ABSTRACT
Bamboo is of ecological and socio-economic importance in the world. However, knowledge on its potential in climate change mitigation remains superficial in Cameroon. The present study identified bamboo diversity and estimated carbon stocks of the dominant species in Cameroon. Ground truth method and local informants were used for a bamboo species survey in five Agro-ecological zones (AEZs). Twenty-two circular plots of 100 m² each were utilized for biomass and density data collection in AEZ 2, AEZ 3 and AEZ 4. Destructive method was used to collect 5% of culms per plot sampled for bamboo biomass estimation. Culm density and carbon stocks for each bamboo species were extrapolated to hectares. A total of 8 bamboo species were recorded in the inventory. Three dominant bamboo species were identified (Bambusa vulgaris, Oxytenanthera abyssinica and Phyllostachys aurea) in different AEZs. For the three dominant bamboo species, biomass of culm was greater (76-84%), than those of branches (13-19%) and leaves (4-9%). Culm density varied significantly across the different bamboo species, that is, 2296, 4374 and 38017 culm/ha respectively for B. vulgaris, O. abyssinica and P. aurea. Carbon stocks varied from 13.13 tC ha-1 (O. abyssinica); 29.62 tC ha-1 (B. vulgaris) and 67.78 tC ha-1 (P. aurea), with significant variations (P< 0.05) across the different bamboo species. The fast growth rate of bamboo underpins its potential for climate change mitigation and could influence decisions and strategy for the fight against climate change in Cameroon.
Key words: Agro-ecological zone, climate change mitigation, culm density, REDD+ strategy, Cameroon.
The bamboo plant is a perennial woody-stemmed grass which belongs to the Bambusoideae sub-family, Graminae (Poaceae) family. It can be classified into monopodial (running), sympodial (clumping) and amphipodia (Arun et al., 2015). It is fast growing, widespread, and renewable (Lodovikov et al., 2007; Terefe et al., 2019). It easily adapts to an extreme and diverse range of climates and soil conditions (Xu et al., 2018). According to International world checklist Bamboos and Rattans (Maria et al., 2016), 1642 bamboo species have been identified in the world. Bamboo covers approximately 37 million hectares of forests across the tropical and subtropical world: Africa, Asia and Central and South America which is about 3.2% of the world’s total forest area (FAO and INBAR, 2018). In Africa, there is an estimated 43 species of bamboo covering about 1.5 million hectares (Gurmessa et al., 2016). Madagascar alone counts 43 species including 32 native African species (INBAR, 2018). In Cameroon, the preliminary inventory done by Ingram et al. (2010)recorded a diversity of 5 bamboo species.
Bamboo plays an important role in ecosystem services, biodiversity conservation and socio-economic development (Ingram et al., 2010; Yuen et al., 2016, 2017; Terefe et al., 2019). In the context of climate change mitigation, it is recognized as an important carbon sink (Gurmessa et al., 2016; Li et al., 2016; Yuen et al., 2016; Xu et al., 2018; Xayalath et al., 2019). In Cameroon, bamboo is considered as a Non-Timber Forest Product (NTFP) by decision n° 0209/D/MINFOF/ CAB of 26 April 2019 of the Government of Cameroon. It has an important socio-economic value of Cameroonians (Ingram et al., 2010). Ecologically, it is used to preserve river banks, and to restore some degraded lands due to its extensive fibrous rhizome and root systems that can decrease surface soil erosion, lower the risk of shallow landslides, and stabilize river banks (Song et al., 2011). However, bamboo forests in Cameroon are today under threat by deforestation and degradation, because they have been historically criminalized as invasive species and increasingly discouraged, leaving it with no guarantee to continue its socio-economic and ecological function (Ingram et al., 2010; Yuen et al., 2017).
