Simultaneous estimation as an alternative to young eucalyptus aboveground biomass modeling in ecophysiological experiments
Resumo
Accurate forest biomass estimates require the selection of appropriate models of individual trees. Thus, two properties are required in tree biomass modeling: (1) additivity of biomass components and (2) estimator efficiency. This study aimed to develop a system of equations to estimate young eucalyptus aboveground biomass and guarantee additivity and estimator efficiency. Aboveground eucalyptus biomass models were calibrated using four methods: generalized least squares (GLS), weighted least squares (WLS), seemingly unrelated regression (SUR), and weighted seemingly unrelated regression (WSUR). The approaches were compared with regard to performance, additivity, and estimator efficiency. The methods did not differ with regard to the mean biomass estimation; therefore, their performance was similar. The GLS and WLS approaches did not satisfy the additivity principle, as the sum of the biomass components was not equal to total biomass. However, this was not observed with the SUR and WSUR approaches. With regard to estimator efficiency, the WSUR approach resulted in narrow confidence intervals and an efficiency gain of over 20%. The WSUR approach should be used in forest biomass modeling as it resulted in effective estimators while ensuring equation additivity, thus providing an easy and accurate alternative to estimate the initial biomass of eucalyptus stands in ecophysiological models.
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Referências
António, N., Tomé, M., Tomé, J., Soares, P., & Fontes, L. (2007). Effect of tree, stand, and site variables on the allometry of Eucalyptus globulus tree biomass. Canadian Journal of Forest Research, 37, 895-906. DOI: 10.1139/X06-276
Behling, A., Péllico Netto, S., Sanquetta, C. R., Corte, A. P. D., Affleck, D. L. R., Rodrigues, A. L., & Behling, M. (2018). Critical analyses when modeling tree biomass to ensure additivity of its components. Anais da Academia Brasileira de Ciências, 90(2), 1759-1774. DOI: 10.1590/0001-3765201820170684
Binkley, D., Stape, J. L., & Ryan, M. G. (2004). Thinking about efficiency of resource use in forests. Forest Ecology and Management, 193, 5-16. DOI: 10.1016/j.foreco.2004.01.019
Dong, L.; Zhang, L., & Li, F. (2014). A compatible system of biomass equations for three conifer species in Northeast, China. Forest Ecology and Management, 329, 306-317. DOI: 10.1016/j.foreco.2014.05.050
Fu, L., Zeng, W., & Tang, S. (2017). Individual tree biomass models to estimate forest biomass for large spatial regions developed using four pine species in China. Forest Science, 63(3), 241-249. DOI: 10.5849/FS-2016-055
Hakamada, R., Hubbard, R. M., Ferraz, S., Stape, J. L., & Lemos, C. (2017). Biomass production and potential water stress increase with planting density in four highly productive clonal Eucalyptus genotypes. Southern Forests: a Journal of Forest Science, 79(3), 251-257. DOI: 10.2989/20702620.2016.1256041
Nizami, S. M., Yiping, Z., Zheng, Z., Zhiyun, L., Guoping, Y., & Liqing, S. (2017). Evaluation of forest structure, biomass and carbon sequestration in subtropical pristine forests of SW China. Environmental Science and Pollution Research, 24, 8137-8146. DOI: 10.1007/s11356-017-8506-7
Parresol, B. R. (1999). Assessing tree and stand biomass: critical comparisons. Forest Science, 45(4), 573-593.
Parresol, B. R. (2001). Additivity of nonlinear biomass equations. Canadian Journal of Forest Research, 31, 865-878. DOI: 10.1139/x00-202
Payn, T., Carnus, J. M., Freer-Smith, P., Kimberley, M., Kollert W, Liu, S., … Wingfield, M. J. (2015). Changes in planted forests and future global implications. Forest Ecology and Management, 352, 57-67. DOI: 10.1016/j.foreco.2015.06.021
Picard, N., Santi-André, L., & Henry, M. (2012). Manual for building tree volume and biomass allometric equations: from field measurement to prediction. Rome, IT: FAO; CIRAD.
Sanquetta, C. R., Behling, A., Corte, A. P. D., Péllico Netto, S., Schikowski. A. B., & Amaral, M. K. (2015). Simultaneous estimation as alternative to independent modeling of tree biomass. Annals of Forest Science, 72, 1099-1112. DOI: 10.1007/s13595-015-0497-2
Statistical Analysis System [SAS]. (2009). SAS/STAT 9.2 User’ s Guide (2nd ed.). Cary, NC: SAS Institute Inc.
Vega-Nieva, D. J., Valero, E., Picos, J., & Jiménez, E. (2015). Modeling the above and belowground biomass of planted and coppiced Eucalytpus globulus stands in NW Spain. Annals of Forest Science, 72, 967-980. DOI: 10.1007/s13595-015-0493-6
Viera, M., Schumacher, M. V., Bonacina, D. M., Oliveira Ramos, L. O., & Rodríguez-Soalleiro, R. (2017). Biomass and nutrient allocation to aboveground components in fertilized Eucalyptus saligna and E. urograndis plantations. New Forest, 48, 445-462. DOI: 10.1007/s11056-017-9572-x
Vonderach, C., Kändler, G., & Dormann, C.F. (2018). Consistent set of additive biomass functions for eight tree species in Germany fit by nonlinear seemingly unrelated regression. Annals of Forest Science, 75(49). DOI: 10.1007/s13595-018-0728-4
Wang, X., Zhao, D., Liu, G., Yang, C., & Teskey, R. O. (2018). Additive tree biomass equations for Betula platyphylla Suk. plantations in Northeast China. Annals of Forest Science, 75(60). DOI: 10.1007/s13595-018-0738-2
Zellner, A. (1962). An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. Journal of American Statistical Association, 57(298), 348-368. DOI: 10.1080/01621459.1962.10480664
Zhang, C., Peng, D. L., Huang, G. S., & Zeng, W. S. (2016). Developing aboveground biomass equations both compatible with tree volume equations and additive systems for single-trees in poplar plantations in Jiangsu Province, China. Forests, 7(32). DOI: 10.3390/f7020032
Zhang, H., Wang, K., Xu, X., Song, T., Xu, Y., & Zeng, F. (2015). Biogeographical patterns of biomass allocation in leaves, stems, and roots in Chinas forests. Scientific Reports, 5, 1-12. DOI: 10.1038/srep15997
Zhao, D., Kane, M., Markewitz, D., Teskey, R., & Clutter, M. (2015). Additive tree biomass equations for midrotation loblolly pine plantations. Forest Science, 61(4), 613-623. DOI: 10.5849/forsci.14-193
Zhao, D., Westfall, J., Coulston, J. W., Lynch, T. B., Bullock, B. P., & Montes, C. R. (2019). Additive biomass equations for slash pine trees: Comparing three modeling approaches. Canadian Journal of Forest Research, 49, 27-40. DOI: 10.1139/cjfr-2018-0246
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