.CRIS - Publication (Artículos de proyectos financiados)

Dry forests are ecosystems of great importance worldwide, but in recent decades they have been affected by climate change and changes in land use. In this study, we evaluated land use and land cover changes (LULC) in dry forests in Peru between 2017 and 2021 using Sentinel-2 images, and cloud processing with Machine Learning (ML) models. The results reported a mapping with accuracies above 85% with an increase in bare soil, urban areas and open dry forest, and reduction in the area of crops and dense dry forest. Protected natural areas lost 2.47% of their conserved surface area and the areas with the greatest degree of land use impact are located in the center and north of the study area. The study provides information that can help in the management of dry forests in northern Peru.

The Peruvian Amazon faces an increasing threat of soil erosion, driven by unsustainable agricultural practices and accelerated deforestation. In Neshuya (Ucayali region), agricultural activity has intensified since 2014, but the effect on soil erosion is unknown. The present study aimed to evaluate the increase in erosion levels, at a subbasin of the central–eastern Amazon of Peru, in a Geographic Information System (GIS) environment. The revised universal soil loss equation (RUSLE) model was used for assessing the effect of vegetation cover change from 2016 to 2022. In the Neshuya sub-basin (973.4 km2 ), the average erosion increased from 3.87 to 4.55 t ha−1 year−1 , on average. In addition, there is great spatial variability in the values. In addition, 7.65% of the study area (74.52 km2 ) exceeds the soil loss tolerance limit (15 t ha−1 year−1 ). The deforestation rate was 17.99 km2 year−1 and by 2022 the forested area reached 237.65 km2 . In conclusion, the transition from forest to farmland was related to the most critical erosion values. Unsustainable soil management practices can be the underlying explanation of changes in soil chemical and physical properties. Also, social dynamic changes and differences in landscape patterns play a role.

Purple maize has gained global significance due to its numerous nutraceutical benefits. However, sustaining its production typically requires high doses of nitrogen fertilizers, which, when applied in excess, can contaminate vital resources such as soil and water. Inoculation with nitrogenfixing microorganisms, such as those from the Azospirillum genus, has emerged as an alternative to partially or fully replace nitrogen fertilizers. This study aimed to evaluate the inoculation effect with A. brasilense and varying nitrogen fertilization levels on the yield and quality of purple maize. The experiment was carried out using a randomized complete block design (RCBD) with a 2 × 5 factorial arrangement and five replications. Treatments comprised two inoculation levels (control without inoculation and inoculation with A. brasilense) under five nitrogen doses (0, 30, 60, 90, and 120 kg・ha−1, applied as urea). Inoculation with A. brasilense resulted in a 10.5% increase in plant height, a 16.7% increase in root length, a 21.3% increase in aboveground fresh biomass, a 30.1% increase in root fresh biomass, and a 27.7% increase in leaf nitrogen concentration compared to the no inoculated control. Regarding yield, the inoculated plants surpassed the control in both purple maize yield (kg・ha−1) and cob weight by 21.8% and 11.6%, respectively. Across all fertilization levels and parameters assessed, the inoculated treatments outperformed the control. Furthermore, for parameters, namely plant height, leaf nitrogen content, and cob dimensions (length, diameter, and weight), the A. brasilense inoculation treatment with 90 kg N・ha−1 was statistically equivalent or superior to the non-inoculated control with 120 kg N・ha−1. These results indicate that inoculation with A. brasilense positively impacted purple maize at all nitrogen levels tested and improved nitrogen use efficiency, enabling a reduction of 30 kg N・ha-1 without compromising performance in key parameters.

Soil is a vital nonrenewable resource characterized by rapid degradation and slow regeneration processes. In this study, soil degradation in Jaén and San Ignacio was assessed via a multicriteria evaluation approach combined with remote sensing (RS) data. Nine factors were analyzed classified three categories: environmental, topographic, and edaphological factors. The results revealed that the slope (59.07%) was the main influencing factor, followed by land use and land cover (LULC) (56.36%). The degradation map revealed that 83.48% of the area exhibited moderate degradation, 14.49% low degradation, and 1.56% high degradation. The districts of Pomahuaca and San José de Lourdes demonstrated the largest areas of moderate degradation, accounting for 13.71% and 22.54%, respectively. Bellavista and Huarango exhibited the largest areas of very high degradation, accounting for 0.27% and 0.08%, respectively. The (AHP) method and RS data were employed to assess soil degradation, highlighting the need for sustainable soil restoration and conservation strategies.