OptOrch: A modular optimization toolkit for forest tree seed orchard deployment

Area of Science:

• Forestry
• Quantitative Genetics
• Computational Biology

Background:

• Forest tree breeding programs rely on seed orchards (SO) for genetic improvement.
• Optimizing SO deployment is crucial for maximizing genetic gain while maintaining diversity.
• Existing software often lacks flexibility in handling SO-specific biological and operational constraints.

Purpose of the Study:

• To introduce OptOrch, a transparent and modular optimization toolkit for forest tree seed orchard deployment.
• To provide breeders with direct control over objective functions and constraints for customized SO management.
• To enable evaluation of various deployment strategies under realistic conditions.

Main Methods:

• Implementation of SO-specific optimal contribution models using AMPL.
• Separation of biological assumptions, input data, and numerical solvers.
• Exposure of objective functions and constraints for user modification (e.g., status-number thresholds, graft availability, pollen flow).
• Algebraic framework supporting alternative formulations for complex biological constraints.

Main Results:

• OptOrch allows modification of SO-specific requirements, including contribution bounds and coancestry restrictions.
• The toolkit facilitates evaluation of solutions using solver-reported metrics.
• Simulation-based scenarios demonstrate quantification of gain-diversity trade-offs and assessment of pollen contamination effects.

Conclusions:

• OptOrch provides a flexible and transparent framework for forest tree seed orchard deployment optimization.
• The toolkit enables breeders to compare feasible strategies considering biological and operational constraints.
• OptOrch facilitates informed decision-making in forest tree breeding for enhanced genetic improvement and diversity.