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Land cover change in the Bolivian Amazon and its implications for REDD+ and endemic biodiversity

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Abstract

Tropical deforestation is a major contributor to green house gas emissions in developing countries. Incentive mechanisms, such as reducing emissions from deforestation and forest degradation (REDD), are currently being considered as a possible emissions reduction and offset solution. Although REDD has expanded its scope to include co-benefits such as sustainable management of forests and biodiversity conservation (known as REDD+), current carbon-base methodologies do not specifically target projects for the parallel protection of these co-benefits. This study demonstrates the incorporation of both carbon and biodiversity benefits within REDD+ in the Bolivian Amazon, through the analysis of land cover change and future change scenario modeling to the year 2050. Current protected areas within the Bolivian Amazon were evaluated for REDD+ project potential by identifying concordant patterns of carbon content, species biodiversity and deforestation vulnerability. Biodiversity-based versus carbon-based protection schemes were evaluated and protected areas were prioritized using irreplaceability-vulnerability plots. Deforestation projection scenarios to the year 2050 varied depending on the historical period analyzed, producing low, intermediate and high deforestation scenarios. All scenarios showed increasing deforestation pressure in the northern region of Bolivia along with high levels of biodiversity loss. Expected reductions in the carbon pool ranged from 8 to 48%, for the low and high demand scenarios respectively. Some protected areas presented large numbers of endemic species, high concentrations of carbon and high deforestation vulnerability, demonstrating the potential for win–win REDD+ projects in Bolivia.

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References

  • Angelsen A, Wertz-Kanounnikoff S (2008) What are the key design issues for REDD and the criteria for assessing options? In: Angelsen A (ed) Moving ahead with REDD: issues, options and implications. CIFOR, Bogor, pp 11–22

    Google Scholar 

  • Avoided Deforestation Partners (2009) REDD methodology framework Version 1.0 Available from http://www.v-c-s.org/methodology_rmm.html. Accessed March 2011

  • Ball IR, Possingham HP, Watts M (2009) Marxan and relatives: software for spatial conservation prioritisation. In: Moilanen A, Wilson KA, Possingham HP (eds) Spatial conservation prioritisation: quantitative methods and computational tools. Oxford University Press, Oxford, pp 185–195

    Google Scholar 

  • Bishop CM (1995) Neural networks for pattern recognition. Oxford University Press, Oxford

    Google Scholar 

  • Bojanic AH (2001) Bolivia’s participation in the UN Framework on climate change. Overseas Development Institute, London

    Google Scholar 

  • Brown D, Seymour F, Peskett L (2008) How do we achieve REDD co-benefits and avoid doing harm? In: Angelsen A (ed) Moving ahead with REDD: issues options and Implications. CIFOR, Bogor, pp 107–108

    Google Scholar 

  • Burnham BO (1973) Markov intertemporal land use simulation model. South J Agric Econ 5:253–258

    Google Scholar 

  • Capen DE, Fenwick JW, Inkley DB, Boynton AC (1986) On the measurement of multivariate models of songbird habitat in New England forests. In: Verner JA, Morrison ML, Ralph CJ (eds) Wildlife 2000: modelling habitat relationships of terrestrial vertebrates. University of Wisconsin Press, Madison, pp 171–175

    Google Scholar 

  • Chomitz KM, Gray DA (1996) Roads, land use, and deforestation: a spatial model applied to Belize. World Bank Econ Rev 10(3):487–512

    Google Scholar 

  • Chorley RJ, Haggett P (1965) Trend-surface mapping in geographical research. Trans Inst British Geogr 37:47–67

    Article  Google Scholar 

  • Duchelle A, Almeyda A, Hoyos N, Marsik M, Broadbent E, Kainer KA (2010) Conservation in an Amazonian tri-national frontier: patterns and drivers of land cover change in community-managed forests. In: Proceedings of the conference Taking stock of smallholder and community forestry: where do we go from here? Montpellier, 24–26 March 2010

