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Spectacled bears (SB) (Tremarctos ornatus) are the only bear species native to South America. This particular bear is the single species of its genus, and it is listed as vulnerable according to the IUCN red list. A critical SB conservation habitat is in the rural territories of the Peruvian Amazon, where anthropogenic land-use changes and landscape fragmentation threaten SB habitats. The following questions arise in this context: How much has land-use changed? How to design the establishment of ecological corridors (ECs) to support the conservation of SB?. We investigated the temporal land use and land cover changes for last 30 years (1990–2020) for a better projection of the ECs and to quantify the temporal landscape metrics. Furthermore, we integrated cloud computing, machine learning models with cost-effective techniques to delineate the ECs for SB within the rural territories. Ensemble Random Forest model associated with Google Earth Engine (GEE) was used to develop four land use and land cover (LULC) maps (for the years 1990, 2000, 2010 and 2020). The least cost path (LCP) model based on Dijkstra’s shortest path algorithm was assembled based on six variables (altitude; slope; distance to roads; distance to population centers; land use map; inventory map of SB). Then, we calculated the ECs based on the multidirectional origin-destination points, we found that forest patches increased by 57% between 1990 and 2020. Results showed statistically significant agreement (R2 = 0.47; p

The northeastern region of Peru is one of the centers of origin of cocoa due to the great diversity of this cultivar. The objective of this study is, therefore, to search for different genetic groups of 146 ecotypes of fine-aroma native cacao from the northeastern region of Peru, based on the morphological descriptors of pods, seeds, sensory, yield, and sampling altitude. The data were analyzed using multivariate statistics; a cluster analysis was performed with the numerical and categorical variables, followed by a principal component analysis (PCA) and the DGC (Di Rienzo, Guzmán y Casanoves) mean comparison test for the numerical data. Contingency tables and the multiple correspondence analysis (MCA) were performed for the categorical data. We differentiated 5 genetic groups; helpfully, sensory characteristics of the flowers and pod, size and weight of the seeds, and pod index were in fact crucial in separating the groups. The ecotypes of the groups labeled as “Indes” and “Bagüinos” reported the best sensory characteristics with high floral and fruity notes and with a good yield expressed in pod index (13.88 and 11.88, respectively). Furthermore, these ecotypes are found at medium and high altitudes, above 500 m a.s.l., a factor that enables them to express their sensory and yield attributes. On the contrary, the ecotypes known as “Toribianos” and “Cajas” report the highest pod indices (20.77 and 16.78, respectively), resulting in low productivity. In the future, the variability of the ecotypes found will help establish genetic improvement programs that contribute to the development of cocoa farming in general.

Cocoa cultivation is of considerable economic and social importance to the Amazonas region and is commonly associated with forest species in the region. However, the diversification level and composition of cacao agroforestry systems in Peru are poorly understood. The objective of this study is, therefore, to describe the diversity of tree species in cocoa AFS by plantation age. Accordingly, the number of species of 15 plots covering a total of 1.5 hectares was recorded. Moderately low levels of tree species diversity were reported (H´ ranged 0.89–1.45). In total 17 species were reported throughout the study area. The most abundant botanical family was represented by a single Musa sp. species. The dissimilarity indices show a moderate similarity between the age ranges evaluated (over 62%). Additionally, the IVI indicates that the most important species are used for food and timber apart from providing shade, additionally major of this species are introduced intentionally for the farmers. Based on the observations, it may be concluded that the farmer’s interest in obtaining further benefits from the plot, mostly economic benefits affect the diversification of cocoa agroforestry systems.

The evaluation of suitable landfill sites is a complex process and requires various legislative, technical, social, and environmental criteria. Therefore, this study provides a management tool for identifying suitable sites for landfills through the integrated use of the analytic hierarchy process (AHP), geographic information systems (GISs), and remote sensing (RS). Accordingly, fourteen subcriteria were identified and grouped into physical (7), environmental (3), and socioeconomic (4) criteria and were weighed using pairwise comparison matrices (PCMs). The weighted linear combination (WLC) approach of maps allowed us to generate models and submodels of land suitability. From the territory of the districts of Chachapoyas and Huancas, 0.9% (1.71 km2), 71.1% (141.89 km2), 21.0% (41.86 km2), 0.0%, and 7.7% (14.21 km2) have highly suitable, moderately suitable, marginally suitable, unsuitable, and restricted conditions, respectively, for a landfill site. Twelve highly suitable sites were identified, of which three were selected based on their shape and the minimum area required for the operation of the landfill until 2040. In fact, this study proposes a management tool for decision-makers (DMs) that improve the process of selecting landfill sites, supported by engineering and its applications for territorial sustainability.

