Stand growth modeling system for planted teak (Tectona grandis L.f.) in tropical highlands

•Including site index and stand density improved the prediction of the growth and yield of planted teak.•A simultaneous modeling system used to predict the growth of the planted teak stand.•Planted growth and yield of teak were predicted under varying management regimes. We developed a system for mo...

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Veröffentlicht in:Trees, Forests and People (Online) Forests and People (Online), 2022-09, Vol.9, p.100308, Article 100308
Hauptverfasser: Huy, Bao, Truong, Nguyen Quy, Khiem, Nguyen Quy, Poudel, Krishna P., Temesgen, Hailemariam
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Sprache:eng
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Zusammenfassung:•Including site index and stand density improved the prediction of the growth and yield of planted teak.•A simultaneous modeling system used to predict the growth of the planted teak stand.•Planted growth and yield of teak were predicted under varying management regimes. We developed a system for modeling the growth and yield of planted teak (Tectona grandis L.f.) for small diameter products under varying management regimes in the tropical Central Highlands of Viet Nam. We compared an independent and simultaneous system of models to predict dominant height (Ho), quadratic mean diameter (Dg), averaged tree height (Hg) with Dg, and mean tree volume (V) versus stand age (A). In addition, the model system performance with and without site index (SI) and stand density (N) as covariates were compared using K-fold cross-validation. The best modeling system was obtained with the simultaneously fit models that included SI and N and were in the form of: Dg=Dm/(1 + a × exp(-b × A)) × exp[e1 × (SI– 15) + e2/1000 × (N – 722)]; Hg=Hm × exp(-a × exp(-b × A)) × exp[e1 × (SI– 15) + e2/1000 × (N – 722)]; and V=π4×104Dg2×Hg×0.45; where Dm, Hm, a, b, e1and e2 were the parameters to be estimated. These models will help predict the growth and yield of teak planted for different planting schemes, includings monoculture, agroforestry, and forest enrichment planting in this region.
ISSN:2666-7193
2666-7193
DOI:10.1016/j.tfp.2022.100308