Analysing Amazonian forest productivity using a new individual and trait-based model (TFS v.1)
Analysing Amazonian forest productivity using a new individual and trait-based model (TFS v.1)
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DOI：
10.5194/gmd-7-1251-2014
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发表时间：
2014-01-01
影响因子：
5.1
通讯作者：
Lloyd, J.
中科院分区：
文献类型：
--
作者：
Fyllas, N. M.;Gloor, E.;Lloyd, J.
反复的长期普查揭示了亚马逊盆地森林结构和活力的大规模空间格局，该盆地西部的一些森林的地上生物量生产和树木补充率高达东部森林的两倍。造成这种差异的可能原因可能是整个流域的气候和土壤梯度和/或树种组成的空间分布。为了帮助了解这种差异的原因，已经开发了一种新的基于个体的热带森林生长模型，旨在充分利用亚马逊森林调查网络(RAIN-FOR)提供的森林普查数据。该模型考虑了林内树木大小分布和主要功能性状的差异，以及林间气候和土壤物理和化学性质的差异。它在林分水平上运行，有四个功能性状--单位面积叶片干质量(M-a)、叶氮(N-L)、叶磷(P-L)含量和木材密度(D-W)--以一种复制每一林分内观察到的连续性的方式进行。我们首先应用该模式验证了三个涡旋协方差通量测量点的冠层水通量。对所有三个站点的冠层水通量进行了充分的模拟。然后，我们将该模型应用于七个地块，在这些地块上，可以进行密集的碳分配测量。每棵树的多年生长率与对小树的观测结果基本一致，但对较大的树则存在偏差。在林分水平上，通过40个样地的模拟，研究了气候和土壤养分有效性对总初级生产力(PI(G))和净初级生产力(PI(N))以及碳利用效率(C-U)的影响。模拟PI(G)、PI(N)和C-U与温度无关。另一方面，林分水平生产力的三个指标均与年平均降雨量和土壤养分状况呈正相关。敏感性研究表明，林内和林间性状变异的准确参数对模型预测的保真度具有明显的重要性。例如，当功能树种多样性不包括在模型中时(即只有一个植物功能类型和全流域的平均性状值)，模型的预测能力就会降低。在每个林分中应用盆地范围(而不是特定地点)的性状分布时也是如此。我们的结论是，热带森林碳、能量和水循环的模型应该努力准确地表示在相关尺度范围内观察到的重要功能特征的变化。
Repeated long-term censuses have revealed large-scale spatial patterns in Amazon basin forest structure and dynamism, with some forests in the west of the basin having up to a twice as high rate of aboveground biomass production and tree recruitment as forests in the east. Possible causes for this variation could be the climatic and edaphic gradients across the basin and/or the spatial distribution of tree species composition. To help understand causes of this variation a new individual-based model of tropical forest growth, designed to take full advantage of the forest census data available from the Amazonian Forest Inventory Network (RAIN-FOR), has been developed. The model allows for within-stand variations in tree size distribution and key functional traits and between-stand differences in climate and soil physical and chemical properties. It runs at the stand level with four functional traits - leaf dry mass per area (M-a), leaf nitrogen (N-L) and phosphorus (P-L) content and wood density (D-W) varying from tree to tree - in a way that replicates the observed continua found within each stand. We first applied the model to validate canopy-level water fluxes at three eddy covariance flux measurement sites. For all three sites the canopy-level water fluxes were adequately simulated. We then applied the model at seven plots, where intensive measurements of carbon allocation are available. Tree-by-tree multi-annual growth rates generally agreed well with observations for small trees, but with deviations identified for larger trees. At the stand level, simulations at 40 plots were used to explore the influence of climate and soil nutrient availability on the gross (Pi(G)) and net (Pi(N)) primary production rates as well as the carbon use efficiency (C-U). Simulated Pi(G), Pi(N) and C-U were not associated with temperature. On the other hand, all three measures of stand level productivity were positively related to both mean annual precipitation and soil nutrient status. Sensitivity studies showed a clear importance of an accurate parameterisation of within- and between-stand trait variability on the fidelity of model predictions. For example, when functional tree diversity was not included in the model (i.e. with just a single plant functional type with mean basin-wide trait values) the predictive ability of the model was reduced. This was also the case when basin-wide (as opposed to site-specific) trait distributions were applied within each stand. We conclude that models of tropical forest carbon, energy and water cycling should strive to accurately represent observed variations in functionally important traits across the range of relevant scales.