The high-level language of R is recognized as one of the mostpowerful and flexible statistical software environments, and israpidly becoming the standard setting for quantitative analysis,statistics and graphics. R provides free access to unrivalledcoverage and cutting-edge applications, enabling the user to applynumerous statistical methods ranging from simple regression to timeseries or multivariate analysis. Building on the success of the author’s bestsellingStatistics: An Introduction using R, The R Book ispacked with worked examples, providing an all inclusive guide to R,ideal for novice and more accomplished users alike. The bookassumes no background in statistics or computing and introduces theadvantages of the R environment, detailing its applications in awide range of disciplines. Provides the first comprehensive reference manual for the Rlanguage, including practical guidance and full coverage of thegraphics facilities. Introduces all the statistical models covered by R, beginningwith simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression andanalysis of variance, through to generalized linear models,generalized mixed models, time series, spatial statistics,multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.

The last 30 years has seen the development of increasingly sophisticated models that quantify canopy carbon exchange. These models are now essential parts of larger models for prediction and simulation of crop production, climate change, and regional and global carbon dynamics. There is thus an urgent need for increasing expertise in developing, use and understanding of these models. This in turn calls for an advanced, yet easily accessible textbook that summarizes the “canopy science” and introduces the present and the future scientists to the theoretical background of the current canopy models. This book presents current knowledge of functioning of plant canopies, models and strategies employed to simulate canopy function, and the significance of canopy architecture, physiology and dynamics in ecosystems, landscape and biosphere.

Increasingly used to represent climatic, biogeochemical, and ecological systems, computer modeling has become an important tool that should be in every environmental professional’s toolbox. Environmental Modeling: A Practical Introduction is just what it purports to be, a practical introduction to the various methods, techniques, and skills required for computerized environmental modeling. Exploring the broad arena of environmental modeling, the book demonstrates how to represent an environmental problem in conceptual terms, formalize the conceptual model using mathematical expressions, convert the mathematical model into a program that can be run on a desktop or laptop computer, and examine the results produced by the computational model. Equally important, the book imparts skills that allow you to develop, implement, and experiment with a range of computerized environmental models. The emphasis is on active engagement in the modeling process rather than on passive learning about a suite of well-established models. The author takes a practical approach throughout, one that does not get bogged down in the details of the underlying mathematics and that encourages learning through “hands on” experimentation. He provides a set of software tools and data sets that you can use to work through the various examples and exercises presented in each chapter, as well as presentational material and handouts for course tutors. Comprehensive and up-to-date, the book discusses how computational models can be used to represent environmental systems and illustrates how such models improve understanding of the ways in which environmental systems function.