International Forestry Review Vol.XX(X), 2016 1

Contribution of non-timber forest products to cash and non-cash income of remote forest communities in Central AfricaD. ENDAMANA1, K.A. ANGU1, G.N AKWAH2, G. SHEPHERD3 and B.C. NTUMWEL4

1International Union for Conservation of Nature, Central and West Africa Programme, Bastos, PO Box 5506, Yaoundé, Cameroon. E-mail: dominique.endamana@iucn.org and kenneth.angu@iucn.org2International Union for Conservation of Nature, Global Forest and Climate Change Programme, REDD+ office. E-mail: george.akwah@iucn.org 3International Development Department, Ecosystems, Commission for Ecosystem Management, IUCN. E-mail: gillshepherd@compuserve.com 4Ministry of Environment, Nature Protection and Sustainable Development, Ebolowa, Cameroun. Regional Brigade for Environmental Inspections. E-mail: bonitochia@yahoo.fr

Email: dominique.endamana@iucn.org and dendamana@yahoo.fr

SUMMARY

This paper evaluates the contribution of NTFPs to cash and non-cash income of local communities within the jointly managed Sangha Tri-National and Dja-Odzala-Minkébé Tri-National forest landscapes that lie between Cameroon, Republic of Congo, Gabon and the Central African Republic in Central Africa. Data were collected from respectively 172 and 158 Bantu and IP households by applying the Poverty-Forests Linkages Toolkit method. Ten species of NTFPs that are important sources of cash and non-cash income for the study groups were recorded. More than 45% and 55% of Bantu and IP incomes are respectively derived from NTFPs. NTFPs contribute higher to non-cash income for the Bantu and IP in Cameroon and CAR but contribute more to cash income in Congo. Bantu communities get higher total incomes from NTFPs than IP. In all groups, Bushmeat is the most important income generating NTFP. These results could contribute to resource allocation for implementation of long-term development plans in Central Africa, for instance programmes for Reducing Emissions from Deforestation and Forest Degradation.

Keyswords: cash-income, Central Africa, household, non-cash income, NTFP

Contribution des produits forestiers non-ligneux aux revenus monétaires et non-monétaire des communautés forestières d’Afrique centrale

D. ENDAMANA, K.A. ANGU, G.N AKWAH, G. SHEPHERD et B.C. NTUMWEL

Le présent article évalue la contribution des produits forestiers non ligneux (PFNLs) aux revenus monétaires et non-monétaires des communau-tés riveraines des paysages de la Tri-National de la Sangha et la Tri-National Dja-Odzala-Minkébé, situés entre le Cameroun, le Congo, le Gabon et la République Centrafricaine (RCA), en Afrique centrale. Les données ont été collectées dans 172 ménages Bantu et 158 ménages des peuples autochtones (PA) par l’application de la boîte à outil forêt-pauvreté. Dix espèces de PFNLs importantes sources de revenu monétaire et non-monétaire des riverains ont été enregistrées. Les PFNLs contribuent respectivement au revenu de plus de 45% et 55% des ménages Bantu et PA. Au Cameroun et en RCA, les PFNL contribuent plus au revenu non-monétaire des ménages Bantus et PA. Par contre, ils contribuent plus au revenu monétaire des ménages au Congo. Les Bantus génèrent plus de revenu total que les PA. La viande de brousse est le PFNL qui génère le plus de revenu pour les Bantu et PA. Ces résultats pourront contribuer à guider la répartition des ressources dans le cadre de la mise en œuvre des mécanismes de développement en Afrique centrale à l’instar du programme de réduction des émissions dues à la déforestation et à la dégradation des forêts.

Contribución de los productos forestales no leñosos a las rentas monetarias y no monetaria comunidades forestales de África central

D. ENDAMANA, K.A. ANGU, G.N AKWAH, G. SHEPHERD y B.C. NTUMWEL

El artículo presente evalúa la contribución de los productos forestales no leñosos (PFNLs) en las rentas monetarias y no monetarias de las comunidades ribereñas de los paisajes de Selección - Nacional de Sangha y Selección - National Dja-Odzala-Minkébé, situadas entre Camerún, el Congo, Gabón y la República Centroafricana (RCA), en África central. Los datos han sido recolectados en 172 gobiernos de la casa Bantu

2 D. Endamana et al.

organised in such a way that the communities derive sustain-able benefits from the sales of their harvested products, with strict respect of the national forestry regulations in force. This is one of the reasons why countries from Central Africa endorsed REDD+ during the seventeenth conference of parties of the United Nations convention for the fight against climate change in Durban, South Africa and have placed REDD+ as a tool to achieve sustainable development. In Cameroon, involving civil society and local communities in identifying livelihood enhancement options as part of REDD+ strategies helps both governments and local communities to understand the potential for REDD+ as a development tool. It allows communities to gain ownership of REDD+ pilot projects and feel more motivated to help with the implementa-tion of the national REDD+ strategies in the region (Angu Angu and Endamana 2015).

Within the implementation of this mechanism, knowledge of cash and non-cash income derived from NTFPs is impor-tant in guiding the allocation of financial assistance in par-ticular and, benefit sharing and decision making in general. For the REDD+ mechanism to succeed in Central Africa, there is an urgent need to evaluate accurately the cash and non-cash income values of NTFPs, and the other related income generating activities that contribute to the livelihoods of the local communities. This paper evaluates the contribu-tion of NTFPs to cash and non-cash income of local commu-nities within the jointly managed Sangha Tri-National (TNS) and Dja-Odzala-Minkébé Tri-National (TRIDOM) forest landscapes that lie between Cameroon, Congo and the CAR in Central Africa.

