Contributors:Avila Jose M, Gallardo Antonio, Ibañez Beatriz
Here we assessed the effects of Quercus suber dieback, caused by the exotic root pathogen Phytophthora cinnamomi, on the soil microbial community and key components of the C and N cycle. We used a spatially-explicit neighbourhood approach to analyse the effects of Q. suber trees with different health status and non-declining coexistent species on soil variables. The study was replicated in the two main Q. suber forest types of the region (closed forests and open woodlands) with contrasting soil texture characteristics. Pathogen-induced tree dieback did not affect microbial functional diversity or biomass, but translated into lower soil microbial respiration. Tree mortality induced changes in several variables of the C and N cycle, but the sign and magnitude of these effects varied depending on the local characteristics of soil texture. Coexistent species differed strongly from Q. suber in their effects on the C and N cycle. Overall, our results show that tree dieback due to invasive pathogens translates into complex short- and long-term effects on different components of the C and N cycles, despite no effects on microbial functional diversity and biomass.
There are two spreadsheets with data. The spreadsheet "soil dataset" contains raw soil data. The spreadsheet "tree dataset" contains the information about neighbour trees (species, position, size and defoliation index). After each data spreadsheet, there is a spreadsheet with the associated metadata, where a description of all the variables and units can be found.
This dataset collects data on psychological factors which may influence students' anticipated and perceived learning in a Smart Learning Environment. The data was collected by surveying students before and after they took part in a public relations crisis simulation. A 7-point Likert scale was used. The items included are career relatedness (before and after), social support (before and after), ease of use (before and after), anticipated learning (before) and perceived learning (after).
The data show community structure at local sites. The datasheet has an abundance matrix (with sites as rows and taxa as columns). The community data were collected in the Cangshan Mountains located in a national, nature reserve in Yunnan Province, Southwest China. From November to December in 2012 (the dry season), 46 sites were surveyed along six streams on the east (21 sites) and west aspects (25 sites). At each site, macroinvertebrate samples were collected along a river reach of 50 to 100 m. Five replicates of the macroinvertebrate sample were collected from multiple habitats. For each replicate, macroinvertebrates were collected using a Surber sampler (30 × 30 cm with 500 μm mesh).
This data is supporting data for the manuscript entitled "Assessing differential binding of aggregation induced emission-based luminogens to host interacting surface proteins of SARS-CoV-2 and influenza virus- an in silico approach". The PDB coordinates of TPE-P and TPE-S docked onto the SARS-COV2 spike proteins, and hemagglutinin protein of influenza virus, and the molecular dynamics simulations average structure of last 3 nano seconds of total 20 nano seconds coordinates files can hep in describing the binding molecules.
Scores displayed for ‘median’ patient: male, 41 years old, BMI 25, Fitzpatrick skin type 2, no usage of concomitant medication; IGA, Investigator Global Assessment; NRS, Numerical Rating Scale; Estimated probability ranging from 0 to 100% for the answer categories based on our ordinal logistic mixed-effects models; a Registered in the Amsterdam UMC only.