Marxans

Marxans are a family of decision-support tools used in systematic conservation planning to identify spatial networks of sites that meet biodiversity targets at minimum cost. The core tool, Marxan, uses a heuristic optimization approach, typically simulated annealing, to search the space of planning units and select a subset that satisfies user-defined representation targets for species or habitats while minimizing overall cost or impact. Users input planning unit costs (economic or social), species targets, and often constraints or penalties such as boundary length to promote compactness of the reserve network. The output includes preferred planning units, solution scores, and alternative portfolios to compare trade-offs among costs, targets, and connectivity.

Marxans were developed in the late 1990s by researchers at The University of Queensland and collaborating institutions, and have since become widely used for terrestrial, freshwater, and marine conservation planning. Over time, several variants and extensions have been released, including Marxan with Zones, which enables multiple zones with different management or protection levels within a single planning unit, and newer software adaptations that integrate with geographic information systems and other decision-support tools. The framework has been applied in numerous countries to design protected area networks, reserve systems, and marine protected area networks, often influencing policy and land-use planning.

Limitations include sensitivity to input data quality and the choice of targets and costs, potential for multiple near-optimal solutions, and computational demands on large landscapes. Users must carefully document assumptions and conduct sensitivity analyses. Related tools and approaches, such as prioritization packages in R, also implement Marxan-inspired algorithms.