Search Results (157)

Similarly to conventional field crops, weeds often pose significant problems in the cultivation of medicinal plants. To date, no comprehensive documentation exists regarding weed infestation levels in these crops in Serbia. The objective of this study was to provide a valuable foundation for developing effective, site-specific weed management strategies in medicinal crop production. Weeds in five medicinal crops (lemon balm, fennel, peppermint, ribwort plantain, German chamomile), were surveyed based on the agro-phytosociological method between 2019 and 2024, and across 59 plots. A total of 109 weed species were recorded, belonging to 29 families and 88 genera. Among them, 75 were annuals and 34 perennials, including 93 broadleaved species, 10 grasses, and one parasitic species. All surveyed plots were heavily infested with perennial weeds such as Elymus repens, Cirsium arvense, Convolvulus arvensis, Lepidium draba, Rumex crispus, Sorghum halepense, Taraxacum officinale, etc. Also, several annual species were found in high abundance and frequency, including Amaranthus retroflexus, Chenopodium album, Galium aparine, Lactuca serriola, Lamium amplexicaule, L. purpureum, Papaver rhoeas, Stellaria media, Veronica hederifolia, V. persica, etc. The most important ecological factors influencing the composition of weed vegetation in investigated medicinal crops were temperature and light for fennel and peppermint plots, soil reaction for lemon balm and ribwort plantain plots, and nutrient content for German chamomile plots. A perspective for exploitation of these results is the development of effective weed control programs tailored to this specific cropping system. Weed control strategies should consider such information, targeting the control of the most frequent, abundant, and dominant species existing in a crops or locality. Full article

Soil acidity is one of the main limiting factors for coffee production in Peruvian rainforests. The objective of this study is to predict the spatial acidity variability for recommending site-specific liming and phosphorus fertilization treatments. We analyzed thirty-six edaphoclimatic variables, eight methods for estimating liming doses, and three geospatial variables from 552 soil samples in the Pichanaqui district of Peru. Multivariate statistics, nonparametric comparison, and geostatistical analysis with Ordinary Kriging interpolation were used for data analysis. The results showed low coffee yields (0.70 ± 0.16 t ha⁻¹) due to soil acidification. The interquartile ranges (IQR) were found to be 3.80–5.10 for pH, 0.21–0.87 cmol Kg⁻¹ for Al⁺³, and 2.55–6.53 mg Kg⁻¹ for available P, which are limiting soil conditions for coffee plantations. Moreover, pH, Al⁺³, Ca⁺², and organic matter (OM) were the variables with the highest accuracy and quality in the spatial prediction of soil acidity (R² between 0.77 and 0.85). The estimation method of liming requirements, MPM (integration of pH and organic material method), obtained the highest correlation with soil acidity-modulating variables and had a high spatial predictability (R² = 0.79), estimating doses between 1.50 and 3.01 t ha⁻¹ in soils with organic matter (OM) > 4.00%. The MAC (potential acidity method) method (R² = 0.59) estimated liming doses between 0.51 and 0.88 t ha⁻¹ in soils with OM < 4.00% and potential acidity greater than 0.71 cmol Kg⁻¹. Regarding phosphorus fertilization (DAP), the results showed high requirements (median = 137.21 kg ha⁻¹, IQR = 8.28 kg ha⁻¹), with high spatial predictability (R² = 0.74). However, coffee plantations on Ferralsols, with Paleogene parental material, mainly in dry forests, had the lowest predicted fertilization requirements (between 6.92 and 77.55 kg ha⁻¹ of DAP). This research shows a moderate spatial variation of acidity, the need to optimize phosphorus fertilization, and an optimal prediction of liming requirements using the MPM and MAC methods, which indicate high requirements in the southwest of the Pichanaqui district. Full article

