Search Results (27)

Carbapenem-resistant Klebsiella pneumoniae (CR-Kp) is eroding therapeutic options for urinary tract infections. We isolated a multidrug-resistant strain from the urine of a chronically bacteriuric patient and confirmed its identity by Vitek-2 and MALDI-TOF MS. Initial disk-diffusion profiling against 48 antibiotics revealed susceptibility to only 5 agents. One month later, repeat testing showed that tetracycline alone remained active, highlighting the strain’s rapidly evolving resistome. Given the scarcity of drug options, we performed an “aromatogram” with seven pure essential oils, propolis, and two commercial phytotherapeutic blends. Biomicin Forte^® produced a 30 mm bactericidal halo, while thyme, tea tree, laurel, and palmarosa oils yielded clear inhibition zones of 11–22 mm. These in vitro data demonstrate that carefully selected plant-derived products can target CR-Kp where conventional antibiotics fail. Integrating aromatogram results into One Health’s stewardship plans may therefore help preserve last-line antibiotics and provide adjunctive options for persistent urinary infections. Full article

Climate-amplified extreme heat events are particularly dangerous for city dwellers. Nature-based solutions such as urban greening may serve as an effective preventative strategy against extreme heat. Driven by historical injustices such as redlining, disadvantaged communities often face limited green space and a heightened risk of vulnerability to extreme heat in urban environments. This paper investigates community engagement strategies for heat-vulnerable community participation in urban greening research as a part of a broader transdisciplinary environmental research praxis focused on multistakeholder co-creation. We conducted semi-structured interviews with community leaders in heat-vulnerable neighborhoods in New York City to explore community co-creation in the design and implementation of tree planting, and compared these themes with interviews with urban tree professionals and other community groups. Overall, the participants agreed on broad themes of environmental justice, intergenerational engagement, community building, and socioecological relationships, although community leaders differed in both a greater emphasis of experiential knowledge and reduced focus on volunteer community stewardship. The findings inform our research process and associated community engagement, including building online resources and addressing community-specific concerns during the research process. We conclude by recommending future steps for facilitating multistakeholder conversations to build inclusive and equitable urban greening heat-adaptive strategies. Full article

Background: Antimicrobial resistance (AMR) poses a growing threat to veterinary medicine and food safety. This study examines Escherichia coli antibiotic resistance patterns in ducks, focusing on multidrug-resistant (MDR) strains. Understanding resistance patterns and predicting MDR occurrence are critical for effective intervention strategies. Methods: E. coli isolates were collected from duck samples across multiple regions. Descriptive statistics and resistance frequency analyses were conducted. A decision tree classifier and a neural network were trained to predict MDR status. Cross-resistance relationships were visualized using graph-based models, and Monte Carlo simulations estimated MDR prevalence variations. Results: Monte Carlo simulations estimated an average MDR prevalence of 79.6% (95% CI: 73.1–86.1%). Key predictors in MDR classification models were enrofloxacin, neomycin, amoxicillin, and florfenicol. Strong cross-resistance associations were detected between neomycin and spectinomycin, as well as amoxicillin and doxycycline. Conclusions: The high prevalence of MDR strains underscores the urgent need to revise antibiotic usage guidelines in veterinary settings. The effectiveness of predictive models suggests that machine learning tools can aid in the early detection of MDR, contributing to the optimization of treatment strategies and the mitigation of resistance spread. The alarming MDR prevalence in E. coli isolates from ducks reinforces the importance of targeted surveillance and antimicrobial stewardship. Predictive models, including decision trees and neural networks, provide valuable insights into resistance trends, while Monte Carlo simulations further validate these findings, emphasizing the need for proactive antimicrobial management. Full article

