Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

Family farming is based on knowledge and techniques developed by generations, to establish integrated production systems with the purpose of achieving self-sufficiency and maintaining their subsistence. Achieving local, regional and global food sovereignty requires a deep understanding of agroecosystems. This research focused on knowing the effects of neoliberal policies such as the green revolution, urban expansion due to population growth and how the reduction of agricultural areas influences peri-urban agriculture and determinate ways of resistance in front of these dominant system pressures. Through participant observation, surveys, collection, and herbalization we identified plant species, their diversity, uses and richness. We found that family gardens in San Felipe Ecatepec, Chiapas, Mexico are systems, with subsystems, functions, composition and management, with a high number of species, richness from high to moderate, and the home gardens surfaces oscillating between 600 m² and 2500 m². Producing next to the house provides healthy and fresh food, creates a useful, productive space and conserve agrobiodiversity. It is an agroecosystem where each family and site or home garden interact with other families and other home gardens, integrating local knowledge, and offering a space for family coexistence. The home gardens can be considered spaces of resistance based on traditional knowledge, it also contributes to the control maintenance of their resources, and to individual and collective food sovereignty.

Bamboo is a forest resource that, due to its rapid growth, requires frequent evaluations (monitoring) to define the most appropriate management strategies; however this entails a high cost and a great investment of time. In this study, an analysis is made of the use of unmanned aerial vehicles (UAVs), to generate information on the canopy cover of Guadua spp bamboo strains, and relate it to other of their dasometric parameters. The areas of the bamboo strains were defined based on generated aerial images, where each strain was delimited, differentiating them from their environment, for which 4 types of thresholds were defined. The relationship of the crown area with each dasometric parameter suggests that there is a positive trend, where in most cases there was an adequate significance (P <0.05): height R2= 0.67 (P= 0.0222); Diameter 1.3 m R2= 0.56 (P= 0.0367); diameter of culmo 0.3 m R2= 0.57 (P= 0.0313) and number of culms R2= 0.54 (P= 0.130). In this way, the results showed that with the UAV it was possible to determine the coverage area of ​​individual bamboo strains and that some of their dasometric parameters could be estimated based on their allometric relationship.

Objective: To determine the water quality of an aquaponic system interconnected by a biofilter, using loofah (Luffa cylindrica) as an inert support. Design/methodology/approach: The organisms used in the aquaponic system were juvenile tilapia (Oreochromis niloticus) and epazote (Chenopodium ambrosioides). The physical-chemical parameters analyzed in the water were: temperature, pH, dissolved oxygen, electrical conductivity, NH4+, NO2- and NO3-. The data generated in this work were subjected to analysis of variance (ANOVA) and comparison of means (Tukey p<0.05). Results: Recirculation of pond water through the biofilter and plants reduced NH4+ and NO3- by 31.6% and 18.5%, respectively. In the pond, the total ammoniacal nitrogen did not exceed 0.022 mg L-1. The survival of the fish was 100% and 725.8 g of epazotes were harvested, which did not show symptoms of mineral deficiency. Limitations on study/implications: Aquaponic production is still limited to small areas due to the costs involved in its management. Findings/conclusions: The water quality parameters of the tilapia (Oreochromis niloticus)-epazote (Chenopodium ambrosioides) aquaponic system, interconnected through a biofilter with Luffa cylindrica were maintained within the recommendations for said system. Keywords: Biofilter, aquaculture, mineralization, ammonia

Objective: To identify the agricultural crops in rotation carried out by the producers during one year of two rural communities of Champotón, Campeche. Design / methodology / approach: The research was carried out in 2019, in Santo Domingo Kesté and Sihochac, communities belonging to Champotón, Campeche. Descriptive exploratory character. Documentary research was carried out and a survey was applied with 200 questionnaires in total, using the "snowball" technique. Descriptive statistics, were applied using the statistical packages of Excel. Results: Chihua squash (Cucurbita argyrosperma Huber) and sugar cane (Sacharumm officinarum) are the most economically important crops for Santo Domingo Kesté and Sihochac, respectively. Corn is grown both in Sihochac in May and in Kesté in various months of the year. Chihua squash, peanuts (Arachis hypogaea), beans (Phaseolus vulgaris), sesame (Sesamum indicum), sweet potatoes (Ipomoea batatas), cassava (Manihot esculenta) and roselle (Hibiscus sabdariffa) are produced only in Kesté at different times of the year. Limitations of the study / implications: This research is local in nature, so its results cannot be generalized, but they can be similar to other regions in the country. Findings / conclusions: Crop rotation is practiced in Kesté and not in the community of Sihochac. The way in which each community is organized to grow its crops responds to cultural-social factors and its available resources.

Mining operations associated with the extraction of coal and emeralds in the department of Boyacá, Colombia, contribute to the generation of acid mine drainage (AMD), which affects the ecosystems close to the mining activity. Applying basic systems such as limestone anoxic drains (DAC) make it possible to counteract the acidity present in the MAD by raising the pH. However, they cannot significantly remove sulfate and ferrous iron from the waste. Due to the above, this work studies the behavior of anoxic synthetic acid drainage (SAD), treated through a DAC system, using the area's limestone as a future possibility of application for the treatment of these wastes at an industrial level. Synthetic samples were analyzed with hydraulic retention times of 8, 16, and 24 hours under anoxic conditions. The results show pH regulation after 8 hours of treatment. The alkalinity of the prepared 10 and 100 mg·L-1 Fe+2 samples reach their maximum peak in this same period, reducing the Fe+2 concentration present in the DAS samples by 88% with a retention time of 24h. This study shows that the application of DAC to treat this type of water significantly reduces the concentration of Fe+2, which may be associated with the formation of carbonates.

