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A water budget approach to predicting tree species growth and abundance, utilizing paleoclimatology sources

机译:一种利用古气候学资源预测树木物种生长和丰度的水费预算方法

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摘要

Biogeographers and ecologists often need to quantify species-environment relationships to understand the distribution of vegetation, and to assess changes in patterns resulting from environmental change. A water budget approach, which incorporates evaporative demand and moisture availability, is compared to traditional climatic variables in terms of ability to predict species growth and abundance in eastern North America. Firstly, tree growth is examined using tree-ring chronologies obtained from the International Tree-Ring Data Bank, correlated with climatic data from the nearest site in the US Historical Climatology Network. Secondly, logistic regression is used to model the range of American beech (Fagus grandifolia) using pollen records from the World Data Center for Paleoclimatology, and climatic data from NCAR's Community Climate Model (CCM1) general circulation model (GCM) for the control, 6 ka, and 11 ka runs. Tree growth, especially for oaks and other deciduous trees, correlates more strongly with early growing-season deficit than with precipitation. Water budget variables (actual evapotranspiration and deficit) are also more effective than traditional climatic variables in modeling the range of beech. A water budget approach is attractive for modeling vegetation dynamics because it transcends geographic scale; it is able to model both local and continental-scale phenomena.
机译:生物地理学家和生态学家经常需要量化物种与环境的关系,以了解植被的分布,并评估环境变化导致的格局变化。在预测北美东部物种生长和丰度的能力方面,将结合了蒸发需求和水分供应的水预算方法与传统的气候变量进行了比较。首先,使用从国际树木年轮数据库获得的树木年轮年代来检查树木的生长情况,并与美国历史气候学网络中最近站点的气候数据相关联。其次,使用来自世界古气候学数据中心的花粉记录和来自NCAR的社区气候模型(CCM1)总体环流模型(GCM)的气候数据进行对数回归,对数回归采用logistic回归模型进行建模,6 ka,跑11 ka树木的生长,特别是橡树和其他落叶乔木的生长,与早期生长季节赤字的相关性强于与降水的相关性。在对山毛榉范围进行建模时,水预算变量(实际蒸散和水分亏缺)也比传统的气候变量更有效。水费预算方法超越了地理尺度,因此对建模植被动力学很有吸引力。它能够模拟本地和大陆尺度的现象。

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