Understanding the drivers of spatial patterns of genomic diversity has emerged as a major goal of evolutionary genetics. The flexibility of forward-time simulation makes it especially valuable for these efforts, allowing for the simulation of arbitrarily complex scenarios in a way that mimics how real populations evolve. Here, we present Geonomics, a Python package for performing complex, spatially explicit, landscape genomic simulations with full spatial pedigrees that dramatically reduces user workload yet remains customizable and extensible because it is embedded within a popular, general-purpose language. We show that Geonomics results are consistent with expectations for a variety of validation tests based on classic models in population genetics and then demonstrate its utility and flexibility with a trio of more complex simulation scenarios that feature polygenic selection, selection on multiple traits, simulation on complex landscapes, and nonstationary environmental change. We then discuss runtime, which is primarily sensitive to landscape raster size, memory usage, which is primarily sensitive to maximum population size and recombination rate, and other caveats related to the model's methods for approximating recombination and movement. Taken together, our tests and demonstrations show that Geonomics provides an efficient and robust platform for population genomic simulations that capture complex spatial and evolutionary dynamics.

Spiny lizards (genus Sceloporus) have long served as important systems for studies of behavior, thermal physiology, dietary ecology, vector biology, speciation, and biogeography. The western fence lizard, Sceloporus occidentalis, is found across most of the major biogeographical regions in the western United States and northern Baja California, Mexico, inhabiting a wide range of habitats, from grassland to chaparral to open woodlands. As small ectotherms, Sceloporus lizards are particularly vulnerable to climate change, and S. occidentalis has also become an important system for studying the impacts of land use change and urbanization on small vertebrates. Here, we report a new reference genome assembly for S. occidentalis, as part of the California Conservation Genomics Project (CCGP). Consistent with the reference genomics strategy of the CCGP, we used Pacific Biosciences HiFi long reads and Hi-C chromatin-proximity sequencing technology to produce a de novo assembled genome. The assembly comprises a total of 608 scaffolds spanning 2,856 Mb, has a contig N50 of 18.9 Mb, a scaffold N50 of 98.4 Mb, and BUSCO completeness score of 98.1% based on the tetrapod gene set. This reference genome will be valuable for understanding ecological and evolutionary dynamics in S. occidentalis, the species status of the California endemic island fence lizard (S. becki), and the spectacular radiation of Sceloporus lizards.