Frontiers in Plant Science最新文献

{"title":"Home-field advantage effect weakened over time but was strengthened by labile carbon input in later litter decomposition stage.","authors":"Yafang Xue, Ning Ma, Lei Jiang, Weimin Wang, Shenggong Li","doi":"10.3389/fpls.2025.1545311","DOIUrl":"10.3389/fpls.2025.1545311","url":null,"abstract":"<p><p>Home-field advantage (HFA) hypothesis proposes that leaf litter decays more rapidly in its original place than elsewhere owing to specific litter-field affinity. However, the HFA effect may vary over time and receive influences from other external factors, and it remains unclear whether the labile carbon (C) in root exudates influences the HFA effect during later decomposition stage. We aim to 1) elucidate how the HFA effect varies over time, 2) demonstrate how the HFA effect changes when stimulated by labile C at the later decomposition stage, and 3) explore how fungi affect the HFA effect. We conducted a reciprocal litter transplant experiment using two tree species, (<i>Pinus elliottii</i> and <i>Cunninghamia lanceolata</i>) with a two-phase design (early vs. late decomposition, plus glucose addition). We harvested the samples of soil and litter after decomposition for 1, 2, 4 and 6 months. Glucose (labile C) was added to soil after decomposition of 4 months. The HFA effect decreased over time, and the fungal community dissimilarity between home and away soils, especially Eurotiomycetes, affected variations in HFA. Additionally, glucose additions led to a significant increase of 15.19% in the HFA effect (<i>p</i><0.05) during later decomposition stage, which was primarily associated with Sordariomycetes. Our findings implies that the HFA in litter decomposition was mainly associated with specific fungal taxa. Importantly, the introduction of labile C strengthened the HFA effect at later decomposition stage. Therefore, it cannot be overlooked that the priming effect of labile C input on the HFA effect at later decomposition stage in future research. Our two-phase design study further highlights the differences in litter decomposition between home and away soils at different decomposing stages and the regulation of HFA by specific fungal taxa and labile carbon inputs, especially in the later decomposition stage.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1545311"},"PeriodicalIF":4.1,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951264/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143751706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EMSAM: enhanced multi-scale segment anything model for leaf disease segmentation.","authors":"Junlong Li, Quan Feng, Jianhua Zhang, Sen Yang","doi":"10.3389/fpls.2025.1564079","DOIUrl":"10.3389/fpls.2025.1564079","url":null,"abstract":"<p><p>Accurate segmentation of leaf diseases is crucial for crop health management and disease prevention. However, existing studies fall short in addressing issues such as blurred disease spot boundaries and complex feature distributions in disease images. Although the vision foundation model, Segment Anything Model (SAM), performs well in general segmentation tasks within natural scenes, it does not exhibit good performance in plant disease segmentation. To achieve fine-grained segmentation of leaf disease images, this study proposes an advanced model: Enhanced Multi-Scale SAM (EMSAM). EMSAM employs the Local Feature Extraction Module (LFEM) and the Global Feature Extraction Module (GFEM) to extract local and global features from images respectively. The LFEM utilizes multiple convolutional layers to capture lesion boundaries and detailed characteristics, while the GFEM fine-tunes ViT blocks using a Multi-Scale Adaptive Adapter (MAA) to obtain multi-scale global information. Both outputs of LFEM and GFEM are then effectively fused in the Feature Fusion Module (FFM), which is optimized with cross-branch and channel attention mechanisms, significantly enhancing the model's ability to handle blurred boundaries and complex shapes. EMSAM integrates lightweight linear layers as classification heads and employs a joint loss function for both classification and segmentation tasks. Experimental results on the PlantVillage dataset demonstrate that EMSAM outperforms the second-best state-of-the-art semantic segmentation model by 2.45% in Dice Coefficient and 6.91% in IoU score, and surpasses the baseline method by 21.40% and 22.57%, respectively. Particularly, for images with moderate and severe disease levels, EMSAM achieved Dice Coefficients of 0.8354 and 0.8178, respectively, significantly outperforming other semantic segmentation algorithms. Additionally, the model achieved a classification accuracy of 87.86% across the entire dataset, highlighting EMSAM's effectiveness and superiority in plant disease segmentation and classification tasks.