Based on vegetation maps of Inner Mongolia, SPOT-VEGETATION normalized difference vegetation index (NDVI) data, and temperature and precipitation data from 118 meteorological stations, this study analysed changes in NDVI, temperature and precipitation, and performed correlation analyses of NDVI, temperature and precipitation for eight different vegetation types during the growing seasons (April-October) of the period 1998-2007 in Inner Mongolia, China. We also investigated seasonal correlations and lag-time effects, and our results indicated that for different vegetation types, NDVI changes during 1998-2007 showed great variation. NDVI correlated quite differently with temperature and precipitation, with obvious seasonal differences. Lag-time effects also varied among vegetation types and seasons. On the whole, Inner Mongolia is becoming warmer, and drier for most regions, and ecological pressure in Inner Mongolia is increasing, and our focus on such issues is therefore important.
Our work is the first study to explore the national and provincial composite carbon storage variations in terrestrial ecosystems of China caused by the entire flows of land use type conversion (LUTC). Only water body was excluded. The results indicated that terrestrial ecosystems of China lost 219 Tg-C due to LUTC from 1980 to 1995, and the amount was 60 Tg-C during the period 1995-2010. Despite the decrease in the total amount, carbon losses from LUTC intensified, but most of the losses were balanced by the opposite conversions. Our analyses also revealed that LUTCs in China were becoming detrimental to carbon reduction, mainly due to the insufficient increase of forest land to meet the growing demand for carbon absorption, the accelerating disappearance of grassland and the rapid expansion of settlements. More than 50% of the carbon storage variations for a single LUTC flow concentrated in several provinces. To improve China’s LUTC status from the aspect of low-carbon, Heilongjiang, Sichuan, Inner Mongolia, Tibet, Qinghai, Xinjiang and coastal regions, such as Shandong, Jiangsu and Liaoning, should be dealt with first according to their conditions. This study can be helpful to planners, policy makers and scholars concerned about carbon reduction in China.
This paper optimises projected land-use structure in 2020 with the goal of increasing terrestrial ecosystem carbon storage and simulates its spatial distribution using the CLUE-S model. We found the following: The total carbon densities of different land use types were woodland > water area > cultivated land > built-up land > grassland > shallows. Under the optimised land-use structure projected for 2020, coastal Jiangsu showed the potential to increase carbon storage, and our method was effective even when only considering vegetation carbon storage. The total area will increase by reclamation and the original shallows will be exploited, which will greatly increase carbon storage. For built-up land, rural land consolidation caused the second-largest carbon storage increase, which might contribute the most as the rural population will continue to decrease in the future, while the decrease of cultivated land will contribute the most to carbon loss. The area near the coastline has the greatest possibility for land-use change and is where land management should be especially strengthened.
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