In patients with an intracranial pressure of more than 20 mm Hg after traumatic brain injury, therapeutic hypothermia plus standard care to reduce intracranial pressure did not result in outcomes better than those with standard care alone. (Funded by the National Institute for Health Research Health Technology Assessment program; Current Controlled Trials number, ISRCTN34555414.).

Global species richness, whether estimated by taxon, habitat, or ecosystem, is a key biodiversity metric. Yet, despite the global importance of biodiversity and increasing threats to it (e.g., we are no better able to estimate global species richness now than we were six decades ago. Estimates of global species richness remain highly uncertain and are often logically inconsistent. They are also difficult to validate because estimation of global species richness requires extrapolation beyond the number of species known. Given that somewhere between 3% and >96% of species on Earth may remain undiscovered, depending on the methods used and the taxa considered, such extrapolations, especially from small percentages of known species, are likely to be highly uncertain. An alternative approach is to estimate all species, the known and unknown, directly. Using expert taxonomic knowledge of the species already described and named, those already discovered but not yet described and named, and those still awaiting discovery, we estimate there to be 830,000 (95% credible limits: 550,000-1,330,000) multi-cellular species on coral reefs worldwide, excluding fungi. Uncertainty surrounding this estimate and its components were often strongly skewed toward larger values, indicating that many more species on coral reefs is more plausible than many fewer. The uncertainties revealed here should guide future research toward achieving convergence in global species richness estimates for coral reefs and other ecosystems via adaptive learning protocols whereby such estimates can be tested and improved, and their uncertainties reduced, as new knowledge is acquired.

Bayesian statistical modeling has several benefits within an ecological context. In particular, when observed data are limited in sample size or representativeness, then the Bayesian framework provides a mechanism to combine observed data with other "prior" information. Prior information may be obtained from earlier studies, or in their absence, from expert knowledge. This use of the Bayesian framework reflects the scientific "learning cycle," where prior or initial estimates are updated when new data become available. In this paper we outline a framework for statistical design of expert elicitation processes for quantifying such expert knowledge, in a form suitable for input as prior information into Bayesian models. We identify six key elements: determining the purpose and motivation for using prior information; specifying the relevant expert knowledge available; formulating the statistical model; designing effective and efficient numerical encoding; managing uncertainty; and designing a practical elicitation protocol. We demonstrate this framework applies to a variety of situations, with two examples from the ecological literature and three from our experience. Analysis of these examples reveals several recurring important issues affecting practical design of elicitation in ecological problems.

Summary1. Species' distribution modelling relies on adequate data sets to build reliable statistical models with high predictive ability. However, the money spent collecting empirical data might be better spent on management. A less expensive source of species' distribution information is expert opinion. This study evaluates expert knowledge and its source. In particular, we determine whether models built on expert knowledge apply over multiple regions or only within the region where the knowledge was derived. 2. The case study focuses on the distribution of the brush-tailed rock-wallaby Petrogale penicillata in eastern Australia. We brought together from two biogeographically different regions substantial and well-designed field data and knowledge from nine experts. We used a novel elicitation tool within a geographical information system to systematically collect expert opinions. The tool utilized an indirect approach to elicitation, asking experts simpler questions about observable rather than abstract quantities, with measures in place to identify uncertainty and offer feedback. Bayesian analysis was used to combine field data and expert knowledge in each region to determine: (i) how expert opinion affected models based on field data and (ii) how similar expert-informed models were within regions and across regions. 3. The elicitation tool effectively captured the experts' opinions and their uncertainties. Experts were comfortable with the map-based elicitation approach used, especially with graphical feedback. Experts tended to predict lower values of species occurrence compared with field data. 4. Across experts, consensus on effect sizes occurred for several habitat variables. Expert opinion generally influenced predictions from field data. However, south-east Queensland and north-east New South Wales experts had different opinions on the influence of elevation and geology, with these differences attributable to geological differences between these regions. 5. Synthesis and applications. When formulated as priors in Bayesian analysis, expert opinion is useful for modifying or strengthening patterns exhibited by empirical data sets that are limited in size or scope. Nevertheless, the ability of an expert to extrapolate beyond their region of knowledge may be poor. Hence there is significant merit in obtaining information from local experts when compiling species' distribution models across several regions.

Anthropogenic increases of atmospheric carbon dioxide lead to warmer sea surface temperatures and altered ocean chemistry. Experimental evidence suggests that coral calcification decreases as aragonite saturation drops but increases as temperatures rise toward thresholds optimal for coral growth. In situ studies have documented alarming recent declines in calcification rates on several tropical coral reef ecosystems. We show there is no widespread pattern of consistent decline in calcification rates of massive Porites during the 20th century on reefs spanning an 11° latitudinal range in the southeast Indian Ocean off Western Australia. Increasing calcification rates on the high-latitude reefs contrast with the downward trajectory reported for corals on Australia's Great Barrier Reef and provide additional evidence that recent changes in coral calcification are responses to temperature rather than ocean acidification.