Framework for risk assessment for maritime transportation systems

Maritime accidents involving ships carrying passengers may pose a high risk with respect to human casualties. For effective risk mitigation, an insight into the process of risk escalation is needed. This requires a proactive approach when it comes to risk modelling for maritime transportation systems. Most of the existing models are based on historical data on maritime accidents, and thus they can be considered reactive instead of proactive. This paper introduces a systematic, transferable and proactive framework estimating the risk for maritime transportation systems, meeting the requirements stemming from the adopted formal definition of risk. The framework focuses on ship-ship collisions in the open sea, with a RoRo/Passenger ship (RoPax) being considered as the struck ship. First, it covers an identification of the events that follow a collision between two ships in the open sea, and, second, it evaluates the probabilities of these events, concluding by determining the severity of a collision. The risk framework is developed with the use of Bayesian Belief Networks and utilizes a set of analytical methods for the estimation of the risk model parameters. The model can be run with the use of GeNIe software package. Finally, a case study is presented, in which the risk framework developed here is applied to a maritime transportation system operating in the Gulf of Finland (GoF). The results obtained are compared to the historical data and available models, in which a RoPax was involved in a collision, and good agreement with the available records is found.

A return-on-investment framework to identify conservation priorities in Africa

Environmental conservation activities must continue to become more efficient and effective, especially in Africa where development and population growth pressures continue to escalate. Recently, prioritization of conservation resources has focused on explicitly incorporating the economic costs of conservation along with better defining the outcomes of these expenditures. We demonstrate how new global and continental data that spans social, economic, and ecological sectors creates an opportunity to incorporate return-on-investment (ROI) principles into conservation priority setting for Africa. We suggest that combining conservation priorities that factor in biodiversity value, habitat quality, and conservation management investments across terrestrial, freshwater, and coastal marine environments provides a new lens for setting global conservation priorities. Using this approach we identified seven regions capturing interior and coastal resources that also have high ROI values that support further investment. We illustrate how spatially explicit, yet flexible ROI analysis can help to better address uncertainty, risk, and opportunities for conservation, while making values that guide prioritization more transparent. In one case the results of this prioritization process were used to support new conservation investments. Acknowledging a clear research need to improve cost information, we propose that adopting a flexible ROI framework to set conservation priorities in Africa has multiple potential benefits.