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首页> 外文期刊>Forest Ecology and Management >Modelling seed germination in forest tree species through survival analysis. The Pinus pinea L. case study.
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Modelling seed germination in forest tree species through survival analysis. The Pinus pinea L. case study.

机译:通过生存分析模拟林木物种的种子发芽。松树案例研究。

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摘要

The direct application of existing models for seed germination may often be inadequate in the context of ecology and forestry germination experiments. This is because basic model assumptions are violated and variables available to forest managers are rarely used. In this paper, we present a method which addresses the aforementioned shortcomings. The approach is illustrated through a case study of Pinus pinea L. Our findings will also shed light on the role of germination in the general failure of natural regeneration in managed forests of this species. The presented technique consists of a mixed regression model based on survival analysis. Climate and stand covariates were tested. Data for fitting the model were gathered from a 5-year germination experiment in a mature, managed P. pinea stand in the Northern Plateau of Spain in which two different stand densities can be found. The model predictions proved to be unbiased and highly accurate when compared with the training data. Germination in P. pinea was controlled through thermal variables at stand level. At microsite level, low densities negatively affected the probability of germination. A time-lag in the response was also detected. Overall, the proposed technique provides a reliable alternative to germination modelling in ecology/forestry studies by using accessible/suitable variables. The P. pinea case study highlights the importance of producing unbiased predictions. In this species, the occurrence and timing of germination suggest a very different regeneration strategy from that understood by forest managers until now, which may explain the high failure rate of natural regeneration in managed stands. In addition, these findings provide valuable information for the management of P. pinea under climate-change conditions.
机译:在生态和林业发芽实验的背景下,直接应用现有模型进行种子发芽通常可能不足。这是因为违反了基本模型假设,并且很少使用森林管理者可用的变量。在本文中,我们提出了一种解决上述缺点的方法。通过对松树的案例研究说明了该方法。我们的发现还将阐明发芽在该物种的管理森林中自然再生的一般失败中的作用。提出的技术由基于生存分析的混合回归模型组成。测试了气候和林分协变量。模型拟合的数据是从西班牙北部高原成熟的,管理的P. pinea林分中进行的为期5年的发芽实验中收集的,在其中可以找到两种不同的林分密度。与训练数据相比,模型预测被证明是无偏的且非常准确。杉木的萌发通过林分水平的热变量控制。在微型站点级别,低密度会对发芽的可能性产生负面影响。还检测到响应存在时滞。总体而言,通过使用可访问的/合适的变量,所提出的技术为生态/林业研究中的发芽建模提供了可靠的替代方法。 P. pinea案例研究强调了产生无偏预测的重要性。在该物种中,发芽的发生和时间表明与森林管理者迄今所理解的不同的再生策略,这可以解释受管理林分自然再生的高失败率。此外,这些发现为在气候变化条件下对P. pinea的管理提供了有价值的信息。

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