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Classifying drivers of global forest loss
Mapping global deforestation patterns
Forest loss is being driven by various factors, including commodity production, forestry, agriculture, wildfire, and urbanization. Curtis et al. used high-resolution Google Earth imagery to map and classify global forest loss since 2001. Just over a quarter of global forest loss is due to deforestation through permanent land use change for the production of commodities, including beef, soy, palm oil, and wood fiber. Despite regional differences and efforts by governments, conservationists, and corporations to stem the losses, the overall rate of commodity-driven deforestation has not declined since 2001.
Science, this issue p. 1108
Abstract
Global maps of forest loss depict the scale and magnitude of forest disturbance, yet companies, governments, and nongovernmental organizations need to distinguish permanent conversion (i.e., deforestation) from temporary loss from forestry or wildfire. Using satellite imagery, we developed a forest loss classification model to determine a spatial attribution of forest disturbance to the dominant drivers of land cover and land use change over the period 2001 to 2015. Our results indicate that 27% of global forest loss can be attributed to deforestation through permanent land use change for commodity production. The remaining areas maintained the same land use over 15 years; in those areas, loss was attributed to forestry (26%), shifting agriculture (24%), and wildfire (23%). Despite corporate commitments, the rate of commodity-driven deforestation has not declined. To end deforestation, companies must eliminate 5 million hectares of conversion from supply chains each year.
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Supplementary Material
Summary
Materials and Methods
Figs. S1 to S10
Tables S1 to S7
Data S1 to S4
Resources
References and Notes
1
S. Donofrio, P. Rothrock, J. Leonard, “Supply Change: Tracking Corporate Commitments to Deforestation-Free Supply Chains” (Forest Trends, 2017); www.forest-trends.org/documents/files/doc_5521.pdf#.
2
A. Sen, “Pathways to Deforestation-Free Food” (Oxfam, 2017); https://policy-practice.oxfam.org.uk/publications/pathways-to-deforestation-free-food-developing-supply-chains-free-of-deforestat-620332.
3
M. C. Hansen, P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, J. R. G. Townshend, High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).
4
Global Forest Watch, http://globalforestwatch.org.
5
D. Schoene, W. Killmann, H. von Lüpke, M. L. Wilkie, “Definitional Issues Related to Reducing Emissions from Deforestation in Developing Countries” (Food and Agriculture Organization of the United Nations, 2007); www.fao.org/tempref/docrep/fao/009/j9345e/j9345e00.pdf.
6
N. Harris, R. Petersen, C. Davis, O. Payne, “Global Forest Watch and the Forest Resources Assessment, Explained in 5 Graphics” (World Resources Institute, 2016); www.wri.org/blog/2016/08/insider-global-forest-watch-and-forest-resources-assessment-explained-5-graphics.
7
R. S. DeFries, R. A. Houghton, M. C. Hansen, C. B. Field, D. Skole, J. Townshend, Carbon emissions from tropical deforestation and regrowth based on satellite observations for the 1980s and 1990s. Proc. Natl. Acad. Sci. U.S.A. 99, 14256–14261 (2002).
8
M. C. Hansen, S. V. Stehman, P. V. Potapov, Quantification of global gross forest cover loss. Proc. Natl. Acad. Sci. U.S.A. 107, 8650–8655 (2010).
9
See supplementary materials.
10
H. J. Geist, E. F. Lambin, Proximate Causes and Underlying Driving Forces of Tropical Deforestation. Bioscience 52, 143–150 (2002).
11
G. Molinario, M. C. Hansen, P. V. Potapov, Forest cover dynamics of shifting cultivation in the Democratic Republic of Congo: A remote sensing-based assessment for 2000–2010. Environ. Res. Lett. 10, 094009 (2015).
12
R. Tropek, O. Sedláček, J. Beck, P. Keil, Z. Musilová, I. Símová, D. Storch, Comment on “High-resolution global maps of 21st-century forest cover change”. Science 344, 981 (2014).
13
P. Olofsson, G. M. Foody, M. Herold, S. V. Stehman, C. E. Woodcock, M. A. Wulder, Good practices for estimating area and assessing accuracy of land change. Remote Sens. Environ. 148, 42–57 (2014).
14
A. Tyukavina, A. Baccini, M. C. Hansen, P. V. Potapov, S. V. Stehman, R. A. Houghton, A. M. Krylov, S. Turubanova, S. J. Goetz, Aboveground carbon loss in natural and managed tropical forests from 2000 to 2012. Environ. Res. Lett. 10, 074002 (2015).
15
United Nations Framework Convention on Climate Change, “Warsaw Framework for REDD-Plus” (2013); http://unfccc.int/land_use_and_climate_change/redd/items/8180.php.
