A quantitative structure−property relationship (QSPR) treatment of the normal boiling points was performed for a structurally wide variety of organic compounds using the CODESSA (comprehensive descriptors for structural and statistical analysis) technique. A highly significant two-parameter correlation (R 2 = 0.9544, s = 16.2 K) employs just two molecular parameters, a bulk cohesiveness descriptor, G I 1/3, and the area-weighted surface charge of the hydrogen-bonding donor atom(s) in the molecule. A more refined QSPR model (with R 2 = 0.9732 and s = 12.4 K) includes, in addition, the most negative atomic partial charge and the number of the chlorine atoms in the molecule. The four-parameter equation offers an average predicted error of 2.3% for a standard set of compounds with an average experimental error of 2.1%. The QSPR equations developed allow remarkably accurate predictions of the normal boiling points for a number of simple inorganic compounds, including water.

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QSPR correlation equations were developed for the prediction of the solubilities of organic gases and vapors in water. A two-parameter correlation with the squared correlation coefficient R 2 ) 0.977 gives excellent predictions for 95 alkanes, cycloalkanes, alkenes, alkylarenes, and alkynes. A satisfactory description (R 2 ) 0.941) of the gas solubilities of 406 organic compounds with a large structural variablity was obtained using a five-parameter QSPR equation. Notably, all the parameters involved in these equations can be derived solely from the chemical structure of the compounds which makes them very useful for the prediction of the solubilities of unknown or unavailable compounds.

Biodiversity is thought to help regulate the impacts of disease through the dilution effect, where biodiversity among potential host species helps limit the impacts of pathogens. However, our knowledge is fragmentary about the direction and magnitude of the effects of plant species richness on disease impact. Here, we gathered data from 145 comparisons presented in 21 papers to conduct a systematic meta‐analysis on the effect of plant species richness on aboveground plant disease impact. We estimated the effect size using Pearson's correlation coefficient (r) with Fisher's z‐transformation. We evaluated how the magnitude of effect size varies between systems, including ecosystem type (grassland versus forest), pathogen taxon (virus versus fungus), study design (observational versus manipulative), parasite life history (biotroph versus necrotroph) and kinds of symptoms associated with the disease. We also tested whether there was a latitudinal trend of the effect size. We found there was a significant overall dilution effect in plant communities, but the magnitude varied among systems. Studies based on manipulative experiments and those in grassland ecosystems showed a significant dilution effect, as did both viral and fungal pathogens. Furthermore, obligate biotrophic pathogens but not necrotrophs showed a significant dilution effect. Diseases with different kinds of symptom manifestation differed, but not in a consistent pattern to the life history of the pathogens. The dilution effect was notably stronger at lower latitudes in the mid‐temperate region than at higher latitudes. This latitudinal trend existed in forest ecosystems, both observational and manipulative experiments, and necrotrophs. Dilution effects occur prevalently in plant communities, although the magnitude depends on ecosystem type, pathogen life history and kinds of symptoms associated with the disease. In conclusion, this study shows the importance of preserving the biodiversity of plants for maintaining ecosystem health.