Identifying the Determinants of Farmers' uptake of Silvopastoral Systems in Caquetá, Colombia

HB Botero Degiovanni, AP Barnes, Marcela Quintero, Miguel Romero

Research output: Contribution to conferencePaperpeer-review


Deforestation is threatening the existence of the Colombian Amazon forest. Farmers in the region tend to clear forest to establish cattle production farms. The Colombian National Federation (FEDEGAN) has a program that incentivise Colombian farmers to stop deforestation and pursue sustainable production practices. This program seeks to intensity cattle production based on the use of silvopastoral systems (SPS). Based on a sample of 341 farmers in the department of Caquetá, Colombia, we classify farmers’ perception of climate change using a latent class approach. We find that there is a gradient of perception and concern towards climate change in this farming community. Utilising a logit model, we also investigate if climate change perception is one of the drivers behind the uptake of silvopastoral systems in Caquetá, Colombia. We find that farmers that are more concerned about the future consequences of climate change and who have a larger number of cows producing milk are more likely to have a silvopastoral system in place. We also find that distance to the farm is another important driver of uptake: farmers living farther away from their urban centres are more likely to establish a silvopastoral system. These drivers can be exploited by FEDEGAN to design communication and engagement strategies conducive to maximize the uptake of silvopastoral systems as a sustainable intensification strategy in the region.
Original languageEnglish
Publication statusPrint publication - 22 Sept 2021
EventLandscape 2021 - Diversification for Sustainable and Resilient Agriculture - Berlin, Berlin, Germany
Duration: 20 Sept 202122 Sept 2021


ConferenceLandscape 2021 - Diversification for Sustainable and Resilient Agriculture
Internet address


  • Climate change
  • Silvopastoral systems
  • Logit/Probit
  • Colombia
  • Amazon
  • Regression Analysis
  • Sustainable agricultural intensification
  • Development economics


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