Population decline and the new nature: Towards experimental “refactoring” in landscape development of post-industrial regions
Introduction
Population decline and de-industrialization are pressing phenomena especially in regions across the formerly socialist east. Lower birth rates and out-migration often go hand in hand with an on-going economic decline of regions. The east of Germany, for instance, has lost more than 10% of its population since 1990 due to low birth rates and movement of labor to the West. Since the fall of the Berlin wall in 1990, more than 1.5 million people have left eastern Germany. Some demographers have predicted that only half of the 18 million who lived in Eastern Germany when it imploded will be left in 2020 [1].1 On a global scale, since 1990, every fourth city has been shrinking, and this tendency is on the rise [3]. One of the most well-known examples for these developments is the city of Leipzig and vicinity in Eastern Germany in the state of Saxony. Leipzig has a long history as an important urban center in Germany and today has around 500,000 inhabitants. Since 1990, after the fall of the Berlin Wall, the city has even lost over 12% of its population in comparison to the number in the late 1980s. Despite ongoing tearing down of buildings and an increasing number of buildings listed for demolition, this development has led to a residential vacancy number of 55,000 empty flats in 2006.
These developments are also a challenge for the future of science in the context of its application, since no blueprints in terms of ecological implementations and engineering are available. In the first-half of this paper, I will discuss some of these challenges illustrating the unique development of opencast mining areas in Eastern Germany in order to subsequently suggest to combine two strategies, an experimental, as developed in relation to their future scenarios in science studies during the last two decades [4], [5], [6], and with the concept of refactoring, derived from software engineering, where it describes a process of clarifying and simplifying the design of an existing code, without changing its behavior. The two strategies are taken into consideration, since the more the unexpected in research is anticipated, the more is the growth of expectations to control or steer the surprising events properly or to even reverse some of them. Considering these uncertainties, I will suggest an “experimental strategy” of “refactoring” that is able to grasp surprising events and is able to cope with ignorance in scientific knowledge. Consequently, to come to grips with future events of such kind more than ever curiosity and the fostering of surprises need to be unleashed and controlled in an experimental modularization.
Section snippets
Depopulation and the future of post-industrial landscapes
In some debates on processes of population decline, the phenomenon is perceived as urban sprawl in reverse. Although population shrinkage and lack of economic growth should be expected to operate against urban sprawl, in many western cities the decline in population has not been accompanied by a proportional reduction of households and buildings [7], [8]. Instead, the consumption of the surface for new buildings in the affluent suburbs has been rising so that the development of natural areas
Not enough people: the future of mining lakes and regional planning
Since the late 1990s, the step-by-step implementation of the project called “Regional Network Neuseenland” can be called an experimental field unique of its kind. As a representative of Regional Planning Office in the city of Leipzig put it: “For what we do here in the field of landscape reclamation, there are no blueprints whatsoever. … In 1990, we simple stood here empty-handed. There were no concepts about what we should do and what was going to happen” (interview February 2006).
Experimental strategies and the refactoring of research and development
An experimental strategy outside the scientific laboratory, as it has been developed in several interdisciplinary fields [4], [5], [17], [18], refers to a performance in networks of collective actors. Experimental strategies are founded on the insight that human actors (scientists, concerned citizens or other decisions makers) do not know enough to manage urban systems, regional development or ecological implementations with master plans of action. To differentiate experimental strategies from
The robustness of experimental refactoring
In the beginning of most developments many options are given, albeit more often than not chance is an important factor in the direction of a certain development in ecological design. Historian of technology Thomas Hughes [35] has elaborated the connection and feedback loops between innovation, implementation and the observation of aberrations in research and development. In his view, sometimes a process is no longer able to break out of a lock-in, that is, a process where innovative
Outlook: environmental science and its publics
Science in the real world is always unique, with heterogeneous actors involved and special institutional embeddings. However, in the idea to design them in a robust fashion there lies a structural frequency of occurrence. The notion of robustness thus should be understood in a particular meaning. Robustness most of the time referred to the quality of a research and design strategy, both in everyday life as well as in more academic or “scientific” contexts. Robustness is needed in order to reach
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