BACKGROUND

In Africa, more than two-thirds of the population rely partly on forests products to satisfy their livelihood needs (Arnold 2001, CIFOR 2005, Kaimowitz 2003). Aside from timber, NTFPs play an important role in providing between 29–39% of food, medicine and income needs to about 80% of the local populations living in forest areas of Central Africa (Loubelo 2012; Levang et al. 2015). NTFPs are goods of biological origin other than timber, derived from forests and agro-forest-ry areas (FAO 1999, Loubelo 2012). They are equally used as trophies, for making ethno-musical instruments, jewellery, for decoration, magico-religious issues and offer multipur-pose services (Alison 2007, Bobo et al. 2015, Lohani 2010, Mallesson et al. 2008, Timko et al. 2010). Bushmeat is the main NTFP of animal origin (Ngoye 2010), meanwhile those

y 158 gobiernos de la casa de los pueblos autóctonos (PA) por la aplicación de le cojea a herramienta bosque-pobreza. Diez especies de PFNLs que importan para la renta monetaria y no monetaria de los ribereños han sido registradas. PFNLs contribuyen respectivamente a la renta de más del 45 % y el 55 % de los gobiernos de la casa Bantu y EL PA. En Camerún y en RCA, PFNL contribuyen más a la renta no monetaria de los gobiernos de la casa Bantus y PA. En cambio, ellos contribuyen más a la renta monetaria de los gobiernos de la casa en el Congo. Bantus generan más renta total que PA. La carne de selva es PFNL que genera la más renta para Bantu y PA. Estos resultados podrán contribuir a guiar la repartición de los recursos en el ámbito de la puesta en marcha de los mecanismos de desarrollo en África central a semejanza del programa de reducción de las emisiones debidas a desforestación y a la degradación de los bosques.

INTRODUCTION

The African continent as a whole has the highest proportion of people in the world who live on less than 1.25 US dollar a day (Anderson et al. 2006, OMD 2013). The proportion of those living in extreme poverty has declined from 56.5% in 1990 to 48.5% in 2010 (OMD 2013). With its 2.8 million km2 of diversified and rich forests, the Congo Basin offers the one option for local populations to meet their daily livelihood needs. Forest people have developed a multitude of tech-niques to exploit forest lands and the related resources. Today, besides other sources of income, the harvesting of Non- Timber Forest Products (NTFPs) is not only one of the most important income generating activity for local people, but equally a source of food, medicines and serves other multi-purpose values. Yet, a major challenge persists in the accurate evaluation of NTFPs as a revenue component for the liveli-hoods of local people (Ngalim 2011). The importance of NTFPs in household’ income is not well known due to the absence of a systematic and rigorous data collection system at the country levels (FAO 2001). Generally, only a part of the NTFPs traded in markets is recorded and the proportion of NTFPs consumed in the household and used for other non-commercial purposes are little known. Similarly, the products of illicit trade is not considered (Ingram et al. 2010). The non-cash income values of NTFPs for local people have rarely been incorporated in official land use planning and sus-tainable development schemes (CBD 2001). More recently, there has been a growing interest in the economic potential of NTFPs. This is because of the role they can play in reducing poverty levels and promoting sustainable development. Supporting programs to develop certain NTFPs for larger commercial markets, could provide more equitable income redistribution on the long term (Peters 2000). At the same time, a number of Central African countries, including Cameroon, Congo and the Central Africa Republic (CAR) are currently engaging in long-term development mechanisms like Reducing Emissions from Deforestation and Forest Degradation (REDD+) in order to improve the livelihoods of local people and implement sustainable forest management practices (Sjaastad et al. 2005). REDD+ is an international mechanism aiming at encouraging developing countries to protect and upgrade their carbon stock levels (Mogba 2013, PROFOREST 2011) by supporting actions that reduce defor-estation and forest degradation. It seeks to reduce the pressure on forest resources meanwhile upgrading the benefits derived by people living on the resource. Local communities harvest-ing and living on NTFPs for example will be legalised and

Contribution of non-timber forest products to cash and non-cash income of remote forest communities in Central Africa 3

of plant origin include raffia palm, mushrooms, seeds, wild vegetables, medicinal plants and all plant related derived products (oils and silk) (Adjanahoum et al. 1996). A number of studies have tried to ascertain the effective contribution of NTFPs to the revenue of local communities in Africa (Ndoye et al. 1999, Ruiz et al. 2000, Tieguhong and Zwolinski 2009). But, these studies have been limited to evaluating only the cash income derived from the sales of NTFPs and omitting the non-cash value derived from the non-commercial use of NTFPs. Specific research methods for collecting and evaluat-ing the contribution of NTFPs to household economies were initially developed by Tabuna (1999), and have been widely implemented (Medicinal Plants Specialist Group 2007, Ndoye et al. 1999, PROTA 2008, Ruiz et al. 2000). More recently, Loubelo (2012) assessed the impact of NTFPs on household economies and food security in the Democratic Republic of Congo, and Ingram et al. (2010) reported on the contribution of NTFPs in national economies and strategies for sustainable resource management in Central Africa. Nowadays, the need for accurately evaluating the contribution of NFTPs to the revenue of rural peoples at both the regional and national levels is highly discussed (Ingram et al. 2010, Ngoye 2010, Noubissie et al. 2008, Tieguhong et al. 2008, Tieguhong and Zwolinski 2009). Both CIFOR's PEN project and PROFOR and IUCN's Poverty-Forests Linkages Toolkit (FPTK) have been developed to facilitate the evaluation and consideration of the non-cash value of NTFPs in calculating total income (Angelsen et al. 2014, Wunder et al. 2014).

The TRIDOM and TNS forest landscapes in Central Africa lie between Cameroon, Congo and the CAR, where local people directly use NTFPs for both commercial and non-commercial purposes. They enclose several land use systems that are managed as a common entity between the three countries (Endamana et al. 2010, Fondjo 2013, Ngoufo et al. 2012, TNS 2009) and offer the best chance to evaluate, the cash and non-cash income generated from NTFPs, while using scientifically proven methods. Communities living within the TRIDOM and TNS forests are comprised of the Bantu and the Indigenous people (TNS 2009). The similarity in ethnicity between the communities in the three Central African countries allows for cross comparisons of the contri-bution of NTFPs to the income of the local people. This study is based on the hypothesis that the evaluation of the sum of the cash and non-cash income derived from NTFPs contribute significantly to the total income of the Bantu and IP in the study area.

