scholarly journals The Diversity Patterns of Rare to Abundant Microbial Eukaryotes Across a Broad Range of Salinities in a Solar Saltern

2021 ◽  
Author(s):  
Hyeon Been Lee ◽  
Dong Hyuk Jeong ◽  
Byung Cheol Cho ◽  
Jong Soo Park
Keyword(s):  
Community Dynamics ◽  
High Abundance ◽  
Solar Saltern ◽  
Hypersaline Environments ◽  
Predator Prey ◽  
Operational Taxonomic Units ◽  
Eukaryotic Community ◽  
Salinity Gradients ◽  
Microbial Eukaryotes ◽  
Taxonomic Novelty

AbstractSolar salterns are excellent artificial systems for examining species diversity and succession along salinity gradients. Here, the eukaryotic community in surface water of a Korean solar saltern (30 to 380 practical salinity units) was investigated from April 2019 to October 2020 using Illumina sequencing targeting the V4 and V9 regions of 18S rDNA. A total of 926 operational taxonomic units (OTUs) and 1,999 OTUs were obtained with the V4 and V9 regions, respectively. Notably, most of the OTUs were microbial eukaryotes, and the high-abundance groups (> 5% relative abundance (RA), Alveolata, Stramenopila, Archaeplastida, and Opisthokonta) usually accounted for > 90% of the total cumulative read counts and > 80% of all OTUs. Moreover, the high-abundance Alveolata (larger forms) and Stramenopila (smaller forms) groups displayed a significant inverse relationship, probably due to predator–prey interactions. Most of the low-abundance (0.1–5% RA) and rare (< 0.1% RA) groups remained small portion during the field surveys. Taxonomic novelty (at < 90% sequence identity) was high in the Amoebozoa, Cryptista, Haptista, Rhizaria, and Stramenopila groups (69.8% of all novel OTUs), suggesting the presence of a large number of hidden species in hypersaline environments. Remarkably, the high-abundance groups had little overlap with the other groups, implying the weakness of rare-to-prevalent community dynamics. The low-abundance Discoba group alone temporarily became the high-abundance group, suggesting that it is an opportunistic group. Overall, the composition and diversity of the eukaryotic community in hypersaline environments may be persistently stabilized, despite diverse disturbance events.

scholarly journals POTENTIAL ROLES OF BIOTIC FACTORS IN REGULATING ZOOPLANKTON COMMUNITY DYNAMICS IN JAKARTA BAY SHALLOW WATER COASTAL ECOSYSTEM

2012 ◽  
Vol 4 (1) ◽  
Author(s):  
Arief Rachman ◽  
Nurul Fitriya
Keyword(s):  
Food Availability ◽  
Community Dynamics ◽  
Phytoplankton Bloom ◽  
Zooplankton Community ◽  
Mesh Size ◽  
High Abundance ◽  
Zooplankton Abundance ◽  
Biotic Factors ◽  
Predator Prey ◽  
Prey Interaction

<p>The dynamics in zooplankton abundance were regulated by changes in water physical-chemical parameters and interaction with biotic factors. In this research we examined the relationship between zooplankton community dynamic and important biotic factors, such as predation and food availability, in Jakarta bay. Plankton samplings were done in 10 sampling stations in Jakarta bay, from July to November 2009. Zooplankton samples were collected using horizontal towing method with NORPAC plankton net (mesh size 300 μm). Salinity, water depth, water temperature, and water transparency were measured. Phytoplankton samples were also collected with the same method as zooplankton, using Kitahara plankton net (mesh size 80 μm). Zooplankton taxas were grouped into two groups, the prey and predatory zooplankton. The results showed that there were two different patterns in zooplankton groups dynamic i.e., the single and double peak. The abundance peak in most zooplankton groups, such as copepods, cirripeds, luciferids, and tunicates, were induced by the high food availability during the phytoplankton bloom in August. The high abundance of prey zooplankton groups in August was responded by the predatory zooplankton groups, resulting in high abundance of predatory zooplankton in adjacent month. The high abundance of ctenophores and chordates (fish larvae) were suggested as the main factor for the low abundance of other zooplankton in September. Physical and chemical factors were not the regulating factors due to the stability of those factors during this research period. Thus we concluded that food availability and predator-prey interaction were the main factors which regulate zooplankton community dynamics in Jakarta bay.</p><p>Keywords: predator-prey interaction, zooplankton, abundance peak, food availability, phytoplankton bloom</p>

scholarly journals POTENTIAL ROLES OF BIOTIC FACTORS IN REGULATING ZOOPLANKTON COMMUNITY DYNAMICS IN JAKARTA BAY SHALLOW WATER COASTAL ECOSYSTEM

