Economic and social constraints on reforestation for climate mitigation in Southeast Asia

Tollefson, J. The hard truths of climate change—by the numbers. Nature 573, 324–327 (2019).

CAS  Google Scholar 

Rogelj, J. et al. in Special Report on Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al.) Ch. 2 (IPCC, WMO, 2018).

Egli, F. & Stunzi, A. A dynamic climate finance allocation mechanism reflecting the Paris Agreement. Environ. Res. Lett. 14, 114024 (2019).

Google Scholar 

Griscom, B. W. et al. We need both natural and energy solutions to stabilize our climate. Glob. Change Biol. 25, 1889–1890 (2019).

Google Scholar 

Griscom, B. W. et al. Natural climate solutions. Proc. Natl Acad. Sci. USA 114, 11645–11650 (2017).

CAS  Google Scholar 

Smith, P. et al. Biophysical and economic limits to negative CO₂ emissions. Nat. Clim. Change 6, 42–50 (2015).

Google Scholar 

Fargione, J. E. et al. Natural climate solutions for the United States. Sci. Adv. 4, eaat1869 (2018).

Google Scholar 

Bastin, J.-F. et al. The global tree restoration potential. Science 365, 76–79 (2019).

CAS  Google Scholar 

Busch, J. et al. Potential for low-cost carbon dioxide removal through tropical reforestation. Nat. Clim. Change 9, 463–466 (2019).

CAS  Google Scholar 

Luedeling, E. et al. Forest restoration: overlooked constraints. Science 366, 315 (2019).

Google Scholar 

Chazdon, R. & Brancalion, P. Restoring forests as a means to many ends. Science 365, 24–25 (2019).

CAS  Google Scholar 

Cohn, A. S. et al. Smallholder agriculture and climate change. Annu. Rev. Environ. Resour. 42, 347–375 (2017).

Google Scholar 

Lazos-Chavero, E. et al. Stakeholders and tropical reforestation: challenges, trade-offs, and strategies in dynamic environments. Biotropica 48, 900–914 (2016).

Google Scholar 

Barr, C. M. & Sayer, J. A. The political economy of reforestation and forest restoration in Asia–Pacific: critical issues for REDD. Biol. Conserv. 154, 9–19 (2012).

Google Scholar 

Wilson, K. A. et al. Optimal restoration: accounting for space, time and uncertainty. J. Appl. Ecol. 48, 715–725 (2011).

Google Scholar 

Kettle, C. J. Ecological considerations for using dipterocarps for restoration of lowland rainforest in Southeast Asia. Biodivers. Conserv. 19, 1137–1151 (2010).

Google Scholar 

Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A. & Hansen, M. C. Classifying drivers of global forest loss. Science 361, 1108–1111 (2018).

CAS  Google Scholar 

Estoque, R. C. et al. The future of Southeast Asia’s forests. Nat. Commun. 10, 1829 (2019).

Google Scholar 

Hengl, T. et al. Global mapping of potential natural vegetation: an assessment of machine learning algorithms for estimating land potential. PeerJ 6, e5457 (2018).

Google Scholar 

Budiharta, S. et al. Restoring degraded tropical forests for carbon and biodiversity. Environ. Res. Lett. 9, 114020 (2014).

Google Scholar 

Oakleaf, J. R. et al. Mapping global development potential for renewable energy, fossil fuels, mining and agriculture sectors. Sci. Data 6, 101 (2019).

Google Scholar 

Lewis, S. L., Wheeler, C. E., Mitchard, E. T. A. & Koch, A. Restoring natural forests is the best way to remove atmospheric carbon. Nature 568, 25–28 (2019).

CAS  Google Scholar 

Löfqvist, S. & Ghazoul, J. Private funding is essential to leverage forest and landscape restoration at global scales. Nat. Ecol. Evol. 3, 1612–1615 (2019).

Google Scholar 

Meyfroidt, P. & Lambin, E. F. The causes of the reforestation in Vietnam. Land Use Policy 25, 182–197 (2008).

Google Scholar 

Chazdon, R. L. & Guariguata, M. R. Natural regeneration as a tool for large-scale forest restoration in the tropics: prospects and challenges. Biotropica 48, 716–730 (2016).

Google Scholar 

Chazdon, R. L. Beyond deforestation: restoring forests and ecosystem services on degraded lands. Science 320, 1458–1460 (2008).

CAS  Google Scholar 

Brancalion, P. H. S. et al. Global restoration opportunities in tropical rainforest landscapes. Sci. Adv. 5, eaav3223 (2019).

Google Scholar 

Sheil, D. et al. Forest restoration: transformative trees. Science 366, 316–317 (2019).

Google Scholar 

Delzeit, R. et al. Forest restoration: expanding agriculture. Science 366, 316–317 (2019).

Google Scholar 

Strassburg, B. B. N. et al. Strategic approaches to restoring ecosystems can triple conservation gains and halve costs. Nat. Ecol. Evol. 3, 62–70 (2019).

Google Scholar 

National Inventory Submissions 2019 (UNFCCC, 2019); https://unfccc.int/process-and-meetings/transparency-and-reporting/reporting-and-review-under-the-convention/greenhouse-gas-inventories-annex-i-parties/national-inventory-submissions-2019

Crouzeilles, R. et al. Achieving cost-effective landscape-scale forest restoration through targeted natural regeneration. Conserv. Lett. 13, e12709 (2020).

Google Scholar 

Financing Emission Reductions for the Future: State of Voluntary Carbon Markets 2019 (Forest Trends’ Ecosystem Marketplace, 2019).

Tobón, W. et al. Restoration planning to guide Aichi targets in a megadiverse country. Conserv. Biol. 31, 1086–1097 (2017).

