气候变化领域集成服务门户(CCPortal): Modeling spatial climate change landuse adaptation with multi-objective genetic algorithms to improve resilience for rice yield and species richness and to mitigate disaster risk

CCPortal

DOI	10.1088/1748-9326/aaf0cf
	Modeling spatial climate change landuse adaptation with multi-objective genetic algorithms to improve resilience for rice yield and species richness and to mitigate disaster risk
	Yoon E.J.; Thorne J.H.; Park C.; Lee D.K.; Kim K.S.; Yoon H.; Seo C.; Lim C.-H.; Kim H.; Song Y.-I.
发表日期	2019
ISSN	17489318
卷号	14 期号:2
英文摘要	As climate change is ongoing, many studies have recently focused on adaptation to climate change from a spatial perspective. However little is known about how changing the spatial composition of landuse could improve climate change resilience. Consideration of climate change impacts when spatially allocating landuse could be a useful and fundamental long term adaptation strategy, particularly for regional planning. Here, we identify climate adaptation scenarios based on existing extents of three landuse classes using multi-objective genetic algorithms for a 9982 km 2 region with 3.5 million inhabitants in South Korea. We selected five objectives for adaptation based on predicted climate change impacts and regional economic conditions: minimization of disaster damage and existing landuse conversion, maximization of rice yield, protection of high species richness areas, and economic value. We generated 17 Pareto landuse scenarios by six weighted combinations of the adaptation objectives. Most scenarios, although varying in magnitude, showed better performance than the current spatial landuse composition for all adaptation objectives, suggesting that some alteration of current landuse patterns could increase overall climate resilience. Given the flexible structure of the optimization model, we expect that regional stakeholders could efficiently generate other scenarios by adjusting model parameters (weighting combinations) or replacing input data (impact maps), and selecting a scenario depending on preference or a number of problem-related factors. © 2019 The Author(s). Published by IOP Publishing Ltd.
英文关键词	economic value; landslides; landuse conversion; scenario planning; South Korea; trade-offs
语种	英语
scopus关键词	Disasters; Economic and social effects; Economics; Flexible structures; Genetic algorithms; Landslides; Regional planning; Structural optimization; Adaptation strategies; Adaptation to climate changes; Climate change impact; Economic values; Multi-objective genetic algorithm; Scenario Planning; South Korea; Trade off; Climate change; adaptive management; climate change; climate effect; crop yield; disaster management; economic conditions; genetic algorithm; landslide; modeling; rice; risk assessment; species richness; trade-off; South Korea
来源期刊	Environmental Research Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/154715
作者单位	Interdisciplinary Program in Landscape Architecture, Seoul National University, Seoul, 08826, South Korea; Department of Environmental Science and Policy, University of California, Davis, CA 95616, United States; Department of Landscape Architecture, University of Seoul, Seoul, 02504, South Korea; Department of Landscape Architecture and Rural System Engineering, Seoul National University, Seoul, 08826, South Korea; Department of Plant Science, Seoul National University, Seoul, 08826, South Korea; Division of Ecological Survey Research, National Institute of Ecology, Seocheon-gun, 33657, South Korea; Institute of Life Science and Nature Resources, Korea University, Seoul, 02481, South Korea; Korea Adaptation Center for Climate Change, Korea Environment Institute, Sejong, 30121, South Korea
推荐引用方式 GB/T 7714	Yoon E.J.,Thorne J.H.,Park C.,et al. Modeling spatial climate change landuse adaptation with multi-objective genetic algorithms to improve resilience for rice yield and species richness and to mitigate disaster risk[J],2019,14(2).
APA	Yoon E.J..,Thorne J.H..,Park C..,Lee D.K..,Kim K.S..,...&Song Y.-I..(2019).Modeling spatial climate change landuse adaptation with multi-objective genetic algorithms to improve resilience for rice yield and species richness and to mitigate disaster risk.Environmental Research Letters,14(2).
MLA	Yoon E.J.,et al."Modeling spatial climate change landuse adaptation with multi-objective genetic algorithms to improve resilience for rice yield and species richness and to mitigate disaster risk".Environmental Research Letters 14.2(2019).