View source: R/hill_func_parti.R
hill_func_parti | R Documentation |
Calculate functional gamma, alpha, and beta diversity for all communities, as well as site similarity. These values are based on ALL communities.
hill_func_parti(
comm,
traits,
traits_as_is = FALSE,
q = 0,
base = exp(1),
check_data = TRUE,
rel_then_pool = TRUE,
ord = c("podani", "metric"),
stand_dij = FALSE,
show_warning = TRUE
)
comm |
A data frame of vegetation data. Sites as rows, species as columns. |
traits |
A data frame of species functional traits data. Species as rows, traits as columns. It can include both continuous and categorical data. It will be transformed into a distance matrix using 'FD::gowdis(traits)'. If all traits are numeric, then it will use Euclidean distance. |
traits_as_is |
if |
q |
Hill number, |
base |
default is |
check_data |
whether to check data first? Default is |
rel_then_pool |
default is |
ord |
ord in |
stand_dij |
whether to standardize distance matrix to have max value of 1? Default is |
show_warning |
whether to print warning, default is |
a data frame with one row (across all sites), including these columns: q, RaoQ of pooled assemblage, gamma diversity, alpha diversity, beta diversity, local species overlap (similar to Sorensen), and region species overlap (similar to Jaccard). See Chiu and Chao 2014 Table 3 for more information.
Chao, Anne, Chun-Huo Chiu, and Lou Jost. Unifying Species Diversity, Phylogenetic Diversity, Functional Diversity, and Related Similarity and Differentiation Measures Through Hill Numbers. Annual Review of Ecology, Evolution, and Systematics 45, no. 1 (2014): 297–324. <doi:10.1146/annurev-ecolsys-120213-091540>.
Chiu, Chun-Huo, and Anne Chao. Distance-Based Functional Diversity Measures and Their Decomposition: A Framework Based on Hill Numbers. PLoS ONE 9, no. 7 (July 7, 2014): e100014. <doi:10.1371/journal.pone.0100014>.
hill_taxa_parti
, hill_func
dummy = FD::dummy
hill_func_parti(comm = dummy$abun, traits = dummy$trait, q = 0)
hill_func_parti(comm = dummy$abun, traits = dummy$trait, q = 1)
hill_func_parti(comm = dummy$abun, traits = dummy$trait, q = 0.9999)
hill_func_parti(comm = dummy$abun, traits = dummy$trait, q = 2)
hill_func_parti(comm = dummy$abun, traits = dummy$trait, q = 3)
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