METHODOLOGY

Study area

This study was conducted in six villages in the TNS and the TRIDOM forest landscapes that encompass portions of south-eastern Cameroon, north-western Congo, and the southwest-ern part of the CAR (Figure 1). These are Massea and Gribe (Cameroon), Kabo and Bomassa (Congo) and Moussapoula and Lindjombo (CAR) (Table 1). The villages in Cameroon,

Congo and the CAR are located at the periphery of the Nki national park, Nouabale Ndoki national park and the Dzanga Sangha reserve, respectively. The TNS and TRIDOM are located between 3°32′12″–0°40′29″ latitudes North and 15°28′26″–17°34′8″ longitudes East, and between 3°29′53″–0°26′28″ latitudes North and 11°51′54″–15°57′21″ longitudes East, respectively (EDF 2006). The TNS and TRIDOM are identified as high priority conservation areas for their rela-tively intact forest, and as habitat for many threatened species. The TNS forest extends over approximately 44,000 km2 (TNS 2009), meanwhile TRIDOM covers 141,000 km2 (EDF 2006). They lie within the Guineo-Congolian lowland rain-forest in the Congo basin and are characterised by semi- deciduous, swamp forest with patches of wet savannah known as Bais. The climate is typically of the equatorial with annual rainfall that ranges between 1600 and 2000 mm in the TRIDOM and, 1450 and 1600 mm in the TNS. In the last two decades, logging activities have increased because of the growing demand for timber and progressive opening up of the area. Wildlife in the area is very rich and diversified. Species like the Bongo (Tragelaphus eurycerus Isaaci), giant forest hog (Hylochoerus meinertzhageni Thomas), giant pangolin (Manis gigantea Illiger), and a number of threatened species like African forest elephant (Loxondonta africana cyclotis Matschie), lowland gorilla (Gorilla gorilla Savage), and the chimpanzee (Pan troglodytes Blumenbach) occur in the area.

The area is rich in biocultural diversity and encloses a multitude of ethnic groups having different socio-economic orientations. The most important and widely distributed ethnic group across the three studied countries in the TNS and TRIDOM landscapes, are the Bantu people. In the study area, the Bantu were the Mpiemou, Kounabeemb, Mpou’mpong, Bangando and Bakwele in Cameroon (CEES and UICN 2010), and the Gbaya, Sangha-Sangha, Mpiemo, Oubanguien and Ngbaka in CAR (APDS 2011). The area equally encloses more than 12,000 indigenous people (IP) who live perma-nently in the villages. The common languages of communica-tion among the study communities are Kouna-mbembe, Kako and Bangando in Cameroon, Bomassa and Pomos in Congo, and Ngbandi, Gbanu, Kaba and Banda in CAR. Population densities are estimated at four people/km2 and one person/km2 in the TNS and TRIDOM areas respectively (EDF 2006, TNS 2009).

The main subsistence activities practiced by local people are agriculture and the harvesting of NTFPs of both plant and animal origin. In the area, agriculture faces the problem of crop destruction by wildlife and the unavailability of farm- to-market roads because the area is particularly remote and isolated. People rely on the harvesting of Bushmeat, NTFPs of plant origin (e.g. Irvingia gabonensis Aubry-Lecomte ex O’Rorke, Gnetum africanum Welw, Baillonella toxisperma Pierre, Ricinodendron heudelotii Baillon) and fishing to meet their daily livelihood and income needs. NTFPs have been reported as vital for the social development of these commu-nities (Endamana et al. 2013). The area has little to no physi-cal infrastructure and facilities, making it very remote and underdeveloped. Among the Bantu people, forest resources

4 D. Endamana et al.

TABLE 1 List of the villages and number of households interviewed by country and ethnic groups

Countries VillagesNumber of households interviewed per ethnic group

Bantu IPs Total

Cameroon Malea Ancien 40 40 80Gribe 40 40 80

Republic of Congo Bomassa 20 13 33Kabo 22 15 37

Central Africa Republic Mousapoula 20 30 50Lindjombo 30 20 50

Total 172 158 330

FIGURE 1 Location of the study area showing the Sangha Tri National (TNS) and the Dja-Odzala-Minkébé Tri-National (TRIDOM) landscapes

are often locally managed at the village level by the tradi-tional council that is headed by a chief. Meanwhile for IP, the resources are managed, allocated and redistributed at the family level by the head of the household.

Socioeconomic profile of household respondents

The interviewed household respondents (HRs) were mainly adults between 40 and 44 years old (i.e. the mean age of HRs in Congo, Cameroon and CAR was 40, 42 and 44 years, respectively). They represented the active age group in all sites and were the eldest persons found per household during

interviews. In the study area, about 66% of the HRs went to school. Among those, about 57% of Bantu HRs and 45% of IP HRs had completed primary education. About 26% of Bantu HRs and 1% of IP HRs had attained secondary educa-tion level. About 65% of HRs manage large families (aver-agely five persons per household) because they are legally engaged. About 84% of HRs lived as husband and wife in Cameroon, 32% in the CAR and 69% in Congo. In the study area as a whole, the major economic activities are made up of agriculture (4%) livestock breeding (5%) and harvesting of NTFP (32%). The total number of households varied between 33 and above per village.

Contribution of non-timber forest products to cash and non-cash income of remote forest communities in Central Africa 5

communities were recorded in a table, which was later used to produce a score chart. From the list of all NTFPs identified during the group discussions, groups of NTFPs were consti-tuted. For example, all NTFPs of animal origin were grouped under the Bush meat category. NTFPs that are used for tradi-tional medicines made up the group of medicinal plants and all NTFPs that were used as vegetables made up the group of wild vegetables. The most common NTFPs identified as the most important sources of income in Cameroon, Congo and the CAR are presented in Table 2.

