Sustainable Ecosystem Research Articles

Real-time nitrogen monitoring and management to augment N use efficiency and ecosystem sustainability – A review

Agriculture faces the pressing challenge of feeding a growing population while preserving the environment and natural resources. Nitrogen (N) is an essential nutrient for plant growth, and its availability in soil is a key indicator of fertility. However, the indiscriminate use of N fertilizers can lead to nutrient imbalances and soil degradation, underscoring the need for accurate and efficient soil N management. Traditional sampling and analysis methods are time-consuming and prone to error, making real-time soil N assessments crucial for effective management. Moreover, precise estimation of soil N is vital for monitoring losses, developing targeted fertilizer strategies, and enhancing crop productivity and N use efficiency. Real-time N management, which involves applying N as needed during critical growth stages, can significantly improve its usage efficiency. To achieve this, the leaf color chart offers a simple, inexpensive, and user-friendly solution for assessing N needs based on leaf color, facilitating real-time management. Furthermore, sensors and the Internet of Things (IoT) play a key role in sustainable soil management and crop productivity, contributing to the development of resilient food systems and reducing uncertainty in global food markets. Accurate, rapid, cost-effective methods for assessing soil N levels are essential to achieve these sustainable goals. This review delves into the current status, limitations, and future of N-sensing in precision agriculture, highlighting cutting-edge technologies such as real-time monitoring using remote and proximal sensors, ground-based canopy sensors, drones, and Unmanned Aerial Vehicle (UAV) equipped with high-resolution cameras or multispectral/hyperspectral sensors, Geographic Information Systems (GIS)- Global Positioning Systems (GPS) integration (GIS-GPS), data analysis, Variable Rate Technology (VRT) and crop models for precise N management. By harnessing these innovations, we can revolutionize agriculture, benefiting plant health and promoting a more sustainable future.

The role of telecommunications in enabling Internet of Things (IoT) connectivity and applications

This review paper explores the pivotal role of telecommunications in enabling Internet of Things (IoT) connectivity and applications, providing a comprehensive overview of the current landscape and future prospects. The primary objective is to synthesize existing research and industry insights to highlight how advancements in telecommunications infrastructure and technology have catalyzed the adoption and expansion of IoT. The review systematically examines the evolution of telecommunications technologies, including 4G, 5G, and emerging network protocols such as Narrowband IoT (NB-IoT) and Long-Term Evolution for Machines (LTE-M). It assesses how these technologies enhance IoT connectivity by providing the necessary bandwidth, low latency, and reliability for real-time data exchange and device interoperability. Key findings from the literature reveal that the deployment of 5G networks has been a game-changer for IoT, offering unprecedented speeds and connectivity capabilities that support a wide range of applications in smart cities, healthcare, agriculture, and industrial automation. Additionally, the paper discusses the role of telecommunications in addressing challenges related to security, scalability, and energy efficiency in IoT deployments. The review concludes that telecommunications are integral to the growth and sustainability of IoT ecosystems. As telecommunications technology continues to advance, its ability to support increasingly complex and ubiquitous IoT applications will drive innovation and enhance efficiency across various sectors. The paper emphasizes the necessity for ongoing investment in telecommunications infrastructure and research to fully exploit the transformative potential of IoT connectivity and applications.

Transforming library systems in Africa: advancing literacy and cultural preservation through digital innovation

Transforming library systems in Africa is essential for advancing literacy and preserving cultural heritage in an increasingly digital world. The integration of digital innovation into African libraries has the potential to revolutionize access to information, promote lifelong learning, and safeguard indigenous knowledge. This review explores the role of modern technologies, such as digital archiving, e-libraries, and mobile platforms, in enhancing literacy rates and preserving Africa's rich cultural traditions. By transitioning from traditional, print-based models to digital systems, libraries can bridge the educational gap in underserved communities, offering wider access to educational resources and promoting literacy at all levels. Additionally, digitization facilitates the preservation of local languages, oral histories, and cultural artifacts, ensuring that future generations can engage with Africa's diverse heritage. The challenges of digital transformation in African library systems, including limited infrastructure, funding, and digital literacy, are also discussed. The review emphasizes the need for strategic investments in technology, capacity building, and policy frameworks to create a sustainable digital ecosystem. By harnessing digital innovation, African libraries can evolve into dynamic centers of learning and cultural preservation, contributing to both socio-economic development and the protection of African identities. This transformation is critical to fostering a more educated, culturally aware, and globally connected African society.

