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Verticillium dahliae is an important fungal pathogen affecting cotton yield and quality. Therefore, the mining of V. dahlia-resistance genes is urgently needed. Proteases and protease inhibitors play crucial roles in plant defense responses. However, the functions and regulatory mechanisms of the protease inhibitor PR6 gene family remain largely unknown. This study provides a comprehensive analysis of the PR6 gene family in the cotton genome. We performed genome-wide identification and functional characterization of the cotton GhPR6 gene family, which belongs to the potato protease inhibitor I family of inhibitors. Thirty-nine PR6s were identified in Gossypium arboreum, G. raimondii, G. barbadense, and G. hirsutum, and they were clustered into four groups. Based on the analysis of pathogen-induced and Ghlmm transcriptome data, GhPR6-5b was identified as the key gene for V. dahliae resistance. Virus-induced gene silencing experiments revealed that cotton was more sensitive to V. dahliae V991 after PR6-5b silencing. The present study established that GhWRKY75 plays an important role in resistance to Verticillium wilt in cotton by positively regulating GhPR6-5b expression by directly binding to the W-box TTGAC(T/C). Our findings established that GhWRKY75 is a potential candidate for improving cotton resistance to V. dahliae, and provide primary information for further investigations and the development of specific strategies to bolster the defense mechanisms of cotton against V. dahliae.

Abstract Individual may response to drug treatment differently due to their genetic variants located in enhancers. These variants can alter transcription factor’s (TF) binding strength, affect enhancer’s chromatin activity or interaction, and eventually change expression level of downstream gene. Here, we propose a computational framework, PERD, to Predict the Enhancers Responsive to Drug. A machine learning model was trained to predict the genome-wide chromatin accessibility from transcriptome data using the paired expression and chromatin accessibility data collected from ENCODE and ROADMAP. Then the model was applied to the perturbed gene expression data from Connectivity Map (CMAP) and Cancer Drug-induced gene expression Signature DataBase (CDS-DB) and identify drug responsive enhancers with significantly altered chromatin accessibility. Furthermore, the drug responsive enhancers were related to the pharmacogenomics genome-wide association studies (PGx GWAS). Stepping on the traditional drug-associated gene signatures, PERD holds the promise to enhance the causality of drug perturbation by providing candidate regulatory element of those drug associated genes.

Leaf shape is a vital agronomic trait that affects plant and canopy architecture, yield, and other production attributes of upland cotton. Compared with normal leaves, lobed leaves have potential advantages in improving canopy structure and increasing cotton yield. A chromosomal introgression segment from Gossypium barbadense L. conferring sub-okra leaf shape to Gossypium hirsutum L. was identified on chromosome D01. To determine the effects of this transferred sub-okra leaf shape on the leaf anatomical characteristics, photosynthesis-related traits, and yield of short-season cotton, we performed a field experiment with three sets of near-isogenic lines carrying okra, sub-okra, and normal leaf shape in Lu54 (L54) and Shizao 2 (SZ2) backgrounds. Compared with normal leaves, sub-okra leaves exhibited reduced leaf thickness and smaller leaf mass per area; moreover, the deeper lobes of sub-okra leaves improved the plant canopy structure by decreasing leaf area index by 11.24%–22.84%. Similarly, the intercepted PAR rate of lines with sub-okra leaf shape was also reduced. The chlorophyll content of sub-okra leaves was lower than that of okra and normal leaf shapes; however, the net photosynthetic rate of sub-okra leaves was 8.17%–29.81% higher than that of other leaf shapes at most growth stages. Although the biomass of lines with sub-okra leaf shape was less than that of lines with normal leaves, the average first harvest yield and total yield of lines with the sub-okra leaf shape increased by 6.36% and 5.72%, respectively, compared with those with normal leaves. Thus, improvements in the canopy structure and photosynthetic and physiological characteristics contributed to optimizing the light environment, thereby increasing the yield of lines with sub-okra leaf shape. Our results suggest that the sub-okra leaf trait from G. barbadense L. may have practical applications for cultivating short-season varieties with high photosynthetic efficiency, and improving yield, which will be advantageous for short-season varieties.

