Search Results (2,412)

Plants and insects are developing strategies to avoid each other’s defense systems. Host plants may release volatile compounds to attract the natural enemies of herbivores; insect pests may also select host plants that are deterrent to natural enemies to avoid such predation. Here we investigated whether the host plant preference of Hyphantria cunea correlates with the attractiveness of these plants to Chouioia cunea, a parasitoid wasp that serves as the primary natural enemy of H. cunea. We found Morus alba was the preferred host plant for female H. cunea. Although M. alba provided suboptimal nutritional value for H. cunea growth and development compared to other plants, it attracted fewer C. cunea relative to alternative host plants. Gas chromatography–mass spectrometry (GC–MS) coupled with gas chromatography–electroantennographic detection (GC-EAD) analysis identified six distinct compounds among the herbivore-induced plant volatiles (HIPVs) produced following H. cunea feeding. Notably, M. alba was the sole plant species that did not emit tridecane. These results suggest that H. cunea utilizes M. alba as a reduced predation enemy-free space, thereby minimizing parasitization by C. cunea. Our research emphasizes the importance of considering adaptive responses of herbivores within the context of multi-trophic relationships, rather than solely focusing on optimizing herbivore growth on the most nutritionally suitable plant host. Full article

The surface of the Great Wall harbors a large number of non-vascular plants dominated by cyanobacteria, lichens and mosses as well as microorganisms, and form biocrusts by cementing with the soils and greatly alters the pore structure of the soil and the ecohydrological processes associated with the soil pore space, and thus influences the soil resistance to erosion. However, the microscopic role of the biocrusts in influencing the pore structure of the surface of the Great Wall is not clear. This study chose the Warring States Qin Great Wall in Weiyuan, Gansu Province, China, as research site to quantify thepore structure characteristics of the three-dimensional of bare soil, cyanobacterial-lichen crusts, and moss crusts at the depth of 0–50 mm, by using optical microscopy, scanning electron microscopy, and X-ray computed tomography and image analysis, and the precipitation infiltration process. The results showed that the moss crust layer was dominated by large pores with long extension and good connectivity, which provided preferential seepage channels for precipitation infiltration, while the connectivity between the cyanobacterial-lichen crust voids was poor; The porosity of the cyanobacterial-lichen crust and the moss crust was 500% and 903.27% higher than that of the bare soil, respectively. The porosity of the subsurface layer of cyanobacterial-lichen crust and moss crust was significantly lower than that of the biocrusts layer by 92.54% and 97.96%, respectively, and the porosity of the moss crust was significantly higher than that of the cyanobacterial-lichen crust in the same layer; Cyanobacterial-lichen crusts increased the degree of anisotropy, mean tortuosity, moss crust reduced the degree of anisotropy, mean tortuosity. Biocrusts increased the fractal dimension and Euler number of pores. Compared with bare soil, moss crust and cyanobacterial-lichen crust increased the isolated porosity by 2555% and 4085%, respectively; Biocrusts increased the complexity of the pore network models; The initial infiltration rate, stable infiltration rate, average infiltration rate, and the total amount of infiltration of moss crusted soil was 2.26 and 3.12 times, 1.07 and 1.63 times, respectively, higher than that of the cyanobacterial-lichen crusts and the bare soil, by 1.53 and 2.33 times, and 1.13 and 2.08 times, respectively; CT porosity and clay content are significantly positively correlated with initial soil infiltration rate (|r| ≥ 0.85), while soil type and organic matter content are negatively correlated with initial soil infiltration rate. The soil type and bulk density are directly positively and negatively correlated with CT porosity, respectively (|r| ≥ 0.52). There is a significant negative correlation between soil clay content and porosity (|r| = 0.15, p < 0.001). Biocrusts alter the erosion resistance of rammed earth walls by affecting the soil microstructure of the earth’s great wall, altering precipitation infiltration, and promoting vascular plant colonisation, which in turn alters the erosion resistance of the wall. The research results have important reference for the development of disposal plans for biocrusts on the surface of archaeological sites. Full article