Climate Change, Air Pollution, African Dust Impacts on Public Health and Sustainability in Europe

Abstract Climate change poses a significant threat to environmental sustainability and public health, leading to extreme weather events, rising sea levels, and biodiversity loss. Research on air pollution from African dust adversely associated with climate change highlights its significant role in trapping heat in the atmosphere and causing heat-related illnesses, cardiovascular disorders, and respiratory ailments. Smog, dust, acid rain, and ozone depletion also negatively impact ecosystems. The methods of the study also include the dynamics of climate change-induced air pollution. The implications for public health and environmental sustainability through GWR modeling and MODIS-NDVI analysis of controlling air pollution are crucial for reducing the climate crisis, safeguarding public health, and maintaining ecosystem sustainability. Results from particulate matter (PM 2.5-10), which consists of tiny particles with varying diameters, can enter the respiratory system through inhalation. This can lead to a diameter of less than 10 μm (PM 2.5-10). According to the relevant legislation, the limit value refers to the daily average value and must not exceed 50 μg/m3. While ozone in the stratosphere serves a protective function against ultraviolet radiation, excessive levels at ground level can be harmful and have been recorded in atmospheric samples ranging from 146.6 μg/m3 up to 702.3 μg/m3. impacting the respiratory and cardiovascular systems. Policy leaders, businesses, and individuals need to be proactive in reducing air pollution, adopting clean energy technology, and implementing stricter pollution rules. Stricter pollution rules, environmentally friendly transportation choices, and the adoption of clean energy technology. The sustainability of the ecosystem and public health are significantly impacted by climate change linked to air pollution. To solve these global problems and move toward a healthier, cleaner future for future generations, we must act now on climate justice. Key messages • Examine the impact of African dust air pollution on public health and its significant impacts from climate change, provide solutions to mitigate its effects on environmental sustainability in Europe. • Public health workers, Policymakers and stakeholders must prioritize reducing emissions and enforcing strict air quality laws to mitigate the negative impact of African dust on European populations.

Exploring Accounting for the Ocean: Utilisation of the Sociology of Worth to Assess Current Practice and Develop Propositions for Holistic Accounting

ABSTRACT The world’s oceans are vital for planetary health as well as food and energy security. Recently though, they have been increasingly considered as a solution to stagnating economic growth, with ocean resources and ocean spaces being used for both public and private benefit. This puts pressure on the sustainability of ocean ecosystems. These complex challenges have meant a need for an integrated understanding of and a more holistic approach to ocean accounting and governance. We adopt the Sociology of Worth to evaluate the application of the Ocean Accounts framework according to a range of competing and compromising perspectives on the concept of the common good within a contested case study. We find that Ocean Accounts fall short on key social and cultural aspects. However, there is scope to draw on alternative accounts to better inform the use of oceans. While the accounting literature presents a plethora of studies on environmental sustainability, studies on accounting for our ocean are limited. This is the first paper in accounting to focus on the Ocean Accounts framework.

Embedding Sustainability in Tourism Education: Bridging Curriculum Gaps for a Sustainable Future

The evolving challenges in the tourism industry, particularly those related to sustainability, demand significant revisions to current degree programs. This paper presents the design of a higher education curriculum for tourism studies at a Spanish university, responding to industry needs for broader, high-level knowledge and skills, with a strong emphasis on sustainability, digital transformation, and socially responsible practices. The curriculum prioritizes critical and strategic thinking alongside liberal reflection to empower students to lead in sustainable tourism development. Developed collaboratively with the entire tourism faculty, the curriculum design was informed by an extensive analysis of 105 international university courses, 204 job offers, feedback from 195 alumni, and ongoing consultations with professionals and community partners. Grounded in the concept of curriculum space and the philosophic practitioner framework, the curriculum integrates knowledge, soft skills, and attitudes to foster an innovative, sustainable learning ecosystem that prepares graduates to tackle the complexities of modern tourism with a focus on long-term environmental and social impacts.

