Search Results (51)

Forest biomass is closely related to carbon sequestration capacity and can reflect the level of forest management. This study utilizes four machine learning algorithms, namely Multivariate Stepwise Regression (MSR), K-Nearest Neighbors (k-NN), Artificial Neural Network (ANN), and Random Forest (RF), to estimate forest aboveground biomass (AGB) in Chenzhou City, Hunan Province, China. In addition, a canopy height model, constructed from a digital surface model (DSM) derived from Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) and an ICESat-2-corrected SRTM DEM, is incorporated to quantify its impact on the accuracy of AGB estimation. The results indicate the following: (1) The incorporation of multi-source remote sensing data significantly improves the accuracy of AGB estimation, among which the RF model performs the best (R² = 0.69, RMSE = 24.26 t·ha⁻¹) compared with the single-source model. (2) The canopy height model (CHM) obtained from InSAR-LiDAR effectively alleviates the signal saturation effect of optical and SAR data in high-biomass areas (>200 t·ha⁻¹). When FCH is added to the RF model combined with multi-source remote sensing data, the R² of the AGB estimation model is improved to 0.74. (3) In 2018, AGB in Chenzhou City shows clear spatial heterogeneity, with a mean of 51.87 t·ha⁻¹. Biomass increases from the western hilly part (32.15–68.43 t·ha⁻¹) to the eastern mountainous area (89.72–256.41 t·ha⁻¹), peaking in Dongjiang Lake National Forest Park (256.41 t·ha⁻¹). This study proposes a comprehensive feature integration framework that combines red-edge spectral indices for capturing vegetation physiological status, SAR-derived texture metrics for assessing canopy structural heterogeneity, and canopy height metrics to characterize forest three-dimensional structure. This integrated approach enables the robust and accurate monitoring of carbon storage in subtropical forests. Full article

Cotton root systems sustain photosynthesis by nutrient uptake and coordinate with above-ground growth to influence yield. This study explored the effects of fulvic acid (FA) and phosphorus (P) fertilizers on the relationships between cotton photosynthetic capacity (CAP) and root carbohydrate metabolism. A field experiment was conducted including five treatments: no P fertilizer (CK), 105 kg P₂O₅ ha⁻¹ (P1), 150 kg P₂O₅ ha⁻¹ (P2), 105 kg P₂O₅ ha⁻¹ + FA (FP1), and 150 kg P₂O₅ ha⁻¹ + FA (FP2). Results found that FP2 showed the most significant advantage, ensuring a suitable leaf area index (LAI) and cotton fractional interception of photosynthetically active radiation (IPAR) and consequently maintaining a high CAP. Compared with FP2, FP1 resulted in an increase in the boll loading of the root system (BLR) by 8.1% and the boll capacity of the root system (BCR) by 9.3%. From the peak flowering stage to the peak boll setting stage, sucrose and starch contents in FP1 were 6.2–19.2% and 26.5–27.9% lower than those in FP2, respectively. Conversely, fructose and glucose contents in FP1 were 6.4–10.8% and 7.2–8.8% higher than in FP2. The cotton reproductive organ biomass was increased by 11.1% and 14.7% relative to FP2. Moreover, FP1 achieved the highest yield, with an increase of 8.5% and 11.0% compared with P2 and FP2, respectively. Taken together, our study suggests that application of FP1 (105 kg P₂O₅ ha⁻¹ + FA) could be a proper P fertilization method in cotton production of saline-alkali and arid regions. Full article

