Artigo - Editora Artemis

Artigo

Baixe agora

Livros
capa do ebook EXPLORANDO LA VARIABILIDAD EN EL AGROECOSISTEMA DE CAFÉ UTILIZANDO EL MODELO PRESUPUESTARIO DE RECURSOS.

EXPLORANDO LA VARIABILIDAD EN EL AGROECOSISTEMA DE CAFÉ UTILIZANDO EL MODELO PRESUPUESTARIO DE RECURSOS.

The drastic annual fluctuations in agricultural prices are a significant source of instability about the quality of life of farmers, especially farmers in small farms. In order to understand the mechanism of this phenomenon, we propose to apply a presupposed resource model (MPR) to coffee systems. The model proposes that the allocation of resources has different biological functions due to certain limitations between the same. We link the predictions derived from the MPR to the perspectives of interviewed producers and a field experiment to analyze the effects of the practices in the handling of oscillations. The results support the applicability of the MPR in the coffee system and suggest that the greatest fertilizer can exaggerate the variability in production over the long term.

Ler mais

EXPLORANDO LA VARIABILIDAD EN EL AGROECOSISTEMA DE CAFÉ UTILIZANDO EL MODELO PRESUPUESTARIO DE RECURSOS.

  • DOI: 10.37572/EdArt_24830122021

  • Palavras-chave: café, modelar, estabilidad, fluctuaciones, ecología aplicada

  • Keywords: coffee, modelling, stability, alternate-bearing, applied ecology

  • Abstract:

    Drastic fluctuations in crop yield, or alternate-bearing, are a major source of farmer livelihood instability and a substantial concern to small-scale coffee farmers. To form a mechanistic understanding of the phenomenon, we propose the extension of the resource budget model (RBM) to coffee agroecosystems. We link the model's predictions with farmer interviews and a field study to analyze the effects of farm management practices on yield variability. The results support the model's applicability in the coffee system and suggest that fertilization may exagerate long-term fluctuations. Application of the RBM in coffee agroecosystems allows for a mechanistic understanding of variability and how it is impacted by management practices.

  • Número de páginas: 11

  • Gabriela Marie García
  • Colin Mark Orians