Since several studies have been reporting an increase in the decline of forests, a major issue in ecology is to better understand and predict tree mortality. The interactions between the different factors and the physiological processes giving rise tree mortality, as well as the inter-individual variability in mortality risk, still need to be better assessed. This study investigates mortality in a rear-edge population of European beech (Fagus sylvatica L.) using a combination of statistical and process-based modelling approaches. Based on a survey of 4323 adult beeches since 2002 within a natural reserve, we first used statistical models to quantify the effects of competition, tree growth, size, defoliation and fungi presence on mortality. Secondly, we used an ecophysiological process-based model (PBM) to separate out the different mechanisms giving rise to temporal and inter-individual variations in mortality by simulating depletion of carbon stocks, loss of hydraulic conductance and damage due to late frosts in response to climate. The combination of all these simulated processes was associated with the temporal variations in the population mortality rate. The individual probability of mortality decreased with increasing mean growth, and increased with increasing crown defoliation, earliness of budburst, fungi presence and increasing competition, in the statistical model. Moreover, the interaction between tree size and defoliation was significant, indicating a stronger increase in mortality associated to defoliation in smaller than larger trees. Finally, the PBM predicted a higher conductance loss together with a higher level of carbon reserves for trees with earlier budburst, while the ability to defoliate the crown was found to limit the impact of hydraulic stress at the expense of the accumulation of carbon reserves. We discuss the convergences and divergences obtained between statistical and process-based approaches and we highlight the importance of combining them to characterize the different processes underlying mortality, and the factors modulating individual vulnerability to mortality.

中文翻译：

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比较统计模型和机理模型以识别后山毛榉种群内的死亡率驱动因素

由于已有几项研究报告了森林退化的加剧，因此生态学的主要问题是更好地了解和预测树木的死亡率。仍然需要更好地评估不同因素与导致树死亡率上升的生理过程之间的相互作用以及个体间死亡风险的变异性。这项研究使用统计和基于过程的建模方法相结合，调查欧洲山毛榉（Fagus sylvatica L.）的后缘种群的死亡率。根据自2002年以来在自然保护区内对4323只成年山毛榉进行的调查，我们首先使用统计模型来量化竞争，树木生长，大小，落叶和真菌的存在对死亡率的影响。其次，我们使用了基于生态生理过程的模型（PBM），通过模拟碳库的枯竭，水力传导率的损失以及由于气候变化而导致后期霜冻造成的破坏，来分离导致死亡率随时间和个体间变化的不同机制。所有这些模拟过程的结合与人口死亡率的时间变化有关。在统计模型中，个体死亡的概率随着平均生长的增加而降低，并随着冠叶的脱叶，芽芽的早期性，真菌的存在和竞争的加剧而增加。此外，树木大小与落叶之间的相互作用非常显着，这表明较小的树木与较大的树木相比，与落叶相关的死亡率有更大的提高。最后，PBM预测出芽较早的树木会有更高的电导损耗和更高的碳储量，而人们发现树冠的脱叶能力限制了水力压力的影响，但却以碳储量的积累为代价。我们讨论了统计方法和基于过程的方法之间的趋同和分歧，并强调了将它们结合起来以表征潜在的不同死亡率过程以及调节个体对死亡率的脆弱性的因素的重要性。