2012 ◽  
Vol 4 (1) ◽  
Author(s):  
Arief Rachman ◽  
Nurul Fitriya
Keyword(s):  
Food Availability ◽  
Community Dynamics ◽  
Phytoplankton Bloom ◽  
Zooplankton Community ◽  
Mesh Size ◽  
High Abundance ◽  
Zooplankton Abundance ◽  
Biotic Factors ◽  
Predator Prey ◽  
Prey Interaction

The dynamics in zooplankton abundance were regulated by changes in water physical-chemical parameters and interaction with biotic factors. In this research we examined the relationship between zooplankton community dynamic and important biotic factors, such as predation and food availability, in Jakarta bay. Plankton samplings were done in 10 sampling stations in Jakarta bay, from July to November 2009. Zooplankton samples were collected using horizontal towing method with NORPAC plankton net (mesh size 300 μm). Salinity, water depth, water temperature, and water transparency were measured. Phytoplankton samples were also collected with the same method as zooplankton, using Kitahara plankton net (mesh size 80 μm). Zooplankton taxas were grouped into two groups, the prey and predatory zooplankton. The results showed that there were two different patterns in zooplankton groups dynamic i.e., the single and double peak. The abundance peak in most zooplankton groups, such as copepods, cirripeds, luciferids, and tunicates, were induced by the high food availability during the phytoplankton bloom in August. The high abundance of prey zooplankton groups in August was responded by the predatory zooplankton groups, resulting in high abundance of predatory zooplankton in adjacent month. The high abundance of ctenophores and chordates (fish larvae) were suggested as the main factor for the low abundance of other zooplankton in September. Physical and chemical factors were not the regulating factors due to the stability of those factors during this research period. Thus we concluded that food availability and predator-prey interaction were the main factors which regulate zooplankton community dynamics in Jakarta bay.Keywords: predator-prey interaction, zooplankton, abundance peak, food availability, phytoplankton bloom

scholarly journals What drives interaction strengths in complex food webs? A test with feeding rates of a generalist stream predator

2018 ◽  
Author(s):  
Daniel L. Preston ◽  
Jeremy S. Henderson ◽  
Landon P. Falke ◽  
Leah M. Segui ◽  
Tamara J. Layden ◽  
...  
Keyword(s):  
Food Webs ◽  
Body Mass ◽  
Prey Density ◽  
Scaling Laws ◽  
Community Dynamics ◽  
Abiotic Factors ◽  
Interaction Strength ◽  
Feeding Rates ◽  
Predator Prey ◽  
Mass Ratios

AbstractDescribing the mechanisms that drive variation in species interaction strengths is central to understanding, predicting, and managing community dynamics. Multiple factors have been linked to trophic interaction strength variation, including species densities, species traits, and abiotic factors. Yet most empirical tests of the relative roles of multiple mechanisms that drive variation have been limited to simplified experiments that may diverge from the dynamics of natural food webs. Here, we used a field-based observational approach to quantify the roles of prey density, predator density, predator-prey body-mass ratios, prey identity, and abiotic factors in driving variation in feeding rates of reticulate sculpin (Cottus perplexus). We combined data on over 6,000 predator-prey observations with prey identification time functions to estimate 289 prey-specific feeding rates at nine stream sites in Oregon. Feeding rates on 57 prey types showed an approximately log-normal distribution, with few strong and many weak interactions. Model selection indicated that prey density, followed by prey identity, were the two most important predictors of prey-specific sculpin feeding rates. Feeding rates showed a positive, accelerating relationship with prey density that was inconsistent with predator saturation predicted by current functional response models. Feeding rates also exhibited four orders-of-magnitude in variation across prey taxonomic orders, with the lowest feeding rates observed on prey with significant anti-predator defenses. Body-mass ratios were the third most important predictor variable, showing a hump-shaped relationship with the highest feeding rates at intermediate ratios. Sculpin density was negatively correlated with feeding rates, consistent with the presence of intraspecific predator interference. Our results highlight how multiple co-occurring drivers shape trophic interactions in nature and underscore ways in which simplified experiments or reliance on scaling laws alone may lead to biased inferences about the structure and dynamics of species-rich food webs.

