ASSESSMENT OF SUSTAINABILITY OF COMMUNITY FORESTRY THROUGH COMBINED ANALYSIS OF FIELD AND REMOTELY SENSED INDICATORS (A CASE STUDY IN SIRAHA AND SAPTARI DISTRICTS, NEPAL)
By MOHAN PRASAD POUDEL FEBRUARY 2002
INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION ENSCHEDE, THE NETHERLANDS
ASSESSMENT OF SUSTAINABILITY OF COMMUNITY FORESTRY THROUGH COMBINED ANALYSIS OF FIELD AND REMOTELY SENSED INDICATORS (A case study in Siraha and Saptari districts, Nepal)
By MOHAN PRASAD POUDEL
Thesis submitted to the International Institute for Geo-Information Science and Earth Observation in partial fulfillment of the requirements for the degree of Master of Science in Natural Resources Management (Forestry for Sustainable Development).
Degree Assessment Board Prof. Dr. Ir. A. de Gier Chairman and Head of Forest Science Division Prof. Dr. R. De Wulf External Examiner Dr. Y. A. Hussin SA FSD.2 Dr. M. Mc Call External member ITC Mr. R. Albricht, M.Sc., 1st Supervisor Dr. M. Weir 2nd Supervisor
INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION ENSCHEDE, THE NETHERLANDS
Disclaimer
This document describes work undertaken as part of a programme of study at the International Insti- tute for Geo-information Science and Earth Observation. All views and opinions expressed therein remain the sole responsibility of the author, and do not necessarily represent that of the institute.
This thesis is dedicated to my late grand father Gazadhar Poudel who passed away while I was following this course I could not see him at his last time I respect him forever I am proud of him
ABSTRACT
Community Forestry has been increasingly recognized as a promising approach to achieve sustainable management of forest and improve livelihood mostly in rural areas of developing countries. Nepal also has incorporated Community Forestry (CF) as a main approach to manage the country’s forest since 1988. It is widely believed that CF shows promising results in ecological, economic and social fronts and is leading towards sustainability. However, results are varied all over the country leading to several doubts and debates regarding the sustainability of existing CF approach in some parts of the country.
This research aimed to assess sustainability of CF in Siwalik range (very fragile series of several ridges starting from lowland Terai). The area is characterized by very high incidence of poverty, overuse of firewood and timber smuggling as an alternative source of income. Criteria and Indicators (C&I) were used for the assessment. C&I promise to be useful tools for assessing, monitoring and evaluating progress towards sustainable forest management. Regarding local condition, relevant C&I from several literature sources were modified and new ones were generated using multi criteria analysis approach (MCA).
Two Community Forest Users Groups (Majhau and Jiva) were selected as study sites. Basis for selection were: at least five years of hand over and internal management approach being implemented. Designed sampling method was simple random sampling. RRA tools were used for socio-economic data collection. Forest stand variables and other ecological indicators were measured for ecological data. Based on distribution pattern of stand variables, the t test and Mann-Whitney test were used for significance test of difference between the two study sites. Secondary data regarding the history of the study sites such as initial operational plan and inventory data were also collected for trend analysis. The sign test was used for significance test of trend of both the social and ecological condition. Satellite images (1992 TM, 1999TM and 2001ASTER) were classified and compared to establish the changes over time. Related information from different data sources were triangulated to validate each other. Selected indicators for both social and ecological condition were finally assessed based on analyzed information mentioned above.
Comparing study sites, Majhau that was characterized by: homogenous group with similar needs and interests of users; no problem with distant users; equity in benefit sharing; few conflicts and high awareness, was found comparatively more sustainable in social condition. Social condition in Jiva was characterized by: problems with distant users; poor awareness; haphazard decision-making; diverse needs and interests; prevailing conflicts and lack of common understanding among users. Jiva was found socially unsustainable. Trend in both social and ecological condition since being handed over was also found to be significantly positive in Majhau but not in Jiva. However, forest and other ecological condition at present were not significantly different between the study sites at 90% confidence level. The social and ecological conditions of Community Forestry were found to be significantly related with each other. Comparing independently classified images, in overall, positive changes in forest condition were observed. The same changes also observed in the surroundings (1.5 km vicinity) of the both study sites. No major differences were observed between the trends on satellite images and field indicators (social and ecological).
ACKNOWLEDGEMENT
I am deeply indebted to all the individuals and organizations who supported me during my M. Sc. study at ITC. I am especially thankful to the Government of the Netherlands for giving me a fellowship for this course.
I would like to express my sincere gratitude to both my supervisors Mr. R. Albricht and Dr. M. Weir, without whose continuous supports, this thesis would not have been worth reading. Robert Albricht always encouraged me in my works and supported my ideas sharing his ideas and experiences. I found him always seeking supportive literature for my research work and wishing success. I appreciate his patience in correcting my writing through reading and re-reading the draft. Michael Weir guided me during my fieldwork. He enabled me to tackle with practical problems during data collection. Despite his busy time, he always helped me during the whole course.
I am grateful to Professor Alfred de Gier, Head of the Forest Science Division, Dr. Yousif Ali Hussin M. Sc. student’s advisor, Martin Gelens, Edwin Kiezer and Mrs. Louise van Leeuwen for regular support and encouragement throughout the course. They were always helpful.
I would like to thank Mr. Dibya Deo Bhatta, Director general of the Department of Forest Nepal for his valuable support and suggestions during my fieldwork. I would also like to thank Mr. Damodar Parajuli, MFSC; Mr. J. K. Tamrakar, DF; Mr. I. S. Karki, former DG, DF; Dr. Binod Bhatt; and Mr. Sagandra Tiwari for their moral supports in due course of time. My special thanks go to Mr. Santosh Mani Nepal, Department of Forest, for his appreciative cooperation during fieldwork in Nepal. Mr. Nabin Giri, AFO Morang, also deserves special thanks for his logistic arrangement to my supervisor at the beginning of fieldwork while I was not with him. My friend Kiran deserves special thanks who provided images of my study area.
I am grateful to Churia Forest Development Project for providing me valuable supports and suggestions in fieldwork. Mr. Bishwas Rana and Mr. Netra Regmi deserve special mention. I am grateful to Ranger Gyanendra Pradhananga and his range post team (Mahuli, Saptari) and Ranger Raya and his assistance (Mirchaiya, Siraha) for their help during data collection. I am grateful to DFO Dr. J. C. Baral for his supports and suggestions in fieldwork. I am also grateful to all committee members and respondents of both Majhau and Jiva CFUG for their support during data collection.
I would like to thank my classmate Robert Aguma; Padam Dahal; Alejandra Fregoso; Andres Hernandez; and Ana Sotomayor who helped me in many ways and became cheerful companions throughout the course. I thank my friends Lara; Merise; Subanath; Rabindra; Santosh; Kandel and Nil Mani Regmi. Thanks to all-Nepali friends studying at ITC, with whom I shared enjoyable moments during my stay in Enschede.
Last but not least, I am very much grateful to my family who provided encouragement and inspiration during the difficult part of my study. I would like to extend my special thanks to my beloved wife Neelam who always sacrificed her interests and wished for my success. My sweet daughter Monu is thanked for her patience to wait me. I always missed them. I know they are eagerly looking up in the sky for my back to home with success.
Table of contents
1. INTRODUCTION...... 1 1.1. General Background...... 1 1.2. Community Forestry (CF) in Nepal...... 2 1.3. Problems in Sustainable Community Forestry in Siwalik Range...... 2 1.4. Justification of Research ...... 3 1.5. Objectives...... 5 1.6. Research Hypothesis ...... 5 1.7. Research Questions ...... 5 1.8. Conceptual Approach ...... 6
2. LITERATURE REVIEW...... 7 2.1. Sustainable Forest Management...... 7 2.2. Sustainability Assessment ...... 8 2.3. C&I to Assess Sustainability of Community Forestry ...... 9 2.4. Use of RS Data to Discriminate Forest Cover Types and Assess Changes ...... 10
3. METHODS AND MATERIALS ...... 12 3.1. Country Background...... 12 3.2. Selection of Study Area...... 13 3.2.1. Siwalik Range (Churia) of Siraha and Saptari Districts...... 13 3.2.2. Selection of Study Sites (CFUGs)...... 13 3.3. Research Framework...... 15 3.4. Research Methods ...... 16 3.4.1. Sampling Design...... 16 3.4.2. Selection of C&I...... 17 3.4.3. Data Collection...... 19 3.4.4. Data Analysis...... 20 3.5. Research Materials ...... 23
4. STUDY SITES DESCRIPTION ...... 24 4.1. General Description of Study Sites ...... 24 4.1.1. Majhau Community Forest Users Group, Saptari, Nepal...... 24 4.1.2. Jiva Community Forest Users Group, Siraha, Nepal...... 27 4.2. Summary of General Features of Study Sites...... 30
5. RESULTS ...... 31 5.1. Results of Existing Social Condition Analysis...... 31 5.1.1. General Social Condition Analysis ...... 31 5.1.2. Social Indicators Analysis ...... 32 5.2. Result of Existing Ecological Condition Analysis...... 36 5.2.1 Stand Variables Analysis...... 36 5.2.2 Ecological Condition Analysis...... 37 5.3. Result of Relationship Analysis Between Social and Ecological Condition ...... 40 5.4. Result of Remote Sensing (RS) Data Analysis ...... 41 5.4.1 Supervised Classification of study sites’ Forests ...... 41 5.4.2 Supervised Classification of the Surroundings of study sites ...... 44 5.5. Assessment of the Trend in Social Condition ...... 46 5.6. Assessment of the Trend in Ecological Condition ...... 47
6. DISCUSSION ...... 49 6.1. Social Condition Analysis ...... 49 6.2. Ecological Condition Analysis...... 54 6.2.1. Stand Variables Distribution ...... 54 6.2.2. Ecological Condition...... 54 6.3. Relationship Between Social and Ecological Condition...... 57 6.4. Trend in Social Condition ...... 58 6.5. Trend in Ecological Condition ...... 59 6.6. Trend in RS Data and its Comparision with Field Data...... 60 6.7. Problems and Constraints...... 61
7. CONCLUSIONS AND RECOMMENDATIONS...... 62 7.1. Conclusions ...... 62 7.2. Recommendations ...... 64
REFERENCES ...... 65
APPENDICES...... 70 List of Tables SN Tables Pages 1 Table 3.1: Strengths and weaknesses of using MCA to select C&I for community level. 18 2 Table 3.2: Stand variables measured and corresponding plots sizes. 19 3 Table 3.3: Stand variables measured and corresponding analysis techniques. 22 4 Table 3.4: Materials used in different phases of research. 23 5 Table 4.1: Quantities of sold Khair and corresponding income in Jiva. 28 6 Table 4.2: Summary information of study sites. 30 7 Table 5.1: Assessment of social condition of study sites based on locally adjusted 33 indicators. 8 Table 5.2: Descriptive statistics of stand variables. 36 9 Table 5.3: Statistical test of difference for stand variables between the study sites. 37 10 Table 5.4: Assessment of ecological condition of study sites based on locally adjusted 38 indicators. 11 Table 5.5: Forest condition change matrix, Majhau. 42 12 Table 5.6: Forest condition change matrix, Jiva. 43 13 Table 5.7: Assessment of trend in social condition of study sites. 46 14 Table 5.8: Descriptive statistics of stand variables in different years. 47 15 Table 5.9: Assessment of trend in ecological condition of study sites. 48
List of Figures SN Figures Pages 1 Figure 3.1: Layout of sample plots for different stand variables. 16 2 Figure 3.2: Hierarchical structure of P, C, I and Verifiers for the study sites. 18 3 Figure 5.1: User’s awareness status in the study sites. 31 4 Figure 5.2: User’s perceptions on decision-making and benefit sharing system. 32 5 Figure 5.3: Comparative bar chart of social condition between the study sites at 35 criterion level. 6 Figure 5.4: Comparative bar chart of stand composition between the study sites. 37 7 Figure 5.5: Comparative bar chart of diameter distribution between the study sites. 37 8 Figure 5.6: Comparative bar chart of ecological condition between the study sites at 40 criterion level. 9 Figure 5.7: Comparative bar chart showing relationship between social and ecological 40 condition. 10 Figure 5.8: Trend in forest condition at the surroundings, Majhau. 44 11 Figure 5.9: Trend in forest condition at the surroundings, Jiva. 45 12 Figure 5.10: Comparative bar graphs showing trend in regeneration and basal area 47 between the study sites.
List of Maps SN Maps Pages 1 Map 3.1: Map of Nepal showing different physiographic zones. 12 2 Map 3.2: Siwalik range of Siraha and Saptari districts, Nepal: locating study sites. 14 3 Map 4.1: Majhau Community Forest with respect to road network. 24 4 Map 4.2: Jiva Community Forest with respect to road network. 27 5 Map 5.1: Classified images 2001, 1999 and 1992, Majhau. 42 6 Map 5.2: Classified images 2001, 1999 and 1992, Jiva. 43 7 Map 5.3: Classified images 2001, 1999 and 1992 of the surroundings, Majhau. 44 8 Map 5.4: Classified images 2001, 1999 and 1992 of the surroundings, Jiva. 45
List of Flow Charts SN Flow Charts Pages 1 Flow chart 1.1: Logical flow of conceptual framework. 6 2 Flow chart 3.1: Logical flow of research framework. 15 3 Flow chart 3.2: Summary of the process of selection and verification of C&I. 17 4 Flow chart 3.3: Summary of the process of RS data analysis. 23
List of Pictures SN Pictures Pages 1 Picture 4.1: User bringing grass from Community Forest, Majhau. 26 2 Picture 4.2: Uncontrolled firewood collection in side the forest, Jiva. 29
List of Appendices SN Appendices Pages 1 Appendix 1: Criteria to be met to form (handover) Community Forest in Nepal. 70 2 Appendix 2: Relevant set of C&I adopted from different authors. 70 3 Appendix 3: Locally adjusted indicators for the study sites. 72 4 Appendix 4: Questionnaire (Check list for semi-structured interview). 75 5 Appendix 5: Data sheet for office record review. 77 6 Appendix 6: Data sheet for social data 2001. 79 7 Appendix 7: Data sheet for inventory data 2001. 81 8 Appendix 8: Data sheet for inventory data 1998. 83 9 Appendix 9: Data sheet for inventory data 1995. 83 10 Appendix 10: Measuring basal area using Relascope. 84 11 Appendix 11: Sample point’s distribution. 85 12 Appendix 12: Accuracy assessment (confusion matrix) of classified images 2001. 85 13 Appendix 13: Trend in forest cover classes in the study sites. 86 14 Appendix 14: Histogram of classified images (surroundings). 87 15 Appendix 15: Feature space of training sample. 88
List of Abbreviations AFO: Assistant Forest Officer CBS: Central Bureau Of Statistics CF: Community Forestry CFUG: Community Forest Users Group ChFDP: Churia Forest Development Project C&I: Criteria and Indicators DF: Department of Forest DFO: District Forest Office FUG: Forest Users Group GIS: Geographical Information System GPS: Global Positioning System HH: Household HMGN: His Majesty’s Government of Nepal ILWIS: Integrated Land and Water Information System MFSC: Ministry of Forests and Soil Conservation MPFS: Master Plan for Forestry Sector RRA: Rapid Rural Appraisal RS: Remote Sensing (Remotely Sensed) TROF: Tree Resources Outside the Forest NTFP: Non Timber Forest Products
CHAPTER 1: INTRODUCTION
1. INTRODUCTION
1.1. General Background Forest is an essential natural resource for the livelihood of rural people in the developing countries where it serves significant contribution to national economic as well. Increasing population has led to increase demand of forest resources and ultimately become scarce day after day. A large number of initiatives and actions have been implemented to meet increasing demand and control overexploitation of the forests. But it is fair to say that most programs have gone through a pattern of getting launched with much fanfare and unrealistic claims about their potentials. Nevertheless, two types of tree planting programs have accomplished tangible results: plantation forestry and tree planting out side the forests described by agro forestry and related variants such as social and Community Forestry (Nair, 1998).
Community Forestry (CF) evolved out of the realization that conventional forest management in developing countries is incapable of and inefficient for active people’s participation in forest conservation (Repetto, 1988 cited in Baral, 1998). Main characteristics of the CF are that it: recognizes the intimate relationship of people and forests; recognizes indigenous forest management systems; aims to meet the basic needs of forest products of the users; focus on increasing the benefits from forests for local people, especially women and disadvantaged groups; and involves local people in project identification, design, implementation, monitoring and evaluation (FAO, 1989). Sustainability is a first requirement for CF management systems. Any CF management system must be long-term, productive and should guarantee a stable, high and preferably diverse production of interests to the villagers. Likewise, support to CF activities must be sustainable and aimed at making the activity self-sustaining (Melnik, 1992).
To be able to apply the concept of sustainable management as clearly and simply as possible, it has been necessary to describe it in terms of guiding principles, criteria and corresponding indicators. In this regard, the results of international initiatives (ITTO, 1992; Helsinki, 1995; Montreal, 1995) are significant (Varma, et al. 2000). Based on those initiatives, several criteria and indicators (C&I) have been compiled to assess sustainability. Ritchie et al. (2000) reported that C&I can help organize local and scientific knowledge in such a way that it can be used as a forest and forest management health check. However, comparatively little work has been done to implement them to achieve sustainability.
Nevertheless, some countries including Nepal have incorporated basic sustainability principles in their forest management system. CF policy and guidelines in Nepal are based on sustainability concept. It is widely believed that CF has shown promising results in ecological, economic and social fronts and is leading towards sustainability. However, experiences and results are not same all over the country. To understand the problems related to CF and its sustainability issue, it is necessary to understand its background in Nepal.
1 CHAPTER 1: INTRODUCTION
1.2. Community Forestry (CF) in Nepal Nepal has experienced various rules, regulations and policies to conserve and manage the forest resources. The Master Plan for the Forestry Sector (MPFS) approved by the government of Nepal in 1988 was a very important step towards the CF in Nepal with strategy of sustainable management. MPFS is a 25 years plan for forest development that recognized CF as an essential forest management approach for Nepal. Regarding the strategies made by the MPFS, a new forest regulation was introduced in 1993. The forest regulation 1993 legislated CF Policy in Nepal.
According to the Forest Act 1993, ‘Community Forest is a part of national forest that is handed over to user group for management and utilization for collective benefit’. The Act specifically recognizes Community Forest User Group (CFUG) as a legal entity and makes provision for its formation and administration. Although the land ownership of CF is under the government, forest products belong to the CFUG. CFUG have full authority to decide on protection, development, management and utilization of the resources. Each user group must prepare an operational plan (OP) with the help of the District Forest Office (DFO). Constitution for CFUG is also compulsory to be prepared, which describes rights and responsibilities of the users. The operational plan is usually developed for five years with detail of the forest condition, species, existing stock and different blocks with different management scheme. It is a guideline as well as calendar of activities for the people to manage their forest in sustainable basis meeting their needs. Moreover, it also serves as base to assess change at the end.
The Department of Forest (DF) has implemented this policy in most part of the country. Shrestha, (2000) has reported, “By the end of the 1999, more than 750,000 ha of the national forests have been handed over to more than 9,000 CFUGs”.
1.3. Problems in Sustainable Community Forestry in Siwalik Range CF in Nepal has already passed its infant stage of development and now has entered in to its young stage of development. However, several problems relating to its sustainability has been realized. Deforestation is still a major problem. Population pressure, increasing demand for people’s subsistence such as land, fuel wood, fodder and new settlements are major factors leading to deforestation.
However, the problems are not same everywhere. It has been realized that managerial problems of forest in Terai and Siwalik is very prominent than in the Midhills. Siwalik is very fragile series of several ridges starting from the Terai (lowland). It is an immediate (major) watershed of most part of the Terai. People from Terai have depleted it over the years because of overexploitation. Immigrants from Midhills have also depleted it. The area is characterized by very high incidence of poverty caused by the rapid growth of population. Forest resources are also depleted quite rapidly because of high consumption of firewood and timber smuggling (GTZ, 1996).
Furthermore, identifying users in Siwalik has many different and difficult problems than in the Midhills. Traditional users of the forest have been pushed away from the forests and people who claim to be users often happen to be the encroachers of the past. The society is heterogeneous with big gaps between rich and poor. Off-farm income and market forces control rural economy. All these factors acting together tend to make little room for consensus based community management of forests (Karki & Tiwari, 1998). As a
2 CHAPTER 1: INTRODUCTION consequence, the process of CF implementation is slow and the management has not the same momentum as in the Midhills.
Nevertheless, several attempts have been done to implement CF in Siwalik range. At the time, while CF intervention in Terai was experiencing problems, experiences in Siwalik were positive in terms of rehabilitation of the degraded forest. In addition, changes in forest cover of this area have been experiencing after the implementation of Churia Forest Development Project (ChFDP) with technical and financial support of the GTZ in 1995. Baral & Subedi (2000) have reported that degraded Siwalik forest has being improved and deforestation has being decreased, but unintended social anomalies have arisen. They found that elite person always hold control over the committee and manipulate the situation in their favor. The normal trend in CF has shown that the elite members of the society tend to take all positions of the executive committee and make decisions regarding harvest, product distribution and mobilization of fund accrued. Other members of the group are least involved in the overall process and have virtually no idea whatsoever related to harvest and the financial matters of their community forest.
In addition, it has often been reported that the driving force has been to make money out of the commercially viable forest rather than to build a common ground for the community management of forests. The Forest Act 1993 and Forest By-law 1995 have stipulated the provision of handing over but the forestry policy 1988 (MPFS) is not very precise in this particular matter (Baral & Subedi, 2000).
Moreover, the ninth five-year development plan of the government for Siwalik has created doubt regarding continuation of CF in Siwalik range. The ninth five year development plan (1997-2002) says, “Priority should be given to soil conservation activities in the Siwalik range,” It indicates that existing CF approach is not able to control soil erosion and ecological degradation in Siwalik range.
1.4. Justification of Research From the above, it is clear that there are several doubts and debates regarding the sustainability of the CF in Nepal. It is more prominent in Terai and Siwalik region than in the Midhills. Some Community Forests have been shown positive results and seemed sustainable, but others have found not so enthusiastic. It indicates that site-specific factors are responsible for that. Hobley (1996), Kashio (1998) and Pokharel (1998) have also reported site-specific factors affecting sustainability. It justifies the need of site-specific assessment to assess impacts brought by the management regime being implemented. Furthermore, Pokharel (1998) has justified the need of considering both social as well as ecological criteria and corresponding indicators equally while evaluating the outcome of resource management.
Most of the studies such as Yadav & Branney (1999); Baral (1998); Bartlett et al. (1992); Kandel (2001) conducted in this regard on CF in Nepal have focused in Midhills. Some studies such as Baral & Subedi (2000); Paudel (2000); Khanal (2001); Pokharel (1998) in recent days have been conducted in Terai region also. Khanal (2001) tried to analyze stockholder’s conflicts and its impacts in CF management in Terai region. Similarly, Kandel (2001) and Paudel (2000) have attempted to find out some factors (criteria) and conditions to evaluate the potential and scope of the community based leasehold forestry in the Midhills and CF for the Terai respectively.
