Transparency and governance in non-wood forest product commodity chains, an example from : a need to include NWFP in the FLEGT mechanism.

Julius Chupezi TIEGUHONG1, Ousseynou NDOYE, Sophie GROUWELS, Armand ASSENG ZE, Juliane MASUCH, Ignace Fokou SAKAM and William MALA

1Email: [email protected] & [email protected]; Tel: +237 75622222 Fax: +237 22204811

At the World Forestry Congresses (WFC) in 2003 and 2009, good governance and efficient institutions were reiterated as necessary indicators to consider when measuring positive outcomes resulting from long-term thinking in the forest discourse at all levels. It was further stressed that without good governance and effective institutions, the scope of sustainable forest management will remain limited. This discourse dwells on concepts such as democratisation, accountability, empowerment, equity, corruption, illegality, governance and transparency. Examined in this paper are the practical applications of four of the latter interrelated concepts as they relate to the production, transportation and trade of non-wood forest products, and looking specifically at a case study on Gnetum spp, a leafy vegetable in Cameroon. Data was collected from traders on all of the financial transactions involved in accessing, transporting and selling Gnetum spp from the zone of production to the point of export over a period of one year. A total of 18368 transactions were documented during 302 journeys. 81.6% of the transactions were illegal but covered 33.5% of the total costs of all transactions (341 250 960 CFAF equivalent to US$ 780558) over the study period. There were a total of 122 locations and major reasons for making a financial transaction with only 10.7% that covered legal transactions while 65.6% covered completely illegal transactions and 23.7% both legal and illegal transactions. Further analysis revealed the major locations and kind of agents playing the leadership roles in illegal transactions in terms of frequency and characteristics of the proportions of total amounts of money retained. A major recommendation from the paper is related to the needs of sensitising government agents on their responsibilities vis-a-vis NWFP value chains and to link the NWFP sector in the Forest Law Enforcement Governance and Trade (FLEGT) process.

Key Words: Illegality, Government agents, Non-wood forest products, FLEGT

1 Introduction

According to the findings of the Commission for Africa (2005), all the difficulties caused by the interactions in Africa’s history over the past 40 years may be attributed to weaknesses of governance and the absence of an effective state. At the World Forestry Congresses (WFC) in 2003 and 2009, good governance and efficient institutions were reiterated as necessary indicators to consider when measuring positive outcomes resulting from long-term thinking in the forest discourse at all levels. It was further stressed that without good governance and effective institutions, the scope of sustainable forest management will remain limited (WFC, 2009). This discourse dwells on concepts such as democratisation, accountability, empowerment, equity, corruption, illegality, governance and transparency. Examined in this paper are the practical applications of four of the latter interrelated concepts as they relate to the production, transportation and trade of non-wood forest products (NWFP), looking specifically at a case study on Gnetum spp (Gnetum africanum and Gnetum buchholzianum), a leafy vegetable in Cameroon. This paper makes use of the definition of good governance as it was established by the Commission for Africa (2005). This definition states good governance as the ability of government and public services to create the right economic, social and legal framework that will encourage economic growth and allow in it the participation of poor people. Bad governance is exactly the opposite of good governance. In economics, growth is generally driven by the private sector, requiring governments to provide a favourable climate in which ordinary people (small farmers or managers of larger firms) can get on with their daily tasks untroubled and feel that it is worthwhile to invest in their own future. That climate is what is consistently lacking across Africa (Commission for Africa, 2005), including in Cameroon. The authors of this papers have attempted to answer a major research question: how transparent are financial transactions in the non- wood forest product commodity chain in Cameroon? This question is pertinent within the framework of the Central African Forestry Commission (COMIFAC)’s vision of improving the legal and institutional frameworks governing the NWFP sector in Central Africa. In addition, forest governance is now a concept that has become generally accepted in discussions about forests. In fact, governance and institutions are viewed as the decisive factors for success and substantial progress in such matters as sustainable production chains, combating illegality, modernising the forestry sector, and responsible business activity (WFC, 2009). In the same vein, one of the emerging economic mechanisms that promises to promote sustainable forest management and improve governance in the forest sector is the Forest Law Enforcement, Governance and Trade (FLEGT) process (Assembe-Mvondo, 2009; 2010; Eba’a Atyi et al., 2008). Hitherto, timber products were targeted with complete neglect of NWFP when talking about compliance to national forestry laws. Today, this is viewed as an oversight in light of the economic importance of NWFP at local, regional, and international levels (Tieguhong et al., 2010, 2009a&b; Tiveau, 2008; Warner, 2007Tieguhong and Ndoye, 2006; Ndoye and Tieguhong, 2004). This paper gives some insights on the impacts of law enforcement officers’ control measures in the field in relation to the NWFP value chains in Cameroon, reflecting

