Abstract
A long-standing hypothesis in biogeography predicts that a species’ abundance is highest at the center of its geographical range and decreases toward its edges. In this study, we test the abundant-center hypothesis of ectomycorrhizal (ECM) fungal communities associated with Picea crassifolia, an endemic species widely distributed in northwest China. We analyzed the taxonomic richness and the relative abundance of ECM fungi in four main distribution areas, from center to edges. In total, 234 species of ECM fungi were detected, and of these, 137 species were shared among all four sites. Inocybe, Sebacina, Tomentella, and Cortinarius were the dominant genera. ECM fungal richness and biodiversity were highest at the central and lower at peripheral sites. Our results indicated that ECM fungal species richness was consistent with the abundant-center hypothesis, while the relative abundances of individual fungal genera shifted inconsistently across the plant’s range.
Highlights
Ectomycorrhiza (ECM) is an intimate symbiotic association between plant roots and ECM fungi
We examined the ECM fungal community associated with P. crassifolia to test if the distribution of ECM fungal species fit the abundant-center hypothesis model
High-throughput sequencing technology has greatly facilitated the acquisition of genome data (Li et al, 2020), which allows us to investigate the ecophysiology of uncultured microbes (Wagner, 2009)
Summary
Ectomycorrhiza (ECM) is an intimate symbiotic association between plant roots and ECM fungi. As biotic and abiotic components usually show strong interdependencies, it is methodologically difficult to assess the contributions made by each specific factor in the ECM fungal community and their response to environmental changes (Weißbecker et al, 2018). The effect of different driving factors at different scales is variable Physiographic factors such as altitude and soil properties including soil microorganisms and soil physicochemical properties are usually important drivers of ECM fungal communities in the local-scale sampling area, such as carbon content and pH (Vasco-Palacios et al, 2020), altitude and forest age (Matsuoka et al, 2016; Geml et al, 2017; Schön et al, 2018) and host genetic and phenotypic characteristics
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