The primary aim of this study was to explore the influence of abiotic factors on weed development in maize fields, with the goal of informing more effective weed management practices. We focused on identifying key environmental, edaphic, and agricultural variables that contribute to weed infestations, particularly before the application of spring herbicide treatments. Field investigations were conducted from 2018 to 2021 across selected maize-growing regions in Hungary. Over the four-year period, a total of 51 weed species were recorded, with Echinochloa crus-galli, Chenopodium album, Portulaca oleracea, and Hibiscus trionum emerging as the most prevalent taxa. Collectively, these four species accounted for more than half (52%) of the total weed cover. Altogether, the 20 most dominant species contributed 95% of the overall weed coverage. The analysis revealed that weed cover, species richness, and weed diversity were significantly affected by soil properties, nutrient levels, geographic location, and tillage systems. The results confirm that the composition of weed species was influenced by several environmental and management-related factors, including soil parameters, geographical location, annual precipitation, tillage method, and fertilizer application. Environmental factors collectively explained a slightly higher proportion of the variance (13.37%) than farming factors (12.66%) at a 90% significance level. Seasonal dynamics and crop rotation history also played a notable role in species distribution. Nutrient inputs, particularly nitrogen, phosphorus, and potassium, influenced both species diversity and floristic composition. Deep tillage practices favored the proliferation of perennial species, whereas shallow cultivation tended to promote annual weeds. Overall, the composition of weed vegetation proved to be a valuable indicator of site-specific soil conditions and agricultural practices. These findings underscore the need to tailor weed management strategies to local environmental and soil contexts for sustainable crop production. Full article

Artificial reservoirs in arid regions provide unique ecological environments for studying the spatial and functional dynamics of plankton communities under the combined stressors of climate change and anthropogenic activities. This study conducted a systematic investigation of the phytoplankton community structure and its environmental drivers in 17 artificial reservoirs in the Ili region of Xinjiang in August and October 2024. The Ili region is located in the temperate continental arid zone of northwestern China. A total of 209 phytoplankton species were identified, with Bacillariophyta, Chlorophyta, and Cyanobacteria comprising over 92% of the community, indicating an oligarchic dominance pattern. The decoupling between numerical dominance (diatoms) and biomass dominance (cyanobacteria) revealed functional differentiation and ecological complementarity among major taxa. Through multivariate analyses, including Mantel tests, principal component analysis (PCA), and redundancy analysis (RDA), we found that phytoplankton community structures at different ecological levels responded distinctly to environmental gradients. Oxidation-reduction potential (ORP), dissolved oxygen (DO), and mineralization parameters (EC, TDS) were key drivers of morphological operational taxonomic unit (MOTU). In contrast, dominant species (SP) were more responsive to salinity and pH. A seasonal analysis demonstrated significant shifts in correlation structures between summer and autumn, reflecting the regulatory influence of the climate on redox conditions and nutrient solubility. Machine learning using the random forest model effectively identified core taxa (e.g., MOTU1 and SP1) with strong discriminatory power, confirming their potential as bioindicators for water quality assessments and the early warning of ecological shifts. These core taxa exhibited wide spatial distribution and stable dominance, while localized dominant species showed high sensitivity to site-specific environmental conditions. Our findings underscore the need to integrate taxonomic resolution with functional and spatial analyses to reveal ecological response mechanisms in arid-zone reservoirs. This study provides a scientific foundation for environmental monitoring, water resource management, and resilience assessments in climate-sensitive freshwater ecosystems. Full article

Biogas slurry (BGS), a nutrient-rich by-product of anaerobic digestion, presents a promising opportunity for sustainable agriculture on sandy soils. This review explores the agronomic potential of using BGS for improving sorghum’s (Sorghum bicolor) productivity by enhancing soil fertility and the nutrient availability. It focuses on the sources and properties of BGS, its application methods, and their effects on the soil nutrient dynamics and crop productivity. The findings indicate that BGS improves the soil health and crop yields, offering an eco-friendly alternative to synthetic fertilizers, especially in resource-limited settings. Despite these benefits, research gaps persist, including the need for long-term field trials, the optimization of application strategies for sandy soils, and comprehensive economic evaluations. Additionally, concerns such as nutrient imbalances, phosphorus accumulation, and slurry composition variability must be addressed. This review recommends standardizing BGS nutrient profiling and adopting site-specific management practices to maximize its agronomic benefits and environmental safety. Integrating BGS into sustainable soil fertility programs could contribute significantly to achieving agricultural resilience and circular economy goals. Full article

