Biological invasions are responsible for tremendous impacts globally, including huge economic losses and management expenditures. Efficiently mitigating this major driver of global change requires the improvement of public awareness and policy regarding its substantial impacts on our socio-ecosystems. One option to contribute to this overall objective is to inform people on the economic costs linked to these impacts; however, until now, a reliable synthesis of invasion costs has never been produced at a global scale. Here, we introduce InvaCost as the most up-to-date, comprehensive, harmonised and robust compilation and description of economic cost estimates associated with biological invasions worldwide. We have developed a systematic, standardised methodology to collect information from peer-reviewed articles and grey literature, while ensuring data validity and method repeatability for further transparent inputs. Our manuscript presents the methodology and tools used to build and populate this living and publicly available database. InvaCost provides an essential basis (2419 cost estimates currently compiled) for worldwide research, management efforts and, ultimately, for data-driven and evidence-based policymaking.
This chapter presents and discusses current approaches and trends in computer-based modelling of pathways and movement networks in archaeology. After an introduction to the theoretical concepts involved, we present a state of the art of methodologies applied for reconstructing pathways and movement in ancient landscapes and discuss the various difficulties in using these methods as well as the most important technical hurdles involved. The problems of integrating optimal pathfinding algorithms with 'softer' socio-cultural variables are highlighted, as well as the limitations of modelling connections between places using least-cost path techniques. Network analysis reconstruction and analysis approaches are then reviewed as tools to better understand the overall structure of movement and communication in ancient landscapes. It is concluded that, while the potential of current approaches for understanding ancient movement is considerable, improvement is still needed in three main areas: the integration of approaches, sensitivity analysis and validation, and the theoretical underpinning of models of ancient movement.
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This paper proposes an ontological approach to connect the archaeological topographic evidence for movement in the landscape which can be derived from interpretation and spatial analysis of airborne lidar data with models of movement derived from modeling exercises such as Agent Based Modelling or Cost Path Modelling. This computational ontology enables the investigation of movement and its topographic manifestations in the landscape at various spatio-temporal scales. It creates an explicit framework for accessing meaningful information about movement generated through research using both detection and modelling-led approaches. Developing explicit computational frameworks to provide meaningful context is critical, particularly as remote sensing and modelling projects increase in scale and complexity. The process of developing a computational ontology exposes a deeper underlying issue, and one applicable to many topics we address as archaeologists: if we begin to unpack the concept of 'movement' it is readily apparent that it is a complex phenomenon, like many human habits, and studying it requires drawing together a variety of types of physical evidence and multiple, often competing, theoretical models of human processes and practices. If we wish to make archaeological 'data' on movement available, how do we create appropriate contextual information -really useful metadata -so that this data can be incorporated into the variety of studies for which knowledge of movement is relevant? This is essentially the challenge posed broadly by the FAIR principles, and in particular by the principle of interoperability, which suggests that we "use a formal, accessible, shared, and broadly applicable language for knowledge representation". Rather than simply seeking to fulfill the requirements of an arbitrary standard, attempting to meet the challenge of interoperability provides an impetus and opportunity to attempt to bridge the gap between data and model, and to reconsider how we conceive and represent knowledge in archaeological digital data and modelling projects. This kind of computational ontology, we suggest, can serve as the key for making the data from both these sources actually FAIR.
The amount of information available to archaeologists has grown dramatically during the last ten years. The rapid acquisition of observational data and creation of digital data has played a significant role in this “information explosion”. In this paper, we propose new methods for knowledge creation in studies of movement, designed for the present data-rich research context. Using three case studies, we analyze how researchers have identified, conceptualized, and linked the material traces describing various movement processes in a given region. Then, we explain how we construct ontologies that enable us to explicitly relate material elements, identified in the observed landscape, to the knowledge or theory that explains their role and relationships within the movement process. Combining formal pathway systems and informal movement systems through these three case studies, we argue that these systems are not hierarchically integrated, but rather intertwined. We introduce a new heuristic tool, the “track graph”, to record observed material features in a neutral form which can be employed to reconstruct the trajectories of journeys which follow different movement logics. Finally, we illustrate how the breakdown of implicit conceptual references into explicit, logical chains of reasoning, describing basic entities and their relationships, allows the use of these constituent elements to reconstruct, analyze, and compare movement practices from the bottom up.
In this paper, we describe an exploratory analysis of the possibilities of combining least cost path analysis and network analysis techniques. Accessibility is a potentially important site location factor. So far, the cost paths. However, these methods do not provide direct information on the foci of movement. Starting from networks created from least cost paths, network analysis and space syntax were used to obtain additional information on the structural features of the network. It is concluded that both techniques can be used with least cost path-based networks, and will provide new insights into the characteristics of the network. For most applications however the space syntax measures that take the geographical dimension into account seem to be preferable to the simple network analysis measures used here.
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