Climate change significantly influences plants’ physiology, flowering phenology, and nectar production, affecting pollinator interactions and apicultural sustainability. This study examines the physiological responses of Pseudolysimachion rotundum (Nakai) Holub var. subintegrum (Nakai) T.Yamaz. (Plantaginaceae) under projected climate change scenarios, focusing on flowering traits, nectar secretion, and honey production potential. Elevated CO₂ levels enhanced its net photosynthesis and water-use efficiency, supporting sustained carbohydrate assimilation and promoting aboveground biomass accumulation. However, the increased nitrogen demand for vegetative growth and inflorescence production may have led to reduced allocation of nitrogen to the nectar, contributing to a decline in its amino acid concentrations. The flowering period advanced with rising temperatures, with peak bloom occurring up to four days earlier under the SSP5 conditions. While the nectar secretion per flower remained stable, an increase in floral abundance led to a 3.8-fold rise in the estimated honey production per hectare. The analysis of the nectar’s composition revealed that sucrose hydrolysis intensified under higher temperatures, shifting the nectar toward a hexose-rich profile. Although nectar quality slightly declined due to reductions in sucrose and nitrogen-rich amino acids, phenylalanine—the most preferred amino acid by honeybees—remained dominant across all scenarios. These findings confirm the strong climate resilience of P. rotundum var. subintegrum, highlighting its potential as a sustainable nectar source in future apicultural landscapes. Given the crucial role of nitrogen in both plant growth and nectar composition, future research should explore soil nitrogen dynamics and plant nitrogen metabolism to ensure long-term sustainability in plant–pollinator interactions and apicultural practices. Full article

High pH, ${\mathrm{Na}}^{+}$, and $({\mathrm{CO}}_3^{2-}+{\mathrm{HCO}}_3^{-}$) are the primary characteristics of soda saline–alkali soil. Current strategies for ameliorating soda saline–alkali soil often involve the combined use of cow manure and maize straw, the addition of biochar (BC), and the inoculation of Bacillus subtilis (BS). In this study, B. subtilis-loaded biochar (BSC) was prepared using an adsorption technique. An incubation experiment was conducted. The treatments were as follows: soda saline–alkali soil amended with maize straw and cow manure (T₁), which was used as a control; T₁ supplemented with earthworms (T₂); and T₂ supplemented with BS (T₃), BC (T₄), or BSC (T₅). After a 60-day incubation, T₅ showed the most significant reduction in pH, ESP, and (${\mathrm{H}\mathrm{C}\mathrm{O}}_3^{-}$ + ${\mathrm{C}\mathrm{O}}_3^{2-}$) concentrations, with reductions of 0.24 units, 3.26%, and 120 mg kg⁻¹, respectively, compared to the T₁ treatment. The content of soil humic acid, available potassium, and available nitrogen and the activities of β-glucosidase and urease were highest in T₅, increasing by 33.5%, 70.1%, 26.1%, 19.0%, and 17.9%, respectively. Microbial sequencing analysis revealed that the Bacillus abundance in T₃ was highest during the first 45 days (2.51–3.65%), while the Bacillus abundance in T₅ peaked at 3.22% after the 60-day incubation. The soil that was cultivated for 60 days in the experiments was then used for planting alfalfa. T₅ showed the highest alfalfa aboveground biomass and peroxidase, increasing by 30.1% and 73.1%, respectively, compared with T₁. This study demonstrated that loading onto biochar is beneficial for the survival of B. subtilis in soda saline–alkali soil. When traditional organic materials are used, the combination of earthworms and B. subtilis-loaded biochar significantly alleviates the constraints of soda saline–alkali soil. Full article

This study investigated the long-term (70 years) effects of N fertilisation (ammonium nitrate [AN], ammonium sulphate [AS]) at 70 and 211 kg N kg/ha, and liming (L) on plant–microbial interaction and soil carbon stability in a semi-arid grassland in South Africa. Aboveground biomass increased with N addition, particularly AN211, showing a 119% increase compared to the control, while both liming and N applications increased belowground biomass. Nitrogen addition significantly altered plant stoichiometric ratios, with root N ratios showing greater treatment-induced variation (12.7–51.3) than shoot N ratios (10.2–16.8). Microbial biomass carbon peaked with AN70 treatment, while dehydrogenase activity was highest in lime-only plots but suppressed in non-limed N treatments. Conversely, urease activity was highest in the control group and suppressed in most fertilised treatments. Despite increased biomass production, SOC remained unchanged across treatments (49.7–57.6 g/kg), whereas soil pH was lowest (<3.5) and highest (>6) under N fertilisation and lime, respectively. PCA revealed distinct clustering of treatments, with N forms differentially affecting plant allocation patterns and microbial parameters. This study demonstrates that plant–soil–microbe stoichiometric imbalances and pH-induced limitations on microbial function explain the disconnect between plant productivity and carbon sequestration in this semi-arid grassland ecosystem. Full article