Background/Objectives: Infections in dogs caused by methicillin-resistant staphylococci (MRS) present limited treatment options. This study’s objective was to investigate the molecular epidemiology of Staphylococcus spp. cultured exclusively from clinical canine skin and ear samples in Queensland, Australia, using whole-genome sequencing (WGS). Methods: Forty-two Staphylococcus spp. isolated from clinical canine skin and ear samples, from an unknown number of dogs, were sourced from two veterinary diagnostic laboratories between January 2022 and May 2023. These isolates underwent matrix-assisted laser desorption ionisation– time of flight bacterial identification, minimum inhibitory concentration testing using Sensititre^TM plates and WGS. Phylogenetic trees and core genome multilocus sequence typing (cgMLST) minimum spanning trees (MSTs) were constructed. Results: The isolates included methicillin-resistant and -sensitive S. pseudintermedius (MRSP: 57.1%, 24/42; and MSSP: 19.1%, 8/42), methicillin-resistant and -sensitive S. coagulans (MRSC: 14.3%, 6/42; and MSSC: 2.4%, 1/42) and methicillin-resistant coagulase-negative staphylococci (MR-CoNS: 7.1%, 3/42). Thirty-nine isolates were included after WGS, where all MRS harboured the mecA gene. Eighteen sequence types (STs) were identified, including three novel MRSP and six novel MSSP STs. MRSP ST496-V-VII (23%; 9/39) and MRSP ST749-IV-(IVg) (12.8%; 5/39) were commonly isolated. Phylogenetic analysis of single nucleotide polymorphisms showed that MRSP, MRSC and MSSC were similar to globally isolated staphylococci from canine skin and ear infections. Using cgMLST MSTs, MRSP isolates were not closely related to global strains. Conclusions: Our findings revealed a genotypically diverse geographical distribution and phylogenetic relatedness of staphylococci cultured from clinical canine skin and ear samples across Queensland. This highlights the importance of ongoing surveillance to aid in evidence-based treatment decisions and antimicrobial stewardship. Full article

Forests contain just under 58% of all known species globally, with approximately 61% of these found in countries with Forest Stewardship Council (FSC)-certified forests. Few studies have directly analyzed the association between biodiversity and certification, often focusing on limited geographical or temporal scopes. There is a lack of understanding regarding the socio-political and ecological drivers of FSC certification’s relationship with biodiversity conservation. We assess the associations between country-level characteristics and the relationship between FSC’s forest management (FSC-FM) certification area and independently made biodiversity estimates from the International Union for Conservation of Nature (IUCN). Specifically, using generalized random forests (GRF) and data from 91 countries between 2008 and 2019, we examine the associated factors that govern FSC-FM certifications relationship with percentage threatened species. The results indicate that increasing FSC-FM-certified areas is linked to a reduction in the percentage of threatened species by 0.1 to 0.15. Moreover, FSC-FM certifications show a positive relationship with biodiversity in regions with high population densities and significant tree cover loss. Enhanced perception of corruption control and reduced extraction of non-forestry resources further strengthen this association. These findings provide the FSC with strategic insights to expand FM certification, contributing to biodiversity conservation through sustainable forest management. Full article

Within the U.S., there is a growing need to integrate environmentally friendly practices into conventional agriculture. Agroforestry enhances environmental and resource stewardship in agricultural landscapes while offering potential economic benefits to farmers. Despite rising interest, limited information on its application in the U.S. hinders development efforts. A spatiotemporal analysis of current farm operations can provide crucial insights. This study examined patterns of agroforestry and tree crop adoption in the U.S. Corn Belt using USDA Census data (2012, 2017, and 2022) and spatial tools (Global Moran’s I, Local Moran’s I, and Moran scatterplots). The tree crops included in the analysis were chestnut (Castanea spp.), hazelnut (Corylus spp.), improved northern pecan (Carya illinoinensis), elderberry (Sambucus spp.), and pawpaw (Asimina triloba). The results showed increasing farm operations with agroforestry and tree crops over time for all census periods. Agroforestry had the strongest spatial cluster patterns, with Local Moran’s I revealing R2 values rising from 0.30 to 0.35 between 2017 and 2022. Chestnut, hazelnut, and improved pecan had clustered spatial patterns, but had decreasing spatial autocorrelations from 2012 to 2022, while elderberry clustered in 2017 but not 2022. This study reveals an upward trend in agroforestry adoption and the spatial expansion of certain tree crops in the U.S. Corn Belt, highlighting potential for region-specific agroforestry development. The findings offer insights to guide strategies and programs supporting sustainable agricultural practices. Full article

