Environment and Development Economics (EDE) was established 15 years ago to provide a publication outlet for theoretical and applied scientific papers dealing with issues at the intersection of environmental, resource and development economics, as well as to actively support capacity building in the developing world. In the years since its inception, EDE has published a large number of articles on topics ranging from sustainable development, the environmental Kuznets curve, and green accounting, to trade and environment, poverty and natural resource use, and the economics of ecosystems.

This paper examines the complex relationship that exists between poverty and natural resource degradation in developing countries. The rural poor are often concentrated in fragile, or less favorable, environmental areas. Consequently, their livelihoods can be intimately dependent on natural resource use and ecosystem services. The relationship between poverty and natural resource degradation may depend on a complex range of choices and tradeoffs available to the poor, which in the absence of capital, labor, and land markets, is affected by their access to outside employment and any natural resource endowments. The paper develops a poverty–environment model to characterize some of these linkages, and concludes by discussing policy implications and avenues for further research.

Accelerating economic growth and social development is necessary to reduce the vulnerability and enhance the adaptive capacity of sub-Saharan Africa to cope with the consequences of predicted unfavorable future climate. This requires major investments and policy reforms to induce a needed radical transformation of the way development is currently pursued to a more climate-sensitive path of low carbon growth. Key gaps in the current knowledge base that call for major investments and urgent attention include the ability to forecast more robust local future climate and to account for the uncertainties associated with climate risks for ecosystems' functions and probable nonconvexities in future impacts to project more plausible scenarios for future development in sub-Saharan Africa and provide better information on the costs and benefits of potential actions to avert the negative consequences of climate change.

This paper studies the interactions between harvesters, whose income depends on a renewable natural resource as a key factor of production (e.g., fisheries) and industries that can have important impacts on the renewable resource, but whose production does not depend on it (e.g., off-shore oil extraction) in the context of a growing economy. We examine these issues for a closed economy focusing on how the co-existence between these two sectors affects sustainable development and the well-being of the poor, i.e., the harvesters. We show that under certain conditions the existence and expansion of a resource-impacting industrial sector may be consistent with sustainable development. However, if these conditions are not met, growth of the resource-impacting sector leads to further resource depletion and may even threaten the feasibility of sustainable development.

This paper is concerned with the theory of resilience pricing and sustainability measurement in the presence of risk for regime shift in a dynamic economy–environment system. Following Holling (Annual Review of Ecology and Systematics, vol. 4, 1973, pp. 1–23), we consider resilience as the maximal perturbation that the system can absorb without flipping into a qualitatively different state. Using a multisector growth model under uncertainty, we derive the shadow price of resilience that affects the probabilities of the system to flip in the future. We also analyze the role of resilience on sustainability with both ex-ante and ex-post welfare measures.

This paper assesses how the economics of biodiversity, as a field, has evolved in response to developments in biodiversity science and policy over the life of the journal, Environment and Development Economics. Several main trends in the economics of biodiversity are identified. First, biodiversity change has come to be analyzed largely through its impact on ecosystem services (in the sense of the Millennium Ecosystem Assessment). Second, there has been a growing focus on factors that optimally lead to biodiversity decline, i.e., the benefits to be had from reducing the abundance of pests, predators, pathogens, and competitors. Third, increasing attention is being paid to two global drivers of biodiversity change, climate and global economic integration, and the effect they have on the distribution and abundance of both beneficial and harmful species. Fourth, there has been growing interest in the development of instruments to deal with the transboundary public good aspect of biodiversity, and in particular in the development of payments for ecosystem services. The paper identifies the influence of these trends on attempts to model the role of biodiversity in the production of goods and services.

Mechanisms generating patterns in spatial domains have been extensively studied in biology, but also in economics in the context of new economic geography. The Turing mechanism or Turing diffusion-induced instability has been central to the understanding of forces which endogenously generate spatial patterns, but in a context where agents do not explicitly optimize an objective. The present paper reviews tools to study, in the spirit of Turing's analysis, a mechanism generating optimal diffusion-induced instability where optimizing agents generate optimal agglomerations. By extending the maximum principle to the optimal control of partial differential equations, it is shown how under certain conditions it will be optimal to design controls so that the price-quantity system implied by the costate–state functions of the optimal control of distributed parameter systems induces optimal spatial patterns. These methods might be useful in studying pattern formation both in problems of resource management and of economic development.