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Annals of Forest Science

, Volume 66, Issue 2, pp 208–208 | Cite as

Biomass component equations for Latin American species and groups of species

  • José NávarEmail author
Original Article

Abstract

  • • Studies dealing with the estimation of biomass, site productivity and the contribution of forests to the global carbon balance require the use of allometric equations. There have been a great number of equations developed to estimate biomass components of trees and shrubs in various ecosystems. However, there are less literature compilations that address the calculations of biomass components.

  • • I report a total of 229 sets of allometric equations to estimate biomass components for 102 species in 72 different forest communities of arid, semi-arid, subtropical, tropical and temperate Latin-American ecosystems.

  • • The selection of the appropriate allometric model is a key element in the accurate estimation of biomass, stand productivity, carbon stocks and fluxes, and as a consequence, it is important to apply special effort to the selection and estimation of biomass equations.

  • • I also discuss statistical methods of parameter estimation and recommend the dissection of two conventional allometric equations when biomass studies are conducted on a wide range of diameters. In order to use nondestructive procedures of biomass estimation such as the fractal theory, the null hypothesis that the mean slope b value is equal to 2.67 was rejected for Latin American biomass species.

  • • This information is critical for the establishment of environmental projects that aim to estimate conventional parameters (i.e., productivity, habitat quality and fuel wood) as well as environmental features (i.e., stocks and fluxes of carbon and nitrogen).

Keywords

intrinsically linear nonlinear and seemingly unrelated regression weighting procedures 

Équations des composantes de la biomasse pour des espèces et des groupes d’espèces d’Amérique latine

Résumé

  • • Les études portant sur l’estimation de la biomasse, la productivité des stations et la contribution des forêts à l’équilibre mondial du carbone nécessitent l’emploi d’équations allométriques. Il y a eu un grand nombre d’équations qui ont été développées pour estimer la biomasse des composantes des arbres et des arbustes dans différents écosystèmes. Cependant, il existe beaucoup moins de compilations de la littérature scientifique qui portent sur les calculs des composantes de la biomasse.

  • • Je rapporte un total de 229 séries d’équations allométriques pour estimer les composantes de la biomasse de 102 espèces différentes dans 72 communautés forestières des zones arides, semi-arides, sub-tropicales, tempérées des écosystèmes latino-américains.

  • • La sélection du modèle allométrique est un élément clé pour l’estimation précise de la biomasse, de la productivité des stations, des stocks de carbone et des flux et, en conséquence, il est important de bien sélectionner les équations permettant l’estimation de la biomasse.

  • • J’ai également discuté les méthodes statistiques d’estimation des paramètres et recommandé la dissection des deux équations allométriques classiques lorsque les études sur la biomasse sont conduites sur une large gamme de diamètres. Afin d’utiliser les procédures non destructives d’estimation de la biomasse telles que la théorie des fractales, l’hypothèse nulle que la pente moyenne b a une valeur égale à 2,67 a été rejetée pour la biomasse des espèces de l’Amérique latine.

  • • Cette information est critique pour la mise en place de projets environnementaux qui visent à estimer des paramètres classiques (c’est-à-dire, la productivité, la qualité du site, le bois de chauffage), ainsi que des caractéristiques environnementales (c’est-à-dire, les stocks et les flux de carbone et d’azote).

Mots-clés

intrinsèquement linéaires non linéaires et apparemment sans lien de régression procédures de pondération 