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1564079"},"PeriodicalIF":4.1,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11949962/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143752282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum: Comparative transcriptomic analysis and functional characterization reveals that the class III peroxidase gene <i>TaPRX-2A</i> regulates drought stress tolerance in transgenic wheat.","authors":"Peisen Su, Chao Sui, Yufei Niu, Jingyu Li, Shuhan Wang, Fanting Sun, Jun Yan, Shangjing Guo","doi":"10.3389/fpls.2025.1565141","DOIUrl":"https://doi.org/10.3389/fpls.2025.1565141","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.3389/fpls.2023.1119162.].</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1565141"},"PeriodicalIF":4.1,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951114/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143752272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Image-based yield prediction for tall fescue using random forests and convolutional neural networks.","authors":"Sarah Ghysels, Bernard De Baets, Dirk Reheul, Steven Maenhout","doi":"10.3389/fpls.2025.1549099","DOIUrl":"10.3389/fpls.2025.1549099","url":null,"abstract":"<p><p>In the early stages of selection, many plant breeding programmes still rely on visual evaluations of traits by experienced breeders. While this approach has proven to be effective, it requires considerable time, labour and expertise. Moreover, its subjective nature makes it difficult to reproduce and compare evaluations. The field of automated high-throughput phenotyping aims to resolve these issues. A widely adopted strategy uses drone images processed by machine learning algorithms to characterise phenotypes. This approach was used in the present study to assess the dry matter yield of tall fescue and its accuracy was compared to that of the breeder's evaluations, using field measurements as ground truth. RGB images of tall fescue individuals were processed by two types of predictive models: a random forest and convolutional neural network. In addition to computing dry matter yield, the two methods were applied to identify the top 10% highest-yielding plants and predict the breeder's score. The convolutional neural network outperformed the random forest method and exceeded the predictive power of the breeder's eye. It predicted dry matter yield with an R² of 0.62, which surpassed the accuracy of the breeder's score by 8 percentage points. Additionally, the algorithm demonstrated strong performance in identifying top-performing plants and estimating the breeder's score, achieving balanced accuracies of 0.81 and 0.74, respectively. These findings indicate that the tested automated phenotyping approach could not only offer improvements in cost, time efficiency and objectivity, but also enhance selection accuracy. As a result, this technique has the potential to increase overall breeding efficiency, accelerate genetic progress, and shorten the time to market. To conclude, phenotyping by means of RGB-based machine learning models provides a reliable alternative or addition to the visual evaluation of selection candidates in a tall fescue breeding programme.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1549099"},"PeriodicalIF":4.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11936891/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143718465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nitrogen allocation among leaves and roots mediates the interaction between plant life history trade-off and density dependence.","authors":"Junkang Cheng, Shixiao Yu","doi":"10.3389/fpls.2025.1549801","DOIUrl":"10.3389/fpls.2025.1549801","url":null,"abstract":"<p><strong>Introduction: </strong>Carbon, nitrogen and phosphorus, as the basic components of plants, determine plant growth and adaptation strategies, while there are certain differences in nutrient allocation among different plant organs. However, little is known about the manner in which resource allocation mediates the plant life history strategy.</p><p><strong>Methods: </strong>Here, we collected three census field survey datasets from the Heishiding 50-ha dynamic plot showing functional traits and nutrient allocation among leaves and roots (⍺_nutrient) from 92 woody species to determine the relationship between nutrient allocation and the plant life history strategy.