引调水河道氮的迁移转化及微生物群落结构特征——以望虞河为例

以引江济太调水工程-望虞河为研究对象,探究引调水河道氮素的迁移转化规律及微生物群落结构特征.于2020年10月、12月以及2021年1月在望虞河沿程布设监测点位并采集水样,分析其水体理化性质、氮的形态分布及含量、微生物群落结构变化特征.结果 表明:①硝酸盐氮是望虞河沿程水体中氮素的主要存在形态,占总氮浓度的75.3％～...     

厌氧氨氧化菌富集培养过程微生物群落结构及多样性

为深入理解厌氧氨氧化菌富集培养过程微生物群落变化特征,采用ASBR反应器进行厌氧氨氧化菌富集培养,考察了不同培养时间微生物群落组成、多样性及物种网络关系.结果表明,通过逐步提高基质浓度,实现了厌氧氨氧化菌富集,NH₄⁺-N和NO₂^--N去除率分别为97.6%和95.4%,总氮去除率为84.9%.高通量测序发现,整个培养过程优势菌门（相对丰度>5%）为变形菌门（Proteobacteria）、拟杆菌门（Bacteroidetes）、绿弯菌门（Chloroflexi）、浮霉菌门（Planctomycetes）、装甲菌门（Armatimonadetes）和放线菌门（Actinobacteria）;富集培养获得的主要厌氧氨氧化菌为Candidatus Brocadia,相对丰度从1.42%增长到24.66%;培养过程,微生物群落优势菌群组成未发生变化,但相对丰度呈现显著差异（P<0.05）.富集培养过程不同时间,微生物群落α多样性呈现先升高后降低的趋势,且存在显著差异（P<0.05）;微生物群落β多样性在富集培养过程发生明显空间分异特征,且存在显著差异（R=0.5672,P<0.01）.培养过程不同时间,物种网络密度分别为0.188、0.068、0.059、0.18和0.0735;虽然富集培养过程导致微生物间的关联作用变弱,但浮霉菌门相关类群的物种成为网络中的主要节点.     

底泥与衰亡植物营养释放及细菌群落演替差异的比较分析

为揭示两种"湖泛"因素对水质影响及细菌群落演替差异,对泸沽湖草海底泥和衰亡植物营养释放过程进行对比研究,并通过冗余分析阐明影响细菌群落不同阶段变化的主要环境因子.结果表明,前期是衰亡植物与底泥营养释放及细菌演替差异显著的主要阶段.植物腐解过程中,细菌前期厌氧发酵更剧烈,水体迅速处于低pH、低DO和低ORP(Oxidat...     

水位波动和植被恢复对三峡水库消落带土壤原核微生物群落结构的交互影响

水库消落带是典型的生态脆弱敏感区.水位波动是影响消落带土壤环境的主要因素,植被恢复是消落带土壤保育的重要手段.然而,在水库消落带中,水位波动和植被恢复对土壤微生物群落结构的交互影响尚不清楚.为此,选取三峡水库消落带中不同水位高程的撂荒草地和人工林地为研究对象,利用16S rRNA高通量测序技术探究土壤原核微生物群落组成和多样性,并探讨驱动土壤原核微生物群落结构的主要环境因子.结果表明,消落带的低水位高程中土壤原核微生物α多样性最高,其中163 m高程的Pielou_e指数、Shannon指数和Simpson指数显著高于168 m高程,Chao1指数和Shannon指数显著高于173 m高程.但撂荒草地和人工林地的土壤菌群α多样性并无显著差异.同时,水位波动和植被恢复均对土壤原核微生物的群落组成产生显著影响,不同样地中生物标志物类别具有明显差异.值得注意的是,植被恢复模式差异对土壤原核微生物群落结构的影响强于水位波动.此外,层次分割结果显示土壤pH是三峡水库消落带土壤原核微生物群落结构变化的主要驱动因子.以上结果可深化对水库消落带土壤微生物群落结构的认识,并为水库消落带生态系统的恢复重建提供科学参考.     

