Search Results (1,898)

The impact of arbuscular mycorrhiza fungi (AMF) on root–shoot scaling strategies under zinc and phosphorus deficiency remains poorly understood in maize. The aims of this study were (i) To quantify the effects of zinc/phosphorus deficiency on AMF colonization, (ii) to quantify biomass accumulation in different plant parts in the presence of AMF, and (iii) to characterize how AMF alter root–shoot allometric scaling under zinc/phosphorus deficiency. We conducted a pot experiment arranged in RCBD split plot with 6 replications. SUWAN 5819 maize seeds were grown for 22 days under five Hoagland’s solution-based nutrient regimes (+Zn+P, −Zn−P, +Zn−P, −Zn+P, and deionized water), with and without AMF. AMF colonization was highest (49.6%) under −Zn+P contrary to hypothesis 1 which predicted highest colonization under dual deficiency, while the deionized water treatment had the lowest colonization (30.1%). Phosphorus was the dominant factor affecting biomass accumulation with a 2–4-fold reduction in organ dry weights for phosphorus-deficient treatments compared to phosphorus-sufficient treatments. AMF colonization significantly reduced dry weights in +Zn+P by 8.6%, 19.0%, and 47.5% in the leaf, stem, and roots, respectively, consistent with mycorrhiza-induced growth depression (MGD). Nutrient deficiency resulted in root biomass accumulation, consistent with the optimal partitioning theory. AMF increased shoot mass fraction from 50% to 63% in +Zn+P, and from 41% to 52.5% in −Zn−P, suggesting AMF role in modulating biomass accumulation. Root–shoot scaling slopes derived from LMM revealed that zinc deficiency caused negative scaling trajectory, and AMF was associated with positive root–shoot scaling trajectory in the −Zn+P treatment, though the scaling relationship was not confirmed by SMA analysis. These findings highlight nutrient specific AMF-mediated growth dynamics in early vegetative stage. Full article

This study examined the effect of east–west orientation of willow tree (Salix alba L.) rows on soil biological activity and weed dynamics in a temperate maize (Zea mays L.) intercropped agroforestry (AF) system in Eastern Hungary. The experiment evaluated how the year (2022, 2023), location (distance from the rows), and irrigation (IR) influenced spatial patterns of earthworm (EW) parameters and weed cover. The study aimed to assess how willow-based AF systems influence soil biological and weed community dynamics under varying IR and row spacing, in comparison with monoculture cropland (MC) systems, and to evaluate their potential role in climate change adaptation in arable farming. Both soil sampling for the EW survey and vegetation studies were conducted along perpendicular transects extending from the tree rows to measure EW abundance and biomass, as well as total weed cover. Experimental results revealed clear spatial gradients in EW distribution and weed abundance near the tree rows, driven by litter input, shading, moisture, and reduced disturbance. These effects were intensified under IR at narrower row spacings. No significant differences were observed between AF-South (shaded), AF-Center, and MC plots; however, significantly higher EW abundance and biomass were found on the AF-North (sunny) side. As for the location, significantly greater total EW abundance was found at AF-North (105.0 individual m⁻²) compared with the MC plots. AF systems enhance soil biological activity and shape weed dynamics through spatial ecological gradients influenced by tree row spacing and irrigation, supporting their role as sustainable land-use systems while emphasizing the need for site-specific management and further long-term optimization. Full article

The switch in land use of abandoned tailings can precondition their reuse as newly built parks. This study investigated the feasibility of reusing a remediated mercury (Hg) retorting site in Wanshan, Guizhou Province, China, as a functional urban park by assessing residual heavy metal risks and associated vegetation responses. Field investigations were conducted across 31 park sites distributed along an east–west geographical gradient from the former mining area to urban parks, using replicated plots to sample the surface soils and dominant plant species. The concentrations of arsenic (As), cadmium (Cd), mercury (Hg), manganese (Mn), and lead (Pb) in soil and plant tissues were quantified using inductively coupled plasma–mass spectrometry, and vegetation structure and diversity were evaluated using standard community indices. The results showed significant spatial variability in soil and plant metal concentrations, with higher levels generally observed near historically impacted areas of the mine. However, all soil metal concentrations were below the national safety thresholds. Plant tissues exhibit controlled metal accumulation within normal or regulated ranges, reflecting the effective screening of tolerant and hyperaccumulating species. Increasing heavy metal concentrations were associated with reduced vegetation coverage, height, and diversity along the gradient. Overall, the findings indicate that the reclaimed Hg retorting site almost met ecological safety requirements, but more data on deep soils, groundwater, and long-term observations are needed to draw more conclusive conclusions. Full article

