scholarly journals Use of null models to compare the assembly of northeast Atlantic bacterial community in the presence of crude oil with either chemical dispersant or biosurfactant

2020 ◽  
Author(s):  
Christina Nikolova ◽  
Umer Zeeshan Ijaz ◽  
Tony Gutierrez
Keyword(s):  
Bacterial Community ◽  
Crude Oil ◽  
Community Assembly ◽  
Beta Diversity ◽  
Evolutionary Process ◽  
Null Model ◽  
Null Models ◽  
Relative Importance ◽  
Diversity Pattern ◽  
Chemical Dispersant

AbstractThe compositions of marine microbial communities in response to crude oil in the presence of biosurfactant or synthetic dispersants have been extensively studied in the last decade. Assembly processes, however, in such communities are poorly understood. In this study, we used seven different but complementing null model approaches, such as elements of metacommunity structure, Raup-Crick beta-diversity, normalised stochasticity ratio, Tucker’s null model, quantitative process estimates, lottery assembly, and phylogenetic dispersion models, to quantify the relative importance of ecological process that drive the community assembly. We found that the presence of chemical dispersant in the oil-amended microcosms induced significant temporal changes in the assembly processes that were different from the oil-only or biogenic dispersant-amended microcosms. The assembly processes in all microcosms were neither purely deterministic nor stochastic, but increasingly deterministic in dispersant-amended microcosms. Furthermore, the relative importance of determinisms varied over time and was strongest during the middle phase of incubation. Tucker’s null model revealed that phylogenetically distinct taxa might have shaped the bacterial community assembly in the different microcosms towards more niche or neutral processes. Moreover, there was faster recruitment of phylogenetically distant species in the dispersant-amended community. Drift, homogenising selection and dispersal limitation were the dominant assembly processes in all microcosms, but variable selection was only important in dispersant-amended microcosms. In conclusion, our study highlights that the assembly processes in marine bacterial communities are not static but rather dynamic, and the chemical dispersant can cause significantly different patterns of community assembly compared to non-amended or biosurfactant-amended microcosms.ImportanceThe null model strategy is designed to intentionally exclude an ecological or evolutionary process of interest and create a beta diversity pattern that would be expected in the absence of this particular process – i.e. the community structure is random in respect to the process being tested. Recent advancements of bioinformatics and statistical tools have made it possible to apply theoretical macroecological concepts to microbial metagenomics in order to better understand and quantify the mechanisms and patterns controlling the complexity of microbial ecology. The conclusions from the null models can help predict the changes in microbial biodiversity and ecosystem services in oil polluted environments and therefore assist in making effective decisions with regards to what would be the best oil spill response option for similar environmental conditions.

scholarly journals A quantitative framework reveals ecological drivers of grassland microbial community assembly in response to warming

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Daliang Ning ◽  
Mengting Yuan ◽  
Linwei Wu ◽  
Ya Zhang ◽  
Xue Guo ◽  
...  
Keyword(s):  
Animal Ecology ◽  
Microbial Community ◽  
Community Assembly ◽  
Null Model ◽  
High Accuracy ◽  
Relative Importance ◽  
Experimental Warming ◽  
Community Based ◽  
Microbial Community Assembly ◽  
Over Time

Abstract Unraveling the drivers controlling community assembly is a central issue in ecology. Although it is generally accepted that selection, dispersal, diversification and drift are major community assembly processes, defining their relative importance is very challenging. Here, we present a framework to quantitatively infer community assembly mechanisms by phylogenetic bin-based null model analysis (iCAMP). iCAMP shows high accuracy (0.93–0.99), precision (0.80–0.94), sensitivity (0.82–0.94), and specificity (0.95–0.98) on simulated communities, which are 10–160% higher than those from the entire community-based approach. Application of iCAMP to grassland microbial communities in response to experimental warming reveals dominant roles of homogeneous selection (38%) and ‘drift’ (59%). Interestingly, warming decreases ‘drift’ over time, and enhances homogeneous selection which is primarily imposed on Bacillales. In addition, homogeneous selection has higher correlations with drought and plant productivity under warming than control. iCAMP provides an effective and robust tool to quantify microbial assembly processes, and should also be useful for plant and animal ecology.

