Search Results (10,029)

As agricultural land continues to expand, the conversion of forests to farmland has intensified, significantly altering the structure and function of agroecosystems. However, the dynamic ecological responses and their interactions with economic outcomes remain insufficiently modeled. This study proposes an integrated framework that combines a dynamic food web model with the Eco-Economic Benefit and Sustainability (EEBS) model, utilizing empirical data from Brazil and Ghana. A system of ordinary differential equations solved using the fourth-order Runge–Kutta method was employed to simulate species interactions and energy flows under various land management strategies. Reintroducing key species (e.g., the seven-spot ladybird and ragweed) improved ecosystem stability to over 90%, with soil fertility recovery reaching 95%. In herbicide-free scenarios, introducing natural predators such as bats and birds mitigated disturbances and promoted ecological balance. Using XGBoost (Extreme Gradient Boosting) to analyze 200-day community dynamics, pest control, resource allocation, and chemical disturbance were identified as dominant drivers. EEBS-based multi-scenario optimization revealed that organic farming achieves the highest alignment between ecological restoration and economic benefits. The model demonstrated strong predictive power ($R^2$ = 0.9619, RMSE = 0.0330), offering a quantitative basis for green agricultural transitions and sustainable agroecosystem management. Full article

Evaluation of the effectiveness of state policy instruments is a permanent element of economic science. This paper addresses the issue of investment support under the Common Agricultural Policy (CAP). Using data on Polish farms from 2015–2023, a Propensity Score Matching–Difference in Differences (PSM-DiD) analysis was conducted to assess changes in the economic results of agricultural producers that invest using this support. The comparison of the economic results achieved by supported investors with both non-investing agricultural producers and unsupported investors is a distinguishing element of this study. The relatively rarely used Competitivness Index (CI), which measures the ratio of earned income to the sum of the alternative use of the owned means of production, was used. The positive change in the CI during the analyzed period was 0.14 higher for supported investors than non-investors. No statistically significant change was found were compared to unsupported investors. A clear increase in income, total fixed assets, liabilities, and the level of production in the population of producers using support in relation to non-investors and investing without CAP support was also observed. However, in relationships with investors using their own funds, these differences were mainly due to the difference in the level of investments and were not statistically significant when introducing a correction regarding the scale of the investment. The obtained results remain in line with the results of research shown by a significant part of economists undertaking a similar issue. Full article

With the rapid development of the social economy, human activities have increasingly disrupted water environments, and the continuous input of pollutants poses significant challenges for water environment management. Taking the Xiaoxingkai Lake basin as the study area, this paper develops a social–economic–water environment model based on the system dynamics methodology, incorporating subsystems for population, agriculture, and water pollution. The model focuses on four key indicators of pollution severity, namely, total nitrogen (TN), total phosphorus (TP), chemical oxygen demand (COD), and ammonia nitrogen (NH₃-N), and simulates the changes in pollutant loads entering the river under five different scenarios from 2020 to 2030. The results show that agricultural non-point sources are the primary contributors to TN (79.5%) and TP (73.7%), while COD primarily originates from domestic sources (64.2%). NH₃-N is mainly influenced by urban domestic activities (44.7%) and agricultural cultivation (41.2%). Under the status quo development scenario, pollutant loads continue to rise, with more pronounced increases under the economic development scenario, thus posing significant sustainability risks. The pollution control enhancement scenario is most effective in controlling pollutants, but it does not promote socio-economic development and has high implementation costs, failing to achieve coordinated socio-economic and environmental development in the region. The dual-reinforcement scenario and moderate-reinforcement scenario achieve a balance between pollution control and economic development, with the moderate-reinforcement scenario being more suitable for long-term regional development. The findings can provide a scientific basis for water resource management and planning in the Xiaoxingkai Lake basin. Full article

