Wood production parameters for Kasewe plantation forest.
Forest and woodland are renewable natural resources providing basic human necessities. They have the ability to sequester carbon and mitigate climate change. Sustainable forest management is guided by forest mensuration and inventory which include measuring and calculating growth and changes in trees and forests. The objective of the study was to estimate timber resources and carbon stock using simple hand tools in Kasewe and Singamba forests in the southern part of Sierra Leone. All trees with diameter at breast height (DBH) ≥ 10 cm were measured in every plot for DBH, and three trees were measured for height. The correlation between mean wood volume and carbon stock was highly significant. For Kasewe plantation forest, mean wood volume and carbon stock were 151 m3 ha−1 and 44 t C ha−1, respectively, and for the Singamba natural forest, they were 181 m3 ha−1 and 82 t C ha−1, respectively. The linear correlation between basal area and volume, DBH and volume and basal area and total biomass was significant for the plantation species tested. Realistic national forest inventory and community forestry are inevitable for sustainable forest management in Sierra Leone.
- community forestry
- carbon stock
- forest mensuration and inventory
- sustainable forest management
Forest and woodland (tree and shrub savannah, parklands and bush fallows ) are renewable natural resources providing basic human necessities [2, 3]. Although both ecosystems are wooded habitats where trees predominate , the former consists of closed canopy [4, 5] which permits very little sunlight to penetrate to the ground below, while the later has a more open canopy  and its sparse woody mid-storey allows more sunlight to reach the ground . They have the ability to sequester carbon and mitigate climate change . Forest ecosystems are mostly viable carbon sinks [6, 7] globally due to net growth in planted trees  with the majority of sequestered carbon held in woody biomass  but can also be a carbon source when degraded . The rainforest of West Africa, a hotspot of biodiversity, has approximately 9000 species of vascular plant, including 1800 endemic species [8, 9] and an estimated area of 621,705 km2. This forest area declines every year through anthropogenic activities  and natural disasters such as landslides, earthquakes and flooding .
Forest resource assessment in relation to timber volume [11, 12, 13] and carbon stocks [14, 15] provides information about the status of the productivity of the forest. This assessment is traditionally done through ground forest inventory. Forest assessment is very important for decision-making and policy formulation  and establishment of sustainable management plans at both national and international levels.
The objective of the study was to estimate timber resources and carbon stock using simple hand tools in Kasewe and Singamba forests in the southern part of Sierra Leone.
2. Materials and methods
2.1 Sampling design
2.1.1 Method of sampling in Kasewe plantation forest
A systematic sampling design was established for conducting timber inventory in this plantation forest at the age of 14 years. A trunk road (Bo-Freetown highway at Moyamba Junction) passing through the forest served as the baseline.
This method was replicated in the adjacent
2.1.2 Sampling design in Singamba natural forest
Within the Singamba mixed forest, two vegetation communities or ecology types, namely, secondary forest (aged over 5 years after its last farming disturbance) and forest regrowth (resulting from shifting cultivation farming about 2–5 years ago), adjacent to each other, were identified for data collection. Systematic sampling was employed for this study area. Circular plots of radius of 10 m were adopted for data collection. These have the advantage of reducing the edge effect in the sample. Using an existing footpath as a baseline, two quadrants, 100 m by 80 m and 100 m by 60 m, respectively, were demarcated; a total of 20 plots, 12 and 8 plots in the respective quadrants, was laid out systematically on transects that were 25 m apart (Figure 3) in each ecology type.
2.2 Data collection
2.2.1 Data collection in Kasewe plantation forest
All trees within each plot were measured for diameter at breast height (DBH) at 1.3 m above the ground, and three dominant trees were measured for total height. A minimum of 10 cm DBH [16, 17] was considered for a tree to be enumerated, targeting commercial stems. Tree height was measured using a Suunto hypsometer, and DBH was measured using a diameter tape. A linear function of DBH and height (Figure 4) was developed from the data for dominant trees for estimating the height of the remaining trees not measured in the field.
