A Diachronic Study of Networks of Ceramic Assemblage Similarity in Neolithic Western Anatolia,the Aegean and the Balkans (c.6600–5500 bc)

This study compares the results of Jaccard and Kulczynski‐2 similarity measures on a sample of ceramic assemblages to reveal spatio‐temporal patterns in the relationship between Neolithic sites in western Anatolia and south‐eastern Europe (c.6600–5500 bc ). The results show that the relationship between spatial distance and ceramic assemblage similarity has increased through time, which supports previous interpretations of leapfrog migrations and subsequent regionalization in ceramic assemblages during the Neolithic. A diachronic network analysis demonstrates the continuation of Aegean networking after the spread of farming.     

Modelling the built environment: Spatial patterns,siting techniques and layout works of non-monumental architecture in Early Bronze Age Eastern Arabia

Interest in the built environment of Early Bronze Age (EBA) Eastern Arabia is rapidly increasing with the emergence of new field data from the excavation of settlement sites. However, little is known about architectural planning and spatial patterns in the region. This article explores non-monumental architecture throughout the third millennium BCE. A series of methods (Pythagorean triples, modular grids, interception of circles) were used to assess the geometric and metric characteristics of buildings, and to stress regularities and variation in the long term. The results of these analyses suggest the application of specific techniques in layout and construction works: the intersection of circles during the Hafit occupations, and more sophisticated techniques, combining the properties of circles and triangles, during the Umm an-Nar period. The diachronic approach allowed by the temporal span of the occupations highlights a firm progression of architectural paradigms and building crafts throughout the EBA. The evidence hints at the existence of a specialised workforce since the dawn of the Bronze Age, and reveals a sharp increase of technicity and standardisation towards the end of the third millennium.     

The study of spatiotemporal patterns integrating temporal uncertainty in late prehistoric settlements in northeastern Spain

This paper explores the integration of two variables that are typically difficult to use in spatial analysis: time and uncertainty. A framework is constructed to analyse mid- and long-term variation in settlement dynamics during late prehistory in northeastern Spain. Following previous proposals, an aoristic model is built with ceramic dating to feed a Monte Carlo simulation that explores the case study using a discrete time-step approach. At the same time, available radiometric dating is used to validate the accuracy of the simulation results. Departing from the static analysis of spatial variables, the model proposes a new approach by which researchers can address temporal uncertainty. The results show that patterns detected by classical spatial analysis can be produced by artefacts derived from the division of time in chronological units instead of discrete time periods. The model is also used to compare a priori identical variations whose rate of change, when analysed with this approach, is revealed to be completely different.     

Quantifying Animal Trajectories Using Spatial Aggregation and Sequence Analysis: A Case Study of Differentiating Trajectories of Multiple Species

The increasing availability of telemetry data with high spatial and temporal resolution promises to greatly advance scientific understandings of the movement patterns of individual organisms across space and time. The amount of data provided by such methods, however, can be challenging to analyze and interpret. In this study, we present a new approach for analyzing animal movements that aggregates telemetry locations into spatial clusters and extracts the information from sequences formed by individuals passing through these spatial clusters. We applied this integrated approach of spatial aggregation and sequence analysis to quantify and compare trajectories of cattle (Bos taurus), mule deer (Odocoileus hemionus), and elk (Cervus elaphus) tracked by automated telemetry at the Starkey Experimental Forest and Range in northeastern Oregon, USA. Our approach effectively differentiated movement patterns of the three species. It provides a useful mean of quantifying movement patterns of species in a landscape.     

Spatial Analysis in Physical Geography and the Challenge of Deterministic Uncertainty

The application of complex and nonlinear dynamical systems (NDS) theory in physical geography and geosciences has proceeded through several stages, and has recently entered a phase where field-testable hypotheses and historical or mechanistic explanations are being generated. However, there are some fundamental challenges. It seems clear that chaos and dynamical self-organization are present, and may be common in earth surface systems, and that these phenomena have spatial manifestations in the landscape. However, NDS theory and methods have been formulated primarily in the temporal domain and are typically ill-suited to real-world spatial data. Spatial analytical methods are not generally capable of distinguishing deterministic complexity and uncertainty from noise. Thus, the detection of the signals of complex deterministic dynamics in real landscapes and spatial data is a major challenge. Entropy-based methods of spatial analysis can be directly linked to nonlinear dynamics, and are at present the best available method to approach this problem. However, there is evidence in the spatial analysis literature suggesting that development of techniques to detect deterministic uncertainty is possible. Pending such a break-through, three general approaches are described, based on spatial analysis of chronosequences, the characteriziation of changes in spatial structure over time, and the spatial-domain testing of specific hypotheses relevant to deterministic uncertainty. Current trends generally suggest a shift in mathematical modeling and spatial analysis in physical geography away from traditional determinism toward approaches that incorporate locational, historical, and scale contingency.     

