The Brazil nut tree (Bertholletia excelsa) is an iconic and economically valuable species that dominates vast swathes of the Amazon Basin. This species seems to have been an important part of human subsistence strategies in the region from at least the Early Holocene, and its current distribution may be a legacy of past human settlement. Because B. excelsa is a long-lived pioneer tree it requires natural or human disturbances to increase light availability in the understory for a successful establishment. However, it remains unclear how the long-term population dynamics of this species have been shaped by pre-colonial and post-colonial human practices. Here, we use tree-ring analyses to look at changes in growing conditions over the past 400 years in a Brazil nut tree population in Central Amazonia. We identify changes in tree recruitment and growth rates associated not only with regional climatic variability, but also major political and socio-economic activities recorded by historical documents in the vicinity of Manaus. We demonstrate that the expansion of a post-colonial political center (Manaus) from the middle of the 18 th century onwards coincided with a reduction in recruitment of B. excelsa. We argue that this hiatus suggests the interruption of indigenous management practices, probably due to the collapse of pre-Columbian societies. A second recruitment pulse, and unprecedented cycles of growth release and suppression, aligns with a shift to modern exploitation of the forest into the 20 th century. Our findings shed light on how past histories of human-forest interactions can be revealed by the growth rings of trees in Amazonia. Future interdisciplinary analysis of these trees should enable more detailed investigation of how human forest management has changed in this part of the world, through pre-colonial, colonial, and industrial periods of human activity, with potential implications for conservation. © 2019 Caetano Andrade et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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