Scenario-based land abandonment projections: Method, application and implications.

Sci Total Environ

Environmental Impact Assessment Section, National Institute for Environmental Studies, Fukushima Branch, Fukasaku 10-2, Miharu, Tamura District, Fukushima 963-7700, Japan; Department of Environmental and Civil Engineering, Toyama Prefectural University, Kurokawa 5180, Imizu City, Toyama 939-0398, Japan.

Published: November 2019

AI Article Synopsis

  • Land abandonment, especially in agriculture, has significant social and ecological effects, making it crucial to predict its future extent and patterns based on various factors.
  • A framework was developed for projecting land abandonment scenarios in Fukushima Prefecture, Japan, examining two socioeconomic growth scenarios from 2014 to 2050: low (LL) and high (HH).
  • Results showed that under the HH scenario, agricultural abandonment would increase significantly due to a decline in the farmer population, while under the LL scenario, urban and residential land abandonment would rise because of a greater decline in total population, providing valuable insights for adaptive development planning.

Article Abstract

Land abandonment, e.g. agricultural land abandonment, can result in various social and ecological impacts. It would thus be helpful if the extent and spatial pattern of future land abandonment could be projected. However, the trajectory of future land abandonment generally depends on various factors, including biophysical conditions and future changes in socioeconomic indicators in the area. In this study, we developed a general framework for a scenario-based land abandonment projection, featuring a coupled regional economic and spatially explicit land change modeling approach. We applied this framework in selected municipalities in Fukushima Prefecture, Japan, under two socioeconomic development scenarios (2014-2050): low population and economic growth (LL scenario) and high population and economic growth (HH scenario). The case study results, which are also visualized through a set of hot spot maps, revealed that agricultural land abandonment would be more intense under the HH scenario due to the much higher future decline in farmer population driven by the shift in people's employment and main source of livelihood. Under the LL scenario, residential and urban land abandonment would be more profound because of the much higher future decline in total population. In general, our results provide insights into some plausible future socioeconomic changes, their interplay and their consequent land abandonment in the case study area, which would be useful in the context of forward-looking adaptive development planning. The proposed framework can be applied to other case study areas.

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Source
http://dx.doi.org/10.1016/j.scitotenv.2019.07.204DOI Listing

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