New models for estimating the carbon sink capacity of Spanish softwood species

Ricardo Ruiz-Peinado, Miren del Rio, Gregorio Montero


Quantifying the carbon balance in forests is one of the main challenges in forest management. Forest carbon stocks are usually estimated indirectly through biomass equations applied to forest inventories, frequently considering different tree biomass components. The aim of this study is to develop systems of equations for predicting tree biomass components for the main forest softwood species in Spain: Abies alba Mill., A. pinsapo Boiss., Juniperus thurifera L., Pinus canariensis Sweet ex Spreng., P. halepensis Mill., P. nigra Arn., P. pinaster Ait., P. pinea L., P. sylvestris L., P. uncinata Mill. For each species, a system of additive biomass models was fitted using seemingly unrelated regression. Diameter at the breast height and total height were used as independent variables. Diameter appears in all component models, while tree height was included in the stem component model of all species and in some branch component equations. Total height was included in order to improve biomass estimations at different sites. These biomass models were compared to previously available equations in order to test their accuracy and it was found that they yielded better fitting statistics in all cases. Moreover, the models fulfil the additivity property. We also developed root:shoot ratios in order to determine the partitioning into aboveground and belowground biomass. A number of differences were found between species, with a minimum of 0.183 for A. alba and a maximum of 0.385 for P. uncinata. The mean value for the softwood species studied was 0.265. Since the Spanish National Forest Inventory (NFI) records species, tree diameter and height of sample trees, these biomass models and ratios can be used to accurately estimate carbon stocks from NFI data.

Full Text:



Akaike H., 1974. A new look at the statistical model identification. IEEE Transactions on Automatic Control 19, 716-723.

Antonio N., Tomé M., Tomé J., Soares P., Fontes L., 2007. Effect of the tree, stand and site variables of the allometry of Eucalyptus globulus tree biomass. Can J For Res 37, 895-906.

Balboa-Murias M.A., Rodríguez-Soalleiro R., Merino A., Álvarez-González J.G., 2006. Temporal variations and distribution of carbon stocks in aboveground biomass of radiata pine and maritime pine pure stands under different silvicultural alternatives. For Ecol Manage 237, 29-38.

Bi H.Q., Turner J., Lambert M.J., 2004. Additive biomass equations for native eucalypt forest trees of temperate Australia. Trees-Struct Funct 18, 467-479.

Bravo F., Bravo-Oviedo A., Díaz Balteiro L., 2008. Carbon sequestration in Spanish Mediterranean forest under two management alternatives: a modeling approach. Eur J Forest Res 127, 225-234.

Brown S., 2002. Measuring carbon in forests: current status and future challenges. Environmental Pollution 116, 363-372.

Cabanettes A., Rapp M., 1978. Biomass, nutrient distribution and productivity in a Pinus pinea forest.1. Biomass. Oecologia Plantarum 13, 271-286.

Cairns M.A., Brown S., Helmer E.H., Baumgardner G.A., 1997. Root biomass allocation in the world's upland forests. Oecologia 111, 1-11.

Cannell M.G.R., 1982. World forest biomass and primary production data. Academic Press, London. 391 pp. PMCid:2494121

Carvalho J.P., Parresol B.R., 2003. Additivity in tree biomass components of Pyrenean oak (Quercus pyrenaica Willd.). For Ecol Manage 179, 269-276.

Cienciala E., Cerny M., Tatarinov F., Apltauer J., Exnerova Z., 2006. Biomass functions applicable to Scots pine. Trees-Struct Funct 20, 483-495.

Clark D.A., Brown S., Kicklighter D.W., Chambers J.Q., Thomlinson J.R., NI J., 2001. Measuring net primary production in forests: concepts and field methods. Ecological Applications 11, 356-370.[0356:MNPPIF]2.0.CO;2

Cole T.G., Ewel J.J., 2006. Allometric equations for four valuable tropical tree species. For Ecol Manage 229, 351-360.

