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Analytical framework for reconstructing heterogeneous environmental variables from mammal community structure

Louys, J, Meloro, C, Elton, S, Ditchfield, P and Bishop, LC (2015) Analytical framework for reconstructing heterogeneous environmental variables from mammal community structure. Journal of Human Evolution, 78 (1). pp. 1-11. ISSN 1095-8606

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Abstract

We test the performance of two models that use mammalian communities to reconstruct multivariate palaeoenvironments. While both models exploit the correlation between mammal communities (defined in terms of functional groups) and arboreal heterogeneity, the first uses a multiple multivariate regression of community structure and arboreal heterogeneity, while the second uses a linear regression of the principal components of each ecospace. The success of these methods means the palaeoenvironment of a particular locality can be reconstructed in terms of the proportions of heavy, moderate, light, and absent tree canopy cover. The linear regression is less biased, and more precisely and accurately reconstructs heavy tree canopy cover than the multiple multivariate model. However, the multiple multivariate model performs better than the linear regression for all other canopy cover categories. Both models consistently perform better than randomly generated reconstructions. We apply both models to the palaeocommunity of the Upper Laetolil Beds, Tanzania. Our reconstructions indicate that there was very little heavy tree cover at this site (likely less than 10%), with the palaeo-landscape instead comprising a mixture of light and absent tree cover. These reconstructions help resolve the previous conflicting palaeoecological reconstructions made for this site.

Item Type: Article
Uncontrolled Keywords: 0603 Evolutionary Biology, 1601 Anthropology, 2101 Archaeology
Subjects: Q Science > QH Natural history > QH301 Biology
Divisions: Natural Sciences and Psychology (closed 31 Aug 19)
Publisher: Elsevier
Related URLs:
Date Deposited: 12 Oct 2015 09:04
Last Modified: 04 Sep 2021 14:12
DOI or ID number: 10.1016/j.jhevol.2014.11.001
URI: https://researchonline.ljmu.ac.uk/id/eprint/1598

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