Electrochemically Driven C-H Hydrogen Abstraction Processes with the Tetrachloro-Phthalimido-N-Oxyl (Cl₄PINO) Catalyst

The radical redox mediator tetrachloro-phthalimido-N-oxyl (Cl4PINO) is generated at a glassy carbon electrode and investigated for the model oxidation of primary and secondary alcohols with particular attention to reaction rates and mechanism. The two-electron oxidation reactions of a range of primary, secondary, and cyclic alcohols are dissected into an initial step based on C-H hydrogen abstraction (rate constant k1, confirmed by kinetic isotope effect) and a fast radical-radical coupling of the resulting alcohol radical with Cl4PINO to give a ketal that only slowly releases the aldehyde/ketone and redox mediator precursor back into solution (rate constant k2). In situ electrochemical EPR reveals Cl4PINO sensitivity towards moisture. DFT methods are applied to confirm and predict C-H hydrogen abstraction reactivity

Ancient Lowland Maya neighborhoods: Average Nearest Neighbor analysis and kernel density models, environments, and urban scale

Many humans live in large, complex political centers, composed of multi-scalar communities including neighborhoods and districts. Both today and in the past, neighborhoods form a fundamental part of cities and are defined by their spatial, architectural, and material elements. Neighborhoods existed in ancient centers of various scales, and multiple methods have been employed to identify ancient neighborhoods in archaeological contexts. However, the use of different methods for neighborhood identification within the same spatiotemporal setting results in challenges for comparisons within and between ancient societies. Here, we focus on using a single method—combining Average Nearest Neighbor (ANN) and Kernel Density (KD) analyses of household groups—to identify potential neighborhoods based on clusters of households at 23 ancient centers across the Maya Lowlands. While a one-size-fits all model does not work for neighborhood identification everywhere, the ANN/KD method provides quantifiable data on the clustering of ancient households, which can be linked to environmental zones and urban scale. We found that centers in river valleys exhibited greater household clustering compared to centers in upland and escarpment environments. Settlement patterns on flat plains were more dispersed, with little discrete spatial clustering of households. Furthermore, we categorized the ancient Maya centers into discrete urban scales, finding that larger centers had greater variation in household spacing compared to medium-sized and smaller centers. Many larger political centers possess heterogeneity in household clustering between their civic-ceremonial cores, immediate hinterlands, and far peripheries. Smaller centers exhibit greater household clustering compared to larger ones. This paper quantitatively assesses household clustering among nearly two dozen centers across the Maya Lowlands, linking environment and urban scale to settlement patterns. The findings are applicable to ancient societies and modern cities alike; understanding how humans form multi-scalar social groupings, such as neighborhoods, is fundamental to human experience and social organization

Ancient Lowland Maya neighborhoods: Average Nearest Neighbor analysis and kernel density models, environments, and urban scale

Many humans live in large, complex political centers, composed of multi-scalar communities including neighborhoods and districts. Both today and in the past, neighborhoods form a fundamental part of cities and are defined by their spatial, architectural, and material elements. Neighborhoods existed in ancient centers of various scales, and multiple methods have been employed to identify ancient neighborhoods in archaeological contexts. However, the use of different methods for neighborhood identification within the same spatiotemporal setting results in challenges for comparisons within and between ancient societies. Here, we focus on using a single method—combining Average Nearest Neighbor (ANN) and Kernel Density (KD) analyses of household groups—to identify potential neighborhoods based on clusters of households at 23 ancient centers across the Maya Lowlands. While a one-size-fits all model does not work for neighborhood identification everywhere, the ANN/KD method provides quantifiable data on the clustering of ancient households, which can be linked to environmental zones and urban scale. We found that centers in river valleys exhibited greater household clustering compared to centers in upland and escarpment environments. Settlement patterns on flat plains were more dispersed, with little discrete spatial clustering of households. Furthermore, we categorized the ancient Maya centers into discrete urban scales, finding that larger centers had greater variation in household spacing compared to medium-sized and smaller centers. Many larger political centers possess heterogeneity in household clustering between their civic-ceremonial cores, immediate hinterlands, and far peripheries. Smaller centers exhibit greater household clustering compared to larger ones. This paper quantitatively assesses household clustering among nearly two dozen centers across the Maya Lowlands, linking environment and urban scale to settlement patterns. The findings are applicable to ancient societies and modern cities alike; understanding how humans form multi-scalar social groupings, such as neighborhoods, is fundamental to human experience and social organization

Building an Archaeology of Maya Urbanism: Planning and Flexibility in the American Tropics

International audience“A dynamic multi-scalar view of Maya cities showing them to be long-lived, complex, ever-changing landscapes that included not only architecture but the larger agricultural landscape that helped sustain them—they were garden cities in a neotropical landscape.”—Claudia García-Des Lauriers, California State Polytechnic University, PomonaBuilding an Archaeology of Maya Urbanism tears down entrenched misconceptions of Maya cities to build a new archaeology of Maya urbanism by highlighting the residential dynamics that underwrote one of the most famous and debated civilizations of the ancient Americas. Exploring the diverse yet interrelated agents and processes that modified Maya urban landscapes over time, this volume highlights the adaptive flexibility of urbanization in the tropical Maya Lowlands.Integrating recent lidar survey data with more traditional excavation and artifact-based archaeological practices, chapters in this volume offer broadened perspectives on the patterns of Maya urban design and planning by viewing bottom-up and self-organizing processes as integral to the form, development, and dissolution of Classic lowland cities alongside potentially centralized civic designs. Full of innovative examples of how to build an archaeology of urbanism that can be applied not just to the Lowland Maya and across the region, Building an Archaeology of Maya Urbanism simultaneously improves interpretations of lowland Maya culture history and contributes to empirical and comparative discussions of tropical, non-Western cities worldwide

Ancient lowland Maya complexity as revealed by airborne laser scanning of northern Guatemala

International audienc

PLI_Phase_1_natural_defenses

All identified natural defensive features within PLI Phase 1 dataset. Format: ZIP file containing geo-masked ESRI shpfil

PLI_Phase_1_pre/post-lidar ground coverage

All areas surveyed prior to PLI Phase 1 and all areas verified after PLI Phase 1. Format: ZIP file containing geo-masked ESRI shpfil

PLI_Phase_1_wetland_&_upland_field_zones

All identified wetland & upland field zones within PLI Phase 1 dataset. Format: ZIP file containing geo-masked ESRI shpfil

PLI_Phase_1_wetland_field_zones

All identified wetland field zones within PLI Phase 1 dataset. Format: ZIP file containing geo-masked ESRI shpfil

Data from: Ancient lowland Maya complexity as revealed by airborne laser scanning of northern Guatemala

Lowland Maya civilization flourished in the tropical region of the Yucatan peninsula and environs for more than 2500 years (~1000 BCE to 1500 CE). Known for its sophistication in writing, art, architecture, astronomy, and mathematics, Maya civilization still poses questions about the nature of its cities and surrounding populations because of its location in an inaccessible forest. In 2016, an aerial lidar survey across 2144 square kilometers of northern Guatemala mapped natural terrain and archaeological features over several distinct areas. We present results from these data, revealing interconnected urban settlement and landscapes with extensive infrastructural development. Studied through a joint international effort of interdisciplinary teams sharing protocols, this lidar survey compels a reevaluation of Maya demography, agriculture, and political economy and suggests future avenues of field research