Journal of Environmental & Earth Sciences

Population Dynamics of Parasitic Nematodes as an Indicator of Soil Health of Eagle Island Mangrove Ecosystem, Port Harcourt

2025-12-05T20:19:47+08:00

Mangrove forests globally are biodiversity hotspots, supporting microbes, vertebrates, and invertebrates. We thus postulate that, because mangrove soil is a habitat for numerous organisms, it will be a hotbed of both soil- and plant-based nematodes. This study is significant because there is a dearth of information on nematode studies in the Niger Delta region. The present study was based on samples collected from five stations to assess dynamics in population and trophic diversities in a mangrove ecosystem. Data Analysis showed a significant difference (p ≤ 0.05) of nematodes in Rhizophora spp. (61.2%) and Avicennia spp (38.8%). Nematode community composition was evaluated as enumerated by the Shannon-Wiener diversity (H’), Simpson’s (D) and Hill’s Index of evenness based on the weighted means of Colonizer-Persister (c-p) guilds. A total of 13 genera of nematodes were recorded with bacterivores representing (10%), fungal feeders (13%) and obligates (77%). Based on taxonomic groups, (49%) belong to the family, Tylenchoidae, 28.3% Dorylaimoidae, 10.3% Rhabditidae, 7.4% Criconematoidae and 4.1% Aphelenchoididae. The Shannon and Simpson indices registered values of 1.0 and 0.5 respectively indicating low diversity. Evenness Index scored a value of 0.8, which is close to 1. Our findings indicate an average even distribution amongst families within the Eagle Island soil which indicates stability of the community. The contribution of bacterivorous and herbivorous nematodes with high c-p values was high in our study. This thus led to high Maturity Index (3.5), indicating stability.

The Impact of Agricultural Sector Growth on Total National Greenhouse Gas Emissions in Southeast Asia

2026-04-13T17:32:48+08:00

The agricultural sector plays a significant role in greenhouse gas emissions, particularly in developing countries within the ASEAN region. Despite ASEAN’s status as a group of emerging economies, environmental pressures continue to increase alongside economic and demographic growth. This study aims to examine the determinants of greenhouse gas emissions in six ASEAN countries—Indonesia, Vietnam, Thailand, Myanmar, the Philippines, and Malaysia—using panel data from 1997 to 2019 obtained from the World Bank’s World Development Indicators (WDI). Employing a robust fixed-effects model to address heteroskedasticity and autocorrelation, the results reveal that forest area and population size have a positive and statistically significant impact on greenhouse gas emissions, while fertilizer consumption, agricultural land, livestock production, and gross domestic product (GDP) are not statistically significant. These findings indicate that environmental degradation in ASEAN is driven by land-use dynamics and demographic pressures. The positive effect of forest area suggests that increases in forest coverage do not necessarily translate into lower emissions, likely due to forest degradation, deforestation, and land conversion. Meanwhile, the significant role of population highlights the increasing demand for resources, energy, and food as key drivers of emissions. Therefore, this study emphasizes the importance of strengthening sustainable land-use management, improving forest governance, and enhancing resource efficiency.

Integrated Stability Assessment of Mine Tailings under Static and Seismic Conditions: Application of Limit Equilibrium Methods and Eurocode 7 to the Auzelles Site (France)

2026-03-27T10:44:40+08:00

The instability of mine tailings represents a major environmental and geotechnical challenge, particularly due to the risk of slope failure and contamination of surrounding watercourses. At the Auzelles site (Auvergne, France), the absence of prior stability assessment combined with steep natural slopes (35°–40°) constitutes a critical factor of instability. This study aims to evaluate the stability of slag heap 1 by analyzing the influence of slope geometry under both static and pseudo-static conditions. The methodology is based on limit equilibrium analysis using Talren software, with the simplified Bishop method, in accordance with both the traditional approach and the EN1997-1 Eurocode 7 framework. Two representative cross-sections were analyzed before and after earthworks. The analysis assumes free-draining tailings conditions, with no pore water pressure considered. The results show that the initial state of the slopes is unstable, with safety factors of 1.07 under static conditions, 0.89 under pseudo-static conditions, and 0.78 using the Eurocode approach, indicating a high risk of failure. After slope regrading to 27°, a significant improvement in stability is observed. The safety factors increase to 1.42–1.44 under static conditions, 1.11–1.15 under pseudo-static conditions, and 1.03–1.05 using the Eurocode approach, satisfying the required stability criteria. These results demonstrate that slope geometry is the primary controlling factor of stability at the site, and that reprofiling significantly enhances safety conditions. The study confirms the effectiveness of combining traditional and normative approaches for reliable stability assessment and highlights the importance of considering both static and seismic conditions in the long-term management of tailings storage facilities.

