Soil Resources Research Articles

Etude expérimentale des performances technicoéconomiques et environnementales de l’agriculture de conservation dans les régions semi-arides en Tunisie

Conservation agriculture, based on direct seeding, offers an ecological production method based on an integrated and sustainable management of mulch and soil resources. The techno-economic and environmental impacts of this production alternative are variable depending on the production system and the agroecological zone. This work aims to assess different impacts of conservation agriculture compared to conventional agriculture, using a set of agronomic, economic and environmental indicators at the scale of an experimental station. The experimental device combines a set of crop rotations, in rainfall and irrigated system under conventional and conservation agriculture. The analytical methodological framework used the tools of descriptive statistics and multidimensional analysis, including principal component analysis (PCA). Results show the added value of conservation agriculture, which has higher economic and agronomic performance and positive environmental benefits.

Deep Sandstone Reservoir Characteristics and Pore Structure Classification Based on Fractal Theory: A Case Study of the Bayingobi Formation in Guaizihu Sag, Yin'e Basin.

The paper focuses on deep oil and gas resources in the Bayingobi Formation of Guaizihu Sag in the Yin'e Basin. Previous studies overlooked the differences between the pores and throats, mainly focusing on pore analysis. This work aims to analyze the pore structure and petrophysical properties of the reservoir using various methods. The study utilized the constant velocity mercury intrusion method to quantify pores and throats separately. Scanning electron microscopy and casting thin section techniques characterize the pore and throat morphology. The analysis compares the pore structures in reservoirs with different petrophysical properties. Additionally, pore and throat types are classified based on fractal dimensions, and factors influencing their development are discussed. Results reveal feldspar lithic sandstone as the predominant rock type with a low compositional maturity. The sandstone reservoirs exhibit low porosity (10.23%) and ultralow permeability (0.99 mD). Primary reservoir pore spaces include intergranular pores, dissolution pores, and microfractures. Pore radius averages at 195.32 μm, while throat radius is 3.76 μm. Pore structures are categorized as micropore small-throat, small-pore small-throat, and large-pore coarse-throat types. The study area generally exhibits a high pore-to-throat ratio, impacting reservoir petrophysical properties significantly. Pore development is primarily influenced by early diagenesis, organic acid dissolution, and hydrocarbon filling. Weak compaction and cementation transformations provide a material and spatial basis for the subsequent dissolution. The presence of thick organic-rich mudstone above and below the reservoir contributes to organic acid dissolution and hydrocarbon filling.

Study on the Spatiotemporal Evolution of Urban Land Use Efficiency in the Beijing–Tianjin–Hebei Region

The Beijing–Tianjin–Hebei region (BTH) is one of the crucial areas for economic development in China. However, rapid urban expansion and industrial development in this region have severely impacted the surrounding ecological environment. The air quality, water, and soil resources face significant pressure. Due to the close relationship between land utilization, population, investment, and industry, effective land use is a key factor in the coordinated development of the region. Therefore, clarifying the patterns of urban land use change and revealing its influencing factors can provide important scientific evidence for the coordinated development of the BTH region. This study aims to improve urban land use efficiency (ULUE) in the BTH region. Firstly, based on the input and output data of land elements for the 13 cities in the BTH region, the Data Envelopment Analysis (DEA) method is used to quantify the ULUE of the BTH urban agglomeration and analyze the spatiotemporal characteristics of ULUE. Input indicators includes capital, labor, and land. Output indicators includes economy, society, and environment. The results show that the overall ULUE in the BTH region has increased, albeit with notable fluctuations. Between 2000 and 2010, ULUE rose swiftly across all cities except Beijing and Tianjin, where changes were minimal. Post-2010, cities exhibited varied trends: steady growth, slow growth, sustained growth, step-wise growth, and initial growth followed by decline. Spatially, before 2010, the BTH showed a “high in the northeast and low in the southwest” pattern, transitioning post-2010 to a smoother “core-periphery” pattern. Mid-epidemic, high ULUE values reverted to the core area, shifting southward post-epidemic. Secondly, panel data analysis is conducted to explore the factors influencing ULUE. The results indicate that fiscal balance, the level of openness, the level of digitalization, industrial structure, and the level of green development are significant factors affecting ULUE. Finally, strategies are proposed to improve ULUE in the BTH region, including national spatial planning, industrial layout, existing land use, infrastructure construction, optimization of local fiscal revenue, and improvement in the business environment, aiming to enhance ULUE and promote the coordinated development of industries in the BTH region.