Bark thickness of all sample trees in every plot was measured in both the
2.2.2 Data collection in Singamba natural forest
In each circular plot located in both secondary forest and forest regrowth (within the natural forest), tree or shrub species of a minimum DBH of 10 cm was identified by a local tree spotter in the Mende language; this was recorded and later translated to botanical name using Trees of Sierra Leone  and further verified from . Diameter measurement was taken for all trees 10 cm and above at 1.3 m above ground level in each plot. The total height of three dominant trees was also measured in every plot.
2.3 Data analysis
2.3.1 Kasewe plantation forest
For the estimation of tree yield (stem count, basal area and volume), biomass and carbon non-harvest techniques  were adopted for the following parameters:
Volume over bark
Carbon stock in standing trees
18.104.22.168 Yield parameters
A linear function was first developed (from the dominant trees) for estimating the height of all the trees not measured for height in the field.
22.214.171.124.1 Stem count
126.96.36.199.2 Basal area calculation
188.8.131.52.3 Volume estimation of trees per hectare
The volume (m3) of all trees in the sample plots in both the
(Note: Eq. (1) is applied best to trees with DBH ≥ 10 cm)
Volume under bark (ob) was estimated from DBH under bark.
184.108.40.206 Estimation of live tree biomass and carbon stock for
For the purpose of this study, biomass carbon has been considered and studied for only trees of minimum DBH of 10 cm in both natural and plantation forests. The accumulated biomass and carbon contained in the standing trees of
220.127.116.11.1 Aboveground biomass
To estimate the aboveground biomass (AGB), the equation according to Arias  was adopted for
Then, it was converted to tonne ha−1 (t ha−1) after multiplying by a scaling up factor (SF) : SF = 10,000/NA; NA is the area of single plot in m2.
18.104.22.168.2 Belowground biomass
The belowground biomass (BGB) was estimated according to the recommendation of the Intergovernmental Panel for Climate Change (IPCC) :
22.214.171.124 Estimation of live tree biomass and carbon for
The AGB for teak was estimated using a method similar to that for
2.3.2 Data analysis for Singamba forest
126.96.36.199 Wood production parameters
The quantitative metric data was used to estimate three parameters for wood production: the number of stems ha−1 (N), basal area ha−1 (G) and wood volume ha−1 (V).
188.8.131.52.1 Number of stems ha−1
This was estimated using Eq. (1) (Section 184.108.40.206)
220.127.116.11.2 Basal area ha−1
The formula used was Eq. (2) (Section 18.104.22.168).
22.214.171.124.3 Wood volume ha−1
This was estimated using the formulae according to Eqs. (12) and (13) ; a form factor of 0.562 from Mattia and Dugba  for natural mangrove forest (comprised of seven mangrove species) in Tanzania was employed:
126.96.36.199 Estimation of live tree biomass and carbon stock for Singamba rainforest
The following equation was adopted for estimating biomass of the natural forest :
And the scaling factor applied was 10,000/(314.16).
The calculation of BGB, AGC, BGC, total biomass and total carbon followed the same method as that for Kasewe plantation forest (Section 188.8.131.52; definitions of all terms remain the same as before).
2.3.3 Statistical analysis
The above tree parameters were calculated using Excel software. Means, standard deviations, variances, standard errors and confidence intervals [32, 33] for various wood production parameters were computed. Relationships between basal area and wood volume, between basal area and total biomass and between total biomass and carbon stock, were determined using regression analysis.
3.1 Kasewe plantation forest
3.1.1 Wood volume
The mean DBH and height are shown in Table 1. The overall mean wood volume of Kasewe plantation forest was 151.06 m3 ha−1; the mean volumes over bark for
|Species||Mean DBH (cm)||Mean height (m)||M. BA (m2 ha−1)||Wood volume ob (m3 ha−1)||M. D. DBH (cm)||M. D. ht (m)||Stem count (stem ha−1)|
The volume of wood for
The percentage of volume (ob) of
3.1.2 Stem count and basal area
The stem density of the plantation forest at Kasewe was 253 stems per ha; 264 and 240 stems per ha were recorded for
The mean basal area of the Kasewe plantation forest was 14.22 m2 ha−1 (Table 1).
