, the latest high-resolution satellite images from the 12-year period were classified into a map of distinctive dark patches suspected to be C. tumulosa with an average overall accuracy of 78%. Accuracy assessments of the classification results of C. tumulosa based on field survey data collected in 2019-2021 resulted in an overall accuracy of 79%. This study leverages the use of remote sensing to map a newly discovered alga in a remote area in the hopes of providing managers with a methodology to further monitor the species for long-term management.

Indexed as

RhodophytaSatellite ImagerySeaweedChondria tumulosacryptic speciesimage analysismacroalgaeNorthwestern Hawaiian Islandsremote sensing

Identifiers

PMID40353826
PMCPMC12168099

What OpenQuestion holds

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LicenceCC BY-NC
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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.