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Biogenic secondary organic aerosols (SOA) contribute to a large fraction of fine aerosols globally, impacting air quality and climate. The formation of biogenic SOA depends on not only emissions of biogenic volatile organic compounds (BVOCs) but also anthropogenic pollutants including primary organic aerosol, sulfur dioxide (SO2), and nitrogen oxides (NOx). However, the anthropogenic impact on biogenic SOA production (AIBS) remains unclear. Here we use the decadal trend and variability of observed OA in the southeast US, combined with a global chemistry-climate model, to better constrain AIBS. We show that the reduction in SO2 emissions can only explain 40 % of the decreasing decadal trend of OA in this region, constrained by the low summertime month-to-month variability of surface OA. We hypothesize that the rest of OA decreasing trend is largely due to reduction in NOx emissions. By implementing a scheme for monoterpene SOA with enhanced sensitivity to NOx, our model can reproduce the decadal trend and variability of OA in this region. Extending to centennial scale, our model shows that global SOA production increases by 36 % despite BVOC reductions from preindustrial period to present day, largely amplified by AIBS. Our work suggests a strong coupling between anthropogenic and biogenic emissions in biogenic SOA production that is missing from current climate models.

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Surface ozone damages photosynthesis and reduces the ability of land ecosystems to assimilate carbon from the atmosphere thereby further increasing global warming1,2. Ozone is not emitted directly but formed in the atmosphere during complex chemical reactions of precursors, carbon monoxide, methane, non-methane volatile organic compounds and nitrogen oxides, in sunlight. These ozone precursors are emitted from a wide range of anthropogenic activities. Reductions in ozone precursor emissions are needed to mitigate ozone vegetation damage but it is unclear which are the most effective source sectors to target. Here, we apply a global Earth system model to compare the benefits to gross primary productivity of stringent 50% emission reductions in the seven largest anthropogenic ozone source sectors. Deep cuts in air pollutant emissions from road transportation and the energy sector are the most effective mitigation measures for ozone-induced gross primary productivity losses in Eastern China, Eastern United States, Europe and globally. Our results suggest that mitigation of ozone vegetation damage is a unique opportunity to contribute to negative carbon emissions, offering a natural climate solution that links fossil fuel emission abatement, air quality and climate. However, achieving these benefits requires ambitious mitigation pathways that tackle multiple source sectors. Ozone forms in the atmosphere when other anthropogenically emitted gases react with sunlight and negatively impacts terrestrial gross primary productivity (GPP). Reducing emissions of ozone precursors by 50%, particularly in the road transportation and energy sectors, could increase GPP by 750 TgC yr–1.

A newly developed dataset from the Interagency Monitoring of PROtected Visual Environments (IMPROVE) observation network, combined with a 3-D chemical transport model, is used to evaluate the spatial and temporal variability of brown carbon (BrC) in the United States. The model with BrC emitted from biomass burning and biofuel emissions agrees with the seasonal and spatial variability of BrC planetary boundary layer (PBL) absorption aerosol optical depth (AAOD) observations within a factor of 2. The model without whitening, the tendency for absorption to decrease with aerosol aging, overestimates the observed BrC PBL AAOD, and does not reflect the measured BrC PBL AAOD spatial variability. The model shows higher absorption direct radiative effects (DRE) from BrC at northern high latitudes than at mid-latitudes in spring and summer, due to boreal fire emissions, long whitening lifetimes and high surface albedos. These findings highlight the need to study BrC over the Arctic region.

