This package provides functionality to access data from the European Tracking Network (ETN) database hosted by the Flanders Marine Institute (VLIZ) as part of the Flemish contribution to LifeWatch. ETN data is subject to the ETN data policy and can be: - restricted: under moratorium and only accessible to logged-in data owners/collaborators - unrestricted: publicly accessible without login and routinely published to international biodiversity facilities The ETN infrastructure currently requires the package to be run within the LifeWatch.be RStudio server, which is password protected. A login can be requested at http://www.lifewatch.be/etn/contact.

A set of functions that can be used to spatially thin species occurrence data. The resulting thinned data can be used in ecological modeling, such as ecological niche modeling.

Automated assessment of accuracy and geographical status of georeferenced biological data. The methods rely on reference regions, namely checklists and range maps. The package includes functions to obtain data from the Global Biodiversity Information Facility (https://www.gbif.org) and from the Global Inventory of Floras and Traits (https://gift.uni-goettingen.de/home). Alternatively, the user can input their own data. Furthermore, it provides easy visualisation of the data and the results through the plotting functions. It is especially suited for large datasets. The reference for the methodology is: Arlé et al. https://doi.org/10.1111/2041-210X.13629

The package provides features to manage the complete workflow for biodiversity data cleaning: uploading data, gathering input from users (in order to adjust cleaning procedures), cleaning data and finally, generating various reports and several versions of the data. It facilitates user-level data cleaning, designed for the inexperienced R users.

The package contains a number of discrete functions, each of which can be used to assess a particular form of bias, uncertainty or coverage. Generally, users must pass their occurrence data to the functions along with a list of time periods into which the outputs will be split. The functions generally return a list with two elements: a ggplot2 object, and the data that underpins that plot.

Framework for microclimate and mechanistic niche models. It provides an interface to a suite of biophysical modelling algorithms including the Niche Mapper system.

A set of algorithms for climate and ecological-niche factor analyses. The package includes functions for visualisation of spatial variability of species sensitivity, exposure, and vulnerability to climate change. It supports processing of large files and parallel methods.

The package provides a single function with all arguments necessary to calculate ENMs: variable collinearity control, bias control, accessible area delimitation, pseudoabsence allocation, data partition, several algorithms, thresholds, evaluation metrics, over-prediction, ensemble modelling, and projections over time and space.

The package allows creating spatially or environmentally separated folds for cross-validation to provide a robust error estimation in spatially structured environments. Moreover, it permits to investigate and visualise the effective range of spatial autocorrelation in continuous raster covariates and point samples to find an initial realistic distance band to separate training and testing datasets spatially described in Valavi, R. et al. (2019), https://doi.org/10.1111/2041-210X.13107.

A set of functions for reproducible and shareable analysis of models from an online repository, comparing and diagnostic models. The package has been developed specifically to improve reproducibility and comparability of SDMs in R by allowing users to encode entire SDM analyses as repeatable and extensible workflows consisting of independently executable, community-contributed modules. The module-workflow structure enables scientists to more easily create and share components of their analysis, and then, access, modify, reuse and combine the components of others.