MultiTraits (version 0.6.0)

PTN: Generate Plant Trait Network

Description

This function creates a network graph from a plant trait correlation matrix, applying thresholds for correlation strength and significance. It supports both standard correlations and phylogenetic independent contrasts.

Usage

PTN(
  traits_matrix,
  rThres = 0.2,
  pThres = 0.05,
  method = "pearson",
  phylo_correction = FALSE,
  phylo_tree = NULL
)

Value

Returns an igraph object representing the trait network with the following attributes:

• Edge attribute 'correlation': original correlation values (positive or negative)

• Edge attribute 'weight': absolute correlation values used for network analysis

• Vertices represent traits that pass the correlation and significance thresholds

Arguments

traits_matrix

A numeric matrix or data frame where each column represents a plant trait and each row represents a sample/species. Row names should contain species names when using phylogenetic correction.

rThres

Numeric, threshold for correlation coefficient, default is 0.2. Correlations with absolute values below this threshold are set to zero.

pThres

Numeric, threshold for p-value, default is 0.05. Only correlations with p-values below this threshold are included in the network.

method

Character, specifies the correlation method to use: "pearson" (default) or "spearman".

phylo_correction

Logical, whether to apply phylogenetic correction using phylogenetic independent contrasts, default is FALSE.

phylo_tree

A phylo object from the ape package containing the phylogenetic tree. Required when phylo_correction = TRUE. Species names in the tree must match row names in traits_matrix.

Details

The function performs the following steps:

1. Validates input parameters and phylogenetic tree compatibility (if applicable).

2. Calculates correlation coefficients and p-values using either standard correlation or phylogenetic independent contrasts.

3. Applies correlation coefficient and p-value thresholds to filter relationships.

4. Adjusts p-values using False Discovery Rate (FDR) correction.

5. Constructs an unweighted undirected graph from the filtered correlation matrix.

6. Removes self-loops and isolated nodes from the graph.

7. Adds correlation coefficients as edge attributes.

When phylo_correction = TRUE, the function:

• Matches species names between traits_matrix and phylo_tree

• Calculates phylogenetic independent contrasts for each trait

• Computes correlations between contrasts to control for phylogenetic relatedness

References

1. 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.

2. Li, Y., Liu, C., Sack, L., Xu, L., Li, M., Zhang, J., & He, N. (2022). Leaf trait network architecture shifts with species‐richness and climate across forests at continental scale. Ecology Letters, 25(6), 1442-1457.

Examples

# Example 1: Standard trait network analysis
data(PFF)
rownames(PFF) <- PFF$species
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)

ptn_result <- PTN(traits_matrix = PFF_traits, rThres = 0.2, pThres = 0.05, method = "pearson")
ptn_result

# Example 2: Phylogenetically corrected trait network analysis
data(PFF_tree)

# Trait network with phylogenetic correction
ptn_phylo_result <- PTN(traits_matrix = PFF_traits,
                      rThres = 0.2,
                      pThres = 0.05,
                      method = "pearson",
                      phylo_correction = TRUE,
                      phylo_tree = PFF_tree)
ptn_phylo_result