Hentschel Rainer, Möller Katrin, Wenning Aline, Degenhardt Annett, Schröder Jens
Faculty of Forest and Environment, University for Sustainable Development, Eberswalde, Germany.
Brandenburg State Forestry Center of Excellence, Eberswalde, Germany.
Front Plant Sci. 2018 Nov 13;9:1667. doi: 10.3389/fpls.2018.01667. eCollection 2018.
Climate change challenges forest vitality both directly by increasing drought and heat periods and indirectly, e.g., by creating favorable conditions for mass outbreaks of phyllophagous insects. The large forests dominated by Scots pine ( L.) that cover the lowland regions in northeast Germany have already been affected regularly by cyclic mass propagations of defoliating insect species in the past with climate projections implying an even more advantageous environment for devastating outbreaks in the future. To improve predictive and responsive capacities we have investigated a wide range of ecological parameters to identify those most strongly related to past outbreak waves of three central species. In total, we analyzed 3,748 variables covering stand and neighborhood properties, site quality, and climatic conditions for an area of roughly 750,000 ha of pine forests in the period 2002-2016. To reflect sensitivity against varying climate, we computed "floating windows" in relation to critical phenological phases of the respective insects. The parameters with the highest explanatory power resulted from the variable importance measures of the Random Forest (RF) methodology and have been evaluated by a 10-fold cross-validation process. Our findings closely reflect the known specific gradation patterns and show that relative variable importance varies with species. While L. feeding was mainly dependent on the surroundings of the respective stand, L. proved to be almost exclusively susceptible to climatic effects in its population dynamics. L. exhibited a mixed pattern of variable importance involving both climatic and forest structure parameters. In many cases the obtained statistical results support well-known ecological cause-effect relations and long-term population change dynamics. The RF delivered very high levels of sensitivity and specificity in the developed classifications and proved to be an excellent tool to handle the large amounts of data utilized for this study. While the presented classification approach may already support a better prognosis of the amplitude during the outbreak culmination, the obtained (most important) variables are proposed as preferable covariates for modeling population dynamics of the investigated insect species.
气候变化对森林活力构成挑战，一方面直接通过延长干旱和高温期，另一方面间接通过为食叶昆虫大规模爆发创造有利条件。德国东北部低地地区以苏格兰松（Pinus sylvestris L.）为主的大片森林，过去已定期受到落叶昆虫物种周期性大规模繁殖的影响，而气候预测表明未来将出现更有利于毁灭性爆发的环境。为提高预测和应对能力，我们研究了广泛的生态参数，以确定与三种主要物种过去爆发浪潮关系最密切的参数。在2002年至2016年期间，我们总共分析了约75万公顷松林中3748个涵盖林分和邻域属性、立地质量和气候条件的变量。为反映对气候变化的敏感性，我们针对各昆虫的关键物候期计算了“滑动窗口”。具有最高解释力的参数来自随机森林（RF）方法的变量重要性度量，并通过10折交叉验证过程进行了评估。我们的研究结果密切反映了已知的特定分级模式，并表明相对变量重要性因物种而异。虽然松异舟蛾（Thaumetopoea pityocampa）的取食主要取决于各林分的周边环境，但松毒蛾（Lymantria dispar）在其种群动态中几乎完全受气候影响。落叶松叶蜂（Pristiphora erichsonii）呈现出涉及气候和森林结构参数的混合变量重要性模式。在许多情况下，获得的统计结果支持了众所周知的生态因果关系和长期种群变化动态。随机森林在已开发的分类中具有非常高的敏感性和特异性，并且被证明是处理本研究中使用的大量数据的优秀工具。虽然所提出的分类方法可能已经有助于更好地预测爆发高峰期的幅度，但所获得的（最重要的）变量被提议作为模拟所研究昆虫物种种群动态的优选协变量。