scholarly journals Hill-based Dissimilarity Indices and Null Models for Analysis of Microbial Community Assembly

2020 ◽  
Author(s):  
Oskar Modin ◽  
Raquel Liebana ◽  
Soroush Saheb-Alam ◽  
Britt-Marie Wilén ◽  
Carolina Suarez ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Community Assembly ◽  
Null Model ◽  
Amplicon Sequencing ◽  
Null Models ◽  
Marker Genes ◽  
Experimental Systems ◽  
Microbial Community Assembly ◽  
The Impact

Abstract Background: High-throughput amplicon sequencing of marker genes, such as the 16S rRNA gene in Bacteria and Archaea, provides a wealth of information about the composition of microbial communities. To quantify differences between samples and draw conclusions about factors affecting community assembly, dissimilarity indices are typically used. However, results are subject to several biases and data interpretation can be challenging. The Jaccard and Bray-Curtis indices, which are often used to quantify taxonomic dissimilarity, are not necessarily the most logical choices. Instead, we argue that Hill-based indices, which make it possible to systematically investigate the impact of relative abundance on dissimilarity, should be used for robust analysis of data. In combination with a null model, mechanisms of microbial community assembly can be analyzed. Here, we also introduce a new software, qdiv, which enables rapid calculations of Hill-based dissimilarity indices in combination with null models.Results: Using amplicon sequencing data from two experimental systems, aerobic granular sludge (AGS) reactors and microbial fuel cells (MFC), we show that the choice of dissimilarity index can have considerable impact on results and conclusions. High dissimilarity between replicates because of random sampling effects make incidence-based indices less suited for identifying differences between groups of samples. Determining a consensus table based on count tables generated with different bioinformatic pipelines reduced the number of low-abundant, potentially spurious amplicon sequence variants (ASVs) in the data sets, which led to lower dissimilarity between replicates. Analysis with a combination of Hill-based indices and a null model allowed us to show that different ecological mechanisms acted on different fractions of the microbial communities in the experimental systems.Conclusions: Hill-based indices provide a rational framework for analysis of dissimilarity between microbial community samples. In combination with a null model, the effects of deterministic and stochastic community assembly factors on taxa of different relative abundances can be systematically investigated. Calculations of Hill-based dissimilarity indices in combination with a null model can be done in qdiv, which is freely available as a Python package (https://github.com/omvatten/qdiv). In qdiv, a consensus table can also be determined from several count tables generated with different bioinformatic pipelines.

scholarly journals A quantitative framework reveals the ecological drivers of grassland soil microbial community assembly in response to warming

2020 ◽  
Author(s):  
Daliang Ning ◽  
Mengting Yuan ◽  
Linwei Wu ◽  
Ya Zhang ◽  
Xue Guo ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Community Assembly ◽  
Soil Microbial Community ◽  
Null Model ◽  
Relative Importance ◽  
Community Based ◽  
Grassland Soil ◽  
Soil Microbial ◽  
Microbial Community Assembly

AbstractUnraveling the drivers controlling community assembly is a central issue in ecology. Selection, dispersal, diversification and drift are conceptually accepted as major community assembly processes. Defining their relative importance in governing biodiversity is compellingly needed, but very challenging. Here, we present a novel framework to quantitatively infer community assembly mechanisms by phylogenetic bin-based null model analysis (iCAMP). Our results with simulated microbial communities showed that iCAMP had high accuracy (0.93 - 0.99), precision (0.80 - 0.94), sensitivity (0.82 - 0.94), and specificity (0.95 - 0.98), which were 10-160% higher than those from the entire community-based approach. Applying it to grassland microbial communities in response to experimental warming, our analysis showed that homogeneous selection (38%) and “drift” (59%) played dominant roles in controlling grassland soil microbial community assembly. Interestingly, warming enhanced homogeneous selection, but decreased “drift” over time. Warming-enhanced selection was primarily imposed on Bacillales in Firmicutes, which were strengthened by increased drought and reduced plant productivity. This general framework should also be useful for plant and animal ecology.