IntroductionBelowground bud banks play integral roles in vegetation regeneration and ecological succession of plant communities; however, human-caused changes in land use severely threaten their resilience and regrowth. Although vegetation attributes and soil properties mediate such anthropogenic effects, their influence on bud bank size and composition and its regulatory mechanisms under land use change have not been explored.MethodsWe conducted a field investigation to examine impacts of land use change on bud bank size and composition, vegetation attributes, and soil properties in wetlands (WL), farmlands (FL), and alpine meadow (AM) ecosystems in Zhejiang Province, China.ResultsOverall, 63 soil samples in close proximity to the vegetation quadrats were excavated using a shovel, and samples of the excavated soil were placed in plastic bags for onward laboratory soil analysis. The total bud density (1514.727 ± 296.666) and tiller bud density (1229.090 ± 279.002) in wetland ecosystems were significantly higher than in farmland and alpine meadow ecosystems [i.e., total (149.333 ± 21.490 and 573.647 ± 91.518) and tiller bud density (24.666 ± 8.504 and 204.235 ± 50.550), respectively]. While vegetation attributes critically affected bud banks in WL ecosystems, soil properties strongly influenced bud banks in farmland and alpine meadow ecosystems. In wetland ecosystems, total and tiller buds were predominantly dependent on soil properties, but vegetation density played a significant role in farmlands and alpine meadow ecosystems. Root sprouting and rhizome buds significantly correlated with total C in the top 0 – 10 cm layer of farmland and alpine meadow ecosystems, respectively, and depended mainly on soil properties.DiscussionOur results demonstrate that land use change alters bud bank size and composition; however, such responses differed among bud types in wetland, farmland, and alpine meadow ecosystems.

Abstract This study aims to make clear of grassland coverage change and quantitative assessment its effect factors. We collected the data from the National Bureau of Statistics ( http://www.stats.gov.cn ) and "China 20th Century Land Use/Cover Change (LUCC) Spatio-temporal Platform". Grassland coverage area showed an upward trend from 1980 to 1990, and the grassland coverage area is gradually decreasing from 1990 to 2000, and the grassland coverage area has not changed much from 2000 to 2018. The medium-coverage grassland area has the highest correlation with the total population, and the high-coverage grassland area has the lowest correlation with the total population. Land use types and the composite of gross agricultural output have influence on grassland coverage area. It is hoped that relevant policies should consider land use types and ecological benefits while balancing economic development and urban development.

Desertification in degraded grasslands is manifested through the development of bare sandy patches, which eventually lead to habitat fragmentation. The ability of these bare sandy patches to regenerate naturally through in-situ soil seed banks is not well understood. To fill this knowledge gap, we randomly selected 24 bare sandy patches with areas ranging from 19 to 898 m2 in a desertified grassland of the Horqin sandy land, Northern China to determine whether soil seed bank can be used for natural regeneration of bare sandy patches. Species composition and density of soil seed bank as well as aboveground vegetation composition, abundance and coverage were investigated. We then determined their relationships with in-situ habitat characteristics. Our observations showed that the studied area had low soil seed bank density and species richness, as well as depauperate soil seed bank communities. Consequently, local soil seed bank was not able to provide sufficient seed source for natural regeneration. This was indicated by the relationships between aboveground vegetation, soil seed bank and the in-situ habitat characteristics. For bare patches with an area between 300 m2 and 900 m2, increase the soil seed bank density and species richness should be the main restoration measures. For bare patches with a small area of less than 50 m2, restoration of vegetation density should be the main measure. Our data highlighted that different extents of desertification, indicated by different bare patches, are requiring distinct restoration measures.

Protecting rare and endangered plants is important for maintaining ecosystem structure and function, conserving biodiversity, and even sustaining national economic growth. However, the effects of habitat characteristics, geographical distribution, and climatic factors on the distribution of rare and endangered plants in China, home to 19.4 % of the world’s endangered species, remain unclear. To address this important knowledge gap, we collected information on climate, altitude, habitat, and distribution of rare and endangered plants in China to determine their habitat characteristics, geographical distribution, and the relationships between environmental factors and species density. We found that rare and endangered plants tend to occur in warm, humid, and forested habitats. Mountains, rather than plains, hills, eolian landforms, tablelands, lakes, and glaciers, can provide mesophytic and less-disturbed refuges for rare and endangered plants. In particular, medium and medium high-altitude mountains located in monsoon dominated regions with high precipitation, temperature, and humidity provide habitats for species of rare and endangered plants with high density. Our findings highlight the importance for a more explicit consideration of these mountains for in situ conservation of rare and endangered plants.

