Non-random patterns in the Yellowstone ecosystem: inferences from mammalian body size, order and biogeographical affinity

Aim Our aim was to investigate how the environment, species characteristics and historical factors at the subcontinental scale affect patterns of diversity. We used the assembly of the Yellowstone biota over the past 10,000 years as a natural experiment for investigating the processes that generate a modern non-volant mammal species pool. Location The data represent species from throughout North America with special attention to the non-volant mammals of Yellowstone National Park, USA. Methods We used digitized range maps to determine biogeographical affinity for all non-volant mammals in the Rocky Mountains, Deserts and Great Plains biogeographical regions of North America. This biogeographical affinity, along with taxonomic order and body size class, was used to test whether non-random patterns exist in the assemblage of Yellowstone non-volant mammals. These characteristics were also used to investigate the strength of non-random processes, such as habitat or taxon filtering, on particular groups of species or individual species. Results Our results indicated that the Yellowstone fauna is composed of a non-random subset of mammals from specific body size classes and with particular biogeographical affinities. Analyses by taxonomic order found significantly more Carnivora from the Rocky Mountains region and significantly fewer Rodentia from the Deserts region than expected from random assembly. Analyses using body size classes revealed deviations from expectations, including several significant differences between the frequency distribution of regional body sizes and the distribution of those species found within Yellowstone. Main conclusions Our novel approach explores processes affecting species pool assembly in the Yellowstone region and elsewhere, and particularly identifies unique properties of species that may contribute to non-random assembly. Focusing on the mechanisms generating diversity, not just current diversity patterns, will assist the design of conservation strategies given future environmental change scenarios.