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MultiTraits 1.0.0 (2026-3-22)

New Features and Major Improvements

• PTMN Module (Plant Trait Multilayer Networks): Introduced a comprehensive new module for constructing, analyzing, and visualizing plant trait multilayer networks. This module systematically integrates multilayer network theory with plant functional trait analysis and includes three core functions:

  • PTMN(): Constructs phylogenetic trait multilayer networks where nodes represent traits organized into layers (e.g., organs or functional systems) and edges represent significant correlations. It supports correlation thresholding, p-value filtering, FDR correction, and optional phylogenetic correction using independent contrasts.
  • PTMN_metrics(): Calculates node-level and global network metrics for PTMNs, identifying hub traits and cross-layer modules. Included metrics are interlayer degree, closeness, clustering coefficient, edge density, path length, and modular association.
  • PTMN_plot(): Visualizes PTMNs with options for standard and circular layouts, customizable node and edge aesthetics, and layer/module highlighting. It clearly differentiates intralayer edges (black) from interlayer edges (red).

Bug fixes

• LHS_strategy_scheme(): Corrected an error in the strategy description mapping. The trait sequence was previously misinterpreted as a Leaf-Seed-Height order. The text descriptions in the strategy column have now been fixed to accurately reflect the standard Leaf-Height-Seed (L-H-S) framework.

MultiTraits 0.6.0 (2025-10-01)

New Features and Major Improvements

• PTN Module (Plant Trait Network): Functions in the trait network module have been renamed from the TN_ prefix to PTN_ for consistency (e.g., PTN(), PTN_metrics()). Functionality for phylogenetic correction has been added, allowing PTN() and PTN_corr() to account for species’ evolutionary relatedness during analysis.

• CSR Module: The module has been expanded with the CSR_hodgson() function, implementing an alternative CSR classification method based on Hodgson et al. (1999).

• NPT Module: A discrete classification scheme has been added to the Niche Periodic Table module.

• Data: A new phylogenetic tree for the PFF dataset (PFF_tree) has been included to support the new phylogenetic correction capabilities.

• Other minor improvements and documentation enhancements have been made across the package.

Bug fixes

• CSR_plot(): Removed the dependency on the ggtern package (no longer maintained) and implemented plotting using ggplot2 to ensure continued compatibility and improve stability.

MultiTraits 0.5.0 (2025-4-20)

Bug fixes and minor improvements

• Modify the community detection algorithm of the TN_metrics function to cluster_edge_betweenness
• Modified TN function to support unweighted networks

MultiTraits 0.4.0 (2025-4-16)

Bug fixes and minor improvements

• Modified TN_metrics function to support unweighted networks

MultiTraits 0.3.0 (2025-2-21)

Infrastructure

• Added unit testing infrastructure using testthat package
• Added test coverage for core functions

Bug fixes and minor improvements

• Removed deprecated vegan::summary() call in NPT function in favor of direct scores() method

MultiTraits 0.2.0 (2024-12-21)

Bug fixes and minor improvements

• Fixed bug where discrete scales could not map aesthetics only consisting of NAs
• Fixed spurious warnings from sec_axis() with breaks = NULL.
• Patterns and gradients are now also enabled in geom_sf().
• The default behaviour of resolution() has been reverted to pre-3.5.0 behaviour. Whether mapped discrete vectors should be treated as having resolution of 1 is controlled by the new discrete argument.
• Fixed bug in guide_bins() and guide_coloursteps() where discrete breaks, such as the levels produced by cut(), were ordered incorrectly.
• Fixed calculation issues in CSR module
• Resolved NaN errors in TN module
• Optimized visualization effects across all modules (CSR, LHS, NPT, TN)
• Removed WH dataset
• Updated examples across package modules

MultiTraits 0.1.0 (2024-11-26)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.