Hasil untuk "Plant ecology"

J. Vacheron, Guilhem Desbrosses, M. Bouffaud et al.

The rhizosphere supports the development and activity of a huge and diversified microbial community, including microorganisms capable to promote plant growth. Among the latter, plant growth-promoting rhizobacteria (PGPR) colonize roots of monocots and dicots, and enhance plant growth by direct and indirect mechanisms. Modification of root system architecture by PGPR implicates the production of phytohormones and other signals that lead, mostly, to enhanced lateral root branching and development of root hairs. PGPR also modify root functioning, improve plant nutrition and influence the physiology of the whole plant. Recent results provided first clues as to how PGPR signals could trigger these plant responses. Whether local and/or systemic, the plant molecular pathways involved remain often unknown. From an ecological point of view, it emerged that PGPR form coherent functional groups, whose rhizosphere ecology is influenced by a myriad of abiotic and biotic factors in natural and agricultural soils, and these factors can in turn modulate PGPR effects on roots. In this paper, we address novel knowledge and gaps on PGPR modes of action and signals, and highlight recent progress on the links between plant morphological and physiological effects induced by PGPR. We also show the importance of taking into account the size, diversity, and gene expression patterns of PGPR assemblages in the rhizosphere to better understand their impact on plant growth and functioning. Integrating mechanistic and ecological knowledge on PGPR populations in soil will be a prerequisite to develop novel management strategies for sustainable agriculture.

M. van Kleunen, E. Weber, M. Fischer

M. Furlong, D. Wright, L. Dosdall

J. Kesselmeier, M. Staudt

E. Bernays, R. Chapman

J. Silvertown, D. Charlesworth

W. Bond, J. Midgley

L. Després, J. David, C. Gallet

R. Pennington, M. Lavin, A. Oliveira-Filho

C. Vacher, A. Hampe, A. Porté et al.

Longhui Zhao, Jiayi Jian, Haixia Long et al.

Amphibians, the most threatened vertebrate group, are particularly vulnerable to temperature changes due to their ectothermic nature, but the impact of distinct thermal environments on their calling behaviors remains unclear. In this study, we used a combination of human-based field surveys and passive acoustic monitoring (PAM) techniques to investigate the calling behaviors of four anurans (Microhyla fissipes, Leptobrachium hainanensis, Hylarana guentheri, and Amolops torrentis) within the confines of the Hainan Tropical Rainforest National Park. We also examined the relationship between this behavior and daily temperature fluctuations in these species. The results showed that four anurans had temporal partitioning in daily calling activities. All species exhibited a narrow preferred temperature range for calling: M. fissipes, L. hainanensis, and H. guentheri preferred [24/25°C, 29°C), while A. torrentis preferred [23°C, 26°C). The calling count of L. hainanensis was unaffected by environmental temperature; however, the calling activity of the other three species either increased or decreased as temperatures rose. Furthermore, temperature had no impact on the call durations of two terrestrial species (M. fissipes and L. hainanensis), but had a significant influence on those of two water species (H. guentheri and A. torrentis). These results suggest that four anurans are sensitive to changes in the environmental temperature and respond differently to daily temperature variations. This study enhances our understanding of how poikilothermic animals’ vocalisations respond to specific thermal environments and provides insights into the impact of global warming on amphibians.

Lifen Hao, Lifen Hao, Yabin Liu et al.

IntroductionThe invasion of Solanum rostratum is causing severe damage to grassland ecosystems in northern China, with the species now spreading rapidly through ongoing emergence of new populations. To prevent further expansion, it is urgent to understand its dispersal patterns and identify the sources of new invasions. This study tested two hypotheses: (i) new invasions originate from established populations that serve as anthropogenic dispersal hubs, and (ii) gene flow is asymmetric, reflecting patterns consistent with human-mediated jump dispersal.MethodsWe integrated population genomics and invasion history by analyzing genome-wide single nucleotide polymorphisms (SNPs) from 261 individuals across 30 populations. Populations were categorized as early-invaded (long-established), mid-invaded (moderately recent), or newly invaded based on county-level invasion records. Phylogenetic relationships, population structure, gene flow patterns, and dispersal networks were reconstructed using phylogenetic, clustering, and gene flow analyses to trace evolutionary relationships and potential dispersal routes.ResultsPhylogenetic analysis resolved seven major monophyletic groups (A–G), while population structure analysis inferred seven ancestral gene pools (P1–P7), with strong concordance between the two independent datasets. Early-invaded populations exhibited clear spatial genetic differentiation. In contrast, newly invaded populations showed genetic admixture with ancestries overlapping multiple gene pools, indicating multiple origins and supporting a mixed dispersal pattern involving both local spread and long-distance jump dispersal. Specifically, new invasions in the Xilin Gol (XL) grassland were traced to agricultural regions in Zhangjiakou (ZJ) and Chifeng (CF). Gene flow and network analyses identified these early-invaded agricultural regions as key dispersal hubs supplying migrants to newly invaded areas. Source populations exhibited higher genetic diversity (Ne, Ho, He, Fis, π), whereas newly invaded populations showed reduced diversity, consistent with founder effects.DiscussionThese findings confirm the hypothesis of asymmetric, human-mediated jump dispersal and clarify the invasion genetic architecture of S. rostratum. By identifying agricultural regions as critical dispersal hubs, this study provides precise targets for early management interventions, offering actionable insights to prevent further expansion and enhance grassland biosecurity.