Eutrophication driven by nitrogen and phosphorus discharge remains a critical global environmental challenge. This study developed a sustainable strategy for synergistic nutrient removal and recovery by fabricating MgO-coated biochar (Mg-MBC600) through co-pyrolysis of municipal sludge and sunflower stalk (300–700 °C). Systematic investigations revealed temperature-dependent adsorption performance, with optimal nutrient removal achieved at 600 °C pyrolysis. The Mg-MBC600 composite exhibited enhanced physicochemical properties, including a specific surface area of 156.08 m²/g and pore volume of 0.1829 cm³/g, attributable to magnesium-induced structural modifications. Advanced characterization confirmed the homogeneous dispersion of MgO nanoparticles (~50 nm) across carbon matrices, forming active sites for chemisorption via electron-sharing interactions. The maximum adsorption capacities of Mg-MBC600 for nitrogen and phosphorus reached 84.92 mg/L and 182.27 mg/L, respectively. Adsorption kinetics adhered to the pseudo-second-order model, indicating rate-limiting chemical bonding mechanisms. Equilibrium studies demonstrated hybrid monolayer–multilayer adsorption. Solution pH exerted dual-phase control: acidic conditions (pH 3–5) favored phosphate removal through Mg₃(PO₄)₂ precipitation, while neutral–alkaline conditions (pH 7–8) promoted NH₄⁺ adsorption via MgNH₄PO₄ crystallization. XPS analysis verified that MgO-mediated chemical precipitation and surface complexation dominated nutrient immobilization. This approach establishes a circular economy framework by converting waste biomass into multifunctional adsorbents, simultaneously addressing sludge management challenges and enabling eco-friendly wastewater remediation. Full article

Tourism offers many economic benefits but can have long-lasting ecological effects when improperly managed. Tourism can cause overwhelming pressure on wastewater treatment systems, as in Belize, where some of the over 400 small islands (cayes) that were once temporary sites for fishermen have become popular tourist destinations. An overabundance of nitrogen, in part as a result of incomplete wastewater treatment, threatens human health and ecosystem services. The tourism industry is a complex and dynamic industry with many sectors and stakeholders with conflicting goals. In this study, a systems thinking approach was adopted to study the dynamic interactions between stakeholders and the environment at Laughing Bird Caye National Park in Belize. The project centered on nutrient discharges from the caye’s onsite wastewater treatment system. An archetype analysis approach was applied to frame potential solutions to nutrient pollution and understand potential behaviors over time. “Out of control” and “Underachievement” were identified as system archetypes; “Shifting the Burden” and ‘‘Limits to Success’’ were used to model specific cases. Based on these results, upgrading of the wastewater treatment system should be performed concurrently with investments in the user experience of the toilets, education on the vulnerability of the treatment system and ecosystem, and controls on the number of daily tourists. Full article

Delineating soil management zones in cocoa cultivation areas can help optimize production and minimize ecological and environmental risks. This research assessed the spatial distribution of heavy metal concentration and soil fertility indicators in Cross River State, Nigeria, to delineate soil management zones (MZs). A total of n = 63 georeferenced, composite soil samples were collected at the 0–30 cm depth increment, air-dried, and subjected to physicochemical analysis. The soil data were subjected to principal component analysis (PCA), and the selected principal components (PCs) were used for fuzzy c-means clustering analysis to delineate the MZs. The result indicated that soil pH varied from 4.8 (strongly acidic) to 6.3 (slightly acidic), with high average organic carbon contents. The degree of contamination was low, while the ecological risk indicator (RI) of the environment under cocoa cultivation ranged from low risk (RI = 18.24) to moderate risk (RI = 287.15), with moderate risk areas mostly found in patches around the central and upper regions. Higher pH was associated with increased levels of exchangeable Ca, Mg, and K, and TN and OC. Strong spatial dependence was observed for silt, pH, OC, Mg, Zn, Cu, Pb, Cd, Cr, and DC. The result showed the first six principal components (PCs) with eigenvalues >1 accounting for 83.33% of the cumulative variance, and three MZs were derived via the selected six PCs using fuzzy c-means clustering analysis. The results of this study further indicated that MZ3 had the highest pH (6.06), TN (0.24%), OC (2.79%), exchangeable Ca (10.62 cmol/kg), Mg (4.01 cmol/kg), and K (0.12 cmol/kg). These were significantly (p < 0.05) higher than those observed in MZ2 and MZ1, and they represent the most fertile parts of the study area. Furthermore, 40.6% of the study area had marginal soil (i.e., soil under MZ2). Full article

