Research Article | Open Access
How Good is the Governance Status in Community Forestry? A Case Study from Midhills in Nepal
Five representative community forest user groups (CFUGs) from Gorkha district in Nepal were studied in order to evaluate the status of good governance in community forestry (CF). Eight criteria and their local indicators were employed to quantify the governance status in CF using simple mathematical procedures. Results show that overall governance level ranges from 70.7% to 79.8%. Among the eight criteria, “consensus-oriented” received the highest score (90.72%), and “accountability” acquired the lowest score (65.34%). Lack of accountability was the striking factor in all CFUGs. Crafting CFUGs and their executive committees more accountable and responsive to all CFUG users including poor, women, and disadvantaged groups, was one of the major challenges. However, the practice of regular auditing of CFUG funds, maintenance of records and other documents, and inclusion of women and poor in the executive committee were some striking opportunities. Because of the inequitable distribution system of forest products, the gap between the rich and poor users is widening and the involvement of poor and marginalized members in CFUG activities has been decreasing.
Governance is generally defined as the process of decision-making by which decisions are implemented or not. Governance is a neutral term, and it turns out to be good if its attributes are in accordance with the principles of governance . Good governance has eight major characteristics as stated by UNESCAP: the rule of law, participation, consensus, accountability, transparency, responsiveness, efficiency and effectiveness, and equity and inclusiveness. It assures that corruption is minimized, the views of marginalized and disadvantaged people are taken into account, and that the voices of the most vulnerable in society are heard in the decision-making process . Even though the concept of good governance is abstract and almost impossible to achieve in its integrity, it is regarded as a crucial direction to achieve the millennium development goals and to eradicate extreme poverty . The World Bank has operated a specific “Demand for Good Governance” concept which refers to the ability of citizens and other stakeholders to hold the state accountable and to make it responsive to their needs.
On the current paradigm shift processes of forest tenure reform throughout the world, and forest governance represents a major issue in the participatory common resource management approach. Since the mid-1980s, most of the developing countries in Africa, Asia, and Latin America have initiated decentralization practices in natural resource management . Major prevailing practices of forest governance include decentralization of forest management in developing countries, simplified logging mechanisms in publicly owned commercial forests in the tropical area, and growing importance of market-oriented certification efforts in temperate forests in the developed world . Decentralization reforms not only promoted local and more democratic participation in governance but also fostered innovative uses of forest benefits.
The community forestry (CF) in Nepal is a prime example of the decentralization of forest management system, which has been commenced with the failure of the centralized forest protection system in late 1970s. The purposes of the decentralization of forestry policy in Nepal were to reduce deforestation and costs of administration and to provide greater benefits to local users along with their active participation in the forest management . It is the highly prioritized national program by which thousands of local institutions have been created and millions of people have participated. These local institutions, called community forest user groups (CFUGs), have a full authority to manage the community forests in the interest of each member of the groups. Forest governance generally deals with the decision-making processes related to forests and forest-dependent communities.
The CF program in Nepal has been regarded as a learning ground for governance reform in terms of participatory decision-making, bottom-up planning process, gender and equity sensitivity, partnership among government, nongovernment and private sector agencies, participatory monitoring, and evaluation mechanism . It has also contributed to five goals out of eight millennium development goals . Both Nepalese government’s strategies, tenth five-year plan (2002–2007) and poverty reduction strategy paper , have envisioned improved governance as one of the strategic pillars of the economic development in Nepal. Good governance helps to improve the condition of CFs and the feeling of ownership among local communities . The CF program has retained its most innovative element of governance through decentralization and devolution of forest management rights and responsibilities . Annual review and reporting as well as public hearing and public auditing are some of the initiatives from the communities towards good governance in CF . Likewise, in terms of inclusiveness of poor and female members, Pokharel and Tiwari  found that executive committees of project-supported CFUGs are more or less inclusive of gender and wealth class. Similarly, Paudel and Vogel  documented the activities of service providers to promote community forestry governance in Nepal and revealed that several government and nongovernment organizations have been playing an effective role in improving the status of good governance in terms of participation, transparency, and accountability.
Despite some achievements, there are many challenges that CF program has been facing for improving the governance system within the CFUG. Lack of inclusive policy making process and propoor policy outcomes, lack of adaptive organizational structure and bottom-up planning, and inequitable decision making and benefit distribution systems are the some of the current governance related issues of CF [7, 15]. Only few CFUGs practice transparent, participatory, and inclusive decision making process . Kanel and Subedi  indicate that the contribution of CF towards supporting the poorest, most vulnerable, and marginalized member of society has been limited within the CFUGs. Rich and poor, male and female, and so-called upper caste and lower caste speak and are heard differently [10, 18]. Kanel and Niraula  conclude that the distribution of forest products is inequitable, and interest of poor and disadvantaged groups is not properly incorporated in poor CF governance.
