Abstract
Classical allometries determine biomass from measurements of diameter at breast height or volume. Neither of these measurements is currently possible to be derived directly from remote sensing. As biomass estimates at larger scales require remotely sensed data, new allometric relations are required using crown area and/or tree height as predictor of biomass, which can both be derived from remote sensing. Allometric equations were developed from 72 trees semi-randomly selected for destructive sampling in three 100 km2 sentry sites in western Kenya. The equations developed fit the data well with about 85 % of the observed variation in aboveground biomass explained by crown area. Addition of height and wood density as second predictor variables improved model fit by 6 and 2 % and lowered the relative error by 7 and 2 %, respectively. The equation with crown area in combination with height and wood density estimated representative aboveground biomass carbon to be about 20.8 ± 0.02 t C ha−1; which is about 19 % more than the amount estimated using an allometry with diameter at breast height as predictor. These results form the basis for a new generation of allometries using crown area as a predictor of aboveground biomass in agricultural landscapes. Biomass predictions using crown area should be supported by height and wood density and the application of crown area equations for remote sensing based up-scaling should consider crown interactions with competing or coexisting neighboring trees.
Similar content being viewed by others
References
Bar Massada A, Carmel Y, Even Tzur G, Grünzweig JM, Yakir D (2006) Assessment of temporal changes in aboveground forest tree biomass using aerial photographs and allometric equations. Can J For Res 36:2585–2594
Baskerville GL (1972) Use of logarithmic regression in the estimation of plant biomass. Can J For Res 2(1):49–53
Basuki TM, van Laake PE, Skidmore AK, Hussin YA (2009) Allometric equations for estimating the above-ground biomass in tropical lowland Dipterocarp forests. For Ecol Manag 257:1684–1694
Bergen KM, Dobson MC (1999) Integration of remotely sensed radar imagery in modeling and mapping of forest biomass and net primary production. Ecol Model 122:257–274
Brown S (1997) Estimating biomass and biomass change of tropical forests: a primer. FAO forestry paper-134, FAO, Rome
Brown S (2002) Measuring carbon in forests: current status and future challenges. Environ Pollut 116:363–372
Chave J, Andalo C, Brown S, Cairns MA, Chambers JQ, Eamus D, Fölster H, Fromard F, Higuchi N, Kira T, Lescure J-P, Nelson BW, Ogawa H, Puig H, Riéra B, Yamakura T (2005) Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145(1):78–99
Drake JB, Dubayah RO, Clark DB, Knox RG, Blair JB, Hofton MA, Chazdon RL, Weishampel JF, Prince S (2002) Estimation of tropical forest structural characteristics using large-footprint lidar. Remote Sens of Environ 79:305–319
Drake JB, Knox RG, Dubayah RO, Clark DB, Condit R, Blair JB, Hofton M (2003) Above-ground biomass estimation in closed canopy neotropical forests using lidar remote sensing: factors affecting the generality of relationships. Glob Ecol Biogeogr 12:147–159
Gibbs HK, Brown S, Niles JO, Foley JA (2007) Monitoring and estimating tropical forest carbon stocks: making REDD a reality. Environ Res Lett 2(4):1–13. doi:10.1088/1748-9326/2/4/045023
Halpern CB, Miller EA, Geyer MA (1996) Equations for predicting aboveground biomass of plant species in early successional forests of the western Cascade range, Oregon. Northwest Sci 70:306–320
Jaetzold R, Schmidt H (1982) Farm management handbook of Kenya. Natural conditions and farm management information, vol 2. Ministry of Agriculture, Kenya, pp 137–370
Ketterings QM, Coe R, van Noordwijk M, Ambagau Y, Palm CA (2001) Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests. For Ecol Manag 146:199–209
Kuyah S, Dietz J, Muthuri C, Jamnadass R, Mwangi P, Coe R, Neufeldt H (2012) Allometric equations for estimating biomass carbon in agricultural landscapes: I. aboveground biomass. Agri Ecosyst Environ. doi:10.1016/j.agee.2012.05.011
Myeong S, Nowak DJ, Duggin MJ (2006) A temporal analysis of urban forest carbon storage using remote sensing. Remote Sens Environ 101:277–282
O’Brien ST, Hubbell SP, Spiro P, Condit R, Foster RB (1995) Diameter, height, crown, and age relationship in eight neotropical tree species. Ecology 76(6):1926–1939
Peek JM (1970) Relation of canopy area and volume to production of three woody species. Ecology 51:1098–1101
Sah JP, Ross MS, Koptur S, Snyder JR (2004) Estimating aboveground biomass of broadleaved woody plants in the understory of Florida keys pine forests. For Ecol Manag 203:319–329
Sampaio EVS, Silva GC (2005) Biomass equations for Brazilian semiarid Caatinga plants. Acta Bot Brasilica 19(4):935–943
Segura M (2005) Allometric models for tree volume and total aboveground biomass in a tropical humid forest in Costa Rica1. Biotropica 37(1):2–8
Shepherd KD, Soule MJ (1998) Soil fertility management in west Kenya: dynamic simulation of productivity, profitability and sustainability at different resource endowment levels. Agric Ecosyst Environ 71:131–145
Sprugel DG (1983) Correcting for error in log-transformed allometric equations. Ecology 64(1):209–210
Velarde SJ, Ugarte-Guerra J, Tito MR, Capella JL, Sandoval M, Hyman G, Castro A, Marín JA, Barona E (2010) Reducing emissions from all land uses in Peru. Final National Report ASB partnership for the tropical forest margins, Nairobi, Kenya
Verbist B, Van Goidsenhoven M, Dewulf R, Muys B (2011) Reducing emissions from deforestation and degradation. KLIMOS working paper 3, KLIMOS, Leuven, Belgium
Wulder MA, White JC, Fournier RA, Luther JE, Magnussen S (2008) Spatially explicit large area biomass estimation: three approaches using forest inventory and remotely sensed imagery in a GIS. Sensors 8:529–560
Acknowledgments
This work was carried out within the Carbon Benefits Project and was supported by a grant from the Global Environment Facility. We would like to thank ICRAF Kisumu Technical staff, Tom Ochinga, Joash Mango, Walter Adongo, and Peter Okoth for helping with data collection and farmers who permitted their trees to be harvested.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Kuyah, S., Muthuri, C., Jamnadass, R. et al. Crown area allometries for estimation of aboveground tree biomass in agricultural landscapes of western Kenya. Agroforest Syst 86, 267–277 (2012). https://doi.org/10.1007/s10457-012-9529-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10457-012-9529-1