Methods for species distribution modeling, that is, predicting the environmental similarity of any site to that of the locations of known occurrences of a species.

Functionality for manipulating values of associative
  maps.  The package is a dependency for mvp-type
  packages that use the STL map class: it traps
  plausible idiom that is ill-defined (implementation-specific) and
  returns an informative error, rather than returning a possibly
  incorrect result.  To cite the package in publications please use
  Hankin (2022) <doi:10.48550/ARXIV.2210.03856>.

The disparity filter algorithm is a network reduction technique to
    identify the 'backbone' structure of a weighted network without destroying
    its multi-scale nature. The algorithm is documented in M. Angeles Serrano,
    Marian Boguna and Alessandro Vespignani in "Extracting the multiscale
    backbone of complex weighted networks", Proceedings of the National Academy
    of Sciences 106 (16), 2009. This implementation of the algorithm supports
    both directed and undirected networks.

Simulates demic diffusion building on models previously developed
	for the expansion of Neolithic and other food-producing economies during
	the Holocene (Fort et al. (2012) <doi:10.7183/0002-7316.77.2.203>, Souza et al.
	(2021) <doi:10.1098/rsif.2021.0499>). Growth and emigration are modelled as
	density-dependent processes using logistic growth and an asymptotic threshold
	model. Environmental and terrain layers, which can change over time, affect
	carrying capacity, growth and mobility. Multiple centres of origin with
	their respective starting times can be specified.

Provides methods for analyzing the dispersion of tabular datasets
    with batched and ordered samples. Based on convex hull or integrated covariance
    Mahalanobis, several indicators are implemented for inter and intra batch dispersion
    analysis. It is designed to facilitate robust statistical assessment of data
    variability, supporting applications in exploratory data analysis and quality
    control, for such datasets as the one found in metabololomics studies.
    For more details see Salanon (2024) <doi:10.1016/j.chemolab.2024.105148> and
    Salanon (2025) <doi:10.1101/2025.08.01.668073>.