Using ten English adjectives, this study tests the hypothesis that the vowels in adjectives in predicative constructions are longer than those in attributive constructions in spoken conversation. The analyses considered a number of factors: occurrence before a pause, lexical adjective, vowel identity, probability given surrounding words, and others. Two sets of statistical techniques were used: a Mixed-effects model and the Random Forest Analysis based on Conditional Inference Trees (CIT). Both analyses showed strong effects of predicative vs. attributive constructions and individual lexical adjectives on vowel duration in the predicted direction, as well as effects of many of the phonological variables tested. The results showed that the longer duration in the predicative construction is not due to lengthening before a pause, though it is related to whether the adjective is internal or final in the predicative construction. Nor is the effect attributable solely to the probability of the occurrence of the adjective; rather construction type has to be taken into account. The two statistical techniques complement each other, with the Mixed-effects model showing very general trends over all the data, and the Random Forest / CIT analysis showing factors that affect only subsets of the data.

Identifying the relative importance of urban and non-urban land-use types for potential denitrification derived N2O at a regional scale is critical for quantifying the impacts of human activities on nitrous oxide (N2O) emission under changing environments. In this study we used a regional dataset from China including 197 soil samples and six land-use types to evaluate the main predictors (land use, heavy metals, soil pH, soil moisture, substrate availability, functional and broad microbial abundances) of potential denitrification using multivariate and pathway analysis. Our results provide empirical evidence that soils on farms have the greatest potential denitrifying ability (PDA) (10.92±6.08ng N2O-N·g–1 dry soil·min–1) followed by urban soil (6.80±5.35ng N2O-N·g–1 dry soil·min–1). Our models indicate that land use (low vs. high human activity), followed by total nitrogen (TN) and heavy metals (Cu, Zn, Pb, Cd) was the most important driver of PDA. In addition, our path analysis suggests that at least part of the impacts of land use on potential denitrification were mediated via microbial abundance, soil pH and substrates including TN, dissolved organic carbon and nitrate. This study identifies the main predictors of denitrification at a regional scale which is needed to quantify the impact of human activities on ecosystem functionality under changing conditions.