Machine learning (ML) for classification and prediction based on a set of features is used to make decisions in healthcare, economics, criminal justice and more. However, implementing an ML pipeline including preprocessing, model selection, and evaluation can be time-consuming, confusing, and difficult. Here, we present mikropml (prononced "meek-ROPE em el"), an easy-to-use R package that implements ML pipelines using regression, support vector machines, decision trees, random forest, or gradient-boosted trees. The package is available on GitHub, CRAN, and conda.

The North American tiger salamander species complex, including its best-known species, the Mexican axolotl, has long been a source of biological fascination. The complex exhibits a wide range of variation in developmental life history strategies, including populations and individuals that undergo metamorphosis; those able to forego metamorphosis and retain a larval, aquatic lifestyle (i.e., paedomorphosis); and those that do both. The evolution of a paedomorphic life history state is thought to lead to increased population genetic differentiation and ultimately reproductive isolation and speciation, but the degree to which it has shaped population- and species-level divergence is poorly understood. Using a large multilocus dataset from hundreds of samples across North America, we identified genetic clusters across the geographic range of the tiger salamander complex. These clusters often contain a mixture of paedomorphic and metamorphic taxa, indicating that geographic isolation has played a larger role in lineage divergence than paedomorphosis in this system. This conclusion is bolstered by geography-informed analyses indicating no effect of life history strategy on population genetic differentiation and by model-based population genetic analyses demonstrating gene flow between adjacent metamorphic and paedomorphic populations. This fine-scale genetic perspective on life history variation establishes a framework for understanding how plasticity, local adaptation, and gene flow contribute to lineage divergence. Many members of the tiger salamander complex are endangered, and the Mexican axolotl is an important model system in regenerative and biomedical research. Our results chart a course for more informed use of these taxa in experimental, ecological, and conservation research.

The North American tiger salamander species complex, including its flagship species the axolotl, has long been a source of biological fascination. The complex exhibits a wide range of variation in developmental life history strategies, including populations and individuals that undergo metamorphosis and those able to forego metamorphosis and retain a larval, aquatic lifestyle (i.e., paedomorphosis). Such disparate life history strategies are assumed to cause populations to become reproductively isolated, but the degree to which they have actually shaped population- and species-level boundaries is poorly understood. Using a large multi-locus dataset from hundreds of samples across North America, we identified genetic clusters with clear signs of admixture across the geographic range of the tiger salamander complex. Population clusters often contain a mixture of paedomorphic and metamorphic taxa, and we conclude that geography has played a large role in driving lineage divergence relative to obligate paedomorphosis in this system. This conclusion is bolstered by model-based analyses demonstrating gene flow between metamorphic and paedomorphic populations. Even the axolotl, a paedomorphic species with an isolated native range, apparently has a history of gene flow with its neighboring populations. This fine-scale genetic perspective on life-history variation establishes a framework for understanding how plasticity, local adaptation, and gene flow contribute to lineage divergence. The axolotl is currently used as the vertebrate model system in regenerative biology, and our findings chart a course for more informed use of these and other tiger salamander species in experimental and field research, including conservation priorities.