Designing crop pollination services: A spatially explicit agent-based model for real agricultural landscapes

• Autores: Santibañez, Fernanda; Joseph, Julien; Abramson, Guillermo; Kuperman, Marcelo N.; Laguna, María F.; Garibaldi, Lucas Alejandro
• Año de publicación: 2022
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: Agricultura (General); Biodiversidad y Conservación; Ecología; Pollination; Agriculture; Landscape ecology; Apis mellifera; Spill-over; Competition; Agricultura (General); Biodiversidad y Conservación; Ecología
• Institución: Universidad Nacional de Río Negro

Fil: Santibañez, Fernanda. Universidad Nacional de Río Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina.
Fil: Santibañez, Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina.
Fil: Joseph, Julien. Université de Lyon. Universite Claude Bernard Lyon I. École Normale Supérieure de Lyon. Francia.
Fil: Abramson, Guillermo. Centro Atómico Bariloche (CNEA). Río Negro, Argentina.
Fil: Kuperman, Marcelo N. Centro Atómico Bariloche (CNEA). Río Negro, Argentina.
Fil: Laguna, María F. Centro Atómico Bariloche (CNEA). Río Negro, Argentina.
Fil: Garibaldi, Lucas Alejandro. Universidad Nacional de Río Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina.
Fil: Garibaldi, Lucas Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina.
The decline of pollinators is a widespread problem in today's agriculture, affecting the yield of many crops. Improved pollination management is therefore essential, and honey bee colonies are often used to improve pollination levels. In this work, we applied a spatially explicit agent-based model for the simulation of crop pollination by honey bees under different management scenarios and landscape configurations. The model includes 1) a representation of honey bee social dynamics; 2) an explicit representation of resource dynamics; 3) a probabilistic approach to the foraging site search process; and 4) a mechanism of competition for limited resources. We selected 60 sample units from the rural landscape of the Chilean region with the largest apple-growing area and evaluated the effectiveness of different pollination strategies in terms of number of visits and number of pollinated flowers per hectare of apple crops. Finally, we analyzed how the effects of these practices depended on the structure of adjacent landscapes. Higher colony density per hectare in the focal crop increased the number of honey bee visits to apple inflorescences; however, the effects were nonlinear for rates of pollinated flowers, suggesting that there is an optimum beyond which a greater number of honey bees does not signify increased levels of crop pollination. Furthermore, high relative proportions of mass flowering crops and natural habitats in the landscape led to a decrease in honey bee densities in apple fields in landscapes with high relative cover of apple orchards (dilution effect). Our results indicate that for optimal crop pollination, strategies for management of pollinator species should consider the modulating effects of the surrounding landscape on pollination effectiveness. This model could thus be a useful tool to help farmers, beekeepers, and policy-makers plan the provision of pollination services, while also promoting the biodiversity and sustainability of agroecosystems.
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