3 CHAPTER 1: INTRODUCTION
However, none of them have paid attention about the problems and prospective of sustainability of CF in Siwalik range. Furthermore, none of them have looked and analyzed the relationship between social and ecological factors affecting sustainability. Poteete & Ostrom (2002) argue that comparatively little effort has been devoted to studying conditions under which people have maintained and even enhanced forest conditions through their stewardship. Therefore, it is essential to analyze the relationship between social and ecological factors to understand the complexity of the sustainability of CF. The important question should be answered is: What conditions favor the development and survival of institutions that regulate forest use in a sustainable manner? The unintended social anomalies as reported by Baral & Subedi (2000) should be addressed and correlated with its consequences in ecology. Assessing existing social as well as ecological indicators with respect to its initial condition could resolve those issues. Furthermore, assessment could also identify the relationship between those factors (social and ecological) and its consequences to the sustainability of CF. It is also important to understand underlying causes and consequences of institutional factors (Poteete & Ostrom, 2002).
In addition, Remote Sensing (RS) data with appropriate Geographical Information Systems (GIS) techniques can be used to further justify the relation in terms of saving time and money. As the forests cover large areas that are difficult to assess, a combination of RS and GIS can supply suitable tool for acquiring continuous changing information (Sader et al., 2001; ICIMOD, 1999). For example, Normalize Difference Vegetation Index (NDVI) of different periods gives the trend of changes in quality of the vegetation (Lyon, 1998). Multi-band combination and supervised classification (independently) of images taken in different periods (years) are commonly used image processing techniques to assess the trends by superimposing and comparing them. Interpretation of trends is an essential part of the plan- do –monitor loop referred to the earlier. If the cause of the trends in collected data is known, then appropriate responses can be made. However identify causes is rarely simple (Dymond et al., 2001). If causes and their significant relation with RS data are identified, then RS data can be more efficient, cost effective and desirable to repeatedly monitor the forest and it’s different parameters over large area. It can also be considered as one of the major indicators of sustainability with reflecting ecological condition of CF cost effectively.
This research analyzes the social condition and its consequences in social as well as ecological sustainability of the Community Forestry. It also identifies the relationship between social and ecological condition of CF by assessing indicators and trends of respective condition overtime. In addition, it uses RS data to find the changes in forest condition. Comparison is performed to find the relationship between trends obtained from RS data and trends in social and ecological condition over time.
Output of this research is used to evaluate the sustainability of existing CF management approach in Siwalik range. It helps to establish effective self-monitoring system through the indicators developed on the basis of their own management plan that may be replicable in future. In addition, it also helps to resolve the contradiction regarding the relationship between social and ecological sustainability of CF. It is very useful to local people adjusting their management regime towards sustainable management. Furthermore, it also helps DFOs, planers, policy makers and researchers to understand and incorporate RS data to assess sustainability of Community Forestry.
4 CHAPTER 1: INTRODUCTION
1.5. Objectives 1) To assess and compare the sustainability of two Community Forest Users Group in Siwalik range by analysing social indicators. 2) To assess and compare the sustainability of two Community Forests in Siwalik range by analysing ecological indicators. 3) To identify the relationship between social and ecological condition of the Community Forestry. 4) To identify and compare the changes in forest condition using satellite imagery.
1.6. Research Hypothesis 1) There is significant positive trend in social condition of Community Forests Users Group’s towards sustainability. 2) There is significant positive trend in forest and other ecological condition of Community Forests towards sustainability. 3) Social and ecological conditions of Community Forestry are significantly correlated with each other. 4) Remote sensing data (satellite imagery) significantly reflect the trend of forest condition.
1.7. Research Questions 1) What is the trend in social condition for each Community Forest Users Group? 2) Which Community Forest Users Group is more sustainable based on social indicators? 3) What is the trend in forest and other ecological condition for each Community Forest? 4) Which Community Forest is more sustainable based on forest and other ecological indicators? 5) Is there any relationship between social and ecological condition of the Community Forestry? 6) What is the trend in forest condition observed on satellite imagery? 7) Is there any difference between the trends obtained from field indicators (social and ecological) and satellite imageries? If yes, what may be the reasons?
5 CHAPTER 1: INTRODUCTION
1.8. Conceptual Approach Practical problems regarding sustainable implementation of CF in Siwalik range in Nepal are the factors inspiring to design this research. This conceptual approach starts with CF Policy and its effective implementing practices in Nepal. Social as well as ecological condition of the area before hand over to the people can be a threshold to assess changes in future. Those changes can be analyzed to assess sustainability of the approach being implemented. The logical flow of the conceptual approach of this research is given below in flowchart 1.1.
CF Policy in Nepal
Social condition Ecological condition (initial) (initial) RS data Need of CF
CFUG constitution CFUG operational plan (Social management criteria) (Ecological management criteria)
CFUG formation
Implementation Ecological changes Social changes
Sustainability issue Social indicators Ecological indicators
Need of assessment
Assessment Assessment
Results RS data
Conclusion
Flowchart 1.1 Logical flow of conceptual framework
6 CHAPTER 2: LITERATURE REVIEW
2. LITERATURE REVIEW
This chapter deals with review of several literature on sustainable management of Community Forestry. The review focuses on concept of sustainable forest management, way of assessing sustainability, C&I to assess sustainability and use of RS data to discriminate and assess changes in forest condition that are related to the objectives of this research.
2.1. Sustainable Forest Management
Sustainable development concept was elaborated by the World Commission on Environment and Development in 1987, and endorsed by the United Nations Conference on Environment and Development (UNCED) in June 1992. Since then, it has become the most important issue in the development aspirations of the 1990s. In the forestry sector, this concept has triggered a review of the traditional forest management systems, under which the natural forests have been continuously degraded and deforested (Kashio, 1998). Sustainable forest management has been described as forestry’s contribution to sustainable development. This is development, which is economically viable, environmentally sound and socially beneficial and which balances present and future needs.
Socially beneficial Economically viable
Sustainable
management
Ecologically sound
Sustainable forest management is the forestry component of sustainable development. Different authors have defined it in different way. ITTO (1998) has defined as “Sustainable forest management is the process of managing forests to achieve one or more clearly specified objectives of management with regard to the production of a continuous flow of desired forest products and services, without undue reduction of its inherent values and future productivity and without undue undesirable effects on the physical and social environment”.
However, in the context of this research, the definition proposed by Prabhu et al., (1999): ‘A set of objectives, activities and outcomes consistent with maintaining or improving the forest’s ecological integrity and contributing to people’s well-being both now and in the future’ has been used.
According to Higman et al., (1999), sustainable forest management must define balance of different management objectives that they are aiming to achieve. It also means that objectives of forest management will change over time as different forest products and services become more valued or less
7 CHAPTER 2: LITERATURE REVIEW desirable. The implication and operational significance of the sustainable forest management have changed with time as a result of changing social needs and values regarding forest resources.
The concept of sustainable forest management does not relate exclusively to forest as ecological systems, but to forest as human influenced environments that are in many respects subordinated to the socio-economic environment (Chorley, 1973 cited in Weirsum, 1995). Consequently, the norms for sustainability in forestry may relate to both ecological and social characteristics, as well as to the reciprocal relations between these categories. Thus, achievement of sustainable forest management ultimately depends upon the reconciliation of different social values with respect to forest resources (Weirsum, 1995). In this regard, CF has been emerged as an important achievement towards the sustainable management of forest resources focusing both social as well as ecological issues.
2.2. Sustainability Assessment Sustainability is an effectiveness of the management approach being implemented to achieve defined goals. It should be measured and analyzed to know whether things are getting better or worse. However, questions of effectiveness require specification of the criteria suitable for the defined goals, objectives and actors involved.
Several methods have been developed and tested to assess changes by different authors. Development of Criteria and Indicators (C&I) has been resulted significant tools for assessing trends in forest condition and forest management. C&I provide a common framework for describing, monitoring and evaluating progress towards sustainable forest management and implicitly define in (Prabhu et al., 1998). International efforts to develop criteria and indicators of sustainable forest management reflect a growing recognition that human interventions can promote the sustainability of forest (Poteete & Ostrom, 2002).
The international Tropical Timber Organization (ITTO) Japan, introduced the C&I concept and terminology in 1992. Since then several organizations and professionals have worked together upon the process of generating and testing appropriate C&I to suit their own condition. Some other important institutions working on international level are Forest Stewardship Council (FSC), Center for International Forestry Research (CIFOR) Indonesia and Regional Community Forestry Training Center (RECOFTC) Thailand. Three main conceptual tools constituting the important components of the C&I framework are namely: Principles, Criteria and Indicators.
Principles: A fundamental truth or law as the basis of reasoning or action. Principles in the context of sustainable forest management are seen as providing the primary framework for managing forests in a sustainable fashion (Mendoza et al., 1999).
Criterion: “An aspect that is considered important by which sustainable forest management may be assessed” (ITTO, 1998). The criteria constitute a set of key elements that define the scope of the concept of sustainable forest management. “They are standards by which our progress towards meeting the principles can be judged”
8 CHAPTER 2: LITERATURE REVIEW
Indicator: “A quantitative, qualitative or descriptive attribute that, when periodically measured, indicates the direction of the change” (ITTO, 1998). Indicators are the components or variables of the forest or management system that imply or indicate the state or condition required by criterion (Ritchie et al, 2000).
Verifiers: Verifiers are the data or information needed for assessing an indicator (Ritchie et al., 2000). They define the specific details that would show whether an indicator is met.
2.3. C&I to Assess Sustainability of Community Forestry Since CF is essentially about sustainable management of both people and resource, both institutional and ecological criteria must therefore be considered equally when evaluating the outcome of management. For CF to be implemented sustainably through users group, users group themselves need to be sustainable and capable of implementing the provision of operational plan.
Complexity of common property institution has often been realized as a serious constraint to assess impacts. One of the main challenges facing social assessors is to understand how communities may be impacted by a particular policy or proposal, and how they may respond to this change (Coakes et al., 1999). However, several authors involving CF development have been developing and using different approaches to assess the effectiveness of management regime being implemented.
Ostrom (1990) has highlighted the essential factors to assess the success institutions involving common resources management. She tried to establish why it is that collective action groups in some common property systems create solutions and therefore resist the “tragedy of the commons” while other collapse. She describes eight “design principles” which she believes are the essential elements or conditions that help to account for the success of collective action. Hobley (1996) has argued that the indicators for well functioning organization depend on the perspective from which the organization being assessed. For example, an organization dominated by the male elite could be considered to be successful from the traditional forester’s point of view; if, however, those whose livelihoods are dependent on access to the forest being denied it and are suffering as a consequence, perhaps this is then a failure. She has listed some indicators of institutional maturity for comparative analysis (see Hobley, 1996 for detail).
Varma et al., (2000) have attempted geographic information system-based multi-criteria evaluation technique for measuring sustainability of forest management. It integrates and utilizes spatial and temporal data on diverse ecological, economic and social variables, while handling data and decision- rule uncertainty. Pokharel (1998) has given more attention on equity and effective forest resource management. Technical aspect of resource management should also be accounted as an important indicator to optimize the production capacity of the resource. Furthermore, James & Karen, (1997) and Poteeto & Ostrom, (2002) have explained important attributes of the resource, resource users and established institution to manage the resource that can be used to assess effectiveness of Community Forestry. Relevant set of C&I for this study adopted from different authors described above are given in appendix 2.
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2.4. Use of RS Data to Discriminate Forest Cover Types and Assess Changes RS data have been used for the change detection from several years. The basic premise of the change detection through remote sensing is that the spectral signatures change commensurate with the change in the land cover (Roy, 1999). Different objects in the earth surface have different reflectance characteristics, on the basis of which discrimination of them and their extent and quality is possible. Discrimination of different forest types from RS data is one of the most important applications of RS and has been proved as very useful and cost effective tool. RS data are snap shot record of real world situation at one point in time. Therefore, RS data taken at different dates form a basis for change analysis. It has played a pivotal role in generating information about forest cover, vegetation type and land use changes (Roy 1999).
The reflectances of the green vegetation in different portion of the spectrum are different. Ideal reflectance curve of vegetation shows highest reflectance in the near infrared (NIR) portion of the spectrum. It also depends on the leaf development stage and cell structure. In the middle infrared, the free water in the leaf tissues mainly determines the reflectance; more water results in less reflectance (Bakker et al., 2000).
However, discriminating plant species with their unique identification from the curve is difficult because of the numerous problems present in the real world measurement such as angle of view, atmospheric properties, spectral mixture, moisture content and illumination angle (Cochrane, 2000). Variance can occur within a species due to microclimates, soil characteristics, precipitation, topography and a host of the other environmental factors. In addition, stress factors such as air pollution, heavy metals and drought can change the spectral properties of the foliage (Price 1994). At the time of leaf shedding there is no photosynthesis causing more reflectance in red band and reflectance in NIR may decrease.
Nevertheless, RS data has been used successfully for vegetation stratification by several authors. According to Roy (1999), forest vegetation types are classified based on physiognomy, structure function, composition, and distinction of woody tissue. Different studies carried in this regard have demonstrated and concluded that RS data can be used to stratify based on following criteria:
• Phenological types such as function of leaf duration (e.g. evergreen, semi-evergreen and deciduous) • Major communities and gregarious species (e.g. Sal, Dipterocarpus, Pines, Teak, Bamboo, Oak) • Vegetation types of unique environmental set-up (e.g. mangroves, shoals, riverine, alpine etc.) • Canopy closure expressed as forest density (e.g. encroachments, and different density levels)
Extraction of information from RS data require appropriate image processing techniques. Which type of image processing techniques will be useful depends on what information is needed. For example, vegetation index is an image processing techniques to measure the vegetation vigor. The most commonly used vegetation index on vegetation studies is NDVI (Lyon, 1998; Nelson, 1983; Tucker, 1985). The NDVI suppresses differential solar illumination effects of slope and aspect orientation and helps to normalize differences in brightness values when processing multiple dates of imagery (Singh, 1986; Lyon, 1998).
10 CHAPTER 2: LITERATURE REVIEW
Classification is one of the common techniques to discriminate different cover types. It also serves to assess changes by super imposing and comparing classification of the image taken in different period. Basic assumption for image classification is that specific parts of the feature space correspond to the specific class (Bakker et al., 2000). In post classification change detection, two images from different dates are independently classified and labeled. The area of change is then extracted through the direct comparison of the classification results. Although this method is not critically affected by level of image registration, co registration, and there is no need for any type of scene-to-scene radiometric normalization, accuracy of the classification is critical. It depends upon the selected classifier and quality of training classes. It is often reported that post classification change detection methods have relatively low accuracy (Lunetta & Elvidge, 1999). Visual interpretation of images with different band combination also gives the impression of the condition of forest and its trend.
However, RS data alone is usually not sufficient in order to analyze the nature of change. Integration of RS data and ancillary data in a GIS environment can increase the accuracy of image analysis (mapping) (Molenaar, 1991 cited in Shrestha & Zink, 2001). Agenda 21 of the United Nations Conference on Environment and Development (UNCED) 1992 emphasize sustainable forest management as a condition for sustainable development. UNCED have concluded that the combination of field data, local knowledge and information derived from RS data are a prerequisite for effective monitoring and efficient management which can be supported by the use of geographic information systems (Venema, ND; De Gier et al., 1999). Lillesand & Kiefer (1994) have argued that the RS image with appropriate processing and interpretation process complements, rather that replaces, the field activities.
11 CHAPTER 3: METHODS AND MATERIALS
3. METHODS AND MATERIALS
This chapter deals with the methodology applied for conducting the research. Chapter consists the country background, selection of study area, research approach, research methods and required materials. Research methods are describing in three different steps: sampling design, data collection and data analysis.
3.1. Country Background Nepal is a small mountainous country situated between China and India. The total area of the country is about 147,181 km². On the basis of altitude from mean sea level, the whole country is divided in to five major physiographic zones (Map 3.1): High Himal (2500-8848m) covers about 23% area, High Mountain (2000-2500m) covers 20%, Middle Mountain (700-2000m) covers 30%, Siwalik (300-700m) covers 13% and the Terai (< 300m) covers 14% area of the whole country (MPFS, 1988). Because of high variation in altitude with varied topography there is wide variation in climate.
Map 3.1: Map of Nepal showing different physiographic zones.
The distribution of vegetation is also to large extent determined by altitude and climate. Forest covers about 4.27 million ha (29%) area of the country. About 1.56 million ha. (10.6%) of the country’s area is covered by the scrubland (DFRS, 1999). About 16% of the total area is cultivated. Total population of the country in 2000 was estimated to be around 22.9 million and the growth rate was about 2.4% per year. More than 90% of the rural populations are depending on fuel wood for their daily energy. Consumption of fuel wood is predicted to be double in terms of absolute quantities during the period
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1980 to 2010, without any substitute foreseen in the near future (CBS, 2000). Because of the increasing population and their demands indeed, for subsistence livelihood, Nepal is facing sever deforestation problems. Annual deforestation rate has been reported about 0.4%, since 1965. Most of the deforestation is happening in the Terai forest, which is flat lowland having commercially important forest tree species. Annual deforestation rate in Terai is 1.3% (HMGN, 1998).
3.2. Selection of Study Area
3.2.1. Siwalik Range (Churia) of Siraha and Saptari Districts Main objective of this study was to assess sustainability of CF in Siwalik range of Nepal. Regarding objectives and available time, study should be focused on particular area of the Siwalik range. Siraha and Saptari districts, where CF development program has already been implemented for several years, were appropriate areas to be selected for this study. Furthermore, accessibility, availability of required data, and familiarity with the area to complete fieldwork within available time also had to be taken in to account while selecting the study area.
Siwalik range covers 23% (595 km²) area of both Siraha (1228 km²) and Saptari (1359 km²) districts. Climate of this area is sub-tropical hypothermic. It comprises people of different cultures and communities with high diversity in their needs and interests. Siwaliks are fragile and geologically unstable series of low; hog back ridges at the north part of the districts extending from east to west, where most of the districts forest confines. Increasing population in Terai and their demand for forest products results in degradation of the Siwalik forest and creates several ecological problems (DFO, 1999/2000). Any ecological disruption in this region results in an imbalance in the ecology of not only Siwalik but also the Terai lowlands as a whole. In addition, new settlements inside the forests have been making the situation even more critical.
Main tree species are Sal (Shorea robusta), Khair (Acacia catachu), Saj (Terminalia tomentosa), Jamun (Syzygium cumini) and Sissoo (Dalbergia sissoo). Most of the forest areas (mostly degraded) have already been handed over to community as CF. According to the Churia Forest Development Project, (working at that area since 1992) 97 Community Forests have already been handed over in both districts covering 10432 ha. Most of them are in Siwalik range and several others are in process of being handed over.
3.2.2. Selection of Study Sites (CFUGs) Considering available time and stated objectives, it was decided to select two CFUGs as study sites in such a way that assessment and comparison of their sustainability could meet the stated objectives. Selection of two study sites (CFUGs) was done in two phases. At first, all CFUGs in the Siwalik range were divided into two groups i.e. CFUGs that have passed at least one working plan phase (5 years) and not passed. It was because, CF rules and regulations developed by the Ministry of Forest and other CF development projects working in Nepal have recognized five years period as a period of a working plan. CFUGs that have already passed at least five years were further grouped into two classes on the basis of existing resource management approach i.e. individual plot management and usual group approach.
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There are some user groups, in one hand, dividing their Community Forest in small plot for each household (HH), where corresponding user is fully responsible to protect and utilize resources under approved operational plan. Some, on the other hand, managing their forest as usual group approach. It has been realized that those different approaches have different impacts in community and their forest. Districts Forest Offices Siraha and Saptari, Churia Forest Development Project (ChFDP) and other related stakeholders were consulted in this regard before making decision. Regarding the objectives, discussions were made to find appropriate way to select two CFUGs. Consulted stakeholders agreed to make two groups on the basis of the conditions mentioned above. Lastly, existence of time series data that were essential for trend analysis was also considered. For this, reliability of adopted sampling design and data collection method were considered (in previous sampling). On the basis of which, two CFUGs (one from each) were finally selected as study sites. Both of them had inventory data taken at same year (1998) and with same sampling method.
Selected two CFUGs are: Majhau Community Forest Users Group, Mahuli, Saptari and Jiva (Ramnagar khoria) Community Forest Users Group, Siraha. Map 3.2 given below shows the location of the study sites. (Detail descriptions of study sites are given in chapter four).
Siwalik range Jiva
Majhau
Siwalik range
Source: ChFDP
Map 3.2: Siwalik range of Siraha and Saptari districts, Nepal: locating study sites.
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3.3. Research Framework In order to manage the research work in proper way within limited time and available resources, this research work was divided in three different phases: preparation, field work and post field work. Literature review, image processing and field preparation were main activities in the preparation phase. Required ground truth data were collected in the fieldwork. Collected data were rearranged, tested and analyzed using different test algorithms to answer the research questions at post fieldwork phase. The flow chart of this research framework is given below in figure 3.1.
Research conceptualisation • Literature review • Identification of research issue
Research proposal • Back ground issue • Justification • Objectives and questions formulation • Research design
Data requirements • Remote sensing (RS) data • Generic C&I from literature • Primary data (social & ecological) • Secondary data
Sampling design • Image processing Simple random sampling Selection of C&I • Geo-reference Sampling methods • Multi Criteria • • Band combination Social data: RRA tools Analysis (MCA) • • NDVI Ecological data: plot measurements
Data analysis: • Social data: Data management, coding, triangula- tion and scoring indicator. • Ecological: Data management, normality test, t test, M-W test, triangulation, scoring indicators • RS data: Classification based on sampling data, secondary data and familiarity. • Trend analysis: “The sign” test. • Analysis of relationship: Chi-square test.
Result: • Analysis of results (discussion) • Conclusions & Recommendations
Flowchart 3.1: logical flow of research framework showing different steps and activities.
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3.4. Research Methods Since this research intends to assess sustainability of CF using different predefined C&I, it is a kind of criterion sampling. According to Patton (1988), ‘the logic of criterion sampling is to review and study all cases that meet some predetermined criterion of importance. The point of criterion sampling is to be sure to understand cases which are likely to be information rich because they may reveal major system weaknesses which become targets of opportunity for program or system improvement’. Sampling was designed regarding C&I to be measured and information need to be verified them. Social, ecological and RS data were needed in this regard. Each data belongs to different statistical population i.e. CFUG is the population of social data and the forest managed by CFUG is the population of ecological data. Different population requires different research methods to extract reliable information. Different steps of research and corresponding methods are describing in following paragraphs.
3.4.1. Sampling Design Sampling design for social data: Social conditions such as management system adopted, people’s perception toward CF and conflicts indicate the level and trend of sustainability of management regime being implemented. Regarding nature of social data, sampling was designed in two different ways: random HH selection and purposive visit. At least 15 HH were planned to visit in each study sites. All HH in each study site were numbered and multiplied by random numbers generated in pocket calculator for HH survey and semi-structured interview. Some additional HH of marginalized people were also selected if they were not in random selection. It is because; most of the marginalized people depend on forest for their livelihood. Their involvement and perception towards the CF and its management system play great role in sustainable Community Forestry. DFO Siraha, ChFDP Lahan and user group offices were also listed to visit for additional information that was mostly used for data triangulation.
