Allometric Models for Estimating Tree Biomass of Dryland Secondary Forest in East Halmahera
Isi Artikel Utama
Abstrak
Biomass estimation of secondary forests is required to support the emission reduction of carbon dioxide through an enhancement of forest carbon stocks. Commonly, forest biomass is indirectly estimated using tree biomass allometric models that are developed based on a destructive sampling of sample trees. The availability of biomass allometric models for secondary forests in Indonesia is still limited, particularly for secondary forest ecosystems in eastern Indonesia. This study aimed to develop allometric biomass models for mixed-species trees in a secondary forest of East Halmahera, North Maluku, and to compare their accuracies with some other allometric biomass models that commonly used for estimating biomass of secondary forests. The tree biomass measurement was conducted by using a destructive sampling of 18 mixed-species trees (with diameter range of 5,4 – 36,9 cm) in a secondary forest. The samples of each tree component (stem, branch, twig, and leaf) were analyzed in a laboratory to determine the biomass of each sample tree. Allometric models were developed by using a non-linear regression analysis, which were then compared with other allometric models. This study revealed that the biomass of mixed-species trees in the study area could be estimated accurately using the M7 model that used diameter, height, and wood density variables. Such local allometric model was more accurate than other allometric models commonly used for estimating tropical forest biomass. Alternatively, the M3 model that used diameter and height variables could also be used when wood density data was not available. The local allometric models from this study can enrich the availability of biomass allometric models for secondary forest ecosystems in eastern Indonesia.
Rincian Artikel
Hak Cipta (c) 2020 Jurnal Wasian
Artikel ini berlisensi Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright and License
All articles published in Wasian Journal are the property of the authors. By submitting an article to Wasian Journal, authors agree to the following terms:
-
Copyright Ownership: The author(s) retain copyright and full publishing rights without restrictions. Authors grant the journal the right to publish the work first and to distribute it as open access under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
-
Licensing: Articles published in Wasian Journal are licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). This license allows others to share, copy, and redistribute the material in any medium or format, and adapt, remix, transform, and build upon the material for any purpose, even commercially, provided that proper credit is given to the original author(s) and the source of the material
This work is licensed under a Creative Commons Attribution 4.0 International License. -
Author's Rights: Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges and greater citation of published work.
-
Third-Party Content: If your article contains material (e.g., images, tables, or figures) for which you do not hold copyright, you must obtain permission from the copyright holder to use the material in your article. This permission must include the right for you to grant the journal the rights described above.
-
Reprints and Distribution: Authors have the right to distribute the final published version of their work (e.g., post it to an institutional repository or publish it in a book), provided that the original publication in Wasian Journal is acknowledged.
For the reader you are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rightsmay limit how you use the material.
Anitha, K., Verchot, L. V., Joseph, S., Herold, M., Manuri, S., & Avitabile, V. (2015). A review of forest and tree plantation biomass equations in Indonesia. Annals of Forest Science, 72(8), 981–997. https://doi.org/10.1007/s13595-015-0507-4
Basuki, T. M., van Laake, P. E., Skidmore, A. K., & Hussin, Y. A. (2009). Allometric equations for estimating the above-ground biomass in tropical lowland Dipterocarp forests. Forest Ecology and Management, 257(8), 1684–1694. https://doi.org/10.1016/j.foreco.2009.01.027
Brown, I. F., Martinelli, L. A., Thomas, W. W., Moreira, M. Z., Cid Ferreira, C. A., & Victoria, R. A. (1995). Uncertainty in the biomass of Amazonian forests: An example from Rondônia, Brazil. Forest Ecology and Management, 75(1), 175-189. https://doi.org/10.1016/0378-1127(94)03512-U
BSN. (2011). SNI 7725: 2011 Penyusunan Persamaan Alometrik untuk Penaksiran Cadangan Karbon Hutan Berdasar Pengukuran Lapangan (Ground Based Forest Carbon Accounting). Jakarta: Badan Standarisasi Indonesia (BSN).
Burnham, K. P., & Anderson, D. R. (2002). Model Selection and Multimodel Inference: a Practical Information-Theoretic Approach. New York: Springer-Verlag.
Chave, J., Réjou-Méchain, M., Búrquez, A., Chidumayo, E., Colgan, M. S., Delitti, W. B. C., & Vieilledent, G. (2014). Improved allometric models to estimate the aboveground biomass of tropical trees. Global Change Biology, 20(10), 3177–3190. https://doi.org/10.1111/gcb.12629
Dutcă, I., McRoberts, R. E., Næsset, E., & Blujdea, V. N. B. (2019). A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models. Forestry: An International Journal of Forest Research, 92(5), 627-634. https://doi.org/10.1093/forestry/cpz041
Ebuy, J., Lokombe, J., Ponette, Q., Sonwa, D., & Picard, N. (2011). Allometric equation for predicting aboveground biomass of three tree species. Journal of Tropical Forest Science, 23(2), 125–132.