Wetland landscapes in the Southern Maya Lowlands (Naachtun, Guatemala) from the ancient agroecosystems to the tropical biosphere reserve: Ecology, exploitation and management of water and soil resources, and heritage legacy

AbstractIn the Biosphere Reserve of the Maya Lowlands, the large‐scale characterisation of the current wetlands ecology and the exploitation and management of their natural resources by the ancient Maya is severely constrained by the forest. This paper presents an integrated geomatic, geoarchaeological and ecological approach, developed to overcome this obstacle in the microregion of the Naachtun Maya city. It is based on the analysis of LiDAR, and field and laboratory data. This approach has revealed the mosaic of current ecological conditions of the wetlands, thanks to the characterisation and spatial modelling of the landforms, hydrology, vegetation and soil cover. It has enabled the characterisation of numerous hydraulic and agricultural structures: 70 large reservoirs, raised fields (the largest over 1.5 km²), canals and ditches (with a cumulative length of over 300 km) and dikes. Eight morphological types of hybrid structures—hydraulic and agricultural—are described. These constructions have enabled the intensive exploitation of water and soil resources, their management and the resulting environmental risks. This study has shown that the agroecosystems of lowland areas were created as early as ~1500 B.C.E. and evolved in a polyphasic way, until a phase of radical decline around 1000 C.E. This study has made it possible to characterise the legacy of the Maya Early Anthropocene on current wetlands, as well as their important natural and cultural heritage.

Traditional gold mining in the highlands of Ethiopia: Its effect on soil loss and possible reclamation measures

Traditional gold mining (TGM) is among the off-farm income sources of smallholder communities in the highlands of Ethiopia. However, information on their impact on land degradation, taking soil loss as a key indicator, was scant. Hence, this study aimed at i) analyzing local communities’ attitudes toward TGM practice, ii) TGM impact on soil loss, and iii) possible restoration measures for the degraded gold-mined landscapes. For the evaluation of community perceptions, 96 beneficiaries were selected from three gold mining sites following stratified random sampling techniques. Soil loss measurement was done through measurement of i) the mass of soil excavated and transported to the river (TR) from 96 individuals and ii) soil volume excavated in 45 excavated soil pits (EP). Descriptive statistics and one-way ANOVA were used to analyze soil loss data, while community perception was analyzed qualitatively. The survey results indicated that the average soil loss from TR and EP were 6,075.97±8.9 t ha-1 yr-1 and 32,549.99±753.68 t ha-1, respectively. The magnitude of soil loss also showed a significant (p<0.001) difference among the three sites. Due to a lack of awareness and hiding the reality, most of the gold miners believe that TGM practice has no negative impact on the soil resource, and no post-mined reclamation strategy is implemented. It can be concluded that the existing TGM practices are not done in an environmentally friendly approach and result in adverse soil loss. Hence, stabilizing the topography of the mined sites via backfilling of mined pits and topsoil conservation and amendment measures can be suggested.

Taxes in the Time of Revolution: An Experimental Test of the Rentier State during Algeria's Hirak

abstract: This article examines the rentier thesis that a government's control over oil resources should help it to resist pressures for democratization. The authors' online survey experiment, implemented during a nationwide mobilization for regime change in Algeria known as the Hirak, used interactive experimental treatments to provide information about the Algerian government's subsidies for fuel resources and low value-added taxes. Based on a sample of 9,721 Algerians, the authors find that when Algerians learn about their country's relatively high level of fuel subsidies and low level of taxes, their assessments of the government's performance improve. However, the treatment has null effects for outcomes involving demands for representation, such as intentions to join protest movements. An analysis of treatment heterogeneity in terms of wealth shows that the wealthy became much more supportive of the regime in response to the treatment while in some cases the poor became much less so. This treatment heterogeneity appears to be related to divergent views among the wealthy and the poor concerning the goals of the protest movement, with the wealthy favoring institutional reforms while the poor prioritized redistributive justice.

