Prioritizr: Systematic Conservation Planning Data for R

Prioritizr is an R package for systematic conservation prioritization using mixed integer linear programming (MILP). It provides a flexible interface for building and solving conservation planning problems, with solutions guaranteed to be optimal or within a specified gap. The package was authored by Jeffrey O. Hanson, with a related paper published in 2025.

Use Cases

• Optimizing spatial allocation of conservation actions based on the MILP framework.
• Identifying multi-stakeholder solutions by constructing problems with different management zones.
• Solving large-scale conservation problems using exact algorithm solvers like Gurobi or CPLEX.

Strengths

• Solutions are guaranteed to be optimal or within a pre-specified optimality gap.
• Supports integration with multiple commercial and open-source solvers (Gurobi, CPLEX, CBC).
• Can construct problems to optimize multiple management actions or zones.

Limitations

• Row count and column-level documentation are absent; data structure must be inferred after download.
• Last update date is unknown; freshness unverified.
• Description metadata is limited; actual data quality requires manual inspection.

Provenance

Source

Jeffrey O. Hanson, via the paperswithcode platform.

Collection Method

Likely contains data structures and examples for building conservation planning models in R.

Time Range

Temporal coverage is unknown.

Freshness

Last updated date is unknown.

Geography

Spatial coverage is unknown.