Carbon (C) sequestration and nitrogen (N) and phosphorus (P) accumulation in urban forest green spaces are significant for global climate regulation and alleviating nutrient pollution. However, the effects of management and conservation practices across different urban forest vegetation types on soil C, N, and P contents and stoichiometric ratios remain largely unexplored. We selected forest soils from Guangzhou, a major Metropolis in China, as our study area. Soil samples were collected from two urban secondary forests that naturally regenerated after disturbance (108 samples) and six urban forest parks primarily composed of artificially planted woody plant communities (72 samples). We employed mixed linear models and variance partitioning to analyze and compare soil C, N, and P contents and their stoichiometry and its main driving factors beneath suburban forests and urban park vegetation. These results exhibited that soil pH and bulk density in urban parks were higher than those in suburban forests, whereas soil water content, maximum storage capacity, and capillary porosity were higher in urban forests than in urban parks. Soil C, N, and P contents and their stoichiometry (except for N:P ratio) were significantly higher in suburban forests than in urban parks. Multiple analyzes showed that soil pH had the most pronounced negative influence on soil C, N, C:N, C:P, and N:P, but the strongest positive influence on soil P in urban parks. Soil water content had the strongest positive effect on soil C, N, P, C:N, and C:P, while soil N:P was primarily influenced by the positive effect of soil non-capillary porosity in suburban forests. Overall, our study emphasizes that suburban forests outperform urban parks in terms of carbon and nutrient accumulation, and urban green space management should focus particularly on the impact of soil pH and moisture content on soil C, N, and P contents and their stoichiometry. Full article

Proanthocyanidins are a subclass of flavonoids formed through a poorly understood polymerization process that forms chains of 3–30 catechins and epi-catechins. Proanthocyanidins serve as UV protectants and antifeedants that accumulate in diverse plant species, including the lotus. To identify candidate genes underlying proanthocyanidin synthesis and polymerization, we generated and functionally annotated transcriptomes from seedpods and seed epicarps of two lotus cultivars, “Guoqing Hong” and “Space Lotus”, which accumulate markedly divergent proanthocyanidin levels across the immature, near-mature, and mature developmental stages. Our transcriptome analysis was based on a total of 262.29 GB of raw data. We aligned the transcriptome data with the lotus genome and obtained an alignment efficiency that ranged from 91.74% to 96.44%. Based on the alignment results, we discovered 4774 new genes and functionally annotated 3232 genes. A total of 14,994 differentially expressed genes (DEGs) were identified from two-by-two comparisons of transcript libraries. We found 61 DEGs in the same developmental stage in the same tissue of different species. Comparative transcriptome analysis of seedpods and seed epicarps from two cultivars identified 14,994 differentially expressed genes (DEGs), of which 10 were functionally associated with proanthocyanidin synthesis and 9 were possibly implicated in the polymerization reactions. We independently quantified the expression of the candidate genes using qRT-PCR. Significant differences in the expression of candidate genes in different tissues and periods of lotus species are consistent with particular genes contributing to the polymerization of catechins and epi-catechins into proanthocyanidins in lotus seedpods and seed epicarps. Full article

Virtual power plants (VPPs) coordinate distributed energy resources (DERs) to collectively meet grid dispatch instructions. When a dispatch command is issued to a VPP, it must be disaggregated optimally among the individual DERs to minimize overall operational costs. However, existing methods for VPP dispatch instruction disaggregation often require solving complex optimization problems for each instruction, posing challenges for real-time applications. To address this issue, we propose a multi-parametric programming-based method that yields an explicit mapping from any given dispatch instruction to an optimal DER-level deployment strategy. In our approach, a parametric optimization model is formulated to minimize the dispatch cost subject to DER operational constraints. By applying Karush–Kuhn–Tucker (KKT) conditions and recursively partitioning the DERs’ adjustable capacity space into critical regions, we derive analytical expressions that directly map dispatch instructions to their corresponding resource allocation strategies and optimal scheduling costs. This explicit solution eliminates the need to repeatedly solve the optimization problem for each new instruction, enabling fast real-time dispatch decisions. Case study results verify that the proposed method effectively achieves the cost-efficient and computationally efficient disaggregation of dispatch signals in a VPP, thereby improving its operational performance. Full article

