optimLanduse: A package for multiobjective land-cover composition optimization under uncertainty

Kai Husmann, Volker von Groß, Kai Bödeker, Jasper M. Fuchs, Carola Paul, Thomas Knoke

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


How to simultaneously combat biodiversity loss and maintain ecosystem functioning while improving human welfare remains an open question. Optimization approaches have proven helpful in revealing the trade-offs between multiple functions and goals provided by land-cover configurations. The R package optimLanduse provides tools for easy and systematic applications of the robust multiobjective land-cover composition optimization approach of Knoke et al. (2016). The package includes tools to determine the land-cover composition that best balances the multiple functions a landscape can provide, and tools for understanding and visualizing the reasoning behind these compromises. A tutorial based on a published dataset guides users through the application and highlights possible use-cases. Illustrating the consequences of alternative ecosystem functions on the theoretically optimal landscape composition provides easily interpretable information for landscape modelling and decision-making. The package opens the approach of Knoke et al. (2016) to the community of landscape modellers and planners and provides opportunities for straightforward systematic or batch applications.

Original languageEnglish
Pages (from-to)2719-2728
Number of pages10
JournalMethods in Ecology and Evolution
Issue number12
StatePublished - Dec 2022


  • land-cover composition optimization
  • landscape modelling
  • multiobjective optimization
  • reference point optimization
  • robust optimization


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