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Data-based modelling and environmental sensitivity of vegetation in China

机译:基于数据的中国植被建模与环境敏感性

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pstrongAbstract./strong A process-oriented niche specification (PONS) model was constructed to quantify climatic controls on the distribution of ecosystems, based on the vegetation map of China. PONS uses general hypotheses about bioclimatic controls to provide a "bridge" between statistical niche models and more complex process-based models. Canonical correspondence analysis provided an overview of relationships between the abundances of 55 plant communities in 0.1?° grid cells and associated mean values of 20 predictor variables. Of these, GDDsub0/sub (accumulated degree days above 0 ?°C), Cramera??Prentice ?± (an estimate of the ratio of actual to equilibrium evapotranspiration) and mGDDsub5/sub (mean temperature during the period above 5 ?°C) showed the greatest predictive power. These three variables were used to develop generalized linear models for the probability of occurrence of 16 vegetation classes, aggregated from the original 55 types by ik/i-means clustering according to bioclimatic similarity. Each class was hypothesized to possess a unimodal relationship to each bioclimate variable, independently of the other variables. A simple calibration was used to generate vegetation maps from the predicted probabilities of the classes. Modelled and observed vegetation maps showed good to excellent agreement (iκ/i = 0.745). A sensitivity study examined modelled responses of vegetation distribution to spatially uniform changes in temperature, precipitation and [COsub2/sub], the latter included via an offset to i?±/i (based on an independent, data-based light use efficiency model for forest net primary production). Warming shifted the boundaries of most vegetation classes northward and westward while temperate steppe and desert replaced alpine tundra and steppe in the southeast of the Tibetan Plateau. Increased precipitation expanded mesic vegetation at the expense of xeric vegetation. The effect of [COsub2/sub] doubling was roughly equivalent to increasing precipitation by ~ 30%, favouring woody vegetation types, particularly in northern China. Agricultural zones in northern China responded most strongly to warming, but also benefited from increases in precipitation and [COsub2/sub]. These results broadly conform to previously published findings made with the process-based model BIOME4, but they add regional detail and realism and extend the earlier results to include cropping systems. They provide a potential basis for a broad-scale assessment of global change impacts on natural and managed ecosystems./p.
机译:> >摘要。基于中国的植被图,构建了面向过程的生态位规范(PONS)模型,以量化对生态系统分布的气候控制。 PONS使用有关生物气候控制的一般假设来在统计细分模型与更复杂的基于过程的模型之间提供“桥梁”。典型的对应分析概述了0.1?°网格单元中55个植物群落的丰度与20个预测变量的相关平均值之间的关系。其中,GDD 0 (高于0°C的累计度数天),Cromera ?? Prenticeα±(实际蒸腾量与平衡蒸散量的比率的估算值)和mGDD 5 (高于5°C的期间内的平均温度)显示出最大的预测能力。根据生物气候相似性,使用这三个变量针对16种植被类型的发生概率开发了广义线性模型,这些模型通过 k -均值聚类从最初的55种植被类型汇总而来​​。假设每个类别与每个生物气候变量都具有单峰关系,而与其他变量无关。一个简单的标定用于根据类别的预测概率生成植被图。建模和观察到的植被图显示出良好的一致性(κ = 0.745)。一项敏感性研究研究了植被分布对温度,降水和[CO 2 ]在空间上均匀变化的响应,该响应通过与?±的偏移量(包括基于森林净初级生产的基于数据的独立,基于数据的光利用效率模型)。气候变暖使大多数植被类别的边界向北和向西移动,而温带草原和沙漠取代了青藏高原东南部的高山苔原和草原。降水增加使中生植被膨胀,但以旱生植被为代价。 [CO 2 ]倍增的效果大致相当于使降水增加约30%,有利于木质植被类型,特别是在中国北方。中国北方的农业区对变暖的反应最强烈,但也受益于降水量和[CO 2 ]的增加。这些结果大致上与先前基于过程的模型BIOME4所发表的发现一致,但是它们增加了区域细节和真实感,并将早期的结果扩展到包括种植系统。它们为大规模评估全球变化对自然生态系统和受管理生态系统的影响提供了潜在的基础。

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