scholarly journals Space race functional responses

2015 ◽  
Vol 282 (1801) ◽  
pp. 20142121 ◽  
Author(s):  
Henrik Sjödin ◽  
Åke Brännström ◽  
Göran Englund
Keyword(s):  
Functional Response ◽  
Community Dynamics ◽  
Simple Structure ◽  
Functional Responses ◽  
Response Models ◽  
Predator Prey ◽  
Prey System ◽  
Space Race ◽  
Functional Response Models ◽  
The Relationship

We derive functional responses under the assumption that predators and prey are engaged in a space race in which prey avoid patches with many predators and predators avoid patches with few or no prey. The resulting functional response models have a simple structure and include functions describing how the emigration of prey and predators depend on interspecific densities. As such, they provide a link between dispersal behaviours and community dynamics. The derived functional response is general but is here modelled in accordance with empirically documented emigration responses. We find that the prey emigration response to predators has stabilizing effects similar to that of the DeAngelis–Beddington functional response, and that the predator emigration response to prey has destabilizing effects similar to that of the Holling type II response. A stability criterion describing the net effect of the two emigration responses on a Lotka–Volterra predator–prey system is presented. The winner of the space race (i.e. whether predators or prey are favoured) is determined by the relationship between the slopes of the species' emigration responses. It is predicted that predators win the space race in poor habitats, where predator and prey densities are low, and that prey are more successful in richer habitats.

scholarly journals System Biology Modeling with Compositional Microbiome Data Reveals Personalized Gut Microbial Dynamics and Keystone Species

2018 ◽  
Author(s):  
Chenhao Li ◽  
Lisa Tucker-Kellogg ◽  
Niranjan Nagarajan
Keyword(s):  
Microbial Communities ◽  
High Throughput Sequencing ◽  
Community Dynamics ◽  
Keystone Species ◽  
Microbial Interactions ◽  
Natural Environments ◽  
Sequencing Data ◽  
Predator Prey ◽  
Public Datasets ◽  
Microbiome Data

AbstractA growing body of literature points to the important roles that different microbial communities play in diverse natural environments and the human body. The dynamics of these communities is driven by a range of microbial interactions from symbiosis to predator-prey relationships, the majority of which are poorly understood, making it hard to predict the response of the community to different perturbations. With the increasing availability of high-throughput sequencing based community composition data, it is now conceivable to directly learn models that explicitly define microbial interactions and explain community dynamics. The applicability of these approaches is however affected by several experimental limitations, particularly the compositional nature of sequencing data. We present a new computational approach (BEEM) that addresses this key limitation in the inference of generalised Lotka-Volterra models (gLVMs) by coupling biomass estimation and model inference in an expectation maximization like algorithm (BEEM). Surprisingly, BEEM outperforms state-of-the-art methods for inferring gLVMs, while simultaneously eliminating the need for additional experimental biomass data as input. BEEM’s application to previously inaccessible public datasets (due to the lack of biomass data) allowed us for the first time to analyse microbial communities in the human gut on a per individual basis, revealing personalised dynamics and keystone species.

scholarly journals Dynamics of Predator-Prey Community with Age Structures and Its Changing Due To Harvesting

2020 ◽  
Vol 15 (1) ◽  
pp. 73-92
Author(s):  
G.P. Neverova ◽  
O.L. Zhdanova ◽  
E.Ya. Frisman
Keyword(s):  
Community Dynamics ◽  
Initial Conditions ◽  
Reproductive Potential ◽  
Stable State ◽  
Stability Domain ◽  
Prey Population ◽  
Dynamic Mode ◽  
Predator Population ◽  
Time Model ◽  
Predator Prey