This study quantified total biomass stocks in Carrasco (CAR, n = 12), a dense tropical deciduous vegetation type from the Brazilian semi-arid region for which biomass information remains scarce. We also evaluated differences in floristic composition, diversity, structure, and biomass allocation patterns relative to Cerrado sensu stricto (CSS, n = 40). Forest inventories were conducted in southeastern Brazil. Woody biomass was estimated using a regional allometric equation. Roots were sampled in a position adjacent to the plots, and litter was collected at the center of each plot using a frame. Necromass was assessed along a linear transect corresponding to the length of each plot using the line-intersect method. Biomass differences between vegetation types were assessed using generalized linear and mixed-effects models (GLMs and GLMMs). Total biomass reached 45.24 Mg ha⁻¹ in CSS and 59.01 Mg ha⁻¹ in CAR. In CSS, woody biomass predominated (20.47 Mg ha⁻¹; 45%), followed by roots (18.47 Mg ha⁻¹; 41%), litter (5.49 Mg ha⁻¹; 12%), and necromass (0.81 Mg ha⁻¹; 2%). In CAR, roots were the dominant component (32.37 Mg ha⁻¹; 55%), followed by woody biomass (16.57 Mg ha⁻¹; 28%), litter (8.39 Mg ha⁻¹; 14%), and necromass (1.68 Mg ha⁻¹; 3%). CSS and CAR shared only 10% of their species and showed significant differences in total biomass (TB) and belowground biomass (BGB), while aboveground biomass (AGB), aboveground woody biomass (AGWB), litter, and necromass did not differ significantly (α = 0.05). The BGB/AGWB ratio was <1 in CSS and >1 in CAR, resembling global patterns of savanna/shrubland and grassland formations, respectively. Considering the sampling design adopted, despite the higher stem density in CAR, larger individuals in CSS compensated for structural differences, resulting in similar aboveground biomass stocks. Our findings reinforce the floristic and structural distinctiveness of Carrasco and reveal contrasting biomass allocation strategies, with a strong dominance of belowground biomass in CAR. These results demonstrate that aboveground-based assessments can substantially underestimate total biomass in semi-arid transitional vegetation and highlight the need to incorporate non-forest ecosystems into biomass inventories, conservation planning, and climate change mitigation strategies. Full article

Fertilizer nitrogen-to-phosphorus (N/P) stoichiometry diverges between soil test recommendations and conventional farmer practices in tropical Asia; however, its associations with labile soil carbon fractions remain poorly characterized. This regional exploratory study quantified N/P input divergence and examined co-occurring soil carbon patterns across four cropping systems in northern Thailand. A fertilizer management dataset of 138 field records was combined with a complementary soil property dataset of 303 topsoil samples (101 plots × 3 management groups: App (soil test-based fertilizer recommendation), Farmer (conventional practice), and NF (No-Fertilizer control)). The two datasets were drawn from the same regional agroecosystem context but were not paired plot-by-plot; therefore, the results are interpreted as associations rather than direct cause–effect linkages. Soil properties included pH, macronutrients, total soil organic carbon (SOC), permanganate-oxidizable carbon (POXC), and oxidizable fractions (labile, less labile, and non-labile) quantified by wet oxidation. The App N/P mass ratios (kg N kg⁻¹ P) exceeded Farmer in all systems, with the greatest divergence in Rice (9.14 vs. 1.83) and Vegetables (7.62 vs. 2.24). Total SOC did not differ among management groups (p = 0.828), but labile carbon (LC) was significantly higher under Farmer (13.59 g kg⁻¹) than under App (7.46) and NF (3.34; p < 0.001), while POXC was elevated under NF and pH under App (both p < 0.001). Management associations were consistent across the soil orders and crop groups. LC and POXC appeared to be more sensitive short-term indicators than bulk SOC in this dataset. Because the soil property dataset is not paired plot-by-plot with the fertilizer dataset, and because management contrasts are also confounded with co-occurring differences in total fertilizer input, organic matter management, residue management, and environmental conditions, the observed associations cannot establish a direct causal role for the N/P ratio per se. The results suggest a possible association between low-N/P farmer fertilization and higher labile carbon in smallholder systems in northern Thailand; confirmation of causal mechanisms requires paired within-plot longitudinal studies. Full article