Feldpausch, T. R., Banin, L., Phillips, O. L., Baker, T. R., Lewis, S. L., Quesada, C. A., & Lloyd, J. (2011). Height-diameter allometry of tropical forest trees. Biogeosciences, 8(5), 1081–1106. https://doi.org/10.5194/bg-8-1081-2011
Feldpausch, T. R., Lloyd, J., Lewis, S. L., Brienen, R. J. W., Gloor, M., Monteagudo Mendoza, A., & Phillips, O. L. (2012). Tree height integrated into pantropical forest biomass estimates. Biogeosciences, 9(8), 3381–3403. https://doi.org/10.5194/bg-9-3381-2012
Flores, O., & Coomes, D. A. (2011). Estimating the wood density of species for carbon stock assessments. Methods in Ecology and Evolution, 2(2), 214–220. https://doi.org/10.1111/j.2041-210X.2010.00068.x
He, H., Zhang, C., Zhao, X., Fousseni, F., Wang, J., Dai, H., & Zuo, Q. (2018). Allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, Northeastern China. PLOS ONE, 13(1), e0186226. https://doi.org/10.1371/journal.pone.0186226
Henry, M., Besnard, A., Asante, W. A., Eshun, J., Adu-Bredu, S., Valentini, R., & Saint-André, L. (2010). Wood density, phytomass variations within and among trees, and allometric equations in a tropical rainforest of Africa. Forest Ecology and Management, 260(8), 1375–1388. https://doi.org/10.1016/j.foreco.2010.07.040
Hunter, M., Keller, M., Vitoria, D., & Morton, D. (2013). Tree height and tropical forest biomass estimation. Biogeosciences, 10(12), 8385–8399. https://doi.org/10.5194/bg-10-8385-2013
Huy, B., Kralicek, K., Poudel, K. P., Phuong, V. T., Khoa, P. V., Hung, N. D., & Temesgen, H. (2016). Allometric equations for estimating tree aboveground biomass in evergreen broadleaf forests of Viet Nam. Forest Ecology and Management, 382, 193–205. https://doi.org/10.1016/j.foreco.2016.10.021
ICRAF. (2020). Tree functional attributes and ecological database: Wood density. Retrieved November 25, 2020, from World Agroforestry (ICRAF). http://db.worldagroforestry.org//wd
Ketterings, Q. M., Coe, R., van Noordwijk, M., 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. Forest Ecology and Management, 146(1), 199–209. https://doi.org/10.1016/S0378-1127(00)00460-6
Krisnawati, H., Adinugroho, W. C., & Imanuddin, R. (2012). Monograf: Model-Model Alometrik untuk Pendugaan Biomassa Pohon pada Berbagai Tipe Ekosistem Hutan di Indonesia. Bogor: Pusat Penelitian dan Pengembangan Konservasi dan Rehabilitasi, Badan Penelitian dan Pengembangan Kehutanan.
Kusmana, C., Hidayat, T., Tiryana, T., Rusdiana, O., & Istomo. (2018). Allometric models for above- and below-ground biomass of Sonneratia spp. Global Ecology and Conservation, 15, e00417. https://doi.org/10.1016/j.gecco.2018.e00417
Kuyah, S., Dietz, J., Muthuri, C., Jamnadass, R., Mwangi, P., Coe, R., & Neufeldt, H. (2012). Allometric equations for estimating biomass in agricultural landscapes: I. Aboveground biomass. Agriculture, Ecosystems & Environment, 158, 216–224. https://doi.org/10.1016/j.agee.2012.05.011
Larjavaara, M., & Muller-Landau, H. C. (2013). Measuring tree height: a quantitative comparison of two common field methods in a moist tropical forest. Methods in Ecology and Evolution, 4(9), 793-801. https://doi.org/10.1111/2041-210X.12071
Magnussen, S., Kleinn, C., & Fehrmann, L. (2020). Wood volume errors from measured and predicted heights. European Journal of Forest Research, 139(2), 169–178. https://doi.org/10.1007/s10342-020-01257-9
MAP. (2018). RKUPHHK-HA dalam Hutan Alam pada Hutan Produksi Berbasis IHMB Periode Tahun 2018–2027. Jakarta: MAP (PT Mahakarya Agra Pesona).
Mardiatmoko, G., Kastanya, A., & Hatulesila, J. W. (2016). Persamaan allometrik pala (Myristica fragrans Houtt) untuk pendugaan biomassa atas tanah pada lahan agroforestri guna mendukung program REDD+ di Maluku. Jurnal Makila, 9(1), 97–107.
