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.

The ecological and evolutionary energetics of hunter-gatherer residential mobility.

Residential mobility is a key aspect of hunter-gatherer foraging economies and therefore is an issue of central importance in hunter-gatherer studies. Hunter-gatherers vary widely in annual rates of residential mobility. Understanding the sources of this variation has long been of interest to anthropologists and archeologists. The vast majority of hunter-gatherers who are dependent on terrestrial plants and animals move camp multiple times a year because local foraging patches become depleted and food, material, and social resources are heterogeneously distributed through time and space. In some environments, particularly along coasts, where resources are abundant and predictable, hunter-gatherers often become effectively sedentary. But even in these special cases, a central question is how these societies have maintained viable foraging economies while reducing residential mobility to near zero.

The macroecology of sustainability.

The discipline of sustainability science has emerged in response to concerns of natural and social scientists, policymakers, and lay people about whether the Earth can continue to support human population growth and economic prosperity. Yet, sustainability science has developed largely independently from and with little reference to key ecological principles that govern life on Earth. A macroecological perspective highlights three principles that should be integral to sustainability science: 1) physical conservation laws govern the flows of energy and materials between human systems and the environment, 2) smaller systems are connected by these flows to larger systems in which they are embedded, and 3) global constraints ultimately limit flows at smaller scales. Over the past few decades, decreasing per capita rates of consumption of petroleum, phosphate, agricultural land, fresh water, fish, and wood indicate that the growing human population has surpassed the capacity of the Earth to supply enough of these essential resources to sustain even the current population and level of socioeconomic development.

Drivers and hotspots of extinction risk in marine mammals.

The world's oceans are undergoing profound changes as a result of human activities. However, the consequences of escalating human impacts on marine mammal biodiversity remain poorly understood. The International Union for the Conservation of Nature (IUCN) identifies 25% of marine mammals as at risk of extinction, but the conservation status of nearly 40% of marine mammals remains unknown due to insufficient data. Predictive models of extinction risk are crucial to informing present and future conservation needs, yet such models have not been developed for marine mammals. In this paper, we: (i) used powerful machine-learning and spatial-modeling approaches to understand the intrinsic and extrinsic drivers of marine mammal extinction risk; (ii) used this information to predict risk across all marine mammals, including IUCN "Data Deficient" species; and (iii) conducted a spatially explicit assessment of these results to understand how risk is distributed across the world's oceans. Rate of offspring production was the most important predictor of risk. Additional predictors included taxonomic group, small geographic range area, and small social group size. Although the interaction of both intrinsic and extrinsic variables was important in predicting risk, overall, intrinsic traits were more important than extrinsic variables. In addition to the 32 species already on the IUCN Red List, our model identified 15 more species, suggesting that 37% of all marine mammals are at risk of extinction. Most at-risk species occur in coastal areas and in productive regions of the high seas. We identify 13 global hotspots of risk and show how they overlap with human impacts and Marine Protected Areas.

The maximum rate of mammal evolution.

How fast can a mammal evolve from the size of a mouse to the size of an elephant? Achieving such a large transformation calls for major biological reorganization. Thus, the speed at which this occurs has important implications for extensive faunal changes, including adaptive radiations and recovery from mass extinctions. To quantify the pace of large-scale evolution we developed a metric, clade maximum rate, which represents the maximum evolutionary rate of a trait within a clade. We applied this metric to body mass evolution in mammals over the last 70 million years, during which multiple large evolutionary transitions occurred in oceans and on continents and islands. Our computations suggest that it took a minimum of 1.6, 5.1, and 10 million generations for terrestrial mammal mass to increase 100-, and 1,000-, and 5,000-fold, respectively. Values for whales were down to half the length (i.e., 1.1, 3, and 5 million generations), perhaps due to the reduced mechanical constraints of living in an aquatic environment. When differences in generation time are considered, we find an exponential increase in maximum mammal body mass during the 35 million years following the Cretaceous-Paleogene (K-Pg) extinction event. Our results also indicate a basic asymmetry in macroevolution: very large decreases (such as extreme insular dwarfism) can happen at more than 10 times the rate of increases. Our findings allow more rigorous comparisons of microevolutionary and macroevolutionary patterns and processes.

