Shu Wang, Wang Peng, Ding Ming-Jun, Zhang Hua, Huang Gao-Xiang, Nie Ming-Hua
School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China.
Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China.
Huan Jing Ke Xue. 2022 Mar 8;43(3):1434-1446. doi: 10.13227/j.hjkx.202107173.
The aim of this study was to examine the relationships between land use and bacterioplankton communities at different spatial scales and the mechanisms underlying the effects of land use on bacterioplankton communities. Here, surface water samples were collected in 14 tributaries of the Yuanhe River in August 2019 (wet season) and January 2020 (dry season), and high-throughput sequencing technology was used to determine the characteristics of the bacterioplankton communities. Statistical methods such as Bioenv and variance partitioning analysis (VPA) were used to explore the relationships among landscape structure (i.e., landscape compositions and landscape configurations), water chemistry, and bacterioplankton communities. Furthermore, metacommunity theory was employed to explain the mechanisms by which land use and water chemistry affect bacterial communities. The results showed that:① in general, the effects of landscape configuration on bacterial communities were weak, whereas the effects of landscape composition on bacterial communities were significant and greater at the buffer scale than that at the sub-basin scale. ② There was no distinct distance-decay pattern for the effects of landscape composition on bacterial communities from the near-distance (100 m) to the long-distance (1000 m) buffer zones, with the maximal effects occurring in the 500 m circular buffer (wet season) and 300 m riparian buffer (dry season), respectively. ③ Land use influenced the bacterioplankton communities both directly through exogenous inputs (i.e., "mass effect" process) and indirectly by affecting water chemistry (i.e., "species sorting" process). VPA showed that the total explanation of bacterial community variations by water chemistry and the intersection of water chemistry and land use (13.5% in the wet season and 11.7% in the dry season) was higher than that of land use alone (2.7% in the wet season and 6.9% in the dry season). These results suggest that mass effects and species sorting jointly shaped bacterial community assembly but that the effects of species sorting outweighed those of mass effects. This study revealed the variability of landscape structure at different spatial scales on bacterial communities, and its results will help to determine the optimal spatial scale affecting bacterial communities and provide a reference basis for watershed land-use management.
本研究旨在探讨不同空间尺度下土地利用与浮游细菌群落之间的关系，以及土地利用对浮游细菌群落产生影响的潜在机制。在此，于2019年8月（雨季）和2020年1月（旱季）在袁河的14条支流采集了地表水样本，并采用高通量测序技术来确定浮游细菌群落的特征。运用Bioenv和方差分解分析（VPA）等统计方法来探究景观结构（即景观组成和景观格局）、水化学与浮游细菌群落之间的关系。此外，采用集合群落理论来解释土地利用和水化学影响细菌群落的机制。结果表明：①总体而言，景观格局对细菌群落的影响较弱，而景观组成对细菌群落的影响显著，且在缓冲尺度下比在子流域尺度下更大。②从近距离（100米）到远距离（1000米）缓冲带，景观组成对细菌群落的影响不存在明显的距离衰减模式，最大影响分别出现在500米圆形缓冲带（雨季）和300米河岸缓冲带（旱季）。③土地利用通过外源输入（即“质量效应”过程）直接影响浮游细菌群落，也通过影响水化学（即“物种分选”过程）间接影响浮游细菌群落。VPA表明，水化学以及水化学与土地利用的交集对细菌群落变异的总解释率（雨季为13.5%，旱季为11.7%）高于土地利用单独的解释率（雨季为2.7%，旱季为6.9%）。这些结果表明，质量效应和物种分选共同塑造了细菌群落的组装，但物种分选的影响超过了质量效应。本研究揭示了不同空间尺度下景观结构对细菌群落的变异性，其结果将有助于确定影响细菌群落的最佳空间尺度，并为流域土地利用管理提供参考依据。
