Search Results (235)

Background: Extreme drought and flood events continuously threaten the stability of forest and crop production. Long-term hydrological records derived from tree-ring anatomical proxies provide critical evidence for revealing historical drought hazard differentiation. Methods: Cell wall thickness chronologies of Betula platyphylla (northern forest) and Picea koraiensis (southern agro-pastoral zone) were developed to reconstruct nearly 300-year annual runoff sequences. Pearson correlation, quadratic regression, wavelet transform and superposed epoch analysis (SEA) were applied to quantify hydrological evolution, periodic signals, large-scale climate forcing and statistical coupling between dry/wet extremes and historical yield reduction records. Results: The northern watershed showed stronger interannual runoff oscillation. Both regions entered persistent low-flow phases post-1950. Pacific Decadal Oscillation (PDO) acted as the dominant driver, while solar radiation exerted weak secondary regulation. Severe drought events corresponded closely to historical forest and grain yield losses, with far higher agricultural vulnerability in the southern agro-pastoral ecotone. Conclusions: This study reconstructed the long-term historical runoff of the Greater Khingan Range from the thickness of the cell wall, analyzed the different impacts of PDO on it, and clarified the differentiated effects of drought and flood on agricultural and forestry production losses and the interrelated impact of land use on hydrology and the value of agricultural output. Full article

The nemoral biome encompasses some of the most diverse and productive ecosystems in Europe, yet it has been extensively transformed by human activity. The capacity of secondary forests that have developed on sites of clear-cut broadleaved forests to sustain ground beetle diversity remains insufficiently studied. Ground beetles were sampled using pitfall traps during May–July in 21 post-logging forest stands across six administrative regions of Central Russia. A total of 90 ground beetle species were recorded. The superdominant species in most habitats were Carabus cancellatus Ill. and Pterostichus melanarius Ill. The median species richness per sampling plot was 17, and the median activity density was 33.6 individuals per 100 trap-days. The similarity of ground beetle assemblages, in terms of both species composition and community structure, is determined primarily by habitat characteristics rather than by the spatial proximity of sampling sites. The most robust predictor of both species composition and community structure was the percentage cover of Corylus avellana. A large proportion of exposed soil within forest stands is associated with a higher activity density of mixophytophagous stratohortobionts, predominantly Harpalus rufipes L. As the distance from large forest tracts increased, the activity density of large walking epigeobiont zoophages declined. Overall, the species structure of ground beetle assemblages was only weakly predictable. Full article

Forest cover change alters land–atmosphere exchanges of energy, water, and carbon, thereby influencing local and regional climate. This study assessed climatic patterns associated with afforestation in Khyber Pakhtunkhwa, Pakistan, from 2003 to 2023 using remote sensing data and Google Earth Engine. Land surface temperature (LST) was treated as the primary response variable, while evapotranspiration (ET) was analyzed as a secondary response variable. Air temperature; precipitation; vegetation indices, including the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI); and elevation were used as supporting variables to interpret the broader climatic and biophysical responses of afforestation. MODIS land-cover, LST, ET, and vegetation-index products, together with climate research unit (CRU) climate data and ALOS-PALSAR DEM, were used to evaluate spatiotemporal trends and variable relationships. The results showed that mean LST increased by 0.520 ± 0.070 °C across KP during 2003–2023; however, areas classified as forest gain showed a localized cooling pattern of 0.490 ± 0.050 °C during the 2013–2023 forest-cover transition assessment window. Afforested areas also exhibited increased ET, whereas forest-loss areas showed reduced ET and higher LST. Specifically, ET increased by 0.013 ± 0.002 mm/8-day in afforested areas, whereas forest-loss areas showed a decline of 0.005 ± 0.001 mm/8-day. CRU-derived regional air temperature showed an increasing tendency of 0.310 ± 0.050 °C, whereas precipitation showed only a weak and statistically non-significant regional tendency; therefore, precipitation was used only as background climatic context. The NDVI and the EVI were negatively correlated with daytime LST, and elevation showed a strong negative relationship with LST. Overall, the findings indicate that forest-cover gain was associated with localized surface cooling patterns and improved vegetation–climate regulation indicators in the study area. Full article

