| 西南地区不同类型植被NPP时空演变及影响因素探究 |
| 摘要点击 814 全文点击 184 投稿时间：2023-02-15 修订日期：2023-03-27 |
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| 中文关键词 中国西南地区 不同植被类型 植被净初级生产力 时空演变 地理探测器 |
| 英文关键词 southwest China different vegetation types vegetation net primary productivity spatio-temporal variation Geo Detector |
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| 中文摘要 |
| 研究植被净初级生产力（NPP）时空变化规律并探明其驱动影响因素,对于深入了解植被时空变化,指导因地制宜的生态恢复与管理工程具有重要的现实意义.以MODIS NPP数据为基础,结合基于站点的气象数据、土地利用数据和植被类型数据,通过Theil-Sen Median斜率估计和Mann-Kendall显著性检验探究西南地区不同类型植被NPP时空演变特征,并结合稳定性分析和地理探测器揭示不同类型植被NPP空间分异的影响因素及影响因素间的交互作用.结果表明：①时间上,2000~2021年西南地区植被NPP、NPPPre（仅气候变化影响下植被NPP）和NPPRes（仅人类活动影响下植被NPP）均呈波动上升趋势.在不同类型植被中,除乔木类植被NPPRes以-0.183 g·（m2·a）-1的速率呈微弱下降趋势外,其余类型植被NPP、NPPPre和NPPRes均呈上升趋势,其中,经济类植被NPP、NPPPre和NPPRes上升速率均最显著,分别为5.96、3.09和2.94 g·（m2·a）-1；空间上,下降趋势最大的乔木类植被NPP主要分布在西藏和云南南部,上升趋势最高的经济类植被NPP主要分布在四川省东部.西南地区植被NPP稳定性呈“南低北高”的空间分布格局,波动系数平均值以乔木类（0.101）、灌木类（0.105）、草本类（0.110）和经济类（0.114）的顺序依次升高.地表温度和相对湿度的交互作用是西南地区植被NPP空间分异的主要影响因素,而日照时数∩温暖指数对西南地区植被影响提升最大,提升百分比为30.91%；不同类型植被对不同气候因子需求存在差异,但对地表温度和温暖指数的需求存在高度一致性,当地表温度为21.03~28.49℃,温暖指数为106.46~167.2时,不同类型植被NPP均会达到峰值.自然演替下,气候对植被的影响程度与植被群落稳定性成反比,稳定性高的乔木类植被群落受气候影响小,稳定性低的草本类植被群落受气候影响大,而经济类植被由于受人类活动的影响,导致气候对其影响程度与稳定性成正比.研究结果可为调查区域气候变化对不同类型植被生长影响,制定因地制宜的西南地区生态恢复治理方案提供理论依据. |
| 英文摘要 |
| 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. |
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