Where trees cannot grow - Particulate matter accumulation by urban meadows.

It has already been proven that trees and shrubs, can efficiently remove particulate matter (PM) from air. However, almost nothing is known about PM accumulation by herbaceous plants (grasses and forbs) found in urban meadows. Meadows, unlike trees and shrubs, can be located close to roads, one of the main sources of PM in cites. The aim of this study was to investigate the tolerance to urban condition and PM accumulation in the immediate roads vicinity of selected plants species in urban meadows. PM accumulation of annual and perennial meadows was compared with that of lawns. Results were interpreted in the context of species composition, biomass production, soil conditions and ambient PM concentrations. Of the species grown in annual meadows, the highest PM accumulation was found in Achillea millefolium L., Chenopodium album L. and Echium vulgare L., while Centaurea scabiosa L., Echium vulgare L. and Convolvulus arvensis L. accumulated the largest amounts of PM in perennial meadows. PM deposition on plants was positively correlated with a feathery leaf shape. For species in the annual meadows, a positive correlation was also found between PM accumulation and the wax content on plants. The presence of hairs on leaves, leaf size and plant growth pattern had no effect on PM deposition on plants. PM accumulation in one square metre of urban meadow was on average greater than that of lawn, regardless of meadow species' composition, age and location. The greatest accumulation of PM was found in a perennial meadow with low biodiversity but the greatest biomass. It would appear that the biomass produced by meadows and canopy structure has a crucial impact on the amount of PM accumulated by meadow plants. The results obtained indicate that meadows could be an important element of nature-based solutions for mitigating air pollution in urbanised areas.

Urban wastelands: On the frontline between air pollution sources and residential areas.

In urban areas, particulate matter (PM) represents an increasing threat to human health. The ability of plants in parks and along roads in cities to accumulate PM has already been demonstrated, but nothing is known about the effect of wasteland vegetation on air quality, despite a significant proportion of greenery in polluted areas being on wastelands. The aim of this study was to document the accumulation of PM and trace elements (TE) by wasteland species (Robinia pseudoacacia L., Populus × canescens (Aiton) Sm., Acer negundo L., Solidago gigantea (Aiton) and Poaceae) growing on Central European urban wastelands with differing levels of air pollution. On average, the largest amounts of PM accumulated on the foliage of R. pseudoacacia and S. gigantea, and the smallest amounts accumulated on P. × canescens leaves. However, accumulation of PM depended more on the distance from the emission source than on species selection, and was higher on the polluted wasteland where the plants' gas exchange was the lowest. The results also suggest that in order to effectively accumulate PM from the air, it is critical to have the correct configuration of plants, with the wasteland vegetation having a layered structure and layers differing in PM retention, as shown in this study using the examples of R. pseudoacacia (a tall tree with low PM retention) and S. gigantea (below-tree vegetation with high PM retention). P. × canescens accumulated the highest concentrations of Cd and Zn, S. gigantea accumulated the highest concentration of Cu, and Poaceae accumulated the highest concentrations of Cr and Ni. These findings have implications for urban vegetation management in areas where there is no organised greenery, and offer proof that vegetation in wasteland areas should be maintained since it is an excellent tool for reducing concentrations of PM at its place of origin.

Bayesian QTL analyses using pedigreed families of an outcrossing species, with application to fruit firmness in apple.

KEY MESSAGE: Proof of concept of Bayesian integrated QTL analyses across pedigree-related families from breeding programs of an outbreeding species. Results include QTL confidence intervals, individuals' genotype probabilities and genomic breeding values. Bayesian QTL linkage mapping approaches offer the flexibility to study multiple full sib families with known pedigrees simultaneously. Such a joint analysis increases the probability of detecting these quantitative trait loci (QTL) and provide insight of the magnitude of QTL across different genetic backgrounds. Here, we present an improved Bayesian multi-QTL pedigree-based approach on an outcrossing species using progenies with different (complex) genetic relationships. Different modeling assumptions were studied in the QTL analyses, i.e., the a priori expected number of QTL varied and polygenic effects were considered. The inferences include number of QTL, additive QTL effect sizes and supporting credible intervals, posterior probabilities of QTL genotypes for all individuals in the dataset, and QTL-based as well as genome-wide breeding values. All these features have been implemented in the FlexQTL(™) software. We analyzed fruit firmness in a large apple dataset that comprised 1,347 individuals forming 27 full sib families and their known ancestral pedigrees, with genotypes for 87 SSR markers on 17 chromosomes. We report strong or positive evidence for 14 QTL for fruit firmness on eight chromosomes, validating our approach as several of these QTL were reported previously, though dispersed over a series of studies based on single mapping populations. Interpretation of linked QTL was possible via individuals' QTL genotypes. The correlation between the genomic breeding values and phenotypes was on average 90 %, but varied with the number of detected QTL in a family. The detailed posterior knowledge on QTL of potential parents is critical for the efficiency of marker-assisted breeding.