Simulating the effects of salinization on irrigation agriculture in southern Mesopotamia

A model of irrigation agriculture is applied to southern Mesopotamian for the areas around Nippur and Uruk. Field systems around late third millennium BC (Ur III period) cities are modeled in order to understand the effects of salinization and what strategies might limit progressive salinization that hinders agricultural yields. Scholars have long suspected that progressive salinization may constrain irrigation agriculture in southern Mesopotamia. This is not only demonstrated by modeling, but methods to mitigate the effects of salinization and promote the resilience of agricultural systems are presented. Strategies that incorporate fallowing regimes and which promote natural and/or engineered leaching create resilient agricultural systems in which ancient farmers could have made decisions about when to crop and irrigate based on the effects of salinization. Simulation results not only demonstrate to what extent and under what conditions salinization could be limited, but also model results indicate that irrigation-induced salinity could have ultimately become a major constraint to settlements and agriculture in southern Mesopotamia

Settlement dynamics and hierarchy from agent decision-making: a method derived from entropy maximization

This paper presents an agent-based complex system simulation of settlement structure change using methods derived from entropy maximization modeling. The approach is applied to model the movement of people and goods in urban settings to study how settlement size hierarchy develops. While entropy maximization is well known for assessing settlement structure change over different spatiotemporal settings, approaches have rarely attempted to develop and apply this methodology to understand how individual and household decisions may affect settlement size distributions. A new method developed in this paper allows individual decision-makers to chose where to settle based on social-environmental factors, evaluate settlements based on geography and relative benefits, while retaining concepts derived from entropy maximization with settlement size affected by movement ability and site attractiveness feedbacks. To demonstrate the applicability of the theoretical and methodological approach, case study settlement patterns from the Middle Bronze (MBA) and Iron Ages (IA) in the Iraqi North Jazirah Survey (NJS) are used. Results indicate clear differences in settlement factors and household choices in simulations that lead to settlement size hierarchies comparable to the two evaluated periods. Conflict and socio-political cohesion, both their presence and absence, are suggested to havemajor roles in affecting the observed settlement hierarchy. More broadly, the model is made applicable for different empirically based settings, while being generalized to incorporate data uncertainty, making the model useful for understanding urbanism from top-down and bottom-up perspectives

The importance of flat archaeological sites in the Age of Empires and new digital methods for their identification and analysis: A case study from the Peshdar Plain in Iraqi Kurdistan

In the Age of Empires of the first millennium BCE when large, major urban centres dominated the plains of Mesopotamia and the coastal regions of the Mediterranean, the rural landscape began to transform, with settlements often located away from traditional, mounded sites. Finding these sites can be challenging but is not impossible. However, the mountainous regions in Iraq and the neighbouring areas present special methodological challenges. Many sites occupied were flat and low, making them less visible in surveys and even in satellitebased remote sensing data. Machine-learning techniques and the use of point pattern analysis of stone debris offer the possibility of finding the typically less detectable flat sites using drone (UAV) imagery. Once detected, flat sites offer the considerable advantage that street networks and urban zones can be more easily mapped by using geophysical prospection. This provides advantages in understanding movement within such sites using graph analysis and can help provide insight into social behaviour in the use of urban zones and land use more easily than Bronze Age mounded sites. This paper explores both these issues and discusses their usefulness in Iraqi Kurdistan and beyond

Modeling Strategic Decisions in the Formation of the Early Neo-Assyrian Empire

Understanding patterns of conflict and pathways in which political history became established is critical to understanding how large states and empires ultimately develop and come to rule given regions and influence subsequent events. We employ a spatiotemporal Cox regression model to investigate possible causes as to why regions were attacked by the Neo-Assyrian (912-608 BCE) state. The model helps to explain how strategic benefits and costs lead to likely pathways of conflict and imperialism based on elite strategic decision-making. We apply this model to the early 9th century BCE, a time when historical texts allow us to trace yearly campaigns in specific regions, to understand how the Neo-Assyrian state began to re-emerge as a major political player, eventually going on to dominate much of the Near East and starting a process of imperialism that shaped the wider region for many centuries even after the fall of this state. The model demonstrates why specific locations become regions of conflict in given campaigns, emphasizing a degree of consistency with which choices were made by invading forces with respect to a number of factors. We find that elevation and population density deter Assyrian invasions. Moreover, costs were found to be more of a clear motivator for Assyrian invasions, with distance constraints being a significant driver in determining where to campaign. These outputs suggest that Assyria was mainly interested in attacking its weakest, based on population and/or organization, and nearest rivals as it began to expand. Results not only help to address the emergence of this empire, but enable a generalized understanding of how benefits and costs to conflict can lead to imperialism and pathways to political outcomes that can have major social relevance

