Trade-offs in rooting strategy dimensions along an edaphic gradient in a grassland ecosystem

Roots are essential to the diversity and functioning of plant communities, but trade-offs in rooting strategies are still poorly understood. We evaluated existing frameworks of rooting strategy trade-offs and tested their underlying assumptions, guided by the hypothesis that community-level rooting strategies are best described by a combination of variation in organ-level traits, plant-level root:shoot allocation and symbiosis-level mycorrhizal dependency. We tested this hypothesis using data on plant community structure, above-and below-ground biomass, eight root traits including mycorrhizal colonisation and soil properties from an edaphic gradient driven by elevation and water availability in sandhills prairie, Nebraska, USA. We found multidimensional trade-offs in rooting strategies represented by a two-way productivity-durability trade-off axis (captured by root length density and root dry matter content) and a three-way resource acquisition trade-off between specific root length, root:shoot mass ratio and mycorrhizal dependence. Variation in rooting strategies was driven to similar extents by interspecific differences and intraspecific responses to soil properties. Organ-level traits alone were insufficient to capture community-level trade-offs in rooting strategies across the edaphic gradient. Instead, trait variation encompassing organ, plant and symbiosis levels revealed that consideration of whole-plant phenotypic integration is essential to defining multidimensional trade-offs shaping the functional variation of root systems

The impact of building operations on urban heat/cool islands under urban densification: a comparison between naturally-ventilated and air-conditioned buildings

Many cities are suffering the effects of urban heat islands (UHI) or urban cool islands (UCI) due to rapid urban expansion and numerous infrastructure developments. This paper presents a lumped urban-building thermal coupling model which captures the fundamental physical mechanism for thermal interactions between buildings and their urban environment. The benefits of the model are its simplicity and high computational efficiency for practical use in investigating the diurnal urban air temperature change and its asymmetry in a city with both naturally-ventilated (NV) and air-conditioned (AC) buildings. Our model predicts a lower urban heat island and higher urban cool island intensity in a city with naturally-ventilated buildings than for a city with air-conditioned buildings. During the urban densification (from a low-rise, low-density city to a high-rise, high-density one), the increases in the time constant and internal heat gain give rise to asymmetric warming phenomena, which become more obvious in a city with air-conditioned buildings rather than naturally-ventilated ones. Unlike previous studies, we found that a low-rise, low-density city experiences a stronger urban cool island effect than a high-rise, high-density city due to less heat being emitted into the urban atmosphere. The urban cool/heat island effect will firstly increase/decrease, and then rapidly decrease/increase and ultimately disappear/dominate with increasing time constant in the process of urbanization/urban densification

Induction of defensive enzymes (isozymes) during defense against two different fungal pathogens in pear calli

Activities of defensive enzymes peroxidase (POD), superoxide dismutase (SOD), catalase (CAT), polyphenol oxidase (PPO) and esterase (EST) and their isozymes in pear calli were studied to reveal their role in the defensive response to different fungal infections and to find some clues to enhance their antimicrobial properties. The results confirm the fact that the activities and isozymes of these five enzymes showed differences in response to different fungal infections. After the inoculation of two different fungi for the same calli, its defensive enzymes’ activities changed relatively when compared with those of the control and in Botryosphaeria berengriana f.sp. piricola (BBP)-infected calli, the enzymes’ activities changed more significantly than those of Monilinia fructigena Honcy (MFH). Meanwhile, more new isozymes were induced by BBP infection. These are in agreement with the fact that the BBP-infected calli decay was slower than that of the MFH. These results suggest that enhancing defensive enzymes’ activities and inducing new isozymes may be related to mitigating pathogen-induced oxidative damage which result in the decrease of calli decay, and this implies that antioxidant defense response may be involved in the mechanisms of plant against fungal pathogen.Keywords: Pear callus, fungi infection, defense enzyme, isozyme, biochemical defense mechanis

\u3ci\u3eZea mays\u3c/i\u3e genotype influences microbial and viral rhizobiome community structure