Sentiment and success potential of farmers’ producer organizations: A systematic literature review

Farmer Producer Organisations (FPOs) are a viable alternative to cooperative farming, offering a commercialization model and improved income for smallholders. However, their adoption is often met with mixed sentiment among farmers, who lack capital, technical expertise, and institutional innovations. This study aims to explore the sentiments related to the adoption and success of FPOs in establishing a beneficial platform for small and marginal farmers, using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), sentiment and thematic analysis. The findings suggest that FPOs can enhance marketing strategies and agricultural productivity, but their impact on agriculture is case-sensitive. Cooperatives, characterized by member ownership and bottom-up development approaches, are essential factors in the context. A programmatic and comprehensive understanding of FPOs can help to develop a better agricultural and allied business ecosystem for diversified categories of farmers. Study aims to assess the sentiments and success potential of FPOs under an abundance of small and marginal farmers, comparing them to cooperative and contract farming legislation, to encourage a sustainable agribusiness ecosystem in India.

The role of light rail systems in urban regionalisation processes and in defining the bioregional vision of the Pontine plain in Italy

ABSTRACT Urban regionalisation or new regionalism is a land transformation process that involves the emergence of new sprawl settlements in the European Union and North America. These settlements are often composed of residential or micro-productive units that cause ecological fragmentation, biodiversity loss, and spatial reorganisation. This process challenges conventional spatial analytical and planning frameworks and calls for a new approach. This paper argues that bioregional units which account for complex human-environment interactions and the sustainability of natural resources and ecosystems can provide a new analytical and planning framework. Bioregions represent the main living environments for people, and mobility is a key driver shaping their lifestyle choices. This paper explores the role of light rail systems (LRSs) in enhancing the sustainability and well-being of bioregions, using the Pontine bioregion in Italy as a case study. It reviews the bioregional theory and applies the bioregional framework to the Pontine plain presenting the main features of the Pontine bioregion, including its internal and external urban relationships. Building on these analyses, the paper then discusses the proposal of a new railway network system that integrates LRSs as strategic elements for efficient mobility, urban regeneration, social cohesion, and environmental sustainability of the bioregional territory.

Research on a Non-Stationary Groundwater Level Prediction Model Based on VMD-iTransformer and Its Application in Sustainable Water Resource Management of Ecological Reserves

The precise forecasting of groundwater levels significantly influences plant growth and the sustainable management of ecosystems. Nonetheless, the non-stationary characteristics of groundwater level data often hinder the current deep learning algorithms from precisely capturing variations in groundwater levels. We used Variational Mode Decomposition (VMD) and an enhanced Transformer model to address this issue. Our objective was to develop a deep learning model called VMD-iTransformer, which aims to forecast variations in the groundwater level. This research used nine groundwater level monitoring stations located in Hangjinqi Ecological Reserve in Kubuqi Desert, China, as case studies to forecast the groundwater level over four months. To enhance the predictive performance of VMD-iTransformer, we introduced a novel approach to model the fluctuations in groundwater levels in the Kubuqi Desert region. This technique aims to achieve precise predictions of the non-stationary groundwater level conditions. Compared with the classic Transformer model, our deep learning model more effectively captured the non-stationarity of groundwater level variations and enhanced the prediction accuracy by 70% in the test set. The novelty of this deep learning model lies in its initial decomposition of multimodal signals using an adaptive approach, followed by the reconfiguration of the conventional Transformer model’s structure (via self-attention and inversion of a feed-forward neural network (FNN)) to effectively address the challenge of multivariate time prediction. Through the evaluation of the prediction results, we determined that the method had a mean absolute error (MAE) of 0.0251, a root mean square error (RMSE) of 0.0262, a mean absolute percentage error (MAPE) of 1.2811%, and a coefficient of determination (R2) of 0.9287. This study validated VMD and the iTransformer deep learning model, offering a novel modeling approach for precisely predicting fluctuations in groundwater levels in a non-stationary context, thereby aiding sustainable water resource management in ecological reserves. The VMD-iTransformer model enhances projections of the water level, facilitating the reasonable distribution of water resources and the long-term preservation of ecosystems, providing technical assistance for ecosystems’ vitality and sustainable regional development.

