International Journal of Environmental Research University of Tehran ISSN: 1735-6865 EISSN: 2008-2304 Vol. 4, Num. 3, 2010, pp. 501-506

International Journal of Environmental Research, Vol. 4, No. 3, July-September, 2010, pp. 501-506

Article

Community-based preferences for economic incentives to promote biodiversity conservation in a tropical rainforest

Ezebilo, E.E.

Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, P. O. Box 49, 230 53 Alnarp, Sweden

Correspondence Address: *Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, P. O. Box 49, 230 53 Alnarp, Sweden
Eugene.Ezebilo@ess.slu.se

Date of Submission: 02-Sep-2009
Date of Decision: 07-Mar-2010
Date of Acceptance: 15-Mar-2010

Code Number: er10055

Abstract

Keywords: Transaction costs, Biodiversity, Conservation, Property rights, Nigeria

Introduction

Governments often use various policy instruments to reduce environmental degradation. For example, command-and-control, i.e. those that provide firms with relatively little flexibility to achieve goals (Harris, 2006), and incentive-based, i.e. those that provide firms with greater flexibility in making sustained environmental progress. The command-and-control set uniform tar-gets with regards to how much firms should emit, i.e. firms are only encouraged to reduce emissions to a regulated level (Spence and Weitzman, 1994). Incen-tive-based approach provides continuous motivation to encourage polluting entities to reduce releases of harmful pollutants. The use of incentive-based ap-proach results in a lower cost compared to the com-mand-and-control approach (Pigou, 1920; Panyotou, 1994) because firms will reduce their emissions as long as it is financial valuable to do so (Tietenberg and Lewis, 2010; Asafu-Adejaye, 2000). Examples of the incentive-based approaches include: marketable emission per-mits, taxes, fees, charges, subsidies and tax-subsidy combinations. Economic incentives are compatible with the free market ideologies e.g. privatization of public assets, trade liberalisation, greater decentralisation in decision making and enhance role for the private sec-tor. Developing countries are often encouraged to adopt market based instruments to improve economic well-being. However, there is little empirical evidence on the use of economic incentives in natural resource management in developing countries (UNEP, 1995; Arntzen, 1992; McNeely, 1993).

Environmental goods and services are often clas-sified as public good which is characterised by non-rivalry, i.e. consumption of the good by one person does not reduce the quantity available for others. Public goods are also non-excludable, i.e. no one can be ex-cluded from environmental benefits. This often results in market failures, i.e. under-pricing of environmental asset. Inappropriate valuation of natural resources may often contribute to environmental degradation. In or-der to reduce environmental degradation most gov-ernment in developing countries have often estab-lished national parks. They often use public property rights to justify the management of the parks. Prop-erty rights over land may be used as an instrument to promote biodiversity conservation (Libecap, 1989; Eggertsson, 1990), because it is important in setting the incentive structure in economic production. Prop-erty rights over land often reflect conflicting economic interests and bargaining strength of affected individu-als (Libecap, 1989; Platteau, 2006). It can influence individual's behaviour with regard to exploitation and nature conservation. Undefined property rights may result in open access and overexploitation of natural resources. This may risk to making biodiversity con-servation unsustainable. Well defined property rights may serve as an incentive for biodiversity conserva-tion. Public property rights restrict individual's access to resources in national parks, thus, risking to reduc-ing livelihoods of individuals who once depend on the area for sustenance. This often generates conflict be-tween biodiversity conservation efforts with local sub-sistence demands (Shyamsunder and Kramer, 1996). Experience has shown that this type of biodiversity conservation management has not been effective in practice e.g. the denial of local communities right to use Mount Kenya Forest failed to stop illegal forest utilisation. Biodiversity conservation which focuses mainly on disincentives may not win the support of local communities because it tends to weaken their livelihoods. To minimise transaction costs associated with biodiversity conservation such as, negotiation cost and cost of conflicts with local resident, there may be a need to modify public property rights over land to incorporate incentives that may encourage more people to support nature conservation. In bargaining over the modification of property rights, the positions taken by bargaining parties are modelled by their ex-pected gains, as well as by the actions of other parties (Libecap, 1989). Every governance structure has a transaction cost (North, 1990; Stavins, 1994, Coase, 1937) and individuals who are affected by the struc-ture will need to make investment to enable them fit into the structure. The study reported in this paper is to examine the local community's preferences for biodiversity conservation management institutions and its determinants.

