Institutional complexity emerges from socioecological complexity in small-scale human societies.

Human lifestyles vary enormously over time and space and so understanding the origins of this diversity has always been a central focus of anthropology. A major source of this cultural variation is the variation in institutional complexity: the cultural packages of rules, norms, ontologies and expectations passed down through societies across generations. In this article, we study the emergence of institutions in small-scale societies. There are two primary schools of thought. The first is that institutions emerge top-down as rules are imposed by elites on their societies in order to gain asymmetrical access to power, resources and influence over others through coercion. The second is that institutions emerge bottom-up to facilitate interactions within populations as they seek collective solutions to adaptive problems. Here, we use Bayesian networks to infer the causal structure of institutional complexity in 172 small-scale societies across ethnohistoric western North America reflecting the wide diversity of indigenous lifestyles across this vast region immediately prior to European colonization. Our results suggest that institutional complexity emerges from underlying socioecological complexity because institutions are solutions to coordination problems in more complex environments where human-environment interactions require increased management.

Effects of Voice Pitch on Social Perceptions Vary With Relational Mobility and Homicide Rate.

Fundamental frequency ( fo) is the most perceptually salient vocal acoustic parameter, yet little is known about how its perceptual influence varies across societies. We examined how fo affects key social perceptions and how socioecological variables modulate these effects in 2,647 adult listeners sampled from 44 locations across 22 nations. Low male fo increased men's perceptions of formidability and prestige, especially in societies with higher homicide rates and greater relational mobility in which male intrasexual competition may be more intense and rapid identification of high-status competitors may be exigent. High female fo increased women's perceptions of flirtatiousness where relational mobility was lower and threats to mating relationships may be greater. These results indicate that the influence of fo on social perceptions depends on socioecological variables, including those related to competition for status and mates.

Modeling the social drivers of environmental sustainability among Amazonian indigenous lands using Bayesian networks.

Amazonia is an invaluable global asset for all its ecological and cultural significance. Indigenous peoples and their lands are pivotal in safeguarding this unique biodiversity and mitigating global climate change. Understanding the causal structure behind variation in the degree of environmental conservation across different indigenous lands-each with varying institutional, legal, and socioenvironmental conditions-is an essential source of information in the struggle for long-term sustainable management of Amazonian ecosystems. Here, we use data from the Instituto Socioambiental for 361 indigenous lands in the Brazilian Amazon coded for environmental integrity, territorial integrity, legal stability, indigenous governance, and threats due to infrastructure projects. Using Bayesian networks to learn the causal structure amongst these variables reveals two causal pathways leading to environmental integrity. One causal pathway starts with territorial integrity and is mediated by infrastructure projects, while the other is directly from legal stability. Hence, safeguarding indigenous lands from exploitation is best accomplished via legal land rights and stricter enforcement instead of placing the onus on indigenous governance, which is also a direct outcome of legal stability.

Bullet ricochet mark plan-view morphology in concrete: an experimental assessment of five bullet types and two distances using machine learning.

Bullet ricochets are common occurrences during shooting incidents and can provide a wealth of information useful for shooting incident reconstruction. However, there have only been a small number of studies that have systematically investigated bullet ricochet impact site morphology. Here, this study reports on an experiment that examined the plan-view morphology of 297 ricochet impact sites in concrete that were produced by five different bullet types shot from two distances. This study used a random forest machine learning algorithm to classify bullet types with morphological dimensions of the ricochet mark (impact) with length and perimeter-to-area ratio emerging as the top predictor variables. The 0.22 LR leaves the most distinctive impact mark on the concrete, and overall, the classification accuracy using leave-one-out cross-validation is 62%, considerably higher than a random classification accuracy of 20%. Adding in distance to the model as a predictor increases the classification accuracy to 66%. These initial results are promising, in that they suggest that an unknown bullet type can potentially be determined, or at least probabilistically assessed, from the morphology of the ricochet impact site alone. However, the substantial amount of overlap this study documented among distinct bullet types' ricochet mark morphologies under highly controlled conditions and with machine learning suggests that the human identification of ricochet marks in real-world shooting incident reconstructions may be on occasion, or perhaps regularly, in error. Key points: Bullet ricochet impact sites can help with shooting incident reconstruction.A random forest machine learning algorithm classified bullet type from ricochet morphology.Results suggest that unknown bullets can potentially be determined from ricochet impact site morphology.Human identification of bullet types from ricochet sites may be erroneous.

Remote sensing evidence for population growth of isolated indigenous societies in Amazonia.

Isolated indigenous societies who actively avoid sustained peaceful contact with the outside world are critically endangered. Last year, "Tanaru", the lone surviving man of his tribe for at least 35 years, died in Southwest Amazonia, marking the latest cultural extinction event in a long history of massacres, enslavement, and epidemics. Yet in the upper reaches of the Amazon Basin, dozens of resilient isolated tribes still manage to survive. Remote sensing is a reliable method of monitoring the population dynamics of uncontacted populations by quantifying the area cleared for gardens and villages, along with the fire detections associated with the burning of those clearings. Remote sensing also provides a method to document the number of residential structures and village fissioning. Only with these longitudinal assessments can we better evaluate the current no-contact policies by the United Nations and governments, along with the prospects for the long-term survival of isolated tribes. While the world's largest isolated indigenous metapopulation, Pano speakers in Acre, Brazil, appears to be thriving, other smaller isolated populations disconnected from metapopulations continue to be extremely vulnerable to external threats. Our applied anthropological conservation approach is to provide analyses of publicly available remote sensing datasets to help inform policies that enhance the survival and well-being of isolated cultural groups.