Plant Site Research Articles

Repurposing coal plants—regional economic impacts from low carbon generation

Repurposing coal power plants in the United States may provide significant opportunities to incentivize low-carbon and renewable electricity generation created by the Inflation Reduction Act (IRA). Re-using coal sites for their existing electric grid interconnections and infrastructure could reduce costs and provide benefits to coal-based communities experiencing energy transitions. This study estimates local employment, labor income, and tax revenue effects from renewable and low-carbon generation options repurposing coal power plants and meeting their economic impacts at existing coal plant sites in North Carolina. The study bridges gaps in energy transition studies by including site feasibility assessment of advanced reactors for former coal power plant sites, renewable electricity generation, and thermal energy storage. It also considers cost advantages of reusing existing power plant interconnections, IRA discounts, and generation technology economic impacts using IMPLAN. A least-cost quadratic optimization model considers different site-specific electricity generation portfolios to analyze site-based economic impacts and associated technology costs meeting or exceeding site-based coal generation and its economic impacts. This study finds that replacing coal generation costs less than maintaining the current coal fleet, a technology-inclusive portfolio provides the least-cost pathway, and benefits may exceed site-based impacts of existing coal plants. Local tax revenues from advanced reactors and thermal energy storage systems may increase revenues by at least $28 million. Across all repurposing scenarios, replacing existing coal plants with energy storage, renewable, and low-carbon generation leads to net employment growth and tax revenues, indicating further benefits to a rapid and more equitable decarbonization through economic development.

Mass flowering and unprecedented extended pseudovivipary in seagrass (Posidonia oceanica) after a Marine Heat Wave

Seagrasses are marine flowering plants that create critical coastal ecosystems and are threatened by warming. Clonal expansion is generally the dominant strategy for meadow recovery, while sexual reproduction strongly differs among species (e.g., monoecious and diecious species, some creating seed banks, viviparous seedlings). In 2022, the Western Mediterranean underwent unprecedented warming, and, associated with it, we observed flowering (100 %) across 11 Posidonia oceanica meadows in Mallorca, Balearic Islands. Furthermore, 64 % of the sites also exhibited pseudovivipary, an extremely rare phenomenon in angiosperms whereby plantlets replace sexual reproductive structures, producing clones of the maternal plant. Our results support the notion that P. oceanica flowering and pseudovivipary (genetically confirmed) are triggered by warming, never before being pseudovivipary reported across multiple sites in a marine plant. Considering the negative impacts that warming can have on seagrasses, existence of widespread pseudovivipary is a critical aspect to consider for understanding mechanisms of resilience in seagrasses.

Bringing genomics to the field: An integrative approach to seed sourcing for forest restoration.

Global anthropogenic change threatens the health and productivity of forest ecosystems. Assisted migration and reforestation are tools to help mitigate these impacts. However, questions remain about how to approach sourcing seeds to ensure high establishment and future adaptability. Using exome-capture sequencing, we demonstrate a computational approach to finding the best n-sets from a candidate list of seed sources that collectively achieve high genetic diversity (GD) and minimal genetic load (GL), while also increasing evolvability in quantitative traits. The benefits of this three-part strategy (diversity-load-evolvability) are to increase near-term establishment success while also boosting evolutionary potential to respond to future stressors. Members of The Nature Conservancy and the Central Appalachian Spruce Restoration Initiative planted 58,000 seedlings across 255 acres. A subset of seedlings was monitored for establishment success and variation in growth. The results show gains in GD relative to GL and increases in quantitative genetic variation in seedling growth for pooled vs. single-source restoration. No single "super source" was observed across planting sites; rather, monitoring results demonstrate that pooling of multiple sources helps achieve higher GD:GL and evolvability. Our study shows the potential for integrating genomics into local-scale restoration and the importance of building partnerships between academic researchers and applied conservation managers.