scholarly journals Hill-based dissimilarity indices and null models for analysis of microbial community assembly

2020 ◽  
Author(s):  
Oskar Modin ◽  
Raquel Liébana ◽  
Soroush Saheb-Alam ◽  
Britt-Marie Wilén ◽  
Carolina Suarez ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Community Assembly ◽  
Null Model ◽  
Amplicon Sequencing ◽  
Null Models ◽  
Marker Genes ◽  
Experimental Systems ◽  
Microbial Community Assembly ◽  
The Impact

Abstract Background: High-throughput amplicon sequencing of marker genes, such as the 16S rRNA gene in Bacteria and Archaea, provides a wealth of information about the composition of microbial communities. To quantify differences between samples and draw conclusions about factors affecting community assembly, dissimilarity indices are typically used. However, results are subject to several biases and data interpretation can be challenging. The Jaccard and Bray-Curtis indices, which are often used to quantify taxonomic dissimilarity, are not necessarily the most logical choices. Instead, we argue that Hill-based indices, which make it possible to systematically investigate the impact of relative abundance on dissimilarity, should be used for robust analysis of data. In combination with a null model, mechanisms of microbial community assembly can be analyzed. Here, we also introduce a new software, qdiv, which enables rapid calculations of Hill-based dissimilarity indices in combination with null models.Results: Using amplicon sequencing data from two experimental systems, aerobic granular sludge (AGS) reactors and microbial fuel cells (MFC), we show that the choice of dissimilarity index can have considerable impact on results and conclusions. High dissimilarity between replicates because of random sampling effects make incidence-based indices less suited for identifying differences between groups of samples. Determining a consensus table based on count tables generated with different bioinformatic pipelines reduced the number of low-abundant, potentially spurious amplicon sequence variants (ASVs) in the data sets, which led to lower dissimilarity between replicates. Analysis with a combination of Hill-based indices and a null model allowed us to show that different ecological mechanisms acted on different fractions of the microbial communities in the experimental systems.Conclusions: Hill-based indices provide a rational framework for analysis of dissimilarity between microbial community samples. In combination with a null model, the effects of deterministic and stochastic community assembly factors on taxa of different relative abundances can be systematically investigated. Calculations of Hill-based dissimilarity indices in combination with a null model can be done in qdiv, which is freely available as a Python package (https://github.com/omvatten/qdiv). In qdiv, a consensus table can also be determined from several count tables generated with different bioinformatic pipelines.

scholarly journals Disturbance alters beta-diversity but not the relative importance of community assembly mechanisms

2015 ◽  
Vol 103 (5) ◽  
pp. 1291-1299 ◽  
Author(s):  
Jonathan A. Myers ◽  
Jonathan M. Chase ◽  
Raelene M. Crandall ◽  
Iván Jiménez
Keyword(s):  
Community Assembly ◽  
Beta Diversity ◽  
Relative Importance

scholarly journals Synthesis of photochemical transformations of oil in the sea

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Collin P. Ward ◽  
Edward B. Overton
Keyword(s):  
Crude Oil ◽  
Oil Spill ◽  
Research Question ◽  
Photochemical Oxidation ◽  
Relative Importance ◽  
Weathering Processes ◽  
Photochemical Transformations ◽  
Chemical Dispersant ◽  
Oil Spill Response ◽  
Physical And Chemical

Abstract: In this presentation and article, we synthesize findings from a workshop about our understanding of the interplay between crude oil photochemical oxidation and oil spill response, emphasizing how this understanding has evolved since the 2010 DWH spill. Our discussion is guided by one overarching questions: what role does photochemical oxidation play towards informing effective oil spill response operations? We show that prior to the DWH spill, our understanding of the relative importance of oil weathering processes, specifically photochemical weathering, was incomplete. We further explore how accounting for photochemical changes to oil's properties (physical and chemical) could improve the effectiveness of oil spill response operations, specifically chemical dispersant applications. Lastly, we identify priority knowledge gaps related to this guiding research question.

