A5050680337- Species Distribution and Climate Change
- COVID-19 epidemiological studies
- Ecology and Vegetation Dynamics Studies
- SARS-CoV-2 and COVID-19 Research
- Statistical Methods and Bayesian Inference
- Microbial Community Ecology and Physiology
- Forecasting Techniques and Applications
- Coral and Marine Ecosystems Studies
- COVID-19 Pandemic Impacts
- Plant Parasitism and Resistance
- Data Analysis with R
- COVID-19 Clinical Research Studies
- Mental Health Research Topics
- Marine and fisheries research
- Botany and Plant Ecology Studies
- Genomics and Phylogenetic Studies
- Bayesian Modeling and Causal Inference
- Plant and animal studies
- Marine and coastal plant biology
- Agronomic Practices and Intercropping Systems
- COVID-19 impact on air quality
- Aquatic Ecosystems and Phytoplankton Dynamics
- Data Visualization and Analytics
- SARS-CoV-2 detection and testing
- Allelopathy and phytotoxic interactions
King Abdullah University of Science and Technology
2019-2025
Consejo Superior de Investigaciones Científicas
2024
Institut de Ciències del Mar
2024
National Guard Health Affairs
2022
King Abdulaziz Medical City
2022
University of Amsterdam
2016-2019
Wageningen University & Research
2011-2014
COMSATS University Islamabad
2012-2014
Tennessee State University
2002
Bayesian hypothesis testing presents an attractive alternative to p value testing. Part I of this series outlined several advantages testing, including the ability quantify evidence and monitor update as data come in, without need know intention with which were collected. Despite these other practical advantages, tests are still reported relatively rarely. An important impediment widespread adoption is arguably lack user-friendly software for run-of-the-mill statistical problems that...
Bayesian parameter estimation and hypothesis testing present attractive alternatives to classical inference using confidence intervals p values. In part I of this series we outline ten prominent advantages the approach. Many these translate concrete opportunities for pragmatic researchers. For instance, allows researchers quantify evidence monitor its progression as data come in, without needing know intention with which were collected. We end by countering several objections testing. Part...
This paper introduces JASP, a free graphical software package for basic statistical procedures such as t tests, ANOVAs, linear regression models, and analyses of contingency tables. JASP is open-source differentiates itself from existing solutions in two ways. First, provides several innovations user interface design; specifically, results are provided immediately the makes changes to options, output attractive, minimalist, designed around principle progressive disclosure, can be peer...
Abstract Question Quantification of the effect species traits on assembly communities is challenging from a statistical point view. A key question how occurrence and abundance can be explained by trait values environmental at sites. Methods Using sites × table, site environment data table we address above using novel generalized linear mixed model ( GLMM ) approach. The overcomes problems pseudo‐replication heteroscedastic variance including as random factors. method equally applicable to...
J amil M, C harnikhova T, ardoso C, U eno K, V erstappen F, A sami T & B ouwmeester HJ (2011). Quantification of the relationship between strigolactones and Striga hermonthica infection in rice under varying levels nitrogen phosphorus. Weed Research 51 , 373–385. Summary Strigolactone exudation, as well germination attachment, was studied different (N) phosphorus (P) two cultivars (IAC 165 TN 1). Exudation by highest mineral‐deficient conditions, whereas increasing N P dose reduced...
The analysis of R×C contingency tables usually features a test for independence between row and column counts. Throughout the social sciences, adequacy hypothesis is generally evaluated by outcome classical p-value null-hypothesis significance test. Unfortunately, however, comes with number well-documented drawbacks. Here we outline an alternative, Bayes factor method to quantify evidence against in tables. First describe different sampling models provide corresponding default factors as...
Global climate change has profound implications on species distributions and ecosystem functioning. In the coastal zone, ecological responses may be driven by various biogeochemical physical environmental factors. Synergistic interactions can occur when combined effects of stressors exceed their individual effects. The Red Sea, characterized strong gradients in temperature, salinity, nutrients along latitudinal axis provides a unique opportunity to study over range these variables. Using...
Abstract As the Earth's temperature continues to rise, coral bleaching events become more frequent. Some of most affected reef ecosystems are located in poorly monitored waters, and thus, extent damage is unknown. We propose use marine heatwaves (MHWs) as a new approach for detecting zones susceptible bleaching, using Red Sea model system. corals exceptionally heat‐resistant, yet have increased frequency. By applying strict definition MHWs on >30 year satellite‐derived sea surface...