Measurement of Environmental Gamma Radiation Dose Rates and Estimation of Radiation Risk near the Construction Site of the Nuclear Power Plant, Indoor and Outdoor Locations of the Research Reactor, and Coal-Fired Thermal Power Plant Area

Measurement of Environmental Gamma Radiation Dose Rates and Estimation of Radiation Risk near the Construction Site of the Nuclear Power Plant, Indoor and Outdoor Locations of the Research Reactor, and Coal-Fired Thermal Power Plant Area

Quantum-Enhanced SOLAR Site Selection: A Novel MCDM Approach

In the pursuit of optimizing renewable energy sources, the selection of solar plant installation sites presents a complex decision-making challenge that involves multiple criteria. This research introduces a groundbreaking algorithm, leveraging quantum computing techniques to enhance Multi-Criteria Decision Making (MCDM) for solar plant site selection. The proposed algorithm harnesses the superposition and entanglement properties of quantum bits to evaluate extensive datasets and criteria with unprecedented speed and accuracy. By integrating quantum versions of established MCDM methods such as the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the algorithm provides a sophisticated tool for decision-makers. The research demonstrates the algorithm’s superiority over classical methods through rigorous simulation and validation processes. The findings suggest that quantum-enhanced MCDM can significantly streamline the solar plant site selection, paving the way for a more efficient deployment of solar energy infrastructure and contributing to a sustainable energy future.

The former industrial site of the Angarsk Metallurgical Plant (Svirsk, Russia) 10 years later: current geochemical state and interannual change analysis based on Earth remote sensing data

The former industrial site of the Angarsk Metallurgical Plant (Svirsk, Russia) 10 years later: current geochemical state and interannual change analysis based on Earth remote sensing data

How do seasonal and technical factors affect generation efficiency of photovoltaic power plants?

Regions with limited space for constructing renewable power generation systems need to maximize electricity generation by optimizing the operational efficiency of existing plants and selecting an optimal location for the new construction of PV power plants with favorable weather conditions and surrounding environment. Utilizing monthly input and output data, including four inputs (solar irradiation, temperature, number of modules, and photovoltaic (PV) array rated capacity) and one output (electricity generation) from utility-scale PV power plants, meta-frontier data envelopment analysis was employed in this study to identify factors contributing to power generation inefficiency. Additionally, a Monte Carlo experiment analyzed the impact of solar irradiation uncertainty on power generation efficiency. The findings revealed that the average power generation inefficiency during the study period was 0.445, primarily attributable to seasonal and technical factors. Since these factors are difficult to control once a power plant is in operation, it is important to select an optimal site for power plants by considering meteorological and geographical data. Moreover, the results indicated a significant gap between observed and simulated values of power generation efficiency, arising from variations in weather conditions, power plant site area, and the data used in the research. Employing PV modules with higher electricity output levels can boost the DC/AC ratio, thereby increasing power generation, enhancing efficiency, and contributing to a stable power supply, thus reducing daily and seasonal fluctuations in power generation.

Simulation Model for Assessing High-Temperature Stress on Rice

Rice is a staple grain crop extensively cultivated in Fujian Province, China. This study examined the impact of high-temperature stress on rice yield and its components, focusing on four representative rice varieties, including early and middle rice grown in Fujian Province. Results indicate significant yield losses, with the most severe reduction of 60.8% observed during the flowering stage of early rice and over 40% during the meiosis and flowering stages of middle rice. High-temperature stress primarily affects early rice yield more at the flowering stage than at the grain-filling stage, whereas in middle rice, it is more severe at the meiosis stage than at the flowering stage. Leveraging historical climatic data spanning the past 20 years, a simulation model for high-temperature stress on rice yield was developed to assess disaster-induced yield loss rates, aiming to enhance prevention and disaster damage assessment for rice under high-temperature stress. Application of the model to four rice planting sites in Fujian Province revealed contrasting temporal changes between loss rates and meteorological yield, with middle rice experiencing more severe damage than early rice. The model’s effectiveness is validated by the strong correspondence between yield loss rate and meteorological yield across different regions, highlighting its robust simulation capabilities.

The volcanic aspect on determining Site of nuclear power plant in Indonesia: Gap analysis between standard and regulations