Isoprene plays a critical role in air quality and climate. Photosynthesis (gross primary productivity, GPP) and formaldehyde (HCHO) are both related to isoprene emission at large spatiotemporal scales, but neither is a perfect proxy. We apply multiple satellite products and site-level measurements to examine the impact of water deficit on the three interlinked variables at the Missouri Ozarks site during a 20-day mild dryness stress in summer 2011 and a 3-month severe drought in summer 2012. Isoprene emission shows opposite responses to the short- and long-term droughts, while GPP was substantially reduced in both cases. In 2012, both remote-sensed solar-induced fluorescence (SIF) and satellite HCHO column qualitatively capture reductions in flux-derived GPP and isoprene emission, respectively, on weekly to monthly time scales, but with muted responses. For instance, as flux-derived GPP approaches zero in late summer 2012, SIF drops by 29–33% (July) and 19–27% (August) relative to year 2011. A possible explanation is that electron transport and photosystem activity are maintained to a certain extent under the drought stress. Similarly, flux tower isoprene emissions in July 2012 are 54% lower than July 2011, while the relative reductions in July for 3 independent satellite-derived HCHO data products are 27%, 12% and 6%, respectively. We attribute the muted HCHO response to a photochemical feedback whereby reduced isoprene emission increases the oxidation capacity available to generate HCHO from other volatile organic compound sources. Satellite SIF offers a potential alternative indirect method to monitor isoprene variability at large spatiotemporal scales from space, although further research is needed under different environmental conditions and regions. Our analysis indicates that fairly moderate reductions in satellite SIF and HCHO column may imply severe drought conditions at the surface.

With growingly demands for better performances in electronic-related applications, further improving thermal and fire safety of nylon 612 (PA612) becomes extremely pressing. In this work, we have reported the fabrication of flame retardant and thermally stable and conductive PA612 composites by using two-dimensional alumina platelets. Alumina platelets are observed being uniformly dispersed within the PA612 matrix. Thermal analysis demonstrates that addition of alumina platelets noticeably increases thermal stability and conductivity of PA612. Cone calorimetry results show that 40 wt% of alumina platelets addition decreases the peak heat release rate (pHRR) and total smoke production of PA612 by 54% and 29%, respectively, indicating largely enhanced flame resistance. Rheology tests demonstrate that there exists a nearly qualitative correlation between the flammability (pHRR) and viscoelastic behaviors (storage modulus). This work offers a new approach for creating advanced polymer composites with enhanced thermal and flame retardancy properties by using alumina platelets as multifunctional filler.

Methane (CH4) is both a greenhouse gas and a precursor of tropospheric ozone, making it an important focus of chemistry–climate interactions. Methane has both anthropogenic and natural emission sources, and reaction with the atmosphere's principal oxidizing agent, the hydroxyl radical (OH), is the dominant tropospheric loss process of methane. The tight coupling between methane and OH abundances drives indirect linkages between methane and other short-lived air pollutants and prompts the use of interactive methane chemistry in global chemistry–climate modeling. In this study, an updated contemporary inventory of natural methane emissions and the soil sink is developed using an optimization procedure that applies published emissions data to the NASA GISS ModelE2-Yale Interactive terrestrial Biosphere (ModelE2-YIBs) global chemistry–climate model. Methane observations from the global surface air-sampling network of the Earth System Research Laboratory (ESRL) of the US National Oceanic and Atmospheric Administration (NOAA) are used to guide refinement of the natural methane inventory. The wetland methane flux is calculated as a best fit; thus, the accuracy of this derived flux assumes accurate simulation of methane chemical loss in the atmosphere and accurate prescription of the other methane fluxes (anthropogenic and natural). The optimization process indicates global annual wetland methane emissions of 140 Tg CH4 yr−1. The updated inventory includes total global annual methane emissions from natural sources of 181 Tg CH4 yr−1 and a global annual methane soil sink of 60 Tg CH4 yr−1. An interactive methane simulation is run using ModelE2-YIBs, applying dynamic methane emissions and the updated natural methane emissions inventory that results from the optimization process. The simulated methane chemical lifetime of 10.4±0.1 years corresponds well to observed lifetimes. The simulated year 2005 global-mean surface methane concentration is 1.1 % higher than the observed value from the NOAA ESRL measurements. Comparison of the simulated atmospheric methane distribution with the NOAA ESRL surface observations at 50 measurement locations finds that the simulated annual methane mixing ratio is within 1 % (i.e., +1 % to −1 %) of the observed value at 76 % of locations. Considering the 50 stations, the mean relative difference between the simulated and observed annual methane mixing ratio is a model overestimate of only 0.5 %. Comparison of simulated annual column-averaged methane concentrations with SCIAMACHY satellite retrievals provides an independent post-optimization evaluation of modeled methane. The comparison finds a slight model underestimate in 95 % of grid cells, suggesting that the applied methane source in the model is slightly underestimated or the model's methane sink strength is slightly too strong outside of the surface layer. Overall, the strong agreement between simulated and observed methane lifetimes and concentrations indicates that the ModelE2-YIBs chemistry–climate model is able to capture the principal processes that control atmospheric methane.

