EcoService Models Library (ESML)
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: (EM-788)
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EM-788: Wild bee community change over a 26-year chronosequence of restored tallgrass prairie
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EM Identity and Description
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
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 |
βrich | |
Qualitative-Quantitative
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Quantitative (Cardinal Only) |
Cardinal-Ordinal
variable.detail.cardinalOrdinalHelp
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Cardinal |
unitless |
Variable Typology
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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Response |
Predictor Variable Type
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Not applicable |
Response Variable Type
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Computed Variable |
Data Source/Type
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Not applicable |
Variable Classification Hierarchy
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5. Ecosystem Attributes and Potential Supply of Ecosystem Goods and Services |
--Biological characteristics, processes or requirements of living ecosystem components |
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----Biological characteristics, processes or requirements of fauna |
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------Pollinators (nonspecific) |
Variable Spatial Characteristics
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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10-100 km^2 |
Spatially Distributed?
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Yes |
Observations Spatially Patterned?
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Yes |
Spatial Grain Type
variable.detail.spGrainTypeHelp
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other (specify), for irregular (e.g., stream reach, lake basin) |
Spatial Grain Size
variable.detail.spGrainSizeHelp
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Area varies by site |
Spatial Density
variable.detail.spDensityHelp
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Not applicable |
EnviroAtlas URL
variable.detail.enviroAtlasURLHelp
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Variable Temporal Characteristics
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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1988-2014 |
Temporally Distributed?
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Not applicable |
Regular Temporal Grain?
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Not applicable |
Temporal Grain Size Value
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Not applicable |
Temporal Grain Size Units
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Not applicable |
Temporal Density
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Not applicable |
Variable Values
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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Not reported ?Comment:Reported as pairwise dissimilarity of bee communities plotted against pairwise dissimilarity in age. |
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Min Value
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Not reported |
Max Value
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Not reported |
Other Value Type
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Not applicable |
Other Value
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Not reported |
Variable Variability and Sensitivity
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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No |
Variability Metric
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None |
Variability Value
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None |
Variability Units
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None |
Resampling Used?
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Not applicable |
Variability Expression Used in Modeling?
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Not applicable |
Variable Operational Validation (Response Variables only)
Richness effects (of changes in bee community composition over time) | |
Variable ID
variable.detail.varIdHelp
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19155 |
Validated?
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Not applicable |
Validation Approach (within, between, etc.)
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None |
Validation Quality (Qual/Quant)
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None |
Validation Method (Stat/Deviance)
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None |
Validation Metric
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None |
Validation Value
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None |
Validation Units
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None |
Use of Measured Response Data
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None |