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Robust design of multiscale programs to reduce deforestation

Published online by Cambridge University Press:  11 April 2011

ANDREA CATTANEO*
Affiliation:
The Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA 02540-1644, USA. Tel: +508 540-9900 ext. 161. Email: [email protected]

Abstract

A framework is provided for structuring programs aimed at reducing emissions from deforestation and forest degradation (REDD). Crediting reference levels and the coordination among different implementing entities at multiple geographic scales are discussed. A crediting reference level has an error component if it differs from the business-as-usual (BAU) without REDD. Both the BAU emissions and the impact of REDD actions are uncertain, implying that participating in REDD entails stakeholder risk, the distribution of which depends on REDD program design. To categorize REDD architectures we define scale-neutrality whereby, for a given REDD design, crediting relative to the reference level at a given scale is not affected by errors in reference levels at scales below it. Sufficient conditions are derived for scale-neutrality to hold. A Brazilian Amazon example is provided, comparing potential REDD architectures, and highlighting how a cap-and-trade approach may match the environmental outcome obtainable with perfect foresight of the BAU emissions.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2011

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References

Angelsen, A. (2008), ‘Preface’, in Angelsen, A. (ed), Moving Ahead with REDD: Issues, Options and Implications, Bogor, Indonesia: CIFOR.Google Scholar
Angelsen, A., Streck, C., Peskett, L., Brown, J., and Luttrell, C. (2008), ‘What is the right scale for REDD’, in Angelsen, A. (ed), Moving Ahead with REDD: Issues, Options and Implications, Bogor, Indonesia: CIFOR, pp. 3140.Google Scholar
Ashton, R. et al. (2008), How to Include Terrestrial Carbon in Developing Nations in the Overall Climate Change Solution, Boston, MA: The Terrestrial Carbon Group.Google Scholar
Börner, J. and Wunder, S. (2008), ‘Paying for avoided deforestation in the Brazilian Amazon: from cost assessment to scheme design’, International Forestry Review 10 (3): 496511.CrossRefGoogle Scholar
Busch, J., Strassburg, B., Cattaneo, A., Lubowski, R., Bruner, A., Rice, D., Creed, A., Ashton, R., and Boltz, F. (2009a), ‘Comparing climate and cost impacts of reference levels for reducing emissions from deforestation’, Environmental Research Letters 4: 044006.CrossRefGoogle Scholar
Busch, J., Strassburg, B., Cattaneo, A., Lubowski, R., Bruner, A., Rice, R., Creed, A., Ashton, R., and Boltz, F. (2009b), Open Source Impacts of REDD Incentives Spreadsheet. OSIRIS v2.6. http://www.conservation.org/osiris.CrossRefGoogle Scholar
Cattaneo, A. (2001), ‘Deforestation in the Brazilian Amazon: comparing the impacts of macroeconomic shocks, land tenure, and technological change’, Land Economics 77 (2): 219240.CrossRefGoogle Scholar
Cattaneo, A. (2005), ‘Inter-regional innovation in Brazilian agriculture and deforestation in the Amazon: income and environment in the balance’, Environment and Development Economics 10 (4): 485511.CrossRefGoogle Scholar
Cattaneo, A. (2008), ‘Regional comparative advantage, location of agriculture, and deforestation in Brazil’, Journal of Sustainable Forestry 27: 2542.CrossRefGoogle Scholar
Cattaneo, A. (2010a), ‘Incentives to reduce emissions from deforestation: a stock-flow approach with target reductions’, in Bosetti, V. and Lubowski, R. (eds), Deforestation and Climate Change: Reducing Carbon Emissions from Deforestation and Forest Degradation, Cheltenham, UK: Elgar Publications.Google Scholar
Cattaneo, A., Lubowski, R., Busch, J., Creed, A., Strassburg, B., Boltz, F., and Ashton, R. (2010b), ‘On international equity in reducing emissions from deforestation’, Environmental Science & Policy 13 (8): 742753.CrossRefGoogle Scholar