References

  1. Agee J.K., 1983. Fuel weighting for understory-grown conifers in southern Oregon. Can. J. For. Res. 13: 648–656.CrossRefGoogle Scholar
  2. Albarran V. and Zerpa F., 1992. Modelos matemáticos para generar tablas de volumen y peso verde en plantaciones de Pinus caribaea var. Hondurensis del oriente Venezolano. Boletín Técnico # 5. C.V.G.PROFORCA, Edo. Monagas.Google Scholar
  3. Alvarez E., 1993. Composición florística, diversidad, estructura y biomasa de un bosque inundable en la Amazonia Colombiana. Tesis de Maestria en Biología, Universidad de Antioquia, Facultad de Ciencias Naturales y Exactas, Medellín, Colombia.Google Scholar
  4. Alvarez E., 2001. Comparación de ecuaciones para la estimación de la biomasa de árboles, palmas y lianas en un bosque inundable de la Amazonia Colombiana. Simposio Internacional Medición y Monitoreo de la captura de Carbono en Ecosistemas Forestales. Valdivia, Chile 18–20 de Octubre de 2001.Google Scholar
  5. Araujo T.M., Higuchi N., and Carvalho J.A., 1999. Comparison of formulae for biomass content determination in a tropical rain forest site in the state of Para, Brazil. For. Ecol. Manage. 117: 43–52.CrossRefGoogle Scholar
  6. Ares A., Boniche J., Quesada J.P., Yost R., Molina E., and Smyth T.J., 2002. Estimación de biomasa por métodos alométricos, nutrimientos y carbono en plantaciones de palmito en Costa Rica. Agronomía Costarricense 26: 19–30.Google Scholar
  7. Beekman F., 1981. Structural and dynamic aspects of the occurrence and development of lianes in the tropical rain forest. Department of Forestry, Agricultural University, Wageningen, The Netherlands.Google Scholar
  8. Bekersville G.L., 1965. Dry matter production in immature balsam fir stands. Forest Science Monograph. Society of American Foresters, Washington, DC, 41 p.Google Scholar
  9. Bhatti J.S., Foster N.W., Oja T., Moayeri M.H., and Arp P.A., 1998. Modelling potentially sustainable biomass porductivity in jack pine forest stands. Can. J. Soil Sci. 78: 105–113.CrossRefGoogle Scholar
  10. Brandeis T.J., Delaney M., Parresol B.R., and Royer L., 2006. Development of equations for predicting Puerto Rican tropical dry forest biomass and volume. For. Ecol. Manage. 233: 133–142.CrossRefGoogle Scholar
  11. Bratti M.R., Wrann J.H., and Vita A.A., 1998. Efecto de la altura de corte en el rebrote de Acacia saligna (Labill.) H. Wendl. Ciencia e Investigación Forestall — Instituto Forestal / Chile 12: 40–50.Google Scholar
  12. Brown S., 1997. Los bosques y el cambio climático: el papel de los terrenos forestales como sumideros de carbono. In Actas del XI Congreso Mundial Forestal: Recursos Forestales y Arboles. Vol 1. Antalya, Turkia 13–22 October 1997.Google Scholar
  13. Brown S., Gillespie A.J., and Lugo A.E., 1989. Biomass estimation methods for tropical forests with aplications to forest inventory data. For. Sci. 35: 881–902.Google Scholar
  14. Brown S. and Iverson L.R., 1992. Biomass estimates for tropical forests. World Resour. Rev. 4: 366–384.Google Scholar
  15. Cairns M.A., Olmsted I., Granados J., and Argaez J., 2003. Composition and aboveground tree biomass of a dry semi-evergreen forest on Mexico’s Yucatan Peninsula. For. Ecol. Manage. 186: 125–132.CrossRefGoogle Scholar
  16. Carvalho Jr., Higuchi J.A., Araujo N., and Santos J.C., 1998. Combustion completeness in a rainforest clearing experiment in Manaus, Brazil. J. Geophys. Res. 103: D11, 13,915–13,199.CrossRefGoogle Scholar
  17. Castañeda-Mendoza A., Vargas-Hernández J., Gómez-Guerrero A., Valdez-Hernández J.I., and Vaquera-Huerta H., 2004. Acumulación de carbono en la biomasa áerea de una plantación de Bambusa oldhamii. Agrociencia 39: 107–116.Google Scholar