3.1.3 Relationship among different growth parameters
The number of
Similar to the volume, the total biomass of trees varied positively and linearly with variation in its basal area (Figure 8). The basal area explains slightly higher proportion (i.e. 99.5%) of variation recorded in total biomass than the volume.
The carbon stock of trees of
3.1.4 Accumulated biomass and carbon in
The estimated net biomass of the stems and roots (total biomass) ranges from 51 to 136 tonne ha−1 with a mean of 94.26 tonne ha−1; the carbon stock ranges from 24 to 64 tonne ha−1 with a mean of 19 tonne ha−1; and the CO2 sequestered ranges from 72 to 190 tonne ha−1 with a mean of 131.21 tonne ha−1 (Table 2).
|Plots||DBH (cm)||Height (m)||AGB (t ha−1)||BGB (t ha−1)||Total biomass (t ha−1)||Carbon stock (t ha−1)||CO2 (t ha−1)|
3.1.5 Accumulated biomass and carbon in teak trees at Kasewe plantation forest
As in the case of
|Plot||DBH (cm)||Height (m)||AGB (t ha−1)||BGB (t ha−1)||Total biomass (t ha−1)||Carbon stock (t ha−1)||CO2 (t ha−1)|
3.1.6 Estimation of wood volume, biomass and carbon stock in standing trees of teak of Kasewe plantation forest
Estimation of volume, biomass and carbon stock using DBH and height was highly significant (
3.2 Results for Singamba natural forest
3.2.1 Diameter and height
The overall mean diameter for all the trees enumerated in the whole forest was 20.02 cm; the mean diameter for the secondary forest ecology was 21.87 cm, and the forest regrowth ecology was 15.85 cm. The overall mean height for the entire forest was 16.59 m, 18.45 m for the secondary forest and 12.40 m for the forest regrowth.
3.2.2 Wood volume, basal area and stocking of Singamba natural forest
The mean wood volume is summarized in Table 4. The overall wood volume and basal area for the entire forest were 181 and 16 m2 ha−1, respectively, and the stocking was 920 stems ha−1.
|Vegetation type||Av. DBH (cm)||Av. height (m)||Av. basal area (m2 ha−1)||Av. stocking (stems ha−1)||Av. wood volume (m3 ha−1)|
3.2.3 Accumulated biomass and carbon sequestration in Singamba natural forest
The biomass and carbon stock of the natural forest are presented in Table 5. For the whole forest, the estimated biomass ranges from 115 to 236 tonne ha−1 with a mean of 60.66 tonne ha−1; the carbon stock ranges from 54 to 111 tonne ha−1 with a mean of 28.51 tonne ha−1; and the CO2 sequestered ranges from 160 to 330 tonne ha−1 with a mean of 84.65 tonne ha−1.