Barn districts—ensembles of agricultural buildings situated at the edges of rural settlements—once played a key role in the spatial and economic organization of agrarian communities in Central Europe. Today, many of these structures remain marginalized and underexplored in contemporary landscape and heritage planning. This paper presents a comparative study of six barn districts in Poland’s Kraków-Częstochowa Upland, where vernacular construction, ecological adaptation, and local tradition shaped distinctive rural–urban interfaces. We applied a mixed-methods approach combining cartographic and archival analysis, field surveys, and interviews with residents and experts. The research reveals consistent patterns of landscape transformation, functional decline, and latent adaptive potential across varied morphological and material typologies. Despite differing levels of preservation, barn districts retain symbolic, spatial, and socio-cultural value for communities and local landscapes. The study emphasizes the importance of reintegrating these marginal heritage structures through adaptive reuse strategies rooted in the values of the New European Bauhaus—sustainability, aesthetics, and inclusion. The findings contribute to broader discussions on rural socio-ecological resilience and landscape-based development, highlighting how place-based strategies can bridge past identities with future-oriented spatial planning. Full article

To evaluate water pollution status and sustainable development potential in the Huai River Basin, this study focused on the spatiotemporal evolution and influencing factors of the grey water footprint (GWF) across 35 cities in the basin from 2005 to 2020. This study quantifies the GWF from agricultural, industrial, and domestic perspectives and analyzes its spatial disparities by incorporating spatial autocorrelation analysis. The Tapio decoupling model was applied to explore the relationship between pollution and economic growth, and geographic detectors along with the STIRPAT model were utilized to identify driving factors. The results revealed no significant global spatial clustering of GWF in the basin, but a pattern of “high in the east and west, low in the north and south” emerged, with high-value areas concentrated in southern Henan and northern Jiangsu. By 2020, 85.7% of cities achieved strong decoupling, indicating improved coordination between the environment and economy. Key driving factors included primary industry output, crop sown area, and grey water footprint intensity, with a notable interaction between agricultural output and grey water footprint intensity. The quantitative analysis based on the STIRPAT model demonstrated that seven factors, including grey water footprint intensity and total crop sown area, exhibited significant contributions to influencing variations. Ranked by importance, these factors were grey water footprint intensity > total crop sown area > urbanization rate > population size > secondary industry output > primary industry output > industrial wastewater discharge, collectively explaining 90.2% of the variability in GWF. The study provides a robust scientific basis for water pollution control and differentiated management in the river basin and holds significant importance for promoting sustainable development of the basin. Full article

The activities of birds present increasing challenges in agriculture, aviation, and environmental conservation. This has led to economic losses, safety risks, and ecological imbalances. Attempts have been made to address the problem, with traditional deterrent methods proving to be labour-intensive, environmentally unfriendly, and ineffective over time. Advances in artificial intelligence (AI) and the Internet of Things (IoT) present opportunities for enabling automated real-time bird detection and repellence. This study reviews recent developments (2020–2025) in AI-driven bird detection and repellence systems, emphasising the integration of image, audio, and multi-sensor data in IoT and edge-based environments. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework was used, with 267 studies initially identified and screened from key scientific databases. A total of 154 studies met the inclusion criteria and were analysed. The findings show the increasing use of convolutional neural networks (CNNs), YOLO variants, and MobileNet in visual detection, and the growing use of lightweight audio-based models such as BirdNET, MFCC-based CNNs, and TinyML frameworks for microcontroller deployment. Multi-sensor fusion is proposed to improve detection accuracy in diverse environments. Repellence strategies include sound-based deterrents, visual deterrents, predator-mimicking visuals, and adaptive AI-integrated systems. Deployment success depends on edge compatibility, power efficiency, and dataset quality. The limitations of current studies include species-specific detection challenges, data scarcity, environmental changes, and energy constraints. Future research should focus on tiny and lightweight AI models, standardised multi-modal datasets, and intelligent, behaviour-aware deterrence mechanisms suitable for precision agriculture and ecological monitoring. Full article

