alexa Growth and Yield Models for Uneven-Aged Secondary Forest in IITA, Ibadan, Nigeria
ISSN: 2168-9776

Forest Research: Open Access
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Research Article

Growth and Yield Models for Uneven-Aged Secondary Forest in IITA, Ibadan, Nigeria

Aghimien EV1, Osho JSA2, Hauser S3, Deni B3, Ade-Oni VD4* and Oboite FO5

1Department of Forestry Technology, Federal College of Forestry, Oyo State, Nigeria

2Department of Forest Resources Management, University of Ibadan, Oyo State, Nigeria

3International Institute of Tropical Agriculture (IITA), Oyo State, Nigeria

4Department of Forest Production and Products, Federal University of Agriculture, Makurdi, Benue State, Nigeria

5Department of Forestry and Wildlife, University of Benin, Edo State, Nigeria

*Corresponding Author:
Ade-Oni VD
Department of Forestry Technology
Federal College of Forestry
Oyo State, Nigeria
Tel: +234-805-064-4493
E-mail: [email protected]

Received date: Feb 04, 2016; Accepted date: Mar 23, 2016; Published date: Mar 30, 2016

Citation: Aghimien EV, Osho JSA, Hauser S, Deni B, Ade-Oni VD, et al. (2016) Growth and Yield Models for Uneven-Aged Secondary Forest in IITA, Ibadan, Nigeria. Forest Res 5:173. doi:10.4172/2168-9776.1000173

Copyright: © 2016 Ade-Oni VD, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

The development of effective and accurate models to predict forest growth and products is essential for forest managers and planners. Decision-makers need information on the present yield of the forest for the purpose of monitoring growth. Despite the importance of growth and yield models in the determination of appropriate forest management strategies, no study has been undertaken in IITA’s Forest Reserve. Volume equations for predicting tree volume were developed for tree species in IITA’s Forest Reserve. Complete enumeration of trees larger than 5 cm was carried out in fifteen permanent sample plots of size 20 m × 20 m. The data assessed were diameter at base, diameter at middle, diameter at top, diameter at breast height and total height for 1214 tree species. All trees encountered in each plot were identified with their botanical names. The results revealed that there were 34 important tree species distributed among 23 families in the reserve. The most abundant tree species is Newbouldia laevis while the family with the highest number of species is Moraceae with six species. The number of observations per species ranged from 1 to 255 while the diameter at breast height ranged from 5.00 cm to 201.20 cm and highest percentage of the trees belong to the least diameter class (5-9 cm). The volume equations were fitted for individual species greater than or equal to five and all species combined. The assessment criteria coefficient of determination (R2), Standard error of estimate (SEE) with the validation results (using simple linear regression equation, percentage bias and probability plots of residuals) show that the model of logarithm transformed diameter at base and logarithm transformed total height was of good fit. Very high R2 values, small SEE and percentage biases were obtained. The model was discovered to be very adequate for tree volume estimation in the study area. It is therefore recommended for further use in this ecosystem and in any other forest ecosystem with similar site condition.

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