Mostrar el registro sencillo del ítem

dc.contributor.authorAndrade, Hernán J.spa
dc.contributor.authorOrjuela, Jose Alfredospa
dc.contributor.authorHernández Joven, Carlosspa
dc.date.accessioned2022-07-01 05:14:18
dc.date.accessioned2023-09-19T21:10:36Z
dc.date.available2022-07-01 05:14:18
dc.date.available2023-09-19T21:10:36Z
dc.date.issued2022-07-01
dc.identifier.issn0120-0739
dc.identifier.urihttp://test.repositoriodigital.com:8080/handle/123456789/44504
dc.description.abstractLos modelos de biomasa son herramientas clave para estimar carbono en agroecosistemas. Esta investigación fue desarrollada en Caquetá, Colombia, en plantaciones y sistemas agroforestales. Se seleccionaron 41 árboles de Hevea brasiliensis y 40 de Theobroma grandiflorum para estimar la biomasa aérea (Ba); y 19 y 12 árboles fueron excavados respectivamente para estimar biomasa subterránea (Bb). Se ajustaron los modelos con base en el coeficiente de determinación (R2), el R2 ajustado, y los criterios de información de Akaike y Bayesiano. Los modelos recomendados para Ba en H. brasiliensis y T. grandiflorum fueron Ln(Ba)=-2.99+2.72*Ln(DAP) y Ln(Ba)=-2.59+2.48*Ln(D30), respectivamente (Ba: kg.árbol-1; DAP: diámetro a la altura del pecho en cm; D30: diámetro del tronco a 30 cm de altura). Adicionalmente, se desarrollaron modelos con base en diámetro y altura, así como otros basados en el área de la copa. Estos modelos son un avance para mejorar las estimaciones de biomasa y carbono, alcanzando un Tier 2 (Nivel 2), en investigación y proyectos de mitigación.spa
dc.description.abstractBiomass models are key tools for estimating carbon in agroecosystems. This research was conducted in Caquetá, Colombia, in plantations and agroforestry systems. A total of 41 trees of Hevea brasiliensis and 40 of Theobroma grandiflorum were sampled to estimate the above-ground biomass (Ab); and 19 and 12 trees, respectively, were excavated to estimate the below-ground biomass (Bb). The models were adjusted based on the determination coefficient (R2), the adjusted R2, and Akaike’s and the Bayesian information criteria. The recommended models for Ab in H. brasiliensis and T. grandiflorum were Ln(Ab)=-2.99+2.72*Ln(DBH) and Ln(Ab)=-2.59+2.48*Ln(D30), respectively (Ab: kg.tree-1; DBH: diameter at breast height in cm; D30: trunk diameter at a 30 cm height). Additionally, models based on diameter and height were developed, as well as others based on the crown area. These models constitute an advancement in improving estimations of biomass and carbon, thus reaching Tier 2 in research and mitigation projects.eng
dc.format.mimetypeapplication/pdfspa
dc.format.mimetypetext/xmlspa
dc.language.isospaspa
dc.publisherUniversidad Distrital Francisco José de Caldasspa
dc.rightsColombia forestal - 2022spa
dc.rights.urihttps://creativecommons.org/licenses/by-sa/4.0/spa
dc.sourcehttps://revistas.udistrital.edu.co/index.php/colfor/article/view/18464spa
dc.subjectCarbon storageeng
dc.subjectExcavationeng
dc.subjectMitigationeng
dc.subjectRootseng
dc.subjectAgroforestry systemseng
dc.subjectAlmacenamiento de carbonospa
dc.subjectExcavaciónspa
dc.subjectMitigaciónspa
dc.subjectRaícesspa
dc.subjectSistemas agroforestalesspa
dc.titleModelos de biomasa aérea y subterránea de <i>Hevea brasilienses</i> y <i>Theobroma grandiflorum</i> en la Amazonía colombianaspa
dc.typeArtículo de revistaspa
dc.identifier.doi10.14483/2256201X.18464
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1spa
dc.type.localJournal articleeng
dc.title.translatedAbove- and below-ground biomass models of Hevea brasilienses and Theobroma grandiflorum in the Colombian Amazoneng
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa
