中文摘要：

物种多样性和生产力（或生物量）间的关系是生态学最关注的问题之一.传统的观点认为群落生产力影响物种多样性,而近些年研究发现,随着物种多样性变化,群落生产力会发生改变.不同角度的研究引出了多样性和生产力之间谁驱动谁的争议.多变量生产力-多样性假说整合已有观点为解释两者关系提供了一个框架模型,该假说认为环境除了直接影响生产力外,还通过影响物种多样性从而间接影响生产力,而物种多样性则直接决定群落将环境资源转化为生产力的效率.本研究利用古田山样地数据对该假说进行了检验.结果表明,环境因子直接影响地上生物量,并通过影响林冠层优势度和林下层物种丰富度间接影响地上生物量.优势度对林冠层和林下层生物量均有直接影响,但仅有林下层地上生物量受物种丰富度的影响,这可能与林冠和林下的光照差异引起不同林层内物种间关系不同有关.本研究为多变量生产力-多样性假说提供了一个实例,也表明保护优势物种和维持高的物种丰富度对森林生物量的提高都是必要的.

英文摘要：

The correlation between primary producer diversity and the productivity （or biomass） of ecosystems is one of the most important and broadly studied relationship in ecology. Ecologists have discussed this relationship from two fundamentally different perspectives. Historically, productivity has been viewed as driver of species diversity. Recently, many studies have demonstrated that diversity can also control, rather than responds to, the production of biomass. These contrasting points of view have led to the debate about whether species diversity is the cause or the consequence of community productivity. Multivariate productivity-diversity hypothesis has been put forward to reconciling this debate. This hypothesis state that： （i） the environmental factors are the direct driver of species that can coexist within an area; （ii） the biomass of the area is directly influenced by the environmental factors that limit production; （iii） the environmental factors indirectly influenced biomass of the area via influencing the species number to coexist within the area that affects how efficiently environmental resources are converted into biomass. To date, empirical support for this hypothesis is scarce, especially for structurally complex terrestrial ecosystems. In this study, we modified multivariate productivity- diversity hypothesis to accommodate complex vertical structure of forest ecosystems, and used structural equation modeling and data from a large evergreen broad-leaved forest dynamic plot （24 hm2 in area） in subtropical China to understand the causal relationships among environmental factors, species richness, dominance and aboveground biomass. Trees were grouped into tow functional groups （overstorey and understorey） in order to improve the ability to detecting the diversity effect. The final model explained 30% and 58% of the variation in aboveground biomass of overstorey and understorey, respectively. Dominance was the most important factor in explaining the variation of aboveground bi