期刊论文详细信息
Carbon Balance and Management
Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps
Sandra Brown1  Nancy L Harris1  Scott J Goetz2  Gregory P Asner5  Alessandro Baccini2  Sassan S Saatchi3  Edward TA Mitchard4 
[1] Ecosystem Services Unit, Winrock International, 2121 Crystal Drive, Suite 500, Arlington, VA 22202, USA;Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA 02540-1644, USA;Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA;School of GeoSciences, University of Edinburgh, Crew Building, The King’s Buildings, Edinburgh EH9 3JN, UK;Department of Global Ecology, Carnegie Institution for Science, 260 Panama Street, Stanford, CA 94305, USA
关键词: UNFCCC;    Tropical forests;    Remote sensing;    REDD+;    REDD;    Random forest;    Maxent;    Data inter-comparison;    Carbon;    Aboveground biomass;   
Others  :  790577
DOI  :  10.1186/1750-0680-8-10
 received in 2013-07-01, accepted in 2013-10-17,  发布年份 2013
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【 摘 要 】

Background

Mapping the aboveground biomass of tropical forests is essential both for implementing conservation policy and reducing uncertainties in the global carbon cycle. Two medium resolution (500 m – 1000 m) pantropical maps of vegetation biomass have been recently published, and have been widely used by sub-national and national-level activities in relation to Reducing Emissions from Deforestation and forest Degradation (REDD+). Both maps use similar input data layers, and are driven by the same spaceborne LiDAR dataset providing systematic forest height and canopy structure estimates, but use different ground datasets for calibration and different spatial modelling methodologies. Here, we compare these two maps to each other, to the FAO’s Forest Resource Assessment (FRA) 2010 country-level data, and to a high resolution (100 m) biomass map generated for a portion of the Colombian Amazon.

Results

We find substantial differences between the two maps, in particular in central Amazonia, the Congo basin, the south of Papua New Guinea, the Miombo woodlands of Africa, and the dry forests and savannas of South America. There is little consistency in the direction of the difference. However, when the maps are aggregated to the country or biome scale there is greater agreement, with differences cancelling out to a certain extent. When comparing country level biomass stocks, the two maps agree with each other to a much greater extent than to the FRA 2010 estimates. In the Colombian Amazon, both pantropical maps estimate higher biomass than the independent high resolution map, but show a similar spatial distribution of this biomass.

Conclusions

Biomass mapping has progressed enormously over the past decade, to the stage where we can produce globally consistent maps of aboveground biomass. We show that there are still large uncertainties in these maps, in particular in areas with little field data. However, when used at a regional scale, different maps appear to converge, suggesting we can provide reasonable stock estimates when aggregated over large regions. Therefore we believe the largest uncertainties for REDD+ activities relate to the spatial distribution of biomass and to the spatial pattern of forest cover change, rather than to total globally or nationally summed carbon density.

