Agriculture, forestry and fi shery statistics provides a selection of recent, topical data. Information is presented for the European Union (EU) and its Member States, and is supplemented (when available) with data for the United Kingdom, EFTA members, candidate countries to the EU and potential candidates. This publication aims to cover some of the most popular data within the domain of agriculture, forestry and fi shery statistics as well as some of the wider food chain. It may be viewed as an introduction to European statistics in this area and provides a starting point for those who wish to explore the broad range of data that are freely available on Eurostat's website.

Recoge : The International Year of Forests 2011 - Forestry in the world: 1. Forests - 2. The economics of forestry and wood processing - 3. Wood and wood products - 4. Woods as a source of energy - Annexes.

Forest Biometrics presents the methods of mathematical statistics and biometrics that are significant to forestry. This book explores other fields related to forestry, which are explained with the help of a large number of practical examples. Organized into 25 chapters, this book starts with an overview of the variety of data that play a significant role in forest management, including the age of trees, the damage caused by storms, the fluctuation of timber prices, bark beetle infestation, and timber volume. This text then examines the factors that are responsible for a random distribution of the values in biological experimentation. Other chapters consider the important advantages of sample surveys compared to complete enumerations, include cheaper samples, wider applicability, quick results, and greater accuracy. The final chapter deals with the factors to be considered in determining the best time for harvesting of timber. This book is a valuable resource for students, research project leaders, and practical workers.

Forest Analytics with R combines practical, down-to-earth forestry data analysis and solutions to real forest management challenges with state-of-the-art statistical and data-handling functionality. The authors adopt a problem-driven approach, in which statistical and mathematical tools are introduced in the context of the forestry problem that they can help to resolve. All the tools are introduced in the context of real forestry datasets, which provide compelling examples of practical applications. The modeling challenges covered within the book include imputation and interpolation for spatial data, fitting probability density functions to tree measurement data using maximum likelihood, fitting allometric functions using both linear and non-linear least-squares regression, and fitting growth models using both linear and non-linear mixed-effects modeling. The coverage also includes deploying and using forest growth models written in compiled languages, analysis of natural resources and forestry inventory data, and forest estate planning and optimization using linear programming. The book would be ideal for a one-semester class in forest biometrics or applied statistics for natural resources management. The text assumes no programming background, some introductory statistics, and very basic applied mathematics.

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. Features: · Describes the theory and applications of selected statistical methods and illustrates their use and basic concepts through examples with forestry and environmental data in R. · Rigorous but easily accessible presentation of the linear, nonlinear, generalized linear and multivariate models, and their mixed-effects counterparts. Chapters on tree size, tree taper, measurement errors, and forest experiments are also included. · Necessary statistical theory about random variables, estimation and prediction is included. The wide applicability of the linear prediction theory is emphasized. · The hands-on examples with implementations using R make it easier for non-statisticians to understand the concepts and apply the methods with their own data. Lot of additional material is available at www.biombook.org. The book is aimed at students and researchers in forestry and environmental studies, but it will also be of interest to statisticians and researchers in other fields as well.

Recoge : 1. General description of forest sector - 2. Production and trade of wood and wood products.

This book presents recent developments in statistical methodologies with particular relevance to applications in forestry and environmental sciences. It discusses important methodologies like ranked set sampling, adaptive cluster sampling, small area estimation, calibration approach-based estimators, design of experiments, multivariate techniques, Internet of Things, and ridge regression methods. It also covers the history of the implementation of statistical techniques in Indian forestry and the National Forest Inventory of India. The book is a valuable resource for applied statisticians, students, researchers, and practitioners in the forestry and environment sector. It includes real-world examples and case studies to help readers apply the techniques discussed. It also motivates academicians and researchers to use new technologies in the areas of forestry and environmental sciences with the help of software like R, MATLAB, Statistica, and Mathematica.