|Ecology||Mean DBH (cm)||AGB (t ha−1)||BGB (t ha−1)||Total biomass (t ha−1)||Carbon stock (t ha−1)||CO2 (t ha−1)|
3.2.4 Estimation of wood volume, biomass or carbon stock for the entire Singamba forest
ANOVA of the regression showed that estimation of wood volume, biomass or carbon stock using DBH, height or basal area was significant (
|Wood production parameters||Plot count||Mean (value ha−1)||Variance||Standard error|
|Basal area (m2/ha)||40||16.50||0.159||0.063|
|AGC (t C/ha)||40||66.91||5211.129||11.414|
|BGC (t C/ha)||40||15.72||287.785||2.682|
|Total biomass (t/ha)||40||175.82||35980.733||29.992|
|Total carbon (t C/ha)||40||82.63||7948.144||14.096|
4.1 Stand yield of plantation species
4.1.1 Stand volume
In the present study, it was found that volume and biomass and subsequently the carbon stock increased with growth of DBH and height of the stems of all the plantation species. Various allometric equations for volume and biomass (developed by different researchers) were used to estimate these parameters. Of the two species in Kasewe,
The results showed that the
4.1.2 Basal area
Basal area is known to be an indication of site potential  which gives support to the growth rate of trees in the forest. The result of this research for Kasewe is in agreement with those of other researchers, for example, in Nigeria. A basal area of 17.5–20.0 m2 ha−1 was recorded for
The estimated stem density for Kasewe plantation forest was 253 stems per ha;
4.1.4 Biomass and carbon stock of plantation stands
As already stated, volume and biomass and subsequently the carbon stock increased with the increase in growth of DBH and height of the stems of all the plantation species. The range of coefficient of determination was found to be 98 and 99% for
The means of carbon stock of living trees (stems DBH ≥ 10 cm and roots), in the present study, from all plots were 94.26 and 94.59 t ha−1 for
4.2 Natural stands
4.2.1 Forest productivity
The estimated wood volume was 245.24 m3 ha−1. Within Singamba forest the secondary forest ecology was found to be more productive than the forest regrowth, meaning the former has more usable trees than that of the latter. The basal area was 21.87 m2 ha−1 for Singamba forest. This parameter estimate seems to be relatively high for Singamba forest and can be compared with other tropical areas , generally serving as an indication for good site potential for wood production. As suggested before, deforestation was actively reducing the potential wood production of Kasewe plantation forest as a result of intensive sawmill and farming activities, and farming was also evident in Singamba natural forest.
The wood volume and basal area of Singamba forest are in close agreement with that for Gola rainforest . This could be attributed to these two being natural forests which have higher soil nutrient for tree growth from litter fall, decomposition and high rate of microbial activities. Also, they could be less undisturbed than the forests of National Agricultural Training Centre (NATC), Njala University  and Kasewe plantation forest in Sierra Leone and are of high stand density and species diversity  which can help in increasing growth variables such as height and diameter at breast height which are responsible for the volume and basal area measurement.
The quantitative estimates of current and future wood volume and biomass of timber and other forest products are essential for forest management practices. Thus the information (e.g. mean height, DBH, volume and stem density) derived from the natural stands could be used by forest managers, researchers and policy makers at national and local levels.
4.2.2 Biomass and carbon stocks of the natural stand
The present study has attempted to provide the first estimate of tree biomass and carbon stock in Singamba based on representative field sampling. This has demonstrated how carbon density can vary across a disturbed forest ecosystem  with respect to human activities. Patterns of biomass  largely reflected past farming history in Singamba forest, demonstrating impact of disturbance on forest biomass, as had been noted for logging impact on Gola forest . Despite human disturbance in the forest in the recent past (forest regrowth), there is clearly an indication (secondary forest) that the Singamba forest still retains substantial carbon stocks and can accumulate further if left undisturbed.
The estimates of C stock for the entire Singamba forest (from all 40 plots) were found to be 82 t C ha−1 (Table 5), and this included all above- and belowground biomass of living trees over 10 cm DBH but excluded standing dead wood, woody debris and leaf litter . There was variation in C biomass for the plots and ecology, but the higher biomass was found in the secondary forest which seems relatively stable.
The overall C stock for Gola forest was 160 t C ha−1 , but the overall carbon stock for Singamba was far lower than that of Gola in the present study. Although values of Singamba did not accord well with those for Gola, if disturbance by the forest edge communities is minimized, especially the slash and burn farming; this could improve the carbon stock for Singamba.
Timber inventory using simple hand tools is an efficient measure to manage these resources especially for land owners. One hundred percent enumeration of trees in a discrete forest is tedious, time-consuming and not economical. Hence forest sampling is professionally accepted.
Management of forest carbon is a concern across the globe for mitigation of global warming. The two plantation species being studied at Kasewe,
This chapter enhances foresters and related technicians to be able to estimate and give account of carbon stocks in the forests of West Africa which are undergoing rapid deforestation, degradation and even encroachment . In Sierra Leone, community-based forestry and forest inventory at national level are recommended for sustainable exploitation and conservation of forests.