Variance partitioning and variable selection using redundancy analysis (RDA) and distance-based redundancy analysis (dbRDA) showing the unique and shared contributions of three sets of explanatory variables to variation in dung beetle assemblages. [AUB], [BUC], and [AUC] represent the variation fractions explained jointly or uniquely by combinations of predictor sets: environmental variables (A), forest productivity (B), and forest diversity metrics (C). See methods for detailed matrix definitions.
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https://figshare.com/articles/dataset/Variance_partitioning_and_variable_selection_using_redundancy_analysis_RDA_and_distance-based_redundancy_analysis_dbRDA_showing_the_unique_and_shared_contributions_of_three_sets_of_explanatory_variables_to_variation_in_dung_beetle_assemblag/30793925
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Variance partitioning and variable selection using redundancy analysis (RDA) and distance-based redundancy analysis (dbRDA) showing the unique and shared contributions of three sets of explanatory variables to variation in dung beetle assemblages. [AUB], [BUC], and [AUC] represent the variation fractions explained jointly or uniquely by combinations of predictor sets: environmental variables (A), forest productivity (B), and forest diversity metrics (C). See methods for detailed matrix definitions.
创建时间：
2025-12-04