Protecting Human Creativity in AI-Generated Music with the Introduction of an AI-Royalty Fund

Abstract Artificial Intelligence (AI) is posited to revolutionise the creative industries, prompting global calls for legislative intervention to ensure human creativity remains at the centre of the copyright system. As AI systems gain prowess in analysing and generating content, they promise new levels of creativity and innovation at accelerated pace and reduced costs compared to human production. Alongside these benefits come concerns of displacement, particularly in fields like music, where AI-generated music could potentially supplant human-authored creative endeavours. Suggestions ranging from taxation to levies have been proposed to address this challenge. This paper, however, advocates for a novel perspective: evolving copyright law to not only compensate creators for income lost to technological disruption but also to foster sustainability aligned with the principles of the Council of Europe’s European Social Charter. Proposing an ‘AI-royalty fund’ represents a more optimal approach to this dilemma. Such a fund would acknowledge the intrinsic value of music and support a sustainable and inclusive creative industry ecosystem. Essential to this vision is the role of a national collective, entrusted with administering this fund to ensure equitable distribution and uphold the interests of human authors in an AI-driven landscape, contribute to regional and local plans of growth and foster cultural diversity and innovation. In essence, as AI redefines the boundaries of creativity, adapting the copyright paradigm becomes imperative to preserving the livelihoods of human creators while promoting a resilient and sustainable creative economy.

Emergy-Based Evaluation of the Sustainability of Agricultural Ecosystem in Dazhou, China, from 2002 to 2022

Our aim is to analyze the emergy evaluation indicators of the agricultural ecosystem in Dazhou, northeastern Sichuan, and provide practical and effective recommendations for sustainable agricultural development. Using emergy analysis, the emergy inputs and outputs of an agricultural ecosystem from 2002 to 2022 were calculated. Five emergy indicators were selected for evaluation: emergy yield ratio (EYR), emergy self-sufficiency ratio (ESR), emergy input ratio (EIR), environmental load ratio (ELR), and emergy sustainable indices (ESI). The total emergy input of the agricultural ecosystem showed an upward trend from 2002 to 2017, thus the industrial auxiliary emergy input decreased, somewhat curbing its continued rise from 2017 to 2022. The structure of emergy inputs, in descending order, is as follows: industrial auxiliary > organic emergy > renewable environmental resources > non-renewable environmental resources. The total emergy output of the agricultural ecosystem was highest in 2007, reaching 2.31 × 1022 Sej, and lowest in 2012, at 1.83 × 1022 Sej. The structure of emergy outputs, in descending order, is as follows: livestock > planting > fishery > forestry. The emergy yield ratio fluctuated down from 3.12 to 2.51, with an average of 2.88, below the provincial average of 3.07. The emergy self-sufficiency ratio fluctuated down from 0.30 to 0.26, with an average of 0.27, above the provincial average of 0.13. The emergy input ratio fluctuated up from 2.31 to 2.91, with an average of 2.66, above the provincial average of 1.86. The environmental load ratio fluctuated from 3.8 to 4.75, with an average of 4.40, which is higher than the provincial average of 1.68. The emergy sustainable indices fluctuated down from 0.81 to 0.53, with an average of 0.67, below the provincial average of 1.17. The efficiency of resource utilization in the agricultural ecosystem of Dazhou has decreased, economic inputs have increased, and it is in a consumptive production process. The pressure on the local natural environment is increasing, and the capacity for sustainable development remains at a low level over the long term.

A Decision Support Framework for Resilient and Sustainable Service Design

AbstractResilient and sustainable service design is essential for ensuring the longevity and effectiveness of service systems. However, existing literature often neglects key aspects such as articulating resilience attributes and integrating sustainability dimensions. This study proposes a decision support model for a “resilient-sustainable service design” that merges service design principles with resilient system attributes and organizational sustainability goals. The framework incorporates a multi-objective mathematical programming model and a multi-phased Quality Function Deployment (QFD) approach to derive Pareto optimal solutions using the Brute Force algorithm. Applied in the m-health service sector in Bangladesh, the study reveals significant challenges, including limited awareness of services and logistical inefficiencies. To address these issues, flexible strategies such as demand planning and service innovation are implemented. The findings have direct implications for the improvement of service delivery processes and underscore the importance of considering both resilience and sustainability. While focusing on Bangladesh’s m-health sector, the insights gained have broader relevance globally. The integration of resilience and sustainability principles into service design is crucial for addressing complex challenges across sectors and regions. Future research could involve longitudinal studies to capture evolving resilience strategies and explore resilient-sustainable service systems from a broader perspective. This entails examining various factors such as technological advancements and socio-economic dynamics shaping resilient and sustainable service ecosystems.

