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International Journal of Scientific and Education Research

Vol. 3, No. 03; 2019

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CONTRIBUTION OF PRIVATE FORESTRY TO FOREST

DEVELOPMENT IN NIGERIA: A CASE STUDY OF EVERGREEN

PLANTER, OGUN STATE

Akinbowale A.S., Adesuyi F.E., Offiah C.J and Fasalejo O.F

Department of Forestry and Wood Technology, Akure, Nigeria. Federal University of

Technology.

P.M.B 704, Ondo State, Akure, Nigeria

ABSTRACT

Private forest refers to trees on private agricultural or forest land used to supplement animal

fodder, fuel wood and other basic resources or simply to provide saleable produce. Data were

collected from Bisrod Furniture Company which is located at Ijari, ijebu-Ogun state. The

company is divided into two sections; The Evergreen tree planter (Plantation section) and the

Furniture section. Interview guides was used to collect information from the company records.

The dominant tree species with plantations of various ages, established by the Evergreen Tree

Planter were selected for measurement of growth characteristics. Four age classes were selected

such that age ranges of the plantations were covered. The Tectona grandis plantation are of two

age-series established in 2005 and 2008, respectively while Mansonia altissima and Nauclea

diderrichii plantations were established in 2005. From each age class, one hectare block was

demarcated and divided into 25 m × 25 m temporary sample plots, from which three (3) plots

were randomly selected. A total of 332 trees were recorded in the sample plots for all the age

series. Number of stem per plot were 88, 78, 84, 82 individuals for Mansonia altissima, Nauclea

diderrichii, Tectona grandis (2005), and Tectona grandis (2008) respectively. Simple linear

model and Logarithm models were generated for volume estimation. Logarithm model gave the

best assessment criteria, and was recommended for further use. The interview guide revealed

that, the company has contributed positively to forest development in Nigeria through

employment opportunities to the people, thus, preventing illegal felling.

Keywords: Private Forestry, Forest Development, Tectona grandis, Mansonia altissima, Nauclea

diderrichii

INTRODUCTION

Nigeria is blessed with large expanse of land area and vegetation. However, these important

resources are not sustainably used or managed. In the past, many people in Nigeria treated the

forest resources as though they were inexhaustible. Today, the story appears to be different as the

average Nigerian now realizes that the forest is highly degraded, however exploitation (both

legally and illegally) of the remaining forests has continued till date. The Nigerian natural

forests, which are the sources of economic trees that produce timber (either for building

construction, furniture, shipbuilding), veneer log, fuel wood or the medicinal plants, etc. have

being over exploited and highly degraded, with some of the species under the threat of becoming

extinct (Ladipo, 2010). Despite this, government investment in the regeneration and management


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of the forest is low and dwindling. Though, the Federal government of Nigeria intended to

establish 1,000,000 ha and 800,000 ha of forest plantations in the high forest and the savannah

zones, respectively by the year 2000, only an estimated 700,000 ha of plantations have been

established in the whole country by 2008 (Sayeret al., 1992; Onyekwelu and Fuwape, 2008).This

has led to the involvement of the private sector in the development and the management of forest

resources in Nigeria. Government tree planting programme operating with limited resources will

not be able to establish trees at the required rate, thereby gradually causing wood shortage in the

country. The only way to quickly set out of this problem is to involve private sector participation

in forestry development in Nigeria.

Private forest refers to trees on private agricultural or forest land used to supplement animal

fodder, fuel wood and other basic resources or simply to provide saleable produce. It may be tree

in small woodlot or trees integrated with agricultural crops as agro forestry (Gwandu, 2001).It

can be integrated into agricultural system to provide forest products and to complement existing

farming enterprise or it can be a stand-alone use of the land. Involvement of private forest

owners in management of forest resources implies the use and management of forest resources

by people who are opportune to own natural or artificial forests. Recognition of the role of forest

management and successful reform of the agriculture sector contributed to the introduction of

private forest. It allows people to participate in forest management through organized

programmes which will educate the populance on importance of growing trees and the benefits

of the forest and its resources, thereby preventing deforestation (Gwandu, 2001).(Adeyoju, 2001)

also stated that the forest service in Nigeria failed to take advantage of the harvest boom period

enjoyed by multinational companies in Nigeria to strike for joint investments in forest plantation

and or regeneration schemes. Today, most of the private sector involvement in plantation

establishment has been limited to individuals and schools.