Las Áreas de Conservación Privada (ACP) son uno de los mecanismos de conservación, gestionadas por ciudadanos privados que más protagonismo han adquirido en los escenarios de conservación local en los últimos años. En este estudio evaluamos la efectividad de cuatro ACP gestionadas por comunidades locales (CC). Se aplicó el Índice de Efectividad Compuesto (IEC) para determinar la efectividad del diseño, la integridad ecológica y la gestión. Los resultados muestran sistemas de gestión con una efectividad media, tres de las cuatro ACP evaluados (Copallín, Huaylla Belén-Colcamar y Tilacancha) reportan un diseño efectivo. Los rangos altitudinales protegidos están entre 2500 y 3500 m.s.n.m., con un índice de representatividad de la superficie promedio de 4,55% con respecto al área conservada en la categoría ACP para el departamento de Amazonas. La evaluación de la integridad ecológica indica que las ACP presentan menor superficie transformada (TS) (0-10%) y mayor TS en sus áreas circundantes, especialmente en el ACP Tilacancha (13,37% de TS en un buffer de 1,5 km). La suma ponderada de los índices individuales resulta en índices de efectividad compuestos de mayor a menor para el ACP Copallín (2,22), Hierba Buena Allpayacku (1,82), Huaylla Belen Colcamar (1,81) y Tilacancha (1,56).

Amazonas is a mountain region in Peru with high cloud cover, so using optical data in the analysis of surface changes of water bodies (such as the Burlan and Pomacochas lakes in Peru) is difficult, on the other hand, SAR images are suitable for the extraction of water bodies and delineation of contours. Therefore, in this research, to determine the surface changes of Burlan and Pomacochas lakes, we used Sentinel-1 A/B products to analyse the dynamics from 2014 to 2020, in addition to evaluating the procedure we performed a photogrammetric flight and compared the shapes and geometric attributes from each lake. For this, in Google Earth Engine (GEE), we processed 517 SAR images for each lake using the following algorithms: a classification and regression tree (CART), Random Forest (RF) and support vector machine (SVM).) 2021-02-10, then; the same value was validated by comparing the area and perimeter values obtained from a photogrammetric flight, and the classification of a SAR image of the same date. During the first months of the year, there were slight increases in the area and perimeter of each lake, influenced by the increase in rainfall in the area. CART and Random Forest obtained better results for image classification, and for regression analysis, Support Vector Regression (SVR) and Random Forest Regression (RFR) were a better fit to the data (higher R2), for Burlan and Pomacochas lakes, respectively. The shape of the lakes obtained by classification was similar to that of the photogrammetric flight. For 2021-02-10, for Burlan Lake, all 3 classifiers had area values between 42.48 and 43.53, RFR 44.47 and RPAS 45.63 hectares. For Pomacohas Lake, the 3 classifiers had area values between 414.23 and 434.89, SVR 411.89 and RPAS 429.09 hectares. Ultimately, we seek to provide a rapid methodology to classify SAR images into two categories and thus obtain the shape of water bodies and analyze their changes over short periods. A methodological scheme is also provided to perform a regression analysis in GC using five methods that can be replicated in different thematic areas.

The inhabitants of Tunants and Yahuahua face water supply problems in terms of quantity and quality, leading to socio-environmental and health impacts in the areas. The objective of this research, therefore, is to determine the technical and economic feasibility of a proposal for a rainwater harvesting and treatment system for human consumption in the native communities. For the technical feasibility, monthly water demand per family was compared with the amount of water collected in the rainy and dry seasons. In addition, 16 physical, chemical, and microbiological parameters were evaluated at the inlet and outlet of the water system. The economic feasibility was determined by the initial investment and maintenance of the systems; with the benefits, we obtained the net present social value (NPSV), social internal rate of return (SIRR), and cost-effectiveness (CE). Technically, oxygenation and chlorination in the storage tanks allowed for water quality in physical, chemical, and microbiological aspects, according to the D.S. N° 031-2010-SA standard, in all cases. Finally, with an initial investment of S/2,600 and S/70.00 for annual maintenance of the system, it is possible to supply up to six people per family with an average daily consumption of 32.5 L per person. It is suggested that the system be used at scale in the context of native communities in north-eastern Peru.

