Landscape Ecological Risk Assessment of Ya'an-Kangding Expressway Based on PLUS Model

Liu Jingjing; Li Xu; Peng Peihao

doi:10.13961/j.cnki.stbctb.2023.03.019

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Landscape Ecological Risk Assessment of Ya'an-Kangding Expressway Based on PLUS Model

- Landscape Ecological Risk Assessment of Ya'an-Kangding Expressway Based on PLUS Model
- Bulletin of Soiland Water Conservation Vol. 43, Issue 3, Pages: 148-158(2023)
- 作者机构：
  
  1. 成都理工大学地球科学学院,四川,成都,610059
  2. 成都理工大学旅游与城乡规划学院,四川,成都,610059
  3. 成都理工大学生态资源与景观研究所,四川,成都,610059
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2023.03.019
  CLC： X22;F301.2
- Published：2023
- 稿件说明：
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Liu Jingjing, Li Xu, Peng Peihao. Landscape Ecological Risk Assessment of Ya'an-Kangding Expressway Based on PLUS Model[J]. Bulletin of Soiland Water Conservation, 2023, 43(3): 148-158.
DOI：

Liu Jingjing, Li Xu, Peng Peihao. Landscape Ecological Risk Assessment of Ya'an-Kangding Expressway Based on PLUS Model[J]. Bulletin of Soiland Water Conservation, 2023, 43(3): 148-158. DOI： 10.13961/j.cnki.stbctb.2023.03.019.

摘要

[目的] 评价区域景观生态风险，揭示其时空变化规律，为降低区域生态风险，维护区域生态安全，推进区域绿色发展提供支撑。[方法] 以土地利用数据为基础，通过其变化来建立景观生态风险评价模型，探讨2000—2020年雅康高速公路穿越县市景观生态风险的时空变化特征，并利用最优参数的地理探测器模型定量分析景观生态风险变化的驱动因素，采用PLUS模型模拟2035年雅康高速经过县市景观生态风险的空间分布特征和变化趋势。[结果] ①2000—2020年，研究区主要景观类型为林地、草地、耕地，不透水面面积增长速率最快，林地面积增加最多； ②研究区景观生态风险等级以低、较低和中风险等级为主，风险等级由高到低呈向外扩散现象； ③NDVI值、高程、年均降水等自然因素是景观生态风险变化的主要驱动因子； ④2035年两种不同情景下研究区中、较高、高风险等级的面积均有所下降，其中生态保护情景下，下降较为明显。[结论] 研究区内景观生态风险等级较低，以低、较低和中风险等级为主，生态环境呈逐渐向好趋势。生态保护情景更加符合区域可持续发展理念。

Abstract

[Objective] The regional landscape ecological risks were evaluated

and their spatiotemporal variation was analyzed in order to provide important support for reducing regional ecological risks

maintaining regional ecological security

and promoting regional green development.[Methods] We constructed a landscape ecological risk assessment model based on land use change

and determined the temporal and spatial change characteristics of landscape ecological risk for the Ya'an-Kangding Expressway crossing counties and cities from 2000 to 2020. A geographic detector model with optimized parameters was used to quantitatively analyze the driving factors of landscape ecological risk change. We used the PLUS model to simulate the spatial distribution characteristics and changing trends of landscape ecological risks for the Ya'an-Kangding Expressway passing through counties and cities in 2035.[Results] ① From 2000 to 2020

the main landscape types in the study area were forest land

grassland

and cultivated land

with the fastest growth rate occurring for the impervious surface area (expressway)

and the largest increase occurring in forest land area. ② Low and medium landscape ecological risk grades were the main factors. The risk grades spread outward from high to low. ③ Natural factors such as NDVI

elevation

and average annual precipitation were the main driving factors for changes in landscape ecological risk. ④ In 2035

the areas of medium

high

and high risk grades in the study area will decrease under the two different scenarios. The area of significant decline will be particularly obvious under the ecological protection scenario.[Conclusion] The landscape ecological risk levels in the study area were relatively low

mainly low

lower

and medium risk levels

and the ecological environment was gradually improving. The ecological protection scenario was more consistent with the concept of regional sustainable development.

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Keywords

references

Wu Jianguo. Landscape sustainability science:Ecosystem services and human well-being in changing landscapes[J]. Landscape Ecology, 2013,28(6):999-1023.

崔杨林,高祥,董斌,等.县域景观生态风险评价[J].浙江农林大学学报,2021,38(3):541-551.

彭建,党威雄,刘焱序,等.景观生态风险评价研究进展与展望[J].地理学报,2015,70(4):664-677.

