Package index • IASDT.R

Package info

IASDT.R IASDT.R-package: IASDT.R: Modelling the distribution of invasive alien plant species in Europe

Prepare species distribution data

GBIF_process() GBIF_download() GBIF_read_chunk() GBIF_species_data(): Process GBIF occurrence data for the IASDT

EASIN_process() EASIN_taxonomy() EASIN_download() EASIN_plot(): Process EASIN data for the IASDT

eLTER_process(): Process eLTER data for the IASDT

IAS_process() IAS_distribution() IAS_plot(): Process and map Invasive Alien Species (IAS) data for the IASDT

get_species_name(): Get species name or information of an IASDT species ID

Prepare abiotic data

CLC_process(): Process Corine Land Cover (CLC) data for the IASDT

CHELSA_variables: Detailed information on CHELSA climate variables

CHELSA_process() CHELSA_prepare() CHELSA_project(): Process CHELSA Climate Data for the IASDT

efforts_process() efforts_request() efforts_download() efforts_summarize() efforts_split() efforts_plot(): Process GBIF sampling effort data for the IASDT

railway_intensity(): Calculate railway intensity based on OpenStreetMap data

road_intensity(): Calculate road intensity per grid cell

river_length(): Calculate the length of rivers in each Strahler order per grid cell

bioreg_process(): Process biogeographical regions dataset

Modelling functions

Functions for preparing data, running the models, and postprocessing of model outputs

Data preparation

Prepare input data and scripts for fitting Hmsc-HPC on GPU

mod_CV_prepare(): Prepare spatial-block cross-validation folds for spatial analysis

prepare_knots(): Prepare knot locations for Hmsc GPP models

mod_prepare_HPC() mod_prepare_data(): Prepare initial models for model fitting with Hmsc-HPC

mod_SLURM() mod_SLURM_refit(): Prepare SLURM scripts for Hmsc-HPC model fitting

mod_fit_windows(): Fit Hmsc-HPC models on UFZ Windows Server

mod_CV_fit(): Prepare cross-validated Hmsc models for HPC fitting

install_hmsc_windows(): Install Hmsc-HPC in a python virtual environment on Windows

solve1() solve2() solve2vect() fast_pnorm() exp_neg_div(): helper C++ functions for fast matrix computations

Model postprocessing

Postprocessing model outputs, including checking for convergence, making spatial predictions, evaluation, and plotting.

coda_to_tibble(): Convert a Coda object to a tibble with specified parameter transformations

trim_hmsc(): Trim an Hmsc Model Object by Removing Specified Components

mod_get_posteriors(): Combines posteriors exported by Hmsc-HPC into an Hmsc object

mod_merge_chains() mod_merge_chains_CV(): Merge model chains into Hmsc and coda objects

mod_summary(): Summary of Hmsc model parameters

resp_curv_prepare_data() resp_curv_plot_species() resp_curv_plot_species_all() resp_curv_plot_SR(): Prepare and plot response curve data for Hmsc models

predict_latent_factor(): Draws samples from the conditional predictive distribution of latent factors

plot_latent_factor(): Plot spatial variation in site loadings of HMSC models

predict_hmsc(): Calculates predicted values from a fitted Hmsc model

predict_maps() predict_maps_CV(): Predict habitat suitability of Hmsc models

plot_prediction(): Plot species and level of invasion predictions as JPEG files using ggplot2

mod_postprocess_1_CPU() mod_prepare_TF() mod_postprocess_2_CPU() mod_postprocess_CV_1_CPU() mod_postprocess_CV_2_CPU(): Model pipeline for post-processing fitted Hmsc models

plot_evaluation(): Generate plots for the explanatory power of Hmsc models

mod_heatmap_beta() mod_heatmap_omega(): Heatmaps for the beta and omega parameters of the Hmsc model

convergence_plot() convergence_alpha() convergence_rho() convergence_Beta_ranges(): Plot model convergence of a selected model

convergence_plot_all(): Plot model convergence of multiple modelling alternatives

variance_partitioning_compute() variance_partitioning_plot(): Computes and visualise variance partitioning of Hmsc models

plot_gelman() plot_gelman_alpha() plot_gelman_beta() plot_gelman_omega() plot_gelman_rho(): Plot Gelman-Rubin-Brooks