Decision Support

IIS AU has developed a sophisticated user-friendly decision support platform (DSP) for multi-criteria spatial optimisation planning of forest and landscape restoration (FLR). Our DSP can be customised for a wide range of objectives, scales and planning contexts

We solve spatial optimisation planning problems using Linear Programming based on spatially explicit predictive models. Our approach is proved to be at least 30% more accurate than other methods. It can improve formulation of forest restoration planning problems and inform management plans, as well as reduce the uncertainty within risk assessments and costs of mitigation measures. Our DSP can inform both top-down and bottom-up decision-making processes and significantly improve outcomes of policies, programs and projects for biodiversity conservation, sustainable development, climate change mitigation and poverty alleviation.

Questions that can be answered using our approach:

> Where are the priority areas for restoration that would maximise multiple benefits while minimising costs?
> What benefits are likely to be achieved over an area to be restored and what are the costs?
> How do trade-offs between benefits and costs affect restoration priorities?
> Where and when should actions be scheduled in space?
> Where and how intensively should restoration actions be implemented?

WePlan - Forests: A Decision Support Platform for spatial optimisation planning of forest ecosystem restoration

Since 2019, IIS AU has been developing the WePlan - Forests in partnership with IIS Rio, the UN Convention on Biological Diversity (CBD), and the Center for International Forestry Research. Our goal is to offer a decision support platform for developing country Parties to the CBD with tropical forests that will allow them to formulate more ambitious, realistic and specific forest ecosystem plans and targets within their global commitments.

These sophisticated analytical tools are generally used by highly trained staff and modellers, who work for scientific organisations or universities. WePlan, however, can be easily used by governments, NGOs, investors, restoration practitioners, or even local communities.

The problem formulation achieves a range of potential objectives within a given percentage of converted land to be restored:
> maximising benefits for biodiversity conservation
> maximising benefits for climate change mitigation
> minimising restoration establishment costs (while accounting for the potential for natural forest regrowth)
> minimising cost of land

WePlan allows for eight main analyses and outputs:
> identification of priority areas for forest restoration
> evaluation of where forest restoration activities can achieve the greatest benefits
> quantification of trade-offs among objectives (benefits and costs)
> identification of good compromise solutions
> quantification and risk reduction in the context of uncertainty
> exploration of the impacts of a variety of 'alternative futures’ in scenario analysis
> taking advantage of the potential for natural forest regrowth
> evaluation of the effectiveness of policy instruments that affect prices and/or costs

Related Content

Related collaborators (16)

Related Partners (14)

Conservation International Forest Ecosystem Restoration Initiative Convention on Biological Diversity Center for International Forestry Research (CIFOR) International Institute for Sustainability U.S. Agency for International Development European Union Korean Forest Service The University of Queensland The University of Melbourne Universidade Veiga de Almeida World Resources Institute Forestation International Food and Agriculture Organization of the United Nations