Ecological Niches And Geographic Distributions Mpb 49

This book provides a first synthetic view of an emerging area of ecology and biogeography, linking individual- and population-level processes to geographic distributions and biodiversity patterns. Problems in evolutionary ecology, macroecology, and biogeography are illuminated by this integrative view. The book focuses on correlative approaches known as ecological niche modeling, species distribution modeling, or habitat suitability modeling, which use associations between known occurrences of species and environmental variables to identify environmental conditions under which populations can be maintained. The spatial distribution of environments suitable for the species can then be estimated: a potential distribution for the species. This approach has broad applicability to ecology, evolution, biogeography, and conservation biology, as well as to understanding the geographic potential of invasive species and infectious diseases, and the biological implications of climate change. The authors lay out conceptual foundations and general principles for understanding and interpreting species distributions with respect to geography and environment. Focus is on development of niche models. While serving as a guide for students and researchers, the book also provides a theoretical framework to support future progress in the field.

Terminology, conceptual overview, biogeography, modeling.

Terminology, conceptual overview, biogeography, modeling.

This book disseminates the latest results and envisages new challenges in the application of mathematics to various practical situations in biology, epidemiology, and ecology. It comprises a collection of the main results presented at the Ninth Edition of the International Workshop “Dynamical Systems Applied to Biology and Natural Sciences – DSABNS”, held from 7 to 9 February 2018 at the Department of Mathematics, University of Turin, Italy. While the principal focus is ecology and epidemiology, the coverage extends even to waste recycling and a genetic application. The topics covered in the 12 peer-reviewed contributions involve such diverse mathematical tools as ordinary and partial differential equations, delay equations, stochastic equations, control, and sensitivity analysis. The book is intended to help both in disseminating the latest results and in envisaging new challenges in the application of mathematics to various practical situations in biology, epidemiology, and ecology.

Representing the definitive reference work for this broad and dynamic field, The International Encyclopedia of Geography arises from an unprecedented collaboration between Wiley and the American Association of Geographers (AAG) to review and define the concepts, research, and techniques in geography and interrelated fields. Available as a robust online resource and as a 15-volume full-color print set, the Encyclopedia assembles a truly global group of scholars for a comprehensive, authoritative overview of geography around the world. Contains more than 1,000 entries ranging from 1,000 to 10,000 words offering accessible introductions to basic concepts, sophisticated explanations of complex topics, and information on geographical societies around the world Assembles a truly global group of more than 900 scholars hailing from over 40 countries, for a comprehensive, authoritative overview of geography around the world Provides definitive coverage of the field, encompassing human geography, physical geography, geographic information science and systems, earth studies, and environmental science Brings together interdisciplinary perspectives on geographical topics and techniques of interest across the social sciences, humanities, science, and medicine Features full color throughout the print version and more than 1,000 illustrations and photographs Annual updates to online edition

This comprehensive volume discusses the patterns and processes analyzed in macroecology with a distinct look at the theoretical and methodological issues underlying the discipline as well as deeper epistemological matters. The book serves as a synthesis of macroecological literature that has been published since Brown and Maurer proposed and defined the term “macroecology” in 1989. Author José Alexandre Felizola Diniz-Filho draws from the different disciplines and branches (ecology, evolutionary biology, physiology, behavioral sciences, climatology, and paleontology) that make up macroecology to present a full, holistic picture of where the discipline stands. Through ten chapters, Diniz-Filho moves from a discussion of what macroecology actually is to macroecological modeling to the more applied side of the discipline, covering topics such as richness and diversity patterns and patterns in body size. The book concludes with a synthesis of how macroecological research is done in a theoretical and operational sense as well as unifying explanations for each of the macroecological patterns discussed, moving on to evaluate which theories and models are still useful and which ones can be abandoned. The book is intended for academics, young researchers and students interested in macroecology and conservation biogeography. In addition, because of the integrative nature of macroecology and the theoretical and methodological background in the book, it can be of interest to researchers working in related fields including but not limited to ecology and evolutionary biology.

From the Foreword: "While large-scale machine learning and data mining have greatly impacted a range of commercial applications, their use in the field of Earth sciences is still in the early stages. This book, edited by Ashok Srivastava, Ramakrishna Nemani, and Karsten Steinhaeuser, serves as an outstanding resource for anyone interested in the opportunities and challenges for the machine learning community in analyzing these data sets to answer questions of urgent societal interest...I hope that this book will inspire more computer scientists to focus on environmental applications, and Earth scientists to seek collaborations with researchers in machine learning and data mining to advance the frontiers in Earth sciences." --Vipin Kumar, University of Minnesota Large-Scale Machine Learning in the Earth Sciences provides researchers and practitioners with a broad overview of some of the key challenges in the intersection of Earth science, computer science, statistics, and related fields. It explores a wide range of topics and provides a compilation of recent research in the application of machine learning in the field of Earth Science. Making predictions based on observational data is a theme of the book, and the book includes chapters on the use of network science to understand and discover teleconnections in extreme climate and weather events, as well as using structured estimation in high dimensions. The use of ensemble machine learning models to combine predictions of global climate models using information from spatial and temporal patterns is also explored. The second part of the book features a discussion on statistical downscaling in climate with state-of-the-art scalable machine learning, as well as an overview of methods to understand and predict the proliferation of biological species due to changes in environmental conditions. The problem of using large-scale machine learning to study the formation of tornadoes is also explored in depth. The last part of the book covers the use of deep learning algorithms to classify images that have very high resolution, as well as the unmixing of spectral signals in remote sensing images of land cover. The authors also apply long-tail distributions to geoscience resources, in the final chapter of the book.