Increasing Behavioral Flexibility? An Integrative Macro-Scale Approach to Understanding the Middle Stone Age of Southern Africa

The Middle Stone Age (MSA) of southern Africa represents a period during which anatomically modern humans adopted a series of diverse cultural innovations. Researchers generally attribute these behavioral changes to environmental, neurological, or demographic causes, but none of these alone offers a satisfactory explanation. Even as patterns at site level come into focus, large-scale trends in cultural expansions remain poorly understood. This paper presents different ways to view diachronic datasets from localities in southern Africa and specifically tests hypotheses of environmental and cultural causality. We employ an array of analyses in an attempt to understand large-scale variability observed during the MSA. We evaluated the diversity of stone tool assemblages to model site use, examined transport distances of lithic raw materials to understand patterns of movement, assessed the cultural capacities required to manufacture and use different sets of tools, applied stochastic models to examine the geographic distribution of sites, and reconstructed biome classes and climatic constraints. Our large-scale analysis allowed the research team to integrate different types of information and examine diachronic trends during the MSA. Based on our results, the range of cultural capacity expanded during the MSA. We define cultural capacity as the behavioral potential of a group expressed through the problem-solution distance required to manufacture and use tools. Our dataset also indicates that the actual behavior exhibited by MSA people, their cultural performance as expressed in the archaeological record, is not equivalent to their cultural capacity. Instead we observe that the main signature of the southern African MSA is its overall variability, as demonstrated by changing sets of cultural performances. Finally, at the scale of resolution considered here, our results suggest that climate is not the most significant factor driving human activities during the MSA. Instead, we postulate that behavioral flexibility itself became the key adaptation.     

Quantifying Interpolation Errors in Urban Airborne Laser Scanning Models

Airborne laser scanning (ALS) is becoming an increasingly popular data capture technique for a variety of applications in urban surface modeling. Raw ALS data are captured and supplied as a 3D point cloud. Many applications require that these data are interpolated onto a regular grid in order that they may be processed. In this article, we identify and analyze the magnitudes and spatial patterning of residuals from ALS models of urban surfaces, at a range of different scales. Previous research has demonstrated the effects of interpolation method and scale upon the nature of error in digital surface models (DSMs), but the size and spatial patterning of such errors have not hitherto been investigated for urban surfaces. The contribution of this analysis is thus to investigate the ways in which different methods may introduce error, and to understand the uncertainty that characterizes urban surface models that are devised for a wide range of applications. The importance of the research is shown using examples of how the different methods may introduce different amounts of error and how the uncertainty information may benefit users of ALS height models. Our analysis uses a range of validation techniques, including split-sample, cross-validation, and jackknifing, to estimate the error created in DSMs of urban areas.     

Eco-cultural niches of the Badegoulian: Unraveling links between cultural adaptation and ecology during the Last Glacial Maximum in France

This study details an application of eco-cultural niche modeling (ECNM) using two modeling architectures—a genetic algorithm (GARP) and maximum entropy (Maxent)—aimed at examining the ecological context of sites with archaeological remains attributed to the culture termed the Badegoulian (ca. 22–20 k cal BP), which dates to the middle part of the Last Glacial Maximum (ca. 23–19 k cal BP). We reconstructed the ecological niche of the Badegoulian and assessed whether eco-cultural niche variability existed within this technocomplex. We identified two broad but distinct spatial entities in the distribution of Badegoulian sites based on lithic raw material sources and circulation, and found that these spatial units share a similar ecological niche. We discuss the implications of territorial differentiation within this niche in light of research on land use by culturally affiliated groups within a broad cultural entity. We propose that Badegoulian circulation networks reflect distinct social territories associated with particular conditions within a single ecological niche. This study illustrates the utility of combining ecological niche reconstructions with archaeological data to identify and evaluate diachronic trends in cultural continuity for situations where such patterns may be missed when the focus of study is restricted solely to lithic technology and typology.     

