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The Complex Biodiversity-Ecosystem Function Relationships for the Qinghai-Tibetan Grassland Community

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Despite the long history of the study of the biodiversity-ecosystem function relationship, uncertainty remains about the relationship of natural grassland ecosystems under stressful conditions. Recently, trait- and phylogenetic-based tests provide… Click to show full abstract

Despite the long history of the study of the biodiversity-ecosystem function relationship, uncertainty remains about the relationship of natural grassland ecosystems under stressful conditions. Recently, trait- and phylogenetic-based tests provide a powerful way to detect the relationship in different spaces but have seldom been applied to stressful zones on a large spatial scale. We selected Qinghai-Tibetan as the study area and collected a grassland community database involving 581 communities. We calculated biomass and species’, functional, and phylogenetic diversity of each community and examined their relationships by using linear and non-linear regression models. Results showed an overall positive biodiversity-productivity relationship in species’, functional and phylogenetic space. The relationship, however, was non-linear, in which biodiversity explained better the variation in community biomass when species diversity was more than a threshold, showing a weak effect of biodiversity on ecosystem function in low species diversity communities. We also found a filled triangle for the limit of the relationship between species and functional diversity, implying that functional diversity differs significantly among communities when their species diversity is low but finally converges to be a constant with increasing communities’ species diversity. Our study suggests that multiple niche processes may structure the grassland communities, and their forces tend to balance in high-biodiversity communities.

Keywords: diversity; relationship; biodiversity; biodiversity ecosystem; community; ecosystem function

Journal Title: Frontiers in Plant Science
Year Published: 2021

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