scholarly journals Hill-based dissimilarity indices and null models for analysis of microbial community assembly

2020 ◽  
Author(s):  
Oskar Modin ◽  
Raquel Liébana ◽  
Soroush Saheb-Alam ◽  
Britt-Marie Wilén ◽  
Carolina Suarez ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Community Assembly ◽  
Null Model ◽  
Amplicon Sequencing ◽  
Null Models ◽  
Marker Genes ◽  
Experimental Systems ◽  
Microbial Community Assembly ◽  
The Impact

Abstract Background: High-throughput amplicon sequencing of marker genes, such as the 16S rRNA gene in Bacteria and Archaea, provides a wealth of information about the composition of microbial communities. To quantify differences between samples and draw conclusions about factors affecting community assembly, dissimilarity indices are typically used. However, results are subject to several biases and data interpretation can be challenging. The Jaccard and Bray-Curtis indices, which are often used to quantify taxonomic dissimilarity, are not necessarily the most logical choices. Instead, we argue that Hill-based indices, which make it possible to systematically investigate the impact of relative abundance on dissimilarity, should be used for robust analysis of data. In combination with a null model, mechanisms of microbial community assembly can be analyzed. Here, we also introduce a new software, qdiv, which enables rapid calculations of Hill-based dissimilarity indices in combination with null models.Results: Using amplicon sequencing data from two experimental systems, aerobic granular sludge (AGS) reactors and microbial fuel cells (MFC), we show that the choice of dissimilarity index can have considerable impact on results and conclusions. High dissimilarity between replicates because of random sampling effects make incidence-based indices less suited for identifying differences between groups of samples. Determining a consensus table based on count tables generated with different bioinformatic pipelines reduced the number of low-abundant, potentially spurious amplicon sequence variants (ASVs) in the data sets, which led to lower dissimilarity between replicates. Analysis with a combination of Hill-based indices and a null model allowed us to show that different ecological mechanisms acted on different fractions of the microbial communities in the experimental systems.Conclusions: Hill-based indices provide a rational framework for analysis of dissimilarity between microbial community samples. In combination with a null model, the effects of deterministic and stochastic community assembly factors on taxa of different relative abundances can be systematically investigated. Calculations of Hill-based dissimilarity indices in combination with a null model can be done in qdiv, which is freely available as a Python package (https://github.com/omvatten/qdiv). In qdiv, a consensus table can also be determined from several count tables generated with different bioinformatic pipelines.

scholarly journals Hill-based dissimilarity indices and null models for analysis of microbial community assembly

Microbiome ◽  
2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Oskar Modin ◽  
Raquel Liébana ◽  
Soroush Saheb-Alam ◽  
Britt-Marie Wilén ◽  
Carolina Suarez ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Community Assembly ◽  
Null Model ◽  
Amplicon Sequencing ◽  
Null Models ◽  
Marker Genes ◽  
Experimental Systems ◽  
Microbial Community Assembly ◽  
The Impact

Abstract Background High-throughput amplicon sequencing of marker genes, such as the 16S rRNA gene in Bacteria and Archaea, provides a wealth of information about the composition of microbial communities. To quantify differences between samples and draw conclusions about factors affecting community assembly, dissimilarity indices are typically used. However, results are subject to several biases, and data interpretation can be challenging. The Jaccard and Bray-Curtis indices, which are often used to quantify taxonomic dissimilarity, are not necessarily the most logical choices. Instead, we argue that Hill-based indices, which make it possible to systematically investigate the impact of relative abundance on dissimilarity, should be used for robust analysis of data. In combination with a null model, mechanisms of microbial community assembly can be analyzed. Here, we also introduce a new software, qdiv, which enables rapid calculations of Hill-based dissimilarity indices in combination with null models. Results Using amplicon sequencing data from two experimental systems, aerobic granular sludge (AGS) reactors and microbial fuel cells (MFC), we show that the choice of dissimilarity index can have considerable impact on results and conclusions. High dissimilarity between replicates because of random sampling effects make incidence-based indices less suited for identifying differences between groups of samples. Determining a consensus table based on count tables generated with different bioinformatic pipelines reduced the number of low-abundant, potentially spurious amplicon sequence variants (ASVs) in the data sets, which led to lower dissimilarity between replicates. Analysis with a combination of Hill-based indices and a null model allowed us to show that different ecological mechanisms acted on different fractions of the microbial communities in the experimental systems. Conclusions Hill-based indices provide a rational framework for analysis of dissimilarity between microbial community samples. In combination with a null model, the effects of deterministic and stochastic community assembly factors on taxa of different relative abundances can be systematically investigated. Calculations of Hill-based dissimilarity indices in combination with a null model can be done in qdiv, which is freely available as a Python package (https://github.com/omvatten/qdiv). In qdiv, a consensus table can also be determined from several count tables generated with different bioinformatic pipelines.

