蒙古沙冬青群落区系组成及分类研究

蒙古沙冬青是西北地区珍稀濒危树种,探究区系组成和群落特征对于维持西北干旱荒漠区脆弱生态系统具有重要意义。该研究调查了26个蒙古沙冬青群落样地,采用TWINSPAN进行群落分类,同时利用典范对应分析(CCA)分析沙冬青群落物种组成与生态因子的关系,为珍稀濒危植物蒙古沙冬青的保护提供基础数据。结果表明:(1)蒙古沙冬青群落物种组成以豆科、禾本科、菊科和藜科植物为主,隶属于28科63属90种,区系组成以地中海、北温带分布及世界分布为主。(2)TWINSPAN等级分类可将26个蒙古沙冬青样地划分为9个群落类型,即蒙古沙冬青+蓍状亚菊群落、蒙古沙冬青+红砂群落、蒙古沙冬青+新巴黄耆群落、蒙古沙冬青+无芒隐子草群落、蒙古沙冬青+霸王群落、蒙古沙冬青+驼绒藜群落、蒙古沙冬青+白刺群落、蒙古沙冬青+沙鞭群落和蒙古沙冬青+毛刺锦鸡儿群落。(3)CCA排序分析显示,年均降雨量(F=2.8,P=0.002)、生长季降雨量(F=2.6,P=0.002)、速效氮(F=2.1,P=0.006)、太阳辐射量(F=2.1,P=0.008)、蒸汽压(F=1.9,P=0.006)、土壤有机质(F=1.7,P=0.04)、纬度(F=1.7,P=0.006)是影响蒙古沙冬青群落组成的主要生态因子。

Study on the Community Classification and Floristic Composition of Ammopiptanthus mongolicus

Ammopiptanthus mongolicus is a rare and endangered species in northwest China. It is of great significance to explore floristic composition and community characteristics to maintain the fragile ecosystem in the arid desert area of northwest China. In this paper, 26 sample sites of A. mongolicus were investigated. We used TWINSPAN to classify the communities, and canonical correspondence analysis (CCA) to analyze the relationship between species composition and ecological factors of A. mongolicus. The results showed that: (1) the species composition of A. mongolicus was mainly leguminous, gramineae, compositae and chenopodiaceae, belonging to 28 families, 63 genera and 90 species, and the floristic composition was mainly distributed in Mediterranean, north temperate zone and the world. (2) TWINSPAN classification can divide 26 A. mongolicus sample plots into 9 community types. (3) According to the ranking analysis of CCA, average annual rainfall (F = 2.8, P = 0.002), the growing season rainfall (F = 2.6, P = 0.002), available nitrogen (F = 2.1, P = 0.006), solar radiation (F = 2.1, P = 0.008), the vapor pressure (F = 1.9, P = 0.006), soil organic matter (F = 1.7, P = 0.04), latitude (F = 1.7, P = 0.006) are the main ecological factors affecting the A. mongolicus community composition, the results can provide the protection of the rare and endangered plants of Mongolia sand Holly with basic data.