The coevolutionary dynamics metaecosystems package, COMETA, uses EvoDynamics.jl with forward spatially explicit simulations to connect complex polygenic trait architecture to biodiversity dynamics. Cometa uses the open-source julia computing language.
Coupling genomic and trait architecture in species-rich landscapes refers to the study of the relationship between an organism's genetic makeup, i.e., genomics, and its observable characteristics or traits, the phenome, and how such a coupling, the architecture connecting genes to traits, contribute to species diversity. Architecture gradients can be used to better understand and conserve biodiversity in the face of ongoing environmental challenges, such as climate change and habitat destruction. Yet, exploring the architecture of genes and traits that are important for an organism's survival and reproduction, is full of challenges mostly because many studies in ecology and evolution have reported complex genotype to trait interactions suggesting that selection does not operate on traits in isolation, but instead act on combinations of traits. In addition, the relative contributions of each trait to fitness as well as the fitness functions are mostly unknown for most taxa. Thus, the relevant theory connecting complex genotype-to-trait architecture to multispecies assemblages and biodiversity dynamics is at a very incipient stage. COMETA aims to use flexible forward simulations using the EvoDynamics.jl package to explore the interplay between complex genotype-to-trait architecture and biodiversity dynamics. It explores correlations between interacting traits and also traits operating in isolation with modular architecture along hierarchy gradients, i.e., trait contributions to fitness can be equal, forming an heterarchy, but it can also be strongly dominant, forming a trait hierarchy. Which of these scenarios predict more resilient biodiversity responses to rapidly changing ecosystems?