Power law in species–area relationship overestimates bacterial diversity in grassland soils at larger scales

Author:

Zhang Biao1ORCID,Xue Kai1234ORCID,Liu Wenjing1,Zhou Shutong1,Nie Shipeng5,Rui Yichao6,Tang Li1,Pang Zhe1,Li Linfeng1,Dong Junfu7,Xu Cong8,Jiang Lili9,Wang Shaopeng5ORCID,Hao Yanbin310ORCID,Cui Xiaoyong310,Wang Yanfen1311ORCID

Affiliation:

1. College of Resources and Environment University of Chinese Academy of Sciences Beijing China

2. State Key Laboratory of Plateau Ecology and Agriculture Qinghai University Xining China

3. Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of Sciences Beijing China

4. Binzhou Institute of Technology Weiqiao‐UCAS Science and Technology Park Binzhou City China

5. College of Urban and Environment Sciences Peking University Beijing China

6. Department of Agronomy Purdue University West Lafayette Indiana USA

7. College of Life Sciences Shandong University Jinan China

8. State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

9. State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research Chinese Academy of Sciences Beijing China

10. College of Life Sciences University of Chinese Academy of Sciences Beijing China

11. State Key Laboratory of Tibetan Plateau Earth System Science (LATPES) Beijing China

Abstract

AbstractAimSpecies–area relationships (SAR) are widely utilized for estimating the species richness and its spatial turnover across various scales. Despite the prevalent characterization of SAR using the power law in many microbial community studies, its efficacy remains unvalidated. This study aims to characterize the microbial SAR and its mechanisms in alpine grassland soils on the Qinghai‐Tibet Plateau (QTP).LocationQinghai‐Tibet Plateau, China.Time PeriodAugust 2014.Major Taxa StudiedSoil bacteria.MethodsSoil samples were collected from five alpine grassland sites on the QTP. Employing a nested sampling strategy at each site, soil samples were collected in plot sizes ranging from 0.5 × 0.5 m2 to 2048 × 2048 m2. Soil bacterial communities were analysed by sequencing 16S ribosomal RNA gene amplicons using an Illumina MiSeq.ResultsThe bacterial SAR exhibited a logarithmic power law (R2: 0.952–0.999), outperforming the power law (R2: 0.701–0.852). Consequently, the most widely adopted power law led to an overestimation of species richness by up to 15.07% in areas >256 × 256 m2, and the regional maximum theoretical richness based on Chao1 by up to 9.88%. Mechanistically, the passive sampling hypothesis was refuted through the rarefied species richness analysis, and the disproportionate effect hypothesis was rejected based on analyses of the effective numbers of species number conversions for the probability of interspecific encounters (SPIE). Notably, Pearson and multiple linear regression analyses indicated that the spatial turnover of bacterial richness was determined by the environmental heterogeneity (R2: 0.855–0.999), rather or better than environmental variables themselves, supporting the ‘environment heterogeneity hypothesis’.Main ConclusionsSoil bacterial SAR in alpine grasslands exhibited a logarithmic power relationship. Spatial turnover was primarily governed by the environmental heterogeneity. In contrast, the traditional power law leads to an overestimation of soil bacterial diversity at the regional scale.

Funder

Max-Planck-Gesellschaft

Chinese Academy of Sciences

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Wiley

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