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2000—2030年云贵高原碳储量和生境质量时空格局演变

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郭佳晖, 刘晓煌, 李洪宇, 邢莉圆, 杨朝磊, 雒新萍, 王然, 王超, 赵宏慧. 2024. 2000—2030年云贵高原碳储量和生境质量时空格局演变. 地质通报, 43(9): 1485-1497. doi: 10.12097/gbc.2023.11.016
引用本文: 郭佳晖, 刘晓煌, 李洪宇, 邢莉圆, 杨朝磊, 雒新萍, 王然, 王超, 赵宏慧. 2024. 2000—2030年云贵高原碳储量和生境质量时空格局演变. 地质通报, 43(9): 1485-1497. doi: 10.12097/gbc.2023.11.016
shu
GUO Jiahui, LIU Xiaohuang, LI Hongyu, XING Liyuan, YANG Chaolei, LUO Xinping, WANG Ran, WANG Chao, ZHAO Honghui. 2024. Evolution of spatial and temporal patterns of carbon stocks and habitat quality on the Yunnan-Guizhou Plateau during 2000—2030. Geological Bulletin of China, 43(9): 1485-1497. doi: 10.12097/gbc.2023.11.016
Citation: GUO Jiahui, LIU Xiaohuang, LI Hongyu, XING Liyuan, YANG Chaolei, LUO Xinping, WANG Ran, WANG Chao, ZHAO Honghui. 2024. Evolution of spatial and temporal patterns of carbon stocks and habitat quality on the Yunnan-Guizhou Plateau during 2000—2030. Geological Bulletin of China, 43(9): 1485-1497. doi: 10.12097/gbc.2023.11.016
shu

2000—2030年云贵高原碳储量和生境质量时空格局演变

  • 1.

    自然资源要素耦合过程与效应重点实验室, 北京 100055

  • 2.

    新疆大学地理与遥感科学学院, 新疆 乌鲁木齐 830017

  • 3.

    中国地质调查局自然资源综合调查指挥中心, 北京 100055

  • 4.

    金沙江高山峡谷区水土资源演化与固碳增汇效应云南省野外科学观测研究站, 云南 楚雄 651400

  • 5.

    中国地质调查局昆明自然资源综合调查中心, 云南 昆明 650111

  • 基金项目: 中国地质调查局项目《自然资源要素监测与综合观测工程》（编号：DD20230112）、《云南中北部干热河谷区土壤侵蚀调查监测与评价》（编号：DD20220888）、《自然资源观测监测一体化技术体系研究》（编号：DD20230514），中国地质科学院基础科研业务费用专项资金《黄河三角洲滨海盐土植被对浅层地下水变化的响应》（编号：JKYQN202362），荒漠−绿洲生态监测与修复工程技术创新中心开放基金课题《开孔河流域绿洲耕地扩张的水土资源匹配与生态格局优化研究》（编号：2023KFKTA001）
详细信息
    作者简介: 郭佳晖（1998− ），男，在读硕士生，从事自然资源学和地理信息科学。E-mail：734908307@qq.com
    通讯作者: 刘晓煌（1972− ），男，博士，正高级工程师，从事自然资源观测研究。E-mail：15313256806@mail.cgs.gov.cn

  • 中图分类号: X171.1; P96

Evolution of spatial and temporal patterns of carbon stocks and habitat quality on the Yunnan-Guizhou Plateau during 2000—2030

  • 1.

    Key Laboratory of Natural Resource Coupling Process and Effects, Ministry of Natural Resources, Beijing 100055, China

  • 2.

    College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, Xinjiang, China

  • 3.

    Command Center of Natural Resource Comprehensive Survey, China Geological Survey, Beijing 100055, China

  • 4.

    Yunnan Province Field Science Observation and Research Station on the Evolution of Soil and Water Resources and the Carbon Sequestration Enhancement Effects in the Alpine Gorge Area of the Jinsha River, Chuxiong 651400, Yunnan, China

  • 5.

    Kunming General Survey of Natural Resources Center, China Geological Survey, Kunming 650111, Yunnan, China

More Information

    摘要

  • 云贵高原岩溶地质条件导致当地的石漠化严重、生态环境脆弱，对该地区的生态系统服务功能进行评价有助于改善生态环境问题。基于InVEST模型和PLUS模型定量评估了云贵高原2000—2030年的碳储量和生境质量，结合自然资源区划，分析该地区2000—2030年碳储量和生境质量的时空变化特征及驱动因子。结果表明： 2000—2030年云贵高原碳储量均值为7.323×109 t，多年呈现下降趋势，共减少0.471×109 t，空间上呈西部高、东部低的特征，最高的四级区划是丽江市东部楚雄北部小区；碳储量贡献率最高的地类是林地（>60%），其次是耕地（>28%）；碳储量空间分异解释力最强的因子是高程，交互作用最强的因子是土地利用和坡向。 2000—2030年云贵高原生境质量均值为0.755，多年呈下降趋势，共减少0.016，空间上呈现西部高、中部和东部低的特征，最高的四级区划是丽江市西部—怒江傈僳族自治州东南部小区；林地的生境质量最高，指数为0.83。研究结果揭示了云贵高原碳储量与生境质量演变规律及分布格局，可为该区生态环境建设提供科学依据。