The development of nuclear power plants is in three phases. The first phase is a consideration before the decision on the NPP construction program is approved, the second phase is the preparatory work for making contracts and preparing for the construction of NPP after the NPP construction policy is approved, and the third phase is contracting, licensing and building the first NPP. As a volcanically active country, Indonesia contains over 130 active volcanoes that are part of the Pacific Ring of Fire. The volcanic aspect is one of the safety factors considered while deciding the location of an NPP. Research on the potential of natural external risks to the determination of nuclear power plants in Indonesia, including the volcanic aspect, has been conducted based on the safety reference or safety guide of the IAEA and the Nuclear Energy Regulatory Body (BAPETEN) Regulation. Due to technological advancements, safety needs have evolved so the existing Indonesia National Standard (SNI) must be updated to comply with BAPETEN regulations. The substance in SNI 18-2034-1990 relating to volcanic features seems less relevant in actual conditions, given that more complete and exact criteria for determining a site guarantee the safety and health of residents and surrounding the environment site. The study intends to conduct a gap analysis of volcanic issues in SNI and volcanic regulations. The method used is identification requirements for volcanic aspects in SNI 18-2034-1990 about Determining Site of Nuclear Reactor Guidance with BAPETEN Chairman Regulation (BCR) number 4 of 2018 about Nuclear Installation Site Evaluation Safety Provisions and BCR number 5 of 2015 about Evaluation of Nuclear Installation Sites for Volcanic Aspects, and analysis uses a qualitative method of inductive techniques. The outcome of this research applies to suggesting a revision of SNI number 18-2034-1990, especially the volcanic aspect.

Geospatial optimisation of wind and solar energy generation: A framework for optimised resource allocation

Wind and solar power generation profiles exhibit a high degree of power output variability and uncertainty compared to conventional fossil fuel generation plants. However, it is generally accepted that this variability and uncertainty can be mitigated by geographic siting and dispersion of the renewable energy plants, particularly with the view to leverage aggregation effects. In this context, this paper proposes a framework for the geospatial optimisation of wind and solar PV generation for scenarios with a high penetration of wind and solar renewable energy. The proposed optimisation framework represents a probabilistic risk-based approach that seeks to minimise the number of events where high residual load values require ancillary service interventions to maintain power balance. In this approach, the wind and solar resources are categorised in terms of the statistical properties of the associated spatiotemporal wind and solar power profiles for a given set of daily and seasonal Time of Use periods. It is thereby recognised that the resource characteristics and grid impact of wind and solar generation profiles can be interpreted with reference to the daily and seasonal cycles exhibited by the demand profiles, wherein some Time of Use periods are more important than others. The proposed framework is implemented for a number of baseline case studies and optimisation case studies, using wind and solar resource data sets covering South Africa. Overall, it is concluded that this approach can leverage geospatial site optimisation to substantially reduce the risks associated with high residual load events. Furthermore, the proposed framework is highly flexible in that the formulation of the minimum and maximum allocation constraints allows application for real-world scenarios whereby stringent capacity allocation constraints can be applied.

Isolation and Molecular Profiling of Halotolerant Plant Growth Promoting Rhizosphere Fungi from Salt affected Agroforestry Plantation

Soil salinity is a major abiotic stress that adversely affects plant growth, and productivity. About 20% of irrigated lands are affected by salinity worldwide; In India, there are 6.74 million hectares of salt-affected lands. Salt-tolerant Plant Growth Promoting (PGP) microorganisms can enhance the growth of plants in such salt-stressed areas. Therefore, this study aimed to investigate the diversity of beneficial fungal communities, screen for their ability to support plant growth, and evaluate the production of various essential compounds in view of plant growth in salt-stressed lands. A total of 68 fungal colonies were isolated from 5 different agroforestry plantation sites in Karur, Tamil Nadu, South India at quarterly intervals. The isolates were screened for sodium chloride (NaCl) tolerance (0%, 5%, 10%, 15%, and 20% concentration). A total of 7 isolates showed considerable salt tolerance and were tested qualitatively in-vitro, for PGP traits such as phosphate, potassium, and zinc solubilization, nitrogen fixation, hydrogen cyanide production, siderophore production, and ACC deaminase production. Finally, 5 isolates with maximum values for PGP properties under 20% NaCl concentration were tested for the quantity of Indole-3-Acetic Acid (IAA) and Exo-polysaccharide (EPS) production. All 5 isolates were identified up to the species level using 18S rRNA gene sequencing. To the best of our knowledge, this is the first report on isolating saline-tolerant PGP Fungi (PGPF) from the rhizosphere region of Casuarina equisetifolia and Eucalyptus camaldulensis in Karur, Tamil Nadu, India. In the future, the bioformulation of PGPF and its application will boost the cultivation of tree saplings in this salt affected regions.