To explore the distribution patterns of plant communities in southwestern Xizang and their relationships to environmental factors, this study focused on providing a theoretical basis for the conservation of biodiversity and ecological restoration of plant communities in the study area. Based on survey data from 87 sample plots in southwestern Xizang, in this study, two-way indicator species analysis (TWINSPAN) and canonical correspondence analysis (CCA) were employed for quantitative classification and ordination purposes, respectively. Additionally, the diversity of the classified community types obtained was analyzed, along with the factors influencing them. The results indicated that: a total of 295 species of vascular plants belonging to 171 genera and 61 families were recorded in the 87 sample plots; according to TWINSPAN classification, the plants in southwestern Xizang were divided into 17 associations, with the vegetation types being dominated by tussock-forming grass alpine steppes and tussock-forming Kobresia alpine meadows; CCA ordination revealed that the annual average temperature, annual precipitation, and altitude exhibited significant explanatory power; both the α- and β-diversity indices of the coniferous forest community type were the highest, indicating notable community stability; and annual average temperature and annual precipitation significantly affected plant diversity, while the altitude was negatively correlated with the above diversity indices. In summary, the temperature and precipitation were the main environmental factors influencing the composition and distribution of plant communities in southwestern Xizang. The research results could provide a theoretical basis for further investigation and conservation of plant diversity as well as ecological restoration in southwestern Xizang. Full article

Expansion of the global aluminum industry has produced severe landscape degradation through surface bauxite mining and massive accumulation of bauxite residue (red mud). This study explores a circular economy strategy for rehabilitating post-bauxite mining Oxisols in the Tayan Bauxite Mining Cluster (0°02′01″ S, 110°06′07″ E), West Kalimantan, Indonesia, by applying red mud blended with composted cow manure as soil ameliorants. A 6-month field trial using a Randomised Block Design (RBD) (20 plots) assessed the effects of graded red mud–manure combinations on foliar nutrient uptake and vegetative growth of Neolamarckia cadamba (Jabon). Treatment C (1.0 kg red mud + 13.5 kg manure) optimised soil chemical conditions most effectively, yielding the highest foliar macronutrient concentrations per plant (N: 3.47%, P: 0.57%, K: 1.63%) and the greatest height increment (84.99 cm, a 36.9% gain over the unamended control at six months). Higher doses (Treatment D) produced diminishing returns, pointing to an inferred sodium-induced inhibitory threshold based on observed growth responses. These findings indicate that integrating a source of sodium from red mud with organic matter shows strong potential as an effective soil ameliorant for post-mining rehabilitation. The approach supports SDG (Sustainable Development Goals) 12 (Responsible Consumption and Production) by converting industrial waste into a productive soil input, and SDG 15 (Life on Land) by facilitating ecological recovery on degraded mine landscapes. Full article

High-throughput and non-destructive phenotyping approaches are increasingly needed to support precision agriculture and plant breeding. This study evaluates the use of unmanned aerial vehicle (UAV) multispectral imagery combined with machine learning to estimate anthocyanin content in red lettuce genotypes under field conditions. High-resolution RGB and multispectral images were acquired using a low-cost UAV platform, and vegetation indices sensitive to pigment variation were extracted at the plot scale. Ridge regression, decision tree, and random forest models were trained using 80% of the dataset and validated with the remaining 20%. Random forest achieved the highest performance for anthocyanin estimation, with coefficients of determination reaching R² = 0.84 and lower prediction errors than linear approaches. Overall, the results demonstrate that UAV-based multispectral sensing integrated with machine learning provides a robust, scalable, and cost-effective solution for non-destructive pigment phenotyping, with direct applications in biofortification-oriented breeding and precision agriculture. Full article

