Published in

Wiley Open Access, GCB Bioenergy, 3(8), p. 561-578, 2015

DOI: 10.1111/gcbb.12270

Links

Tools

Export citation

Search in Google Scholar

What can and can't we say about indirect land use change in Brazil using an integrated economic - land use change model?

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

It is commonly recognized that large uncertainties exist in modelled biofuel induced indirect land use change, but until now, spatially explicit quantification of such uncertainties by means of error propagation modelling has never been performed. In this paper, we demonstrate a general methodology to stochastically calculate direct and indirect land use change (dLUC and iLUC) caused by an increasing demand for biofuels, with an integrated economic – land use change model. We use the global Computable General Equilibrium model MAGNET, connected to the spatially explicit land use change model PLUC. We quantify important uncertainties in the modelling chain. Next, dLUC and iLUC projections for Brazil up to 2030 at different spatial scales and the uncertainty herein are assessed. Our results show that cell (5 x 5 km2) based probabilities of dLUC range from 0 to 0.77, and of iLUC from 0 to 0.43, indicating that it is difficult to project exactly where dLUC and iLUC will occur, with more difficulties for iLUC than for dLUC. At country level, dLUC area can be projected with high certainty, having a coefficient of variation (cv) of only 0.02, while iLUC area is still uncertain, having a cv of 0.72. The latter means that, considering the 95% confidence interval, the iLUC area in Brazil might be 2.4 times as high or as low as the projected mean. Because this confidence interval is so wide that it is likely to straddle any legislation threshold, our opinion is that threshold evaluation for iLUC indicators should not be implemented in legislation. For future studies we emphasize the need for provision of quantitative uncertainty estimates together with the calculated LUC indicators, to allow users to evaluate the reliability of these indicators and the effects of their uncertainty on the impacts of land use change, like greenhouse gas emissions.This article is protected by copyright. All rights reserved.