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world congress of agroforestry 2009 nairobi kenya 23 28 august n.
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World Congress of Agroforestry 2009 Nairobi - Kenya, 23-28 August PowerPoint Presentation
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World Congress of Agroforestry 2009 Nairobi - Kenya, 23-28 August

World Congress of Agroforestry 2009 Nairobi - Kenya, 23-28 August

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World Congress of Agroforestry 2009 Nairobi - Kenya, 23-28 August

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  1. Can fiscal policies be designed to reward biodiversity conservation and support small tree products enterprises?P. 1Mbile, L. 2Popoola, Z 1Tchoundjeu, A 1Degrande & C 1Facheux World Congress of Agroforestry 2009 Nairobi - Kenya, 23-28 August 1 World Agroforestry Center, West and Central Africa, Yaoundé, Cameroon 2 Department of Forest Resources Management, University of Ibadan, Nigeria

  2. Can fiscal Policies reward biodiversity conservations? YES, but,… Enthusiasm is not very strong about feasibility. However, there is broad agreement with the principle, however There is feeling that the State should assume greater responsibility in financing biodiversity conservation There is surprisingly strong mistrust for loose collegiality in managing funds….needs further analyses There is expectation that such funds should be seen to clearly improve livelihoods & protect biodiversity Contributors should be regularly informed and they should be able to opt out if funds are managed badly

  3. Forest Context..1…Cameroon • Cameroon still has an estimated 19,632,000 hectares of forests • 12, 177,395 (62%) is classified as permanent (comprising mainly PAs -20.7%, FMUs -39.4%, Council forests -1.9%) • 7,453,605 (38%) is classified as non permanent estates (comprising private plantations -0.3%, community forests -3.2% and State domains (34.5%) • Emerging community forest enterprises subsist on 3.2% of forest over which communities have formal agreements with the State, and occur in official Agro-Forestry Zones

  4. Context..2: Study Site: an undisputed laboratory for forest policy and conservation value analyses - Guinea-congolian zone of endemism - 300 woody plant species • 54 mammal species • 90 species of birds • 120 species of fish • Up to 80% endemism • (CARPE, 2000, White, 1983, 1993 )

  5. Context…3 : Policy.. • Currently, no direct revenue accrues yet to communities living inside or around protected areas. • The law provides forest fees to communities and councils bordering active FMUs. • State supports RIGC project to fund critical aspects of community forest development • Council and community forests exist to facilitate direct management of forests by local people. • State recognizes that community forests still face big challenges

  6. And in case you were wondering what Agroforestry has to do with community forests Thenkabail (undated), Gokowski et al, 2004. 1,434,035 ha analysed Prim. Forest = 25.7% Sec. forest = 22.9% Cocoa Agroforest = 8% Tree-based farmlands = 16.2% Fallows = 14% Total tree-based systems = 38% = 544,933 has of Agroforestry lands

  7. Community forest fast facts as of end 2008 Challenges faced as ‘enterprises’ • Credit • Marketing/promotion • Technology • Business skills • Networking • Enforcement of contracts with customers..

  8. What is the value-added that Agroforestry brings?

  9. The ‘Utility’ theory developed under a timber exploitation regime(Adapted from the Hanemann & Kanninen model (1998) • Q,1 to Q1 > Q0 -----------------------------------(1) • V(P,Q1,Y,S,E) ≥ V(P,Q0,Y,S,E)-----------------------(2) V=utility; Y=income; S=other consumer attributes; E =random variable; Q = option or intrinsic value of biodiversity representing ‘utility’ to the consumer V(P,Q,Y,S,E)-----------------------------------(3) = Random Utility Maximization When asked if she/he would be willing to pay to conserve tree Biodiversity • Pr: "Yes" ONLY if, V(P,Q1,Y-X,S,E) ≥ V(P,Q0,Y, S, E),--------(4) Otherwise "NO", Hence,

  10. Survey development: sampling, pilot and implementation (i) • Against a wishful sample size of 600, 400 respondents were contacted in Yaoundé (early 2008) and firm appointments taken. • With support from experts, colleagues and literature a pilot consisted of evaluating products, services, question formats, categorical scales, suggestions for improvement • A non-probabilistic survey; of 3 groups of employers; civil society (30%), international organizations (26%) & Government (44%)

  11. Survey implementation (ii) • Agreement was reached on ‘referendum’ and likert scales including ‘indifferent’ or ‘non-committals’ to payments • 4 part questionnaire: (i) respondent attributes; (ii) products & services; (iii) awareness/perception of mitigating biodiversity (iv)payment card option – discrete & or % on market price • With expert advice, a probabilistic sampling of 400 observations (100% response rate) to produce 304 analyzable questionnaires using random sampler completed the survey

  12. Survey implementation (iii) Data were tabulated in MS ACCESS, exported and analyzed in SPSS 17 . Independent & dependent variables were explored descriptively. Then Chi-square /Fischer’s exact tests for significance of associations between dependent/independent variables; Kendal W NPAR tests for concordance within groups was performed. Then Model was evaluated inferentially.

  13. Summary results/..1 • 2 x as many males than females gave detail responses • 50% of resp. between 30-40 yrs. <90% Cameroonian • Dominant zones of origin were savannah (45%), forest (43%) • 75% were regularly employed; 52% receive per/month income of 200-1000 $US • 55% were of intermediate decision-making • 63% did not own cars, while 83% were regular intercity bus users • Air travelers and non-air travelers was split down the middle • 77% used hotels regularly, same proportion regularly paid audio-visual taxes & consumed alcohol while <10% used tobacco regularly. • WILL SKIP DEPENDENT DESCRIPTIVES

  14. Summary results/..1— Most probable assocs. (p<0.005)

  15. Summary results/.2..emergence of random variable • In terms of payment amounts or percentages 83% were non-committal or indifferent preferring not to provide discrete amounts. • 13.8% agreed to pay amounts ≥5 $ while 3.9 agreed to pay amounts between 1 and 5 $US either as a % or as tax above market prices for goods and services as expression of ‘utility’. • Contrarily the mean “YES” response rate for all respondents irrespective of characteristic following the referendum was 79%: compare with mean of 82.9% (CI =±3.7, 95% CL) unwilling to provide currency amount as taxation. • We assumed that there must be a random factor or measurement error explaining the willingness to support biodiversity, financially yet unwilling to commit themselves. So we searched for patterns in awareness/perception of responsibility conservation and conditionalities for support

  16. Summary results: responsibility –NPAR tests Statement 4: The Cameroon Government should assume greater financial responsibility for biodiversity conservation.

  17. In search of the random factor: conditionality….1

  18. In search of the random factor: conditionality….2

  19. In search of the random factor: conditionality….3

  20. Summary results: Conditionality NPAR tests Cond5: If funds are managed by the State Cond6: If funds are managed collegially by government, NGOs, and local councils? Cond3: If funds support livelihoods as well as biodiversity management Cond7&8: Consumer is regularly informed and can opt out.

  21. Can fiscal Policies reward biodiversity conservations? • YES, but,… • Enthusiasm is not very strong about feasibility. • However, there is broad agreement with the principle, however • There is feeling that the State should assume greater responsibility in financing biodiversity conservation • There is surprisingly strong mistrust for loose collegiality in managing funds….needs further analyses • There is expectation that such funds should be seen to clearly improve livelihoods & protect biodiversity • Contributors should be regularly informed and they should be able to opt out if funds are managed badly

  22. Asante Thank you for your attention