LAI is a critical parameter for forest management and global ecosystem monitoring. GEDI provides global-scale vegetation structure data, yet its L2B LAI product often exhibits systematic biases. This study investigates the Maoer Mountain forest in China, utilizing a total of 60 validated GEDI footprints as the primary dataset. To address the limitations of the standard GEDI L2B algorithm, which assumes a horizontally uniform canopy, we integrated a four-scale geometric optical model to characterize canopy clumping effects. This model was employed to simulate the geometric proportions of sunlit/shaded canopy and ground components within each footprint to derive a footprint-specific clumping index, thereby refining the gap rate estimates. The accuracy of the revised leaf area index was rigorously verified by using the measured data from the sample plots in the Maoer Mountain area. The results indicate that the original GEDI L2B data underestimates LAI, with a mean absolute error (MAE) of 1.79 m²/m², a root mean square error (RMSE) of 1.47 m²/m², and a bias of −1.25 m²/m². After correcting for canopy clumping, accuracy improved significantly, reducing the MAE to 0.65 m²/m² and the RMSE to 0.82 m²/m², while effectively mitigating underestimation. These findings demonstrate that accounting for non-uniform canopy distribution effectively reduces errors, providing a robust methodological basis for high-precision LAI retrieval using spaceborne lidar. Despite these improvements, this method still has certain limitations: the model’s performance is constrained in extremely steep terrain due to waveform aliasing and in fragmented vegetation areas where sub-footprint heterogeneity is high. Future research should incorporate topographic corrections and multi-source data fusion to enhance the model’s robustness in complex landscapes. Full article

Water shortage severely restricts agricultural output in arid and semi-arid regions, rendering improved irrigation management approaches necessary. This study assessed the hydraulic behavior of furrow irrigation in non-vegetated clay loam soil, investigating the effects of different land slopes (LS) 0, 0.05, and 0.15% and furrow length (FL) 50 and 75 m. In order to do this, field tests were conducted on a privately held farm in Banha, Qalyubia Governorate, Egypt, in March 2024. The experiment utilized a split-plot design with three repetitions, and laser-based land smoothing was used to establish the desired slopes accurately. Key hydraulic variables, namely advance time, recession time, infiltration rate, application efficiency (AE), deep percolation (DP), and distribution uniformity (DU), were recorded and calculated. The field data collected were used to calibrate and validate the WinSRFR model version 5.1.1, and its predictive ability was assessed using the coefficient of determination, root mean square error, Nash–Sutcliffe efficiency, and percent bias. The results showed that shorter FL 50 m paired with steeper gradients (0.15%) achieved better hydraulic outcomes than longer ones (75 m) with gentler slopes. Statistical analysis demonstrated that furrow length exerted a highly significant influence on all hydraulic parameters (p < 0.001). Ground slope also demonstrated a statistically meaningful influence (p < 0.05 to p < 0.01) for selected performance indicators, and the combination of LS and FL was also significant (p < 0.05). The most effective configuration, a 50 m FL paired with a 0.15% LS, yielded the highest DU (90%) and AE (87%) and the smallest DP (6%). The WinSRFR model showed outstanding accuracy in estimating advance times (R² > 0.99, RMSE < 0.55 min) and infiltration depths (R² > 0.98, RMSE < 1.3 mm), and reasonable performance for recession times (R² > 0.87, RMSE < 5.4 min). Consequently, the validated model can be confidently used to design and manage furrow irrigation in clay loam soils. These findings are anticipated to promote sustainable water consumption in farming and provide valuable input for water management policy-making. Full article