Long‐term straw mulching alleviates microbial nutrient limitations and increases carbon‐use efficiency within aggregates

AbstractLong‐term straw mulching was known to change soil nutrient content, aggregate distribution and extracellular enzyme activities. However, the impact of long‐term straw mulching on microbial nutrient limitations and carbon‐use efficiency (CUEst) within aggregates remains unclear. To fill the gap, we conducted a 10‐year field experiment in a semi‐arid region and used an ecoenzymatic stoichiometry model to quantify microbial resource limitations in soil aggregates under long‐term mulching. We studied the effects of two mulching measures (plastic film mulching [FM] and straw mulching [SM], with no mulching as the control [CK]) on the nutrient content and limitations within aggregates. The results show that compared with FM, SM increased the proportion of aggregates to larger >2 mm and decreased the proportion of aggregates in the 2–0.25 mm classes. Additionally, FM resulted in carbon (C) and phosphorus (P) limitations in the soil, particularly in the >2 mm class, while SM alleviated these constraints. This effect was primarily attributed to the increase in soil organic carbon (SOC) and microbial biomass carbon content (Cm), especially the enhanced carbon content associated with larger aggregates (>2 mm) and the increased activities of carbon–nitrogen (C–N)‐acquiring enzymes. SM also resulted in high CUEst by influencing microbial P limitation. Random forest analysis indicates that soil abiotic factors, particularly SOC and total nitrogen (TN), were the main drivers of microbial resource limitations within the aggregates. These findings suggest that the mulching material determines the development of soil aggregates and resource allocation within these aggregates. Thus, the study provides valuable insights for formulating effective carbon management strategies in semi‐arid regions.

Research on optimal allocation of soil and water resources based on water–energy–food–carbon nexus

Current population growth and rapid urbanization in China have intensified the demand for water, energy, and food. This is threatening the intertwined global water, energy, and food security. Therefore, it is necessary to formulate interconnected and interdependent water, energy, food, and carbon policies. In this study, based on the theory of water–energy–food–carbon nexus, a soil and water resource optimization allocation model was developed by establishing an optimization modeling framework to achieve coordination between various sectors of water allocation. The model is an effective decision-making tool that fully considers the close relationship within the nexus system, and multiple uncertainty conditions. It was applied on the Fen River Basin in Shanxi Province as the study area, and a series of optimized allocation schemes were obtained. The results indicated that the current water allocation to each sector is meeting its minimum water demand. The planting structure optimization of two crops, wheat and corn, reduces the regional agricultural water consumption. For example, in dry years, the area of wheat cultivation (which needs more irrigation and has lower net economic benefits) is reduced and that of corn (which needs less irrigation and consumes less water) is increased in each subdistrict. The wheat plantation area in the midstream and downstream is decreased by 2.08% and 26.25%, respectively. The water use structure of crops indicated that precipitation and groundwater resources significantly contribute to the production of both crops throughout the entire growth process. This model can be applied in other regions; the model's economic and ecological benefits are combined so that decision makers can consider the stability of the water–energy–food–carbon system and provide optimal resource allocation under various scenarios, contributing to achieving the goal of sustainable development.

