Back

Experimental Thermal Stress Increases Corallicolid Relative Abundance in the Stony Coral Pocillopora damicornis

Znamenacek, H. G.; Wilson, E. R.; Bonacolta, A. M.; Brendtro, K. S.

2026-08-20 ecology
10.64898/2026.08.17.745262 bioRxiv
Show abstract

Rising ocean temperatures disrupt previously stable coral-microbe interactions, leading to widespread coral mortality and threatening reef ecosystems worldwide. Growing evidence demonstrates the coral microbiome, including protists, plays a critical role in the host response to thermal stress. Specifically, corallicolids (Phylum: Apicomplexa) are positively correlated with thermal stress mortality in soft corals. This study investigates changes in the eukaryotic microbiome of the stony coral, Pocillopora damicornis, across an experimental thermal stress event. Using anti-metazoan 18S rRNA gene metabarcoding, protist communities were assessed at four time-points during experimental thermal stress. Outside of the Symbiodiniaceae, a prominent shift in microbiome composition during thermal stress was observed, most notably a significant increase and dominance in Corallicolida abundance in heat-stressed corals, while other protists declined substantially. Increased corallicolid abundance concurrent with bleaching suggests an overlooked compounding stressor beyond the loss of algal symbionts during heat stress. These results contrast with previous research on Pocillopora microbiomes showing prokaryotic community stability throughout stress, and support the hypothesis that thermal stress may alter the coral-corallicolid relationship, potentially shifting corallicolids from a commensal to a parasitic role, and synergistically contributing to coral mortality during and after heat stress. This work provides critical insight into the role of protists in marine holobionts, supports their inclusion in future microbiome studies, and informs strategies to improve coral resilience under climate change.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.