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 |
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container_title | Journal of agricultural, biological, and environmental statistics |
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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. |
doi_str_mv | 10.1198/108571108X336593 |
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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.</description><identifier>ISSN: 1085-7117</identifier><identifier>EISSN: 1537-2693</identifier><identifier>DOI: 10.1198/108571108X336593</identifier><language>eng</language><publisher>New York: American Statistical Association and the International Biometric Society</publisher><subject>Agriculture ; Agronomy. 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Jr</creatorcontrib><title>Using a master sample to integrate stream monitoring programs</title><title>Journal of agricultural, biological, and environmental statistics</title><addtitle>JABES</addtitle><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.</description><subject>Agriculture</subject><subject>Agronomy. Soil science and plant productions</subject><subject>Animal and plant ecology</subject><subject>Animal, plant and microbial ecology</subject><subject>Biological and medical sciences</subject><subject>Biometrics, statistics, experimental designs, modeling, agricultural computer applications</subject><subject>Biostatistics</subject><subject>case studies</subject><subject>Design</subject><subject>Ecoregions</subject><subject>environmental monitoring</subject><subject>Forest service</subject><subject>Fresh water ecosystems</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Generalities. Biometrics, experimentation. 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Soil science and plant productions</topic><topic>Animal and plant ecology</topic><topic>Animal, plant and microbial ecology</topic><topic>Biological and medical sciences</topic><topic>Biometrics, statistics, experimental designs, modeling, agricultural computer applications</topic><topic>Biostatistics</topic><topic>case studies</topic><topic>Design</topic><topic>Ecoregions</topic><topic>environmental monitoring</topic><topic>Forest service</topic><topic>Fresh water ecosystems</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Generalities. Biometrics, experimentation. Remote sensing</topic><topic>Health Sciences</topic><topic>Mathematics and Statistics</topic><topic>Medicine</topic><topic>Monitoring/Environmental Analysis</topic><topic>Natural resources</topic><topic>Sample size</topic><topic>sampling</topic><topic>spatial distribution</topic><topic>Statistics</topic><topic>Statistics for Life Sciences</topic><topic>Streams</topic><topic>Survey design</topic><topic>Survey sampling</topic><topic>Synecology</topic><topic>water management</topic><topic>Water resources</topic><topic>Watersheds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Larsen, David P</creatorcontrib><creatorcontrib>Olsen, Anthony R</creatorcontrib><creatorcontrib>Stevens, Donald L. Jr</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><jtitle>Journal of agricultural, biological, and environmental statistics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Larsen, David P</au><au>Olsen, Anthony R</au><au>Stevens, Donald L. Jr</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Using a master sample to integrate stream monitoring programs</atitle><jtitle>Journal of agricultural, biological, and environmental statistics</jtitle><stitle>JABES</stitle><date>2008-09-01</date><risdate>2008</risdate><volume>13</volume><issue>3</issue><spage>243</spage><epage>254</epage><pages>243-254</pages><issn>1085-7117</issn><eissn>1537-2693</eissn><abstract>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.</abstract><cop>New York</cop><pub>American Statistical Association and the International Biometric Society</pub><doi>10.1198/108571108X336593</doi><tpages>12</tpages></addata></record> |
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source | JSTOR Mathematics & Statistics; JSTOR Archive Collection A-Z Listing; SpringerLink Journals - AutoHoldings |
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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