The sale of heritage on eBay: Market trends and cultural value

The marketisation of heritage has been a major topic of interest among heritage specialists studying how the online marketplace shapes sales. Missing from that debate is a large-scale analysis seeking to understand market trends on popular selling platforms such as eBay. Sites such as eBay can inform what heritage items are of interest to the wider public, and thus what is potentially of greater cultural value, while also demonstrating monetary value trends. To better understand the sale of heritage on eBay’s international site, this work applies named entity recognition using conditional random fields, a method within natural language processing, and word dictionaries that inform on market trends. The methods demonstrate how Western markets, particularly the US and UK, have dominated sales for different cultures. Roman, Egyptian, Viking (Norse/Dane) and Near East objects are sold the most. Surprisingly, Cyprus and Egypt, two countries with relatively strict prohibition against the sale of heritage items, make the top 10 selling countries on eBay. Objects such as jewellery, statues and figurines, and religious items sell in relatively greater numbers, while masks and vessels (e.g. vases) sell at generally higher prices. Metal, stone and terracotta are commonly sold materials. More rare materials, such as those made of ivory, papyrus or wood, have relatively higher prices. Few sellers dominate the market, where in some months 40% of sales are controlled by the top 10 sellers. The tool used for the study is freely provided, demonstrating benefits in an automated approach to understanding sale trends

Toward a typology for social-ecological systems

Characterizing and understanding social-ecological systems (SESs) is increasingly necessary to answer questions about the development of sustainable human settlements. To date, much of the literature on SES analysis has focused on "neat" systems involving a single type of resource, a group of users, and a governance system. While these studies provide valuable and specific insights, they are of limited use for application to "messy" SESs that encompass the totality of human settlements, including social organization and technologies that result in the movement of materials, energy, water, and people. These considerations, in turn, create distribution systems that lead to different types of SESs. In messy SESs the concept of resilience, or the ability of a system to withstand perturbation while maintaining function, is further evolved to posit that different settlements will require different approaches to foster resilience. This article introduces a typology for refining SESs to improve short- and long-term adaptive strategies in developing human settlements

The Market for Heritage: Evidence from eBay using Natural Language Processing

The trade in antiquities and cultural objects has proven difficult to understand and yet is highly dynamic. Currently, there are few computational tools that allow researchers to understand the nature of the legal market, which can also potentially provide insights into the illegal market such as types of objects traded and countries trading antiquities. Online sales in antiquities and cultural objects are often unstructured data; relevant cultural affiliations, types, and materials for objects are important for distinguishing what might sell, but these data are rarely organized in a format that makes the quantification of sales a simple process. Additionally, sale locations and the total value of sales are relevant to understanding the focus and size of the market. These data all provide potentially useful insights into how the market in antiquities and cultural objects is developing. Based on this need, this work presents the results of a machine learning approach using natural language processing and dictionary-based searches that investigates relatively low-end but high sales volume objects sold on eBay’s US site, where sales are often international, between October 2018 and May 2019. The use of named entity recognition, using a conditional random field approach, classifies objects based on the cultures in which they come from, what type of objects they are, and what the objects are made of. The results indicate that objects from the UK, affiliated with the Roman period, mostly constituting jewelery, and made of metals sell the most. Other important countries for selling ancient and cultural objects include the United States, Thailand, Germany, and Cyprus. Some countries appear to focus on specific types of objects, such as Egypt being a leader in selling Islamic cultural objects. Overall, the approach and tool used demonstrate that it is possible to monitor the online antiquities and cultural objects market while potentially gaining useful insights into the market. The tool developed is provided as part of this work so that it can be applied for other cases and online sites, where it can be applied in real time or using historical data