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Selecting Populations for Non-Analogous Climate Conditions Using Universal Response Functions: The Case of Douglas-Fir in Central Europe

机译:使用通用响应函数选择非模拟气候条件下的种群:以中欧道格拉斯-菲尔为例

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摘要

Identifying populations within tree species potentially adapted to future climatic conditions is an important requirement for reforestation and assisted migration programmes. Such populations can be identified either by empirical response functions based on correlations of quantitative traits with climate variables or by climate envelope models that compare the climate of seed sources and potential growing areas. In the present study, we analyzed the intraspecific variation in climate growth response of Douglas-fir planted within the non-analogous climate conditions of Central and continental Europe. With data from 50 common garden trials, we developed Universal Response Functions (URF) for tree height and mean basal area and compared the growth performance of the selected best performing populations with that of populations identified through a climate envelope approach. Climate variables of the trial location were found to be stronger predictors of growth performance than climate variables of the population origin. Although the precipitation regime of the population sources varied strongly none of the precipitation related climate variables of population origin was found to be significant within the models. Overall, the URFs explained more than 88% of variation in growth performance. Populations identified by the URF models originate from western Cascades and coastal areas of Washington and Oregon and show significantly higher growth performance than populations identified by the climate envelope approach under both current and climate change scenarios. The URFs predict decreasing growth performance at low and middle elevations of the case study area, but increasing growth performance on high elevation sites. Our analysis suggests that population recommendations based on empirical approaches should be preferred and population selections by climate envelope models without considering climatic constrains of growth performance should be carefully appraised before transferring populations to planting locations with novel or dissimilar climate.
机译:识别可能适应未来气候条件的树种内的种群是重新造林和协助移民计划的重要要求。可以通过基于数量性状与气候变量相关性的经验响应函数,或通过比较种子源和潜在生长地区的气候的气候包络模型,来识别此类种群。在本研究中,我们分析了中欧和非欧陆非气候条件下种植的花旗松的气候增长响应的种内差异。利用来自50个常见花园试验的数据,我们开发了树高和平均基础面积的通用响应函数(URF),并将选定的表现最佳的种群的生长表现与通过气候包络法确定的种群的生长表现进行了比较。发现试验地点的气候变量比人口起源的气候变量更能预测生长性能。尽管人口来源的降水方式变化很大,但在模型中没有发现与人口起源有关的与降水有关的气候变量具有重要意义。总体而言,URF解释了超过88%的增长绩效差异。在当前情景和气候变化情景下,URF模型确定的人口均来自西部喀斯喀特以及华盛顿和俄勒冈州的沿海地区,并显示出比通过气候包络法确定的人口更高的增长表现。 URF预测案例研究区域的中低海拔地区的生长性能下降,而高海拔地区的生长性能提高。我们的分析表明,应首选基于经验方法的种群建议,并且在将种群转移到气候新颖或不同的种植地点之前,应仔细评估不考虑生长表现的气候约束的气候包膜模型进行的种群选择。

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