</p><p><strong>Results: </strong>Carbon allocation ⍺_carbon was mainly determined by intraspecific variation while nitrogen allocation ⍺_nitrogen and phosphorus allocation ⍺_phosphorus was determined by interspecific variation. Species allocating more nitrogen to leaves showed greater resource acquisition traits, while species allocating more nitrogen to roots showed greater resource conservation traits. We found a trade-off between the plant relative growth rate and conspecific density dependence; fast-growing species showed higher mortality with conspecific neighbors but tended to allocate more nitrogen to leaves rather than roots.</p><p><strong>Discussion: </strong>Our study revealed interspecific variation in nutrient allocation among leaves and roots as well as their relationship with functional traits and the plant life history strategy.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1549801"},"PeriodicalIF":4.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11936912/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143718548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of genetic factors influencing flavonoid biosynthesis through pooled transcriptome analysis in mungbean sprouts.","authors":"Yeonghun Cho, Hakyung Kwon, Byeong Cheol Kim, Donghwan Shim, Jungmin Ha","doi":"10.3389/fpls.2025.1540674","DOIUrl":"10.3389/fpls.2025.1540674","url":null,"abstract":"<p><strong>Introduction: </strong>Mungbean (<i>Vigna radiata L</i>.) is gaining increasing interest among legume crops because of its nutritional value. Various secondary metabolites that act as antioxidants and bioactive compounds are beneficial for human health. The secondary metabolite content in plants is easily influenced by environmental conditions, and this influence varies depending on the genotype.</p><p><strong>Materials and methods: </strong>Here, we screened six genotypes with consistently high and low content of major secondary metabolites (gallic acid, chlorogenic acid, neo-chlorogenic acid, genistin, formononetin, catechin, syringic acid, and resveratrol) across environmental replicates. Transcriptome data obtained from the individual genotypes were pooled into two groups: high and low levels of secondary metabolites.</p><p><strong>Results and discussion: </strong>Of the 200 differentially expressed genes identified using stringent criteria, 23 were annotated in the secondary metabolite pathway. By combining the results of the secondary metabolite and transcriptome data, we identified six key genes encoding four enzymes (<i>CCoAOMT1</i>; Caffeoyl-CoA O-methyltransferase, <i>CYP81E1</i>; 4'-methoxyisoflavone 2'-hydroxylase, <i>DFR</i>; dihydroflavonol-4-reductase, and <i>HCT</i>; shikimate O-hydroxycinnamoyltransferase) that commonly influence the content of secondary metabolites (catechin, chlorogenic acid, formononetin, and genistin) in mungbeans. Through regulatory network analysis, NAC042 and MYB74 transcription factors were identified. These transcription factors regulate the expression of four key genes in mungbean, <i>CCoAOMT1(Vradi02g00000724.1), CYP81E1(Vradi09g00002897.1), DFR(Vradi07g00001336.1)</i>, and <i>HCT(Vradi07g00000614.1)</i> leading to high flavonoid content.</p><p><strong>Conclusion: </strong>These results provide information on the common genetic factors involved in the production of secondary metabolites, which can improve the nutritional value of mungbeans and contribute to the development of elite mungbean cultivars.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1540674"},"PeriodicalIF":4.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11936997/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143718463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regulation of alfalfa growth, water and nitrogen utilization and distribution in arid region of Northwest China by optimizing irrigation method.","authors":"Hongxiu Ma, Peng Jiang, Xiaojuan Zhang, Ruliang Liu, Quan Sun, Lei Wang","doi":"10.3389/fpls.2025.1517398","DOIUrl":"10.3389/fpls.2025.1517398","url":null,"abstract":"<p><p>The water and nitrogen use efficiency of alfalfa is very low in the arid region of Northwest China currently. In this field experiments in 2022 and 2023, the effects of traditional flood irrigation (FI-12, 1200 mm; FI-8, 880 mm), sprinkler irrigation (SI-8, 880 mm; SI-5, 520 mm), and subsurface drip irrigation (DI-5, 520 mm; DI-8, 880 mm)) on alfalfa yield, water use efficiency (WUE), and nitrogen use efficiency (NUE) were studied. The results showed that the DI and SI treatments, especially DI-5, increased alfalfa seed yield by increasing the number of inflorescences and pods compared with the FI treatments. The DI and SI treatments, especially DI, reduced water loss during the first two crops in each growing season compared with the FI treatments, improving the WUE. The DI treatments had the lowest