Correia A.C., Tomé M., Pacheco C.A., Faias S., Dias A.C., Freire J., Carvalho P.O., Pereira J.S., 2010. Biomass allometry and carbon factors for a Mediterranean pine (Pinus pinea L.) in Portugal. Forest Systems 19, 418-433.

Crow T.R., Laidly P.R., 1980. Alternative models for estimating woody plant biomass. Can J For Res 10, 367-370.

Dixon R.K., Brown S., Houghton R.A., Solomon A.M., Trexler M.C., Wisniewski J., 1994. Carbon pools and flux of global forest ecosystem. Science 263, 185-190. PMid:17839174

Drexhage M., Colin F., 2001. Estimating root system biomass from breast-height diameters. Forestry 74, 491-497.

Fang J.Y., Chen A.P., Peng C.H., Zhao S.Q., Ci L., 2001. Changes in forest biomass carbon storage in China between 1949 and 1998. Science 292, 2320-2322. PMid:11423660

Fattorini L., Gasparini P., Nocetti M., Tabacchi G., To V., 2004. Above-ground tree phytomass prediction and preliminary shrub phytomass assessment in the forest stands of Trentino. Studi Trent. Sci Nat, Acta Biol 81, 75-121.

Gadow K.V., Real P., Álvarez González J.G. (eds), 2001. Modelización del crecimiento y la evolución de bosques. IUFRO, Vienna.

Goodale C.L., Apps M.J., Birdsey R.A., Field C.B., Heath L.S., Houghton R.A., Jenkins J.C., Kohlmaier G.H., Kurz W., Liu S.R., Nabuurs G.J., Nilsson S., Shvidenko A.Z., 2002. Forest carbon sinks in the Northern Hemisphere. Ecological Applications 12, 891-899.[0891:FCSITN]2.0.CO;2

Grunzweig J.M., Gelfand I., Fried Y., Yakir D., 2007. Biogeochemical factors contributing to enhanced carbon storage following afforestation of a semi-arid shrubland. Biogeosciences 4, 891-904.

Gutiérrez Oliva A., Plaza Pulgar F., 1967. Características físico-mecánicas de las maderas españolas. Ministerio de Agricultura, Madrid. 103 pp.

IPCC, 2003. Good practice guidance for land use, land-use change and forestry. Institute for Global Environmental Strategies, Kanagawa, Japan.

Ketterings Q.M., Coe R., Van Noordwijk V., Ambagau Y., Palm C.A., 2001. Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests. For Ecol Manage 146, 199-209.

Kozak A., 1970. Methods for ensuring additivity of biomass components by regression analysis. Forestry Chronicle 46, 402-404.

Kurz W., Beukema S., Apps M., 1996. Estimation of root biomass and dynamics for the carbon budget model of the Canadian forest sector Can J For Res 26, 1973-1979.

Lambert M.C., Ung C.H., Raulier F., 2005. Canadian national tree aboveground biomass equations. Can J For Res 35, 1996-2018.

Le Goff N., Ottorini J.M., 2001. Root biomass and biomass increment in a beech (Fagus sylvatica L.) stand in North-East France. Ann For Sci 58, 1-13.

Lehtonen A., Cienciala E., Tatarinov F., Makipaa R., 2007. Uncertainty estimation of biomass expansion factors for Norway spruce in the Czech Republic. Ann For Sci 64, 133-140.

Lehtonen A., Makipaa R., Heikkinen J., Sievanen R., Liski J., 2004. Biomass expansion factors (BEFs) for Scots pine, Norway spruce and birch according to stand age for boreal forests. For Ecol Manage 188, 211-224.

Lemoine B., Gelpe J., Ranger J., Nys C., 1986. Biomass and growth of maritime pine - a study of variability in a 16 years old stand. Ann Sci For 43, 67-84.

Levy P.E., Hale S.E., Nicoll B.C., 2004. Biomass expansion factors and root:shoot ratios for coniferous tree species in Great Britain. Forestry 77, 421-430.