Materials and Methods

Okwangwo Division (OD) of Cross River National Park is located in the Cross River State in tropical rainforest of the south-eastern Nigeria and covers an area of 1000 Km΂. The OD plays an important role in the protection of fisheries, watersheds and climatic stability, ecotourism and preservation of genetic re-sources (Coldecott et al., 1990). Mammals found in the OD include antelopes, chimpanzees, high forest monkeys, buffaloes, high forest elephants, manatees, and wild pigs. Others are baboon, leopards and goril-las. The park is a centre of endemism for frogs, birds and four primates, including the endangered Cross River Gorilla - - Gorilla gorilla diehli (Oates et al., 1990; White, 1990). It is claimed (Chukwuone and Okorji, 2008) that the OD has the highest diversity of primate species recorded at any single site in Africa. The OD is surrounded by 66 villages and subsistence agriculture is the main stay of the economy of these villages. Crops cultivated in the area include banana, plantain, cocoa, sweet potatoes, cassava, and yam. Livestock reared include poultry, cattle, sheep and goat. The local people also engage in gathering, trapping and hunting of non-timber forest products such as bush mango (Irvingia gabonensis), afang - - a leafy wild vegetable (Gnetum africanum Welw), fuelwood and game animals such as deer, antelopes, and wild pigs. Cash income for house-hold financial requirements is mainly generated from the sale of livestock, crop products and non-timber forest products (Ite, 1995; Ezebilo and Mattsson, 2010). Some of the people engage in non-traditional (formal) employment such as teaching, nursing and catering for their livelihood. Presently, local residents are not allowed access to resources in the OD and this have often generated conflicts between the local residents and the park managers. Local residents are often of the opinion that the OD have been part of their land and that they need to be compensated for a reduction in livelihoods.

The data originated from a standardized face-to-face interview conducted in 2008. Prior to the main survey a pre-test survey was conducted in 2007. Find-ings from the pre-test prompted some changes in the questionnaire such as, the wording of the hypotheti-cal biodiversity conservation institutions. The survey was conducted with the help of two assistants. They were recruited and trained for two days. Three villages from the 66 villages located within the catchment area of the OD were randomly selected for the survey. The villages comprised of Bukalom, Butatong and Wula in the Boki Local Government Area of Cross River State. Every other house along the street was visited in each of the villages. If a house was not occupied, then it was omitted and the next house was visited. The re-spondents alternated between the eldest male and the eldest female in each selected household. If the gen-der of the eldest in a household did not coincide with the respondents' selection method, then a member of the opposite gender was interviewed and the respondent's gender was alternated again from there on. Interviews were conducted in the Boki language. A total of 150 respondents were interviewed in the study area (50 respondents in each village).

The motivation about the study was described to the respondents and they were asked about their age and total annual income. Furthermore, they were asked about their income from farming activities and whether they were native to the area. Respondents were asked about their income from non-timber forest products and whether they were member of any environmental group. Three potential biodiversity conservation man-agement institutions (A, B, C) were described to the respondents and they were asked to choose the insti-tution which they prefer. The potential biodiversity conservation management institutions were:

• A was about the integration of public property rights over land with provision of infrastructure such as health care services and vocational training centre.
• B was about the integration of public property rights over land with access to non-timber forest prod-ucts in the OD under the supervision of the national park officials.
• C was about the integration of public property rights with communal property rights, i.e. allocating the local residents a piece of land outside the park where they may establish community forest for their own use.