  • Eastman JR (2009) IDRISI Taiga guide to GIS and image processing. Clark University, Clark Labs, IDRISI Productions, Worcester

    Google Scholar 

  • Eastman JR, Jin W, Kyem PAK, Toledano J (1995) Raster procedures for multi-criteria/multi-objective decisions. Photogramm Eng Remote Sens 61(6):539–547

    Google Scholar 

  • Eastman JR, Solorzano LA, Van Fossen M (2005) Transition potential modeling for land-cover change. In: Maguire DJ, Batty M, Goodchild MF (eds) GIS, spatial analysis and modeling. ESRI Press, Redlands, pp 357–385

    Google Scholar 

  • Etter A, McAlpine C, Pullar D, Possingham H (2006) Modelling the conversion of Colombian lowland ecosystems since 1940: drivers, patterns and rates. J Environ Manag 79(1):74–87

    Article  Google Scholar 

  • Eva HD, Huber O (eds) (2005) A proposal for defining the geographical boundaries of Amazonia. Office for Official Publications of the European Communities

  • Fuller DO, Hardiono M, Meijaard E (2011) Deforestation projections for carbon-rich peat swamp forests of Central Kalimantan, Indonesia. Environ Manag 48(3):436–447

    Article  Google Scholar 

  • Grace J, Lloyd J, McIntyre J, Miranda AC, Meir P, Miranda HS, Nobre C, Moncrieff J, Massheder J, Malhi Y, Wright I, Gash J (1995) Carbon dioxide uptake by an undisturbed tropical rain forest in southwest Amazonia, 1992 to 1993. Science 270(5237):778–780

    Article  CAS  Google Scholar 

  • Helmer EH, Brandeis TJ, Lugo AE, Kennaway T (2008) Factors influencing spatial pattern in tropical forest clearance and stand age: Implications for carbon storage and species diversity. J Geophys Res 113(G2):G02S04

    Google Scholar 

  • IUCN (2010) IUCN red list of threatened species. Version 2010.4. Available form http://www.iucnredlist.org/. Accessed March 2011

  • IUCN, Conservation International, Natureserve (2006) Global amphibian assessment Version 1.1. Available from http://natureserve.org. Accessed November 2008

  • IUCN, UNEP (2010) The world database on protected areas (WDPA). UNEP-WCMC. Cambridge

  • Killeen TJ, Calderon V, Soria L, Quezada B, Steininger MK, Harper G, Solorzano LA, Tucker CJ (2007) Thirty years of land-cover change in Bolivia. AMBIO. J Human Environ 36(7):600–606

    Article  Google Scholar 

  • Killeen T, Guerra A, Calzada M, Correa L, Calderon V, Soria L, Quezada B, Steininger MK (2008) Total historical land use change in eastern Bolivia: who, where, when, and how much. Ecol Soc 13:16–27

    Google Scholar 

  • Kim OS (2010) An assessment of deforestation models for reducing emissions from deforestation and forest degradation (REDD). Transact GIS 14(5):631–654

    Article  Google Scholar 

  • Kleinbaum DG, Klein M (2002) Logistic regression. A self-learning text. Springer, New York

    Google Scholar 

  • Kremen C, Cameron A, Moilanen A, Phillips SJ, Thomas CD, Beentje H, Dransfield J, Fisher BL, Glaw F, Good TC, Harper GJ, Hijmans RJ, Lees DC, Louis E Jr, Nussbaum RA, Raxworthy CJ, Razafimpahanana A, Schatz GE, Vences M, Vieites DR, Wright PC, Zjhra ML (2008) Aligning conservation priorities across taxa in madagascar with high-resolution planning tools. Science 320(5873):222–226

    Article  PubMed  CAS  Google Scholar 

  • Laurance WF, Vasconcelos HL, Lovejoy TE (2000) Forest loss and fragmentation in the Amazon: implications for wildlife conservation. Oryx 34(1):39–45

