EcoService Models Library (ESML)
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Variables Details
: (EM-788)
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2-3 year age sites
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EM Identity and Description (* Note that run information is shown only where run data differ from the "parent" entry for that variable)
EM-788 | |
Document Author
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Griffin, S. R, B. Bruninga-Socolar, M. A. Kerr, J. Gibbs and R. Winfree |
Document Year
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2017 |
Variable General Info (* Note that run information is shown only where run data differ from the "parent" entry for that variable)
Richness effects (of changes in bee community composition over time) ?Comment:We decomposed the changes in bee community composition over time, as measured above, into their two components, species replacement and richness effects. To accomplish this, we used the beta diversity partitioning analysis described by Carvalho et al. (2012). This analysis is based on presence–absence data and uses the Jaccard index of dissimilarity rather than presence–absence Bray–Curtis. Richness effects (βrich) can be defined as: βrich = |b − c| ∕ (a + b + c) , in which |b−c| represents absolute difference in richness between sites. Thus, βrepl and βrich are additive and sum to βtot. A more detailed explanation of these equations can be found in Carvalho et al. (2012). We used each of these three measures to create pairwise dissimilarity matrices, which we plotted against a matrix of pairwise age differences between our sites using code from Ensing (2011). For each of our three plots (βtot, βrepl, and βrich vs. age difference), we fitted least square regressions and examined the y-intercept and slope of each. These regressions were used to compare intercepts and slopes in a heuristic way only, because the plotted points were calculated from all possible pairwise comparisons within the dataset and thus not independent from each other. To statistically assess the significance of the relationship between dissimilarity and age difference for each of the three dissimilarity metrics, we used a Mantel test (Lichstein 2006; Carvalho et al. 2012) in the package ecodist (Goslee & Urban 2007). |
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Variable ID
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19155 |
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Qualitative-Quantitative
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Cardinal-Ordinal
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Variable Typology (* Note that run information is shown only where run data differ from the "parent" entry for that variable)
Richness effects (of changes in bee community composition over time) ?Comment:We decomposed the changes in bee community composition over time, as measured above, into their two components, species replacement and richness effects. To accomplish this, we used the beta diversity partitioning analysis described by Carvalho et al. (2012). This analysis is based on presence–absence data and uses the Jaccard index of dissimilarity rather than presence–absence Bray–Curtis. Richness effects (βrich) can be defined as: βrich = |b − c| ∕ (a + b + c) , in which |b−c| represents absolute difference in richness between sites. Thus, βrepl and βrich are additive and sum to βtot. A more detailed explanation of these equations can be found in Carvalho et al. (2012). We used each of these three measures to create pairwise dissimilarity matrices, which we plotted against a matrix of pairwise age differences between our sites using code from Ensing (2011). For each of our three plots (βtot, βrepl, and βrich vs. age difference), we fitted least square regressions and examined the y-intercept and slope of each. These regressions were used to compare intercepts and slopes in a heuristic way only, because the plotted points were calculated from all possible pairwise comparisons within the dataset and thus not independent from each other. To statistically assess the significance of the relationship between dissimilarity and age difference for each of the three dissimilarity metrics, we used a Mantel test (Lichstein 2006; Carvalho et al. 2012) in the package ecodist (Goslee & Urban 2007). |
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Predictor-Intermediate-Response
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Predictor Variable Type
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Response Variable Type
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Data Source/Type
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Variable Classification Hierarchy
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Variable Spatial Characteristics (* Note that run information is shown only where run data differ from the "parent" entry for that variable)
Richness effects (of changes in bee community composition over time) ?Comment:We decomposed the changes in bee community composition over time, as measured above, into their two components, species replacement and richness effects. To accomplish this, we used the beta diversity partitioning analysis described by Carvalho et al. (2012). This analysis is based on presence–absence data and uses the Jaccard index of dissimilarity rather than presence–absence Bray–Curtis. Richness effects (βrich) can be defined as: βrich = |b − c| ∕ (a + b + c) , in which |b−c| represents absolute difference in richness between sites. Thus, βrepl and βrich are additive and sum to βtot. A more detailed explanation of these equations can be found in Carvalho et al. (2012). We used each of these three measures to create pairwise dissimilarity matrices, which we plotted against a matrix of pairwise age differences between our sites using code from Ensing (2011). For each of our three plots (βtot, βrepl, and βrich vs. age difference), we fitted least square regressions and examined the y-intercept and slope of each. These regressions were used to compare intercepts and slopes in a heuristic way only, because the plotted points were calculated from all possible pairwise comparisons within the dataset and thus not independent from each other. To statistically assess the significance of the relationship between dissimilarity and age difference for each of the three dissimilarity metrics, we used a Mantel test (Lichstein 2006; Carvalho et al. 2012) in the package ecodist (Goslee & Urban 2007). |
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Spatial Extent Area
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Spatially Distributed?
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Observations Spatially Patterned?