Heads of households were then sensitised on the data collection process to be held during the following day. Sepa-rate discussions were held with the IP and Bantu households in order to avoid the influence of one group on the other.

The scoring exerciseThe following day, heads of households were grouped into the previously identified wealth categories. The four groups constituted were separated from each other during the data collection process.

A researcher and one assistant facilitated each of the groups. The scoring process was explained to each group member and the conceived score chart per village was spread as a large table on the ground. Twenty seeds each were given to every member of the group (each representing a house-hold). Each household was invited to distribute the 20 seeds as a function of the level of contribution of each product to his total income. The household representative was free to put as many seeds on a given product such that the sum of distrib-uted seeds among the list of product equalled 20. The same exercise was repeated for non-cash income for each product with the exception of services. At this stage, the proportion of a product that generate cash income (PrI) and/or non-cash income (PrNI) could be evaluated. The total number of seeds per product per household was reported on a score sheet. Cash income was understood as income resulting directly from the sales of a product at the local market. Non-cash income was understood as part of the product that is consumed in the household, offered as a gift to a tierce person or used for other non-commercial purposes. From the scoring exercise, it was possible to determine the number of households

Data collection

Data were collected in two villages of each of the three countries covered by the TNS and TRIDOM between March 2012 and April 2012 using the Poverty-Forests Linkages Toolkit (FPTK) (PROFOR 2009). PROFOR developed a FPTK to facilitate relevant data collection and analysis. The Toolkit was conceived from the partnership with CIFOR, IUCN, ODI, and Winrock International. The Poverty-Forest Linkages Toolkit includes a set of rapid appraisal methods for gathering information on economic as well as other contribu-tions of forests to household livelihoods. This method of ana-lysing field data facilitates the evaluation of the role of forests in reducing poverty and vulnerability. The toolkit suggests how to frame the results in order to make them relevant to planners, government agencies and other institutions and organisations, at both local and national levels. It equally explains the Poverty Reduction Strategy Paper (PRSP) process and it identifies the required strategies and skills for influencing the PRSP process (including potential entry points for forestry) (Shepherd and Blockhus 2008).

The FPTK was chosen because it has been proven effi-cient in collecting information on the role of forest goods and services in the livelihoods of rural households (Mayers et al. 2013). The toolkit equally enables the collection and analysis of data on the contribution of NTFPs, timber forest products, cash crops, food crops, fishery and livestock products to the revenue of households as well as other livelihood services (temporal and permanent jobs, cash transfers etc.). In this paper, only an assessment of the different NTFPs that contrib-ute to cash and non-cash income, their percentage contributions and the related monetary values for all the HRs (irrespective of wealth rank, gender or age) per ethnic group is documented. The data collection process consisted in organising focus group discussions with Bantu and Indigenous peoples sepa-rately, grouping categories on the main sources of income in the village (NTFPs, agriculture, livestock and others), performing a scoring exercise and household interviews.

Focus group discussionIn each village, the purpose of the study was first presented to the chief who assisted in producing a list of all the households in the village. The chief then gathered between 15 and 20 permanent village residents including men, women and the young people. Group discussions were performed to facilitate the classification of households according to local wealth criteria. The Rich and Poor local wealth criteria classes were identified. After the classification exercise, 40 sample house-holds were selected randomly and distributed into four groups (A for rich men, B for poor men, C for rich women, and D for poor women). The sample rate varied between 33% to 76% of the total households of IP and 34% to 62% of the total house-holds of Bantu. Through continuous group discussions, the understanding of the village landscape and the identification of timber forest products, NTFPs, agricultural products and services that accounted for the cash and non-cash income of households in the previous year was mapped. The twenty most important NTFPs that are sources of income for the

TABLE 2 The most common NTFPs identified as the most important sources of cash income in Cameroon, Congo and the CAR

NTFP Cameroon Congo CAR

Bush meat yes yes yesHoney yes yes yesMedicinal plants yes yes yesOkok yes yes yesBush Mangoes (Irvingia ssp.) yes yes yesCola nuts yes yes noPalm wine and mat yes yes yesCaterpillars no yes yesMushrooms no yes yesMarantacae leaves no yes yes

6 D. Endamana et al.

obtaining cash and non-cash income from each product and the percentage contribution of each product in the total revenue of the household. At the end of the exercise, a semi-structured interview was administered to each household.

Household interviewsA questionnaire was addressed to each of the households chosen by simple random sampling among households in the four wealth groups. Questions were asked about the socio-demography and socio-economic characteristics of house-holds such as age, level of education, membership in a formal group etc. Similarly, HRs were asked to estimate the annual cash income for the previous year derived from each source of income including NTFPs. The score of each product that is sold (source of cash-income) and that is consumed or offered as gift (source of non-cash income) was obtained from the scoring exercise and all the scores for all the products were recorded in the datasheet of the interviewed household.

A total of 330 HRs from the six studied villages of Cameroon, Congo and the CAR participated in the exercise (Table 1).

Data analysis

Data from group discussions, scoring exercise and household interviews were compiled in Microsoft Excel 2007. The cross table analysis tool was used to evaluate the percentage of household obtaining cash and non-cash income from each NTFP and the contribution of NTFPs to the total household incomes. It also permitted for the evaluation of the relative proportions of NTFPs that are important revenue components and their contribution to total household income. Details of the calculations of the cash and non-cash income obtained from NTFPs is presented in table 3.

Percentage of household obtaining cash and non-cash income from each NTFPProducts were considered when they contributed to the cash income and non-income of the household on the score chart. The scores per NTFP were converted to dichotomous values. The score took the value 1 if it is different from zero means that the NTFP contribute to the household revenue, and zero otherwise. For each product, a mean value was calculated. This mean value represented the proportion of households who obtain cash income from the product. The same method was applied to calculate the proportion of households who obtain non-cash income from the product. Percentage of household obtaining cash and non-cash income from each NTFP per ethnic group per country is compiled in Table 4.