root/shoot ratio (R/S), which facilitated the distribution of photosynthetic products to the reproductive organs and inhibited the overgrowth of the root system. The small R/S in the late growth stage of the DI-5 treatment also helped to achieve high WUE. Besides, the DI treatments also had the largest root length density, which promoted the uptake and utilization of water and nitrogen by alfalfa. The DI treatments increased the nitrogen accumulation of plants, and reduced the soil nitrate (NO₃ ^--N) leaching and NH₃ volatilization at maturity stage compared with the SI and FI treatments, improving the NUE. In summary, the subsurface drip fertigation, especially DI-5, coordinated the vegetative and reproductive growth, and reduced the water loss, nitrate leaching, and NH₃ volatilization, improving the seed yield, WUE, and NUE of alfalfa. This study will advance understanding of the mechanism of subsurface drip irrigation regulating alfalfa root growth and water and nitrogen use, and provide a scientific basis for the application of subsurface drip fertigation in arid and semi-arid areas.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1517398"},"PeriodicalIF":4.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11936995/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143718550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Antibacterial potential of silver-selenium nanocomposites in mitigating fire blight disease in <i>Pyrus communis</i> L.","authors":"Muhammad Imran, Muhammad Umer, Naveed Iqbal Raja, Fozia Abasi, Nimra Sardar, Ubaidur Rahman, Syed Azaz Mustafa Naqvi, Muhammad Yousuf Jat Baloch, Abdulwahed Fahad Alrefaei","doi":"10.3389/fpls.2025.1541498","DOIUrl":"10.3389/fpls.2025.1541498","url":null,"abstract":"<p><p><i>Pyrus communis</i> L. is a vital fruit tree known for its nutritional and economic importance. Thus, for humans, it is an essential element for their balanced nutritional diet, as it contains the major dietary fibers, vitamins, and minerals. All of these nutritionally important aspects decrease with the impact of disease fire blight. <i>Erwinia amylovora</i> is a causative agent of fire blight. This infection causes a considerable loss in the production of <i>Pyrus communis</i> L. Annually, approximately 50% of pear fruit in Pakistan is misplaced because of these illnesses. Therefore, we propose nanotechnology remediation to treat pear plants and obtain the desired yield. In this regard, an experiment was designed to treat infected plants with different concentrations of silver-selenium nanocomposites, which was based on a literature review that indicated the antimicrobial activities of silver and selenium nanoparticles. Silver-selenium nanocomposites were prepared using a green synthesis method, and their synthesis was confirmed using characterization techniques. The experiment was performed at a farmhouse in Chakwal district, Punjab, Pakistan. The experimental results showed increased morphological, physiological, and biochemical parameters. In this regard, the best treatment remained at 50 ppm for the Ag-Se nanocomposite, which improved the plant in different aspects. At the same time, they have improved fruit metrics, such as vitamin C, pH, and juice content. Thus, these results show a possible improvement in enhancing the resistance against fire blight by using green-synthesized Ag-Se NCs. Further studies are needed to understand fully the molecular mechanisms and actions of <i>Pyrus communis</i> L. in treating fire blight disease and to establish the optimal treatment plan.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1541498"},"PeriodicalIF":4.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11936962/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143718544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploration of biophoton characteristics of fresh <i>Isatis indigotica</i> fort leaves under salt and drought stresses and the feasibility analysis for the quality prediction of <i>Isatidis Folium</i>.","authors":"Zhiying Wang, Baorui Cao, Yueyue Ma, Weifan Xu, Jialei Fu, Zhongwen Zhang, Jinxin Du, Tingting Deng, Jingxiang Pang, Meina Yang, Jinxiang Han","doi":"10.3389/fpls.2025.1523636","DOIUrl":"10.3389/fpls.2025.1523636","url":null,"abstract":"<p><strong>Introduction: </strong><i>Isatidis Folium</i>, derived from the dried leaves of <i>Isatis indigotica</i> Fort, has been used for centuries as a traditional Chinese herb with antibacterial and antiviral properties. However, both the cultivation conditions and the growth status of <i>Isatis indigotica</i> Fort have been negatively affected by climatic and environmental degradation, which has made it challenging to accurately assess the quality of <i>Isatidis Folium</i>. The current quality control system for <i>Isatidis Folium</i> lacks precision and comprehensive identification indices, and importantly, the cultivation process has not been integrated into this system.