中国不同植被类型对潜在蒸散量和降水量的响应

Haojie Liu, Wei Wei, GuangLei Zhu, Yibo Ding, Xiongbiao Peng
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摘要

全球气候变化被认为是世界上最大的环境威胁之一。预计它将极大地改变全球水文循环。水循环的两个主要组成部分--潜在蒸散量(PET)和降水量(P)与植被动态密切相关。本研究采用偏相关分析方法,以网格单元为基础,分析归一化植被指数(NDVI)与气候因子(PET 和 P)之间的关系。PET 采用 FAO-56 Penman-Monteith 方法计算。此外,我们还研究了不同植被覆盖类型的 NDVI 和气候因子。结果表明,中国的草地、森林和耕地与 PET 和 P 呈正相关。森林植被的 NDVI 与 PET、P 的偏相关系数在华北地区较高,而相关时间尺度的空间分布则相反。华北地区森林植被的 NDVI 与 PET、P 的偏相关系数较高。然而,相关时间尺度的空间分布却相反。耕地植被 NDVI 与 PET、P 的相关系数以及与 PET 相关的时间尺度具有明显的空间异质性。华北地区耕地植被 NDVI 与 P 的相关时间尺度约为 2 个月。磷对研究区各类植被的生长影响较大,其中草地植被受磷影响的时间尺度最短。我们将本研究结果与其他相关研究结果进行了比较和分析。这些结果为探索不同植被类型的动态变化及其影响因素提供了参考。
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The different vegetation types responses to potential evapotranspiration and precipitation in China
Global climate change is considered one of the greatest environmental threats in the world. It is expected to significantly change the global hydrological cycle. The two main water cycle components, potential evapotranspiration (PET) and precipitation (P), are closely related to vegetation dynamics. In this study, the partial correlation analysis method was used to analyzed the relationship between Normalized Difference Vegetation Index (NDVI) and climate factors (PET and P) based on grid cells. PET was calculated by FAO-56 Penman–Monteith method. Moreover, we also investigated the NDVI and climate factors in different vegetation cover types. The results showed that grassland, forest and cropland in China were positively correlated with PET and P. The time scales of the maximum partial correlation coefficients between NDVI and PET of grassland vegetation were mostly longer than 5–6 months. These time scales were longer than the time scales related to P. The partial correlation coefficients between NDVI and PET, P of forest vegetation were higher in northern China, whereas the spatial distribution of related time scales was the opposite. The partial correlation coefficients between NDVI and PET, P of forest vegetation were higher in northern China. However, the spatial distribution of related time scales was the opposite. The correlations between NDVI and PET, P of cropland vegetation and the time scales related to PET had clear spatial heterogeneity. The time scale of the correlation between NDVI and P for cropland in the northern China was about 2 months. P had a strong influence on the growth of various types of vegetation in the study area, and grassland vegetation was affected by P over the shortest time scale. We compare and analyze the results of this study with other related studies. These results provide a reference for exploring the dynamic changes in different vegetation types and factors impacting them.
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