Finger millet, pearl millet, and sorghum are important drought-tolerant crops used as primary staple crops in drylands. Despite their long history, they have received less attention in recent years and their production has decreased. New models show that annual precipitation is not the only factor affecting their agriculture, but other variables like growing cycle duration, soil water-holding capacity, and soil nutrient availability also play a crucial role, as evidenced by ethnographic data. The traditional cultivation practices of these crops can be a sustainable response to the increasing aridity levels worldwide and can contribute to the resilience of dryland agriculture.

Finger millet, pearl millet, and sorghum are important drought-tolerant crops used as primary staple crops in drylands. Despite their long history, they have received less attention in recent years and their production has decreased. New models show that annual precipitation is not the only factor affecting their agriculture, but other variables like growing cycle duration, soil water-holding capacity, and soil nutrient availability also play a crucial role, as evidenced by ethnographic data. The traditional cultivation practices of these crops can be a sustainable response to the increasing aridity levels worldwide and can contribute to the resilience of dryland agriculture.

Finger millet, pearl millet, and sorghum are important drought-tolerant crops used as primary staple crops in drylands. Despite their long history, they have received less attention in recent years and their production has decreased. New models show that annual precipitation is not the only factor affecting their agriculture, but other variables like growing cycle duration, soil water-holding capacity, and soil nutrient availability also play a crucial role, as evidenced by ethnographic data. The traditional cultivation practices of these crops can be a sustainable response to the increasing aridity levels worldwide and can contribute to the resilience of dryland agriculture.

The second and third parts of this book classify the economic systems of foraging and agricultural societies in the SCCS based on correlations between their institutions of property an distribution. These economic types are then examined for relationships with other social, political, demographic, and environmental factors in order to draw tentative conclusions regarding the origins of the Agricultural and Industrial Revolutions. The fourth part of the book uses cross-national data to examine similar associations in industrial/service economies, and is not included here.

In this article, the authors seek to determine cross-culturally valid predictors of dominant types of human subsistence around the world. They did this by formulating multiple models that incorporate different combinations of environmental, geographic, and social factors. These models were then used to test various hypotheses posed throughout the anthropological literature surrounding factors that determine dominant subsistence strategies.

The authors investigate the relationship between linguistic diversity and various environmental and spatial variables associated with biodiversity. Most of these variables predict linguistic diversity variably across different continents, and more so within Africa and extended Asia (Asia, the Pacific, and Australia) than within Europe and the Americas. This divide is theorized to be a result of differences in demography and impact of colonialism between the two global regions. However, two environmental factors, landscape roughness and density of river systems, are found to be significant predictors across all global regions. The authors suggest that, as in processes of speciation, rough terrain and watercourses both create physical barriers between which languages can develop in isolation while, in the case of river junctions, also providing transportation routes whereby hybrid languages can occasionally manifest.

In this paper, the authors analyzed data on 20 hunter-gatherer groups in order to understand the factors that influence the diversity and elaborateness of their tool assemblages. They used data collected by a variety of ethnographers to draw inferences about the complexity of implement assemblages and how it is affected by ecological constraints, modes of resource procurement, group movement, and population size. Regression analysis showed that the two strongest predictors of implement complexity were growth season (GS) (as a proxy for risk) and the number of annual residential moves (NMV). With the understanding that NMV and GS are likely not independent, the authors created addition and interaction models to understand how these variables may work in tandem to influence implement diversity and elaborateness. The results show that a shorter growing season (higher risk) and a lower number of moves are correlated with greater implement complexity. This analysis also divided the hunter-gatherers into two subgroups: a subgroup characterized by higher diversity of complex implements and more elaborate individual implements than predicted by the model, and a subgroup characterized by lower diversity and less elaborateness than predicted. These subgroups were found to correspond with the distinction between foragers (groups that move more-or-less as a unit while gathering) and collectors (groups that gather (logistically from a more-or-less fixed settlement), with the higher diversity subgroup being made up mostly of collectors and the lower diversity subgroup being made up mostly of foragers. Finally, the authors suggest that under conditions where population growth leads to increased density, foraging strategies will tend to shift to collector strategies in conjunction with increased elaborateness of implements to exploit resources with greater intensity.

Prior research by Oswalt (1973, 1976) and Torrence (1983, 2001) has suggested that risk of resource failure is a significant predictor of toolkit complexity and diversity among hunter-gatherers. In this paper, the same relationship is tested among small-scale herding and farming groups. However, no significant correlation is discovered between any measure of resource risk and any measure of toolkit complexity. The researchers suggest that this absence may be the result of greater reliance on non-technological diversification methods among farmers (i.e. spatial diversification, mixed farming, intercropping), or of other unaccounted-for sources of risk (i.e. intergroup raiding and warfare).

Inter-group variation is greater in humans than in any other animal, and scholars continue to debate the cause of this diversity. Two competing explanatory models of human variation emphasize either (1) ecological differences and "evoked" culture or (2) population-level effects of cultural transmission. The former emphasizes mechanisms that operate within a single generation, while the latter emphasizes cumulative cultural history operating over many generations. To test these competing models, the authors measured the relative power of ecological variables as compared to culture history to predict behavioral variation in 172 western North American tribes. Culture history is subdivided into culture phylogeny (based on language phylogeny) and spatial distance.

Inter-group variation is greater in humans than in any other animal, and scholars continue to debate the cause of this diversity. Two competing explanatory models of human variation emphasize either (1) ecological differences and "evoked" culture or (2) population-level effects of cultural transmission. The former emphasizes mechanisms that operate within a single generation, while the latter emphasizes cumulative cultural history operating over many generations. To test these competing models, the authors measured the relative power of ecological variables as compared to culture history to predict behavioral variation in 172 western North American tribes. Culture history is subdivided into culture phylogeny (based on language phylogeny) and spatial distance.