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Estimates of forest vegetation carbon storage in China varied due to different methods used in the assessments. In this paper, we estimated the forest vegetation carbon storage from the Fourth Forest Inventory Data (FFID) in China using a modified volume-derived method. Results showed that total carbon storage and mean carbon density of forest vegetation in China were 3.8 Pg C (about 1.1% of the global vegetation carbon stock) and 41.32 Mg/ha, respectively. In addition, based on linear multiple regression equation and factor analysis method, we analyzed contributions of biotic and abiotic factors (including mean forest age, mean annual temperature, annual precipitation, and altitude) to forest carbon storage. Our results indicated that forest vegetation carbon storage was more sensitive to changes of mean annual temperature than other factors, suggesting that global warming would seriously affect the forest carbon storage. [ABSTRACT FROM AUTHOR]

This paper measures the economic impacts of climate change on China's agriculture based on the Ricardian model. By using county-level cross-sectional data on agricultural net revenue, climate, and other economic and geographical data for 1275 agriculture dominated counties, we find that under most climate change scenarios both higher temperature and more precipitation would have an overall positive impact on China's agriculture. However, the impacts vary seasonally and regionally. Autumn effect is the most positive, but spring effect is the most negative. Applying the model to five climate scenarios in the year 2050 shows that the East, the Central part, the South, the northern part of the Northeast, and the Plateau would benefit from climate change, but the Southwest, the Northwest and the southern part of the Northeast may be negatively affected. In the North, most scenarios show that they may benefit from climate change. In summary, all of China would benefit from climate change in most scenarios. [ABSTRACT FROM AUTHOR]