  18. Castedo-Dorado F., Diéguez-Aranda U., Barrio Anta M., and Álvarez González J.G., 2007. Modelling stand basal area growth for radiata pine plantations in Northwestern Spain using the GADA. Ann. For. Sci. 64: 609–619.CrossRefGoogle Scholar
  19. Castellanos J.F., Velázquez-Martínez A., Vargas-Hernández J., and Rodríguez-Franco C., 1993. Producción de biomasa en un rodal de Pinus patula Schl. and Cham. I Congreso Mexicano de Recursos Forestales, Saltillo, México.Google Scholar
  20. Chambers J.Q., dos Santos J., and Ribeiro R.J., 2001. Tree damage, allometric relationships, and above-ground net primary production in central Amazon forest. For. Ecol. Manage. 152: 73–84.CrossRefGoogle Scholar
  21. Chavé J., Riera B., and Dubois M.A., 2001. Estimation of biomass in a neotropical forest of French Guiana: spatial and temporal variability. J. Trop. Ecol. 17: 79–96.CrossRefGoogle Scholar
  22. Chavé J., Condit R., Lao S., Caspersen J.P., Foster R.B., and Hubbell S.P., 2003. Spatial and temporal variations of biomass in a tropical forest; results from a large census plot in Panama. J. Ecol. 91: 240–252.CrossRefGoogle Scholar
  23. Clark D.A., Brown S., Kicklighter D.W., Tomlison J.Q., and Ni J., 2001. Measuring net primary production in forests; concepts and field methods. Ecol. Appl. 11: 356–370.CrossRefGoogle Scholar
  24. Cole T.G. and Ewel J.J., 2006. Allometric equations for tour valuable tropical tree species. For. Ecol. Manage. 229: 351–360.CrossRefGoogle Scholar
  25. Colorado G.J., 2001. Ecuaciones de biomasa aérea para los árboles de los bosques secundarios del área de influencia de la Central hidroeléctrica Porce II. Trabajo de grado para optar por el título de Ingeniero Forestal, Universidad Nacional de Colombia, Medellín, Colombia.Google Scholar
  26. Crow T.R., 1980. A rainforest chronicle: a 30-year record of change in structure and composition at El Verde, Puerto Rico. Biotropica 12: 42–55.CrossRefGoogle Scholar
  27. Cruz G.M. and Quintana A.G., 2008. Funciones de biomasa para una plantación de 7 años de Quillaza saponaria Mol. En el secano interior de Chile Central. http://www.umayor.cl/jornadas/forestales/ descargas/trabajos/trabajos_0014.pdf.Google Scholar
  28. Cunia T. and Briggs R.D., 1984. Forcing additivity of biomass tables — some empirical results. Can. J. For. Res. 14: 376–384.CrossRefGoogle Scholar
  29. Cunia T. and Briggs R.D., 1985. Forcing additivity of biomass tables — use of the generalized least-square method. Can. J. For. Res. 15: 23–28.CrossRefGoogle Scholar
  30. DeWalt S.J. and Chave J., 2004. Structure and biomass of four lowland neotropical forests. Biotropica 36: 7–19.Google Scholar
  31. Dias A.T.C., de Matos E.A., Vieira S.A., Azeredo J.V., and Scarano F.R., 2006. Aboveground biomass stock of native woodland on a Brazil sandy coastal plain: estimates based on the dominant tree species. For. Ecol. Manage. 226: 367–367.CrossRefGoogle Scholar
  32. Durán-Garáte L.P., 2005. Evaluación de la producción y productividad en biomasa aérea de boldo (Peumus boldus Mol.) en un bosque esclerófilo de la comuna de María Pinto, Provincia de Melipilla, Region Metropolitana. Memoria para optar al título profesional de Ingeniero Forestal, Facultad de Ciencias Forestales, Universidad de Chile.Google Scholar
  33. Enquist B.J., Brown J.H., and West J.B., 1998. Allometric scaling of plant energetics and population density. Nature 395: 163–165.CrossRefGoogle Scholar
  34. Etchevers-Barra J.D., Vargas-Hernández J., Acosta-Mireles M., and Velásquez-Martínez A., 2002. Estimación de la biomasa aérea mediante el uso de relaciones alométricas en seis especies arbóreas en Oaxaca, México. Agrociencia 36: 725–736.Google Scholar