Patterns of maximum body size evolution in Cenozoic land mammals: eco-evolutionary processes and abiotic forcing.

There is accumulating evidence that macroevolutionary patterns of mammal evolution during the Cenozoic follow similar trajectories on different continents. This would suggest that such patterns are strongly determined by global abiotic factors, such as climate, or by basic eco-evolutionary processes such as filling of niches by specialization. The similarity of pattern would be expected to extend to the history of individual clades. Here, we investigate the temporal distribution of maximum size observed within individual orders globally and on separate continents. While the maximum size of individual orders of large land mammals show differences and comprise several families, the times at which orders reach their maximum size over time show strong congruence, peaking in the Middle Eocene, the Oligocene and the Plio-Pleistocene. The Eocene peak occurs when global temperature and land mammal diversity are high and is best explained as a result of niche expansion rather than abiotic forcing. Since the Eocene, there is a significant correlation between maximum size frequency and global temperature proxy. The Oligocene peak is not statistically significant and may in part be due to sampling issues. The peak in the Plio-Pleistocene occurs when global temperature and land mammal diversity are low, it is statistically the most robust one and it is best explained by global cooling. We conclude that the macroevolutionary patterns observed are a result of the interplay between eco-evolutionary processes and abiotic forcing.

Amazonian societies on the brink of extinction.

OBJECTIVES: Greater Amazonia harbors as many as 100 locations of isolated indigenous peoples. Few options are available to assess the demographic health of these populations given their limited contact with the outside world. Remote sensing offers one option. METHODS: An isolated village in Brazil near the Peruvian border is visible with Google Earth imagery from 2006. The area of the fields and village, as well as the living area of the four longhouses, are measured and compared to population-by-area measurements for 71 other Brazilian indigenous communities. RESULTS: The estimated population of the village is no more than 40 people. A village as small as this one, if it has become disconnected from a metapopulation, risks imminent extinction if it has fallen below a minimum viable population size. CONCLUSIONS: An active remote surveillance program is urgently needed to track the movements and demographic health of isolated peoples in hopes of improving their dire chances for long-term survival. They need protected areas that are large enough to mitigate against external threats.

Macroecology Meets Macroeconomics: Resource Scarcity and Global Sustainability.

The current economic paradigm, which is based on increasing human population, economic development, and standard of living, is no longer compatible with the biophysical limits of the finite Earth. Failure to recover from the economic crash of 2008 is not due just to inadequate fiscal and monetary policies. The continuing global crisis is also due to scarcity of critical resources. Our macroecological studies highlight the role in the economy of energy and natural resources: oil, gas, water, arable land, metals, rare earths, fertilizers, fisheries, and wood. As the modern industrial technological-informational economy expanded in recent decades, it grew by consuming the Earth's natural resources at unsustainable rates. Correlations between per capita GDP and per capita consumption of energy and other resources across nations and over time demonstrate how economic growth and development depend on "nature's capital". Decades-long trends of decreasing per capita consumption of multiple important commodities indicate that overexploitation has created an unsustainable bubble of population and economy.

Effects of allometry, productivity and lifestyle on rates and limits of body size evolution.

Body size affects nearly all aspects of organismal biology, so it is important to understand the constraints and dynamics of body size evolution. Despite empirical work on the macroevolution and macroecology of minimum and maximum size, there is little general quantitative theory on rates and limits of body size evolution. We present a general theory that integrates individual productivity, the lifestyle component of the slow-fast life-history continuum, and the allometric scaling of generation time to predict a clade's evolutionary rate and asymptotic maximum body size, and the shape of macroevolutionary trajectories during diversifying phases of size evolution. We evaluate this theory using data on the evolution of clade maximum body sizes in mammals during the Cenozoic. As predicted, clade evolutionary rates and asymptotic maximum sizes are larger in more productive clades (e.g. baleen whales), which represent the fast end of the slow-fast lifestyle continuum, and smaller in less productive clades (e.g. primates). The allometric scaling exponent for generation time fundamentally alters the shape of evolutionary trajectories, so allometric effects should be accounted for in models of phenotypic evolution and interpretations of macroevolutionary body size patterns. This work highlights the intimate interplay between the macroecological and macroevolutionary dynamics underlying the generation and maintenance of morphological diversity.