Development of russian-mongolian foreign trade relations in food industry

In the context of shifting trade emphasis to the East, Russia attaches great importance to the development of cooperation with the Asia-Pacific countries, where Mongolia is a key partner. The purpose of the article is to reveal global trade trends and identify key areas for the development of Russian-Mongolian foreign trade relations in the food industry. Having conducted a comprehensive analysis of the economic and political factors shaping bilateral trade, the article provides insights into the challenges and opportunities for expanding cooperation in the food sector. Global trend in the food market is that China a leader. China accounts for the largest share (35%) in Russia turnover also. Mongolian trade ties with Russia are becoming closer year by year. This was demonstrated by the official visit of Russian President Vladimir Putin to Mongolia in September 2024. We can observe that Mongolia closely cooperates with such a region of Russia as Buryatia. Through a detailed examination of trade patterns, regulatory frameworks, and market trends, the study uncovers areas of untapped potential and identifies barriers to optimal trade flow. Drawing on industry best practices and case studies from other global food trade partnerships, the paper offers a series of practical recommendations for stakeholders. These recommendations cover infrastructure development, promotion of cultural exchange, harmonization of legal and regulatory frameworks, absorption and use of technology to create a more robust and sustainable trade ecosystem.

Identification of dominant drivers of streamflow spatiotemporal variations in typical mountainous areas in the Hexi Corridor, China

Study regionTypical mountain areas in the Hexi Corridor, China. Study focusWater security and ecosystem sustainability of arid inland river basins are highly dependent on upstream streamflow. However, due to the complex geographical environment and limited observation data in the study region, the attribution of spatiotemporal variations in streamflow influenced by climate change and/or human activities remains unclear. Here, we used partial least squares regression (PLSR) and the Budyko framework to unravel the dominant drivers of spatiotemporal variation in streamflow over the past 30 yr. New hydrological insight for the regionPrecipitation, topographic wetness index, slope, forest land, gross primary productivity, hydrological connectivity, soil organic carbon content, silt content, relative relief, NDVI and gravel content dominated spatial variation in streamflow. Temporal variation of streamflow was sensitive to precipitation and land surface. Specifically, increased precipitation and land surface alteration dominated the increase in streamflow in 50 % of the watersheds and the decrease in streamflow in 33 % of them, respectively. Further, land surface alteration was dominated by expansion of agricultural and built-up areas, weakened hydrological connectivity, increased landscape aggregation and forest cover. Controlling agricultural and built-up areas and the scale of afforestation, and focusing on the dynamics of hydrological connectivity and landscape patterns in the upstream reaches are imperative to maintain the security and sustainability of water resources in the arid inland river basins.

Mycolichenological portrait of alder forest: alpha diversity revealed in 1ha plot in the Samursky National Park (Republic of Dagestan, Russia)

