Found 2108 Hypotheses across 211 Pages (0.006 seconds)
  1. Topographic complexity will be a predictor of language diversity in North America.Cuelho, Mario Tulio Pacheco - Drivers of geographical patterns of North American language diversity, 2019 - 2 Variables

    The authors examine multiple ecological variables as possible predictors of language diversity in North America using path analysis, mechanistic simulation modelling, and geographically weighted regression. They conclude that many of the variables do not predict language diversity, but rather are mediated by population density. The authors also find that the variables' ability to predict is not universal across the continent, but rather more regional.

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  2. River density, ecoregion richness, topographic complexity, climate change velocity, precipitation constancy, and temperature constancy all help explain variation in population density.Cuelho, Mario Tulio Pacheco - Drivers of geographical patterns of North American language diversity, 2019 - 7 Variables

    The authors examine multiple ecological variables as possible predictors of language diversity in North America using path analysis, mechanistic simulation modelling, and geographically weighted regression. They conclude that many of the variables do not predict language diversity, but rather are mediated by population density. The authors also find that the variables' ability to predict is not universal across the continent, but rather more regional.

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  3. Ecoregion richness will be a predictor of language diversity in North America.Cuelho, Mario Tulio Pacheco - Drivers of geographical patterns of North American language diversity, 2019 - 2 Variables

    The authors examine multiple ecological variables as possible predictors of language diversity in North America using path analysis, mechanistic simulation modelling, and geographically weighted regression. They conclude that many of the variables do not predict language diversity, but rather are mediated by population density. The authors also find that the variables' ability to predict is not universal across the continent, but rather more regional.

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  4. Climate change velocity will be a predictor of language diversity in North America.Cuelho, Mario Tulio Pacheco - Drivers of geographical patterns of North American language diversity, 2019 - 2 Variables

    The authors examine multiple ecological variables as possible predictors of language diversity in North America using path analysis, mechanistic simulation modelling, and geographically weighted regression. They conclude that many of the variables do not predict language diversity, but rather are mediated by population density. The authors also find that the variables' ability to predict is not universal across the continent, but rather more regional.

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  5. Precipitation constancy will be a predictor of language diversity in North America.Cuelho, Mario Tulio Pacheco - Drivers of geographical patterns of North American language diversity, 2019 - 2 Variables

    The authors examine multiple ecological variables as possible predictors of language diversity in North America using path analysis, mechanistic simulation modelling, and geographically weighted regression. They conclude that many of the variables do not predict language diversity, but rather are mediated by population density. The authors also find that the variables' ability to predict is not universal across the continent, but rather more regional.

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  6. Population density will be a predictor of language diversity in North America.Cuelho, Mario Tulio Pacheco - Drivers of geographical patterns of North American language diversity, 2019 - 2 Variables

    The authors examine multiple ecological variables as possible predictors of language diversity in North America using path analysis, mechanistic simulation modelling, and geographically weighted regression. They conclude that many of the variables do not predict language diversity, but rather are mediated by population density. The authors also find that the variables' ability to predict is not universal across the continent, but rather more regional.

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  7. Carrying capacity with group size limits will be a predictor of language diversity in North America.Cuelho, Mario Tulio Pacheco - Drivers of geographical patterns of North American language diversity, 2019 - 2 Variables

    The authors examine multiple ecological variables as possible predictors of language diversity in North America using path analysis, mechanistic simulation modelling, and geographically weighted regression. They conclude that many of the variables do not predict language diversity, but rather are mediated by population density. The authors also find that the variables' ability to predict is not universal across the continent, but rather more regional.

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  8. Ecoregion richness is positively associated with language diversity, which implies that resource partitioning may contribute to language diversification (4).Coelho, Marco Túlio Pacheco - Drivers of geographical patterns of North American language diversity, 2019 - 2 Variables

    Researchers investigated further into why and how humans speak so many languages across the globe, and why they are spread out unevenly. Using two different path analyses, a Stationary Path analysis and a GWPath, researchers tested the effect of eight different factors on language diversity. Out of the eight variables (river density, topographic complexity, ecoregion richness, temperature and precipitation constancy, climate change velocity, population density, and carrying capacity with group size limits), population density, carrying capacity with group size limit, and ecoregion richness had the strongest direct effects. Overall, the study revealed the role of multiple different mechanisms in shaping language richness patterns. The GWPath showed that not only does the most important predictor of language diversity vary over space, but predictors can also vary in the direction of their effects in different regions. They conclude that there is no universal predictor of language richness.

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  9. A larger number of individuals (greater population density) is positively correlated with a greater accumulation of languages (greater language diversity) (3).Coelho, Marco Túlio Pacheco - Drivers of geographical patterns of North American language diversity, 2019 - 2 Variables

    Researchers investigated further into why and how humans speak so many languages across the globe, and why they are spread out unevenly. Using two different path analyses, a Stationary Path analysis and a GWPath, researchers tested the effect of eight different factors on language diversity. Out of the eight variables (river density, topographic complexity, ecoregion richness, temperature and precipitation constancy, climate change velocity, population density, and carrying capacity with group size limits), population density, carrying capacity with group size limit, and ecoregion richness had the strongest direct effects. Overall, the study revealed the role of multiple different mechanisms in shaping language richness patterns. The GWPath showed that not only does the most important predictor of language diversity vary over space, but predictors can also vary in the direction of their effects in different regions. They conclude that there is no universal predictor of language richness.

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  10. Higher potential carrying capacity with limits on group size is positively correlated with greater language diversity (4).Coelho, Marco Túlio Pacheco - Drivers of geographical patterns of North American language diversity, 2019 - 2 Variables

    Researchers investigated further into why and how humans speak so many languages across the globe, and why they are spread out unevenly. Using two different path analyses, a Stationary Path analysis and a GWPath, researchers tested the effect of eight different factors on language diversity. Out of the eight variables (river density, topographic complexity, ecoregion richness, temperature and precipitation constancy, climate change velocity, population density, and carrying capacity with group size limits), population density, carrying capacity with group size limit, and ecoregion richness had the strongest direct effects. Overall, the study revealed the role of multiple different mechanisms in shaping language richness patterns. The GWPath showed that not only does the most important predictor of language diversity vary over space, but predictors can also vary in the direction of their effects in different regions. They conclude that there is no universal predictor of language richness.

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