Radiocarbon dates as data: quantitative strategies for estimating colonization front speeds and event densities

Archaeological analysis of large-scale prehistoric population history requires us to estimate rates of spatial spread during dispersals, and rates and magnitudes of temporal contraction during crashes. Using OxCal’s MCMC sampling routine, I introduce and demonstrate a simple and easily implemented method of estimating front speeds that takes due account of the uncertainty in the archaeological data (in both dates and distances), and argue that this method is more appropriate than those most often used in front speed estimation at present. I also propose a simple and easily implemented method of estimating event densities as a demographic proxy, as an alternative to summed calibrated probability distributions. I argue that this alternative is a significantly better technique, and show that its use also enables us to identify individual archaeological dates that are exerting particularly strong influence on the results, so that we can efficiently allocate our attention when assessing the possible effects of exogenous sampling uncertainty. To illustrate these methods I re-analyse two published datasets relating to the early Paleoindian colonization of North America. My results with the new technique indicate that even with a very noisy dataset, there was clear evidence in the framework of the INTCAL04 calibration curve for a drastic reduction in archaeological event densities following the Younger Dryas onset, followed by a prolonged period of reduced human activity, and a possible renewed phase of rapid growth after the Younger Dryas termination and onset of the Holocene. However, the revised estimate of the Younger Dryas marine reservoir offset in the INTCAL09 calibration curve for ∼12,550–12,900 cal BP changes the picture significantly, by flattening the peak in Clovis-age events and pushing it forward in time into the early Younger Dryas itself.     

Unraveling a Neanderthal palimpsest from a zooarcheological and taphonomic perspective

Practically all archeological assemblages are palimpsests. In spite of the high temporal resolution of Abric Romaní site, level O, dated to around 55 ka, is not an exception. This paper focuses on a zooarcheological and taphonomic analysis of this level, paying special attention to spatial and temporal approaches. The main goal is to unravel the palimpsest at the finest possible level by using different methods and techniques, such as archeostratigraphy, anatomical and taxonomical identification, taphonomic analysis, faunal refits and tooth wear analysis. The results obtained are compared to ethnoarcheological data so as to interpret site structure. In addition, activities carried out over different time spans (from individual episodes to long-term behaviors) are detected, and their spatial extent is explored, allowing to do inferences on settlement dynamics. This leads us to discuss the temporal and spatial scales over which Neanderthals carried out different activities within the site, and how they can be studied through the archeological record.     

Applying Geostatistical Analysis to Crime Data: Car-Related Thefts in the Baltic States

Geostatistical methods have rarely been applied to area-level offense data. This article demonstrates their potential for improving the interpretation and understanding of crime patterns using previously analyzed data about car-related thefts for Estonia, Latvia, and Lithuania in 2000. The variogram is used to inform about the scales of variation in offense, social, and economic data. Area-to-area and area-to-point Poisson kriging are used to filter the noise caused by the small number problem. The latter is also used to produce continuous maps of the estimated crime risk (expected number of crimes per 10,000 habitants), thereby reducing the visual bias of large spatial units. In seeking to detect the most likely crime clusters, the uncertainty attached to crime risk estimates is handled through a local cluster analysis using stochastic simulation. Factorial kriging analysis is used to estimate the local- and regional-scale spatial components of the crime risk and explanatory variables. Then regression modeling is used to determine which factors are associated with the risk of car-related theft at different scales.     

Agricultural potential and actualized development in Hawai’i: an airborne LiDAR survey of the leeward Kohala field system (Hawai’i Island)

Archaeological investigations of Hawaiian agriculture have relied on relatively coarse-grained data to investigate archipelago-wide processes, or on fine-grained data to examine patterning within localized zones of agricultural production. These trade-offs between spatial coverage and data resolution have inhibited understanding of both spatial patterns and temporal trends. Our analysis of 173 km² of high-resolution airborne Light Detection and Ranging (LiDAR) data for leeward Kohala, Hawai’i Island identifies spatial and temporal patterning in regional agricultural development. Differential densities of alignments suggest variable levels of agricultural intensity. Agricultural processes of expansion, segmentation, and intensification can also be discriminated, with distinct zones of the field system having undergone different mixes of development. Areas within the field system with moderate to high levels of both average production and variability in production (determined using a climate-driven productivity model) were utilized relatively early in a highly intensified manner; these areas often underwent processes of segmentation and intensification. Less productive areas were developed later and exhibit evidence of expansion with lower amounts of segmentation and intensification, at set levels of intensity. The spatial and temporal variability in agricultural activities was influenced by the diverse environmental conditions across the landscape as well as variation in cultivars and cultivation techniques. Combining the high-resolution LiDAR data from a large area with potential productivity modeling allows for a more fine-grained understanding of agricultural development in this region of the Hawaiian archipelago.     

