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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
The overlooked spatial dimension of climate-smart agriculture
Reinhard Prestele1, Peter H Verburg1,2
1Environmental Geography Group, Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Abstract:
Climate-smart agriculture (CSA) and sustainable intensification (SI) are widely claimed to be high-potential solutions to address the interlinked challenges of food security and climate change. Operationalization of these promising concepts is still lacking and potential trade-offs are often not considered in the current continental- to global-scale assessments. Here we discuss the effect of spatial variability in the context of the implementation of climate-smart practices on two central indicators, namely yield development and carbon sequestration, considering biophysical limitations of suggested benefits, socioeconomic and institutional barriers to adoption, and feedback mechanisms across scales. We substantiate our arguments by an illustrative analysis using the example of a hypothetical large-scale adoption of conservation agriculture (CA) in sub-Saharan Africa. We argue that, up to now, large-scale assessments widely neglect the spatially variable effects of climate-smart practices, leading to inflated statements about co-benefits of agricultural production and climate change mitigation potentials. There is an urgent need to account for spatial variability in assessments of climate-smart practices and target those locations where synergies in land functions can be maximized in order to meet the global targets. Therefore, we call for more attention toward spatial planning and landscape optimization approaches in the operationalization of CSA and SI to navigate potential trade-offs.
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