Human and environmental controls over aboveground carbon storage in Madagascar

Carbon Balance and Management

David E Knapp³  Matthew S Colgan³  Léna Maatoug³  Ty Kennedy-Bowdoin³  Aravindh Balaji³  Maminiaina Rasamoelina⁴  Ghislain Vieilledent¹  K Dana Chadwick³  Romuald Vaudry²  Joseph Mascaro³  John K Clark³  Gregory P Asner³ 

[1] CIRAD, UR105 Forest Ecosystem Goods and Services, TA C-105/D, Campus de Baillarguet, 34398 Montpellier Cedex 5, France & DRP Forêt et Biodiversité, BP 853, Antananarivo, Madagascar;GoodPlanet Foundation, Carrefour de Longchamp, 75116 Paris, France;Department of Global Ecology, Carnegie Institution for Science, 260 Panama Street, Stanford, CA USA;World Wide Fund for Nature, BP 738, Antananarivo, Madagascar

关键词: tropical forest;    REDD;    LiDAR;    CLASlite;    Carnegie Airborne Observatory;    carbon stocks;    biomass;    aboveground carbon density;   

Others  :  792441
DOI  :  10.1186/1750-0680-7-2

 received in 2011-11-02, accepted in 2012-01-30,  发布年份 2012

【 摘 要 】

Background

Accurate, high-resolution mapping of aboveground carbon density (ACD, Mg C ha^-1) could provide insight into human and environmental controls over ecosystem state and functioning, and could support conservation and climate policy development. However, mapping ACD has proven challenging, particularly in spatially complex regions harboring a mosaic of land use activities, or in remote montane areas that are difficult to access and poorly understood ecologically. Using a combination of field measurements, airborne Light Detection and Ranging (LiDAR) and satellite data, we present the first large-scale, high-resolution estimates of aboveground carbon stocks in Madagascar.

Results

We found that elevation and the fraction of photosynthetic vegetation (PV) cover, analyzed throughout forests of widely varying structure and condition, account for 27-67% of the spatial variation in ACD. This finding facilitated spatial extrapolation of LiDAR-based carbon estimates to a total of 2,372,680 ha using satellite data. Remote, humid sub-montane forests harbored the highest carbon densities, while ACD was suppressed in dry spiny forests and in montane humid ecosystems, as well as in most lowland areas with heightened human activity. Independent of human activity, aboveground carbon stocks were subject to strong physiographic controls expressed through variation in tropical forest canopy structure measured using airborne LiDAR.

Conclusions

High-resolution mapping of carbon stocks is possible in remote regions, with or without human activity, and thus carbon monitoring can be brought to highly endangered Malagasy forests as a climate-change mitigation and biological conservation strategy.

【 授权许可】

   
2012 Asner et al; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

Figure 9.

