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- Hatlestad, Kailin
(författare)
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Exploring Uncertainty and Significance : Analysing Human Response to Environmental Risk with Computational Archaeology
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- As humanity confronts the escalating challenges posed by rapid climate change, it becomes increasingly urgent to understand the complex dynamics of human-environment interactions to mitigate its multifaceted impacts. Archaeology, with its long-term perspective, offers the opportunity to examine past societal responses to environmental risks across diverse locations in Northwestern Europe and temporal scales. This dissertation aims to contribute to this critical endeavour by exploring the socio-environmental dynamics and adaptive strategies of past societies, to inform effective responses to climate change challenges in both the present and future. Utilizing computational archaeology, which integrates digital technologies and computational methods to analyse big data, the dissertation employs probabilistic approaches, including Bayesian modelling like summed probability distributions of radiocarbon (14C) data, to confront uncertainties inherent in reconstructing past human-environmental dynamics from interdisciplinary datasets. Additionally, quantitative methods, such as correlation tests and null hypothesis testing of 14C data, are employed to identify significant shifts in these dynamics, translating insights into quantitative terms for enhanced integration with policy-making processes. The primary objective of the dissertation is to illustrate how the integration of archaeological and environmental big data can enrich the understanding of human responses to environmental challenges. The papers in this thesis demonstrate how computational methods can be applied to big data to understand spatiotemporal changes in human-environmental variables, uncovering risk management strategies and societal vulnerabilities. The papers highlight cases where human communities experienced mitigated adverse effects from severe environmental shifts due to diverse socioeconomic strategies. Simultaneously, the results emphasize regional variations in the impacts of climate change, crucial for understanding the effectiveness of human responses. Moreover, the thesis exhibits how big data analytics both complement and challenge existing archaeological interpretations, contributing to the development of new theories. Importantly, it underscores the significance of diverse socioeconomic strategies in mitigating risks, especially in the face of abrupt environmental events.
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| 2. |
- Morrison, Kathleen D., et al.
(författare)
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Mapping past human land use using archaeological data : A new classification for global land use synthesis and data harmonization
- 2021
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Ingår i: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 16:4
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Tidskriftsartikel (refereegranskat)abstract
- In the 12,000 years preceding the Industrial Revolution, human activities led to significant changes in land cover, plant and animal distributions, surface hydrology, and biochemical cycles. Earth system models suggest that this anthropogenic land cover change influenced regional and global climate. However, the representation of past land use in earth system models is currently oversimplified. As a result, there are large uncertainties in the current understanding of the past and current state of the earth system. In order to improve representation of the variety and scale of impacts that past land use had on the earth system, a global effort is underway to aggregate and synthesize archaeological and historical evidence of land use systems. Here we present a simple, hierarchical classification of land use systems designed to be used with archaeological and historical data at a global scale and a schema of codes that identify land use practices common to a range of systems, both implemented in a geospatial database. The classification scheme and database resulted from an extensive process of consultation with researchers worldwide. Our scheme is designed to deliver consistent, empirically robust data for the improvement of land use models, while simultaneously allowing for a comparative, detailed mapping of land use relevant to the needs of historical scholars. To illustrate the benefits of the classification scheme and methods for mapping historical land use, we apply it to Mesopotamia and Arabia at 6 kya (c. 4000 BCE). The scheme will be used to describe land use by the Past Global Changes (PAGES) LandCover6k working group, an international project comprised of archaeologists, historians, geographers, paleoecologists, and modelers. Beyond this, the scheme has a wide utility for creating a common language between research and policy communities, linking archaeologists with climate modelers, biodiversity conservation workers and initiatives.
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