| 基于植被动态模式预估中国植被净初级生产力变化格局 |
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| 引用本文： | 马忠学,崔惠娟,葛全胜.基于植被动态模式预估中国植被净初级生产力变化格局[J].地理学报,2022,77(7):1821-1836. |
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| 作者姓名： | 马忠学 崔惠娟 葛全胜 |
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| 作者单位： | 1.中国科学院地理科学与资源研究所 中国科学院陆地表层格局与模拟重点实验室,北京1001012.中国科学院大学,北京100049 |
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| 基金项目： | 中国科学院战略性先导科技专项(XDA23100401);国家自然科学基金项目(41877454);中国科学院青年创新促进会会员人才专项(2019053) |
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| 摘 要： | 本文选用部门间影响模式比较计划（ISI-MIP）提供的6个植被动态模式数据,对比遥感反演值计算了各模式在中国不同植被区的拟合优度,评估了模式的适用性;并提出了以拟合优度为权重的区域年均净初级生产力（NPP）算法,有效解决了已有研究由于数据和方法的不同而对中国NPP估算效果较差的问题。结合两种浓度路径下（RCP2.6和RCP6.0）的模式估算结果,评估了未来30 中国NPP的变化格局。结果表明：单个模式数据对中国大部分区域NPP的拟合效果较差（R² < 0.4）,所计算的中国平均NPP整体偏高33%~97%,但能较为准确地反映空间上从东南向西北递减的趋势。通过加权合成的新序列整体拟合优度为0.86,在单一植被区的拟合优度也基本大于0.3,能更好地反映未来NPP的变化格局。未来中国平均NPP仍将保持由东南向西北递减的分布,中国均值呈波动增长状态,在2035年达到8.8 μg/(m² s),2050年达到9.7 μg/(m² s)左右。随着时间的推移,RCP2.6路径下主要增长区将由南方地区向北偏移,在华北地区增长变显著,在西南、中南地区增速变慢,显著增长的面积变小;在RCP6.0路径下主要增长区将向东北、东南和西部地区退缩,中东部地区增长变不显著。研究发现高浓度路径对2016—2025年间植被NPP的增长主要起促进作用,但在2035—2050年间开始起抑制作用。同时,高浓度路径下NPP的空间分布将变得更加极端,特别是位于青藏高原西北部的高寒荒漠、温性荒漠及灌木半灌木荒漠将增长缓慢或不增长。
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| 关 键 词： | 净初级生产力 部门间影响模式比较计划 气候变化 变化格局 |
| 收稿时间： | 2021-11-10 |
| 修稿时间： | 2022-05-02 |
Prediction of net primary productivity change pattern in China based on vegetation dynamic models |
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| MA Zhongxue,CUI Huijuan,GE Quansheng.Prediction of net primary productivity change pattern in China based on vegetation dynamic models[J].Acta Geographica Sinica,2022,77(7):1821-1836. |
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| Authors: | MA Zhongxue CUI Huijuan GE Quansheng |
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| Institution: | 1. Key Laboratory of Land Surface Patterns and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China2. University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | Six vegetation dynamic models, provided by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), are selected and verified for net primary productivity (NPP) in China based on remote sensing retrials. Then the goodness of fit of each model is used as the weight to synthesize a new sequence to estimate the future change pattern of China's NPP under the RCP2.6 and RCP6.0 scenarios. This study aims to solve inaccuracy of the estimation on the change pattern of China's NPP due to differences in data and methods. The results show that the single model has a poor fitting effect on NPP in most regions of China (R2 < 0.4), the average NPP is 33%-97% higher than the remotely sensed value, but it can well reflect the decreasing trend from southeast to northwest China. The overall goodness of fit of the proposed NPP data is 0.85, and the goodness of fit in most vegetation zones is basically greater than 0.3. In the future 30 years, China's average NPP will continue to decrease from southeast to northwest, and the average value will show a fluctuating growth, which is expected to reach 8.8 μg/(m² s) in 2035 and 9.7 μg/(m² s) in 2050. With the elaspe of time, the main growth area under the RCP2.6 scenario will shift from southern to northern China. This is reflected in the fact that NPP in north China will increase significantly at a rate greater than 0.15 μg/(m² s) per year, but the growth rate will slow down and the area of significant growth will decrease in the southwestern and central-south regions. Under the RCP6.0 scenario, the main growth areas will retreat to the northeastern, southeastern and western regions, and the growth in the central and eastern regions will become insignificant. The high emission scenario will promote the growth of NPP before 2035 and inhibit the growth after 2035. The NPP will be extremely distributed under the RCP 6.0 scenario. For instance, the alpine desert grassland, temperate desert, shrub and semi-shrub desert in the northwest of Qinghai-Tibet Plateau will grow slowly or even stop growing. |
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| Keywords: | net primary productivity ISI-MIP climate change change pattern |
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