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Uruguayan native grasslands net aerial primary production model and its application on safe stocking rate concept

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  • Dieguez, Francisco José
  • Pereira, Marcelo

Abstract

Native pastures in Uruguay grasslands are the main resource for livestock extensive farming. Remote sensing data of Net Aerial Primary Production is a useful tool to enhance knowledge about grasslands dynamics and behaviour. The pasture productivity on grasslands is highly affected by climate and droughts episodes impacts directly on secondary productivity of livestock systems. Using remote sensing data, a harmonic sinusoidal model affected by a "climate coefficient" is proposed to generate prospective scenarios and to study an implementation of the Safe stocking rate concept. This information can be use in extension activity to help farmers to adapt their systems to native grass dynamics on the adaptive management paradigm.

Suggested Citation

  • Dieguez, Francisco José & Pereira, Marcelo, 2020. "Uruguayan native grasslands net aerial primary production model and its application on safe stocking rate concept," Ecological Modelling, Elsevier, vol. 430(C).
    • Handle: RePEc:eee:ecomod:v:430:y:2020:i:c:s0304380020301320
    DOI: 10.1016/j.ecolmodel.2020.109060
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    References listed on IDEAS

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    1. Ungar, Eugene David, 2019. "Perspectives on the concept of rangeland carrying capacity, and their exploration by means of Noy-Meir's two-function model," Agricultural Systems, Elsevier, vol. 173(C), pages 403-413.
    2. Fort, Hugo & Dieguez, Francisco & Halty, Virginia & Lima, Juan Manuel Soares, 2017. "Two examples of application of ecological modeling to agricultural production: Extensive livestock farming and overyielding in grassland mixtures," Ecological Modelling, Elsevier, vol. 357(C), pages 23-34.
    3. May, Gary & Jones, Rodney D. & Langemeier, Michael R. & Dhuyvetter, Kevin C., 2002. "Influence of Grazing Lease Terms on Economic Optimal Stocking Rates," Staff General Research Papers Archive 10078, Iowa State University, Department of Economics.
    4. Dieguez Cameroni, Francisco & Fort, Hugo, 2017. "Towards scientifically based management of extensive livestock farming in terms of ecological predator-prey modeling," Agricultural Systems, Elsevier, vol. 153(C), pages 127-137.
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    Cited by:

    1. Paruelo, José M. & Texeira, Marcos & Tomasel, Fernando, 2024. "Hybrid modeling for grassland productivity prediction: A parametric and machine learning technique for grazing management with applicability to digital twin decision systems," Agricultural Systems, Elsevier, vol. 214(C).

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