Biocapacity optimization in regional planning
Date
2017
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Nature Research
Abstract
Ecological overshoot has been accelerating across the globe. Optimizing biocapacity has become a key to resolve the overshoot of ecological demand in regional sustainable development. However, most literature has focused on reducing ecological footprint but ignores the potential of spatial optimization of biocapacity through regional planning of land use. Here we develop a spatial probability model and present four scenarios for optimizing biocapacity of a river basin in Northwest China. The potential of enhanced biocapacity and its effects on ecological overshoot and water consumption in the region were explored. Two scenarios with no restrictions on croplands and water use reduced the overshoot by 29 to 53%, and another two scenarios which do not allow croplands and water use to increase worsened the overshoot by 11 to 15%. More spatially flexible transition rules of land use led to higher magnitude of change after optimization. However, biocapacity optimization required a large amount of additional water resources, casting considerable pressure on the already water-scarce socio-ecological system. Our results highlight the potential for policy makers to manage/optimize regional land use which addresses ecological overshoot. Investigation on the feasibility of such spatial optimization complies with the forward-looking policies for sustainable development and deserves further attention.
Description
CITATION: Guo, J., et al. 2017. Biocapacity optimization in regional planning. Scientific Reports, 7:41150, doi:10.1038/srep41150.
The original publication is available at https://www.nature.com
The original publication is available at https://www.nature.com
Keywords
Biocapacity optimization, Ecology -- Mathematical models, Crops -- Ecology, Water -- Ecology, Forest ecology, Regional planning -- Environmental aspects
Citation
Guo, J., et al. 2017. Biocapacity optimization in regional planning. Scientific Reports, 7:41150, doi:10.1038/srep41150