Using a representative sample of 339 hunter-gatherer societies, researchers examine the relationship between hunter-gatherer use of space, size of population and supply of resources to see if they are similar to other organisms. By combining all factors into a single model, the authors claim to explain 86% of the variation in home range. Hunters have greater resource distribution than gatherers but both more so than aquatic foragers. Lastly, terrestrial foragers have more extensive home ranges than aquatic foragers.

Using a representative sample of 339 hunter-gatherer societies, researchers examine the relationship between hunter-gatherer use of space, size of population and supply of resources to see if they are similar to other organisms. By combining all factors into a single model, the authors claim to explain 86% of the variation in home range. Hunters have greater resource distribution than gatherers but both more so than aquatic foragers. Lastly, terrestrial foragers have more extensive home ranges than aquatic foragers.

Using a representative sample of 339 hunter-gatherer societies, researchers examine the relationship between hunter-gatherer use of space, size of population and supply of resources to see if they are similar to other organisms. By combining all factors into a single model, the authors claim to explain 86% of the variation in home range. Hunters have greater resource distribution than gatherers but both more so than aquatic foragers. Lastly, terrestrial foragers have more extensive home ranges than aquatic foragers.

Using a representative sample of 339 hunter-gatherer societies, researchers examine the relationship between hunter-gatherer use of space, size of population and supply of resources to see if they are similar to other organisms. By combining all factors into a single model, the authors claim to explain 86% of the variation in home range. Hunters have greater resource distribution than gatherers but both more so than aquatic foragers. Lastly, terrestrial foragers have more extensive home ranges than aquatic foragers.

Using a representative sample of 339 hunter-gatherer societies, researchers examine the relationship between hunter-gatherer use of space, size of population and supply of resources to see if they are similar to other organisms. By combining all factors into a single model, the authors claim to explain 86% of the variation in home range. Hunters have greater resource distribution than gatherers but both more so than aquatic foragers. Lastly, terrestrial foragers have more extensive home ranges than aquatic foragers.

The capacity for cumulative cultural evolution has often been invoked to explain the great diversity of habitats occupied by humans. This theory of cultural evolution emphasizes the gradual accumulation of technologies and cultural practices over many generations, and predicts that larger populations will generate more complex cultural adaptations than smaller, isolated ones. Here, the authors investigate the marine foraging tool repertoires of 10 Oceanic societies to determine whether population size and intergroup contact affect the cultural processes by which tool kits evolve.

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.

The capacity for cumulative cultural evolution has often been invoked to explain the great diversity of habitats occupied by humans. This theory of cultural evolution emphasizes the gradual accumulation of technologies and cultural practices over many generations, and predicts that larger populations will generate more complex cultural adaptations than smaller, isolated ones. Here, the authors investigate the marine foraging tool repertoires of 10 Oceanic societies to determine whether population size and intergroup contact affect the cultural processes by which tool kits evolve.

This paper builds off previous research into the effect of population size and resource risk on complexity of subsistence technology by investigating the relationship between these independent variables and total number of material items and techniques used by various western North American hunter-gatherer groups. This tally of total technological complexity is found to be insignificantly related to population size or residential mobility; however, there is a significant correlation in the expected direction between technological complexity and one measure of resource risk (mean annual temperature during driest month). Tying this finding to previous analyses of subsistence technologies, the authors theorize that environmental risk is a pervasive driver of technological ingenuity and cultural evolution.

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.