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.

Predicting the geographic distribution of ancient Amazonian archaeological sites with machine learning.

Amazonia has as least two major centers of ancient human social complexity, but the full geographic extents of these centers remain uncertain. Across the southern rim of Amazonia, over 1,000 earthwork sites comprised of fortified settlements, mound villages, and ditched enclosures with geometric designs known as geoglyphs have been discovered. Qualitatively distinct and densely located along the lower stretches of major river systems and the Atlantic coast are Amazonian Dark Earth sites (ADEs) with deep anthropogenic soils enriched by long-term human habitation. Models predicting the geographic extents of earthworks and ADEs can assist in their discovery and preservation and help answer questions about the full degree of indigenous landscape modifications across Amazonia. We classify earthworks versus ADEs versus other non-earthwork/non-ADE archaeological sites with multi-class machine learning algorithms using soils, climate, and distances to rivers of different types and sizes as geospatial predictors. Model testing is done with spatial cross-validation, and the best model at the optimal spatial scale of 1 km has an Area Under the Curve of 0.91. Our predictive model has led to the discovery of 13 new geoglyphs, and it pinpoints specific areas with high probabilities of undiscovered archaeological sites that are currently hidden by rainforests. The limited, albeit impressive, predicted extents of earthworks and ADEs means that other non-ADE/non-earthwork sites are expected to predominate most of Western and Northern Amazonia.

Multiple ecological pathways to extinction in mammals.

As human population and resource demands continue to grow, biodiversity conservation has never been more critical. About one-quarter of all mammals are in danger of extinction, and more than half of all mammal populations are in decline. A major priority for conservation science is to understand the ecological traits that predict extinction risk and the interactions among those predictors that make certain species more vulnerable than others. Here, using a new database of nearly 4,500 mammal species, we use decision-tree models to quantify the multiple interacting factors associated with extinction risk. We show that the correlates of extinction risk vary widely across mammals and that there are unique pathways to extinction for species with different lifestyles and combinations of traits. We find that risk is relative and that all kinds of mammals, across all body sizes, can be at risk depending on their specific ecologies. Our results increase the understanding of extinction processes, generate simple rules of thumb that identify species at greatest risk, and highlight the potential of decision-tree analyses to inform conservation efforts.

Population stability, cooperation, and the invasibility of the human species.

The biogeographic expansion of modern humans out of Africa began approximately 50,000 years ago. This expansion resulted in the colonization of most of the land area and habitats throughout the globe and in the replacement of preexisting hominid species. However, such rapid population growth and geographic spread is somewhat unexpected for a large primate with a slow, density-dependent life history. Here, we suggest a mechanism for these outcomes by modifying a simple density-dependent population model to allow varying levels of intraspecific competition for finite resources. Reducing intraspecific competition increases carrying capacities, growth rates, and stability, including persistence times and speed of recovery from perturbations. Our model suggests that the energetic benefits of cooperation in modern humans may have outweighed the slow rate of human population growth, effectively ensuring that once modern humans colonized a region long-term population persistence was near inevitable. Our model also provides insight into the interplay of structural complexity and stability in social species.

Understanding hunter-gatherer cultural evolution needs network thinking.

Hunter-gatherers past and present live in complex societies, and the structure of these can be assessed using social networks. We outline how the integration of new evidence from cultural evolution experiments, computer simulations, ethnography, and archaeology open new research horizons to understand the role of social networks in cultural evolution.

Social complexity and linguistic diversity in the Austronesian and Bantu population expansions.

Reconstructing the rise and fall of social complexity in human societies through time is fundamental for understanding some of the most important transformations in human history. Phylogenetic methods based on language diversity provide a means to reconstruct pre-historic events and model the transition rates of cultural change through time. We model and compare the evolution of social complexity in Austronesian (n = 88) and Bantu (n = 89) societies, two of the world's largest language families with societies representing a wide spectrum of social complexity. Our results show that in both language families, social complexity tends to build and decline in an incremental fashion, while the Austronesian phylogeny provides evidence for additional severe demographic bottlenecks. We suggest that the greater linguistic diversity of the Austronesian language family than Bantu likely follows the different biogeographic structure of the two regions. Cultural evolution in both the Bantu and Austronesian cases was not a simple linear process, but more of a wave-like process closely tied to the demography of expanding populations and the spatial structure of the colonized regions.

