基于域—生物群系—功能群分类的生态系统类型识别及时空格局变化分析——以河北省太行山区为例

毕善婷; 陈影; 李泽; 屈爽; 赵文超; 梁阅兵

doi:10.13961/j.cnki.stbctb.2024.02.025

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基于域—生物群系—功能群分类的生态系统类型识别及时空格局变化分析——以河北省太行山区为例

试验研究

- 基于域—生物群系—功能群分类的生态系统类型识别及时空格局变化分析——以河北省太行山区为例
- Ecosystem Type Recognition and Spatiotemporal Pattern Change Analysis Based on Realms-Biomes-Ecosystem Classification—A Case Study of Taihang Mountains Area in Hebei Province
- 水土保持通报 2024年44卷第2期页码：236-244
- 作者机构：
  
  1. 河北农业大学国土资源学院,河北,保定,071000
  2. 河北省农田生态环境重点实验室,河北,保定,071000
  3. 河北农业大学资源与环境科学学院,河北,保定,071000
- 作者简介：
- 基金信息：
  
  河北省重点研发项目“基于障碍特征分异的河北省滨海盐碱地生态改良关键技术研究”(20327506D);国家自然科学基金项目“农村居民点空闲地形成机理及其再利用模式”(42071249);河北省科技厅科技对口合作项目“阳原县盐碱地适宜作物种植技术示范与推广”
- DOI：10.13961/j.cnki.stbctb.2024.02.025
  中图分类号： X171.1
- 纸质出版：2024
- 稿件说明：
移动端阅览
毕善婷, 陈影, 李泽, 等. 基于域—生物群系—功能群分类的生态系统类型识别及时空格局变化分析——以河北省太行山区为例[J]. 水土保持通报, 2024,44(2):236-244.

Bi Shanting, Chen Ying, Li Ze, et al. Ecosystem Type Recognition and Spatiotemporal Pattern Change Analysis Based on Realms-Biomes-Ecosystem Classification—A Case Study of Taihang Mountains Area in Hebei Province[J]. Bulletin of Soiland Water Conservation, 2024, 44(2): 236-244.
毕善婷, 陈影, 李泽, 等. 基于域—生物群系—功能群分类的生态系统类型识别及时空格局变化分析——以河北省太行山区为例[J]. 水土保持通报, 2024,44(2):236-244. DOI： 10.13961/j.cnki.stbctb.2024.02.025.

Bi Shanting, Chen Ying, Li Ze, et al. Ecosystem Type Recognition and Spatiotemporal Pattern Change Analysis Based on Realms-Biomes-Ecosystem Classification—A Case Study of Taihang Mountains Area in Hebei Province[J]. Bulletin of Soiland Water Conservation, 2024, 44(2): 236-244. DOI： 10.13961/j.cnki.stbctb.2024.02.025.

摘要

[目的

]

科学识别河北省太行山区生态系统类型，是理解河北省太行山区生态系统时空分布格局和支撑生态系统分类管理的基础。 [方法

]

基于域—生物群系—功能群(RBE)的分类原理，构建了包括3个1级，8个2级和24个3级类的生态系统分类体系，并集成多源数据，开展了2000和2020年的河北省太行山区生态系统的分类制图。基于RUSLE模型、InVEST模型和热点分析等方法，分析生态系统服务的时空格局演变。 [结果

]

①河北省太行山区20 a间建设用地生态系统增加最多，主要来自农田生态系统。农田生态系统缩减了61 105.95 hm

，以雨养农田为主。受人类活动的影响，河流和人工湿地面积分别增加了5 584.32和2 535.66 hm

，而林地和草地生态系统减幅分别为0.96%和8.18%。未利用地生态系统受研究区生态保护措施影响减少5 800.68 hm

。 ②生态系统服务值受生态系统类型分布影响总体呈现西高东低的分布格局，除粮食供给服务为西低东高，主要是由于农田主要分布在东部地区。 ③冷热点区域空间分布整体上具有重叠性，但仍有差异。 [结论

]

提出的分类体系具有可行性，分类精度达到80%以上，符合研究区的生态系统类型变化趋势，可为识别山区生态系统分类和生态系统保护修复政策提供科学支撑，进而促进山区生态发展目标和可持续发展的实现。

Abstract

[Objective] The ecosystem types in the Taihang Mountain area of Hebei Province were scientifically identified in order to provide a basis for understanding the spatial and temporal distribution pattern of ecosystems in the area and to support ecosystem classification management. [Methods] Based on the classification principle of realms-biomes-ecosystem (RBE) functional groups

a classification system including 3 primary classes

8 secondary classes and 24 tertiary classes was constructed

and multi-source data was integrated to carry out classification mapping of the ecosystems in the Taihang Mountains area in Hebei Province in 2000 and 2020. The spatio-temporal evolution of ecosystem services was analyzed based on the RUSLE model

the InVEST model

and hot spot analysis. [Results] ① The construction land ecosystem in the Taihang Mountain area increased the most during the past 20 years

mainly coming from the farmland ecosystem. The farmland ecosystem decreased by 61 105.95 hm2 and was dominated by rain-fed farmland. Due to the influence of human activities

the areas of rivers and constructed wetlands increased by 5 584.32 hm2 and 2 535.66 hm2

respectively

while the areas of forest and grassland ecosystems decreased by 0.96% and 8.18%

respectively. The area of the unused land ecosystem decreased by 5 800.68 hm2 due to the ecological protection measures instituted in the study area. ② The distribution of ecosystem types affected the overall distribution pattern of ecosystem service values

with high values in the west and low values in the east. The exception was for food supply service values where the distribution was low in the west and high in the east

mainly because farmland was located in the eastern region. ③ The spatial distribution of cold spots and hot spots generally overlapped

but there were still differences. [Conclusion] The classification system proposed in this study is feasible

with a classification accuracy of greater than 80%

which is in line with the trend for ecosystem type changes in the study area. This classification system can provide scientific support for the identification of mountain ecosystem classification and ecosystem protection and restoration policies

thereby promoting the realization of mountain ecological development goals and sustainable development.

关键词

Keywords

references

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