Aim. Xylobiont fungi and lichens determine the sustainability of forest ecosystems, but their species richness and taxonomic diversity depend on the forest type and the degree of its disturbance. Alder forests, characterised by a specific set of ecological conditions, represent poorly studied habitats in terms of myco‐ and lichenobiota. The aim of this work was to determine the species composition of aphyllophoroid fungi and epiphytic lichens on a 1 ha sample plot in a lowland floodplain forest dominated by Alnus glutinosa in the Delta Samura area of the Samursky National Park.The authors collected basidiomata of lignicolous fungi and lichen specimens on a sample plot of 1 ha during field studies. The surveyed forest area is represented by a community dominated by Alnus glutinosa and lianas. The material was identified using light microscopy techniques and a standard set of chemical reactions.Thirty‐three species of aphyllophoroid fungi (Basidiomycota) and 53 species of lichens and allied fungi (Ascomycota) were identified. Among them, 16 species (48 %) of aphyllophoroid fungi were recorded for the first time for the Samursky National Park, including six species revealed for the first time for the Republic of Dagestan, of which three species (Donkia pulcherrima, Phanerochaete cumulodentata and Sertulicium granuliferum) were new to the Northern Caucasus. Lichen species Arthothelium ruanum, Bacidia arceutina and Graphis pulverulenta are listed for the first time for the Republic of Dagestan. At the same time, 21 species of lichenized fungi were recorded for the first time on Alnus glutinosa within the region.The taxonomical structure of aphyllophoroid fungi revealed reflects the spring period of basidiomata‐based field study. The predominance of corticioid fungi and revealing hydnoid species among morphological groups may be indicative of the generally wetter habitats of alder forests in comparison to other forest types distributed in the studied area. Most of species were recorded on dead wood of Alnus glutinosa as the main forest‐forming tree. At the same time, each of other substrates (Carpinus betulus and Corylus avellana) turned out to be the habitat of species new to the region. The group of fungal species developing on large‐scale substrate units, represented by fallen trunks, was the most prevalent and is to be considered as more vulnarable in a case of anthropogenical habitat disturbance. The majority of epiphytic lichens discovered on alder are not specific to this woody substrate, except for single findings. These species belong to epiphytes inhabiting the Samur forest, the core of the lichenobiota of which is composed of thermophilous lichens of lowland deciduous forests. In our opinion, the relict character of the forest, which is an isolated and rather small forest massif with relatively homogeneous climatic conditions, causes a high similarity between the species composition of lichens revealed in the surveyed sample plot with Alnus glutinosa and previously studied plots dominated by Carpinus betulus, Populus alba, and Quercus robur.

The Effect of Climate Change on Indicator Wetland Insects: Predicting the Current and Future Distribution of Two Giant Water Bugs (Hemiptera: Belostomatidae) in South Korea.

Giant water bugs (Hemiptera: Belostomatidae) are top predators in wetland ecosystems, serving as biological indicators of the health of lentic ecosystems and as effective biological control agents for freshwater snails and mosquitoes. This study aimed to predict the current and future distribution of two Korean giant water bugs, Appasus japonicus and Diplonychus esakii, under three climate change scenarios, contributing to the sustainable management of wetland ecosystems in South Korea. Using MaxEnt models, we employed seven climatic and three non-climatic variables to investigate the habitat preferences and distribution patterns of the species. The results revealed that A. japonicus is likely to experience a northward range contraction due to climate change, while D. esakii is predicted to expand its distribution northward without losing its current range. These responses may lead to occupancy turnover between the two species, potentially driving reassembly in aquatic organism community. Elevation was the primary factor influencing the distribution of A. japonicus, whereas annual mean temperature was the most informative variable for D. esakii, both factors derived under the current climate conditions. These findings suggest that both species are highly sensitive to climate change, with potential range shifts toward higher latitudes and elevations. This study provides insights into how climate change could impact two giant water bugs, thereby supporting future efforts to manage and conserve wetland ecosystems in this country.

A global analysis of nearshore and submarine springs: spatial distribution, controlling factors, and probability of presence

Coastal springs act as bi-directionally preferential flow paths between coastal aquifers and oceans. While these springs can supply coastal ecosystems with nutrients, they also present vulnerabilities such as contamination and seawater intrusion. Despite their significance, substantial knowledge gaps exist regarding coastal springs due to their complex hydrogeological nature. This study provides a comprehensive global assessment of coastal springs, focusing on their distribution, controlling factors, and likelihood of occurrence. A global dataset of known coastal springs was compiled and analyzed, revealing 66 % of identified springs in the Mediterranean region, mainly linked to karst systems. In contrast, fewer springs were noted in Africa, South America, and South Asia. Key factors influencing spring occurrence were examined using geostatistical methods and integrated into a multi-criteria decision-making framework to develop a Coastal Spring Probability Index (CSPI) along coastline. High-potential areas for coastal springs were identified in regions characterized by significant carbonate and volcanic rock formations, wetter climates, and active tectonic margins, such as southern Europe, the Caribbean, tropical islands, and eastern Asia. Conversely, regions with dry climates and high water demand, such as North Africa and South America, exhibited a lower likelihood of spring presence. These findings will serve as a baseline for local-scale studies and aimed at improving coastal spring inventories and establishing monitoring networks. It will contribute to vulnerability assessment studies, thereby enhancing the management of coastal groundwater resources. The study emphasizes the importance of multidisciplinary approaches to understand coastal spring dynamics and advocates for a strategic planning in groundwater management and conservation. Ongoing efforts to inventory and monitor coastal springs, coupled with targeted conservation measures, are essential for ensuring the long-term sustainability of coastal water resources and ecosystems.

