Multivariate Time Series Analysis in Climate and Environmental Research


Book Description

This book offers comprehensive information on the theory, models and algorithms involved in state-of-the-art multivariate time series analysis and highlights several of the latest research advances in climate and environmental science. The main topics addressed include Multivariate Time-Frequency Analysis, Artificial Neural Networks, Stochastic Modeling and Optimization, Spectral Analysis, Global Climate Change, Regional Climate Change, Ecosystem and Carbon Cycle, Paleoclimate, and Strategies for Climate Change Mitigation. The self-contained guide will be of great value to researchers and advanced students from a wide range of disciplines: those from Meteorology, Climatology, Oceanography, the Earth Sciences and Environmental Science will be introduced to various advanced tools for analyzing multivariate data, greatly facilitating their research, while those from Applied Mathematics, Statistics, Physics, and the Computer Sciences will learn how to use these multivariate time series analysis tools to approach climate and environmental topics.




Ecological Time Series


Book Description

This book results from a summer school held at Cornell University in 1992. The participants were graduate students and postdoctoral researchers selected from a broad range of interests and backgrounds in ecological studies. The summer school was the second in a continuing series whose underlying aim and the aim of this volume-is to bring together the different methods and concepts underpinning terrestrial, freshwater, and marine ecology. The first volume in the series focused on patch dynamics in these three ecologi cal sectors. Here we have endeavored to complement that volume by extending its comparative approach to the consideration of ecological time series. The types of data and the methods of collection are necessarily very different in these contrasting environments, yet the underlying concept and the technical problems of analysis have much in common. It proved to be of great interest and value to the summer school participants to see the differences and then work through to an appreciation ofthe generalizable concepts. We believe that such an approach must have value as well for a much larger audience, and we have structured this volume to provide a comparable reading experience.




Ecological Forecasting


Book Description

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




Handbook of Environmental and Ecological Statistics


Book Description

This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its scope of data collection including observational data, satellite-derived data, and computer model output. The resultant impact in this latter community has been substantial; no longer are simple regression and analysis of variance methods adequate. The contribution of this handbook is to assemble a state-of-the-art view of this interface. Features: An internationally regarded editorial team. A distinguished collection of contributors. A thoroughly contemporary treatment of a substantial interdisciplinary interface. Written to engage both statisticians as well as quantitative environmental researchers. 34 chapters covering methodology, ecological processes, environmental exposure, and statistical methods in climate science.




Multivariate Analysis of Ecological Data


Book Description

La diversidad biológica es fruto de la interacción entre numerosas especies, ya sean marinas, vegetales o animales, a la par que de los muchos factores limitantes que caracterizan el medio que habitan. El análisis multivariante utiliza las relaciones entre diferentes variables para ordenar los objetos de estudio según sus propiedades colectivas y luego clasificarlos; es decir, agrupar especies o ecosistemas en distintas clases compuestas cada una por entidades con propiedades parecidas. El fin último es relacionar la variabilidad biológica observada con las correspondientes características medioambientales. Multivariate Analysis of Ecological Data explica de manera completa y estructurada cómo analizar e interpretar los datos ecológicos observados sobre múltiples variables, tanto biológicos como medioambientales. Tras una introducción general a los datos ecológicos multivariantes y la metodología estadística, se abordan en capítulos específicos, métodos como aglomeración (clustering), regresión, biplots, escalado multidimensional, análisis de correspondencias (simple y canónico) y análisis log-ratio, con atención también a sus problemas de modelado y aspectos inferenciales. El libro plantea una serie de aplicaciones a datos reales derivados de investigaciones ecológicas, además de dos casos detallados que llevan al lector a apreciar los retos de análisis, interpretación y comunicación inherentes a los estudios a gran escala y los diseños complejos.




Analyzing Ecological Data


Book Description

This book provides a practical introduction to analyzing ecological data using real data sets. The first part gives a largely non-mathematical introduction to data exploration, univariate methods (including GAM and mixed modeling techniques), multivariate analysis, time series analysis, and spatial statistics. The second part provides 17 case studies. The case studies include topics ranging from terrestrial ecology to marine biology and can be used as a template for a reader’s own data analysis. Data from all case studies are available from www.highstat.com. Guidance on software is provided in the book.




Ecological Models and Data in R


Book Description

Introduction and background; Exploratory data analysis and graphics; Deterministic functions for ecological modeling; Probability and stochastic distributions for ecological modeling; Stochatsic simulation and power analysis; Likelihood and all that; Optimization and all that; Likelihood examples; Standar statistics revisited; Modeling variance; Dynamic models.




Population Dynamics in Ecological Space and Time


Book Description

As profound threats to ecosystems increase worldwide, ecologists must move beyond studying single communities at a single point in time. All of the dynamic, interconnected spatial and temporal processes that determine the distribution and abundance of species must be understood in order to develop new conservation and management strategies. This volume is the first to integrate mathematical and biological approaches to these crucial topics. The editors include not only a wide variety of theoretical approaches, but also a broad range of experimental and field studies, with chapters written by renowned experts in community ecology, ecological modeling, population genetics, and conservation biology. In addition to providing new insights into well-known topics such as migration, the authors also introduce some less familiar subjects, including bacterial population genetics and ecotoxicology. For anyone interested in the study, management, and conservation of populations, this book will prove to be a valuable resource.




Ecological Inference


Book Description

Drawing upon the recent explosion of research in the field, a diverse group of scholars surveys the latest strategies for solving ecological inference problems, the process of trying to infer individual behavior from aggregate data. The uncertainties and information lost in aggregation make ecological inference one of the most difficult areas of statistical inference, but these inferences are required in many academic fields, as well as by legislatures and the Courts in redistricting, marketing research by business, and policy analysis by governments. This wide-ranging collection of essays offers many fresh and important contributions to the study of ecological inference.




Patch Dynamics


Book Description

From the preface by Joel E. Cohen: "A century from now humanity will live in a managed - or mismanaged - global garden. We are debating the need to preserve tropical forests. Farming of the sea is providing an increasing part of our fish supply. We are beginning to control atmospheric emissions. In 100 years, we shall use novel farming practices and genetic engineering of bacteria to manipulate the methane production of rice fields. The continental shelf will be providing food, energy, possibly even living space. To make such intensive management possible will require massive improvements in data collection and analysis, and especially in our concepts. A century hence we will live on a wired earth: the oceans and the crust of the earth will receive the same comprehensive monitoring now devoted to weather. As the peoples of currently developing countries increase their levels of wealth, the need for global management will become irresistible as impatience with the accidents of nature and intolerance of mismanagement of the environment - especially of living resources - grow. Our control of physical perturbations and chemical inputs to the environment will be judged by the consequences to living organisms and biological communities. How can we obtain the factual and theoretical foundation needed to move from our present, fragmented knowledge and limited abilities to a managed, global garden?" This problem was addressed in the lectures and workshops of a summer school on patch dynamics at Cornell University. The school emphasized the analysis and interpretation of spatial patterns in terrestrial and marine environments. This book contains the course material of this school, combining general reviews with specific applications.