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Assessing ecosystem services from multifunctional trees in pastures using Bayesian belief networks

Author

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  • Barton, David N.
  • Benjamin, Tamara
  • Cerdán, Carlos R.
  • DeClerck, Fabrice
  • Madsen, Anders L.
  • Rusch, Graciela M.
  • Salazar, Álvaro G.
  • Sanchez, Dalia
  • Villanueva, Cristóbal

Abstract

A Bayesian belief network (BBN) was developed to assess preferred combinations of trees in live fences and on pastures in silvopastoral systems. The BBN was created with information from Rivas, Nicaragua, using local farmer knowledge on tree species, trees' costs and benefits, farmers' expressed needs and aspirations, and scientific knowledge regarding tree functional traits and their contribution to ecosystem services and benefits. The model identifies combinations of trees, which provide multiple ecosystem services from pastures, improving their productivity and contribution to farmer livelihoods. We demonstrate how the identification of portfolios of multifunctional trees can satisfy a profile of desired ecosystem services prioritized by the farmer. Diagnostics using Bayesian inference starts with an identification of farmer needs and ‘works backwards’ to identify a silvopastoral system structure. We conclude that Bayesian belief networks are a promising modeling technique for multi-criteria decisions in farm adaptation processes, where interventions must be adapted to specific contexts and farmer preferences.

Suggested Citation

  • Barton, David N. & Benjamin, Tamara & Cerdán, Carlos R. & DeClerck, Fabrice & Madsen, Anders L. & Rusch, Graciela M. & Salazar, Álvaro G. & Sanchez, Dalia & Villanueva, Cristóbal, 2016. "Assessing ecosystem services from multifunctional trees in pastures using Bayesian belief networks," Ecosystem Services, Elsevier, vol. 18(C), pages 165-174.
  • Handle: RePEc:eee:ecoser:v:18:y:2016:i:c:p:165-174
    DOI: 10.1016/j.ecoser.2016.03.002
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    Cited by:

    1. Hadis Mohajerani & Majid Kholghi & Abolfazl Mosaedi & Raziyeh Farmani & Amir Sadoddin & Markus Casper, 2017. "Application of Bayesian Decision Networks for Groundwater Resources Management Under the Conditions of High Uncertainty and Data Scarcity," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(6), pages 1859-1879, April.
    2. Tschopp, Maurice & Ceddia, M. Graziano & Inguaggiato, Carla & Bardsley, Nicholas O. & Hernández, Hernán, 2020. "Understanding the adoption of sustainable silvopastoral practices in Northern Argentina: What is the role of land tenure?," Land Use Policy, Elsevier, vol. 99(C).
    3. Agudelo, César Augusto Ruiz & Bustos, Sandra Liliana Hurtado & Moreno, Carmen Alicia Parrado, 2020. "Modeling interactions among multiple ecosystem services. A critical review," Ecological Modelling, Elsevier, vol. 429(C).
    4. Feng, Zhe & Jin, Xueru & Chen, Tianqian & Wu, Jiansheng, 2021. "Understanding trade-offs and synergies of ecosystem services to support the decision-making in the Beijing–Tianjin–Hebei region," Land Use Policy, Elsevier, vol. 106(C).

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