Young forest stands from natural regeneration are characterized by high competitive pressure and dynamic changes over time, especially in the initial growth stages. Despite their increasing area in the temperate zone, they have received significantly less scientific attention than old forest stands. Therefore, our research was conducted on young, over-dense European beech (Fagus sylvatica L.) forest originating from natural regeneration, grown in central Slovakia, Western Carpathians. Repeated measurements of tree height and stem diameter measured on the base within a beech stand revealed significant temporal changes in their relationship. Over 16 years, height increased more than stem diameter. Both Lorey’s height and mean diameter d₀ showed continuous growth, with Lorey’s height increasing 3.5-fold and mean diameter increasing 2.8-fold. The height-to-diameter ratio increased until stand age 15, then briefly declined before rising again. Stand density decreased over time, with the sharpest decline occurring between ages 15 and 16 (dropping from 843 to 599 trees per 100 m²). Mortality rates peaked at age 16, with an average annual rate of 9.4% over the entire observation period (2008–2023). Specific leaf area (SLA) was negatively related to tree size, and its value was smaller in 10- than in 20-year-old stands. The increase in SLA was driven by greater leaf area relative to leaf weight. Additionally, allometric relationships showed that branch and leaf contributions to aboveground biomass decreased with tree size within the stand but were greater in the older stand than in the younger growth stage. Estimated aboveground biomass was 667 ± 175 kg per 100 m² in the 10-year-old stand and 1574 ± 382 kg per 100 m² in the 20-year-old stand, with stems contributing the majority of biomass. Leaf Area Index (LAI) remained similar across both stand ages, while the Leaf Area Ratio (LAR) was nearly twice as high in the younger stand. These findings highlight dynamic shifts in beech stand structure, biomass allocation, and leaf traits over time, reflecting growth patterns and competition effects. The outputs indicate that competition in young forest stands is a dominant force in tree mortality. Understanding key interactions in young stands is crucial for sustainable forest management, as these interactions influence long-term stand stability and ecosystem functions. Full article

Forests mitigate greenhouse gas (GHG) emissions by capturing CO₂ and storing it as carbon in various forms, including living biomass, dead wood, soil, and forest litter. Importantly, when trees are harvested, a portion of the above-ground biomass is converted into harvested wood products (HWPs), which can retain carbon for decades. With approximately 7 million hectares of forest (30% of its land area), Romania significantly contributes to the country’s carbon budget through the HWP pool. Using country-specific data from 1961 to 2022 and an IPCC method, we tracked HWP carbon storage and projected future scenarios to evaluate the category’s significance in achieving the 2050 climate target. During this period, the carbon stored in Romanian HWPs more than doubled from 28.20 TgC to 60.76 TgC, with sawnwood products as major contributors. Fluctuations were influenced by domestic policies, market dynamics, and industry changes, notably after the 1990s. Annual carbon inflow dipped to 0.65 TgC in 1994 and peaked at 2.54 TgC in 2013. By analyzing the scenarios, we demonstrated that a moderate growth trajectory in carbon inflow, combined with a focus on producing long-lived wood products, could double carbon stock changes by 2050 to 4.4 TgC—roughly 4% of the country’s current total emissions excluding the LULUCF sector. Additionally, based on sustainable forest management practices in Romania, this approach would significantly enhance the carbon pool and its importance in achieving the country’s climate policies. Full article

