Mixed Taper Equations for African Mahogany Plantations ( Khaya grandifoliola C. DC.) Near Thinning and Clear-cut Ages
Ximena Mendes de Oliveira; Andressa Ribeiro; Rafaella Carvalho Mayrinck; Antonio Carlos Ferraz Filho
Abstract
Keywords
References
Alvares CA, Stape JL, Sentelhas PC, Gonçalves JLM, Sparovek G. Köppen’s climate classification map for Brazil. Meteorologische Zeitschrift. 2013; 22(6): 711-728.
Assis AL, Scolforo JRS, Mello JM, Oliveira AD. Avaliação de modelos polinomiais não-segmentados na estimativa de diâmetros e volumes comerciais de Pinus taeda. Ciência Florestal. 2002; 12(1): 89-107.
Burkhart HE, Tomé M. Modeling forest trees and stands. New York: Springer; 2012.
Costa MS, Cabacinha CD, Schettino S, Fonseca MFV. Viabilidade econômica dos sortimentos de madeira de um povoamento de mogno africano (Khaya spp.) não desbastado. Revista Delos, 2023, 16(50): 4043–4060.
Curto RA, Lauro AC, Tonini H, Kohler SV, Araújo EJG, Biazatti SH. Cubagem de árvores em pé com dendrômetro óptico em sistema de integração lavoura-pecuária-floresta. Pesquisa Florestal Brasileira. 2019; 39: 1-11.
Efron B. The jackknife, the bootstrap and other resampling plans. Philadelphia, Penn.: Society for Industrial and Applied Mathematics; 1982.
Ferraz Filho AC, Ribeiro A. Crescimento e produção de mogno-africano:quantificação e influências. In: Reis CF, Oliveira EB, Santos AM.(Ed.). Mogno-africano (Khaya spp.): atualidades e perspectivas do cultivo no Brasil. Brasília, DF: Embrapa. Cap. 8, 198-234; 2019.
Ferraz Filho AC, Ribeiro A, Bouka GUD, Frank Júnior M, Terra G. African mahogany plantation highlights in Brazil. Floresta e Ambiente. 2021; 28(3): e20200081.
Figueiredo Filho A, Retslaff FAS, Kohler SV, Becker M, Brandes D. Efeito da idade no afilamento e sortimento em povoamentos de Araucaria angustifólia. Floresta e Ambiente. 2015; 22(1): 50-59.
Hall KB, Stape JL, Bullock BP, Frederick D, Wright J, Scolforo HF, Cook R. A Growth and Yield Model for Eucalyptus benthamii in the Southeastern United States. Forest Science. 2019; 1(1): 1-13.
Hradetzky J. Analyse und interpretation statistisher abränger keiten. (Biometrische Beiträge zuaktuellen forschungs projekten). Baden: Württemberg Mitteilungen der FVA; 1976.
ITTO. Tropical Timber Market Report. 2023; 27(11):1-15.
Kohler SV, Koehler HS, Figueiredo Filho A, Arce JE, Machado AS. Evolution of tree stem taper in Pinus taeda stands. Ciência Rural. 2016; 46(7): p.1185-1191.
Koirala A, Montes CR, Bullock BP, Wagle BH. Developing taper equations for planted teak (Tectona grandis L.f.) trees of central lowland Nepal. Trees, Forests and People. 2021; 5: 100103.
Kozak A. Effects of upper stem measurements on the predictive ability of a variable exponent taper equation. Canadian Journal of Forest Research. 1988; 28: 1078–1083.
Kozak A. My last words on taper equations. The Forestry Chronicle. 2004; 80(4): 507-515.
Lanssanova RL, Machado SA, Orso GA, Pelissari AL, Figueiredo Filho A, Silva FA. Calibration of a mixed-effect stem taper model for Tectona grandis. Journal of Tropical Forest Science. 2020; 32(4): 341–348.
Liu Y, Trancoso R, Ma Q, Yue C, Wei X, Blanco JA. Incorporating climate effects in Larix gmelinii improves stem taper models in the Greater Khingan Mountains of Inner Mongolia, northeast China. Forest Ecology and Management. 2020b; 464: 118065.
Liu Y, Yue C, Wei X, Blanco JA, Trancoso R. Tree profile equations are significantly improved when adding tree age and stocking degree: an example for Larix gmelinii in the Greater Khingan Mountains of Inner Mongolia, northeast China. European Journal of Forest Research. 2020a; 139(3): 443-458.
Max TA, Burkhart HE. Segmented polynomial regression applied to taper equations. Forest Science. 1976; 22(3): 283 - 289.
Mayrinck RC, Ferraz Filho AC, Ribeiro A, Oliveira XM, Lima RR. A comparison of diameter distribution models for Khaya ivorensis A. Chev. plantations in Brazil. Southern Forests. 2018; 80(4):373-380.
Monteiro BC, Abreu JC, Souza RLF, Santos BC, Oliveira IR, Lima RB. Uso de modelos mistos para estimativa de volume de árvores individuais em tipologias florestais no Estado do Amapá. Biota Amazônica. 2021; 11(2): 7-10.