Global climate change has inspired and instilled an increasing interest of scientific and policy stakeholders in the study of global carbon storage in order to look for a way to mitigate the trends of increasing CO2 concentration in the atmosphere. One important thing about bamboo here is that some major species are introduced and can be accepted in the context of degraded forests restoration in Cameroon, thus constituting one major carbon sinks in the Congo Basin forests. Nevertheless, knowledge on bamboo in Cameroon is still very limited and studies on carbon stocks potential of bamboo are few. Many authors have mentioned bamboo as a solution to climate change mitigation owing to its fast growing nature and high capacity to sequestrate and store carbon (Jyoti et al., 2009; Nath et al., 2012, 2015; Zhuang et al., 2015; Li et al., 2016; Yuen et al., 2017). Considering that Cameroon is involved in many initiatives related to landscape restoration and natural resource management, such as REDD+ mechanism, Afr100 and Nationally Determined Contribution (NDC) with the commitment to reduce emissions (32% by horizon 2035) as a contribution to the global effort of COP 21, it is important to measure the contribution of all potential carbon pools in order to orientate a climate change mitigation strategy. Within this context, bamboo forest ecosystem was a candidate for this study. This study was initiated to (1) investigate the number of bamboo species in Cameroon; (2) characterise the most common bamboo species in Cameroon, (3) estimate bamboo carbon storage capacity with the different agro-ecological zones in Cameroon.
Study area
This study was carried out across the national territory of Cameroon which covers a total surface area of 475 000 km2. Cameroon is located between latitudes 2° and 13° N and longitudes 8° 30’ and 16° 10’ E. It is divided into 5 AEZs. A summary of the climate and relief of these 5 AEZs is presented in Table 1. Four major types of soil are common across Cameroon; ferralitic soil essentially in the southern part of Cameroon, representing 67% of the soils in the country, volcanic soils within the Cameroon volcanic belt, ferruginous soil covering almost all of the Northern Regions (Adamawa, North and Far North) of the country and hydromorphic soils found especially in wetlands. The hydrographical network is dense in Cameroon (e.g. Sanaga, Benue, Wouri, Moungo, Kadey etc). More than 47% of Cameroon’s national territory is forested (de Wasseige et al., 2009). The forest is mainly closed tropical broad-leaved rainforest with three predominant types: lowland evergreen, lowland semi-deciduous, and montane. The closed forests are concentrated in the south and along the coast. Concerning vegetation, Cameroon is characterized by both forest and grassland. From the southern part of Cameroon to the northern part, we can find humid forest, transition forest, savannah, etc. (Ingram et al., 2010). Climate of Cameroon is summarized in Table 1.
Cameroon’s population was estimated at 19.4 million as of 1 January 2010, a projection derived from the Population and Housing Census of November 2005. This is based on an estimated annual growth rate of 2.6%. A little over half (50.5%) of the population is female, and 43.6% of the population is less than 15 years old (Ingram et al., 2010). The principal activities of the population are subsistence agriculture through slash and burn, gathering and marketing of NTFPs, hunting and fishing. Bamboo is one of the NTFPs exploited in Cameroon. They are exploited for socio-economic purposes as per listed uses: furniture; fencing and hedges; construction materials; utensils, baskets and containers; hunting implements; crop supports (climbers: bean, yams, tomatoes), musical instruments; ornamental and decorative planting; fuelwood paper and food etc (Ingram et al., 2010).
Selection of sample sites
This was done with the aid of literature reviews (Ingram et al., 2010; Ingram and Tieguhong, 2013; Ingram, 2017) on bamboo in Cameroon. Literature helped to identify the geographic location of bamboo production, processing and consumption zones in Cameroon. Local bamboo experts (informants) were identified within the bamboo primary stakeholders in the different AEZs of Cameroon. These informants were knowledgeable of bamboo production and different bamboo groves in order to lead field technical research teams for data collection. Five technical data collection teams were deployed to the different AEZs for ground truthing (field verification to ascertain truth) and data collection. Here the geographical coordinates of the bamboo groves were recorded (Figure 1). Bamboo specimen vouchers were collected to identity confirmation in the National Herbarium Obili at Yaounde. These data permitted us to complement and confirm the major bamboo species present in the AEZs in Cameroon. This survey in the 5 AEZs and literature permitted this study to count the number of bamboo species in the lineage of Bambuseae in Cameroon.