Sustainability: study on rural properties affected by the construction of a hydroelectric power plant in northern region of the state of Mato Grosso/Brazil

The northern region of the State of Mato Grosso (MT), in Brazil, nationally recognized as a significant grain producer in the country, is undergoing transformations regarding key aspects of sustainability in certain areas near the construction site of the Hydroelectric Power Plant - HPP. In this scenario, the objective of this research was defined as studying the sustainability aspects perceived in the rural properties affected by the construction of a hydroelectric power plant in the municipality of SINOP (MT). To achieve the stated objective, a study was conducted on a sample of 15 rural properties that had a portion of their land affected by the construction of the power plant and in the process of reservoir flooding. Data collection occurred through the application of questionnaires, semi-structured script interviews with rural property owners, on-site and documentary observation, whose results will be presented through qualitative argumentative analysis, supported when necessary by quantitative parameters. The obtained results reveal that properties located in this region were directly impacted by the construction of this project, undergoing changes in environmental, economic, and social aspects, causing irreversible damage to the properties and hindering sustainable development in the region. In this context, sustainability assessment processes are considered important allies for managing sustainability in the agriculture sector and decision-making, as farmers in this region express concern about maintaining sustainability criteria and seek a balance between increased productivity and sustainable development.

On Integrating Time-Series Modeling with Long Short-Term Memory and Bayesian Optimization: A Comparative Analysis for Photovoltaic Power Forecasting

The means of energy generation are rapidly progressing as production shifts from a centralized model to a fully decentralized one that relies on renewable energy sources. Energy generation is intermittent and difficult to control owing to the high variability in the weather parameters. Consequently, accurate forecasting has gained increased significance in ensuring a balance between energy supply and demand with maximum efficiency and sustainability. Despite numerous studies on this issue, large sample datasets and measurements of meteorological variables at plant sites are generally required to obtain a higher prediction accuracy. In practical applications, we often encounter the problem of insufficient sample data, which makes it challenging to accurately forecast energy production with limited data. The Holt–Winters exponential smoothing method is a statistical tool that is frequently employed to forecast periodic series, owing to its low demand for training data and high forecasting accuracy. However, this model has limitations, particularly when handling time-series analysis for long-horizon predictions. To overcome this shortcoming, this study proposes an integrated approach that combines the Holt–Winters exponential smoothing method with long short-term memory and Bayesian optimization to handle long-range dependencies. For illustrative purposes, this new method is applied to forecast rooftop photovoltaic production in a real-world case study, where it is assumed that measurements of meteorological variables (such as solar irradiance and temperature) at the plant site are not available. Through our analysis, we found that by utilizing these methods in combination, we can develop more accurate and reliable forecasting models that can inform decision-making and resource management in this field.

Growth and yield of Retrophyllum rospigliosii pure plantations in the Colombian Andes

Most reforestation in Colombia, especially in the Andean region, are monocultures of pines and eucalyptus with defined nursery and silvicultural packages. Planting native species would avoid the widespread controversy over reforestation with exotic species. Nevertheless, there are few studies that evaluate the growth and yield of native species and provide supported data to establish new projects. Here, we modeled the growth and yield of the native coniferous Retrophyllum rospigliosii in different areas of the Colombian Andes in terms of mean diameter (D), height (H), and volume (V) as a function of age, based on longitudinal data from 115 research sample plots from three sites that were remeasured between 4 and 9 times for 20 years. We fitted the von Bertalanffy growth model for D, H, and V through Bayesian generalized nonlinear mixed models to model tree growth. The adjustment of the models for the absolute growth of R. rospigliosii was 0.99, 0.99, and 0.97 for D, H, and V, respectively. All models fulfilled all regression assumptions. Although the growth rates of R. rospigliosii differed between planted sites, R. rospigliosii plantations generally exhibited low growth and barely reached the sizes required for commercialization. These results suggest that the extensive use of R. rospigliosii in pure plantations is unlikely and discourages the massive propagation of R. rospigliosii.

