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Cited by 146Archaeology and ancient environmental studiesRice Cultivation and Yield ImprovementPacific and Southeast Asian Studies

The DOI matches its Crossref record; 90 of the 90 references it cites were found in a registry or an index.

Modelling the Geographical Origin of Rice Cultivation in Asia Using the Rice Archaeological Database

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Silva, Fabio, Stevens, Chris J., Weisskopf, Alison, Castillo, Cristina, Qin, Ling, Bevan, Andrew, Fuller, Dorian Q.·2015·PLOS ONE
DOI 10.1371/journal.pone.0137024PMC PMC4556484
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Abstract

We have compiled an extensive database of archaeological evidence for rice across Asia, including 400 sites from mainland East Asia, Southeast Asia and South Asia. This dataset is used to compare several models for the geographical origins of rice cultivation and infer the most likely region(s) for its origins and subsequent outward diffusion. The approach is based on regression modelling wherein goodness of fit is obtained from power law quantile regressions of the archaeologically inferred age versus a least-cost distance from the putative origin(s). The Fast Marching method is used to estimate the least-cost distances based on simple geographical features. The origin region that best fits the archaeobotanical data is also compared to other hypothetical geographical origins derived from the literature, including from genetics, archaeology and historical linguistics. The model that best fits all available archaeological evidence is a dual origin model with two centres for the cultivation and dispersal of rice focused on the Middle Yangtze and the Lower Yangtze valleys.

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Crossref · 10.1371/journal.pone.0137024

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Figures

Fig 1 Map of the Rice Archaeological Database version 2.0. Sites with cultivated rice are shown as filled black dots, whereas open ones represent archaeological sites with wild rice. The background layer shows the quantile interpolation of the median dates for the arrival of cultivated rice. The grey-shaded region has been excluded from the interpolation (see main text). Major rivers have been included for reference (source: ESRI World Major Rivers).
Fig 1 Map of the Rice Archaeological Database version 2.0. Sites with cultivated rice are shown as filled black dots, whereas open ones represent archaeological sites with wild rice. The background layer shows the quantile interpolation of the median dates for the arrival of cultivated rice. The grey-shaded region has been excluded from the interpolation (see main text). Major rivers have been included for reference (source: ESRI World Major Rivers).CC BY · PubMed Central
Fig 2 Domain used for the modelling. Regions excluded were those with annual total number of degree-days lower than 2,500 (blue-shaded) and desert eco-regions (red-shaded). Kept were the landmass region (grey-shaded) and 40 km offshore buffers for coastal transport (green shaded). Database sites with cultivated rice retained for analysis marked as black dots.
Fig 2 Domain used for the modelling. Regions excluded were those with annual total number of degree-days lower than 2,500 (blue-shaded) and desert eco-regions (red-shaded). Kept were the landmass region (grey-shaded) and 40 km offshore buffers for coastal transport (green shaded). Database sites with cultivated rice retained for analysis marked as black dots.CC BY · PubMed Central
Fig 3 Number of times the real dispersal source was selected by different fitness indices over a range of underlying correlation coefficients. The R 2 adj curve (in yellow) is exactly the same, and therefore hidden behind, the AIC OLS curve (in black).
Fig 3 Number of times the real dispersal source was selected by different fitness indices over a range of underlying correlation coefficients. The R 2 adj curve (in yellow) is exactly the same, and therefore hidden behind, the AIC OLS curve (in black).CC BY · PubMed Central
Fig 4 Map of the domain showing the gridpoints that were used in the unconstrained search for the best dispersal origin. The region not included in the domain is grey-shaded. For reference, the background layer includes elevation data (source: USGS Shuttle Radar Topography Mission data), as well as major rivers (source: ESRI World Major Rivers).
Fig 4 Map of the domain showing the gridpoints that were used in the unconstrained search for the best dispersal origin. The region not included in the domain is grey-shaded. For reference, the background layer includes elevation data (source: USGS Shuttle Radar Topography Mission data), as well as major rivers (source: ESRI World Major Rivers).CC BY · PubMed Central
Fig 5 Locations of the origins used in the tested literature models. Specific archaeological sites: 1—Mahagara, 4—Non Nok Tha, 7- Pengtoushan, 8—Shangshan; general areas: 2—Assam, 3—Burma, 5—Northern Vietnam, 6—Pearl river delta. For reference, there is a background layer containing elevation data (source: USGS Shuttle Radar Topography Mission data) and the major rivers (source: ESRI World Major Rivers).
Fig 5 Locations of the origins used in the tested literature models. Specific archaeological sites: 1—Mahagara, 4—Non Nok Tha, 7- Pengtoushan, 8—Shangshan; general areas: 2—Assam, 3—Burma, 5—Northern Vietnam, 6—Pearl river delta. For reference, there is a background layer containing elevation data (source: USGS Shuttle Radar Topography Mission data) and the major rivers (source: ESRI World Major Rivers).CC BY · PubMed Central
Fig 6 Interpolated map of ΔAIC values obtained from the results of the unconstrained search algorithm. The gridpoint with lowest AIC is marked by the cross. The black dots mark the sites with cultivated rice in the Rice Archaeological Database. Major rivers are also shown, for reference (source: ESRI World Major Rivers).
Fig 6 Interpolated map of ΔAIC values obtained from the results of the unconstrained search algorithm. The gridpoint with lowest AIC is marked by the cross. The black dots mark the sites with cultivated rice in the Rice Archaeological Database. Major rivers are also shown, for reference (source: ESRI World Major Rivers).CC BY · PubMed Central
Fig 7 Scatterplots of age with cost distance for all models considered. The black dots represent records in the Rice Archaeological Database whereas the blue line represents the best-fitting log-log quantile regressed line for each model.
Fig 7 Scatterplots of age with cost distance for all models considered. The black dots represent records in the Rice Archaeological Database whereas the blue line represents the best-fitting log-log quantile regressed line for each model.CC BY · PubMed Central
Fig 8 Predicted arrival times of cultivated rice in eastern and southeastern Asia, based on best-fitting model L7. Areas in dark grey were not included in the modelling framework (see main text). Major rivers (source: ESRI World Major Rivers) and country borders shown for reference.
Fig 8 Predicted arrival times of cultivated rice in eastern and southeastern Asia, based on best-fitting model L7. Areas in dark grey were not included in the modelling framework (see main text). Major rivers (source: ESRI World Major Rivers) and country borders shown for reference.CC BY · PubMed Central
Fig 9 Scatterplot of the dataset for the best-fitting model L7. The quantile interpolation of the 10th-percentile of the data (blue line) shows that the distribution follows a power law rule. Sites earlier than the model are circled and identified (see the text for related discussion).
Fig 9 Scatterplot of the dataset for the best-fitting model L7. The quantile interpolation of the 10th-percentile of the data (blue line) shows that the distribution follows a power law rule. Sites earlier than the model are circled and identified (see the text for related discussion).CC BY · PubMed Central

