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Detection of Climate-Sensitive Zones and Identification of Climate Change Indicators: A Case Study from the Bavarian Forest National Park

机译:气候敏感区的发现和气候变化指标的确定:以巴伐利亚森林国家公园为例

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We determined the climate-sensitive zones along an altitudinal gradient in a low mountain range forest, the Bavarian Forest National Park in south-eastern Germany, and studied which vascular plant species are likely to respond to climate change. Plants were recorded on 273 plots along four straight transects. The composition of the plant species and their environmental correlates were detected using unconstrained correspondence analysis (DCA) with post-hoc correlation of axes against site variables. We tested the effect of site variables on species composition using maximally selected rank statistics, which allow the simultaneous identification of a threshold and assessment of its significance. Species turnover within the vascular plant community along the altitudinal gradient was assessed using the same method on the basis of the DCA sample scores. Using geostatistical models of local temperature and Bayesian methods with binomial errors that account for spatial structure, we tested the influence of temperature on selected single vascular plant species and assessed the suitability of the species as climate change indicators. Temperature was the most important factor explaining the variability in vascular plant community composition, which changed discretely along the altitudinal gradient, with a climate-sensitive zone found between 1,100 and 1,200 m a.s.l. The distribution of ten species with their lower or upper altitudinal limit in this zone was significantly driven by temperature. To track vegetation responses to climate change effectively, we suggest a three-level monitoring program, flexible with regard to the volume of required sampling effort.
机译:我们在德国东南部的巴伐利亚森林国家公园的低山脉森林中沿海拔梯度确定了对气候敏感的区域,并研究了哪些维管植物可能对气候变化做出响应。沿四个笔直样线在273个样地上记录了植物。使用无约束对应分析(DCA)以及轴与位置变量的事后相关性,可以检测植物物种的组成及其与环境的相关性。我们使用最大选择的秩统计数据测试了站点变量对物种组成的影响,该统计可以同时识别阈值并评估其重要性。基于DCA样本评分,使用相同的方法评估了维管植物群落中沿海拔梯度的物种更新。使用局部温度的地统计学模型和具有空间结构二项式误差的贝叶斯方法,我们测试了温度对选定的单个维管植物物种的影响,并评估了该物种作为气候变化指标的适用性。温度是解释维管植物群落组成变化的最重要因素,维管植物群落组成随高度梯度离散地变化,并在1100 m.s.l.l.和100 m-1.200 m。a.s.l之间存在一个气候敏感区。温度在此区域内十种具有最低或最高海拔极限的物种的分布显着。为了有效跟踪植被对气候变化的响应,我们建议采用三级监控程序,该程序可以灵活调整所需的采样工作量。

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