Index

1. INTRODUCTION

Tropical forests are particularly important because of the extent of anthropogenic transformations and the amount of carbon that they contain per unit area. Currently, almost all tropical regions are experiencing major changes that modify their structure either through shifting cultivation or through logging activities (Cuny, 2011). Uncertainties remain on the contribution of forests in the Congo Basin to the global carbon cycle due to its floristic diversity estimated at more than 500 species per hectare (dbh> 10 cm), its high variability in size and density of trees, the types of forests, the natural disturbances such as mortality, recruitment, etc. (Chave et al., 2005; GIEC, 2007; Lewis et al., 2009) . Malhi et al. (1999) estimated that tropical forests contribute at about 32-36% of terrestrial net primary carbon production and for this purpose Picard et al. (2012) indicated that special emphasis should be placed on these forests. Therefore, Fearnside (1997) and Reyes et al. (1992) highlighted the need of developing wood density databases for the estimation of tropical biomass.

Dry wood density can be defined as the ratio of the anhydrous mass of a sample to the mass of a volume of water corresponding to the volume of the anhydrous sample (Fearnside, 1997). Different ways of calculating wood density include apparent density or density at X% (the ratio of weight to volume at a given moisture level), green density (green weight / green volume), basic density obtained by the ratio between the dry weight and the volume of green wood (Fearnside, 1997; De Souza et al., 2002; ASTM, 2007) . In addition of being an excellent indicator of the amount of wood present in a sample and its workability (Silva, 1984; Trugilho et al., 1990; Chimelo, 1992; ASTM, 2007) wood density is linked to other wood properties such as strength, porosity, organization of anatomical elements, and also the number, size and chemical composition of cells (Kollmann and Cote, 1968; Trugilho et al., 1990; Simpson and Tenwolde, 1999; Ilic et al., 2000; Hacke et al., 2001; ASTM, 2007) . Although wood density has recently emerged as a key variable in carbon cycle research (Ilic et al., 2000; Chave et al., 2006) wood density data published in the tropics are very often limited to commercial species that represent only a fraction of the forest biomass (Maniatis et al., 2011).

One of the difficulties in using wood density data when available is that they have frequently been collected using different sampling procedures in similar or different stands (Balodis, 1994; Downes et al., 1997; Ilic et al., 2000) . Studies of Chave et al. (2006) and Maniatis et al. (2011) showed that tropical woods densities range from 0.08 for light wood to 1.39 g / cm3 for heavy wood.

However, the wood density of many tropical trees remains unknown (Slik, 2006). There is very little information on the relationship between crown width and wood density throughout ontogeny (Aiba and Nakashizuka, 2009). However, there could be a relationship between wood density and tree architecture that should be taken into account when estimating biomass. In general, studies including radial and longitudinal variations in species wood density in the Amazon showed either results for some species limited to certain functional groups, or only radial variation or only longitudinal variation (Amorim, 1991; De Macedo, 1991; Higuchi and Carvalho, 1994) . The wood density measured at breast height decreases from the center to the bark (Nogueira et al., 2005; Henry et al., 2010). Moreover, the portions of the trunk which are the most recent have a lower wood density creating a decreasing longitudinal pattern on the tree. However, the study of Nogueira et al. (2005) and De Macedo (1991) have shown that in some cases the wood density of trees can increase longitudinally with the height of the tree. For these authors, these observations are a consequence of wood degradation that precedes the formation of a hollow nucleus which would be more advanced near the base of the tree, where hollow nuclei are the most common. In general, different biological and eco-physiological aspects such as structural requirements, climatic zone, light and rapid growth have been reported as responsible for variation in trunk density (De Zeeuw, 1965; Favrichon, 1994; Ter Steege and Hammond, 2001).

Henry et al. (2010) and Nogueira et al. (2005) showed that along the same tree, the wood density varies from the base to the top of the trunk and, also radially from the cambium to the heartwood. However, in global databases the wood density reported do not take into account these variations and are also often restricted to commercial species (Zanne et al., 2009). Although 105 °C is the recommended temperature in the Official Wood Density Protocol (ASTM, 2007) tests at 80 °C were carried out as part of the density estimation in the Amazon (Nogueira et al., 2005). Based on these differences, the objectives of this study were to test 1. the effect of vertical variation (base to the crown), 2. the differences in wood density between species, 3. the effect of temperature variation (80 °C, 105 °C) on the specific wood density of the species in a semi-deciduous forest of the Eastern Cameroon.

