用于探究气候变化影响的树木存活建模
Modelling tree survival for investigating climate change effects
AI总结：
本研究基于德国森林健康监测数据，采用带随机效应的平滑加性Cox模型及新的模型选择方案，探究树木死亡驱动因素与落叶的关联，发现落叶对死亡率的影响强且单调，部分树种存在落叶阈值。
摘要：
我们利用德国森林健康监测数据，探究导致树木死亡的主要驱动因素，以及落叶与死亡率之间的关联，具体包括三个问题：（a）落叶是否是气候、土壤、水分收支等其他协变量的代理指标；（b）落叶是否是树木缓解气候变化影响的一种响应；（c）是否存在可作为不可逆损伤早期预警信号的落叶阈值。\n结果表明，导致树木死亡的环境驱动因素因树种而异，但部分驱动因素是模型中始终需要纳入的。落叶对死亡率的影响同样存在树种差异，但始终表现出强且单调的特征。有证据表明，云杉、冷杉和山毛榉存在落叶阈值。\n我们采用平滑加性Cox模型对树木存活进行建模，该模型引入随机效应以处理相邻树木间的依赖性，并纳入落叶、气候、土壤和水文特征相关的时空变化及函数型预测因子的非线性函数。由于样本量大且参数数量多，我们将并行计算与协变量的边际离散化相结合使用。我们提出了一种“前向提升后向惩罚”的模型选择方案，该方案结合了分量梯度提升与集成后向选择方法。
英文摘要：
Using German forest health monitoring data we investigate the main drivers leading to tree mortality and the association between defoliation and mortality; in particular (a) whether defoliation is a proxy for other covariates (climate, soil, water budget); (b) whether defoliation is a tree response that mitigates the effects of climate change and (c) whether there is a threshold of defoliation which could be used as an early warning sign for irreversible damage. Results show that environmental drivers leading to tree mortality differ by species, but some are always required in the model. The defoliation effect on mortality differs by species but it is always strong and monotonic. There is some evidence that a defoliation threshold exists for spruce, fir and beech. We model tree survival with a smooth additive Cox model allowing for random effects taking care of dependence between neighbouring trees and non-linear functions of spatial time varying and functional predictors on defoliation, climate, soil and hydrology characteristics. Due to the large sample size and large number of parameters, we use parallel computing combined with marginal discretization of covariates. We propose a 'boost forward penalise backward' model selection scheme based on combining component-wise gradient boosting with integrated backward selection.
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