陈利顶,傅伯杰,赵文武."源""汇"景观理论及其生态学意义[J].生态学报,2006,26(5):1444-1449.

曹祺文,张曦文,马洪坤,等.景观生态风险研究进展及基于生态系统服务的评价框架:ESRISK[J].地理学报,2018,73(5):843-855.

吕乐婷,张杰,孙才志,等.基于土地利用变化的细河流域景观生态风险评估[J].生态学报,2018,38(16):5952-5960.

莫贵芬,冯建中,王中美,等.中亚阿姆河跨境流域景观生态风险时空演变特征分析[J].干旱地区农业研究,2022,40(1):123-131.

李琛,高彬嫔,吴映梅,等.基于PLUS模型的山区城镇景观生态风险动态模拟[J].浙江农林大学学报,2022,39(1):84-94.

王敏,胡守庚,张绪冰,等.干旱区绿洲城镇景观生态风险时空变化分析:以张掖绿洲乡镇为例[J].生态学报,2022,42(14):5812-5824.

张玉娟,曲建光,侯建国.哈尔滨市景观生态风险时空变化驱动力及分布预测[J].测绘通报,2022(2):83-89.

陈心怡,谢跟踪,张金萍.海口市海岸带近30年土地利用变化的景观生态风险评价[J].生态学报,2021,41(3):975-986.

于航,刘学录,赵天明,等.基于景观格局的祁连山国家公园景观生态风险评价[J].生态科学,2022,41(2):99-107.

韩振华,李建东,殷红,等.基于景观格局的辽河三角洲湿地生态安全分析[J].生态环境学报,2010,19(3):701-705.

Wang Hong, Liu Xingming, Zhao Chuanyan, et al. Spatial-temporal pattern analysis of landscape ecological risk assessment based on land use/land cover change in Baishuijiang National Nature Reserve in Gansu Province, China[J]. Ecological Indicators, 2021,124:107454.

Mondal B, Sharma P, Kundu D, et al. Spatio-temporal assessment of landscape ecological risk and associated drivers:A case study of Delhi[J]. Environment and urbanization Asia, 2021,12:S85-S106.

Liu Di, Chen Hai, Zhang Hang, et al. Spatiotemporal evolution of landscape ecological risk based on geomorphological regionalization during 1980-2017:A case study of Shaanxi Province, China[J]. Sustainability, 2020,12,941.

Ai Jingwen, Yu Kunyong, Zeng Zhen, et al. Assessing the dynamic landscape ecological risk and its driving forces in an island city based on optimal spatial scales:Haitan Island, China[J]. Ecological Indicators, 2022,137:108771.

王洁,摆万奇,田国行.青藏高原景观生态风险的时空特征[J].资源科学,2020,42(9):1739-1749.

高彬嫔,李琛,吴映梅,等.川滇生态屏障区景观生态风险评价及影响因素[J].应用生态学报,2021,32(5):1603-1613.

Yang Jie, Huang Xin. 30 m annual land cover and its dynamics in China from 1990 to 2019[J]. Earth System Science Data Discussions, 2021,2021:1-29.

潘竟虎,刘晓.疏勒河流域景观生态风险评价与生态安全格局优化构建[J].生态学杂志,2016,35(3):791-799.

王劲峰,徐成东.地理探测器:原理与展望[J].地理学报,2017,72(1):116-134.

曾一笑.基于CA-Markov模型和景观格局的生态保护红线评估效果分析[J].测绘通报,2021(S2):244-249.

齐麟,许东,朱琪,等.基于GeoSOS-FLUS平台的东北森林屏障带生态格局优化[J].生态学杂志,2021,40(11):3448-3462.

Liang X, Guan Q, Clarke K C, et al. Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model:A case study in Wuhan, China[J]. Computers Environment and Urban Systems, 2021,85:101569.

王保盛,廖江福,祝薇,等.基于历史情景的FLUS模型邻域权重设置:以闽三角城市群2030年土地利用模拟为例[J].生态学报,2019,39(12):4284-4298.

胡丰,张艳,郭宇,等.基于PLUS和InVEST模型的渭河流域土地利用与生境质量时空变化及预测[J].干旱区地理,2022,45(4):1125-1136.

孙定钊,梁友嘉.基于改进Markov-CA模型的黄土高原土地利用多情景模拟[J].地球信息科学学报,2021,23(5):825-836.

陈理庭,蔡海生,张婷,等.基于Markov-FLUS模型的饶河流域土地利用多情景模拟分析[J].生态学报,2022,42(10):3947-3958.

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