基于过程模型的天山北坡树轮多指标气候响应与树木生长预测

项目名称： 基于过程模型的天山北坡树轮多指标气候响应与树木生长预测

项目编号： No.41501049

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 天文学、地球科学

项目作者： 徐国保

作者单位： 中国科学院寒区旱区环境与工程研究所

项目金额： 25万元

中文摘要： 树木生长受气候和非气候因素的综合作用。气候因素对树木生长的控制作用并非完全稳定和线性的，其主要气候驱动因子会随时间和环境水热平衡发生变化，使均一性原则部分失效。MAIDENiso前向过程模型基于树木和气候的非线性关系，用气候和其他环境因子(CO2浓度等)为驱动来模拟树木径向生长和年轮稳定碳氧同位素比率变化，揭示气候变化和树轮指标的响应，预测树木生长。同时，基于MAIDENiso模型建立反向模型能准确重建过去气候。本研究拟采用MAIDENiso模型，通过蒙特卡洛检验法率定模型参数，模拟天山中段北坡云杉树轮宽度、稳定碳氧同位素比率的变化，明确研究区树轮多指标和气候、非气候因素的关系；开展树木生长的预测研究。基于MAIDENiso模型建立反向模型，分离非气候因素（如CO2浓度升高）对气候重建的贡献，进行可靠气候重建和不确定性评价。该方法的成功应用对古气候和森林生态系统动态变化研究有重要借鉴意义。

中文关键词： 树轮；过程模型；稳定同位素；气候重建；树木生长

英文摘要： Tree growth is influenced by both climatic and non-climatic factors. The relationships between tree growth and the climatic factors were not always stable and linear, and the main limiting climatic factor will altered in tree growth and stable isotope fractionation under the water-heat balance along the time evolution, which may lead to uniformitarian principle invalidation partly in climate reconstruction. MAIDENiso forward process model considered the nonlinear relationship between tree growth and climate. In this model, climatic factors and environmental factors, such as CO2 concentration, was used as the driven factors to simulate the tree-ring width and tree-ring cellulose δ13C and δ18O. The forward process model could greatly reveal the responses between climate change and tree-ring proxies, and the forward process model can use to predict the tree-ring growth. A inverse model could be established by comparison the simulation results based on forward process model with the actual measuremental value. The backward model can be used to reconstruct past climate change accurately. In this study, the MAIDENiso process model will be used to simulate the tree-ring width, tree-ring cellulose δ13C and δ18O in the north slope of the central Tianshan Mountains. The monte carlo parametric test method will be used to calibrate model parameters. The aims of the study is to 1) reveal the relationships between climatic and non-climatic factors and tree-ring proxies and predict tree ring growth based on the MAIDENiso process model; 2) to establish a backward model on the base of MAIDENiso process model; 3) to separate the contribution of climatic and no-climatic factors (e.g., CO2 concentration increase) in climate reconstruction; 4) to reconstruct the past climate change more accurately and to assess the uncertainty. The successful application of this method has important significance for the palaeo-climate research and forest ecosystem dynamics studies.

英文关键词： Tree rings;Process model;Stable isotopes;Climate reconstruction;Tree growth