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- 저자 : Hibiki M. Noda (검색결과 1 건)
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Taku M. Saitoh,Shin Nagai,Hibiki M. Noda,Hiroyuki Muraoka,Kenlo Nishida Nasahara 한국산림과학회 2012 Forest Science And Technology Vol.8 No.2
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 (LAI_pred) 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 LAI_pred on estimates of gross primary production (GPP), net ecosystem production (NEP), and latent heat flux (LE) calculated with a land-surface model using LAI_pred as an input parameter. During the growing period, cloudy kp varied from 0.47 to 1.12 and sunny kp from 0.45 to 1.59. Results suggest that the value of LAI_pred was adequately estimated with the k_p obtained under cloudy conditions during the fully-leaved period (0.53–0.57). However, LAI_pred was overestimated by up to 0.6 m2 m–2 inMay 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 Wm^–2 in LE, which is close to the measurement errors recognized in the tower flux measurement. LAI_pred 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.
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