Engineering Resilience: Novel Approaches in Ecosystem Restoration

2026-03-03T10:41:01+08:00

Climate nonstationary and exacerbated disturbance regimes, as well as ubiquitous human alteration of landscapes and seascapes, are increasingly challenging ecosystem restoration. In this scenario, restoration strategies based on static reference states, or short-term structural goals, tend to provide delicate results that fail when subjected to extreme events, new stress factors, or changing baselines. The current essay is a synthesis of the new paradigm of engineering resiliency towards ecosystem restoration that combines the principles of design-oriented engineering and theories of ecology of complexity, thresholds, and adaptive capacity. We explain conceptual differences and complement between ecological and engineering resilience, as well as highlighting resistance, recovery trajectories, and adaptability as aspects of the operation of performance. We also study fresh resilience-enabling strategies, such as nature-based solutions and gray-green systems, ecological engineering and system-level design, digital technologies of monitoring and prediction, and adaptive management based on the concept of feedback-control. In the land, freshwater, coastal, and urban systems, we evaluate such strategies underway to increase the integration of persistence of functions and provide ecosystem-vitality despite disturbance, as well as the inescapable problems related to scaling, governance, equity, and long-term sustainability. Last but not least, we define the areas of priority in research, such as the standardized measures of resilience, long-term monitoring, uncertainty-aware models, and responsible innovation to reduce unintentional ecological and social effects. Reconceptualizing restoration as a performance-based design challenge that is enshrined in coupled human-natural systems, engineering resilience provides a transdisciplinary, rigorously grounded approach to creating ecosystems that survive and adapt in a fast-changing world.

Eco-Intelligent Trade Networks: AI Applications in Regional Economic Development and Their Implications for Environmental Management

2026-01-16T13:57:01+08:00

Eco-intelligent trade networks are emerging as a critical governance frontier where regional economic development and environmental management intersect. With the increase in networked production and logistics systems, the environmental issues of greenhouse gas emissions, air contamination, water stress, and land-use change spread across jurisdiction by trade. Artificial intelligence can provide new functionality to monitor, assign, and control these impacts because it combines the different streams of heterogeneous data, such as customs and transaction data, logistics telemetry, remote sensing data, facility monitoring data, and corporate disclosures. The review is a synthesis of artificial intelligence (AI) applications that help in direct support of environmental management functions in trade networks, i.e., monitoring and anomaly detection, measurement-reporting-verification, risk-based enforcement targeting, and regulatory decision support. It also looks at the operationalization of AI-enabled intelligence using policy tools and corporate practices such as green corridors and smart ports, sustainable procurement and due diligence, certification, and claims verification, green upgrading industrial policy, and environmentally linked finance-based risk management. In these spheres, it can be seen that AI can enhance transparency and resource distribution, although the results will rely on the backbone of data and accounting, institutional capabilities, as well as governance protections. Major risks are rebound effects, which increase overall burdens with efficiency increase, a burden on less monitored areas and suppliers, and exclusion of data-poor suppliers and regions, and obscurity, which adversely affects procedural legitimacy. The review frames AI as a component of an auditable decision system and not a context-independent tool of optimization, offering priorities to priorities on causal assessment, benchmarking, and inclusive guidelines to implementation.

Beyond Point Sampling: AI-Enabled Sensor Fusion and Holistic Frameworks for Aquatic System Intelligence

2026-03-04T17:34:55+08:00

The fast-changing environment is becoming a greater influence on aquatic systems, and the traditional approaches still look at conventional monitoring as point-based sampling, which under-samples the spatiotemporal variation and episodic dynamics. This review summarizes future trends toward ultraviolet sampling using Artificial Intelligence (AI)-enhanced sensor fusion and comprehensive conceptualizations of the intelligence of aquatic systems. We then explore how aquatic observation has evolved over the years by beginning with the limitations of fixed stations and grab sampling and moving on to multi-modal observations involving the incorporation of in-situ networks, remote sensing, and mobile autonomous systems. Subsequently, we are interested in AI methods that allow integration of heterogeneous streams of data with an accent on fusion architectures, representation learning, and hybrids that are based on data-driven inference and physics-based constraints. We elaborate on these developments with holistic models that combine sensor fusion with system-level modeling, such as digital aquatic twins, real-time assimilation, and adaptive spatiotemporal intelligence for detecting events and understanding processes. In a variety of uses, including water quality evaluation, ecosystem health surveillance, and hazards early warning, among others, we point out how the combination of AI and AI-sensing systems can be used to enhance state estimation, forecasting, and decision support in the face of uncertainty. Lastly, we discover unresolved issues, such as a lack of data, no stationarities in generalization, the limitations of computational and operational projects, and the need to have trustworthy, scalable aquatic intelligence, and outline future research opportunities. This review brings together sensing, AI, and systems thinking to create a roadmap on how to transform heterogeneous observations into actionable insights that result in resilient aquatic management.

Integrating Aesthetic Value into Ecosystem Services Assessment: A Conceptual Framework for Sustainable Landscape Management

2026-03-02T11:26:47+08:00

The concept of aesthetic value as a part of ecosystem services (ES) assessment is needed to manage the landscape sustainably, although it is still conceptually limited and methodologically divided. This review brings together progress in defining, measuring, and integrating aesthetic value into ES frameworks, and specifically how it can be viewed as a cultural ecosystem service, and how it mediates between ecological conditions and human well-being and behavior. We look at qualitative and participatory methods, which can capture contextual and culturally ingrained perceptions, quantitative measures, and metrics of the landscape that can be compared, and spatially explicit approaches that can be used in planning and scenario analysis. We also evaluate the emerging computational methods, the crowdsourced and image-based information, and point out the possibilities of mapping on a large scale and the difficulties of representativeness, bias, and validation. Based on this synthesis, we suggest a conceptual integration pathway that considers aesthetic value as a joint product between landscape qualities and human senses, expressly showing their interactions, synergies, and trade-offs with other ecosystem services on different scales. It finds significant standardization gaps, dynamics of time, and plural valuation identified and describes the next directions of research on mixed-methods designs, uncertainty management, and more robust science-policy interfaces. Landscape planning can be used to create ecological sustainability and multifunctional landscapes by incorporating aesthetic value in more explicit ES assessment, which can be used to support resilient and multifunctional landscapes.