Plant genotype is recognized to contribute to variations in microbial community structure in the rhizosphere, soil adherent to roots. However, the extent to which the viral community varies has remained poorly understood and has the potential to contribute to variation in soil microbial communities. Here we cultivated replicates of two Zea mays genotypes, parviglumis and B73, in a greenhouse and harvested the rhizobiome (rhizoplane and rhizosphere) to identify the abundance of cells and viruses as well as rhizobiome microbial and viral community using 16S rRNA gene amplicon sequencing and genome resolved metagenomics. Our results demonstrated that viruses exceeded microbial abundance in the rhizobiome of parviglumis and B73 with a significant variation in both the microbial and viral community between the two genotypes. Of the viral contigs identified only 4.5% (n = 7) of total viral contigs were shared between the two genotypes, demonstrating that plants even at the level of genotype can significantly alter the surrounding soil viral community. An auxiliary metabolic gene associated with glycoside hydrolase (GH5) degradation was identified in one viral metagenome-assembled genome (vOTU) identified in the B73 rhizobiome infecting Propionibacteriaceae (Actinobacteriota) further demonstrating the viral contribution in metabolic potential for carbohydrate degradation and carbon cycling in the rhizosphere. This variation demonstrates the potential of plant genotype to contribute to microbial and viral heterogeneity in soil systems and harbors genes capable of contributing to carbon cycling in the rhizosphere

Evaluation of precipitable water vapor from five reanalysis products with ground-based GNSS observations

At present, the global reliability and accuracy of Precipitable Water Vapor (PWV) from different reanalysis products have not been comprehensively evaluated. In this study, PWV values derived by 268 Global Navigation Satellite Systems (GNSS) stations around the world covering the period from 2016 to 2018 are used to evaluate the accuracies of PWV values from five reanalysis products. The temporal and spatial evolution is not taken into account in this analysis, although the temporal and spatial evolution of atmospheric flows is one of the most important information elements available in numerical weather prediction products. The evaluation results present that five reanalysis products with PWV accuracy from high to low are in the order of the fifth generation of European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA5), ERA-Interim, Japanese 55-year Reanalysis (JRA-55), National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), and NCEP/DOE (Department of Energy) according to root mean square error (RMSE), bias and correlation coefficient. The ERA5 has the smallest RMSE value of 1.84 mm, while NCEP/NCAR and NCEP/DOE have bigger RMSE values of 3.34 mm and 3.51 mm, respectively. The findings demonstrate that ERA5 and two NCEP reanalysis products have the best and worst performance, respectively, among five reanalysis products. The differences in the accuracy of the five reanalysis products are mainly attributed to the differences in the spatial resolution of reanalysis products. There are some large absolute biases greater than 4 mm between GNSS PWV values and the PWV values of five reanalysis products in the southwest of South America and western China due to the limit of terrains and fewer observations. The accuracies of five reanalysis products are compared in different climatic zones. The results indicate that the absolute accuracies of five reanalysis products are highest in the polar regions and lowest in the tropics. Furthermore, the effects of different seasons on the accuracies of five reanalysis products are also analyzed, which indicates that RMSE values of five reanalysis products in summer and in winter are the largest and the smallest in the temperate regions. Evaluation results from five reanalysis products can help us to learn more about the advantages and disadvantages of the five released water vapor products and promote their applications.Peer ReviewedPostprint (published version

Modeling rules of regional flash flood susceptibility prediction using different machine learning models

The prediction performance of several machine learning models for regional flash flood susceptibility is characterized by variability and regionality. Four typical machine learning models, including multilayer perceptron (MLP), logistic regression (LR), support vector machine (SVM), and random forest (RF), are proposed to carry out flash flood susceptibility modeling in order to investigate the modeling rules of different machine learning models in predicting flash flood susceptibility. The original data of 14 environmental factors, such as elevation, slope, aspect, gully density, and highway density, are chosen as input variables for the MLP, LR, SVM, and RF models in order to estimate and map the distribution of the flash flood susceptibility index in Longnan County, Jiangxi Province, China. Finally, the prediction performance of various models and modeling rules is evaluated using the ROC curve and the susceptibility index distribution features. The findings show that: 1) Machine learning models can accurately assess the region’s vulnerability to flash floods. The MLP, LR, SVM, and RF models all predict susceptibility very well. 2) The MLP (AUC=0.973, MV=0.1017, SD=0.2627) model has the best prediction performance for flash flood susceptibility, followed by the SVM (AUC=0.964, MV=0.1090, SD=0.2561) and RF (AUC=0.975, MV=0.2041, SD=0.1943) models, and the LR (AUC=0.882, MV=0.2613, SD=0.2913) model. 3) To a large extent, environmental factors such as elevation, gully density, and population density influence flash flood susceptibility

The stable oxygen isotope ratio of resin extractable phosphate derived from fresh cattle faeces