Marklund L.G., 1988. Biomass functions for pine, spruce and birch in Sweden. Rapport-Sveriges Lantbruksuniversitet, Institutionen foer Skogstaxering (Sweden).

MARM, 2008. Anuario de Estadísticas Forestales 2007 [online]. Ministerio de Medio Ambiente y Medio Rural y Marino). Available in [15 July, 2010].

Mokany K., Raison R.J., Prokushkin A.S., 2006. Critical analysis of root:shoot ratios in terrestrial biomes. Glob Change Biol 12, 84-96.

Montero G., Ortega C., Cañellas I., Bachiller A., 1999. Productividad aérea y dinámica de nutrientes en una población de Pinus pinaster Ait. sometida a distintos regímenes de claras. Invest Agrar: Sist Recur For Fuera de Serie, 175-206.

Montero G., Ruiz-Peinado R., Muñoz M., 2005. Producción de biomasa y fijación de CO2 por los bosques españoles. Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Ministerio de Educación y Ciencia, Madrid. 270 pp.

Montes N., Bertaudiere-Montes V., Badri W., Zaoui E.H., Gauquelin T., 2002. Biomass and nutrient content of a semi-arid mountain ecosystem: the Juniperus thurifera L. woodland fo Azzaden Valley (Morocco). For Ecol Manage 166, 35-43.

Montes N., Gauquelin T., Badri W., Bertaudiere V., Zaoui E.H., 2000. A non-destructive method for estimating aboveground forest biomass in threatened woodlands. For Ecol Manage 130, 37-46.

Muukkonen P., 2007. Generalized allometric volume and biomass equations for some tree species in Europe. Eur J Forest Res 126, 157-166.

Myers R.H., 1990. Classical and modern regression with applications. Duxbury Press Belmont, Calif. 488 pp.

Návar J., 2009. Allometric equations for tree species and carbon stocks for forests of northwestern Mexico. For Ecol Manage. 257, 427-434.

Neirynck J., Maddelein D., Keersmaeker L.D., Lust N., Muys B., 1998. Biomass and nutrient cycling of a highly productive Corsican pine stand on former heathland in northern Belgium. Ann For Sci 55, 389-405.

Pardé J., 1980. Forest biomass. Forestry Abstracts 41, 343-363.

Parresol B.R., 1999. Assessing tree and stand biomass: a review with examples and critical comparisons. For Sci 45, 573-593.

Parresol B.R., 2001. Additivity of nonlinear biomass equations. Can J For Res 31, 865-878.

Pastor J., Aber J.D., Melillo J.M., 1983/1984. Biomass prediction using generalized allometric regressions for some northeast tree species. For Ecol Manage 7, 265-274.

Porte A., Trichet P., Bert D., Loustau D., 2002. Allometric relationships for branch and tree woody biomass of Maritime pine (Pinus pinaster Ait.). For Ecol Manage 158, 71-83.

SAS Institute INC, 2004. SAS/ETS(R) 9.1 User's guide. In SAS Institute Inc, Cary, NC.

Scarascia-Mugnozza G., Oswald H., Piussi P., Radoglou K., 2000. Forests of the Mediterranean region: gaps in knowledge and research needs. For Ecol Manage 132, 97-109.

Schlamadinger B., Marland G., 1996. The role of forest and bioenergy strategies in the global carbon cycle. Biomass & Bioenergy 10, 275-300.

Schroeder P.E., Brown S., Mo J., Birdsey R.A., Cieszewski C., 1997. Biomass estimation for temperate broadleaf forest of the United States using inventory data. For Sci 43, 424-434.

Wirth C., Schumacher J., Schulze E.D., 2004. Generic biomass functions for Norway spruce in Central Europe - a meta-analysis approach toward prediction and uncertainty estimation. Tree Physiol 24, 121-139. PMid:14676030

Zellner A., 1962. An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. J Am Stat Assoc, 348-368.

DOI: 10.5424/fs/2011201-11643