However, it is important to note that our study on bamboo carbon stocks estimation laid emphasis on Oxytenanthera abyssinica (A. Rich.) Munro; Phyllostachys aurea Riviére & C. Riviére., and Bambusa vulgaris Schrad. ex J.C.Wendl. in three AEZs where they were found in great quantities in Cameroon and was in AEZ 2, 3 and 4 respectively.
Data collection
Ecological factors
The three bamboo species were from three different ecological zones (Agroecological zones): O. abyssinica from (AEZ 2), P. aurea from AEZ 3 and B. vulgaris from AEZ 4. Since the environment upon which the plants grow affect the plants, the ecological factors of the plots were collected and presented in Table 2 (AEZ 2), Table 3 (AEZ 3) and Table 4 (AEZ 4).
Carbon stocks assessment
Bamboo density and biomass data were collected in a forest of bamboo, meeting the definition of a forest as defined by FAO (2010). The size and shape of the sample plots were consistent across the sample plot system. The circular plot of 100 m² was laid out for running bamboo (P. aurea) when the density of bamboo was 60-120 culms plot-1 and for clumping bamboo (B. vulgaris and O. abyssinica) when 1.5-2 clumps plot-1(Huy and Trinh, 2019).
Bamboo culm density and biomass data were collected in a total of 22 circular plot of 100 m² (5.64 m radius): eight plots of O. abyssinica; 6 plots of P. aurea and 8 plots of B. vulgaris. Bamboo culm densities and biomass plots designed for clumping bamboo (O. abyssinica; and B. vulgaris) were as follows: at a GPS waypoint placed by convenience in the plot on arrival, the nearest bamboo clump was determined; from there five distances of six nearest bamboo clumps sequentially were measured (Huy and Trinh, 2019). From the average distance between the bamboo clumps, the number of bamboo clumps per hectare was calculated. The number of culms (Nculms) per clump was also counted.
Bamboo biomass estimation was done using the destructive approach because, allometric equations developed for these species elsewhere did not have the same environmental factors (e.g. edaphic factor, climatic variables, etc.). According to this context and in each circular plot, 5 % of bamboo with respect to age group was felled for sampling; for each clump present (sympodial bamboo B. vulgaris or O. abyssinica) and for P. aurea (running bamboo) in the plot. In all, 5 % of all total culms in circular plots were sampled. It is important to note that for each plot sampled, three age classes were considered. The age class was divided into 1 year, 2 year and ≥ 3 year old culms (Devi et al., 2018). Bamboo morphology and color change aided in identifying different age groups (Huy et al., 2013; Li et al., 2016). For each culm sampled, in addition to specimen collection for bamboo species identity confirmation, dendrometric variables were the height, the diameter at 1.50 cm (Huy and Trinh, 2019) and age class. For sympodial bamboo, additional data like girth (m) and number of culms (Nculm) were also collected. Then, the harvested bamboo was sorted out into components (e.g. culms, branches and leaves), weighed with an electronic suspension scale (capacity 300 kg) separately for total fresh biomass of the bamboo. Subsamples of the different bamboo components: culm (at 3 positions on the culm: root collar, middle and top); branches and leaves with approximately 100-300 g (using electronic scale of precision 0.1 g) were collected for each bamboo sampled. These subsamples were oven dried at 105°C until constant weight, in the laboratory of Rural Engineering of the University of Dschang, Cameroon; in order to obtain the biomass ratio.
Data analysis
Data analysis was done using R software version 3.4.1. Descriptive analysis was done for measurement variables and bamboo biomass of components.
Comparative carbon analysis
For the comparison of culm density, biomass and carbon stocks amongst 3 bamboo species, firstly, the Shapiro-Wilk normality test was used to test data for normality test. ANOVA and Turkeys tests (parametric test) were used for data which follow a normal distribution and the non-parametric tests (Kruskal-Wallis and Wilcoxon) used for data do not follow a normal distribution; were performed to test for significant difference amongst these bamboos. In this study, Kruskal-Wallis and Wilcoxon tests were used for bamboo culm density comparison and ANOVA and Turkey tests were used to compare biomass of the different bamboo species.