Cattaneo, A., Soares-Filho, B., Alencar, A., Merry, F., Bowman, M., Nepstad, D., Busch, J., Moutinho, P., Stickler, C., Hissa, L. Viana, Stella, O., and Lima, A. (2010c), BANTER: The Brazilian Amazon Negotiation Toolbox for the Economics of REDD, available online at http://www.whrc.org/policy/banter.html, accessed December 12, 2010.Google Scholar
Clark, W.A.V. and Avery, K.L. (1976), ‘The effects of data aggregation in statistical analysis’, Geographical Analysis 8: 428438.CrossRefGoogle Scholar
Evans, T. and Kelley, H. (2004), ‘Multi-scale analysis of a household level agent-based model of land cover change’, Journal of Environmental Management 72 (1–2): 5772.CrossRefGoogle Scholar
da Fonseca, G.A.B., Rodriguez, C.M., Midgley, G., Busch, J., Hannah, L., and Mittermeier, R.A. (2007), ‘No forest left behind’, Public Library of Science Biology 5 (8):e216.Google ScholarPubMed
Geist, H.J. and Lambin, E.E. (2002), ‘Proximate causes and underlying driving forces of tropical deforestation’, BioScience 52 (2): 143150.CrossRefGoogle Scholar
Gibson, C.C., Ostrom, E., and Ahn, T.K. (2000), ‘The concept of scale and the human dimensions of global change: a survey’, Ecological Economics 32: 217239.CrossRefGoogle Scholar
Goodchild, M.F. and Quattrochi, D.A. (1997), ‘Scale, multiscaling, remote sensing and GIS’, in Quattrochi, D.A. and Goodchild, M.F. (eds), Scale in Remote Sensing and GIS, Boca Raton, FL: Lewis Publishers, pp. 111.Google Scholar
Jackson, M.O. (2008), Social and Economic Networks, Oxford: Princeton University Press.CrossRefGoogle Scholar
Marceau, D.J. (1999), ‘The scale issue in the social and natural sciences’, Canadian Journal of Remote Sensing 25 (4): 347356.CrossRefGoogle Scholar
Mollicone, D., Achard, F., Federici, S., Eva, H., Grassi, G., Belward, A., Raes, F., Seufert, G., Stibig, H.-J., Matteucci, G., and Schulze, E.-D. (2007), ‘An incentive mechanism for reducing emissions from conversion of intact and non-intact forests’, Climatic Change 83 (4): 477493.CrossRefGoogle Scholar
Openshaw, S. and Taylor, P.J. (1981), ‘The modifiable areal unit problem’, in Wrigley, N. and Bennett, R.J. (eds), Quantitative Geography: A British View, London: Routledge, pp. 6069.Google Scholar
Pedroni, L., Dutschke, M., Streck, C., and Porrúa, M.E. (2009) ‘Creating incentives for avoiding further deforestation: the nested approach’, Climate Policy 9 (2): 207220.CrossRefGoogle Scholar
Santilli, M., Moutinho, P., Schwartzman, S., Nepstad, D., Curran, L., and Nobre, C. (2005), ‘Tropical deforestation and Kyoto Protocol’, Climatic Change 71 (3): 267276.CrossRefGoogle Scholar
Skutsch, M. and van Laake, P. (2008), ‘REDD as multi-level governance in the making’, Energy and Environment 19 (6): 831844.CrossRefGoogle Scholar
Soares-Filho, B.S., Nepstad, D.C., Curran, L.M., Cerqueira, G.C., Garcia, R.A., Ramos, C. Azevedo, Voll, E., Macdonald, A., Lefebvre, P., and Schlesinger, P. (2006), ‘Modelling conservation in the Amazon basin’, Nature 440: 520523.CrossRefGoogle ScholarPubMed
Stern, N.H. (2007), The Economics of Climate Change, Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Strassburg, B., Turner, K., Fisher, B., Schaeffer, R., and Lovett, A. (2009), ‘REDD: The combined incentives mechanism’, Global Environmental Change 19 (2): 265278.CrossRefGoogle Scholar
Streck, C., Pedroni, L., Porrua, M.E., and Dutschke, M. (2008), ‘Creating incentives for avoiding further deforestation: the nested approach’, in Streck, C., O'Sullivan, R., Janson-Smith, T., and Tarasofsky, R. (eds), Climate Change and Forests: Emerging Policy and Market Opportunities, Washington, DC: Brookings Institution Press, pp. 237249.Google Scholar
Turner, M.G., O'Neill, R.V., Gardner, R.H., and Milne, B.T. (1989), ‘Effects of changing spatial scale on the analysis of landscape pattern’, Landscape Ecology 3 (3/4): 153162.CrossRefGoogle Scholar
Verburg, P.H., Schot, P.P., Dijst, M.J., and Veldkamp, A. (2004), ‘Land use change modelling: current practice and research priorities’, GeoJournal 61: 309324.CrossRefGoogle Scholar
Wu, H. and Li, Z.L. (2009), ‘Scale issues in remote sensing: a review on analysis, processing and modeling’, Sensors 9 (3): 17681793.CrossRefGoogle ScholarPubMed
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