Subsistence strategy mediates ecological drivers of human violence.

Inter-personal violence (whether intra- or inter-group) is a pervasive yet highly variable human behavior. Evolutionary anthropologists suggest that the abundance and distribution of resources play an important role in influencing differences in rates of violence, with implications for how resource conditions structure adaptive payoffs. Here, we assess whether differences in large-scale ecological conditions explain variability in levels of inter-personal human violence. Model results reveal a significant relationship between resource conditions and violence that is mediated by subsistence economy. Specifically, we find that interpersonal violence is highest: (1) among foragers and mixed forager/farmers (horticulturalists) in productive, homogeneous environments, and (2) among agriculturalists in unproductive, heterogeneous environments. We argue that the trend reversal between foragers and agriculturalists represents differing competitive pathways to enhanced reproductive success. These alternative pathways may be driven by features of subsistence (i.e., surplus, storage, mobility, privatization), in which foragers use violence to directly acquire fitness-linked social payoffs (i.e., status, mating opportunities, alliances), and agriculturalists use violence to acquire material resources that can be transformed into social payoffs. We suggest that as societies transition from immediate return economies (e.g., foragers) to delayed return economies (e.g., agriculturalists) material resources become an increasingly important adaptive payoff for inter-personal, especially inter-group, violence.

Climate change-induced population pressure drives high rates of lethal violence in the Prehispanic central Andes.

Understanding the influence of climate change and population pressure on human conflict remains a critically important topic in the social sciences. Long-term records that evaluate these dynamics across multiple centuries and outside the range of modern climatic variation are especially capable of elucidating the relative effect of­and the interaction between­climate and demography. This is crucial given that climate change may structure population growth and carrying capacity, while both climate and population influence per capita resource availability. This study couples paleoclimatic and demographic data with osteological evaluations of lethal trauma from 149 directly accelerator mass spectrometry 14C-dated individuals from the Nasca highland region of Peru. Multiple local and supraregional precipitation proxies are combined with a summed probability distribution of 149 14C dates to estimate population dynamics during a 700-y study window. Counter to previous findings, our analysis reveals a precipitous increase in violent deaths associated with a period of productive and stable climate, but volatile population dynamics. We conclude that favorable local climate conditions fostered population growth that put pressure on the marginal and highly circumscribed resource base, resulting in violent resource competition that manifested in over 450 y of internecine warfare. These findings help support a general theory of intergroup violence, indicating that relative resource scarcity­whether driven by reduced resource abundance or increased competition­can lead to violence in subsistence societies when the outcome is lower per capita resource availability.

Plant species richness at archaeological sites suggests ecological legacy of Indigenous subsistence on the Colorado Plateau.

Humans have both intentional and unintentional impacts on their environment, yet identifying the enduring ecological legacies of past small-scale societies remains difficult, and as such, evidence is sparse. The present study found evidence of an ecological legacy that persists today within an semiarid ecosystem of western North America. Specifically, the richness of ethnographically important plant species is strongly associated with archaeological complexity and ecological diversity at Puebloan sites in a region known as Bears Ears on the Colorado Plateau. A multivariate model including both environmental and archaeological predictors explains 88% of the variation in ethnographic species richness (ESR), with growing degree days and archaeological site complexity having the strongest effects. At least 31 plant species important to five tribal groups (Navajo, Hopi, Zuni, Ute Mountain Ute, and Apache), including the Four Corners potato (Solanum jamesii), goosefoot (Chenopodium sp.), wolfberry (Lycium pallidum), and sumac (Rhus trilobata), occurred at archaeological sites, despite being uncommon across the wider landscape. Our results reveal a clear ecological legacy of past human behavior: even when holding environmental variables constant, ESR increases significantly as a function of past investment in habitation and subsistence. Consequently, we suggest that propagules of some species were transported and cultivated, intentionally or not, establishing populations that persist to this day. Ensuring persistence will require tribal input for conserving and restoring archaeo-ecosystems containing "high-priority" plant species, especially those held sacred as lifeway medicines. This transdisciplinary approach has important implications for resource management planning, especially in areas such as Bears Ears that will experience greater visitation and associated impacts in the near future.

Advancing predictive modeling in archaeology: An evaluation of regression and machine learning methods on the Grand Staircase-Escalante National Monument.

Predictive models are central to both archaeological research and cultural resource management. Yet, archaeological applications of predictive models are often insufficient due to small training data sets, inadequate statistical techniques, and a lack of theoretical insight to explain the responses of past land use to predictor variables. Here we address these critiques and evaluate the predictive power of four statistical approaches widely used in ecological modeling-generalized linear models, generalized additive models, maximum entropy, and random forests-to predict the locations of Formative Period (2100-650 BP) archaeological sites in the Grand Staircase-Escalante National Monument. We assess each modeling approach using a threshold-independent measure, the area under the curve (AUC), and threshold-dependent measures, like the true skill statistic. We find that the majority of the modeling approaches struggle with archaeological datasets due to the frequent lack of true-absence locations, which violates model assumptions of generalized linear models, generalized additive models, and random forests, as well as measures of their predictive power (AUC). Maximum entropy is the only method tested here which is capable of utilizing pseudo-absence points (inferred absence data based on known presence data) and controlling for a non-representative sampling of the landscape, thus making maximum entropy the best modeling approach for common archaeological data when the goal is prediction. Regression-based approaches may be more applicable when prediction is not the goal, given their grounding in well-established statistical theory. Random forests, while the most powerful, is not applicable to archaeological data except in the rare case where true-absence data exist. Our results have significant implications for the application of predictive models by archaeologists for research and conservation purposes and highlight the importance of understanding model assumptions.

Marriage dynamics in old Lower California: ecological constraints and reproductive value in an arid peninsular frontier.

It is commonly expected that natural selection will favor earlier reproduction, yet ecological constraints can force people to delay marriage. Furthermore, humans demonstrate sex-specific preferences in marriage partners - with grooms normally a few years older than their brides; however, the age at which individuals marry can influence the spousal age gap. We investigate factors influencing age at first marriage and age difference at marriage using nineteenth-century historical demographic data from Baja California Sur, Mexico. Analyses suggest ecological constraints affected male, but not female, age at first marriage. Males who migrated from their natal community and who married in communities whose primary economic activity was agriculture experienced delayed age at first marriage. The age at which females first married increased over time causing a reduction in the age gap between spouses. Furthermore, the spousal age gap showed sex-specific effects: women who married early in life were much younger than their husbands, while women who married late in life were older than their husbands, suggesting that variation in female reproductive value influenced mate choice. Males, on the other hand, who married late in life showed a preference for marrying much younger females, indicating preferences for females with high reproductive value.