| 空间分辨率对总初级生产力模拟结果差异的影响 |
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| 引用本文： | 王苗苗,周蕾,王绍强,汪小钦,孙雷刚.空间分辨率对总初级生产力模拟结果差异的影响[J].地理研究,2016,35(4):617-626. |
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| 作者姓名： | 王苗苗 周蕾 王绍强 汪小钦 孙雷刚 |
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| 作者单位： | 1. 福州大学空间数据挖掘与信息共享教育部重点实验室,福建省空间信息工程研究中心,福州 3500022. 中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室,北京 1001013. 河北省科学院地理科学研究所,石家庄 050000 |
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| 基金项目： | 中国科学院战略性先导科技专项（XDA05050602,XDA05050702）;国家科技支撑计划项目（2013BAC03B03）;国家自然科学基金项目（41401110）;中国科学院科技服务网络计划（STS计划）项目（KFJ-EW-STS-001）;河北省科技计划项目（14293703D）;河北省科学院两院合作项目（161301） |
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| 摘 要： | 利用模型分析气候变化对陆地生态系统功能的影响,是当前全球变化生态学的研究热点,然而模型模拟不确定性来源之一就是空间异质性的问题。空间异质性是尺度的函数,基于气象和遥感数据驱动的生态系统过程模型（BEPS模型）,分别模拟2003-2005年中国生态系统通量观测与研究网络（ChinaFLUX）长白山站、千烟洲站、海北站及当雄站在1 km和8 km空间分辨率下的总初级生产力（GPP）的时间动态变化,并结合土地覆盖类型及叶面积指数(LAI)的差异,探讨两种空间分辨率输入数据对GPP模拟结果的影响。结果表明：① 差异性主要是由于8 km范围内混合像元导致LAI的不同,4个站点月均差异值分别为0.85、1.60、0.13及0.04;② 两种空间分辨率均能较好地反映各站点GPP的季节动态变化,与GPP观测值的相关性R2为0.79~0.97 (1 km)、0.69~0.97(8 km),月均差异值为11.46~29.65 gC/m2/month (1 km)、11.87~24.81 gC/m2/month (8 km);③ 4个通量站点在两种空间分辨率下的GPP月均差异值分别为14.43,12.05,4.79,3.22 gC/m2/month,不同空间分辨率的模拟结果在森林站的差异大于草地站,且生长季的差异大于非生长季。因此,模型在模拟大尺度、长时间序列GPP时,为了提高模型模拟效率,适度降低空间分辨率是可行的,但应尽量减小低空间分辨率对于森林生态系统以及生长季GPP模拟上的误差。
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| 关 键 词： | BEPS模型 空间分辨率 总初级生产力 通量数据 空间异质性 |
| 收稿时间： | 2015-11-05 |
| 修稿时间： | 2016-02-18 |
An analysis of the Gross Primary Productivity simulation difference resulting from the spatial resolution |
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| Miaomiao WANG,Lei ZHOU,Shaoqiang WANG,Xiaoqin WANG,Leigang SUN.An analysis of the Gross Primary Productivity simulation difference resulting from the spatial resolution[J].Geographical Research,2016,35(4):617-626. |
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| Authors: | Miaomiao WANG Lei ZHOU Shaoqiang WANG Xiaoqin WANG Leigang SUN |
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| Institution: | 1. Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, Spatial Information Research Center of Fujian Province, Fuzhou University, Fuzhou 350002, China2. Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographical Sciences and Nature Resources Research, Chinese Academy of Sciences, Beijing 100101, China3. Institute of Geographical Sciences, Hebei Academy of Sciences, Shijiazhuang 050000, China |
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| Abstract: | Currently, analyzing the impact of climate change on terrestrial ecosystem functions based on models is the focus of global change ecology. However, one of the model simulation uncertainties stems from the spatial heterogeneity. Spatial heterogeneity is a function of scale. In this paper, an ecological process-based model Boreal Ecosystem Productivity Simulator (BEPS) was used to simulate the daily Gross Primary Productivity (GPP) in the spatial resolutions of both 1 km and 8 km from 2003 to 2005 at four sites of ChinaFLUX, including Changbaishan (CBS), Qianyanzhou (QYZ), Haibei (HBGC) and Lasadangxiong (LSDX). In terms of Land Cover data and Leaf Area Index (LAI), we try to find how these differences influence the GPP simulation difference influenced by spatial resolutions of model inputs. The results show: (1) the finding that GPP simulations varied with spatial resolutions is mainly due to LAI diversity in the 8-km mixed pixels, the averaged absolute difference values of the LAI between 1 km and 8 km across the four sites are 0.85, 1.60, 0.13 and 0.04, respectively; (2) GPP simulations at the spatial resolution of both 1 km and 8 km could capture the GPP's seasonal dynamics across the four sites, the correlation coefficients (R2) between the simulated and eddy covariance flux measurements, range from 0.79-0.97 (1 km), and 0.69-0.97 (8 km), and the absolute difference is 11.46-29.65 gC/m2/month (1 km), and 11.87-24.81 gC/m2/month (8 km); (3) the averaged monthly GPP absolute differences derived from spatial resolutions in the four sites are 14.43 (CBS), 12.05 (QYZ), 4.79 (HBGC) and 3.22 (LSDX) gC/m2/month, in which greater differences were found at the forest site than at the grass site, and in growing season than in non-growing season. In conclusion, it is feasible to input coarser spatial resolutions data to improve the large-scales and long-term GPP simulations. Also, we should reduce the simulation differences at the forest sites as well as in the growing seasons. |
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| Keywords: | BEPS model spatial resolution GPP (Gross Primary Productivity) carbon flux spatial heterogeneity |
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