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The digitization and open availability of life history traits measured directly from individuals provide a key means of linking organismal function to environmental and ecological contexts at fine resolution. These linkages play a critical role in understanding trait‐mediated response to global change, with particular need to resolve them for taxa that are secretive and hard to monitor, like most mammals. In this study, we use digitized museum specimen and census data to document how climate and body size each shape a key life history trait – litter size – in 39 small mammals across North America. We employ mixed models to test associations between litter size, climate and body size, with a focus on joint estimation of inter‐ and intraspecific trends. Among species, no single climate predictor explained a large amount of litter size variation. Instead, interactions between temperature‐related (continentality, solar irradiation) and moisture‐related (annual precipitation, relative humidity) indices, along with body size, exert a stronger influence on litter size. We observed maximal litter sizes for species inhabiting seasonal or xeric regions under conditions of increased moisture availability, or conversely, mesic or aseasonal regions under conditions of reduced moisture availability. These patterns are consistent with primary productivity as a mechanistic driver of litter size. At the intraspecific level, litter size responds to continentality and temperature‐related indices experienced by populations, but is most strongly shaped by body size of individual females. We also find evidence of phylogenetic covariation in these intraspecific trends. Our study demonstrates how life history traits assembled from individual‐level biodiversity records improve precision and granularity of ecological studies, help to parse among‐ and within‐species trends, and foster improved understanding of tradeoffs between energetic supply and demand (e.g. reproduction) in wild mammals. [ABSTRACT FROM AUTHOR]

The availability of user-friendly software and publicly available biodiversity databases has led to a rapid increase in the use of ecological niche modelling to predict species distributions. A potential source of error in publicly available data that may affect the accuracy of ecological niche models (ENMs), and one that is difficult to correct for, is incorrect (or incomplete) taxonomy. Here we remind researchers of the need for careful evaluation of database records prior to use in modelling, especially when the presence of cryptic species is suspected or many records are based on indirect evidence. To draw attention to this potential problem, we construct ENMs for the North American Sasquatch (i.e. Bigfoot). Specifically, we use a large database of georeferenced putative sightings and footprints for Sasquatch in western North America, demonstrating how convincing environmentally predicted distributions of a taxon’s potential range can be generated from questionable site-occurrence data. We compare the distribution of Bigfoot with an ENM for the black bear, Ursus americanus, and suggest that many sightings of this cryptozoid may be cases of mistaken identity. [ABSTRACT FROM AUTHOR]