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Research works printed but not linked: 3

  1. H Akaike, 1973, Second International Symposium on Information Theory, 267
  2. AWF Edwards, 1992, Expanded edition
  3. PJ Ribeiro Jr, 2001, geoR: a package for geostatistical analysis, R-NEWS, 1, 15

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Metadata

Authors
Silva, F., Stevens, C. J., Weisskopf, A., Castillo, C., Qin, L., Bevan, A., & Fuller, D. Q.
Affiliations
  • University College London (GB)
  • Peking University (CN)
ORCID
Venue
PLOS ONE
Publisher
Public Library of Science (PLoS)
Published
2015-09-01
Volume
10
Issue
9
Pages
e0137024
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0137024
PMC
PMC4556484
OpenAlex
W1825971118
Cited by
146
References
90
Citations by year
2026: 10 · 2025: 6 · 2024: 5 · 2023: 10 · 2022: 17 · 2021: 19 · 2020: 18 · 2019: 12 · 2018: 10 · 2017: 28 · 2016: 8 · 2015: 3
FWCI
12.39
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Bournemouth University Research Online (Bournemouth University) (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • UCL Discovery (University College London) (submittedVersion)
Funders
  • Natural Environment Research Council (NE/G005540/1, NE/K003402/1, NRCF010002)
  • FP7 Ideas: European Research Council (323842)
Topics
  • Social Sciences › Archeology › Archaeology and ancient environmental studies
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Rice Cultivation and Yield Improvement
  • Social Sciences › Anthropology › Pacific and Southeast Asian Studies
Keywords
rice cultivation, archaeological site, archaeobotany, power-law regression, fast marching method, East Asia, Southeast Asia, South Asia, crop domestication
MeSH terms
Archaeology, Asia, Geography, Models, Theoretical, Oryza, Databases, Factual

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