Coastal wetlands play an important carbon sequestration role in China’s “carbon peaking” and “carbon neutrality” goals. Monitoring aboveground biomass (AGB) is crucial for wetland management. Satellite remote sensing enables efficient retrieval of AGB. However, a variety of statistical models can be used for biomass inversion, depending on factors such as the vegetation type and inversion method. In this study, Landsat 8 Operational Land Imager (OLI) images were preprocessed in the study area through radiation calibration and atmospheric correction for modeling. In terms of model selection, 13 different models, including the univariate regression model, multiple regression model, and machine learning regression model, were compared in terms of their accuracy in estimating the biomass of various wetland vegetation types under their respective optimal parameters. The findings revealed that: (1) the regression models varied across vegetation types, with the accuracy of the biomass estimates decreasing in the order of Scirpus spp. > Spartina alterniflora > Phragmites australis; (2) overall modeling, without distinguishing vegetation types, addressed the challenges of limited samples availability and sampling difficulty. Among them, the random forest regression model outperformed the others in estimating wet and dry AGB with R² values of 0.806 and 0.839, respectively. (3) Comparatively, individual modeling of vegetation types can better reflect the biomass of each wetland vegetation type, especially the dry AGB of Scirpus spp., whose R² and RMSE values increased by 0.248 and 11.470 g/m², respectively. This study evaluates the impact of coastal saltmarsh vegetation types on biomass estimation, providing insights into biomass dynamics and valuable support for wetland conservation and restoration, with potential contributions to global habitat assessment models and international policies like the 30x30 Conservation Agenda. Full article

Sustainable Kikuyu (Pennisetum clandestinum) production in the Peruvian highlands was evaluated through productivity, growth, and chemical composition. This study assessed the effects of nitrogen (N) rate, organic matter application, and cutting frequency on Kikuyu grass’s yield, chemical composition, plant height, and growth rate. The experiment followed a randomised block design with split plots. A multivariate analysis of variance (MANOVA) assessed the differences across study factors. Applying 120 kg of N ha⁻¹ yr⁻¹ raised the protein yield to 3454.53 kg ha⁻¹, with a crude protein (CP) content of 23.54%. Moreover, fencing with cypress (Cupressus lusitanica) trees influenced the Kikuyu biomass, producing 19,176.23 kg of dry matter (DM) ha⁻¹ yr⁻¹ at 8.5–11.5 m from the tree base. Organic matter enhanced the Kikuyu aboveground biomass. While dry matter production showed no significant difference between 30- and 60-day cutting intervals, CP content was higher at 30 days (p < 0.05). Peak daily dry matter (DM) production occurred at 45 days, achieving a biomass accumulation of 21,186.9 kg of DM ha⁻¹ yr⁻¹. Given its high yield and favourable chemical composition, Kikuyu is a viable option for dairy cattle feed, especially in highland areas. Implementing a plant improvement programme for Kikuyu could further enhance its nutritional value for high-production dairy cows. Full article

The national level carbon sequestration estimation for urban trees generally relies on diameter at breast height (DBH) increments. However, limited research on urban tree growth has led to uncertain estimates. In this study, we determined the DBH increment of six major urban tree species in South Korea using three analytical methods (mean, linear regression, and generalized additive model) and two data classifications (total and segmented). Additionally, wedeterminded the aboveground woody biomass (AGWB) increment, which was calculated using the estimated DBH increment, and the accuracy of the estimates using different methods. We found wide variations in DBH increment (0.616 to 1.002 cm yr⁻¹) among the assessed tree species. Metasequoia glyptostroboides exhibited the highest mean growth, while Pinus densiflora showed the lowest. The peak DBH increment occurred at a median of 25.4 cm for Quercus spp. and 40.0 cm for Prunus yedoensis. The total mean method led to overestimations of AGWB increment, especially for the largest trees (i.e., those in the top 5% of DBH). Our study suggests that relying on a simple total mean method can lead to significant uncertainties in estimating AGWB increment. Therefore, more accurate methods for estimating DBH increment, especially in urban environments, are needed. Full article

