Global S&T Development Trend Analysis Platform of Resources and Environment
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, Eun Joo1; Thorne, James H.2; Park, Chan3; Lee, Dong Kun4; Kim, Kwang Soo5; Yoon, Heeyeun4; Seo, Changwan6; Lim, Chul-Hee7; Kim, Haeryung1; Song, Young-Il8 | |
2019-02-01 | |
发表期刊 | ENVIRONMENTAL RESEARCH LETTERS |
ISSN | 1748-9326 |
出版年 | 2019 |
卷号 | 14期号:2 |
文章类型 | Article |
语种 | 英语 |
国家 | South Korea; USA |
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. |
英文关键词 | scenario planning landslides economic value landuse conversion trade-offs South Korea |
领域 | 气候变化 |
收录类别 | SCI-E ; SSCI |
WOS记录号 | WOS:000456334200001 |
WOS关键词 | USE ALLOCATION ; OPTIMIZATION APPROACH ; MANAGEMENT ; BIODIVERSITY ; NETHERLANDS ; SIMULATION ; TOOLS ; AREAS |
WOS类目 | Environmental Sciences ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/30960 |
专题 | 气候变化 |
作者单位 | 1.Seoul Natl Univ, Interdisciplinary Program Landscape Architecture, Seoul 08826, South Korea; 2.Univ Calif Davis, Dept Environm Sci & Policy, Davis, CA 95616 USA; 3.Univ Seoul, Dept Landscape Architecture, Seoul 02504, South Korea; 4.Seoul Natl Univ, Dept Landscape Architecture & Rural Syst Engn, Seoul 08826, South Korea; 5.Seoul Natl Univ, Dept Plant Sci, Seoul 08826, South Korea; 6.Natl Inst Ecol, Div Ecol Survey Res, Seocheon Gun 33657, South Korea; 7.Korea Univ, Inst Life Sci & Nat Resources, Seoul 02481, South Korea; 8.Korea Environm Inst, Korea Adaptat Ctr Climate Change, Sejong 30121, South Korea |
推荐引用方式 GB/T 7714 | Yoon, Eun Joo,Thorne, James H.,Park, Chan,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]. ENVIRONMENTAL RESEARCH LETTERS,2019,14(2). |
APA | Yoon, Eun Joo.,Thorne, James H..,Park, Chan.,Lee, Dong Kun.,Kim, Kwang Soo.,...&Song, Young-Il.(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, Eun Joo,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). |
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