The paper studies dynamic modes of discrete-time model of structured predator-prey community like “arctic fox – rodent” and changing its dynamic modes due to interspecific interaction. We paid special attention to the analysis of situations in which changes in the dynamic modes are possible. In particularly, 3-cycle emerging in prey population can result in predator extinction. Moreover, this solution corresponding to an incomplete community simultaneously coexists with the solution describing dynamics of complete community, which can be both stable and unstable. The anthropogenic impact on the community dynamics is studied, that is realized as harvest of some part of predator or prey population. It is shown that prey harvesting leads to expansion of parameter space domain with non-trivial stable numbers of community populations. In this case, the prey harvest has little effect on the predator dynamics; changes are mainly associated with multistability areas. In particular, the multistability domain narrows, in which changing initial conditions leads to different dynamic regimes, such as the transition to a stable state or periodic oscillations. As a result, community dynamics becomes more predictable. It is shown that the dynamics of prey population is sensitive to its harvesting. Even a small harvest rate results in disappearance of population size fluctuations: the stable state captures the entire phase space in multistability areas. In the case of the predator population harvest, stability domain of the nontrivial fixed point expands along the parameter of the predator birth rate. Accordingly, a case where predator determines the prey population dynamics is possible only at high values of predator reproductive potential. It is shown that in the case of predator harvest, a change in the community dynamic mode is possible because of a shifting dynamic regime in the prey population initiating the same nature fluctuations in the predator population. The dynamic regimes emerging in the community models with and without harvesting were compared.

scholarly journals From Forest Soil to the Canopy: Increased Habitat Diversity Does Not Increase Species Richness of Cercozoa and Oomycota in Tree Canopies

2020 ◽  
Vol 11 ◽  
Author(s):  
Robin-Tobias Jauss ◽  
Susanne Walden ◽  
Anna Maria Fiore-Donno ◽  
Kenneth Dumack ◽  
Stefan Schaffer ◽  
...  
Keyword(s):  
Species Richness ◽  
Beta Diversity ◽  
High Throughput Sequencing ◽  
Habitat Diversity ◽  
Specific Primers ◽  
Operational Taxonomic Units ◽  
Microbial Eukaryotes ◽  
Tree Canopies ◽  
Species Performance ◽  
Factor Governing

Tree canopies provide habitats for diverse and until now, still poorly characterized communities of microbial eukaryotes. One of the most general patterns in community ecology is the increase in species richness with increasing habitat diversity. Thus, environmental heterogeneity of tree canopies should be an important factor governing community structure and diversity in this subsystem of forest ecosystems. Nevertheless, it is unknown if similar patterns are reflected at the microbial scale within unicellular eukaryotes (protists). In this study, high-throughput sequencing of two prominent protistan taxa, Cercozoa (Rhizaria) and Oomycota (Stramenopiles), was performed. Group specific primers were used to comprehensively analyze their diversity in various microhabitats of a floodplain forest from the forest floor to the canopy region. Beta diversity indicated highly dissimilar protistan communities in the investigated microhabitats. However, the majority of operational taxonomic units (OTUs) was present in all samples, and therefore differences in beta diversity were mainly related to species performance (i.e., relative abundance). Accordingly, habitat diversity strongly favored distinct protistan taxa in terms of abundance, but due to their almost ubiquitous distribution the effect of species richness on community composition was negligible.

scholarly journals Community dynamics and sensitivity to model structure: towards a probabilistic view of process-based model predictions

2018 ◽  
Vol 15 (149) ◽  
pp. 20180741 ◽  
Author(s):  
Clement Aldebert ◽  
Daniel B. Stouffer
Keyword(s):  
Biological Sciences ◽  
Community Dynamics ◽  
Parametric Uncertainty ◽  
Proof Of Concept ◽  
Predator Prey ◽  
Predictive Uncertainty ◽  
Structural Sensitivity ◽  
Model Predictions ◽  
Complex Models ◽  
Process Based Models

Statistical inference and mechanistic, process-based modelling represent two philosophically different streams of research whose primary goal is to make predictions. Here, we merge elements from both approaches to keep the theoretical power of process-based models while also considering their predictive uncertainty using Bayesian statistics. In environmental and biological sciences, the predictive uncertainty of process-based models is usually reduced to parametric uncertainty. Here, we propose a practical approach to tackle the added issue of structural sensitivity, the sensitivity of predictions to the choice between quantitatively close and biologically plausible models. In contrast to earlier studies that presented alternative predictions based on alternative models, we propose a probabilistic view of these predictions that include the uncertainty in model construction and the parametric uncertainty of each model. As a proof of concept, we apply this approach to a predator–prey system described by the classical Rosenzweig–MacArthur model, and we observe that parametric sensitivity is regularly overcome by structural sensitivity. In addition to tackling theoretical questions about model sensitivity, the proposed approach can also be extended to make probabilistic predictions based on more complex models in an operational context. Both perspectives represent important steps towards providing better model predictions in biology, and beyond.