Vegetation on dunes regulates the water supply from the dunes to the inter-dune lowland, which is a crucial factor affecting lake water dynamics in the inter-dune lowland. Previous researchers have paid insufficient attention to the water regulation function of dunes on a landscape- and regional scale. To fill this gap, both remote sensing technology and field observations were used to analyze the variations in the lake area and their influence factors, such as vegetation coverage and precipitation in the lake watershed, on a multi-year scale (2000–2020) and one-year scale (2021), respectively. The results showed that precipitation is the main factor influencing the changes in lake water, and artificial sand vegetation can regulate the changes in lake water. On the multi-year scale, with the coverage of artificial sand-fixing vegetation increasing on sand dunes in the lake watershed, the areas of the lakes were gradually decreasing. On the one-year scale, with dune vegetation coverage increased, the water supply from dunes to lakes showed a decreasing trend. This model can provide a possibility for estimating and predicting the influence of water supply from dunes to lakes that is affected by sand-fixing vegetation. The findings have significant theoretical and practical utility for the rational utilization of water resources in sandy land, as well as for assisting in the selection of an optimized construction mode for desert control projects.

Abstract Gastric cancer, or stomach cancer, that originates in the inner lining of the stomach, was the fifth most common cancer and the fourth mortality globally, with over one million new cases in 2020 and an estimated 769,000 deaths. The molecular characteristics of gastric cancer has been complicated by histological and intratumor heterogeneity. The incidence of gastric cancer shows wide geographical variation. As the largest and highest region in China, Qinghai-Tibetan Plateau is one of the important global biodiversity hotspots. Here, we collect tumour and paired normal bio-samples from 31 primary gastric cancer patients from Qinghai Provincial People’s Hospital, and discuss the molecular characteristics for gastric cancer patients living in plateau. They have more single nucleotide polymorphisms (SNP) located in chromosome 7 with C → T and G → A as the most common alteration types, barely share the cancer driver genes with western patients, and have no significant differences in various Chinese nation. These characteristics offers a great opportunity to further understanding the divergent mechanism of gastric cancer, increase the efficacy for diagnosis and prognosis, finally lead the optimal targeted therapeutics.

BackgroundThe 2009 pandemic H1N1 influenza A virus (pdm09) continue to evolve, and few studies have systemically analyzed the evolution, replication, and transmission of pmd09 viruses in China.MethodsTo better understand the evolution and pathogenicity of pdm09 viruses, we systematically analyzed viruses that were confirmed in 2009–2020 in China and characterized their replication and transmission ability. We extensively analyzed the evolution characteristics of pdm/09 in China over the past decades. The replication ability of 6B.1 and 6B.2 lineages on Madin-Darby canine kidney (MDCK) and human lung adenocarcinoma epithelial (A549) cells and their pathogenicity and transmission in guinea pigs were also compared.ResultsIn total, 3,038 pdm09 viruses belonged to clade 6B.1 (62% of all pdm09 viruses) and clade 6B.2 (4%). Clade 6B.1 pdm09 viruses are the predominant clade, with proportions of 54.1%, 78.9%, 57.2%, 58.6%, 61.7%, 76.3%, and 66.6% in the North, Northeast, East, Central, South, Southwest, and Northeast regions in China, respectively. The isolation proportion of clade 6B.1 pdm/09 viruses was 57.1%, 74.3%, 96.1%, 98.2%, 86.7%, and 78.5% in 2015–2020, respectively. A clear differentiation time point appeared in 2015 before which the evolution trend of pdm09 viruses in China was similar to that in North America but then showed a different trend after that point. To characterize pdm09 viruses in China after 2015, we further analyzed 33 pdm09 viruses isolated in Guangdong in 2016–2017, among which A/ Guangdong/33/2016 and A/Guangdong/184/2016 (184/2016) belonged to clade 6B.2, and the other 31 strains belonged to clade 6B.1. A/Guangdong/887/2017 (887/2017) and A/Guangdong/752/2017 (752/2017) (clade 6B.1), 184/2016 (clade 6B.2) and A/California/04/2009 (CA04) replicated efficiently in MDCK cells and A549 cells, as well as the turbinates of guinea pigs. 184/2016 and CA04 could transmit among guinea pigs through physical contact.ConclusionOur findings provide novel insights into the evolution, pathogenicity, and transmission of pdm09 virus. The results show that enhancing surveillance of pdm09 viruses and timely evaluation of their virulence are essential.

