How to get started


You can:

  • try out the package using the provided example data in the Data-Tab taken from Gosling et al. (2020).
    It is a study that took place in a forest frontier region in Eastern Panama and used data from interviews with local farmers. The farmers ranked the performance of different conventional land-cover types and two agroforestry land-cover types against various socio-economic and ecological indicators. The data table contains the necessary expectations and uncertainties.

  • upload your own dataset with which strictly follows the format specifications of the example data:
    • Indicators for different land cover types
    • with their average expectations and uncertainties
    • and a further column with the direction for each indicator to indicate whether more or less of the indicator is desirable

  • go to Tab Data to upload the example data or your own data
  • go to Tab Model to perform the optimization and evaluate the results.

Example of needed xlsx-file structure:



Package Info


This is a graphical shiny application for the package optimLanduse to get a quick idea of the functionalities of the package. optimLanduse (version 1.2.0) has been released on CRAN and can be accessed via the project page.

Short summary


  • How to simultaneously combat biodiversity loss and maintain ecosystem functioning while increasing human welfare remains an open question. Multiobjective 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 how these compromises are reasoned. A tutorial on the basis of a published data set 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 modeling and decision making.

  • The package opens the approach of Knoke et al. (2016) to the community of landscape and planners and provides opportunities for straightforward systematic or batch applications.

    • References

    Knoke, T., Paul, C., Hildebrandt, P. et al. Compositional diversity of rehabilitated tropical lands supports multiple ecosystem services and buffers uncertainties. Nat Commun 7, 11877 (2016). https://doi.org/10.1038/ncomms11877
    Gosling, E., Reith, E., Knoke, T. et al. Exploring farmer perceptions of agroforestry via multi-objective optimisation: a test application in Eastern Panama. Agroforest Syst 94, 2003-2020 (2020). https://doi.org/10.1007/s10457-020-00519-0
    A data example is preloaded.
    The file used for upload must be of type xlsx. This file must also correspond to a certain structure for further processing. You can download the example data named exampleGosling.xlsx by clicking the following button:
    Download Example
    Info: Please use the following Options only if you are sure what they do. Values are limited to <= 10!
    Download Plot Download Data


    Authors

    Package:
    Kai Husmann[1], Volker von Gross[1], Kai Boedeker[2], Jasper M. Fuchs[1], Carola Paul[1], Thomas Knoke[2]
    Dashboard:
    Volker von Gross[1], Carola Paul[1]

    [1]Department of Forest Economics and Sustainable Land-use Planning, Georg-August University Goettingen
    [2]Institute of Forest Management, TUM School of Life Sciences Weihenstephan, Department of Life Science Systems, Technical University of Munich

    Contact

    Mail: volker.vongross@uni-goettingen.de

    GitHub: https://github.com/Forest-Economics-Goettingen/optimLanduse_shiny


    Acknowledgments


    V. v. G. was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)
    Project number 192626868 – SFB 990 in the framework of the collaborative German – Indonesian research project CRC 990.


    • Data and Code


    optimLanduse (version 1.2.0) has been released on CRAN and can be accessed via the project page https://github.com/Forest-Economics-Goettingen/optimLanduse