Mugasha WA, Mwakalukwa EE, Luoga E, Malimbwi RE, Zahabu E, Silayo DS, et al. Allometric models for estimating tree volume and aboveground biomass in lowland forests of Tanzania. International Journal of Forestry Research. 2016; 2016: 1-14.
Nicoletti MF, Carvalho SPC, Machado SA, Costa VJ, Silva CA, Topanotti LR. Bivariate and generalized models for taper stem representation and assortments production of loblolly pine (Pinus taeda L.). Journal of Environmental Management. 2020; 270: 110865.
Oliveira XM, Ribeiro A, Ferraz Filho AC, Mayrinck RC, Lima RR, Scolforo JRS. Volume equations for Khaya ivorensis A. Chev. plantations in Brazil. Anais da Academia Brasileira de Ciências. 2018; 90(4): 3285-3298.
Pinheiro J, Bates D, DebRoy S, Sarkar D, Heisterkamp S, Van Willigen B, Ranke J. nlme: Linear and nonlinear mixed effects models. R Package versioin 3.1-141.
Pinheiro LP, Couto L, Pinheiro DT, Brunetta JMFC. Ecologia, silvicultura e tecnologia de utilização dos mognos africanos (Khaya spp.). Viçosa: Sociedade Brasileira de Agrossilvicultura- SBAG; 2011.
R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. URL
Reis CAF, Oliveira EB, Santos AM. Mogno-africano (Khaya spp.): atualidades e perspectivas de cultivo no Brasil. Embrapa Florestas; 2019.
Ribeiro A, Ferraz Filho AC, Scolforo JRS. Tree height prediction in Brazilian Khaya ivorensis stands. Bosque. 2018a; 39(1):15-26.
Ribeiro A, Ferraz Filho AC, Tomé M, Scolforo JRS. Site quality curves for African mahogany plantations in Brazil. Cerne. 2016; 22(4): 439-448.
Ribeiro A, Silva CSJ, Ferraz Filho AC, Scolforo JRS. Financial and risk analysis of African mahogany plantations in Brazil. Ciência e Agrotecnologia. 2018b; 42(2): 148-158.
Ribeiro A, Ferraz Filho AC, Scolforo JRS. O cultivo do mogno africano (Khaya spp.) e o crescimento da atividade no Brasil. Floresta e Ambiente. 2017; 24: 1-11.
Santos GM, Oliveira XM, Homczinski I, Mayrinck RC, Cavassim WS. Modelagem mista generalizada para estimar afilamento do fuste de árvores de Pinus taeda em diferentes espaçamentos de plantio. Advances in Forestry Science. 2021a; 8(1): 1261-1269.
Santos GM, Oliveira XM, Homczinski I, Mayrinck RC, Cavassim WS. Effect of spacing on volume, form factor and taper for Pinus taeda trees in Paraná, Brazil. Advances in Forestry Science. 2021b; 8(3): 1557-1566.
Schöepfer W. Automatisierung des massen, Sorten und Wertberechnung stenender Waldbestande Schriftenreihe Bad. Berlin: Wurtt-Forstl; 1966.
Scolforo HF, McTague JP, Raimundo MR, Weiskittel A, Carrero O, Scolforo JRS. Comparison of taper functions applied to eucalypts of varying genetics in Brazil: Application and evaluation of the penalized mixed spline approach. Canadian Journal of Forest Research. 2018; 1: cjfr-2017-0366.
Souza GSA, Cosenza DN, Araújo ACSC, Pimenta LVA, Souza RB, Almeida FM, Leite HG. Evaluation of non-linear taper equations for predicting the diameter of Eucalyptus trees. Revista Árvore. 2018; 42(1): e420102.
Stenman V, Kangas A, Holopainen M. Upper stem diameter and volume prediction strategies in the National Forest Inventory of Finland. Silva Fennica. 2023; 57(3): 23021.
Téo SJ, Esteves JH. Efeito da idade sobre o polinômio do quinto grau para afilamento de Pinus taeda L. BIOFIX Scientific Journal. 2022; 7(1): 66-73.
Terra DLCV, Andrade VCL, Ferreira Junior JM. Funções segmentadas de taper para o clone GG100 no sudeste do Tocantins. Cerrado Agrociências. 2017; 8: 104-115.
Vendruscolo DGS, Drescher R, Carvalho SPC, Souza HS, Silva RS, Chaves AGS. Forma do fuste de árvores de Tectona grandis em diferentes espaçamentos. Advances in Forestry Science. 2016; 3(3): 51-54.
Wickham H. ggplot2: Elegant graphics for data analysis.
Xie L, Widagdo FRA, Dong L, Li F. Modeling Height–Diameter Relationships for Mixed-Species Plantations of Fraxinus mandshurica Rupr. and Larix olgensis Henry in Northeastern China. Forests. 2020; 11(610): 1-22.
Xu Y, Goodacre R. On splitting training and validation set: a comparative study of cross‑validation, bootstrap and systematic sampling for estimating the generalization performance of supervised learning. Journal of Analysis and Testing. 2018; 2(3): 249-262.
Submitted date:
12/23/2023
Accepted date:
11/13/2024