Bamboo species in Cameroon
Bamboo species inventoried nationwide permit the identification of eight (8) bamboo species in the lineage of Bambuseae (tropical woody). These bamboo species were: Bambusa vulgaris Schrad. ex J. C. Wendl., Oxytenanthera abyssinica (A. Rich.) Munro, Bambusa sp. longinternode, Phyllostachys aurea Riviére & C. Riviére., Phyllostachys sp., Ochlandra travancorica (Bedd.) Gamble, Phyllostachys atrovaginata C. S. Chao & H. Y. Chou and Dendrocalamus strictus (Roxb.) Nees. Out of these bamboo species in Cameroon, only Oxytenanthera abyssinica (A. Rich.) Munro is endemic in Africa. B. vulgaris was found represented in all the different AEZs. They were in great quantities (abundant) as the dominant bamboo species in AEZ4 and AEZ5. Some bamboo species like Dendrocalamus strictus and Ochlandra travancorica. were less common in Cameroon. Bamboo species like Phyllostachys aurea and Dendrocalamus strictus were found in AEZ3 and AEZ4, respectively (Table 4).
Literature however, provided the following bamboo species in Cameroon: Dendrocalamus aurea (MINFOF 2018), Puelia atractocarpa and Oreobambos buchwaldi (Bystriakova et al., 2002; Ohrnberger and Goerrings 1988); Yushania alpina (Ingram et al., 2010), making a total of 12 bamboos of the lineage of Bambuseae. Data from the National Herbarium, Yaounde identifies 11 bamboos to species level and 4 species to sp. level; giving a total of 15 bamboo species in Cameroon.
Characteristics variables of the three bamboo species
According to our observation in the field, three bamboo species appeared dominant in Cameroon (study area). Their characteristics are presented in Table 5. Considering the fact that P. aurea is not a sympodial species, data like girth (m) and Nculms were not available for this bamboo species. B. vulgaris had the largest diameter with main diameter of 7.62±1.21 and the highest height with mean 15.95±2.96. For girth, B. vulgaris was still the largest with mean value of 20.75±9.76. Therefore, B. vulgaris > O. abyssinica > P. aurea in diameter. Comparing height, B. vulgaris > P. aurea > O. abyssinica. For girth of clump and number of culms per clump: B. vulgaris > P. aurea. Nculms.clump-1:
Characteristic of biomass components (leaves, branches, culms and total AGB culm bamboo) of these three bamboo species
Summary of bamboo biomass of the three most abundant bamboo species in Cameroon is given in Table 6. Biomass of bamboo culm was higher than those of branches and leaves. Average biomass of bamboo leaves for the three bamboo species was: B. vulgaris ˃ P. aurea ˃ O. abyssinica. Those of branches and culm follow the gradient B. vulgaris ˃ O. abyssinica ˃ P. aurea. Concerning the percentage of biomass for the different bamboo components, aboveground biomass for bamboo was 84, 13 and 4% respectively for culms, branches and leaves of B. vulgaris. For O. abyssinica, it was 77, 19 and 4% respectively; and for P. aurea, bamboo biomass was 76, 14 and 9% respectively for the three components.
Culm density and carbon stocks of the three bamboo species on study
Since P. aurea is running bamboo, the Nclump ha-1 was not estimated. The arithmetic average with standard deviation and statistical analysis of density, biomass, carbon stocks and CO2 stocks are summarized in Table 7. The results showed that average culm per hectare varied significantly with respect to the bamboo species (Kruskal-Wallis test, p˂0.000). However, Wilcoxon test showed that this difference was not significant between culm number per ha of B. vulgaris and O. abyssinica. The high value of culm per ha was found for P. aurea which was significantly different from those of these two bamboo species (Figure 2A). The contrary was observed with average culm bamboo biomass (kg) which varied significantly with respect to the bamboo species (Figure 2B) where that of P. aurea was low and significantly different from those of B. vulgaris and O. abyssinica (Kruskal-Wallis and Wilcoxon tests, p ˂0.000). ANOVA test (p ˂0.000) showed a significant difference between the three bamboo species with respect to carbon stocks and CO2eq (Figure 2C, D). Comparing the carbon stocks or CO2 stocks of these bamboo species two by two, Turkey test showed a significant difference (p ˂0.000). Globally, average carbon stocks of the three (3) bamboo species significantly followed the gradient of: P. aurea (67.78 tC ha-1) ˃B. vulgaris (29.62 tC ha-1) ˃ O. abyssinica (13.13 tC ha-1) Table 8.