Satellite-derived vegetation indices and climate data from 2018 to 2024 were analysed to quantify smallholder agricultural responses to climate variability in two rural villages in the Eastern Cape, South Africa. Using Google Earth Engine, R programming 4.4.0, and ArcGIS Pro 3.6, the study assessed spatiotemporal trends in vegetation condition in relation to bioclimatic variables and plot-scale land ownership. The results showed an overall accuracy of 96%, with producer and user accuracies at 79% and 85%, respectively, and a kappa coefficient of 0.95. Time-series analysis revealed a trend of decreasing rainfall and increasing temperatures across the study area, accompanied by elevated Plant Senescence Reflectance Index (PSRI > 0.294) values indicative of advanced vegetation stress. Spatial analysis showed that valley areas exhibited higher moisture accumulation potential and aligned with drainage networks, reflecting enhanced soil moisture retention relative to surrounding terrain. These findings demonstrate the strong influence of topography-mediated water availability on vegetation health in rain-fed smallholder systems. In accordance with the Sustainable Development Goals, the study stresses the importance of gender equity in combating climate change and achieving food security, highlighting the value of integrating multi-scale remote sensing and climate data to identify localised agricultural vulnerability, and underscores the importance of gender-responsive, climate-aware land management strategies to support food security under changing environmental conditions. By situating smallholder agriculture within a land system science framework, the study advances understanding of how topography-mediated soil moisture retention, climate variability, and gendered land governance jointly shape land system trajectories in communal tenure settings. Full article

Degraded rangelands in semi-arid pastoral systems are widely associated with declining vegetation, soil carbon loss, and worsening household livelihoods. However, the mechanisms linking rangeland degradation to household income remain poorly understood, particularly in a panel-data context. This study examines how rangeland condition, vegetation dynamics, and livestock by-product underutilization are related to household income in Öndörshireet Soum, Töv Aimag, Mongolia. The analysis is based on a multi-source panel dataset covering 2018 to 2024, combining Sentinel-2 NDVI time series, soil organic carbon measurements from 120 permanent plots, and a five-wave survey of 114 households. The results indicate widespread and persistent degradation. Nearly 90 percent of monitored plots are at least moderately degraded; NDVI shows a steady decline over time; and average soil carbon levels remain well below those observed at a managed reference site. Over the same period, real household income declined despite a gradual increase in herd size. Econometric estimates show that vegetation condition is positively associated with income, whereas higher levels of by-product waste are associated with lower income, even after accounting for precipitation variability. The interaction results further suggest that the benefits of herd expansion weaken when production losses remains high. Taken together, these findings indicate that ecological decline and low value capture from livestock operate simultaneously to constrain pastoral livelihoods. Improvements in pasture condition alone appear insufficient to offset these pressures when a substantial share of livestock value is not recovered. While the results offer useful insights for rangeland policy, further evidence from multiple sites would be needed to assess causality and the extent to which these patterns apply beyond a single soum. Full article

Subalpine grasslands (SGs) of the Loess Plateau in China play a crucial role in the global carbon cycle of terrestrial ecosystems. However, the distribution pattern of total carbon stores along an elevation gradient on the SG plants of the eastern plateau remains unclear. In this study, eight typical mountains with one well-developed SG being surveyed as plot for each mountain were selected along an elevation gradient from 1722 m to 2954 m on the east of the plateau. The vegetation area, hydrothermal factors, soil elements, and species composition were analyzed using methods of spatial analysis and a partial least squares structural equation model (PLS-SEM), and these were used to estimate the total carbon stores of different plant functional groups for the entire area of each SG. This study revealed the driving factors of the elevational pattern of plant carbon storage in the SGs. The entire plant carbon storage of the eight SGs was 35,880.98 Mg in total. In addition, the aboveground and belowground carbon storage values both exhibited U-shaped trends along the elevation gradient. Significant minimum values were observed at the mid-elevation regions, ranging from 2305 m to 2673 m. The plant carbon storage was predominantly allocated to the belowground portions (accounting for 72.3% of the total carbon storage), and this allocation strategy was more pronounced at both low- and high-elevation regions. The carbon storage proportion among the different plant functional groups was the largest for forbs (average in 2348.85 Mg, accounting for 52%), medium for sedges (average in 1982.81 Mg, accounting for 44%), and the smallest for grasses (average in 153.47 Mg, accounting for 4%). The plant species diversity promoted carbon accumulation in the sedges and forbs, while the soil total phosphorus exhibited an inhibitory effect. In the PLS-SEM, hydrothermal factors (total effect = −0.8107) and species diversity (total effect = 0.4969) were the primary drivers of the plant carbon storage elevational pattern in the SGs, while the soil properties (total effect = −0.3501) and biomass (total effect = 0.0697) effects did not reach statistical significances. Therefore, the plant carbon storage distribution pattern along the elevation gradient was driven by hydrothermal factors and species diversity on the SGs of the eastern plateau. The plants such as forbs and sedges might play more important roles in improving regional plant carbon storage in high-elevation grasslands, through interactions with hydrothermal factors. Full article

