Deep Adaptation - The Spatial Dimension

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DOI:

https://doi.org/10.47982/spool.2022.2.00

Keywords:

Deep Adaptation, Editorial, Spool, Jem Bendell

Abstract

The future, which we thought we had maybe another decade to prepare for, is now suddenly here. In all likelihood, we can expect further crises such as the Covid-19 pandemic or of similar severity, especially in the context of climate change. They will render the 21st century radically different from the 20th: conventions, techniques, and social practices we are familiar with will disappear. Our responsibilities and roles as architects and urban planners will also change fundamentally in this process. We will work in increasingly volatile and vulnerable contexts and constellations.

Until now, many actors in politics, but also in academia and research, have played down or denied the vulnerability of our urban structures to the risks that are the direct effects of our current way of life. In the search for alternative and, in a sense, more realistic perspectives, Jem Bendell’s concept of “Deep Adaptation”, which has been widely and controversially discussed since its first publication in 2018, calls for a shift: he urges us to prepare for the collapse of certain systems that currently govern our lives – and to see this as an opportunity for positive change.

This change and the resulting challenges we are facing are primarily not technological, but above all social, economic, and organisational in nature. Moreover, they are highly interdependent and all-encompassing; they require systemic change, profound transformations, and adaptations of action. It is therefore not a question of developing technical solutions in isolation, but rather of fundamentally rethinking the way we live, operate, work, travel, and interact.

This issue of SPOOL seeks to explore the spatial dimension of the Deep Adaptation concept and how it can be put to use in the spatial disciplines such as urban planning, landscape planning, urban design, and architecture.

How to Cite

Daniel Zwangsleitner, D. Z., Carnelli, E., & Boucsein, B. (2022). Deep Adaptation - The Spatial Dimension. SPOOL, 9(2), 3–4. https://doi.org/10.47982/spool.2022.2.00

Published

2022-07-01

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