Package index • dissmapr

Overview of dissMapR functions

The package consists of 10 core functions that address key steps in biodiversity data analysis, from sourcing raw occurrence and environmental data to mapping bioregions and predicting compositional turnover. It also leverages existing tools, such as the zetadiv package (specifically the zetadiv::Zeta.msgdm function) for MS-GDM, alongside widely used R libraries like terra, sf, and ggplot2.

Core Functions

get_occurrence_data(): Import and harmonise biodiversity-occurrence data

generate_grid(): Generate Spatial Grid and Gridded Summaries

assign_mapsheet(): Add Nearest Mapsheet Code and Center Coordinates

get_enviro_data(): Retrieve, crop, resample, and link environmental rasters to sampling sites

format_df(): Format Biodiversity Records to Long / Wide

compute_orderwise(): Compute Order-wise Metrics

rm_correlated(): Remove Highly Correlated Predictors

predict_dissim(): Predict Pairwise Compositional Turnover (ζ-dissimilarity) with Richness

map_bioreg(): Raster-based Clustering and Interpolation of Bioregional Data

map_bioregDiff(): Map Bioregional Change Metrics Between Categorical Raster Layers

ζ-MSGDM Workflow

Functions to automate a ζ-MSGDM workflow that fits, extracts and visualizes I-spline models for any set of zeta orders in just three function calls:

run_ispline_models(): Run multiple Zeta.msgdm ispline models and return both models and combined ispline table

plot_ispline_lines(): Plot ispline partial effects with quantile and start‐point markers

plot_ispline_boxplots(): Plot facetted boxplots for all ispline basis columns

Available Metrics

Use helper_indices to choose a specific function for the func parameter in compute_orderwise, enabling the calculation of one of the following metrics:

geodist_helper(): Calculate geographic distance via Haversine formula (helper)

richness(): Calculate Species Richness

turnover(): Calculate Species Turnover or Beta Diversity

abund(): Calculate Species Abundance

phi_coef(): Calculate Phi Coefficient

cor_spear(): Calculate Spearman's Rank Correlation

cor_pears(): Calculate Pearson's Correlation

diss_bcurt(): Calculate Bray-Curtis Dissimilarity

orderwise_diss_gower(): Compute Gower dissimilarity between two site vectors

mutual_info(): Calculate Mutual Information