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Researchers increasingly rely on aggregations of radiocarbon dates from archaeological sites as proxies for past human populations. This approach has been critiqued on several grounds, including the assumptions that material is deposited, preserved, and sampled in proportion to past population size. However, various attempts to quantitatively assess the approach suggest there may be some validity in assuming date counts reflect relative population size. To add to this conversation, here we conduct a preliminary analysis coupling estimates of ethnographic population density with late Holocene radiocarbon dates across all counties in California. Results show that counts of late Holocene radiocarbon-dated archaeological sites increase significantly as a function of ethnographic population density. This trend is robust across varying sampling windows over the last 5000 BP. Though the majority of variation in dated-site counts remains unexplained by population density. Outliers reveal how departures from the central trend may be influenced by regional differences in research traditions, development-driven contract work, organic preservation, and landscape taphonomy. Overall, this exercise provides some support for the “dates-as-data” approach and offers insights into the conditions where the underlying assumptions may or may not hold. 

Archaeological data often come in the form of counts. Understanding why counts of artifacts, subsistence remains, or features vary across time and space is central to archaeological inquiry. A central statistical method to model such variation is through regression, yet despite sophisticated advances in computational approaches to archaeology, practitioners do not have a standard approach for building, validating, or interpreting the results of count regression. Drawing on advances in ecology, we outline a framework for evaluating regressions with archaeological count data that includes suggestions for model fitting, diagnostics, and interpreting results. We hope these suggestions provide a foundation for advancing regression with archaeological count data to further our understanding of the past. 

Past population change is connected to significant shifts in human behavior and experience including landscape manipulation, subsistence change, sedentism, technological change, material inequality and more. However, population change appears to result from a complex interplay of human-environment interactions that feedback on each other, influencing and simultaneously impacted by processes such as subsistence intensification and climate change. Here we explore complex system dynamics of population change using theoretical and Approximate Bayesian Computational modeling combined with the archaeological record of the past 4,000 years in the Colorado Plateau and Great Basin regions of western North America as case studies to identify causal relationships and the different manners in which climate change may have interplayed with subsistence economic intensification and population dynamics. Using standard distance metric evaluation on the performance of 1,000,000 simulations compared with reconstructed past population sizes in each region reveals how climate change impacting landscape productivity can influence carrying capacity and structure population growth such that, when populations reach carrying capacity (Malthusian ceilings), intensification in their subsistence economy can send feedbacks into the socioecological system spurring rapid, differential, population growth. Comparisons of the two regions highlights how varied socioecological circumstances can produce alternative pathways to, and limitations on, population expansions. 

Processes driving nutrient retention in stormwater green infrastructure (SGI) are not well quantified in water-limited biomes. We examined the role of plant diversity and physiochemistry as drivers of microbial community physiology and soil N dynamics post precipitation pulses in a semi-arid region experiencing drought. We conducted our study in bioswales receiving experimental water additions and a montane meadow intercepting natural rainfall. Pulses of water generally elevated soil moisture and pH, stimulated ecoenzyme activity (EEA), and increased the concentration of organic matter, proteins, and N pools in both bioswale and meadow soils. Microbial community growth was static, and N assimilation into biomass was limited across pulse events. Unvegetated plots had greater soil moisture than vegetated plots at the bioswale site, yet we detected no clear effect of plant diversity on microbial C:N ratios, EEAs, organic matter content, and N pools. Differences in soil N concentrations in bioswales and the meadow were most directly correlated to changes in organic matter content mediated by ecoenzyme expression and the balance of C, N, and P resources available to microbial communities. Our results add to growing evidence that SGI ecological function is largely comparable to neighboring natural vegetated systems, particularly when soil media and water availability are similar. 