Previous morphological studies have confirmed that Canton settlements maintain a stable cultural landscape sequence consisting of ponds, open spaces, ancestral halls, residences, and forests. Villages in the Dongjiang River Basin exhibit an inherent coordination between cultural landscape patterns and rainwater drainage and storage systems, contributing to strong resilience against frequent heavy rainfall events. This study selects Jiangbian Village in Dongguan as a case study and develops a quantitative analysis framework by integrating GIS and SWMM (Storm Water Management Model). Using DEM-derived terrain data and land use interpretation, a hydrological model incorporating ponds, drainage channels, paddy fields, and threshing floors was established. Five levels of functional failure severity and five design rainfall return periods were applied to systematically evaluate hydrological regulation performance. The results show that (1) ponds serve as the core water-storage component of the entire system, and a 25% reduction in their functionality leads to a substantial decline in flood mitigation capacity. Paddy field ridges and drainage channels jointly provide secondary buffering functions, while village boundary structures play a significant role in flood regulation. These landscape elements possess distinct hydrological functions and collectively shape the production, living, and ecological landscapes of the village. (2) Influenced by steep topographic gradients, the village adopts a spatial configuration characterized by horizontal alleys and terraced forms, which enhance transverse drainage and connect ponds through longitudinal channels. This comb-like settlement pattern demonstrates strong adaptation to local terrain conditions. This study reveals the terrain-adaptation characteristics of traditional Canton villages and provides valuable insights for the sustainable conservation of rural cultural landscapes. Full article

The proposition that expanding education uniformly advances the 2030 Agenda is widely held in policy discourse—embedded in SDG 4, amplified by UNESCO, and routinely invoked in national development strategies. This paper shows that this proposition holds only partially. Using a balanced panel of 193 countries observed over 2000–2023, we estimate 96 two-way fixed-effects regressions connecting eight measures of education—spanning expenditure, enrolment, completion, attainment, and accumulated stock—to twelve Sustainable Development Goal outcomes. The estimates reveal a pronounced block asymmetry. On the social side, educational expansion is a robust correlate of progress against poverty: a one-standard-deviation increase in secondary enrolment is associated with a 0.16-log-point lower $2.15/day extreme-poverty headcount and a 4.35-point lower value on the 0–100 SDG-1 composite, both significant at p < 0.001. On the environmental side, the same education measure is associated with a coefficient of β = +0.048 (p = 0.014) on production-based CO₂ per capita and β = −0.260 (p = 0.031) on forest area—associations that are statistically significant but directionally perverse, though small in magnitude (approximately 0.05–0.26 SD on the standardised outcome). Higher schooling is also associated with higher within-country inequality (β = +0.71 on the Gini, p = 0.006). The asymmetry survives Driscoll–Kraay standard errors, Oster sensitivity bounds, and two-year lagged specifications. The findings qualify the optimistic narrative that frames education as a uniform instrument for sustainable development: schooling is a robust predictor of social-block progress, but appears insufficient on its own for environmental progress and is best understood as a complement to, rather than a substitute for, dedicated environmental policy. The 2030 architecture may benefit from differentiated instrument–goal pairs rather than reliance on any single instrument across all goals. Full article

The assessment of humanity’s ecological footprint has become increasingly critical in contemporary discourse due to growing environmental challenges. This study examines the economic evaluation of the ecological footprint with a particular focus on forest ecosystem services and food productivity. Using harmonized secondary data from FAOSTAT, EUROSTAT, the World Bank, and IPBES, the analysis covers selected developed and emerging economies, including the European Union, the United States, China, Brazil, and other representative countries. This study investigates the macroeconomic implications of natural capital degradation by applying a panel data econometric model to European Union countries over the period 2010–2023. Moving beyond descriptive approaches, the research formulates and tests three hypotheses linking biodiversity, environmental pressure, and green transition variables to economic performance. Using harmonized data from Eurostat and Statista, the study employs a fixed-effects regression framework to estimate the impact of biodiversity indicators, greenhouse gas emissions, renewable energy share, and environmental protection expenditures on GDP per capita. The results demonstrate that biodiversity preservation and resource efficiency are positively associated with economic performance, while environmental degradation—proxied by greenhouse gas emissions—exerts a statistically significant negative effect. Additionally, the findings confirm that investments in renewable energy and environmental protection contribute to long-term economic stability. By providing a transparent data structure, explicit variable operationalization, and reproducible econometric specification, the study offers an original empirical contribution to ecological economics and addresses the limitations of prior literature that relied primarily on descriptive synthesis. Full article

