Models and form factors for stand volume estimation in natural forest ecosystems: a case study of Katarniaghat Wildlife Sanctuary (KGWS), Bahraich District, India

Adekunle, V. A. J.; Nair, K. S. S.; Srivastava, Anita; Singh, Niraj Kumar

doi:10.1007/s11676-013-0347-8

Cited by 24 publications

(26 citation statements)

References 22 publications

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“…Similarly, we also applied a number of previously developed total tree volume models (Munishi and Shear, 2004;Adekunle, 2007;Adekunle et al, 2013) and then compared predicted volumes with observed volumes by means of MPE values that were tested for statistical significance by means of student t-tests. The results are shown in Table 8.…”

Section: Test Of Previously Developed Volume Modelsmentioning

confidence: 99%

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Volume Models for Single Trees in Tropical Rainforests in Tanzania

Masota¹,

Zahabu²,

Malimbwi³

et al. 2014

JENR

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The present study was the first to develop total tree, stem and branches volume models for rainforests in southeastern Africa based on destructive sampling. The number of sample trees was 60 and diameter at breast height (dbh) and total tree height (h) ranged from 6 to 117 cm and from 6.4 m to 50 m, respectively. Large parts of the total volume and stem volume variations were explained by the models (Pseudo-R 2 ranged from 0.85 to 0.93) and they performed relatively well over different size classes. When considering the challenges in height measurements in rainforests, we in general recommend applying model 3 with dbh only as independent variable. For large trees we recommend model 2 (dbh and h as independent variables) because of the moderating effect h has on volume predictions. If accurate stem volumes are needed for forestry licensing or for calculating compensation of timber loss, we also recommend model 2. As long as the allometry of the trees obviously is not different from that of our study site, the developed models may also be applied for rainforests elsewhere in Tanzania, but further testing of the models is also recommended.

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Section: Test Of Previously Developed Volume Modelsmentioning

confidence: 99%

“…From Adekunle (2007) we applied the following volume model: v = 43.36(1-e -0.067×g ) 3 , where e is the base of the natural logarithm. The model was based on data from a rainforest in southwest Nigeria.…”

Section: Test Of Previously Developed Volume Modelsmentioning

confidence: 99%

Volume Models for Single Trees in Tropical Rainforests in Tanzania

Masota¹,

Zahabu²,

Malimbwi³

et al. 2014

JENR

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“…Therefore, it can be assumed that these variables tend to present intercorrelation or collinearity (Scolforo, 2005;Silva, Ferreira, Silva, & Cespedes, 2009;Valente, Queiroz, Pinheiro, & Monteiro, 2011). Although this happened, the Student's t-test becomes important for choosing models with multiple parameters, presenting a value not different from zero and indicating that the variable is not relevant to explain significant variations in the response variable (Mayer & Butler, 1993;Rykiel Jr., 1996;Robinson & Froese, 2004;Adekunle, Nair, Srivastava, & Singh, 2013;Lima et al, 2014;Silva & Santana, 2014). Equations using log diameter alone as an explanatory variable resulted in adjustments with less statistical precision for all cases.…”

Section: Discussionmentioning

confidence: 99%

Lumber volume modeling of Amazon Brazilian species

Lima

Ferreira

Silva

et al. 2018

Journal of Sustainable Forestry

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Accurate estimates of lumber volume become an important indicator of production and monetary value for a sawmill. However, such estimates are only obtained directly after logging, and no accurate predictions are made for the Amazonian commercial species. In this sense, the objective was to generate equations of lumber volume for commercial species in Amapá (a state in northern Brazil) by adjusting and selecting regression models. The data of 50 logs processed from 10 commercial species were collected, as well as the quantity and volume of sawn products. Sixteen (16) statistical models were adjusted and statistical weights were performed to evaluate the quality of the estimates and to select the best equation by species. In summary, precise estimates of lumber volume can be obtained by the nº16 model for Carapa guianensis, while the models nº13 and nº15 are the most recommended for Dinizia excelsa and Hymenolobium petraeum, respectively. Model 7 presented the best adjustments for Hymenaea courbaril and Vochysia guianensis. Equations using only the log diameter variable suggest less precise estimates. Also, the log volume should be considered as an important predictor variable to obtain the serrated/ lumber volume for the different Amazonian commercial species.

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“…The volume modeling theme has been treated by many researchers and regression analysis is applied to fit equations, as presented in: Rufini et al (2010), Abdullah et al (2011), Alegria (2011), Özçelik and Brooks (2012), Özçelik and Bal (2013), Adekunle et al (2013), Fortin et al (2013), Gonzalez-Benecke et al (2014), Ver Planck and MacFarlane (2014), Téo et al (2018), Urbano et al (2018).…”

Section: Introductionmentioning

confidence: 99%