Abstract

Aims

Accurate prediction of spatiotemporal variations in carbon and water fluxes of heterogeneous landscape is critical to comprehensively address the effects of climate change and vegetation dynamics on landscape and regional carbon and water cycling.

Methods

A field study was conducted to characterize the seasonal variations in gas fluxes and explore their relationships with abiotic and biotic factors in a small grassland landscape. Daytime carbon and water fluxes including net ecosystem exchange, gross ecosystem productivity, ecosystem respiration and evapotranspiration (ET) were measured for three types of grassland patches over a growing season using the closed chamber method. The key plant trait variables were measured, and functional variance (FDvar) was calculated based on community-weighted mean (CWM).

Important Findings

The results showed that the temporal variations in the carbon and water fluxes were regulated by meteorological, soil and community functional variables. Inclusion of the CWM and FDvar of plant trait measures greatly improved the degree of explanation of the predict models. Specific leaf area and leaf δ¹³C content (Lδ¹³C) were the most important trait variables in affecting the variations of the gas fluxes. CWMs indices had greater importance than FDvar indices in predicting the variation of the C fluxes but FDvar indices were more important for ET than C fluxes. Our findings demonstrated that mass ratio hypothesis and the complementary effects hypothesis are not mutually exclusive but have different relative importance for different ecosystem processes. Community functional traits played important roles in predicting the spatiotemporal variations of carbon and water fluxes in semiarid grassland.

中文翻译：

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植物性状对半干旱草原斑块中碳和水通量随时间变化的解释的贡献

摘要

目的

准确预测异质景观的碳和水通量的时空变化对于全面解决气候变化和植被动态对景观以及区域碳和水循环的影响至关重要。

方法

进行了野外研究，以表征通量的季节性变化，并探讨它们与小型草原景观中非生物和生物因子的关系。使用密闭室法测量了生长季内三种类型草地的白天碳和水通量，包括净生态系统交换，生态系统总生产力，生态系统呼吸和蒸散（ET）。测量了关键的植物性状变量，并基于社区加权平均值（CWM）计算了功能变异（FDvar）。

重要发现

结果表明，碳，水通量的时间变化受气象，土壤和群落功能变量的调节。CWM和FDvar包含植物性状度量极大地提高了预测模型的解释程度。比叶面积，叶δ ¹³ C的含量（LΔ ¹³C）是影响气体通量变化的最重要的性状变量。在预测碳通量的变化方面，CWMs指数比FDvar指数更重要，但对于ET而言，FDvar指数比C通量更重要。我们的发现表明，质量比假说和互补效应假说不是互斥的，但对不同的生态系统过程具有相对的重要性。群落功能性状在预测半干旱草地碳和水通量的时空变化中起着重要作用。