dc.relation.referencesÁlvarez, E., Duque, A., Saldarriaga, J., Cabrera, K., Salas, G., Valle, I., Lema, A., Moreno, F., Orrego, S. & Rodríguez, L. (2012). Tree above-ground biomass allometries for carbon stocks estimation in the natural forests of Colombia. Forest Ecology and Management, 267, 297-308. https://doi.org/10.1016/j.foreco.2011.12.013 Anaya, J. A., Chuvieco, E., & Palacios-Orueta, A. (2009). Aboveground biomass assessment in Colombia: a remote sensing approach. Forest Ecology and Management, 257, 1237-1246. https://doi.org/10.1016/j.foreco.2008.11.016 Andrade, H. J., Segura, M. A., Feria, M., & Suárez, W. (2018). Above-ground biomass models for coffee bushes (Coffea arabica L.) in Líbano, Tolima, Colombia. Agroforestry Systems, 92(3), 775-784. https://doi.org/10.1007/s10457-016-0047-4 Andrade, H. J., Segura, M. A., & Forero, L. A. (2014). Desarrollo de modelos alométricos para volumen de madera, biomasa y carbono en especies leñosas perennes: conceptos básicos, métodos y procedimientos. Sello Editorial Universidad del Tolima. Brahma, B., Sileshi, G. W., Nath, A. J., & Das, A. K. (2017). Development and evaluation of robust tree biomass equations for rubber tree (Hevea brasiliensis) plantations in India. Forest Ecosystems, 4, 14. https://doi.org/10.1186/s40663-017-0101-3 Cairns, M. A., Brown, S., Helmer, E. H., & Baumgardner, G. A. (1997). Root biomass allocation in the world's upland forests. Oecologia, 111(1), 1-11. https://doi.org/10.1007/s004420050201 Chapman, M., Walker, W. S., Cook-Patton, S.C., Ellis, P. W., Farina, M., Griscom, B. W., & Baccini, A. (2020). Large climate mitigation potential from adding trees to agricultural lands. Global Change Biology, 26(8), 4357-4365. https://doi.org/10.1111/gcb.15121 Chave, J., Andalo, C., Brown, S., Cairns, M. A., Chambers, J. Q., Eamus, D., Fölster, H., Fromard, F., Higuchi, N., Kira, T., Lescure, J. P., Nelson, B. W., 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), 87-99. https://doi.org/10.1007/s00442-005-0100-x Cifuentes-Jara, M., Henry, M., Réjou-Méchain, M., Wayson, C., Zapata-Cuartas, M., Piotto, D., Alice-Guier, F., Castañeda-Lombis, H., Castellanos-López, E., Cuenca-Lara, R., Cueva-Rojas, K., del Águila-Pasquel, J., Duque-Montoya, A., Fernández-Vega, J., Jiménez-Galo, A., López, O. R, Marklund, L. G., Michel-Fuentes, J. M. … Westfall, J. (2014). Guidelines for documenting and reporting tree allometric equations. Annals of Forest Science 72, 763-768. https://doi.org/10.1007/s13595-014-0415-z Defrenet, E., Roupsard, O., van den Meersche, K., Charbonnier, F., Pérez-Molina, J. P., Khac, E., Prieto, I., Stokes, A., Roumet, C., Rapidel, B., de Filho, M. V. E., Vargas, V. J., Robelo, D., Barquero, A., & Jourdan, C. (2016) Root biomass, turnover and net primary productivity of a coffee agroforestry system in Costa Rica: effects of soil depth, shade trees, distance to row and coffee age. Annals of Botany, 118, 833-851. https://doi.org/10.1093/aob/mcw153 Doelman, J. C., Stehfest, E., van Vuuren, D. P., Tabeau, A., Hof, A. F., Braakhekke, M. C., Gernaat, D. E. H. J., van den Berg, M., van Zeist, M., Daioglou, V., van Mijil, H., & Lucas, P. L. (2020). Afforestation for climate change mitigation: Potentials, risks and trade-offs. Global Change Biology, 26(3), 1576-1591. https://doi.org/10.1111/gcb.14887 Dossa, E., Fernandes, E. C. M., Reid, W. S., & Ezui, K. (2008). Above-and belowground biomass, nutrient and carbon stocks contrasting an open-grown and a shaded coffee plantation. Agroforestry Systems 72, 103-115. https://doi.org/10.1007/s10457-007-9075-4 FAO (2021). FAOSTAT. http://www.fao.org/faostat/es/#data/QCL Fox, J., Vogler, J. B., Sen, O. L., Giambelluca, T. W., & Ziegler, A. D. (2012). Simulating land-cover change in montane mainland Southeast Asia. Environmental Management 49:968–979. https://doi.org/10.1007/s00267-012-9828-3 Gomes, L.C., Bianchi, F. J. J. A., Cardoso, I. M., Fernandes, R. B. A., Fernandes Filho, E. I., & Schulte, R. P. O. (2020). Agroforestry systems can mitigate the impacts of climate change on coffee production: A spatially explicit assessment in Brazil. Agriculture, Ecosystems & Environment, 294, 106858. https://doi.org/10.1016/j.agee.2020.106858 Intergovernmental Panel on Climate Change (IPCC) (2003). Supplementary