Direct evidence for deterministic assembly of bacterial communities in full-scale municipal wastewater treatment facilities

2021 ◽  
Author(s):  
Taegyu Kim ◽  
Sebastian Behrens ◽  
Timothy M. LaPara
Keyword(s):  
Wastewater Treatment ◽  
Bacterial Community ◽  
Community Composition ◽  
Community Assembly ◽  
Continuous Flow ◽  
Bacterial Community Composition ◽  
Null Model ◽  
Indirect Methods ◽  
Bioreactor Design ◽  
Treatment Facilities

In this study we investigated whether bacterial community composition in full-scale wastewater treatment bioreactors can be better explained by niche- or neutral- based theory (deterministic or stochastic) and whether bioreactor design (continuous-flow vs. fill-and-draw) affected community assembly. Four wastewater treatment facilities (one with quadruplicated continuous-flow bioreactors, two with one continuous-flow bioreactor each, one with triplicated fill-and-draw bioreactors) were investigated. Bioreactor community composition was characterized by sequencing of PCR-amplified 16S rRNA gene fragments. Replicate bioreactors at the same wastewater treatment facility had largely reproducible (i.e., deterministic) bacterial community composition, although bacterial community composition in continuous-flow bioreactors was significantly more reproducible ( P < 0.001) than in fill-and-draw bioreactors (Bray-Curtis dissimilarity: μ = 0.48 ± 0.06 vs. 0.58 ± 0.08). Next, we compared our results to previously-used indirect methods for distinguishing between deterministic and stochastic community assembly mechanisms. Synchronicity was observed in the bacterial community composition among bioreactors within the same metropolitan region, consistent with deterministic community assembly. Similarly, a null model-based analysis also indicated that all wastewater bioreactor communities were controlled by deterministic factors and that continuous-flow bioreactors were significantly more deterministic ( P < 0.001) than fill-and-draw bioreactors (nearest-taxon index: μ = 3.3 ± 0.6 vs. 2.7 ± 0.8). Our results indicate that bacterial community composition in wastewater treatment bioreactors is better explained by deterministic community assembly theory; simultaneously, our results validate previously-used but indirect methods to quantify whether microbial communities were assembled via deterministic or stochastic mechanisms. IMPORTANCE Understanding the mechanisms of bacterial community assembly is one of the grand challenges of microbial ecology. In environmental systems, this challenge is exacerbated because “replicate” experiments are typically impossible; that is, microbial ecologists cannot fabricate multiple field-scale experiments of identical, natural ecosystems. Our results directly demonstrate that deterministic mechanisms are more prominent than stochastic mechanisms in the assembly of wastewater treatment bioreactor communities. Our results also suggest that wastewater treatment bioreactor design is pertinent, such that the imposition of feast-famine conditions (i.e., fill-and-draw bioreactors) nudge bacterial community assembly more towards stochastic mechanisms compared to the imposition of stringent nutrient limitation (i.e., continuous-flow bioreactors). Our research also validates the previously-used indirect methods (synchronous community dynamics and an application of a null-model) for characterizing the relative importance of deterministic versus stochastic mechanisms of community assembly.

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