16
Huffington Post Canada, “Canada Largest Contributor to Deforestation Worldwide” (2014); www.huffingtonpost.ca/2014/09/05/canada-deforestation-wost-in-world_n_5773142.html.
17
FAO Country Profiles: Geographic and Economic Groups (Food and Agriculture Organization of the United Nations, 2017); www.fao.org/countryprofiles/geographic-and-economic-groups/en/.
18
T. M. Therneau, B. Atkinson, B. Ripley, R Package ‘rpart’ version 4.1-13 (2018); http://cran.r-project.org/web/packages/rpart/rpart.pdf.
19
NASA Earth Observation Data: Active Fire Data; https://earthdata.nasa.gov/earth-observation-data/near-real-time/firms/active-fire-data.
20
M. N. Tuanmu, W. Jetz, A global 1-km consensus land-cover product for biodiversity and ecosystem modeling. Glob. Ecol. Biogeogr. 23, 1031–1045 (2014).
21
Center for International Earth Science Information Network (CIESIN), Documentation for the Gridded Population of the World, Version 4 (GPWv4), Revision 10 Data Sets (NASA Socioeconomic Data and Applications Center, 2017); https://doi.org/10.7927/H4PG1PPM.
22
W. G. Cochran, in Sampling Techniques (Wiley, ed. 3, 1977), pp. 150–188.
23
I. D. Thompson, M. R. Guariguata, K. Okabe, C. Bahamondez, R. Nasi, V. Heymell, C. Sabogal, An operational framework for defining and monitoring forest degradation. Ecol. Soc. 18, 20 (2013).
24
M. Parisien, C. Miller, S. A. Parks, E. R. DeLancey, F. Robinne, M. D. Flannigan, The spatially varying influence of humans on fire probability in North America. Environ. Res. Lett. 11, 075005 (2016).
25
Global Forest Resources Assessment 2015 (Food and Agriculture Organization of the United Nations, 2017); www.fao.org/forest-resources-assessment/past-assessments/fra-2015/en/.
26
“Progress on the New York Declaration on Forests – An Assessment Framework and Initial Report: Technical Annexes. Goal 1: At least halve the rate of loss of natural forests globally by 2020 and strive to end natural forest loss by 2030.” Prepared by Climate Focus, in collaboration with Environmental Defense Fund, Forest Trends, Global Alliance for Clean Cookstoves, Global Canopy Program and The Sustainability Consortium (2015); http://forestdeclaration.org/wp-content/uploads/2015/09/FD-Goal_1-Draft-17-12-15.pdf.
27
United Nations Framework Convention on Climate Change, “Report on the Conference of the Parties on Its Seventh Session” (2002); https://unfccc.int/resource/docs/cop7/13a01.pdf.
28
D. Schoene, W. Killmann, H. von Lüpke, M. L. Wilkie, “Definitional Issues Related to Reducing Emissions from Deforestation in Developing Countries” (Food and Agriculture Organization of the United Nations, 2007); www.fao.org/docrep/009/j9345e/j9345e00.htm…/fao/009/j9345e/j9345e00.pdf.
29
G. Molinario, M. C. Hansen, P. V. Potapov, Forest cover dynamics of shifting cultivation in the Democratic Republic of Congo: A remote sensing-base assessment for 2000-2010. Environ. Res. Lett. 10, 094009 (2015).
30
A. Grainger, Difficulties in tracking the long-term global trend in tropical forest area. Proc. Natl. Acad. Sci. U.S.A. 105, 818–823 (2008).
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Published In
Science
Volume 361 | Issue 6407
14 September 2018
14 September 2018
Copyright
Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
This is an article distributed under the terms of the Science Journals Default License.
Submission history
Received: 31 May 2018
Accepted: 14 August 2018
Published in print: 14 September 2018
Acknowledgments
We thank M. Maier, A. Chao, M. Millstein, and J. Paltseva for their contributions to this project in its early stages of development; P. V. Potapov for the tree cover loss and gain data that were so integral to this project; the members of The Sustainability Consortium for their financial support; and L. Goldman for her cartographic assistance in creating figures for the paper and for calculating map-based summary statistics. Funding: This project was funded by The Sustainability Consortium. The World Resources Institute provided additional resources to the project. Author contributions: P.G.C.: conceptualization, formal analysis, methodology, validation, visualization, and writing; C.M.S.: conceptualization, funding acquisition, project administration, supervision, and writing; N.L.H.: methodology, resources, project administration, and writing; A.T.: methodology, validation, and writing; M.C.H.: writing. Competing interests: Authors declare no competing interests. Data and materials availability: All data are available in the main text or the supplementary materials.
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