  35. Farinha-Watzlawick L., Sanquetta C.R., de Mello A.A., and Arce J.E., 2001. Ecuaciones de biomasa aérea em plantaciones de Araucaria angustifolia en el Sur del Estado de Paraná, Brasil. Simposio Internacional de Medición y Monitoreo de la Captura de Carbono en Ecosistemas Forestales, Valdivia, Chile, 18–21 Octubre de 2001.Google Scholar
  36. Feldpausch T.R., McDonald A.J., Passos C.A.M., Lehmann J., and Riha S.J., 2006. Biomasa, harvestable area, and forest structure estimated from commercial forest inventories and remote sensed imagery in Southern Amazonia. For. Ecol. Manage. 233: 121–132.CrossRefGoogle Scholar
  37. Fernández-Tschieder E., Martiarena R., Goya J., Lupi A., and Frangi J., 2008. Determinación de la biomasa aérea de plantaciones de Araucaria angustifolia (Berth) O. KTZE en el norte de la Provincia de Misiones. 11as Jornadas Técnicas Forestales y Ambientales, FCF UnaM, EEA, Montecarlo, INTA. Argentina, http://www.inta.gov.ar/ montecarlo/info/documentos/forestales/f_tschieder.pdfGoogle Scholar
  38. Ferrando J.J., Goya J.F., Barrera M.D., Yapura P.F., and Frangi J.L., 2001. Biomasa y productividad aérea de Austrocedrus chilensis en Río Negro, Argentina. Revista de la Facultad de Agronomía de la Plata 104: 139–149.Google Scholar
  39. Frangi J.L. and Lugo A.E. 1985. Ecosystem dynamics of a sub-tropical floodplain forest. Ecol. Monogr. 55: 351–369.CrossRefGoogle Scholar
  40. Fuentes-Salinas M., 1995. Tecnologìa de la Madera II. Propiedades Físico-Mecánicas, División de Ciencias Forestales, Universidad Autónoma Chapingo, Chapingo, México, 64 p.Google Scholar
  41. Gaillard de Benitez C., Pece M., Juarez de Galíndez M., Maldonado A., Acosta V.H., and Gomez A., 2002. Biomasa aerea de ejemplares de Quebracho blanco (Aspidosperma quebracho-blanco) en dos localidades del Parque Chaqueño seco. Quebracho 9: 115–127.Google Scholar
  42. Gehring C., Park S., and Denich M., 2004. Liana allometric biomass equations for Amazonian primary and secondary forest. For. Ecol. Manage. 195: 69–83.CrossRefGoogle Scholar
  43. Gerwin J.J. and Farias D.L., 2000. Integrating liana abundance and forest stature into an estimate of total aboveground biomass for an eastern Amazonian forest. J. Trop. Ecol. 16: 327–335.CrossRefGoogle Scholar
  44. Gillespie A.J.R., Brown S., and Lugo A.E., 1992. Tropical forest biomass estimation from truncated stand tables. For. Ecol. Manage. 48: 68–87.CrossRefGoogle Scholar
  45. Giraldo L.A., Zapata M., and Montoya E., 2007. Estimación de la captura y flujo de carbono en silvopastoreo de Acacia mangium asociada con Brachiaria dyctioneura en Colombia. http://dict.isch.edu.cu/dict/publicacionesdeeventos/agroforesteria%202007/data/conferencias/luisagiraldo.pdf.Google Scholar
  46. Guerra J.C., Ganoso J.A., Schlatter J.V., and Nespolo R.R., 2005. Análisis e la biomasa de las raíces en diferentes tipos de bosques. Avances de la evaluación de Pinus radiata en Chile. Bosque (Valdivia) 26: 5–21.Google Scholar
  47. Hase H. and Folster H., 1983. Impact of plantation forestry with teak (Tectona grandis) on the nutrient status of young alluvial soils in west Vnezuela. J. Soil Sci. 39: 123–133.Google Scholar
  48. Higuchi N., Santos J., Ribeiro R.J., Miente L., and Biot Y., 1998. Biomassa da parte aérea da vegetação da floresta tropical úmida da Terra Firme da Amazônia Brasileira. Acta Amazônica 28: 153–166.Google Scholar
  49. Hughes R.F., Kauffman J.B., and Jaramillo V.J., 1999. Biomass, carbon, and nutrient dynamic of secondary forests in a humid tropical region of Mexico. Ecology 80: 1892–1907Google Scholar