【 参考文献 】

• [1]Angelsen A: Moving Ahead with REDD: issues, options and implications. Bogor, Indonesia: Center for International Forestry Research (CIFOR); 2008.
• [2]Pelletier J, Ramankutty N, Potvin C: Diagnosing the uncertainty and detectability of emission reductions for REDD + under current capabilities: an example for Panama. Environmental Research Letters 2011, 6:024005.
• [3]Asner GP: Painting the world REDD: addressing scientific barriers to monitoring emissions from tropical forests. Environmental Research Letters 2011, 6:021002.
• [4]Avitabile V, Herold M, Henry M, Schmullius C: Mapping biomass with remote sensing: a comparison of methods for the case study of Uganda. Carbon Balance and Management 2011, 6:7. BioMed Central Full Text
• [5]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 Balance and Management 2009., 4doi:10.1186/1750-0680-1184-1182
• [6]Asner GP, Rudel TK, Aide TM, Defries R, Emerson RE: A Contemporary Assessment of Change in Humid Tropical Forests. Conservation Biology 2009, 23:1386-1395.
• [7]Brown KA, Gurevitch J: Long-term impacts of logging on forest diversity in Madagascar. Proceedings of the National Academy of Sciences 2004, 101:6045-6049.
• [8]Green GM, Sussman RW: Deforestation history of the eastern rain forests of Madagascar from satellite images. Science 1990, 248:212-215.
• [9]Harper GJ, Steininger MK, Tucker CJ, Juhn D, Hawkins F: Fifty years of deforestation and forest fragmentation in Madagascar. Environmental Conservation 2007, 34:325-333.
• [10]Ingram JC, Dawson TP, Whittaker RJ: Mapping tropical forest structure in southeastern Madagascar using remote sensing and artificial neural networks. Remote Sensing of Environment 2005, 94:491-507.
• [11]Gonzalez P, Asner GP, Battles JJ, Lefsky MA, Waring KM, Palace M: Forest carbon densities and uncertainties from Lidar, QuickBird, and field measurements in California. Remote Sensing of Environment 2010, 114:1561-1575.
• [12]Lefsky MA, Cohen WB, Harding DJ, Parker GG, Acker SA, Gower ST: Lidar remote sensing of above-ground biomass in three biomes. Global Ecology and Biogeography 2002, 11:393-399.
• [13]Drake JB, Dubayah RO, Clark DB, Knox RG, Blair JB, Hofton MA, Chazdon RL, Weishampel JF, Prince SD: Estimation of tropical forest structural characteristics using large-footprint lidar. Remote Sensing of Environment 2002, 79:305-319.
• [14]Mascaro J, Detto M, Asner GP, Muller-Landau HC: Evaluating uncertainty in mapping forest carbon with airborne LiDAR. Remote Sensing of Environment 2011, 115:3770-3774.
• [15]Asner GP: Tropical forest carbon assessment: integrating satellite and airborne mapping approaches. Environmental Research Letters 2009, 3:1748-9326.
• [16]Helmer EH, Lefsky MA, Roberts DA: Biomass accumulation rates of Amazonian secondary forest and biomass of old-growth forests from Landsat time series and the Geoscience Laser Altimeter System. Journal of Applied Remote Sensing 2009, 3:033505.
• [17]Asner GP, Powell GVN, Mascaro J, Knapp DE, Clark JK, Jacobson J, Kennedy-Bowdoin T, Balaji A, Paez-Acosta G, Victoria E, Secada L, Valqui M, Hughes RF: High-resolution forest carbon stocks and emissions in the Amazon. Proceedings of the National Academy of Sciences 2010, 107:16738-16742.
• [18]Herold M, Skutsch M: Monitoring, reporting and verification for national REDD + programmes: two proposals. Environmental Research Letters 2011, 6:014002.
• [19]Du Puy D, Moat J: A refined classification of the primary vegetation of Madagascar based on the underlying geology: Using GIS to map its distribution and to assess its conservation status. Edited by Lourenco WR. Editions de l'ORSTOM - Paris; 1996:205-218. Proceedings of the International Symposium on the Biogeography of Madagascar; September 1995; Paris
• [20]Justice CO, Vermote E, Townshend JRG, DeFries R, Roy DP, Hall DK, Salomonson VV, Privette JL, Riggs G, Strahler A, Lucht W, Myneni RB, Knyazikhin Y, Running SW, Nemani RR, Wan Z, Huete AR, Leeuwen Wv, Wolfe RE, Giglio L, Muller J-P, Lewis P, Barnsley MJ: The Moderate Resolution Imaging Spectroradiometer (MODIS): Land remote sensing for global change research. Geoscience and Remote Sensing 1998, 36:1212-1227.
• [21]Saatchi SS, Harris NL, Brown S, Lefsky M, Mitchard ETA, Salas W, Zutta BR, Buermann W, Lewis SL, Hagen S, Petrova S, White L, Silman M, Morel A: Benchmark map of forest carbon stocks in tropical regions across three continents. Proceedings of the National Academy of Sciences 2011, 108:9899-9904.
• [22]Ranson KJ, Sun G, Weishampel JF, Knox RG: Forest biomass from combined ecosystem and radar backscatter modeling. Remote Sensing of Environment 1997, 59:118-133.
