Understanding vegetation C, N, and P stoichiometry helps us not only to evaluate biogeochemical cycles and ecosystem functions but also to predict the potential impact of environmental change on ecosystem processes. The foliar C, N, and P stoichiometry in Northern Tibetan grasslands, especially the controlling factors, has been highlighted in recent years. In this study, we have collected 340 plant samples and 162 soil samples from 54 plots in three grassland types, with the purpose of evaluating the foliar C, N, and P stoichiometry and underlying control factors in three grassland types along a 1,500-km east-to-west transect in the Northern Tibetan Plateau. Our results indicated that the averaged foliar C, N, and P concentrations were 425.9 ± 15.8, 403.4 ± 22.2, and 420.7 ± 30.7 g kg−1; 21.7 ± 2.9, 19.0 ± 2.3, and 21.7 ± 5.2 g kg−1; and 1.71 ± 0.29, 1.19 ± 0.16, and 1.59 ± 0.6 g kg−1 in the alpine meadow (AM), alpine steppe (AS), and desert steppe (DS) ecosystems, respectively. The foliar C and N ratios were comparable, with values of 19.8 ± 2.8, 20.6 ± 1.9, and 19.9 ± 5.8 in the AM, AS, and DS ecosystems, respectively. Both the C/P and N/P ratios are the lowest in the AM ecosystem, with values of 252.2 ± 32.6 and 12.8 ± 1.3, respectively, whereas the highest values of 347.3 ± 57.0 and 16.2 ± 3.2 were obtained in the AS ecosystem. In contrast, the soil C, N, C/P, and N/P values decreased from the AM to DS ecosystem. Across the whole transects, leaf C, N, and P stoichiometry showed no obvious trend, but soil C and N concentrations showed an increasing trend, and soil P concentrations showed a decreasing trend with the increasing longitude. Based on the general linear model analysis, the vegetation type was the dominant factor controlling the leaf C, N, and P stoichiometry, accounting for 42.8% for leaf C, 45.1% for leaf N, 35.2% for leaf P, 52.9% for leaf C/N, 39.6% for leaf C/P, and 48.0% for leaf N/P; the soil nutrients and climate have relatively low importance. In conclusion, our results supported that vegetation type, rather than climatic variation and soil nutrients, are the major determinants of north Tibet grassland leaf stoichiometry.

Growth-regulating factors (GRFs) are plant-specific transcription factors that contain two highly conserved QLQ and WRC domains, which control a range of biological functions, including leaf growth, floral organ development, and phytohormone signaling. However, knowledge of the evolutionary patterns and driving forces of GRFs in Gramineae crops is limited and poorly characterized. In this study, a total of 96 GRFs were identified from eight crops of Brachypodium distachyon, Hordeum vulgare, Oryza sativa L. ssp. indica, Oryza rufipogon, Oryza sativa L. ssp. japonica, Setaria italic, Sorghum bicolor and Zea mays. Based on their protein sequences, the GRFs were classified into three groups. Evolutionary analysis indicated that the whole-genome or segmental duplication plays an essential role in the GRFs expansion, and the GRFs were negatively selected during the evolution of Gramineae crops. The GRFs protein function as transcriptional activators with distinctive structural motifs in different groups. In addition, the expression of GRFs was induced under multiple hormonal stress, including IAA, BR, GA3, 6BA, ABA, and MeJ treatments. Specifically, OjGRF11 was significantly induced by IAA at 6 h after phytohormone treatment. Transgenic experiments showed that roots overexpressing OjGRF11 were more sensitive to IAA and affect root elongation. This study will broaden our insights into the origin and evolution of the GRF family in Gramineae crops and will facilitate further research on GRF function.

IntroductionFire and nitrogen (N) deposition each impact biodiversity and ecosystem productivity. However, the effect of N deposition on ecosystem recovery after fire is still far from understood, especially in coastal wetlands.MethodsWe selected a typical coastal shrubland to simulate three N deposition levels (0, 10, and 20 g N m−2 year−1) under two different burned conditions (unburned and burned) in the Yellow River Delta of North China. Soil properties, soil microbial biodiversity, shrub growth parameters, herbaceous biodiversity, and aboveground productivity were determined after experimental treatments for 1 year.ResultsWe found that fire had a stronger influence on the ecosystem than N addition. One year after the fire, shrub growth had significantly decreased, while soil pH, soil electrical conductivity, herbaceous biodiversity, soil microbial biodiversity, and herbaceous aboveground productivity significantly increased. Conversely, a single year of N addition only slightly increased herbaceous aboveground productivity. The combined effect of fire and N addition was only significant for fungus biodiversity and otherwise had minimal influence. Interestingly, we found that herbaceous aboveground productivity was positively associated with fungal community diversity under unburned conditions but not in burned shrublands. Fire showed a great impact on soil parameters and biodiversity in the coastal wetland ecosystem even after a full year of recovery.DiscussionFire may also diminish the influence of several belowground factors on herbaceous aboveground productivity, which ultimately reduces recovery and stability. Appropriate N addition may be an effective way to improve the ecosystem productivity in a wetland dominated by shrub species.