The Evergreen Tree Planter situated at Ijari, Ijebu-ode is a private forest in Nigeria established to

preserve our natural resources that have been neglected over the years, to promote tree planting,

combat environmental degradation, create job and restore the wealth of Nigeria. Therefore, this

study seeks to assess the level of involvement of private plantation owners in the management

and protection of forest resources in Ogun state, Nigeria.

METHODOLOGY

Study Area

The study was conducted at Ijari, Ijebu-ode, Ogun state, in the tropical rainforest ecosystem of

south-western Nigeria. The area lies between latitude 7.0000ᵒ and longitude 3.5833ᵒ .The

population is about 154,032 (Census, 2006). The area has a warm tropical climate with land area

of 192 km2. It has a geographical landscape that consists of extensive fertile soil suitable for

agriculture. The Mean maximum day-time temperature could be as high as about 32ºC while the

average night-time minimum temperature could drops to about 22ᵒC.The rainy season lasts for 9

months annually, between March and November while the dry seasons usually last for 3 months,

between December and February. Agriculture is the main occupation of the people providing


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income and employment for a large percentage of the population. The evergreen forest

vegetation makes the soil suitable for cultivation of cash crops and food crops.

Methods of Data collection

Data were collected from Bisrod Furniture Company which is located at Ijari, ijebu-Ogun state.

The company is divided into two sections; The Evergreen tree planter (Plantation section) and

the Furniture section. Below is how the data were collected.

Company profile, Activities and Challenges

The data on Evergreen Tree Planter profile was obtained from

(i). The company’s documentations (i.e. records) and

(ii). Through interview guides.

Age and silvicultural history of the plantation was obtained from records. The interview guides

was used to collect information from company records. The interviews targeted top management

staffs that are conversant with the company’s activities, both present and previous.

Measurement of tree growth data

The dominant tree species (with plantations of various ages), established by the Evergreen Tree

Planter were selected for measurement of growth characteristics. Four age classes were selected

such that age ranges of the plantations were covered. From each age class, one hectare block was

demarcated and divided into 25 m x 25 m temporary sample plots, from which three (3) plots

were randomly selected. The following growth variables were enumerated within each selected

sample plot:Diameter at breast height (dbh) of all trees, Diameter at the base, middle and top of

two mean trees, whose dbh are closest to the mean dbh of the plot, Total height of the two mean

trees.

Method of data analysis

The data were obtained from the company records and from the interviews.

Basal Area Estimation: The basal area for each tree was computed using the formula suggested

by (Husch et al., 2003):

4

2DBA

Where: BA = Basal area in m2, D = Diameter at breast height (m), π = Pi (3.142)


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Basal area per hectare for each age series was computed by first pooling and summing the basal

areas of the sample plot from the age series and finding their mean and secondly by multiplying

the mean basal area per plot by 16 (i.e. the number of 25 m x 25 m sample plots in one hectare).

Volume Estimation: The volume of all trees in the sample plots was calculated using the

Newton’s formula:

V=

Where V = Volume (m³), H = Total height (m), Db = Diameter at the base (cm), Dm = Diameter

at the middle (cm), Dt = Diameter at the top (cm) and π = 3.142

Volume per hectare for each age series was computed by first summing the volume of the sample

plots from the age series and finding their mean and secondly by multiplying the mean volume

per plot by 16 (i.e. the number of 25 m x 25 m sample plots in one hectare).

Volume model generation: Volume equations are mathematical expressions which relate tree

volume to tree’s measurable attributes such as diameter at breast and/or height. They are used to

estimate the average content for standing trees of various sizes and species (Avery and Burkhart,

2002). It is estimated as:

V= α + β1D + eij

LnV= α + β1LnD + eij

V= α + β1D2H + eij

Where, V = tree volume, D is the DBH, H = tree height, Ln = natural logarithm, α, and β1 are the

regression parameters, eij is an error term

where, V is the tree volume, D is the DBH (cm), H is the tree height (m), α, β1 and β2 are

regression coefficients to be determined, Ln is the natural logarithm.

Assessment of the models: The models were assessed to test their plausibility and suitability for

further use. The following statistical criteria were used:

Significance of regression (F - ratio): - The tabulated critical value of F at p < 0.05 was

compared with the calculated F-ratio. Where F-calculated exceeds F-tabulated, equations were

considered significant and useful for prediction.