Sewage Treatment Equipment Supply Chain Collaboration and Resilience Improvement Path Analysis: Collaborative Decision-Making, Information Sharing, Risk Management

Since the dawn of the 21st century, supply chains (SCs) have faced an array of unprecedented challenges, encompassing economic volatility, escalating geopolitical conflicts, intensified trade disputes, and persistent environmental degradation. These challenges have imposed immense pressures on SCs, amplifying both the risks and occurrences of disruptions. In response to these critical demands, there has been a substantial increase in academic, industrial, and governmental focus on the resilience and recovery capabilities of SCs. In this context, the supply chain (SC) for sewage treatment equipment has been significantly affected. This study aims to systematically investigate collaborative strategies and mechanisms for bolstering the resilience of manufacturing SCs within the sewage treatment sector, with particular attention to collaborative decision-making, information sharing, and risk mitigation throughout the SC lifecycle. Following a comparative analysis of various methodologies, this paper employed the structural equation model (SEM) and subsequently conducted a comprehensive survey of manufacturers specializing in glass fiber sewage treatment systems, yielding 385 valid responses. Through this data, a structural equation model was developed to analyze pathways for resilience enhancement. A thorough analysis of the results indicates that Supply Chain Collaboration (SCC) and collaborative decision-making are instrumental in strengthening Glass Fiber Sewage Treatment Supply Chain Resilience (SCR) through the implementation of effective information sharing and risk management practices. These findings contribute to the theoretical framework of SCC and SCR by clarifying the influence of collaborative practices while also providing practical guidance for the governance and strategic management of sewage treatment equipment enterprises and their associated SCs. The conclusions drawn from this study can guide us in establishing a more resilient and sustainable SC ecosystem, making it more directive and capable of mitigating complex disruptions.

Spatial and temporal variation of marine megafauna off coastal beaches of south-eastern Queensland, Australia

Context Coastal beach environments provide habitats for marine megafauna, including turtles, rays, marine mammals and sharks. However, accessing these variable energy zones has been difficult for researchers by using traditional methods. Aims This study used drone-based aerial surveys to assess spatio-temporal variation of marine megafauna across south-eastern Queensland, Australia. Methods Drones were operated at five south-eastern Queensland beaches. Megafauna sightings and key variables including location, month and turbidity were analysed to assess variation across locations. Key results Overall, 3815 individual megafauna were detected from 3273 flights. There were significant differences in the composition of megafauna assemblages throughout the year and among beaches, with megafaunal sightings in >80% of flights conducted off North Stradbroke Island. Conclusions Strong temporal presence was found that is congruent with other studies examining seasonality. This supports the use of drones to provide ecological data for many hard-to-study megafauna species and help inform long-term sustainable management of coastal ecosystems. Implications Results indicated that environmental conditions can influence the probability of sighting marine megafauna during aerial surveys.

Dynamic analysis of a modified Leslie-Gower model with Michaelis-Menten prey harvesting and additive allee effect on predator population

In the current study, the dynamics of a Leslie-Gower model have been studied considering the Allee effect in the growth of the predator and the Michaelis-Menten type harvesting effect on the prey from biological and theoretical perspectives. Key findings highlight how these effects influence the existence of positive equilibria, with local stability properties and potential bifurcation behaviors examined using the center manifold theorem and linearization. Criteria for saddle-node bifurcation are established through Sotomayor’s theorem, while the direction and stability of Hopf bifurcation are explored via the first Lyapunov exponent. An optimal control model is developed to promote sustainable ecosystem development, utilizing the harvesting rate as a control parameter. Further, a few numerical simulations validate our significant findings using phase portrait diagrams.