碳汇
固碳
水槽(地理)
城市林业
林业
环境科学
碳纤维
绿色基础设施
播种
农林复合经营
业务
环境资源管理
生态学
地理
计算机科学
气候变化
二氧化碳
农学
生物
地图学
算法
复合数
作者
Yang Yun-feng,YU Chun-hua,Sha Li,David Bramston
标识
DOI:10.1016/j.ecolind.2024.111619
摘要
This research study identified the communal green at Nanjing Forestry University as an example and focused on the carbon sink benefits of the plant communities. Firstly, the representative plant communities in the communal green were investigated, and the parameters of the plant communities were established so that the carbon sink benefits of each plant community could be quantified. Secondly, by applying correlation analysis to study the influence degree of varied plant community factors on the benefits of carbon sink, it was found that the canopy closure, diameter class structure and tree density showed significant positive correlation; the correlation between community density and daily carbon sequestration per unit area was significant; the correlation between community density and carbon storage per unit area showed none significance; and the correlation between the proportion of trees and shrubs and the carbon sink benefits was of no significance. Thirdly, regression analysis was used to study the curve trends of the carbon sink benefits of the plant communities, from which it was concluded that increasing canopy density, average plant height, average crown width and tree density will improve carbon sink benefits. Increasing the average DBH would achieve positive effects for increasing daily carbon sequestration per unit area only at the early stage of the community growth. The plant community density showed positive effects on the increase of the daily carbon sequestration per unit area within a limited range. Since most regression formulas resulted in S-curves, certain threshold bottlenecks were found existed of improving the carbon sinks benefits by increasing the plant community factors. Finally, the characteristics of plant communities with high carbon sink benefit were summarized to provide theoretical references for forming a planting optimization strategy of urban green.
科研通智能强力驱动
Strongly Powered by AbleSci AI