A method for measuring the comparability of different sampling methods used in biological surveys: implications for data integration and synthesis

Y. Cao, C.P. Hawkins, Andrew Storey

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    26 Citations (Scopus)

    Abstract

    1. Numerous methods have been developed to sample the biota occurring in different ecosystems. However, the comparability of data derived from different sampling methods is generally unknown and is a major concern when integrating data from different studies.2. Examination of assemblage-level attributes such as taxa richness and biotic index scores is generally inappropriate for evaluating the degree to which different sampling methods produce comparable descriptions of entire assemblages, because these measures provide no information regarding taxonomic composition. Multivariate methods are generally more appropriate for this purpose, but some of the methods previously used are not satisfactory and others have not been tested. A useful measure of sampling-method comparability (SMC) should be independent of sampling effort, independent of the sites sampled and have an explicit biological interpretation.3. We used simulated data to compare two potential methods of assessing SMC, the R-value produced by ANOSIM and a modified version of classification strength (CS-SMC) derived from Van Sickle's Mean Similarity Analysis. Analyses were based on similarities between the assemblages captured by two different sampling methods (electrofishing and seining) employed at the same sites. Similarities were calculated two different ways: the Bray-Curtis index and the Jaccard coefficient.4. Based on simulated data, ANOSIM R-values were strongly affected by sampling effort, highly variable across sites and difficult to interpret biologically. In contrast, CS-SMC values were highly stable over a range of sampling effort, across sites and easy to interpret biologically.5. Application of CS-SMC to field data showed that seining and electrofishing produced highly comparable samples of fish in small streams: 97% comparable on average for species lists and 94% comparable for relative abundances. Kicknet and Surber samples of benthic invertebrates were also comparable after being standardised to a fixed count, but to a lesser extent than fish samples: 77% comparable on average for the taxa lists and 93% comparable for relative abundances. CS-SMC should be of general use when integrating and synthesising assemblage data from a variety of assemblages.
    Original languageEnglish
    Pages (from-to)1105-1115
    JournalFreshwater Biology
    Volume50
    DOIs
    Publication statusPublished - 2005

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    biological survey
    synthesis
    sampling
    methodology
    electrofishing
    method
    measuring
    relative abundance
    fish

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    title = "A method for measuring the comparability of different sampling methods used in biological surveys: implications for data integration and synthesis",
    abstract = "1. Numerous methods have been developed to sample the biota occurring in different ecosystems. However, the comparability of data derived from different sampling methods is generally unknown and is a major concern when integrating data from different studies.2. Examination of assemblage-level attributes such as taxa richness and biotic index scores is generally inappropriate for evaluating the degree to which different sampling methods produce comparable descriptions of entire assemblages, because these measures provide no information regarding taxonomic composition. Multivariate methods are generally more appropriate for this purpose, but some of the methods previously used are not satisfactory and others have not been tested. A useful measure of sampling-method comparability (SMC) should be independent of sampling effort, independent of the sites sampled and have an explicit biological interpretation.3. We used simulated data to compare two potential methods of assessing SMC, the R-value produced by ANOSIM and a modified version of classification strength (CS-SMC) derived from Van Sickle's Mean Similarity Analysis. Analyses were based on similarities between the assemblages captured by two different sampling methods (electrofishing and seining) employed at the same sites. Similarities were calculated two different ways: the Bray-Curtis index and the Jaccard coefficient.4. Based on simulated data, ANOSIM R-values were strongly affected by sampling effort, highly variable across sites and difficult to interpret biologically. In contrast, CS-SMC values were highly stable over a range of sampling effort, across sites and easy to interpret biologically.5. Application of CS-SMC to field data showed that seining and electrofishing produced highly comparable samples of fish in small streams: 97{\%} comparable on average for species lists and 94{\%} comparable for relative abundances. Kicknet and Surber samples of benthic invertebrates were also comparable after being standardised to a fixed count, but to a lesser extent than fish samples: 77{\%} comparable on average for the taxa lists and 93{\%} comparable for relative abundances. CS-SMC should be of general use when integrating and synthesising assemblage data from a variety of assemblages.",
    author = "Y. Cao and C.P. Hawkins and Andrew Storey",
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    T1 - A method for measuring the comparability of different sampling methods used in biological surveys: implications for data integration and synthesis

    AU - Cao, Y.