In Peru, grasslands monitoring is essential to support public policies related to the identification, recovery and management of livestock systems. In this study, therefore, we evaluated the spatial dynamics of grasslands in Pomacochas and Ventilla micro-watersheds (Amazonas, NW Peru). To do this, we used Landsat 5, 7 and 8 images and vegetation indices (normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and soil adjusted vegetation index (SAVI). The data were processed in Google Earth Engine (GEE) platform for 1990, 2000, 2010 and 2020 through random forest (RF) classification reaching accuracies above 85%. The application of RF in GEE allowed surface mapping of grasslands with pressures higher than 85%. Interestingly, our results reported the increase of grasslands in both Pomacochas (from 2457.03 ha to 3659.37 ha) and Ventilla (from 1932.38 ha to 4056.26 ha) micro-watersheds during 1990–2020. Effectively, this study aims to provide useful information for territorial planning with potential replicability for other cattle-raising regions of the country. It could further be used to improve grassland management and promote semi-extensive livestock farming.

Biodiversity is an indispensable resource and contributes to the balance of ecosystems, being of great importance for the development of a society and its culture through good management of natural spaces. However, the reduction in and fragmentation of habitats, trafficking, and illegal trade in wild animals affect the great diversity of wild flora and fauna that characterize Peru. Considering this problem, we modeled the biogeographic distribution of five species of wildlife categorized as threatened by Peruvian legislation and included in the red list of threatened species of the International Union for the Conservation of Nature (IUCN): critically endangered (CR) Lagothrix flavicauda, endangered (EN) Aotus miconax, in vulnerable-status (VU) Tremarctos ornatus and Lagothrix cana, and in the near-threatened category (NT) Panthera onca. Our study aimed to identify their current potential distribution in the Peruvian territory which is legally protected by the conservation areas of national, regional, or private administration. In this regard, we used a maximum-entropy approach (MaxEnt), integrating 14 variables (7 bioclimatic variables, 3 topographic, 3 variables of vegetation cover, and relative humidity). It was observed that 3.6% (46,225.50 km2) of the Peruvian territory presented a high probability (>0.6) of distribution of the evaluated species and 10.7% (136,918.28 km2) of moderate distribution (0.4–0.6). Based on this, our study allowed us to identify the geographical spaces for threatened species on which conservation actions should focus, through the formulation of strategies, plans, policies, and participatory management in the Peruvian territory.

Meteorological observations play a major role in land management; thus, it is vital to properly plan the monitoring network of weather stations (WS). This study, therefore, selected ‘highly suitable’ sites with the objective of replanning the WS network in Amazonas, NW Peru. A set of 11 selection criteria for WS sites were identified and mapped in a Geographic Information System, as well as their importance weights were determined using Analytic Hierarchy Process and experts. A map of the suitability of the territory for WS sites was constructed by weighted superimposition of the criteria maps. On this map, the suitability status of the 20 existing WS sites was then assessed and, if necessary, relocated. New ‘highly suitable’ sites were determined by the Near Analysis method using existing WS (some relocated). The territory suitability map for WS showed that 0.3% (108.55 km2) of Amazonas has ‘highly suitable’ characteristics to establish WS. This ‘highly suitable’ territory corresponds to 26,683 polygons (of ≥30 × 30 m each), from which 100 polygons were selected in 11 possible distributions of new WS networks in Amazonas, with different number and distance of new WS in each distribution. The implementation of this methodology will be a useful support tool for WS network planning.

