Numerous hypotheses have been proposed to explain the dynamics in abundance of individual species, how species interact, how communities assemble, and how interactions between biotic and abiotic processes shape ecosystem stability. Many if not most of these hypotheses find some degree of support, but often only within relatively narrow spatial and temporal ranges. This is because conditions vary over time and from place to place, and so the strength and extent of processes that were the focus of a given a hypothesis become altered by other forces. Ecologists have confronted variability from two perspectives; conceptual and statistical. Conceptually, spatial and temporal variability are now recognized as being scale dependent and hierarchical. Statistically, there are many models that ecologists readily use that account for the hierarchical and scale-dependence of variability present in many datasets. But linking the two perspectives into a meaningful understanding of what variability means in real systems has been much less successful. For example, it is common to see studies where the fixed effects of a generalized linear mixed model are reported, but very often random effects are completely ignored or, at best, given scant attention. The likelihood of this being a significant problem increases greatly in what are rapidly becoming more common studies that utilize datasets spanning long temporal and/or large spatial scales, or when extreme and often unpredictable events (gray and black swans) occur.

Fluctuations in the environmental conditions impacting life are ubiquitous. This book brings together contributions to provide readers with a comprehensive look at the challenges for ecological systems and ecological research alike. It offers a comprehensive range of topics, from environmental variability itself to its ecosystem-level impact.

The International Society for Ecological Modelling (ISEM) sponsors conferences, workshops and training courses with the aim of advancing the development of ecological and environmental modelling. The 3rd International Conference on the state-of-the-art in ecological modelling was sponsored by the ISEM in cooperation with the National Park Service Water Resources Laboratory and hosted by the Natural Resource Ecology Laboratory at Colorado State University. Its theme was the application of ecological modelling to environmental management and this book contains the full texts of the three invited papers presented in the five general sessions, plus the final summaries and syntheses of the topics covered during those sessions.

Systems analysis in forestry has continued to advance in sophistication and diversity of application over the last few decades. The papers in this volume were presented at the eighth symposium in the foremost conference series worldwide in this subject area. Techniques presented include optimization and simulation modelling, decision support systems, alternative planning techniques, and spatial analysis. Over 30 papers and extended abstracts are grouped into the topical areas of (1) fire and fuels; (2) networks and transportation; (3) forest and landscape planning; (4) ecological modeling, biodiversity, and wildlife; and (5) forest resource applications. This collection will be of interest to forest planners and researchers who work in quantitative methods in forestry.

Choosing the optimal management option requires environmental risk managers and decision makers to evaluate diverse, and not always congruent, needs and interests of multiple stakeholders. Understanding the trade-offs of different options as well as their legal, economic, scientific, and technological implications is critical to performing accurate

Understanding the conditions under which variability in performance may arise, and the processes related to its emergence, gives us insight into the development of techniques for improving the quality of performance. Variability in Human Performance details the scientific and the practical implications of human performance variability by providing a broad perspective on how and why such variability occurs across a number of disciplinary domains. The text takes an approach that rests upon the idea of context, or design, specificity in performance, namely that variability in performance is closely referenced to design factors in the environment in which performance is occurring. An exploration of the link between variability and related processes, the book introduces a comprehensive framework for understanding human performance variability, presented in terms of how human control of behavior is closely tied to design factors in the performance environment. The authors introduce empirical evidence, as well as practical examples and application areas, in support of this framework. The book begins with coverage of neurobiological and biomechanical basis of movement variability, then examines rich and extensive empirical evidence available for context specificity in cognitive performance and learning, as a basis for cognitive performance variability. The book then reviews the evidence for context specificity in: Student learning Displaced feedback conditions Human error behavior Affective performance Social and team performance The authors also explore work performance as influenced by complex sociotechnical systems and as a basis for performance variability, applying control systems concepts to an interpretation of the nature and basis of performance variability in all of these domains. They conclude by taking an evolutionary perspective on the origins and behavioral significance of human performance variability. The book then provides strategies on how individuals, groups, and organizations can significantly reduce variability in human performance that often leads to systems failures.