An Exploration of Scenarios to Support Sustainable Land Management Using Integrated Environmental Socio-economic Models
- First Online:
- Cite this article as:
- Fleskens, L., Nainggolan, D. & Stringer, L.C. Environmental Management (2014) 54: 1005. doi:10.1007/s00267-013-0202-x
- 530 Downloads
Scenario analysis constitutes a valuable deployment method for scientific models to inform environmental decision-making, particularly for evaluating land degradation mitigation options, which are rarely based on formal analysis. In this paper we demonstrate such an assessment using the PESERA–DESMICE modeling framework with various scenarios for 13 global land degradation hotspots. Starting with an initial assessment representing land degradation and productivity under current conditions, options to combat instances of land degradation are explored by determining: (1) Which technologies are most biophysically appropriate and most financially viable in which locations; we term these the “technology scenarios”; (2) how policy instruments such as subsidies influence upfront investment requirements and financial viability and how they lead to reduced levels of land degradation; we term these the “policy scenarios”; and (3) how technology adoption affects development issues such as food production and livelihoods; we term these the “global scenarios”. Technology scenarios help choose the best technology for a given area in biophysical and financial terms, thereby outlining where policy support may be needed to promote adoption; policy scenarios assess whether a policy alternative leads to a greater extent of technology adoption; while global scenarios demonstrate how implementing technologies may serve wider sustainable development goals. Scenarios are applied to assess spatial variation within study sites as well as to compare across different sites. Our results show significant scope to combat land degradation and raise agricultural productivity at moderate cost. We conclude that scenario assessment can provide informative input to multi-level land management decision-making processes.