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Aim: Land ownership norms are well documented and play a central role in social–ecological systems. Yet only recently has the spatial and temporal distribution of land ownership been examined using biogeographical and evolutionary approaches. We incorporate biogeographical and evolutionary modelling to test associations between land ownership and environmental, subsistence and cultural contact predictors. Location: Africa. Taxon: Bantu and Bantoid ethnolinguistic groups (73 societies). Methods: Based on ethnographies for 73 societies, we coded land ownership norms as none, group, kin or individual. We paired these data with language phylogenies, and measured phylogenetic and geographical signal and modelled alternative evolutionary trajectories using maximum likelihood methods. We tested the influence of environmental, subsistence and cultural predictors on spatial variation in land ownership, using a multi‐model inference approach based on logistic regression. Results: Bantu land ownership norms likely evolved on a unilinear trajectory (i.e. societies progress or regress along a series of ownership types), but not one requiring consistent increase in exclusivity (i.e. restrictions towards ownership by smaller groups) as suggested by prior theory. Our biogeographical analyses suggest land ownership is more likely where neighbours also own land and resource productivity is predictable. Reliance on agriculture has relatively small effect sizes and low importance in the model. Main Conclusions: We find support for multiple evolutionary pathways. Lack of resolution may be due to localized horizontal transfer of norms consistent with the influence of neighbours we find from biogeographical analyses. We cannot rule out other untested mechanisms. Although long‐standing theories propose links between subsistence practices and land ownership, our results suggest subsistence plays only a modest role. Our results also support resource defensibility theory (i.e. land ownership is more likely where environmental productivity is predictable). Overall, we demonstrate the value of combining analytical approaches from evolution and biogeography to test hypotheses on the spatial and temporal variation of human cultural traits. [ABSTRACT FROM AUTHOR]

The article presents a social science research study on the importance of genealogical constraints on linguistic diversity and the impact of language loss. Topics include the Grambank database, the largest comparative grammatical database, which allows for quantifying the effects of genealogical inheritance on the structural diversity of languages; and the roles of genealogy and geography in shaping grammatical diversity, highlighting ongoing debates in the field of linguistics.

The Uto-Aztecan language family is one of the largest language families in the Americas. However, there has been considerable debate about its origin and how it spread. Here we use Bayesian phylogenetic methods to analyze lexical data from thirty-four Uto-Aztecan varieties and two Kiowa-Tanoan languages. We infer the age of Proto-Uto-Aztecan to be around 4,100 years (3,258-5,025 years) and identify the most likely homeland to be near what is now Southern California. We reconstruct the most probable subsistence strategy in the ancestral Uto-Aztecan society and infer no casual or intensive cultivation, an absence of cereal crops, and a primary subsistence mode of gathering (rather than agriculture). Our results therefore support the timing, geography, and cultural practices of a northern origin and are inconsistent with alternative scenarios. [ABSTRACT FROM AUTHOR]

Land ownership shapes natural resource management and social–ecological resilience, but the factors determining ownership norms in human societies remain unclear. Here we conduct a global empirical test of long‐standing theories from ecology, economics and anthropology regarding potential drivers of land ownership and territoriality. Prior theory suggests that resource defensibility, subsistence strategies, population pressure, political complexity and cultural transmission mechanisms may all influence land ownership. We applied multi‐model inference procedures based on logistic regression to cultural and environmental data from 102 societies, 71 with some form of land ownership and 31 with no land ownership. We found an increased probability of land ownership in mountainous environments, where patchy resources may be more cost effective to defend via ownership. We also uncovered support for the role of population pressure, with a greater probability of land ownership in societies living at higher population densities. Our results also show more land ownership when neighboring societies also practiced ownership. We found less support for variables associated with subsistence strategies and political complexity. [ABSTRACT FROM AUTHOR]

The naming of colors has long been a topic of interest in the study of human culture and cognition. Color term research has asked diverse questions about thought and communication, but no previous research has used an evolutionary framework. We show that there is broad support for the most influential theory of color term development (most strongly represented by Berlin and Kay [Berlin B, Kay P (1969) (Univ of California Press, Berkeley, CA)]); however, we find extensive evidence for the loss (as well as gain) of color terms. We find alternative trajectories of color term evolution beyond those considered in the standard theories. These results not only refine our knowledge of how humans lexicalize the color space and how the systems change over time; they illustrate the promise of phylogenetic methods within the domain of cognitive science, and they show how language change interacts with human perception. [ABSTRACT FROM AUTHOR]

The article examines the linguistic niche hypothesis, which suggests that languages adapt to their environments based on factors like the number of native and nonnative speakers. It tests these claims using a global dataset of grammatical structures and analyzes the impact of sociodemographic factors on grammatical complexity.