The terrestrial biosphere has experienced dramatic changes in recent decades. Estimates of historical trends in land carbon fluxes remain uncertain because long-term observations are limited on the global scale. Here, we use the Yale Interactive terrestrial Biosphere (YIBs) model to estimate decadal trends in land carbon fluxes and emissions of biogenic volatile organic compounds (BVOCs) and to identify the key drivers for these changes during 1982–2011. Driven by hourly meteorology from WFDEI (WATCH forcing data methodology applied to ERA-Interim data), the model simulates an increasing trend of 297 Tg C a−2 in gross primary productivity (GPP) and 185 Tg C a−2 in the net primary productivity (NPP). CO2 fertilization is the main driver for the flux changes in forest ecosystems, while meteorology dominates the changes in grasslands and shrublands. Warming boosts summer GPP and NPP at high latitudes, while drought dampens carbon uptake in tropical regions. North of 30° N, increasing temperatures induce a substantial extension of 0.22 day a−1 for the growing season; however, this phenological change alone does not promote regional carbon uptake and BVOC emissions. Nevertheless, increases of leaf area index at peak season accounts for ~ 25 % of the trends in GPP and isoprene emissions at the northern lands. The net land sink shows statistically insignificant increases of only 3 Tg C a−2 globally because of simultaneous increases in soil respiration. Global BVOC emissions are calculated using two schemes. With the photosynthesis-dependent scheme, the model predicts increases of 0.4 Tg C a−2 in isoprene emissions, which are mainly attributed to warming trends because CO2 fertilization and inhibition effects offset each other. Using the MEGAN (Model of Emissions of Gases and Aerosols from Nature) scheme, the YIBs model simulates global reductions of 1.1 Tg C a−2 in isoprene and 0.04 Tg C a−2 in monoterpene emissions in response to the CO2 inhibition effects. Land use change shows limited impacts on global carbon fluxes and BVOC emissions, but there are regional contrasting impacts over Europe (afforestation) and China (deforestation).

Atmospheric oxidation of isoprene emission from land plants affects radiative forcing of global climate change. There is an urgent need to understand the factors that control isoprene emission variability on large spatiotemporal scales but such direct observations of isoprene emission do not exist. Two readily available global-scale long-term observation-based data sets hold information about surface isoprene activity: gross primary productivity (GPP) and tropospheric formaldehyde column variability (HCHOv). We analyze multi-year seasonal linear correlations between observed GPP and HCHOv. The observed GPP–HCHOv correlation patterns are used to evaluate a global Earth system model that embeds three alternative leaf-level isoprene emission algorithms. GPP and HCHOv are decoupled in the summertime in the southeast US (r=−0.03). In the Amazon, GPP and HCHOv are weakly correlated in March-April-May (MAM), correlated in June-July-August (JJA) and weakly anticorrelated in September-October-November (SON). Isoprene emission algorithms that include soil moisture dependence demonstrate greater skill in reproducing the observed interannual seasonal GPP–HCHOv correlations in the southeast US and the Amazon. In isoprene emission models that include soil moisture dependence, isoprene emission is correlated with photosynthesis and anticorrelated with HCHOv. In an isoprene emission model without soil moisture dependence, isoprene emission is anticorrelated with photosynthesis and correlated with HCHOv. Long-term monitoring of isoprene emission, soil moisture and meteorology is required in water-limited ecosystems to improve understanding of the factors controlling isoprene emission and its representation in global Earth system models.

