Nnamdi Azikiwe Üniversitesi, Awka, Nijerya'daki Tectona grandis Linn f. plantasyonunun yerüstü biyokütle tahmin modelleri

Abstract

Ağaç biyokütlesi, çok çeşitli çevresel koşullarda orman ekosistemlerinin yapısal ve işlevsel özelliklerinin önemli bir göstergesi olarak kabul edilir. Topraküstü biyokütle (TÜB), gövde, kütük, dal, kabuk, tohum ve yapraklar dahil olmak üzere toprağın üstündeki canlı bitki örtüsünü ifade etmektedir. Tik (Tectona grandis Linn f.), Nijerya'da popüler bir egzotik ağaç türü olup büyük ve küçük topluluklar halinde ormanlık alanlarda yaygın olarak yetiştirilmektedir. Bu çalışmanın amacı, sürdürülebilir yönetim için Nijerya Awka’daki Nnamdi Azikiwe Üniversitesi’nde bulunan tik plantasyonundaki biyokütle miktarının tahmini için modeller geliştirmektir. Plantasyondaki tüm tik ağaçlarının göğüs yüksekliği çapı (DBH), kütük çapı (Ds) ve toplam ağaç boyu (TH) ölçülmüştür. Kütük çapını bir değişken olarak kullanan bir denklem yardımıyla tüm ağaçların topraküstü biyokütle miktarları tahmin edilmiştir. Verilere ait tanımlayıcı istatistikler belirlenmiş, iki değişkenli korelasyon analizi yapılmış ve altı (6) doğrusal regresyon fonksiyonu geliştirilmiştir. Toplamda 295 ağaç ile gerçekleştirilen bu çalışmada, ortalama topraküstü biyokütle miktarı 18.61 kg olarak belirlenmiştir. Çalışma kapsamında geliştirilen modeller arasında en başarılı model, en yüksek düzeltilmiş belirleme katsayısı (0,984), en düşük tahminin standart hatası (0,308) ve en düşük Akaike bilgi kriteri (-690,974) ile Semi Log 3 (B5) modeli olmuştur. Bu nedenle, Model B5, plantasyonun gelecekteki envanteri ve yönetimi için önerilmektedir.

Keywords

• Karbon bütçesi
• Orman envanteri
• Orman modelleme
• Regresyon
• Ağaç büyüme değişkenleri

Aboveground biomass estimation models for Tectona grandis Linn f. plantation in Nnamdi Azikiwe University, Awka, Nigeria

Abstract

Tree biomass is considered a useful indicator of structural and functional attributes of forest ecosystems across a wide range of environmental conditions. The aboveground biomass refers to the living vegetation above the soil, including stem, stump, branches, bark, seeds, and foliage. Teak (Tectona grandis Linn f.) is a popular exotic tree species in Nigeria; it is widely grown in both large scale and small community woodlots. The objective of this study was to develop models for estimation of biomass content of Teak plantation in Nnamdi Azikiwe University, Awka, Nigeria for sustainable management. Data on the diameter at breast height (D) and total height (H) of all teak stands in the plantation were recorded. Non-destructive method using an existing equation was used to estimate the aboveground biomass (AGB) of the individual stands from stump diameter. The Data was subjected to descriptive statistics, bivariate correlation analysis and fitted to six (6) linear regression functions. A total of 295 trees were measured with mean AGB of 18.61 kg. Out of the AGB prediction models developed for the study area, the Semi Log 3 (B5) model had the best predictive ability; with the highest adjusted coefficient of determination (0.984) and the lowest standard error of estimate (0.308), and Akaike information criterion (-690.974). Model B5 (B=0.764+0.764D-0.105lnH) is therefore recommended for future inventory and management of the plantation.

Keywords

• Carbon stocks
• Forest inventory
• Forest modelling
• Regression
• Tree growth variables

