Back

From stress to survival: identifying heat-resistant corals in Belize for conservation and restoration

Dawson, D. D.

2025-08-20 ecology
10.1101/2025.08.17.670758 bioRxiv
Show abstract

Rising ocean temperatures intensify coral bleaching, yet the response to high temperatures may also hold the key to reef survival. The potential lies in identifying individuals or populations that can withstand elevated temperatures, which could help inform more targeted conservation and restoration efforts. This study assessed the thermal resistance of four dominant coral species in Belize to identify populations best suited for long-term survival under increasing ocean temperatures. Coral populations from six characterized thermal reef sites were subjected to short-term heat exposure to determine bleaching thresholds (ED50), using Visual Bleaching Scores and experimental Degree Heating Days. As in other studies, we found a wide range of heat tolerance within and among species. The massive starlet coral (Siderastrea siderea) exhibited the highest resistance to thermal stress, while the brain coral (Pseudodiploria strigosa) was the most susceptible. The mountainous star coral (Orbicella faveolata) and mustard hill coral (Porites astreoides) showed intermediate heat resistance that varied by site. Notably, the shallower reefs ([~]1-2 meters) of both inshore, central Belize and offshore Turneffe Atoll on the Belize Barrier Reef housed the highest proportion of the most thermally resistant corals. These findings highlight two key adaptive reef management opportunities: conserving naturally heat-resistant reefs and prioritizing thermally tolerant corals in transplantation efforts for restoration. By identifying corals and reef sites with the highest survival potential, this study provides essential insights to help safeguard Belizes reefs against climate change, ensuring their continued ecological and economic benefits.

Matching journals

The top 3 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.