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Spatial Grain Type
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Spatial Grain Size
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Spatial Density
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EnviroAtlas URL
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Variable Temporal Characteristics (* Note that run information is shown only where run data differ from the "parent" entry for that variable)
Richness effects (of changes in bee community composition over time) ?Comment:We decomposed the changes in bee community composition over time, as measured above, into their two components, species replacement and richness effects. To accomplish this, we used the beta diversity partitioning analysis described by Carvalho et al. (2012). This analysis is based on presence–absence data and uses the Jaccard index of dissimilarity rather than presence–absence Bray–Curtis. Richness effects (βrich) can be defined as: βrich = |b − c| ∕ (a + b + c) , in which |b−c| represents absolute difference in richness between sites. Thus, βrepl and βrich are additive and sum to βtot. A more detailed explanation of these equations can be found in Carvalho et al. (2012). We used each of these three measures to create pairwise dissimilarity matrices, which we plotted against a matrix of pairwise age differences between our sites using code from Ensing (2011). For each of our three plots (βtot, βrepl, and βrich vs. age difference), we fitted least square regressions and examined the y-intercept and slope of each. These regressions were used to compare intercepts and slopes in a heuristic way only, because the plotted points were calculated from all possible pairwise comparisons within the dataset and thus not independent from each other. To statistically assess the significance of the relationship between dissimilarity and age difference for each of the three dissimilarity metrics, we used a Mantel test (Lichstein 2006; Carvalho et al. 2012) in the package ecodist (Goslee & Urban 2007). |
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Temporal Extent
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2011-2014 |
Temporally Distributed?
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Regular Temporal Grain?
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Temporal Grain Size Value
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Temporal Grain Size Units
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Temporal Density
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Variable Values (* Note that run information is shown only where run data differ from the "parent" entry for that variable)
Richness effects (of changes in bee community composition over time) ?Comment:We decomposed the changes in bee community composition over time, as measured above, into their two components, species replacement and richness effects. To accomplish this, we used the beta diversity partitioning analysis described by Carvalho et al. (2012). This analysis is based on presence–absence data and uses the Jaccard index of dissimilarity rather than presence–absence Bray–Curtis. Richness effects (βrich) can be defined as: βrich = |b − c| ∕ (a + b + c) , in which |b−c| represents absolute difference in richness between sites. Thus, βrepl and βrich are additive and sum to βtot. A more detailed explanation of these equations can be found in Carvalho et al. (2012). We used each of these three measures to create pairwise dissimilarity matrices, which we plotted against a matrix of pairwise age differences between our sites using code from Ensing (2011). For each of our three plots (βtot, βrepl, and βrich vs. age difference), we fitted least square regressions and examined the y-intercept and slope of each. These regressions were used to compare intercepts and slopes in a heuristic way only, because the plotted points were calculated from all possible pairwise comparisons within the dataset and thus not independent from each other. To statistically assess the significance of the relationship between dissimilarity and age difference for each of the three dissimilarity metrics, we used a Mantel test (Lichstein 2006; Carvalho et al. 2012) in the package ecodist (Goslee & Urban 2007). |
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* ?Comment:Reported as pairwise dissimilarity of bee communities plotted against pairwise dissimilarity in age. |
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Min Value
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Max Value
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Other Value Type
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Other Value
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Variable Variability and Sensitivity (* Note that run information is shown only where run data differ from the "parent" entry for that variable)
Richness effects (of changes in bee community composition over time) ?Comment:We decomposed the changes in bee community composition over time, as measured above, into their two components, species replacement and richness effects. To accomplish this, we used the beta diversity partitioning analysis described by Carvalho et al. (2012). This analysis is based on presence–absence data and uses the Jaccard index of dissimilarity rather than presence–absence Bray–Curtis. Richness effects (βrich) can be defined as: βrich = |b − c| ∕ (a + b + c) , in which |b−c| represents absolute difference in richness between sites. Thus, βrepl and βrich are additive and sum to βtot. A more detailed explanation of these equations can be found in Carvalho et al. (2012). We used each of these three measures to create pairwise dissimilarity matrices, which we plotted against a matrix of pairwise age differences between our sites using code from Ensing (2011). For each of our three plots (βtot, βrepl, and βrich vs. age difference), we fitted least square regressions and examined the y-intercept and slope of each. These regressions were used to compare intercepts and slopes in a heuristic way only, because the plotted points were calculated from all possible pairwise comparisons within the dataset and thus not independent from each other. To statistically assess the significance of the relationship between dissimilarity and age difference for each of the three dissimilarity metrics, we used a Mantel test (Lichstein 2006; Carvalho et al. 2012) in the package ecodist (Goslee & Urban 2007). |
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Variability Expression Given?
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Variability Metric
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Variability Value
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Variability Units
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Resampling Used?
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Variability Expression Used in Modeling?
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Variable Operational Validation (Response Variables only; * Note that run information is shown only where run data differ from the "parent" entry for that variable)
Richness effects (of changes in bee community composition over time) | |
Variable ID
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19155 |
Validated?
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Validation Approach (within, between, etc.)
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Validation Quality (Qual/Quant)
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Validation Method (Stat/Deviance)
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Validation Metric
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Validation Value
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Validation Units
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Use of Measured Response Data
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