Shared temporal increases in bill size among songbirds of the San Francisco bay area are due to different seasonal selective pressures

Museum specimens offer a unique and powerful tool for understanding the impact of anthropogenic change on populations over time. Morphological traits can be impacted by many different environmental variables that are difficult to separate from one another as potential driving factors. Comparative analyses among similar species jointly experiencing change in the same environmental variables can help pinpoint the selective pressures driving temporal morphological change. We assessed temporal change in bill size, tarsus length, and body size between six species of songbirds from the San Francisco Bay Area over the past 150 years. Wing length, as a proxy for body size, exhibited idiosyncratic temporal changes among species. In contrast, we found a significant increase in bill surface area across all but one species. Quantile regression analyses on bill size variation additionally revealed that temporal increases over the past century have been driven by increases in the largest bill sizes i..., The dataset includes morphological measurements made from 1,001 museum specimens at Museum of Vertebrate Zoology, University of California Berkeley and California Academy of Sciences. Measurements were all made using digital calipers. Climate variables for each specimen come from the PRISM climate database and were extracted using locality info from each specimen. , , # Data from: Shared temporal increases in bill size among songbirds of the San Francisco bay area are due to different seasonal selective pressures

[https://doi.org/10.5061/dryad.98sf7m0v5](https://doi.org/10.5061/dryad.98sf7m0v5)

## Description of the data and file structure

Dataset of morphological measurements from 1,001 bird specimens of six species. Morphological characters include: bill length, bill width, bill depth, wing length and tarsus length. Dataset also includes specimen voucher numbers, locality coordinates, and time of collection. Finally, the data includes climate data extracted from PRISM dataset for year and location of specimen collected. Climate variables include: annual maximum temperature, annual minimum temperature, annual maximum vapor pressure deficit, annual minimum vapor pressure deficit. We also calculated 3 and 5-year averages of each climate parameter before year of collection for each specimen. Cells in the dataset with NA represent cases where data is...,