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Geography of artiodactyl locomotor morphology as an environmental predictor

Cite this dataset

Short, Rachel; Lawing, A. Michelle (2021). Geography of artiodactyl locomotor morphology as an environmental predictor [Dataset]. Dryad.


Aim: We investigate locomotor function in artiodactyls, represented by calcaneal gear ratio, as it relates to multiple environments. Using an ecometrics approach, we develop a trait-environment model to investigate ecosystem level changes through time and to reconstruct past environments. We apply the trait-environment model to a case study of six sites in Kenya to evaluate changes over the past 100 years.

Location: Global.

Methods: Locomotor morphology was represented by calcaneal gear ratios measured as the overall length of a calcaneum divided by length of its in-lever, i.e. calcaneal tuber. We collected calcaneal gear ratio measurements from skeletal specimens of 157 artiodactyl species in museum collections and used species’ spatial distributions to determine the composition of 47,420 communities globally. For 21,827 communities with three or more species of artiodactyls, we used maximum likelihood to model ecometric relationships between community-level locomotor morphology and five environmental variables, including mean annual temperature, annual precipitation, elevation, vegetation cover, and ecoregion province.

Results: Community mean gear ratios range from 1.43 to 1.56 (µ = 1.50). Mean gear ratios are highest in the tropical regions and lowest in the mid-latitudes. Variance in mean calcaneal gear ratio is related to ecoregion division (68.6%), vegetation cover (63.5%), and precipitation (60.7%). In a case study of Kenyan sites, we demonstrate habitat homogenization patterns that match mammal community turnover patterns.

Main conclusions: With this ecometric framework, fossils of artiodactyl postcrania can be used to assist in interpreting past ecoregion, vegetation cover, and precipitation for a more comprehensive understanding of paleoenvironment. These relationships between functional traits and environment will enable better models of biotic responses for conservation of functional diversity under changing environments.