Google Scholar 

Griggs, D. et al. Sustainable development goals for people and planet. Nature 495, 305–307 (2013).

Google Scholar 

Miettinen, J. & Liew, S. C. Degradation and development of peatlands in Peninsular Malaysia and in the islands of Sumatra and Borneo since 1990. Land Degrad. Dev. 21, 285–296 (2010).

Google Scholar 

Miettinen, J., Shi, C. & Liew, S. C. Land cover distribution in the peatlands of Peninsular Malaysia, Sumatra and Borneo in 2015 with changes since 1990. Glob. Ecol. Conserv. 6, 67–78 (2016).

Google Scholar 

Bunting, P. et al. The global mangrove watch—a new 2010 global baseline of mangrove extent. Remote Sens. 10, 1669 (2018).

Google Scholar 

Land Cover CCI Product User Guide Version 2 (ESA, 2017); http://maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdf

Graham, V., Laurance, S. G., Grech, A. & Venter, O. Spatially explicit estimates of forest carbon emissions, mitigation costs and REDD+ opportunities in Indonesia. Environ. Res. Lett. 12, 044017 (2017).

Google Scholar 

Baccini, A. et al. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nat. Clim. Change 2, 182–185 (2012).

Google Scholar 

Avitabile, V. et al. An integrated pan-tropical biomass map using multiple reference datasets. Glob. Change Biol. 22, 1406–1420 (2016).

Google Scholar 

Worthington, T. & Spalding, M. Mangrove Restoration Potential: A Global Map Highlighting a Critical Opportunity (Univ. Cambridge, 2018); https://doi.org/10.17863/CAM.39153

Miettinen, J., Shi, C. & Liew, S. C. Deforestation rates in insular Southeast Asia between 2000 and 2010. Glob. Change Biol. 17, 2261–2270 (2011).

Google Scholar 

Miettinen, J., Shi, C. & Liew, S. C. 2015 Land cover map of Southeast Asia at 250 m spatial resolution. Remote Sens. Lett. 7, 701–710 (2016).

Google Scholar 

Friedlingstein, P., Allen, M., Canadell, J. G., Peters, G. P. & Seneviratne, S. I. Comment on ‘The global tree restoration potential’. Science 366, eaay8060 (2019).

Google Scholar 

Veldman, J. W. et al. Comment on ‘The global tree restoration potential’. Science 366, eaay7976 (2019).

Google Scholar 

Buendia, C. et al. (eds) 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories Volume 4: Agriculture, Forestry and Other Land Use (IPCC, 2019).

Fritz, S. et al. Mapping global cropland and field size. Glob. Change Biol. 21, 1980–1992 (2015).

Google Scholar 

Requena Suarez, D. et al. Estimating aboveground net biomass change for tropical and subtropical forests: Refinement of IPCC default rates using forest plot data. Glob. Change Biol. 25, 3609–3624 (2019).

Google Scholar 

Cameron, C., Hutley, L. B., Friess, D. A. & Brown, B. High greenhouse gas emissions mitigation benefits from mangrove rehabilitation in Sulawesi, Indonesia. Ecosyst. Serv. 40, 101035 (2019).

Google Scholar 

World Development Report 2013: Jobs (World Bank, 2012).

The World Bank Annual Report 2018 (World Bank, 2018).

FAOSTAT (FAO, 2017); http://www.fao.org/faostat/en/#data

Producer Prices-Annua (FAO, 2017); http://www.fao.org/faostat/en/#data/PP

Global Agro-Ecological Zones: Suitability and Potential Yield — Agro-Climatic Yield (International Institute for Applied Systems Analysis, 2015); http://gaez.fao.org/Main.html#

Employment by Sex and Age—ILO Modelled Estimates (International Labour Organization, 2014); https://ilostat.ilo.org/data

World Development Indicators (The World Bank, 2018); http://data.worldbank.org/data-catalog/world-development-indicators

Naylor, R. L., Higgins, M. M., Edwards, R. B. & Falcon, W. P. Decentralization and the environment: assessing smallholder oil palm development in Indonesia. Ambio 48, 1195–1208 (2019).

Google Scholar 

Hewson, J., Crema, S. C., González-Roglich, M., Tabor, K. & Harvey, C. A. New 1 km resolution datasets of global and regional risks of tree cover loss. Land 8, 14 (2019).

Google Scholar 

The World Database on Protected Areas (WDPA) (UNEP-WCMC and IUCN, 2016); http://protectedplanet.net

Weiss, D. J. et al. A global map of travel time to cities to assess inequalities in accessibility in 2015. Nature 553, 333–336 (2018).

CAS  Google Scholar 

Potapov, P. et al. The last frontiers of wilderness: tracking loss of intact forest landscapes from 2000 to 2013. Sci. Adv. 3, e1600821 (2017).

Google Scholar 

Page, S. E. et al. Review of Peat Surface Greenhouse Gas Emissions from Oil Palm Plantations in Southeast Asia White Paper No. 15 (International Council on Clean Transportation, 2011).

Reijnders, L. & Huijbregts, M. A. J. Palm oil and the emission of carbon-based greenhouse gases. J. Clean. Prod. 16, 477–482 (2008).

Google Scholar 

Saragi-Sasmito, M. F., Murdiyarso, D., June, T. & Sasmito, S. D. Carbon stocks, emissions, and aboveground productivity in restored secondary tropical peat swamp forests. Mitig. Adapt. Strateg. Glob. Change 24, 521–533 (2019).

Google Scholar 

R v.3.6.0 (R Foundation for Statistical Computing, 2019).

Hijmans, R. J. et al. raster: Geographic data analysis and modeling. R package v.2.5-8.

QGIS Geographic Information System Version 2.14 (Open Source Geospatial Foundation Project, 2019); http://qgis.org