Bamboo species and characterization
The diversity of bamboo showed that, many species were small sized bamboo except of the pan-tropical species (Bambusa sp.) which are medium. Cameroon still need to have big sized bamboos and this will probably be introduced species. The medium and big sized bamboo shall be very important for industrial transformation into other utilities. Cameroon has 12 bamboo species and other studies reports Madagascar, Ethiopia and Ghana with 33, 25 and 8 bamboo species respectively (INBAR 2018, Mulatu et al., 2016; Amare and Shiferaw, 2020; Kwame et al., 2020).
Bamboo has 10 000 documented uses (INBAR, 2019) and every part of the plant can be utilised. This knowledge on the number, diversity in species and characteristics (diameter, height, culm density and clump density per hectare) of bamboo are very important to inform policy makers and planners in the bamboo sector of the resources available, their ecological conditions and location. This information shall have an impact on the bamboo choices to be promoted for different transformation sectors. For the case of Cameroon, O. abyssinica (lowland bamboo) is best adapted to the semi-arid zones with mean annual rainfall of ≤1200 mm and temperature of ≤ 23°C (Guinea savannah and Sudano-
Sahel zones). The planting of O. abyssinica can be promoted in degraded landscapes, marginal lands, plantations and even intercropped in agroforestry systems (Arun et al., 2015) in Guinea Savannah and Sudano-Sahel zones to mitigate climate change (FAO and INBAR, 2018; Terefe et al., 2019; Yuen et al., 2017), serve as bioenergy (fodder, animal feed, hay, firewood, Charcoal, pellet, biogas etc.) for both animals and the local population. Bamboo can be processed in various ways to become an important source of biomass energy for cooking, heating and electricity, and has important co-benefits for farmers (INBAR, 2019a). B. vulgaris strives perfectly well in tropical zones with high temperatures and rainfall. In fact, B. vulgaris recorded in all the agro-ecological zones of Cameroon, therefore, its plantations could be promoted to serve as feed stocks for industrial transformation of bamboo throughout the country. P. aurea and Y. alpina are western highlands species (volcanic soils) in Cameroon. The western highlands local population are known for using bamboo for handicrafts, culture, housing, beehive keeping, fishing, drying rags, crop staking (Neba et al., 2020; Ingram et al., 2010; Tchamba et al., 2020).
Bamboo carbon stocks in Cameroon
Average AGBculm (kg) was significantly different with respect to the three bamboo species. B. vulgaris was the bamboo species with the highest significant AGBculm biomass compared to the two other bamboo species. In fact, we observed that similar to trees (Yuen et al., 2016), the AGBculm increased with increase in culm diameter. For this reason, therefore, the diameter follows the gradient: B. vulgaris ˃ O. abyssinica ˃ P. aurea. The same gradient was found for total culm aboveground biomass. Nevertheless, concerning aboveground biomass proportions of the bamboo components, it was approximately similar for the three bamboo species. This has also been reported by several authors who studied these three bamboo species and other bamboo species in the world (Gurmessa et al., 2016; Li et al., 2016; Nath et al., 2012; Yuen et al., 2017; Zhuang et al., 2015). With respect to literature review, bamboo carbon stocks found in the world vary in function of bamboo species (Jyoti et al., 2009; Nath et al., 2012; Patricio and Dumago, 2014; Yuen et al., 2016, 2017). This observation was confirmed in the context of this study where the average carbon stocks of three bamboo species varied in relation to the bamboo species: 13.13; 29.62 and 67.78 t C. ha-1 respectively for O. abyssinica, B. vulgaris and P. aurea. In fact, the review of bamboo aboveground carbon (AGC) for seventy bamboo species by Yuen et al. (2017)showed a range of 16 to 128 Mg C ha-1 for the different bamboo species. Many things could explain the variation of carbon stocks between bamboo species. Despite the faster growing rate of bamboo than other trees, these differences may be explained by the fact that, different bamboo species seem to have a different capacity in terms of carbon stocks. The density of culm/ha seems also to explain the significant difference of carbon stocks found between these bamboo species. For example, though P. aurea has a low AGBculm (kg) when compared to B. Vulgaris and O. abyssinica, its abundance per hectare may have a significant influence on its carbon stocks potential making it the bamboo species with the highest carbon stocks per hectare. Its abundance per hectare was 9 and 17 times greater than that of B. vulgaris and O. abyssinica respectively. In addition, ecological conditions (clump crowding, and culm position within a clump) and bamboo morphology (sympodial or running) may also influence the carbon storage potential (Xayalath et al., 2019; Yuen et al., 2017).
