Efectos de la toxicidad de cadmio en la morfología de plantas de Bidens pilosa L

Cadmium is a metal that affects natural resources, plants and human beings. Therefore, different methods have been sought to mitigate the problem, one of them is phytoremediation that makes use of species that have the potential to accumulate the heavy metal in their plant tissues. The objective of this research was to evaluate the effect of cadmium toxicity on the morphology of cadmium cadmium plants (Bindes pilosa L.). The plants were planted in two types of substrate with pH 6.27 and 5.53, adding different concentrations of cadmium chloride (CdCl2) (0, 5 and 10 ppm) inside a greenhouse; where there were 6 treatments with 5 replicates, thus having 30 experimental units. Morphological parameters and Cd concentrations in the root and foliar parts were evaluated. From the results obtained, the cadillo planted in the substrate with pH 5.53 without CdCl2 had greater height with 27.18 cm, with the same substrate plus 10 ppm of CdCl2 higher values were obtained in the variables; number of shoots (16 shoots), foliar fresh weight (26.70 g), foliar dry weight (10.92 g), root fresh weight (5.77 g), root dry weight (1.04 g) and root length (26.90 mm). Regarding the accumulation of Cd in plant tissues, a higher concentration was obtained in the foliar part (7.27 ppm) and less in the root (2.57 ppm). It is concluded that this species could be useful in the phytoremediation of Cd-contaminated soils.  El cadmio es un metal que afectan los recursos naturales, plantas y seres humanos. Ante ello, se ha buscado diferentes métodos para mitigar el problema, uno de ellos es la fitorremediación que hace uso de especies que tienen el potencial de acumular el metal pesado en sus tejidos vegetales. Esta investigación tuvo por objetivo evaluar el efecto que causa la toxicidad de cadmio en la morfología de plantas de cadillo (Bindes pilosa L.). Las plantas fueron sembradas en dos tipos de sustrato con pH 6.27 y 5.53, agregando diferentes concentraciones de cloruro de cadmio (CdCl2) (0, 5 y 10 ppm) dentro de un invernadero; donde se tuvo 6 tratamientos con 5 repeticiones, teniendo así 30 unidades experimentales. Se evaluó parámetros morfológicos y concentraciones de Cd en la parte radicular y foliar. De los resultados obtenidos, el cadillo sembrado en el sustrato con pH 5.53 sin CdCl2 tuvo mayor altura con 27.18 cm, con el mismo sustrato más 10 ppm de CdCl2 se obtuvo mayores valores en las variables; número de brotes (16 brotes), peso fresco foliar (26.70 g), peso seco foliar (10.92 g), peso fresco radicular (5.77 g), peso seco radicular (1.04 g) y longitud de raíz (26.90 mm). Respecto a la acumulación de Cd en los tejidos vegetales se obtuvo mayor concentración en la parte foliar (7.27 ppm) y menos en la raíz (2.57 ppm). Se concluye, que esta especie podría tener utilidad en la fitorremediación de suelos contaminados con Cd

Presence of Heavy Metals in Purple Crab (Platyxanthus orbignyi) Tissues in Southern Peru

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

Spatiotemporal Dynamics of Grasslands Using Landsat Data in Livestock Micro-Watersheds in Amazonas (NW 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

Site Selection for a Network ofWeather Stations Using AHP and Near Analysis in a GIS Environment in Amazonas, NW Peru

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

Estudios globales sobre el cadmio en relación con Theobroma cacao: Un análisis bibliométrico desde Scopus (1996 -2020)

En el año 2014, la Unión Europea impuso estándares máximos de tolerancia en cadmio, para la importación de productos a base de cacao, causando preocupación en los países. Se analizó estudios globales referidos a investigaciones en Theobroma cacao, relacionados con la actividad del cadmio en la atmósfera. Se utilizaron análisis bibliométricos en los programas R y VOSviewer, para examinar 64 documentos publicados en la base de datos Scopus según palabras clave. Se identificaron 811 palabras clave en coocurrencias de términos, 5 grupos temáticos en acoplamiento bibliográfico, 20 instituciones como afiliaciones más importantes, 20 países de procedencia de autores corresponsales, 112 instituciones en red de coautoría de los cuales 5 están en documentos primarios, y dos grupos en similaridad temática en co-citación de documentos. Estados Unidos lidera la producción científica con 11 documentos, seguido de Colombia (8) y Ecuador (7). En 1996 se registró el primer artículo científico para la red, con incrementos de hasta 11 publicaciones al 2020. En conclusión, se evidencia la necesidad de fortalecer y crear más redes de investigaciones entre países, instituciones, autores y coautores. Se espera que los resultados permitan desentrañar de manera integral la trayectoria de investigaciones cadmio-cacao, al tiempo que arrojen nuevas investigaciones prospectivas

Distribution Models of Timber Species for Forest Conservation and Restoration in the Andean-Amazonian Landscape, North of Peru

