Spatial-temporal characteristics of 2000—2019 vegetation NPP of the Dongting Lake basin and their driving factors
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摘要: 植被净初级生产力(net primary production,NPP)是流域生态系统的重要评价指标,该文基于2000—2019年MODIS长时序NPP数据产品,分析了洞庭湖流域20 a间植被NPP时空变化规律,进而采用时空分析与地理探测器等方法揭示了气象、地表等驱动因素对研究区植被NPP的影响特征及贡献程度。结果表明: ①洞庭湖流域植被NPP多年均值为0.65 kgC/(m2·a),高值区域主要分布在流域西部及南部,低值区域则主要位于洞庭湖附近; ②2000—2019年,洞庭湖流域植被NPP呈现平稳上升趋势(y=0.003x+0.622 7, R2=0.437,p<0.001),增长区域主要位于流域西北及中部偏南,而减少区域主要在流域东北及西南边界地区,植被NPP重心在平衡发展中呈微弱迁移趋势; ③洞庭湖流域植被NPP变化总体上受气象因素(尤其是气温)影响较显著,但NPP空间特征则主要受土地利用影响,降水与高程次之。此外,不同因子间交互作用显著,主要表现为双因子增强(高程与土地利用或降水)及非线性增强(气温与降水、土地利用或高程,降水与土地利用)2种类型。研究结果有助于正确认识与把握洞庭湖流域NPP时空变化特征及其内在影响机制,从而为流域生态系统管理与治理提供科学的辅助依据。Abstract: The net primary productivity (NPP) of vegetation is a vital indicator for assessing a basin ecosystem. Based on a long time series of NPP data of 2000—2019 from a moderate resolution imaging spectroradiometer (MODIS), this study analyzed the spatio-temporal variations in the vegetation NPP of the Dongting Lake basin in the past 20 years. Then, it revealed the influence characteristics and contribution of driving factors (e.g., meteorology and ground surface) on the vegetation NPP of the study area using methods including the GIS spatio-temporal analysis and GeoDetector. The results are as follows. ① The NPP values in the study area have an average of 0.65 kgC/(m2·a), with high values mainly distributed in the west and south of the basin and low values concentrated near the lake. ② During 2000—2019, the vegetation NPP of the Dongting Lake basin presented a slightly rising trend (y=0.003x+0.622 7, R2=0.437, p<0.001). It increased in the northwest and south-central parts and decreased in the northeast and southwest boundaries, and its center of gravity slightly shifted. ③ The changes in the vegetation NPP of the Dongting Lake basin was significantly affected by meteorological factors (especially temperature). By contrast, its spatial characteristics were mainly affected by land use, followed by precipitation and DEM. In addition, the results suggested significant interactions between different factors, which was mainly reflected by the bi-factor enhancement (DEM and land use, or DEM and precipitation) and nonlinear enhancement (temperature and precipitation, land use and DEM, and precipitation and land use). The conclusions of this study help to correctly understand and grasp the spatio-temporal characteristics of the vegetation NPP of the Dongting Lake basin and their internal influencing mechanisms, thus providing a scientific basis for the management and governance of the ecosystem in the basin.
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Key words:
- Dongting Lake basin /
- vegetation NPP /
- spatio-temporal characteristics /
- driving factor
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