Salinity drives meiofaunal community structure dynamics across the Baltic ecosystem.
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ABSTRACT:
SUBMITTER: Broman E
PROVIDER: S-EPMC6852176 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Understanding the key processes that control bacterial community composition has enabled predictions of bacterial distribution and function within ecosystems. In this study, we used the Baltic Sea as a model system to quantify the phylogenetic signal of salinity and season with respect to bacterioplankton community composition. The abundances of 16S rRNA gene amplicon sequencing reads were analyzed from samples obtained from similar geographic locations in July and February along a brackish to marine salinity gradient in the Baltic Sea. While there was no distinct pattern of bacterial richness at different salinities, the number of bacterial phylotypes in winter was significantly higher than in summer. Bacterial community composition in brackish vs. marine conditions, and in July vs. February was significantly different. Non-metric multidimensional scaling showed that bacterial community composition was primarily separated according to salinity and secondly according to seasonal differences at all taxonomic ranks tested. Similarly, quantitative phylogenetic clustering implicated a phylogenetic signal for both salinity and seasonality. Our results suggest that global patterns of bacterial community composition with respect to salinity and season are the result of phylogenetically clustered ecological preferences with stronger imprints from salinity.
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Project description:Habitat loss is jeopardizing marine biodiversity. In the Mediterranean Sea, the algal forests of Cystoseira spp. form one of the most complex, productive and vulnerable shallow-water habitats. These forests are rapidly regressing with negative impact on the associated biodiversity, and potential consequences in terms of ecosystem functioning. Here, by comparing healthy Cystoseira forests and barren grounds (i.e., habitats where the macroalgal forests disappeared), we assessed the effects of habitat loss on meiofaunal and nematode biodiversity, and on some ecosystem functions (here measured in terms of prokaryotic and meiofaunal biomass). Overall, our results suggest that the loss of Cystoseira forests and the consequent barren formation is associated with the loss of meiofaunal higher taxa and a decrease of nematode biodiversity, leading to the collapse of the microbial and meiofaunal variables of ecosystem functions. We conclude that, given the very limited resilience of these ecosystems, active restoration of these vulnerable habitats is needed, in order to recover their biodiversity, ecosystem functions and associated services.
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Project description:Progress in molecular methods has enabled the monitoring of bacterial populations in time. Nevertheless, understanding community dynamics and its links with ecosystem functioning remains challenging due to the tremendous diversity of microorganisms. Conceptual frameworks that make sense of time series of taxonomically rich bacterial communities, regarding their potential ecological function, are needed. A key concept for organizing ecological functions is the niche, the set of strategies that enable a population to persist and define its impacts on the surroundings. Here we present a framework based on manifold learning to organize genomic information into potentially occupied bacterial metabolic niches over time. Manifold learning tries to uncover low-dimensional data structures in high-dimensional data sets that can be used to describe the data in reduced dimensions. We apply the method to re-construct the dynamics of putatively occupied metabolic niches using a long-term bacterial time series from the Baltic Sea, the Linnaeus Microbial Observatory (LMO). The results reveal a relatively low-dimensional space of occupied metabolic niches comprising groups of taxa with similar functional capabilities. Time patterns of occupied niches were strongly driven by seasonality. Some metabolic niches were dominated by one bacterial taxon, whereas others were occupied by multiple taxa, depending on the season. These results illustrate the power of manifold learning approaches to advance our understanding of the links between community composition and functioning in microbial systems. IMPORTANCE The increase in data availability of bacterial communities highlights the need for conceptual frameworks to advance our understanding of these complex and diverse communities alongside the production of such data. To understand the dynamics of these tremendously diverse communities, we need tools to identify overarching strategies and describe their role and function in the ecosystem in a comprehensive way. Here, we show that a manifold learning approach can coarse grain bacterial communities in terms of their metabolic strategies and that we can thereby quantitatively organize genomic information in terms of potentially occupied niches over time. This approach, therefore, advances our understanding of how fluctuations in bacterial abundances and species composition can relate to ecosystem functions and it can facilitate the analysis, monitoring, and future predictions of the development of microbial communities.