R code for Hastings, Y. D. (2022). Green Infrastructure Microbial Community Response to Simulated Pulse Precipitation Events in the Semi-Arid Western United States (Master's thesis, The University of Utah). This study was supported by a grant from the US National Science Foundation (DEB 2006308). R code for and Hastings, Y. D., et al. Green Infrastructure Microbial Community Response to Simulated Pulse Precipitation Events in the Semi-Arid Western United States. In review. Abstract: Nutrient retention in urban stormwater green infrastructure (SGI) of water-limited biomes is not well quantified, especially when stormwater inputs are scarce. We examined the role of plant diversity and physiochemistry as drivers of microbial community physiology and soil N pools and fluxes in bioswales subjected to simulated precipitation and a montane meadow experiencing natural rainfall within a semi-arid region during drought. Precipitation generally elevated soil moisture and pH, stimulated ecoenzyme activity, and increased the concentration of organic matter, proteins, and N pools in both bioswale and meadow soils; but the magnitude of change differed between events. Microbial community growth was static and N assimilation into biomass was limited across precipitation events. Unvegetated SGI plots had greater soil moisture, yet effects of plant diversity treatments on microbial C:N ratios, organic matter content, and N pools were inconsistent. Differences in soil N concentrations in bioswales and the meadow were most directly correlated to changes in organic matter content mediated by ecoenzyme expression and the balance of C, N, and P resources available to microbial communities. Our results add to growing evidence that ecological function of SGI is comparable to neighboring natural vegetated systems, particularly when soil media and water availability are similar. The file and R code structure is as follows: Data - Contains all data used for the analysis Results - Contains all figures, RMANOVA, and Piecewise Structural Equation Modeling results. renv - R environment used for project EEA_Vector_Analysis.R - R code used to analyze coenzyme (EEA) responses, including RMANOVA to look for significant differences in EEA response to simulated pulse events and Vector Analysis to determine the nutrient resource acquisition. Gravimetric_soil_moisture_pH.R - R code used for RMANOVA of gravimetric soil moisture and pH responses to simulated pulse events. MicrobialBiomass_EEA.Rproj - Downloaded R project Microbial_biomass.R - R code used for RMANOVA of microbial biomass carbon, nitrogen, and C:N responses to simulated pulse events. OM_protien_N_pools_fluxes.R - R code used for RMANOVA of organic matter content, proteins, and N pools and fluxes responses to simulated pulse events. PSEM_final.R - R code used for Pearson Correlation and Piecewise Structural Equation Modeling. Rclimate.R - R code used to obtain summary statistics of climate data from GIRF and TM climate and soil sensors. 

Local-scale human–environment relationships are fundamental to energy sovereignty, and in many contexts, Indigenous ecological knowledge (IEK) is integral to such relationships. For example, Tribal leaders in southwestern USA identify firewood harvested from local woodlands as vital. For Diné people, firewood is central to cultural and physical survival and offers a reliable fuel for energy embedded in local ecological systems. However, there are two acute problems: first, climate change-induced drought will diminish local sources of firewood; second, policies aimed at reducing reliance on greenhouse-gas-emitting energy sources may limit alternatives like coal for home use, thereby increasing firewood demand to unsustainable levels. We develop an agent-based model trained with ecological and community-generated ethnographic data to assess the future of firewood availability under varying climate, demand and IEK scenarios. We find that the long-term sustainability of Indigenous firewood harvesting is maximized under low-emissions and low-to-moderate demand scenarios when harvesters adhere to IEK guidance. Results show how Indigenous ecological practices and resulting ecological legacies maintain resilient socio-environmental systems. Insights offered focus on creating energy equity for Indigenous people and broad lessons about how Indigenous knowledge is integral for adapting to climate change. This article is part of the theme issue ‘Climate change adaptation needs a science of culture’. 

Abstract Climatic conditions exert an important influence on wildfire activity in the western United States; however, Indigenous farming activity may have also shaped the local fire regimes for millennia. The Fish Lake Plateau is located on the Great Basin–Colorado Plateau boundary, the only region in western North America where maize farming was adopted then suddenly abandoned. Here we integrate sedimentary archives, tree rings, and archeological data to reconstruct the past 1200 years of fire, climate, and human activity. We identify a period of high fire activity during the apex of prehistoric farming between 900 and 1400 CE, and suggest that farming likely obscured the role of climate on the fire regime through the use of frequent low-severity burning. Climatic conditions again became the dominant driver of wildfire when prehistoric populations abandoned farming around 1400 CE. We conclude that Indigenous populations shaped high-elevation mixed-conifer fire regimes on the Fish Lake Plateau through land-use practices.