The Andean-Amazonian landscape has been universally recognized for its wide biodiversity, and is considered as global repository of ecosystem services. However, the severe loss of forest cover and rapid reduction of the timber species seriously threaten this ecosystem and biodiversity. In this study, we have modeled the distribution of the ten most exploited timber forest species in Amazonas (Peru) to identify priority areas for forest conservation and restoration. Statistical and cartographic protocols were applied with 4454 species records and 26 environmental variables using a Maximum Entropy model (MaxEnt). The result showed that the altitudinal variable was the main regulatory factor that significantly controls the distribution of the species. We found that nine species are distributed below 1000 m above sea level (a.s.l.), except Cedrela montana, which was distributed above 1500 m a.s.l., covering 40.68%. Eight of 10 species can coexist, and the species with the highest percentage of potential restoration area is Cedrela montana (14.57% from Amazonas). However, less than 1.33% of the Amazon has a potential distribution of some species and is protected under some category of conservation. Our study will contribute as a tool for the sustainable management of forests and will provide geographic information to complement forest restoration and conservation plans

Dynamics of the Burlan and Pomacochas Lakes Using SAR Data in GEE, Machine Learning Classifiers, and Regression Methods

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

Carbon Sequestration in Fine Aroma Cocoa Agroforestry Systems in Amazonas, Peru

One way to mitigate climate change is by reducing atmospheric CO2 levels with the establishment of agroforestry systems (AFSs) that can capture and store atmospheric CO2. This study therefore estimated the carbon sequestration in two components, aboveground (cocoa trees, other tree species, and leaf litter) and soil, in 15 fine aroma cocoa AFSs in Amazonas, Peru. These cocoa AFSs had a minimum area of 1.5 ha and were distributed into three age groups (each group consisted of five systems or farms): young cocoa trees between 8 and 15 years old, middle-aged cocoa trees between 16 and 29 years old, and adult cocoa trees between 30 and more than 40 years old. Generalized linear mixed model (GLMM) analysis followed by Fisher’s LSD mean comparison test (p > 0.05) determined the significant level of total aboveground biomass and total carbon content in the AFSs’ components. The present findings confirm that Theobroma cacao, Mussa sp., Cordia sp., and Persea sp. were the most common species in all AFSs. Clearly, biomass and carbon content in Theobroma cacao and Cordia sp. increased slightly with age, while fruit species Mussa sp. and Persea sp. decreased with age. The total aboveground carbon stock in young cocoa tree systems (13.64 Mg ha−1) was lower than in middle-aged cocoa systems (20.50 Mg ha−1) and adult cocoa systems (24.86 Mg ha−1); nevertheless, no significant differences were found for any of the age ranges. On the other hand, carbon stocks in soil (up to 30 cm depth) in the AFSs ranged from 119.96 Mg ha−1 to 131.96 Mg ha−1. Meanwhile, the total carbon stored by aboveground and soil components in adults cocoa systems (156.81 Mg ha−1) was higher compared to middle-aged cocoa systems (140.60 Mg ha−1) and young cocoa systems (133.59 Mg ha−1), although no statistically significant differences were found. Eventually, the CO2 sequestration for young cocoa systems was 490.28 Mg ha−1, and middle-aged and adult cocoa system recorded more than 500 Mg ha−1 of CO2. Furthermore, these data can further be used by national governments, local governments, and organisations of producers, particularly in accessing payments for environmental services, which may improve economic incomes and contribute to climate change mitigation by reserving biomass and sequestering C from these agroforestry cocoa systems

The Challenge of Wildlife Conservation from Its Biogeographical Distribution Perspectives, with Implications for Integrated Management in Peru

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

Land Suitability for Cocoa Cultivation in Peru: AHP and MaxEnt Modeling in a GIS Environment

Peru is one of the world’s leading exporters of cocoa beans, which directly impacts the household economy of millions of small farmers. Currently, the expansion and modernization of the cocoa-growing area require the zoning of the territory with suitable biophysical and infrastructural conditions to facilitate optimizing productivity factors. Therefore, we analyzed land suitability for cocoa (Theobroma cacao L.) production on the Peruvian mainland as a support measure for sustainable agriculture. To this end, the climatological, edaphological, orographic, and socioeconomic criteria determining sustainable cocoa cultivation were identified and mapped. Three modeling approaches (Analytic Hierarchy Process—AHP, Maximum Entropy—MaxEnt, and AHP—MaxEnt combined) were further used to hierarchize the importance of the criteria and to model the potential territory for sustainable cocoa cultivation. In all three modeling approaches, climatological criteria stood out among the five most important criteria. Elevation (orographic criteria) is also featured in this group. On the other hand, San Martin and Amazonas emerged as the five regions with the largest area ‘Highly suitable’ for cocoa cultivation in all three modeling approaches, followed by Loreto, Ucayali, Madre de Dios, Cusco, Junín, and Puno, which alternated according to modeling approach. From most to least restrictive, the AHP, MaxEnt, and AHP–MaxEnt modeling approaches indicate that 1.5%, 5.3%, and 23.0% of the Peruvian territory is ‘Highly suitable’ for cocoa cultivation, respectively