ABSTRACT
As coral bleaching events become more frequent and intense, our ability to predict and mitigate future events depends upon our capacity to interpret patterns within previous episodes. Responses to thermal stress vary among coral species; however the diversity of coral assemblages, environmental conditions, assessment protocols, and severity criteria applied in the global effort to document bleaching patterns creates challenges for the development of a systemic metric of taxon-specific response. Here, we describe and validate a novel framework to standardize bleaching response records and estimate their measurement uncertainties. Taxon-specific bleaching and mortality records (2036) of 374 coral taxa (during 1982-2006) at 316 sites were standardized to average percent tissue area affected and a taxon-specific bleaching response index (taxon-BRI) was calculated by averaging taxon-specific response over all sites where a taxon was present. Differential bleaching among corals was widely variable (mean taxon-BRI = 25.06 ± 18.44%, ±SE). Coral response may differ because holobionts are biologically different (intrinsic factors), they were exposed to different environmental conditions (extrinsic factors), or inconsistencies in reporting (measurement uncertainty). We found that both extrinsic and intrinsic factors have comparable influence within a given site and event (60% and 40% of bleaching response variance of all records explained, respectively). However, when responses of individual taxa are averaged across sites to obtain taxon-BRI, differential response was primarily driven by intrinsic differences among taxa (65% of taxon-BRI variance explained), not conditions across sites (6% explained), nor measurement uncertainty (29% explained). Thus, taxon-BRI is a robust metric of intrinsic susceptibility of coral taxa. Taxon-BRI provides a broadly applicable framework for standardization and error estimation for disparate historical records and collection of novel data, allowing for unprecedented accuracy in parameterization of mechanistic and predictive models and conservation plans.