The atmospheric air quality is one of the crucial factors determining people’s health, duration and quality of life. The importance of ammonia (NH₃) and ethylene (C₂H₄) is due to the fact that they are precursors of secondary organic aerosols (SOA) and phytotoxicants, which significantly affect air quality, cause human diseases and damage plants. The Fourier Transform Infrared (FTIR) spectrometry is a powerful tool for long-term monitoring of the atmospheric gas composition, including toxic gases. The paper presents the results of atmospheric FTIR measurements of NH₃ and C₂H₄ at the St. Petersburg State University observational site (59.88° N, 29.83° E, 20 m above sea level) located in a suburb of greater Saint Petersburg. This work demonstrates the applicability of the ground-based atmospheric FTIR spectroscopy to long-term monitoring of air pollution in urbanized areas and in particular to provide information on the NH₃ and C₂H₄ abundance in the atmosphere, including the analysis of their annual cycle, long-term trends, and positive anomalies. It was shown that for NH₃ and C₂H₄, a statistically significant decrease in column-averaged dry-air mole fraction values (X_NH3 and X_C2H4) was observed, amounting to (−2.3 ± 0.2)%/year for the 2009–2025 period and with the rate (−2.2 ± 0.4)%/year for the 2016–2025 period, respectively. Periodically recorded X_NH3 anomalies indicate the presence of intensive emission sources in the region, subjecting ecosystems in adjacent areas to constant exposure to NH₃ concentrations exceeding the critical level. Anomalously high values of X_NH3 and X_C2H4 were recorded simultaneously only once—on 17 October 2017. Using data on HCN total column (as a forest fire indicator) and the results of atmospheric dispersion modeling, it was shown that this pollution event was caused by the influence of biomass burning products emitted from wildfires located approximately 250 km to the north-west from the observational site in the Helsinki area (Finland). Full article

The valorization of secondary biomass streams is an important step toward more resource-efficient biorefinery concepts and reduced dependence on fossil-based materials. In this study, agricultural and forest residues, namely Atlas cedar cones, mixed conifer cones, hazelnut shells, walnut shells, coffee silverskin, and cocoa shells, were investigated as feedstocks for producing colloidal lignin particles. Lignin-rich extracts were obtained by Organosolv pretreatment using 60 wt% aqueous ethanol, followed by particle formation through solvent shifting and purification by ultrafiltration. A particular novelty of this work is that highly different feedstocks were processed under identical Organosolv and solvent-shifting conditions, enabling a direct comparison of their suitability for colloidal lignin particle production within one consistent process route. The feedstocks differed markedly in extractive content and chemical profile, as shown by sequential Soxhlet extraction and qualitative GC-MS screening. Despite these differences in extract composition, solvent shifting yielded colloidal lignin particles with largely similar properties. Dynamic light scattering showed hydrodynamic diameters of 65–88 nm immediately after precipitation for all samples except cocoa shell, which formed strong agglomerates. The ultrafiltration step further introduced an industry-relevant downstream purification stage by removing most water-soluble low-molecular-weight compounds before product evaluation. After purification and redispersion, particle sizes ranged from 121 to 389 nm, indicating partial aggregation but overall successful recovery of stable colloidal dispersions. All purified particle suspensions exhibited comparable antioxidant activity in the FRAP (ferric reducing antioxidant power) assay, ranging from 12.3 to 18.4 mg lignin per mg ascorbic acid equivalents. These results demonstrate that even chemically diverse biomass side streams can be converted into purified colloidal lignin suspensions with similar colloidal behavior and functional performance. The findings highlight the potential of low-value agricultural and forest residues as promising raw materials for lignin-based antioxidant and material applications. Full article

Microbial pigments are secondary metabolites that represent promising alternatives to synthetic colorants, offering advantages even over other natural sources. These pigments can be produced independently of seasonality and at low cost, especially when using agro-industrial residues as substrates, and their production can be optimized. Bioprospecting of microorganisms in unexplored environments offers valuable opportunities to discover safer and more efficient pigment producers. Brazil harbors vast biodiversity across multiple biomes, providing a rich reservoir for such discoveries. Biomes such as the Atlantic Forest, Pampa, Pantanal and Coastal Marine are still poorly explored with respect to the bioprospecting of pigment-producing microorganisms, representing a valuable opportunity for the discovery of novel pigments. However, several bottlenecks still hinder the regulatory approval of microbial pigments, particularly those produced by filamentous fungi, due to the frequent co-production of mycotoxins. To overcome these challenges, genetic engineering tools are crucial for eliminating mycotoxin co-production. CRISPR-Cas9, CRISPRi and CRISPR-Cpf1 have become the most widely used techniques for this purpose. Another key application of CRISPR is the enhancement of pigment yields, which can accelerate the industrial adoption of microbial pigments. Together, these two strategies, bioprospecting new environments and genetic engineering, can significantly speed up the transition from synthetic pigments to safer and more eco-friendly microbial alternatives. Full article

