Advances in soil ecosystem services: concepts, models, and applications for earth system life support

The ecosystem services approach is gaining wide acceptance at the policy-making level as a framework for integrating science and policy regarding the natural environment. It is important that soil science clearly articulates how knowledge and understanding of the vadose zone soils can be transmitted through this framework into the decision-making process. Competition between food production, living space, and maintaining habitat for all of earth’s life-forms has never been so intense, so the need for soil security and vadose zone protection is paramount. Soil management can no longer be thought of in terms of single function management but instead needs to be considered and managed in the context of the multiple functions it offers. In this 10th anniversary issue of the journal, we assess progress in the development of a coherent soil ecosystem services framework using the natural resource management stock-flow and fund-service resource approach. We go on to examine some of the areas where the application of an ecosystems approach is gaining traction, which include national and local decision making as well as support for legal arguments in court

Learning Linearly Separable Languages

Abstract. This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane in that space. It initiates the study of the linear separability of automata and languages by examining the rich class of piecewise-testable languages. It introduces a high-dimensional feature map and proves piecewise-testable languages to be linearly separable in that space. The proof makes use of word combinatorial results relating to subsequences. It also shows that the positive definite kernel associated to this embedding can be computed in quadratic time. It examines the use of support vector machines in combination with this kernel to determine a separating hyperplane and the corresponding learning guarantees. It also proves that all languages linearly separable under a regular finite cover embedding, a generalization of the embedding we used, are regular.