In a natural or artificial channel, the presence of vegetation at the bottom and on the wall is usual. The effects produced by the presence of this is an alteration of the flow field. The magnitude of the changes in the flow field depends on the extension, height, density, and flexibility of the vegetation. To analyze the turbulent structures in detail in this work, an experimental study was carried out in a laboratory, in a rectangular channel with a section of submerged, flexible and artificial vegetation. The measurement region was located upstream of the vegetation zone until the end of it, in addition, the asymmetry that the presence of the channel wall can induce was determined. The measurements were performed with an Acoustic Doppler Velocimeter (ADV) instrument. The results allow to identify the development of the mixing layer from the average velocity patterns and the Reynolds stress. In the case of the average velocity profiles over the vegetation layer, it was possible to identify an inflection point where Kelvin-Helmholtz instabilities type were identified. In order to analyze the processes in the mixing layer, a phenomenological model is proposed based on the analysis of the curvature of the averaged velocities. In addition, the contribution to the moment transport rate by the identified turbulent structures were determined with a quadrant analysis of fluctuating velocities.

La eficacia de las estrategias de la administración pública se ha medido en la forma en que manejan las pandemias y los efectos en cadena que se producen en el medio ambiente o la sociedad, y en este caso, en el abastecimiento de agua rural en México en tiempos de pandemia. El acceso al agua en las zonas rurales de México y cómo el gobierno ha manejado el aumento de la demanda durante las pandemias se exploran mediante una revisión sistemática de 51 documentos. El sistema de agua de México está por debajo de la media y es necesario realizar más inversiones en los planes de gestión comunitaria. Se requiere la participación de la ciudadanía en el desarrollo de esquemas de gestión comunitaria para encontrar una solución a la demanda y oferta cambiantes.

El pronóstico de caudales de un río es de gran importancia para el desarrollo de sistemas de alerta temprana. Los algoritmos de inteligencia artificial han demostrado ser una herramienta eficaz en la modelación hidrológica basado en datos, pues permiten establecer relaciones entre los datos de entrada y salida de una cuenca hidrográfica, y de esta manera tomar decisiones basado en datos. Este artículo investiga la aplicabilidad del algoritmo k vecino más cercano (KNN) para el pronóstico de caudales medios diarios del río Ramis en la estación hidrométrica Ramis. Como insumo de entrada al algoritmo de aprendizaje automático KNN utilizamos un conjunto de datos de precipitación media de la cuenca y caudal medio diario de estaciones hidrometeorológicas con varios rezagos. El rendimiento del algoritmo KNN se evaluó cuantitativamente con métricas de habilidad hidrológica, como el error porcentual absoluto medio (MAPE), anomalía del coeficiente de correlación (ACC), eficiencia de Nash-Sutcliffe (NSE), eficiencia de Kling-Gupta (KGE') y ángulo espectral (SA). Los resultados para realizar pronóstico de caudales del río Ramis con el algoritmo de aprendizaje automático KNN alcanzaron altos niveles de confiabilidad, sobre todo con rezagos de caudales de uno y dos días, y precipitación con tres días. El algoritmo utilizado es simple, pero robusto para efectuar pronósticos de caudales a corto plazo, y puede ser integrado como una alternativa para el fortalecimiento del pronóstico hidrológico diario del río Ramis.

Predicting the hydrological behavior in hydrographic basins composed of high Andean ecosystems that have a variety of climates, with complex geology, highly varied topography, and soils with a high content of organic matter that generate a very heterogeneous vegetation cover, is very difficult, and if it is added the scarcity of hydrometric information in hydrographic networks causes great uncertainty when planning the use of water resources. The predominant trend for prediction is through hydrological models that relate precipitation and runoff, which require historical information that is not available in most cases. The application of the artificial neural networks technique allows a methodology adaptable to the information available in each basin to analyze the relationship between precipitation and runoff. Because of its robustness, results can be obtained with great precision. This research aimed to estimate and predict the average monthly flows for the Crisnejas river basin, located in the northern region of the Peruvian Andes, for which there were historical records of 12 meteorological stations and a hydrometric station, using flow data, precipitation, temperature and normalized difference vegetation index (NDVI), with a multilayer perceptron-type artificial neural network, which achieved a goodness of fit of 81 % in the coefficient of determination. Then with the generated record, another network of the recurrent type was trained to predict monthly mean flows for eight years with a goodness of fit of 71 %.

In recent years, the application of numerical water quality models has been a useful tool for evaluating and predicting environmental problems such as eutrophication, consequently a valuable tool for the management of water resources. In general, these models are preceded by hydrodynamic modeling. In this work, the two-dimensional numerical model MIKE 21 is applied to the San Roque reservoir (Córdoba, Argentina). It was used to study and evaluate the dynamics of hydrodynamic and water quality variables associated with eutrophication processes and in response to flood events that occurred in the period January-April 2017. The hydrodynamic variables (speed and water levels), the biological water quality variables (chlorophyll a), and inorganic variables (dissolved oxygen, phosphorus and nitrogen) were modeled evaluated. The results showed the effect that flood events had on the spatial and temporal distribution of these variables. The model presented a good performance with respect to the hydrodynamic and inorganic water quality variables with Absolute Percentage Errors (MAPE) below 10 %. However, a lower adjustment of the biological water quality variables was observed.