methods and good practice guidance arising from the Kyoto Protocol. En J. Penman, M. Gytarsky, T. Hiraishi, T. Krug, D. Kruger, R. Pipatti, L. Buendia, K. Miwa & T. Ngara (Eds.), Good Practice Guidance for Land Use, Land-Use Change and Forestry, Japan (p. 590). Institute for Global Environmental Strategies (IGES) for the IPCC. Intergovernmental Panel on Climate Change (IPCC) (2013). Cambio climático 2013: bases físicas. Contribución del grupo de trabajo I al quinto informe de evaluación del grupo intergubernamental de expertos sobre el cambio climático. IPCC. Kalita, R. M., Das, A. K., & Nath, A. J. (2015). Allometric equations for estimating above-and belowground biomass in Tea (Camellia sinensis (L.) O. Kuntze) agroforestry system of Barak Valley, Assam, northeast India. Biomass and Bioenergy, 83, 42-49. https://doi.org/10.1016/j.biombioe.2015.08.017 Kongsager, R., Napier, J. & Mertz, O. (2013). The carbon sequestration potential of tree crop plantations. Mitigation and Adaptation Strategies for Global Change 18, 1197-1213. https://doi.org/10.1007/s11027-012-9417-z Kuyah, S., Dietz, J., Muthuri, C., Jamnadass, R., Mwangi, P., Coe, R., & Neufeldt, H. (2012). Allometric equations for estimating biomass in agricultural landscapes: II. Belowground biomass. Agriculture, Ecosystems & Environment, 158, 225-234. https://doi.org/10.1016/j.agee.2012.05.010 Levillain, J., Thongo M’Bou, A., Deleporte, P., Saint-André, L., & Jourdan, C. (2011). Is the simple auger coring method reliable for below-ground standing biomass estimation in Eucalyptus forest plantations? Annals of Botany, 108(1), 221-230. https://doi.org/10.1093/aob/mcr102 Loetsch, F., Haller, K. E., & Zöhrer, F. (1973). Forest inventory (2 ed., vol. II). BLV Verlagsgesellchaft. Magalhães, T. M., & Seifert, T. (2015). Tree component biomass expansion factors and root-to-shoot ratio of Lebombo ironwood: measurement uncertainty. Carbon Balance and Management, 10(1), 9. https://doi.org/10.1186/s13021-015-0019-4 Magalhães, T. M. (2015). Allometric equations for estimating belowground biomass of Androstachys johnsonii Prain. Carbon Balance and Management, 10(1), 16. https://doi.org/10.1186/s13021-015-0027-4 Meyer, V., Saatchi, S., Clarck, D. B., Keller, M., Vicent, G., Ferraz, A., Espírito-Santo, F., Oliveira, M. V. N. D., Kaki, D., & Chave, J. (2018). Canopy area of large trees explains aboveground biomass variations across neotropical forest landscapes. Biogeosciences, 15(11), 3377-3390. https://doi.org/10.5194/bg-15-3377-2018 Minang, P. A., Duguma, L. A., Bernard, F., Mertz, O., & van Noordwij, M. (2014). Prospects for agroforestry in REDD+ landscapes in Africa. Current Opinion in Environmental Sustainability, 6, 78-82. https://doi.org/10.1016/j.cosust.2013.10.015 Monroy-Rivera, C., & Návar-Cháidez, J. J. (2004). Ecuaciones de aditividad para estimar componentes de biomasa de Hevea brasiliensis Muell. Arg., en Veracruz, México. Madera y Bosques, 10(2), 29-43. https://www.redalyc.org/articulo.oa?id=61710203 Moreno, J. A., Salcedo, J. D. B., Nieves, H. E., & Buitrago, C. E. (2005). Modelo alométrico general para la estimación del secuestro de carbono por plantaciones de caucho Hevea brasilensis mull arg. en Colombia. Colombia Forestal, 9(18), 5-21. https://doi.org/10.14483/udistrital.jour.colomb.for.2005.1.a01 Orjuela-Chaves, J. O., Andrade, H. J., & Vargas-Valenzuela, Y. (2014). Potential of carbon storage of rubber (Hevea brasiliensis Müll. Arg.) plantations in monoculture and agroforestry systems in the Colombian Amazon. Tropical and Subtropical Agroecosystems, 17, 231-240. https://www.redalyc.org/articulo.oa?id=93931761009 Picard, N., Saint-André, L., & Henry, M. (2012). Manual for building tree volume and biomass allometric equations: from field measurement to prediction. Manual for building tree volume and biomass allometric equations: from field measurement to prediction. Food and Agricultural Organization of the United Nations. Ramachandra, T. V., & Bharath, S. (2019). Carbon