Abstract Dispersal ability is important for the introduction, establishment, and spread of alien plant species. Therefore, determination of the geographical distribution of the dispersal ability of such species, and the relationship between dispersal ability and socio-climatic factors are essential to elucidate the invasion strategies of the alien plant species. Analytic hierarchy process and inventory, risk rank, and dispersal mode data available on Chinese alien plant species were used to determine their dispersal ability, the geographical distribution thereof, and the relationship between socio-climatic factors and dispersal ability. High-risk alien plant species had a higher natural dispersal ability (or several natural dispersal modes) but a lower anthropogenic dispersal ability (or few anthropogenic dispersal modes) than low-risk alien plant species. The geographical distribution of the dispersal ability of the alien plant species showed an inverse relationship with species density. Alien plant species with low dispersal ability (i.e., with fewer dispersal modes and distribution in the southeast) showed a tendency to adapt to environments with mild climates, while those with high dispersal ability (i.e., with more disposal nodes and distribution in the northwest) showed a tendency to adapt to harsh environments. It is essential for land managers and policy makers to understand the geographical distribution of the dispersal ability of alien plant species and their socio-climatic control factors to formulate strategies to control the natural and anthropogenic dispersal of such plants.

Accurately predicting the response of a cancer patient to a therapeutic agent remains an important challenge in precision medicine. With the rise of data science, researchers have applied computational models to study the drug inhibition effects on cancers based on cancer genomics and transcriptomics. Moreover, a common epigenetic modification, DNA methylation, has been related to the occurrence and development of cancer, as well as drug effectiveness. Therefore, it is helpful for improvement of drug response prediction through exploring the relationship between DNA methylation and drug effectiveness. Here, we proposed a computational model to predict drug responses in cancers through integration of cancer genomics, transcriptomics, epigenomics, and compound chemical properties. Meanwhile, we applied a regularized regression model (Least Absolute Shrinkage and Selection Operator, lasso) to detect the methylation sites that were closely related to drug effectiveness. The prediction models were trained on a well-known pharmacogenomics data resource, Genomics of Drug Sensitivity in Cancer (GDSC). The cross-validation indicates that the performance of the prediction model using DNA methylation is comparable to that of using other cancer omics, including oncogene mutation and gene expression data. It indicates the important role of DNA methylation in prediction of drug responses. Encyclopedia of DNA Elements (ENCODE) and Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining (TRRUST2) database analyses suggest that the methylation sites associated with drug effectiveness are mainly located in the transcription factor (TF) binding region. Therefore, we hypothesized that the sensitivity of cancer cells to drugs could be regulated by changing the methylation modification of TF binding region. In conclusion, we confirmed the important role of DNA methylation in prediction of drug responses, and provided some methylation sites that closely related to the drug effectiveness, which may be a great regulatory target for improvement of drug treatment effects on cancer patients.

