Chapter 1 expands on the Introduction’s brief exploration of Norbert Wiener’s theories alongside modernist literary aesthetics to argue that Ezra Pound’s Cantos and radio broadcasts employ the logic of cybernetic feedback as a pedagogical model for teaching twentieth-century readers how to negotiate large quantities of data, find meaningful patterns within messages from the past, and adapt their conduct to best achieve their goals. Elucidating arguments that Pound makes in his radio broadcasts and poetry (particularly the Chinese History Cantos) and comparing them to Wiener’s mid-century theories of cybernetic feedback, Love challenges the critical tendency to compare Pound’s work to unidirectional radio transmission. Instead, the chapter’s analyses illustrate that Pound champions the principle of circulation and positions his readers as cybernetic machines, inviting them to learn from the feedback loops that circulate throughout history, culture, and language.

This chapter examines the contribution that domestic courts may have in the development of rules or guidelines for the interpretation of customary international law (CIL). Through an examination of national cases where courts interpret both domestic and international custom, the chapter traces methodologies of interpretation and motivations behind them. The chapter then asks two questions: how can we learn from domestic interpretive practices? and why should we learn from them? In answer to the first question, the chapter argues that domestic courts can contribute to the development of rules for CIL interpretation beyond the role assigned to them in the framework of sources, and also in informal ways. In answer to the second question, the chapter argues that looking to domestic interpretive approaches for custom may help us fill the ‘gap’ currently existing on this issue in international law, that domestic courts offer a wealth of cases from which we can draw, and that by learning from domestic interpretive practices international law can provide domestic judges with various familiar tools for their further engagement with CIL in the future.

This chapter describes methods used for dissemination of the plan, including information exchange systems used for situational awareness, a common operating picture, and use of information technology.

In this chapter two examples are presented that demonstrate the added value of integrated ecological-economic modelling. Both examples consider market-based conservation instruments, the first analysing the impact of the agglomeration bonus on the coexistence of two competing species, and the second analysing the dynamics and cost-effectiveness of output-based payments that reward the presence of a species on the land. The second example involves a feedback loop between ecological and economic system components that is analysed in detail. It is shown that the feedback loop increases the uncertainty in the system, which implies that the performance of the payment scheme is uncertain. This uncertainty is then addressed by a co-viability analysis to derive trade-off curves between the certainty of achieving a desired ecological outcome (keeping the population size above a specified target) and the certainty of achieving a desired economic outcome (keeping scheme costs below a specified limit).

This chapter opens Part IV on ecological-economic modelling. It starts with a brief synopsis of the history of economic thought that leads on to an outline of the subdisciplines of environmental economics and ecological economics. Major achievements highlighted include, among others, the development of market-based instruments to protect the environment, the consideration of the dynamic complexity of coupled ecological-economic systems, and the development of the concepts of resilience and sustainability. The chapter concludes with recommendations for ecological-economic modelling, which include the consideration of uncertainties, non-linearities, feed-back loops, evolution and adaptation and the use of adeqate models of human behaviour.

Next to its purpose, a model may be characterised by the features it possesses. The features of a model are determined by the features of the system modelled as well as the model purpose. Five features are highlighted in this chapter. The first is spatial structure, where three types are distinguished: spatially differentiated, spatially explicit, and spatially differentiated and explicit. The second is dynamics, which can be considered in different ways. The third model feature is stochasticity or randomness. The fourth is variability among individuals (plants or animals in the ecological models, and human agents in the economic models), and the last is feedback loops, such that model components affect each other in a mutual way. As in Chapter 2, various model studies from the literature are used, and the relevance of each of the five model features is demonstrated by way of example.

Ecological-economic modelling has advantages but also involves some challenges. Two advantages are presented: the incompatibility of disciplinary solutions which prevents the derivation of good integrated ecological-economic policies and strategies from purely disciplinary research results and feedback loops so that the ecological system component affects the economic one and vice versa. The relevance of these two issues is demonstrated in examples from the literature. A challenge to ecoological-economic modelling is that ecological and economic models often differ in their purposes and features, such as the consideration of uncertainty and spatial structure. The discussion is supported by a literature review on ecological, economic and ecological-economic models. Despite differences between the disciplines’ modelling approaches, ecology and economics share a number of concepts that facilitate integrated modelling, concepts which are outlined in the final section of the chapter.