The sensitivity of surface ozone, a major pollutant, to climate warming is shown to be positive but variable over the southeast United States.

We apply the NCAR CAM5-Chem global aerosol–climate model to quantify the net global radiative effects of black and organic carbon aerosols from global and Indian solid fuel cookstove emissions for the year 2010. Our updated assessment accounts for the direct radiative effects, changes to cloud albedo and lifetime (aerosol indirect effect, AIE), impacts on clouds via the vertical temperature profile (semi-direct effect, SDE), and changes in the surface albedo of snow and ice (surface albedo effect). In addition, we provide the first estimate of household solid fuel black carbon emission effects on ice clouds. Anthropogenic emissions are from the IIASA GAINS ECLIPSE V5a inventory. A global dataset of black carbon (BC) and organic aerosol (OA) measurements from surface sites and aerosol optical depth (AOD) from AERONET is used to evaluate the model skill. Compared with observations, the model successfully reproduces the spatial patterns of atmospheric BC and OA concentrations, and agrees with measurements to within a factor of 2. Globally, the simulated AOD agrees well with observations, with normalized mean bias close to zero. However, the model tends to underestimate AOD over India and China by ~ 19 % but overestimate it over Africa by ~ 25 %. Without BC serving as ice nuclei (IN), global and Indian solid fuel cookstove aerosol emissions have a net cooling impact on global climate of −141 ± 4 mW m−2 and −12 ± 4 mW m−2, respectively. The net radiative impacts are dominated by the AIE and SDE mechanisms, which originate from enhanced cloud condensation nuclei concentrations for the formation of liquid and mixed-phase clouds, and a suppression of convective transport of water vapor from the lower troposphere to the upper troposphere/lower stratosphere that in turn leads to reduced ice cloud formation. When BC is allowed to behave as a source of IN, the net global climate impacts of the global and Indian solid fuel cookstove emissions range from −260 to +135 mW m−2 and −33 to +24 mW m−2, with globally averaged values −51 ± 210 and 0.3 ± 29 mW m−2 respectively. The uncertainty range is calculated from sensitivity simulations that alter the maximum freezing efficiency of BC across a plausible range: 0.01, 0.05 and 0.1. BC–ice cloud interactions lead to substantial increases in high cloud (

Centipedegrass ( Eremochloa ophiuroides ) is an important warm-season turfgrass native to the warm temperate and tropical regions of China. Seed yield, vegetative characters and cold tolerance are important horticultural traits affecting the widespread application of this species. To elucidate the genetic mechanisms of these characteristics, we constructed genetic maps based on a population of 87 F 1 plants from a cross between two ecotypes (E142 and E022) that significantly differed for the traits. Two types of molecular markers, sequence-related amplification polymorphisms (SRAPs) and expressed sequence tags from wheat [ Triticum aestivum ] ( Ta ESTs), were employed to construct the genetic maps. The genetic map of E142 spanned a total genetic distance of 878.48 cM and contained 82 polymorphic loci, with an average genetic distance of 12.92 cM per marker. The genetic map of E022 covered a total genetic distance of 566.25 cM and contained 69 polymorphic loci, with an average genetic distance of 9.93 cM per marker. A total of 14 QTLs, comprising eight for seed yield, five for vegetative traits and one for cold tolerance, were detected on nine linkage groups: seven linkage groups of the E142 genetic map and two linkage groups of the E022 genetic map. Each of these QTLs explained 8.71–23.61% of the phenotypic variation. The results presented here will enhance the understanding of the genetic basis of seed yield, vegetative traits and cold tolerance in centipedegrass and enable further marker-assisted breeding in the species.