The increasing demand for tropical timber from natural forests has reduced the population sizes of native species such as Cedrela spp. because of their high economic value. To prevent the decline of population sizes of the species, all Cedrela species have been incorporated into Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). The study presents information about the modeled distribution of the genus Cedrela in Peru that aims to identify potential habitat distribution of the genus, its availability in areas protected by national service of protected areas, and highlighted some areas because of their conservation relevance and the potential need for restoration. We modeled the distribution of the genus Cedrela in Peru using 947 occurrence records that included 10 species (C. odorata, C. montana, C. fissilis, C. longipetiolulata, C. angustifolia, C. nebulosa, C. kuelapensis, C. saltensis, C. weberbaueri, and C. molinensis). We aim to identify areas environmentally suitable for the occurrence of Cedrela that are legally protected by the National Service of Protected Areas (PAs) and those that are ideal for research and restoration projects. We used various environmental variables (19 bioclimatic variables, 3 topographic factors, 9 edaphic factors, solar radiation, and relative humidity) and the maximum entropy model (MaxEnt) to predict the probability of occurrence. We observed that 6.7% (86,916.2 km2) of Peru presents a high distribution probability of occurrence of Cedrela, distributed in 17 departments, with 4.4% (10,171.03 km2) of the area protected by PAs mainly under the category of protection forests. Another 11.65% (21,345.16 km2) of distribution covers areas highly prone to degradation, distributed mainly in the departments Ucayali, Loreto, and Madre de Dios, and needs immediate attention for its protection and restoration. We believe that the study will contribute significantly to conserve Cedrela and other endangered species, as well as to promote the sustainable use and management of timber species as a whole.

The authors would like to make the following corrections to the published paper [...]

Agricultural productivity in the Peruvian region of Amazonas is being jeopardized by conflicts and inadequate land use, that are ultimately contributing to environmental degradation. Therefore, our aim is to assess land suitability for potato (Solanum tuberosum L.) farming in the Jucusbamba and Tincas microwatersheds located in Amazonas, in order to improve land-use planning and enhance the crop productivity of small-scale farmers. The site selection methodology involved a pair-wise comparison matrix (PCM) and a weighted multicriteria analysis using the Analytical Hierarchy Process (AHP) on selected biophysical and socioeconomical drivers. Simultaneously, land cover mapping was conducted using field samples, remote sensing (RS), geostatistics and geographic information systems (GIS). The results indicated that for potato crop farming, the most important criteria are climatological (30.14%), edaphological (29.16%), topographical (25.72%) and socioeconomical (14.98%) in nature. The final output map indicated that 8.2% (22.91 km2) was highly suitable, 68.5% (190.37 km2) was moderately suitable, 21.6% (60.11 km2) was marginally suitable and 0.0% was not suitable for potato farming. Built-up areas (archaeological sites, urban and road networks) and bodies of water were discarded from this study (4.64 km2). This study intends to promote and guide sustainable agriculture through agricultural land planning.

Peru is one of the world’s main coffee exporters, whose production is driven mainly by five regions and, among these, the Amazonas region. However, a combined negative factor, including, among others, climate crisis, the incidence of diseases and pests, and poor land-use planning, have led to a decline in coffee yields, impacting on the family economy. Therefore, this research assesses land suitability for coffee production (Coffea arabica) in Amazonas region, in order to support the development of sustainable agriculture. For this purpose, a hierarchical structure was developed based on six climatological sub-criteria, five edaphological sub-criteria, three physiographical sub-criteria, four socio-economic sub-criteria, and three restrictions (coffee diseases and pests). These were integrated using the Analytical Hierarchy Process (AHP), Geographic Information Systems (GIS) and Remote Sensing (RS). Of the Amazonas region, 11.4% (4803.17 km2), 87.9% (36,952.27 km2) and 0.7% (295.47 km2) are “optimal”, “suboptimal” and “unsuitable” for the coffee growing, respectively. It is recommended to orient coffee growing in 912.48 km2 of territory in Amazonas, which presents “optimal” suitability for coffee and is “unsuitable” for diseases and pests. This research aims to support coffee farmers and local governments in the region of Amazonas to implement new strategies for land management in coffee growing. Furthermore, the methodology used can be applied to assess land suitability for other crops of economic interest in Andean Amazonian areas.

