Isaac I. T. Ullah

Land use, water and Mediterranean landscapes: modelling long-term dynamics of complex socio-ecological systems

The evolution of Mediterranean landscapes during the Holocene has been increasingly governed by the complex interactions of water and human land use. Different land-use practices change the amount of water flowing across the surface and infiltrating the soil, and change water’s ability to move surface sediments. Conversely, water amplifies the impacts of human land use and extends the ecological footprint of human activities far beyond the borders of towns and fields. Advances in computational modelling offer new tools to study the complex feedbacks between land use, land cover, topography and surface water. The Mediterranean Landscape Dynamics project (MedLand) is building a modelling laboratory where experiments can be carried out on the long-term impacts of agropastoral land use, and whose results can be tested against the archaeological record. These computational experiments are providing new insights into the socio-ecological consequences of human decisions at varying temporal and spatial scales.

Computational modeling and neolithic socioecological dynamics: A case study from Southwest Asia

Archaeology has an opportunity to offer major contributions to our understanding of the long-term interactions of humans and the environment. To do so, we must elucidate dynamic socioecological processes that generally operate at regional scales. However, the archaeological record is sparse, discontinuous, and static. Recent advances in computational modeling provide the potential for creating experimental laboratories where dynamic processes can be simulated and their results compared against the archaeological record. Coupling computational modeling with the empirical record in this way can increase the rigor of our explanations while making more transparent the concepts on which they are based. We offer an example of such an experimental laboratory to study the long-term effects of varying landuse practices by subsistence farmers on landscapes, and compare the results with the Levantine Neolithic archaeological record. Different combinations of intensive and shifting cultivation, ovicaprid grazing, and settlement size are modeled for the Wadi Ziqlab drainage of northern Jordan. The results offer insight into conditions under which previously successful (and sustainable) landuse practices can pass an imperceptible threshold and lead to undesirable landscape consequences. This may also help explain long-term social, economic, and settlement changes in the Neolithic of Southwest Asia.

3.9 GIS-Based Soil Erosion Modeling

This chapter explains the theory and methods for GIS-based modeling of soil erosion, sediment transport, and deposition by surface water flow. The mathematical foundations of erosion models are introduced and simplified equations, suitable for GIS implementation, are derived. The presented methods cover modeling of hillslope erosion and deposition, gully formation, and landscape evolution processes. Coupling of erosion models with GIS is discussed, followed by examples of GIS implementation of simple and advanced models. The concepts and methods are illustrated using two case studies, that focus on feedbacks between the human activity and landscape processes.

Toward a theory of punctuated subsistence change

Significance The questions of how, when, and why humans transitioned from hunting and gathering to food production are important to understand the evolution and sustainability of agricultural economies. We explore cross-cultural data on human subsistence with multivariate techniques and interpret the results from the perspective of human societies as complex adaptive systems. We gain insight into several controlling variables that may inordinately influence the possibilities for subsistence change and into why the forager–farmer transition occurred quickly in some cases and more gradually in others. Discourse on the origins and spread of domesticated species focuses on universal causal explanations or unique regional or temporal trajectories. Despite new data as to the context and physical processes of early domestication, researchers still do not understand the types of system-level reorganizations required to transition from foraging to farming. Drawing upon dynamical systems theory and the concepts of attractors and repellors, we develop an understanding of subsistence transition and a description of variation in, and emergence of, human subsistence systems. The overlooked role of attractors and repellors in these systems helps explain why the origins of agriculture occurred quickly in some times and places, but slowly in others. A deeper understanding of the interactions of a limited set of variables that control the size of attractors (a proxy for resilience), such as population size, number of dry months, net primary productivity, and settlement fixity, provides new insights into the origin and spread of domesticated species in human economies.

Managing Hybrid Model Composition Complexity: Human–Environment Simulation Models

Multimodeling approaches are increasingly required for simulating multifaceted systems across many scientific disciplines. Such approaches represent the system as a set of subsystem models, each with its own structure and behavior. Some multimodeling approaches use modeling methods to define how the subsystem structures and behaviors interact. However, modeling a system this way brings about subsystem and composition complexity that must be managed. The complexities of hybrid models resulting from the interactions of the composed models can be reduced using interaction models. Independently developing and utilizing such interaction models provides additional flexibility in system model design, modification, and execution for both the subsystem models and the resultant hybrid system model. This chapter discusses the use of the polyformalism model composition approach for researching human–environment dynamics with direct support for managing the complexity, which results from subsystem model interactions within this domain.