2 elements of transparency, corruption, illegality and governance, as enshrined in the FLEGT process.

Methodology Data was collected from traders on 18368 financial transactions involved in accessing, transporting and selling Gnetum spp. (Gnetum africanum and Gnetum buchholzianum) from the zone of production to the point of export over a period of one year. All actors and corresponding transactions and values were recorded according to locations and dates. Data was collected along the two main routes from the source of production at Sa’a to the destination at Idenau. The first route (Sa’a via Yaounde to Idenau) covers a distance of 517 km while the second (Sa’a via Bangante to Idenau) covers 683 km. A literature review was conducted on past studies, including on the concepts of corruption and transparency in the natural resource management sector. Data gathered was entered into Microsoft Excel and analysed using SPSS software. Estimates were made on the cost of production and income of producers based on number of trips made per week/per month and the number of months of activity per year

Results Controls and financial transactions

A consitent follow-up with traders from the production zone to the exit point over a period of one year showed that there were 18368 financial transactions effected over a period of one year, 81.6% of which were illegal (forceful payments without the delivery of receipts to law enforcement officers) and only 18.4% legal (payments with the delivery of receipts and in conformity with the law). In terms of total amount of money spent for all transactions made during the period, 33.5% was spent on illegal transactions (341 250 960 CFAF, equivalent to US$ 758335.5, exchange rate US$1=450 FCFA as of January 2010) (Table 1).

3 Table 1: Distribution of number of transactions and amount spent, by route taken and legality status Legal status Route Variables Illegal Legal Total Sa’a-Yaounde -Idenau = 1 Total number of transactions 9198 1799 10997 % of number of transactions 83,6 16,4 100,0 Total expenses (FCFA) 68346500 131250860 199597360 % of expenses 34,2 65,8 100,0 Sa’a-Bangante -Idenau = 2 Total number of transactions 5795 1576 7371 % of number of transactions 78,6 21,4 100,0 Total expenses (FCFA) 45873100 95780500 141653600 % of expenses 32,4 67,6 100,0 Grand total number of transactions 14993 3375 18368 % of grand number of transactions 81,6 18,4 100,0 Grand total expenses (FCFA) 114219600 227031360 341250960 % of grand expenses 33,5 66,5 100,0

Among the 122 locations/reasons (locations and reasons are not interchangeable concepts but are lumped together because some reasons for making a financial transaction was not tight to a specific location such as transportation, communication, money transfer, fuel and feeding) for making a financial transaction, only 10.6% of them were legal, 65.6% were illegal and 23.8% had both legal and illegal operations (Appendix 1). For the completely illegal locations, 23 of them including Ahala, , , Bikoko, Bonabari, Buea, Limbe, , , Mboumnyebel, Monatele, , Mutengene, Nkometou, , Nomayos, Nyassa, , Olembe, Ombe, Sombo, Tiko and Yaounde, covered more than half of all illegal expenses. Both legal and illegal locations such as Idenau, Sa’a and Bota respectively had 45.1%, 19.5% and 0.2% of financial transactions as illegal (Appendix 2). Major legal expenses included transactions such as transportation (49.5%), hiring of waybills (14%), payment of custom duties (8.9%), loaders (10.5%) and offloaders (6.1%), as well as expenses related to accommodation/feeding (2.3%). The remaining 8.7% was spent on communication, payment to councils, toll gate fees, other minor taxes and miscellaneous expenses (Table 2).