The contribution of forestry sector to poverty alleviation can only be achieved through the implementation of the effective forest governance. Given the two conflicting schools of literature views regarding the contribution of CF in Nepal, it is quite imperative to investigate the status of good governance at the CFUG level. In order to document and quantify the role of community forestry in acquiring good governance in local level, this study assesses the status of good governance in five selected CFUGs of Gorkha district in Nepal. Employing the locally developed indicators of UNESCAP’s eight criteria of good governance, this study simply quantifies the percentage score of each criterion. The findings of the study could provide important insights on the contribution of CF program in promoting good governance in the local grass-root level in Nepal.
2. Method and Materials
Taking the UNESCAP’s eight criteria of good governance into account, this study specifically develops the local indicators and assesses the status of the governance in Gorkha district of Nepal. Table 1 presents the eight criteria and their respective local indicators of good governance in CFUGs.
Gorkha is one of the midhill districts in Nepal where CF is a major forestry program with more than 350 CFUGs. Figure 1 depicts the geographical location of the district in the midhills of Nepal. The district is well diversified in natural resources and social structures among the CFUGs. Based on the 2001 national census, total population of the district is 288,134, of which the female represents almost 54%. In order to collect the data, five CFUGs were selected in consultation with District Forest Office personnel using the following criteria: more than 5 years old, active in forest management, and heterogeneous groups in terms of social and economic status. Table 2 includes the general descriptions of five selected CFUGs of Gorkha District.
Both primary and secondary data were collected using the participatory approaches. The wealth ranking method was used to determine the relative economic position of each household in each CFUG. User group members were involved in the wealth ranking exercise. They were asked to rank each household in different categories of wealth class as rich, medium, and poor based on fixed properties like land holding size and house, supported by quality of land, food sufficiency, and income sources as well as educational status of the household. Triangulation to verify that the ranking was performed separately with some key informants who were familiar with all users. A proportionate number of respondents from each class were sampled for data collection.
For convenience and to reduce the chances of the error due to heterogeneity, stratified random sampling was used to identify the sample size for interviewing process. Stratification was carried out based on the results of wealth ranking. A sample of 15% households from each wealth class was taken as respondents for theinterview using a set of questionnaires. The questionnaires were pretested in the field and revised wherever necessary. The existing wealth ranking of the users from the CF operational plan was used for sampling the households. Moreover, focus group discussions with specific groups as committee members, women, and professional interest groups were carried out to get various research questions answered and also to help to check the reliability of the answers obtained from other means.
In order to triangulate as well as verify the information, field observation in respondents’ home, community forest, CFUG offices and meetings, user participation in discussion, and decision-making processes in the meetings were conducted as far as possible. Implementation of various good forest governance activities such as benefit sharing, transparency, and participation was also observed during the field visits. The forest officials, village elders, school teachers, and social workers were consulted during the research period.
At the end of the data collection process, a one-day workshop was organized for the stakeholders at the district headquarter of Gorkha. The participants were first informed about the preliminary results of the study and were asked to discuss and list out the appropriate local indicators of good governance in the CF program. The findings from the workshop were included in developing the local indicators of good governance and analyzing the data as well. For secondary data/information, the operational plan, constitution, minute books, financial and administrative records of CFUGs, and audit reports were reviewed thoroughly. Other necessary data were collected from different libraries.
Qualitative and quantitative methods were applied to analyze the data. Simple statistics such as percentage and mean were used to interpret the results. The results of both qualitative and quantitative data were discussed and interpreted in tabular and graphical forms. The data collected for each criterion and indicator were scored from 1 to 5 on point scale. All the qualitative indicators were scored on the basis of priority of the respondents during interview in the scale of very poor , poor , fair , good , and very good . Overall response of an individual respondent on good forest governance was also calculated. Some of the indicators were subjective which were not assigned scores but were analyzed logically.
