The package evaluates the biasing impact of geographic features such as airports, cities, roads, rivers in datasets of coordinates based biological collection datasets, by Bayesian estimation of the parameters of a Poisson process. It enables also spatial visualization of sampling bias and includes a set of convenience functions for publication level plotting. The package is also available as shiny app.

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 provides a simple method to display and characterise the multidimensional ecological niche of a species. Moreover, the method estimates the optimums and amplitudes along each niche dimension (index D). It gives also an estimation of the degree of niche overlapping between species. See Kleparski and Beaugrand (2022), https://doi.org/10.1002/ece3.8830 for further details.

The package provides individual-based simulations of spatial eco-evolutionary dynamics. It is based on the software RangeShifter, making it flexible and fast. RangeShiftR models the processes of demography, dispersal and evolution in an inter-dependent way, offering substantial complexity in the corresponding modelling choices. It is entirely open-source and aims to facilitate the application of individual-based and mechanistic modelling to eco-evolutionary questions.

A tool for Quality Controlling Darwin Core based datasets according to the EMODnet Biology guidelines. The tool performs a thorough QC on OBIS-env datasets and occurrence core datasets. It can use an IPT resource URL as input. Quality controlling a dataset is fundamental in order to ensure its appropriate usage. The EMODnetBiocheck R package is developed in the framework of the LifeWatch and EMODnet Biology projects, and managed by the EurOBIS (European Ocean Biodiversity Information System) Data Management Team at the Flanders Marine Institute (VLIZ). It helps users to Quality Control their (marine) biological datasets by performing a varied number of quality checks on both published and unpublished datasets. This R package also allows a thorough visual exploration of the dataset, while highlighting potential issues within the dataset. The R package can be used on: i) public IPT resources; ii) loaded data tables. The only requirement to use the R package is the existence of an Occurrence table in the dataset, although the analysis reaches its full potential using an IPT resource with OBIS-ENV data format (Core: "Event"; Extensions: "Occurrence" and "Extended Measurements or Facts").

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.

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 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.

bioRad provides standardized methods for extracting and reporting biological signals from weather radars. It includes functionality to inspect low-level radar data, process these data into meaningful biological information on animal speeds and directions at different altitudes in the atmosphere, visualize these biological extractions, and calculate further summary statistics.

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.