Aim Coral reefs are widely considered to be particularly vulnerable to changes in ocean temperatures, yet we understand little about the broad-scale spatio-temporal patterns that may cause coral mortality from bleaching and disease. Our study aimed to characterize these ocean temperature patterns at biologically relevant scales.
Location Global, with a focus on coral reefs.
Methods We created a 4-km resolution, 21-year global ocean temperature anomaly (deviations from long-term means) database to quantify the spatial and temporal characteristics of temperature anomalies related to both coral bleaching and disease. Then we tested how patterns varied in several key metrics of disturbance severity, including anomaly frequency, magnitude, duration and size.
Results Our analyses found both global variation in temperature anomalies and fine-grained spatial variability in the frequency, duration and magnitude of temperature anomalies. However, we discovered that even during major climatic events with strong spatial signatures, like the El Niño–Southern Oscillation, areas that had high numbers of anomalies varied between years. In addition, we found that 48% of bleaching-related anomalies and 44% of disease-related anomalies were less than 50 km2, much smaller than the resolution of most models used to forecast climate changes.
Main conclusions The fine-scale variability in temperature anomalies has several key implications for understanding spatial patterns in coral bleaching- and disease-related anomalies as well as for designing protected areas to conserve coral reefs in a changing climate. Spatial heterogeneity in temperature anomalies suggests that certain reefs could be targeted for protection because they exhibit differences in thermal stress. However, temporal variability in anomalies could complicate efforts to protect reefs, because high anomalies in one year are not necessarily predictive of future patterns of stress. Together, our results suggest that temperature anomalies related to coral bleaching and disease are likely to be highly heterogeneous and could produce more localized impacts of climate change.