This review explores the potential of biopolymers as sustainable alternatives to conventional plastics in food packaging. Biopolymers derived from plant or animal sources are crucial in extending food shelf life, minimizing degradation, and protecting against oxidative and microbial agents. Their physical and chemical properties, influenced by the raw materials used, determine their suitability for specific applications. Biopolymers have been successfully used in fruits, vegetables, meats, and dairy products, offering antimicrobial and antioxidant benefits. Consequently, they represent a functional and eco-friendly solution for the packaging industry, contributing to sustainability while maintaining product quality.

Forest fires are the result of poor land management and climate change. Depending on the type of the affected eco-system, they can cause significant biodiversity losses. This study was conducted in the Amazonas department in Peru. Binary data obtained from the MODIS satellite on the occurrence of fires between 2010 and 2022 were used to build the risk models. To avoid multicollinearity, 12 variables that trigger fires were selected (Pearson ≤ 0.90) and grouped into four factors: (i) topographic, (ii) social, (iii) climatic, and (iv) biological. The program Rstudio and three types of machine learning were applied: MaxENT, Support Vector Machine (SVM), and Random Forest (RF). The results show that the RF model has the highest accuracy (AUC = 0.91), followed by MaxENT (AUC = 0.87) and SVM (AUC = 0.84). In the fire risk map elaborated with the RF model, 38.8% of the Amazonas region possesses a very low risk of fire occurrence, and 21.8% represents very high-risk level zones. This research will allow decision-makers to improve forest management in the Amazon region and to prioritize prospective management strategies such as the installation of water reservoirs in areas with a very high-risk level zone. In addition, it can support awareness-raising actions among inhabitants in the areas at greatest risk so that they will be prepared to mitigate and control risk and generate solutions in the event of forest fires occurring under different scenarios.

The genus Cinchona belongs to the Rubiaceae family and comprises native Peruvian tree species distributed in tropical areas. It is currently endangered due to human disturbance and overexploitation for medicinal, forestry and food uses. To date, the current and future distribution of Cinchona spp. under the climate change scenario is unknown. Here, we modeled the present and future spatial distribution of the genus Cinchona using bioclimatic, edaphic and topographic variables using the maximum entropy algorithm (MaxEnt). The results indicate that 8.08% (103,547.89 km²) and 6.02% (77,163.81 km²) of the surface of Peru possesses areas with high and moderate distribution probabilities, respectively, to host the genus Cinchona, distributed mainly in the departments of Cusco, Amazonas, San Martín and Cajamarca. Furthermore, according to future climate scenarios, the areas of high suitability will increase their extension for the years 2050 and 2070 by 3.65% and 3.9%, respectively. Since Peru seeks to promote the forest sector to be the other force for its development, this study can be considered as a basis for the establishment of priority zones for the conservation, restoration, reforestation and sustainable management of Cinchona spp. species in Peru.

This study examines the use of a spatial multi-criteria approach based on GIS and AHP techniques to model landslide risk in the Utcubamba river basin, Peru. The methodology consisted of selecting twelve triggering variables: slope angle, geology, precipitation, distance to faults, drainage density, TWI, relative relief, profile curve, land use, elevation, distance to roads, and distance to population centers. These variables were then analyzed using the AHP method and then integrated into a GIS environment, where the weighted linear combination (WLC) method was used to map landslide risk. The risk was categorized into five classes, ranging from very low (1) to very high (5). The main results indicate that 32.81% of the area analyzed in the Utcubamba river basin presents a high and very high risk of landslides. The high-risk areas are mainly located in the southern part of the basin and coincide with areas with steep slopes, high rainfall, and proximity to population centers or communication routes. The model generated was highly accurate (AUC of 0.82), confirming that the integration of the AHP method with GIS allows for the precise identification of critical areas, which is useful for territorial planning, the prioritization of interventions, and emergency management, making it a reliable and replicable methodology in other parts of Peru.

The high rate of depredation of forest resources causes major climatic changes that affect the economic activities and health of populations, plunging them into poverty and social problems. The state is responsible for dealing with these problems, because it has the technical, legal, and economic power to do so. This research aims to identify the factors that limit the design and formulation of public policies for the conservation of natural resources at the level of local district and provincial governments in Peru. For this study, we used qualitative methodology and non-probabilistic sampling, as well as techniques such as unstructured interviews, focus groups, and documentary review; moreover, for data analysis, we applied the theoretical saturation design in grounded theory. The results show that the conservation of natural resources is not positioned as a priority public policy in municipal administrations; furthermore, the organic units of natural resources suffer financial restrictions, and not because of a lack of budget availability, but because of a lack of will and decision-making capacity of authorities and civil servants, as well as a lack of coordination between the different national governments. It concludes that there are conflicts of interest in public policy making, with abuse of power and corruption predominating. Furthermore, the complexity of addressing sustainability criteria and the inability to confront the environmental crisis mean that international summits and national norms are attenuated in the face of the problems of environmental degradation. Deforestation should be considered a major public priority problem because of its environmental, economic, social, and health impacts. These problems require a holistic approach that combines local, national, and international policies and fosters effective and participatory governance.

Dengue, a febrile disease that has caused epidemics and deaths in South America, especially Peru, is vectored by the Aedes aegypti mosquito. Despite the seriousness of dengue fever, and the expanding range of Ae. aegypti, future distributions of the vector and disease in the context of climate change have not yet been clearly determined. Expanding on previous findings, our study employed bioclimatic and topographic variables to model both the present and future distribution of the Ae. aegypti mosquito using the Maximum Entropy algorithm (MaxEnt). The results indicate that 10.23% (132,053.96 km²) and 23.65% (305,253.82 km²) of Peru’s surface area possess regions with high and moderate distribution probabilities, respectively, predominantly located in the departments of San Martín, Piura, Loreto, Lambayeque, Cajamarca, Amazonas, and Cusco. Moreover, based on projected future climate scenarios, it is anticipated that areas with a high probability of Ae. aegypti distribution will undergo expansion; specifically, the extent of these areas is estimated to increase by 4.47% and 2.99% by the years 2070 and 2100, respectively, under SSP2-4.5 in the HadGEM-GC31-LL model. Given the increasing dengue epidemic in Peru in recent years, our study seeks to identify tools for effectively addressing this pressing public health concern. Consequently, this research serves as a foundational framework for assessing areas with the highest likelihood of Ae. aegypti distribution in response to projected climate change in the second half of the 21st century.