scholarly journals Metamorphosis of a Scleractinian Coral in Response to Microbial Biofilms

2004 ◽  
Vol 70 (2) ◽  
pp. 1213-1221 ◽  
Author(s):  
Nicole S. Webster ◽  
Luke D. Smith ◽  
Andrew J. Heyward ◽  
Joy E. M. Watts ◽  
Richard I. Webb ◽  
...  
Keyword(s):  
Community Structure ◽  
Coral Reef ◽  
Scleractinian Coral ◽  
Denaturing Gradient Gel Electrophoresis ◽  
Marine Invertebrate ◽  
Principal Component ◽  
Coralline Algae ◽  
Larval Metamorphosis ◽  
Microbial Biofilms ◽  
Wide Range

ABSTRACT Microorganisms have been reported to induce settlement and metamorphosis in a wide range of marine invertebrate species. However, the primary cue reported for metamorphosis of coral larvae is calcareous coralline algae (CCA). Herein we report the community structure of developing coral reef biofilms and the potential role they play in triggering the metamorphosis of a scleractinian coral. Two-week-old biofilms induced metamorphosis in less than 10% of larvae, whereas metamorphosis increased significantly on older biofilms, with a maximum of 41% occurring on 8-week-old microbial films. There was a significant influence of depth in 4- and 8-week biofilms, with greater levels of metamorphosis occurring in response to shallow-water communities. Importantly, larvae were found to settle and metamorphose in response to microbial biofilms lacking CCA from both shallow and deep treatments, indicating that microorganisms not associated with CCA may play a significant role in coral metamorphosis. A polyphasic approach consisting of scanning electron microscopy, fluorescence in situ hybridization (FISH), and denaturing gradient gel electrophoresis (DGGE) revealed that coral reef biofilms were comprised of complex bacterial and microalgal communities which were distinct at each depth and time. Principal-component analysis of FISH data showed that the Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, and Cytophaga-Flavobacterium of Bacteroidetes had the largest influence on overall community composition. A low abundance of Archaea was detected in almost all biofilms, providing the first report of Archaea associated with coral reef biofilms. No differences in the relative densities of each subdivision of Proteobacteria were observed between slides that induced larval metamorphosis and those that did not. Comparative cluster analysis of bacterial DGGE patterns also revealed that there were clear age and depth distinctions in biofilm community structure; however, no difference was detected in banding profiles between biofilms which induced larval metamorphosis and those where no metamorphosis occurred. This investigation demonstrates that complex microbial communities can induce coral metamorphosis in the absence of CCA.

scholarly journals Transects, quadrats, or points? What is the best combination to get a precise estimation of a coral community?

2019 ◽  
Author(s):  
Luis M. Montilla ◽  
Emy Miyazawa ◽  
Alfredo Ascanio ◽  
María López-Hernández ◽  
Gloria Mariño-Briceño ◽  
...  
Keyword(s):  
Community Structure ◽  
Coral Reef ◽  
Effect Size ◽  
Standard Error ◽  
Scleractinian Coral ◽  
Statistical Power ◽  
Coral Community ◽  
Sampling Effort ◽  
Precise Estimation

ABSTRACTThe characteristics of coral reef sampling and monitoring are highly variable, with numbers of units and sampling effort varying from one study to another. Numerous works have been carried out to determine an appropriate effect size through statistical power, however, always from a univariate perspective. In this work, we used the pseudo multivariate dissimilarity-based standard error (MultSE) approach to assess the precision of sampling scleractinian coral assemblages in reefs of Venezuela between 2017 and 2018 when using different combinations of number of transects, quadrats and points. For this, the MultSE of 36 sites previously sampled was estimated, using four 30m-transects with 15 photo-quadrats each and 25 random points per quadrat. We obtained that the MultSE was highly variable between sites and is not correlated with the univariate standard error nor with the richness of species. Then, a subset of sites was re-annotated using 100 uniformly distributed points, which allowed the simulation of different numbers of transects per site, quadrats per transect and points per quadrat using resampling techniques. The magnitude of the MultSE stabilized by adding more transects, however, adding more quadrats or points does not improve the estimate. For this case study, the error was reduced by half when using 10 transects, 10 quadrats per transect and 25 points per quadrat. We recommend the use of MultSE in reef monitoring programs, in particular when conducting pilot surveys to optimize the estimation of the community structure.

scholarly journals The use of pseudo-multivariate standard error to improve the sampling design of coral monitoring programs

