Greenhouse gases (GHGs) carbon dioxide (CO₂) and nitrous oxide (N₂O), contribute significantly to global warming, and they have increased substantially over the years. Reforestation is considered as an important forestry application for carbon sequestration and GHGs emission reduction, however, it remains unknown whether reforestation may instead produce too much CO₂ and N₂O contibuting to GHGs pollution. This study was performed to characterize and examine the CO₂ and N₂O emissions and their controlling factors in different species and types of pure and mixture forest used for reforestation. Five soil layers from pure forest Platycladus orientalis (PO), Robinia pseudoacacia (RP), and their mixed forest P-R in the Taihang mountains of central China were sampled and incubated aerobically for 11 days. The P-R soil showed lower CO₂ and N₂O production potentials than those of the PO soils (P < 0.01). The average reduction rate of cumulative CO₂ and N₂O was 31.63% and 14.07%, respectively. If the mixed planting pattern is implemented for reforestation, the annual CO₂ reduction amounts of China’s plantation can be achieved at 8.79 million tonnes. With the increase of soil depths, cumulative CO₂ production in PO and RP soils decreased, whereas CO₂ and N₂O production in P-R soil did not show similar pattern. Soil particle size fraction was the main factor influencing GHGs emissions, and the clay fraction showed negative correlation with cumulative CO₂ and N₂O production. In summary, compared with PO pure artificial forests, the mixture plantation mode can not only reduce GHGs pollution but also improve soil fertility, which is conducive to sustainable management of artificial forests.

Rapid urbanization and the excessive human harvesting of forests have led to a continuous decline in the carrying capacity of forests in China. As a result, quantitative means of measuring forest resource carrying capacity are greatly needed, with a view to identifying problem areas and their causes and formulating effective response strategies. This paper puts forward a framework and methodology for constructing a forest resource carrying capacity index (FRCCI). To do this, we first calculate a forest ecological security index (FESI), using an evaluation index system. Ideal FESI values are then simulated by introducing a forest ecological location coefficient (FELC), and the FRCCI is obtained as the difference between the ideal FESI and the FESI. The study considers the 1086 counties that compose the Yangtze River Economic Belt in China, using forest and socioeconomic data for 2015. The resulting FRCCI values indicate that the forests of Yunnan province are generally in a state of “no overload,” while Sichuan, Guizhou, Chongqing, Hunan, Hubei, Jiangxi, and Zhejiang provinces occupied a state of “critical overload” and Anhui and Jiangsu provinces experienced “general overload.” The spatial pattern of the FRCCI in the study region presented significant centralization, with high FRCCI values mainly clustered in areas in the upper reaches of the Yangtze River and low FRCCI values mainly clustered in areas in the midstream and downstream reaches of the River. The study identifies 416 counties identified as forest carrying capacity problem areas (38.31% of the study area); these areas were mainly concentrated in Shanghai and Anhui province. We argue that a number of measures would be helpful in improving FRCCI values, including promoting the forest state index by strengthening reforestation as well as afforestation, reducing the external pressure on forests by means of energy saving and emission reduction strategies, and formulating comprehensive policy measures to promote the carrying capacity of forests in the whole study area and in the problem areas.