Background/Objectives: Inexperienced dentists and dental students are especially prone to misdiagnosis, and this represents a huge problem regarding antimicrobial stewardship. We aimed to develop a mobile app for rational antibiotic prescribing in dentistry based on local–systemic symptoms and patient factors, rather than solely on diagnosis, to tackle misdiagnosis. Methods: The study involved 64 participants, 50 of which were third-year dental students attending a pharmacology course focusing on antimicrobials, comprising lectures and practical sessions without (noAPP group, n = 22) or with (APP group n = 28) the assistance of a mobile application. The other 14 participants were practicing dentists who decided to register and use the application. All registered users of the application were asked to take a feedback survey, while learning outcomes were evaluated via a pharmacology quiz. Results: A decision tree was used for application development. In total, 76 impressions were collected on the application. The majority of the impressions were related to odontogenic–endodontic infections. Multiple linear regression analysis did not reveal differences in survey responses between practicing dentists and undergraduate students in the feedback survey responses. There was a significant difference in the mean pharmacology test scores between the noAPP and APP groups (5.50 ± 1.80 vs. 7.21 ± 1.03, p = 0.0001). Conclusions: The dentalantibiotic.com application was developed to support rational antibiotic prescribing, in view of tackling misdiagnosis, among inexperienced dentists, as well as to assist in undergraduates’ pharmacology learning, and the current study shows its large impact as an educational tool. The majority of participants considered it easy to use, efficient in facilitating the right antibiotic choice, and useful for everyday decision-making. Full article

This work conducts a rigorous examination of the economic influence of tourism in Saudi Arabia, with a particular focus on predicting tourist spending patterns and classifying spending behaviors during the COVID-19 pandemic period and its implications for sustainable development. Utilizing authentic datasets obtained from the Saudi Tourism Authority for the years 2015 to 2021, the research employs a variety of machine learning (ML) algorithms, including Decision Trees, Random Forests, K-Neighbors Classifiers, Gaussian Naive Bayes, and Support Vector Classifiers, all meticulously fine-tuned to optimize model performance. Additionally, the ARIMA model is expertly adjusted to forecast the economic landscape of tourism from 2022 to 2030, providing a robust predictive framework for future trends. The research framework is comprehensive, encompassing diligent data collection and purification, exploratory data analysis (EDA), and extensive calibration of ML algorithms through hyperparameter tuning. This thorough process tailors the predictive models to the unique dynamics of Saudi Arabia’s tourism industry, resulting in robust forecasts and insights. The findings reveal the growth trajectory of the tourism sector, highlighted by nearly 965,073 thousand tourist visits and 7,335,538 thousand overnights, with an aggregate tourist expenditure of SAR 2,246,491 million. These figures, coupled with an average expenditure of SAR 89,443 per trip and SAR 9198 per night, form a solid statistical basis for the employed predictive models. Furthermore, this research expands on how ML and AI innovations contribute to sustainable tourism practices, addressing key aspects such as resource management, economic resilience, and environmental stewardship. By integrating predictive analytics and AI-driven operational efficiencies, the study provides strategic insights for future planning and decision-making, aiming to support stakeholders in developing resilient and sustainable strategies for the tourism sector. This approach not only enhances the capacity for navigating economic complexities in a post-pandemic context, but also reinforces Saudi Arabia’s position as a premier tourism destination, with a strong emphasis on sustainability leading into 2030 and beyond. Full article