Sampling design for ecological data: Required sample size and method are based on the objectives, desired accuracy, available time and other resources (Freese, 1984)). Considering available time and other related resources for fieldwork, 30 plots in each area i.e. 60 sample plots in total were selected. Simple random sampling was used to select sample points. Because, it is the most used sampling design where each possible combination of ‘n’ sampling units from the population of N units has equal chance of being selected (De Gier, 2000). Random numbers generated in hand calculator were used to find random coordinates for sample points using B (r=7.98m) following formula: X = Xmin + (Xmax - Xmin)*RN, A
Where X = Easting coordinate of the point r=1.78m Xmax = maximum Easting coordinate, Xmin = minimum Easting coordinate of the study area and RN= random number Y = Ymin +(Ymax - Ymin)*RN, where Y = Northing coordinate of the point, Y max = maximum Northing and Y min = minimum Figure 3.1: Layout of field sample Northing coordinate of the study area. plots for different stand variables. Selected coordinates were loaded in GPS to locate in the field. Sample points were located with the help of topographic map of the area and GPS. Before going field, selected sample points were located in topographic map, which helped to get idea about the location and determine easy way to find in the
16 CHAPTER 3: METHODS AND MATERIALS field. Local field assistances were consulted for this. Circular sample plots, which are easy to layout, common and widely used, were used to measure different stand variables. Furthermore, circular plots have fewer perimeters or have largest ratio of the area to its perimeter, which reduces the probability of the borderline variables (Spurr, 1952). Figure 3.1 shows the sizes of sample plots adopted i.e. radius (r) = 1.78 m for seedling and 7.98 m for sapling (adopted from Seppanen & Weikberg, 1995).
3.4.2. Selection of C&I Although several types C&I have been developed to assess sustainability of forest management, in practice, however, only a limited number of indicators can be used which are sensitive to spatial and temporal changes and also meet the requirements of ease of data collection and application (Liverman et al., 1998). Lanly (1995) in Varma et al. (2000) has reported that the criteria of sustainability are applicable both locally and at higher planning levels. It is not happened for the indicators. Some may be common to different levels, but others are more relevant at the local level.
Since there were no standard sets of C&I developed for the area, selection of C&I to be used for assessment was started with the selection of some relevant C&I from different literature (see appendix 2). Those C&I were compared with the national level Community Forestry guidelines (see appendix 1) and re-phrased some indicators to fit with objectives and approach of CF management in Nepal. Lastly, the list of C&I were further verified and adjusted according to the local condition in the study area for their compatibility with management objectives and other prevailing local conditions. Existing CF management plans and constitutions were reviewed. Some indicators and most of the verifiers were re- phrased and adjusted ensuring their appropriateness to assess sustainability at community level. It was also essential to test the validity of indicators regarding objectives of the study. Different experts involved in CF at that area i.e. DFO, ChFDP staff, rangers and community members were consulted for this purpose. Indicators were ranked based on relative importance using Multi Criteria Analysis (MCA) approach. MCA approach is a tool to evaluate the relative importance of all C&I involved, and reflect their importance in the final decision-making process (Mendoza et al., 1999; Mendoza & Prabhu, 2000). Indicators are judged by their degree of importance and are then given ranks accordingly. Summary of the selection and verification process for C&I is given below.
• Research objectives Secondary sources on
• Background information Select initial Prin- generic C&I ciples, C&I
Verified and adjusted with national guidelines of Nepal
• Local stakeholders Select, rephrase and rank C&I accord-
• Field condition ing to relative importance
Final set of P, C&I Define verifiers
Develop decision rules for final assessment
Flowchart 3.2: Summary of the selection and verification process for C&I.
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In total 14 indicators under five criteria and one principle were selected for each of social and ecological assessment. Because of similar socio-economic condition, biophysical condition and management objectives, the same set of criteria, indicators and verifiers were used for both study sites. Hierarchical structure of defined Principal, C&I is given in figure 3.2. Data collection format and questionnaire that had been developed before going field were also changed according to final set of C&I. Detail set of C&I in hierarchical structure are given in appendix 3.
Ecological sustainability of CF is assured Social sustainability of CF is assured. Principles
C1 C2 C3 C 4 C5 Criteria C 1 C 2 C 3 C 4 C 5
I I I I I I I I I I 1.1 2.1 3.1 4.1 5.1 1.1 2.1 3.1 4.1 5.1 1.2 2.2 3.2 4.2 2.2 3.2 4.2 5.2 1.3 3.3 2.3 3.3 4.3 5.3 3.4 Indicators 2.4 3.5 3.6
V V V V V Verifiers V V V V V
Figure 3.2: Hierarchical structure of Principles, Criteria, Indicators and Verifiers for the study sites.
Strengths and weaknesses of using MCA method to define C&I for community level: Using MCA to select and adjust C&I for forest management unit level (community level) has its own strengths and weaknesses. The strengths and weaknesses of using multi criteria analysis (MCA) method are given in table 3.1 below.
Table 3.1: Strengths and weaknesses of using MCA to select C&I for community level. In addition to researchers experience, some points are adopted from Prabhu et al., (1999) and Mendoza et al., (1999).
Strengths: Weaknesses: • Capability to accommodate multiple criteria • Decision-making requires consensual in the analysis. agreement amongst the various interest • It allows the direct involvement of multiple groups, which may be difficult to achieve. experts, interest groups and stakeholders. • The C&I used must cover the full range of • Analysis is transparent to participants. diverse goods and services provided by the • MCA includes mechanisms for feedback forest. concerning the consistency of the • Risk of generating wrong decision because of judgements made. hiding some negative aspects of the • It allows for the incorporation of both management system by the local qualitative and quantitative information. stakeholders. • Produce valid set of C&I based on their • Chances of subjective bias while ranking relative importance. indicators. • Verifiers may not be replicable. • Verifier may not be transferable to other sites.
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3.4.3. Data Collection Required data to answer the research questions were collected during fieldwork. Different types of data were needed to answer different research questions. Therefore, different data collection methods were applied according to source and nature of the data.
Collection of baseline information: Since management plan (operational plan) should contain detail resource information and management objectives with specified activities, it can be used as baseline information to assess changes. Management plan and constitution of the study FUGs were reviewed to get information about the initial condition. FAO (1998); Yadav & Branney (1999); and Bartlett et al., (1992) have described and used base line data to assess the changes respectively.
Social data collection: Different RRA tools such as HH survey, semi-structured interview, group discussions and office visit were done to collect social data. RRA has been widely used technique for social survey (Chambers, 1992; Chambers & Guijt, 1995). Selected HH were visited and interviewed. Semi-structured interview technique was used as suggested by FAO (1998). CFUG offices were visited and reviewed the records. Decision making systems and representation of women, marginalized and lower cast in executive committee were also looked and recorded. In addition, account system such as income generation, balance, expenditures, audit and transparency were also looked and recorded. Information from CFUG were further triangulated with secondary information from DFO Siraha, Saptari, and ChFDP. All data were recorded in properly designed sheet for further analysis. These data has been used to answer the research question number one and two (data sheets are given in appendix 5&6).
Ecological data collection: Different ecological parameters were defined regarding different indicators and verifiers to be measured. Stand density such as saplings and seedlings, basal area, height distribution; crown coverage; adopted silvicultural operations; and evidences of damage were major variables measured in the sample plots. Crown cover (CC) was measured using ocular method. It was considered dense forest if CC was found >= 70%, open forest= 30%-69%, degraded forest 10-29% and open field< 10%. The same had done by Seppanen & Weikberg (1995) and in ChDFP too. Encroachment, damaged boundary pillars and grazing problems were also looked and recorded. List of some stand variables measured with corresponding sizes of sample plots recommended by Seppanen & Weikberg (1995) and adopted by ChFDP for forest inventory in 1995 and 1998 are given below in table 3.2. Research questions four and five were answered by analyzing these data.
Table 3.2: Stand variables measured and corresponding plots sizes. Stand class Plot size Criteria Variables Basal area Size less Relascope plots DBH >10cm Species, basal area/ha, height Sapling 200 m² DBH 2-10cm & Species, numbers/plot height=>1.3m Seedling 10 m² Height< 1.3m Species, numbers/plot
RS data collection: Using RS data as an indicator of the forest and other ecological condition since formation of CF is one of the objectives of this research. Satellite images of three different year’s 1992, 1999 and 2001 were collected from different sources. Landsat (TM) image of years 1992 and 1999
19 CHAPTER 3: METHODS AND MATERIALS were collected from the Forest Research and Survey division Nepal. Since having similarities in spectral resolution in optical bands, ASTER image of year 2001 was also collected and used.
3.4.4. Data Analysis Data analysis is the process of bringing order to the data, organizing what is there into patterns, categories, and basic descriptive units (Patton, 1988). Regarding stated research questions, appropriate data analysis techniques were chosen to process and analyze data in the context of scientific research. Different analysis techniques for different data collected for this research are described in the following paragraphs.
Analysis of social data: Most of the social data were qualitative data that were collected using RRA tools as described above. Qualitative data consist of all the descriptive information one has about the study sites including all the interview data, observational data, records, impressions and statements of others about the study area (Patton, 1988). Analysis of social data was started with organizing them in tabular forms in Excel spreadsheet.
A) Indicators analysis: Acquired information from different RRA methods were categorized and coded in order to summarize and simplify them in to some meaningful and manageable themes in the context of defined C&I. Patton (1988) has described this process as data converging and diverging process of qualitative data. To be able to assess and compare level of sustainability of the study sites, information belonged to each indicator were further assigned ordinal value. In the methods of transfer categorical response into numeric value, responses are judged by their relative importance and magnitude of verification (Mendoza & Prabhu, 2000). According to Seigel & Castellan (1998), the interpretable operations on a given set of scores are dependent on the level of measurement achieved.
On the basis of presence and absence, indicators were assigned ordinal values. If the indicator was fully present or completely verified it was said fully met (FM) and assigned 3. Indicator that met partially was called PM and assigned 2 (pm+= relatively strong) and 1 (PM-= relatively weak) based on the level of evidence. If indicator was not met or verified it was considered as not met (NM) and assigned 0. Weighted scores of each indicator were calculated based on given score and its relative importance (Score*RI). Weighted scores were first summed at corresponding criterion level. Total weighted score from all criteria was calculated and visualized as percentage in relation to its maximum possible score representing actual social condition of the area. Mann-Whitney test was used to test whether difference in social condition between the study sites were significant or not. Mann-Whitney test ranked the scores for each set of observation and summed to find differences (Kent & Coker 1992).
B) Trend analysis: Trend in social condition (since CF formation) was analyzed using “the sign test”. 14 statements (trend/performance indicators) were used as assessment items for this purpose. 18 persons (15 users, 1 DFO, 1 ChFDP and 1 Researcher) were asked whether they agree or not with the statements. According to Poteete & Ostrom (2002), local populations have witnessed the evaluation of their society and the forest over many years and their perceptions can be used as a variable in explanation of trend. In the absence of repeat studies, RS data can be used for comparison. Data triangulation approach was used to avoid risk of making wrong decision. It was essential to check reliability and consistency of data from different data sources such as interview, office records,
20 CHAPTER 3: METHODS AND MATERIALS workshop report and other general impression. Responses were grouped into three i.e. agree, not sure and not agree on the basis of which three different signs were assigned i.e. agree (+), not sure (0) and not agree (-). If more respondents agreed with the statement, positive sign was assigned and considered positive trend at that particular aspect. It was coded as negative if more respondents did not agree and considered the trend was not positive. Responses on each statement were summed and signs were assigned accordingly. The “sign test” was used to test whether the trend is significant or not. According to Seigel & Castellan (1998), the sign test is a non-parametric statistical test, applicable in the cases where experimenter wishes to establish that two conditions are different. The null hypothesis tested by the sign test is that: P [Xi>Yi] = P [Xi Comparative bar charts were also used to visualize social condition. Bar charts are effective, when comparing differences between similar information (FAO, 1998). Analysis of ecological data: Collected ecological data were re-organized in tabular form in Excel spreadsheet. Descriptive statistics of the measured variables were generated to perform statistical test for the differences over time in each area as well as differences between two areas. A) Normality test: All quantitative data measured in the sample plots were tested whether distribution of measured variables were normal or not. Based on the pattern of distribution, different statistical methods of significant test were used. For example, “t” test always requires normally distributed data. Anderson-Darling test for normality was used in MINITAB statistical software. Significant level for this test was 0.05 i.e. data were considered normally distributed if P-value of the test was more then 0.05. B) Two-sample ‘t’ test: Normally distributed data were tested using the ‘t’ test for unpaired plots whether or not the group means were different. According to Freese (1984), the ‘t’ test of unpaired plots assumes that each group has the same population variance (also see Moore & McCabe, 1999). Microsoft Excel spreadsheet (analysis toolpak) was used for the test. Assumption was made that each group has equal variance. Confidence level for this test was 95% (α = 0.05). Formula to calculate ‘t’ is: t= XA -XB/[√s2 (nA + nB)/(nA)(nB)] Where: XA and XB = arithmetic means for groups A and B nA and nB =The number of observations in groups A and B S2 =the pooled within–group variance [S2= (SSA +SSB)/(nA-1)+(nB-1)] and SS = sum of square of the measured variables (see Freese, 1984 for detail). Inventory data from two study sites were considered as two groups and tested whether or not the group means were different. Similarly, inventory data 1998 for each area was (collected from ChFDP office) considered as a group (population) and significance mean differences were tested with inventory data of corresponding area collected during fieldwork (2001). Sampling methods and plot sizes were same for both 1998 and 2001 measurements. C) Mann-Whitney test: Measured stand variables that were not normally distributed were tested using ‘Mann-Whitney’ test. This is one of the most powerful of the nonparametric tests, and it is a very 21 CHAPTER 3: METHODS AND MATERIALS useful alternative to the parametric ‘t’ test when the researcher wishes to avoid the ‘t’ test’s assumption (Seigel & Castellan, 1998). According to Kent & Coker (1992), Mann-Whitney test can be performed with two samples of differing sizes. Test was performed using MINITAB software. List of stand variables and their corresponding statistical tests are given below in table 3.3. Table 3.3: Stand variables measured and corresponding analysis techniques. Variables Seedling Sapling Trees Grass Measurement Species distribution Species distribution Basal area (M2/ha) Production Density (no/ha) Density (no/ha) Mean height (m) (kg/ha/y) Median DBH (cm) Distribution test Normality test Normality test Normality test **** Significance test t-test Mann-Whitney t-test/Mann-Whitney test **** Triangulation and analysis of indicators: Collected qualitative (observational, interview, records) and quantitative (records, inventory data) ecological data were triangulated before assigning score to each indicator. According to Patton (1988), triangulation means checking consistency and validating information obtained from different sources and methods. Before scoring indicators whether full or partial score to assign related data such as inventory and office records were triangulated. In case of differences and inconsistency, decisions were made based on the strongest evidence such as inventory data and its statistical test. The same procedure that were used in social were used for qualitative ecological and their trends analysis. Analysis of relationship: Relationship between social and ecological condition was analyzed based on overall weighted score given. Chi-square test for two independent samples was used for this purpose. It is a test to find whether relationship do exist between two categorical variables or not (Seigel & Castellan, 1998). Weighted score for each category (social and ecological) of two study sites were tested. MINITAB software was used for this test. Analysis of RS data: Available images (1992, 1999 and 2001) of the study area were georeferenced using 1:25000 topographic maps. Sub maps were created including 1.5km surroundings of both study sites. Based on researchers experience and users’ response, 1.5km was considered as an immediate surrounding (vicinity) that can easily exert impact to the forest. If surroundings’ ecological condition is good, there is less pressure from outsiders. Study sites were delineated using boundary map obtained from ChFDP. Each year image was processed and classified to discriminate forest cover classes and visualized the differences. Images were classified based on crown coverage. 50% sample plots (15 plots) were used for classification of image 2001. Since there were no such ground truths (GPS points) for image 1999 and 1992, classification was done based on reflectance characteristics and qualitative information available. Regarding present condition, ground truths 2001 were also used to calibrate the condition at 1999 and 1992. For example, if plot consisted planted trees with few old natural stands, it was considered as degraded forest in 1992. Different band combinations with NDVI were used to perform better classification. The maximum likelihood classifier was used considering provide the best results. Maximum likelihood takes in to account the shape, size and orientation of the cluster and provide best result (Shrestha & Zink, 2001). NDVI was used to reduce illumination problem in slope terrain. Classification accuracy for classified image 2001 was assessed using 50% of the sample plots (15 plots) of each area. Since there were not such test points for image 1999 and 1992, accuracy assessment was difficult. Regarding similar image processing approach, classification method and 22 CHAPTER 3: METHODS AND MATERIALS indirect use of ground truths 2001 for classification, the same classification accuracy was assumed for both classified images 1992 and 1999 too. Flow chart of different steps in RS data analysis is given below (flow chart 3.3). LandsatTM 1992 LandsatTM 1999 ASTER 2001 Topographic map Create coordinate system and Geo-reference (1:25000) Create sub maps with surroundings Sub map: Jiva 1992, 1999, Sub map: Majhau 1992, and 2001 1999 and 2001 NDVI & band combination. Visual interpretation. ½ sample points Familiarity Supervised classification (Forest type discrimination) Base line data Accuracy assessment ½ sample points Classified map Jiva 1992, 1999 and 2001 Classified map Majhau 1992, 1999 and 2001 (Masked and with surroundings) (Masked and with surroundings) Cross Cross Result interpretation Flowchart 3.3: Summary of the process of RS data analysis 3.5. Research Materials Different materials that were used to complete this research are given in table 3.4 below. Table 3.4: Materials used in different phases of research Materials Use 1 Topographic maps: (1:25000) produced by the Survey Used for creating coordinate system and geo- Department of HMG of Nepal in cooperation with referencing images. It was also used for locating FINIDA (based on aerial photos of 1992). randomly selected sample points. 2. Global Positioning System (GPS): Garmin 12 XL Locating and recording coordinates of randomly receivers. selected sample points. 3. Relascope: Spiegel Relascope ®. Made in Austria. Measuring basal area i.e. cross-sectional area (m2) of all trees in 1 ha. 4. Measuring tape, altimeter, clinometers, protractor, Measuring stand variables, altitude, slope, angle, DBH tape, slope correction table. direction diameters, etc. 5 Computer and software (Microsoft word, Excel, ILWIS Data processing, analysing and writing. & MINITAB). 23 CHAPTER 4: STUDY SITES DESCRIPTION 4. STUDY SITES DESCRIPTION This chapter describes general features of the two CFUGs (study sites). It is expected that this chapter help readers to be familiar with the actual condition of the study sites to understand the assessment results, discussions and final conclusions. In addition to field observations, constitutions and operational plans of each site as will as information from DFOs and ChFDP were used as source of information. 4.1. General Description of Study Sites 4.1.1. Majhau Community Forest Users Group, Saptari, Nepal Majhau Community Forest is covering 141 ha area in Bakdhuwa Village of the Saptari district. Community Forest is located to the North and nears from the east-west highway. Map 4.1 given below is showing its spatial location with respects to the road network in the area. [Map source: ChFDP] CF CF : Village road : Highway Map 4.1: Majhau Community Forest with respect to road network. Forests: According to the initial management plan, most of the forest area was characterized by open degraded natural forest when people started to protect in 1988. It states that it was not so ten years earlier. It was dense and wild area until 1975. The forest consists of both natural and planted stands. DFO Saptari in request of the local people did most of the plantation in 1988/89. However, it was officially handed to the people in 1991/92. Sal (Shoria robusta) and khair (Acacia catachu) are major commercial species found in natural forest. Sissoo (Dalbergia sissoo), Khair (Acacia catachu) are major commercial species planted. However, most of the original species composition of forest has been changed because of fodder and grass species plantation. Forest area is elongated from South to North. Natural gullies flowing from North to South are outside boundaries. Other Community Forests in East and West surround forest area. 24 CHAPTER 4: STUDY SITES DESCRIPTION Users: Total 153 households are registered as users and getting benefit from this Community Forest. Most of its users live near to the forest. Initially, only 103 HH were registered and additional 50 HH were included latter during the time of operational plan revision in 1998. About 90% of users are immigrants who started to migrate about 25 years ago from hilly districts of the country. Although, some original ethnic people are living at the area, users group is almost homogenous group of migrant people. Main occupation of the users is livestock farming. Average livestock per HH is 8.0 (CFUG, 1998). Total population is 857 and average per HH is 5.6. Because of very marginal agricultural land and low productivity, people are keeping more livestock and managing daily needs from milking. Management objectives: Main objective of this CFUG is to “get daily HH needs in sustainable basis by improving ecological condition of the area”. According to operational plan 1998, specific objectives of this CFUG are as follows: • Protection of forest from illegal cutting, encroachment, grazing and uncontrolled fire. • Controlled and prescribed use of resources ensuring sustainability. • Reduce fuel wood consumption by introducing alternatives. • Introduce income generation activities focusing on women and marginalized people. • Aware, strong, united, democratic and transparent community (institutionalization). • Ensured equity (proper benefit sharing mechanism). • Sustainable social development through proper and prescribed use of resources. Management System: CFUG has its own operational plan (OP) and users constitution. It has up-dated its operational plan in 1998 with a detailed forest inventory and GPS survey. Total area is divided into six management blocks. Most of the areas (Five blocks) are managed as individual plotting system. Numbers of plots are equals to number of HH. Individual HH is responsible for protection, management and utilization of resources from corresponding block. No one can invade to others blocks, otherwise subject to be penalties. There is no other guarding system and/or hired guard yet present. Each HH should pay NRs.25 (0.4 Euro) per month, which is regular income source of the committee. Operational plan has clearly stated how and when people can collect different forest products. However, there is no any specific time restriction for fodder and ground grass collection. There is no other specific income generation or forest development activities so far. Decision making process: An executive body called users committee is an immediate plan implementing and decision-making body. Committee of this FUG consists of 17 members. Out of which, at least two should be women. However, there is only one women member in the committee at present. Users’ general assembly elects all executive committee. Users’ assembly has power to change committee; revise existing rules and regulations under the framework of Nepal’s CF laws and bylaws. There should be at least one assembly per year to evaluate the progress; to approve expenditure; and to revise and approve plan for coming years. Benefit sharing mechanism: Users collect grass and fodder from their respective plots. Basis for the size of plot is productivity/site quality. According to management plan, forest should be measured and marked before making decision about collection of timber and poles. Marked trees and poles should be supervised and approved by the DFO to be harvested. Harvested timbers should be depot and 25 CHAPTER 4: STUDY SITES DESCRIPTION distributed equally to the users. Committee can sell timber and other products if market price is high and less or no consumption inside the FUG. Specific observations and remarks during fieldwork: Protection: forest is protected because of individual plotting system. However, more emphasis on fodder and grass production may have discouraged natural tree species to be grown. As forest grows it starts shading grass species and reduces grass production. Users right: All HH within the same village have not been considered as users. Some HH, who were not involved in scrub cleaning at the beginning, have been excluded. In addition, some users are selling and baying plots as their personal properties against rules. Equity: There are some disagreements regarding plots distribution mechanisms. Income generation: Users are getting regular income from milk production. Main source of feeding their livestock is grass from Community Forest. Issues: Population is increasing. People are still immigrating and existing families are also splitting. Issue of new immigrant’s user right; issue of excluded people’s users right; and issues of family division of blocks have not been clearly addressed yet in management system. Picture 4.1: User bringing grass from Community Forest, Majhau. 