4

Table 2: Characteristics of amount spent per reason/specification and distribution by legal status

Total Mean Minimum Maximum Mean Standard Total Illegal Legal % Reasons/Agents N N expense expense expense Deviation expenses expenses expenses illegal Accomodation 19 0,1 5000 30000 17789 6024 338000 0 338000 0,0 Armée de Terrre 2 0,0 1000 2000 1500 707 3000 3000 0 100,0 Autres 262 0,9 500 200000 19460 28436 5098650 1218500 3880150 23,9 Communication 163 0,5 2000 75000 7847 7825 1279000 0 1279000 0,0 Council 321 1,1 1000 100000 2802 7488 899500 190000 709500 21,1 Douanes 315 1,0 5000 165000 65676 26857 20688000 388000 20300000 1,9 Election barriere 9 0,0 5000 30000 11333 8789 102000 102000 0 100,0 Entrance 241 0,8 3000 80000 19512 7784 4702500 0 4702500 0,0 Escort 1 0,0 200000 200000 200000 #DIV/0! 200000 0 200000 0,0 Feeding 405 1,3 200 150000 11971 10465 4848100 0 4848100 0,0 Forestiers 5022 16,6 1000 200000 9394 10176 47176100 47176100 0 100,0 Fuel 22 0,1 5000 60000 21909 19171 482000 0 482000 0,0 Gendarmerie 3699 12,2 1000 90000 5612 5142 20757000 20757000 0 100,0 Loaders 307 1,0 3000 140000 77427 22682 23770200 0 23770200 0,0 Mixte 27 0,1 2000 20000 6259 4809 169000 169000 0 100,0 Money transfert 38 0,1 1000 160000 15500 26606 589000 0 589000 0,0 Motivation 212 0,7 1000 100000 31377 22693 6652000 0 6652000 0,0 Offloaders 286 0,9 5000 350000 48409 20758 13845000 0 13845000 0,0 Peage 45 0,1 500 7000 4956 1718 223000 0 223000 0,0 Pesage 43 0,1 2000 20000 6837 3422 294000 0 294000 0,0 Phytosanitary 58 0,2 2000 28000 10190 3976 591000 0 591000 0,0 Police 3595 11,9 500 40000 5497 3765 19762500 19762500 0 100,0 Prévention Routière 750 2,5 500 115000 4312 4746 3234000 3234000 0 100,0 PSRF (MINFOF,MINFI) 74 0,2 2000 80000 22500 11609 1665000 1665000 0 100,0 Road blockage 1 0,0 4000 4000 4000 #DIV/0! 4000 4000 0 100,0 Routiers 1718 5,7 500 30000 11380 6503 19550500 19550500 0 100,0 Specification 14 0,0 4000 55000 17071 15593 239000 0 239000 0,0 Taxes 3 0,0 10000 23500 17833 7006 53500 0 53500 0,0 Torches 15 0,0 2000 8000 4133 1598 62000 0 62000 0,0 Tranportation 415 1,4 2000 500000 270543 176524 112275210 0 112275210 0,0 Waybill 286 0,9 11200 954000 110833 60669 31698200 0 31698200 0,0 Total 18368 60,8 200 954000 18579 51431 341250960 114219600 227031360 33,5

Actors and illegal financial transactions A critical analysis of the illegal actors and their contribution to the illegal share showed that a total of 13 groups of actors were involved, with forest agents, police, gerndarmes and routiers playing the most prominent roles. For a total amount of 114219600 CFAF (US$ 253821) illegally collected per annum from traders transporting Gnetum spp from Sa’a to Idenau, 93.89% is extorted by four groups of actors (forestry agents, gendarmes, police and routiers), with forestry agents getting the lion’s share (41.3% - See Figure 1).

5 Forestry agents 41,30 s

Gendarmerie 18,17

Police 17,30 Agents/reason Routiers* 17,12

Road safety officers 2,83

PSRF(MINFOF,MINFI) 1,46

Others 1,07

Customs 0,34

Council 0,17

Mixed control** 0,15

Election barrier 0,09

Road blockage 0,00

Ground Army 0,00

0 5 10 15 20 25 30 35 40 45 Percentage (%)

Figure 1: Agents/reasons and the proportion of money extorted from traders over a period of one year

The amount collected per interest group is a function of the number of stops along the way and the amount collected per stop. For instance, leaving Sa’a to Idenau, traders on average encounter forestry agents, gendarmes, police, routiers, and road safty officers 17, 12, 12, 6 and 3 times respectively. In terms of financial extortions per stop, routiers,

6 forestry agents, gendarmes, police and road safety officers receive on average 11380 CFAF (N=1718; SD=6503), 9394 CFAF (N=5022; SD=10176), 5612 CFAF (N=3699; SD=5142), 5497 CFAF (N=3595; SD=3765) and 4312 CFAF (N=750; SD=4746) respectively. The remaining actors receive modest amounts and make less frequent appearances along the way.