Multiple correlation coefficient (R): R values >0.50 indicated a good fit.

Coefficient of determination (R2): Models were acceptable at R2value >50%.

The regression standard error: The value must be relatively small for a model to be valid.


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Model validation

All the models were validated by comparing predicted volumes with field results with statistical

indices and graphical analyses of residuals (Rupsys and Petrauskas, 2010). All field data were

divided into two sets. The first set is the calibrating set (80%) which comprised growth variables

from 265 trees. These were used for generating the models when all species were pooled. The

second set (validating set) comprised tree data from 67 stems (20%). These were used for

validating the models (Cooper and Weekes 1983). For the species, all data were used for

calibrating and validating (Adekunle et al., 2013). Model outputs were individually compared

with observed values using the Student t-test for paired means (Neter et al., 1996) and the simple

linear regression equation (Amaro et al., 1998). To further assess the accuracy of model

predictions, the biases, percentage biases and the Root Mean Square Error (RMSE) were

calculated for the models (Vanclay 1994; Gadow and Hui, 1998)

RESULTS

Company records and interviews

Table 1 revealed the interview result conducted at the company. The result showed that woods

are exploited from their plantation and some of the trees in the plantation are Tectona grandis,

Mansonia altissima, Nauclea diderrichii, Gmelina arborea etc. The Tectona grandis plantation are

of two age-series established in 2005 and 2008, respectively while Mansonia altissima and

Nauclea diderrichii plantations were established in 2005. Some of the wood species in these

plantations had been harvested. Seeds used to establish these plantations were obtained from

Malaysia and Nigeria. Moreover, some of the silvicultural activities carried out by the company

are clearing, pruning, thinning, chemical treatment etc. Each of these operations is carried out by

their trained staffs that carry out these operations. There are 60 workers in the tree planting

section and about 90 workers in the furniture section. The furniture section is sub-divided into

the following sub-sections: wood construction, upholstery, metal fabrication, spraying,

assembling and loading.

Table 1: The summary table of the interview guide


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Volume estimation

Table 2 showed the statistical summary of data obtained for this study. A total of 332 trees were

recorded in the sample plots for all the age series. Number of stem per plot were 88, 78, 84, 82

individuals for Mansonia altissima, Nauclea diderichii, Tectona grandis (2005), and Tectona

grandis (2008) respectively. Mansonia altissima has the highest number of individuals; this was

followed by Tectona grandis. Mean total height and mean DBH ranged from 5.42 to 8.36 and

10.50 to 18.38, respectively. Basal area per hectare ranged from 0.25 to 0.64 (m-2ha) while

1 When was the Evergreen Tree planter

Established?

1984

2 What are the objectives of establishing the

company?

Production of Furniture

3 What are the various sections of the company? Tree planting and furniture production sections

4 When was the sections established? Furniture section was established in 1958 Tree

Planting section was established in 1984

5 What are the Tree species established in the

company

Nuclea didderichi(2005) ,Mansonia altisima(2005),

Tectona grandis(2005) and Gmelina arborea

(2011)

6 What are the Silvicultural practices carried out in

the Company’s plantation?

Clearing, Prunning, Thinning, Beaten-up Chemical

treatment and so on.

7 Has the Company started harvesting his

Plantation?

Yes

8 Do you consume all harvested trees or sell some

proportion?

The harvest are consumed by the furniture section

9 What are the various sections in the furniture

section?

Wood construction, Upholstery, Metal fabrication,

Spraying, Assembling and Loading.


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volume per hectare ranged from 0.78 to 2.53 (m-3ha). However, all the trees encountered in

sample plots were used to generate models. Table 3 showed the Spearman correlation

coefficients between paired tree growth variables. Generally, there was high and significant

correlation among the variables. Correlation was recorded between the logarithm transformed

values for dbh and volume, while the lowest correlation was between total height and volume.

Selected models for estimation of total volume, and their assessment criteria are presented in

Table 4. For the models involving the pooled data, 265trees were involved in model calibration

while 67 data from the pooled data were used for validation. All selected models had significant

correlation coefficients and coefficients of determination, small standard errors of estimates, and

significant F-values. Exceptional is the Mansonia atissima where the first and last model did not

give a good assessment criteria, although, the logarithm model gave a good assessment criteria.

