TYPE OF SUPPORT
Background
The Marxan Conservation Planning Platform (MaPP) comprises a suite of software applications that support conservation planning and decision-making by identifying cost-effective solutions to complex environmental challenges. Widely regarded as the world's most extensively used spatial planning software, Marxan has thousands of users and has been applied in more than 100 countries.
By supporting collaboration among stakeholders, Marxan helps inform decisions that balance biodiversity conservation with social and economic objectives across terrestrial, freshwater and marine environments.
QCIF Role
Stewardship of the platform has transitioned from The Nature Conservancy to QCIF’s Sustainable Futures team, positioning Marxan for deeper integration with EcoCommons, WildObs and Open EcoAcoustics. Together, these platforms support more connected approaches to environmental research, conservation planning and biodiversity management.
Outcome & Impact
As one of the leading conservation planning tools worldwide, Marxan plays a critical role in informing environmental decision-making. Stewarding this globally renowned platform and integrating it with other Sustainable Futures initiatives will help create more connected, efficient and impactful conservation workflows.
Bringing Marxan into the QCIF Digital Research ecosystem marks a major milestone for global conservation. By bridging world-renowned international planning software with Australia’s trusted national digital research infrastructure, including EcoCommons, WildObs, and Open EcoAcoustics, we are creating a seamless, global-to-local pipeline.
This stewardship allows us to streamline workflows, support data-driven decision-making, and deliver significantly improved biodiversity and socio-economic outcomes worldwide.
Dr Jenna Wraith, Head of Sustainable Futures Department and Principal Data Scientist
Collaborating Organisations
The Nature Conservancy, Professor Hugh Possingham, Dr Jen McGowan, Dr Jenna Wraith, Xiang Zhao, Michael Mallon, Angelo Maynes, Daisy Li