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More About This Textbook
Overview
Written by renowned experts in the field, Sampling Strategies for Natural Resources and the Environment covers the sampling techniques used in ecology, forestry, environmental science, and natural resources. The book presents methods to estimate aggregate characteristics on a per unit area basis as well as on an elemental basis. In addition to common sampling designs such as simple random sampling and list sampling, the authors explore more specialized designs for sampling vegetation, including randomized branch sampling and 3P sampling.
One of the book's unique features is the emphasis on areal sampling designs, including plot/quadrat sampling, Bitterlich sampling, line intersect sampling, and several lesser known designs. The book also provides comprehensive solutions to the problem of edge effect. Another distinguishing aspect is the inclusion of sampling designs for continuums, focusing on the methods of Monte Carlo integration.
By presenting a conceptual understanding of each sampling design and estimation procedure as well as mathematical derivations and proofs in the chapter appendices, this text promotes a deep understanding of the underpinnings of sampling theory, estimation, and inference. Moreover, it will help you reliably sample natural populations and continuums.
What People Are Saying
From the Publisher
This book was written by renowned experts in the field, and thus it is no surprise that they did an excellent job … The bibliography is very comprehensive, and the subject and author indexes are well designed. Numerous examples and exercises illustrate the theoretical developments … I am convinced that this book is absolutely worth having.—Daniel Mandallaz, JASA, 2008
I expect to use Sampling Strategies for Natural Resources and the Environment for some of my environmental science and statistics classes and as a reliable professional reference for many years.
—Anthony J. Sadar, Pollution Equipment News, 2007
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Table of Contents
PREFACE
INTRODUCTION The need for sampling strategies A medley of sampling scenarios Probability sample Inference Population descriptive parameters Historical note Terms to remember Appendix
SAMPLING DISTRIBUTION OF AN ESTIMATOR Distribution of values Estimation Interval estimation The role of simulated sampling Other considerations Terms to remember Exercises Appendix
SAMPLING DESIGNS FOR DISCRETE POPULATIONS Introduction Equal probability designs Unequal probability designs Terms to remember Exercises Appendix
SAMPLING DESIGNS FOR CONTINUOUS POPULATIONS Introduction Crude Monte Carlo Importance sampling Control variate estimation Sampling in two or three dimensions General notation Terms to remember Exercises and projects Appendix
STRATIFIED SAMPLING DESIGNS Introduction Rationale for stratified sampling Estimation with stratified sampling Sample allocation among strata Incorrect assignment of population elements into strata Double sampling for stratification Poststratification Stratified sampling of a continuous population Terms to Remember Exercises Appendix
USING AUXILIARY INFORMATION TO IMPROVE ESTIMATION Generalized ratio estimator Bias of the generalized ratio estimator Variance of the generalized ratio estimator Estimated variance of the generalized ratio estimator Confidence interval estimation Ratio estimation with systematic sampling design Generalized ratio estimation with stratified sampling Generalized regression estimator Double sampling with ratio and regression estimation Terms to Remember Exercises Appendix
SAMPLING WITH FIXED AREA PLOTS Introduction Notation Sampling protocol Estimation Edge effect Plot size and shape Estimating change Terms to remember Exercises Appendix
BITTERLICH SAMPLING Introduction Fundamental concepts Estimation following Bitterlich sampling Edge effect Double sampling Sampling to estimate change in stock Terms to remember Exercises
LINE INTERSECT SAMPLING Introduction LIS with straight-line transects Unit area estimators Estimation with an auxiliary variate Estimating the mean attribute Nesting transects of different lengths Dealing with edge effect in LIS Transects with multiple segments Parallel transects of uneven length Terms to remember Exercises Appendix
A MONTE CARLO INTEGRATION APPROACH TO AREAL SAMPLING Areal sampling Plot sampling Bitterlich sampling Point relascope sampling Line intersect sampling Perpendicular distance sampling Edge correction Redux: Continuous versus discrete Terms to Remember Exercises Appendix
MISCELLANEOUS METHODS Introduction Point relascope sampling Horizontal line sampling Transect relascope sampling Ranked set sampling Adaptive cluster sampling
3P sampling Terms to Remember Exercises Appendix
TWO-STAGE SAMPLING Customary two-stage sampling General two-stage sampling Three-stage sampling Terms to Remember
RANDOMIZED BRANCH SAMPLING Terminology Path selection Estimation Selection probabilities Tools and tricks of the trade Subsampling a path Terms to remember Exercises and projects Appendix
SAMPLING WITH PARTIAL REPLACEMENT Introduction Estimation with partially replaced sampling units Estimation of change SPR with stratification SPR for three occasions Concluding remarks Terms to remember Appendix
BIBLIOGRAPHY
INDEX