Enhancing irrigation and nitrogen fertilizer application has become a vital strategy for ensuring food security in the face of population growth and resource scarcity. A 2-year experiment was conducted to determine to investigate the effects of different irrigation lower limits and nitrogen fertilizer application amounts on millet growth, yield, water use efficiency (WUE), N utilization, and inorganic nitrogen accumulation in the soil in 2021 and 2022. The experiment was designed with four irrigation lower limits, corresponding to 50%, 60%, 70%, and 80% of the field capacity (FC), referred to as I₅₀, I₆₀, I₇₀, and I₈₀. Four nitrogen fertilizer application were also included: 0, 50, 100, and 150 kg·hm⁻² (designated as F₀₀, F₅₀, F₁₀₀, and F₁₅₀), resulting in a total of 16 treatments. Binary quadratic regression equations were established to optimize the irrigation and nitrogen application. The results demonstrated that the plant height, stem diameter, leaf area index, aboveground biomass, yield, spike diameter, spike length, spike weight, WUE, and nitrogen agronomic efficiency for millet initially increased before subsequently decreasing as the irrigation lower limit and nitrogen fertilizer application increased. Their maximum values were observed in the I₇₀F₁₀₀. However, the nitrogen partial factor productivity (PFPN) exhibited a gradual decline with increasing nitrogen application, reaching its peak at F₅₀. Additionally, PFPN displayed a pattern of initial increase followed by a decrease with rising irrigation lower limits. The accumulation of NO₃⁻-N and NH₄⁺-N in the 0~60 cm soil layer increased with the increase of nitrogen fertilizer application in both years, while they tended to decrease as the irrigation lower limit increased. An optimal irrigation lower limit of 64% FC to 74% FC and nitrogen fertilizer application of 80 to 100 kg ha⁻¹ was recommended for millet based on the regression equation. The findings of this study offer a theoretical foundation and technical guidance for developing a drip irrigation and fertilizer application for millet cultivation in Northeast China. Full article

Forest biomass accumulation is fundamental to ecosystem stability, material cycling, and energy flow, and pit lays a crucial role in the carbon cycle. Understanding the factors influencing aboveground biomass (AGB) is essential for exploring ecosystem functioning mechanisms, restoring degraded forests, and estimating carbon balance in forest communities. Tropical karst seasonal rainforests are species-rich and heterogeneous, yet the impact mechanisms of biotic and abiotic factors on AGB remain incompletely understood. Based on the survey data of a 15 ha monitoring plot in a karst seasonal rainforest in Southern China, this study explores the distribution characteristics of AGB and its intrinsic correlation with different influencing factors. The results show that the average AGB of the plot is 125.7 Mg/ha, with notable variations among habitats, peaking in hillside habitats. Trees with medium and large diameters at breast height (DBH ≥ 10 cm) account for 83.94% of the aboveground biomass (AGB) and are its primary contributors; dominant tree species exhibit higher AGB values. Both biotic and abiotic elements substantially influence AGB, with biotic factors exhibiting the largest influence. Among abiotic factors, topographic factors have a strong direct or indirect influence on AGB, while soil physicochemical properties have the smallest indirect impact. This research provides a comprehensive understanding of AGB distribution and its influencing factors in tropical karst forests (KFs), contributing to the management of carbon sinks in these ecosystems. Full article