A Source and Ground Motion Study of the Veracruz Earthquakes of 29 October 2009 (Mw5.7) and 4 August 2021 (Mw4.8): Evidence of Strong Azimuthal Variation of Attenuation

We study two moderate earthquakes that occurred offshore the State of Veracruz, in the southwestern Gulf of Mexico, on 29 October 2009 (Mw 5.7) and 4 August 2021 (Mw 4.8). The former was located near the town of Alvarado and latter near the city of Veracruz. The events were well recorded by accelerographs and seismographs at local and regional distances. W-phase regional centroid moment tensor inversion reveals that they had reverse-faulting mechanism, similar to several other earthquakes in the southwestern Gulf of Mexico. Of the seven focal mechanisms now available along the southwestern margin, two are strike slip and the rest are of thrust type, suggesting a heterogeneous stress regime. We take advantage of local and regional recordings produced by these two earthquakes to study the characteristics of the ground motion. Source spectra computed at each station separately (without correcting for the site effect), assuming a reasonable geometrical spreading and Q = 141f 0.63, show remarkably high variability due to difference in path and local site effects. The geometric mean apparent source spectrum (source spectrum including site effects) of both earthquakes may be modeled by an ω2 -Brune source model with a stress drop, Δσ, of 40 MPa. These source spectra, along with the application of stochastic method, yield peak ground acceleration (PGA) and velocity (PGV) as a function of distance in general agreement with the observations. Of greater practical importance is the ground motion at sedimentary sites in the city of Veracruz and at the Laguna Verde Nuclear Power Plant (LVNPP) site, especially from a postulated Mw 6.5 earthquake which is a reasonable scenario event for the region. For the city of Veracruz and LVNPP we estimate site effect with respect to the ω2 -Brune source with Δσ of 2 MPa. There is some support for this Δσ. We apply both stochastic and empirical Green’s functions (EGF) techniques in the estimation of the ground motion. The recording of the 2021 earthquake is taken as the EGF, and Δσ of the EGF and the target event are assumed to be the same and equal to 2 MPa. The predicted PGA and PGV at sedimentary sites in the city of Veracruz and LVNPP above the hypocenter (depth = 20 km) from the postulated Mw 6.5 earthquake are 0.2 g and 10 cm/s and 0.18 g and 3 cm/s, respectively. These results are preliminary as they are based on several assumptions.

Numerical studies of sCO2 Brayton cycle

This work describes the one-dimensional, thermo-hydraulic model of the sCO2 cycle Sofia developed to investigate optimal control methods and the behaviour of the cycle during operation. This dynamic model includes all devices such as turbomachinery, heat exchangers, valves, and piping including heat loss, in line with concept of the 1 MWe sCO2 cycle, to be realised in the site of a fossil power plant in the Czech Republic.The model assembly and calculations were conducted using the commercial Modelica-based library ClaRa + using the simulation environment Dymola and in combination with another Modelica-based library, UserInteraction; the real-time simulations, with some parameter changes during the calculation, are made and described in this paper.Nominal parameters were achieved during the steady-state simulation, except for the lower mass flow of sCO2. Transient simulation of power turbine start-up from standby state and results are also presented in this paper. The nominal state is achieved with the semi-automatic procedure in approx. 3 h. The simulation results allow more detailed analyses of control methods and a better understanding of real device control and behaviour during start-up, shutdown, or other transients.Careful manipulation of turbine valves in coordination with the pressuriser operation was identified as crucial for optimal control of the system. Also, the initial amount of CO2 in the pressuriser affects its behaviour during transients.

Potassium and Magnesium in American Ginseng Roots as Key Factors in Monitoring Soil Quality, Yield, and Quality: Screening, Prediction, and Validation

Understanding the key roles of nutrient elements in soil–plant systems are essential for herbal medicine production and sustainable development. However, the ecological relationships between soil quality and nutrient elements, yield, saponins, or other active compounds in American ginseng remain unclear. In this study, 20 soil indicators, 10 root nutrient indicators, 9 quality indicators, and yields were investigated. The minimum dataset was constructed by principal component analysis, key factors were screened by correlation analysis and PLS-PM analysis, and the prediction model was constructed using linear fitting and tested by a validation test. The minimum dataset, constructed based on principal component analysis, comprised five indicators: SOM, TP, AK, AMg, and ACa. Correlation analysis, PLS-PM analysis, and linear fitting showed that K and Mg were the key factors relating soil quality to the yield and quality of American ginseng and that when AMg was 0.21 g/kg and AK was 0.30 g/kg, soil organic matter was 27%, total phosphorus was 1.19 g/kg in soil, K content in roots was 15.63 g/kg, Mg content was 1.91 g/kg, and the K/Mg of 8.85 could balance American ginseng yield and quality. In predicting and validating the model, predicting the DW, total ginsenoside, Rb1, Rb2, Rc, and Rd of American ginseng using K/Mg were reliable. This study provides a scientific basis for nutrient regulation, selecting planting sites, assessing soil quality, and predicting and evaluating American ginseng quality.