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8429
Author(s):  
Luis M. Montilla ◽  
Emy Miyazawa ◽  
Alfredo Ascanio ◽  
María López-Hernández ◽  
Gloria Mariño-Briceño ◽  
...  
Keyword(s):  
Community Structure ◽  
Coral Reef ◽  
Standard Error ◽  
Scleractinian Coral ◽  
Statistical Power ◽  
Sampling Design ◽  
Sampling Effort ◽  
Monitoring Programs ◽  
Coral Monitoring

The characteristics of coral reef sampling and monitoring are highly variable, with numbers of units and sampling effort varying from one study to another. Numerous works have been carried out to determine an appropriate effect size through statistical power; however, these were always from a univariate perspective. In this work, we used the pseudo multivariate dissimilarity-based standard error (MultSE) approach to assess the precision of sampling scleractinian coral assemblages in reefs of Venezuela between 2017 and 2018 when using different combinations of number of transects, quadrats and points. For this, the MultSE of 36 sites previously sampled was estimated, using four 30m-transects with 15 photo-quadrats each and 25 random points per quadrat. We obtained that the MultSE was highly variable between sites and is not correlated with the univariate standard error nor with the richness of species. Then, a subset of sites was re-annotated using 100 uniformly distributed points, which allowed the simulation of different numbers of transects per site, quadrats per transect and points per quadrat using resampling techniques. The magnitude of the MultSE stabilized by adding more transects, however, adding more quadrats or points does not improve the estimate. For this case study, the error was reduced by half when using 10 transects, 10 quadrats per transect and 25 points per quadrat. We recommend the use of MultSE in reef monitoring programs, in particular when conducting pilot surveys to optimize the estimation of the community structure.

Allelopathic and Medicinal plant. 26. Millettia speciosa

2020 ◽  
Vol 51 (2) ◽  
pp. 125-146
Author(s):  
Nasiruddin Nasiruddin ◽  
Yu Zhangxin ◽  
Ting Zhao Chen Guangying ◽  
Minghui Ji
Keyword(s):  
Community Structure ◽  
Medicinal Plant ◽  
Gel Electrophoresis ◽  
Denaturing Gradient Gel Electrophoresis ◽  
Wiener Index ◽  
Pseudomonas Spp ◽  
Evenness Index ◽  
Gradient Gel Electrophoresis ◽  
Rhizosphere Pseudomonas

We grew cucumber in pots in greenhouse for 9-successive cropping cycles and analyzed the rhizosphere Pseudomonas spp. community structure and abundance by PCR-denaturing gradient gel electrophoresis and quantitative PCR. Results showed that continuous monocropping changed the cucumber rhizosphere Pseudomonas spp. community. The number of DGGE bands, Shannon-Wiener index and Evenness index decreased during the 3rd cropping and thereafter, increased up to the 7th cropping, however, however, afterwards they decreased again. The abundance of Pseudomonas spp. increased up to the 5th successive cropping and then decreased gradually. These findings indicated that the structure and abundance of Pseudomonas spp. community changed with long-term cucumber monocropping, which might be linked to soil sickness caused by its continuous monocropping.

It is better an approximate answer to the right question than the exact answer to the wrong question : the case of the psychometric analysis of the ASQ:SE

2020 ◽  
Author(s):  
Luis Anunciacao ◽  
janet squires ◽  
J. Landeira-Fernandez
Keyword(s):  
Internal Structure ◽  
Statistical Methods ◽  
Principal Component ◽  
Psychological Theory ◽  
Published Data ◽  
Multivariate Statistical ◽  
Exact Answer ◽  
Wide Range ◽  
Ages And Stages Questionnaire ◽  
The Right

One of the main activities in psychometrics is to analyze the internal structure of a test. Multivariate statistical methods, including Exploratory Factor analysis (EFA) and Principal Component Analysis (PCA) are frequently used to do this, but the growth of Network Analysis (NA) places this method as a promising candidate. The results obtained by these methods are of valuable interest, as they not only produce evidence to explore if the test is measuring its intended construct, but also to deal with the substantive theory that motivated the test development. However, these different statistical methods come up with different answers, providing the basis for different analytical and theoretical strategies when one needs to choose a solution. In this study, we took advantage of a large volume of published data (n = 22,331) obtained by the Ages and Stages Questionnaire Social-Emotional (ASQ:SE), and formed a subset of 500 children to present and discuss alternative psychometric solutions to its internal structure, and also to its subjacent theory. The analyses were based on a polychoric matrix, the number of factors to retain followed several well-known rules of thumb, and a wide range of exploratory methods was fitted to the data, including EFA, PCA, and NA. The statistical outcomes were divergent, varying from 1 to 6 domains, allowing a flexible interpretation of the results. We argue that the use of statistical methods in the absence of a well-grounded psychological theory has limited applications, despite its appeal. All data and codes are available at https://osf.io/z6gwv/.