  50. Hughes R.F., Kauffman J.B., and Jaramillo V.J., 2000. Ecosystem-scale impacts of deforestation and land use in a humid tropical region of Mexico. Ecol. Appl. 10: 515–527.CrossRefGoogle Scholar
  51. Jenkins J.C., Birdsey R.A., and Pan Y., 2001. Biomass and NPP estimation for the mid-atlantic region (USA) using plot-level forest inventory data. Ecol. Appl. 11: 1174–1193.CrossRefGoogle Scholar
  52. Jenkins J., Chojnaky D., Heath L., and Birdsey R., 2004 Comprehensive database of diameter-based biomass regressions for North American tree species. US Department of Agriculture, Forest Service, Delaware, USA, 48 p.Google Scholar
  53. Kie J.G. and White M., 1985. Population-dynamics of white-tailed deer (Odocoileus virginianus) on the Welder wildlife refuge, Texas. Southwestern Naturalist 30: 105–118.CrossRefGoogle Scholar
  54. Kue R. and Lim M., 1999. Forest biomass estimation in Air Hitam Forest Reserve, May 2002 (electronic version), [http://www.geocities.com/EnchantedForest/Palace/1170/biomass.html].Google Scholar
  55. Kumar K. and Tewari V.S., 1999. Above ground biomass tables for Azadirachta indica A. Juss. Int. For. Rev. 1: 111–112.Google Scholar
  56. Laclau P. 2003. Biomasa and carbon sequestration of ponderosa pine plantations and native cypress forests in northwestern Patagonia. For. Ecol. Manage. 173: 353–360.CrossRefGoogle Scholar
  57. Lapeyre T., Alegre J., and Arévalo L., 2004. Determinación de las reservas de carbono de la biomasa aerea en diferentes sistemas de uso de la tierra en San Martín, Perú. Universidad Nacional Agraria La Molina, Lima, Perú.Google Scholar
  58. Loguercio G.A. and Defossé G., 2001. Ecuaciones de biomasa aérea, factores de expansión y reducción de la lenga Nothofagus pumilio (OPEP et Endl.) Krasser en el SO de Chubut, Argentina. Simposio Internacional sobre Medición y Monitoreo de la Captura de Carbono en Ecosistemas Forestales. Valdivia, Chile 18–20 de Octubre de 2001.Google Scholar
  59. Martinez-Yrizar A., Sarukhan J., Perez-Jimenez A., Rincon E., Maass J.M., Solis-Magallanes A., and Cervantes L., 1992. Above-ground phytomass of a tropical deciduous forest on the coast of Jalisco, Mexico. J. Trop. Ecol. 8: 87–96.CrossRefGoogle Scholar
  60. Medeiros T.C.C. and Sampaio E.V.S.B., 2007. Allometry of aboveground biomasses in mangrove species in Itmaraca, Pernambuco, Brazil. Wetl. Ecol. Manage. 1: 1–8.Google Scholar
  61. Mohren F. and Goldewijkt K., 1994. CO2 Fix model. Institute of forestry and nature research, Wageningen, Netherlands.Google Scholar
  62. Monroy C.R. and Navar J., 2004. Ecuaciones de aditividad para estimar componentes de biomasa de Hevea brasiliensis Muell Arg. En Veracruz, México. Madera y Bosques 10: 29–43.Google Scholar
  63. Montero M. and Montagnini F., 2004. Modelos alométricos para la estimación de biomasa de diez especies nativas en plantaciones en la región Atlántica de Costa Rica. Revista Forestal Centroamericana (in press).Google Scholar
  64. Montero M.M. and Kanninen M., 2005. Terminalia amazonia; ecología y silvicultura. Serie Técnica. Informe Técnico No. 339, CATIE, Turrialba, Costa Rica.Google Scholar
  65. Návar J., Méndez E., Nájera A., Graciano J., Dale V., and Parresol B., 2004a. Biomass equations for shrub species of Tamaulipas thornscrub of northeastern Mexico. J. Arid Environ. 59: 657–674.CrossRefGoogle Scholar
  66. Návar J., González N., Maldonado D., Graciano J., Dale V., and Parresol B., 2004b. Additive biomass equations for pine species of forest plantations of Durango, Mexico. Madera y Bosques 10: 17–28.Google Scholar
  67. Návar J., 2009. Allometric equations for tree species and forests of northwestern Mexico. For. Ecol. Manage. 257: 427–434.CrossRefGoogle Scholar
