中国典型陆地生态系统波文比特征及影响因素
收稿日期: 2019-11-06
录用日期: 2020-05-12
网络出版日期: 2020-06-08
基金资助
国家自然科学基金(31670708);国家自然科学基金(31670710);国家自然科学基金(31901366);中央高校基本科研业务费专项资金(2015ZCQ-SB-02)
Characteristics and influencing factors of Bowen ratio variation in typical terrestrial ecosystems in China
Received date: 2019-11-06
Accepted date: 2020-05-12
Online published: 2020-06-08
Supported by
National Natural Science Foundation of China(31670708);National Natural Science Foundation of China(31670710);National Natural Science Foundation of China(31901366);Fundamental Research Funds for the Central Universities(2015ZCQ-SB-02)
波文比(β)是陆面过程中的重要参数, 影响着地表和大气间的能量交换, 明确β的空间变异规律和影响因素有助于对地表能量平衡和气候间反馈关系的预测。该研究收集了在中国不同生态系统类型开展的用涡度相关法(EC)测量地表能量平衡的公开发表文献, 构建了β和气象环境因子数据库, 分析了β在生态系统之间的差异、空间变异特征及影响因素。主要结果: (1)所有生态系统β平均值为0.95 ± 0.64, 变异系数67%, 偏度1.58, 峰度3.07, 整体服从对数正态分布, β平均值最高为灌木生态系统(1.26), 最低为湿地生态系统(0.49)。(2) β在生态系统类型间差异显著: 森林和湿地生态系统β无显著差异, 灌木生态系统β >草地生态系统 β >森林和湿地生态系统 β, 农田生态系统β介于草地生态系统与森林和湿地生态系统之间。(3) β随着纬度的增加而增加, 不随经度和海拔变化。纬度每增加1°,β增加0.038。(4) β随着年降水量(MAP)、年平均气温(MAT)、净辐射(Rn)、当年降水量(PPT)、当年平均气温(Ta)和叶面积指数(LAI)的增加而降低。(5)不同生态系统中β对生物和非生物因素的响应存在显著差异: 草地、森林和灌木生态系统的β对生物和非生物因素变化较为敏感, 而农田和湿地生态系统的β与所有生物和非生物因素均无显著相关关系。(6) MAP和Rn是β变化的直接影响因素, LAI通过影响Rn间接影响β。结果表明了植被类型与气候因素之间具有交互作用, 能量分配最主要的影响因素是降水, 叶面积对能量分配的调节作用并不显著。
黄松宇, 贾昕, 郑甲佳, 杨睿智, 牟钰, 袁和第 . 中国典型陆地生态系统波文比特征及影响因素[J]. 植物生态学报, 2021 , 45(2) : 119 -130 . DOI: 10.17521/cjpe.2019.0301
Aims Bowen ratio (β) is an important parameter in land-surface processes. It affects the energy exchange between the surface and the atmosphere. This paper used integrated analyses to investigate the spatial variability and influencing factors of β.
Methods We collected the published literature on the measurement of surface energy balance by the Eddy Covariance (EC) method carried out in different ecosystem types in China, constructed the database of β and meteorological environment factors and analyzed the difference of β among ecosystems, the spatial variation characteristics of β and its influencing factors.
Important findings (1) The variation of β follows a lognormal distribution. The average β in all ecosystems was 0.95 ± 0.64, the coefficient of variation of β was 67%, the skewness was 1.58, and the kurtosis was 3.07. The shrub ecosystem has the highest mean value (1.26) and the wetland ecosystem has the lowest (0.49). (2) β is significantly different among ecosystems: β of shrub ecosystems is significantly higher than those in grassland, forest and wetland ecosystems, and β of croplands is between grassland ecosystems and forest with wetland ecosystems. (3) β increases with increasing latitude and does not change with longitude and altitude. For every 1° increase in latitude,β increases by 0.038. (4) β decreases with increase in mean annual precipitation (MAP), mean annual temperature (MAT), net radiation (Rn), precipitation of the studied year (PPT), mean temperature of the studied year (Ta), and leaf area index (LAI). (5) There are significant differences in the response of β to biotic and abiotic factors in different ecosystems: β of grassland, forest and shrub ecosystems are sensitive to changes in biotic and abiotic factors, while β of croplands and wetland ecosystems have no correlations with biotic and abiotic factors. (6) MAPand Rn are the direct factors influencing β. MAT affects βindirectly by affecting MAP, Rn and LAI. LAI affects β indirectly by affectingRn. Our results indicate significant effect of the interaction between vegetation types and climatic factors on β. The most important factor affecting energy distribution is precipitation, and the regulation of leaf area on energy distribution is not significant.
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