Using a master sample to integrate stream monitoring programs

The need for aquatic resource condition surveys at scales that are too extensive to census has increased in recent years. Statistically designed sample surveys are intended to meet this need. Simple or stratified random sampling or systematic survey designs are often used to obtain a representative...

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Veröffentlicht in:Journal of agricultural, biological, and environmental statistics biological, and environmental statistics, 2008-09, Vol.13 (3), p.243-254
Hauptverfasser: Larsen, David P, Olsen, Anthony R, Stevens, Donald L. Jr
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container_title Journal of agricultural, biological, and environmental statistics
container_volume 13
creator Larsen, David P
Olsen, Anthony R
Stevens, Donald L. Jr
description The need for aquatic resource condition surveys at scales that are too extensive to census has increased in recent years. Statistically designed sample surveys are intended to meet this need. Simple or stratified random sampling or systematic survey designs are often used to obtain a representative set of sites for data collection. However, such designs have limitations when applied to spatially distributed natural resources, like stream networks. Stevens and Olsen proposed a design that overcomes the key limitations of simple, stratified random or systematic designs by selecting a spatially balanced sample. The outcome of a spatially balanced sample is an ordered list of sampling locations with spatial distribution that balances the advantages of simple or stratified random samples or systematic samples. This approach can be used to select a sample of sites for particular studies to meet specific objectives. This approach can also be used to select a "master sample" from which subsamples can be drawn for particular needs. At the same time, these individual samples can be incorporated into a broader design that facilitates integrated monitoring and data sharing.
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subjects Agriculture
Agronomy. Soil science and plant productions
Animal and plant ecology
Animal, plant and microbial ecology
Biological and medical sciences
Biometrics, statistics, experimental designs, modeling, agricultural computer applications
Biostatistics
case studies
Design
Ecoregions
environmental monitoring
Forest service
Fresh water ecosystems
Fundamental and applied biological sciences. Psychology
Generalities. Biometrics, experimentation. Remote sensing
Health Sciences
Mathematics and Statistics
Medicine
Monitoring/Environmental Analysis
Natural resources
Sample size
sampling
spatial distribution
Statistics
Statistics for Life Sciences
Streams
Survey design
Survey sampling
Synecology
water management
Water resources
Watersheds
title Using a master sample to integrate stream monitoring programs
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