Sampling Strategies for Natural Resources and the Environment

Sampling Strategies for Natural Resources and the Environment

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Features

  • Offers a thorough treatment of probability sampling strategies for both discrete populations and continuums of natural and environmental resources
  • Emphasizes designs that are applicable to the fields of ecology, forestry, natural resources, and environmental science
  • Includes graphical displays of data throughout the text
  • Provides a website that contains data for exercises

Summary

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.

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

Editorial Reviews

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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