This study investigated the effects of planting density and site index on stand attributes and soil nutrients in mature Chinese fir [Cunninghamia lanceolata (Lamb.) Hook.] plantations across Fujian and Sichuan Provinces, elucidating the pathways through which these factors influence standing volume (SV). The results showed that (1) planting density significantly affected stand variables, with average diameter at breast height (ADBH) decreasing and SV initially increasing and then declining with higher density. The number of mortality plants (NMP) and actual stand density (ASD) both increased significantly with higher density. Average tree height (ATH) and dominant height (DH) responses varied by region, with ATH decreasing in Sichuan and DH decreasing in Fujian with higher density. (2) Planting density affected soil nutrients differently in the two provinces, with soil total potassium (TK) increasing in Fujian and phosphorus decreasing in Sichuan. (3) Site index was positively correlated with ATH and ADBH but negatively correlated with ASD and NMP. Its relationship with soil nutrients was province-specific: in Fujian, site index was negatively correlated with total phosphorus (TP) and positively correlated with TK and soil pH, while in Sichuan it was only positively correlated with TK. (4) Structural equation modeling revealed different regulatory pathways: in Fujian, planting density influenced SV through both ASD and soil nutrients, while in Sichuan it affected only through ASD. This study highlights the region-specific interactions between planting density, site index, stand structure, and soil nutrients, providing a foundation for optimized plantation management. Full article

Mineral nutrition management in sweet cherry orchards remains a critical challenge due to the lack of site-specific fertilization guidelines, particularly in Greece, a significant cherry-producing country. This study aimed to develop a predictive framework for total nutrient losses in sweet cherry orchards by proposing simplified estimations using fresh fruit yield as the sole input variable. Field experiments were conducted in two orchards with distinct rootstocks (MxM 14 and CAB-6P), analyzing soil properties, leaf nutrient status, and uptake patterns on different plant components. Results indicated that despite differences in soil texture and pH, nutrient availability was generally sufficient, with only Fe and Zn marginally below optimal levels in leaf tissue. Principal Component Analysis (PCA) revealed distinct nutrient distribution patterns, with N evenly distributed across fruits, peduncles, and prunings, while K was concentrated in fruits and peduncles, and Ca and Mg predominantly in fallen leaves. Notably, K was redistributed from leaves to fruits under high yields, evidenced by negative correlations between leaf biomass and K uptake. Strong relationships (r² > 0.8) were found between fresh fruit yield and uptake of N, P, K, Mg, B, and Cu, enabling reliable predictions of total nutrient losses. Estimated annual nutrient removals were 85.6 kg ha⁻¹ N, 8.94 kg ha⁻¹ P, 42.7 kg ha⁻¹ K, and 12.0 kg ha⁻¹ Mg, with significant fractions retained in prunings and fallen leaves (e.g., 51.8 kg ha⁻¹ N, 6.2 kg ha⁻¹ P). The developed yield-based models provide a practical tool for optimizing fertilization strategies, while our findings highlight the potential for nutrient recycling through sustainable residue management. Full article

The ecological assessment of rivers under the Water Framework Directive (WFD) requires the use of biological quality elements (BQEs) across defined abiotic types of rivers. However, limited evidence exists on how well biological indices perform across multiple typological classes, particularly under the influence of complex, overlapping stressors. This study evaluated the diagnostic performance of four biological indices (IO—diatoms, MIR—macrophytes, MMI_PL—benthic macroinvertebrates, and EFI + PL—fish) in 16 river sites in southern Poland. These were classified into four abiotic types (5, 6, 12, and 17) and subjected to varying levels of human pressure. Biological, physical and chemical, and hydromorphological data were collected along environmental gradients including conductivity, nutrient enrichment, and habitat modification. Statistical analyses were used to evaluate patterns in community composition and index responsiveness. The IO and MMI_PL indices were the most consistent and sensitive in distinguishing between reference and degraded river conditions. MIR and EFI + PL were more variable, especially in lowland rivers, and showed stronger associations with habitat structure and oxygen levels. Conductivity emerged as a key driver of biological responses across all BQEs, with clear taxonomical shifts observed. The results support the need to consider both typological context and local environmental variation in ecological classification. The findings underscore the need for typology-aware, pressure-specific biomonitoring strategies that combine multiple organism groups and integrate continuous environmental variables. Such approaches can enhance the ecological realism and diagnostic accuracy of river assessment systems, supporting more effective water resource management across diverse hydroecological contexts. Full article