Under the background of global climate change and China’s “carbon peak and carbon neutrality” strategy, it is of great significance to assess the carbon sink benefits of urban park plant communities. This study took 20 plant community plots of 20 m × 20 m (400 m²) in Tientsin Water Park as the research object. Carbon sequestration capacity was characterized by carbon stock (CS) and annual carbon sequestration (ACS), and six community structure indicators were quantified: Vegetation Coverage (VC), Canopy Density (CD), Three-Dimensional Green Volume (3DGV), Tree-to-Shrub Ratio (TSR), Vertical Complexity (CV), and Number of Individuals (N). Spearman correlation analysis, principal component analysis, and regression analysis were adopted, and K-means clustering was introduced to identify vegetation structure–function groups, thereby exploring the statistical correlations between these structural characteristic indicators and carbon sink capacity indicators (CS and ACS). The results showed that (1) VC, CD, and 3DGV were significantly positively correlated with CS, suggesting that these factors may be more conducive to long-term carbon pool accumulation; (2) N was significantly positively correlated with ACS, and a nonlinear decreasing trend was observed in the current observation data; (3) the influence of TSR and CV on carbon storage and sequestration also showed a nonlinear correlation. Based on the above correlation findings, the community combinations with higher carbon sink performance in this case were screened out. And suggestions for low-carbon configuration of plant communities, centered on optimizing canopy structure, configuring high-carbon-sequestration tree species, and regulating reasonable density, were proposed, which can be used as a reference for forming hypotheses in subsequent confirmatory studies. Full article

Mediterranean phryganic ecosystems have been shaped for centuries by recurrent herbivory, yet the long-term ecological consequences of grazing cessation remain insufficiently resolved, particularly in protected island landscapes where conservation management often assumes that exclusion promotes recovery. In these drylands, the removal of grazing redirect assembly processes through shifts in dominance, heterogeneity, and functional strategy expression. Here, we use more than three decades-long grazing discontinuity within the Petrified Forest of Lesvos, an insular Mediterranean geopark, to examine how long-term herbivore exclusion reorganizes plant communities across taxonomic and functional dimensions. By integrating floristic inventories, multivariate community analysis, mixed-effects modeling, indicator species analysis, and community-weighted trait approaches, we reconstruct the ecological signature of grazing release in phryganic ecosystems. Long-term exclusion was associated with a broader species pool and a greater representation of protected taxa, while ungrazed communities exhibited lower Shannon and Simpson diversity, greater compositional dispersion, and a marked shift in dominance structure linked to the expansion of Sarcopoterium spinosum. Community differentiation was accompanied by directional reorganization of functional trait structure, with ungrazed plots characterized by taller vegetation and increased leaf and inflorescence length, indicating release from recurrent biomass removal and a transition toward more structurally expansive strategies. These results show that grazing exclusion does not simply enhance biodiversity, but reorganizes Mediterranean plant communities into an alternative ecological state shaped by altered competitive hierarchies, shrub-mediated filtering, and relaxed herbivory. In disturbance-structured island ecosystems, therefore, the ecological outcomes of protection depend not only on whether grazing is removed, but on how strongly community organization has historically depended on its continued presence. Full article