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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. [ABSTRACT FROM AUTHOR]

Human societies exhibit a diversity of social organizations that vary widely in size, structure, and complexity. Today, human sociopolitical complexity ranges from stateless small-scale societies of a few hundred individuals to complex states of millions, most of this diversity evolving only over the last few hundred years. Understanding how sociopolitical complexity evolved over time and space has always been a central focus of the social sciences. Yet despite this long-term interest, a quantitative understanding of how sociopolitical complexity varies across cultures is not well developed. Here we use scaling analysis to examine the statistical structure of a global sample of over a thousand human societies across multiple levels of sociopolitical complexity. First, we show that levels of sociopolitical complexity are self-similar as adjacent levels of jurisdictional hierarchy see a four-fold increase in population size, a two-fold increase in geographic range, and therefore a doubling of population density. Second, we show how this self-similarity leads to the scaling of population size and geographic range. As societies increase in complexity population density is reconfigured in space and quantified by scaling parameters. However, there is considerable overlap in population metrics across all scales suggesting that while more complex societies tend to have larger and denser populations, larger and denser populations are not necessarily more complex. [ABSTRACT FROM AUTHOR]

The expansion of the human species out of Africa in the Pleistocene, and the subsequent development of agriculture in the Holocene, resulted in waves of linguistic diversification and replacement across the planet. Analogous to the growth of populations or the speciation of biological organisms, languages diversify over time to form phylogenies of language families. However, the dynamics of this diversification process are unclear. Bayesian methods applied to lexical and phonetic data have created dated linguistic phylogenies for 18 language families encompassing ~3,000 of the world’s ~7,000 extant languages. In this paper we use these phylogenies to quantify how fast languages expand and diversify through time both within and across language families. The overall diversification rate of languages in our sample is ~0.001 yr-1 (or a doubling time of ~700 yr) over the last 6,000 years with evidence for nonlinear dynamics in language diversification rates over time, where both within and across language families, diversity initially increases rapidly and then slows. The expansion, evolution, and diversification of languages as they spread around the planet was a non-constant process. [ABSTRACT FROM AUTHOR]

At least 50 indigenous groups spread across lowland South America remain isolated and have only intermittent and mostly hostile interactions with the outside world. Except in emergency situations, the current policy of governments in Brazil, Colombia, and Peru towards isolated tribes is a “leave them alone” strategy, in which isolated groups are left uncontacted. However, these no-contact policies are based on the assumption that isolated populations are healthy and capable of persisting in the face of mounting external threats, and that they can maintain population viability in the long-term. Here, we test this assumption by tracking the sizes and movements of cleared horticultural areas made by 8 isolated groups over the last 10–14 years. We used deforestation data derived from remote sensing Landsat satellite sensors to identify clearings, and those were then validated and assessed with high-resolution imagery. We found only a single example of a relatively large and growing population (c. 50 cleared ha and 400 people), whereas all of the other 7 groups exhibited much smaller villages and gardens with no sizable growth through time. These results indicated that the smaller groups are critically endangered, and it prompts an urgent re-thinking of policies toward isolated populations, including plans for well-organized contacts that may help save lives and rescue isolated indigenous populations from imminent extinction. [ABSTRACT FROM AUTHOR]

The headwaters of the Amazon Basin harbor most of the world’s last indigenous peoples who have limited contact with encroaching colonists. Knowledge of the geographic distribution of these isolated groups is essential to assist with the development of immediate protections for vulnerable indigenous settlements. We used remote sensing to document the locations of 28 isolated villages within the four Brazilian states of Acre, Amazonas, Roraima, and Rondônia. The sites were confirmed during previous over-flights and by image evidence of thatched-roof houses; they are estimated to host over 1,700 individuals. Locational data were used to train maximum entropy models that identified landscape and anthropogenic features associated with the occurrence of isolated indigenous villages, including elevation, proximity to streams of five different orders, proximity to roads and settlements, proximity to recent deforestation, and vegetation cover type. Isolated villages were identified at mid elevations, within 20 km of the tops of watersheds and at greater distances from existing roads and trails. We further used model results, combined with boundaries of the existing indigenous territory system that is designed to protect indigenous lands, to assess the efficacy of the existing protected area network for isolated peoples. Results indicate that existing indigenous territories encompass all of the villages we identified, and 50% of the areas with high predicted probabilities of isolated village occurrence. Our results are intended to help inform policies that can mitigate against future external threats to isolated peoples. [ABSTRACT FROM AUTHOR]