On the use of Bayesian decision theory for issuing natural hazard warnings

This is the final version of the article. Available from the Royal Society via the DOI in this record.Warnings for natural hazards improve societal resilience and are a good example of decision-making under uncertainty. A warning system is only useful if well defined and thus understood by stakeholders. However, most operational warning systems are heuristic: not formally or transparently defined. Bayesian decision theory provides a framework for issuing warnings under uncertainty but has not been fully exploited. Here, a decision theoretic framework is proposed for hazard warnings. The framework allows any number of warning levels and future states of nature, and a mathematical model for constructing the necessary loss functions for both generic and specific end-users is described. The approach is illustrated using one-day ahead warnings of daily severe precipitation over the UK, and compared to the current decision tool used by the UK Met Office. A probability model is proposed to predict precipitation, given ensemble forecast information, and loss functions are constructed for two generic stakeholders: an end-user and a forecaster. Results show that the Met Office tool issues fewer high-level warnings compared with our system for the generic end-user, suggesting the former may not be suitable for risk averse end-users. In addition, raw ensemble forecasts are shown to be unreliable and result in higher losses from warnings.This work was supported by the Natural Environment Research Council (Consortium on Risk in the Environment: Diagnostics, Integration, Benchmarking, Learning and Elicitation (CREDIBLE); grant no. NE/J017043/1)

Efficient developmental mis-targeting by the sporamin NTPP vacuolar signal to plastids in young leaves of sugarcane and Arabidopsis

Plant vacuoles are multi-functional, developmentally varied and can occupy up to 90% of plant cells. The N-terminal propeptide (NTPP) of sweet potato sporamin and the C-terminal propeptide (CTPP) of tobacco chitinase have been developed as models to target some heterologous proteins to vacuoles but so far tested on only a few plant species, vacuole types and payload proteins. Most studies have focused on lytic and protein-storage vacuoles, which may differ substantially from the sugar-storage vacuoles in crops like sugarcane. Our results extend the evidence that NTPP of sporamin can direct heterologous proteins to vacuoles in diverse plant species and indicate that sugarcane sucrose-storage vacuoles (like the lytic vacuoles in other plant species) are hostile to heterologous proteins. A low level of cytosolic NTPP-GFP (green fluorescent protein) was detectable in most cell types in sugarcane and Arabidopsis, but only Arabidopsis mature leaf mesophyll cells accumulated NTPP-GFP to detectable levels in vacuoles. Unexpectedly, efficient developmental mis-trafficking of NTPP-GFP to chloroplasts was found in young leaf mesophyll cells of both species. Vacuolar targeting by tobacco chitinase CTPP was inefficient in sugarcane, leaving substantial cytoplasmic activity of rat lysosomal beta-glucuronidase (GUS) [ER (endoplasmic reticulum)-RGUS-CTPP]. Sporamin NTPP is a promising targeting signal for studies of vacuolar function and for metabolic engineering. Such applications must take account of the efficient developmental mis-targeting by the signal and the instability of most introduced proteins, even in storage vacuoles