Bermudagrass (Cynodon dactylon (L.) Pers.) is a widely used turfgrass in tropical, subtropical and warm-temperate regions in the world. It is a salinity-tolerant plant, but much genetic variation exists among its genotypes. Genetic diversity has been shown to exist from a morphologic level to a molecular level among Chinese natural bermudagrass germplasm resources; however, the extent of variation in their salinity tolerance has remained unclear. We conducted greenhouse hydroponic and sand culture experiments to evaluate the variation in salinity tolerance of natural bermudagrass germplasm resources obtained from their main areas of distribution in China and treated at a 33 dS m−1 salinity level for three weeks. Compared with non-saline controls, salinity stress significantly decreased shoot clipping weight (46.5% and 44.2%) and increased leaf firing (41.1% and 37.6%) in hydroponic and sand culture experiments, respectively, across all genotypes. However, significant genetic variations in relative leaf fi...

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar–Ball–Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular and atmospheric carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present-day climatic state that uses 8 plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2 = 64–96%) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr−1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.

Over the past few decades, China has experienced a rapid increase in urbanization. The urban built-up areas (population) in Beijing, Shanghai, and Guangzhou increased by 197% (87%), 148% (65%), and 273% (25%), respectively, from 1996 to 2011. We use satellite retrieval data to quantify the effects of rapid urbanization on the yearly and seasonal changes in tropospheric nitrogen dioxide (NO 2 ) over East China. The results show that rapid urbanization has a profound effect on tropospheric columns of NO 2 . During 1996–2011, the tropospheric columns of NO 2 over the surrounding areas of Guangzhou, Shanghai, and Beijing increased by 82%, 292%, and 307%, respectively. The tropospheric columns of NO 2 reach their maximum in winter and minimum in spring. The anthropogenic emissions related to urbanization are a dominant factor in the long-term changes in the yearly and seasonal mean tropospheric columns of NO 2 , whereas meteorological conditions such as the prevailing winds and precipitation account for the unique spatial patterns. Around the time of the 2008 Beijing Olympic Games, the tropospheric columns of NO 2 over Beijing urban area significantly reduced by 48% in July, 35% in August, and 49% in September, relative to the same monthly averages over 2005–2007. However, this trend was reversed after the Games, and the increased rate was even larger than before. Our results show that the tropospheric NO 2 above the three regions increased at rates 1.3–8 times faster than the rates in a recent inventory estimate of NO x emissions for 2000–2010. We also discuss the influence of urbanization on tropospheric ozone and find that the Ozone Monitoring Instrument (OMI) retrieval tropospheric column shows that ozone levels are relatively insensitive to urbanization and changes in tropospheric NO 2 .

Cold tolerance and the green period are key traits in the breeding of zoysiagrass (Zoysia Willd.). Identification of molecular markers associated with cold tolerance and the green period of zoysiagrass will contribute to efficient selection of elite cultivars. These two traits were measured in 96 zoysiagrass accessions in 2004 and 2005-2006, respectively. The mapping population was screened with 29 pairs of simple sequence repeat (SSR) primers and 54 pairs of sequence-related amplified polymorphism (SRAP) primers. A multi-loci in silico mapping approach implemented with an empirical Bayes method was applied for association mapping of cold tolerance and green period. We detected 254 SSR polymorphic loci and 338 SRAP polymorphic loci, among which three SSR loci (Xgwm131-3B-187, Xgwm469-6D-194 and Xgwm234-5B-244) and one SRAP locus (Me11Em7-406) were significantly associated with cold tolerance with effect values of 57.83%, 38.05%, 36.92% and 37%, respectively. Three SSR loci (Xgwm132-6B-225, Xgwm111-7D-34 and Xgwm102-2D-97) and two SRAP loci (Me19Em5-359 and Me16Em8-483) were significantly associated with the green period with effect values of 79.54%, 62.59%, 99.04%, 49.01% and 82.57%. These markers will be useful for genetic improvement of the cold tolerance and green period of zoysiagrass by marker-assisted breeding.

