An integrated model to study varietal diversity in traditional agroecosystems

Area of Science:

• Ecology
• Agricultural Science
• Computational Modeling

Background:

• Agricultural diversity is fundamental to traditional agroecosystems, holding significant environmental and cultural value.
• The ongoing decline in agricultural diversity raises concerns due to its critical role in global and local food security.
• Understanding local management practices and sustaining mechanisms is vital to counteract this loss.

Purpose of the Study:

• To develop a generalist agent-based model (ABM) that integrates biological, cultural, and social dynamics.
• To explore how these coupled dynamics lead to emergent varietal diversity at the community level.
• To investigate the influence of specific model dynamics on system diversity.

Main Methods:

• Development of a mechanistic agent-based model simulating coupled biological, cultural, and social factors.
• Exploration of four key model dynamics to understand their impact on agricultural diversity.
• Validation of the model using a bibliographic review of Manihot esculenta (manioc) and Zea mays (maize) case studies.

Main Results:

• The agent-based model successfully generated varietal diversity as an emergent property at the community level.
• Model outputs showed compatibility with empirical data on varietal richness for manioc and maize.
• The study identified key dynamics influencing the maintenance of diversity at both household and community scales.

Conclusions:

• The developed agent-based model provides a valuable tool for understanding the emergence and maintenance of agricultural diversity.
• Local management practices and the interplay of biological, cultural, and social factors are crucial for sustaining crop varietal richness.
• Findings support the need for integrated approaches to conserve agricultural biodiversity for enhanced food security.