Numerical Simulation Study on Optimizing the Conical Cutter Bit to Break Deep Strata

Background: Methods that are used to obtain oil and gas resources by penetrating deep strata are gradually being developed. The complex lithology of deep strata causes difficulties for traditional drill bits to cut into the rock effectively, which affects the drilling efficiency. Objective: The goal of this work is to optimize the bit structure and design a patented drill bit for more efficient rock breaking. Methods: Through a series of tests, the rock mechanics parameters of deep strata in a block of Jilin Oilfield were measured, and the drill bit model XFXR5195 was selected to best match the lithology of the formation by using the Virtual Strength Index and the Technique for Order Preference by Similarity to an Ideal Solution. Simulation of the rock breaking process of the conical PDC cutter and cylindrical PDC cutter with the finite element method. Results: The simulation results show that the pre-crushing of the conical cutter can effectively reduce the difficulty of the subsequent cylindrical cutter in breaking and cutting rocks under 100 MPa compressive strength rocks; under 50 MPa compressive strength rocks, the combination of the conical cutter and cylindrical cutter are not effective with regards to drilling. Conclusion: The conical PDC cutter has a more uniform force range and more concentrated stress on the rock than the cylindrical PDC cutter. The rock-breaking ability of the conical PDC cutter is higher than that of the cylindrical PDC cutter under different compressive strength rocks and especially in high compressive strength rocks.

Advancing fluid identification via well-logging data: Leveraging persistent initialization and transformer modeling

In the domain of energy exploration, the forecasting of fluid via well logging is pivotal in directing exploration endeavors. Understanding the composition of fluid underground is key for exploration teams to accurately determine the size, potential reserves, and quality of oil and gas resources. This knowledge is critical in refining exploration tactics and employing resources wisely. We present a novel machine learning architecture termed “PIFormer” for predicting fluid. This design merges Persistence Initialization with a Transformer module. The combination of persistent initialization and Transformer modules is achieved by using the persistent initialization feature representation as input to the Transformer model. Persistent initialization provides a stable starting point, enabling the Transformer model to converge to effective feature representations more rapidly during the learning process. This combination helps address issues in existing methods such as training instability, slow convergence, and local optima problems caused by random initialization. By integrating persistent initialization and the Transformer model, prior knowledge and global information can be more effectively utilized, enhancing the accuracy and robustness of fluid identification. Compared to existing models, the combination of persistent initialization and the Transformer model demonstrates higher accuracy and robustness in fluid identification tasks. Specifically, our approach achieves significant improvements in fluid identification accuracy and outperforms existing models across various types of fluid identification problems. Additionally, our method significantly reduces model training time and improves convergence speed. These results clearly indicate that the combination of persistent initialization and the Transformer model effectively addresses limitations in existing models for fluid identification tasks, providing new avenues and methods for further research and application in this field.

A novel stepwise microwave hydrodistillation and extraction process for separating seed oil and essential oil simultaneously from perilla seeds

Stepwise microwave hydrodistillation and extraction (SMHDE) was utilized to separate perilla essential oil as a byproduct while boosting perilla seed oil yield and quality. The optimal process for producing perilla seed oil was determined by Plackett–Burman and Box–Behnken design experiments based on a factor screening experiment. Under ideal working conditions, the yield of seed oil was 36.49% ± 0.07%. The content of α-linolenic acid in perilla seed oil obtained by SMHDE was 69.90%, which was significantly greater than that obtained by Microwave-assisted method (MAE) (66.59%) and that obtained by Soxhlet extraction (SE) (66.51%). The yield of perilla seed essential oil obtained by SMHDE was 0.55 ± 0.14 mL/kg, and the main component was perillaldehyde, which was present at a concentration of 20.50%. GC‒MS analysis revealed that the content of volatile compounds in seed oil obtained by SMHDE (9.20%) was significantly lower than that obtained by MAE (10.94%) and SE (15.23%). Compared with traditional methods, SMHDE can effectively increase seed oil yield and quality without negatively influencing its fatty acid composition or physicochemical properties. These findings support the use of SMHDE to increase the production and quality of seed oil and prevent the waste of perilla essential oil resources.