26 CHAPTER 4: STUDY SITES DESCRIPTION 4.1.2. Jiva Community Forest Users Group, Siraha, Nepal Jiva Community Forest is one of the largest Community Forests handed over in Siraha district. The forest is located to the North from East-West highway and West from the Kattari highway in Phulbaria village. Map 4.2 given below is showing spatial location of Community Forest with respects to its users village and road network. [Map source: ChFDP] CF : Village road : Highway Map 4.2: Jiva Community forest area with respect to road network. Forest: The area of Community Forest is 418 ha. This forest consists two types of stands i.e. natural and plantation forest. Most of the natural forest confines in slopes while plantation forests are located at the base of the hills near to the village. Khair (Acacia catachu), Karma (Ardina cordifolia), Simal (Bambox ceiba) are timber and commercial species in natural forest. According to background information of the area in operational plan, it was dense forest of valuable Khair species until 1980. In- between 1980 and 1990, most of the khair and other commercial mature trees were cut down and smuggled. Timber and fuel wood smuggling to local markets as will as to India are still practiced. At present, most of the natural forest is covered by several non-timber tree species such as Bell, Hallunde, Chamre, etc. Sissoo (Dalbergia sissoo) and Khair (Acacia catachu) are major planted species. DFO Siraha did Plantation in 1985. After establishment of the plantation, local people started to form group to get the area as their Community Forest. It was handed over in 1994. The forest is rectangular in shape and surrounded by gullies. Users belive that the forest condition has improved since being handed over. Users: Jiva CFUG consists 181 households as registered users from Phulbaria village of Siraha district. Most of the registered users live near to the forest. There were only 163 HH at the beginning. Additional 20 HH were included at the time of operation plan revision in 1998. Users group constitute with different ethnic groups i.e. community is heterogeneous. Majority of the users such as Musahar, Sada, and Mahara are original ethnic inhabitants in the area. However, whole community is controlled by minority immigrant community from different hilly parts of the country about hundreds year before. Economic and social status of these minority people is higher than the original majority people. There are more real (traditional) users of this forest living a bit far but have not been included as users while 27 CHAPTER 4: STUDY SITES DESCRIPTION handing over. It is because; some leading elite people have not wanted them to be included. However, they are still going to the forest and meeting their needs illegally. Management objectives: Main objective of this CFUG is to get daily HH needs in sustainable basis by improving ecological condition of the area. Specific objectives according to users operational plan are as follows: • Improve forest condition with participatory management approach. • Controlled and prescribed use of resources ensuring sustainability. • Reduce fuel wood consumption by introducing alternatives and become self-dependent. • Aware, strong, united, democratic and transparent committee (institutionalization). • Ensure equity (proper benefit sharing mechanism). • Sustainable social development through proper and prescribed use of resources. Management system: At the beginning, there was users rotational patrolling system to protect forest. That system could not sustain for long time. After that, they have started to hire guards for patrolling, which is going on still today. However, illicit cutting and timber smuggling (mostly khair) is still a major problem. In a question regarding this problem, response of general users was that the area is big and committee is hiring two guards to control all illicit activities, which is not possible. Some were saying that the rotational system was better. They do not have any regular source of income established. Main source of income is dead Khair. There is no control mechanism for firewood collection, grazing and fodder/litter collection. Each day hundreds of people come to the forest for firewood and fodder collection. Decision making process: CFUG consists 27 members as a decision making body of the users group. Committee has five years term. According to the users constitution, committee member should be selected in mass meeting of the users following democratic procedures. Chairperson, secretary and treasurer are key posts who have authority to handle income. Chairman and secretary have not changed since the beginning. They have absolute influence in decision-making. Both of them are from minority hilly ethnic group and are elite figures of the area. According to Dhakal (1998), Jiva CFUG has not organized in proper way. With an interest of leader, the committee meeting is organized and decision is taken. Usually very few people come to attend meetings and discussions, which makes them (committee) easy to make decision as they like. It has been realized during fieldwork that some members from marginalized groups (Mahara) do not agree with the decision-making mechanisms but the chairman does not listen to them. Several members from marginalized group that disagreed and argued with chairman had been dismissed from the committee in the past. Most of the respondents said that committee does not allow general users to participate in committee meetings. Benefit sharing mechanism: Regarding the principles of participatory forestry, the benefit sharing mechanism is disappointing at this FUG (no equity). They have sold lots of Khair in different years. Amount of sold Khair and income is given below in table 4.1. Table 4.1: Quantities of sold Khair and corresponding income in Jiva. Year Quantity (kg) Income (NRs.) Remarks 1995 91300 37,000 (Euro=570) 1996 104500 46,000 (Euro=708) 1997 240000 600,000 (Euro=9230) 2000 300000 253,000 (Euro=3893) 60% of total price 28 CHAPTER 4: STUDY SITES DESCRIPTION There are disagreements regarding decision-making procedure. Some people were responding that the whole forests belong to the four persons (chairman, vice-chairman, secretary and treasurer). It indicates that there is no transparency and people do not know what is going on. Several users (poor people) have been demanding timber to repair their houses since last two years but no decision has been made yet in this issue. People are accusing committee that it does not want to distribute timber to the users. Instead, committee has taken decision to sell Khair outside. Although, community has been auditing its annual budget from independent auditors, several questions can be raised over it. General users do not know how much money is there in the accounts. Specific observations and remarks during fieldwork: Protection: Forest protection mechanism is very weak. Several evidences of damage can be seen in the forest. Uncontrolled grazing is deteriorating forest in terms of new regeneration. User rights and Conflicts: Conflicts do exist. Distant users having right to be recognized as users have been excluded. They have been getting resources such as grazing, firewood collection and timber in illicit ways. Those people and some of the registered users also are involving firewood and timber selling business at the local markets and to the India, which is about 40 KM distant in south. Executive committee: Executive body is not functioning as it supposed to be. Committee members are not following the rules made by the group. Executive committee seems more powerful than the users group. Some sorts of hidden political interests do exist and influence the committee. Participation: Self-motivated participation of users is very low. Most of the users are not interested in decision-making process and they believe that committee makes necessary decisions. Similarly, committee is also not looking participatory ways to solve the problems. Ownership: Users are not feeling that they have ownership of the forest. Most users believe that the committee is the owner of the forest because they have to pay if any things to get from forest. Transparency: Record-keeping system is not transparent and also not easily available to the people. Records are not properly organized, which indicates that decisions have not been done in open forum. Only three peoples (chairman, secretary, and treasurer) know how much money they have earned and how much has been spent and for what purpose. Picture 4.2: Uncontrolled firewood collection in side the forest, Jiva. At first they kill small trees by girdling and cut for firewood latter saying dead trees. 29 CHAPTER 4: STUDY SITES DESCRIPTION 4.2. Summary of General Features of Study Sites General impression is that the factors responsible for success and failure are different in each case. CF formation process, users awareness, needs and interests, and decision-making system are some of the most influencing factors found and realized during field study. Summary of important features of study sites are given below in table 4.2. Table 4.2: Summary information of study sites. General features Majhau CFUG Jiva CFUG Initiation. All users Some elite Year of handed over. 1992 1994 Area. 141ha 418 ha Number of HH. 153 181 Population. 857 1086 Users composition. Homogenous (almost) Heterogeneous Users awareness. Comparatively high. Comparatively low. Problems with distant users. Non (almost) Prevail (not registered) Committee members. 17 (one women) 27 (three women) Decision-making. Committee makes most of the Committee makes all kinds of decision. decisions. (Mainly members of key posts) Internal conflicts. Yes, but not prominent. Yes, prominent (mostly among committee members). Benefit sharing. Fuel wood and grasses are free Free access to forest for grazing and fuel from individual plots. Selling wood. Selling timbers and poles. timbers. Ownership. Strong ownership feeling Weak ownership feeling among general among general users. users. Conflicts with neighbouring Not at all. Yes, but not prominent. users. Forest types. Natural and plantation. Natural and plantation. Management system. Fragmented smaller plots Three blocks in records but not specified managing by each HH. activities. Protection system. Each HH is responsible for plot Forest guards hired by committee. belongs to him/her. Surrounding forest condition. Not degrading, mostly Not sure whether degrading or not. Community Forest. G. trend in forest condition. Positive. Not declined. Specific future plan. Improve grass and fodder Dead, dying extraction. production. Relation with DFO. Very good. Poor. Relation with ChFDP. Very good. Poor. 30 CHAPTER 5: RESULTS 5. RESULTS 5.1. Results of Existing Social Condition Analysis 5.1.1. General Social Condition Analysis Before looking in-depth at indicators level, it would better to look overall general social condition of the study sites in the context of community management performance. Social data usually consist of descriptive (qualitative) information acquired from different methods of data collection such as interview, questionnaire survey, observations, records etc. To abstract and visualize required information for meaningful answers of stated questions, those data were organized, converged, diverged, coded and analysed. User’s awareness: Based on the responses of the semi-structured interview, user’s knowledge about CF such as what is CF? What is it for? How does it function etc. was scaled as a measure of user’s awareness. Figure 5.1 given below shows user’s awareness status in study sites. More than 86% users in Majhau and 80% users in Jiva knew “what CF is”. However, only 53% in Majhau and 38% in Jiva knew about the constitution. 27% users in Majhau and 44% in Jiva were completely unaware of the operational plan of their forest. Result is based on social data given in appendix 6. (Questionnaire is given in appendix 4). Users awareness status in Majhau Users awarness status in Jiva 100% 80% 100% 80% 60% ) 60% 40% Users (%) 40% 20% Users (% No 20% 0% No GK CN OP No/yes 0% GK CN OP No/yes Yes/no Yes/no Paremeters Parameters Yes Yes Figure 5.1: User’s awareness status in the study sites. Figure shows awareness in Majhau is better than in Jiva. GK= General knowledge about the CF; CN= Knowledge about the constitution of the CFUG and OP= Knowledge about the operational plan of the CF. Yes = They know and aware, Yes/no = They know about CF, its constitution and plan but are not aware regarding rules and plans, No/yes = Poor knowledge but interested, and No = Do not know and also not interested. 31 CHAPTER 5: RESULTS Decision making/benefit-sharing system: Figure 5.2 given below shows users perceptions regarding decision-making and benefit sharing system in the study sites. 59% users in Majhau and 37% users in Jiva agreed with existing system of decision-making. 27% users in Majhau and 25% users in Jiva, although do not agree with existing decision-making and benefit sharing system, they do not have any idea about other better alternative. However, about 14% users in Majhau and 38% users in Jiva were found to be completely against the existing decision-making system and want to change. Users perceptions on existing Users percptions on existing decision decision making/benefit sharing making/benefit sharing system, Jiva system, Majhau 14% 12% 27% 38% 25% 27% Yes yes Yes! but? yes! but? No! but? No! but? 32% No! No 25% Figure 5.2: User's perceptions regarding decision making /benefit sharing system. Majhau has better aggrement than in Jiva. Yes = Completely agree with existing system, Yes! but? = Agree but still need to be improved, No! but? = Do not agree but no idea about alternatives and No = Completely against the existing system. 5.1.2. Social Indicators Analysis Each study site was assessed based absence and presence of locally adjusted (modified) indicators (see appendix: 3.1). Indicators were ranked based on their relative importance (RI) using MCA method (see 3.4.2) where assigned values for each rank were: highly important (H) = 3, medium important (M) = 2 and low important (L)= 1. On the basis of presence and absence, each indicator was assigned score i.e. fully met (FM) = 3, partially met but relatively strong (PM+) = 2, partially met but relatively weak (PM-) = 1 and not met (NM) = 0. Weighted score for each indicator = score for each indicator* RI. Table 5.1 given below presents qualitative description of social condition of study sites at indicator level and corresponding quantitative score for each indicator. Jiva was found to be poor in its social condition. Indicators 1.1, 1.2, 1.3 and 3.2 were not met in Jiva but all indicators were met (fully or partially) in Majhau. No one indicator fully met in Jiva but four indicators were fully met in Majhau; out of them three indicators 2.2, 3.2 and 3.6 were highly important. [Note: The value 3 for fully met does not mean that it is three times effective as value 1. These values are given to perform comparative and relative assessment. The maximum value a site (CFUG) could get is 102 (100%) if all indicators scored 3. Similarly, the minimum value could be 0, if all indicators scored 0]. 32 CHAPTER 5: RESULTS Table 5.1. Assessment of social condition of study sites based on locally adjusted indicators. Indicators RI Majhau Jiva Status Score Weighted Status Score Weighted score score 1.1 Traditional and real 3 No problem with distant users. Some HH who were not 2 6 Distant users are not considered as users. Traditional 0 0 users are identified and interested at the beginning are not included as individual users right is no more considered. No problem with incorporated. plot owner. Users rights of new immigrants are not defined. immigrants. 1.2 Need and interest of 2 Users are almost homogenous in terms of their needs and 2 4 Users group consists different ethnic groups. Diverse 0 0 users are similar. interests. Major interest of almost all users is grass needs and interests. Complexities do exist to bring (fodder). users in common decision. 1.3 Relation with other 1 Good relation with DFO and ChFDP staffs. Regular commun 3 3 Relation and communication with DFO staffs is poor. 0 0 stakeholders is good. understanding with them. Good relation with neighbouring C Project staffs are also not as positive as with Majhau regarding decision-making, benefit sharing and issue of distant users. 2.1 Users are aware 3 87% users know what CF is. Out of them, 57 % know what 2 6 80% users know what CF is. Out of them, 38% know 1 3 regarding their rights and their rights and responsibilities are. 27% users don’t know what their rights and responsibilities are. But very few responsibilities. constitution. 27% don’t know what operation plan (OP) is. are aware on it. 62% users don’t know about They think committee is responsible to make and approve constitution. 44% don’t know operation plan (OP). They such rules. think committee is responsible for all activities. 2.2 Existence of 3 Users constitution and operation plan do exist. 3 9 Constitution and operation plan do exist. OP has been 1 3 participatory rules and its Constitution never changed but OP has been changed three revised once in 1998. Users committee has absolute effective implementation. times. User committee is formed and works according to power and implements rules, as they want. OP is not constitution. No major offences or sanctions so far. Rules being implemented effectively. Rules are often broken are implemented effectively. because they do not match users need. 3.1 Leadership represents 1 Chairperson of the committee is devoted. He has led the 2 2 Most of the key post holders are local elite and holding 1 1 all groups and factions group since the beginning. Some members are local post since the beginning. They are neither popular nor within the community. politicians but not remarkable influence on CF devoted. Committee has been influenced by hidden management. Poor representation of marginalized group. political interest. Poor representation of women. 3.2. Conflicts are 3 No major conflicts observed. Some disputes regarding 3 9 Several internal and external conflicts do exist. Distant 0 0 managed as fast as excluded user’s right and plots distribution do exist but user’s conflict is prominent. Internal conflicts also do possible. committee is trying to solve it. Committee discusses, exist. Usually chairperson rules to solve internal decides and rules to solve internal conflicts. DFO conflicts. No open discussion. DFO has been called in facilitates sometime to solve conflicts. some issues such as power conflicts. 3.3 Decision making 3 Committee usually decides most of the things. Meetings are 1 3 Committee holds absolute power to decide. Meetings are 1 3 system is participatory not regular. Regular general assembly holds each year. not regular. Users assemblies are not regular. Decisions and transparent. Assemblies usually approve decision made by committee. are not transparent. Decisions are mostly done in interest Transparency is poor. of some key post holders. CHAPTER 5: RESULTS 3.4 Participatory benefit 3 60% users agree with existing individual plotting system. 2 6 37% users agree with existing benefit sharing system 1 3 sharing mechanisms are 14% are against it but they have no any appropriate (12% fully support). 38% are completely against practiced. alternatives. 26% users, who are mostly marginalized, accusing committee member getting more benefit think that there is no equity in plot distribution. Committee (misuse of money). Written plan is not clear about members and their relatives hold more and productive benefit sharing mechanism and let committee decide area. Clearly written guidelines for pole and timber how to distribute benefits. Timber and poles are mostly collection and distribution do exist but not practiced yet. sold to the users. Poor can’t get access in bidding. Free access to forest for firewood, grazing and fodder. 3.5 Interest of women 2 No major interests differences between men and women. 1 2 Women and girls from marginalized group are mostly 1 2 and marginalized people Users, who are fully dependent on milking for income, are involving in fire wood collection and selling at the local are taken into account in equally (men/women) involved in fodder collection. Some market. Some users (male), mostly marginalized, are planning and decision- marginalized people do have somewhat different interests involving in timber smuggling to India. No plan to making. such as charcoal. But no specific plan initiated for them. reduce their dependency on forest. Representation and They have less or almost no influence in decision making. influence of those people in decision-making and benefit sharing is poor. 3.6 Records are up-to- 3 Incoming and outgoing records are up-to-date. Separate 3 9 Record keeping system does exist and up-to-date. 2 6 date and transparent. registers for different items. Office assistance appointed by Committee secretary keeps records in his home. Difficult users is responsible for recording and managing the to get records if secretary is not willing to share. Users records. and even general committee members don’t know about it. 4.1 Internal fund Regular HH income from dairy. Each HH pays Rs. 25.0 No mechanism institutionalized for regular income. generation mechanisms 2 (Euro 0.4) per month to the committee. Collecting fee from 2 4 Large amounts of funds have being generated from 1 2 are established. visitors such as study groups from outside. timber (Khair) selling. 4.2 Proper fund 3 Funds handle by chairman and treasure. Audited by 1 3 Funds handle by chairman and treasure. Audited by 1 3 management mechanisms professionals (once a year). Low transparency i.e. 50% professionals (once a year). Poor transparency. More are implemented. users don’t know about the mechanism. 40% people even than 60% people don’t know about fund management. don’t trust the audit report by hired professional. No public Haphazard expenditures. 58% users are against the auditing system practiced so far. system and don’t trust the audit report. Most of the internal conflicts are because of fund management issues. 5.1 Community is 2 Some money has been donated to the local school. 2 4 Funds have been used for several development works. 2 4 benefited from Contribution to establish cooperative dairy. Significant But, because of poor participation of users in decision- development works. changes in socioeconomic condition by dairy production. making, users doubt money is using properly. Total 29 70(69%) 13 30 (29%) CHAPTER 5: RESULTS Summary result of social condition at criterion level: Figure 5.3 given below summarizes the result of social condition at criterion level. Social status at C1, C2, C3, and C4 were found to be different and C5 was found to be similar between the study sites. Looking at overall result, score in Jiva (29%) was found to be less than average (50%) while Majhau secured 69% score. The overall social conditions between the two sites were found to be significantly different at 90% confidence level (test = Mann- Whitney, P= 0.0037, α= 0.1, and N1=N2=14). Null hypothesis (H0) was that there is no different in social condition between the two study sites. H0 was rejected. Social condition in Majhau was found to be significantly better than Jiva. Comparative bar chart of social indicators analysis result at C1 = Recognition and incor- criterion level poration of real users. 90% C2 = Secured users right and 80% specified responsibilities. 70% C3 = Users participation in 60% decision-making and bene- fit sharing. 50% C4 = Proper financial man- score 40% agement system. 30% C5 = Contribution in social 20% Maj hau development. 10% Jiva 0% C1 C2 C3 C4 C5 Overall Criterion Figure 5. 3: Comparative bar chart of social condition between the study sites at criterion level. 35 CHAPTER 5: RESULTS 5.2. Result of Existing Ecological Condition Analysis 5.2.1 Stand Variables Analysis Statistical methods were used to test and compare variables between the two study sites. The results of different stand variables are presented below. Normality test: Sapling and basal area were found normally distributed in the both study sites. Looking separately, in addition, seedling and grass were found normally distributed in Majhau. But it was not found in Jiva, instead, crown coverage and stand diameter were found normally distributed (table 5.2). Null hypothesis (H0): Corresponding stand variables in the both areas are normally distributed. Table 5.2: Descriptive statistics of stands variables. Probability value (p value) for normal distribution is also presented. Table shows sapling and basal area are normally distributed in the both sites. Majhau Jiva 2001 Normality test 2001 Normality test Stand variables Mean Standard Standard P.value Mean Standard Standard P.value deviation error (α=0.05) deviation error (α=0.05) Crown Cover (%) 53.67 27.51 5.023 0.032 54.5 28.66 5.232 * 0.187 Seedling (no./ha) 9266 6091 1112 * 0.525 4800 5436 992.4 0 Sapling (no./ha) 1168 401 73.21 * 0.244 1358 959.2 175.1 * 0.161 B. area (m2/ha) 8.37 4.28 0.936 * 0.104 8.833 5.127 0.936 * 0.574 M. diameter (cm) 15.81 6.282 1.236 0.002 17.41 6.772 1.236 * 0.184 M. height/ha (m) 10.63 3.466 0.633 * 0.158 10.25 5.154 0.941 0.014 Volume (m3/ha) 97.83 63.54 11.6 * 0.082 110.2 106.9 19.52 0 Grass (ton/ha) 28.7 17.91 3.271 * 0.213 3.866 10.51 1.92 0 Human damage (%) 53.5 66.75 * = Significant at 0.05 i.e. H0 cannot be rejected. Test of difference: Based on the result of the Anderson-Darling normality test, two types of statistical test were used for the test of difference in stand variables between the study sites. Two-sample t test for unpaired plots was used for the normally distributed variables. Other variables that were not normally distributed were tested by Mann-Whitney test. In each case, the Null hypothesis (H0) was that there is no difference in stand variables between the two areas. The test was done in 0.05 significance level (α). Average seedlings distribution per hectare was found to be significantly different between the two- study forests. P value calculated (0.0031) for seedling was less than stated sigma value (0.05). Null hypothesis for mean number of seedlings per hectare was rejected. For the remaining stand variables no significant differences (at α=0.05) were detected. However, median diameter was found to be significantly different at 0.10 significance level (table 5.3). 