Books in the Chapman & Hall/CRC Applied Environmental Statistics series

Suitable for graduate courses and a reference for appropriate statistical approaches to specific environmental problems, this title begins by describing the important role statistics play in environmental science. It then focuses on how to collect data, highlighting the importance of sampling and experimental design in conducting rigorous science.

Environmental and Ecological Statistics with R, Second Edition focuses on statistical modeling and data analysis for environmental and ecological problems. By guiding readers through the process of scientific problem solving and statistical model development, it eases the transition from scientific hypothesis to statistical model.

Biometry for Forestry and Environmental Data with Examples in R focuses on statistical methods that are widely applicable in forestry and environmental sciences, but it also includes material that is of wider interest.

Presents the concepts and tools required in finite populations, and develops the Monte Carlo approach in infinite populations to analyze or design complex forest inventories. This book discusses design-based, model-assisted, and model-dependent inference as well as the design of optimal sampling schemes based on the anticipated variance.

Future Sustainable Ecosystems: Complexity, Risk, Uncertainty provides an interdisciplinary, integrative overview of environmental problem-solving using statistics. It shows how statistics can be used to solve diverse environmental and socio-economic problems involving food, water, energy scarcity, and climate change risks.

Containing many recent developments available for the first time in book form, this concise and up-to-date work presents the statistical concepts and tools needed to conduct a modern forest inventory. It develops the Monte Carlo approach for both simple and complex sampling schemes and explores design-based, model-assisted, and model-dependent inference, including geostatistics and Kriging procedures. The book also explains the design of optimal sampling schemes based on anticipated variance, introduces the g-weight technique for variance estimation, and presentsthe stereological approach to transect sampling. In addition, it includes numerous case studies, simulations, and instructive problems with solutions.

Environmental and Ecological Statistics with R, Second Edition focuses on statistical modeling and data analysis for environmental and ecological problems. By guiding readers through the process of scientific problem solving and statistical model development, it eases the transition from scientific hypothesis to statistical mode