Importance of bamboo in restoration of forests and mitigation of climate change
Degradation and deforestation have a direct impact on forest cover. The reduction in forest cover aggravates climate change and global warming because the forest is one of the largest carbon sinks and plays an important role in the global carbon cycle and photosynthesis. Plants grow by CO2 fixation through photosynthetic processes and decrease the concentration of CO2 gases from the atmosphere. Therefore, reforestation with fast growing plants like bamboos (P. aurea) (Arun et al., 2015; Terefe et al., 2019; Yuen et al., 2017)could be recommended in the national strategy, to fight against climate change. To attain the climate change mitigation objective and the fact that P. aurea has the highest carbon storage capacity in Cameroon; this bamboo species is a solution to combat global warming effect. This bamboo species could be recommended in the context of the Bonn Challenge landscape restoration, and Africa 100 000 ha landscape restoration initiatives. The REDD+ mechanism in reducing emissions from deforestation and forest degradation in conserving forest carbon stocks, sustainably managing of forests, and enhancing forest carbon stocks is an initiative to bamboo for its high carbon storage capacity in Cameroon.Yuen et al. (2017) carried out a study on the carbon storage capacity of 70 bamboo species demonstrating that the total bamboo ecosystem carbon storage capacity is lower than that of most types of forests, as it is on a par with that of rubber plantations and tree orchards, but greater than agroforests, oil palm, various types of swidden fallows, grasslands, shrublands, and pastures. This means that bamboo can successfully substitute degraded lands (e.g. agroforestry systems, oil palm plantations, various types of swidden fallows, grasslands, shrublands, and pastures; especially in the Guinea Savannah and Sudano Sahel Regions) and marginal lands, and contribute significantly towards mitigating climate change in Cameroon. It is also feared that bamboo’s rapid growth could modify the original or local biodiversity of an area.
The results of this study on bamboo species, complemented with the literature review confirmed the diversity of 15 bamboo species and data from National Herbarium, Yaounde Cameroon; among which are three native African species. However, three of these bamboo species were more abundant and each in a specific AEZ. Concerning their capacity to mitigate climate change, we found that carbon stocks varied significantly (p < 0.5) with respect to the different bamboo species. P. aurea was the bamboo species with the highest value of carbon stocks (67.78 tC ha-1) and O. abyssinica with the least carbon stocks (13.13 tC ha-1).
The authors have not declared any conflict of interests.
The authors are grateful to the International Bamboo and Rattan Organization (INBAR), under its Inter-Africa bamboo smallholder livelihood Development Programme for funding this study; the University of Dschang for providing laboratories and all laboratory collaborators for collecting field data; and the local experts. The reviewers who assured the quality of this study are also appreciated.
REFERENCES
|
Amare SM, Shiferaw A (2020). Bamboo policy Integration Analysis, Ethiopia. INBAR working paper N° 84. 33 p.
|
|
|
|
Arun JN, Lal R, Das AK (2015). Ethnopedology and soil quality of bamboo (Bambusa sp.) based agroforestry system. Science of the Total Environment 521-522:372-379.