• [23]Luckman A, Baker J, Kuplich TM, Yanasse CDF, Frery AC: A study of the relationship between radar backscatter and regenerating tropical forest biomass for spaceborne SAR instruments. Remote Sensing of Environment 1997, 60:1-13.
• [24]Kasischke ES, Melack JM, Dobson MC: The use of imaging radars for ecological applications - a review. Remote Sensing of Environment 1997, 59:141-156.
• [25]Clark DB, Clark DA: Landscape-scale variation in forest structure and biomass in a tropical rain forest. Forest Ecology and Management 2000, 137:185-198.
• [26]Saatchi SS, Houghton RA, Dos Santos Alvala RC, Soares JV, Yu Y: Distribution of aboveground live biomass in the Amazon basin. Global Change Biology 2007, 13:816-837.
• [27]Asner GP, Mascaro J, Muller-Landau HC, Vieilledent G, Vaudry R, Rasamoelina M, Hall J, van Breugal M: A universal airborne LiDAR approach for tropical forest carbon mapping. Oecologia 2011. doi:10.1007/s00442-011-2165-z
• [28]Mascaro J, Asner GP, Muller-Landau HC, van Breugal M, Hall J, Dahlin K: Controls over aboveground forest carbon density on Barro Colorado Island, Panama. Biogeosciences 2011, 8:1615-1629.
• [29]Drake JB, Knox RG, Dubayah RO, Clark DB, Condit R, Blair JB, Hofton M: Aboveground biomass estimation in closed canopy neotropical forests using lidar remote sensing: Factors affecting the generality of relationships. Global Ecology and Biogeography 2003, 12:147-159.
• [30]Keller M, Palace M, Hurtt G: Biomass estimation in the Tapajos National Forest, Brazil: examination of sampling and allometric uncertainties. Forest Ecology and Management 2001, 154:371-382.
• [31]Chave J, Chust G, Condit R, Aguilar S, Hernandez A, Lao S, Perez R: Error propagation and scaling for tropical forest biomass estimates. In Tropical forests and global atmospheric change. Edited by Malhi Y, Phillips O. London: Oxford University Press; 2004:155-166.
• [32]Mueller-Dombois D, Fosberg RF: Vegetation of the tropical Pacific islands. New York: Springer-verlag; 1998.
• [33]Allnutt TF, Ferrier S, Manion G, Powell GVN, Ricketts TH, Fisher BL, Harper GJ, Irwin ME, Kremen C, Labat J-N, Lees DC, Pearce TA, Rakotondrainibe F: A method for quantifying biodiversity loss and its application to a 50-year record of deforestation across Madagascar. Conservation Letters 2008, 1:173-181.
• [34]Gade DW: Deforestation and Its Effects in Highland Madagascar. Mountain Research and Development 1996, 16:101-116.
• [35]Baccini A, Laporte N, Goetz SJ, Sun M, Dong H: A first map of tropical Africa's above-ground biomass derived from satellite imagery. Environmental Research Letters 2008, 3:045011.
• [36]Asner GP, Knapp DE, Balaji A, Paez-Acosta G: Automated mapping of tropical deforestation and forest degradation: CLASlite. Journal of Applied Remote Sensing 2009, 3:033543.
• [37]Asner GP, Knapp DE, Kennedy-Bowdoin T, Jones MO, Martin RE, Boardman J, Field CB: Carnegie Airborne Observatory: In-flight fusion of hyperspectral imaging and waveform light detection and ranging (LiDAR) for three-dimensional studies of ecosystems. Journal of Applied Remote Sensing 2007., 1DOI:10-.1117/1111.2794018
• [38]Chave J, Andalo C, Brown S, Cairns MA, Chambers JQ, Eamus D, Fölster H, Fromard F, Higuchi N, Puig H, Riéra B, Yamakura T: Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 2005, 145:87-99.
• [39]Vieilledent G, Vaudry R, Andriamanohisoa SFD, Rakotonarivo OS, Randrianasolo HZ, Razafindrabe HN, Bidaud Rakotoarivony C, Ebeling J, Rasamoelina M: A universal approach to estimating biomass and carbon stock in tropical forests using generic allometric models. Ecological Applications 2011. doi:http://dx.doi.org/10.1890/11-0039-.1 webcite.
• [40]Popescu SC, Wynne RH, Scrivani JA: Fusion of small-footprint lidar and multispectral data to estimate plot-level volume and biomass in deciduous and pine forests in Virginia, USA. Forest Science 2004, 50:551-565.
• [41]Drake JB, Dubayah RO, Knox RG, Clark DB, Blair JB: Sensitivity of large-footprint lidar to canopy structure and biomass in a neotropical rainforest. Remote Sensing of Environment 2002, 81:378-392.
• [42]Lefsky MA, Cohen WB, Acker SA, Parker GG, Spies TA, Harding D: Lidar remote sensing of the canopy structure and biophysical properties of Douglas-fir western hemlock forests. Remote Sensing of Environment 1999, 70:339-361.
• [43]Lefsky MA, Cohen WB, Parker GG, Harding DJ: Lidar remote sensing for ecosystem studies. BioScience 2002, 52:19-30.
• [44]Asner GP, Hughes RF, Varga TA, Knapp DE, Kennedy-Bowdoin T: Environmental and biotic controls over aboveground biomass throughout a tropical rain forest. Ecosystems 2009, 12:261-278.
• [45]Baskerville G: Use of logarithmic regression in the estimation of plant biomass. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 1972, 2:49-53.