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A new approach for estimating fine root production in forests: a combination of ingrowth core and scanner

机译:估算森林细根产量的新方法:向内生长核和扫描仪的组合

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Estimating fine root (diameter <= 2 mm) production has been difficult. The best method remains unknown because each method has potential biases associated with the estimation methods and field techniques applied, leading to over- or underestimation. In this study, a new method combining ingrowth core and scanner named as "combined method" was described, and it was applied to a Quercus serrata plantation in Tsukuba, Japan. Comparing accuracy of estimation of fine root production by decision matrix and continuous inflow method using ingrowth core with that by "combined method" was conducted. Closed-box protected scanners and ingrowth cores were buried in a field on December 6, 2012, and fine root images were nondestructively scanned biweekly for growth measurement. In addition, thermometers were used to record temperature automatically at 1 m from the ground and at a depth of 10 cm in soil at 12 a.m. daily to evaluate the effect of temperature on fine root production. The results indicated that the combined method gave 19 and 16 % higher estimation of fine root production than decision matrix and continuous inflow method, respectively. In the combined method, using scanned images at different time intervals gave different estimates. Generally, longer time-interval images gave lower estimates: biweekly-interval images yielded an estimate that was 16 % higher than that yielded using 2-month-interval images. A 1-month time lag relationship (R (2) = 0.84, p < 0.01) between soil temperature and fine root production was found at the study site. This relationship implied that higher fine root production occurred in summer. It was concluded that the combined method gave a more accurate estimation of fine root production in forests among the three methods compared.
机译:很难估计细根(直径<= 2 mm)的产量。最好的方法仍然未知,因为每种方法都有与估计方法和应用的现场技术相关的潜在偏差,从而导致过高或过低的估计。在这项研究中,描述了一种将向内生长核和扫描仪结合在一起的新方法,称为“结合方法”,并将其应用于日本筑波的锯齿栎人工林。通过决策矩阵和采用向内生长核的连续流入法估算细根产量的准确性与通过“组合法”估算的准确性进行了比较。 2012年12月6日,将一盒封闭的受保护的扫描仪和向内生长的核埋葬在一块田地中,每两周对无损的细根图像进行无损扫描以进行生长测量。此外,每天早上12点,使用温度计自动记录距地面1 m和土壤深10 cm处的温度,每天12 am,以评估温度对细根生产的影响。结果表明,与决策矩阵法和连续流入法相比,组合法对细根产量的估算分别高出19%和16%。在组合方法中,使用不同时间间隔的扫描图像会得出不同的估计值。通常,较长时间间隔的图像给出的估计值较低:双周间隔图像得出的估计值比使用2个月间隔图像得出的估计值高16%。在研究地点发现土壤温度与细根产量之间存在1个月的时间滞后关系(R(2)= 0.84,p <0.01)。这种关系暗示在夏天发生较高的细根产量。得出的结论是,在三种比较方法中,组合方法可以更准确地估算森林中细根的产量。

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