When species were pooled, the logarithm-transformed model using LnD as the predictor variable

had the highest correlation coefficient of 0.91 and R2 of 83%.

The models used showed accurate estimates of timber volume. Table 5 showed validation result.

The best model estimates were compared with student T-test. The result showed that there were

no significant differences between the observed and predicted volume for all the models

validated. The result also showed small percentage biases and RMSE value, which confirmed

the goodness of fit of the model. Fig. 1 showed the graphic presentation of residual plots against

predicted volume (total volume for pooled and individual species). All the models have the

regression line passing in between the middle of the data indicating that, there was no upward or

downward bias. Also, there were no multicollinearity problems with these models since only a

single predictor variable was involved in their simulation.

Table 2. Summary of tree growth variables.

Species MDbh(cm) MHt (m) Ba/ha (m2/ha) V/ha (m3/ha)

No of

stem

Mansonia altissima

(2005) 17.66 8.36 0.55 2.26 88.00

Nauclea diderrichii

(2005) 10.50 7.53 0.24 1.11 78.00

Tectona grandis (2005) 18.38 8.35 0.64 2.53 84.00

Tectona grandis (2008) 10.73 5.42 0.25 0.78 82.00

Total 57.28 7.44 1.68 6.68 332.00


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Table 3 Spearman correlation matrix for tree growth variables in ever green planter.

DBH(cm) Ln Dbh

Total height

(m) BA(m2)

volume

(m3) Ln volume

DBH(cm) 1

Ln Dbh 0.97 1

Total height 0.68 0.69 1

BA 0.98 0.91 0.64 1

Total volume (m3) 0.64 0.60 0.54 0.64 1

Ln volume 0.89 0.93 0.79 0.82 0.76 1

Table 4. Models generated for total stand volume estimation and their assessment criteria for

pooled and species in Evergreen planter.

Models R R2 SE F-ratio*

Ma V=0.01+0.67D 0.28 0.08 0.14 7.75

LnV= 0.89+1.88LnD 0.85 0.72 0.44 216.46

V= 0.03+0.06D2H 0.29 0.08 0.14 8.06

Nd V= -0.06+1.01D 0.85 0.72 0.02 193.24

LnV= 2.03+2.42LnD 0.88 0.77 0.42 259.19

V= -0.03+0.01D2H 0.94 0.88 0.01 599.73

Tg (2005) V= -0.01+1.18D 0.88 0.77 0.04 272.78

LnV= 1.42+2.21LnD 0.95 0.9 0.24 731.07

V= -0.04+0.18D2H 0.94 0.89 0.02 677.65

Tg (2008) V=-0.04+0.67D 0.95 0.9 0.01 758.57

LnV= 1.09+2.10LnD 0.98 0.95 0.19 1911.45

V= -0.02+0.10D2H 0.95 0.91 0.01 854.51

All V= -0.06+0.97D 0.60 0.36 0.08 144.94

LnV= 1.24+2.08LnD 0.91 0.83 0.38 1261.83

V= -0.02+0.09D2H 0.62 0.38 0.08 161.45


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D = Diameter at breast height (cm), H = Total height, Ln = Natural logarithm

Ma- Mansonia altissima, Nd – Nauclea diderrichii, and Tectona grandis

* F-ratios were significant for all the models (p<0.05)

Table 5. Validation results of models for predicting the total volume in evergreen planter with

Student’s t-test.

Mean

observed

value

Mean

predicted

value df t-stat

t-

critical P-value Bias Bias% RMSE

Ma 0.14 0.13 88 0.87 1.99 0.39 0.09 9.2 0.01

Nd 0.07 0.07 78 1.17 1.99 0.24 0.04 4.23 0.01

Tg(2005) 0.16 0.16 84 0.55 1.98 0.59 0.01 1.43 0

Tg(2008) 0.05 0.05 82 0.32 1.98 0.75 0.01 0.65 0

All 0.05 0.06 67 1.57 1.97 0.12 -0.21 -21.33 0

Ma- Mansonia altissima, Nd – Nauclea diderichii, and Tg-Tectona grandis


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Fig. 1. Predicted volume against residuals for model validation.


