Measuring coral reef decline through meta-analyses

• Published in: Philosophical transactions of the Royal Society of London. Series B. Biological sciences Vol. 360; no. 1454; pp. 385 - 395
• Main Authors: Côté, I.M, Gill, J.A, Gardner, T.A, Watkinson, A.R
• Format: Journal Article
• Language: English
• Published: London The Royal Society 28-02-2005
• Subjects: Animals; Anthozoa - physiology; Bias; Caribbean; Conservation biology; Coral reefs; Coral-Algal Phase Shifts; Corals; Datasets; Ecology; Geography; Habitat conservation; Habitat Degradation; Habitat Loss; Large-Scale; Marine ecology; Meta analysis; Meta-Analysis as Topic; Models, Biological; Oceans and Seas; Population Density; Population Dynamics; Rates of change; Research Design; Sample Size; Species Specificity; Time Factors; ASW, Caribbean Sea; Caribbean Sea
• ISSN: 0962-8436; 1471-2970
• DOI: 10.1098/rstb.2004.1591

Coral reef ecosystems are in decline worldwide, owing to a variety of anthropogenic and natural causes. One of the most obvious signals of reef degradation is a reduction in live coral cover. Past and current rates of loss of coral are known for many individual reefs; however, until recently, no large-scale estimate was available. In this paper, we show how meta-analysis can be used to integrate existing small-scale estimates of change in coral and macroalgal cover, derived from in situ surveys of reefs, to generate a robust assessment of long-term patterns of large-scale ecological change. Using a large dataset from Caribbean reefs, we examine the possible biases inherent in meta-analytical studies and the sensitivity of the method to patchiness in data availability. Despite the fact that our meta-analysis included studies that used a variety of sampling methods, the regional estimate of change in coral cover we obtained is similar to that generated by a standardized survey programme that was implemented in 1991 in the Caribbean. We argue that for habitat types that are regularly and reasonably well surveyed in the course of ecological or conservation research, meta-analysis offers a cost-effective and rapid method for generating robust estimates of past and current states.