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Net primary productivity in Kazakhstan, its spatio-temporal patterns and relation to meteorological variables

机译:哈萨克斯坦的净初级生产力,时空格局及其与气象变量的关系

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Arid and semiarid environments are susceptible to environmental degradation and desertification. Modelling net primary productivity (NPP) and analysis of spatio-temporal patterns help to understand ecological functioning especially in these areas. In this study, we apply the Biosphere Energy Transfer Hydrology Model (BETHY/DLR) to derive NPP for Kazakhstan for 2003-2011. Results are analyzed regarding spatial, monthly, and inter-annual variations. Mean annual NPP for Kazakhstan is 143 g Cm~(-2) and maximum productivity is reached in June. Most monthly NPP anomalies occur in semiarid North of Kazakhstan. These regions seem to be most strongly affected by changes in meteorology and are likely to be vulnerable to changing climate. Arid ecosystems show lower inter-annual NPP variability than semiarid lands. Correlations between NPP and meteorological parameters reveal variable influence of temperature, PAR, and precipitation on vegetation productivity during the year. Reaction of vegetation growth to precipitation is delayed 1-2 months. Temperature is most critical in spring and precipitation in summer affects NPP in August-October. The results presented in this study help to identify regions that are vulnerable to global change. They allow predictions on possible effects of expected future climate change on vegetation productivity in arid and semiarid Kazakhstan and support sustainable land management.
机译:干旱和半干旱环境容易受到环境退化和沙漠化的影响。对净初级生产力(NPP)进行建模和时空模式分析有助于了解生态功能,尤其是在这些地区。在这项研究中,我们应用生物圈能量转移水文模型(BETHY / DLR)得出2003-2011年哈萨克斯坦的NPP。分析有关空间,每月和年度间变化的结果。哈萨克斯坦的年平均NPP为143 g Cm〜(-2),6月达到最高生产力。 NPP的每月大多数异常都发生在哈萨克斯坦北部的半干旱地区。这些地区似乎受到气象变化的影响最大,并且很容易受到气候变化的影响。干旱生态系统的年NPP变异性低于半干旱地区。 NPP与气象参数之间的相关性揭示了一年中温度,PAR和降水对植被生产力的可变影响。植被生长对降水的反应延迟了1-2个月。春季温度最关键,夏季降水影响8月至10月的NPP。这项研究提出的结果有助于确定容易受到全球变化影响的地区。他们可以预测未来气候变化对哈萨克斯坦干旱和半干旱地区植被生产力的可能影响,并支持可持续土地管理。

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