Mixed forests created by incorporating nitrogen-fixing tree species offer enhanced ecological advantages compared with forests consisting of only one type of tree species. These benefits include habitat rehabilitation and the promotion of biodiversity. Nevertheless, the impact of introducing nitrogen-fixing tree species on ecosystem carbon (C), nitrogen (N), and phosphorus (P) sequestration and storage capacity in the Loess Plateau of China remains inadequately explored. To examine changes in the sequestration and storage capacity of ecosystem C, N, and P, the mixed plantations of P. tabulaeformis and H. rhamnoides (H_rP_t) were selected as the research object, and the pure plantations of H. rhamnoides (H_r) and P. tabulaeformis (P_t) were selected as the control. The results indicated that in comparison to the pure forest, the ecosystem in H_rP_t significantly increased C and N stocks but decreased P stocks. In addition, C, N, and P stocks in the soil layer accounted for more than 60% of the C, N, and P stocks in the pure and mixed forest ecosystems compared with the vegetation layer. Moreover, H_rP_t significantly improved ecosystem C and N sequestration rates relative to the pure forest but decreased P sequestration rates. Furthermore, the soil physicochemical properties can be inferred from the redundancy analysis showing 66.79% and 0.06% in H_r, 44.84% and 0.06% in P_t, as well as 44.28% and 0.04% in H_rP_t, respectively. In conclusion, compared with the pure forest, the introduction of N-fixing tree species was more conducive to the accumulation of C and N. The results offer substantial significance for the scientific guidance of vegetation restoration in degraded landscapes and the stewardship of mixed forests in the Loess Hilly Region, providing essential data for nutrient storage in ecosystems. Full article

The global human population is projected to reach 9.7 billion by 2050, increasing the demand for food and fiber, but also raising concerns about the environmental impact of agricultural production scaled to meet their needs. Silvopastures—integrated tree–forage–livestock systems—have emerged as a viable practice to meet the required productivity and environmental stewardship outcomes. This review consolidates the extensive research on silvopasture practices in the United States and highlights the benefits of these systems. A comprehensive literature search across databases such as ScienceDirect and Google Scholar revealed 152 publications on silvopastures in the United States since 2000, indicating growing interest. These studies have primarily focused on the impacts of silvopastures on livestock welfare and productivity, forage production and composition, soil health and nutrient dynamics, and socio-economic factors. Geographical distribution analysis indicated that the research is more focused in the Southeastern United States, with Florida, Virginia, Alabama, Missouri, and Arkansas being the top five contributing states. The review also offers insights into the tree and forage species used across these states and discusses the challenges to silvopasture adoption among producers and land managers while exploring future prospects. This review may be used as a resource for understanding the multifaceted dimensions of silvopasture adoption, providing insights for researchers, policymakers, and practitioners alike. Full article

Cities worldwide are grappling with complex urban environmental injustices. While environmental justice as a concept has gained prominence in both academia and policy, operationalizing and implementing environmental justice principles and norms remains underexplored. Notably, less attention has been given to centering the perspectives and experiences of community-based actors operating at the grassroots level, who can inform and strengthen urban environmental justice practice. Through ethnographic, participant-as-observer methods, interviews, and geovisualizations, this study explores the perspectives, experiences, knowledge, and practices of community-based urban forest stewards in Philadelphia, Pennsylvania (United States) who are invested in addressing environmental injustices through urban tree-planting and stewardship. Interviewees were asked how they were addressing issues of distribution, procedure, and recognition in urban forest planning and practice, as well as the socio-political and institutional factors that have influenced their perspectives and practices. Particular attention is given to how urban forest stewards implement recognitional justice principles. Findings from this study exposed several complex socio-political challenges affecting steward engagement in community-led tree initiatives and the broader pursuit of environmental justice, including discriminatory urban planning practices, gentrification concerns, underrepresentation of Black and Latinx voices in decision-making, volunteer-based tree-planting models, and tree life cycle costs. Nevertheless, urban forest stewards remain dedicated to collective community-building to address environmental injustices and stress the importance of recognizing, listening to, dialoguing with, and validating the perspectives and experiences of their neighbors as essential to their process. Full article

In the context of escalating energy demands and the quest for sustainable waste management solutions, this paper evaluates the efficacy of three machine learning methods—ElasticNet, Decision Trees, and Neural Networks—in predicting energy recovery from municipal waste across the European Union. As renewable energy sources increasingly dominate the energy production landscape, the integration of Waste-to-Energy (WTE) processes presents a dual advantage: enhancing waste management and contributing to the renewable energy mix. This study leverages a dataset incorporating economic and environmental indicators from 25 European countries, spanning 2013–2020, to compare the predictive capabilities of the three machine learning models. The analysis reveals that Neural Networks, with their intricate pattern recognition capabilities, outperform ElasticNet and Decision Trees in predicting energy recovery metrics, as evidenced by superior performance in key statistical indicators such as R-value, Mean Squared Error (MSE), and Mean Absolute Error (MAE). The comparative analysis not only demonstrates the effectiveness of each method but also suggests Neural Networks as a pivotal tool for informed decision-making in waste management and energy policy formulation. Through this investigation, the paper contributes to the sustainable energy and waste management discourse, emphasizing the critical intersection of advanced technologies, policy considerations, and environmental stewardship in addressing contemporary energy challenges. Full article