再生水构建水环境中沉水植物附着细菌群落特征

沉水植物茎、叶附着生物膜对再生水构建水环境的水质改善具有重要作用.为探究再生水水质及沉水植物种类对附着生物膜细菌群落特征的影响,选取再生水构建的水环境中不同种类沉水植物为研究对象,采用16S rRNA高通量测序技术对其附着生物膜及周围环境样本的细菌群落结构和功能基因进行分析.结果表明,再生水水体中氮磷营养物质在水环境中得到了20%~35%的吸收利用,下游水体中COD、浊度和色度呈现升高趋势.沉水植物附着生物膜中细菌群落与周围环境（土壤、底泥和水体）及再生水处理厂活性污泥的细菌群落存在差异：在群落多样性上,其丰富度和多样性显著低于土壤和底泥中细菌但高于水中浮游细菌;在群落结构上,其优势菌属及对应相对丰度与其它样本不同,主要优势菌属有鞘氨醇单胞菌属（Sphingomonas）、气单胞菌属（Aeromonas）、假单胞菌属（Pseudomonas）和不动杆菌属（Acinetobacter）,分别占比7%~40%.沉水植物种类和再生水水质（BOD₅、TN、NH₄⁺-N和TP）均会影响植物附着细菌群落,但水质对附着细菌群落的影响大于植物种类,且水质也会影响沉水植物附着细菌群落功能基因相对丰度,氮磷浓度较高区域氮循环与磷循环功能基因相对丰度较高.研究结果为揭示沉水植物附着细菌群落特征和优选沉水植物种植种类提供科学依据.     

粉煤灰添加对城市多源有机废弃物联合堆肥效能及堆体细菌群落的影响

为实现粉煤灰和多源有机废弃物的高效资源化利用,采用好氧堆肥的方法,以厨余垃圾、鸡粪和锯末（15:5:2）混合原料为底物,添加底物总湿重的5 %和10 %的粉煤灰作为处理组（5 % FA和10 % FA）,并以不添加粉煤灰作为对照处理（CK）,通过测定联合堆肥过程中理化性质、养分元素和细菌群落结构的变化,探究不同粉煤灰添加量对联合堆肥的促进效果.结果表明,添加5 %和10 %粉煤灰可以显著提高联合堆肥的最高温度（56.6 ℃和56.9 ℃）并延长高温期持续时间（9 d）,相较于对照处理,堆体总养分含量分别提高了4.09 %和13.55 %.在整个堆肥过程中,细菌群落结构发生了较大变化,各处理的细菌多样性均出现了明显的提高.在堆肥前期,变形菌门（Proteobacteria）是主要的优势门类,相对丰度在35.26 %~39.40 %之间.进入堆肥高温期,添加5 %和10 %粉煤灰处理中厚壁菌门（Firmicutes）相对丰度达到最高值,分别为52.46 %和67.72 %.芽孢杆菌属（Bacillus）和放线菌属（Thermobifida）是5 %和10 %粉煤灰添加量处理高温期的优势菌属,相对丰度分别为33.41 %和62.89 %（芽孢杆菌属）、33.06 %和12.23 %（放线菌属）.冗余分析（RDA）结果表明不同理化指标对细菌群落均有不同程度影响,其中有效磷、速效钾、有机质以及pH是影响细菌群落结构的主要环境因子.综上,添加粉煤灰促进了城市多源有机废弃物联合好氧堆肥的无害化和腐熟化,优化了微生物群落结构,提高堆肥产品的质量和效率.     

大通河流域土壤细菌及氮循环功能菌群沿海拔的空间分布

探究土壤微生物的海拔分布格局及其驱动机制对理解气候变化下陆地生态系统的响应至关重要.土壤微生物群落的海拔分布格局随空间尺度有所差异,为此分别沿大通河流域干流流向（海拔梯度1 000 m）和山体坡面（海拔梯度500 m）设置了两种空间尺度的样带,利用高通量测序技术分析土壤细菌群落结构和多样性沿海拔的分布特征,基于FAPROTAX数据库分析氮循环功能类群的海拔分布,探讨驱动土壤细菌群落沿海拔分布的关键环境因子.结果表明:①土壤理化性质沿海拔分布有显著差异,总氮（TN）和硝态氮（NO₃ ^-）含量与海拔正相关（P < 0.01）,土壤容重（BD）、pH与海拔负相关（P < 0.001）;②细菌群落OTU丰度沿海拔升高显著增大（P < 0.01）,丰富度和多样性指数沿海拔增大,但趋势不显著（P > 0.05）;③细菌群落以酸杆菌门（Acidobacteria）、变形菌门（Proteobacteria）和拟杆菌门（Bacteroidetes）为优势门,其相对丰度随海拔升高分别增加、减小和微弱减小;④参与氮循环的功能类群共13种,以硝化作用、好氧氨氧化和好氧亚硝酸盐氧化作用为主,随海拔升高响应规律不同,其中硝化作用细菌丰度显著增加（P < 0.01）,好氧氨氧化和硝酸还原细菌丰度微弱增加,而参与含氮化合物异化还原的细菌丰度先增后减;⑤冗余分析表明海拔（ELEV）、pH和氨氮（NH₄ ⁺）是驱动门水平土壤细菌群落的主要因子,Mantel分析表明土壤细菌氮循环优势类群均受海拔驱动（P < 0.01）.⑥流域和坡面尺度上细菌群落α-多样性沿海拔的规律一致,但土壤性质、氮循环功能菌群丰度和主要环境影响因子均不同.因此从不同空间尺度探究土壤微生物的海拔分布格局具有重要意义.     

