Hide metadata

dc.date.accessioned2020-09-24T17:54:02Z
dc.date.created2020-09-23T14:02:56Z
dc.date.issued2020
dc.identifier.citationChoi, Jungyu Wright, David K. Lima, Helena Pinto . A new local scale prediction model of Amazonian landscape domestication sites. Journal of Archaeological Science. 2020, 123
dc.identifier.urihttp://hdl.handle.net/10852/79945
dc.description.abstractAmazonia has drawn the interest of researchers over the last few decades as a region with evidence for extensive ancient/past indigenous landscape domestication. Among the major issues surrounding the nature of landscape domestication of pre-Columbian Amazonians, its scale is critically connected with other major problems in the history of Amazonia such as forms of urbanism, land engineering and agriculture. In recent years, some research in historical ecology has focused on developing methods to calibrate landscape domestication by interpreting the effects of human activity on the formation of the modern Amazonian landscape. This paper presents regional-scale research in the Floresta Nacional de Caxiuanã (FNC) to provide a method to trace and calibrate long-term forest management. With the data collected from the FNC and satellite images, the relationship between soils, an Enhanced Vegetation Index (EVI) and landscape domestication are explored. The data are interpreted as indicating that zones of anthropogenic enrichment of the soil due to forest management over the last 2000 years have a positive correlation with high EVI values. The research methods have potential to be applied broadly in tropical rainforest environments where pedestrian survey is difficult to undertake.
dc.languageEN
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleA new local scale prediction model of Amazonian landscape domestication sites
dc.typeJournal article
dc.creator.authorChoi, Jungyu
dc.creator.authorWright, David K.
dc.creator.authorLima, Helena Pinto
dc.date.embargoenddate2023-09-17
cristin.unitcode185,14,31,10
cristin.unitnameArkeologi
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2
dc.identifier.cristin1832592
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Journal of Archaeological Science&rft.volume=123&rft.spage=&rft.date=2020
dc.identifier.jtitleJournal of Archaeological Science
dc.identifier.volume123
dc.identifier.doihttps://doi.org/10.1016/j.jas.2020.105240
dc.identifier.urnURN:NBN:no-83054
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn0305-4403
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/79945/1/ChoiEtAl2020_Local-ScalePredicationModel_LandscapeDom_Amazon.pdf
dc.type.versionAcceptedVersion
cristin.articleid105240


Files in this item

Appears in the following Collection

Hide metadata

Attribution-NonCommercial-NoDerivatives 4.0 International
This item's license is: Attribution-NonCommercial-NoDerivatives 4.0 International