Gastric cancer was the fifth most common malignancy and the third deadliest cancer (738,000 deaths in 2018) in the world. The analysis of its molecular characteristics has been complicated by histological and intratumor heterogeneity. Furthermore, the previous studies indicate that the incidence of gastric cancer shows wide geographical variation. As the largest and highest region in China, Qinghai-Tibetan Plateau (QTP) is one of the important global biodiversity hotspots. Here, to better understand the mechanism of gastric cancer and offer the targeted therapeutic strategies specially designed for patients in QTP, we collect tumor and blood samples from 30 primary gastric adenocarcinoma cancer patients at Qinghai Provincial People's Hospital. We discuss the clinical and molecular characteristics for these patients that have been ascribed to the unique features in this place, including high altitude (the average height above sea level is around 4,000 m), multi-ethnic groups, and the specific ways of life or habits (such as eating too much beef and mutton, have alcohol and cigarette problem, et al.). By comparing with the western gastric cancer patients collected from TCGA data portal, some unique characteristics for patients in QTP are suggested. They include high incidence in younger people, most of tumor are located in body, most of SNP are detected in chromosome 7, and the very different molecular atlas in minor ethnic groups and Han Chinese. These characteristics will provide the unprecedented opportunity to increase the efficacy for diagnosis and prognosis of gastric cancer in QTP. Furthermore, to suggest the targeted therapeutics specially designed for these 30 patients, an adapted kernel-based learning model and a compilation of pharmacogenomics data of 462 patient-derived tumor cells (PDCs) that illustrate the diverse genetic and molecular backgrounds of cancer patients, were introduced. In conclusion, our study offers a big opportunity to better understand the mechanism of gastric cancer in QTP and guide the optimal patient-tailored therapy for them.

Long noncoding RNA (lncRNA) transcripts have emerging impacts in cancer studies, which suggests their potential as novel therapeutic agents. However, the molecular mechanism behind their treatment effects is still unclear. Here, we designed a computational model to Associate LncRNAs with Anti-Cancer Drugs (ALACD) based on a bilevel optimization model, which optimized the gene signature overlap in the upper level and imputed the missing lncRNA-gene association in the lower level. ALACD predicts genes coexpressed with lncRNAs mean while matching drug's gene signatures. This model allows us to borrow the target gene information of small molecules to understand the mechanisms of action of lncRNAs and their roles in cancer. The ALACD model was systematically applied to the 10 cancer types in The Cancer Genome Atlas (TCGA) that had matched lncRNA and mRNA expression data. Cancer type-specific lncRNAs and associated drugs were identified. These lncRNAs show significantly different expression levels in cancer patients. Follow-up functional and molecular pathway analysis suggest the gene signatures bridging drugs and lncRNAs are closely related to cancer development. Importantly, patient survival information and evidence from the literature suggest that the lncRNAs and drug-lncRNA associations identified by the ALACD model can provide an alternative choice for cancer targeting treatment and potential cancer pognostic biomarkers. The ALACD model is freely available at https://github.com/wangyc82/ALACD-v1.

In this study, broilers were fed with heavy-metal-containing diets (Zn, Cu, Pb, Cr, As, Hg) at three rates (T1: 5 kg premix/ton feed, T2: 10 kg premix/ton feed and T3: 15 kg premix/ton feed) and Doxycycline (DOX) and Gatifloxacin (GAT) at low or high doses (T4: 31.2 mg DOX/bird/day and 78 mg GAT/bird/day, T5: 15.6 mg DOX/bird/day and 48 mg GAT/bird/day) to assess the accumulation of various heavy metals and the fate of two antibiotics in broiler manure after 35 days of aerobic composting. The results indicated that the two antibiotics changed quite differently during aerobic composting. About 14.96–15.84% of Doxycycline still remained at the end of composting, while Gatifloxacin was almost completely removed within 10 days of composting. The half-lives of Doxycycline were 13.75 and 15.86 days, while the half-lives of Gatifloxacin were only 1.32 and 1.38 days. Based on the Redundancy analysis (RDA), the concentration of antibiotics was significantly influenced by physico-chemical properties (mainly temperature and pH) throughout the composting process. Throughout the composting process, all heavy metal elements remained concentrated in organic fertilizer. In this study the Cr content reached 160.16 mg/kg, 223.98 mg/kg and 248.02 mg/kg with increasing premix feed rates, similar to Zn, which reached 258.2 mg/kg, 312.21 mg/kg and 333.68 mg/kg. Zn and Cr concentrations well exceeded the United States and the European soil requirements. This experiment showed that antibiotic residues and the accumulation of heavy metals may lead to soil contamination and pose a risk to the soil ecosystem.

