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.

It also describes the effects of bulking on errors and the use of ancillary information and regression to improve estimates.

This Forest Service report presents the statistical theory of inventory & monitoring from a probabilistic point of view. It starts with the basics & shows the interrelationships between designs & estimators illustrating the methods with a small artificial population as well as with a mapped realistic population. For such applications, useful open source software is given in Appendix 4. Various sources of ancillary information are described & applications of the sampling strategies are discussed. Classical & bootstrap variance estimators are also discussed. Numerous problems with solutions are given, often based on the experiences of the authors. Key additional references are cited. Illustrated.

Originally published in 1994, the first edition of Field Sampling Methods for Remedial Investigations soon became a premier resource in the field. ThePrinceton Groundwater course designated it as one of the top books on the market that address strategies for groundwater well installation, well completion, and groundwater sampling. This long-awai

Sampling consists of selection, acquisition, and quantification of a part of the population. While selection and acquisition apply to physical sampling units of the population, quantification pertains only to the variable of interest, which is a particular characteristic of the sampling units. A sampling procedure is expected to provide a sample that is representative with respect to some specified criteria. Composite sampling, under idealized conditions, incurs no loss of information for estimating the population means. But an important limitation to the method has been the loss of information on individual sample values, such as, the extremely large value. In many of the situations where individual sample values are of interest or concern, composite sampling methods can be suitably modified to retrieve the information on individual sample values that may be lost due to compositing. This book presents statistical solutions to issues that arise in the context of applications of composite sampling.

Sampling theory considers how methods for selection of a subset of units from a finite population (a sample) affect the accuracy of estimates of descriptive population parameters (mean, total, proportion). Although a sound knowledge of sampling theory principles would seem essential for ecologists and natural resource scientists, the subject tends to be somewhat overlooked in contrast to other core statistical topics such as regression analysis, experimental design, and multivariate statistics. This introductory text aims to redress this imbalance by specifically targeting ecologists and resource scientists, and illustrating how sampling theory can be applied in a wide variety of resource contexts. The emphasis throughout is on design-based sampling from finite populations, but some attention is given to model-based prediction and sampling from infinite populations. Sampling Theory is an introductory textbook suitable for advanced undergraduates, graduate students, professional researchers, and practitioners in the fields of ecology, evolution, conservation biology, and natural resource sciences (including fisheries, wildlife, rangeland, ecology and forestry).

This book presents the state-of-the-art of forest resources assessments and monitoring. It provides links to practical applications of forest and natural resource assessment programs. It offers an overview of current forest inventory systems and discusses forest mensuration, sampling techniques, remote sensing applications, geographic and forest information systems, and multi-resource forest inventory. Attention is also given to the quantification of non-wood goods and services.