The spectacled, or Andean, bear (Tremarctos ornatus) is classified as vulnerable by the IUCN due to climate change and human-induced habitat fragmentation. There is an urgent need for the conservation of spectacled bear at real time. However, the lack of knowledge about the distribution of this species is considered as one of the major limitations for decision-making and sustainable conservation. In this study, 92 geo-referenced records of the spectacled bear, 12 environmental variables and the MaxEnt entropy modelling have been used for predictive modelling for the current and future (2050 and 2070) potential distribution of the spectacled bear in Amazonas, northeastern Peru. The areas of “high”, “moderate” and “low” potential habitat under current conditions cover 1.99% (836.22 km2), 14.46% (6081.88 km2) and 20.73% (8718.98 km2) of the Amazon, respectively. “High” potential habitat will increase under all climate change scenarios, while “moderate” and “low” potential habitat, as well as total habitat, will decrease over the time. The “moderate”, “low” and total potential habitat are distributed mainly in Yunga montane forest, combined grasslands/rangelands and secondary vegetation and Yunga altimontane (rain) forest, while “high” potential habitat is also concentrated in the Jalca. The overall outcome showed that the most of the important habitats of the spectacled bear are not part of the protected natural areas of Amazonas, under current as well as under future scenarios.

During the latest decades, the Amazon has experienced a great loss of vegetation cover, in many cases as a direct consequence of wildfires, which became a problem at local, national, and global scales, leading to economic, social, and environmental impacts. Hence, this study is committed to developing a routine for monitoring fires in the vegetation cover relying on recent multitemporal data (2017–2019) of Landsat-8 and Sentinel-2 imagery using the cloud-based Google Earth Engine (GEE) platform. In order to assess the burnt areas (BA), spectral indices were employed, such as the Normalized Burn Ratio (NBR), Normalized Burn Ratio 2 (NBR2), and Mid-Infrared Burn Index (MIRBI). All these indices were applied for BA assessment according to appropriate thresholds. Additionally, to reduce confusion between burnt areas and other land cover classes, further indices were used, like those considering the temporal differences between pre and post-fire conditions: differential Mid-Infrared Burn Index (dMIRBI), differential Normalized Burn Ratio (dNBR), differential Normalized Burn Ratio 2 (dNBR2), and differential Near-Infrared (dNIR). The calculated BA by Sentinel-2 was larger during the three-year investigation span (16.55, 78.50, and 67.19 km2) and of greater detail (detected small areas) than the BA extracted by Landsat-8 (16.39, 6.24, and 32.93 km2). The routine for monitoring wildfires presented in this work is based on a sequence of decision rules. This enables the detection and monitoring of burnt vegetation cover and has been originally applied to an experiment in the northeastern Peruvian Amazon. The results obtained by the two satellites imagery are compared in terms of accuracy metrics and level of detail (size of BA patches). The accuracy for Landsat-8 and Sentinel-2 in 2017, 2018, and 2019 varied from 82.7–91.4% to 94.5–98.5%, respectively.

Forest and land degradation is a serious problem worldwide and the Peruvian National Map of Degraded Areas indicates that 13.78% (177,592.82 km2) of the country’s territory is degraded. Forest plantations can be a restoration strategy, while conserving economically important species affected by climate change and providing forestry material for markets. This study modelled the species distribution under current conditions and climate change scenarios of five Timber Forest Species (TFS) in the Amazonas Department, northeastern Peru. Modelling was conducted with Maximum Entropy (MaxEnt) using 26 environmental variables. Of the total distribution under current conditions of Cedrelinga cateniformis, Ceiba pentandra, Apuleia leiocarpa, Cariniana decandra and Cedrela montana, 34.64% (2985.51 km2), 37.96% (2155.86 km2), 35.34% (2132.57 km2), 33.30% (1848.51 km2), and 35.81% (6125.44 km2), respectively, correspond to degraded areas and, therefore, there is restoration potential with these species. By 2050 and 2070, all TFS are projected to change their distribution compared to their current ranges, regardless of whether it will be an expansion and/or a contraction. Consequently, this methodology is intended to guide the economic and ecological success of forest plantations in reducing areas degraded by deforestation or similar activities.

