摘要:
植被净初级生产力作为反映植被生态系统对气候变化响应的重要指标，是长期以来备受世界各国关注的焦点问题。基于2001~2022年MODIS NPP以及同年期气候变化和土地利用等数据，本文以黄淮海平原为研究区域，采用趋势分析、偏相关分析等方法研究黄淮海平原植被净初级生产力（NPP）时空变化规律；此外，本文还运用多元回归残差分析方法研究气候变化和人类活动对黄淮海平原植被NPP变化的相对贡献度，并进一步研究了引起植被NPP变化的主要驱动力。结果表明：（1）2001~2022年黄淮海平原植被NPP均值总体呈现波动增长趋势，以5.19 gC·m-2·a-1的速率逐年递增。省域尺度上，研究区内植被NPP由高到低的省份依次为河南省>山东省>河北省>北京市>天津市，即研究区植被NPP空间上总体表现为南高北低的分布特征。（2）黄淮海平原植被NPP变化趋势以增加趋势为主。其中极显著增加区占研究区总面积的44.88%。此外，研究区内河南省植被NPP变化趋势以变化不显著为主，表明河南省植被NPP变化较小。（3）黄淮海平原植被NPP与平均气温和降水呈正偏相关性。偏相关系数均值绝对值大小和偏相关显著性、极显著性面积占比等方面的对比研究表明降水是影响黄淮海平原植被NPP的主要气候因素。（4）研究区植被NPP的变化主要受气候和人类活动的共同影响，其次主要受人类活动影响。省域尺度上，北京市和山东省植被NPP升高受气候变化和人类活动的影响相当，主要以共同作用为主。天津市、河北省植被NPP升高受气候变化和人类活动共同主导作用，其次为气候变化主导作用。河南省植被NPP升高受气候变化和人类活动共同主导作用，其次为人类活动主导作用。探究黄淮海平原植被NPP时空演变，并揭示其主要驱动力，可为研究区植被建设管理、生态安全预警提供数据支撑和辅助决策。
Abstract:
Vegetation net primary productivity (NPP) as an important indicator reflecting the response of vegetation ecosystems to climate change has been concerned by many countries around the world for a long time. Taking the Huanghuaihai Plain as the study area, this paper uses MODIS NPP from 2001 to 2022 and climate change and land use data during the same period, and employs trend analysis, partial correlation analysis and other methods to study the temporal and spatial changes of vegetation NPP in the study area. In addition, this study uses a multiple regression residual analysis method to study the relative contribution of climate change and human activities to the change of vegetation NPP in the Huanghuai Plain and further to determine the main drivers of vegetation NPP change. The results show that: (1) The average vegetation NPP in the Huanghuaihe Plain from 2001 to 2022 showed a fluctuating growth trend overall, increasing by 5.19 gC·m-2·a-1 per year. At the provincial scale, the provinces with the highest vegetation NPP in order from high to low are Henan Province, Shandong Province, Hebei Province, Beijing City, and Tianjin City, indicating that the spatial distribution of vegetation NPP in the study area generally shows a south-high-north-low pattern. (2) The trend of vegetation NPP change in the Huanghuaihe Plain is mainly an increasing trend. Among them, the extremely significant increase area accounts for 44.88% of the total study area. In addition, the trend of vegetation NPP change in Henan Province is mainly characterized by insignificant change, indicating that the vegetation NPP change in Henan Province is relatively small. (3) Vegetation NPP in the Huanghuaihai Plain is positively correlated with average temperature and precipitation. The comparison study on the magnitude of the correlation coefficient, the proportion of significant and extremely significant areas of the correlation, etc., indicates that precipitation is the main climate factor affecting the NPP of vegetation in the Huanghuaihai Plain. (4) The change of vegetation NPP in the study area is mainly affected by the combined effects of climate and human activities, followed by the main effects of human activities. At the provincial scale, the increase of vegetation NPP in Beijing and Shandong is mainly due to the combined effects of climate change and human activities, with the main effect being the combined effect. The increase of vegetation NPP in Tianjin and Hebei is mainly dominated by the combined effects of climate change and human activities, followed by the dominant effect of climate change. The increase of vegetation NPP in Henan is mainly dominated by the combined effects of climate change and human activities, followed by the dominant effect of human activities. Studying the spatial and temporal evolution of vegetation NPP in the Huanghuaihai Plain and revealing its main driving force can provide data support and assist decision-making for vegetation construction management and ecological safety warning in the study area.
百度学术
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