36 CHAPTER 5: RESULTS Table 5.3: Statistical tests of difference for stand variables between the study sites. P value for seedling (0.0031) is strong evidence to reject H0. DF=58 (α=0.05) Majhau Jiva Test (p value) Stand variables Mean Mean 't' test M-W test Crown Cover (%) 53.67 54.5 0.5379 Seedling (no./ha) 9266 4800 *0.0031 Sapling (no./ha) 1168 1358 0.32 Tree (no./ha) 470 451 - - B. area (m2/ha) 8.37 8.833 0.704 M. diameter (cm) 15.81 17.41 0.09 M. height (m) 10.63 10.25 0.3718 Volume (m3/ha) 97.83 110.2 0.7901 *= Significant at 0.05 Stand structure analysis: Figure 5.4 shows, how seedling, sapling and tree were distributed in the both forest. It indicates that the stand composition in Majhau is comparatively better than in Jiva. Figure 5.5 shows how different diameter classes are distributed. Higher number of trees in lower diameter classes further supports that the stand composition in Majhau is comparatively better than in Jiva. In Jiva, middle class diameters were found in higher frequency. Stand composition in study sites (2001) Diameter distribution in study sites (2001) 10000 12 Majhau 8000 10 Majhau Jiva 6000 8 Jiva 6 4000 4 Frequency Frequency/ha 2000 2 0 0 12 16 20 24 28 32 Seedling Sapling Tree DBH class (cm) Figure 5.4: Comparative chart of stand compo- Figure 5.5: Comparative chart of diameter dis- sition between the study sites. Majhau has tribution between the study sites. Majhau has higher frequency of seedling/ha as compare to higher frequency in lower diameter class. Jiva. 5.2.2 Ecological Condition Analysis Table 5.4 given below presents result of ecological condition in the study sites based on locally adjusted indicators (list of C&I is given in appendix 3.2). Table consists qualitative information and corresponding score for each indicator. Five indicators 3.1, 3.2, 4.1, 5.1 and 5.3 were found to be fully met in Majhau but no one fully met in Jiva. Two indicators 2.2 and 4.3 were not met in both sites. . 37 CHAPTER 5: RESULTS Table 5.4: Assessment of ecological condition of study sites based on locally adjusted indicators. Indicators RI Majhau Jiva Status Score Weighted Status ScoreWeighted score Score 1.1 Initial forest and 2 Initial forest and ecological conditions are highlighted in 2 4 Initial forest and ecological conditions are written in 2 4 ecological conditions are operational plan (OP). No initial inventory data existed. operational plan. No initial inventory data existed. Initial specified. Resource problems at the beginning and initiatives for CF problems and justification of need of CF are highlighted in are mentioned in plan. 1992 image shows more degraded OP. 1992 image shows more degraded forest than recent forest than recent image 2001. (Map 5.1) image 2001. (Map 5.2) 2.1 Management objectives 3 Objectives are specified considering ecological 2 6 Objectives are specified considering ecological condition of 2 6 are compatible with condition of the forest and its sustainability. (More in the forest and its sustainability (more in 4.1.2) ecological condition 4.1.1) ensuring its sustainability 2.2 Socio-cultural and 1 No specific recognition existed. 0 0 No specific recognition existed. 0 0 traditional aspect of forest are recognized. 2.3 Forest is divided in to 2 Forest is divided into small individual managing plots. 2 4 Forest is divided into three blocks. But, no activities have 1 2 different zones. (More in 4.1.1) been conducted according to its resource potential. 2.4 TROF is promoted to 2 Some scattered tree species do exist in the village area. 1 2 Rich, who hold more farmland, are planting trees as private 1 2 reduce dependency on Bamboo and Sissoo are common. No block plantation of forest. Fruit trees and timber (Sissoo) are commonly found the forest. private forest. Few HH have trees in kitchen garden. No in and around the land parcel. CFUG have planned to extra effort by the CFUG so far but they have planned to promote TROF. promote TROF in future. 3.1 Implemented 3 Individual is responsible to protect corresponding plot. 3 9 Protection system is not participatory. Hired guards are 2 6 protection system is About 70% users agree on existing protection patrolling forest. Illegal cutting, uncontrolled grazing still effective. mechanism. Some times committee members do going on. About 65% users agree on existing management patrolling. No evidence of new fire damage. Evidences approach. No evidence of fire damage. Evidences of of damaging seedlings while cutting ground grass were damaged seedlings and saplings by browsing animals and observed. debarking for firewood were observed. 3.2 OP is periodically 3 OP has been amended four times since handed over in 3 9 OP has been revised two times so far since 1994. However, 2 6 amended and implemented 1992. Improvement in participatory approach at each revision doesn’t seem to improve management approach but according to ecological time. Plan is implemented effectively. However, only to get approval for selling timber outside. OP is also not clear condition. about 55% users are aware about it. regarding working calendar. 3.3 Forest resources are 3 Clearly written harvesting prescription. Optimum use of 2 6 Harvesting prescriptions are not clearly written in OP. 1 3 used properly ensuring fodder in individual plot. No silvicultural operations Uncontrolled firewood collection and grazing. Getting sustainability (approved such as thinning and pruning have been practiced so far. income from stump and dead khair. No silvicultural by DFO). No evidence of unused dead dying trees in the forest operations such as thinning and pruning have been practiced 38 CHAPTER 5: RESULTS so far. 4.1 Stand composition is 3 Stand composition seems very good in terms of seedling, 3 9 Stand composition seems ok. Distribution of seedling, 2 6 maintained properly. sapling and tree distribution, which are 9266,1168 and sapling and tree are 4800, 1358 and 451/ha respectively. 470 /ha respectively. (Table 5.3 and Figure5.4) (Table 5.3 and Figure5.4) 4.2 Stand stock is 3 Stand volume has been increased significantly from 25.66 2 6 Stand volume has been increased significantly from 25.12 2 6 improved towards m3/ha in 1995 to 85.52 m3/ha in 1998. It increased to m3/ha in 1995 to 110.3 m3/ha in 2001. However increment meeting demands. 97.833 m3/ha till 2001. However, this increment in- from 1998 to 2001 (83 m3/ha to 110.3 m3/ha) is not between 1998-2001 is not statistically significant at 0.05 significant at 0.05 significance level. (Table 5.9 Figure significance level (Table 5.8, Figure 5.10) 5.10) 4.3 NTFPs are promoted 1 No NTFP promoting program initiated. However, users 0 0 Forest consists considerable amount of NTFP such as Neem 0 0 according to demands of are getting grasses as a major resource. Different types (Azadirchta indica), Bhorla etc. Some marginalized HH people and local market. of NTFPs are found in the forest but not properly involve collecting NTFP and selling at the local market. No managed so far. management program initiated by CFUG so far. 5.1 Degraded areas are 3 Trees (mostly fodder) and grasses have been planted. 3 9 Seedling production and replacement planting done in 1996. 2 6 rehabilitated. Regeneration is high. Scrub area has been changed in to Fruit trees (Mango) have been recently planted in about pasture. Some areas mostly Northern side is still poor in two- hectare area. Regeneration capacity is poor in some tree cover but ground cover (grass) is good. Classified areas because of heavy grazing. Classified images of images of different years reveal the trends of different years reveal the trends of rehabilitation. (Map5.2) rehabilitation. (Map5.1) 5.2 Surrounding ecology 2 Other CF from East, West and some part of North side 1 2 Surrounding CFs in East and West and Government 1 2 is not deteriorated. surround the area. Neighboring CF i.e. Malati, managed forest in North side of the CF are deteriorating. Mohanpur and Sahales (near the village) are believed as However, RS data shows there is still dense forest in North. successful CF in Saptari district. RS data also reveal that People from southern boarder of the district come to the the surrounding areas (near to the village) are getting government forest that may exert pressure in CF when no better than before. But forest condition in terms of more resource exists in the surroundings. Neighboring CF productivity is still poor. Government managed forest in are not functioning well. Classified RS data in map5.4 shows North and North East side of CF is in high pressure and that the forest conditions of surrounding have been seems deteriorating. (Map5.3) improving. 5.3 Soil conservation is 3 Soil erosion is controlled. It is mostly because of grazing 3 9 Some new gullies have been observed. Heavily grazed areas 2 6 assured. control and dense ground grass in slopes. Classified RS are more eroded. Nevertheless, it is not so prominent in all data also supports that the amount of sand (bare soil) in over the area. Classified RS data also supports that the the surroundings is decreased. (Map5.3) amount of sand (bare soil) at the basin is decreased. (Map5.4) Total 27 75 (74%) 22 55 (54%) 39 CHAPTER 5: RESULTS Summary of ecological condition at criterion level: Figure 5.6 given below summarizes the result of ecological condition at criterion level. It is simply the sum of weighted score of indicators under the criterion. Both sites scored above the average (50%) in overall ecological condition. Figure indicates that Majhau is comparatively better. However, the difference was not found to be significant at 90% confidence level (test = Mann-Whitney P= 0.2361, α= 0.1, and N1=N2=14). Null hypothesis (H0) was that there is no significant different in ecological condition between the two areas. H0 was not rejected. Observed differences were not sufficient evidences to say that there is significant different in ecological condition between the two study sites at 90% confidence level. Comparative bar chart of ecological indicators analysis C1= Specified initial ecological result at criterion level scenario of the area. 100% C2= Forest and its management 80% plan. C3= Effective implementation of 60% management plan. score 40% C4= Forest structure and its pro- duction function. Majhau 20% C5= Capacity of ecological and Jiva 0% protection function. C1 C2 C3 C4 C5 Overall Criterion Figure 5.6: Comparative bar chart of ecological condition between the study sites at criterion level. 5.3. Result of Relationship Analysis Between Social and Ecological Condition Results of social and ecological condition based on assessment of indicators as presented above were further tested to see whether they have any relationship or not. Before using statistical test, social and ecological conditions of both areas were visualized in a bar chart. Figure 5.7 gives impression of relationship between social and ecological conditions. To verify this impression and conclude, chi- square test was used. Comparative bar chart between social and ecological condition. 80 70 60 50 40 30 Ecological score(%) 20 social condition in 10 0 Majhau Jiva Study areas Figure 5.7: Comparative bar chart showing relation- ship between social and ecological condition. 40 CHAPTER 5: RESULTS Chi- square test for relationship between social and ecological condition Observed value Expected value Majhau Jiva Total Majhau Jiva Total Social 70 30 100 Social 81.96 48.04 130 Ecological 75 55 130 Ecological 63.04 36.96 100 Total 145 85 230 Total 145 85 230 Null Hypothesis (H0): Social and ecological conditions of the Community Forestry are not related (associated) with each other. Alternative Hypothesis (H1): Social and ecological conditions of the Community Forestry are related (associated) with each other. Significance level: α = 0.1 (MINITAB was used for this test). Chi-Sq = 0.590 + 1.007 +0.768 + 1.309 = 3.675, DF = 1, P-Value = 0.055 Decision: Since probability value (0.055) was less than significance level (0.1), the null hypothesis was rejected. Social and ecological conditions in the study sites were found to be associated with each other. The conclusion was that the social and ecological conditions of the Community Forestry are significantly associated with each other. 5.4. Result of Remote Sensing (RS) Data Analysis 5.4.1 Supervised Classification of study sites’ Forests Majhau Supervised classification was performed independently for each year image with the help of collected ground truths (GPS coordinate) and other ancillary data. Crown cover (%) was used to discriminate forest types i.e. >= 70% dense forest, 30- 69% open forest and 10- 29% degraded forest. Independently classified images overlaid by cross operation to get the area of change in forest at the both areas. Confusion matrix (appendix 12) was used to check the classification accuracy for image 2001. Classification accuracy for dense forest and open forest were found 86% and 71% respectively. 67% test pixels for degraded forest were classified correctly and 33% test pixels were misclassified as open forest. Similarly, 16% test pixels for open forest and 14% pixels for dense forest were misclassified. Mean classification accuracy was 79% and overall classification accuracy was 81%. Since there were not assessable ground truths to test the accuracy for image 1999 and 1992, the same classification accuracy as in 2001 was assumed (see chapter 3.4.2). Classified images (map 5.1) and corresponding change matrix (table 5.5) are given below. To prevent error sources from exerting excessive influence on result, detected changes were considered “Real” change only if changes were found beyond the error of misclassification. Dense forest and open forest were found increased by 66% (12.5 ha) and 20% (12 ha) respectively between 1992 and 2001. Because of 33% classification error, change in degraded forest was not considered to be real change between 1992 and 2001. However, degraded forest was reduced by 36% (16 ha) after 1999. 14 ha dense forest was found to be converted into degraded (4ha) and open forest (10 ha) between 1992 and 1999 (negative change). Open field was reduced by about 71% (12.5 ha) since 1992. The overall trend in the forest condition was found being improved. The trend was more pronounced after 1999. Although matrix indicates positive change in all forest classes between 1992 and 1999, it could not be confirmed as “Real” change beyond the error. 41 CHAPTER 5: RESULTS Majhau 2001 Majhau 1999 Majhau 1992 Dense forest Map 5.1: Classified images 2001, 1999 and 1992, Majhau Open forest Degraded forest Open field Sand Change Matrix, Majhau: “Real” changed & not changed are highlighted. Table 5.5: Forest condition change matrix between 1992-1999 (below) and between 1999-2001 (above). To 2001 Dense Open Degraded Open field Sand Total 1999 from 1999 (ha) (ha) (ha) (ha) (ha) (ha) Dense forest 10 9 2 0 0 21 Open forest 14 40 12 1 1 68 Degraded forest 5 24 14 2 0 45 Open field 2 1 1 2 0 6 Sand 0.5 0.5 0 0 0 1 Total 2001 31.5 * 74.5 * 29 5 * 1 141 To 1999 Dense Open Degraded Open field Sand Total 1992 From 1992 (ha) (ha) (ha) (ha) (ha) (ha) Dense forest 5 10 4 0 0 19 Open forest 11 33 16 2 0. 5 62.5 Degraded forest 2 20 17 1 0 40 Open field 2 5 7 3 0.5 17.5 Sand 1 0 1 0 0 2 Total 1999 21 68 45 6 1 141 No change; Negative change; Positive change; * Change between 1992 & 2001 Jiva: In Jiva, 83% dense and 80% open mixed forest were classified correctly. 33% sample pixels for degraded forest were found to be misclassified. Average and overall accuracy were 77% and 79% respectively (confusion matrix: appendix 12). To confirm the “Real” change, the same consideration as in Majhau was applied. Dense forest was increased by about 78.5 ha since 1992. Open field and degraded forest were found to be decreased by 40% (10 ha) and 37% (75 ha) respectively since 1992. Between 1992 and 1999, open forest was decreased by 25% (43 ha). 42 ha open forest was converted into degraded forest during that period. However, same amount was also converted into dense forest. 42 CHAPTER 5: RESULTS 38% (9 ha) of open field was converted into forest between 1992 and 1999. Result indicates that the improvement in forest condition was more pronounced after 1999. During that period dense and open forest were increased by 24% (18.5 ha) and 40% (50 ha) respectively. The degraded forest was decreased by 34% (66 ha). At the same time 28 ha dense forest was found to be converted into open mixed forest. However, the overall trend was found being improved. Classified images (map 5.2) and corresponding change matrix (table 5.6) are given below. Jiva 2001 Jiva 1999 Jiva 1992 Dense forest Map 5.2: Classified images 2001, 1999 and 1992, Jiva Open forest Degraded forest Open field Sand Change matrix, Jiva: “Real” changed & not changed are highlighted. Table 5. 6: Forest condition change matrix between 1992-1999 (below) and between 1999-2001 (above), Jiva. To 2001 Dense Open Degraded Open field Sand Total area from 1999 (ha) (ha) (ha) (ha) (ha) (ha) 1999 Dense forest 45 28 3 0 0 76 Open forest 35 84 9 0.5 0 128.5 Degraded forest 14 66 109 6 0 195 Open field 0.5 1 8 8 0 17.5 Sand 0 0 0.2 1 0.3 1.5 Total 2001 94.5 * 179 129.2 * 15.5 * 0.3 418.5 To 1999 Dense Open Degraded Open field Sand Total area From 1992 (ha) (ha) (ha) (ha) (ha) (ha) 1992 Dense forest 8 7 1 0 0 16 Open forest 42 86 42 1 0 171 Degraded forest 25 35 138 6 0 204 Open field 1 0.5 13 10 1 25.5 Sand 0 0 1 0.5 0.5 2 Total area (ha) 1999 76 128.5 195 17.5 1.5 418.5 No change; Negative change; positive change; * = Change between 1992& 2001 43 CHAPTER 5: RESULTS 5.4.2 Supervised Classification of the Surroundings of study sites Surroundings of the both study sites were classified regarding forest and other ecological conditions and its trend since 1992. 1.5 km distance from the boundary of CF was considered as surrounding. Surrounding ecological condition is one of the important indicators for this assessment. Since the ground truths were same for the study sites and the corresponding surroundings, classifications were done together and areas (surroundings and the study sites) were separated latter using masking function in Ilwis. The same classification accuracy was considered for both, the study areas and the surroundings. Surroundings, Majhau: Dense and open forest were increased by 29% (47 ha) and 78% (261 ha) respectively and the degraded forest was decreased by 35% (155 ha) between 1992 and 2001. However, looking between 1992 and 1999, dense forest was found to be decreased by 15%. Similarly, reduction of degraded forest between 1999 and 2001 was confirmed beyond the possibility of 33% misclassification, which indicates that the protection system became more effective after 1999. Classified maps (Map 5.3) and corresponding figure (Figure 5. 8) based on the histograms of classified images (given in appendix 14) given below make clearer, how conditions were changed between 1992 and 2001. Surroundings, Majhau 2001 Surroundings, Majhau 1999 Surroundings, Majhau 1992 Dense forest Map 5.3: Classified images 2001, 1999 and 1992 of the surroundings, Majhau. Open forest Degraded forest Trend in forest condition in the surroundings, Agricultural field Sand Majahu 700 DGF 600 DF 500 OF 400 300 Area (ha) Area 200 100 0 1992Year 1999 2001 Figure 5.8: Trend in forest condition at the surroundings, Majhau. 44 CHAPTER 5: RESULTS Surroundings, Jiva: Dense forest increased by 38% (116 ha) since 1992. Open forest was found to be decreased till 1999 and started to increase after 1999. However, open forest was not “Really” increased between 1992 and 2001. Degraded forest also was not “Really” decreased till 1999 but it was decreased by 47% (255 ha) after 1999. Overall reduction of degraded forest was 37% since 1992. Overall trend indicates that the forest at the surroundings of Jiva was being improved (notably it was more pronounced after 1999). Classified maps (Map 5.4) and corresponding figures (figure 5.9) based on the histograms of classified images (appendix 14) given below make clearer about the trend. Surroundings, Jiva 2001 Surroundings, Jiva 1999 Surroundings, Jiva 1992 Dense forest Map 5.4: Classified images 2001, 1999 and 1992 of the surroundings, Jiva. Open forest Degraded forest Agricultural field DGF = DegradedSand forest Trend in forest condition in surroundings of DF = Dense forest Jiva OF = Open forest 600 DGF 500 DF 400 OF 300 Area (ha) 200 100 0 DGF = Degraded forest 1992 1999 2001 DF = Dense forest Year OF = Open forest Figure 5.9: Trend in forest condition at the surroundings, Jiva. It indicates that the trend is more positive after 1999. 45 CHAPTER 5: RESULTS 5.5. Assessment of the Trend in Social Condition The sign test: The sign test was chosen to test whether the trend in social condition was significant or not between 1992 and 2001 in the study sites because of CF. Table 5.7 given below shows how did stakeholders response to the social trend assessing statements. Statements were based on the selected and verified indicators for the study sites. Positive (+) and negative (-) sign were given according to the number of stakeholders agree and disagree, respectively. Table 5.7: Assessment of trend in social condition. + Sign indicates positive trend in social condition. Assessing statements Majhau Jiva Yes No Status Sign Yes No Status Sign 1. Dispute with distant users decreased. 14 4 P2 > P1 + 9 9 P2 = P1 0 2. Users awareness increased. 16 2 P2 > P1 + 13 5 P2 > P1 + 3. Need and interests among users 12 6 P2 > P1 + 8 10 P2 < P1 - remain same. 4. Participatory rules implemented 11 7 P2 > P1 + 9 10 P2 < P1 - effectively. 5. Representation of different interests 10 8 P2 > P1 + 8 10 P2 < P1 - in leaderships increased. 6. Conflicts managed. 10 8 P2 > P1 + 5 13 P2 < P1 - 7. Participation of users in decision- 9 9 P2 = P1 0 8 10 P2 < P1 - making increased. 8. Benefit sharing system improved. 13 5 P2 > P1 + 12 6 P2 < P1 - 9. Internal fund generation mechanisms 18 0 P2 > P1 + 9 9 P1 = P2 0 established. 10. Fund management system 8 10 P2 < P1 - 8 10 P2 < P1 - improved. 11. Records keeping system improved 16 2 P2 > P1 + 9 9 P1 = P2 0 12. Relationships with other 18 0 P2 > P1 + 10 8 P2 > P1 + stakeholders improved. 13. Participation of women and 9 9 P2 = P1 0 9 9 P1 = P2 0 marginalized users increased. 14. Contribution in social development 12 6 P2 > P1 + 18 0 P2 > P1 + increased. ‘P1’ = Phase one, ‘P2’ = Phase two, ‘+ sign’: if more respondents agree with statement, ‘- sign’: more respondents don’t agree with statement and ‘= sign’: in case of ties. Null hypothesis (H0): There is no significant positive trend (improvement) in social condition of study sites due to Community Forestry since being implemented. Alternative hypothesis (H1): There is significant positive trend in social condition of study sites due to Community Forestry. Significant level: α = 0.1 and N is the number of items that indicate trends. Decision: Out of total 14 statements, 2 in Majhau and 4 in Jiva could not be decided and coded as zero (0). Because of ties (0), sample size was reduced from N= 14 to N= 12 (14-2) and 10 (14-4) for Majhau and Jiva respectively. Only 1 in Majhau and 7 in Jiva did not show positive trend and coded as negative (-) sign. The remaining statements showed positive change. Now, X is the number of positive 46 CHAPTER 5: RESULTS sign, so X = 11 for Majhau and 3 for Jiva respectively. According to the table of binomial test (table D in Seigel & Castellan, 1998) for N = 12 and 10, the probability of observing X =>11 and X =>3 has one tailed probability, when H0 is true of 0.003 and 0.945. Since the value for Majhau was in the region of rejection for α = 0 .1, H0 was rejected. But in Jiva, H0 could not be rejected. Thus, conclusion was that there is positive trend (improvement) in social condition due to CF in Majhau but it was not significant in Jiva to conclude ‘there is positive trend in its social condition due to Community Forestry’. 5.6. Assessment of the Trend in Ecological Condition The same procedures as in social trend assessment were followed to assess trend in ecological condition of study sites. In addition to stakeholders’ perception and office records, field inventory data from different years (1995, 1998 and 2001) were compared and used as evidences to assess the trend in ecological condition. Data were triangulated to make reliable decision. Field inventory data at different years and statistical test for the differences are given in table 5.8. Saplings in Majhau were found to be significantly increased between 1998 and 2001. Rests of the other variables were not found to be changed significantly at 95% confidence level (α=0.05). However, figure 5.10 visualize that the overall trend in forest condition was positive in the both sites. Regeneration in Majhau although was not significant, indicated declining after 1998. Table 5.8: Descriptive statistics of stand variables in different years. It shows trend and its significance. Data 1995 were not tested, because these data were taken including other more areas (whole district) they were used only to visualize the condition. Majhau Jiva 1995 1998 2001 α=0.05 df = 55 1995 1998 2001 α=0.05,df = 54 Stand variables Mean Mean Mean 't' test M-W test Mean Mean Mean 't' test M-W test Crown cover (%) * 48.5 53.67 * * * 55 54.5 * * Seedling (no./ha) 2415 10370 9266 0.7675 1563 4212 4800 0.9734 Sapling (no/ha) * 897 1168 0.014 * 1423 1358 0.909 B. area (m2/ha) 5.1 7.7 8.37 0.584 4.61 8 8.833 0.36 M.diameter (cm) * 15.2 15.81 0.8161 * 18 17.41 0.9278 M. height (m) * 10.4 10.63 0.7233 * 9.54 10.25 0.723 Volume (m3/ha) 25.66 85.52 97.83 0.4526 25.12 83 110.2 0.2928 Comparative basal area trend in Comparative regeneration trend in the study sites the study sites 10 12000 10000 8 8000 6 6000 4 4000 Majhau BA/ha(m2) Majhau 2000 2 Seedlings/ha Jiva Jiva 0 0 1995 1998 2001 1995 1998 2001 Year Year Figure 5.10: Comparative bar graphs showing trends in regeneration and basal area between the study sites. 47 CHAPTER 5: RESULTS The sign test: Null hypothesis (H0) for the test was that there is no significant positive trend (improvement) in ecological condition of study sites due to Community Forestry since being implemented. Alternative hypothesis (H1) was that there is significant positive trend (improvement) in ecological condition of study sites due to Community Forestry. Test was done at 90% confidence level. Table 5.9: Assessment of trend in ecological condition. Positive sign (+) indicates, change is positive. Assessing statements Majhau Jiva Yes No Status Sign Yes No Status Sign 1. Background information (annual) of forest 12 6 P2 > P1 + 11 7 P2 > P1 + conditions managed. * 2.Compatibility of management objectives 13 5 P2 > P1 + 10 8 P2 > P1 + with forest condition increased. 3. Important socio-cultural and traditional 9 9 P2 = P1 0 9 9 P2 = P1 0 aspects of forest respected. 4. Blocking system of forest implemented 18 0 P2 > P1 + 5 13 P2 < P1 - effectively. 5. TROF promoted. 9 9 P2 = P1 0 9 9 P2 = P1 0 6. Protection system became effective. 14 4 P2 > P1 + 10 8 P2 > P1 + 7. Management plan improved and 16 2 P2 > P1 + 10 8 P2 > P1 + implemented. 8. Ecological sustainability considered while 18 0 P2 > P1 + 9 9 P2 = P1 0 using resources. * 9. Stand composition maintained properly. ** -- -- P2 = P1 0 -- -- P2 = P1 0 10. Timber stocking improved. ** -- -- P2 = P1 0 -- -- P2 = P1 0 11. NTFPs managed. 