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http://dx.doi.org/10.1016/j.cub.2013.07.080 | DOI Listing |
Environ Monit Assess
December 2024
Global Reef, Koh Tao, Thailand.
The current study investigated the morphological dietary preferences of an outbreaking population of corallivorous crown-of-thorn sea stars (Acanthaster sp.) in Koh Tao, situated in the Gulf of Thailand. The local effects of such populations deemed to be in outbreak are currently poorly understood.
View Article and Find Full Text PDFBMC Genomics
November 2024
Third Institute of Oceanography, Ministry of Natural Resources, Xiamen, 361005, China.
Background: Outbreaks of the coral predator Crown-of-Thorns Starfish (CoTS) pose a severe threat to coral reefs in the Indo-Pacific Ocean. In 2018, the South China Sea (SCS) experienced significant CoTS outbreaks, leading to extensive coral mortality across the Xisha, Zhongsha, Dongsha, and Nansha Islands, severely impacting the coral reef ecosystem.
Results: To explore the origins of these outbreaks, we conducted a comprehensive genomic analysis using data from genomic single nucleotide polymorphism sites (SNPs) and mitochondrial haplotypes.
Anal Bioanal Chem
December 2024
Centre for Bioinnovation, University of the Sunshine Coast, Sippy Downs, QLD, 4556, Australia.
Mar Environ Res
November 2024
School of Life and Environmental Sciences, University of Sydney, Sydney, NSW, 2006, Australia. Electronic address:
Critical loss of habitat is the greatest threat to biodiversity, yet some species are inherently plastic to and may even benefit from changes in ecosystem states. The crown-of-thorns sea star (CoTS; Acanthaster spp.) may be one such organism.
View Article and Find Full Text PDFSci Total Environ
November 2024
School of the Environment, University of Queensland, St Lucia 4072, QLD, Australia.
Outbreaks of corallivorous Crown of Thorns Starfish (Acanthaster spp.; CoTS) cause substantial coral mortality throughout the Indo-Pacific, particularly on the Great Barrier Reef (GBR). Refining CoTS population density modelling and understanding the disparities between real-world observations and model predictions is crucial for developing effective control strategies.
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