Heterogeneity of water-retention capacity of forest and its influencing factors based on meta-analysis in the Beijing-Tianjin-Hebei region

• 来源期刊: 地理学报（英文版）
• 年，卷（期）: 2021,（1）
• 所属期刊栏目: Research Articles
• 页码范围: 69-90
• 页数: 22页
• 语种: 英文
• DOI: 10.1007/s11442-021-1833-0

摘要

Water retention is important in forest ecosystem services.The heterogeneity analysis of water-retention capacity and its influencing factors is of great significance for the construction of water-retention functional areas,restoration of vegetation,and the protection of forest ecosystems in the Beijing-Tianjin-Hebei region.A total of 1366 records concerning water-retention capacity in the canopy layer,litter layer,and soil layer of forest ecosystem in this region were obtained from 193 literature published from 1980 to 2017.The influencing factors of water-retention capacity in each layer were analyzed,and path analysis was used to investigate the contribution of the factors to the water-retention capacity of the three layers.The results showed that mixed forests had the highest water-retention capacity,followed by broad-leaved forests,coniferous forests,and shrub forests.In addition,no matter the forest type,the ranking of the water-retention capacity was soil layer,canopy layer,and litter layer from high to low.The main influencing factors of water-retention capacity in forest canopy were leaf area index and maximum daily precipitation(R2=0.49),and the influencing coeffi-cients were 0.34 and 0.30,respectively.The main influencing factors of water-retention ca-pacity in the litter layer were semi-decomposed litter(R2=0.51),and the influencing coefficient was 0.51.The main influencing factors of water-retention capacity in the soil layer were non-capillary porosity and soil depth(R2=0.61),the influencing coefficients were 0.60 and 0.38, respectively.This study verifies the simulation of the water balance model or inversion of remote sensing of the water-retention capacity at the site scale,and provides scientific basis for further study of the impact of global change on water retention.