Contribution of NTFPs to the total household incomesThe contribution of all products to the total household income for each ethnic group was evaluated by multiplying the score assigned to the product by 100/20 (i.e. 5). This contribution is given as a percentage of each product. The sum of percent-ages is equal to 100. These percentages are calculated within each ethnic group and for the entire village studied. The

percentage contribution of NTFPs to the total household income per ethnic group in Cameroon, Congo and the CAR is presented in figure 2.

Estimation of cash and non-cash income in the total household incomeThe cash and non- cash income derived from NTFP in each ethnic group, per country per year was evaluated in US dollars in the SPSS 20.0 software. The value of a US dollar was approximately 500 F CFA. The following process was used:

- The value (Pi) of cash income of each product in the total income of the household is the value obtained by the number of seeds allocated by the HR to the list of products based on their respective contribution to the income of the household surveyed. The sum of the values allocated is equal to 20.

- The annual revenue (RAj) of one of the products contributing to the cash income of the household is declared by the respondent during the individual survey.

- The estimation of the household’s annual gross cash income (CI) is obtained by the rule of three: CI = (RAj*20)/Pi.

- The estimation of the annual gross cash income for each product contributing to household revenue (CIi) is obtained from CI by the rule of three: CIi = (CI*P)/20. Note that the sum of all CIi is equal to CI

- The same operation is done for each household with-in the wealth criteria groups A, B, C and D. The sum of cash income of each NTFP per group is done to obtain the contribution of each NTFP to the cash income of the sampled households per village.

- Given that PrI, is the proportion of the category of a product sold in the market for cash income and PrNI is the proportion of the category of a product that is not sold and generate non-cash income, the annual non-cash income (NCIi) of the product is obtained by the rule of three: [NCIi = CIi* PrNI/PrI].

- The annual total income (ATI) of the product is the sum of the cash income + the non-cash income [ATIi = NIi + NCIi].

- If “n” is the number of households participating in the collection of data, the total income of the group (RTg) is the sum of the ATIi for each household.

- If “m” is the number of groups in each village, the total income of the sample (TIs) is the sum of income of the various groups.

- If “k%” is the true sample of households that partici-pated in collecting the data, the total income of the village (TIv) = [TIs*100/k%]

- Given that “X” is the number of household(s) in the village, and “Y” the average size of the household, the income per household is: Ihh = TIv/X; the income per capita is: Icap = Ihh /Y and the daily income per capita is: Icapd = Icap /365.

Contribution of non-timber forest products to cash and non-cash income of remote forest communities in Central Africa 7

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8 D. Endamana et al.

TABLE 4 Percentage of households obtaining cash and non-cash income from each NTFP per ethnic group per country

Ethnic group

NTFPs Scientific namesCameroon Congo CAR

Cash income

Non-cash income

Cash income

Non-cash income

Cash income

Non-cash income

Bantu

Okok Gnetum africanum 62.5 97.5 72.0 80.3 42.5 72.5Cola nut Cola spp. 25.0 90.0 9.4 12.5 na naDjangsang Ricinidendron heudelotti 76.3 86.3 na na na naBush mangoes Irvingia gabonensis 93.8 100.0 37.3 51.6 25.0 56.3Moabi’s oil Baillonella toxisperma 61.3 76.3 na na na naMedicinal Plants 55.0 83.8 15.6 25.0 17.5 20.0Fish 61.3 87.5 49.2 80.0 46.0 48Lianas Bauhinia liana 42.5 71.3 na na na naRattan Calameae 28.8 52.5 na na na naBush meat 93.8 100.0 73.3 77.6 76.3 86.3Mushroom Amanita muscaria na na 49.3 56.6 40.0 75.0Caterpillars na na 48.3 63.3 46.3 63.8Marantacea leaves na na 31.8 34.3 20.0 36.3Insects (grubs, beetle) na na 14.6 41.7 na naRaffia (wine and mat) Raphia na na 35.0 50.9Wild yam Dioscoreae sp. na na na na 20.0 51.3Honey na na na na 8.8 55.0

Indigenous people

Djangsang Ricinidendron heudelotti 76.3 85.0 na na na naWild vegetables 67.5 98.8 na na na naBush Mangoes Irvingia gabonensis 96.3 100.0 25.0 48.8 87.5 90.5Honey 31.3 68.8 30.0 63.1 85.0 90.0Medicinal Plants 46.3 78.8 na na 65.0 100.0Fish from local rivers and others

58.8 82.5 na na na na

Lianas Bauhinia liana 57.5 81.3 45.0 65.0 na naRaffia (wine and mat) Raphia 63.8 80.0 25.0 30.0 na naBush meat 83.8 97.5 35.0 97.5 87.5 88.0Mushroom Amanita muscaria na na 52.5 73.1 92.5 90.0Caterpillars na na 37.5 53.8 80.0 100.0Okok Gnetum africanum na na 87.5 85.6 90.0 88.5Marantacea leaves na na 45.0 58.8 72.5 70.0Insects (grubs, beetle) na na 30.0 27.5 na naWild yam Dioscoreae sp. na na na na 85.0 90.0

1 not applicable for this area

RESULTS

NTFPs important for revenue components of HRs

The most common NTFPs that were identified in the study villages as the most important sources of cash income in Cameroon, Congo and the CAR are presented in table 2. In Central Africa, HRs depend on NTFPs as a means to support general subsistence and to gain additional income for special needs. This safety net is often more important for the more vulnerable members of the community especially those situated at the bottom of the value chain with little access to alternative activities. According to HRs, NTFPs are used for commercial or non-commercial purposes. HRs identified ten common species or groups of species of NTFPs that are important sources of cash and non-cash income in the study area. Bushmeat, medicinal plants, bush mango (Irvingia gabonensis), okok (Gnetum africanum), raffia palm wine

(Raphia africana Otedoh) and honey appeared to be impor-tant income sources in Cameroon, Congo and the CAR. Mushrooms, caterpillars and Marantaceae leaves were reported only in the CAR and Congo, meanwhile cola nuts (Cola spp.), was reported in Cameroon and Congo only. Other NTFPs like fish, oil from moabi Baillonella toxisperma, djansang Ricinodendron heudelotii, rattan (Eremospatha sp. and Laccosperma sp.), lianas (Bauhinia liana), and wild veg-etables were only reported in Cameroon, yams (Dioscoreae sp.) and squash in the CAR, and insects in Congo.

