Spatio-temporal Variation in Net Primary Productivity of Different Vegetation Types and Its Influencing Factors Exploration in Southwest China

被引：1
|
作者：
Xu Y. [1 ]
Zheng Z.-W. [1 ]
Meng Y.-C. [2 ]
Pan Y.-C. [1 ]
Guo Z.-D. [1 ]
Zhang Y. [1 ]
机构：
[1] College of Geomatics and Geoinformation, Guilin University of Technology, Guilin
[2] Department of Spatial Planning, Technical University of Dortmund, Dortmund
来源：
Huanjing Kexue/Environmental Science | 2024年 / 45卷 / 01期
关键词：
different vegetation types; Geo Detector; southwest China; spatio-temporal variation; vegetation net primary productivity;
D O I：
10.13227/j.hjkx.202302121
中图分类号：
学科分类号：
摘要：
Studying the spatiotemporal variation in vegetation net primary productivity（NPP）and exploring its influencing factors are of considerable practical significance for understanding the spatiotemporal variation in vegetation and for guiding ecological restoration and management projects based on local conditions. Based on MODIS NPP data，combined with in situ meteorological data，land use data，and vegetation type data，this study explores the spatiotemporal variation in different types of vegetation NPP in southwest China via the Mann-Kendall significance test and Theil-Sen Median slope estimator. It reveals the influencing factors of spatial differentiation of different types of vegetation NPP and the interaction between influencing factors in combination with stability analysis and Geo Detectors. The results revealed that on the temporal scale，from 2000 to 2021，vegetation NPP，NPPPre（vegetation NPP exclusively under the influence of climate change），and NPPRes（vegetation NPP exclusively under the influence of human activities）in southwest China showed a fluctuating upward trend. Among different vegetation types，NPP，NPPPre，and NPPRes exhibited an upward trend，except for a minor decline in NPPRes of tree vegetation at a rate of -0. 183 g·（m2·a）-1. Among them，NPP，NPPPre，and NPPRes of economic vegetation showed the most significant upward rates，5. 96，3. 09，and 2. 94 g·（m2·a）-1，respectively. On the spatial scale，the tree vegetation NPP with the most significant downward trend was mainly distributed in Tibet and southern Yunnan，while the economic vegetation NPP with the highest upward trend was primarily distributed in eastern Sichuan Province. The stability of vegetation NPP in southwest China presented a spatial distribution pattern of "low in the south and high in the north，" and the average value of the correlation coefficient increased in the ascending order of arbor vegetation（0. 101），shrub vegetation（0. 105），herb vegetation（0. 110），and economic vegetation（0. 114）. The interaction between surface temperature and relative humidity was the main influencing factor for spatial differentiation of vegetation NPP，while the interaction between sunshine duration and warmth index had the most significant impact on vegetation in southwest China，with an increasing percentage of 30. 91%. Different types of vegetation had different requirements for different climatic factors，but their requirements for surface temperature and warmth index were significantly consistent. When the surface temperature was 21. 03-28. 49℃，and the warmth index was 106. 46-167. 2，the NPP of different vegetation types peaked. Under natural succession，the impact of climate change on vegetation was inversely proportional to the stability of the vegetation community. The arbor vegetation community with high stability was less affected，while the herb vegetation community with low stability was highly affected by climate. In contrast，the stability of economic vegetation was directly proportional to the impact of climate due to the influence of human activities. This study establishes a theoretical foundation for evaluating the impact of regional climate on the growth of different vegetation types and can be crucial for formulating ecological restoration and management strategies in southwest China that are adapted to the local conditions. © 2024 Science Press. All rights reserved.
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页码：262 / 274
页数：12
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