Medicinal plants grown outside their native forest habitat may produce phytochemical profiles that differ from wild-harvested material, yet the ecological mechanisms underlying these differences remain poorly synthesized across disciplines. This review proposes that the forest understory functions as a multi-signal elicitation system in which canopy light filtering, arbuscular mycorrhizal fungi (AMF), and above-ground biotic interactions collectively shape secondary metabolite profiles. AMF-mediated induced systemic resistance and above-ground biotic interactions operate through confirmed jasmonate-mediated pathways. Sunfleck-driven reactive oxygen species signaling is hypothesized but untested, and the red-to-far-red ratio modulated phytochrome B pathway characterized in Arabidopsis remains unconfirmed in shade-tolerant species. Using three saponin-rich medicinal plants (Panax vietnamensis, Panex quinquefolius, and Paris polyphylla) as case studies, we formalize this as a testable chemical terroir hypothesis with three falsifiable predictions. We also translate it into an ecological co-cultivation design principle with three production levels and a two-step operational framework, and identify priority experiments, analytical methods, and implementation challenges needed for validation. These contributions bridge forest ecology and medicinal plant science while identifying critical evidence gaps requiring resolution before field implementation. Full article

Wildfires are an increasingly recurrent disturbance in Mediterranean forest landscapes, yet fire severity assessment remains limited in data-scarce regions such as Lebanon. This study aims to assess wildfire severity patterns and identify the main environmental drivers influencing fire severity across the forests of Akkar, northern Lebanon, within a Digital Landscapes framework. Fire severity was mapped using the Differenced Normalized Burn Ratio (dNBR) derived from multi-temporal Landsat-8 imagery (2013–2024) processed in Google Earth Engine. Vegetation productivity was assessed through annual Net Primary Productivity (NPP), while topographic variables (elevation, slope, and aspect) were derived from a Digital Elevation Model. The results reveal heterogeneous fire severity patterns over the study period and pronounced spatial variability in NPP, with no consistent linear relationship between productivity and fire severity. Principal Component Analysis (PCA) was applied to explore multivariate relationships between fire severity, productivity, and terrain. PCA results show that the first two components explain 77.4% of the total variance, indicating that fire severity is primarily structured by topographic factors, particularly elevation and solar exposure, while vegetation productivity plays a secondary role. These findings highlight the dominant influence of terrain on wildfire severity in Mediterranean mountainous landscapes, and demonstrate the value of integrating remote sensing, cloud-based platforms, and multivariate analysis for fire assessment in data-scarce regions. The study contributes to the advancement of Digital Landscapes approaches by providing a scalable and data-driven framework for understanding fire dynamics and supporting future landscape management and risk assessment strategies. Full article

Organic farming has gained increasing relevance worldwide due to its environmental benefits and its prominent role in sustainable food systems; however, the persistence of organic farms remains uneven across regions, particularly within the European Union. While the number of organic farms has grown overall in the EU, significant exits from organic production highlight the need to better understand the factors shaping farm survival, especially in newer Member States, where organic conversion and maintenance support schemes are often implemented through area-based CAP payments. This study aims to identify the structural and contextual determinants of short-term organic farm persistence in Hungary within a broader European context. Using farm-level data for the period 2020–2023, including Standard Output (SO) indicators, we applied a combined modelling framework based on Logistic Regression, Decision Trees, and Random Forest algorithms to assess the relative importance of economic, structural, and regional variables. The results show that organic farm persistence is primarily driven by structural characteristics such as farm size, economic scale, degree of conversion to organic farming and regional embeddedness, while production specialization and organizational features play a secondary, conditional role. The convergence of results across modelling approaches indicates that survival is shaped by hierarchical structural constraints rather than isolated management decisions. Our findings suggest that policy measures aiming to stabilize and expand the organic sector should move beyond uniform incentives, such as area-based payments, and should place greater emphasis on the structural conditions of farms and region-specific support mechanisms. Full article

The use of bio-based and biodegradable plastic products (BBpPs) ensures the mitigation of environmental effects of fossil-based plastics, especially in humanitarian crises where waste management is challenging. Polyhydroxyalkanoates (PHAs) are promising biodegradable biopolymers that are biocompatible and do not cause microplastic pollution. However, experimental assessment of PHA biodegradation is challenged by its time- and resource-intensiveness. In this study, a comprehensive computational Quantitative Structure–Activity Relationship (QSAR)-based approach was developed to predict biodegradability of short chain length (scl)-PHA-based formulations consisting of various additives and building blocks. A novel curated dataset for the (scl)-PHA poly(-3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV), with literature-reported environmental and biodegradation parameters from lab-scale experiments in soil, marine, freshwater and compost systems, was constructed and used to develop and validate the introduced approach. Random forest (RF) and Extreme Gradient Boosting (XGBoost) machine learning (ML) models were optimized and validated with cross-validation and test set predictions. The optimal models reported high accuracy values of the coefficient of determination R², indicating excellent relationships between structure and biodegradation metrics. Further analysis of descriptor variable importance confirmed that biopolymer biodegradability was favorably affected by biodegradation time, while mechanisms, environmental conditions, and additives contributed secondary yet physically consistent effects. The proposed QSAR framework demonstrated a robust and interpretable web-based tool for predicting the environmental fate of PHBV in natural environments and supported the sustainable safe-by-design (SSbD) approach of next-generation biodegradable polymers. Full article

