Trait-based paleontological niche prediction recovers extinct ecological breadth of the earliest specialized ant predators

Manuscript abstract: Paleoecological estimation is fundamental to the reconstruction of evolutionary and environmental histories. The ant fossil record preserves a range of species in three-dimensional fidelity and chronicles faunal turnover across the Cretaceous and Cenozoic; taxonomically rich and ecologically-diverse, ants are an exemplar system to test new methods of paleoecological estimation in evaluating hypotheses. We apply a broad extant ecomorphological dataset to evaluate Random Forest machine learning classification in predicting the total ecological breadth of extinct and enigmatic “hell ants”. In contrast to previous hypotheses of extinction-prone arboreality, we find hell ants were primarily leaf litter or ground-nesting and foraging predators, and by comparing ecospace occupations of hell ants and their extant analogues, we recover a signature of ecomorphological turnover across temporally and phylogenetically distinct lineages on opposing sides of the KPg boundary. This paleoecological predictive framework is applicable across lineages and may provide new avenues for testing hypotheses over deep time. This supplementary folder is designed to provide all raw data used in this study, and provide a workflow and code to enable duplication of our work. Descriptions of all files included are listed here, with a summary of the data file, definitions of all variables included, and relevance of the file to the work. Replication of the main statistical analyses, the Random Forests analyses predicting the ecology of extinct taxa, may be conducted using the Supplementary Data_Code file under the heading ###Random Forest analyses###, using the training datasets provided (listed as Supplementary Data_Extant Ant Morphometrics, 3 files based on type of morphometric data). The ecology of extinct species may then be predicted using the morphometric data in the Supplementary Data_Fossil Morphometrics files. Please consult the README file for further details on each included file