滇南山区多元民族文化下的土地利用与区域可持续发展

立体性地貌气候特征下的滇南多元民族文化地区,由于文化背景、生活方式及社会经济发展水平的差异性,构成了资源利用及保护的多样性。我们利用遥感、地理信息系统等高新技术,从土地空间结构及土地利用时空变化着手,结合野外村寨调查,研究了民族文化在边疆、山区、民族地区经济生态系统中、在区域可持续发展中的地位和作用。     

Interpreting diachronic osteological variation at the medieval necropolis of the Sant Pere Churches (Terrassa,Spain)

The purpose of this study is to analyse the diachronic variation in the skeletal sample exhumed from the medieval necropolis of Sant Pere Churches, interpreting the results using the archaeological and historical evidence. The Sant Pere Churches are a monumental Romanic complex located in Terrassa (Spain) and built over the earlier Episcopal Cathedral of Egara from the Visigoth period. Egara has traditionally been considered the precursor of the current city of Terrassa; however this name disappeared from historical documentary sources after the period of Muslim incursions into Hispania (8th century). An archaeological excavation undertaken recently at the Sant Pere Churches provided us with the opportunity to study the population that was interred in this complex during that epoch. In total, the skeletal remains of 208 individuals were examined. In order to analyse the diachronic variation, the sample was divided into two periods, that of the Cathedral of Egara (4th–8th centuries; N = 128) and that of the Parish Churches of Terrassa (9th–13th centuries; N = 80). Both periods of the complex exhibited a similar skeletal age distribution, including under‐representation of non‐adult individuals. Nevertheless, a bias towards males in terms of sex distribution, sex differences in the mortality level and greater sexual dimorphism were observed in the population interred at the Cathedral of Egara. Moreover, analysis of the prevalence of skeletal disorders also provided evidence of higher differences between sexes for the period of the Episcopal Cathedral of Egara, the female population exhibiting the lower prevalence. Additionally, diachronic variation in both postcranial and dental disease patterns was observed, suggesting different activity patterns and food consumption between the periods. Overall, the results suggested that diachronic osteological variation observed in the Sant Pere Churches skeletal sample was most probably linked with the changes in the role of the complex following the Muslim incursion of the 8th century. Copyright © 2009 John Wiley & Sons, Ltd.     

SPACE–TIME MEASURES OF DEMAND FOR SERVICE: BRIDGING LOCATION MODELLING AND ACCESSIBILITY STUDIES THROUGH A TIME‐GEOGRAPHIC FRAMEWORK

Demand for service in location modelling is often evaluated based on the spatial proximity of fixed and static reference locations of demand (e.g. home) to a facility, which ignores person‐specific activity–travel patterns and the temporal changes in demand for service throughout the day. To address these limitations, this study draws upon recent developments in space–time measures of individual accessibility to explore the spatial and temporal structures of demand by considering individuals' space–time constraints and impact of existing urban structures. Based on a time‐geographic framework, eight space–time demand measures were developed and compared with three conventional location‐based demand measures for 12 hospitals through an empirical study conducted in Columbus, Ohio. The results show that geographic proximity between clients' home and facilities may not be an effective indicator for service demand, and conventional demand measures tend to underestimate potential demand for service in most situations. The study concludes that space–time demand measures that take into account people's activity‐travel patterns in space–time would lead to better estimation of demand for service in most cases.     