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Project description:Disturbances are natural features of ecosystems that promote variability in the community and ultimately maintain diversity. Although it is recognized that global change will affect environmental disturbance regimes, our understanding of the community dynamics governing ecosystem recovery and the maintenance of functional diversity in future scenarios is very limited. Here, we use one of the few ecosystems naturally exposed to future scenarios of environmental change to examine disturbance and recovery dynamics. We examine the recovery patterns of marine species from a physical disturbance across different acidification regimes caused by volcanic CO2 vents. Plots of shallow rocky reef were cleared of all species in areas of ambient, low, and extreme low pH that correspond to near-future and extreme scenarios for ocean acidification. Our results illustrate how acidification decreases the variability of communities, resulting in homogenization and reduced functional diversity at a landscape scale. Whereas the recovery trajectories in ambient pH were highly variable and resulted in a diverse range of assemblages, recovery was more predictable with acidification and consistently resulted in very similar algal-dominated assemblages. Furthermore, low pH zones had fewer signs of biological disturbance (primarily sea urchin grazing) and increased recovery rates of the dominant taxa (primarily fleshy algae). Together, our results highlight how environmental change can cause ecosystem simplification via environmentally mediated changes in community dynamics in the near future, with cascading impacts on functional diversity and ecosystem function.
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Project description:Climate change is likely to have large effects on the Baltic Sea ecosystem. Simulations indicate 2-4 °C warming and 50-80 % decrease in ice cover by 2100. Precipitation may increase ~30 % in the north, causing increased land runoff of allochthonous organic matter (AOM) and organic pollutants and decreased salinity. Coupled physical-biogeochemical models indicate that, in the south, bottom-water anoxia may spread, reducing cod recruitment and increasing sediment phosphorus release, thus promoting cyanobacterial blooms. In the north, heterotrophic bacteria will be favored by AOM, while phytoplankton production may be reduced. Extra trophic levels in the food web may increase energy losses and consequently reduce fish production. Future management of the Baltic Sea must consider the effects of climate change on the ecosystem dynamics and functions, as well as the effects of anthropogenic nutrient and pollutant load. Monitoring should have a holistic approach, encompassing both autotrophic (phytoplankton) and heterotrophic (e.g., bacterial) processes.
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Project description:Salinity is a significant factor for structuring microbial communities, but little is known for aquatic fungi, particularly in the pelagic zone of brackish ecosystems. In this study, we explored the diversity and composition of fungal communities following a progressive salinity decline (from 34 to 3 PSU) along three transects of ca. 2000 km in the Baltic Sea, the world's largest estuary. Based on 18S rRNA gene sequence analysis, we detected clear changes in fungal community composition along the salinity gradient and found significant differences in composition of fungal communities established above and below a critical value of 8 PSU. At salinities below this threshold, fungal communities resembled those from freshwater environments, with a greater abundance of Chytridiomycota, particularly of the orders Rhizophydiales, Lobulomycetales, and Gromochytriales. At salinities above 8 PSU, communities were more similar to those from marine environments and, depending on the season, were dominated by a strain of the LKM11 group (Cryptomycota) or by members of Ascomycota and Basidiomycota. Our results highlight salinity as an important environmental driver also for pelagic fungi, and thus should be taken into account to better understand fungal diversity and ecological function in the aquatic realm.
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Project description:Microorganisms are vital in mediating the earth's biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: 'When do we need to understand microbial community structure to accurately predict function?' We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.
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Project description:Background Intraspecific public goods are commonly shared within microbial populations, where the benefits of public goods are largely limited to closely related conspecifics. One example is the production of iron-scavenging siderophores that deliver iron to cells via specific cell envelope receptor and transport systems. Intraspecific social exploitation of siderophore producers is common, since non-producers avoid the costs of production but retain the cell envelope machinery for siderophore uptake. However, little is known about how interactions between species (i.e., interspecific interactions) can shape intraspecific public goods exploitation. Here, we predicted that strong competition for iron between species in diverse communities will increase costs of siderophore cooperation, and hence drive intraspecific exploitation. We examined how increasing microbial community species diversity shapes intraspecific social dynamics by monitoring the growth of siderophore producers and non-producers of the plant-growth promoting bacterium Pseudomonas fluorescens, embedded within tree-hole microbial communities ranging from 2 to 15 species. Results We find, contrary to our prediction, that siderophore production is favoured at higher levels of community species richness, driven by increased likelihood of encountering key species that reduce the growth of siderophore non-producing (but not producing) strains of P. fluorescens. Conclusions Our results suggest that maintaining a diverse soil microbiota could partly contribute to the maintenance of siderophore production in natural communities. Supplementary Information The online version contains supplementary material available at 10.1186/s12862-023-02152-8.
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