Contribution of NTFPs to total household income

The NTFPs of both plant and animal origin, are an important second order revenue component for local people after agriculture. According to figure 2, NTFPs account for respec-tively 35% and 39% of non-cash income and, 21% and 14% of cash income in the IP and Bantu households in Cameroon.

Contribution of non-timber forest products to cash and non-cash income of remote forest communities in Central Africa 9

moabi seeds, medicinal plants and fish products. On the other hand, the IP get more than 75% of non-cash income from medicinal plants, lianas, fish products, raffia wine and mat. Altogether, HRs get less than 50% of cash income from cola nuts, lianas and rattan (for the Bantus), and from honey and medicinal plants (for the IP). None of the NTFPs accounts for less than 50% of the non-cash income generated by the Bantu and the IP in Cameroon. In the CAR, both the Bantu and the IP obtain more non-cash income than cash-income from NTFPs (as in Cameroon). The Bantu get more than 75% of both cash and non-cash income from Bushmeat only mean-while, the IP get between 75% and 100% of both cash and non-cash income from Bushmeat, mushrooms, caterpillar, okok and wild yam. The Bantu and the IP equally derive more than 75% of non-cash income from only mushrooms and medicinal plants, respectively. Altogether, only Bantu HRs obtain less than 50% of cash income from medicinal plants, fish resources and leaves of Marantaceae. In Congo, both the Bantu and IP obtain more cash income than non-cash-income from NTFPs (in contrary to Cameroon and CAR). Only the IP get more than 75% of both cash and non-cash income from okok alone. The Bantu derive more than 75% of cash income alone, from Bushmeat, okok and fish products. On the other hand, the IP get more than 75% of cash income alone, from Bushmeat. Altogether, HRs obtain less

In Congo, NTFPs account for 39% and 23% of non-cash income and, 22% and 16% of cash income in the IP and Bantu households, respectively. In the CAR, NTFPs contrib-utes to 39% and 37% of non-cash income and, 17% and 8% of cash income in IP and Bantu households, respectively. Cumulatively, the cash and non-cash income obtained from NTFPs accounts for 56% and 53% of the IP and Bantu house-holds’ income in Cameroon. It accounts for 61% and 39% of household income for the IP and Bantu in Congo. In the CAR, it contributes to 56% and 45% of the IP and Bantu house-holds’ income. Therefore, in Central Africa, more than 55% of the IP rely on NTFPs as a source of income against 45% of the Bantu people.

Percentage of households obtaining cash and non-cash income from each NTFP

The mean proportions of cash and non-cash income derived by households from each NTFPs per ethnic group in Cameroon, the CAR and Congo are presented in table 4. In Cameroon, both the Bantu and the IP derive more non-cash income than cash-income from NTFPs and between 75% and 100% of cash and non-cash income from Bushmeat, bush mangoes and djansang. The Bantu equally get more than 75% of non-cash income from Okok, Cola nuts, oil extracted from

FIGURE 2 Percentage contribution and (value) of NTFPs to the total household incomes per ethnic group in Cameroon, Congo and the CAR

10 D. Endamana et al.

318 US$ in cash income and 1131 US$ in non-cash income). In terms of cash income, the Bantu people gain about two, three and 31times the cash income derived by IP in CAR, Cameroon and Congo, respectively. The value of the non-cash income is about two to four times higher than the cash income in both ethnic groups in Cameroon and the CAR, but not in Congo.

Tables 6, 7 and 8 present the details of annual cash and non-cash incomes (in US$) that is generated by each NTFP per ethnic group in Cameroon, Congo and the CAR respectively.

In Cameroon, the total income from Bushmeat, bush man-goes, oils from moabi and rattan lies between 317 US$ to 460 US$ and account for the highest cash and non-cash income providing NTFPs among the Bantu HRs per year. The IP gain about 102 US$ to 178 US$ yearly from djansang, bush meat and bush mangoes, respectively (table 6). For each of the highest income providing NTFPs in both ethnic groups, non-cash income values are higher than cash income values.

In Congo, Bushmeat accounts for the high total income per year (1272 US$). Other NTFPs such as caterpillars, bush mangoes and insects like grub beetles bring about 241 US$ to 330 US$ among the Bantu households per year. In the IP

than 50% of cash income from cola nuts and medicinal plants (for the Bantu), from bush mango and raffia (for the IP), and both from insects (grubs and beetles). Both the Bantu and the IP get less than 50% of non-cash income from about 90% and 80% of all NTFPs in Congo, respectively.

Globally, among the Bantu, more than 50% of HRs obtain cash income from respectively seven, two and one NTFP(s) in Cameroon, Congo and CAR. On the other hand, more than 50% of IPs households obtain cash income from seven, two and nine NTFPs in Cameroon, Congo and CAR, respectively (table 4).