References

1. Aabeyir, R., Adu-Bredu, S., Agyare, W.A., Weir, M.J.C., 2020. Allometric models for estimating aboveground biomass in the tropical woodlands of Ghana, West Africa. Forest Ecosystems, 7(1): 1-23.
2. Adekunle, V.A.J., Akindele, S.O., Fuwape, J.A., 2004. Structure and yield models of tropical lowland rainforest ecosystem of southwest Nigeria. Food, Agriculture and Environment, 2(2): 395-399.
3. Ali, A., Xu, M.S., Zhao, Y.T., Zhang, Q.Q., Zhou, L.L., Yang, X.D., Yan, E.R., 2015. Allometric biomass equations for shrub and small tree species in subtropical China. Silva Fennica. 49: 1-10.
4. Baccini, A., Walker, W., Carvalho, L., Farina, M., Sulla-Menashe, D., Houghton, R.A., 2017. Tropical forests are a net carbon source based on aboveground measurements of gain and loss. Science, 358(6360): 230-234.
5. 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.
6. Brown, S., Gillespie, A.R., Lugo, A.E., 1989. Biomass estimation methods for tropical forests with applications to forest inventory data. Forest Science, 35: 881-902.
7. Brown, S., 1997. Estimating biomass and biomass change of tropical forests: A Primer (FAO Forestry Paper-134), FAO, United Nations, Rome, Italy.
8. Brown, S.L., Schroeder, P., Kern, J.S., 1999. Spatial distribution of biomass in forests of the eastern USA. Forest Ecology and Management, 123: 81-90.

9. Chave, J., Andalo, C., Brown, S., Cairns, M., Chambers, J.C., Eamus, D., Fölster, H., Fromard, F., Higuchi, N., Kira, T., Lescure, J., 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: 87-99.
10. Chave, J., Réjou‐Méchain, M., Búrquez, A., Chidumayo, E., Colgan, M.S., Delitti, W.B., Duque, A., Eid, T., Fearnside, P.M., Goodman, R.C., Henry, M., 2014. Improved allometric models to estimate the aboveground biomass of tropical trees. Global Change Biology, 20(10): 3177–3190. Chukwu, O., Emebo, A.A., 2020. Nonlinear yield models for young Tectona grandis L. f. stands in Nnamdi Azikiwe University Awka, Southeastern Nigeria. Tropical Plant Research, 7(3): 678-683.
11. Chukwu, O., Ezenwenyi, J.U., 2020. Utilization of Tree Stump Dimension in Forest Modelling and Management. In: Research Trends in Multidisciplinary Research Volume – 14 (Ed: Jayakumar, R.), AkiNik Publications, New Delhi, India, pp.103-121.
12. Chukwu, O., Ezenwenyi, J.U., Kenechukwu, T.V., 2020. Checklist and abundance of open grown medico-ethnoforest tree species in Nnamdi Azikiwe University, Awka, Nigeria. Asian Journal of Biological Sciences, 13(1): 105-112.
13. Claesson, S., Sahlen, K., Lundmark, T., 2001. Functions for biomass estimation of young Pinus sylvestris, Picea abies and Betula spp. From stands in Northern Sweden with high stand densities. Scandinavian Journal Forest Research, 16: 138–146.
14. Cole, T.G., Ewel, J.J., 2006. Allometric equations for four valuable tropical tree species. Forest Ecology and Management, 229 (1-3): 351-360.
15. Emebo, A.A., 2019. Inventory analysis and volume models of for Tectona grandis Linn. f. plantation in Nnamdi Azikiwe University, Awka, Nigeria. Bachelor’s Project, Department of Forestry and Wildlife, Nnamdi Azikiwe University, Awka, Nigeria.
16. Ige, P.O., 2018. Above ground biomass and carbon stock estimation of Gmelina arborea (Roxb.) stands in Omo Forest Reserve, Nigeria. Journal of Research in Forestry, Wildlife and Environment, 10(4): 71-80.
17. Kurz, W.A., Apps, M.J., 1999. A 70-year retrospective analysis of carbon fluxes in the Canadian forest sector. Ecological Applications, 9(2): 526-547.
18. Machado, S.A., Figueiredo, A. 2003. Dendrometria. UFPR, Curitiba. 309 p
19. Mitchard, E.T.A., 2018. The tropical forest carbon cycle and climate change. Nature, 559: 527–534.
20. Pan, Y., Birdsey, R.A., Fang, J., Houghton, R., Kauppi, P.E., Kurz, W.A., Philips, O.L., Shvidenko, A., Lewis, S.L., Canadell, J.G., Ciais, P., Jackson, R.B., Pacala, S.W., McGuire, A.D., Piao, S., Rautiainen, A., Sitch, S., Hayes, D., 2011. A large and persistent carbon sink in the World’s forests. Science, 333 (6045): 988–993.
21. Tsoumis, G., 1991. Science and technology of wood: structure, properties, utilization. Van Nostrand Reinhold, New York.
22. Verhaegen, D., Fofana, I.J., Logossa, Z.A., Ofori, D., 2010. What is the genetic origin of teak (Tectona grandis L.) wood resources and their contribution to supply chains of commercial wood. Australian Forestry, 80:10–25.
23. Yang, K., Tu, J., Chen, T., 2019. Homoscedasticity: an overlooked critical assumption for linear regression. General Psychiatry, 32: e100148.