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1.
Philos Trans R Soc Lond B Biol Sci ; 377(1849): 20200499, 2022 04 25.
Article in English | MEDLINE | ID: mdl-35249381

ABSTRACT

The southwestern Amazon Rainforest Ecotone (ARE) is the transitional landscape between the tropical forest and seasonally flooded savannahs of the Bolivian Llanos de Moxos. These heterogeneous landscapes harbour high levels of biodiversity and some of the earliest records of human occupation and plant domestication in Amazonia. While persistent Indigenous legacies have been demonstrated elsewhere in the Amazon, it is unclear how past human-environment interactions may have shaped vegetation composition and structure in the ARE. Here, we examine 6000 years of archaeological and palaeoecological data from Laguna Versalles (LV), Bolivia. LV was dominated by stable rainforest vegetation throughout the Holocene. Maize cultivation and cultural burning are present after ca 5700 cal yr BP. Polyculture cultivation of maize, manioc and leren after ca 3400 cal yr BP predates the formation of Amazonian Dark/Brown Earth (ADE/ABE) soils (approx. 2400 cal yr BP). ADE/ABE formation is associated with agroforestry indicated by increased edible palms, including Mauritia flexuosa and Attalea sp., and record levels of burning, suggesting that fire played an important role in agroforestry practices. The frequent use of fire altered ADE/ABD forest composition and structure by controlling ignitions, decreasing fuel loads and increasing the abundance of plants preferred by humans. Cultural burning and polyculture agroforestry provided a stable subsistence strategy that persisted despite pronounced climate change and cultural transformations and has an enduring legacy in ADE/ABE forests in the ARE. This article is part of the theme issue 'Tropical forests in the deep human past'.


Subject(s)
Forests , Rainforest , Biodiversity , Bolivia , Climate Change , Humans , Plants , Trees
2.
J R Soc Interface ; 18(183): 20210499, 2021 10.
Article in English | MEDLINE | ID: mdl-34610263

ABSTRACT

The expansion of forest farmers across tropical lowland South America during the Late Holocene has long been connected to climate change. The more humid conditions established during the Late Holocene are assumed to have driven the expansion of forests, which would have facilitated the dispersal of cultures that practised agroforestry. The Tupi, a language family of widespread distribution in South America, occupies a central place in the debate. Not only are they one of the largest families in the continent, but their expansion from an Amazonian homeland has long been hypothesized to have followed forested environments wherever they settled. Here, we assess that hypothesis using a simulation approach. We employ equation-based and cellular automaton models, simulating demic-diffusion processes under two different scenarios: a null model in which all land cells can be equally settled, and an alternative model in which non-forested cells cannot be settled or delay the expansion. We show that including land cover as a constraint to movement results in a better approximation of the Tupi expansion as reconstructed by archaeology and linguistics.


Subject(s)
Archaeology , Climate Change , Forests , Linguistics , South America
3.
PLoS One ; 15(4): e0232367, 2020.
Article in English | MEDLINE | ID: mdl-32339209

ABSTRACT

Human expansions motivated by the spread of farming are one of the most important processes that shaped cultural geographies during the Holocene. The best known example of this phenomenon is the Neolithic expansion in Europe, but parallels in other parts of the globe have recently come into focus. Here, we examine the expansion of four archaeological cultures of widespread distribution in lowland South America, most of which originated in or around the Amazon basin and spread during the late Holocene with the practice of tropical forest agriculture. We analyze spatial gradients in radiocarbon dates of each culture through space-time regressions, allowing us to establish the most likely geographical origin, time and speed of expansion. To further assess the feasibility of demic diffusion as the process behind the archaeological expansions in question, we employ agent-based simulations with demographic parameters derived from the ethnography of tropical forest farmers. We find that, while some expansions can be realistically modeled as demographic processes, others are not easily explainable in the same manner, which is possibly due to different processes driving their dispersal (e.g. cultural diffusion) or problematic/incomplete archaeological data.


Subject(s)
Cultural Evolution/history , Human Migration/history , Models, Theoretical , Spatio-Temporal Analysis , Agriculture , Archaeology , Computer Simulation , History, Ancient , Humans , Language , South America
4.
Science ; 362(6420): 1309-1313, 2018 12 14.
Article in English | MEDLINE | ID: mdl-30545889

ABSTRACT

Domesticated maize evolved from wild teosinte under human influences in Mexico beginning around 9000 years before the present (yr B.P.), traversed Central America by ~7500 yr B.P., and spread into South America by ~6500 yr B.P. Landrace and archaeological maize genomes from South America suggest that the ancestral population to South American maize was brought out of the domestication center in Mexico and became isolated from the wild teosinte gene pool before traits of domesticated maize were fixed. Deeply structured lineages then evolved within South America out of this partially domesticated progenitor population. Genomic, linguistic, archaeological, and paleoecological data suggest that the southwestern Amazon was a secondary improvement center for partially domesticated maize. Multiple waves of human-mediated dispersal are responsible for the diversity and biogeography of modern South American maize.


Subject(s)
Biological Evolution , Domestication , Zea mays/classification , Zea mays/genetics , Genome, Plant , Models, Biological , Mutation , Phylogeny , South America
5.
PLoS One ; 11(7): e0158127, 2016.
Article in English | MEDLINE | ID: mdl-27384341

ABSTRACT

A long held view about the occupation of southern proto-Jê pit house villages of the southern Brazilian highlands is that these sites represent cycles of long-term abandonment and reoccupation. However, this assumption is based on an insufficient number of radiocarbon dates for individual pit houses. To address this problem, we conducted a programme of comprehensive AMS radiocarbon dating and Bayesian modelling at the deeply stratified oversized pit House 1, Baggio I site (Cal. A.D. 1395-1650), Campo Belo do Sul, Santa Catarina state, Brazil. The stratigraphy of House 1 revealed an unparalleled sequence of twelve well preserved floors evidencing a major change in occupation dynamics including five completely burnt collapsed roofs. The results of the radiocarbon dating allowed us to understand for the first time the occupation dynamics of an oversized pit house in the southern Brazilian highlands. The Bayesian model demonstrates that House 1 was occupied for over two centuries with no evidence of major periods of abandonment, calling into question previous models of long-term abandonment. In addition, the House 1 sequence allowed us to tie transformations in ceramic style and lithic technology to an absolute chronology. Finally, we can provide new evidence that the emergence of oversized domestic structures is a relatively recent phenomenon among the southern proto-Jê. As monumental pit houses start to be built, small pit houses continue to be inhabited, evidencing emerging disparities in domestic architecture after AD 1000. Our research shows the importance of programmes of intensive dating of individual structures to understand occupation dynamics and site permanence, and challenges long held assumptions that the southern Brazilian highlands were home to marginal cultures in the context of lowland South America.


Subject(s)
Ceramics , Housing/history , Radiometric Dating , Bayes Theorem , Brazil , Geography , History, 15th Century , History, 16th Century , History, 17th Century , History, Medieval , Humans , Models, Theoretical , Probability
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