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Estimating seasonal variations of leaf area index using litterfall collection and optical methods in four mixed evergreen-deciduous forests

机译:使用凋落物收集和光学方法估算四种混合常绿落叶林中叶面积指数的季节性变化

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Leaf area index (LAI), a critical parameter used in process models for estimating vegetation growth, can be measured through litterfall collection, which is usually referred to as a direct method. This method has been demonstrated to be applicable to deciduous forests, but few studies have used this method for estimating seasonal variations of LAI in mixed evergreen-deciduous forests. In this study, we proposed a practical method to estimate the seasonal variation of LAI directly by combining leaf emergent seasonality and litterfall collection (defined as LAI(dir)) in a mixed broadleaved-Korean pine (Pinus koraiensis) forest (BK), a Korean pine plantation (KP), a spruce-fir valley forest (SV), and a secondary birch (Betula platyphylla) forest (SB). In this direct method, the seasonal variation of LAI in a mixed forest can be quantified by tracking leaf growth and fall patterns throughout the growing season for each major evergreen and deciduous species. Using the LAI(dir) as a reference, we validated optical LA! (effective LAI, L-e) measurements through a digital hemispherical photography (DHP) and the LAI-2000 instrument. We also explored the contribution of major sources of errors to optical LAI, including woody-to-total area ratio (alpha), clumping index (Omega(E)), needle-to-shoot area ratio (gamma(E)) and automatic exposure (E). We determined that DHP L-e, significantly (P0.05) underestimated LAI(dir) from May to November by 48-64% in BK, KP and SV but overestimated LAI(dir) by 7% on average in SB. Similarly, LAI-2000 L-e, also significantly (P0.05) underestimated LAI(dir) by an average of 27-35% in BK, KP and SV but overestimated LAI(dir) by 22% on average in SB. The relative contribution of E to the error in DHP Le is larger than other factors, and the gamma(E) was the largest relative contributor to the underestimation of LAI by LAI-2000. The results from our study demonstrate that seasonal variations of LAI in mixed evergreen-deciduous forests can be optically estimated with high accuracy (85% for DHP and 91% for LAI-2000), as long as accurate corrections are made to the various factors mentioned above. These close agreements between direct and optical LAI results also suggest that the direct method developed in this study is useful for tracking the seasonal variation of LAI in mixed forests. (C) 2015 Elsevier B.V. All rights reserved.
机译:叶面积指数(LAI)是用于估计植被生长的过程模型中的关键参数,可以通过凋落物收集(通常称为直接方法)进行测量。已经证明该方法适用于落叶林,但是很少有研究使用这种方法来估计常绿落叶林中LAI的季节变化。在这项研究中,我们提出了一种实用的方法,通过在混合阔叶红松(Pinus koraiensis)森林(BK),红松人工林(KP),云杉杉木山谷森林(SV)和次生桦木(Betula platyphylla)森林(SB)。在这种直接方法中,可以通过跟踪每个主要常绿和落叶树种在整个生长期的叶片生长和下降模式来量化混合林中LAI的季节变化。使用LAI(dir)作为参考,我们验证了光学LA!数字半球摄影(DHP)和LAI-2000仪器进行有效的LAI,L-e测量)。我们还探讨了主要误差源对光学LAI的贡献,包括木本占总面积比(alpha),结块指数(Omega(E)),针对拍摄面积比(gamma(E))和自动曝光(E)。我们确定BHP,KP和SV的DHP L-e在5月至11月显着低估LAI(dir)48-64%,但在SB中平均高估LAI(dir)7%。同样,LAI-2000 L-e在BK,KP和SV中也平均低估了LAI(dir)平均27-35%,但在SB中平均高估了LAI(dir)22%。 E对DHP Le中误差的相对贡献大于其他因素,并且γ(E)是LAI-2000低估LAI的最大相对贡献者。我们的研究结果表明,只要对上述各种因素进行了正确的校正,就可以用光学方法高精度估计常绿落叶林中LAI的季节变化(DHP为85%,LAI-2000为91%)。以上。这些直接和光学LAI结果之间的紧密联系也表明,本研究中开发的直接方法可用于跟踪混交林中LAI的季节变化。 (C)2015 Elsevier B.V.保留所有权利。

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