Technology Focus: Heavy Oil (April 2024)

Heavy oil can be one of the more technically challenging resources to recover. It is often easy to find but hard to move. This creates an incentive for knowledge seekers and problem solvers: The puzzle pieces are on the table; we just need to put them together. The physical characteristics of heavy oil and the formations in which it is found—the puzzle pieces—are often unique to a region or even to a specific asset, so recovery techniques must be tuned, adapted, and sometimes invented for each region. Creative professionals around the world are taking up this challenge and sharing their work with us in a wealth of excellent recent publications. In particular in our featured papers, we see three different parts of the world working with three different recovery techniques. First, we have a fundamental study in paper SPE 212779 of a perennial question from Canada’s oil sands: Where does the emulsion form in the steam-assisted gravity drainage (SAGD) recovery process, where the effect of a surfactant is studied? Moving south to paper SPE 213199, we review a study that progresses from laboratory work to field implementation using foam injection in Colombia in conjunction with cyclic steam stimulation. From Colombia, we look across to the other side of the world to paper SPE 215943, where we see a transition from steamflood recovery to an adapted configuration of SAGD, with a comprehensive discussion on optimizing production in Mukhaizna field in Oman. The theme of adaptation and invention continues in our recommended reading, with discussions of fundamental research, applied and practical insights on field implementation, and all the steps in between as these are applied to heavy oil production challenges around the world. I hope you enjoy the tour. Recommended additional reading at OnePetro: www.onepetro.org. SPE 212767 Part 1: Kinetics of Methane Exsolution From Bitumen in Thermal Recovery Processes—Experimental Study by Mohammad Khalifi, Imperial Oil Resources, et al. SPE 214113 Physical and Numerical Simulations of Offset Well Pair Combined Steam-Drive and Gravity-Drainage Process To Develop Superheavy Oil or Oil Sands Project by Guangyue Liang, China National Petroleum Corporation, et al. SPE 215342 Optimization of Chemical Acid Stimulation by Improving Selection Intervals in Lateral Section of Horizontal Well in X Field Heavy Oil Steamflood by Fatichin Fatichin, Pertamina, et al.

Carbon sequestration potential of biochar in soil from the perspective of organic carbon structural modification

Application of biochar derived from biomass resources in soil is an encouraging method to decelerate global warming via carbon sequestration. While there has been extensive research on the priming effect of biochar on the mineralization of native soil organic carbon (nSOC), its correlation with soil organic carbon (SOC) structural variations remains poorly understood. A series of incubation experiments with soils amended with biochar prepared at 300 °C, 450 °C, and 600 °C were performed to explore the shifts in nSOC structure and reveal the interconnections among soil properties, SOC structural variation, and the priming effect induced by biochar. Biochar exhibited an “inhibitory concentration” on soil microorganisms, where 1 % biochar enhanced bacterial and fungal richness and diversity, while 3 % biochar reduced bacterial richness and diversity although soil nutrient conditions were improved. Biochar-treated soil had higher humic acid- and humin-like fractions (HAL and HML) but lower fulvic acid-like components (FAL). Moreover, bulk SOC, FAL, HAL, and HML of soils with 300 °C and 450 °C biochar contained more aromatic-type species (e.g., lignin). Such changes were related to improvement of the soil nutrient condition and shifts in microbial community structures, in addition to the “accumulation of biochar-derived OC in the nSOC pool”. Stable carbon isotopes indicated that the inhibitory effect on SOC mineralization (−94.5 to −8.0 mg CO2-C kg−1 soil) induced by biochar was significantly explained by the change in FAL and HAL contents. The findings improved the understanding of the carbon sequestration potential of biochar in soils for SOC structural modification.

Roles of Iot, big data and machine learning in precision agriculture: a systematic review

Precision agriculture utilizes information technologies to efficiently manage water and soil resources in agriculture. This technological revolution has been sparked by the big data analytics, machine learning and Internet of Things (IoT)in numerous industries. This game-changing technology has influence on houses, grids, smart cities, and health. Machine learning and data-intensive decision-making have been made possible, which has created new possibilities for efficiency and innovation in various fields. In several fields, the convergence of IoT, big data analytics, and machine learning has opened the way for cutting-edge solutions and enhanced results.The application of machine learning in the agricultural sector can increase production quantity and quality to meet increasing food demand. These advancements are transforming current agrarian approaches and generating new opportunities, despite some limitations. This paper presents a systematic appraisal of the role of IoT, big data analytics, and machine learning in precision agriculture, highlighting the potential benefits and challenges in this rapidly evolving field.