    The karst geological conditions of the Yunnan–Guizhou Plateau have led to serious rocky desertification and fragile ecological environment. Evaluating the ecosystem service function of the region can help to improve ecological environment problems. Based on the InVEST model and PLUS model, the carbon stock and habitat quality of the Yunnan–Guizhou Plateau from 2000 to 2030 are quantitatively evaluated. Combined with natural resource zoning, the temporal and spatial variation characteristics and driving factors of carbon stock and habitat quality in the region from 2000 to 2030 are analyzed. The results show that from 2000 to 2030, the average carbon stock of the Yunnan–Guizhou Plateau is 7.323 × 109 t, showing a downward trend over the years, with a total reduction of 0.471 × 109 t. Spatially, it was characterized by high in the west and low in the east. The highest fourth-level zoning was the subdivision of the northern part of Chuxiong in the eastern part of Lijiang City. The land type with the highest contribution to carbon stock was the forest land (>60%), followed by cultivated land (>28%). The factor with the strongest explanatory power for the spatial differentiation of carbon stocks was elevation, and the factor with the strongest interaction was land use and slope direction. From 2000 to 2030, the average habitat quality of the Yunnan–Guizhou Plateau is 0.755, showing a downward trend over the years, with a total reduction of 0.016. Spatially, it was characterized by high in the west and low in the middle and east. The highest fourth-level zoning was the subdivision in the west of Lijiang City and the southeast of Nujiang Lisu Autonomous Prefecture. The habitat quality of forest land is the highest, with an index of 0.83. The research results reveal the evolution law and distribution pattern of carbon stock and habitat quality on the Yunnan–Guizhou Plateau, which can provide a scientific basis for the ecological environment construction of the region.

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  • 图 1  研究区地理位置及高程

    Figure 1. 

    下载: 全尺寸图片 幻灯片

    图 2  技术流程图

    Figure 2. 

    下载: 全尺寸图片 幻灯片

    图 3  云贵高原2000—2030年碳储量空间分布（碳储量单位为t/km2）

    Figure 3. 

    下载: 全尺寸图片 幻灯片

    图 4  云贵高原2000—2020年不同区划碳储量

    Figure 4. 

    下载: 全尺寸图片 幻灯片

    图 5  各土地利用类型的碳储量

    Figure 5. 

    下载: 全尺寸图片 幻灯片

    图 6  碳储量驱动因子交互探测结果

    Figure 6. 

    下载: 全尺寸图片 幻灯片

    图 7  云贵高原2000—2030年生境质量等级空间分布

    Figure 7. 

    下载: 全尺寸图片 幻灯片

    图 8  云贵高原2000—2020年各四级区划生境质量指数雷达图

    Figure 8. 

    下载: 全尺寸图片 幻灯片

    图 9  云贵高原2000—2020年各地类生境质量指数

    Figure 9. 

    下载: 全尺寸图片 幻灯片

    图 10  云贵高原不同海拔下生境质量指数分布

    Figure 10. 

    下载: 全尺寸图片 幻灯片

    表 1  数据来源信息

    Table 1.  Information sheet on data sources

    数据类型 数据名称 数据来源 年份
    气候环境数据 年平均实际蒸散量 国家青藏高原数据中心（http://data.tpdc.ac.cn） 2000—2020年
    年降水数据 资源环境科学数据注册与出版系统（http://www.resdc.cn/DOI） 2000—2020年
    NDVI
    土地利用数据
    高程数据 地理空间数据云（http://www.gscloud.cn/home） 2020年
    流域数据 https://www.hydrosheds.org/ 2020年
    土壤数据 国家地球系统科学数据中心（http://soil.geodata.cn/） 2020年
    社会经济数据 国内生产总值、人口数据 资源环境科学数据注册与出版系统（http://www.resdc.cn/DOI） 2019年
    铁路数据 全国地理信息资源目录服务系统（https://www.webmap.cn） 2020年
    高速公路数据
    国道/二级道路数据
    下载: 导出CSV

    表 2  云贵高原不同土地利用类型碳密度

    Table 2.  Carbon intensity of different land use types on the 　　　　　　　　Yunnan−Guizhou Plateau 　　　　t/hm2

    土地类型地上碳密度地下碳密度土壤碳密度死亡有机物碳密度
    耕地1.970.3823.931.00
    林地20.3667.72171.507.80
    草地6.4817.8371.000
    建设用地0.08000
    未利用地0.04000
    下载: 导出CSV

    表 3  各威胁源的敏感性及生境适宜度

    Table 3.  Sensitivity and habitat suitability of each threat source

    生境类型 生境适宜度 D耕地 D建设用地 D未利用地
    耕地 0.5 0.3 0.4 0.4
    林地 1 0.45 0.8 0.2
    草地 0.7 0.45 0.6 0.3
    水域 0.9 0.6 0.8 0.3
    建设用地 0 0 0 0
    未利用地 0.2 0.2 0.2 0.2
    下载: 导出CSV

    表 4  胁迫因子最大影响距离及权重

    Table 4.  Maximum impact distance and weight of stressors

    威胁因子耕地建设用地未利用地
    最大胁迫距离/km4102
    权重0.610.5
    空间衰退类型指数指数指数
    下载: 导出CSV

    表 5  驱动因子探测结果

    Table 5.  Driver detection results

    因子 产水量 高程 坡度 坡向 蒸散发 降雨 NDVI 土地利用
    q 0.041 0.372 0.190 0.293 0.110 0.243 0.184 0.243
    下载: 导出CSV
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