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Implications of ecological data constraints for integrated policy and livelihoods modelling: An example from East Kalimantan, Indonesia
Authors:Alex Smajgl  Alan PN HouseJames RA Butler
Institution:a CSIRO Ecosystem Sciences and Climate Adaptation Flagship, University Drive, Townsville, QLD 4810, Australia
b CSIRO Ecosystem Sciences and Climate Adaptation Flagship, 306 Carmody Road, St Lucia, QLD 4067, Australia
Abstract:Policy and human livelihoods modelling increasingly demands integrated research which requires ecological expertise. However, contributions from ecologists are often based on sparse data. Rather than discounting such data, in this paper we demonstrate how ecological modelling can effectively contribute to the development of policy recommendations in spite of data constraints. In a petrol subsidy analysis in East Kalimantan, Indonesia, we accounted for ecological data uncertainty by (a) assuming large parameter value ranges and (b) conducting a robustness test for policy recommendations. In addition to data scarcity, counter-intuitive results emerged emphasising the need for model validation. These counter-intuitive results indicated that decreasing petrol prices led to increased poverty. This informed a policy recommendation to prevent the reduction of petrol prices below IDR 5500 per litre. Using two key livelihood resources (fish and honey), we found that while a traditional sensitivity analysis suggested highly robust results, a robustness test indicated that policy recommendations would change if the incorrectness of parameter values approached 50%. The results show that ecological modelling can contribute effectively in spite of sparse data to guide policy, as well as identifying future research priorities.
Keywords:Agent-based modelling  Validation  Uncertainty  Livelihoods  Policy analysis
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