9 9 P2 = P1 0 9 9 P2 = P1 0 12. Forest degradation controlled. * 18 0 P2 > P1 + 12 6 P2 > P1 + 13. Forests of surrounding areas improved. * 10 9 P2 > P1 + 8 10 P2 < P1 - 14. Soil erosion controlled. * 18 0 P2 > P1 + 10 8 P2 > P1 + *: Triangulation with RS data. **: Inventory data, based on table 5.8. N = (14 - 5) 9 and (14 - 6) 8 for Majhau and Jiva respectively. Positive sign (+) X = 9 in Majhau and 6 in Jiva. Negative sign (-) = 0 in Majhau and 2 in Jiva. According to table as mentioned above for α = 0.1 significant level, probability of accepting H0 (one tailed test) is 0.002 for Majhau and 0.145 for Jiva Community Forest. Decision: Since the P value for Majhau (0.002) was in the region of rejection for α = 0.1, H0 was rejected. The conclusion was that there is significant positive trend in overall ecological condition in Majhau. But, the P value for Jiva (0.145) was not in the rejection region to reject H0 at α = 0.1 significance level. The conclusion was that there is no significant positive trend in ecological condition in Jiva. Looking at other ecological aspects, trend in rehabilitation of the degraded forest was found positive in the both areas. However, although RS data supported some positive trend after 1999 in the surroundings of Jiva, most of the local users were not agree on it. They said that the surrounding forests whether government or community managed are being degraded and threaten to their forest. Limitation: Since the sign test does not consider the magnitude of differences there is possibility of losing information regarding comparative condition between the two study sites. 48 CHAPTER 6: DISCUSSION 6. DISCUSSION This chapter aims to relate data analysis results with stated objectives and explore underlying factors behind the results before making conclusions. Results are compared and discussed with other related research conclusions to justify reliability of its message in the context of research application. 6.1. Social Condition Analysis Though community can have many things in common, they are still very complex. Community are often composed of diverse groups such as landless and those with land, rich and poor, new immigrants and old residents each with their own needs and interests. This study has concentrated on looking at condition of the social system of FUG that has been established to manage Community Forest. Common property resource management is essentially about sustainable management of both people and resource. Common property management system, which is not socially sustainable, will eventually break down and result in environmental degradation (Arnold & Steward, 1998). Evaluation criteria, whether common property management system is socially sustainable or not, should be based on the existing social condition, needs, and interests of the community. The key issue is whether the community is able to establish common goals and then work together to follow the strategy that has been proposed or not (James & Karen, 1997). Since all (14) assessed social indicators belong to five criteria, discussions are made at criterion level based on results of corresponding indicators. Recognition and incorporation of real users (C1): Fichtenau (1998) and Veltter et al. (2001) have reported that identification and incorporation of real user in Terai and Siwalik region is core problem leading to management failure. Result has demonstrated similar problem in Jiva that the real users have not been identified properly while handing over the forest. Despite its large area (more than 2 ha/HH currently) it has been realized that about 50% of the real users, who live somewhat distant (distant users) have been excluded from the CFUG. Dhakal (1998) has also reported that the distant users in Jiva have been excluded because some elite people (leaders) do not want them to be included. From the above, it is clear that the distant users should be integrated by giving them access rights to the forest resource. Since they are currently not contributing directly to protection and management of the forests they should be paying higher prices for the products. Diverse needs and interests among users is another underlying reason of poor performance found in Jiva. James & Karan (1997); Poteete & Ostrom (2002) have reported that a key factor that determines a community’s ability to manage resources is its social cohesion and willingness to set and strive for common goals. This doesn’t mean that the community must be homogenous, although this often helps. There are many heterogeneous communities working toward common objectives. The key issue is that whether the communities are able to establish common goals, establish strategies for accomplishing those goals and then work together to follow the strategy that has been proposed. In Majhau, needs and interests of users have been found similar and good consensus among users exists. It was not so in Jiva where it has been revealed by the result with zero score in comparison to 72% score of Majhau for this criterion. 49 CHAPTER 6: DISCUSSION Secured rights and specified responsibilities (C2): User’s status, in terms of their education, occupation, interest, and level of knowledge reveals the status of community and sustainability of common property regime. This criterion (17.5% RI) was focused on status of users knowledge and their obligation for betterment of their community. Two indicators i.e. users’ awareness and effectiveness of the implemented rules were assessed under this criterion. Hobley & Shah (1996) have given higher priority on users knowledge as an indicator of groups’ effectiveness. Looking at the results, most of the users (80%) are having general knowledge about the Community Forestry in the both study areas. However, not many users are found to be aware about their rights and responsibilities. Secured user’s right is one of the high ranked indicators for sustainable common property regime. Secured right strengthens ownership of resources; as a consequence willingness to take responsibility is increased. Fichtenau (1998) has evaluated that given responsibilities to the local communities to manage their forests have created strong feelings of ownership and result in better protection of the forest in the ChFDP area. Although result of Majhau fully supports Fichtenau (1998), result in Jiva contradicts somewhat. Looking at the constitution and operation plan of Jiva, users right and responsibilities are written clearly and DFO has given responsibility to them since 1994. However, the results indicate that the users knowledge about their own rights and responsibilities are still very low (44% users were completely unaware). Users’ do not want to take responsibility of protection, because of that the rotational patrolling system could not be sustained and the committee started to hire guards. Users have to pay for timber and poles that restrict poor to access their needs. Consequently, they (poor) start to meet their needs by violating rules without any feeling of ownership. Because of this, Jiva has secured only 33% score in this criterion, which indicates a weak management system that may threaten sustainability of the group in long run. However, it does not mean that the situation is worse than before the formation of CF. It means giving responsibility only may not be sufficient to create feeling of ownership. In addition, users should be aware about the importance of taking responsibility. If users know that the benefits in the future will exceed their investment, ownership and willingness itself develop inside them. Result of Majhau supports this fact, where each HH is taking responsibility to protect corresponding individual plot and getting regular benefits. User’s perception in decision-making and benefits sharing (C3): This criterion was given relatively higher importance (44%) than others. It has six indicators (leadership, conflict, decision-making, benefit sharing, participation of women and marginalized users and transparency). Although leadership was not considered as high ranked indicator, it was used as an essential indicator. It has often been reported that the functioning of CFUG largely depends on the management qualities of the committee and notably on the chairperson (Pietrowicz, 2000 for example). It is even more important if the group is heterogeneous in terms of their needs and interests. Looking at study sites, it was found that the leadership (notably the chairperson) in Majhau were sincere and dedicated to ensure equitable benefit sharing, which was not prevailing in Jiva. Most of the original ethnic users do not trust the leadership in Jiva. Even though, because of other social status such as political and economical, they could not go against the leadership. Because of this reason, several internal and 50 CHAPTER 6: DISCUSSION external problems such as violation of rules are prevailing in Jiva. Capacity to build consensus among different interest groups is another quality of leadership that could ensure that the needs and interests of poor people and women are incorporated during planning and decision-making. Sustainable forest management requires leadership first to empower the villagers either from inside or outside (Debnath, 1998). Looking at the study sites, although having objective to empower women and marginalized people, no evidence was found to support that the leadership were serious in this regard. In Majhau, however, apparent need of such a programme has not been realized because there were somewhat similar needs and interests among users. But situation was different in Jiva. There was apparent need to empower women and marginalized users. However, the existing leadership in Jiva was not so interested to empower marginalized group. They may have seen empowerment of marginalized group as threat to their social status. The community’s experience with conflict and the way it has managed conflicts in the past greatly influence its present degree of social cohesion and its willingness to engage in cooperative resource management activities (James & Karan, 1997). Heterogeneous community might have more chance of having conflicts. But it is not necessary that there should be conflicts only in heterogeneous community, it may take place in homogenous society too. However, it is one of the major indicators discriminating social condition between the two study sites. Jiva has several conflicts such as conflict with distant users, internal power conflict, conflict in decision-making and benefit-sharing etc. Neither any established system nor any evidence of handling (managing) conflicts has found so far in Jiva. It is not only because of diverse needs and interests but also because of some hidden interests of the leaderships such as politics and money. Majhau has very few internal conflicts. Conflicts are brought forward to discuss in monthly regular meeting if any are present. The important point should be considered here is whether conflict management system is institutionalised or not. Sustainability evaluation should be done based on the established system to manage conflicts rather than numbers of conflicts have been solved. If disagreements are listened and taken as feedback than there is hope of getting solution. Focus should be given to the interest of poor and women offering tangible advantages and income opportunities. Implemented benefit sharing and decision-making mechanism mostly govern the robustness of the community. It has been described as priority indicators by several authors (Hobley, 1996; Pietrowicz, 2000; Melink, 1992; James & Karan, 1997; Poteete & Ostrom, 2002) for the sustainable management of Community Forestry. Looking at benefit-sharing mechanism in the study sites, although both have “equal to all” basis written provision of benefit sharing, evidences do not support the reality. In Majhau, however, majority people agree with individual plotting system. Nevertheless, some disagreements (14% users) regarding site quality and size of plots do exist. People’s incentives to follow and participate in a community resource management plan will be stronger when they feel that their interests and concerns are represented in the plan. When peoples concerns are not reflected in the rules, conflicts and even the eventual failure of the project are highly probable (James & Karen, 1997). Disagreement of majority users over existing decision-making system in Jiva indicates that the authority while making decision do not consider the needs and interests of majority users’. There might be several reasons behind, however, some observed reasons are: 51 CHAPTER 6: DISCUSSION heterogeneity in needs and interests of users, haphazard decision and poor awareness. Majority people in Jiva belong to original tribes and most of them are poor. They have different needs and interests than that of the local elite, who hold decisive post of the users committee and decisions are made based on their interests, which are mostly not compatible with the interests of poor people. Situation in Majhau is different. The major need and interest of most of the users is fodder. Individual plotting system is compatible with their interests, which results in more agreement among users. It would better to mention here the argument by Poffenberger (1992) that without rights to an equitable share in forest production profits and with no management authority or tenurial security, communities lack incentives to participate in formal management or protection activities. As a result, in many areas existing management is ineffective, leading to unsustainable management of resource. Although result of this research supports this argument to some extent, it contradicts too. Poor performance of Jiva is not because of not having management authority; it is rather because of misuse of authority by few elites. James & Karen (1997) support this fact that dominance of few powerful people jeopardizes the community at large. All groups and interests should be represented in decision-making body (committee) so that their needs and interests can be discussed and considered while making decision. Pietrowicz (2000) has also made similar argument in his report to ChFDP. He has considered three essential conditions for CF to be successful: • The benefits to the CFUG as well as to each of the members must clearly exceed the charges involved in forest management. Any investment into the CF will have to be covered by income or other tangible benefits derived from forest to CF members. • The use rights of the CFUG must be clearly defined and secured. • The CFUG must provide equal opportunities to all members, notably to those mostly poor people entirely depending on the collection of forest products for their livelihood. Proper financial management system (C4): Financial issues often bring communities into conflict and it is even more in Nepal. Failing to manage community funds as the majority want and failing to maintain transparency may ultimately cause the collapse of the CFUG itself. It was considered as an important criterion allocating 15% relative importance in this research. Pietrowicz (2000) has argued that the benefits to the CFUG as well as to each of the members must clearly exceed the charges involved in forest management. Conditions of both study areas support that argument. Regular fund generation mechanism (each HH should pay Rs 25 (Euro 0.4)/month) has been established in Majhau. But, it has not so in Jiva. Users have not been willing to pay to the committee. They said, ‘we are not meeting our needs from the Community Forest as owner of it, instead, we have to pay if we want to get resources (timber)’. It has been realized that the elite members in Jiva are more interested to earn money rather than satisfy actual needs. An argument made by Karki & Tiwari (1998) supports this fact that the driving force has been to make money out of the commercially viable forests rather than to build a common ground for community management of forest. Jiva has earned lots of money by selling logs and roots of Khair (see chapter 4.1.2). It has also been realized that the debates regarding the share of money among different interest groups and even among committee members was one of the major reasons of conflict in Jiva. Although, auditing is regular, the majority of users doubt whether the money is spent properly. It is because of poor participation of users in decision-making and an opaque record keeping system. 52 CHAPTER 6: DISCUSSION Pietrowicz (2000) has reported that the dominance of social elite in certain CFUG committees hinders transparent and unbiased decision-making process. Although prime interest of the committee is not to sell and earn money, situation of fund management (auditing, transparency) was found somewhat similar in Majhau too. Evidences indicate that the users perceptions of financial management in both areas are not enthusiastic. Contribution in social development (C5): Contribution to social development through the income generated from Community Forest is one of the objectives of both study sites. It has been considered as a criterion for this assessment, allocating 6% relative importance. Although, it would not be fair to expect large (costly) development works from Community Forestry, some small scale development works regarding needs and interests of local people such as primary education, health, establishment of forest based small enterprises etc, are expected. Information (chapter 4.1 and appendix 4) shows that both CFUGs have collected some money (Jiva has collected considerably more money than Majhau). Both CFUGs have invested some of the earned money for several forest and social developments. The most important consideration regarding development work should be the high priority needs of the users. It would be more useful, if fund is invested in a work that ultimately helps to reduce pressure in the forest and improve socio-economic condition of the users. Jiva has spent considerable amount of money in different development works (road, temple, and plantation, see chapter 4.1), however, report shows that the major interests of most of the users were not considered while making decision. Temple and road were not major interests of them; they wanted money to be spent in income generating activities for them. Such type of disagreements were not realized in Majhau. Summary remarks: Different social aspects of community Forestry are connected each other (they are not completely independent) with cause and effect relationship. Better awareness increases willingness; willingness brings agreement and develops common understanding, which is essential for participatory approach. Unanimously developed common approach insists users to take responsibilities. Each responsible individual clearly understands his/her rights over the common properties. When the interests of users differ, achieving a self-governing solution is particularly challenging. Differences in skills and knowledge among users frequently prevent them from arriving at agreements. Unless benefits are shared equitably, Community Forestry will only contribute to the reproduction of rural poverty and lead to division and disharmony among those affected (Ostrom, 1999). It is difficult to define threshold of sustainable management. However, conventionally, it is not so difficult to say management regime is unsustainable if the performance is found to be less than average. In this sense, social condition in Jiva cannot be considered as sustainable. Haphazard formation, diverse needs and interests and poor participation of users in decision-making are major underlying reasons for this. Based on this, looking at Majhau, it should be considered as sustainable. However, it may not always be applied. Sustainable and unsustainable are relative terms unless threshold is defined or full score is met. In this regard, Social condition in Majhau is confirmed to be more sustainable than in Jiva. 53 CHAPTER 6: DISCUSSION 6.2. Ecological Condition Analysis 6.2.1. Stand Variables Distribution A distribution function shows, for a population, the relative frequency with which different values of a given variable occur. Knowing the distribution function, we can say what proportions of the individuals are within certain size limits (Freese, 1984). Result shows distribution of seedlings, saplings and basal area were normal in Majhau but not such in Jiva. It indicates that the stand composition in Jiva is not following similar pattern all over the area as in original natural forest. Several reasons may be responsible for this. Since Jiva has problems with timber smugglers and excessive firewood collectors, it may have resulted into its distribution pattern. Selective cutting of particular size results absent or minimum number of that particular tree size in the forest. Looking at significant different in seedlings but not in other variables between the study sites, it can easily be said that it is because of the different in protection system (notably, grazing control) implemented between the study sites. Majhau has controlled grazing and managed forest dividing in to several individual plots, but grazing has not been controlled in Jiva. Several studies have reported that grazing is a serious problem deteriorating ecology of the Siwalik range. Fichtenau (1998) has reported that free grazing prevent natural regeneration of the forest resource. Veltter et al. (2001) has argued that free grazing is a disastrous practice in the forest. The same was observed in Jiva. It is obvious that the seedlings are more easily affected and damaged than sapling and trees by free ranging animals. However, it doesn’t mean that seedlings are always protected in Majhau. Several evidences of damaged seedlings were found in Majhau too. It was found that the plot owner were discouraging non fodder tree species. They cut seedlings of some non-timber and non- fodder species with grass. As forest grows it starts shading grass species and reduces grass production. 6.2.2. Ecological Condition The way that users manage the resource will determine the nature of the benefits and also the sustainability of the resources. Most of the ecological indicators assessed in this research are focused to determine actual ecological condition brought by implemented management practices. The following paragraphs interpret and discuss the result of ecological indicators. Since all 14 indicators belong to five criteria, discussions are made at criterion level based on result of corresponding indicators. Specified initial ecological scenario of the area (C1): FAO (1998) has reported that baseline enables to measure and evaluate change in specific condition providing a common understanding, from the beginning, of how change will be measured. Initial information about the condition of the particular area gives an important baseline to assess changes and its trend in future. Looking at the study sites’ information, some written descriptions about the initial ecological condition were found in the both areas. However, actual forest condition such as stocking of trees, saplings and seedlings at the beginning of the CF had not been measured and specified to be used as threshold to assess change in the future. Nevertheless, stated initial scenarios of both sites were useful to perceive change. Forest and its management plan (C2): Management plan of the Community Forestry, which is also known as operational plan at local level, is a combine information of the forest; needs and interests of the users; and the way users are planning to manage the forest. It has often been reported that most of the failure cases in resource management are because of mismatch between the real condition of the 54 CHAPTER 6: DISCUSSION resource and the adopted management plan (Pietrowicz, 2000; Hobley, 1996 for example). Looking at study sites, management objectives were compatible with the condition of the forest in the both areas. However, in practice, activities have not been focused properly to achieve objectives. In Jiva, although the forest has been divided into three different blocks, there are no specific objectives related to each block. To improve forest condition with regular resource supply, users should set their own realistic objectives for each block (Hobley, 1996). Jiva has failed in this regard. But, the situation is better in Majhau. The whole forest has been divided into six blocks and five out of six have been further divided into several individual plots to protect, manage and meet each HH needs. Although both areas have an objective to promote tree planting outside the forest, result indicates no initiative has been done so far. Existence of trees in home garden (mostly fruit), around the land parcel and along the roadside indicates that people are aware and interested about TROF. However, because of very small land size and marginal productivity, tree planting in and around the land parcel seem to be less practiced. Specific plan of tree planting with other reliable and regular sources of income generating activities are needed to establish TROF that can reduce pressure in the forest. Effective implementation of management plan (C3): Result indicates that the Majhau has implemented its management plan more effectively than Jiva. Since, this criterion was given 26.5% relative importance, it has more influence in the overall assessment of ecological sustainability. Effective protection system, regular resource supply under prescribed rules, and revision of management plan on the basis of changing social and ecological scenario of the community were indicators measured to evaluate this criterion. Comparing effectiveness of protection system between the study sites, a more effective protection system was found in Majahu. It has implemented participatory protection system effectively through individual plotting system. Each HH is responsible to protect its corresponding plot. However, although controlling by forest guard is considered to be stricter that is followed in Jiva with daily patrolling, result does not support it. Several cases of violating rules were found in Jiva, but no single evidence of effective sanction was found. One reason behind may be the forest size. Although there are some debates regarding the size of forest and its users, area should not be too large for effective protection and monitoring. It has recently been agreed among DFOs in Nepal that CF area should not be more than 1 ha per HH. More effective protection in Majhau clearly indicates that participatory (whether manual or money) approach itself is a strong evidence of effective protection system as well as users group. This fact supports the argument made by Hobley (1996) that the conventional or strict protection may reflect the fragility of the users organization. In that it is easier to forbid general access to a forest than it is to control regular harvesting of products, where one group may exploit their right to use the forest at the expense of other members of the organization. Baral & Subedi (2000) have also made similar conclusion that the employment of paid watchers does not seem sustainable simply because the committee people may not be able to employ watcher any longer after the fund ceases, and that people are not ready to co-operate. Poteete & Ostrom (2002) also made same argument. Therefore, protection system in Jiva cannot be considered as an effective nor can it be considered a sustainable approach. Although the management plan has been revised, evidence does not support that the effective implementation in terms of regular resource supply and its sustainability has been ensured in Jiva. 55 CHAPTER 6: DISCUSSION Users participation to prepare the management plan was found poor in Jiva that may have negatively affected its implementation. An argument made by Banerjee (1992) supports this fact that there is risk of severe mismatch between planners’ perceptions about the needs and aspirations of the people and their actual needs. In that event the plans can quickly degenerate in to little more than arbitrary targets. This creates problems for the implementers, dissatisfaction among the targeted beneficiaries, wastage of resources and ultimate failure of the project. Management plan of the forest should be developed considering both resource potential, capacity of local people to implement and needs and aspirations of the people. It could only be possible if users are involved in every stage of its preparation. Forest structure and its production function (C4): Stand structure and its production function reveal how healthy the forest is. Stand should be able to produce different kind of products such as timber, fuel wood, fodder, pole, and NTFP to meet needs of the users. Only properly structured stand (normal forest) can supply such diverse products in perpetuity. Or, in other word, proportion of seedlings should be more than saplings and the proportion of saplings should be more than trees. Normal or original type of stand structure with capacity of supplying diverse products in sustainable basis is an indicator of sustainable management of CF in both social and ecological perspectives. Frequency of seedling, sapling and tree distribution per unit area is a major indicator of stand structure. Looking at study sites results, both areas were found to be higher frequency of seedlings than saplings and trees. In general, it indicates stand structure has been maintained in both areas. However, comparing proportional frequency distribution per hectare of seedlings, saplings and trees measured in the study sites with the stand structure as recommended by Seppanen & Weikberg (1995), Jiva was found under stocked in seedlings and saplings i.e. 4800, 1358 per hectare respectively. They have recommended that the proportion of seedlings, saplings and trees should be 5000-10000, 3000-4000 and 400-700 per hectare respectively for the Terai in Nepal. Although number of saplings per hectare was under stocked, Majhau was found to be better regarding recommended range in seedlings and trees stocking. Distribution of diameter classes is another indicator to understand stand composition. Sustainably managed forest should have larger frequency of lower class diameter. Looking at study sites, low frequency of small trees in Jiva clearly supports the fact that there is uncontrolled access for firewood collection and timber smuggling. Firewood collectors usually prefer smaller tree rather than big that need more time and energy to split. Timber smugglers also do the same. Fichtenau (1998) has also reported that low frequency of lower diameter classes indicates a predominant removal of young tress for firewood purposes. Looking at trend, both sites have been improving their stand structure since handed over. Although changes in all stand variables were not found to be statistically significant between 1998 and 2001, overall indication was positive. Result of RS data also supports this fact that the overall forest condition has been changing positively. However, field evidences clearly reveal that there is still not enough tree resource to meet the demand in the both sites. Fichtenau (1998) has also made similar conclusion that the handed over Community Forests (that were nearly depleted) in the ChFDP area can presently not fulfill the rising demand. 