Jasmonic acid pretreatment improves salt tolerance of wheat by regulating hormones biosynthesis and antioxidant capacity

Salt stress is a severe environmental factor that detrimentally affects wheat growth and production worldwide. Previous studies illustrate that exogenous jasmonic acid (JA) significantly improved salt tolerance in plants. However, little is known about the underlying molecular mechanisms of JA induced physiochemical changes in wheat seedlings under salt stress conditions. In this study, biophysiochemical and transcriptome analysis was conducted to explore the mechanisms of exogenous JA induced salt tolerance in wheat. Exogenous JA increased salt tolerance of wheat seedlings by alleviating membrane lipid oxidation, improving root morphology, enhancing the contents of ABA, JA and SA and increasing relative water content. In the RNA-seq profiles, we identified a total of 54,263 unigenes and 1,407 unigenes showed differentially expressed patterns in JA pretreated wheat seedlings exposed to salt stress comparing to those with salt stress alone. Subsequently, gene ontology (GO) and KEGG pathway enrichment analysis characterized that DEGs involved in linoleic acid metabolism and plant hormone signal transduction pathways were up-regulated predominantly in JA pretreated wheat seedlings exposed to salt stress. We noticed that genes that involved in antioxidative defense system and that encoding transcription factors were mainly up- or down-regulated. Moreover, SOD, POD, CAT and APX activities were increased in JA pretreated wheat seedlings exposed to salt stress, which is in accordance with the transcript profiles of the relevant genes. Taken together, our results demonstrate that the genes and enzymes involved in physiological and biochemical processes of antioxidant system, plant hormones and transcriptional regulation contributed to JA-mediated enhancement of salt tolerance in wheat. These findings will facilitate the elucidation of the potential molecular mechanisms associated with JA-dependent amelioration of salt stress in wheat and lay theoretical foundations for future studies concerning the improvement of plant tolerance to abiotic environmental stresses

Urban Growth Modeling and Future Scenario Projection Using Cellular Automata (CA) Models and the R Package Optimx

Cellular automata (CA) is a spatially explicit modeling tool that has been shown to be effective in simulating urban growth dynamics and in projecting future scenarios across scales. At the core of urban CA models are transition rules that define land transformation from non-urban to urban. Our objective is to compare the urban growth simulation and prediction abilities of different metaheuristics included in the R package optimx. We applied five metaheuristics in optimx to near-optimally parameterize CA transition rules and construct CA models for urban simulation. One advantage of metaheuristics is their ability to optimize complexly constrained computational problems, yielding objective parameterization with strong predictive power. From these five models, we selected conjugate gradient-based CA (CG-CA) and spectral projected gradient-based CA (SPG-CA) to simulate the 2005-2015 urban growth and to project future scenarios to 2035 with four strategies for Su-Xi-Chang Agglomeration in China. The two CA models produced about 86% overall accuracy with standard Kappa coefficient above 69%, indicating their good ability to capture urban growth dynamics. Four alternative scenarios out to the year 2035 were constructed considering the overall effect of all candidate influencing factors and the enhanced effects of county centers, road networks and population density. These scenarios can provide insight into future urban patterns resulting from today's urban planning and infrastructure, and can inform future development strategies for sustainable cities. Our proposed metaheuristic CA models are also applicable in modeling land-use and urban growth in other rapidly developing areas

Urban expansion simulation and scenario prediction using cellular automata: comparison between individual and multiple influencing factors

Quantifying the contribution of driving factors is crucial to urban expansion modeling based on cellular automata (CA). The objective of this study is to compare individual-factor-based (IFB) models and multi-factor-based (MFB) models as well as examine the impacts of each factor on future urban scenarios. We quantified the contribution of driving factors using a generalized additive model (GAM), and calibrated six IFB-DE-CA models and fifteen MFB-DE-CA models using a differential evolution (DE) algorithm. The six IFB-DE-CA models and five MFB-DE-CA models were selected to simulate the 2005–2015 urban expansion of Hangzhou, China, and all IFB-DE-CA models were applied to project future urban scenarios out to the year 2030. Our results show that terrain (DEM) and population density (POP) are the two most influential factors affecting urban expansion of Hangzhou, indicating the dominance of biophysical and demographic drivers. All DE-CA models produced defensible simulations for 2015, with overall accuracy exceeding 89%. The IFB-DE-CA models based on DEM and POP outperformed some MFB-DE-CA models, suggesting that multiple factors are not necessarily more effective than a single factor in simulating present urban patterns. The future scenarios produced by the IFB-DE-CA models are substantially shaped by the corresponding factors. These scenarios can inform urban modelers and policy-makers as to how Hangzhou city will evolve if the corresponding factors are individually focused. This study improves our understanding of the effects of driving factors on urban expansion and future scenarios when incorporating the factors separately