Gregory J. Cooke, Nikku Madhusudhan, Emily G. Mitchell

New observations are opening the possibility of characterising habitable environments in exoplanetary systems, with the recent example of the candidate hycean world K2-18 b. This motivates an exploration of the possible ecological conditions on such planets to better interpret biosignatures as well as understand the nature of potential life. On Earth, the Lotka-Volterra equations have been used to model numerous coupled populations within ecosystems, from interactions between large vertebrates, to systems with multiple microbial species. In this work, we apply the Lotka-Volterra equations to the ecology of habitable exoplanets for the first time, focusing on hycean worlds. We simulate scenarios in a vertical water column with between 1-5 bacterial species that thrive in anoxic environments on Earth, i.e. similar to predicted hycean conditions. We find that a wide range of ecological diversity is possible for microbial populations under hycean conditions. We demonstrate that dominating phototrophic bacteria at the top of a water column out-compete deeper dwelling phototrophic bacteria, analogous to bacterial blooms on Earth. Incorporating microbial viruses (bacteriophages) within our models can cause ecosystem collapse depending on the time of their introduction, and such phage inclusion can be beneficial to ecological diversity. Finally, our work shows that bacterial populations inhabiting tidally locked exoplanets may be more stable due to constant illumination of the ocean, but can have lower peak population densities in such cases when compared to seasonal scenarios. Our work provides an initial step towards understanding the possible ecological diversity on habitable worlds beyond Earth.

G. Lewin, C. Carlos, M. Chevrette et al.

A. Agrawal

Hongye Zhang, Cheng Yang, Lei Zong et al.

The pathogens on the leaves of the Camellia sasanqua seriously affected the ornamental value. Illuminating the underlying molecular mechanisms is of extraordinary importance in C. sasanqua to improve resistance variety. We isolated the pathogens of Fusarium sambucinum, Alternaria alternata, Phyllosticta capitalensis, and Diaporthe amygdali from the diseased leaves of C. sasanqua. These four pathogens might cause the leaf spot of C. sasanqua by working together. The transcriptomic analysis detected differences between healthy and diseased leaf samples of C. sasanqua, and 8139 DEGs were identified, including 4544 up-regulated genes and 3595 down-regulated genes. KEGG enrichment analysis of the canonical defensive pathways and the genes with high expression levels indicated that the response of C. sasanqua to pathogens was a complex signal network, including signal recognition and transmission, plant hormones including SA and ABA, activation of transcription factors of MYB, AP2/ERF, WRKY, and secondary metabolic accumulation. The genes of the phenylpropanoid biosynthesis pathway were expressed significantly in the response processes. We further cloned the genes of CAD (Cinnamic alcohol dehydrogenase) and COMT (Caffeic acid 3-O-methyltransferase), respectively, in the phenylpropanoid biosynthesis pathway, and then characterized their functions in tobacco. The results showed that overexpressing CsCAD5 and CsCOMT1 could influence the accumulation of lignins. We speculated that the increased lignin content in plants might be achieved by thickening and lignifying the cell wall. In summary, our findings discussed the complexities and interactions of C. sasanqua responses to leaf spot, identifying potential resistance genes and molecular mechanisms for preventing and controlling plant diseases.

Xiuming Chen, Qin Wang, Fei Wang et al.

The Moth orchid is globally recognized as one of the most popular and important ornamental species. However, due to the complicated history of hybridization, long growth cycles, and industrial vegetative propagation, there are huge challenges in cultivar identification and protection leading to market issues. Consequently, it is important to develop effective and stable markers to identify and preserve core Phalaenopsis cultivar resources. In this study, we collected 53 commercially prevalent Phalaenopsis cultivars in China. Through detailed phenotypic observations, morphological genetic diversity was measured in 19 quantitative and 15 qualitative traits. By genome skimming and the subsequent SNP calling pipeline, we discovered 5,984 high-quality single nucleotide polymorphisms (SNPs) and constructed a comprehensive Phalaenopsis SNP database of cultivars. These SNPs got a high correlation with variation for quantitative traits ranging from 16.09% to 154.60%, while those for qualitative traits spanned from 20.54% to 130.81%. This database demonstrated a high degree of genetic diversity and a robust capacity for identifying polymorphisms and distinguishing among current varieties. These discovered SNPs consist of 12 types, C/T (23.86%), G/A (22.31%), A/G (8.89%), and T/C (7.84%). The ratio of transition to transversion was approximately 1.70. 70.91% of the SNP loci were in intergenic regions, 9.61% in upstream regions, and 9.37% within intronic regions. Fifty three cultivar PCAs could serve as three groups, which was matched with trait clusters. Based on 5,984 SNP sites, we conducted secondary screening and screened out 14 core sites. The clustering results of the NJ tree based on 14 core SNP loci and the NJ tree based on 5,984 whole genome SNP loci were consistent among 53 Phalaenopsis cultivars. Besides, each variety was then encoded with a unique barcode by 14 core SNP markers. This preliminary approach offers a putative and effective tool for variety identification, genetic analysis, and further development of Phalaenopsis germplasm resources.