The pandemic of the COVID-19 disease extended from China across north-temperate zone, and more recently to tropics southern hemisphere. hypothesis that spread is temperature-dependent was tested based on data derived nations world provinces in China. No evidence a pattern between rates ambient temperature found, suggesting unlikely behave as seasonal respiratory virus.
The global ocean genome (the pool of genes in marine organisms and the functional information they encode) is a major, untapped resource for science society with growing range biotechnology applications sectors such as biomedicine, energy, food. Shotgun sequencing metagenomics can now be used to catalog diversity microbial life explore its potential, but has been limited by sample coverage, access suitable platforms, computational capacity. Here we provide novel synthesis based on analysis...
Abstract The race between pathogens and their hosts is a major evolutionary driver, where both reshuffle genomes to overcome reorganize the defenses for infection, respectively. Evolutionary theory helps formulate predictions on future dynamics of SARS-CoV-2, which can be monitored through unprecedented real-time tracking SARS-CoV-2 population genomics at global scale. Here we quantify accelerating evolution by mutation globally, with focus Receptor Binding Domain (RBD) spike protein...
1. Abstract The pandemic of the COVID-19 disease extended from China across north-temperate zone, and more recently to tropics southern hemisphere. We find no evidence that spread rates decline with temperatures above 20 °C, suggesting is unlikely behave as a seasonal respiratory virus.
<title>Abstract</title> <bold>Background</bold> In this study, xTitan, a field-deployable, automated, and versatile nucleic acid extraction system was employed to characterize microbial communities in Red Sea-derived samples, including coral colonies, mangrove sediments, seawater. The use of the xTitan field intended minimize sample transport bias, obtaining data that may be closer “ground truth” for diversity. observed from DNA extracted using were compared extractions performed laboratory...
Niche theory predicts that species occurrence and abundance show non-linear, unimodal relationships with respect to environmental gradients. Unimodal models, such as the Gaussian (logistic) model, are however more difficult fit data than linear ones, particularly in a multi-species context ordination, trait modulated response when phylogeny traits must be taken into account. Adding squared terms model is possibility but gives uninterpretable parameters.This paper explains why generalized...
In this paper we attempt to explain observed niche differences among species (i.e. in their distribution along environmental gradients) by trait values (e.g. volume) phytoplankton communities. For this, propose the trait-modulated Gaussian logistic model which parameters (optimum, tolerance and maximum) are made linearly dependent on traits. The is fitted data Bayesian framework using OpenBUGS (Bayesian inference Using Gibbs Sampling) identify according variables there differentiation We...
We present a method based on deep learning for detecting and localizing abnormal/extreme events in sea surface temperature (SST) of the Red Sea images using training samples normal only. The operates two stages; first one involves features extraction from each patch SST input image convolutional layers extracted pretrained neural network. In second stage, methods are used model data. uses one-class support vector machine (1-SVM) classifier that allows fast robust abnormal detection presence...
Abstract Estimates of marine plastic stocks, a major threat to life (1), are far lower than expected from exponentially-increasing litter inputs, suggesting important loss factors (2, 3). These may involve microbial degradation, as the plastic-degrading polyethylene terephthalate enzyme (PETase) has been reported in communities (4). An assessment 416 metagenomes planktonic across global ocean identifies 68 oceanic PETase variants (oPETase) that evolved ancestral enzymes degrading polycyclic...
To understand patterns of variation in species biomass terms traits and environmental variables a one-to-one approach might not be sufficient, multitrait multienvironment will necessary. A is proposed, based on mixed model for biomass. In the model, are species-dependent random terms, whereas fixed trait-environment relationships interaction terms. this approach, identifying important relationship becomes selection problem. Because mix we propose novel tiered forward this. first tier,...
Abstract The analysis of ocean and atmospheric datasets offers a unique set challenges to scientists working in different application areas. These include dealing with extremely large volumes multidimensional data, supporting interactive visual analysis, ensembles exploration visualization, exploring model sensitivities inputs, mesoscale features predictive analytics, heterogeneity complexity observational representing uncertainty, many more. Researchers across disciplines collaborate...