sequestration potential of the forest ecosystems in the Western Ghats, a global biodiversity hotspot. Natural Resources Research, 29, 2753-2771. https://doi.org/10.1007/s11053-019-09588-0 Rosenstock, T. S, Wilkes, A., Jallo, C., Namoi, N., Bulusu, M., Suber, M., Mboi, D., Mulia, R., Simelton, E., Richards, M., Gurwick, N., & Wollenberg, E. (2019). Making trees count: Measurement and reporting of agroforestry in UNFCCC national communications of non-Annex I countries. Agriculture, Ecosystems & Environment, 284, 106-569. https://doi.org/10.1016/j.agee.2019.106569 Segura, M., & Andrade, H.J. (2008). ¿Cómo construir modelos alométricos de volumen, biomasa o carbono de especies leñosas perennes? How to develop biomass models of woody perennials species. Agroforestería en las Américas, 46, 89-96. https://repositorio.catie.ac.cr/bitstream/handle/11554/6935/Como_construir_modelos_alometricos.pdf?sequence=1 Segura, M., & Kanninen, M. (2005). Allometric models for tree volume and total aboveground biomass in a tropical humid forest in Costa Rica. Biotropica, 37(1), 2-8. http://dx.doi.org/10.1111/j.1744-7429.2005.02027.x Silva, L. N., Freer-Smith, P., & Madsen, P. (2019). Production, restoration, mitigation: a new generation of plantations. New Forests, 50, 153-168. https://doi.org/10.1007/s11056-018-9644-6 Sione, S., Andrade-Castañeda, H. J., Ledesma, S. G., Rosenberger, L. J., Oszust, J. D., & Wilson, M. G. (2019). Aerial biomass allometric models for Prosopis affinis Spreng. in native Espinal forests of Argentina. Revista Brasileira de Engenharia Agrícola e Ambiental,23(6), 467-473. http://doi.org/10.1590/1807-1929/agriambi.v23n6p467-473 Sone, K., Watanabe, N., Takase, M., Hosaka, T., & Gyokusen, K. (2014). Carbon sequestration, tree biomass growth and rubber yield of PB260 clone of rubber tree (Hevea brasiliensis) in North Sumatra. Journal of Rubber Research, 17(2), 115-127. https://kyushu-u.pure.elsevier.com/en/publications/carbon-sequestration-tree-biomass-growth-and-rubber-yield-of-pb26 Sterling, A., Suárez, J., Caicedo, D., Rodríguez, C., Salas-Tobón, Y., & Virgüez-Diaz, Y. (2015). Crecimiento inicial de clones promisorios de Hevea brasiliensis (Willd. ex A. Juss.) Müll. Arg. en sistema agroforestal en Caquetá, Colombia. Colombia Forestal, 18(2), 175-192. https://doi.org/10.14483/udistrital.jour.colomb.for.2015.2.a01 Tang, J. W., Pang, J. P., Chen, M. Y., Guo, X. M., & Zeng, R. (2009). Biomass and its estimation model of rubber plantations in Xishuangbanna, Southwest China. Chinese Journal of Ecology, 28, 1942-1948. van Breugel, M., Ransijn, J., Craven, D., Bongers, F., & Hall, J.S. (2011). Estimating carbon stock in secondary forests: Decisions and uncertainties associated with allometric biomass models. Forest Ecology and Management 262(8), 1648-1657. https://doi.org/10.1016/j.foreco.2011.07.018spa
dc.rights.creativecommonsEsta obra está bajo una licencia internacional Creative Commons Atribución-CompartirIgual 4.0.spa
dc.type.coarversionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTspa
dc.type.versioninfo:eu-repo/semantics/publishedVersionspa
dc.relation.citationvolume25spa
dc.relation.citationissue2spa
dc.relation.citationeditionNúm. 2 , Año 2022 : Julio-diciembrespa
dc.relation.ispartofjournalColombia forestalspa
dc.identifier.eissn2256-201X
dc.identifier.urlhttps://doi.org/10.14483/2256201X.18464
dc.relation.citationstartpage57
dc.relation.citationendpage69
dc.relation.bitstreamhttps://revistas.udistrital.edu.co/index.php/colfor/article/download/18464/18298
dc.relation.bitstreamhttps://revistas.udistrital.edu.co/index.php/colfor/article/download/18464/18365
dc.type.contentTextspa
dspace.entity.typePublicationspa


Ficheros en el ítem

FicherosTamañoFormatoVer

No hay ficheros asociados a este ítem.

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem

Colombia forestal - 2022
Excepto si se señala otra cosa, la licencia del ítem se describe como Colombia forestal - 2022