Harsh environmental conditions promote cooperative behavior in an epiphytic fern

ABSTRACT Harsh, unpredictable environments are known to favor cooperative groups in animals. Whether plants exhibit similar relationships is unknown. Staghorn ferns (Platycerium bifurcatum, Polypodiaceae) are epiphytes that form cooperative groups which build communal water and nutrient ‘nests’ at the tops of trees, a habitat characterized by water and nutrient stress. We conducted field observations to test whether staghorn ferns continue to live in large, reproductively active groups after they become dislodged from the canopy and fall to the forest floor, where they are less limited by water and nutrient deprivation. To rule out the potentially confounding effects of light limitation on the forest floor, we also conducted a multi-year glasshouse experiment where we transplanted individual plants into soil and onto vertically oriented boards under standardized light conditions. Results from field observations showed that dislodged colonies formed smaller groups that reproduced less than epiphytic colonies. Results from the glasshouse experiment showed that even when growing in full sun, terrestrial individuals tended to remain solitary, while epiphytic individuals tended to recruit new individuals into colonies. Results also showed that plants growing in potting soil and exposed to full sunlight sporulated more heavily than plants growing epiphytically. However, localities that are characterized by both elevated soil and light resources are generally not available to staghorn ferns in the wild, perhaps with the exception of large, epiphytic colonies with well-developed nests at the top of tree canopies. Overall results indicate that the harsh environmental conditions at the tops of trees trigger the formation of colonies in staghorn ferns, similarly to group living animals.

Application of the United Nations Framework Classification to assessment of the prospective resources of hydrocarbons in Azerbaijan

The oil and gas industry plays an important role in Azerbaijan's economy, contributing significantly to GDP and government revenues. However, the existing classification of hydrocarbon reserves and resources is outdated and does not reflect the economic efficiency of extraction. In this regard, the United Nations Framework Classification for Resources (UNFC) helps to determine the feasibility, technical viability, and maturity of resource development projects. This paper examines the assessment of hydrocarbon resource categories by comparing the current classification system for oil and gas reserves and resources in Azerbaijan with the UNFC. The objective of this work is to conduct a comparative analysis of prospective resource categories and thus provide a basis for the preparation of a bridge document describing the relationship between the United Nations Framework Classification and the existing 1984 classification used in Azerbaijan. To conduct this research, a hypothetical field called «Structure C» was used in which resource assessments were conducted at various times in 1984, 1988, 1993, 2001, and 2011 based on the 1984 classification of the former Soviet Union. Keywords: prospective resources of hydrocarbons; UN framework classification; case study.

Modeling gully initiation by two codeless nonlinear methods: A case study in a small watershed on the Tibetan Plateau

Land and soil resources are scarce in the Tibetan Plateau, and the region is facing ecological pressure from climate warming and increasing human activities. As a major ecological problem, gully erosion is destroying land and soil resources on the Tibetan Plateau, but related research is limited, and susceptibility areas and influencing factors are unclear. Machine learning methods are often applied to study gully initiation susceptibility, but they require a programming foundation. Therefore, the Redui watershed on the southern Tibetan Plateau with severe gully erosion was selected to evaluate the susceptibility and influencing factors of gully initiation through 12 influencing factors including topography, human activity, and underlying surface conditions, and all 2310 gully headcut sites. Two non-code nonlinear modeling methods, the categorical Regression (CATREG) and geographical detector (Geodetector) methods, were first used in the spatial modeling of gully initiation susceptibility. The results showed that the gully initiation susceptibility of the hillslope around the alluvial fan was highest. The very high susceptibility areas of the CATREG model and Geodetector model account for 18.2% and 16% of the total, respectively. The main influencing factors of gully initiation were elevation, relief, and soil type recognized by CATREG, and elevation, human footprint, and soil type recognized by Geodetector. Elevation is the primary factor controlling downstream susceptibility in both models. The primary factors in the upper and middle reaches are soil type and relief identified by CATREG. Human footprint, soil type, and distance to road are primary factors in the upper and middle reaches identified by Geodetector. The explanatory power of elevation, elevation-relief interaction, Geodetector model and CATREG model were 39%, 54%, 46.4% and 73.8%, respectively, at extremely significant levels (P < 0.001), which means that the influencing factors were well considered and that the methods have great application potential in the future.