Phosphorus losses from agriculture pose an environmental threat to watercourses. A new approach using the stable oxygen isotope ratio of oxygen in phosphate (δ18OPO4 value) may help elucidate some phosphorus sources and cycling. Accurately determined and isotopically distinct source values are essential for this process. The δ18OPO4 values of animal wastes have, up to now, received little attention. Methods Phosphate (PO4) was extracted from cattle faeces using anion resins and the contribution of microbial PO4 was assessed. The δ18OPO4 value of the extracted PO4 was measured by precipitating silver phosphate and subsequent analysis on a thermal conversion elemental analyser at 1400°C, with the resultant carbon monoxide being mixed with a helium carrier gas passed through a GC column into a mass spectrometer. Faecal water oxygen isotope ratios (δ18OH2O values) were determined on a dual-inlet mass spectrometer through a process of headspace carbon dioxide equilibration with water samples. Results Microbiological results indicated that much of extracted PO4 was not derived directly from the gut fauna lysed during the extraction of PO4 from the faeces. Assuming that the faecal δ18OH2O values represented cattle body water, the predicted pyrophosphatase equilibrium δ18OPO4 (Eδ18OPO4) values ranged between +17.9 and +19.9‰, while using groundwater δ18OH2O values gave a range of +13.1 to +14.0‰. The faecal δ18OPO4 values ranged between +13.2 and +15.3‰. Conclusions The fresh faecal δ18OPO4 values were equivalent to those reported elsewhere for agricultural animal slurry. However, they were different from the Eδ18OPO4 value calculated from the faecal δ18OH2O value. Our results indicate that slurry PO4 is, in the main, derived from animal faeces although an explanation for the observed value range could not be determined

Testing the Hypothesis of Multiple Origins of Holoparasitism in Orobanchaceae: Phylogenetic Evidence from the Last Two Unplaced Holoparasitic Genera, Gleadovia and Phacellanthus

Orobanchaceae is the largest family among the parasitic angiosperms. It comprises non-parasites, hemi- and holoparasites, making this family an ideal test case for studying the evolution of parasitism. Previous phylogenetic analyses showed that holoparasitism had arisen at least three times from the hemiparasitic taxa in Orobanchaceae. Until now, however, not all known genera of Orobanchaceae were investigated in detail. Among them, the unknown phylogenetic positions of the holoparasites Gleadovia and Phacellanthus are the key to testing how many times holoparasitism evolved. Here, we provide clear evidence for the first time that they are members of the tribe Orobancheae, using sequence data from multiple loci (nuclear genes ITS, PHYA, PHYB, and plastid genes rps2, matK). Gleadovia is an independent lineage whereas Phacellanthus should be merged into genus Orobanche section Orobanche. Our results unambiguously support the hypothesis that there are only three origins of holoparasitism in Orobanchaceae. Divergence dating reveals for the first time that the three origins of holoparasitism were not synchronous. Our findings suggest that holoparasitism can persist in specific clades for a long time and holoparasitism may evolve independently as an adaptation to certain hosts

The New Is Old: Novel Germination Strategy Evolved From Standing Genetic Variation in Weedy Rice

Feralization of crop plants has aroused an increasing interest in recent years, not only for the reduced yield and quality of crop production caused by feral plants but also for the rapid evolution of novel traits that facilitate the evolution and persistence of weedy forms. Weedy rice (Oryza sativa f. spontanea) is a conspecific weed of cultivated rice, with separate and independent origins. The weedy rice distributed in eastern and northeastern China did not diverge from their cultivated ancestors by reverting to the pre-domestication trait of seed dormancy during feralization. Instead, they developed a temperature-sensing mechanism to control the timing of seed germination. Subsequent divergence in the minimum critical temperature for germination has been detected between northeastern and eastern populations. An integrative analysis was conducted using combinations of phenotypic, genomic and transcriptomic data to investigate the genetic mechanism underlying local adaptation and feralization. A dozen genes were identified, which showed extreme allele frequency differences between eastern and northeastern populations, and high correlations between allele-specific gene expression and feral phenotypes. Trancing the origin of potential adaptive alleles based on genomic sequences revealed the presence of most selected alleles in wild and cultivated rice genomes, indicating that weedy rice drew upon pre-existing, “conditionally neutral” alleles to respond to the feral selection regimes. The cryptic phenotype was exposed by activating formerly silent alleles to facilitate the transition from cultivation to wild existence, promoting the evolution and persistence of weedy forms