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Strategic Environmental Assessment aims to incorporate environmental and sustainability considerations into strategic decision making processes, such as the formulation of policies, plans and programmes. In order to be effective, the assessment must take the real decision making process as the departure point. Existing SEA approaches are frequently tailored after an EIA model conceived from a rational perspective on decision making. However, there are good reasons to assume that most strategic decision making processes are characterised by a bounded rationality. Furthermore, the predictability of environmental consequences generally becomes weaker at strategic levels than at the project level and complexity increases in terms of the numbers of actors involved in the decision. This paper examines various theoretical perspectives to decision making and discusses the implications for decision support in general and SEA in particular. The authors argue that the design of the SEA must be more sensitive to the real characteristics of the decision making context.

All complex life on Earth is composed of ‘eukaryotic’ cells. Eukaryotes arose just once in 4 billion years, via an endosymbiosis — bacteria entered a simple host cell, evolving into mitochondria, the ‘powerhouses’ of complex cells. Mitochondria lost most of their genes, retaining only those needed for respiration, giving eukaryotes ‘multi-bacterial’ power without the costs of maintaining thousands of complete bacterial genomes. These energy savings supported a substantial expansion in nuclear genome size, and far more protein synthesis from each gene.

The efficiency of complex industrialized farming systems are compared to that of natural environmental systems while taking into account economic and environmental benefit as well as the needs of farmers and cattle.

Existing approaches to modeling natural systems are inadequate to exhibit all the properties of complex phenomena. Current models in the field of complex systems, such as cellular automata, are straightforward to understand and give interesting theoretical results, but they are not very pertinent for a real case study. We show that hierarchical multi-agent modeling provides an interesting alternative for modeling complex systems through two case examples: a virtual ecosystem for studying species dynamics and the simulation of gravitational structures in cosmology.

This paper defines a new approach for cosmological simulation based on complex systems theory: a hierarchical multi-agent system is used to study stellar dynamics. At each level of the model, global behavior emerges from agent interactions. The presented model uses physically-based laws and agent-interactions to present stellar structures has the result of self-organization. Nevertheless a strong bond with cosmology is kept by showing the capacity of the model to exhibit structures close to those of the observable universe.

This chapter provides guidance for solving practical, high-level management and policy challenges in sustainability and disaster resilience. These two fields must be considered together so that they do not work at cross-purposes. Sustainability is framed in a positive and useful way that transcends shallow and self-serving treatments that are all too common. Although sustainability is a multi-faceted problem, climate change is the focus because it is globally important and because it is particularly troublesome due to its global and long-term scale. The discussion on sustainability highlights the challenge of extreme uncertainty. Knowledge of system complexity is necessary for understanding and contending with extreme uncertainty. Thus, this chapter summarizes some fundamental knowledge and draws from it recommendations for decision-making. An example illustrates the suggested approach and provides additional insight. Complex systems are hard to understand and no course of action is guaranteed to be successful. However, without systems thinking, failure is almost assured. The recommendations in this chapter, although not infallible, will help find effective ways to intervene in societal systems to meet stated objectives while avoiding unintended consequences.

All complex life on Earth is composed of ‘eukaryotic’ cells. Eukaryotes arose just once in 4 billion years, via an endosymbiosis — bacteria entered a simple host cell, evolving into mitochondria, the ‘powerhouses’ of complex cells. Mitochondria lost most of their genes, retaining only those needed for respiration, giving eukaryotes ‘multi-bacterial’ power without the costs of maintaining thousands of complete bacterial genomes. These energy savings supported a substantial expansion in nuclear genome size, and far more protein synthesis from each gene.

Strategic Environmental Assessment aims to incorporate environmental and sustainability considerations into strategic decision making processes, such as the formulation of policies, plans and programmes. In order to be effective, the assessment must take the real decision making process as the departure point. Existing SEA approaches are frequently tailored after an EIA model conceived from a rational perspective on decision making. However, there are good reasons to assume that most strategic decision making processes are characterised by a bounded rationality. Furthermore, the predictability of environmental consequences generally becomes weaker at strategic levels than at the project level and complexity increases in terms of the numbers of actors involved in the decision. This paper examines various theoretical perspectives to decision making and discusses the implications for decision support in general and SEA in particular. The authors argue that the design of the SEA must be more sensitive to the real characteristics of the decision making context.