2. MATERIALS AND METHOD

2.1. Study Area

The study was carried out in a forest management unit located in the district of Belabo, Division of Lom and Djerem, in the Eastern Cameroon at about 80 km from Bertoua. It is located in a dense humid forest at Sterculiaceae and Ulmaceae (Letouzey, 1985). The relief of the area is fairly diverse and not very rugged and has been strongly influenced by the different tectonic activities. It is characterized by the presence of small hills of low altitude with an average between 500 and 800 meters (PCB, 2012). The hills are separated from valleys which serve as beds for most of the rivers that cross the study area and fall into the Sanaga river. The river system is very dense characterized by the presence of the Sanaga river and its tributaries. There are also numerous streams and backwaters that dry up during the great dry season. The soils of the zone are mainly ferralitic, sandy clay or silty clay, which are generally found in the plains with a laterite cuirass. They are characterized by the low nutrient retention and can be depleted rapidly. The lateritic texture characterizes the presence of rocky blocks covered with a laterite mantle of altered rocks. There is also the presence of hydromorphic soils encountered in the lowlands, very rich in organic matter. However, these soils are most often flooded with water during rainy seasons and poorly drained in dry seasons (PCB, 2012). The climate is equatorial, of Guinean type with temperatures varying from 20 °C between July-August and 30 °C between January-February. The average annual rainfall is 1500 mm, characterized by the presence of four seasons which are the great dry season (mid-October to March), the small dry season (June to mid-August), the great rainy season (mid-August to October) and the small rainy season (March to June) (CTFT, 2013).

3. DATA COLLECTION

3.1. Sampling Design

The data were collected in plots of 100 m2 (10 m × 10 m) for trees with  diameter  below 5 cm and in plots of 200 m2 (20 m × 10 m) for trees with diameter between 5 and 10 cm. Trees of diameter ≥ 10 cm were collected in plots of 5000 m2 (20m × 250m). For each tree inventoried, vernacular or scientific names were recorded, specimens collected, pressed, impregnated with ethyl alcohol diluted at 95 °C and dried in the laboratory of ecology and systematics of the University of Yaounde 1. These specimens were then sent to the national herbarium of Yaoundé to confirm the identification of species. For each tree selected, total height was measured with the Suunto clinometer or Relascope of Bitterlich and diameter measured at 0.30 cm aboveground for trees of diameter <5 cm and at 1.30 for trees with dbh (diameter at breast height) ≥ 5 cm and at 0.30 cm above the buttresses for the trees having buttresses above 1.30 cm. Trees were felled using a machete or chainsaw depending on size to collect samples having average weight of 38 g at the levels of tree breast height (base), trunk and branches. The samples were then labeled (names, numbers, plots) and transported to the Laboratory of Ecology and Systematics at the University of Yaoundé 1. 356 samples were collected at the base, middle and branch levels from 162 trees with diameter between 1 cm and 146 cm.

3.2. Wood Density

The wet weight was directly measured in the field using a high-precision electronic balance and the volume calculated using Archimedes principle. According to this principle, a solid immersed in water experiences an upward force equal to the weight of the water it displaces because the wood density of water is 1 g/cm³ (Djomo et al., 2010). For determination of volume, each green sample was fully immersed in water on a graduated cylinder and the weight of the displaced water read from the electronic balance calibrated at 0. The dry weight was obtained by drying the samples in an oven to a constant weight for 48 to 72 hours depending on the type of species. The constant weight was known after multiple weighing of the samples at regular intervals every six (6) hours until it repeats at least 3 consecutive times. The volume and the dry mass measurements were used to calculate wood density using the formula  

where Mi is the dry mass (g), Vi is the green volume (cm3) and WDi is the basic wood density (g/cm−3) of the wood sample i. The wood density was calculated by dividing the dry weight over the wet volume. In order to test the effect of temperature on the wood density, the same samples were dried at 105 °C and then rehydrated for 7 days and dried again at 80 °C. The green volume and dry weight were recalculated for determination of the wood density at 80 °C. For the determination of average wood density of each species, the temperature of 105 °C was considered (ASTM, 2007).

3.3. Data Analysis

The mean wood density of each tree was obtained using the formula  where  is the wood density at the base,  the wood density at the middle of the trunk,  the wood density at the level of the branches and , ,  the volume at the base, middle and branches respectively (Nogueira et al., 2007). The longitudinal variation of wood density in each tree species was analyzed by comparing the wood density obtained at the base, the middle and the level of the branches. To analyze intra-specific variation, the species that repeated at least five times in the dataset were used and their average densities compared. Interspecific variation was analyzed by comparing the average wood density of different species. ANOVA was used to test these variations with R software. The densities obtained from this study were compared with the Global Wood Density database.

