ABSTRACT
Predicting tree frost tolerance is critical to select adapted species according to both the current and predicted future climate. The relative change in water to carbohydrate ratio is a relevant trait to predict frost acclimation in branches from many tree species. The objective of this study is to demonstrate the interspecific genericity of this approach across nine tree species. In the studied angiosperm species, frost hardiness dynamics were best correlated to a decrease in water content at the early stage of acclimation (summer and early autumn). Subsequently, frost hardiness dynamics were more tightly correlated to soluble carbohydrate contents until spring growth resumption. Based on different model formalisms, we predicted frost hardiness at different clade levels (angiosperms, family, genus and species) with high to moderate accuracy (1.5-6.0 °C root mean squared error (RMSE)) and robustness (2.8-6.1 °C prediction RMSE). The TOT model, taking all soluble carbohydrate and polyols into account, was more effective and adapted for large scale studies aiming to explore frost hardiness across a wide range of species. The ISC model taking the individual contribution of each soluble carbohydrate molecule into account was more efficient at finer scale such as family or species. The ISC model performance also suggests that the role of solutes cannot be reduced to a 'bulk' osmotic effect as could be computed if all of them were located in a single, common, compartment. This study provides sets of parameters to predict frost hardiness in a wide range of species, and clues for targeting specific carbohydrate molecules to improve frost hardiness.
Subject(s)
Trees , Water , Acclimatization , Carbohydrates , SeasonsABSTRACT
Most former industrial sites are contaminated by mixtures of trace elements and organic pollutants. Levels of pollutants do not provide information regarding their biological impact, bioavailability and possible interactions between substances. There is genuine interest in combining chemical analyses with biological investigations. We studied a brownfield where several industrial activities were carried out starting in the 1970s, (incineration of pyralene transformers, recovery of copper by burning cables in the open air). Four representative plots showing different levels of polychlorobiphenyls were selected. Organic and trace metal levels were measured together with soil pedological characteristics. The bacterial community structure and functional diversity were assessed by 16S metagenomics with deep sequencing and community-level physiological profiling. Additionally, a vegetation survey was performed. Polychlorobiphenyls (8 mg.kg-1 to 1500 mg.kg-1) were from 2.4 × 103-fold to 6 × 105-fold higher than the European background level of 2.5 µg.kg-1. Polychlorinated dibenzo-p-dioxins and dibenzofurans ranged from 0.5 to 8.0 µg.kg-1. The soil was also contaminated with trace metals, i.e., Cu > 187, Zn > 217 and Pb > 372 mg.kg-1. Location within the study area, trace metal content and soil humidity were stronger determinants than organic pollutants of bacterial community structures and activities. Thus, the highest biological activity and the greatest bacteriological richness were observed in the plot that was less contaminated with trace metals, despite the high level of organic pollutants in the plot. Moreover, trace element pollution was associated with a relatively low presence of Actinobacteria and Rhizobia. The plot with the highest metal contamination was rich in metal-resistant bacteria such as Sphingomonadales, Geodermatophilaceae and KD4-96 (Chloroflexi phylum). Acidobacteria and Sphingomonadales, capable of resisting trace metals and degrading persistent organic pollutants, were dominant in the plots that had accumulated metal and organic contamination, but bacterial activity was lower in these plots than in the other plots.
