Package index • invasimapr

Overview of invasimapr functions

Quantifies and visualises invasion fitness from occurrence and trait data. Computes trait centrality, maps trait dispersion, and estimates interaction strength. Assesses site-level invasibility and community openness to new invasions. Produces interaction matrices and trait-specific invasion risk indicators. Aligns with Hui et al. (2023): integrates traits, propagule pressure, and environment.

Wrapper Functions

invasimap(): Run the full invasimapr pipeline

prepare_inputs(): Prepare inputs (assemble & align core tables)

prepare_trait_space(): Prepare trait space and resident crowding (no site-z)

model_residents(): Model residents and build standardized predictors (\(r_{js}^{(z)}, C_{js}^{(z)}, S_{js}^{(z)}\))

learn_sensitivities(): Learn sensitivities (αᵢ, βᵢ, θᵢ/γᵢ) and optional site-varying αᵢₛ, Γᵢₛ

predict_invaders(): Build standardized invader predictors (r_is_z, C_is_z, S_is_z)

predict_establishment(): Compute invasion fitness (\(\lambda\)) and optional establishment probability (\(P\))

summarise_results(): Summarise invasiveness / invasibility (tables, maps, rankings)

Core Functions

get_trait_data(): Scrape and Analyze Wikipedia & Trait Data for a Species

assemble_matrices(): Assemble community matrices for invasion-fitness workflows

simulate_invaders(): Simulate hypothetical invader trait profiles from a resident trait pool

standardise_model_inputs(): Standardise model inputs (no leakage) for residents and invaders

compute_trait_space(): Shared trait-space construction (Gower + PCoA), resident hull, centroid, and density plot

compute_centrality_hull(): Compute trait-space centrality (robust Mahalanobis) and hull status, with visuals

compute_resident_crowding(): Resident crowding C_js via Hellinger composition and Gower–Gaussian trait kernel

build_model_formula(): Flexible formula constructor for residents-only trait–environment models

prep_resident_glmm(): Build residents-by-sites long table and fit the residents-only GLMM

standardise_by_site(): Standardize a site-by-species matrix by site (row-wise z) with optional robust SD

compute_site_saturation(): Compute site-only saturation (\(S_s\)) and global z-score (\(S_s^{(z)}\))

fit_auxiliary_residents_glmm(): Auxiliary GLMM for trait-varying (and optionally site-varying) slopes

derive_sensitivities(): Derive trait-varying sensitivities (alpha_i, beta_i) and abiotic slope (theta, gamma_i)

site_varying_alpha_beta_gamma(): Site-varying α_is and Γ_is, plus β_i (and signed variants)

build_invader_predictors(): Build standardized invader predictors r_is_z, C_is_z, S_is_z (expects env/traits frames already projected to model columns)

compute_invasion_fitness(): Compute invasion fitness \(\lambda_{is}\) for multiple model options

compute_establishment_probability(): Probabilistic establishment from invasion fitness

summarise_invasiveness_invasibility(): Summaries of invasion fitness: species invasiveness, trait effects, and site invasibility