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DISCUSSION

The species used in this study area are typical of plantation forest. These species are very useful

for timber, pole, and pulp. Two age series of Tectona grandis which were established in 2005

and 2008 were used for this study. The tree growth variable measured in the study area showed

that mean Dbh of Mansonia altissima, Nauclea diderrichii, and Tectona grandis (Year 2005 and

2008) are 17.66cm, 10.50cm, 18.38cm and 10.73cm respectively. This implies that majority of

the trees encountered in this study area below the minimum merchantable size of 48cm stipulated

by logging policy of southwestern Nigeria (Adekunle 2002). Also, considering the sources of

error in height and stem diameter measurement, it is necessary to develop volume estimation

models using a variable, such as DBH Adekunle (2013). This method is fast, requires less work,

and is therefore cost efficient in forest inventories (Segura and Kennien2005).

Bisrod Furniture Company is one of the private forestry that still exists today. The company was

founded in the year 1958 and has two sections; Plantation section (Evergreen tree planter) and

Furniture section. The company aim to produce round wood for the furniture section of the

company. The company does not have a natural forest where wood can be exploited. Woods are

exploited from their plantation. The objective of the company is in a way different from the

primary objective of private forestry. According to (Odebiyi, 1992) the objectives of private

forestry are to encourage the development and management of forest estates as well as to

increase the quality of forest resources for enhanced living standards and environmental

protection. However, the company has contributed positively to forest development in Nigeria

through employment opportunities to the people, thus, preventing illegal felling and also through

seminars which enlightens foresters more and local people on the importance of planting trees.

In the context of sustainability, it is best to reduce the objective of investment to multifunctional

purpose on landscape basis, even though timber production may be the main objective of some

private investor. A private investor should therefore aim at improving and sustaining the quality

of life and livelihood, environmentally, socially and economically through the planting of

desirable and suitable species of trees. Numerous good and services, apart from wood, are

derivable from investment in forestry, usually beyond the contemplation of the investor. For

active participation of private sector, the need for the provision of enabling environment, the

political will and support as well as other necessary incentives are very essential (Dosunmu,

2001). The rate of deforestation and tree planting in Nigeria is difficult to estimate. In most

cases, the data is not available and the rates vary from state to state. However, nobody can

dispute the fact that the rate of deforestation is far higher than that of tree planting. In the light of

these circumstances, there is need to plant more and more trees in Nigeria especially in the

country. Indigenous communities feel resentful and unsatisfied by the government action by

keeping their forest without allowing them to benefit from the natural resources. This could

encourage deforestation. (Embaye, 2001) stated that the private sector has a major role to play in

the collection and distribution of tree seeds and planting stock. However, these goals are still far


Vol. 3, No. 03; 2019



from being accomplished considering the fact that only government agencies have been majorly

involved in forest development in Nigeria. It is however important that individuals, groups, non-

governmental organization and local communities should also be involved in forest development.

If these goals are met, private forestry initiative can help to boost forest development in the

country by supplementing productions from state owned forests.

Model was developed for volume estimation of trees in evergreen tree planter. All the

assessment criteria revealed of the model had a good fit. The statistical fits were generally good.

Student t-test was used for validation. The result revealed that there were no significant

differences between observed and predicted volumes. The conformity to regression assumptions

when tested with the probability plot of residual and predicted values conformed to the

observation of Ajit (2010). The scatter-plots were consistent with the results of other statistical

indices for validation. This shows that the regression assumptions were not violated (Adekunle et

al., 2013). Other tree growth modelling studies, including (Andreassen and Tomter, 2003; Zhao

et al., 2004; Trasobares and Pukkala, 2004; Sonmez et al., 2009) also observed no constant

variance of residuals, an inevitable phenomenon for forest populations due to the nature of the

growth process.

CONCLUSION

This study has given in sight strategy on how private forestry can effectively contribute to forest

development in Nigeria. Also, the study has helped to gather information that provides one of the

bases for taking important decision in forestry and enabled us to access/determine the growth

rate and yield of individual trees being worked upon within the plantation. The result of the

volume estimation revealed that more volume per hectare was recorded for Tectona grandis than

Mansonia altissima and Nauclea diderrichii established the same year. This is as a result of high

fertility of the soil (soil type) and several silvicultural practices during early growth rate. Also,

the entire model used for this study gave good assessment criteria but logarithm model was

ranked first due to its high coefficient of determination f-ratio. Logarithm model could therefore

be used for management context and future studies.

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