Examination of the extinction coefficient in the Beer–Lambert law for an accurate estimation of the forest canopy leaf area index
Examination of the extinction coefficient in the Beer–Lambert law for an accurate estimation of the forest canopy leaf area index
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DOI：
10.1080/21580103.2012.673744
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发表时间：
2012-05
影响因子：
1.9
通讯作者：
T. Saitoh;S. Nagai;H. Noda;H. Muraoka;K. Nasahara
中科院分区：
文献类型：
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作者：
T. Saitoh;S. Nagai;H. Noda;H. Muraoka;K. Nasahara
叶面积指数(LAI)是反映冠层结构和控制生态系统许多功能和过程的重要生态参数，但叶面积指数的直接测量和长期监测是困难的，尤其是在森林中。估算森林叶面积指数季节格局的一种间接方法是测量树冠对光合作用有效辐射(PAR)的衰减，然后根据Beer-Lambert定律计算叶面积指数。使用这种方法需要估计PAR消光系数(K)，这是计算PAR衰减所需的参数。然而，k的测定本身需要直接测量各季节的叶面积指数。我们的目标是确定(1)模拟森林中可能随季节变化的k值的最佳方法，以及(2)冠层生态系统功能估计对估计叶面积指数的误差的敏感性。本文首先利用Beer-Lambert定律的倒置形式，分析了日本落叶阔叶林在阴天和晴天条件下的“真”k(Kp)的季节格局。接下来，我们计算了假设常数k(LAIpred)时基于PAR的LAI估计的误差，并确定在什么条件下我们应该期望k在生长期内近似恒定。最后，我们考察了LAIpred的误差对使用LAIpred作为输入参数的陆面模式计算的总初级生产(GPP)、净生态系统生产(NEP)和潜热通量(LE)的估计的影响。在整个生育期，多云的kp变化在0.47到1.12之间，晴天的kp变化在0.45到1.59之间。结果表明，在完全落叶期(0.53-0.57)，用多云条件下的kp可以很好地估计LAIpred的值。然而，LAIpred在5月和11月被高估了高达0.6m2-2。模拟碳通量和潜热通量的误差在GPP为-0.21~0.32gCm-2day-1，NEP为-0.09~0.19gCm-2day-1，LE为-3.2~3.9Wm-2，接近塔通量测量的测量误差。假设常数k估计的LAIpred对于某些生态系统研究是有用的，如果k等于在多云条件下测量的kp的值，特别是在完全落叶期间。
Leaf area index (LAI) is a crucial ecological parameter that represents canopy structure and controls many ecosystem functions and processes, but direct measurement and long-term monitoring of LAI are difficult, especially in forests. An indirect method to estimate the seasonal pattern of LAI in a given forest is to measure the attenuation of photosynthetically active radiation (PAR) by the canopy and then calculate LAI by the Beer–Lambert law. Use of this method requires an estimate of the PAR extinction coefficient (k), a parameter needed to calculate PAR attenuation. However, the determination of k itself requires direct measurement of LAI over seasons. Our goals were to determine (1) the best way to model k values that may vary seasonally in a forest, and (2) the sensitivity of estimates of canopy ecosystem functions to the errors in estimated LAI. We first analyzed the seasonal pattern of the “true” k (k p) under cloudy and sunny conditions in a Japanese deciduous broadleaved forest by using the inverted form of the Beer–Lambert law with the true LAI and PAR. We next calculated the errors of PAR-based LAIs estimated with an assumed constant k (LAIpred) and determined under what conditions we should expect k to be approximately constant during the growing period. Finally, we examined the effect of errors in LAIpred on estimates of gross primary production (GPP), net ecosystem production (NEP), and latent heat flux (LE) calculated with a land-surface model using LAIpred as an input parameter. During the growing period, cloudy k p varied from 0.47 to 1.12 and sunny k p from 0.45 to 1.59. Results suggest that the value of LAIpred was adequately estimated with the k p obtained under cloudy conditions during the fully-leaved period (0.53–0.57). However, LAIpred was overestimated by up to 0.6 m2 m–2 in May and November. The errors in LAIpred propagated to errors in modeled carbon and latent heat fluxes of –0.21 to 0.32 g C m–2 day–1 in GPP, –0.09 to 0.19 g C m–2 day–1 in NEP, and –3.2 to 3.9 W m–2 in LE, which is close to the measurement errors recognized in the tower flux measurement. LAIpred estimated with an assumed constant k can be useful for some ecosystem studies as a second-best alternative if k is equated to the value of k p measured under cloudy conditions especially during the fully-leaved period.