Identifying the key climate variables affecting optical saturation values (OSVs) in forest aboveground biomass (AGB) estimation using optical remote sensing is crucial for analyzing OSV changes. This can improve AGB estimation accuracy by addressing the uncertainties associated with optical saturation. In this study, Pinus yunnanensis forests and Landsat 8 OLI imagery from Yunnan were used as case studies to explain this issue. The spherical model was applied to determine the OSVs using specific spectral bands (Blue, Green, Red, Near-Infrared (NIR), and Short-Wave Infrared Band 2 (SWIR2)) derived from Landsat 8 OLI imagery. Canonical correlation analysis (CCA) uncovered the intricate relationships between climatic variables and OSV variations. The results reveal the following: (1) All Landsat 8 OLI spectral bands showed a negative correlation with the Pinus yunnanensis forest AGB, with OSVs ranging from 104.42 t/ha to 209.11 t/ha, peaking in the southwestern region and declining to the lowest levels in the southeastern region. (2) CCA effectively explained 93.2% of the OSV variations, identifying annual mean temperature (AMT) as the most influential climatic factor. Additionally, the mean temperature of the wettest quarter (MTQ) and annual precipitation (ANP) were significant secondary determinants, with higher OSV values observed in warmer, more humid areas. These findings offer important insights into climate-driven OSV variations, reducing uncertainty in forest AGB estimation and enhancing the precision of AGB estimations in future research. Full article

The application of nanotechnology in agriculture has received much attention in order to improve crop yield, quality and food safety. In the present study, a Cd-tolerant endophytic fungus Colletotrichum fructicola KL19 was first ever reported to produce SeNPs, and the production conditions were optimized using the Box–Behnken design in the Response Surface Methodology (RSM-BBD), achieving a peak yield of 1.06 mM under optimal conditions of 2.62 g/20 mL biomass, 4.56 mM Na₂SeO₃, and pH 6.25. Following this, the properties of the biogenic SeNPs were elucidated by using TEM, DLS, and FTIR, in which the 144.8 nm spherical-shaped SeNPs were stabilized by different functional groups with a negative zeta potential of −18.3 mV. Furthermore, strain KL19 and SeNPs (0, 5, 10, 20 and 50 mg/L) were inoculated in the root zone of small-leaf spinach (Spinacia oleracea L.) seedlings grown in the soil with 33.74 mg/kg Cd under controlled conditions for seven weeks. Impressively, compared with Cd stress alone, the strain KL19 and 5 mg/L SeNPs treatments significantly (p < 0.05) exhibited a reduction in Cd contents (0.62 and 0.50 folds) within the aboveground parts of spinach plants and promoted plants’ growth by improving the leaf count (0.92 and 1.36 folds), fresh weight (2.94 and 3.46 folds), root dry weight (4.00 and 5.60 folds) and root length (0.14 and 0.51 folds), boosting total chlorophyll synthesis (0.38 and 0.45 folds), enhancing antioxidant enzymes (SOD, POD) activities, and reducing the contents of reactive oxygen species (MDA, H₂O₂) in small-leaf spinach under Cd stress. Overall, this study revealed that utilizing endophytic fungus C. fructicola or its derived SeNPs could mitigate reactive oxygen species generation by enhancing antioxidant enzyme activity as well as diminish the absorption and accumulation of Cd in small-leaf spinach, promoting plant growth under Cd stress. Full article

Accurate estimation of livestock carrying capacity (LCC) and implementation of an appropriate actual stocking rate (ASR) are key to the sustainable management of grazing adapted alpine grassland ecosystems. The reliable determination of aboveground biomass is fundamental to these determinations. Peak aboveground biomass (AGB_P) captured from satellite data at the peak of the growing season (POS) is widely used as a proxy for annual aboveground biomass (AGB_A) to estimate LCC of grasslands. Here, we demonstrate the limitations of this approach and highlight the ability of POS in the estimation of ASR. We develop and trail new approaches that incorporate remote sensing phenology timings of grassland response to grazing activity, considering relations between biomass growth and consumption dynamics, in an effort to support more accurate and reliable estimation of LCC and ASR. The results show that based on averaged values from large-scale studies of alpine grassland on the Qinghai-Tibet Plateau (QTP), differences between AGB_P and AGB_A underestimate LCC by about 31%. The findings from a smaller-scale study that incorporate phenology timings into the estimation of annual aboveground biomass reveal that summer pastures in Haibei alpine meadows were overgrazed by 11.5% during the study period from 2000 to 2005. The methods proposed can be extended to map grassland grazing pressure by predicting the LCC and tracking the ASR, thereby improving sustainable resource use in alpine grasslands. Full article