Impacts of frequent illegal check points

The mean number of bundles of Gnetum spp per trip that decay in transit was estimated at 207 (SD=164) with a total of 13234 bundles registered as shortage over six months. There were also a number of rejected bundles of Gnetum spp by buyers at Idenau due to deformation of the leaves and partial decay and drying up of leaves. Results show that up to 995 bundles were rejected per trip with a mean of 428 bundles per trip (SD= 278 bundles) and total of 36783 bundles (37 tons) rejected over a period of six months. This translates into financial losses (Table 3).

Table 3: Characteristics of costs, revenue and number of bundles of Gnetum counted and sold between June and December 2008.

Std.

Variables N Minimum Maximum Sum Mean Deviation

Total expenses (FCFA) 86 352000 2261000 111932960 1301546 250229

Total counted bundles 86 1160 14655 692024 8047 2613

Rejected bundles 86 0 995 36783 428 278

Good bundles 86 1100 13697 651993 7581 2445

Selling price of good bundles (FCFA) 86 563 1200 70956 825 161

Selling price of rejected bundles (FCFA) 86 282 600 35478 413 80

Shortage of bundles 64 9 1180 13234 207 164

Shortage value lower end (FCFA) 65 0 295000 3308500 50900 41238

Shortage value upper end (FCFA) 65 0 354000 3970200 61080 49486

7 Impacts of long administrative procedures on transaction costs

Frequently, long administrative procedures keep small and medium scale forest enterprises (SMFE) from accessing legal permits to do business, only making it possible for influential people with social ties in the capital city to get most of the annual quotas. The latter group of people are dubbed as passive quota holders that render the quota allocation system non-transparent. They are few in number but always get a higher share of quotas, which they resell at higher prices in the form of waybills (or ‘lettre de voiture’) to SMFE. The consequences are losses of revenues by the government and the SMFE at the profit of a few individuals, also termed as rent seekers. In Cameroon, the government sells quotas at 10 CFAF per kg dubbed as regeneration taxes (hardly used by government to that end as it is paid into the central treasury and hardly reallocate for regeneration), regardless of the varying regeneration needs of the multitude of species. Waybills sold by passive quota holders/rent seekers were very expensive between 2000 and 2002 compared to the price of government quotas, leading to a very high private rent or profit earned by individuals (See Figure 2). This influenced many SMFE in their decision to operate illegally by transporting their NWFP without permits. Given that the validity of quotas cannot be extended over one year, a stock of waybills in the hands on passive holders seeking windfall gains cannot materialise, and due to the fear of the expiration of the waybills, most of them are forced to resell at lower prices. It could be stated that the current permit system has some shortcomings including the flat rate generalised for all NWFP, the centralised nature of allocation and the vulnerability of the allocation system to the greed of influencial personalities. These render tax recovery difficult. According to Betti (2007), the government of Cameroon has difficulties collecting the regeneration taxes of 10 Francs CFA/kg recovery rate oscillating around 60%. Moreover, permit system does not guarantee sustainable exploitation of the resource because the length of validity of the exploitation permit is one year, which encourages the cut and run behaviours (get as much as possible this year because next year I am not sure to be there). These weakness in the permit system encourgage SMFE hired waybills to exploit NWFP in whatever way possible to reach the limit of their quotas, regardless of ethics towards sustainability.