56 CHAPTER 6: DISCUSSION Regarding NTFP, in ChFDP a lot of hope and expectations are placed on the economic potential of the vast variety of NTFP (notably; fruit, herbs and medicinal plants) that are being extracted from the forest and marketed locally (Pietrowicz, 2000). However, little data is available on the currently available products, exact places of origin and quantities involved. In most of the FUGs, management of NTFP is often neglected and their role in community development is poorly defined (Baral 1998). The same were observed in either site. In spite of improving grass production in Majhau, no other initiatives regarding NTFP were observed in the both sites. It has been realized that there is insufficient knowledge and information to properly assess the opportunities of NTFP. Capacity of ecological and protection function (C5): Looking at results of the both study sites, although do not indicate negative trend, about 47% area in Jiva and 21% area in Majhau are still under degraded forest. It indicates ecological condition in Jiva is not good as compared to Majhau. It has been realised that the open grazing and dense invasive weed (Banmara) are the main reasons for the more degraded forest in Jiva. Nevertheless, results of classified images indicate that the degraded forest has been reduced in the both areas. Jiva has rehabilitated about 50% of the degraded forest since 1992. Looking at forest and other ecological condition at the surroundings, although overall trends are found to be positive, there are still lot of degraded areas that may threaten sustainability in the future. Summary remarks: One of the main aims of resource management is the avoidance of resource degradation. In this regard, resource management goals should be a level of ecological sustainability “that gives future generations the option to continue such management or liquidate the resource” (Bromley, 1986 cited in Pokharel, 1998). Looking at the study sites, the overall ecological conditions in both areas (that are above the average score) seem not to be deteriorated. However, some indications of threats to its sustainability were observed. Prevailing threats observed in Jiva was ineffective implementation of management plan resulting in poor regeneration quality and increasing invasive weeds instead, which indicates an active management (effective implementation of plan) is required to maintain sustainable protection and production function of the ecology. Although the differences were not found to be significant between the study sites, however, indication was that the overall ecological condition in Majhau is comparatively better than in Jiva. 6.3. Relationship Between Social and Ecological Condition Sustainable CF is essentially about sustainable management of both resource and resource dependent people. Society depends on forest for a number of goods and services. The forest has to serve as a resource to supply goods and services required by the society and for that maintenance of production potential of the ecosystem is necessary. The two-way interaction determines the relationship between forest ecosystem and the society. In this sense, the meaning of sustainable management of forest is simply the sustainability of that inter-relationship. It has been believed that the social and ecological conditions of the rural community are correlated with each other. Finding of this research also supports that correlation does exist between them. However, some contradictory findings have also been reported. Regarding finding of this research, apparent contradiction is realised with the finding by Yadav & Branney (1999). They found no correlation between the level of activity of FUG in managing their forest and their level of awareness or institutional development. According to them, in Midhills of Nepal, some FUG are managing their 57 CHAPTER 6: DISCUSSION forest well, but may have poor levels of participation of users in planning, decision making, implementing and benefit sharing- again the poor and disadvantaged groups may be missing out. However, it is not so clear in the conclusion made by Yadav & Branney (1999) whether they looked at the perspectives of sustainability or not. It has also been found in many cases that Community Forest could be protected without considering participation of all users if excluded people are socially and economically dominated by the committee members (poor fears to act against elite); and if they are not dependent and/or interested on forest for their livelihood. Looking at situation in the Midhills and the Terai in Nepal, level of users’ dependency over forest is different. Some people in Terai are fully dependent on forest products (firewood and illegal timber selling) for their livelihood. But, it is seldom in hills, rather rich people use more resources because they usually keep more livestock and need more fodder, firewood and leaf litter. However, in either case sustainability could not be expected. Various authors (Fichtenau, 1998; Baral & Subedi, 2000; Hobley, 1996; James & Karen, 1997; Prabhu et. al, 1999) support this fact. Poteete & Ostrom (2002) argue that the attribute of forest and of forest users are most likely to be associated with efforts by users to organize themselves to protect forest resources. Observed evidences, analysed results and cited literature clearly indicate that there is significant correlation between social and ecological condition that is essential for the sustainability of Community Forestry. However, result has raised as many questions as it has provided answers. The key question is, what type of relationship does exist? Does one variable always depend upon other or not? If yes, which is what? Some contradictions among several authors do exist regarding nature of relationship. Hobley (1996) contradicts with resource scarcity theory of Gilmour and Fisher (1991). Poteete & Ostrom (2002) describe a curvilinear relationship between group size and effective collective action for forest management. Another apparent question can be raised is about the validity of the result in all aspects of social and ecological condition over all Siwalik range. This study has only been focused on forest users group management issues, not all social aspects of the two CFUG. Many other things are changing in the areas studied such as health; education; agricultural services; livestock farming; politics; roads; electricity. All these are also likely to have impacts on local livelihoods, local needs and eventually in the forest condition. No attempt has been made to separate out such impacts, but simply to recognize that they exist. In the context of limited time; efforts; and objectives, answering those questions were beyond the scope of this research. 6.4. Trend in Social Condition Assessment of existing indicators only may not necessarily reflect the trends of changes happened that are essential to understand whether changes are positive towards sustainable management or not. Although some passiveness and weakness do exist, overall trend (notably awareness, regularity in meetings and discussions) indicates social condition in Majhau is significantly moving towards sustainable management of Community Forestry. Similar finding has been reported by Fichtenau (1998) that positive signs are found to be raising awareness among the local population towards forest related aspects in the ChFDP area. At the same time, however, some critical issues such as social conflicts within the users group have also been reported to be raised. Looking at Jiva, social problems such as conflicts regarding users rights, decision-making and benefit sharing have been prevailing from 58 CHAPTER 6: DISCUSSION the beginning. Trend in Jiva is very much similar to the finding by Baral & Subedi (2000). They have reported that there is a conspicuous degree of positive change in forest condition after handover in Siwalik, but several practical and social anomalies also prevail. Such anomalies essentially constitute of inequity and unfairness in the local level and in terms of long-term sustainability of forest resources. Nevertheless, result in Jiva should not be perceived as negative impact of Community Forestry in social condition. There are several positive signs but not statistically significant so far. 6.5. Trend in Ecological Condition Prefeasibility study report for ChFDP in 1996 has reported that the forest situations in the area is characterized by persistent deforestation and sever ecological degradation. Annually repeated human- induced forest fires cause damage to the small seedlings and strongly hamper the natural regeneration of the degraded forests by preventing the seedlings from growing in to larger- sized poles and trees. Uncontrolled and excessive grazing by the huge and rapidly growing livestock population is another prevailing factor, as it gives rise to an extensive browsing of seedlings and permanent soil compaction by hooves. Similar situation had also been reported by Subedi et al., (1992). Although the reports mentioned above are based on the whole Siwalik range of Siraha and Saptari districts, they make clear that the ecological condition elsewhere in Siwalik range was degraded before implementation of the CF. Moreover, background description of the study areas presented in chapter 4 support the fact that ecological condition of the both areas was very degraded before being handed over to the user groups. Looking at the results in the study sites, Majhau has shown a significant positive trend in ecological condition since formation of FUG. Fichtenau (1998) has reported that positive signs are found to be rising towards forest related aspects, in many cases a better fulfilment of demands for fodder, fuel wood and timber. Similarities can be found in the results of this study too. For example availability of grass has increased in Majhau. However, it does not apply in the case of timber. Users are now actually getting fewer timbers from Community Forest than they were before hand-over even though the availability of timber has increased. It has often been reported that the areas with open grazing and social conflicts are not achieving the same progress as other areas do (Fichtenau, 1998 for example). Looking at situation in Jiva, the same can be realized. Although some positive changes were observed, overall trend in ecological condition in Jiva was not found to be significantly positive. Free access for fuel wood and grazing (even for outsider) may have affected stocking of small size trees and seedlings. Nevertheless, probability of positive trend (p=0.145 is near to stated α = 0.1 ) is still higher and considerable. Occurrence of human induced fire has been reduced significantly. Regarding change in stand stocking, it should not be forgotten that the significant test was between inventory data at 1998 and 2001 (three years), which may not be sufficient time to expect significant change in forest condition in particular at the area of low increment. GTZ (1996) has reported that due to very slow increment rate (2 m3/ha) of forests it is impossible to assess any significant changes of product availability over short time span. However, no minimum time span that may require for significant changes has been recommended. 59 CHAPTER 6: DISCUSSION 6.6. Trend in RS Data and its Comparision with Field Data Image time series are often used to identify and monitor land cover dynamics. Usually classification is done to discriminate different cover types. It also serves to assess changes by superimposing and comparing classification of the images taken in different periods. The basic premise of the change detection through remote sensing is that that the spectral signatures change commensurate with the change in the land cover (Roy, 1999). Positive trends in forest condition observed in classified images supports the trends obtained from field inventory data and other reports mentioned above that indicate the overall trends were positive between 1992 and 2001. Trends at the surroundings were also found to be positive in terms of forest condition. However, trends around the Jiva were not confirmed to be positive before 1999. According to office reports, most of the areas near by Jiva have been handed over as CF after 1996, which result positive change at 1999. And, it supports the fact that the CF has positive impact to rehabilitate the Siwalik areas. However, some dissimilarity between information from RS data and field inventory data were also observed. In both study sites, RS data confirmed (beyond the classification error) the overall positive change in forest condition between 1999 and 2001 that was not confirmed by significance test of field data between 1998 and 2001. At the same time RS data also indicated some areas of degrading quality (dense to open for example) but such indications were not identified from field measurements, which in fact is very difficult to be identified unless the same sample points (permanent plots) are measured in the successive measurements. And, such successive measurements of permanent plots were not available. Since RS data covers whole area, exact area of change can be detected comparing time series data. Nevertheless, it has been identified during fieldwork that some areas far from the users’ village were still in pressure from illegal cutting in the both study sites. It has obvious even near to the village in Jiva because of free grazing and fuel wood collection by children. Children usually do not go far to collect resources. Although it was not so obvious, however, some evidences of illegal cuttings in block number six (Northern part) that has not been divided in to individual plots were found in Majhau too. Although it was not confirmed beyond the classification error, the occurrence of negative trend in forest condition indicates a risk of degradation again if management fails to meet users demands. Notably, these types of risks are more pronounced in Jiva. In the interpretation of the trends from RS data, it is vital to have an accuracy assessment of the classification. Without an accuracy assessment, it is easy to make false conclusions about trends, which are then followed by false interpretation. Only when trends lie outside error limits should they be considered seriously (Dymond, 2001). Several reasons might have contributed error while processing and classifying RS data. Major reason that might have contributed error is seasonal differences (differences) between images and fieldwork. Different images were taken in different seasons i.e. ASTER 2001 was taken in March, TM 1999 was taken in April and TM 1992 was taken in November. Notably study sites are characterized by deciduous forest that has high phenological variation between dry and wet season, where March is season of leaf shedding; April is beginning of spring; and November is growing season (post rainy season). At the time of leaf shedding there is no 60 CHAPTER 6: DISCUSSION photosynthesis causing more reflectance in red band and reflectance in NIR may decrease. At that time, dense forest may also be appeared as degraded forest. Similarly, seasonal differences between images and ground truth collection also do exist. Field data were collected in the growing season (September/October). Other reasons that could contribute error are: spatial resolution and spectral differences between images; cloud cover and other environmental disturbances and differences; differences in the radiometric performance between sensors or change in the performance of an individual sensor overtime; variation in solar radiance; zenith angle; solar azimuth; and spatial mis-registration of images as reported by Lunetta & Elvidge (1999). All of these factors might have contributed some error during classification. There is low classification accuracy for degraded forest in the both study sites. In both cases misclassifications are mostly between degraded and open forest. Since the base of discriminating forest was crown cover (%) and technique used to measure crown cover was ocular, some errors were expected. Rembold et al. (2000), have also reported same type of classification problems. Within remotely sensed images, a significant proportion of pixels may be of mixed class composition. Pixels at the boundary between cover classes may contain mixed reflectance. Nevertheless, obtained overall accuracies (81% in Majhau and 79% in Jiva) for both areas are acceptable regarding interest of using RS data that is to interpret and verify general trend in ecological condition combine with ancillary data. Spectral classification alone would not be sufficient to conclude about the correlation between field and RS data particularly in the context of Community Forestry where the areas are mostly small (few hectares) and different management prescriptions are applied in different blocks. To find relationship, more effort to collect ground truth (establish permanent sample points and measure in time series); aerial photos; high-resolution images such as IKONOS; and more advance techniques of image processing and classification (FCD mapper, neural network for example) may be needed, which was beyond the scope of this research. 6.7. Problems and Constraints Although the stated objectives have been met by the results to a considerable extent representing actual field condition with possible precautions taken, the findings may still be subject to errors due to some constraints and problems encountered. Available time was one constraint limiting study sites into two CFUG. Result would be more valid for whole Siwalik, if more CFUG could have taken as study sites. So far more than 100 CFUG have been handed over in the Siwalik range of Siraha and Saptari districts. Reliability would also be improved if more samples HH were taken with sufficient time for rapport building. Since there were no established standards indicators; verifiers; and thresholds, measuring indicators and their trends were difficult. Defining thresholds based on descriptive information; defining locally adjusted indicators and their verifiers; allocating relative importance; interpreting and scoring indicators were subjective and could have resulted in inconsistencies. Since images were not from same sensor and same season, error could have introduced during image classification; particularly in 1992 and 1999 images that classifications were done mostly based on spectral characteristics (calibrating ground truth 2001). 61 CHAPTER 7: CONCLUSIONS AND RECOMMENDATIONS 7. CONCLUSIONS AND RECOMMENDATIONS 7.1. Conclusions Based on the data analysis results and discussions in the preceding chapters the conclusions of the study are presented as following: Objective 1: To assess and compare the sustainability of two Community Forest Users Groups (CFUG) in Siwalik range by analysing social indicators. Research question 1: What is the trend in social condition for each Community Forest Users Group? In general, Community Forestry seems to be effective in improving social condition of users group. However, the level of effectiveness depends upon several social aspects. In Majhau, most of the social aspects have been institutionalized since its formation. Regularities in meeting and assemblies; improvement in awareness; fund generating mechanism; equity in benefit sharing; and conflict management mechanism are some of the most important achievements in Majhau. The trend in social condition in Majhau shows an improvement and is highly conducive towards sustainable management of forest resources. In Jiva, however, the overall trend in social condition is not significantly positive. Although some aspects such as awareness and contribution in social development are appreciated, the rest of highly important social aspects are not significantly improved. Poor awareness; lack of self motivated participation; diverse needs and interests; haphazard decision-making; and prevailing conflicts are major factors resulting in marginal social condition in Jiva. Research question 2: Which Community Forest Users Group is more sustainable based on social indicators? Based on the result of assessed social indicators, there is a significant different in the social condition between the two study sites. Some major criteria contributing such apparent differences are: incorporation of real users; status of users rights and responsibilities; and equity in benefit sharing. In each criterion Jiva has very weak performance. Another underlying factor in Jiva is conflicting interests among users. Analyzing the differences with some supportive previous findings, it can be concluded that the Majhau CFUG is comparatively more sustainable in its social condition than Jiva CFUG. The current social condition in Jiva cannot be considered sustainable. Objective 2: To assess and compare the sustainability of two Community Forests in Siwalik range by analysing ecological indicators. Research question 3: What is the trend in forest and other ecological condition for each Community Forest? In overall the trends in ecological condition after formation of CF are positive. However, level of trends towards sustainable management differs from community to community. Different social, managerial and ecological factors are responsible for that. Effective implementation of the operational plan (approved by professional) is the most important factor. Based on information analyzed and other 62 CHAPTER 7: CONCLUSIONS AND RECOMMENDATIONS supportive previous findings, conclusion can be made that Majhau has positive trend in its overall ecological condition after formation of Community Forestry. However, it is not so in Jiva. There is no sufficient evidence in Jiva to conclude that the trend is significantly positive. Nevertheless, analysis result is sufficient to conclude that the forest and other ecological conditions in overall have not been deteriorated after the formation of CF in Jiva too. Research question 4: Which Community Forest is more sustainable based on forest and other ecological indicators? There is no so much difference in the overall ecological condition (at present) between Majhau and Jiva to be concluded as significant. Nevertheless, there is stillroom to argue that Majhau is comparatively more sustainable in its ecological condition than Jiva. Majhau has better status at each criterion level. It has significant positive trend in its ecological condition since its formation. And analyzed result has also been supported by other related findings to conclude that Majhau is comparatively more sustainable than Jiva. In Majhau, there are promising attempts to effectively manage the CF for the benefit of the users in a sustainable manner. Objective 3: To identify the relationship between social and ecological condition of the Community Forestry. Research question 5: Is there any relationship between social and ecological condition of the Community Forestry? Yes, social and ecological conditions of the Community Forestry are significantly related with each other. Both social and ecological conditions in Majhau are comparatively better than in Jiva. It can be said that if social condition is improved, collective action becomes effective and results into improved ecological condition. This fact with support of several previous findings, it can also be concluded that the sustainable inter-relationship between society and natural resource is essential for the sustainability of each. Objective 4: To identify and compare the changes in forest condition using satellite imagery. Research question 6: What is the trend in forest condition observed on satellite imagery? Degraded forests in both areas and even in surroundings have been reduced. Open forest and dense forest have increased. In overall, the trend in forest condition of both Majhau and Jiva are observed positive on satellite imagery since 1992. However, observed trends are not always similar. Observed positive trend between 1999 and 2001 is more apparent than the trend between 1992 and 1999 in the both areas. The trend at the surroundings of Jiva is not positive before 1999. Some negative trends although are very small as compare to positive also observed on satellite imageries in the both areas. Research question 7: 63 CHAPTER 7: CONCLUSIONS AND RECOMMENDATIONS Is there any difference between the trends obtained from field (social and ecological) indicators and satellite imageries? If yes, what may be the reasons? There is no much difference between the trends in forest condition obtained from field indicators (social and ecological) and observed on satellite imageries. In overall, both indicate positive trend in forest condition in the both study sites. However, exact locations and its extent of changes are observed on satellite imageries but not from field indicators. Area coverage and associated errors in each method may have resulted dissimilarities. Satellite imageries cover whole area and can give both location and extent of changes but it is difficult to detect exact locations of changes from field data. 7.2. Recommendations Social: • Excluded real users must be incorporated and conflict management system must be institutionalised amending existing constitutional rules if needed (particularly important for Jiva). • Awareness most be created at each HH level regarding rights and responsibilities to be taken for sustainable management of Community Forestry. • Concentrated efforts should be given to ensure that dis-empowered groups are not marginalized in decision-making. Ecological: • Operational plan should be revised periodically regarding changing needs and interests of users and availability of resources. Free grazing in Jiva should be controlled. • Appropriate silvicultural operations such as thinning, pruning and selective cutting should be practiced to harvest allowable products based on annual increment. • Forest based income generating activities should be promoted exploring NTFP and its market. This may include training for cultivation of selected herbs as cash crops but not agricultural crops. • TROF should be promoted by introducing/producing and distributing economically viable multipurpose tree species. Research: • Further research to assess relationship between group characteristics such as group size; heterogeneity in needs and interests and effectiveness of collective action would be required to avoid impractical plan to be implemented. • For the vast and probably promising field of NTFP a research would be required in order to assess the status, the modes and dynamics of exploitation, markets, uses as well as production potentials for species of promising economic value. • A research about how TROF could be promoted particularly among the people who are holding small land size and mostly depend upon the forest for daily needs would be required. 