【 授权许可】

   
2013 Mitchard et al.; licensee BioMed Central Ltd.

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【 参考文献 】
  • [1]van der Werf GR, Morton DC, DeFries RS, Olivier JGJ, Kasibhatla PS, Jackson RB, Collatz GJ, Randerson JT: CO2 emissions from forest loss. Nat Geosci 2009, 2:737-738.
  • [2]Pan Y, Birdsey RA, Fang J, Houghton R, Kauppi PE, Kurz WA, Phillips OL, Shvidenko A, Lewis SL, Canadell JG, et al.: A large and persistent carbon sink in the World’s forests. Science 2011, 333:988-993.
  • [3]Harris NL, Brown S, Hagen SC, Saatchi SS, Petrova S, Salas W, Hansen MC, Potapov PV, Lotsch A: Baseline Map of carbon emissions from deforestation in tropical regions. Science 2012, 336:1573-1576.
  • [4]Laurance WF: Can carbon trading save vanishing forests? Bioscience 2008, 58:286-287.
  • [5]UNFCCC: Appendix 1: Guidance and safeguards for policy approaches and positive incentives on issues relating to reducing emissions from deforestation and forest degradation in developing countries; and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries. The Cancun Agreements: Outcome of the work of the Ad Hoc Working Group on Long-term Cooperative Action under the Convention 2010, 26-27. FCCC/CP/2010/7/Add1. http://unfccc.int/documentation/documents/advanced_search/items/6911.php?priref=600006173 webcite
  • [6]Clements GR, Sayer J, Boedhihartono AK, Venter O, Lovejoy T, Koh LP, Laurance WF: Cautious optimism over Norway-Indonesia REDD pact. Conserv Biol 2010, 24:1437-1438.
  • [7]Caravani A, Nakhooda S, Watson C: The Evolving Global Climate Finance Architecture. Heinrich Boll Stiftung: Overseas Development Institute; 2012.
  • [8]Diaz D, Hamilton K, Johnson E: State of the forest carbon markets 2011. Forest Trends 2011. http://www.forest-trends.org/publication_details.php?publicationID=2963 webcite
  • [9]GOFC-GOLD: A sourcebook of methods and procedures for monitoring and reporting anthropogenic greenhouse gas emissions and removals caused by deforestation, gains and losses of carbon stocks in forests, remaining forests, and forestation. 2009. Version COP15-1 edition. Available at: http://www.gofcgold.wur.nl/redd/ webcite
  • [10]Woodhouse IH, Mitchard ETA, Brolly M, Maniatis D, Ryan CM: Radar backscatter is not a 'direct measure' of forest biomass. Nature Clim Change 2012, 2:556-557.
  • [11]Lu DS: The potential and challenge of remote sensing-based biomass estimation. Int J Rem Sens 2006, 27:1297-1328.
  • [12]Saatchi S, Ulander L, Williams M, Quegan S, LeToan T, Shugart H, Chave J: Forest biomass and the science of inventory from space. Nature Clim Change 2012, 2:826-827.
  • [13]Clark DB, Kellner JR: Tropical forest biomass estimation and the fallacy of misplaced concreteness. J Veget Sci 2012, 23:1191-1196.
  • [14]Goetz S, Baccini A, Laporte N, Johns T, Walker W, Kellndorfer J, Houghton R, Sun M: Mapping and monitoring carbon stocks with satellite observations: a comparison of methods. Carbon Bal Manag 2009, 4:2. BioMed Central Full Text
  • [15]Saatchi SS, Harris NL, Brown S, Lefsky M, Mitchard ETA, Salas W, Zutta BR, Buermann W, Lewis SL, Hagen S, et al.: Benchmark map of forest carbon stocks in tropical regions across three continents. Proc Natl Acad Sci 2011, 108:9899-9904.
  • [16]Baccini A, Goetz SJ, Walker WS, Laporte NT, Sun M, Sulla-Menashe D, Hackler J, Beck PSA, Dubayah R, Friedl MA, et al.: Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature Clim Change 2012, 2:182-185.
  • [17]Lefsky M: A global forest canopy height map from the moderate resolution imaging spectroradiometer and the geoscience laser altimeter system. Geophys Res Lett 2010., 37L15401
  • [18]Chave J, Andalo C, Brown S, Cairns MA, Chambers JQ, Eamus D, Folster H, Fromard F, Higuchi N, Kira T, et al.: Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 2005, 145:87-99.
  • [19]Mitchard ETA, Saatchi SS, Lewis SL, Feldpausch TR, Gerard FF, Woodhouse IH, Meir P: Comment on 'A first map of tropical Africa's above-ground biomass derived from satellite imagery'. Environ Res Lett 2011, 6:049001.
  • [20]FAO: Global Forests Resources Assessment 2010. Rome: FAO Forestry Paper; 2010:163.
  • [21]Asner GP, Clark JK, Mascaro J, Galindo García GA, Chadwick KD, Navarrete Encinales DA, Paez-Acosta G, Cabrera Montenegro E, Kennedy-Bowdoin T, Duque Á, et al.: High-resolution mapping of forest carbon stocks in the Colombian Amazon. Biogeosciences 2012, 9:2683-2696.
  • [22]Feldpausch TR, Lloyd J, Lewis SL, Brienen RJW, Gloor M, Monteagudo Mendoza A, Lopez-Gonzalez G, Banin L, Abu Salim K, Affum-Baffoe K, et al.: Tree height integrated into pantropical forest biomass estimates. Biogeosciences 2012, 9:3381-3403.
  • [23]Strobl C, Boulesteix A-L, Zeileis A, Hothorn T: Bias in random forest variable importance measures: illustrations, sources and a solution. BMC Bioinformatics 2007, 8:25. BioMed Central Full Text
  • [24]Prasad A, Iverson L, Liaw A: Newer classification and regression tree techniques: bagging and random forests for ecological prediction. Ecosystems 2006, 9:181-199.
  • [25]Phillips SJ, Dudík M: Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 2008, 31:161-175.
  • [26]Romijn E, Herold M, Kooistra L, Murdiyarso D, Verchot L: Assessing capacities of non-Annex I countries for national forest monitoring in the context of REDD+. Environ Sci Pol 2012, 19–20:33-48.
  • [27]Chave J, Condit R, Lao S, Caspersen JP, Foster RB, Hubbell SP: Spatial and temporal variation of biomass in a tropical forest: results from a large census plot in Panama. J Ecol 2003, 91:240-252.
  • [28]Bucki M, Cuypers D, Mayaux P, Achard F, Estreguil C, Grassi G: Assessing REDD+ performance of countries with low monitoring capacities: the matrix approach. Environ Res Lett 2012, 7:014031.
  • [29]Chave J, Muller-Landau HC, Baker TR, Easdale TA, Ter Steege H, Webb CO: Regional and phylogenetic variation of wood density across 2456 neotropical tree species. Ecol Appl 2006, 16:2356-2367.
  • [30]IPCC: Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press; 2007.
  • [31]IPCC: Good Practice Guidance for Land Use, Land-Use Change and Forestry. Geneva; 2003. http://www.ipcc-nggip.iges.or.jp/public/gpglulucf/gpglulucf.html webcite
  • [32]Chave J, Condit R, Aguilar S, Hernandez A, Lao S, Perez R: Error propagation and scaling for tropical forest biomass estimates. Philos Trans R Soc Lond A 2004, 359:409-420.
  • [33]Fritz S, Bartholomé E, Belward A, Hartley A, Stibig HJ, Eva H, Mayaux P, Bartalev S, Latifovic R, Kolmert S, et al.: Harmonisation, mosaicing and production of the Global Land Cover 2000 database (beta version). Brussels: European Commissions – Joint Research Centre; 2003.
  • [34]Mayaux P, Eva H, Gallego J, Strahler AH, Herold M, Agrawal S, Naumov S, De Miranda EE, Di Bella CM, Ordoyne C, et al.: Validation of the global land cover 2000 map. IEEE Trans Geosci Rem Sens 2006, 44:1728-1739.
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