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2025 , Vol. 48 >Issue 7: 1220 - 1232

DOI: https://doi.org/10.12118/j.issn.1000-6060.2024.425

生态与环境

基于PLUS-InVEST模型的甘肃通渭滑坡区生境质量时空变化及预测

  • 张晓明 ,
  • 宿星 ,
  • 张军 ,
  • 贾静
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  • 1.甘肃农业大学资源与环境学院，甘肃 兰州 730070
    2.甘肃省科学院地质自然灾害防治研究所，甘肃 兰州 730000
张晓明(1997-)，男，硕士研究生，主要从事灾损土地利用与生态修复研究. E-mail: 18219763882@163.com
张军(1977-)，男，博士，教授，主要从事生态系统服务研究. E-mail: zhangjun@gsau.edu.cn

收稿日期: 2024-07-25

  修回日期: 2024-09-25

  网络出版日期: 2025-07-04

基金资助

甘肃省重点研发计划项目(23YFFA0030);甘肃省科学院应用研发项目(2021JK-08);国家自然科学基金项目(42067066);甘肃省重点人才项目(2022RCXM094);第二次青藏高原综合科学考察研究项目(2019QZKK0902)

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Spatiotemporal variation and prediction of habitat quality in Tongwei landslide area of Gansu Province based on PLUS-InVEST model

  • ZHANG Xiaoming ,
  • SU Xing ,
  • ZHANG Jun ,
  • JIA Jing
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  • 1. College of Resources and Environmental science, Gansu Agricultural University, Lanzhou 730070, Gansu, China
    2. Institute of Geological Natural Disaster Prevention and Control, Gansu Academy of Sciences, Lanzhou 730000, Gansu, China

Received date: 2024-07-25

  Revised date: 2024-09-25

  Online published: 2025-07-04

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摘要

甘肃通渭滑坡区生境质量的时空演变研究对通渭县以及西北相似地区的生态可持续发展具有重要意义。首先采用斑块生成土地利用模拟（PLUS）模型对2035年的土地利用类型进行预测，然后运用生态系统服务和权衡的综合评估（InVEST）模型对1985—2020年及2035年的通渭县和滑坡区生境质量及其滑坡区生境退化时空演变特征进行分析预测，最后利用地理探测器对通渭县滑坡区生境质量变化驱动力因子进行探测。结果表明：（1） 2020—2035年通渭县各土地利用类型相互扩张转移，其中耕地向草地扩张最明显，通渭县土地利用类型仍然以耕地和草地为主，其他土地利用类型面积占比较少。（2） 空间尺度上，通渭县和滑坡区生境质量由南向北呈上升趋势，均以低等级和较低等级为主。滑坡区生境退化以中度退化和高度退化为主，由南向北呈下降趋势。（3） 时间尺度上，1985—2035年通渭县和滑坡区生境质量均呈先下降后上升再下降的变化规律，通渭县生境质量指数平均值线性拟合呈下降趋势，但滑坡区生境质量指数平均值线性拟合呈上升趋势。生境退化指数平均值呈先下降再上升的变化规律，线性拟合呈上升趋势。（4） 归一化植被指数（NDVI）是影响滑坡区生境质量空间分异的最关键因子。各因子交互作用以非线性增强为主，其中NDVI与年均降水量交互作用最强。

关键词： 滑坡区; PLUS模型; InVEST模型; 生境质量; 地理探测器; 通渭县

本文引用格式

张晓明 , 宿星 , 张军 , 贾静 . 基于PLUS-InVEST模型的甘肃通渭滑坡区生境质量时空变化及预测[J]. 干旱区地理, 2025 , 48(7) : 1220 -1232 . DOI: 10.12118/j.issn.1000-6060.2024.425

Abstract

The study of the spatial and temporal evolution of habitat quality in the landslide area of Tongwei County, Gansu Province, is crucial for the ecological sustainable development of Tongwei County and similar regions in northwest China. First, the patch-based land use simulation model was employed to predict land use types for the year 2035. Subsequently, the integrated valuation of ecosystem services and tradeoffs model was utilized to analyze and predict ecosystem quality as well as the temporal and spatial evolution characteristics of habitat quality in Tongwei County and the landslide area from 1985 to 2020 and projected to 2035. Finally, the geodetector model was applied to identify the driving factors behind changes in habitat quality in the landslide area of Tongwei County. The results showed the following. (1) From 2020 to 2035, all land use types in Tongwei County are expected to expand and shift, with the most significant transition occurring from arable land to grassland. Arable land and grassland will continue to dominate the land use types, whereas other types will represent a relatively small proportion. (2) Spatially, habitat quality in Tongwei County and the landslide area exhibited an increasing trend from south to north, remaining predominantly low and lower grades. Habitat degradation in the landslide area was dominated by moderate and high degradation, with decreasing degradation from south to north. (3) Temporally, from 1985 to 2035, habitat quality in Tongwei County and the landslide area followed a pattern of decreasing, then increasing, and subsequently decreasing again. In Tongwei County, the linear trend of the average habitat quality showed a decline, whereas in the landslide area, it showed an increase. The average habitat degradation followed a pattern of decreasing followed by increasing, with a linear fit indicating an upward trend. (4) The normalized vegetation index (NDVI) is the most significant factor affecting spatial differentiation of habitat quality in landslide areas. Interactions among factors are predominantly characterized by nonlinear enhancement, with the interaction between NDVI and average annual precipitation being the strongest.

Key words： landslide area; PLUS model; InVEST model; habitat quality; geographical detector; Tongwei County

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