Marine trophic levels targeted between AD 300 and 1500 on the Georgia coast,USA

The marine trophic levels targeted during Swift Creek (AD 300–700) and Savannah (AD 1200–1500) occupations at the Cathead Creek site (9Mc360) and at two sites from the Kings Bay Locality (9CAM171a, 9CAM177), coastal Georgia, USA, differ in a consistent temporal and spatial pattern. Vertebrate and invertebrate remains from these three coastal sites contain similar suites of estuarine animals. However, Swift Creek peoples at these distinct hydrological settings obtained more biomass from fishes and less from molluscs compared to the subsequent Savannah occupants. The two Swift Creek faunal collections are less rich, more diverse, and more equitable than the two subsequent Savannah collections regardless of location. Furthermore, the mean trophic level is higher in the Swift Creek collections compared to the Savannah ones at both locations. These observations apply to both biomass and Minimum Number of Individuals. These differences likely are defining characteristics distinguishing the Swift Creek and the Savannah economies. More research is needed to determine the extent to which these temporal and spatial patterns are attributable to environmental and cultural variables.     

Climate change, uncertainty and prehistoric hunter–gatherer mobility

The onset of Little Ice Age conditions in California’s Sierra Nevada mountains resulted in increased temporal and spatial variability, and hence uncertainty regarding the distribution and production of resources targeted by its inhabitants, the Western Mono. The Mono responded with a risk-averse strategy composed of lowland winter population aggregation supported by logistical forays and seasonal residential dispersals to the high country, both ways of averaging variance in environmental productivity. These patterns were reconstructed using surface archaeology, GIS, and two straightforward spatial statistics, nearest-neighbor and variance-to-mean ratios, that combined provide a robust, objective picture of population aggregation and dispersal and the scale of these phenomena in different environments and seasons. These diverse strategies conform to expectations regarding the best ways for hunter–gatherers to cope with uncertainty, particularly in mountain environments. Despite this, the residentially mobile aspect of the pattern is rare in mountains and probably the result of historical connections between the Mono and Great Basin groups employing similar behaviors. Ultimately, this research suggests that climate change and environmental variability condition risk-averse, satisficing economic behaviors focused more on security than optimization, implying that pronounced environmental variability runs counter to economic intensification and its association with the evolution of more complex societies.     

Duration Modeling of Spatial Point Patterns

This paper attempts to further the research by Odland and Ellis (1992) in applying event history methodology to the analysis of spatial point patterns (that is, event patterns). Its empirical focus is the event pattern derived from the adoption of an agricultural innovation, the Harvestore, in southern Ontario, Canada, from 1963 to 1986. Event history analysis involves the use of discrete-state, continuous-time stochastic models to investigate a temporal longitudinal record on discrete variables. Event history models are usually concerned with durations of time between events and the effects of intertemporal time dependencies on future event occurrences. As such, they are often referred to as duration models. Many of the methods used in event history analysis allow the use of other nonnegative interval measurements in place of standard temporal intervals to investigate a series of events. In particular, spatial intervals (or durations) of distances between events may also be accommodated by event history models. Our analysis extends the previous research of Odland and Ellis (1992) by using a wider range of parametric models to explore duration dependence, investigating the role of spatial censoring, and using a more extensive set of explanatory variables. In addition, simulation experiments and graphical tests are used to evaluate the empirical event pattern against one generated from Complete Spatial Randomness. Results indicate that the event pattern formed by the Harvestore adopter farms is clustered (that is, is described by positive duration dependency), the sales agent is a significant factor in the distribution of adopters, and that contrasting results are obtained from the analysis using censored data versus uncensored data.     

Who are the People in my Neighborhood?: The “Contextual Fallacy” of Measuring Individual Context with Census Geographies

Scholars frequently use counts of populations aggregated into geographic units like census tracts to represent measures of neighborhood context. Decades of research confirm that variation in how individuals are aggregated into geographic units can dramatically alter analyses conducted with these units. While most researchers are aware of the problem, they have lacked the tools to determine its magnitude or its capacity to affect analytical results obtained using these contextual measures. Using confidential access to the complete 2010 U.S. Decennial Census, we can construct—for all persons in the U.S.—individual-specific contexts, which we group according to Census-assigned block, block group, and tract. We compare these individual-specific measures to the published statistics at each scale, and we then determine the degree to which published measures could be affected by how boundaries are drawn using a simple statistic, the standard deviation of individual context (SDIC). For three key measures (percent Black, percent Hispanic, and Entropy—a measure of ethno-racial diversity), we find that block-level Census statistics frequently contain a high degree of uncertainty meaning that they may not capture the actual context of individuals within them. More problematic, we uncover systematic spatial patterns in the uncertainty associated with contextual variables at all three scales.