When ichthyologists conduct their fieldwork, they collect much more than the specimens themselves. Fish biologists minimally collect geographic (e.g., latitude and longitude) and temporal (date and time) data, but they frequently collect habitat information, depth, salinity, temperature, visibility, and a wealth of other ecological data that are databased along with the specimen identification and information in databases such as those at The Field Museum. Individually, these records are valuable for ichthyologists interested in the distribution or biogeography of particular species, but when taken in aggregate (e.g., through pooled resources such as GBIF) these data can be explored in "meta-analysis" that can inform countless ecological and evolutionary studies. For example, predictive modeling of organismal distributions has brought these data together to better predict the expansion of introduced species, to predict the potential presence of animals or plants in unexplored regions, and to test for the impacts of climate change. These predictions and analyses are only going to become more critical as species continue to be introduced, species distributions continue to shrink toward extinction, fieldwork becomes more difficult, or large-scale climate change becomes increasingly studied. These collection data, based on well-curated specimens, are the only verifiable data that can be brought to bear on these questions. Distributional data that lack preserved specimens (vouchers) can always be questioned at a later date because the species identifications cannot be reassessed. This same value in being able to reassess species identifications based on whole-specimen vouchers is equally important for genetic or DNA-based research where the discovery of cryptic species (morphologically similar species representing diagnosable and genetically different forms) is a frequent occurrence. In cases where there are no voucher specimens to examine, researchers are required to return to the field to corroborate their molecular hypotheses. These are just a few of the cases where specimens and their associated data have contributions well beyond ecology and evolutionary biology. Listen to the podcast to learn additional examples!