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  Quantitative methods demonstrate that environment alone is an insufficient predictor of present-day language distributions in New Guinea

Antunes, N., Schiefenhövel, W., d’Errico, F., Banks, W. E., & Vanhaeren, M. (2020). Quantitative methods demonstrate that environment alone is an insufficient predictor of present-day language distributions in New Guinea. PLoS One, 15(10): e0239359. Retrieved from https://doi.org/10.1371/journal.pone.0239359.

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https://doi.org/10.1371/journal.pone.0239359.s001 (Supplementary material)
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S1 Fig. Eco-Linguistic Niches (ELNs) of New Guinea language groups
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https://doi.org/10.1371/journal.pone.0239359.s002 (Supplementary material)
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S1 File. Supplementary texts 1–2 and tables 1–6 Text 1.
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https://doi.org/10.1371/journal.pone.0239359.s003 (Supplementary material)
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S2 File. ELNM–Variable correlations: Should correlated environmental variables be excluded from the ELN estimation process for New Guinea (NG)?
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 Creators:
Antunes, Nicolas1, Author           
Schiefenhövel, Wulf, Author
d’Errico, Francesco, Author
Banks, William E., Author
Vanhaeren, Marian, Author
Affiliations:
1Archaeogenetics, Max Planck Institute for the Science of Human History, Max Planck Society, ou_2074310              

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Free keywords: Language, Language families, Ecological niches, Linguistic geography, Geographic distribution, Islands, Environmental geography, Cartography
 Abstract: Environmental parameters constrain the distributions of plant and animal species. A key question is to what extent does environment influence human behavior. Decreasing linguistic diversity from the equator towards the poles suggests that ecological factors influence linguistic geography. However, attempts to quantify the role of environmental factors in shaping linguistic diversity remain inconclusive. To this end, we apply Ecological Niche Modelling methods to present-day language diversity in New Guinea. We define an Eco-Linguistic Niche (ELN) as the range of environmental conditions present in the territory of a population speaking a specific language or group of languages characterized by common language traits. In order to reconstruct the ELNs, we used Papuan and Austronesian language groups, transformed their geographical distributions into occurrence data, assembled available environmental data for New Guinea, and applied predictive architectures developed in the field of ecology to these data. We find no clear relationship between linguistic diversity and ELNs. This is particularly true when linguistic diversity is examined at the level of language groups. Language groups are variably dependent on environment and generally share their ELN with other language groups. This variability suggests that population dynamics, migration, linguistic drift, and socio-cultural mechanisms must be taken into consideration in order to better understand the myriad factors that shape language diversity.

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Language(s): eng - English
 Dates: 2020-10-072020-10
 Publication Status: Issued
 Pages: 27
 Publishing info: -
 Table of Contents: Introduction
Results
- Geographic distribution of Eco-Linguistic Niches (ELNs)
- Ecological space positions of ELNs
- Eco-Linguistic Patterns (ELPs)
- ELPs and language diversity
- ELNs and ecological risk
- ELNs and environmental suitability
Discussion
- Does environment determine the extent of linguistic areas?
- Does environment determine linguistic diversity?
- Did environment determine the expansion of language families in NG?
Conclusion
Materials and methods
- Predictive algorithms
- Linguistic data occurrences
- Geographical extent
- Environmental data
- Climate data
- Topographic data
- Prediction reliability improvement
- Statistical analysis and characterisation of Eco-Linguistic Niches (ELNs)
- Eco-linguistic potential calculation
- Ecological risk calculation
 Rev. Type: -
 Degree: -

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Title: PLoS One
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 15 (10) Sequence Number: e0239359 Start / End Page: - Identifier: ISSN: 1932-6203
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000277850