Nitrate sources and formation of rainwater constrained by dual isotopes in Southeast Asia:example from Singapore

Emission of reactive nitrogen species has a major impact on atmospheric chemistry, ecosystem and human health. The origin and formation mechanisms of wet-deposited nitrate are not well understood in Southeast Asia (SEA). In this study, we measured stable isotopes of nitrate (δ15N and δ18O) and chemical compositions of daily rainwater from May 2015 to July 2017 in Singapore. Our results showed that δ15N-NO3- and δ18O-NO3- varied seasonally with higher values during the Inter-monsoon period (April-May and October-November) than during Northeast (December-March) and Southwest monsoon (June-September). Bayesian mixing modeling, which took account of the isotope fractionation, indicated that traffic emission (47 ± 32%) and lightning (19 ± 20%) contributed the most to NO3- with increased traffic contribution (55 ± 37%) in the Northeast monsoon and lightning (24 ± 23%) during the Inter-monsoon period. Biomass burning and coal combustion, likely from transboundary transport, contributed ∼25% of nitrate in the rainwater. Monte Carlo simulation of δ18O-NO3- indicated that oxidation process by hydroxyl radical contributed 65 ± 14% of NO3-, with the rest from hydrolysis of N2O5. Wind speed had large effect on δ18O-NO3- variations in the atmosphere with more involvement of hydroxyl radical reactions when wind speed increased. Our study highlights the key role of isotopic fractionation in nitrate source apportionment, and the influence of meteorological conditions on nitrate formation processes in SEA.Ministry of Education (MOE)National Research Foundation (NRF)This work is financially supported by National Natural Science Foundation of China (Grant Nos. 41571130072 and 41861144026), National Key R&D Program of China (Grant No. 2016YFA0601002) and also the IAEA Coordinated Research Project (No. 2279/R0) as well as the National Research Foundation Singapore and the Singapore Ministry of Education under the Research Centres of Excellence initiative, which comprises Earth Observatory of Singapore contribution No.231

Five-year record of atmospheric precipitation chemistry in urban Beijing, China

To investigate the chemical characteristics of precipitation in the polluted urban atmosphere in Beijing and possible mechanisms influencing their variations, a total of 131 event-based precipitation samples were collected from March 2001 to August 2005. The concentrations of major ions in the samples were analyzed by using ion chromatography. Intermediate pH (6.1–7.3) was recorded in approximately two-thirds of the precipitation samples and acidic pH (4.2–5.6) in only 16% of the samples. However, the precipitation acidity was on the growth track and the process was likely being accelerated. SO<sub>4</sub><sup>2−</sup>, NO<sub>3</sub><sup>−</sup>, NH<sub>4</sub><sup>+</sup>, and Ca<sup>2+</sup> were the most abundant ions in the precipitations, with their single volume-weighted mean (VWM) concentration all above 100 μeq l<sup>−1</sup>. The two major anions and two major cations accounted for more than 80% of total anionic and cationic mass, respectively. The VWM SO<sub>4</sub><sup>2−</sup> concentration decreased by 13% compared to that during 1995–1998, much less than the 58% reduction in the annual average SO<sub>2</sub> concentration from 1998 to 2005 in Beijing. What seems more counterintuitive is that the VWM NO<sub>3</sub><sup>−</sup> concentration nearly doubled over the period although the annual average NO<sub>2</sub> concentration decreased by 5% from 1998 to 2005. These results imply that the conversion of gaseous precursors to acid compounds and/or the regional transport were reinforced over the decade. The average ratio of neutralizing potential to acidifying potential (i.e. NP/AP) was as high as 1.2 but experienced an evident decline trend. This was mainly ascribed to reduced input of NH<sub>4</sub><sup>+</sup> and Ca<sup>2+</sup> and increased input of NO<sub>3</sub><sup>−</sup>. Furthermore, the equivalent mass ratio of NO<sub>3</sub><sup>−</sup> to non-sea-salt SO<sub>4</sub><sup>2−</sup> presented an increasing trend over the study period, suggesting that the contribution of NO<sub>3</sub><sup>−</sup> to the precipitation acidity increased in recent years. However, the mean ratio was only 0.37 ± 0.11 in the study period, which is significantly lower than those reported in some metropolitan areas in developed countries. This shows that the precipitation acidity in Beijing was still dominantly from SO<sub>2</sub> while the SO<sub>2</sub> contribution was progressively substituted by NO<sub>x</sub>