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Origin of mound-field landscapes: a multi-proxy approach combining contemporary vegetation, carbon stable isotopes and phytoliths
Authors:Delphine Renard  Jago Jonathan Birk  Bruno Glaser  José Iriarte  Gilles Grisard  Johannes Karl  Doyle McKey
Institution:1. Université Montpellier II and Centre d’Ecologie Fonctionnelle et Evolutive, UMR 5175 CNRS, 1919 route de Mende, 34293, Montpellier cedex 5, France
2. Soil Physics Group, University of Bayreuth, Universit?tsstr. 30, Bayreuth, 95447, Germany
3. Department of Archaeology, College of Humanities, University of Exeter, Laver Building, North Park Rd., Exeter, EX4 4QE, UK
Abstract:

Background and aims

Seasonally flooded South American savannas harbor different kinds of mound-field landscapes of largely unknown origin. A recent study used soil carbon-isotope depth profiles and other proxies to infer vegetation history in murundu landscapes in Brazil. Results suggested that differential erosion, not building-up processes (e.g., termite mounds), produced mounds. We tested this approach to inferring mound origin in a mound-field landscape in French Guiana.

Methods

We examined carbon-isotope depth profiles of soil organic matter, phytolith profiles and contemporary vegetation composition in mounds and inter-mounds.

Results

Relative abundance of C3 and C4 plants across habitats was very different from that in murundu landscapes; C3 plants were better represented in inter-mounds than on mounds. Habitat differences in C3/C4 distribution were subtler than in murundu landscapes, limiting inference of vegetation history based on carbon isotopes. Still, carbon-isotope and phytolith depth profiles gave similar pictures of vegetation history, both favoring a building-up hypothesis, corroborating other evidence that these mounds are vestiges of ancient agricultural raised fields.

Conclusions

Carbon-isotope depth profiles are unlikely to be adequate for deciphering origin of mound-field landscapes from vegetation history in seasonally flooded savannas. Including data on current vegetation and phytoliths makes inferences more robust.
Keywords:
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