为了研究碱湖N2O释放速率及其对盐度与pH的响应,选取内蒙古大克泊碱湖的五个沉积物样点,采用15N同位素标记模拟实验,研究反硝化和厌氧氨氧化的速率、相对比例和气体产生情况,揭示高盐和高pH对碱湖氮移除的影响。发现大克泊湖潜在氮移除速率为0~16.06 n mol N mL-1 h-1,潜在反硝化速率为0~12.62 n mol N mL-1 h-1,潜在厌氧氨氧化速率为0~9.81 n mol N mL-1 h-1;当盐度34.00 g·L-1与pH 10.22时,厌氧氨氧化对氮移除贡献较大,达到43.18%~71.79%。反硝化过程气体产物以N2为主,几乎无N2O气体释出。另外,该区域潜在氮移除速率与pH呈正相关关系,与TOC、NO-3、HCO-3呈负相关关系;未发现氮移除速率与盐度之间的相关关系。因此,在研究的碱湖中,氮移除过程中主要为N2排放,而N2O低于检测水平;氮移除过程的影响因素复杂且不限于最主要的环境变量(盐度与pH)。这些结果为研究湖泊N2O排放提供了数据基础。 相似文献
The aim of this paper is to investigate the feasibility of using Landsat TM data to retrieve leaf area index (LAI). To get a LAI retrieval model based ground reflectance and vegetation index, detailed field data were collected in the study area of eastern China, dominated by bamboo, tea plant and greengage. Plant canopy reflectance of Landsat TM wavelength bands has been inversed using software of 6S. LAI is an important ecological parameter. In this paper, atmospheric corrected Landsat TM imagery was utilized to calculate different vegetation indices (VI), such as simple ratio vegetation index (SR), shortwave infrared modified simple ratio (MSR), and normalized difference vegetation index (NDVI). Data of 53 samples of LAI were measured by LAI-2000 (LI-COR) in the study area. LAI was modeled based on different reflectances of bands and different vegetation indices from Landsat TM and LAI samples data. There are certainly correlations between LAI and the reflectance of Tm3, TM4, TM5 and TM7. The best model through analyzing the results is LAI = 1.2097*MSR + 0.4741 using the method of regression analysis. The result shows that the correlation coefficient R2 is 0.5157, and average accuracy is 85.75%. However, whether the model of this paper is suitable for application in subtropics needs to be verified in the future. 相似文献