  68. Northup B.K., Sitzer S.F., Archer S., McMurtry C.R., and Boutton T.W., 2005. Above-ground biomass and carbon and nitrogen content of woody species in a subtropical thornscrub parkland. J. Arid Environ. 62: 23–43.CrossRefGoogle Scholar
  69. Ortiz E., 1997. Estimación de la Biomasa arriba del suelo en árboles de un bosque húmedo tropical. En: Conservación del Bosque en Costa Rica. Ed. EM Flores. Academia Nacional de Ciencias. San José, Costa Rica.Google Scholar
  70. Overmann J.P., Witte H.J., and Saldarriaga J.G., 1994. Evaluation of regression models for aboveground biomass determination in Amazon rainforest. J. Trop. Ecol. 10: 207–218.CrossRefGoogle Scholar
  71. Pacheco-Escalona F.C., Gómez-Guerrero A., Aldrete A., Fierros-González A.M., and Cetina-Alcalá V., 2007. Absorción de nitrógeno y crecimiento de Pinus greggii Engelm. Seis años después de una poda química de raíz. Agrociencia 41: 675–685.Google Scholar
  72. Padrón E. and Navarro-Cerrillo R., 2004. Estimation of above-ground biomass in naturally occurring populations of Prosopis pallida (H. & B. ex. Willd.) H.B.K. in the north of Peru. J. Arid Environ. 56: 283–292.CrossRefGoogle Scholar
  73. Parresol B., 1999. Assessing tree and stand biomass: a review with examples and critical comparisons. For. Sci. 45: 573–593.Google Scholar
  74. Pilli R., Anfodillo T., and Carrer M., 2006. Towards a functional and simplified allometrry for estimating forest biomass. For. Ecol. Manage. 237: 583–593.CrossRefGoogle Scholar
  75. Putz F.E., 1983. Liana biomass and leaf area of “tierra firme” forest in the Rio Negro basin, Venezuela. Biotropica 15: 185–189.CrossRefGoogle Scholar
  76. Reynolds J., Marathon G., Rosales L., and Wright J., 2000. Ecuaciones de volumen y peso para Eucalyptus urophylla y Eucalyptus grandis. Informe de Investigación No. 21, Smurfit-Carton de Venezuela.Google Scholar
  77. Rodríguez R., Hofmann G., Espinoza M., and Ríos D., 2003. Biomasa partitioning and leaf area of Pinus radiata trees sunjected to silvopastoral and conventional forestry in the VI Region, Chile. Revista Chilena de Historia Natural 76: 437–449.Google Scholar
  78. Rodríguez-Laguna R., Jiménez-Pérez J., Aguirre-Calderon O., and Jurado-Ibarra E., 2007. Ecuaciones alométricas para estimar biomasa aérea en especies de encino y pino en Irurbide, N.L. Ciencia Forestal en México 32: 39–56.Google Scholar
  79. Rojo-Martínez G.E., Jasso-Mata J., Vargas-Hernández J., Palma-López D.J., and Velásquez-Martínez A., 2005. Biomasa aérea en plantaciones comerciales de hule (Hevea brasiliensis Mull Arg.) en el estado de Oaxaca, México. Agrociencia 39: 449–456.Google Scholar
  80. Saldarriaga J.G., West D.C., Tharp M.L., and Uhl C., 1988. Long term chronosequence of forest succession in the upper Rio Negro of Colombia and Venezuela. J. Ecol. 76: 938–958.CrossRefGoogle Scholar
  81. Salis S.M., Assis M.A., Mattos P.P., and Piao A.S.S., 2006. Estimating the aboveground biomass and wood volume of savanna woodlands in Brazil’s Pantanal wetlands based on allometric correlations. For. Ecol. Manage. 228: 61–68.CrossRefGoogle Scholar
  82. Sampaio E.V.S.B., and Silva G.C., 2005. Biomass equations for Brazilian semiarid caatinga plants. Acta Botânica Brasílica 19: 935–945.CrossRefGoogle Scholar
  83. Sanquetta C.R., Watzlawick L.F., and Arce J.E., 2002. Ecuaciones de biomasa aérea y subterránea en plantaciones de Pinus taeda en el sur del Estado de Paraná, Brasil. Patagonia Forestal. http://www.ciefap.org.ar/patagoniaforestal/2002-1/biomassa_pinus.htm.Google Scholar
  84. Saunders M. and Wagner R.G., 2008. Height-diameter models with random coefficients and site variables for trees species of Central Maine. Ann. For. Sci. 65: 203.CrossRefGoogle Scholar