8 Waybills, rents seekers and goverment taxes

) 80,0 Price of way bill (CFAF/Kg) 70,0 Price of Government 60,0 Quota (CFAF/Kg 50,0 Private rent 40,0 (CFAF/Kg) 30,0

Amount paid (CFAF/kg 20,0 10,0 0,0 2000 2001 2002 2003 2004 2005 2006 Years

Figure 2. Yearly variation in the prices of waybills (“Lettre de voiture”), rents and taxes

Discussions

Past studies have shown that informal taxes (corruption costs) could represent 20% of revenues for traders (Ndoye and Awono, 2007; 2009; Awono et al., 2002). This study goes even further, showing that the total cost of doing business may be increased by as much as 33.5% due to illegal financial transactions. These corruption costs are transferred to collectors by means of lower purchase prices (paid by traders) and to consumers in terms of higher sales prices (charged by traders). A cross-table analysis between the locations and the reasons for making a financial transaction showed that most locations could be eliminated from controlling the transportation of NWFP such as Gnetum spp from Sa’a to Idenau, thus conspicuously reducing the negative implications of corrupt practices. This is pertinent given that there are hardly any real measures in place for controlling things like the quality of vehicles and the likelihood of having accidents, for example, because over 80% are for extorting illegal taxes from traders.

With over sixty transactions occurring on the way to Idenau, more time is spent on the road, which in turn means more money must be spent on lodging, food, communication and other incidentals. As pinpointed by Freund and Rocha (2009), longer time in transit reduces the speed of trade and exports, as well as translating into many indirect implications on the product being transported in terms of losses and reduction in quality due to, for example, the perishable nature of products like Gnetum spp, which can decay or whose leaves can dry up during transport. Decays and the rejection of certain bundles of Gnetum spp. result in an overall reduction of profit margins for traders, at times

9 losses from business trips. It is important to note that decayed bundles are completely thrown away while rejected bundles (reduced quality) are sold at half the price as good bundles. Another important implication of losses in harvested bundles is that there is a resulting need to increase the volume harvested to meet demand, which may lead to over-exploitation of the resource and over-loading of vehicles, creating yet further problems of security in transporting the product. At the national level, government revenue is never maximized due to tax evasion, giving the sector a lower economic impact in the eyes of policy makers. Weaknesses in the permit acquisition process as well as the high level of informal taxes (corruption costs) associated with several check- points during transit force most traders to continue illegal practices.

It has been noted that the administrative procedures for obtaining permits and gaining access to the NWFP trade chain are cumbersome and lead to high transaction costs in terms of time, financial resources and energy, as well as potentially unsustainable practices through illegal exploitation (FAO, 2008; Betti, 2007). In Cameroon, the number of permits delivered by the forestry administration is low compared to the number of small and medium scale forest enterprises (SMFE) operating in the NWFP sector. This forces many SMFE to operate illegally (Ndoye and Awono, 2009). For instance, Betti (2007) observed a downward trend in the number of exploitation permits delivered by the Ministry of forestry and wildlife of Cameroon with 43 permit holders in 2004, 36 in 2005, 44 in 2006 and only 19 in 2007. This could be associated with the quota allocation system, the systematic attribution of waybills, the duration of validity of permits and the social ties and power influence of rent seekers. The most important NWFP are regulated by the forestry administration through a system of quotas that are set every year by a committee. In some cases, social ties to members of the quota allocation committee and the overall influence of higher rank officials play critical roles in the allocation process. The consequence is that at the end of the process, more quotas are allocated to individuals that do not actually actively participate in the NWFP value chain beyond the stage of quota allocation.

Policy orientations and conclusion Small-scale forest enterprises based on NWFP value chains have a variety of options for reducing poverty and combating food insecurity in Central Africa. However, their performance is negatively affected by irrelevant or non-adapted legal and institutional policies that do not favour their growth and effective management of forest resources as well as business development. Our findings show that several checkpoints in transit result in trade delays, high transaction costs and longer transit times for NWFP from the zone of production to the zone of exports. This reduces the quality of products, actual volume of product exported and profit margins for traders, which in turn has affected the overall livelihood impacts at national and international levels. This conforms with the findings of Freund and Rocha (2009) that Africa’s exporters face many delays. Policies need to be devised to identify and remove the negative factors that delay trade to make sure that the objective of COMIFAC of ensuring that the NWFP sector significantly contributes to poverty reduction in rural areas by increasing revenues while ensuring the sustainable management of the resource base may be realised. The