    AU - Hawkins, C.P.

    AU - Storey, Andrew

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    N2 - 1. Numerous methods have been developed to sample the biota occurring in different ecosystems. However, the comparability of data derived from different sampling methods is generally unknown and is a major concern when integrating data from different studies.2. Examination of assemblage-level attributes such as taxa richness and biotic index scores is generally inappropriate for evaluating the degree to which different sampling methods produce comparable descriptions of entire assemblages, because these measures provide no information regarding taxonomic composition. Multivariate methods are generally more appropriate for this purpose, but some of the methods previously used are not satisfactory and others have not been tested. A useful measure of sampling-method comparability (SMC) should be independent of sampling effort, independent of the sites sampled and have an explicit biological interpretation.3. We used simulated data to compare two potential methods of assessing SMC, the R-value produced by ANOSIM and a modified version of classification strength (CS-SMC) derived from Van Sickle's Mean Similarity Analysis. Analyses were based on similarities between the assemblages captured by two different sampling methods (electrofishing and seining) employed at the same sites. Similarities were calculated two different ways: the Bray-Curtis index and the Jaccard coefficient.4. Based on simulated data, ANOSIM R-values were strongly affected by sampling effort, highly variable across sites and difficult to interpret biologically. In contrast, CS-SMC values were highly stable over a range of sampling effort, across sites and easy to interpret biologically.5. Application of CS-SMC to field data showed that seining and electrofishing produced highly comparable samples of fish in small streams: 97% comparable on average for species lists and 94% comparable for relative abundances. Kicknet and Surber samples of benthic invertebrates were also comparable after being standardised to a fixed count, but to a lesser extent than fish samples: 77% comparable on average for the taxa lists and 93% comparable for relative abundances. CS-SMC should be of general use when integrating and synthesising assemblage data from a variety of assemblages.

    AB - 1. Numerous methods have been developed to sample the biota occurring in different ecosystems. However, the comparability of data derived from different sampling methods is generally unknown and is a major concern when integrating data from different studies.2. Examination of assemblage-level attributes such as taxa richness and biotic index scores is generally inappropriate for evaluating the degree to which different sampling methods produce comparable descriptions of entire assemblages, because these measures provide no information regarding taxonomic composition. Multivariate methods are generally more appropriate for this purpose, but some of the methods previously used are not satisfactory and others have not been tested. A useful measure of sampling-method comparability (SMC) should be independent of sampling effort, independent of the sites sampled and have an explicit biological interpretation.3. We used simulated data to compare two potential methods of assessing SMC, the R-value produced by ANOSIM and a modified version of classification strength (CS-SMC) derived from Van Sickle's Mean Similarity Analysis. Analyses were based on similarities between the assemblages captured by two different sampling methods (electrofishing and seining) employed at the same sites. Similarities were calculated two different ways: the Bray-Curtis index and the Jaccard coefficient.4. Based on simulated data, ANOSIM R-values were strongly affected by sampling effort, highly variable across sites and difficult to interpret biologically. In contrast, CS-SMC values were highly stable over a range of sampling effort, across sites and easy to interpret biologically.5. Application of CS-SMC to field data showed that seining and electrofishing produced highly comparable samples of fish in small streams: 97% comparable on average for species lists and 94% comparable for relative abundances. Kicknet and Surber samples of benthic invertebrates were also comparable after being standardised to a fixed count, but to a lesser extent than fish samples: 77% comparable on average for the taxa lists and 93% comparable for relative abundances. CS-SMC should be of general use when integrating and synthesising assemblage data from a variety of assemblages.

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    DO - 10.1111/j.1365-2427.2005.01377.x

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    JO - Freshwater Biology

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