  85. Segura M., Kanninen M., and Suarez D., 2006. Allometric models for estimating aboveground biomass of shade trees and coffee bushes grown together. Agrofor. Syst. 68: 143–150.CrossRefGoogle Scholar
  86. Scatena F.N., Silver W., Sicamma T., Jonson A., and Sanchez M.J., 1993. Biomass and nutrient content of the Bisley experimental watersheds, Luquillo Experimental Forest, Puerto Rico before and after hurricane Hugo, 1989. Biotropica 25: 15–27.CrossRefGoogle Scholar
  87. Schlegel B., 2001. Estimación de biomasa y carbono en bosques del tipo forestal siempreverde. Simposio Internacional de Medición y Monitoreo de la Captura de Carbono en Ecosistemas Forestales, Valdivia, Chile, 18–21 Octubre de 2001.Google Scholar
  88. Schnitzer S.A., DeWalt S.J., and Chave J., 2006. Censusing and measuring lianas: a quantitative comparison of the common methods. Biotropica 38: 581–591CrossRefGoogle Scholar
  89. Schroeder P., Brown S., Mo J., Birdsey R., and Cieszewski C., 1997. Biomass estimation for temperate broadleaf forest of the United States using inventory data. For. Sci. 43: 424–434.Google Scholar
  90. Sierra C.A., del Valle J.I., Orrego S.A., Moreno F.H., Harmon M.E., Zapata M., Colorado G.J., Herrera M.A., Lara W., Restrepo D.E., Berrouet L.M., Loaiza L.M., and Benjumea J.F., 2007. Total carbon stocks in a tropical forest landscape of the Porce region, Colombia. For. Ecol. Manage. 243: 209–309.Google Scholar
  91. Sierra C.A., 2001. Biomasa de raíces en bosques primarios y secundarios del área de influencia de la central hidroelectrica Porce II. Trabajo de Grado, Universidad Nacional de Colombia, Sede Medellín, Medellín, Colombia.Google Scholar
  92. Ter-Mikaelian M.T. and Korzukhin M.D., 1997. Biomass equations for sixty five North American tree species. For. Ecol. Manage. 97: 1–24.CrossRefGoogle Scholar
  93. Uhl C., Buschbacher R., and Serrao E.A.S., 1988. Abandoned pastures in eastern Amazonia. I Patterns of plant succession. J. Ecol. 76: 663–681.CrossRefGoogle Scholar
  94. Vidal-Corona A., Rodríguez J.R., Naranjo J.Y.B., Rivera R.C.A., and Ríos H.G., 2004. Estimación de la biomasa de copa para árboles en pie de Pinus tropicalis Morelet en la empresa forestal integral Macurije de la Provincia de Pinar del Río, Cuba. Revista Floresta 32: 261–265.Google Scholar
  95. Vargas R., Allen M.F., and Allen E.B., 2008. Biomass and carbon accumulation in a fire chronosequence of a seasonally dry tropical forest. Glob. Change Biol. 14: 109–124.Google Scholar
  96. Weaver P.L., 2002. A chronology of hurricane induced changes in Puerto Rico’s lower montane forest. Interciencia 27: 252–258.Google Scholar
  97. Weaver P.L. and Gillespie A.J.R., 1992. Tree biomass equations for the forests of the Luquillo Mountains, Puerto Rico. Commonwealth Forestry Review 71: 35–39.Google Scholar
  98. West G.B., Brown J.H., and Enquist B.J., 1999. A general model for the structure and allometry of plant vascular system. Nature 400: 664–667.CrossRefGoogle Scholar
  99. Zapata M., del Valle J.I., and Orrego S.A., 2001. Corrección por sesgo en los modelos log-normales alométricos linealizados utilizados para la estimación de la biomasa aérea. Simposio Internacional de Medición y Monitoreo de la Captura de Carbono en Ecosistemas Forestales, Valdivia, Chile. 18–21 Octubre de 2001.Google Scholar
  100. Zianis D. and Mencuccini M., 2004. On simplifying allometric analysis of forest biomass. For. Ecol. Manage. 23: 311–332.CrossRefGoogle Scholar

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© Springer S+B Media B.V. 2009

Authors and Affiliations

  1. 1.Natural Resource ManagementCIIDIR-IPN Unidad DurangoDurango, Dgo.México

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