scholarly journals Phenotypic Characterisation for Growth and Nut Characteristics Revealed the Extent of Genetic Diversity in Wild Macadamia Germplasm

Agriculture ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 680
Author(s):  
Thuy T. P. Mai ◽  
Craig M. Hardner ◽  
Mobashwer M. Alam ◽  
Robert J. Henry ◽  
Bruce L. Topp
Keyword(s):  
Genetic Diversity ◽  
Growth Traits ◽  
Principal Component ◽  
Conservation Strategies ◽  
Wild Germplasm ◽  
Phenotypic Characterisation ◽  
Wide Range ◽  
Genetic And Environmental Factors ◽  
Positive Correlations ◽  
Wild Accessions

Macadamia is a recently domesticated Australian native nut crop, and a large proportion of its wild germplasm is unexploited. Aiming to explore the existing diversity, 247 wild accessions from four species and inter-specific hybrids were phenotyped. A wide range of variation was found in growth and nut traits. Broad-sense heritability of traits were moderate (0.43–0.64), which suggested that both genetic and environmental factors are equally important for the variability of the traits. Correlations among the growth traits were significantly positive (0.49–0.76). There were significant positive correlations among the nut traits except for kernel recovery. The association between kernel recovery and shell thickness was highly significant and negative. Principal component analysis of the traits separated representative species groups. Accessions from Macadamia integrifolia Maiden and Betche, M. tetraphylla L.A.S. Johnson, and admixtures were clustered into one group and those of M. ternifolia F. Muell were separated into another group. In both M. integrifolia and M. tetraphylla groups, variation within site was greater than across sites, which suggested that the conservation strategies should concentrate on increased sampling within sites to capture wide genetic diversity. This study provides a background on the utilisation of wild germplasm as a genetic resource to be used in breeding programs and the direction for gene pool conservation.

scholarly journals Community structure and carbonate production of a temperate rhodolith bank from Arvoredo Island, southern Brazil

2004 ◽  
Vol 52 (3-4) ◽  
pp. 207-224 ◽  
Author(s):  
Douglas F. M. Gherardi
Keyword(s):  
Community Structure ◽  
Coralline Algae ◽  
Carbonate Content ◽  
Production Rates ◽  
Percentage Cover ◽  
Coralline Red Algae ◽  
Carbonate Production ◽  
Random Dispersal ◽  
Long Run ◽  
Main Bank

A small (100,000 m²) rhodolith bank located at the Arvoredo Marine Biological Reserve (Santa Catarina, Brazil) has been surveyed to determine the main bank components, the community structure, and carbonate production rates. Data from five photographic transects perpendicular to Arvoredo Island shore were complemented with sediment samples and shallow cores, all collected by scuba diving. The main bank component is the unattached, nongeniculate, coralline red algae Lithophyllum sp., used as substrate by the zoanthid Zoanthus sp. Percentage cover of living and dead coralline algae, zoanthids and sediment patches account for nearly 98% of the investigated area. Classification and ordination of samples showed that differences in the proportion of live and dead thalli of Lithophyllum sp. determine the relative abundances of zoanthids. Results also indicate that similarity of samples is high and community gradients are subtle. Significant differences in percentage cover along transects are concentrated in the central portion of the bank. Low carbonate content of sediments from deeper samples suggests low rates of recruitment and dispersal of coralline algae via fragmentation. However, carbonate production of Lithophyllum sp ranging from 55-136.3 g m-2 yr-1 agrees with production rates reported for other temperate settings. In the long run, rhodolith density at Arvoredo Is. is likely to be dependent upon random dispersal of spores and/or fragments from other source areas.

