Abstract The frequency, duration, and severity of drought events are expected to increase in the Mediterranean area as a result of climate change, with strong impacts on forest ecosystems and in particular individual tree growth. Tree growth response to drought is strongly influenced by local site and stand characteristics that can be quantified using competition indices (CIs) and water stress indices (WSIs). These indices have been widely used to predict tree growth; however, they are numerous, and few studies have investigated them jointly. In this context, we investigated the potential of using CIs and WSIs to investigate tree behaviour under drought. The main objective of this study was to quantify P. halepensis Mill. annual radial growth using tree size from the previous year, CIs and WSIs. We studied twelve 50-year-old Pinus halepensis plots located in the South-East of France distributed in different density treatments (light, medium and dense). At each plot, all trees were measured (height, circumference), spatialized and the ring-widths were measured for ~15 trees. We also developed a two-strata (over- and understorey) forest water balance model to simulate soil water content at a daily resolution based on stand characteristics (LAI values in particular) and soil properties. A mixed modelling approach was eventually used to investigate the drivers of P. halepensis annual radial growth and to test the performance of five CIs and four WSIs. The best growth model included tree size, the sum of Basal Area of Larger trees in a 5 m-radius (BAL; as CI), and the number of days that trees experienced water stress in a year (as WSI) as predictors. This model explained up to 56% of the variance in observed pine tree growth, which increased up to 77% when the individual tree was included as a random effect on the intercept. We found that distance-independent CIs can perform as well as distance-dependent CIs in our study site. The duration of drought alone appeared to better predict tree growth than drought intensity and duration, or drought timing. The selected model led us to reaffirm the positive effect of thinning on tree secondary growth when facing long and intense drought.

中文翻译：

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竞争和水分胁迫指数作为 Pinus halepensis Mill 的预测因子。干旱条件下径向生长

摘要 由于气候变化，地中海地区干旱事件的频率、持续时间和严重程度预计将增加，对森林生态系统，特别是个体树木生长产生强烈影响。树木生长对干旱的反应受到当地场地和林分特征的强烈影响，可以使用竞争指数 (CI) 和水分压力指数 (WSI) 对其进行量化。这些指数已被广泛用于预测树木生长；然而，它们数量众多，很少有研究对它们进行联合调查。在这种情况下，我们研究了使用 CI 和 WSI 来研究干旱下树木行为的潜力。本研究的主要目的是量化 P. halepensis Mill。使用上一年的树木大小、CI 和 WSI 的年度径向增长。我们研究了位于法国东南部的 12 个 50 年历史的松树地块，这些地块分布在不同的密度处理（轻、中和密）中。在每个地块，测量所有树木（高度、周长）、空间化并测量约 15 棵树的年轮宽度。我们还开发了一个两层（上层和下层）森林水平衡模型，根据林分特征（特别是 LAI 值）和土壤特性，以每日分辨率模拟土壤含水量。最终使用混合建模方法来研究 P. halepensis 年度径向增长的驱动因素，并测试五个 CI 和四个 WSI 的性能。最佳生长模型包括树木大小，5 m 半径内较大树木的基面积总和（BAL；作为 CI），以及树木在一年中经历缺水的天数（作为 WSI）作为预测指标。该模型解释了观察到的松树生长中高达 56% 的方差，当将单棵树作为对截距的随机效应包括在内时，该方差增加了 77%。我们发现，在我们的研究站点中，与距离无关的 CI 的性能与距离相关的 CI 一样好。与干旱强度和持续时间或干旱时间相比，干旱持续时间似乎能更好地预测树木生长。选定的模型使我们重申了在面临长期严重干旱时间伐对树木次生生长的积极影响。我们发现，在我们的研究站点中，与距离无关的 CI 的性能与距离相关的 CI 一样好。与干旱强度和持续时间或干旱时间相比，干旱持续时间似乎能更好地预测树木生长。选定的模型使我们重申了在面临长期严重干旱时间伐对树木次生生长的积极影响。我们发现，在我们的研究站点中，与距离无关的 CI 的性能与距离相关的 CI 一样好。与干旱强度和持续时间或干旱时间相比，干旱持续时间似乎能更好地预测树木生长。选定的模型使我们重申了在面临长期严重干旱时间伐对树木次生生长的积极影响。