A recent study published in PeerJ Life & Environment has established a predictive framework for identifying the source populations of Chondria tumulosa, a cryptogenic red macroalga that has been rapidly overtaking coral reef ecosystems in Hawai'i's Papahānaumokuākea Marine National Monument since its first observation in 2016.
The research, titled "A predictive framework for identifying source populations of non-native marine macroalgae: Chondria tumulosa in the Pacific Ocean," addresses one of the most pressing ecological threats facing the protected monument's pristine coral reef systems.
First discovered at Pearl and Hermes Atoll (Manawai) in 2016, C. tumulosa has exhibited alarming invasive characteristics, with satellite imagery revealing a staggering 115-fold increase in area coverage between 2015 and 2021. The alga now forms extensive mats that smother coral reef habitats, expanding at an exponential rate of approximately 44.75 square kilometers per year.
"Understanding the origin of this potentially invasive species is crucial for developing effective management strategies," said the study's lead author. "Our predictive framework combines dispersal modeling with morphological analysis and molecular phylogenetics to help determine which source populations are most likely to have led to the introduction of C. tumulosa."
The research team's approach provides resource managers with essential tools to:
- Identify potential source populations of the alga
- Track its introduction pathways
- Develop targeted prevention strategies
- Guide future monitoring efforts
The study comes at a critical time, as surveys have documented C. tumulosa forming thick mats on forereefs and creating dark, meandering accumulations throughout Manawai Atoll's inner lagoon, threatening the ecological integrity of one of the world's most protected marine environments.
This peer-reviewed research has been positively received by the scientific community, with reviewers noting that "the results and conclusions are well-founded."
The full article is available as open access at: https://peerj.com/articles/19610/
