The annual variation of effects under different grassland utilization types on typical steppe species interactions in Inner Mongolia

2017 ◽  
Vol 37 (19) ◽  
Author(s):  
高韶勃 GAO Shaobo ◽  
刘磊 LIU Lei ◽  
王宇坤 WANG Yukun ◽  
李静鹏 LI Jingpeng ◽  
赵念席 ZHAO Nianxi ◽  
...  
2012 ◽  
Vol 518-523 ◽  
pp. 5126-5129 ◽  
Author(s):  
Su Ying Li ◽  
Xiu Mei Wang ◽  
Ying Chang ◽  
Xiao Xia Wu ◽  
Qiang Fan

Assessing the inter-annual variation of regional grassland productivity is imperative to meet the local requirements of grassland adaptive management at regional- or landscape- scale. For the semiarid grassland of Inner Mongolia, the improved CASA model, a kind of light-energy-efficiency model, was used to simulate the Net Primary Productivity (NPP) of the regional grassland. And this study further calculated the Standard Deviation (SD) and Coefficient of Variation (CV) of the regional NPP. Both of SD and CV were used to reflect the fluctuations of regional NPP in the study area among years. Approximately 1/3 of the regional NPP over the years were dramatically changed, frequently up to large amplitude by an average rate of 1 times or more.


2020 ◽  
Author(s):  
Xin Lyu

<p>While researchers worldwide have spent much effort on quantitatively evaluating organic carbon at the regional scale, few studies have examined organic carbon pools at different levels, or their driving factors. Comprehensive analysis in this field would facilitate a deeper understanding of carbon pool mechanisms and lay a foundation for future work. In this study, the improved Terrestrial Ecosystem Regional (TECO-R) model was modified and parameters were calibrated for local application. The vegetation, litter, soil, and ecosystem carbon pools in the Xilingol typical steppe region of Inner Mongolia, China were quantitatively modeled for the 2011–2018 period. The organic carbon pools at different levels were compared and analyzed in terms of their spatial distribution, inter-annual variation, and climate-driving factors. Overall, the modified TECO-R model accurately simulated carbon storage, revealing that the various organic carbon pools increased overall and were characterized by different degrees of clustering in their spatial distribution, inter-annual variation, and climate-driving factors. Clear formation mechanisms were observed in the soil, litter, and root carbon pools. As the soil depth increased, the carbon stock of the root carbon pool and the soil carbon pool decreased. Climate factors exerted different degrees of constraints on each carbon pool. Integrated studies, such as this, promote understanding of the compositional differences in grassland carbon pools and the driving mechanism for these carbon pools, which, taken together, can help shape the policy for carbon sink management in grasslands.</p>


2007 ◽  
Vol 146 (1-2) ◽  
pp. 57-69 ◽  
Author(s):  
Yanbin Hao ◽  
Yanfen Wang ◽  
Xiangzhong Huang ◽  
Xiaoyong Cui ◽  
Xiaoqi Zhou ◽  
...  

2019 ◽  
Vol 12 (2) ◽  
pp. 294-302
Author(s):  
Min Yan ◽  
Hejun Zuo ◽  
Haibing Wang ◽  
Zhi Dong ◽  
Gangtie Li

2019 ◽  
Vol 11 (12) ◽  
pp. 3256 ◽  
Author(s):  
Jie Yang ◽  
Zhiqiang Wan ◽  
Suld Borjigin ◽  
Dong Zhang ◽  
Yulong Yan ◽  
...  

Normalized difference vegetation index (NDVI) is commonly used to indicate vegetation density and condition. NDVI was mostly correlated with climate factors. We analyzed changing trends of NDVI in different types of grassland in Inner Mongolia and the response of NDVI to climatic variation from 1982 to 2011. NDVI of meadow steppe increased significantly in spring while it decreased in other seasons. The annual mean NDVI in typical steppe and desert steppe increased significantly in the last 30a. However, in the greatest area of steppe desert, the NDVI had no significant change in summer, autumn, and the growing season. In meadow steppe, typical steppe, and desert steppe, the area showed a positive correlation of NDVI to temperature as highest in spring compared to other seasons, because warming in spring is beneficial to the plant growth. However, in the greatest area of steppe desert, the correlation of NDVI to temperature was not significant. The NDVI was positively correlated to precipitation in four types of grassland. In the steppe desert, the precipitation had no significant effect on the NDVI due to the poor vegetation cover in this region. The NDVI was not significantly correlated to the precipitation in autumn because of vegetation withering in the season and not need precipitation. Precipitation was a more important factor rather than temperature to NDVI in the region. The response of NDVI to temperature and precipitation in different seasons should be studied in more detail and the effect of other factors on NDVI should be considered in future research.


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