Since its first appearance as a human pathogen in 1976, Legionella pneumophila has been identified as a causative agent of community-acquired pneumonia (CAP). It survives in rivers, bays, lakes, and water reservoirs, and it is categorized as the fourth most common causative agent of CAP leading to hospitalization. We aimed to investigate patterns in which environmental, seasonal and regional factors may affect the prevalence of Legionnaires’ disease in Crete during the last two decades (2000–2022).The data used originated from the national surveillance database and included any person reported with travel-associated Legionnaires’ disease (TALD) between January 2000 and December 2022. Meteorological data were collected from the National Weather Service. The meteorological variables included (max) temperature (in °C), cloudiness (in octas), wind speed (in knots), and relative humidity (RH) (%). The statistical analysis was based on a case-crossover design with 1:1 matching characteristic. We revealed both seasonal and regional effects on the incidence of Legionnaires’ disease. Cases are significantly more frequent in autumn, in comparison to the other three seasons, while Rethymnon is the prefecture with fewer cases in comparison to Chania or Heraklion. In addition, our research showed that the majority of cases occurred during the years 2017–2018. TALD in Crete is significantly associated with temperature in °C and wind speed in knots. Our research suggests that temporal and spatial factors significantly influence disease cases. These results are in line with studies from foreign countries. The study results aspire to expand our knowledge regarding the epidemiological characteristics of Legionnaires’ disease in relation to local, geographical and meteorological factors on the island of Crete. Full article

Water-related ecosystem services provide a broad range of benefits, including the mitigation of extreme hydrometeorological events, the provision of water for various uses, the support of tourism, and the provision of cultural services. This study assesses the perceptions and accessibility of these services among communities located near the Alafiarou and Okpara dams in Benin and the Bagré dam in Burkina Faso. The methodology involved designing and implementing a questionnaire in KoboCollect, with trained agents deployed to conduct data collection at each of the three sites. Data analysis indicates that respondents identified biodiversity conservation and the provision of drinking water as the most crucial ecosystem services. Over two-thirds of participants reported observing both positive and negative changes in the services provided by rivers and in socio-economic activities since the construction of the dams. While the majority noted improvements in agriculture, irrigation, water quality, fisheries, and flow rates, other changes included biodiversity loss, a decrease in vegetation cover (notably trees and shrubs), an increase in the population of mosquitoes and other insects, and a decline in fishery resources downstream. Despite these challenges, local communities were strongly willing to participate in initiatives aimed at protecting and restoring river ecosystems and their related services. Full article

This study contributes to scientific theory by analyzing the models proposed within the framework of circular agriculture to determine how the three dimensions of sustainability—environmental, economic, and social—are integrated into their implementation. A systematic review was conducted on articles published between 2016 and 2025, indexed in the Scopus and Web of Science databases, as well as the relevant grey literature. The methodology employed an extensive content analysis designed to minimize bias, applying filters related to specific knowledge areas to delimitate the search scope and enhance the precision of the research. The findings reveal that the research on circular agriculture models is predominantly grounded in the principles of the circular economy and its associated indicators. Moreover, these models tend to focus on environmental metrics, often neglecting a comprehensive exploration of the social and economic dimensions of sustainable development. It can be concluded that a significant gap persists in the literature regarding the circularity of agriculture and its socio-economic impacts and the role of regulatory frameworks, aspects that future research must address in order to achieve sustainability in circular agriculture. Full article

