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Spatiotemporal Dynamics of Vegetation NEP and Identification of Key Driving Factors in Typical Karst Regions
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Pai Chen1, Anjun Lan1, Zemeng Fan2, 3, Wenyao Zhu1, Shishu Lian1, Kuisong Xiao1
Journal of Soil and Water Conservation | 2026, 40(4) : 9 - 22
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Journal of Soil and Water Conservation | 2026, 40(4): 9-22
• "Special Issue on Rocky Desertification Control and Ecological Restoration" •
Spatiotemporal Dynamics of Vegetation NEP and Identification of Key Driving Factors in Typical Karst Regions
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Pai Chen1, Anjun Lan1, Zemeng Fan2, 3, Wenyao Zhu1, Shishu Lian1, Kuisong Xiao1
Affiliations
  • 1.School of Geography and Environmental Sciences,Guizhou Normal University,Guiyang 550025,China
  • 2.State Key Laboratory of Resources and Environmental Information System,Institute of Geographic;Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China
  • 3.College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100039,China
Published: 2026-08-28 doi: 10.13870/j.cnki.stbcxb.2026.04.038
Outline
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Objective This study explores the spatiotemporal dynamics of vegetation net ecosystem productivity (NEP) and identifies its key driving factors in typical karst regions, providing a theoretical basis for the scientific understanding of carbon cycling mechanisms and the formulation of differentiated carbon neutrality strategies. Methods Vegetation NEP in Guizhou Province from 2000 to 2020 was quantitatively assessed based on an improved Carnegie-Ames-Stanford Approach (CASA) model and an empirical equation for soil microbial respiration. Theil-Sen Median trend analysis, Mann-Kendall significance test, Hurst index, and optimal parameters-based geographical detector were applied to systematically analyze the spatiotemporal variation trends, characteristics, and key driving factors of vegetation NEP in Guizhou. Results 1) During the study period, NEP across Guizhou increased significantly, indicating a continuous enhancement of carbon sequestration capacity. Spatially, NEP decreased from the south-central and southwestern regions to the northern and eastern regions. Vegetation NEP in karst regions [278.20 g/(m2·a)(based on C)] was significantly lower than that in non-karst regions [326.83 g/(m2·a)(based on C)], suggesting that differences in geological background were the core reason for divergence in carbon sequestration potential. 2) Across the province, changes in NEP mainly remained stable (50.31%) or showed an increasing trend (46.98%). Increasing trends were concentrated in the western and northeastern regions, while decreasing trends were distributed in the central and eastern regions. Mean Hurst index was 0.48, and areas with Hurst index below 0.5 accounted for 61.59%. 3) Lithology (q=0.41), as the core natural background factor, directly determined basic habitat conditions such as soil development, water retention, and nutrient conservation, while sunshine duration (q=0.35) was the key meteorological factor. Together, they established the inherent carbon sequestration potential of the region. The interactive effects of multiple factors were stronger than those of single factors. Notably, the interaction between sunshine duration and land use had explanatory power of 50%, representing the key driving factor regulating spatiotemporal patterns of carbon sequestration. Conclusion These findings provide scientific data support and decision-making reference for ecological conservation and restoration, carbon sequestration function enhancement, and sustainable development in ecologically fragile karst regions.

net ecosystem productivity (NEP)  /  Carnegie-Ames-Stanford Approach (CASA) model  /  karst region  /  spatiotemporal dynamics  /  driving mechanism
陈排, 兰安军, 范泽孟, 朱雯瑶, 练仕舒, 肖葵淞. 典型喀斯特地区植被NEP时空动态及关键驱动因素识别. 水土保持学报, 2026 , 40 (4) : 9 -22 . DOI: 10.13870/j.cnki.stbcxb.2026.04.038
Pai Chen, Anjun Lan, Zemeng Fan, Wenyao Zhu, Shishu Lian, Kuisong Xiao. Spatiotemporal Dynamics of Vegetation NEP and Identification of Key Driving Factors in Typical Karst Regions[J]. Journal of Soil and Water Conservation, 2026 , 40 (4) : 9 -22 . DOI: 10.13870/j.cnki.stbcxb.2026.04.038
Year 2026 volume 40 Issue 4
199
85
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Article Info
doi: 10.13870/j.cnki.stbcxb.2026.04.038
  • Receive Date:2026-02-03
  • Online Date:2026-09-30
  • Published:2026-08-28
Article Data
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History
  • Received:2026-02-03
  • Revised:2026-03-26
  • Accepted:2026-04-10
Funding
Affiliations
    1.School of Geography and Environmental Sciences,Guizhou Normal University,Guiyang 550025,China
    2.State Key Laboratory of Resources and Environmental Information System,Institute of Geographic;Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China
    3.College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100039,China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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