Anthropic activity affects the hydrogeomorphological quality of fluvial systems. River and valley classifications are fundamental preliminary steps in determining their ecological status, and their prioritization is essential for the proper planning and management of soil and water resources. Given the importance of the High Andean livestock micro-watershed (HAL-MWs) ecosystems in Peru, an integrated methodological framework is presented for morphometric prioritization that uses a Principal Component Analysis (PCA) and Weighted Sum Approach (WSA), geomorphological fluvial classifications (channel, slope, and valley), and hydrogeomorphological evaluations using the Hydrogeomorphological Index (IHG). Of six HAL-MWs studied in Leimebamba and Molinopampa (Amazonas region), the PCWSA hybrid model identified the San Antonio HAL-MW as a top priority, needing the rapid adoption of appropriate conservation practices. Thirty-nine types of river course were identified, by combining 13 types of valley and 11 types of riverbed. The total assessment of the IHG indicated that 7.6% (21.8 km), 14.5% (41.6 km), 27.9% (80.0 km), and 50.0% (143.2 km) of the basin lengths have “Poor”, “Moderate”, “Good”, and “Very good” quality rankings, respectively. The increase in the artificial use of river channels and flood plains is closely linked to the decrease in hydrogeomorphological quality.

Peruvian aquaculture, specifically trout production, has had significant growth over the past ten years. However, the establishment and expansion of small-scale aquaculture have been carried out without considering the suitability of the land. In Peru, such land suitability studies have yet to be reported. Therefore, a methodological framework is presented for inland aquaculture, which may be replicated, with the necessary complements, for the entire Fisheries and Aquaculture sector in Peru. This work modeled the suitability of land for sustainable rainbow trout aquaculture in the Molinopampa district (Peru). Fifteen key criteria (socioeconomic, environmental and physicochemical) were identified for the proper development of fish activity. These were mapped using Remote Sensing (RS) and Geographic Information Systems (GIS). The Analytical Hierarchy Process (AHP) was applied to build peer-to-peer comparison matrices and weight the importance of the criteria. The weighted overlay of maps (criteria) made it possible to determine that 4.26%, 23.03% and 69.73% of the territory is “very suitable”, “moderately suitable” and “marginally suitable”, respectively, for the development of aquaculture. The implementation of this methodology will contribute to more effective investment planning and efforts, both by the government and by private initiative.

Heavy metals (iron, copper, and zinc) were quantified in purple crab (Platyxanthus orbignyi) tissues collected in winter (September 2021), spring (November 2021), and summer (March 2022) at three beaches (Tres Hermanas, Fundición, and El Diablo) in Ilo Harbour (Moquegua), South Peru. The rank order of heavy metal concentrations in purple crab tissues and sediments was similar; iron (Fe) was followed by Copper (Cu), and this last one was followed by Zinc (Zn). The heavy metal concentrations in tissue crabs from the three beaches differed from each other spatially and seasonally. In addition, Fundición Beach was the zone with the highest concentration of those three metals during the summer.

Participatory Geographic Information Systems (PGIS) combine geographic information with citizen or community participation to integrate local knowledge with issues related to natural resource management, territorial planning, and environmental pollution that are fundamental to decision-making. However, the current challenge is involving and educating the population to succeed in the PGIS. For this reason, a PGIS system was implemented to identify areas with higher solid waste accumulation and to determine the accuracy of the reports made by the trained population. A participatory platform was implemented using ArcGIS (Online, Desktop, Survey123, Web App Builder, and Experience Builder) for daily reporting of areas contaminated by solid waste. The information obtained for two months was used to generate Kernel density maps, which made it possible to identify the most contaminated regions of the city. A total of 2778 areas contaminated by solid waste were reported during the evaluation period, where 53 % (1486) presented a low level of contamination (area less than 1 m2), 16 % (442) had a medium level of contamination (area equal to 1 m2) and 31 % (850) reported a high level of contamination (area greater than 1 m2). The results allowed the generation of Kernel density maps showing 24 areas classified as 'Extremely High'. Saturdays and Sundays reported higher contamination concerning the other days of the week. The accumulation of contaminants is mainly in the water bodies located in the study area.