Choice, ranking and rating are elicitation formats used in conjoint analysis applied to environmental valu-ation. Economists tend to prefer ordinal measures, be-cause they conform to the random utility theory (Roe et al., 1996; Holmes and Boyle, 2001; Champ et al., 2003). Since, respondents were required to choose biodiversity conservation management institution al-ternative which they prefer. A rational respondent would choose one alternative over the others if the expected utility of one exceeds the other; thereby maxi-mizing his/her utility (Deaton and Muellbauer, 1980; Hanley et al., 2007). In this case, a rational respondent would prefer one institution over the other if and only if the transaction cost is lower than the other. The logit model can be used to estimate a utility maximization problem where the respondent is assumed to have pref-erences defined over a set of institution alternatives:

U_j = β_j X_i + ε_j          (1)

where, U_j is the utility of institution j, X _i a vector of attributes which characterize the i-th respondent, ~lj represents parameters to be estimated and ε _j is the disturbance term. The disturbance terms are assumed to be independently and identically distributed. If the respondent's choice is alternative institution j, we assume that the utility from alternative j is greater than the utility from other alternatives:

where, U _ij is the utility to the ith respondent of institution j, and U _ik the utility to the ith respondent of institution k. If each institution is considered as a possible decision choice by the respondent he/she is expected to choose the alternative that has higher expected utility among the alternatives. The ith respondent's decision may, therefore, be modelled as maximizing the expected utility from a given institution by choosing the jth regime from among J discrete choice available is:

where, E (U _ij ) is the expected utility of alternative j to the ith respondent, and f _j is a function of the respondent's attributes ( X _i ). The probability of choosing alternative j from among J alternative choices is equal to the probability that the expected utility from alternative j is greater than the expected utility from any other alternative. The multinomial model for institution choice specifies the relationship between the probability of choosing option Y, and the set of explanatory variable (Greene, 2003) as:

where Pr(.) is the probability that the ith respondent most prefers the jth institution. Normalization of the alternatives by one of the categories ( B _k = 0) yields the multinomial logit model as:

The log-likelihood function for the multinomial logit model is:

Where d _ij = 1 if the respondent I chooses alternative j and d _ij = otherwise (Greene, 2003). Since the coeffi-cients of such models are not directly interpreted, mar-ginal effects (δ_j ) were estimated to express the prob-ability of change in alternative institution arrangement with respect to each independent variable, measured from the mean of the variable.

Based on the data collected the multinomial logit model was used to examine factors which might have influenced the respondents' choice decisions. This is presented in [Table - 2]. The means and standard devia-tions for the variables included in the analysis is re-ported in [Table - 1].

Results and Discussion

All individuals who were selected for the survey responded to the interview. This showed that the re-spondents were interested in this type of study and may be willing to participate in activities which may promote biodiversity conservation. Ninety percent of the respondents who belonged to an environmental group preferred institution A. The result of the respon-dents' choice of biodiversity conservation manage-ment institution is presented in [Figure - 1].

The result in [Figure - 1] shows that most of the respon-dents (59%) preferred institution A. The possible rea-son may be that institution A may give them the op-portunity to have access to more livelihood alterna-tives with less transactions costs. For example, intro-duction of vocational training centre to the area may provide the respondents more opportunity to acquire new skills such as, food processing skills. This activ-ity may not require much interaction with the national park managers, hence may result in less transaction costs. Another possible reason may be that respon-dents prefer to reduce the frequency of negotiation with OD managers for economic activities such as, extraction of non-timber forest products. The results in [Figure - 1] shows that more of the respondents preferred institution C (26%) compared with B (15%). This may suggest that more of the respondents may have pref-erence for biodiversity conservation management in-stitution which does not involve much negotiation and policing from national park officials. For example, in-stitution B requires negotiation with regard to how, when and where to collect non-timber forest products. It also requires negotiation about the quantity of non-timber forest products to collect and how it should be distributed among individuals (respondents). Institu-tion C requires negotiation with the OD managers mainly about the size of land for the community forest. Institution B may require more interaction with the OD managers to reduce the tendency of opportunistic behaviour and also for the managers to honour the contractual agreement. To examine factors which might have influenced the respondents' choice the marginal effect multinomial logit model was estimated, as shown in [Table - 2].

