Newly described algae species toughens up corals to endure warming oceans
Global climate change has increased water temperatures in the world's oceans, often causing mass coral bleaching and mortality, which harms not only corals, but also the vast ecosystems they support. Using innovative methods, researchers at Penn State University have identified a new species of stress-tolerant Symbiodinium, a genus of algae that occurs mutualistically with corals in a partnership that promotes the health and growth of coral reef ecosystems. The team's paper, which appears in a recent issue of the journal Phycologia, also describes the geographical distribution of Symbiodinium glynnii, how it differs from other stress-tolerant symbiont species, and its capacity to spread to places around the Pacific and live with different coral hosts.
According to Todd LaJeunesse, associate professor of biology at Penn State, the algae, which he named Symbiodinium glynnii, is common among corals in the pocilloporid and montiporid families that dominate the warm or variable environments of the Pacific Ocean. "Symbiodinium glynnii is a highly abundant species in the Eastern Pacific, which explains, in part, why Pocillopora colonies dominate the coral communities over this broad and environmentally diverse region," said LaJeunesse. "Corals with this species of algal symbiont are physiologically robust and can withstand conditions that would be too extreme for coral colonies harboring other kinds of symbiont."
The researchers relied primarily on genetic evidence gathered from the analysis of hundreds of samples obtained from far-flung sites in the Pacific Ocean, including reefs near Mexico, Panama, the Galapagos Islands, the Phoenix Islands, Hawaii, and Palau. They also examined samples from aquarium collections. The team used a variety of data to identify the new species, including DNA sequences, microsatellite genotyping, host associations, cell sizes, and other traits. They also imported this data into a computer program, pioneering an approach to use machine learning to unambiguously identify species that are normally hard to distinguish.