ABSTRACT Seasonal dynamics in edaphic humidity are influenced by different environmental factors, such as topography, physical and chemical soil conditions, type of vegetation cover and climatic classification. Data from 105 agrometeorological stations in the IDEAM network, distributed throughout Colombia, with records from January, 2001 to April, 2020, were studied. A non-parametric Spearman rank correlation test was used to evaluate the relationship between soil moisture and atmospheric variables. Simultaneously, the behaviors of seasonal dynamics were analyzed, along with their interaction with atmospheric, physical soil and vegetation cover variables. The results showed that soil moisture is more significantly influenced by frequency than by intensity of precipitation; this variable had a seasonal behavior, similar to that of precipitation. The physical variable texture was closely related to the behavior of the soil surface moisture (<10 cm deep). In addition, there was evidence of a surface moisture response to the physical conditions of the soil, topography and availability of plant cover. As the soil depth increased, the soil moisture had less variation because the influence of the atmospheric conditions was greater on the surface and persisted longer over time.

RESUMEN La dinámica estacional de la humedad edáfica está influenciada por diferentes factores ambientales, como la topografía, las condiciones físicas y químicas del suelo, el tipo de cobertura vegetal y la clasificación climática. Se estudiaron los datos de 105 estaciones agrometeorológicas de la red del IDEAM, distribuidas en Colombia, con registros desde enero de 2001 hasta abril de 2020. Se utilizó una prueba no paramétrica de correlación de rangos de Spearman para evaluar la relación entre la humedad del suelo y las variables atmosféricas. Simultáneamente, se analizó el comportamiento de la dinámica estacional, así como su interacción con las variables atmosféricas, físicas del suelo y de la cobertura vegetal. Los resultados mostraron que la humedad del suelo está significativamente influenciada por la frecuencia que por la intensidad de las precipitaciones, esta variable tuvo un comportamiento estacional, similar al de la precipitación. La variable física textura estuvo estrechamente relacionada con el comportamiento de la humedad superficial del suelo (<10 cm de profundidad). Además, se evidenció una respuesta de la humedad superficial a las condiciones físicas del suelo, la topografía y la disponibilidad de cobertura vegetal; a mayor profundidad la humedad presenta menor influencia de las condiciones atmosféricas en superficie y una mayor persistencia de la variable.

Resumo A produtividade da cultura do maracujá depende do comportamento das variáveis climáticas, e a modelagem da relação de dependência destas variáveis com a produtividade da cultura oferece informações que visam a facilitar a tomada de decisão do agronegócio. Como objetivo principal, a produtividade da cultura do maracujá foi estimada por meio de modelos matemáticos. Uma análise estatística multivariada e univariada das variáveis meteorológicas foi realizada durante o período de observação entre 2007 e 2014 das estações climatológicas selecionadas, identificadas e localizadas no trópico médio colombiano (Região administrativa de Huila). Foram analisadas as relações de produtividade com as seguintes variáveis agroclimáticas: temperatura, brilho solar, umidade relativa, precipitação e ENOS em resolução mensal com modelos empíricos e mecanísticos, recomendados na literatura científica. Os resultados mostraram que o modelo de regressão múltipla requer os maiores picos de rendimento; o ajuste do modelo é baixo, enquanto modelos univariados, como o modelo ARIMA, apresentaram melhor ajuste nas séries temporais analisadas. O modelo de rendimento de água de Stewart tem melhor desempenho para estimar rendimento em função da evapotranspiração nas diferentes fases fenológicas.

Abstract Passion fruit crop yield depends on the behavior of climatic variables, and modeling the dependence relationship of these variables regarding crop yield offers information aimed at facilitating agribusiness decision making. As main aim, passion fruit crop yield was estimated using mathematical models. A multivariate and univariate statistical analysis of meteorological variables was carried out during the observation period between 2007 and 2014 of selected weather stations, identified and located in the Colombian middle tropics (County of Huila). The relationship between yield with the following agroclimatic variables were analyzed: temperature, sunlight, relative humidity, rainfall and ENSO at monthly resolution with empirical and mechanistic models, recommended in scientific literature. Results showed that the multiple regression model requires the highest yield peaks; the adjustment of the multiple regression model is low, while univariate models such as the ARIMA model showed better adjustment in the time series analyzed. The Stewart’s water-yield model has better performance to estimate yield as a function of evapotranspiration in the different phenological phases.

RESUMEN En este artículo, como una herramienta de análisis se consideró la capacidad de interacción que tienen los sistemas abiertos frente a la ocurrencia de un disturbio, de tal manera que puedan seguir funcionando con mínimas pérdidas de energía e información, denominada resiliencia y es considerada como una característica emergente de los agro-ecosistemas. Con el objetivo de establecer un método para medir esta característica se evaluaron diez variables, siete culturales: nivel de escolaridad, tipo de tenencia de la tierra, capacidad de ahorro, pertenencia a alguna organización social, infraestructura de la finca, control de arvenses y sistema de producción; y tres variables ecosistémicas: disponibilidad del recurso hídrico, manejo fitosanitario y Estructura Agroecológica Principal (EAP) en agroecosistemas citrícolas tipificados. Estas variables fueron agrupadas metodológicamente en seis dominios de recomendación, es decir grupos de fincas y de citricultores con condiciones ecosistémicos y a la vez culturales similares, que en trabajo previo habían sido caracterizados y tipificados. En cada uno de estos grupos se seleccionaron tres fincas tipo para un total de 18 unidades productivas (Meta, Colombia). Para determinar diferencia entre las variables se aplicaron pruebas de Chi Cuadrado (empleando los estadísticos de Pearson y Fisher). Para determinar la relación entre las variables se aplicó análisis de redes, pudiéndose determinar que el nivel de escolaridad, infraestructura de la finca y EAP no presentaron relación de significancia con la resiliencia. La relación entre las variables culturales presentaron una alta significancia, mientras que las variables ecosistémicas evidenciaron baja significancia estadística con la resiliencia.

ABSTRACT This paper, as a tool for analysis, considered the capacity of the interaction that open systems have against the occurrence of disturbances so that they can continue to function with minimal losses of energy, called resilience, an emerging characteristic of agroecosystems. To establish a method to measure this characteristic, ten variables were evaluated, including seven cultural variables: level of schooling, land tenure type, saving capacity, social organizational identity, farm infrastructure, weed control and production system; and three ecosystem variables: water resource availability, phytosanitary management and Main Agroecological Structure (MAS) in typical citrus fruit agroecosystems. These were methodologically grouped into six recommended domains: groups of farms and citrus growers with similar ecosystem and cultural conditions that have been characterized and typified in a previous study. In each of these groups, three farm types were selected for a total of 18 production units (department of Meta, Colombia). To determine the difference between the variables, Chi-square tests were applied (using the Pearson and Fisher statistics). Network analysis was applied to determine the relationship between the variables. The resilience was not significantly correlated with level of schooling, farm infrastructure or MAS. The relationship between the resilience and cultural variables presented a high significance, whereas the ecosystem variables showed a low statistical significance.