Crossref
|
|
|
|
|
Bystriakova N, Kapos V, Lysenko I (2002). Potential distribution of woody bamboos in Africa and America. In: Working Paper 43, United Nations Environment Program-World Conservation Monitoring Centre (UNEP-WCMC),Cambridge, UK.
|
|
|
|
|
Devi AS, Singh KS, Lalramnghinglova H (2018). Aboveground biomass production of Melocanna baccifera and Bambusa tulda in a sub-tropical tropical bamboo forest in Lengpui, North East India 7(7):23-28.
|
|
|
|
|
de Wasseige C, Devers D, Marcken P, Eba'a Atyi R, Nasi R, Mayaux P (2009). The forests of the Congo Basin, State of the Forest 2008. Office des publications de l'Union Europeenne, Congo Basin Forest Partnership, Yaounde, Cameroon.
|
|
|
|
|
CIRAD (2000). Variations in Soil Fertility Under Cotton Crops in The Bénoué Cotton-Growing Area In Northern Cameroon. Beltwide Cotton Conferences, Nashville, Tennessee. Pp. 1635-1641.
|
|
|
|
|
FAO (2010). Global forest resources assessment 2010 terms and definitions', Forest Resources Assessment Working Paper 144/E. Rome: Forestry Department, FAO, p.27.
|
|
|
|
|
FAO and INBAR (2018). Bamboo for land restoration. INBAR Policy Synthesis Report 4. INBAR: Beijing, China 67 p.
View
|
|
|
|
|
Gurmessa F, Gemechu T, Soromessa T, Kelbessa E (2016). Allometric Equations to Estimate the Biomass of Oxytenanthera Abyssinica (A. Rich.) Munro. (Ethiopian Lowland Bamboo) in Dicho Forest, Oromia Region, Western Ethiopia. International Journal of Research Studies in Biosciences 4(12):
Crossref
|
|
|
|
|
Huy B, Thanh GT, Poudel KP, Temesgen H (2019). Individual plant allometric equations for estimating aboveground biomass and its components for a common bamboo species (Bambusa procera A. Chev. and A. Camus) in tropical forests. Forest. 10(4).
Crossref
|
|
|
|
|
Huy B, Trinh TL (2019). A manual for Bamboo Forest Biomass and Carbon Assessment; INBAR. 155 p.
|
|
|
|
|
International Bamboo and Rattan Organisation (INBAR) (2019). Trade Overview 2018 Bamboo and Rattan Commodities in China, 15 p.
|
|
|
|
|
International Bamboo and Rattan Organisation (INBAR) (2019a). Bamboo as a source of bioenergy 2 p.
|
|
|
|
|
International Bamboo and Rattan Organisation (INBAR) (2018). Remote Sensing-Based Regional Bamboo Resource Assessment Report of Madagascar; Tsinghua University of China.
|
|
|
|
|
Ingram VJ (2017). Shifting global development discourses : Implications for forests and livelihoods Changing governance ... Shifting global development discourses : Implications for forests and livelihoods Changing governance arrangements : NTFP value chains in the Congo B. International Forestry Review 19(S1): 1-18.
Crossref
|
|
|
|
|
Ingram V, Tieguhong JC, Nkamgnia EM, Eyebe JP, Ngawe M (2010). The bamboo production to consumption system in Cameroon. CIFOR Working Paper, 50, x-pp.
View
|
|
|
|
|
Ingram V, Tieguhong JC (2013). Bars to jars: Bamboo value chains in Cameroon. Ambio 42(3): 320-333.
Crossref
|
|
|
|
|
IRAD (2005). République du Cameroun Institut de Recherche Agricole pour le Zones Agro-écologiques , Centres , Stations et Antennes. 237, 2123.
|
|
|
|
|
Jiotsa A. Timothy MO, Yambene H (2015). Cooperative Movements in the Western Highlands of Cameroon.
View retrieve on the 2/10/2019.
|
|
|
|
|
Jyoti NA, Das G, Das AK (2009). Above ground standing biomass and carbon storage in village bamboos in North East India. Biomass and Bioenergy 33(9):1188-1196.
