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The island biogeography of languages

Authors

  • Michael C. Gavin,

    Corresponding author
    1. Human Dimensions of Natural Resources Department, Colorado State University, Fort Collins, Colorado 80573 USA
    2. School of Geography, Environment and Earth Sciences, Victoria University of Wellington, PO Box 600, Wellington 6140, New Zealand
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  • Nokuthaba Sibanda

    1. School of Mathematics, Statistics and Operations Research, Victoria University of Wellington, PO Box 600, Wellington 6140, New Zealand
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Michael C. Gavin, Human Dimensions of Natural Resources Department, Colorado State University, Fort Collins, Colorado 80573 USA. E-mail: michael.gavin@vuw.ac.nz

ABSTRACT

Aim  To examine the degree to which area, isolation, environmental conditions and time since first settlement explain variation in language richness among islands.

Location  Pacific islands ranging east–west from Rapa Nui to Indonesia and north–south from Hawaii to New Zealand.

Methods  We constructed a dataset of 264 Pacific islands that support 1640 languages (c. 24% of the world's languages). We examined possible predictors of language richness using three different types of models: linear regression models, linear mixed models that included random effects for language phylogeny and simultaneous autoregressive models. We tested whether the following variables, alone or in combination, predict language richness: island area and isolation, climate (rainfall, temperature), mean growing season, soil fertility, habitat heterogeneity (elevation, number of ecoregions), time since first human settlement.

Results  We identified two optimal models (delta Akaike information criterion < 2). One (R2= 0.52) included area, with 86% of remaining variation accounted for by random effects for phylogeny. The other (R2= 0.56) included a spatial component, area and a suite of other variables (of which isolation and settlement scale were significant). Of the hypotheses tested (mean growing season, ecological risk, habitat heterogeneity, climate, time since settlement, area–isolation theory), area–isolation performed best, alone explaining 44% of variation in language richness.

Main conclusions  Language diversity relates strongly to island area, and, after controlling for area, with variables linked to isolation (e.g. distance to continent, time since settlement). The influence of environmental productivity may be scale and context dependent. Although environmental productivity may shape language diversity patterns at a global scale, it plays little role on Pacific islands. Approximately half the variance in language richness remains unexplained. Unlike other taxa, for which area, isolation and environmental conditions explain up to 90% of variation in richness, human diversity patterns appear to also be influenced by other variables (e.g. economic, political and social factors).

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