Biomass pyrolysis has emerged as a flexible platform for converting low-value residues into higher-value energy carriers (bio-oil, biochar and gas) and carbon-rich materials, with realistic potential for negative emissions when biochar is deployed in long-lived sinks. Over the last decade, three developments have driven the field forward: first, a finer mechanistic understanding of devolatilization and secondary reactions; second, major improvements in analytical techniques for characterising feedstocks and products; and third, more rigorous techno-economic and life-cycle assessments that place pyrolysis in a broader energy-system context. Recent experimental work on forestry and agro-industrial residues has clarified how biomass composition, ash chemistry and operating conditions jointly govern product yields, energy content and stability. Parallel advances in GC×GC–MS, high-resolution mass spectrometry, NMR and thermogravimetric methods have shifted the discussion from bulk “bio-oil” and “char” to families of molecules and well-defined structural domains, which can be deliberately targeted by reactor and catalyst design. Data-driven models, ranging from support vector machines applied to TGA curves to ANFIS and random forests for yield prediction, are now accurate enough to support process screening and multi-objective optimisation. At the system level, commercial fast pyrolysis biorefineries report overall useful energy efficiencies on the order of 80–86%, while slow pyrolysis configurations centred on biochar can be economically viable when carbon storage and co-products are appropriately valued. Thermodynamic analyses confirm that indirect gasification via fast-pyrolysis oil sacrifices some energy and exergy efficiency relative to direct solid-biomass gasification but may offer logistical and integration advantages. This review synthesises recent work on (i) feedstock and process characterisation; (ii) state-of-the-art analytical methods for bio-oil, biochar and gas; (iii) modelling and machine-learning tools; and (iv) energy-system deployment of pyrolysis products. Throughout, the emphasis is on how characterisation and modelling inform concrete design choices and on the trade-offs that arise when pyrolysis is considered as part of a wider decarbonisation portfolio. By integrating laboratory-scale characterisation with system-level modelling, this review aligns biomass pyrolysis with several United Nations Sustainable Development Goals (SDGs). The optimisation of thermochemical conversion pathways for forestry and agro-industrial residues directly supports SDG 7 (Affordable and Clean Energy) by enhancing the efficiency of bio-oil and syngas production. Furthermore, the deployment of biochar as a stable carbon sink for negative emissions and soil amendment addresses SDG 13 (Climate Action) and SDG 15 (Life on Land). By converting low-value waste streams into high-value energy carriers and chemicals within a circular bioeconomy framework, the research further contributes to SDG 12 (Responsible Consumption and Production) and SDG 9 (Industry, Innovation and Infrastructure). Full article

Canker and dieback diseases caused by fungal pathogens represent an increasing threat to woody plants in both urban and forest environments, where sustainable management options are urgently needed. In this study, the biocontrol potential of Bacillus strain N1 was investigated against Neofusicoccum parvum and Gnomoniopsis smithogilvyi, causal agents of canker diseases on Eucalyptus globulus and Castanea sativa, respectively. The whole-genome sequence confirmed the taxonomic identification of strain N1 as B. velezensis, showing high average nucleotide identity and digital DNA–DNA hybridization values with reference strains. AntiSMASH analysis revealed the presence of multiple biosynthetic gene clusters associated with the production of antimicrobial secondary metabolites, including polyketides, non-ribosomal peptides, and lipopeptides, reflecting strain N1’s genomic potential to produce compounds that may contribute to its antifungal activity. Moreover, B. velezensis strain N1 significantly inhibited the growth of N. parvum and G. smithogilvyi and showed a biocontrol efficacy on detached eucalyptus and chestnut shoots. In both preventive and curative treatments and pathosystems, the application of B. velezensis N1 resulted in a significant reduction in the length of necrotic lesions, compared to pathogen-only controls, while no phytotoxic effects were observed on treated shoots. Overall, this study supported B. velezensis N1 as a promising candidate for the sustainable control of canker-associated pathogens in woody plants. Full article