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Inter- and intra-annual variability of vegetation in the northern hemisphere and its association with precursory meteorological factors

机译：北半球植被的年际和年际变化及其与前兆气象因素的关系

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Determination of phenological variation is one of the most critical challenges in dynamic vegetation modeling, given the lack of a strong theoretical framework. Previous studies generally focused on the timing of a phenological event (e.g., bud-burst or onset of growing season) and its atmospheric prompts, but not on the interactive variations across phenological stages. This study, therefore, investigated the inter- and intra-annual variability existing in all the phenological stages and the relations of the variability with four meteorological variables (surface temperature (T s), shortwave radiation (SW), vapor pressure deficit (VPD), and precipitation (PRCP)) using a 25-year (1982-2006) dataset of leaf area index (LAI) from the Advanced Very High Resolution Radiometer (AVHRR). Our six study sites of each 4° × 4°grids (mixed forest in China, deciduous needle-leaf forest in Siberia, evergreen needle-leaf forest in western Canada, grass in Gobi, and crops in the Central United States and southeastern Europe) include various vegetation types, local climates, and land-use types in the mid-latitudes of the northern hemisphere. Empirical orthogonal function (EOF) analysis with detrended LAI anomalies identified the two leading EOF modes that account for the amplitude and phase of the monthly LAI variations. The inter-annual correlation between the principle components (PCs) of the two modes and the meteorological variables for spring and summer showed that the amplitude and phase modes (AM and PM, respectively) were affected by different dominant meteorological factors. Over most of the study regions, AM was positively correlated with PRCP and negatively with Ts, SW, and VPD, while PM was predominantly positively correlated with Ts. The contrasting responses of the two EOF modes to Ts reflect environmental limitations on plant growth such as early start of growth, but with a reduced value of maximum LAI in a year with a warm spring. In addition, insignificant correlations between AM and PRCP, as well as negative correlations between PM and PRCP, in the crop regions suggest that human interventions such as advanced irrigation systems also play a key role in vegetative activity.
机译：鉴于缺乏强大的理论框架，物候变化的确定是动态植被建模中最关键的挑战之一。以前的研究通常着重于物候事件的发生时间（例如爆发或生长期的爆发）及其大气提示，而不是着眼于物候阶段的互动变化。因此，本研究调查了所有物候期存在的年际和年内变异性，以及变异性与四个气象变量（表面温度（T s），短波辐射（SW），蒸气压赤字（VPD）的关系。和降水（PRCP）），使用了25年（1982-2006）的超高分辨率高分辨率辐射计（AVHRR）的叶面积指数（LAI）数据集。我们每个4°×4°网格的六个研究地点（中国的混交林，西伯利亚的落叶针叶林，加拿大西部的常绿针叶林，戈壁的草以及美国中部和东南欧的农作物）包括北半球中纬度地区的各种植被类型，当地气候和土地利用类型。经验LAE异常趋势的正交函数（EOF）分析确定了两种主要的EOF模式，这些模式说明了每月LAI变化的幅度和相位。两种模式的主成分（PCs）与春季和夏季的气象变量之间的年际相关性表明，振幅和相位模式（分别为AM和PM）受不同的主导气象因素影响。在大多数研究区域中，AM与PRCP正相关，与Ts，SW和VPD负相关，而PM与Ts正相关。两种EOF模式对Ts的不同响应反映了植物生长的环境限制，例如生长的早期开始，但是在春季温暖的一年中，最大LAI值降低了。此外，在作物区域中，AM和PRCP之间无显着相关，而PM和PRCP之间呈负相关，这表明诸如先进灌溉系统之类的人为干预在植物生长活动中也起着关键作用。

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