不同曝气方式对人工湿地细菌多样性、代谢活性及功能的影响

细菌在人工湿地去除污染物过程中起着非常关键的作用.基于DNA和RNA高通量测序技术探讨了不同曝气强化方式影响下的人工湿地单元内细菌多样性、代谢活性和功能.结果发现:①养殖废水和人工湿地处理组共检测到细菌4 042个操作分类单元(OTUs),其中α-变形菌、γ-变形菌和拟杆菌为多样性最高的类群,且人工湿地曝气强化方式会在...     

Effects of site-selection bias on estimates of biodiversity change

Estimates of biodiversity change are essential for the management and conservation of ecosystems. Accurate estimates rely on selecting representative sites, but monitoring often focuses on sites of special interest. How such site-selection biases influence estimates of biodiversity change is largely unknown. Site-selection bias potentially occurs across four major sources of biodiversity data, decreasing in likelihood from citizen science, museums, national park monitoring, and academic research. We defined site-selection bias as a preference for sites that are either densely populated (i.e., abundance bias) or species rich (i.e., richness bias). We simulated biodiversity change in a virtual landscape and tracked the observed biodiversity at a sampled site. The site was selected either randomly or with a site-selection bias. We used a simple spatially resolved, individual-based model to predict the movement or dispersal of individuals in and out of the chosen sampling site. Site-selection bias exaggerated estimates of biodiversity loss in sites selected with a bias by on average 300–400% compared with randomly selected sites. Based on our simulations, site-selection bias resulted in positive trends being estimated as negative trends: richness increase was estimated as 0.1 in randomly selected sites, whereas sites selected with a bias showed a richness change of −0.1 to −0.2 on average. Thus, site-selection bias may falsely indicate decreases in biodiversity. We varied sampling design and characteristics of the species and found that site-selection biases were strongest in short time series, for small grains, organisms with low dispersal ability, large regional species pools, and strong spatial aggregation. Based on these findings, to minimize site-selection bias, we recommend use of systematic site-selection schemes; maximizing sampling area; calculating biodiversity measures cumulatively across plots; and use of biodiversity measures that are less sensitive to rare species, such as the effective number of species. Awareness of the potential impact of site-selection bias is needed for biodiversity monitoring, the design of new studies on biodiversity change, and the interpretation of existing data.     

Identifying robust strategies for assisted migration in a competitive stochastic metacommunity

Assisted migration (AM) is the translocation of species beyond their historical range to locations that are expected to be more suitable under future climate change. However, a relocated population may fail to establish in its donor community if there is high uncertainty in decision-making, climate, and interactions with the recipient ecological community. To quantify the benefit to persistence and risk of establishment failure of AM under different management scenarios (e.g., choosing target species, proportion of population to relocate, and optimal location to relocate), we built a stochastic metacommunity model to simulate several species reproducing, dispersing, and competing on a temperature gradient as temperature increases over time. Without AM, the species were vulnerable to climate change when they had low population sizes, short dispersal, and strong poleward competition. When relocating species that exemplified these traits, AM increased the long-term persistence of the species most when relocating a fraction of the donor population, even if the remaining population was very small or rapidly declining. This suggests that leaving behind a fraction of the population could be a robust approach, allowing managers to repeat AM in case they move the species to the wrong place and at the wrong time, especially when it is difficult to identify a species’ optimal climate. We found that AM most benefitted species with low dispersal ability and least benefited species with narrow thermal tolerances, for which AM increased extinction risk on average. Although relocation did not affect the persistence of nontarget species in our simple competitive model, researchers will need to consider a more complete set of community interactions to comprehensively understand invasion potential.