    Google Scholar 

  • Laurance WF, Albernaz AKM, Fearnside PM, Vasconcelos HL, Ferreira LV (2004) Deforestation in Amazonia. Science 304:1109–1111

    Article  PubMed  CAS  Google Scholar 

  • Lin YP, Chu HJ, Wu CF, Verburg PH (2011) Predictive ability of logistic regression, auto-logistic regression and neural network models in empirical land-use change modeling—a case study. Int J Geogr Inf Sci 25(1):65–87

    Article  Google Scholar 

  • Malhi Y, Roberts JT, Betts RA, Killeen TJ, Li W, Nobre CA (2008) Climate change, deforestation, and the fate of the Amazon. Science 319(5860):169–172

    Article  PubMed  CAS  Google Scholar 

  • Margules CR, Pressey RL (2000) Systematic conservation planning. Nature 405(6783):243–253

    Article  PubMed  CAS  Google Scholar 

  • Mertens B, Lambin EF (1997) Spatial modelling of deforestation in southern Cameroon: spatial disaggregation of diverse deforestation processes. Appl Geogr 17(2):143–162

    Article  Google Scholar 

  • Miles L, Kapos V (2008) Reducing greenhouse gas emissions from deforestation and forest degradation: global land-use implications. Science 320(5882):1454–1455

    Article  PubMed  CAS  Google Scholar 

  • Moilanen A, Franco AMA, Early RI, Fox R, Wintle B, Thomas CD (2005) Prioritizing multiple-use landscapes for conservation: methods for large multi-species planning problems. Proc Royal Soc B Biol Sci 272(1575):1885–1891

    Article  Google Scholar 

  • Nelson A (2008) Travel time to major cities: a global map of accessibility. Office for Official Publications of the European Communities, Luxembourg

    Google Scholar 

  • Nelson GC, Hellerstein D (1997) Do roads cause deforestation? Using satellite images in econometric analysis of land use. Am J Agric Econ 79(1):80–88

    Article  Google Scholar 

  • Paegelow M, Olmedo MTC (2008) Advances in geomatic simulations for environmental dynamics. In: Paegelow M, Olmedo MTC (eds) Modelling environmental dynamics, advances in geomatic solutions. Springer, Berlin, pp 3–54

    Google Scholar 

  • Parker C, Mitchell A, Trivedi M, Mardas N (2009) The little REDD+ book. Global Canopy Programme, Oxford

    Google Scholar 

  • Patterson BD, Ceballos G, Sechrest W, Tognelli MF, Brooks T, Luna L, Ortega P, Salazar I, Young BE (2007) Digital distribution maps of the mammals of the western hemisphere, version 2.0. NatureServe, Arlington, Virginia. Accessed Nov 2008

  • Pedroni L (2008) Methodology for estimating reductions of GHG emissions from mosaic deforestation. BioCarbon Fund, Washington

    Google Scholar 

  • Pelletier J, Ramankutty N, Potvin C (2011) Painting the world REDD: addressing scientific barriers to monitoring emissions from tropical forests. Environ Res Lett 6(2):021002

    Article  Google Scholar 

  • Perz S, Brilhante S, Brown F, Caldas M, Ikeda S, Mendoza E, Overdevest C, Reis V, Reyes JF, Rojas D, Schmink M, Souza C, Walker R (2008) Road building, land use and climate change: prospects for environmental governance in the Amazon. Philos Trans R Soc B Biol Sci 363(1498):1889–1895

    Article  Google Scholar 

  • Pettorelli N, Katzner T, Gordon I, Garner T, Mock K, Redpath S, Gompper M (2009) Possible consequences of the Copenhagen climate change meeting for conservation of animals. Anim Conserv 12(6):503–504

    Article  Google Scholar 

  • Phillips OL, Lewis SL, Baker TR, Chao KJ, Higuchi N (2008) The changing Amazon forest. Philos Trans Royal Soc B Biol Sci 363(1498):1819–1827