Bird-dropping fouling and hotspot anomalies remain the most prevalent and detrimental defects in utility-scale photovoltaic (PV) plants; their co-occurrence on a single module markedly curbs energy yield and accelerates irreversible cell degradation. However, markedly disparate visual–thermal signatures of the two phenomena impede high-fidelity concurrent detection in existing robotic inspection systems, while stringent onboard compute budgets also preclude the adoption of bulky detectors. To resolve this accuracy–efficiency trade-off for dual-defect detection, we present YOLOv8-SG, a lightweight yet powerful framework engineered for mobile PV inspectors. First, a rigorously curated multi-modal dataset—RGB for stains and long-wave infrared for hotspots—is assembled to enforce robust cross-domain representation learning. Second, the HSV color space is leveraged to disentangle chromatic and luminance cues, thereby stabilizing appearance variations across sensors. Third, a single-head self-attention (SHSA) block is embedded in the backbone to harvest long-range dependencies at negligible parameter cost, while a global context (GC) module is grafted onto the detection head to amplify fine-grained semantic cues. Finally, an auxiliary bounding box refinement term is appended to the loss to hasten convergence and tighten localization. Extensive field experiments demonstrate that YOLOv8-SG attains 86.8% mAP@0.5, surpassing the vanilla YOLOv8 by 2.7 pp while trimming 12.6% of parameters (18.8 MB). Grad-CAM saliency maps corroborate that the model’s attention consistently coincides with defect regions, underscoring its interpretability. The proposed method, therefore, furnishes PV operators with a practical low-latency solution for concurrent bird-dropping and hotspot surveillance. Full article

The global rise in urban-related health issues poses significant challenges to public health, particularly in cities facing socio-economic crises. In Lebanon, 70% of the population is experiencing financial hardship, and healthcare costs have surged by 172%, exacerbating the strain on medical services. Given these conditions, improving the quality and accessibility of green spaces offers a promising avenue for alleviating mental health issues in urban areas. This study investigates the psychological impact of nine urban public spaces in Beirut through a comprehensive survey methodology, involving 297 participants (locals and tourists) who rated these spaces using Likert-scale measures. The findings reveal location-specific barriers, with Saanayeh Park rated highest in quality and Martyr’s Square rated lowest. The analysis identifies facility quality as the most significant factor influencing space quality, contributing 73.6% to the overall assessment, while activity factors have a lesser impact. The study further highlights a moderate positive association (Spearman’s rho = 0.30) between public space quality and mental well-being in Beirut. This study employs a hybrid methodology combining Research for Design (RfD) and Research Through Designing (RTD). Empirical data informed spatial strategies, while iterative design served as a tool for generating context-specific knowledge. Design enhancements—such as sensory plantings, shading systems, and social nodes—aim to improve well-being through better public space quality. The proposed interventions support mental health, life satisfaction, climate resilience, and urban inclusivity. The findings offer actionable insights for cities facing public health and spatial equity challenges in crisis contexts. Full article

To elucidate the photosynthetic physiological mechanisms influencing alfalfa (Medicago sativa L.) yield and quality under varying planting densities, the cultivar ‘Zhongmu No.1’ was used as experimental material. The effects of different row spacing (R1, R2, R3) and seeding rate (S1, S2, S3, S4, S5) combinations on chlorophyll content (ChlM), nitrogen flavonol index (NFI), chlorophyll fluorescence parameters, forage quality, and hay yield were systematically analyzed. Results showed that alfalfa under R1S3 treatment achieved peak values for ChIM, NFI, EE, and hay yield, whereas R1S4 treatment yielded the highest Fv/Fm and CP content. Redundancy analysis further indicated that yield was most strongly associated with ChlM, NFI, Y (II), and qP. Y (II), and qP significantly influenced alfalfa forage quality, exerting negative effects on ADF and NDF, while demonstrating positive effects on CP and EE. In conclusion, narrow row spacing (15 cm) with moderate seeding rates (22.5–30 kg·hm⁻²) optimizes photosynthetic performance while concurrently enhancing both productivity and forage quality in alfalfa cultivated, establishing a theoretical foundation for photosynthetic regulation in high-quality and high-yield alfalfa cultivation. Full article

This study examines the impact of vegetation structure on bird species richness and diversity across four urban parks in Chaoyang District, Beijing. Throughout the year, using the Point Count Method (PCM), a total of 68 bird species and 4279 individual observations were recorded, with surveys conducted across all four seasons to capture seasonal variations. The parks with more complex vegetation, such as those with a higher tree canopy cover of species like poplars, ginkgo, and Chinese pines, exhibited higher bird species richness. For example, Olympic Forest Park, with its dense vegetation structure, hosted 42 species, whereas parks with less diverse vegetation supported fewer species. An analysis using PERMANOVA revealed that bird communities in the four parks were significantly different from each other (F = 2.76, p = 0.04075), and every comparison between parks showed significant differences as well (p < 0.001). Variations in the arrangement and level of disturbance within different plant communities likely cause such differences. Principal component analysis (PCA) identified tree canopy cover and shrub density as key drivers of bird diversity. These findings underscore the importance of preserving urban green spaces, particularly those with a diverse range of native tree species, to conserve biodiversity and mitigate the adverse effects of urbanisation. Effective vegetation management strategies can enhance avian habitats and provide ecological and cultural benefits in urban environments. Full article