Bermudagrass (Cynodon ssp.) germplasm is genetically diverse and widely distributed in the world. The study was conducted to identify and assess the molecular variation and relationship among 24 cultivars developed in China, Australia and the USA. Sequence-Related Amplified Polymorphism (SRAP) was applied to cultivars identification in this study for the first time. Thirty of the 90 SRAP primer combinations generated a total of 274 clearly bands encompassing 249 (91%) polymorphic. Each bermudagrass cultivar has its unique binary code and can be distinguished from the others. Three distinct clusters were obtained by unweighted pair-group method with arithmetic averages based on the polymorphic markers. Coefficients of genetic distance among the genotypes ranged from 0.57 to 0.97. The results demonstrated that SRAP marker is a stable molecular marker technique for the identification of bermudagrass cultivars and their genetic relationships.

The terrestrial biosphere has experienced dramatic changes in recent decades. Estimates of historical trends in land carbon fluxes remain uncertain because long-term observations are limited on the global scale. Here, we use the Yale Interactive terrestrial Biosphere (YIBs) model to estimate decadal trends in land carbon fluxes and emissions of biogenic volatile organic compounds (BVOCs) and to identify the key drivers for these changes during 1982–2011. Driven with hourly meteorology from WFDEI (WATCH Forcing Data methodology applied to ERA-Interim data), the model simulates an increasing trend of 297 Tg C a−2 in gross primary productivity (GPP) and 185 Tg C a−2 in the net primary productivity (NPP). CO2 fertilization is the main driver for the flux changes in forest ecosystems, while meteorology dominates the changes in grasslands and shrublands. Warming boosts summer GPP and NPP at high latitudes, while drought dampens carbon uptake in tropical regions. North of 30° N, increasing temperatures induce a substantial extension of 0.22 day a−1 for the growing season; however, this phenological change alone does not promote regional carbon uptake and BVOC emissions. Nevertheless, increases of LAI at peak season accounts for ~ 25 % of the trends in GPP and isoprene emissions at the northern lands. The net land sink shows statistically insignificant increases of only 3 Tg C a−2 globally because of simultaneous increases in soil respiration. In contrast, driven with alternative meteorology from MERRA (Modern Era-Retrospective Analysis), the model predicts significant increases of 59 Tg C a−2 in the land sink due to strengthened uptake in the Amazon. Global BVOC emissions are calculated using two schemes. With the photosynthesis-dependent scheme, the model predicts increases of 0.4 Tg C a−2 in isoprene emissions, which are mainly attributed to warming trends because CO2 fertilization and inhibition effects offset each other. Using the MEGAN (Model of Emissions of Gases and Aerosols from Nature) scheme, the YIBs model simulates global reductions of 1.1 Tg C a−2 in isoprene and 0.04 Tg C a−2 in monoterpene emissions in response to the CO2 inhibition effects. Land use change shows limited impacts on global carbon fluxes and BVOC emissions, but there are regional contrasting impacts over Europe (afforestation) and China (deforestation).

Globally, secondary organic aerosol (SOA) is mostly formed from emissions of biogenic volatile organic compounds (VOCs) by vegetation, but it can be modified by human activities as demonstrated in recent research. Specifically, nitrogen oxides (NOx = NO + NO2) have been shown to play a critical role in the chemical formation of low volatility compounds. We have updated the SOA scheme in the global NCAR (National Center for Atmospheric Research) Community Atmospheric Model version 4 with chemistry (CAM4-chem) by implementing a 4-product volatility basis set (VBS) scheme, including NOx-dependent SOA yields and aging parameterizations. Small differences are found for the no-aging VBS and 2-product schemes; large increases in SOA production and the SOA-to-OA ratio are found for the aging scheme. The predicted organic aerosol amounts capture both the magnitude and distribution of US surface annual mean measurements from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network by 50 %, and the simulated vertical profiles are within a factor of 2 compared to aerosol mass spectrometer (AMS) measurements from 13 aircraft-based field campaigns across different regions and seasons. We then perform sensitivity experiments to examine how the SOA loading responds to a 50 % reduction in anthropogenic nitric oxide (NO) emissions in different regions. We find limited SOA reductions of 0.9–5.6, 6.4–12.0 and 0.9–2.8 % for global, southeast US and Amazon NOx perturbations, respectively. The fact that SOA formation is almost unaffected by changes in NOx can be largely attributed to a limited shift in chemical regime, to buffering in chemical pathways (low- and high-NOx pathways, O3 versus NO3-initiated oxidation) and to offsetting tendencies in the biogenic versus anthropogenic SOA responses.

