Elevational patterns and hierarchical determinants of biodiversity across microbial taxonomic scales

生物 物种均匀度 物种丰富度 生物多样性 β多样性 伽马多样性 生态学 生物地理学 α多样性 分类单元 分类等级 物种多样性 进化生物学 遗传学 细菌
作者
Chih-Fu Yeh,Janne Soininen,Anette Teittinen,Jianjun Wang
出处
期刊:Molecular Ecology [Wiley]
卷期号:28 (1): 86-99 被引量:30
标识
DOI:10.1111/mec.14935
摘要

Abstract Microbial biogeography is gaining increasing attention due to recent molecular methodological advance. However, the diversity patterns and their environmental determinants across taxonomic scales are still poorly studied. By sampling along an extensive elevational gradient in subarctic ponds of Finland and Norway, we examined the diversity patterns of aquatic bacteria and fungi from whole community to individual taxa across taxonomic coverage and taxonomic resolutions. We further quantified cross‐phylum congruence in multiple biodiversity metrics and evaluated the relative importance of climate, catchment and local pond variables as the hierarchical drivers of biodiversity across taxonomic scales. Bacterial community showed significantly decreasing elevational patterns in species richness and evenness, and U‐shaped patterns in local contribution to beta diversity (LCBD). Conversely, no significant species richness and evenness patterns were found for fungal community. Elevational patterns in species richness and LCBD, but not in evenness, were congruent across bacterial phyla. When narrowing down the taxonomic scope towards higher resolutions, bacterial diversity showed weaker and more complex elevational patterns. Taxonomic downscaling also indicated a notable change in the relative importance of biodiversity determinants with stronger local environmental filtering, but decreased importance of climatic variables. This suggested that niche conservatism of temperature preference was phylogenetically deeper than that of water chemistry variables. Our results provide novel perspectives for microbial biogeography and highlight the importance of taxonomic scale dependency and hierarchical drivers when modelling biodiversity and species distribution responses to future climatic scenarios.
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