Rare unclassified 16S rRNA operational taxonomic units from the uncharted Engaño Bay (Argentinean Patagonia)

2018 ◽  
Vol 64 (1) ◽  
pp. 91-96
Author(s):  
Andrea Y. Calvo ◽  
Julieta M. Manrique ◽  
Leandro R. Jones
Keyword(s):  
16S Rrna ◽  
Community Dynamics ◽  
Sequence Data ◽  
River Estuary ◽  
Fragmented Habitats ◽  
Operational Taxonomic Units ◽  
Microbial Community Dynamics ◽  
Argentinean Patagonia ◽  
Culture Independent ◽  
Taxonomic Assignments

Rare microbes make up most of the diversity of marine microbiomes, and recent works have highlighted their importance for microbial community dynamics and in fragmented habitats. Rare taxa have been infrequently studied in comparison with abundant groups, and rare unclassified sequences are common in culture-independent studies. Here, we describe a detailed analysis of nonclassifiable sequences from the Chubut river estuary at the Argentinean Patagonia. Standard taxonomic assignments of environmental 16S rRNA sequences resulted in about 13% unclassified operational taxonomic units (OTUs). The potential affiliations of these OTUs could be narrowed by mapping the classification software assignments on a phylogeny obtained directly from our environmental sequence data. Customized BLAST analyses were remarkably consistent with these phylogenetic assignments, especially when the unclassified OTUs were blasted against sequences from cultured and type microorganisms. In addition, our BLAST analyses revealed significant similarities between several unclassified OTUs and a plethora of unclassified sequences from around the world. Further phylogenetic comparisons with 6194 carefully selected reference sequences showed that these unclassified sequences may correspond to 5 unnamed groups, possibly encompassing ranks from subclass to family inside the Alphaproteobacteria, and to an unknown Gracilibacteria lineage. Overall, these results demonstrate the value of straight phylogenetic analysis, customized BLAST searches, and comparisons with sequences from type material, for the systematic study of rare unclassified sequences.

Composition and distribution patterns of eukaryotic microbial plankton in the ultra-oligotrophic Eastern Mediterranean Sea

2020 ◽  
Vol 84 ◽  
pp. 155-173
Author(s):  
I Santi ◽  
P Kasapidis ◽  
S Psarra ◽  
G Assimakopoulou ◽  
A Pavlidou ◽  
...  
Keyword(s):  
Mediterranean Sea ◽  
Deep Sea ◽  
Environmental Variables ◽  
Eastern Mediterranean ◽  
Distribution Patterns ◽  
Eastern Mediterranean Sea ◽  
Operational Taxonomic Units ◽  
Microbial Eukaryotes ◽  
Levantine Basin ◽  
Microbial Plankton

Marine microbial eukaryotes play crucial roles in water-column ecosystems; however, there are regional gaps in the investigation of natural microbial eukaryote communities, and uncertainties concerning their distribution persevere. This study combined 18S rRNA metabarcoding, biomass measurements and statistical analyses of multiple environmental variables to examine the distribution of planktonic microbial eukaryotes at different sites and water layers in the ultra-oligotrophic Eastern Mediterranean Sea (Western Levantine Basin). Our results showed that microbial eukaryotic communities were structured by depth. In surface waters, different sites shared high percentages of molecular operational taxonomic units (MOTUs), but this was not the case for deep-sea communities (≥1000 m). Plankton biomass was significantly different among sites, implying that communities of a similar composition may not support the same activity or population size. The deep-sea communities showed high percentages of unassigned MOTUs, highlighting the sparsity of the existing information on deep-sea plankton eukaryotes. Water temperature and dissolved organic matter significantly affected community distribution. Micro-eukaryotic distribution was additionally affected by the nitrogen to phosphorus ratio and viral abundance, while nano- and pico-communities were affected by zooplankton. The present study explores microbial plankton eukaryotes in their natural oligotrophic environment and highlights that, even within restricted oceanic areas, marine plankton may follow distribution patterns that are largely controlled by environmental variables.

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