Best practices, errors, and perspectives of half a century of plant translocation in Italy.

Conservation translocations are becoming common conservation practice, so there is an increasing need to understand the drivers of plant translocation performance through reviews of cases at global and regional levels. The establishment of the Italian Database of Plant Translocation (IDPlanT) provides the opportunity to review the techniques used in 186 plant translocation cases performed in the last 50years in the heart of the Mediterranean Biodiversity Hotspot. We described techniques and information available in IDPlanT and used these data to identify drivers of translocation outcomes. We tested the effect of 15 variables on survival of translocated propagules as of the last monitoring date with binomial logistic mixed-effect models. Eleven variables significantly affected survival of transplants: life form, site protection, material source, number of source populations, propagation methods, propagule life stage, planting methods, habitat suitability assessment, site preparation, aftercare, and costs. The integration of vegetation studies in the selection of suitable planting sites significantly increased the success of translocation efforts. Although posttranslocation watering had a generally positive effect on translocation outcome, other aftercare techniques did not always increase transplant survival. Finally, we found that how funds were spent appeared to be more important than the actual amount spent. Plant translocations in Italy and in the Mediterranean area should account for the complexity of speciation, gene flow, and plant migrations that has led to local adaptations and has important implications for the choice and constitution of source material.

Acidic soil-tolerant tree species identification

Previously, surface soil acidity was amended by the application of lime, gypsum, and acidic soil-tolerant crop species. However, their effectiveness in subsurface soil acidity reduction is limited. Thus, this review paper aimed to screen the tree species that easily overcome such problems. Scopus, Science Direct, Google Scholar, African journals online, and Google search engine databases were used. A total of 60 acidic soil-tolerant tree species were identified. Acacia auriculiformis, Acacia crassicarpa, Arbutus unedo L., Casuarina junghuhniana, and Erythrina abyssinica were among the extremely acidic soil-tolerant tree species. Whereas Acacia cincinnata, Acacia mangium, Pinus patula, Albizia saman, Citrus x paradisi, and Cassia reticulata were belongs to some of the strong acidic soil tolerant tree species. Generally, the species' acidic tolerance capacity and planting site compatibility should be considered for the success of amendment works. Scaling out these species and large-scale plantations should be done in addition to estimating their relative percent of acidic soil amendment roles. Producing stable food in line with reclaiming acidic soil is achieved through the integration of stress tolerant fruit trees. Research on large-scale plantations, domestication, skilling up and comparative evaluation of their levels of acidic soil amendment capacity should be performed in the future.

Drivers of tree establishment in planted windbreaks and riparian buffers: A case study of farms in southern Quebec, Canada

Successfully established windbreaks and riparian buffers contribute to protection of soils, crops, watercourses and biodiversity, and help to combat climate change. To improve establishment success of trees planted to form these agroforestry systems, identifying the factors influencing their survival and growth is crucial. We related survival and size of trees planted in windbreaks and riparian buffer strips to 23 abiotic, biotic, structural and technical explanatory factors using multiple generalized linear models. We sampled 52 windbreaks and 26 riparian buffer strips planted in different cultivated fields in southern Quebec (Canada). We analyzed volunteer vegetational composition in the tree planting right-of-way relative to eight explanatory factors. Average survival of planted trees was 86.4% and varied mainly with planting site; tree survival was negatively and significantly correlated with soil pH. We modelled correlations between size of the ten most frequently occurring tree species and 20 explanatory factors, of which six were significant, i.e., method of volunteer vegetation control, soil texture, soil preparation before planting, volunteer vegetation abundance, tree row structure and agroforestry system type (windbreak vs riparian buffer). Relative abundance of different functional types of volunteer vegetation was influenced mainly by the age of agroforestry systems. To increase tree establishment success in winbreaks and riparian buffers, species must be properly selected for planting based upon edaphic conditions, while implementing soil preparation prior to planting and maintaining sufficient spacing between trees to optimize long-term growth. Our results suggest that tree establishment in windbreaks and riparian buffers within an intensive agricultural context should not be perceived as a barrier to their adoption.