Statistical and process‐based modeling analyses of tree growth response to climate in semi‐arid area of north central China: A case study of Pinus tabulaeformis
Statistical and process‐based modeling analyses of tree growth response to climate in semi‐arid area of north central China: A case study of Pinus tabulaeformis
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DOI：
10.1029/2007jg000547
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发表时间：
2008-03
影响因子：
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通讯作者：
Jiangfeng Shi;Yu Liu;E. Vaganov;Jinbao Li;Qiufang Cai
中科院分区：
文献类型：
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作者：
Jiangfeng Shi;Yu Liu;E. Vaganov;Jinbao Li;Qiufang Cai
[1]采用统计建模技术和树木年轮形成的Vaganov-Shashkin （VS）正演模型，研究了华北半干旱地区油松树木生长对气候变化的响应。研究表明，统计和基于过程的建模技术都能够模拟和评估研究区域的气候树生长关系，但基于过程的VS模型产生的结果更具物理可解释性。统计模拟结果表明，在生长季节，湿度和温度对树木生长均有显著影响，其中5 - 8月最为重要。VS建模结果验证了上述统计建模结果，进一步明确了温度和土壤湿度的季节分布、生长季前土壤湿度状况、生长季开始和结束日期对树木生长的影响。在当前和预测的气候情景下，我们的模型结果表明，中国中北部树木生长显著减少，区域森林可能会降低其固碳能力。
[1] Statistical modeling techniques and the Vaganov-Shashkin (VS) forward model of tree ring formation were used to investigate tree growth response of Pinus tabulaeformis to climate variations in semi-arid north central China. Both statistical and process-based modeling techniques were shown to be capable of simulating and evaluating climate-tree growth relationships for the study area, but the process-based VS model produced results that were more physically interpretable. Statistical modeling results indicate that both moisture and temperature have significant effects on tree growth during the growing season, with the most important months being May–August. The VS modeled results validated the above statistical modeling results, and further clarified the effects on tree growth of the seasonal distribution of temperature and soil moisture, soil moisture status prior to the growing season, and the start and end dates of the growing season. Under current and projected climate scenarios, our modeling results suggest significant tree growth reduction in north central China, and the possibility that regional forests may reduce their capacity to sequester carbon.