Cash and non-cash-income derived from NTFP in each ethnic group, per selected village country per year

In US dollars, the cash and non-cash incomes from NTFPs varied per ethnic group and country (table 5). In terms of gross total income, Bantu HRs in Cameroon derive about 2478 US$ (about 813 US$ in cash income and 1665 US$ in non-cash income) per year from NTFPs. In Congo, they derive about 1074 US$ per year from NTFPs (about 717 US$ in cash income and 357 in non-cash income). In the CAR, the Bantu HRs gain about 1449 US$ per year from NTFPs (about

TABLE 6 Average annual household cash and non-cash incomes (in US $) for each NTFP per ethnic group in households of Cameroon

Ethnic group

Non Timber Forest product

Scientific names (where applicable)

Cash income

Non-cash income

Total Income

Bantu

Bush mangoes Irvingia gabonensis 139 289 423Bush meat 154 316 460Cola Cola acuminata 61 129 190Djangsang Ricinodendron heudelotii 91 185 275Rattan Calameae 102 216 317Fish from local rivers and others 64 133 197Lianas Bauhinia liana 73 151 224Okok Gnetum africanum 55 117 172Medicinal Plants 68 142 209Moabi’s oil Baillonella toxisperma 102 223 328

Indigenous people

Bush Mangoes Irvingia gabonensis 70 108 178Bush meat 48 78 127Djangsang Ricinodendron heudelotii 39 63 102Wild vegetables 32 52 84Lianas Bauhinia liana 22 36 58Raffia (wine and mat) Raphia 21 34 55Honey 24 41 65Fish from local rivers and others 17 27 44Medicinal Plants 21 31 52

TABLE 5 Cash and non-cash income values (in US $) of households for each ethnic group per country

CountriesCash income Non-cash income Total income

Bantu IP Bantu IP Bantu IP

Cameroon 813 314 1 665 498 2 478 812Congo 717 23 357 42 1 074 65CAR 318 211 1 131 517 1 449 728

Contribution of non-timber forest products to cash and non-cash income of remote forest communities in Central Africa 11

TABLE 8 Average annual household cash and non-cash incomes (in US $) for each NTFP per ethnic group in households of the CAR

Ethnic group

Non Timber Forest product

Scientific names (where applicable)

Cash income

Non-cash income

Total Income

Bantu

Bush meat 77 282 360Medicinal Plants 47 166 213Okok Gnetum africanum 41 128 168Caterpillars 28 79 106Mushroom Amanita muscaria 39 153 192Fruit payo Irvingia grandifolia 40 160 200Wild yam Dioscoreae sp. 33 124 157Honey 7 25 32Leaves of marantacea 11 30 41

Indigenous people

Bush meat 25 60 85Okok Gnetum africanum 28 68 96Mushroom 23 56 80Caterpillars 22 41 64Payo fruit Irvingia grandifolia 24 58 82Wild squash 31 89 120Medicinal Plants 19 46 64Leaves of marantaceae 18 43 61Wild yam Dioscoreae sp. 14 27 41Honey 16 29 44

TABLE 7 Average annual household cash and non-cash incomes (in US $) for each NTFP per ethnic group in households of Congo

Ethnic group

Non Timber Forest product

Scientific names (where applicable)

Cash income

Non-cash income

Total Income

Bantu

Bush meat 865 406 1272Caterpillars 229 100 330Raffia (wine and mat) Raphia 45 20 65Leaves of marantacea 70 17 87Medicinal Plants 55 29 84Okok Gnetum africanum 141 54 195Insects (grubs beetle etc.) 186 55 241Bush mangoes Irvingia gabonensis 210 67 276Lianas Bauhinia liana 45 20 64Cola nut Cola acuminata 30 15 45Mushroom Amanita muscaria 142 46 187

Indigenous people

Honey 111 64 175Bush meat 141 100 241Leaves of marantacea 148 45 193Mushroom Amanita muscaria 184 45 193Insects (grubs beetle etc.) 225 68 293Caterpillars 219 92 311Okok Gnetum africanum 252 234 486Raffia (wine and mat) Raphia 16 41 57Lianas Bauhinia liana 46 84 130Payo fruit Irvingia grandifolia 94 57 151

12 D. Endamana et al.

households, NTFPs like okok, caterpillars, insects and Bush-meat generate total incomes between 241 US$ to 486 US$ per year. For each of the highest income generating NTFPs in both ethnic groups, cash income values are higher than non-cash income values.

In the CAR, Bushmeat (360 US$), medicinal plants (213 US$), payo fruits (200 US$) and mushroom (192 US$) accounts for the highest cash and non-cash incomes among the Bantu HRs per year. In the IP households, wild squash (120 US$), okok (96 US$), Bushmeat (85 US$) and payo fruits (82 US$) brings the highest incomes per year. For each of the highest income generating NTFPs in both ethnic groups, non-cash income values are higher than cash income values.

Irrespective of the ethnic group and country, Bushmeat is an important source of cash and non-cash income. It generates more income to the Bantu than the IP.

DISCUSSION

In Central Africa, it has been widely documented that NTFPs are important for local communities (FAO 1995, Ingram and Schure 2010). Their contributions to household revenue has always been questionable because of the methods used for evaluating the income generated from their sales. The FPTK is a rapid appraisal method that facilitates data collection and analysis for the evaluation of the contribution of NTFPs to household income. However, it is not very different from other social appraisal methods in terms of variability of infor-mation from households, but has an additional advantage that it provides information on the variation of the dependency of communities on NTFPs which is important for evaluating efforts of the civil society, NGO’s and governments in the pilot area. It is assumed that, HRs declare income values for the previous year that best match the income situation of the household and the part contributed by NTFPs. In the study area, NTFPs were used for commercial and non-commercial purposes. Products like Bushmeat, bush mango, djansang, oil from seeds of moabi, rattan, medicinal plants, okok, insects and insect larvae are commonly used among the Bantu and the IP (Clark and Sunderland 2004, Ingram et al. 2010, Wilkie 1999). The NTFPs that were identified by HRs to be important sources of income accounted for more than 55% of cash income for the IP in Cameroon, Congo and the CAR against 45% for the Bantu peoples. The percentage contribu-tion of all NTFPs to cash and non-cash income of the HRs was evaluated in order to understand the priority NTFPs, the level of dependency of the studied communities and the portions of NTFPs that are rarely considered and used for non-commercial purposes (Angelsen and Wunder 2003, Campbell and Luckert 2002). Given that each NTFP contrib-utes specifically to the total income of HRs, Bushmeat accounted for the highest proportion of NTFPs that provides cash income among the Bantu in Cameroon, Congo and the CAR. It also contributed significantly to the cash income source among the IP but, NTFPs like okok, bush mango, djansang and wild squash appeared to be more important. In