The rapid development of digital tools for crop management offers new opportunities to mitigate the effects of climate change on agriculture. This study examines the Normalized Difference Vegetation Index (NDVI) in coffee-growing areas of the province of Rodriguez de Mendoza, southern Peru, from 2001 to 2022. The objectives were the following: (a) to analyze NDVI trends in these areas; (b) to investigate trends in climatic variables and their correlations with altitude and NDVI; and c) to develop linear models tailored to each coffee-growing area. The study identified significant differences in NDVI trends among coffee plants, with mean NDVI values ranging from about 0.6 to 0.8. These values suggest the presence of stress conditions that should be monitored to improve crop quality, particularly in Huambo. Variability in rainfall, maximum and minimum temperatures, relative humidity, and altitude was also observed, with NDVI values showing a strong negative correlation with altitude. These results are crucial for making informed strategic decisions in integrated crop management and for monitoring crop health using vegetation indices.

Currently, the economic profitability of cocoa is being affected by the increasing incidence of pests, low selling prices, high production costs, and the presence of cadmium in cocoa farms, posing a potential risk of crop abandonment. Therefore, the objective of the present research was to evaluate the economic profitability of carbon sequestration of fine-aroma cacao agroforestry systems in Amazonas, Peru, using the economic indicators of NPV, EIRR, and the benefit–cost ratio. For this purpose, 53 small cocoa producers of the APROCAM cooperative were involved, from which data were obtained on the general characteristics of the production system, production and maintenance costs, indirect costs, and administrative costs; in addition, the costs of implementation and maintenance of an environmental services project were calculated to finally make a cash flow projected over 5 years. As part of the results, the economic analysis was carried out on 104.25 hectares of cocoa belonging to the total number of farmers evaluated, who reported an average yield of 957.32 kg of dry cocoa per he. In addition, it was found that the production cost is PEN 3.91/kg of dry cocoa, and the average selling price is PEN 7.38/kg of dry cocoa. After the economic analysis, it was found that the implementation of an environmental services project is profitable (NPV = PEN 1,454,547.8; EIRR = 44% and B/C = 1.86). These results open up an opportunity for cocoa farmers to diversify and increase their income by contributing to climate change mitigation.

Apiculture plays a vital role in maintaining a genetically diverse ecosystem and is an economic activity that contributes to the development of rural communities, thereby enhancing the livelihoods of beekeepers. However, despite the presence of over forty thousand beekeepers in Peru, there is currently no cartographic information available on optimal areas for the development of apiculture. Our study focused on assessing the suitability of land for apiculture development in rural and indigenous communities within the Amazonas Department in northwest Peru. We integrated biophysical and socioeconomic criteria using the Multiple Criteria Evaluation (MCE) technique, in conjunction with state-of-the-art geoinformation and earth observation techniques, to model and validate land suitability for supporting apiculture. It was identified that suitability is influenced by biophysical criteria (65%) and socioeconomic criteria (35%), resulting in highly suitable areas covering 315.6 km2 within the territory of peasant communities, 128.4 km2 within native communities, and an additional 41.4 km2 within conserved areas. Furthermore, to validate our results, we combined the use of high-resolution satellite imagery and visits to artisanal producers. This research provides valuable insights for spatiotemporal land use planning, emphasizing apicultural activity as a driver of rural development and biodiversity conservation. Consequently, this study contributes as a management tool to promote apicultural activities as support for rural development and in local-level decision making.

Unmanned Aircraft Systems (UAS) are used in a variety of applications with the aim of mapping detailed surfaces from the air. Despite the high level of map automation achieved today, there are still challenges in the accuracy of georeferencing that can limit both the speed and the efficiency in mapping urban areas. However, the integration of topographic grade Global Navigation Satellite System (GNSS) receivers on UAS has improved this phase, leading to a reach of up to a centimeter-level accuracy. It is therefore necessary to adopt direct georeferencing (DG), real-time kinematic positioning (RTK)/post-processed kinematic (PPK) approaches in order to largely automate the photogrammetric flow. This work analyses the positional accuracy using Ground Control Points (GCP) and the repeatability and reproducibility of photogrammetric products (Digital Surface Model and ortho-mosaic) of a commercial multi-rotor system equipped with a GNSS receiver in an urban environment with a DG approach. It was demonstrated that DG is a viable solution for mapping urban areas. Indeed, PPK with at least 1 GCP considerably improves the RMSE (x: 0.039 m, y: 0.012 m, and z: 0.034 m), allowing for a reliable 1:500 scale urban mapping in less time when compared to conventional topographic surveys.