This study investigates the production and economic feasibility of biochar for smallholder and family farms in Central Amazonia, with potential implications for other tropical regions. The costs of construction of a prototype mobile kiln and biochar production were evaluated, using small-sized biomass from acai (Euterpe oleracea Mart.) agro-industrial residues as feedstock. The biochar produced was characterised in terms of its liming capacity (calcium carbonate equivalence, CaCO_3eq), nutrient content via organic fertilisation methods, and ash analysis by ICP-OES. Field trials with cowpea assessed economic outcomes, as well scenarios of fractional biochar application and cost comparison between biochar production in the prototype kiln and a traditional earth-brick kiln. The prototype kiln showed production costs of USD 0.87–2.06 kg⁻¹, whereas traditional kiln significantly reduced costs (USD 0.03–0.08 kg⁻¹). Biochar application alone increased cowpea revenue by 34%, while combining biochar and lime raised cowpea revenues by up to 84.6%. Owing to high input costs and the low value of the crop, the control treatment generated greater net revenue compared to treatments using lime alone. Moreover, biochar produced in traditional kilns provided a 94% increase in net revenue compared to liming. The estimated externalities indicated that carbon credits represented the most significant potential source of income (USD 2217 ha⁻¹). Finally, fractional biochar application in ten years can retain over 97% of soil carbon content, demonstrating potential for sustainable agriculture and carbon sequestration and a potential further motivation for farmers if integrated into carbon markets. Public policies and technological adaptations are essential for facilitating biochar adoption by small-scale tropical farmers. Full article

The fungal pathogen Puccinia striiformis f. sp. tritici, which causes yellow rust disease, poses a significant economic threat to wheat production not only in Uzbekistan but also globally, leading to substantial reductions in grain yield. This study aimed to develop yellow rust-resistance wheat lines by introgressing Yr10 and Yr15 genes into high-yielding cultivar Grom using the marker-assisted backcrossing (MABC) method. Grom was crossed with donor genotypes Yr10/6*Avocet S and Yr15/6*Avocet S, resulting in the development of F₁ generations. In the following years, the F₁ hybrids were advanced to the BC₂F₁ and BC₂F₂ generations using the MABC approach. Foreground and background selection using microsatellite markers (Xpsp3000 and Barc008) were employed to identify homozygous Yr10- and Yr15-containing genotypes. The resulting BC₂F₂ lines, designated as Grom-Yr10 and Grom-Yr15, retained key agronomic traits of the recurrent parent cv. Grom, such as spike length (13.0–11.9 cm) and spike weight (3.23–2.92 g). Under artificial infection conditions, the selected lines showed complete resistance to yellow rust (infection type 0). The most promising BC₂F₂ plants were subsequently advanced to homozygous BC₂F₃ lines harboring the introgressed resistance genes through marker-assisted selection. This study demonstrates the effectiveness of integrating molecular marker-assisted selection with conventional breeding methods to enhance disease resistance while preserving high-yielding traits. The newly developed lines offer valuable material for future wheat improvement and contribute to sustainable agriculture and food security. Full article

Ecosystem restoration represents a promising solution for enhancing ecosystem services and environmental sustainability. However, border regions—characterized by ecological fragility and geopolitical complexity—remain underrepresented in ecosystem service and restoration research. To fill this gap, we coupled spatially explicit models (e.g., InVEST and RUSLE) with scenario analysis to quantify the ecosystem service potential that could be achieved in China’s Tibetan borderlands under two interacting agendas: ecological restoration and border-strengthening policies. Restoration feasibility was evaluated through combining local biophysical constraints, economic viability (via restoration-induced carbon gains vs. opportunity costs), operational practicality, and simulated infrastructure expansion. The results showed that per-unit-area ecosystem services in border counties (particularly Medog, Cona, and Zayu) exceed that of interior Tibet by a factor of two to four. Combining these various constraints, approximately 4–17% of the border zone remains cost-effective for grassland or forest restoration. Under low carbon pricing (US$10 t⁻¹ CO₂), the carbon revenue generated through restoration is insufficient to offset the opportunity cost of agricultural production, constituting a major constraint. Habitat quality, soil conservation, and carbon sequestration increase modestly when induced by restoration, but a pronounced carbon–water trade-off emerges. Planned infrastructure reduces restoration benefits only slightly, whereas raising the carbon price to about US$50 t⁻¹ CO₂ substantially expands such benefits. These findings highlight both the opportunities and limits of ecosystem restoration in border regions and point to carbon pricing as the key policy lever for unlocking cost-effective restoration. Full article