10 improvement of inland transit of NWFP would have major impacts on trade stimulation in the sector by increasing profits of traders and reducing resource waste. Further study may be conducted to observe the impacts of other factors, such as quality of roads and vehicles, likelihood of accidents, theft, total travel times and waiting time at borders on the flow of NWFP from production zones to export ports. The FLEGT process can be very useful for ensuring that appropriate information is provided to guide policies towards legal transctions in NWFP within and across borders in Central Africa. Other important ways forward could be to revise the forestry law to better take into consideration the NWFP sector, render access to permits more favourable to traders by dis-allowing access for rent-seekers, reduce the number of road checks on NWFPs, sensitise government agents on the role of NWFP in reducing poverty and on the need for transparency and clearly set stringent and deterrant measures for corrupt agents with clear punishments for those not abiding by the rules.

REFERENCES

Arnold J.E.M. and Ruiz-Perez M. 1998. The role of non-timber forest products in conservation and development. In: E. Wollenberg and A. Ingles (Eds.). Income from the Forest: Methods for the development and conservation of forest products for local communities. CIFOR and IUCN. Pp. 17-42. Assembe-Mvondo, S. 2010. EU Regulations on Tropical Timber and their Potential Impacts in the Congo Basin Region. Paper Presented for the IUFRO 12th International Symposium on Legal Aspects of European Forests Sustainable Development, Nicosia, Cyprus, 31May- 2 June 2010. Assembe-Mvondo, S. 2009. Sustainable Forest Management Practice in Central African States and Customary Law. International Journal of Sustainable Development & World Ecology, Vol. 16, No 4: 217-227. Awono A., Ngono D. L., Ndoye O., Tieguhong J.C, Eyebe A. and Mahop M. T. 2002. Etude Sur La Commercialisation De Quatre Produits Forestiers Non-Ligneux Dans La Zone Forestière Du Cameroun : Gnetum Spp., Ricinodendron Heudelotii, Irvingia Spp., PRUNUS AFRICANA. Fao. Yaounde, FAO: 96. Commission for Africa. 2005. Our Common Interest. Report of the Commission for Africa. March. 462 pp. Eba’a-Atyi, R., Devers, D., De Wasseige, C & Maisels, F. 2008. State of the Forests of Central Africa: Regional Synthesis. In, C. De Wasseige, D. Devers, P. De Marcken, R. Eba’a Atyi, Nasi, R & Mayaux, P (eds.), The Forests of Congo Basin : State of the Forests 2008. (CBFP: Luxembourg), 17- 44. Freund C. and Rocha N. 2009. What is holding back African exports? www.voxeu.org/index.php?q=node/4359 Accessed 27/08/2010

11 Ndoye, O. and A. Awono. 2009. Regulatory policies and Gnetum spp. trade in Cameroon. Wild Product Governance: Finding Policies that Work for Non-Timber Forest Products. S. A. Laird, R. Mclain and R. P. Wynberg. London, EarthScan: 352 Ndoye, O. and Awono, A. 2007. Regulatory policies and Gnetum spp. trade in Cameroon‟, Forest Livelihood Briefs, no 6, Center for International Forestry Research, April Ndoye O. and Tieguhong J.C. 2004. Forest resources and rural livelihoods: The conflict between timber and Non-timber forest products in the Congo Basin. Scand. J. For. Res. 19 (Suppl. 4): 36-44. Tieguhong J.C., Ndoye O., Grouwels S., Useni K.M. and Asseng Ze A. 2010. Small scale forestry and non wood forest products enterprise development for poverty alleviation in Central Africa. Proceedings IUFRO Conferecne, Small scale forestry and extension, Ljubljana, Slovenia. 06-12 June. PP. 87-101. Tieguhong J.C., Ndoye O., Vantomme P., Grouwels S., Zwolinski J. and Masuch J. 2009a. Coping with crisis in Central Africa: enhanced role for non-wood forest products. Unasylva 233(60): 49-54 Tieguhong J.C., Ndoye O., Tchatat M. and Chikamai B. 2009b. Processing and Marketing of Non-Wood Forest Products for Poverty Alleviation in Africa. Discovery and Innovation 21(SFM Special Edition No.1): 60-65. Tieguhong J.C. and Ndoye O. 2006. Transforming subsistence products to propellers of sustainable rural development: Non-timber forest products (NTFPs) production and trade in Cameroon. Africa-Escaping the Primary Commodities Dilemma. African Development Perspective Yearbook Vol. 11. Unit 1. VERLAG Berlin. Pp. 107-137. ISBN 3-8258-7842-2 Tiveau D. 2008. Harvesting forests to reduce poverty. CIFOR Annual Report 2008: Thinking Beyond the Canopy. CIFOR, Bogor. PP 18-21. Warner K. 2007. Foresterie et moyens d’existence durables. Unasylva 226/227 (58): 80- 87. WFC 2009. Forest Development: A Vital Balance Findings and Strategic Actions. Conclusions. III World Forestry Congress 2009 Buenos Aires, Argentina. 4pp.