4. RESULTS

4.1. Effect of Vertical Variation on Wood Density

ANOVA test (p ˃0.05) showed that there was a variation in wood density at different levels of the tree. The wood density decreased considerably from the base to the branches. There was no significant difference between the base and middle of the trees as well as between the middle of the trees and the branches; however, there was a significant difference between the wood density of the base and the branches (Fig. 1). Table 1 shows the vertical variation in wood density of 30 species estimated at 105 ° C. There was a general pattern of decreasing wood density except few cases such as Petersianthus macrocarpus where the wood density at the base 0.567 g/cm³ increased to 0.594 g/cm³ and then decreased to 0.450 g/cm³ at the level of branches. There was a different pattern for Celtis adolfi-friderici where the wood density at the base 0.566 g/cm³ decreased to 0.496 g/cm³ and then increased to 0.508 g/cm³ at the branches level. The average difference between the densities considered at breast height and those at the branches level was 15%. This difference was 8% (min 1.5% and max 22.3%) between the average wood density of trees and the wood density only taken at breast height.

4.2. Variation of Wood Density within and Among Species

There was no significant variation between individuals of the same species. The following variations were observed Mallotus opposifolium (0.597 ± 0.029), Microdesmis puberula (0.633 ± 0.072), Piptostigma sp. (0.549 ± 0.034), Erythropheum ivorensis (0.708 ± 0.129), Scyphocyse manniana (0.576 ± 0.032), Trichilia rubescens (0.501 ± 0.113), Triplochiton scleroxylon (0.443 ± 0.062). At 5% level, there was a significant difference between the wood density of Triplochiton scleroxylon, Erythropheum ivorensis and Scyphocyse manniana. There was also a significant difference between the wood density of Trichilia rubescens and Piptostigma sp. However, there was no significant difference between the densities of Mallotus opposifolium and Microdesmis puberula (Fig. 2).

4.3. Effect of Drying Temperature (80°C and 105°C)

As can be seen in Table 2, wood density decreased from 0.639 (80 °C) to 0.579 (105 °C) at the base level, from 0.609 (80 °C) to 0.553 (105 °C) at the middle of the trunk, and from 0.572 (80 °C) to 0.525 (105 °C) at the branches level. Overall wood density at 80 °C was 9 to 10% greater than at 105 °C showing that there could be an overestimate of the wood density measured if the drying temperature of 80 °C instead of 105 °C. Therefore, for the estimate of average density of tree species of the study area, the temperature of 105°C was used.

4.4. Average Density of Tree Species (105°C)

Wood densities varied from 0.159 to 0.986 g/cm³ with an average of 0.561 g/cm³. 184 samples were analyzed at the base with the densities varying from 0.227 to 0.986 g/cm³ and an average of 0.584 g/cm³. 83 samples were analyzed at the middle of the trunks with densities ranging from 0.273 to 0.912 g/cm³ and an average of 0.561 g/cm³. 89 samples were analyzed at branches level with densities ranging from 0.159 to 0.909 g/cm³ and an average of 0.514 g/cm³. The average wood density of tree species ranged from 0.295 g/cm³ for Enantia chlorantha (Annonaceae) to 0.912 g/cm³ for Ficus sp. (Moraceae) (Table 1). The mean wood density of the study area was 0.561 g/cm³.

4.5. Species Not Listed in the Global Wood Density Database

10 species from the study area were not included in the Global Wood Density database. These species were Trichilia rubescens, Greenwayodebdron suavealens, Piptostigma sp, Enantia chlorantha, Ghyphae brevis, Mallotus oppositufolium, Microdesmis puberula, Lasiodiscus mannii, Scyphocyse manniana, Rhabdophyllum arnoldianium (Table 3).

5. DISCUSSION

5.1. Average Wood Density

The wood density of this study varied from 0.295 to 0.912 g/cm³ with an average of 0.561 g/cm³. This result was in accordance with other studies in tropical forests. The wood density in the dense wet-evergreen forest of Ghana (Henry et al., 2010) at 105 °C varied from 0.110 to 1.010 g/cm³ with an average of 0.590 g/cm³; wood density variation ranged from 0.284 to 1.152 g/cm³ with an average of 0.630 g/cm³ in a dense rainforest of Cameroon (Fayolle et al., 2013). However, this mean value was lower than the average wood density of 0.700 g/cm³ found by Fearnside (1997) in Amazonian forests. Henry et al. (2010) mentioned that wood densities in moist tropical forests of Africa are lower than those of tropical Amazon rainforests.

Guarea sp. was found in the 186 species listed by Nogueira et al. (2005) measured at 103°C. The wood density of this species was 0.691 (0.619) g/cm³ at the base, 0.605 (0.466) g/cm³ at the top and 0.648 (0.533) g/cm³ on average; the values in bracket are the results of this study showing lower wood density in the Cameroon forest site. The top level in this study (branches) differed from Nogueira et al. (2005) which was the top of the trunk and justified the significant difference at that level. Piptadeniastrum africanum was in common between this study and the 16 species sampled by Henry et al. (2010). The average wood density of this species 0.580 g/cm³ found by these authors was close to 0.570 g/cm³ of this study and was smaller compare to 0.632 g/cm³ found by Fayolle et al. (2013). The temperature used by Fayolle et al. (2013) was not reported and may explain the difference.