The emergence of drug resistance is one of the main obstacles to the treatment of lung cancer patients with EGFR inhibitors. Here, to further understand the mechanism of EGFR inhibitors in lung cancer and offer novel therapeutic targets for anti-EGFR-inhibitor resistance via the deep mining of pharmacogenomics data, we associated DNA methylation with drug sensitivities for uncovering the methylation sites related to EGFR inhibitor sensitivity genes. Specifically, we first introduced a grouped regularized regression model (Group Least Absolute Shrinkage and Selection Operator, group lasso) to detect the genes that were closely related to EGFR inhibitor effectiveness. Then, we applied the classical regression model (lasso) to identify the methylation sites associated with the above drug sensitivity genes. The new model was validated on the well-known cancer genomics resource: CTRP. GeneHancer and Encyclopedia of DNA Elements (ENCODE) database searches indicated that the predicted methylation sites related to EGFR inhibitor sensitivity genes were related to regulatory elements. Moreover, the correlation analysis on sensitivity genes and predicted methylation sites suggested that the methylation sites located in the promoter region were more correlated with the expression of EGFR inhibitor sensitivity genes than those located in the enhancer region and the TFBS. Meanwhile, we performed differential expression analysis of genes and predicted methylation sites and found that changes in the methylation level of some sites may affect the expression of the corresponding EGFR inhibitor-responsive genes. Therefore, we supposed that the effectiveness of EGFR inhibitors in lung cancer may be improved by methylation modification in their sensitivity genes.

Timely harvest is critical to achieve maximum seed viability and vigour in agricultural production. However, little information exists concerning how to reap the best quality seeds of Leymus chinensis, which is the dominant and most promising grass species in the Songnen Grassland of Northern China. The objective of this study was to investigate and evaluate possible quality indices of the seeds at different days after peak anthesis. Seed quality at different development stages was assessed by the colours of the seed and lemmas, seed weight, moisture content, electrical conductivity of seed leachate and germination indices. Two consecutive years of experimental results showed that the maximum seed quality was recorded at 39 days after peak anthesis. At this date, the colours of the seed and lemmas reached heavy brown and yellow, respectively. The seed weight was highest and the moisture content and the electrical conductivity of seed leachate were lowest. In addition, the seed also reached its maximum germination percentage and energy at this stage, determined using a standard germination test (SGT) and accelerated ageing test (AAT). Thus, Leymus chinensis can be harvested at 39 days after peak anthesis based on the changes in parameters. Colour identification can be used as an additional indicator to provide a more rapid and reliable measure of optimum seed maturity; approximately 10 days after the colour of the lemmas reached yellow and the colour of the seed reached heavy brown, the seed of this species was suitable for harvest.

Computational inference of novel therapeutic values for existing drugs, i.e., drug repositioning, offers the great prospect for faster and low-risk drug development. Previous researches have indicated that chemical structures, target proteins, and side-effects could provide rich information in drug similarity assessment and further disease similarity. However, each single data source is important in its own way and data integration holds the great promise to reposition drug more accurately. Here, we propose a new method for drug repositioning, PreDR (Predict Drug Repositioning), to integrate molecular structure, molecular activity, and phenotype data. Specifically, we characterize drug by profiling in chemical structure, target protein, and side-effects space, and define a kernel function to correlate drugs with diseases. Then we train a support vector machine (SVM) to computationally predict novel drug-disease interactions. PreDR is validated on a well-established drug-disease network with 1,933 interactions among 593 drugs and 313 diseases. By cross-validation, we find that chemical structure, drug target, and side-effects information are all predictive for drug-disease relationships. More experimentally observed drug-disease interactions can be revealed by integrating these three data sources. Comparison with existing methods demonstrates that PreDR is competitive both in accuracy and coverage. Follow-up database search and pathway analysis indicate that our new predictions are worthy of further experimental validation. Particularly several novel predictions are supported by clinical trials databases and this shows the significant prospects of PreDR in future drug treatment. In conclusion, our new method, PreDR, can serve as a useful tool in drug discovery to efficiently identify novel drug-disease interactions. In addition, our heterogeneous data integration framework can be applied to other problems.