Urban green spaces are integral components of city ecosystems, supporting essential belowground microbial communities such as arbuscular mycorrhizal fungi (AMF). Understanding how green space types influence AMF communities is key to promoting urban ecological function. This study examines AMF diversity, community assembly, and co-occurrence network structures in two urban green space types—park and roadside—in Kaifeng, Henan Province, China. Soil samples were collected from both sites, and AMF community composition was assessed using high-throughput sequencing. Environmental variables, including total nitrogen (TN), available phosphorus (AP), available potassium (AK), water content, and pH, were measured to evaluate their influence on AMF communities. The results indicate marked differences between the two green space types. Park soils support significantly greater AMF species richness and more complex co-occurrence networks than roadside soils. These differences are correlated with higher nutrient levels in park soils. By contrast, AMF communities in roadside soils are more strongly associated with soil water content and pH, resulting in reduced diversity and more homogeneous community structures. Stochastic processes predominantly govern community assembly in both green space types, with roadside green spaces being more influenced by stochastic processes than park green spaces. These findings highlight the influence of urban landscape type on AMF communities and provide guidance for enhancing urban biodiversity through targeted landscape planning and soil management. In future work, we will implement long-term AMF monitoring across different green-space types and evaluate specific management practices to optimize soil health and ecosystem resilience. Full article

The use of service (cover) crops is widely practiced in soil agriculture due to their many benefits, including enhanced nutrient supply and improved soil health. Bacteria, as major decomposers of plant residues in the soil, play essential roles in nutrient cycling. This study examined the impact of various almond orchard management practices on the soil microbial community composition in a hyper-arid ecosystem. High-throughput sequencing was used to compare the microbial communities in two adjacent almond orchards managed with either organic (ORG) or regenerative agriculture (RA) practices, alongside an uncultivated (UC) site. Notably, little is known about the responses of soil bacterial communities in hyper-arid regions to intercrop mulch from service crops. This study may offer insights into the ecological limits of the benefits of service crops in promoting soil health under extreme conditions. Our findings demonstrate that RA management can alter soil organic carbon levels and reshape microbial communities by increasing overall bacterial abundance and enriching specific keystone taxa. These changes may have significant implications for nutrient cycling processes in hyper-arid agroecosystems. Full article

Tall fescue (Festuca arundinacea Schreb.) is a herbaceous species that is commonly used for ecological slope restoration in China. However, water scarcity often constrains its growth due to the unique site conditions of steep slopes and climate-induced drought stress. This study aims to compare the ameliorative effects of silicon nanoparticles (Si NPs) and cellulose nanocrystals (CNCs) on drought stress in tall fescue and to elucidate their underlying mechanisms of action. The results indicated that drought stress impaired photosynthesis, restricted nutrient absorption, and increased oxidative stress, ultimately reducing biomass. However, Si NPs and CNCs enhanced drought tolerance and promoted biomass accumulation by improving photosynthesis, osmotic regulation, and antioxidant defense mechanisms. Specifically, Si NP treatment increased biomass by 48.71% compared to drought-stressed control plants, while CNCs resulted in a 33.41% increase. Transcriptome sequencing further revealed that both nanomaterials enhanced drought tolerance by upregulating genes associated with photosynthesis and antioxidant defense. Additionally, Si NPs improved drought tolerance by stimulating root growth, enhancing nutrient uptake, and improving leaf structure. In contrast, CNCs play a distinct role by regulating the expression of genes related to cell wall synthesis and metabolism. These findings highlight the crucial roles of these two nanomaterials in plant stress protection and offer a sustainable strategy for the maintenance and management of slope vegetation. Full article

Maize (corn) (Zea mays L.) yield is influenced by complex factors, including abiotic and biotic stress and inconsistent nutrient use efficiency, which challenge optimal yield. Standard management recommendations often fall short, prompting interest in intensive management strategies within an Adaptive Maize Management System (ACMS). To investigate this, we employed an addition/omission technique within a randomized complete block design (RCBD) to compare standard maize management recommendations with an intensive management protocol aimed at identifying yield-limiting factors. Our intensive management approach combined early-season biostimulant applications with mid-season supplementation of phosphorus (P), potassium (K), and nitrogen (N) at the V7 stage, followed by foliar fungicides and additional foliar N at the R1 stage. Field trials spanned five Virginia locations over 2022 and 2023 under both irrigated and non-irrigated conditions, yielding ten site-years of data. Analysis via ANOVA in JMP^® Version 18 with Dunnett’s test revealed that the intensive management approach significantly increased grain yield in 3 of 10 experiments. Under non-irrigated conditions, the intensive management practices averaged 5.9% higher yield than the standard management check. We observed a higher response to irrigation in standard management check (34%) than in intensive management check (8.9%). Site-specific irrigation impacts ranged from 14% to 61%. Results emphasize site-specific input recommendations for yield enhancement. Full article