Identifying ecological change and its causes: A case study on coral reefs

The successful management of ecosystems depends on early detection of change and identification of factors causing such change. Determination of change and causality in ecosystems is difficult, both philosophically and practically, and these difficulties increase with the scale and complexity of ecosystems. Management also depends on the communication of scientific results to the broader public, and this can fail if the evidence of change and causality is not synthesized in a transparent manner. We developed a framework to address these problems when assessing the effects of agricultural runoff on coral reefs of the Australian Great Barrier Reef (GBR). The framework is based on improved methods of statistical estimation (rejecting the use of statistical tests to detect change), and the use of epidemiological causal criteria that are both scientifically rigorous and under-stood by nonspecialists. Many inshore reefs of the GBR are exposed to terrestrial runoff from agriculture. However, detecting change and attributing it to the increasing loads of nutrients, sediments, and pesticides is complicated by the large spatial scale, presence of additional disturbances, and lack of historical data. Three groups of ecological attributes, namely, benthos cover, octocoral richness, and community structure, were used to discriminate between potential causes of change. Ecological surveys were conducted along water quality gradients in two regions: one that receives river flood plumes from agricultural areas and one exposed to runoff from catchments with little or no agriculture. The surveys showed increasing macroalgal cover and decreasing octocoral biodiversity along the gradients within each of the regions, and low hard coral and octocoral cover in the region exposed to terrestrial runoff. Effects were strong and ecologically relevant, occurred independently in different populations, agreed with known biological facts of organism responses to pollution, and were consistent with pollution effects found in other parts of the world. The framework enabled us to maximize the information derived from observational data and other sources, weigh the evidence of changes across potential causes, make decisions in a coherent and transparent manner, and communicate information and conclusions to the broader public. The framework is applicable to a wide range of ecological assessments.