In this study, we investigate the return propagation mechanism, hedging effectiveness, and portfolio performance across several common agricultural commodities, crude oil, and S&P 500 index, ranging from July 2000 to June 2024 by using a time-varying parameter vector autoregression (TVP-VAR) connectedness approach and three common multiple assets portfolio optimization strategies. The empirical results show that, the total connectedness peaked during the 2008 global financial crisis, followed by the European debt crisis and the COVID-19 pandemic, while it remained relatively lower at the onset of the Russia-Ukraine conflict. In the transmission mechanism, commodities and S&P 500 index exhibit distinct and dynamic characteristics as transmitters or receivers. Portfolio analysis reveals that, with exception of the COVID-19 pandemic, all three dynamic portfolios outperform the S&P 500 benchmark across major global crises. Additionally, the minimum correlation and minimum connectedness strategies are superior than transitional minimum variance method in most scenarios. Our findings have implications for policymakers in preventing systemic risk, for investors in managing portfolio risk, and for farmers and agribusiness enterprises in enhancing economic benefits. Full article

Seed oil represents a key trait in soybeans, which holds substantial economic significance, contributing to roughly 60% of global oilseed production. This research employed genome-wide association mapping to identify genetic loci associated with oil content in soybean seeds. A panel comprising 341 soybean accessions, primarily sourced from Northeast China, was assessed for seed oil content at Heilongjiang Province in three replications over two growing seasons (2021 and 2023) and underwent genotyping via whole-genome resequencing, resulting in 1,048,576 high-quality SNP markers. Phenotypic analysis indicated notable variation in oil content, ranging from 11.00% to 21.77%, with an average increase of 1.73% to 2.28% across all growing regions between 2021 and 2023. A genome-wide association study (GWAS) analysis revealed 119 significant single-nucleotide polymorphism (SNP) loci associated with oil content, with a prominent cluster of 77 SNPs located on chromosome 8. Candidate gene analysis identified four key genes potentially implicated in oil content regulation, selected based on proximity to significant SNPs (≤10 kb) and functional annotation related to lipid metabolism and signal transduction. Notably, Glyma.08G123500, encoding a receptor-like kinase involved in signal transduction, contained multiple significant SNPs with PROVEAN scores ranging from deleterious (−1.633) to neutral (0.933), indicating complex functional impacts on protein function. Additional candidate genes include Glyma.08G110000 (hydroxycinnamoyl-CoA transferase), Glyma.08G117400 (PPR repeat protein), and Glyma.08G117600 (WD40 repeat protein), each showing distinct expression patterns and functional roles. Some SNP clusters were associated with increased oil content, while others correlated with decreased oil content, indicating complex genetic regulation of this trait. The findings provide molecular markers with potential for marker-assisted selection (MAS) in breeding programs aimed at increasing soybean oil content and enhancing our understanding of the genetic architecture governing this critical agricultural trait. Full article

This study evaluated the antifungal potential of essential oils (EOs): oregano (Origanum vulgare), rosemary (Salvia rosmarinus), clove (Syzygium aromaticum), thyme (Thymus vulgaris), cinnamon (Cinnamomum verum), and basil (Ocimum basilicum). These oils were tested against fungi isolated from banana peels (Musa paradisiaca). The fungi tested were identified through macroscopic and microscopic analyses and DNA sequencing, after being isolated in potato dextrose agar (PDA) medium modified with 0.05% chloramphenicol. Subsequently, the antifungal properties of the tested essential oils were evaluated in vitro at concentrations of 200, 400, 600, 800, and 1000 ppm prepared in a 0.05% Tween 80 solution. Cinnamon EOs showed the highest antifungal activity, significantly inhibiting the growth of pathogens at a concentration of 400 ppm. Other EOs showed moderate effects at higher concentrations: rosemary inhibited fungal growth at 600 ppm, oregano at 800 ppm, and clove at 1000 ppm. These findings highlight the potential of EOs as eco-friendly alternatives to synthetic fungicides, contributing to the development of sustainable agricultural practices and the post-harvest management of bananas. It is recommended to conduct future research to assess the economic viability and practical impacts of large-scale applications. Full article