5.2. Species Variation in Wood Density

The wood density of the species analyzed showed decreasing trend within an individual from the base to the top of the tree, and a variation between different species. There was no significant variation in the mean of individuals of the same species. Major variations in the environment (abiotic and biotic factors) such as physiological, mechanical, anatomical, genetic and morphological constraints observed in a forest stand would explain the causes of variation in species wood density (Fearnside, 1997). However, this variation in wood density between individuals of different species is more important than variations within individuals of the same species (Zanne et al., 2009; Henry et al., 2010; Quentin et al., 2013) in accordance with this study expressed that intra-species variation though small should not be neglected.

The results obtained from this study showed that non-consideration of longitudinal variation in the wood density would result to an overestimation of the biomass. This variation was not taken into account in most studies (Chave et al., 2005; Djomo et al., 2010; Fayolle et al., 2013; Chave et al., 2014; Djomo et al., 2016) developing allometric equations for the estimation of biomass. This study resulted in an average overestimation of 8% when wood density was only estimated at the breast height and was 15% greater than the wood density estimated at the level of the branches with extreme value reaching a difference of 37%. Our results were greater than those of Nogueira et al. (2005) which showed that considering the wood density only at breast height resulted to values 4.3% on average higher than the ones taking into account the longitudinal variation. Nogueira et al. (2005) indicated that the wood density of 87% of the trees studied decreased from the bottom to the top with extreme difference reaching 57%. 13% of the trees studied by these authors increased with height. This pattern was different from this study where 100% decrease from base to the branches. However, the wood density of two species Petersianthus macrocarpus and Piptadeniastrum africanum increased from the base to the middle before decreasing at the branches. This could not be considered as general trend for these species because in each case only an individual was analyzed and it was far insufficient to make a conclusion.

There may be a relationship between wood density and tree architecture that should be taken into account in estimating biomass. Variations in wood density and characteristics of heartwood are related to several factors: tree age, altitude, compartment on which the sample was measured within the tree (Williamson, 1984). However, there is a difference between fast-growing and slow-growing species with higher densities. Fast growing species are characterized by low density conducting tissues (Wright et al., 2003; Muller-Landau, 2004) which allows rapid growth in size (Favrichon, 1994; Santiago et al., 2004). On the other hand, high-density wood tissue leads to slow growth, which results in a stronger defense against physical damage, predators and pathogens (Rowe and Speck, 2005). In this study, it was not possible to test the variation of wood density in diameter class within individuals of the same species.

10 species did not have wood density appearing in the Global Wood Density database (Zanne et al., 2009). This may indicate an under-representation of Congo Basin wood density data in this database. Reyes et al. (1992) and Fearnside (1997) emphasized the need for an elaborate wood density database for the estimation of tropical biomass.

One of the factors in the variation of wood density is the drying temperature which affects the dry weight of the samples. The results obtained in this study showed that at drying temperature of 80 °C the wood density was on average 9 to 10% higher than at 105 °C drying temperature.  This result was higher than the study of Nogueira et al. (2005) which found a mean density difference at 80 °C higher by 1.1% than at 103 °C in the Amazonian forests.

6. CONCLUSION AND PERSPECTIVES

This study showed that accurate estimation of biomass and carbon stocks is based on reliable estimates of wood density. The vertical variation within individuals of the same species showed the importance of integrating this factor in the estimation of the wood density. This study resulted to an overestimation of the wood density of 8% in average that can reach 20% in extreme case. The variation is much greater between the base (breast height) of the tree and the top that can be 15% on average and 30% in extreme case. Drying temperature is another varying factor in wood density. This can result to an overestimate of up to 9 to 10% if 80 °C is used instead of 105 °C for wood density. 10 species did not have wood density data in the Global Wood Density database. This highlights the need for further wood density studies in the Congo Basin to have a more elaborated database of wood density for biomass studies. This study recommends that future studies of wood density should include the analysis of the effect of radial variation, the effect of diameter class in the same species and to use a large sampling size including individuals of same and different species to facilitate the analysis of the horizontal structure.

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LIST OF TABLES

Table-1. Wood density vertical variation of 30 species (105 °C)

    Source : Result of this research

Table-2. Wood density at drying temperature of 80 °C and 105 °C

Source: : Result of this research

Table-3. Average wood density at 105 °C of species not included in the Global Wood Density database

Source:  Result of this research

LIST OF FIGURES

Captions 

Figure-1. Vertical variation of wood density at different levels on the tree

Source: Result of this research

Figure-2. Interspecific variation of wood density of 7 tree species most represented in the study sample with a minimum of 7 individuals for Erythropheum ivorensis and a maximum of 24 for Microdesmis puberula.

Source: Result of this research