Rivers across the globe experience and respond to changes within the riparian corridor. Disturbance of the riparian corridor can affect warmwater, intermediate, and coldwater streams, which can negatively influence instream physical structure and biological communities. This study focused on assessing the influence of the riparian habitat on instream structure within the Whitewater River, a coldwater stream system within an agricultural watershed in southeastern Minnesota, USA. To understand the influence of the riparian zone on the physical instream habitat, twenty variables (riparian, n = 9; instream, n = 11) were measured at 57 sites across three forks of the Whitewater using a transect method every 10 m across a 150 m reach. We used a modified Wentworth scale approach to assess coarse and fine substrates to describe habitat conditions. Canonical correlation detected significant associations between riparian and instream variables across the river forks, and indicated that wider riparian buffers, more bank grass and shrubs, longer overhanging vegetation, limited bare soil, and more rocks on banks were significantly associated with increased instream cover, high levels of coarse substrates with reduced embeddedness, increased pool habitats, and reduced fine sediments. In contrast, excessive fine sediments, lack of riffle habitat, reduced coarse substrates, and high width to depth ratios indicative of an impaired instream habitat were associated with narrow riparian buffers and high percentages of bare soil on banks. Riparian corridors have the capacity to enhance and protect physical instream habitats and overall ecosystem health when managed properly. Wide, grassy riparian corridors with stable banks, overhanging vegetation, and limited shade from trees should protect and/or enhance the instream physical habitat, providing the structural diversity favored by aquatic communities. We recommend revising the current Best Management Practices to include monitoring for impairments in the riparia, while promoting and developing good land stewardship with private landowners which can be effective in improving river ecosystems in agricultural settings. Full article

Hundreds of thousands of hectares of bushland and accompanying biodiversity were lost over a few short weeks during the Black Summer fires of 2019–2020 along the east coast of Australia. On the night of 19 December 2019, fire swept up the escarpment from the coast, slowed down with the thick understory of temperate rainforest and burnt through the lower dry sclerophyll forest on Plumwood Mountain. The aftermath of the bare, burnt landscape meant a significant change in the structure and diversity of vegetation, while the consequences of the fire also brought about fundamental changes to Plumwood as a conservation and heritage organisation. Plumwood Mountain as a place, the individual plumwood tree as an agentive being, Val Plumwood as a person and Plumwood as an organisation are all an entangled form of natureculture and indicative of a practice-based conservation humanities approach. Conservation as part of the environmental humanities can offer an alternative to mainstream models of conservation with the potential to instigate active participation on the ground, engaging in a different form of stewardship. Full article

Valorizing natural resources through sustainable and eco-friendly processes is a cornerstone in pursuing a greener and more sustainable future. This study focuses on the green extraction of valuable compounds from rubber seed trees (Hevea brasiliensis). This underutilized resource has the potential to yield bioactive compounds of economic and ecological significance. We explore the application of environmentally friendly extraction techniques, including supercritical fluid extraction (SFE), microwave-assisted extraction (MAE) and ultrasound-assisted extraction (UAE), to harness the bioactive potential of rubber seeds. Our research encompasses a comprehensive analysis of the extracted compounds, including their characterization and quantification using state-of-the-art analytical techniques. Environmental and economic sustainability aspects are evaluated, shedding light on the green extraction processes’ ecological footprint and economic feasibility. The paper also delves into these extracted compounds’ diverse applications and utilization prospects, ranging from pharmaceuticals and nutraceuticals to cosmetic and industrial products. We discuss the commercial potential, market opportunities, and emerging trends these sustainable endeavours may shape. In conclusion, this study paves the way for a more sustainable path in harnessing valuable compounds from rubber seed trees, exemplifying the potential for green extraction techniques to play a pivotal role in the journey toward environmental stewardship and economic prosperity. Full article