Universal scaling of production rates across mammalian lineages.

Over many millions of years of independent evolution, placental, marsupial and monotreme mammals have diverged conspicuously in physiology, life history and reproductive ecology. The differences in life histories are particularly striking. Compared with placentals, marsupials exhibit shorter pregnancy, smaller size of offspring at birth and longer period of lactation in the pouch. Monotremes also exhibit short pregnancy, but incubate embryos in eggs, followed by a long period of post-hatching lactation. Using a large sample of mammalian species, we show that, remarkably, despite their very different life histories, the scaling of production rates is statistically indistinguishable across mammalian lineages. Apparently all mammals are subject to the same fundamental metabolic constraints on productivity, because they share similar body designs, vascular systems and costs of producing new tissue.

Lifetime reproductive effort in humans.

Lifetime reproductive effort (LRE) measures the total amount of metabolized energy diverted to reproduction during the lifespan. LRE captures key components of the life history and is particularly useful for describing and comparing the life histories of different organisms. Given a simple energetic production constraint, LRE is predicted to be similar in value for very different life histories. However, humans have some unique ecological characteristics that may alter LRE, such as the long post-reproductive lifespan, lengthy juvenile period and the cooperative nature of human foraging and reproduction. We calculate LRE for natural fertility human populations, compare the findings to other mammals and discuss the implications for human life-history evolution. We find that human life-history traits combine to yield the theoretically predicted value (approx. 1.4). Thus, even with the subsidized energy budget and uniqueness of the adult lifespan, human reproductive strategies converge on the same optimal value of LRE. This suggests that the fundamental demographic variables contained in LRE trade-off against one another in a predictable and highly constrained manner.

Diversity begets diversity in mammal species and human cultures.

Across the planet the biogeographic distribution of human cultural diversity tends to correlate positively with biodiversity. In this paper we focus on the biogeographic distribution of mammal species and human cultural diversity. We show that not only are these forms of diversity similarly distributed in space, but they both scale superlinearly with environmental production. We develop theory that explains that as environmental productivity increases the ecological kinetics of diversity increases faster than expected because more complex environments are also more interactive. Using biogeographic databases of the global distributions of mammal species and human cultures we test a series of hypotheses derived from this theory and find support for each. For both mammals and cultures, we show that (1) both forms of diversity increase exponentially with ecological kinetics; (2) the kinetics of diversity is faster than the kinetics of productivity; (3) diversity scales superlinearly with environmental productivity; and (4) the kinetics of diversity is faster in increasingly productive environments. This biogeographic convergence is particularly striking because while the dynamics of biological and cultural evolution may be similar in principle the underlying mechanisms and time scales are very different. However, a common currency underlying all forms of diversity is ecological kinetics; the temperature-dependent fluxes of energy and biotic interactions that sustain all forms of life at all levels of organization. Diversity begets diversity in mammal species and human cultures because ecological kinetics drives superlinear scaling with environmental productivity.

Scaling human sociopolitical complexity.

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.

The interpretation of urban scaling analysis in time.

Scaling is a general analytical framework used by many disciplines-from physics to biology and the social sciences-to characterize how population-averaged properties of a collective vary with its size. The observation of scale invariance over some range identifies general system types, be they ideal gases, ecosystems or cities. The use of scaling in the analysis of cities quantifies many of their arguably fundamental general characteristics, especially their capacity to create interrelated economies of scale in infrastructure and increasing returns to scale in socio-economic activities. However, the measurement of these effects, and the relationship of observable parameters to theory, hinge on how scaling analysis is used empirically. Here, we show how two equivalent approaches to urban scaling-cross-sectional and temporal-lead to the measurement of different mixtures of the same fundamental parameters describing pure scale and pure temporal phenomena. Specifically, temporal exponents are sensitive to the intensive growth of urban quantities and to circumstances when population growth vanishes, leading to instabilities and infinite divergences. These spurious effects are avoided in cross-sectional scaling, which is more common and closer to theory in terms of quantitative testable expectations for its parameters.