Crossref
|
|
|
|
|
Kwame A, Oduro EA, Obeng HA, Sarah P (2020). Bamboo policy Integration Analysis, West Africa, Ghana. INBAR working paper N° 83. 44 p.
|
|
|
|
|
Li LE, Lin YJ, Yen TM (2016). Using allometric models to predict the aboveground biomass of thorny bamboo (Bambusa stenostachya) and estimate its carbon storage. Taiwan Journal of Forest Science 31(1):37-47.
|
|
|
|
|
MINFOF (2018). Programme National de Développement de la filière du Bambou de Chine au Cameroun.
|
|
|
|
|
Maria SV, Lynn GC, Dransfield J, Govaerts R, Baker WJ (2016). World Checklist of Bamboo and Rattans. INBAR Technical Report No. 37. 454 p.
|
|
|
|
|
Mulatu Y, Alemayehu A, Tadesse Z. (2016). Biology and Management of Indigenous Bamboo Species of Ethiopia. Ethiopian Environment and Forest Research Institute (EEFRI), Addis Ababa.
|
|
|
|
|
Nath AJ, Franklin DC, Lawes MJ, Das MC, Das AK (2012). Impact of Culm Harvest on Seed Production in a Monocarpic Bamboo. Biotropical 4(5):699-704.
Crossref
|
|
|
|
|
Nath AJ, Lal R, Das AK (2015). Managing woody bamboos for carbon farming and carbon trading. Global Ecology and Conservation 3:654-663.
Crossref
|
|
|
|
|
Neba B, Chimi C, Gadinga W, Kaam R (2020). Bamboo policy integration analysis, Cameroon. INBAR Working Paper.
|
|
|
|
|
Ohrnberger D (1999). The bamboos of the world. Elsevier, Amsterdam the Netherlands.
|
|
|
|
|
Patricio JH, Dumago SW (2014). Comparing aboveground carbon sequestration of three economically important bamboo species grown in Bukidnon, Philippines. Journal of Multidisciplinary Studies 3(1):1-15.
Crossref
|
|
|
|
|
Song X, Zhou G, Jiang H, Yu S, Fu J, Li W (2011). Carbon sequestration by Chinese bamboo forests and their ecological benefits : assessment of potential , problems , and future challenges.
Crossref
|
|
|
|
|
Tchamba M., Rene K., Neba B., Chimi C., Tanoungong A (2020). Remote Sensing-Based Bamboo Mapping and Bamboo Stock Assessment in Cameroon. INBAR working Paper.
|
|
|
|
|
Terefe R, Jian L, Kunyong Y (2019). Role of Bamboo Forest for Mitigation and Adaptation to Climate Change Challenges in China. Journal of Scientific Research and Reports 20:1-7.
Crossref
|
|
|
|
|
Toukam MG, Cellier G, Wicker E, Kahane R (2009) Broad diversity of ralstonia solanacearum strains in Cameroon 8 p.
|
|
|
|
|
Xayalath S, Hirota I, Tomita S, Nakagawa M (2019). Allometric equations for estimating the aboveground biomass of bamboos in northern Laos. Journal of Forest Research 24(2):115-119.
Crossref
|
|
|
|
|
Xu M, Ji H, Zhuang S. (2018). Carbon stock of Moso bamboo (Phyllostachys pubescens) forests along a latitude gradient in the subtropical region of China pp. 1-11.
Crossref
|
|
|
|
|
Yerima BPK, Van Ranst E (2005). Major Soil Classification Systems used in the Tropics: Soils of Cameroon. Trafford Publishing, Canada.
|
|
|
|
|
Yuen JQ, Fung T, Ziegler AD (2016). Review of allometric equations for major land covers in SE Asia: Uncertainty and implications for above- and below-ground carbon estimates. Forest Ecology and Management 360:323-340.
Crossref
|
|
|
|
|
Yuen JQ, FungT, Ziegler AD (2017). Carbon stocks in bamboo ecosystems worldwide: Estimates and uncertainties. Forest Ecology and Management 393: 113-138.
Crossref
|
|
|
|
|
Zhuang S, Ji H, Zhang H, Sun B (2015). Carbon storage estimation of moso bamboo (Phyllostachys pubescens) forest stands in Fujian, China. Tropical Ecology 56(3):383-391.
|
|