Dereje Tulu, Melkam Aleme, Shiferaw Temteme et al.

Cassava (Manihot esculenta Crantz) is a vital staple crop in tropical and subtropical regions. Using cassava both as human food and as feed for eri-silkworms (Samia cynthia ricini Boisduval) offers a sustainable way to increase income and optimize cassava use. This study evaluated the adaptability, leaf productivity, and silk yield of 10 cassava genotypes in Southwest Ethiopia to identify their suitability as eri-silkworm feed. Significant variations were observed among the genotypes in terms of plant height, leaf traits, stem diameter, and dry matter (DM) yield, all of which influenced eri-silkworm growth. Genotype 16301 had the tallest plants, while M94/0117 was the shortest. Eri-silkworm performance, including larval weight, survival, hatchability, and effective rate of rearing (ERR), varied by genotype, likely reflecting differences in leaf nutrition. Notably, genotype Umbure achieved the highest ERR (95.8%), survival rate (94.8%), cocoon weight (1.7 g), pupal weight (1.6 g), shell weight (0.3 g), and silk ratio (14.6%). Umbure’s leaves also had superior nutritional qualities, including high crude protein (28.6%), high in vitro dry matter digestibility, and low fiber content (32.4%), making them an excellent protein source for eri-silkworms. Furthermore, Umbure produced the most tubers per plant and the highest total fresh and DM yields per hectare over 2 years, with Qulle having the greatest tuber count and Umbure producing the longest tubers. These results indicate that genotype Umbure is the most promising cassava variety for silk production due to its nutritional value and favorable traits for eri-silkworm rearing. This study highlights the potential of cassava–eri-silkworm integration to improve farmer income and promote sustainable cassava production. Future research and extension efforts should focus on supporting the adoption of this practice.

Nasrin Banu Khan, Soumya Chatterjee, Ganapati Basak et al.

Reproductive fitness is paramount to a plant’s ecological and evolutionary processes, establishing species persistence, population dynamics, and ecosystem stability. The consequences of a plant’s reduced reproductive fitness extend beyond a single individual and can lead to population decline, genetic erosion, and subsequent impairments to ecosystem services. Air pollution is a critical environmental stressor that adversely impacts plant reproduction. To effectively mitigate the detrimental effects of air pollution on plant reproduction, a comprehensive understanding of these complex interactions is essential. This review comprehensively summarizes the harmful effects of airborne pollutants on multiple stages of plant reproduction. Pollutants have strong effects on phenology either by delaying or by advancing the phenoevents, floral morphology, flower production and increased bud abortion rate. With regard to male fitness in pollutant rich areas, it has been well established that the anther wall, pollen morphology, pollen production, and pollen viability are affected due to pollutant exposure. Only a handful of studies have elucidated the effect of air pollutants (PM, O3 and SO2) on pollen germination and tube growth in the stylar region. Floral cues and incentives also get compromised in polluted areas. Consequently, these affect plant-pollinator interactions thereby hindering successful fertilization and yield. Discrete effects of SO₂, NO₂ and O3 have significant negative correlations with yield in agroecosystem such as fruit-set, seed number and seed weight. The present review provides an insight into the influence of various air pollutants on plant reproduction, acting as a compendium of all work conducted thus far, besides also highlighting lacunae in the field that require attention.

Ruiming Du, Guangxun Zhai, Tian Qiu et al.

The precise characterization of plant morphology provides valuable insights into plant environment interactions and genetic evolution. A key technology for extracting this information is 3D segmentation, which delineates individual plant organs from complex point clouds. Despite significant progress in general 3D computer vision domains, the adoption of 3D segmentation for plant phenotyping remains limited by three major challenges: i) the scarcity of large-scale annotated datasets, ii) technical difficulties in adapting advanced deep neural networks to plant point clouds, and iii) the lack of standardized benchmarks and evaluation protocols tailored to plant science. This review systematically addresses these barriers by: i) providing an overview of existing 3D plant datasets in the context of general 3D segmentation domains, ii) systematically summarizing deep learning-based methods for point cloud semantic and instance segmentation, iii) introducing Plant Segmentation Studio (PSS), an open-source framework for reproducible benchmarking, and iv) conducting extensive quantitative experiments to evaluate representative networks and sim-to-real learning strategies. Our findings highlight the efficacy of sparse convolutional backbones and transformer-based instance segmentation, while also emphasizing the complementary role of modeling-based and augmentation-based synthetic data generation for sim-to-real learning in reducing annotation demands. In general, this study bridges the gap between algorithmic advances and practical deployment, providing immediate tools for researchers and a roadmap for developing data-efficient and generalizable deep learning solutions in 3D plant phenotyping. Data and code are available at https://github.com/perrydoremi/PlantSegStudio.