The number of indicators for each criterion of good governance was different based on the availability of information and data. The indicators were determined by virtue of pretested questionnaires and informal discussion with different stakeholders keeping in mind the nature of the criteria in which the respondents could provide maximum information as far as possible. The status of governance was calculated using following simple mathematical procedures:(i)response of each respondent in each criteria = sum of scores in each criterion/number of indicators;(ii)status of each criterion (%) = sum of response of each respondent in each criterion × 100/expected value × number of respondents;(iii)status of governance in each CFUG (%) = sum of the status of each criterion (%)/number of criterion;(iv)status of governance in the study area = sum of status of governance in each CFUG (%) / number of CFUGs.
The number of indicators for each criterion of good governance was different based on the availability of information and data. The indicators were determined by virtue of pretested questionnaires and informal discussion with different stakeholders. The specific indicators as depicted in Table 1 were used keeping in mind the nature of the criteria in which the respondents could provide maximum information as far as possible.
3.1. Status of Governance in Each CFUG
In addition to the logical and descriptive analysis of each criterion, a series of calculations was carried out for statistical analysis. The qualitative data were scored as per specified rules and methods. Each indicator and its score for each respondent of each CFUG were obtained for further analysis. As a basis for assessing the overall governance in the study area, the status of good governance in each CFUG was taken into consideration. The status of governance in each study CFUG was computed using simple calculation. For instance, consider the following:(i)response of each respondent in each criterion = sum of scores in each criterion/number of indicators. For example: average score of Rule of Law for Kuwadi CFUG’s one respondent = (5 + 2 + 5 + 5 + 4 + 4) / 6 = 4.2;(ii)status of each criterion in each CFUG (%) = (sum of responses of each respondent in each criterion × 100) / (expected value × number of respondents). For example: percent score of Rule of Law for Kuwadi CFUG = (64.7 × 100) / (16 × 5) = 80.8%.
In the above example, there were 16 respondents of Kuwadi CFUG, who summed up value 64.7 for the criteria “Rule of Law”. As the highest score value was taken as 5, it was an expected value for each indicators. Similarly, the calculation for other criteria was carried out.
The values thus calculated for each CFUG is tabulated as a summary matrix. Table 3 shows the status of good governance in all of the criteria of each CFUG which was quantified using the scoring of qualitative data. The status of governance in CFUG level was the highest in Jalbire CF (79.8%) and the lowest in Thangsing CFUG (70.8%) (Figure 2). Among the eight criteria, as depicted in Table 2, consensus has the highest score (90.72%) and accountability has the lowest score (65.34%). It indicates that the CFUGs are not accountable to their users but consensus was the highest mainly due to the consensus in the executive committee selection. The CFUGs were found similar in average status of governance despite of the small variation in individual criterion.
On the other hand, the range of score in each criterion is 60 to 98%. If we consider the criteria individually, they need more improvement in accountability, which is a more important criterion in the good governance framework. However, CFUGs are practicing the sense of consensus as the criterion, which received the highest score among all. If the CFUGs have been carrying out a lot of activities for their users without any conflict, the high score of consensus gives a good sense of ensured good governance.
3.2. Status of Overall Governance in the Study Area
The overall status of good governance in this area is the average governance status considering the five studied CFUGs. For instance, the average of the average score of the good governance in the surveyed CFUGs is (76.7 + 79.8 + 79.7 + 74.9 + 70.8/5) = 76.38%. Since there is not any standard scale to measure the governance as bad, medium, or good, the average value should not be considered as an absolute value of good governance. Furthermore, the weightage or importance of all eight criteria can be different and all criteria may not have equal importance in case of the good governance in each CFUG. During the field study, it was noticed that two or more criteria were difficult for users to distinguish and interpret them separately. Therefore, in other similar studies, some of them which have wide coverage or meaning and obvious to measure can be used. For example, the World Bank has been using 6 worldwide indicators of good governance. Similarly, the SAGUN project has considered only 4 criteria of good governance in the same district. From the score obtained from this study, that is, 76.38%, it can be considered as good as it is close to eighty percent. As we have already discussed, the perfect good governance is an ideal condition in its totality, we can infer from the result that there exists a relatively good governance status in the study area.
The study in the five CFUGs of Gorkha district has revealed both challenges and opportunities of practice of good governance in community forestry. The score in percentage of overall status of governance is 76.38, which can be considered as a satisfactory level of the good governance. The most pertinent challenge is that users themselves are not aware about the good governance because they are always busy in their daily subsistence activities. Only educated and elites are able to discuss the terminology and indicators of the good governance. Making CFUG and CFUC more accountable, duly implementation of the constitution and operation plan, financial resource management, leadership development in target groups, planning and implementing poor-focused programs, equitable distribution of forest products, and making fund management more transparent were some of the key challenges for obtaining the good governance status in community forestry in Nepal .
