Abstract Different ecophysiological models are used to predict the productivity of forest plantations worldwide. The Physiological Principles in Prediction Growth (3-PG) model has been successfully used for this purpose since 1997. In this study, the 3-PG model was parameterized and validated to predict the productivity of the most planted clonal eucalypts in Brazil (Eucalyptus urophylla) in different regions of the country and assess the attainable productivity of this same clone for a region little exploited for this plantations in the country. Through data collection carried out between 2012 and 2018, conducted in 36 sites distributed across an environmental gradient that spans over 3500 km in Brazil, it was possible to parameterize the 3-PG model using data that represent a portion of the soil and climate diversity of forest plantations in Brazil. We determined the initial biomass of the compartments (stem, leaf, and root), relationship between net and gross productivity, average wood density, maximum stem biomass for 1000 trees ha−1, maximum stomatal conductance, bark and branch fractions for the initial and mature age, specific leaf area for the initial and mature age, and allometric parameters at different ages. Considering the model initialization period, the initial age was defined at 12 months after planting and the final age was considered at 80 months. Model calibration was performed in four experimental sites (special sites for the calibration set), which correspond to the environmental diversities of the project, and model validation was performed by applying the setup of the model obtained in 10 other sites (regular sites for validation set) of the same experimental network. In all sites tested, estimates of basal area, diameter at breast height, leaf area index, and stem biomass agreed with the measured values. On average, the estimates of diameter and breast height were 4.91% higher than the observed measures, whereas the stem biomass estimates were 16.44% lower and the leaf area index was 26.22% lower; moreover, the estimates were overestimated for the first three years and underestimated in recent years. Overall, the model was able to capture the soil and climate differences for predicting E. urophylla clone productivity. Its application in a region not yet exploited for eucalypts plantations may help investors in the region select areas for acquisition, planting extensions, and extend production technologies.

中文翻译：

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巴西最高表型可塑性桉树克隆的 3-PG 模型的多点评估

摘要 不同的生态生理模型被用来预测世界范围内人工林的生产力。自 1997 年以来，预测生长的生理学原理 (3-PG) 模型已成功用于此目的。在这项研究中，3-PG 模型被参数化和验证，以预测巴西种植最多的无性系桉树 (Eucalyptus urophylla ) 在该国不同地区，并评估该同一无性系在该国该种植园很少开发的地区可达到的生产力。通过在 2012 年至 2018 年间在巴西跨越 3500 多公里的环境梯度分布的 36 个地点进行的数据收集，可以使用代表巴西森林种植园部分土壤和气候多样性的数据对 3-PG 模型进行参数化。我们确定了隔室（茎、叶和根）的初始生物量、净生产力和总生产力之间的关系、平均木材密度、1000 棵树 ha-1 的最大茎生物量、最大气孔导度、初始和成熟年龄，初始和成熟年龄的比叶面积，以及不同年龄的异速生长参数。考虑到模型初始化期，初始年龄定义为种植后 12 个月，最终年龄定义为 80 个月。模型校准在四个实验点（校准集的特殊场地）进行，对应于项目的环境多样性，模型验证是通过应用在同一实验网络的其他 10 个站点（验证集的常规站点）中获得的模型设置进行的。在所有测试地点，基面积、胸高直径、叶面积指数和茎生物量的估计值与测量值一致。平均而言，直径和胸高的估计值比观察到的测量值高 4.91%，而茎生物量估计值低 16.44%，叶面积指数低 26.22%；此外，前三年的估计数被高估，近年来被低估。总体而言，该模型能够捕捉土壤和气候差异以预测 E. urophylla 克隆生产力。