12 Appendix 1: Distribution of transactions and amount spent by location and legal status Legal status of transactions % % spent Illegal expenses Legal expenses per Location Illegal Legal Total (FCFA) (FCFA) Total (FCFA) illegal location Accomodation 19 19 338000 338000 0,0 0,10 Acropole 5 5 25000 25000 100,0 0,01 Ahala 311 311 1530000 1530000 100,0 0,45 Akwa 2 2 4000 4000 100,0 0,00 Autres 475 184 659 4637500 3870150 8507650 54,5 2,49 Bafang 380 380 1085000 1085000 100,0 0,32 Bafia 381 381 3695500 3695500 100,0 1,08 60 60 712000 712000 100,0 0,21 Baganté 241 241 579000 579000 100,0 0,17 Bana 189 1 190 287500 20000 307500 93,5 0,09 Bangou 247 247 761000 761000 100,0 0,22 Bantoum 147 147 308000 308000 100,0 0,09 Barrière 2 2 10000 10000 100,0 0,00 Bastos 11 11 42000 42000 100,0 0,01 Batoke 1 1 2000 2000 100,0 0,00 Bayomen 87 87 300000 300000 100,0 0,09 Bikoko 480 480 5393000 5393000 100,0 1,58 Bonaberi 406 406 1986500 1986500 100,0 0,58 Bonakoh 42 42 707000 707000 100,0 0,21 Bota 3 300 303 50000 20260000 20310000 0,2 5,95 Bridge 31 31 408000 408000 100,0 0,12 Buea 437 437 6201000 6201000 100,0 1,82 Carr Mutzig 54 54 255000 255000 100,0 0,07 Communication 163 163 1279000 1279000 0,0 0,37 104 104 554500 554500 100,0 0,16 7 7 33000 33000 100,0 0,01 Dibong 2 2 8000 8000 100,0 0,00 615 1 616 5681000 50000 5731000 99,1 1,68 Ebang 52 52 290000 290000 100,0 0,08 133 133 755000 755000 100,0 0,22 Edea 526 1 527 3219000 3000 3222000 99,9 0,94 Efok 132 132 689000 689000 100,0 0,20 Efoulan 11 11 49000 49000 100,0 0,01 Emana 288 288 1423000 1423000 100,0 0,42 Entrance 5 5 43600 43600 100,0 0,01 Etoudi 11 11 65000 65000 100,0 0,02 Excort 1 1 200000 200000 0,0 0,06 Ezezang 16 16 77000 77000 100,0 0,02 Feeding 405 405 4848100 4848100 0,0 1,42 Fly over 1 1 5000 5000 100,0 0,00 Fuel 22 22 482000 482000 0,0 0,14 Idenau 823 544 1367 15501500 18847500 34349000 45,1 10,07 Karacta 4 4 40000 40000 100,0 0,01 Kekem 177 177 253000 253000 100,0 0,07 Laie 2 2 8000 8000 100,0 0,00 Limbe 541 541 3701000 3701000 100,0 1,08 Loum 75 75 183500 183500 100,0 0,05 Makenene 183 183 514000 514000 100,0 0,15

