Ecological Forecasting

An authoritative and accessible introduction to the concepts and tools needed to make ecology a more predictive science Ecologists are being asked to respond to unprecedented environmental challenges. How can they provide the best available scientific information about what will happen in the future? Ecological Forecasting is the first book to bring together the concepts and tools needed to make ecology a more predictive science. Ecological Forecasting presents a new way of doing ecology. A closer connection between data and models can help us to project our current understanding of ecological processes into new places and times. This accessible and comprehensive book covers a wealth of topics, including Bayesian calibration and the complexities of real-world data; uncertainty quantification, partitioning, propagation, and analysis; feedbacks from models to measurements; state-space models and data fusion; iterative forecasting and the forecast cycle; and decision support. Features case studies that highlight the advances and opportunities in forecasting across a range of ecological subdisciplines, such as epidemiology, fisheries, endangered species, biodiversity, and the carbon cycle Presents a probabilistic approach to prediction and iteratively updating forecasts based on new data Describes statistical and informatics tools for bringing models and data together, with emphasis on: Quantifying and partitioning uncertainties Dealing with the complexities of real-world data Feedbacks to identifying data needs, improving models, and decision support Numerous hands-on activities in R available online

An authoritative and accessible introduction to the concepts and tools needed to make ecology a more predictive science Ecologists are being asked to respond to unprecedented environmental challenges. How can they provide the best available scientific information about what will happen in the future? Ecological Forecasting is the first book to bring together the concepts and tools needed to make ecology a more predictive science. Ecological Forecasting presents a new way of doing ecology. A closer connection between data and models can help us to project our current understanding of ecological processes into new places and times. This accessible and comprehensive book covers a wealth of topics, including Bayesian calibration and the complexities of real-world data; uncertainty quantification, partitioning, propagation, and analysis; feedbacks from models to measurements; state-space models and data fusion; iterative forecasting and the forecast cycle; and decision support. Features case studies that highlight the advances and opportunities in forecasting across a range of ecological subdisciplines, such as epidemiology, fisheries, endangered species, biodiversity, and the carbon cycle Presents a probabilistic approach to prediction and iteratively updating forecasts based on new data Describes statistical and informatics tools for bringing models and data together, with emphasis on: Quantifying and partitioning uncertainties Dealing with the complexities of real-world data Feedbacks to identifying data needs, improving models, and decision support Numerous hands-on activities in R available online

Ecosystem Management and Sustainability analyzes myriad human-initiated processes and tools developed to foster sustainable natural resource use, preservation, and restoration. It also examines how humans interact with plant, marine, and animal life in both natural and human-altered environments. Experts explain the complex ecosystem relationships that result from invasive species, roads, fencing, and even our homes by addressing topics such as fire and groundwater management, disturbance, and ecosystem resilience. Because most people in the 21st century live in urban environments, the volume pays special attention to the ecology of cities, with detailed coverage on topics ranging from urban agriculture to landscape architecture. The volume focuses on how ecosystems across the world can be restored, maintained, and used productively and sustainably.

Modelling is an important tool for understanding the complexity of forest ecosystems and the variety of interactions of ecosystem components, processes and values. This book describes the hybrid approach to modelling forest ecosystems and their possible response to natural and management-induced disturbance. The book describes the FORECAST family of ecosystem management models at three different spatial scales (tree, stand and landscape), and compares them with alternative models at these three spatial scales. The book will help forest managers to understand what to expect from ecosystem-based forest models; serve as a tool for use in teaching about sustainability, scenario analysis and value trade-offs in natural resources management; and assist policy makers, managers and researches working in assessment of sustainable forest management and ecosystem management. Several real-life examples of using the FORECAST family of models in forest management and other applications are presented from countries including Canada, China, Spain and the USA, to illustrate the concepts described in the text. The book also demonstrates how these models can be extended for scenario and value trade-off analysis through visualization and educational or management games.

Tremendous advances in oceanographic observing and modeling systems over the last decade have led to unprecedented developments in the nature of information available to marine science. While improvements in observational technologies and networks have garnered much attention, remarkable developments in forecasting the ocean have received much less focus. Exploiting this new predictive skill to improve scientific understanding, generate advice and aid in the management of marine resources, is emerging as one of the new challenges of marine science. Translating predictions of the physical environment into biological outcomes, however, is not straightforward. Fisheries scientists, for example, have been trying to understand the links between physics and biology, and generate predictions of variables such as recruitment, for close to a century, with limited success. Nevertheless, spatial distributions and the timing of key events, which have received less focus, are often tightly linked to the physical environment and may have management-relevant applications. The first-such forecasts based on this skill are now starting to emerge. This Frontiers in Marine Science Research Topic provides a snapshot of the state-of-the-art in Marine Ecological Prediction. It covers the opportunities for developing such forecasts, technical approaches that could be employed, and examples where the technology is already being applied. This body of work therefore marks an important milestone on the route to developing this new and exciting field of marine science.