Marginal effects are the probability of change in favour of a specific institution with respect to each in-dependent variable, measured from the mean of that variable. A positive or negative sign of marginal effects indicate an increase or decrease in the probability of preferring a given institution under consideration. It was observed that there were some statistically signifi-cant variables that provide predictive information on the respondents' preferred institution. Overall, the co-efficient associated with income from non-traditional employment provided the most predictive power whether the respondents prefers institution B, or C. The coefficient associated with income from farming and income from non-timber forest products were found to be more relevant in determining the respondents' preference for institution C. All the explanatory vari-ables with regard to the respondents' preference for institution A were not statistically significant.

The coefficient associated with the respondents' income from non-traditional employment has a posi-tive and statistically significant impact on preference for institution C. This suggests that respondents who have more income from non-traditional employment preferred C. However, increase of income from non-traditional employment by one unit (NGN 1) has no effect on the respondents' preference for C. A pos-sible reason may be that respondents who have more income from non-traditional employment often have more formal education. Formal education provides them the opportunity to infer the future benefits of commu-nity forest, e.g. access to forest products at less trans-actions costs. The coefficient associated with the re-spondents' income from non-traditional employment has a negative and statistically significant effect on the respondents' preference for institution B, i.e. the respondents who have less income from non-traditional employment preferred B. The marginal effect shows that a decrease in the respondents' income from non-traditional employment has no effect on the respon-dents' preference for B. A possible reason may be that the respondents who have less income from non-tra-ditional employment may need to earn additional in-come to meet their livelihood needs. This additional income often comes from non-timber forest products. Institution B may provide them with access to non-timber forest products at less investment cost.

The coefficient associated with income from non-timber forest products has a positive and statistically significant impact on the respondents' preference for institution C, i.e. the more the income from non-timber forest products the higher the probability of choosing institution C. The results showed that an increase in income from non-timber forest products by one unit (NGN 1) has no effect on the respondents' preference for C, i.e. it is not likely that respondents who have more income from non-timber forest products will fall to prefer alternative C. A possible reason may be that indi-viduals (respondents) often support institutions that will benefit them at less transactions costs. Institution C may provide the respondents with continuous ac-cess to non-timber forest products at less transaction costs (e.g. negotiations and monitoring).The coefficient associated with income from faming has a positive and statistically significant impact on the respondents' pref-erence for institution C, i.e. respondents who have more income from farming activities preferred C. If the re-spondents' income from farming increases by NGN 1, it is not likely that the respondents may fall in preferring institution C. A possible reason may be that respon-dents who earn a lot of income from farming should have more resources to invest in other livelihood alter-natives to reduce the risk associated with farming ac-tivities (e.g. transaction costs). The diversification of income generating activities may give them the oppor-tunity to have a sustained livelihood, because farming activity is often seasonal.

The coefficients associated with the respondents' age, and origin was not statistically significant.

Conclusion

Many management institutions for biodiversity conservation are often available but natural resource management is often more sustainable when local com-munities are involved. This is because economic ac-tivities of local communities often have effect on the natural environment. This study has focused on the involvement of local residents to choose biodiversity conservation management institution which may mo-tivate more of the people to support primary objec-tives of national park managers (e.g. biodiversity conservation). The study showed that most of the respon-dents preferred regime that combine biodiversity con-servation with provision of infrastructure. Respon-dents' choice of biodiversity conservation institution were influenced by factors such as income from farm-ing, income from non-timber forest products and in-come from non-traditional employment, respectively. Biodiversity conservation management institution which is adopted for conservation should be specific to local condition and flexible in order to accommo-date future changes in the area.^[27]

References

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