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

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, Cameroon2 Department of Forest Resources Management, University of Ibadan, Nigeria

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

WORLD AGROFORESTRY CENTRE

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


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 )


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


And in case you were wondering what Agroforestry has to do with community forests

Land use Proportion

Habitat/farms/fallows 15%

Logged 5%

Secondary forest 40%

Unlogged 40%

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


Community forest fast facts as of end 2008

Community Forests Requests

402

Approved Simple Management Plans

174

Convention signed 135Conventions awaiting signature

39

Demanded 1,306,707.66 ha

Reserved 487,313.91 ha

Attributed/operational

621, 245.4 ha

Estimated Agroforestry farmland

93,187 ha

Challenges faced as

‘enterprises’- Credit- Marketing/promotion- Technology- Business skills- Networking- Enforcement of

contracts with customers..


What is the value-added that Agroforestry brings?

11%

53%

28%

8%

Food & Timber

Medicine & Timber

Food, Medicine & Timber

Cure & Timber


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,


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%)


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


Survey implementation (iii) Categories Returned

questionnaire per category

Completion rate (%)

Probabilistic sample

CL CI (±)

Int. NGOs 102 100 89 (29.3%) 95% 3.7

Civil society

118 100 97 (31.95) 95% 4.2

Gov’t .& Para-statal

180 100 118 (38.8%) 95% 5.3

400 304

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.


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


Summary results/..1— Most probable assocs. (p<0.005)Xtics House Car Inter-city Air travel Hotel Restaurant Audio-

visualAlcohol Tobacco

Sex 2 < 10χ None None None 2 <20χ 2 < 20χ None 2 >20χ 2 < 10χ

Age 2 > 40χ 2 > 50χ None 2 >20χ Fisher’s=25.5

None 2 > 30χ 2 = 10χ None

Employer 2 >20χ 2 > 10χ 2 > 30χ None 2 >10χ 2 > 10χ None None

Decision-making

seniority

2 > 20χ 2 >40χ 2 > 10χ 2 > 40χ Fisher’s=14.3

2 > 20χ 2 > 30χ None None

Income 2 > 10χ 2 > 76χ 2 > 30χ 2 > 80χ Fisher’s=35.3

None 2 > 20χ None None

Nationality

None 2 > 20χ None 2 > 20χ None None 2 > 10χ None None

Ecological origin

None Fisher’s =25.5

Fisher’s =22.3

2 > 20χ None None Fisher’s=15.1

None None

Regularity of

employment

2 > 10χ 2 > 10χ None 2 > 10χ Fisher’s = 12.9,

None 2 > 74χ None None


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


Summary results: responsibility –NPAR tests

Kendall's W Ranks Test result

Mean RankStatement 1 3.61

Statement 2 3.45

Statement 3 3.05

Statement 4 1.32

Kendall's W Ranks Test Statistics

N 304

Kendall's Wa .588

Chi-Square 715.233

df 4

Asymp. Sig. .000

a. Kendall's Coefficient of Concordance

Statement 4: The Cameroon Government should assume greater financial responsibility for biodiversity conservation.


In search of the random factor: conditionality….1

C1

C2

C3

C4

C5

C6

C7

C8

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

MALEFEMALE

Extent of agreement

Cond

ition

aliti

es



C1

C2

C3

C4

C5

C6

C7

C8

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Over_1000 $US

200_1000$US

Under_200 $US

Extent of agreement

Cond

ition

aliti

es



C1

C2

C3

C4

C5

C6

C7

C8

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

Senior

Intermediate

Junior

Extent of agreement

Cond

ition

aliti

es


Summary results: Conditionality NPAR tests

Conditionality 1 Mean Rank

Conditionality 1 5.06








Kendall W Test Statistics of concordance

N 304

Kendall's Wa .269

Chi-Square 573.487

df 7

Asymp. Sig. .000

a. Kendall's Coefficient of Concordance

Cond5: If funds are managed by the StateCond6: If funds are managed collegially by government, NGOs, and local councils?Cond3: If funds support livelihoods as well as biodiversity managementCond7&8: Consumer is regularly informed and can opt out.


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


Asante

Thank you for your attention

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

Documents

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