Niche Modeling

Niche Modeling : Predictions from Statistical Distributions

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Using theory, applications, and examples of inferences, Niche Modeling: Predictions from Statistical Distributions demonstrates how to conduct and evaluate niche modeling projects in any area of application. It features a series of theoretical and practical exercises for developing and evaluating niche models using the R statistics language. The author discusses applications of predictive modeling methods with reference to valid inferences from assumptions. He elucidates varied and simplified examples with rigor and completeness. Topics include geographic information systems, multivariate modeling, artificial intelligence methods, data handling, and information infrastructure. Above all, successful niche modeling requires a deep understanding of the process of creating and using probability. Off-the-shelf statistical packages are tailored exactly to applications but can hide problematic complexities. Recipe book implementations fail to educate users in the details, assumptions, and pitfalls of analysis, but may be able to adapt to the specific needs of each study. Examining the sources of errors such as autocorrelation, bias, long term persistence, nonlinearity, circularity, and fraud, this seminal reference provides an understanding of the limitations and potential pitfalls of prediction, emphasizing the importance of avoiding more

Product details

  • Hardback | 224 pages
  • 157.5 x 236.2 x 17.8mm | 430.92g
  • Taylor & Francis Inc
  • Chapman & Hall/CRC
  • Boca Raton, FL, United States
  • English
  • 77 black & white illustrations, 18 black & white tables
  • 1584884940
  • 9781584884941

Review quote

... this book provides a comprehensive introduction to ecological niche modeling development and evaluation. The intended audience of this book is ecologists and students who have some familiarity in niche modeling and would like to have a better understanding of computation, as well as the limitations of and potential pitfalls in niche model prediction. -Yingwei Peng, Technometrics, August 2010show more

Table of contents

Preface FUNCTIONS Elements Operations Functions Ecological Models Summary DATA Creating Entering Data Queries Joins Loading and Saving a Database Summary SPATIAL Data types Operations Summary TOPOLOGY Formalism Topology Hutchinsonian Niche Environmental Envelope Probability Distribution Machine Learning Methods Data Mining Post-Hutchinsonian Niche Summary ENVIRONMENTAL DATA COLLECTIONS Datasets Archives Summary EXAMPLES Model Skill Calculating Accuracy Predicting House Prices Brown Tree Snake Invasion of Zebra Mussel Observations BIAS Range Shift Range-Shift Model Forms of Bias Quantifying Bias Summary AUTOCORRELATION Types Characteristics Example: Testing Statistical Skill Within Range Generalization to 2D Summary NON-LINEARITY Growth Niches Summary LONG TERM PERSISTENCE Detecting LTP Implications of LTP Discussion CIRCULARITY Climate Prediction Lessons for Niche Modeling FRAUD Methods Summary Referencesshow more

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