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Assessment of soil water carbon and nitrogen cycling in reseeded grassland on the North Wyke Farm Platform using a process-based model

机译:使用基于过程的模型评估North Wyke农场平台上的草场中土壤水碳和氮的循环

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摘要

The North Wyke Farm Platform (NWFP) generates large volumes of temporally-indexed data that provides a valuable test-bed for agricultural mathematical models in temperate grasslands. In our study, we used the primary datasets generated from the NWFP () to validate the SPACSYS model in terms of the dynamics of water loss and forage dry matter yield estimated through cutting. The SPACSYS model is capable of simulating soil water, carbon (C) and nitrogen (N) balance in the soil-plant-atmosphere system. The validated model was then used to simulate the responses of soil water, C and N to reseeding grass cultivars with either high sugar (Lolium perenne L. cv. AberMagic) or deep rooting (Festulolium cv. Prior) traits. Simulation results demonstrated that the SPACSYS model could predict reliably soil water, C and N cycling in reseeded grassland. Compared to AberMagic, the Prior grass could fix more C in the second year following reseeding, whereas less C was lost through soil respiration in the first transition year. In comparison to the grass cultivar of the permanent pasture that existed before reseeding, both grasses reduced N losses through runoff and contributed to reducing water loss, especially Prior in relation to the latter. The SPACSYS model could predict these differences as supported by the rich dataset from the NWFP, providing a tool for future predictions on less characterized pasture.
机译:North Wyke农场平台(NWFP)生成大量的时间索引数据,这些数据为温带草原上的农业数学模型提供了宝贵的试验平台。在我们的研究中,我们使用了从NWFP()生成的主要数据集来验证SPACSYS模型的失水动态和通过切割估算的牧草干物质产量。 SPACSYS模型能够模拟土壤-植物-大气系统中的土壤水分,碳(C)和氮(N)平衡。然后,使用经过验证的模型来模拟土壤水,碳和氮对高糖(黑麦草(Lolium perenne L. cv。AberMagic)或深根(Festulolium cv。Prior)性状的复种草苗的响应。仿真结果表明,SPACSYS模型可以可靠地预测草场草地土壤水,碳和氮的循环。与AberMagic相比,Prior草在播种后的第二年可固定更多的C,而在第一年的过渡期中通过土壤呼吸损失的C较少。与永久播种之前存在的永久性牧草的草种相比,两种草都减少了径流造成的氮损失,并有助于减少水的流失,特别是与后者有关的普里尔。 SPACSYS模型可以预测NWFP丰富的数据集所支持的差异,从而为将来对特征较少的牧场进行预测提供了工具。

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