El presente trabajo tuvo como objetivo realizar una revisión sistemática del uso de imágenes Sentinel-2 para el monitoreo de la cobertura boscosa a nivel global, para lo cual se empleó el protocolo propuesto por Prisma 2009. La búsqueda de los artículos científicos publicados entre el 2015 y 2021 se realizó en las bases de datos: Scopus y Science Direct, analizándose un total de 65 artículos en los que se detalla los diferentes tipos de clasificadores utilizados para procesar las imágenes S-2, la exactitud temática lograda en la cartografía, así como el aumento, mantenimiento o retroceso de los bosques y sus principales causas a nivel mundial. Como resultados se encontró que Random Forest (RF) es el clasificador más utilizado para el procesamiento digital de las imágenes S-2, el cual logra en la mayoría de los casos una exactitud temática superior al 85%. En los trabajos multitemporales, se ha encontrado que la cobertura boscosa en Sudamérica y África se ha visto disminuida por actividades como la agricultura y ganadería. Mientras que, en algunos países asiáticos la cobertura boscosa se ha incrementado como consecuencia de la implementación de programas de reforestación y manejo forestal comunitario. Por lo que lo resultados sugieren que las imágenes Sentinel-2 presentan un enorme potencial para llevar a cabo el seguimiento continuo y sistemático de la pérdida o ganancia de los bosques en todo el planeta.

Coffee is traditionally grown in agroforestry systems. Shade trees in coffee plantations provide important ecosystem services, and their timber may also be a good source of income for coffee growers. However, key information on the value of shade tree timber and its potential contribution to the income of coffee growers based on empirical data is lacking. The income that could be obtained from shade trees was estimated for three coffee plantations with different shade tree species. To estimate the marketable timber volume of standing trees, allometric equations were developed. Our results showed that the value of the shade tree timber varied significantly. It represented only 2-3% of the annual coffee farm income on the coffee plantation dominated by native Inga spp. On the other hand, the plantation predominantly shaded by Eucalyptus trees had high potential annual (50-68% of plantation income) and total (92-96% of plantation income) timber value, followed by the plantation shaded predominantly by Pinus (32-49% of plantation income for annual timber volume and 89-94% of plantation income for total timber volume). It is evident that shade trees may be a good economic reserve for coffee growers when exotic Eucalyptus or Pinus tree species are planted. However, using individual-tree data, it was found that the relatively rare native shade tree Retrophyllum rospigliosii, which was found in almost all plantations, has a high timber value and a large timber supply, making it a shade species with high potential for agroforestry.

This study addressed multi-product optimization in Cedrelinga cateniformis plantations in the Peruvian Amazon, aiming to maximize volumetric yields of logs and sawn lumber. Data from seven plantations of different ages and types, established on degraded land, were analyzed by using ten stem profile models to predict taper and optimize wood use. In addition, the structure of each plantation was evaluated using diameter distributions and height–diameter ratios; log and sawn timber production was optimized using SigmaE 2.0 software. The Garay model proved most effective, providing high predictive accuracy (adjusted R² values up to 0.963) and biological realism. Marked differences in volumetric yield were observed between plantations: older and more widely spaced plantations produced higher timber volumes. Logs of optimal length (1.83–3.05 m) and larger dimension wood (e.g., 25.40 × 5.08 cm) were identified as key contributors to maximizing volumetric yields. The highest yields were observed in mature plantations, in which the total log volume reached 508.1 m³ha⁻¹ and the sawn lumber volume 333.6 m³ha⁻¹. The findings demonstrate the power of data-driven decision-making in the timber industry. By combining precise modeling and optimization techniques, we developed a framework that enables sawmill operators to maximize log and lumber yields. The insights gained from this research can be used to improve operational efficiency and reduce waste, ultimately leading to increased profitability. These practices promote support for smallholders and the forestry industry while contributing to the long-term development of the Peruvian Amazon.

The objective of this research was to evaluate the eco-efficiency of the district municipality Jose Crespo y Castillo de Peru; for this, a baseline was drawn up and indicators were formulated and implemented for the eco-efficiency plan. The standardization of the data was carried out by applying maximums and minimums. The weighting of indicators was established using the Delphi method and the instruments were validated by experts. The development of the biogram was carried out based on the eco-efficiency indices. Higher than expected results were obtained in the planning stage. The state in which the district municipality Jose Crespo y Castillo is located was also known through the biogram, which was not eco-efficient and unstable.

This study analyzed the impact of leachate from a temporary landfill on soil microbial diversity in Tingo María, Huánuco region, Peru. Three treatments were used: untreated soil (S), addition of stream water (T0), leachate (T1), and leachate treated by coagulation and flocculation (T2), with 828.5 ml/week added in three weekly doses. Soil samples were collected from the Reserved Forest of the Universidad Nacional Agraria de la Selva. Twenty-one randomly distributed soil samples were taken and homogenized for analysis. Soil quality parameters measured included sand, clay, silt, texture, pH, organic matter, nitrogen, phosphorus and potassium. As for microorganisms, viable aerobes, lactobacilli, actinomycetes, fungi, nitrogen-fixing bacteria, and Escherichia coli were quantified using specific culture and counting methods for each of them. To evaluate the impact of the leachate on microbial diversity, equity indices (Shannon and inverse Simpson), dominance indices (complementary Simpson and Berger Parker) and the percentage composition of each microorganism per treatment were used. An ANOVA was performed to estimate differences in microbial diversity, with a Tukey test at a significance level of α = 0.05. The study showed that leachates affect soil microbial diversity, reducing equity and increasing the dominance of certain species such as E. coli. They also alter physicochemical parameters, decreasing organic matter and nitrogen but increasing other elements such as phosphorus and potassium. This could have implications for soil health and functionality.

Efecto de abonos orgánicos en el crecimiento inicial de plantaciones de bolaina “guazuma crinita” en Tulumayo