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Modeling leaf maximum net photosynthetic rate of Festuca pallescens, the dominant perennial grass of Patagonian pine-based silvopastoral systems

机译:模拟以巴塔哥尼亚松为主的牧草牧草系统的多年生优势草白桦(Festuca pallescens)的叶片最大净光合速率

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The integrated relationship in a simple mechanistic model between the critical environmental factors controlling leaf photosynthesis of understory species would be a useful tool to optimize the management of the silvopastoral systems. Individual effect of leaf temperature, water stress and light environment over net maximum photosynthetic rate (Pmax) was evaluated on Festuca pallescens leaves grown in a silvopastoral system of two Pinus ponderosa canopy covers (350 and 500 trees ha(-1)) and natural grassland. The aim was to integrate individual functions for Pmax against these environmental factors into a multiplicative model. We measured pre-dawn water potential (psi (pd)), leaf temperature and net photosynthetic rate (Pn), stomatal conductance (gs) and intercellular CO2 concentration (Ci) as a function of photosynthetic photon flux density (PPFD). The highest Pmax under non-limiting conditions was 20.4 mu mol CO2 m(-2) s(-1) and was defined as standardized dimensionless Pmax (s) = 1 for comparison of environmental factors. The leaf temperature function showed an optimum range between 20.2 and 21.8A degrees C where Pmax (s) = 1. Then, Pmax (s) declined by an average 1 mu mol CO2 m(-2) s(-1) C-1 from the optimum to 4.7 and 38.5A degrees C. Pmax (s) decreased at a rate of 9.49 mu mol CO2 m(-2) s(-1) MPa-1 as water potential reaches -1.9 MPa and showed a lower slope as water potential decreased down to -4.3 MPa. The light environment was estimated from hemispherical photograph analysis. Pmax (s) was 20% higher in leaves of open control plants than under the maximum tree canopy cover. The simple multiplicative model accounted for 0.82 of the variation in Pmax. Such a simple mechanistic model is the first step towards a more effective decision support tool.
机译:在简单的机械模型中,控制林下种的叶片光合作用的关键环境因素之间的整合关系将是优化林牧系统的管理的有用工具。在由两个美国黄松冠层覆盖物(350和500棵树ha(-1))和天然草地的牧草系统中生长的Festuca pallescens叶片上,评估了叶温,水分胁迫和光照环境对净最大光合速率(Pmax)的个体影响。 。目的是将针对这些环境因素的Pmax的各个功能集成到乘法模型中。我们测量了黎明前的水势(psi(pd)),叶片温度和净光合速​​率(Pn),气孔导度(gs)和细胞间CO2浓度(Ci)作为光合作用光子通量密度(PPFD)的函数。非限制性条件下的最高Pmax为20.4μmol CO2 m(-2)s(-1),并定义为标准无量纲Pmax(s)= 1,以比较环境因素。叶片温度函数显示出在20.2和21.8A摄氏度之间的最佳范围,其中Pmax(s)=1。然后,Pmax(s)平均下降1μmol CO2 m(-2)s(-1)C-1当水势达到-1.9 MPa时,Pmax以9.49μmol CO2 m(-2)s(-1)MPa-1的速率从最佳温度降至4.7和38.5A摄氏度。水势降低至-4.3 MPa。根据半球照片分析估计光环境。与对照最大树冠覆盖相比,开放对照植物的叶子中的Pmax(s)高20%。简单的乘法模型占Pmax变化的0.82。这种简单的机械模型是朝着更有效的决策支持工具迈出的第一步。

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