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Analytical framework for reconstructing heterogeneous environmental variables from mammal community structure.

Julien Louys1, Carlo Meloro2, Sarah Elton3

  • 1Department of Archaeology and Natural History, School of History, Culture and Languages, ANU College of Asia and the Pacific, The Australian National University, ACT 0200, Australia; Research Centre in Evolutionary Anthropology and Palaeoecology, School of Natural Sciences and Psychology, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK.

Journal of Human Evolution
|December 7, 2014
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Summary

Two models using mammal communities reconstruct past environments by analyzing tree canopy cover. The linear regression model accurately reconstructs heavy tree cover, while the multivariate model excels for other categories, improving palaeoenvironmental reconstructions.

Keywords:
Faunal communityLaeotoliPalaeoecologyPalaeoenvironmentVegetation heterogeneity

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Area of Science:

  • Paleoecology
  • Mammalian Ecology
  • Environmental Reconstruction

Background:

  • Mammalian communities reflect environmental conditions, including arboreal heterogeneity.
  • Previous palaeoecological reconstructions for the Upper Laetolil Beds, Tanzania, have been conflicting.

Purpose of the Study:

  • To test the performance of two models for reconstructing multivariate palaeoenvironments using mammalian communities.
  • To compare the accuracy and precision of a multiple multivariate regression model versus a linear regression model.

Main Methods:

  • Exploiting the correlation between mammal functional groups and arboreal heterogeneity.
  • Applying multiple multivariate regression and linear regression of principal components to ecospace data.
  • Reconstructing palaeoenvironments based on tree canopy cover proportions (heavy, moderate, light, absent).

Main Results:

  • Both models accurately reconstruct palaeoenvironments, outperforming random reconstructions.
  • Linear regression is less biased and more accurate for heavy tree canopy cover.
  • Multiple multivariate regression performs better for moderate, light, and absent tree canopy cover.
  • Application to the Upper Laetolil Beds suggests less than 10% heavy tree cover, with a landscape of light and absent tree cover.

Conclusions:

  • Mammalian community data can reliably reconstruct past tree canopy cover.
  • The models provide a resolution to conflicting palaeoecological interpretations for the Upper Laetolil Beds.
  • These methods offer valuable tools for understanding past terrestrial ecosystems.