Provides functions for covariance matrix comparisons, estimation of repeatabilities in measurements and matrices, and general evolutionary quantitative genetics tools. Melo D, Garcia G, Hubbe A, Assis A P, Marroig G. (2016) <doi:10.12688/f1000research.7082.3>.

Provides an 'R' interface to the 'Evolution API' <https://evoapicloud.com>, enabling sending and receiving 'WhatsApp' messages directly from 'R'. Functions include sending text, images, documents, stickers, geographic locations, and interactive messages (lists). Also includes 'webhook' parsing utilities and channel health checks.

Evolutionary game theory applies game theory to evolving populations 
    in biology, see e.g. one of the books by Weibull (1994, ISBN:978-0262731218) 
    or by Sandholm (2010, ISBN:978-0262195874) for more details. A comprehensive 
	set of tools to illustrate the core concepts of evolutionary game theory, 
	such as evolutionary stability or various evolutionary dynamics, for teaching 
	and academic research is provided.

Provides tools for calculating evolvability parameters from estimated G-matrices as defined 
    in Hansen and Houle (2008) <doi:10.1111/j.1420-9101.2008.01573.x> and fits phylogenetic 
    comparative models that link the rate of evolution of a trait to the state of another evolving 
    trait (see Hansen et al. 2021 Systematic Biology <doi:10.1093/sysbio/syab079>). The package was 
    released with Bolstad et al. (2014) <doi:10.1098/rstb.2013.0255>, which contains some examples of use.

"Evolutionary Virtual Education" - 'evolved' - provides multiple tools to help educators (especially at the graduate level or in advanced undergraduate level courses) apply inquiry-based learning in general evolution classes. In particular, the tools provided include functions that simulate evolutionary processes (e.g., genetic drift, natural selection within a single locus) or concepts (e.g. Hardy-Weinberg equilibrium, phylogenetic distribution of traits). More than only simulating, the package also provides tools for students to analyze (e.g., measuring, testing, visualizing) datasets with characteristics that are common to many fields related to evolutionary biology. Importantly, the package is heavily oriented towards providing tools for inquiry-based learning - where students follow scientific practices to actively construct knowledge. For additional details, see package's vignettes.