Winter squash (Cucurbita moschata Duchesne.) is a vegetable of high socioeconomic importance owing to the nutritional quality of its fruits, seeds, and seed oil. This study aims to review the main aspects related to the characterization, conservation, and breeding of C. moschata, emphasizing the studies with C. moschata accessions maintained by the Vegetable Germplasm Bank of the Federal University of Viçosa (BGH-UFV). Studies on C. moschata germplasm have reported high variability, particularly in Brazil. Currently, Brazil maintains six Cucurbita germplasm collections, kept in research and teaching institutions. The BGH-UFV collection, one of the largest in the country, contains approximately 350 accessions of C. moschata, mostly landraces collected from all over Brazil. Studies characterizing this germplasm have identified promising genotypes as sources of alleles for increasing the carotenoid content in the fruit pulp and oleic acid content in the seed oil. As part of a breeding program to increase seed oil productivity and improve the oil profile, studies with the BGH-UFV germplasm have identified C. moschata genotypes with seed oil productivity of up to 0.27 t ha⁻¹ and accessions producing oil with high oleic acid content (21 to 28%). The genetic breeding program of C. moschata conducted at the UFV has prioritized the development of compact growth habit genotypes to reduce plant spacing and increase seed and oil productivity. The works involving the collection of C. moschata maintained by the BGH-UFV corroborates the importance of this germplasm as a source of alleles for improving seed oil productivity and the oil profile. Full article

Urbanization’s environmental challenges have increased interest in urban biodiversity, traditionally focused on public green spaces, which are shrinking as urban growth escapes government control. This study examines the understudied role of private actors—specifically Concessions held by Catholic Religious Groups (CRGs)—in biodiversity conservation across three DRC cities (Bukavu, Kisangani, Lubumbashi). CRGs were selected due to Catholicism’s dominance and socio-economic influence in the DRC. A systematic flora inventory of 70 randomly sampled CRGs identified 220 species from 76 families and 185 genera. Although the CRG area was smaller in Lubumbashi (1.1 ha) than Bukavu (3.7 ha) and Kisangani (5.2 ha), the area did not correlate with species richness. Plant composition varied significantly within and between cities, dominated by phanerophytes and exotic species. These findings underscore the importance of including private stakeholders in urban biodiversity conservation. Full article

Niche complementarity is suggested to be a main driver of productivity overyielding in diverse environments due to enhanced resource use efficiency and reduced competition. Here, we combined multiple different approaches to demonstrate that niche overlap is the most likely cause to explain a lack of overyielding of three tree species when grown in different species combinations. First, in an experimental planting we found no relationship between productivity and species diversity for leaf, wood, or root production (no slope was significantly different from zero), suggesting a lack of niche differences among species. Second, data extracted from the United States Department of Agriculture Forest Inventory and Analysis revealed that the species do not significantly co-occur in natural stands (p = 0.4065) as would be expected if coexistence was common across their entire range. Third, we compared trait differences among our species and found that they are not significantly different in multi-dimensional trait space (p = 0.1724). By combining multiple analytical approaches, we provide evidence of potential niche overlap that precludes coexistence and a positive diversity–productivity relationship between these three tree species. Full article