Data-Driven Analysis of Engine Mission Severity Using Non-Dimensional Groups

2021 ◽  
Author(s):  
Tim Brandes ◽  
Stefano Scarso ◽  
Christian Koch ◽  
Stephan Staudacher
Keyword(s):  
Support Vector Machine ◽  
Computation Time ◽  
Principal Component ◽  
General Term ◽  
Support Vector ◽  
Physical Parameters ◽  
Machine Model ◽  
Precision Error ◽  
Operational Conditions ◽  
Wide Range

Abstract A numerical experiment of intentionally reduced complexity is used to demonstrate a method to classify flight missions in terms of the operational severity experienced by the engines. In this proof of concept, the general term of severity is limited to the erosion of the core flow compressor blade and vane leading edges. A Monte Carlo simulation of varying operational conditions generates a required database of 10000 flight missions. Each flight is sampled at a rate of 1 Hz. Eleven measurable or synthesizable physical parameters are deemed to be relevant for the problem. They are reduced to seven universal non-dimensional groups which are averaged for each flight. The application of principal component analysis allows a further reduction to three principal components. They are used to run a support-vector machine model in order to classify the flights. A linear kernel function is chosen for the support-vector machine due to its low computation time compared to other functions. The robustness of the classification approach against measurement precision error is evaluated. In addition, a minimum number of flights required for training and a sensible number of severity classes are documented. Furthermore, the importance to train the algorithms on a sufficiently wide range of operations is presented.

scholarly journals Interaction between typical sulfonamides and bacterial diversity in drinking water

2018 ◽  
Vol 16 (6) ◽  
pp. 914-920 ◽  
Author(s):  
Qing Wu ◽  
Shuqun Li ◽  
Xiaofei Zhao ◽  
Xinhua Zhao
Keyword(s):  
Drinking Water ◽  
Community Structure ◽  
Microbial Community ◽  
Bacterial Community ◽  
Bacterial Diversity ◽  
Microbial Community Structure ◽  
Antibiotic Use ◽  
Community Diversity ◽  
Wide Range ◽  
Growth Of Bacteria

Abstract The abuse of antibiotics is becoming more serious as antibiotic use has increased. The sulfa antibiotics, sulfamerazine (SM1) and sulfamethoxazole (SMZ), are frequently detected in a wide range of environments. The interaction between SM1/SMZ and bacterial diversity in drinking water was investigated in this study. The results showed that after treatment with SM1 or SMZ at four different concentrations, the microbial community structure of the drinking water changed statistically significantly compared to the blank sample. At the genus level, the proportions of the different bacteria in drinking water may affect the degradation of the SM1/SMZ. The growth of bacteria in drinking water can be inhibited after the addition of SM1/SMZ, and bacterial community diversity in drinking water declined in this study. Furthermore, the resistance gene sul2 was induced by SM1 in the drinking water.

scholarly journals Separating damage from environmental effects affecting civil structures for near real-time damage detection

2017 ◽  
Vol 17 (4) ◽  
pp. 850-868 ◽  
Author(s):  
William Soo Lon Wah ◽  
Yung-Tsang Chen ◽  
Gethin Wyn Roberts ◽  
Ahmed Elamin
Keyword(s):  
Damage Detection ◽  
Real Time ◽  
Environmental Effects ◽  
Environmental Conditions ◽  
Principal Component ◽  
Detection Methods ◽  
Real Time Monitoring ◽  
Civil Structures ◽  
Data Set ◽  
Wide Range

Analyzing changes in vibration properties (e.g. natural frequencies) of structures as a result of damage has been heavily used by researchers for damage detection of civil structures. These changes, however, are not only caused by damage of the structural components, but they are also affected by the varying environmental conditions the structures are faced with, such as the temperature change, which limits the use of most damage detection methods presented in the literature that did not account for these effects. In this article, a damage detection method capable of distinguishing between the effects of damage and of the changing environmental conditions affecting damage sensitivity features is proposed. This method eliminates the need to form the baseline of the undamaged structure using damage sensitivity features obtained from a wide range of environmental conditions, as conventionally has been done, and utilizes features from two extreme and opposite environmental conditions as baselines. To allow near real-time monitoring, subsequent measurements are added one at a time to the baseline to create new data sets. Principal component analysis is then introduced for processing each data set so that patterns can be extracted and damage can be distinguished from environmental effects. The proposed method is tested using a two-dimensional truss structure and validated using measurements from the Z24 Bridge which was monitored for nearly a year, with damage scenarios applied to it near the end of the monitoring period. The results demonstrate the robustness of the proposed method for damage detection under changing environmental conditions. The method also works despite the nonlinear effects produced by environmental conditions on damage sensitivity features. Moreover, since each measurement is allowed to be analyzed one at a time, near real-time monitoring is possible. Damage progression can also be given from the method which makes it advantageous for damage evolution monitoring.

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