monetary terms, the non-cash income obtained from each of the NTFPs is higher than the cash income in Cameroon (as in Betti 2004), the CAR but not in Congo. In Cameroon and the CAR, there is a poorly developed market network (Makon et al. 2005, Ndoye et al. 1997, Nguimbi 2006) and NTFPs harvested from the forest are primarily used for home con-sumption and to satisfy daily needs (Ingram and Bongers 2009, Loubelo 2012, PROTA 2008). In addition, there are no mechanisms in place to ensure product quality, standardise pricing, adequate transport and processing of these products and, the effective computability of income generated by local people. Similarly, in the South-West and South regions of Cameroon, NTFPs accounts for only 25–50% and 20% of cash income for local people, respectively (Mallesson 1993, Ros-Tonen and Wiersum 2003, 2005) and 29–39% of total income in both regions (Levang et al. 2015). Therefore, the more remote the area the higher the contribution of NTFPs to non-cash income. In a study of household use of natural resources in the Kat River Valley of South Africa Shackleton and Shackleton 2006), NTFPs contributed to about 20% of the total household income and it constituted the highest proportion of incomes for the poorest households per capita.

In this study, NTFPs provide higher non-cash income to the Bantu and the IP in Cameroon and the CAR. Meanwhile in Congo, NTFPs provide higher cash incomes. However, in US dollars, the Bantu people obtain relatively higher total incomes from NTFPs than the IP. In the area, the Bantu appear to have more control over NTFP market mechanisms than the IP. The NTFPs are mostly harvested by the IP and sold at lower prices at the beginning of the value chain. The Bantu’s are situated higher in the market network and most of them buy products from the IP for resale at higher prices. In addition, it was observed that the IP do not receive the maximum income from NFTPs because of their low socio-economic status in the area. It has already been reported in Africa that the highest proportion of people around forest areas live on less than 1.5 US$ a day (Anderson et al. 2006, OMD 2013). However, in the study area, the total annual income derived from NTFPs attests that the local Bantu and IP live far above this level. Bushmeat alone derives 460 US$, 1272 US$ and 360 US$ per year for the Bantu people in Cameroon, Congo and the CAR, respectively. If we suggest that the number of members in each of the studied households per village varies between four and six, therefore Bushmeat alone respectively provides 0.26 US$, 0.72 US$ and 0.2 US$ per day/capita in Cameroon, Congo and the CAR. According to the literature, forest resources contribute to about 1.45 US$/day/capita in Cameroon, 1.81 US$ in Congo and 1.06 US$ in the CAR (Endamana et al. 2015a). Hence, the percent-age contribution of Bushmeat to the total household revenue lies between 18% and 40%. This implies that the combined effect of income generated from all NTFPs could be poten-tially higher than previously believed and could be managed (taking into consideration, the limited access to social and physical livelihood facilities and other related issues) to satisfy the livelihood needs of local people in the studied villages of the three Central African countries.

Contribution of non-timber forest products to cash and non-cash income of remote forest communities in Central Africa 13

To date, these countries have developed long-term development emergency plans that can only succeed if all economic sectors including the forestry sector are considered. The macroeconomic contribution of forest exploitation to Gross Domestic Product, employment and development can be found in the literature. However, within the framework of sustainable development mechanisms like REDD+, success-ful benefit sharing at the micro-economic level requires adequate assessment of the cash and non-cash income values generated by NTFPs on the one hand and other products on the other hand. Yet, these values are absent in national statis-tics and in the literature. The contribution of NTFPs to the total income (including cash and non-cash) could influence considerably political decisions, long-term development mechanisms like REDD+, and the implementation of Sustain-able Development Goals (Endamana et al. 2015b). A key example is that, REDD+ projects will promote the develop-ment of the value chain for NTFPs that are of high economic priority for local communities, sustainable harvesting tech-niques and ensuring that the local communities from sustain-able harvest of priority NTFPs derive maximum benefits. However, the situation of bushmeat may suggest that poach-ing is on the rise in the area. It will be imperative that priority investments within the context of REDD+ should test and implement sustainable alternatives that could compensate for the income derived from bushmeat by the communities in the study area. This will equally be important for all NTFPs that are overharvested or even under threat.

A participatory tool like the FPTK is appropriate for iden-tifying sustainable livelihood options in an on-going REDD+ pilot activity in villages within Central Africa. Angu Angu and Endamana (2015) described national policy efforts to use REDD+ as a lever for sustainable development. The distinct contribution of each NTFP to cash and non-cash income among ethnic groups and countries can provide guidance on investment opportunities for the promotion of NTFPs in these areas.

CONCLUSION

The study confirms that NTFPs contribute significantly to cash and non-cash income of households in the TNS and TRIDOM forest landscape, Central Africa. It is a common and important source of income for the Bantu and the IP living in these areas. The NTFPs account for about 55% and 45% of total cash and non-cash income for HRs who reported income sources from these latter. Total income values gener-ated from the uses of each NTFP is now available for the communities living in these areas. Long-term development mechanisms like REDD+ can integrate these values for each community and country within its financial structure in order to assure adequate resource allocation and benefit sharing in its project sites. It is imperative that poverty alleviation strate-gies, development of alternative activities for local communi-ties and forest management policies assess adequately the income obtained from NTFPs and consider the important role

of NTFPs in improving the livelihoods of local people (as in Mulenga et al. 2011).

ACKNOWLEDGMENTS

This study was conducted thanks to financial support from the Congo Basin Forest Fund. We express our gratitude to local chiefs of the studied villages for hospitality and collaboration. Special thanks to Gervais Ondoua Ondoua, Parfait Bakabana, Mve Mve Joseph for assistance in data collection and processing, to Gretchen Walters, Charlotte Eyong Ako and Mboringong Fideline for editing and revising the manuscript.

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