The spatial distribution of ephemeral and perennial dryland plant species is increasingly modified and restricted by ever-changing climates and development expansion. At the interface of biodiversity conservation and developmental planning in desert landscapes is the growing need for adaptable tools in identifying and monitoring these ecologically fragile plant assemblages, habitats, and, often, heritage sites. This study evaluates usage of Sentinel-2 time series composite imagery to discriminate vegetation assemblages in a hyper-arid landscape. Spatial predictor spaces were compared to classify different vegetation communities: spectral components (PCs), vegetation indices (VIs), and their combination. Further, the uncertainty in discriminating field-verified vegetation assemblages is assessed using Shannon entropy and intensity analysis. Lastly, the intensity analysis helped to decipher and quantify class transitions between maps from different spatial predictors. We mapped plant assemblages in 2022 from combined PCs and VIs at an overall accuracy of 82.71% (95% CI: 81.08, 84.28). A high overall accuracy did not directly translate to high class prediction probabilities. Prediction by spectral components, with comparably lower accuracy (80.32, 95% CI: 78.60, 81.96), showed lower class uncertainty. Class disagreement or transition between classification models was mainly contributed by class exchange (a component of spatial allocation) and less so from quantity disagreement. Different artefacts of vegetation classes are associated with the predictor space—spectral components versus vegetation indices. This study contributes insights into using feature extraction (VIs) versus feature selection (PCs) for pixel-based classification of plant assemblages. Emphasising the ecologically sensitive vegetation in desert landscapes, the study contributes uncertainty considerations in translating optical satellite imagery to vegetation maps of arid landscapes. These are perceived to inform and support vegetation map creation and interpretation for operational management and conservation of plant biodiversity and habitats in such landscapes. Full article

Precise monitoring of vegetative growth is essential for assessing crop responses to environmental changes. Conventional methods of geometric characterization of plants such as RGB imaging, multispectral sensing, and manual measurements often lack precision or scalability for growth monitoring of rice. LiDAR offers high-resolution, non-destructive 3D canopy characterization, yet applications in rice cultivation across different growth stages remain underexplored, while LiDAR has shown success in other crops such as vineyards. This study addresses that gap by using LiDAR for geometric characterization of rice plants at early, middle, and late growth stages. The objective of this study was to characterize rice plant geometry such as plant height, canopy volume, row distance, and plant spacing using the proximal LiDAR sensing technique at three different growth stages. A commercial LiDAR sensor (model: VPL−16, Velodyne Lidar, San Jose, CA, USA) mounted on a wheeled aluminum frame for data collection, preprocessing, visualization, and geometric feature characterization using a commercial software solution, Python (version 3.11.5), and a custom algorithm. Manual measurements compared with the LiDAR 3D point cloud data measurements, demonstrating high precision in estimating plant geometric characteristics. LiDAR-estimated plant height, canopy volume, row distance, and spacing were 0.5 ± 0.1 m, 0.7 ± 0.05 m³, 0.3 ± 0.00 m, and 0.2 ± 0.001 m at the early stage; 0.93 ± 0.13 m, 1.30 ± 0.12 m³, 0.32 ± 0.01 m, and 0.19 ± 0.01 m at the middle stage; and 0.99 ± 0.06 m, 1.25 ± 0.13 m³, 0.38 ± 0.03 m, and 0.10 ± 0.01 m at the late growth stage. These measurements closely matched manual observations across three stages. RMSE values ranged from 0.01 to 0.06 m and r² values ranged from 0.86 to 0.98 across parameters, confirming the high accuracy and reliability of proximal LiDAR sensing under field conditions. Although precision was achieved across growth stages, complex canopy structures under field conditions posed segmentation challenges. Further advances in point cloud filtering and classification are required to reliably capture such variability. Full article

Urbanization poses mental health risks for urban dwellers, whereas natural environments offer mental health benefits by providing restorative experiences through visual stimuli. While urban waterfront spaces are recognized for their mental restorative potential, the specific environmental features and individual visual behaviors that drive these benefits remain inadequately understood. Grounded in restorative environments theory, this study investigates how these factors jointly influence restoration. Employing a controlled laboratory experiment, subjects viewed real-life images of nine representative spatial locations from the waterfront space of Guangzhou Long Bund. Data collected during the multimodal experiments included subjective scales data (SRRS), physiological measurement data (SCR; LF/HF), and eye-tracking data. Key findings revealed the following: (1) The element visibility rate and visual characteristics of plant and building elements significantly influence restorative benefits. (2) Spatial configuration attributes (degree of enclosure, spatial hierarchy, and depth perception) regulate restorative benefits. (3) Visual behavior patterns (attributes of fixation points, fixation duration, and moderate dispersion of fixations) are significantly associated with restoration benefits. These findings advance the understanding of the mechanisms linking environmental stimuli, visual behavior, and psychological restorative benefits. They translate into evidence-based design principles for urban waterfront spaces. This study provides a refined perspective and empirical foundation for enhancing the restorative benefits of urban waterfront spaces through design. Full article