摘要
红树林是"蓝碳"碳汇的主要贡献者,研究红树林湿地土壤有机碳及其与环境因子的关系对促进红树林湿地固碳增汇具有重要意义.以广东台山烽火角15年生人工红树林为例,通过采集水黄皮(Pongamia pinnata)、海杧果(Cerbera manghas)、银叶树(Heritiera littorali)3种半红树林0～100 cm 土壤,分析土壤有机碳含量和碳密度的垂直分布特征及其与土壤理化因子的相关性.结果表明:在0～15 cm、15～30 cm、30～50 cm、70～100 cm 土层中,银叶树的土壤碳密度显著高于水黄皮、海杧果,水黄皮的土壤pH值显著高于海杧果和银叶树,银叶树的土壤电导率显著低于水黄皮、海杧果.在0～15 cm、15～30 cm、30～50 cm 土层中银叶树的铁(Fe)、锌(Zn)、铜(Cu)含量均显著高于水黄皮、海杧果,在50～70 cm、70～100 cm 土层中水黄皮的Zn、Cu含量均显著高于海杧果、银叶树.半红树林下土壤有机碳含量和碳密度与土壤全氮(TN)、Cu、土壤电导率(EC)呈极显著相关(P＜0.01),与土壤全氮(TK)呈显著相关(P＜0.05).3种半红树土壤有机碳分布特征及影响因素为红树林湿地的经济效益提供参考.
Abstract
Mangrove is the main contributor to the"blue carbon sink".It is of great significance to study the relationship between soil organic carbon and environmental factors in mangrove wetland.The vertical distribution characteristics of soil organic carbon content and carbon density,and their correlation with soil physicochemical factors,were analyzed by collecting 0～100 cm soil under Pongamia pinnata,Cerbera manghas,Heritiera littorali in Fenghuojiao,Taishan,Guangdong Province.The results showed as follows:In 0～15 cm,15～30 cm,30～50 cm and 70～100 cm soil layers,the soil carbon density of H.littoralis was significantly higher than that of P pinnata and C.manghas.The soil pH value of the P.pinnata was significantly higher than that of the C.manghasin and the H.littoralis,and the soil conductivity of H.littoralis was significantly lower than that of P.pinnata and C.manghas.In 0～15 cm,15～30 cm and 30～50 cm soil layers,the contents of Fe,Zn,and Cu in H.littoralis were significantly higher than those of P.pinnata and C.manghas.In 50～70 cm and 70～100 cm soil layers,the contents of Zn and Cu in P.pinnata were significantly higher than those of H.littoralis and C.manghas.Soil organic carbon content and carbon density were significantly correlated with TN,Cu and EC(P＜0.01),and significantly correlated with TK(P＜0.05).Characteristics of soil organic carbon distribution and influencing factors under three semi-mangrove forests provide reference for the economic benefits of mangrove wetlands.
维普
万方数据