IntroductionAlfalfa, a globally cultivated forage crop, faces significant challenges due to its vulnerability to salt stress. Jasmonates (JAs) play a pivotal role in modulating both plant growth and response to stressors.MethodsIn this study, alfalfa plants were subjected to 150 mM NaCl with or without methyl jasmonate (MeJA). The physiological parameters were detected and a transcriptomic analysis was performed to elucidate the mechanisms underlying MeJA-mediated salt tolerance in alfalfa.ResultsResults showed that exogenous MeJA regulated alfalfa seed germination and primary root growth in a dose-dependent manner, with 5µM MeJA exerting the most efficient in enhancing salt tolerance. MeJA at this concentration elavated the salt tolerance of young alfalfa seedlings by refining plant growth, enhancing antioxidant capacity and ameliorating Na+ overaccumulation. Subsequent transcriptomic analysis identified genes differentially regulated by MeJA+NaCl treatment and NaCl alone. PageMan analysis revealed several significantly enriched categories altered by MeJA+NaCl treatment, compared with NaCl treatment alone, including genes involved in secondary metabolism, glutathione-based redox regulation, cell cycle, transcription factors (TFs), and other signal transductions (such as calcium and ROS). Further weighted gene co-expression network analysis (WGCNA) uncovered that turquoise and yellow gene modules were tightly linked to antioxidant enzymes activity and ion content, respectively. Pyruvate decar-boxylase (PDC) and RNA demethylase (ALKBH10B) were identified as the most central hub genes in these two modules. Also, some TFs-hub genes were identified by WGCNA in these two modules highly positive-related to antioxidant enzymes activity and ion content.DiscussionMeJA triggered a large-scale transcriptomic remodeling, which might be mediated by transcriptional regulation through TFs or post-transcriptional regulation through demethylation. Our findings contributed new perspectives for understanding the underneath mechanisms by which JA-mediated salt tolerance in alfalfa.

Rice is the staple food for approximately half of the world’s population. Seed vigour has a crucial impact on the yield, which can be evaluated by germination rate, vigor index and etc. Existing seed vigour testing methods heavily rely on manual inspections that are destructive, time-consuming, and labor-intensive. To address the drawbacks of existing rice seed vigour testing, we proposed a multispectral image-based non-destructive seed germination testing approach. Specifically, we collected multispectral data in 19 wavebands for six rice varieties. Furthermore, we designed an end-to-end pipeline, denoted as MsiFormer (MisFormer cod3e will be available at https://github.com/LiaoYun0x0/MisFormer) by integrating a Yolo-based object detector (trained Yolo v5) and a vision transformer-based vigour testing model, which effectively improved the automation and efficiency of existing techniques. In order to objectively evaluate the performance of the proposed method in this paper, we conduct a comparison between MisFormer and other 3 deep learning methods. The results showed that, MisFormer performed much better with the accuracy of 94.17%, which was 2.5%-18.34% higher than the other 3 deep learning methods. Besides MsiFormer, possibilities of CIELab mediated image analysis of TTC (tetrazolium chloride) staining in rice seed viability and nCDA (normalized canonical discriminant analysis) in rice seed vigour were also discussed, where CIELab L* of TTC staining were negatively correlated with vigor index and germination rate, with Pearson’s correlation coefficient of -0.9874, -0.9802 respectively, and CIELab A* of TTC staining were and positively correlated with vigor index and germination rate, with Pearson’s correlation coefficient of 0.9624, 0.9544 respectively, and CIELab A* of nCDA had Pearson’s correlation coefficient of -0.8866 and -0.9340 with vigor index and germination rate, respectively. Besides testing methods, vigour results within and among variety(ies) showed that, there were great variations among the 6 rice varieties, and mean coefficient of variation (CV) of vigor index of individual seed within a variety reached 64.87%, revealing the high risk of conventional methods in random sampling. Vigour variations had close relationship with wavelengths of 780 nm-970 nm, indicating their value in future research.