Wildfire Risk as a Socioecological Pathology

Wildfire risk in temperate forests has become a nearly intractable problem that can be characterized as a socioecological “pathology”: that is, a set of complex and problematic interactions among social and ecological systems across multiple spatial and temporal scales. Assessments of wildfire risk could benefit from recognizing and accounting for these interactions in terms of socioecological systems, also known as coupled natural and human systems (CNHS). We characterize the primary social and ecological dimensions of the wildfire risk pathology, paying particular attention to the governance system around wildfire risk, and suggest strategies to mitigate the pathology through innovative planning approaches, analytical tools, and policies. We caution that even with a clear understanding of the problem and possible solutions, the system by which human actors govern fire-prone forests may evolve incrementally in imperfect ways and can be expected to resist change even as we learn better ways to manage CNHS

Wildfire risk as a socioecological pathology

Wildfire risk in temperate forests has become a nearly intractable problem that can be characterized as a socioecological “pathology”: that is, a set of complex and problematic interactions among social and ecological systems across multiple spatial and temporal scales. Assessments of wildfire risk could benefit from recognizing and accounting for these interactions in terms of socioecological systems, also known as coupled natural and human systems (CNHS). We characterize the primary social and ecological dimensions of the wildfire risk pathology, paying particular attention to the governance system around wildfire risk, and suggest strategies to mitigate the pathology through innovative planning approaches, analytical tools, and policies. We caution that even with a clear understanding of the problem and possible solutions, the system by which human actors govern fire-prone forests may evolve incrementally in imperfect ways and can be expected to resist change even as we learn better ways to manage CNHS

Formal and computational modeling of anticipation mechanisms of resilience in the complex sociotechnical air transport system

With ever-growing numbers of passengers and complexity of the air transport system, it becomes more and more of a challenge to manage the system in an effective, safe, and resilient manner. This is especially evident when disruptions occur. Understanding and improving resilience of the air transport system and its adaptive capacity to disruptions is essential for the system’s uninterrupted successful performance. Using theoretical findings from behavioral sciences, this paper makes the first steps towards formalization of the adaptive capacity of resilience of the air transport system with a particular focus on its ability to anticipate. To this end, an expressive logic-based language called Temporal Trace Language is used. The proposed approach is illustrated by a case study, in which anticipatory mechanisms are implemented in an agent-based airport terminal operations model, to deal with a disruptive scenario of unplanned and challenging passenger demand at the security checkpoint. Results showed that the timing of an adaptive action could have a significant influence on reducing the risk of saturation of the system, where saturation implies performance loss. Additionally, trade-off relations were obtained between cost, corresponding to the extra resources mobilized, and the benefits, such as a decrease in risk of saturation of the passenger queue. Document type: Articl

A Framework for Preventive State Anticipation

A special kind of anticipation is when an anticipated undesired situation makes an agent adapt its behavior in order to prevent that this situation will occur. In this chapter an approach is presented that combines low level reactive and high level deliberative reasoning in order to achieve this type of anticipatory behavior. A description of a general framework for preventive state anticipation is followed by a discussion of different possible instantiations. We focus on one such instantiation, linear anticipation, which is evaluated in a number of empirical experiments in both single- and multi-agent contexts