As a native tree species, Ulmus pumila var. sabulosa (sandy elm) is widely distributed in the Horqin Sandy Land, China. However, seedlings of this species have to withstand various depths of sand burial after emergence because of increasing soil degradation, which is mainly caused by overgrazing, climate change, and wind erosion. An experiment was conducted to evaluate the changes in its survivorship, morphological traits, and biomass allocation when seedlings were buried at different burial depths: unburied controls and seedlings buried vertically up to 33, 67, 100, or 133% of their initial mean seedling height. The results showed that partial sand burial treatments (i.e., less than 67% burial) did not reduce seedling survivorship, which still reached 100 %. However, seedling mortality increased when sand burial was equal to or greater than 100 %. In comparison with the control treatment, seedling height and stem diameter increased at least by 6 and 14% with partial burial, respectively. In the meantime, seedling taproot length, total biomass, and relative mass growth rates were at least enhanced by 10, 15.6, and 27.6 %, respectively, with the partial sand burial treatment. Furthermore, sand burial decreased total leaf area and changed biomass allocation in seedlings, partitioning more biomass to aboveground organs (e.g., leaves) and less to belowground parts (roots). Complete sand burial after seedling emergence inhibited its reemergence and growth, even leading to death. Our findings indicated that seedlings of sandy elm showed some resistance to partial sand burial and were adapted to sandy environments from an evolutionary perspective. The negative effect of excessive sand burial after seedling emergence might help in understanding failures in recruitments of sparse elm in the study region. [ABSTRACT FROM AUTHOR]

We investigated the effects of seed burial depth and soil water content on seedling emergence and growth of Ulmus pumila var. sabulosa (sandy elm), an important native tree species distributed over the European-Asian steppe. Experimental sand burial depths in the soil were 0.5,1.0, 1.5, 2.0 and 2.5 cm, and soil water contents were 4%, 8%, 12% and 16% of field capacity. All two-way ANOVA (five sand burial depths and four soil water contents) results showed that seed burial depths, soil water content and their interactions significantly affected all the studied plant variables. Most of the times, seedling emergence conditions were greater at the lower sand burial depths (less than 1.0 cm) than at the higher (more than 1.0 cm) seed burial depths, and at the lower water content (less than 12%) than at the higher soil water content. However, high seed burial depths (more than 1.5 cm) or low soil water content (less than 12%) reduced seedling growth or change in the root/shoot biomass ratios. In conclusion, the most suitable range of sand burial was from 0.5 to 1.0 cm soil depth and soil water content was about 12%, respectively, for the processes of seedling emergence and growth. These findings indicate that seeds of the sandy elm should be kept at rather shallow soil depths, and water should be added up to 12% of soil capacity when conducting elm planting and management. Our findings could help to create a more appropriate sandy elm cultivation and understand sparse elm woodland recruitment failures in arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

As a native tree species, Ulmus pumila var. sabulosa (Sandy elm) is widely distributed in Horqin Sandy Land. However, seedlings of this species have to withstand various depths of sand burial after emergence because of increasing soil degradation. So an experiment was conducted to evaluate the changes in the survivorship, morphological traits and biomass allocation buried with different burial depths (unburied, and seedlings buried vertically up to 33, 67, 100 or 133% of the initial mean seedling height). The results showed that partial sand burial treatments (i.e., less than 67% burial) did not influence seedling survivorship, which still reached 100%. However, seedling mortality increased as sand burial was equal to or greater than 100%. Seedling height and stem diameter increased at least by 6 to 14% with partial burial in comparison with control treatment. Whilst seeding taproot length, total biomass, and relative growth rates at least enhanced by 10%, 15.6%, and 27.6%, respectively, with the partial sand burial treatment. Furthermore, sand burial decreased total leaf area and changed biomass allocation on seedlings, transferring more biomass to aboveground rather than belowground parts. Complete sand burial after seedling emergence inhibited its growth, and even lead to death. Our findings indicated that seedling of sandy elm had a certain resistance to partial sand burial and acclimated to sandy environments. The negative effects of common excessive sand burial after seedling emergence help to understand failures in recruitment of sparse elm woodland in the Horqin sandy land. [ABSTRACT FROM AUTHOR]