    Article  Google Scholar 

  • Pijanowski BC, Brown DG, Shellito BA, Manik GA (2002) Using neural networks and GIS to forecast land use changes: a land transformation model. Comput Environ Urban Syst 26(6):553–575

    Article  Google Scholar 

  • Pontius RG (2000) Quantification error versus location error in comparison of categorical maps. Photogramm Eng Remote Sens 66:1011–1016

    Google Scholar 

  • Pontius RG, Schneider LC (2001) Land-cover change model validation by an ROC method for the Ipswich watershed, Massachusetts, USA. Agric Ecosyst Environ 85:239–248

    Article  Google Scholar 

  • Potts WJE (2000) Neural network modeling course notes. SAS Institute, Inc., Cary

    Google Scholar 

  • Ridgely RS, Allnutt TF, Brooks T, Mcnicol DK, Mehlman DW, Young BE, Zook JR (2003) Digital distribution maps of the birds of the western hemisphere, Version 1.0. NatureServe, Arlington, Virginia. Accessed Nov 2008

  • Saatchi SS, Houghton RA, Dos Santos Alvalá RC, Soares JV, Yu Y (2007) Distribution of aboveground live biomass in the Amazon basin. Glob Change Biol 13(4):816–837

    Article  Google Scholar 

  • Sampaio G, Nobre C, Costa MH, Satyamurty P, Soares-Filho BS, Cardoso M (2007) Regional climate change over eastern Amazonia caused by pasture and soybean cropland expansion. Geophys Res Lett 34(17):L17709

    Article  Google Scholar 

  • Soares-Filho BS, De A Araujo A, Cerqueira GC, Araujo WL (2001) DINAMICA—a landscape dynamics simulation software. In: Proceedings of the XIV Brazilian symposium on computer graphics and image processing, Florianopolis, Oct 2001

  • Soares-Filho BS, Nepstad DC, Curran LM, Cerqueira GC, Garcia RA, Ramos CA, Voll E, McDonald A, Lefebvre P, Schlesinger P (2006) Modelling conservation in the Amazon basin. Nature 440(7083):520–523

    Article  PubMed  CAS  Google Scholar 

  • Steininger MK, Tucker CJ, Townshend JRG, Killeen TR, Desch A (2001) Tropical deforestation in the Bolivian Amazon. Environ Conserv 28:127–134

    Article  Google Scholar 

  • Stickler CM, Nepstad DC, Coe MT, McGrath DG, Rodrigues HO, Walker WS, Soares-Filho BS, Davidson EA (2009) The potential ecological costs and co-benefits of REDD: a critical review and case study from the Amazon region. Glob Change Biol 15(12):2803–2824

    Article  Google Scholar 

  • Swets JA (1986) Form of empirical ROCs in discrimination and diagnostic tasks: implications for theory and measurement of performance. Psychol Bull 99(2):181–198

    Article  PubMed  CAS  Google Scholar 

  • Tallis H, Ferdana Z, Gray E (2008) Linking terrestrial and marine conservation planning and threats analysis. Conserv Biol 22:120–130

    Article  PubMed  Google Scholar 

  • UNFCCC (2007) Reducing emissions from deforestation in developing countries: approaches to stimulate action. Conference of the parties, Bali, 3–14 Dec 2007

  • Venter O, Laurance WF, Iwamura T, Wilson KA, Fuller RA, Possingham HP (2009) Harnessing carbon payments to protect biodiversity. Science 326(5958):1368

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

The authors would like to thank Tim Killeen at the Noel Kempff Mercado museum, and Conservation International, for providing the land cover maps of Bolivia as well as the driver variables used in this model. We would like to thank Sean Sloan, Clive McAlpine and two anonymous reviewers whose comments significantly improved this manuscript.

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Correspondence to Florencia Sangermano.

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Sangermano, F., Toledano, J. & Eastman, J.R. Land cover change in the Bolivian Amazon and its implications for REDD+ and endemic biodiversity. Landscape Ecol 27, 571–584 (2012). https://doi.org/10.1007/s10980-012-9710-y

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