首页> 外文期刊>European journal of forest research >Predicting individual-tree growth of central European tree species as a function of site, stand, management, nutrient, and climate effects
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Predicting individual-tree growth of central European tree species as a function of site, stand, management, nutrient, and climate effects

机译:预测中心欧洲树种的个体树生长作为现场,立体,管理,营养和气候影响的函数

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We used data from representatively sampled trees to identify key drivers of tree growth for central European tree species. Nonlinear mixed models were fitted to individual-tree basal area increments (BAI) from the Swiss national forest inventory. Data from 1983 to 2006 were used for model fitting and data from 2009 to 2013 for model evaluation. We considered 23 potential explanatory variables specifying individual-tree characteristics, site and stand conditions, management, climate, and nitrogen deposition. Model selection was processed separately for Picea abies, Abies alba, Pinus sp., Larix sp., other conifers, Fagus sylvatica, Quercus sp., Fraxinus sp./Acer sp., and other broadleaves. The selected models explained 56-70% of the BAI variance in the model fitting dataset and 21-64% in the evaluation dataset. While some variables were relevant for all species, the combination of further variables differed among the species, reflecting their physiological properties. In general, BAI was positively related to DBH and temperature and negatively related to basal area of larger trees, stand density, mean DBH of the 100 thickest trees per ha, slope, and soil pH. For most species, harvesting had a positive effect on BAI. In general, nitrogen deposition was positively related to BAI, except for spruce and fir, for which the inverse effect was found. Increasing drought reduced BAI for most species, except for pine and oak. These BAI models incorporate many influencing factors while representing large spatial extents, making them useful for both nationwide scenario analyses and deepening the understanding of the main drivers modulating tree growth throughout central Europe.
机译:我们使用来自代表性采样树的数据来识别中欧树种的树木增长的关键驱动因素。非线性混合模型适用于瑞士国家森林库存的个体树基地增量(BAI)。 1983年至2006年的数据用于2009年至2013年的模型拟合和数据进行模型评估。我们考虑了23个潜在的解释变量,指定单个树特征,现场和站点条件,管理,气候和氮沉积。模型选择是单独处理Picea Abies,Abies Alba,Pinus Sp.,Larix Sp。,其他针叶树,Fagus sylvatica,Quercus sp.,fraxinus sp./acer sp。和其他阔叶。所选模型在模型拟合数据集中解释了56-70%的BAI差异,评估数据集中的21-64%。虽然某些变量与所有物种相关,但是进一步变量的组合在物种之间不同,反映其生理特性。一般而言,白皮与DBH和温度呈正相关,与较大的树木的基础面积呈负相关,展开密度的平均dBH,平均每公顷较长的树木,坡度和土壤pH。对于大多数物种来说,收获对白皮有积极影响。通常,除了云杉和灭菌外,氮沉积与白皮肌呈正相关,未发现抗胃效果。除了松树和橡木之外,大多数物种的干旱减少了白。这些白型模型采用了许多影响因素,同时代表大型空间范围,使其有用于全国范围内的情况分析,并深化对整个中欧的主要驱动器调制树增长的理解。

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