</p><p><strong>Methods: </strong>In this study, we proposed a novel method to distinguish between different stress subtypes in <i>Isatis indigotica</i> Fort based on biophoton emission and attempted to explore the potential relationship between the biophoton characteristics of fresh <i>Isatis indigotica</i> Fort leaves and the quality of <i>Isatidis Folium</i>. The delayed luminescence (DL) and spontaneous photon emission (SPE) characteristics of fresh <i>Isatis indigotica</i> Fort leaves under different stress conditions were detected using a biophoton detection system. An attempt was made to differentiate samples subjected to various stress treatments using biophoton characteristic parameters. Additionally, the content of active ingredients was determined by ultra-high performance liquid chromatography, and the inhibitory activity against Escherichia coli and Staphylococcus aureus was evaluated to identify the quality of <i>Isatidis Folium</i>. Several physiological indicators of fresh <i>Isatis indigotica</i> Fort leaves, including the photosynthetic pigment content, relative electrical conductivity, and reactive oxygen species production rate were also determined.</p><p><strong>Result: </strong>The differences in physiological indices, active ingredient content, and inhibitory activity indicated that the stress conditions significantly inhibited the growth status of <i>Isatis indigotica</i> Fort leaves and the herbal quality. Meanwhile, biophoton characteristic parameters were obtained that could accurately and efficiently distinguish fresh <i>Isatis indigotica</i> Fort leaves between different stress subtypes: initial intensity of DL and counts per second of SPE. Both characteristic parameters were highly correlated with the physiological indicators and quality of <i>Isatidis Folium</i>.</p><p><strong>Discussion: </strong>This study has preliminarily demonstrated the feasibility of utilizing biophoton detection technology for the quality evaluation of <i>Isatidis Folium</i> during cultivation for the first time and provided an improved method for distinguishing samples of various qualities.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1523636"},"PeriodicalIF":4.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11937020/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143718458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive management for alpine grassland of the Tibetan Plateau based on a multi-criteria assessment.","authors":"Tianyu Zhan, Shurong Zhang, Wenwu Zhao","doi":"10.3389/fpls.2025.1518721","DOIUrl":"10.3389/fpls.2025.1518721","url":null,"abstract":"<p><p>With the increasing threats of global climate change and human activities to terrestrial ecosystems, understanding the quality of alpine grassland ecosystems and their influencing factors is fundamental for effective ecosystem management and improving human well-being. However, current adaptive management plans for alpine grasslands based on multi-criteria assessment are limited. This study utilized field investigations at 77 sampling points, drone remote sensing, and satellite remote sensing data to construct an alpine grassland quality index based on vegetation and soil indicators, and assess the ecosystem's resilience and pressure. The assessment revealed that the alpine grasslands of the Tibetan Plateau were classified into five zones, indicating significant differences in quality and pressure levels. Key findings showed that the High-Quality Pressure Zone comprise 41.88% of the area of alpine meadow and 31.89% of alpine steppe, while the Quality Improvement-Limitation Zone account for 21.14% and 35.8% of the respective areas. The study recommends graded protection and recovery strategies for alpine grasslands based on quality levels: prioritizing high-quality grasslands, implementing dynamic monitoring and enhancement for moderate-quality grasslands, and applying artificial interventions and suitable species for low-quality grasslands. This research underscores the importance of zoning-based adaptive strategies for sustainable ecosystem management and provides valuable insights for effective management and protection of alpine grasslands in the Tibetan Plateau.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1518721"},"PeriodicalIF":4.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11937058/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143718543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}