Effect of waste leather dander biochar on soil organic carbon sequestration

In order to determine the carbon sequestration content of waste leather dander biochar (W-BC) at different pyrolysis temperatures and its effect on soil organic carbon mineralization, waste leather dander (WLD) was prepared into BC-300, BC-400 and BC-500 at different temperatures (300, 400 and 500 °C). The results show that the highest carbon sequestration content of BC-400 is 18.23% when the pyrolysis temperature is 400 °C. In addition, after applying BC-400 to the soil for 60 days, the mineralization rate of soil organic carbon decreased to 0.499 mg CO2/ (g·d), and the content of soil moisture, pH and total organic carbon (TOC) increased to 42.35%, 7.25 and 30.94%, respectively. At the same time, the addition of biochar promoted the transformation of bacteria into stable C-dominant phylum (Firmicutes) and the carbon sequestration capacity of soil was enhanced. The data of this study have certain reference value in the field of soil remediation and resource treatment of WLD.

Resilience through mineral resource development, oil, and natural resource efficiency: Strengthening economies

This study examines the role of resilience in bolstering economies via the development of mineral resources and oil, alongside adaptability and natural resource efficiency, particularly within the G7 economies from 1995 to 2022. Employing the Generalized Method of Moments (GMM) model, the research aims to unravel the complexities of how resource-rich economies can leverage their natural assets to enhance economic resilience and sustainability. The investigation reveals a positive correlation between the strategic development of mineral resources, oil, and the adaptability of economies to external shocks, highlighting the critical importance of natural resource efficiency in ensuring long-term economic stability and growth. These findings underscore the necessity for G7 nations to implement policies that not only foster the responsible exploitation and development of natural resources but also promote adaptability and efficiency in resource use. The study's policy implication suggests a paradigm shift towards more sustainable and resilient economic models, emphasizing the balanced integration of resource development and environmental stewardship.

Unraveling Ghana’s Resource Curse Hypothesis: Analyzing Natural Resources and Economic Growth with a Focus on Oil Exploration

This study examines the intricate relationship between natural resource abundance, with a specific focus on oil production, and its impact on economic growth in Ghana. Through the application of the robust Fully Modified OLS methodology and using data spanned from 1960–2021 the research underscores the essential inclusion of oil as a significant variable in comprehending economic growth dynamics. Contrary to traditional resource curse theories, the study unveils a positive nexus between oil production and economic growth, particularly within a comprehensive variable framework. This finding challenges simplistic resource curse notions and underscores the need for a holistic economic perspective. Overall, the results show that the impact of oil production on economic growth is sensitive to the inclusion or exclusion of other variables in the model. In Model 1, where all variables are included, oil production has a significant positive (0.0112**) impact on growth. Ghana’s success in avoiding the resource curse is attributed to a multifaceted strategy encompassing diversified economic approaches, transparent governance, and responsible oil revenue management. Importantly, the inclusion of oil as a pivotal variable is well-justified by its tangible contributions to economic growth. The observed positive impacts emphasize the benefits of harnessing oil resources while maintaining a holistic view of the broader economic context. Looking ahead, the insights inform policymakers in resource-rich nations, illustrating how strategic resource management—illustrated by oil—can drive resilient and comprehensive economic growth. Ghana’s experience serves as a compelling template for informed policy decisions, offering valuable lessons for achieving sustainable prosperity.