13 Mandengue 7 7 65000 65000 100,0 0,02 Mandjo 27 27 41000 41000 100,0 0,01 Matomb 181 181 877000 877000 100,0 0,26 Mballa II 44 44 219000 219000 100,0 0,06 Mbanga 79 79 236000 236000 100,0 0,07 Mbankomo 389 389 2140500 2140500 100,0 0,63 Mboumnyebel 405 405 2537500 2537500 100,0 0,74 Melen 2 2 7000 7000 100,0 0,00 Melong 25 25 43000 43000 100,0 0,01 Messa 6 6 27000 27000 100,0 0,01 Messassi 253 1 254 1233000 10000 1243000 99,2 0,36 5 5 25000 25000 100,0 0,01 85 85 413000 413000 100,0 0,12 Mile 4 168 168 801000 801000 100,0 0,23 Misselele 39 39 250500 250500 100,0 0,07 Monatele 225 225 2781000 2781000 100,0 0,81 Money transfert 38 38 589000 589000 0,0 0,17 Motivation 212 212 6652000 6652000 0,0 1,95 Moume 10 10 17000 17000 100,0 0,00 Moungo 346 346 4433000 4433000 100,0 1,30 Moutenguene 169 169 704000 704000 100,0 0,21 Mvan 6 6 19000 19000 100,0 0,01 Mvog mbi 7 7 35000 35000 100,0 0,01 Ndiki 141 1 142 311500 8000 319500 97,5 0,09 Ngomo 85 85 425000 425000 100,0 0,12 Ngong 14 14 110000 110000 100,0 0,03 Ngousso 2 2 13000 13000 100,0 0,00 Ngueme 25 25 159500 159500 100,0 0,05 Njombe 115 115 581000 581000 100,0 0,17 Nkometou 372 372 3427000 3427000 100,0 1,00 Nkomo 5 5 35000 35000 100,0 0,01 6 6 40000 40000 100,0 0,01 Nkongsamba 482 482 3270500 3270500 100,0 0,96 Nkozoa 18 18 105000 105000 100,0 0,03 Nlongkak 46 46 233000 233000 100,0 0,07 Nomayos 168 168 1214000 1214000 100,0 0,36 Nsam 4 4 20000 20000 100,0 0,01 1 1 2000 2000 100,0 0,00 Nyala 75 75 577000 577000 100,0 0,17 Nyassa 192 192 1386000 1386000 100,0 0,41 Nyoupe 2 2 20000 20000 100,0 0,01 Obala 222 222 1265000 1265000 100,0 0,37 Offloaders 1 1 12000 12000 0,0 0,00 Olembe 242 242 929000 929000 100,0 0,27 Olezoa 4 4 14000 14000 100,0 0,00 Ombe 540 540 6458500 6458500 100,0 1,89 192 192 683000 683000 100,0 0,20 Peage 28 45 73 146500 223000 369500 39,6 0,11 3 3 192000 192000 100,0 0,06 Pesage 12 44 56 64000 299000 363000 17,6 0,11 Phytosanitary 58 58 591000 591000 0,0 0,17 Pont-Bascule 1 1 10000 10000 0,0 0,00

14 Port 8 8 23000 23000 100,0 0,01 Poste centrale 42 42 217000 217000 100,0 0,06 143 143 753500 753500 100,0 0,22 Sa'a 338 600 938 5831500 24111700 29943200 19,5 8,77 Sanaga 5 5 14000 14000 100,0 0,00 Soa 173 173 842500 842500 100,0 0,25 Sokolo 26 26 200000 200000 100,0 0,06 Sombo 213 213 1484000 1484000 100,0 0,43 Sonara 35 35 131000 131000 100,0 0,04 Sondje 2 2 40000 40000 100,0 0,01 Souma 1 1 10000 10000 100,0 0,00 Soya 2 2 6000 6000 100,0 0,00 Specification 14 14 239000 239000 0,0 0,07 Suza 15 15 19000 19000 100,0 0,01 Taxes 3 3 53500 53500 0,0 0,02 Tiko 458 458 1903500 1903500 100,0 0,56 Tonga 2 2 10000 10000 100,0 0,00 Torches 15 15 62000 62000 0,0 0,02 Tranportation 415 415 112275210 1,12E+08 0,0 32,90 Village 165 165 568500 568500 100,0 0,17 Waybill 286 286 31698200 31698200 0,0 9,29 Yaoundé 191 191 1508000 1508000 100,0 0,44 Total 14993 3375 18368 114219600 227031360 3,41E+08 33,5 100,00

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