TN_metrics | R Documentation |
This function computes various node and global metrics for a trait network graph.
TN_metrics(graph)
graph |
An igraph object representing the trait network, typically generated by the |
A list containing two data frames:
node |
A data frame with node-level metrics including degree, closeness, betweenness, and local clustering coefficient. |
global |
A data frame with global metrics including edge density, diameter, average path length, average clustering coefficient, and modularity. |
He, N., Li, Y., Liu, C., et al. (2020). Plant trait networks: improved resolution of the dimensionality of adaptation. Trends in Ecology & Evolution, 35(10), 908-918. https://doi.org/10.1016/j.tree.2020.06.003
Li, Y., Liu, C., Sack, L., Xu, L., Li, M., Zhang, J., & He, N. (2022). Leaf trait network architecture shifts with speciesārichness and climate across forests at continental scale. Ecology Letters, 25(6), 1442-1457. https://doi.org/10.1111/ele.14009
data(PFF)
PFF_traits <- PFF[, c("Height", "Leaf_area","LDMC","SLA","SRL","SeedMass","FltDate",
"FltDur","Leaf_Cmass","Leaf_Nmass","Leaf_CN","Leaf_Pmass",
"Leaf_NP","Leaf_CP","Root_Cmass","Root_Nmass","Root_CN")]
PFF_traits <- na.omit(PFF_traits)
head(PFF_traits)
Tn_result <- TN(traits_matrix = PFF_traits, rThres = 0.2, pThres = 0.05)
TN_metrics(Tn_result)
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