Zoysiagrass (Zoysia Willd.) is an important warm season turfgrass that is grown in many parts of the world. Salt tolerance is an important trait in zoysiagrass breeding programs. In this study, a genetic linkage map was constructed using sequence-related amplified polymorphism markers and random amplified polymorphic DNA markers based on an F1 population comprising 120 progeny derived from a cross between Zoysia japonica Z105 (salt-tolerant accession) and Z061 (salt-sensitive accession). The linkage map covered 1211 cM with an average marker distance of 5.0 cM and contained 24 linkage groups with 242 marker loci (217 sequence-related amplified polymorphism markers and 25 random amplified polymorphic DNA markers). Quantitative trait loci affecting the salt tolerance of zoysiagrass were identified using the constructed genetic linkage map. Two significant quantitative trait loci (qLF-1 and qLF-2) for leaf firing percentage were detected; qLF-1 at 36.3 cM on linkage group LG4 with a logarithm of odds value of 3.27, which explained 13.1% of the total variation of leaf firing and qLF-2 at 42.3 cM on LG5 with a logarithm of odds value of 2.88, which explained 29.7% of the total variation of leaf firing. A significant quantitative trait locus (qSCW-1) for reduced percentage of dry shoot clipping weight was detected at 44.1 cM on LG5 with a logarithm of odds value of 4.0, which explained 65.6% of the total variation. This study provides important information for further functional analysis of salt-tolerance genes in zoysiagrass. Molecular markers linked with quantitative trait loci for salt tolerance will be useful in zoysiagrass breeding programs using marker-assisted selection.

Bermudagrass (Cynodon dactylon (L.) Pers.) is a widely used turfgrass in tropical, subtropical and warm-temperate regions in the world. It is a salinity-tolerant plant, but much genetic variation exists among its genotypes. Genetic diversity has been shown to exist from a morphologic level to a molecular level among Chinese natural bermudagrass germplasm resources; however, the extent of variation in their salinity tolerance has remained unclear. We conducted greenhouse hydroponic and sand culture experiments to evaluate the variation in salinity tolerance of natural bermudagrass germplasm resources obtained from their main areas of distribution in China and treated at a 33 dS m−1 salinity level for three weeks. Compared with non-saline controls, salinity stress significantly decreased shoot clipping weight (46.5% and 44.2%) and increased leaf firing (41.1% and 37.6%) in hydroponic and sand culture experiments, respectively, across all genotypes. However, significant genetic variations in relative leaf firing percentage (RLF) and relative shoot weight (RSW) were found among genotypes in both experiments, and their coefficients of variation ranged from 25.5% to 41.6%, indicating that considerable variation exists in the salinity tolerance of Chinese natural bermudagrass germplasm resources. Shoot Na+ concentrations increased under salinity stress for all genotypes in both experiments. However, significant genetic variations were also found in shoot Na+ concentrations. Salinity tolerance in bermudagrass genotypes was found to be significantly negatively correlated with shoot Na+ concentrations in both experiments. Using a cluster analysis of RLF and RSW data, all genotypes were classified into four groups with different salinity tolerances. The results of our evaluation indicate that there is much potential for improving salinity tolerance among Chinese natural bermudagrass cultivars.