Maulana, S. I., & Pandu, J. (2011a). Persamaan-persamaan allometrik genera Instia sp. untuk pendugaan total biomassa atas tanah pada kawasan hutan tropis Papua. Jurnal Penelitian Sosial dan Ekonomi Kehutanan, 7(4), 275–284.
Maulana, S. I., & Pandu, J. (2011b). Persamaan-persamaan allometrik untuk pendugaan total biomassa atas tanah pada genera Pometia di kawasan hutan tropis Papua. Jurnal Penelitian Sosial dan Ekonomi Kehutanan, 8(4), 288–298.
MoEF. (2018). The State of Indonesia's Forests 2018. Jakarta: MoEF (Ministry of Environment and Forestry).
Molto, Q., Hérault, B., Boreux, J.-J., Daullet, M., Rousteau, A., & Rossi, V. (2014). Predicting tree heights for biomass estimates in tropical forests – a test from French Guiana. Biogeosciences, 11(12), 3121–3130. https://doi.org/10.5194/bg-11-3121-2014
Molto, Q., Rossi, V., & Blanc, L. (2013). Error propagation in biomass estimation in tropical forests. Methods in Ecology and Evolution, 4(2), 175–183. https://doi.org/10.1111/j.2041-210x.2012.00266.x
Picard, N., Saint-André, L., & Henry, M. (2012). Manual for Building Tree Volume and Biomass Allometric Equations: from Field Measurement to Prediction. Rome: FAO/CIRAD.
Pinheiro, J., Bates, D., DebRoy, S., & Sarkar, D. (2020). nlme: Linear and Nonlinear Mixed Effects Models: R package version 3.1-148. Retrieved from https://CRAN.R-project.org/package=nlme
Puc-Kauil, R., Ángeles-Pérez, G., Valdéz-Lazalde, J., Reyes-Hernández, V., Dupuy-Rada, J., Schneider, L., . . . García-Cuevas, X. (2020). Allometric equations to estimate above-ground biomass of small-diameter mixed tree species in secondary tropical forests. [Allometric equations to estimate above-ground biomass of small-diameter mixed tree species in secondary tropical forests]. iForest - Biogeosciences and Forestry, 13(3), 165–174. https://doi.org/10.3832ifor3167-013
R Core Team. (2020). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from URL https://www.R-project.org/
Rawlings, J. O., Pantula, S. G., & Dickey, D. A. (1998). Applied Regression Analysis: A Research Tool (Second ed.). New York: Springer.
Réjou-Méchain, M., Tanguy, A., Piponiot, C., Chave, J., & Hérault, B. (2017). biomass: an r package for estimating above-ground biomass and its uncertainty in tropical forests. Methods in Ecology and Evolution, 8(9), 1163–1167. https://doi.org/10.1111/2041-210x.12753
Rutishauser, E., Noor’an, F., Laumonier, Y., Halperin, J., Rufi’ie, Hergoualc’h, K., & Verchot, L. (2013). Generic allometric models including height best estimate forest biomass and carbon stocks in Indonesia. Forest Ecology and Management, 307, 219–225. https://doi.org/10.1016/j.foreco.2013.07.013
Sanquetta, C. R., Dalla Corte, A. P., Behling, A., de Oliveira Piva, L. R., Péllico Netto, S., Rodrigues, A. L., & Sanquetta, M. N. I. (2018). Selection criteria for linear regression models to estimate individual tree biomasses in the Atlantic Rain Forest, Brazil. Carbon Balance and Management, 13(1), 25. https://doi.org/10.1186/s13021-018-0112-6
Sileshi, G. W. (2014). A critical review of forest biomass estimation models, common mistakes and corrective measures. Forest Ecology and Management, 329, 237–254. https://doi.org/10.1016/j.foreco.2014.06.026
Stas, S. M., Rutishauser, E., Chave, J., Anten, N. P. R., & Laumonier, Y. (2017). Estimating the aboveground biomass in an old secondary forest on limestone in the Moluccas, Indonesia: Comparing locally developed versus existing allometric models. Forest Ecology and Management, 389, 27–34. https://doi.org/10.1016/j.foreco.2016.12.010
Tiryana, T., Tatsuhara, S., & Shiraishi, N. (2011). Empirical models for estimating the stand biomass of teak plantations in Java, Indonesia. Journal of Forest Planning, 16(Special_Issue), 177–188. https://doi.org/10.20659/jfp.16.Special_Issue_177
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.2011.07.018
Zanne, A., Lopez-Gonzalez, G., Coomes, D., Ilic, J., Jansen, S., Lewis, S., & Chave, J. (2009). Global Wood Density Database. Retrieved from