Shifting to active forest management from the existing passive management system is one of the major challenges at present. The poorest users cannot afford to participate and take leadership responsibility because they are not compensated for their time. Thus, poor people’s meaningful involvement in CF process is one of the major challenges in CF of Nepal . Participation in general assemblies and committee meetings was just for formality because most users do not wait and discuss until the decisions are finalized. Benefit sharing mechanism has been operated in equality basis, so both haves and haves-not were treated by the same measures. This practice shows the dissatisfaction to many poor users. Carelessness of users in the silvicultural operations was a common practice since they are not well trained in the technical aspects of various tending operations.
In terms of fund collection and mobilization, most CFUGs have been spending their funds in other development works rather than addressing the needs of their users within the CFUGs. Many users, even executive committee members, are unknown about the provisions mentioned in the constitution and operational plan of their CFUG. The technical and complex sentences of the operational plan make the members of the CFUGs difficult to understand the meanings. The silvicultural prescriptions included in the operational plan were more technically described.
Despite these challenges there were some opportunities to ensure the good governance in CF in study area. The practice of auditing and reporting of funds to the District Forest Office (DFO), provision of office building or room, notice board for public and internal notices, maintenance of minute books and other office records with secretarial work (accounting, stamp), and increased participation of women in the committee have shown a right trajectory towards the good governance.
To what extent the CF in Nepal has contributed towards the poverty reduction could be another topic of study. In this study it was found with reference to the status of governance that the contribution of CF in poverty reduction was either low or not spelled out properly. Because of the inequitable distribution system of forest products, the gap between the rich and poor users has been increasing and the interest of poor in CF activities has been decreased. Therefore, to ensure the increased investment of fund into the propoor activities and effective forest management activities, the committee should be more accountable and responsive towards the underprivileged groups.
The study was carried out in five community forest user groups of Gorkha district in order to assess the status of the good governance in CF. Both primary and secondary data were analyzed using simple statistical methods. A list of local indicators for each UNESCAP’s criterion of the good governance has been developed. A simple quantification of the score on “Rule of Law” shows that Jalbire and Koldanda CFUGs have the highest and lowest scores, respectively. Transparency was the highest in Jalbire and the lowest in Thangsing CFUG. Regarding accountability, Koldanda and Thangsing CFUGs were the highest and the lowest scorer, respectively. The scores of Jalbire and Thangsing were the highest and lowest, respectively, in terms of participation of users. Similarly, Jalbire was the most responsive but Chisapani was the least responsive to their respective users. On the other hand, Koldanda had the highest score in criteria whereas Thangsing the lowest. In case of the efficiency, effectiveness, and consensus-oriented, Jalbire CFUG was the highest scorer and Thangsing received the lowest good governance score.
The overall status of governance in the CFUG level was highest in Jalbire CF (79.8%) and the lowest in Thangsing CFUG (70.8%). Among the eight criteria, consensus has the highest score (90.72%) and accountability has the lowest score (65.34%). It indicates that the CFUGs are not accountable to their users but consensus was highest mainly due to the consensus in the formation of the executive committee. However, the overall status of good governance in the study area was calculated as 76.38%, which is just satisfactory but still promising.
From the above results and discussion, it is clear that good governance is an ideal which is difficult to achieve in its totality. A few community forest user groups can come close to the status of the good governance. However, to ensure sustainable forest management, actions should be taken to work towards this ideal with the aim of making it a reality. On the other hand, despite of its simplicity and clear findings, some technical caveats on research methods and data analysis are in order. Only five CFUGs from one of the several districts hardly represent the overall midhills in Nepal. Likewise, employing a simple scoring techniques and algebraic calculations of the criteria and indicators might not be technically sufficient. Thus, further exploration of statistically strong quantification techniques with a large representative sample size could be a worthwhile endeavor.
Conflict of Interests
The authors, Dhananjaya Lamichhane and Rajan Parajuli, declare that there is no conflict of interests regarding the publication of this paper.
The research study was conducted with the financial support of ComForM Project at Institute of Forestry, Pokhara, Nepal. The authors are thankful to all staff from District Forest Office Gorkha, Federation of Community Forest Users Nepal (FECOFUN) in Gorkha and all CFUG committee members and the respondents, who had cooperated with us in all respects during the field visits and data collection. The authors would also like to thank anonymous reviewers for their valuable and constructive comments which help improve the quality of the paper.
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