64 REFERENCE REFERENCES Arnold, J. E. M., & Steward, W. C., (1998). Common property resource management in India. 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Resource demand (fuel wood, fodder, timber etc) 2.Detail inventory report (stocking of trees, saplings, regeneration, blocking etc) 3.Executive committee (number, power and 3.Resource capacity for sustainable production and sanction, election etc) the ratio of multiple products availability over time. 4. Decision making systems 4. Defined objectives and proposed activities 5. Fund mobilization/ record keeping 5.Operational calendar (protection, silviculture, harvesting, plantation etc.) 6. Provision of punishment against rule breaking 6.Distribution (flow of timber, fuel wood and other benefit sharing) 7. Conflict resolution mechanism 7.Adoption of soil and biodiversity conservation activities 8. Committee meeting and general assemble 8. Income generation activities Adopted from CF Guideline HMG (1995) Appendix 2: Relevant set of C&I adopted from different authers Since both social and ecological aspects are equally important, selected C&I are grouped under two basic principles. Principle 1: Social sustainability of the Community Forestry is assured. Criteria Corresponding indicators Example of important verifiers 1. Size of user ● Users are properly identified and ● Existence of real users not being incorporated. group and incorporated. ● Existence of demarcation (pillar or natural their ● Resource boundary is clearly defined. boundary). resources. ● There is no boundary dispute. ● No evidence of boundary disputes. ● Location and size of the forest is ● Effectiveness of protection. manageable. -Forest is near to the village and is under controlled. ● Users composition is not complex. ● Homogeneity in needs and interests. 2 Users ● Users’ develop their constitution. ● Existence of registered constitution. rights and - Every mature user knows about it. responsibilit ● User rights and obligations are ● Awareness of peoples on their rights and ies (legal cleared. obligations. frame ● Rules are effectively implemented. ● Evidence of sanction and its acceptance by the work). people. ● Rules and regulations are periodically ● Evidence of changes in rules and regulations revised. overtime. 3. Users ● There are regular meetings and ● Frequency of, and attendance of general member participation assemblies. at the meetings and assemblies. in decision ● Decision making system is ● Users participation at the meetings and assemblies. making and participatory and transparent. benefit ● Women and marginalized people are ● Percentages of them in decision-making body. sharing actively involved in participatory 70 APPENDIX (Community decision making. ● Level of consensus and satisfaction of the users management). ● Equity in benefit sharing is assured. on benefit sharing mechanism. ● Leaderships represent all groups and ● Evidences of election for leadership. factions within the community. ● Conflict resolution mechanisms are ● Evidences of conflict resolution without external effectively implemented. support. -Participants’ understanding on discussion. ● Records are up to date and ● Good and transparent record keeping system transparent. (access to all users). 4. Proper ● Existence of internal alternative ● Fund generation doesn’t cause overexploitation. financial funding mechanism rather than selling management timber. ● Every adult user in the community can explain system. ● The group initiates fund generation about the mechanism. mechanism through consensual decision. ● Betterment of resources such as plantation and ● Priority is given for betterment of protection. And financial report of expenditure. resource while expending fund. ● System of providing loan for income generation ● People are benefiting from community activities to the marginalized group. fund. - Evidences of fund used for other social works such as education and health. ● Fund is properly used and audited ● Existence of audit report approved by users transparently. general assembly. Source: (Hobley, 1996; Ostrom, 1990; Ritchie et al., 2000; ITTO, 1998; Pokharel, 1998; and Singh, 1999; James & Karen, 1997) Basic principle 2: Ecological sustainability of the Community Forestry is assured. Criteria Corresponding Indicators Example of important verifiers 1. Initial ● Historical background of the forest is ● Written document on the basis of experience and ecological clearly specified. evidences such as traditional management system, scenario of timber in old house and stumps in the forest. ● Initial baseline on production function ● Forest inventory record on forest structure, the area. of the forest has specified. species composition and production capacity. ● Initial condition of ecological and ● Maps, records and experiences of the old users. protection function are specified. 2.Forest and its ● Management objectives are ● Ecological condition, inventory data and mgmt. management compatible with ecological condition Plan. plan. ensuring its sustainability. - Written strategy for the sustainability. ● Forest is divided in to different zones ● Existence of different blocks with specification of for different use and activities different use and activities. accordance with resource potential. ● Specific plan and consensus for particular site of ● Social, cultural and traditional aspect socially, culturally and traditionally important. of forest are recognized in plan. - Knowledge of the people on that aspect. ● There are different rules and ● Existence and specification of working calendar regulations regarding different for different activities. activities and resource collection. -Fixed schedule and quantity of resource ● Tree resources out side the forest collection and its knowledge among users. (TROF) is promoted to meet demand. ● Interest and land holding size of people. Existence of trees in the village or outside forest. 3. Forest ● Operational plan (OP) is periodically ●Existence of amended plan and specification of reflects effective amended and implemented according blocks and corresponding activities, times and implementation to ecological condition. quantity. ● Silvicultural operations are ● Evidence of thinning, pruning and regulated of plan. implemented. feeling. ● There is regular supply of resources ● Existence of forest product residuals such as in sustainable basis. bedding of livestock’s in the users house and their satisfaction. 71 APPENDIX ● Implemented protection system is ● No evidence of damage such as grazing, fire, effective. illegal cutting and encroachment. 4. Forest ● Stand composition is maintained ● A dense stable forest with a structural structure and properly. comparable with that of the original forest of the its ● Stand stocking is improving towards region. meeting demands in sustainable ● Harvesting system under management production basis. prescription. function is ● Different blocks are producing -Demand and supply condition. maintained. different products to meet multiple ● Forest configuration and evidences of use and needs. satisfaction. ● None timber forest products are ● People’s knowledge about availability and promoted according to demands of collection methods people and local market. -Evidences of collection and use. -Specific plan initiated by CFUG. 5. Capacity of ● Vertical structure of the forest is ● Stratification of forest canopy, varied trunk ecological maintained. diameter and rich floor with seedlings. and ● Capacity of ecosystem to regenerate ● Maintained species richness and restored animal naturally is ensured. habitat. protection ● Soil conservation is assured. ● No evidence of landslide and soil erosion. function is ● Degraded areas are rehabilitated. ● Plantation, regeneration and habitat management maintained. activities conducted. Wildlife observed. ● Surrounding ecology of the study ●Condition of surrounding forest and its possible areas are not deteriorated. consequence in future. Source: (Ostrom, 1990; Ritchie et al., 2000; ITTO, 1998; Pokharel, 1998; Singh, 1999) Appendix 3: Locally adjusted indicators for the study area Regarding management objectives and local socio-ecological conditions of the case studies, generic (relevant) set of C&I (appendix 2) were selected, verified and readjusted to fit at local condition of the study sites using MCA approach. Final set of Principal, Criteria, Indicators and corresponding verifiers for both social and ecological assessment are given below in appendix 3.1 and 3.2 respectively. 3.1: Final list of Criteria, Indicators and corresponding Verifiers for the assessment of social condition in the study sites. Principle: Social sustainability of the Community Forestry is assured. Criteria Indicators Corresponding verifiers R Methods of I assessment 1. Recognition 1.1 Traditional and real users are Evidence of real users not being H Interview and identified and incorporated. incorporated. Observation incorporation 1.2 Need and interest of users are Homogenous community in their M Interview of real users. similar. needs and interests from forest. Records 1.3 Relation with other Regular meeting, discussion and L Records stakeholders is good. communication. Observation 2. Secured 2.1 Users are aware regarding their Level of awareness is high. H Interview users rights rights and responsibilities. Appreciative users ownership and specified feeling. responsibilities 2.2 Existence of participatory rules Participatory registered constitute. H Interview . and its effective implementation. Evidences of sanction and consensus. Discussion 3. Users 3.1 Leaderships represent all Representation of women and L Interview participation in groups and factions within the marginalized users in key positions. Impression. decision- community. Devoted leadership. 72 APPENDIX making and 3.2 Conflicts are managed as fast Recent cases of conflict managed. M Interview benefit sharing. as possible. Mechanism of listening and dealing observation with disputes. 3.3 Decision making system is Regular meetings, users H Interview participatory and transparent. participation, open discussion and Office records decision by consensus. 3.4 Participatory benefit sharing Support and satisfaction of people H Interview mechanisms are practiced. on benefit sharing mechanism 3.5 Interest of women and Response of those groups during L Interview marginalized people are taken interview. Participation in Office record in to account in planning and workshops and trainings conducted decision-making. by DFO and ChFDP. 3.6 Records are up to date and Good and transparent record H Interview transparent. keeping system (access to all users). Records 4. Proper 4.1 Internal fund / income Income generating activities, M Interview financial generation mechanisms are prescribed sale of products and Office records management established. users contribution. system. 4.2 Proper fund management Account, accounting systems and H Interview mechanisms are implemented. transparent audit reports approved Records by user’s assembly. 5. Contribution 5.1 Community is benefited from Use of funds in different social M Interview in social development works. developments activities. Records development. 3.2: List of verified C & I and corresponding verifiers for ecological sustainability in the study sites. Principle: Ecological sustainability of the Community Forestry is assured Criteria Indicators RI Corresponding verifiers Methods of assessment 1. Initial 1.1 Initial forest and ecological L Written documents and experiences of Interview, ecological condition is specified. old local peoples. Maps and photos. records, scenario of image area. processing. 2. Forest and 2.1 Management objectives are H Existing operational plan and its Interview, its compatible with ecological compatibility with ecological condition operational management condition ensuring its of the area. plan review. plan. sustainability. 2.2 Social, cultural and M Existence, recognition and protection of Interview, traditional aspect of forest socio-cultural aspects of forest. plan review, are recognized. observation. 2.3 Forest is divided in to Existence of different blocks and Interview, different zones for different justification. plan review use and activities in and accordance with resource observation. potential. 2.4 Tree resources out side the M Extension, training and nursery Operation forest (TROF) is promoted development activities conducted. review and to reduce dependency in the Interest and land holding size of people. observation. forest. 3. Effective 3. Implemented protection H Existing protection system and Interview, implementation system is effective. effectiveness such as evidences of human sample plots on of damage i.e. grazing, cutting, fire. ** observation. management 3.2 Operational plan (OP) is H Existence of amended plan and Interview and plan. periodically amended and specification of blocks and plan review. implemented according to corresponding activities, times and ecological condition. quantity. 73 APPENDIX 3.3 Forest resources are used H Existence of harvesting prescriptions, Interview, properly ensuring its effective implementation and sampling sustainability. monitoring mechanisms. Removal of plots, records, dead dying trees. Income from resource and selling. observations. 4. Forest 4.1 Stand composition is M Stable stand structure (seedlings, Sampling structure and maintained properly saplings and trees composition). RS data its production 4.2 Stand stock is improving H Trends in BA and saplings (stocking). Sampling function is towards meeting demands. And its situation in comparison to RS data maintained. resource demand. 4.3. NTFP is promoted M Availability of NTFP, existence of Interview, according to demands of management system and production. Its sampling people and local market. contribution in HH income. observation. 5. Capacity of 5.1 Degraded areas are H Plantation, regeneration and habitat Interview, ecological rehabilitated. management activities conducted. sampling and Wildlife observed. Classified maps for plots, RS protection different years from RS data. data. function is 5.2 Surrounding ecology of L Condition of surrounding forest and its Observation maintained. areas are not deteriorated. possible consequence in future. RS data 5.3 Soil conservation is L Evidences of soil erosion (**). Classified Observation assured. images of different years. RS data **: Negative verifiers 74 APPENDIX Appendix 4: Questionnaire (Check list for semi-structured interview) SOCIAL DATA COLLECTION FORM (SEMISTRUCTURED QUESTIONNAIRE) FOR MSc RESEARCH CASE STUDIES: MAJHAU CFUG SAPTARI AND JIVA CFUG SIRAHA, NEPAL. SEPTEMBER/OCTOBER 2001 Data CFUG name:…………… Address:………… Formation date:…………… Total HH: ………… Sample HH no: Name recorder:………… Name interviewee: … … Age: …... Sex: M/FM • What do you know about the CF? Are you a user of any CF? • Why do we need CF? • Do you know the name of your FUG? • Can you explain how your CF has been formed? • Is there any other CF near by your village? About constitution: • Do you know what is user’s constitution? • Do you have it in your group? • Why do you need it? • Who made it and how? • What does it really do? • Have you ever read it? If no how did you know about it? • Has the constitution been changed ever after its registration? How many times and why? About operational plan (OP): • Do you know what CFUG operational plan is? • Do you have OP in your group? If yes, who and how did it make • Why do you need OP? What does it really do? • Have you ever read OP?……….. If no how do you know about it? • Do you think OP really been implemented and every users are following the rules that written in the OP? Has the OP ever been changed after its first approval? • If yes why and how? If no, why? Are there any disagreement within CFUG regarding implementation and revision of OP? About protection and management system: • How far is your forest from your village? • Who usually involve in forest product collection from forest? • Do you know boundaries and total area of your CF? • How are you being involved in protection of the forest? • Do you agree with existing protection system? If not, have you ever try to improve? • If yes, what happened after that? • What types of forest products do you need for your daily need? • Are you regularly getting your needs from your CF? Is that sufficient? • If not how are you managing your need? • How do you collects different types of products? • Is there any systematic ways of collecting products? …… If yes what are they? • Do you know about thinning, pruning, selective cutting etc.? • If yes, what types of operation have already been done and why? • Have you ever been trained on the techniques of such operation? 75 APPENDIX About executive committee: • Do you know what is difference between user committee and user’s executive committee? • How many members are in your user’s committee? ……. How many women? • Have you ever been executive committee member? • What do you think different between general user and committee member? • How the committee has been formed and why? • How many times the committee have been changed and why? About meeting and assembly: • Are their regular meeting and general assembly in your CFUG? • If not what might be the reason? • What types of discussion, debate and decision usually make in meeting and assembly? • Have you regularly go to the meeting and assembly? • How much users usually participate in meetings? • How do usually decision are done? About benefit sharing and decision-making: • How do decisions are made usually? Have you ever participate? • What about women? Do they have different interest? If yes, how are they considered? • From where usually CFUG get income? • Do you know how much money your CFUG has? If yes how do you know? • Who usually handle that money? • How the money has been spending? And what for? Who usually decide about such matter? • Do you think the money has been spending as it supposed to be? • Are all users benefiting?………. If not, can you explain the reasons? • Are they’re regular auditing? When usually it happens and who do it? • Do you think you can ask and check the record of user’s committee? About right and responsibility: • Do you think you have some responsibilities towards the better management of your CF? • Are you fully exercising your right and responsibilities? If not, why About conflict and management: • Are there any conflicts in your CFUG? If yes, with whom and why? • Have any conflict been resolved so far? If yes how? • What is about distant user and close user from the forest? About the trend and sustainability: • What changes do you think happened after formation of your CFUG comparing before? • Are you getting your needs in better and regular, controlled and managed way than before handing over to the CFUG? Can you explain how and because of what? • Do you think forest condition is improving? Can you give some example? • What types of affect might have being in surrounding government managed forest? • Have you realized any problems regarding illicit cutting, grazing, encroachment and boundary dispute? • How long do you think this forest will be managed as CF? • What may be the threats for its sustainability? Government? User themselves? • Because of bad management? Because of more demand than the productivity? Or any reasons other? • Are there any income generating activities going on? If yes what are they? • What about low cast and marginalized people? Are there any specific plans for them or not? Do you think it is necessary to be such plan? If not what would happen? • What else do you want to say more? 76 APPENDIX Appendix 5: Data sheet for office record review 5.1: Office record Majhau SN Activities 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 Average Target 12 12 12 12 2 12 12 12 12 12 Meeting Done 6 8 8 7 6 10 5 8 7 9 7.4 1 (No.) Progress 50% 67% 67% 59% 50% 84% 47% 75% 58% 75% 63% Target 1 1 1 1 1 1 1 1 1 1 Assembly Done 1 1 1 1 1 1 1 1 1 1 1 2 (No.) Progress 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Demand NA NA NA NA NA NA 50 50 50 50 Timber Capacity NA NA NA NA NA NA 23 23 23 23 3 (M3) Supply NA NA NA NA NA NA 20% 20% 20% 20% 20% Demand NA NA NA NA NA NA 612 612 612 612 Fuel wood Capacity N A NA NA NA NA NA 226 226 226 226 4 (Ton) Supply NA NA NA NA NA NA 40% 40% 40% 40% 55% Demand NA NA NA NA NA NA NA NA NA 66500 Capacity NA NA NA NA NA NA NA NA NA NA 5 Grass (ton) Supply NA NA NA NA NA NA 60% 60% 60% 60% 70% Target No No No No No Office No No No No Developme Done Individual plots Office Grass plantation nt 6 Works Progress 100% Protection Target Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes (Mechanis Done Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes 7 m) Progress 70% 75% 75% 75% 80% 80% 80% 80% 80% 80% 78% Target 1 1 1 1 1 1 1 1 1 1 Done 0 1 1 1 1 1 1 1 1 1 8 Audit Progress 0% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Target There were no target made 3852.0 3852. 3852.0 3852.0 Done 9 Income Progress Average progress: 70% Target There were no target made Done * * * * * * * 10 Expenditure Progress Remaining balance now = 8400.00 Average progress: 70% Faced Few Few Few Few Few Few Few Few Few Few Solved Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes 11 Conflict Progress 75% 75% 75% 75% 75% 75% 75% 75% 75% 75% 75% Annual Plan No No No No No No Yes Yes Yes Yes 12 plan Progress NA NA NA NA NA NA 70% 70% 70% 70% 70% Overall Average: 71% NA= Not available 77 APPENDIX 5.2: Office record Jiva SN Activities 1994 1995 1996 1997 1998 1999 2000 2001 Average Target 12 12 12 12 12 12 12 12 Meeting Done 15 13 14 11 4 2 5 8 9 1 (Times) Progress 75% Target 1 1 1 1 1 1 1 1 Assembly Done 1 1 0 0 1 3 2 0 1 2 (Times) Progress 100% 100% 100% 100% 100% 100% 100% Demand NA NA NA NA 104 104 104 104 Timber Capacity NA NA NA NA 150 150 150 150 3 (M3) Supply NA NA NA NA <20% <20% <20% <20% 20% Demand NA NA NA NA 996 996 996 996 Fuel wood Capacity NA NA NA NA 1000 100 1000 1000 4 (Ton) Supply NA NA NA NA 70% 70% 70% 70% 70% Demand NA NA NA NA Grass Capacity NA NA NA NA Free ranging area, no cutting grass 5 (Ton) Supply NA NA NA NA 25% Target No There were no planned target but committee decided Developme Done O* N* S* WS* T* M* R* 6 nt work Progress Good Good Good Good Good Good Good Good Protection Target Yes Yes Yes Yes Yes Yes Yes Yes (Mechanis Done User watcherwatcher watcher watcher watcher watcher watcher 7 m) Progress 60% 60% 60% 60% 60% 60% 60% 60% 60% Target 1 1 1 1 1 1 1 1 Done 1 1 1 1 1 1 0 1 0.875 8 Audit Progress 100% 100% 100% 100% 100% 100% 0% 100% 88% Target They never have any target regarding income Done 0 37000 46000 600000 0 0 255000 0 9 Income Progress Yes Yes Yes Yes 50% Target Annual expenditure for watcher and other office cost. Done Development works and regular expenses till now is= Rs. 1003000. 10 Expenditure Progress Remaining balance= Rs 35000.00 70% Faced Yes Yes Yes Yes Yes Yes Yes Yes Solved Some Some Some Some Some Some Some Some 11 Conflict Progress 0% 5% 5% 15% 10% 0% 40% 40% 15% Plan NA NA NA NA Yes Yes Yes Yes Progress NA NA NA NA 60% 60% 60% 60% 30% 12 Annual plan Overall average 55% NA= Not available * O= Office building construction, N= Nursery construction, S= Seedling production, WS= Drinking water supply, T= Temple construction, M= Mango plantation, R= Village road repair. 78 APPENDIX Appendix 6: Data sheet for social data 2001 6.1: Majhau CFUG HH Knowledge and perception about their own CF SN no. Sex Name Age Q 1 Q 2 Q 3 Q 4 Q 5 Q 6 Q 7 Q 8 Q 9 Q 10 1 61 M K .R. Adhikari 39 Y Y/N Y Y/N Y Y Y/N Y Y Y 2 31 M C. B. Magar 60 Y N/Y Y/N Y/N Y/N Y N/Y Y/N N Y 3 34 M K. B. Bkarma 55 Y N N Y/N N/Y Y/N N/Y N/N Y/N Y/N 4 M P. Acharaya 39 Y Y Y Y/N Y/N Y Y Y Y/N Y 5 F M. Adhikari 32 Y N N/Y N/Y N Y N/Y Y/N Y/N Y 6 16 F Rama Dahal 22 Y N N Y/N N/Y Y/N Y/N N/Y N Y 7 14 M C.B. Pariyar 60 N/Y N N N/Y N/Y Y N N/Y N Y 8 59 M M.B. Ghimire 45 Y Y/N N/Y Y N/Y Y Y Y/N Y Y 9 2 M B. Acharaya 45 Y Y Y Y/N Y Y Y Y Y Y 10 89 M T. B .Basnet 64 Y Y/N Y/N Y/N Y/N Y Y/Y Y/N N/Y Y 11 32 M K. S. Magar 48 N/Y N/Y N Y/N Y/N Y/N N/Y N/Y N Y 12 M P. R. Banjara 41 Y Y Y N Y Y N Y/N Y/N Y/N 13 47 F B. Koirala Y Y/N Y/N Y/N Y/N Y Y Y/N N Y 14 95 F B.N. pariyar Y/N N/Y N/Y N/Y N/Y Y/N Y/N N/Y N Y/N 15 101 M R. Bhujel 25 Y Y/N Y/N Y Y Y Y/N Y/N Y/N Y Total of each response: Y 80% 20% 27% 14% 27% 74% 27% 20% 20% 80% Y/N 7% 33% 27% 60% 33% 26% 33% 47% 33% 20% N/Y 13% 20% 29% 20% 33% 0% 27% 33% 7% 0% N 0% 27% 27% 6% 7% 0% 14% 0% 40% Legend: Y: Level of understanding about CF is high. Positive attitude towards existing management system and its sustainability. Y/N: Level of understudying is ok but not enough. There is some disagreement with existing management system and not sure about its sustainability. N/Y: Level of understanding is low but not against CF. Disagreement with existing management system is high and do not consensus about sustainability. N: Do not know about CF and its management mechanisms. Attitude is negative towards existing management system and do not think it is for the people. 79 APPENDIX 6.2: Jiva CFUG HH Knowledge and perception about their own CF SN no Sex Name Age Q 1 Q 2 Q 3 Q 4 Q 5 Q 6 Q 7 Q 8 Q 9 Q 10 1 128 M Bl. Paswan 40 Y Y/N Y/N N/Y Y/N Y Y/N Y N Y/N 2 176 FM B. Paswan 35 Y Y/N Y/N Y/N Y/N Y/N Y/N Y/N Y/N Y 3 133 M R. C. Paswan 38 Y Y Y N/Y Y Y/N N/Y Y Y Y/N 4 157 M H. Paswan 36 N/Y N N Y Y/N Y/N N N Y/N Y 5 119 M R. Paswan 40 Y/N Y/N Y/N Y/N Y Y/N N/Y Y/N Y/N Y 6 160 FM A. Sah 23 Y/N N N Y/N N Y/N N/Y N/Y Y/N Y/N 7 46 FM D.D. Sada 30 Y/N N N N/Y N/Y Y/N N N/Y N N/Y 8 M R. Mahara 33 Y Y Y Y/N Y/N Y N Y/N Y Y 9 49 M S. Sada 60 Y N N N N/Y Y/N N/Y N/Y N N 10 60 M N. Mahara 57 Y/N N N N/Y Y/N Y/N N N/Y N Y/N 11 41 FM P. Sada 65 N/Y N Y/N Y Y Y/N Y N Y/N Y 12 67 M M. mahara 31 Y/N N N Y/N Y/N Y/N Y/N Y/N N Y/N 13 100 M T.B. Balpaki 60 Y N Y Y Y Y Y Y Y Y 14 37 M B. Ghimire 30 Y Y Y Y Y Y Y/N Y/N Y Y 15 13 M S. Gautom 40 Y N Y/N Y/N Y/N Y N Y/N N Y 16 FM G. Mahara 42 N N N N N NO N N N N Total of each response: Yes 50% 19% 25% 25% 32% 32% 12% 19% 25% 50% Yes/no 31% 19% 31% 38% 44% 62% 25% 37% 32% 32% No/yes 12.5%0% 0% 25% 12% 0% 25% 25% 0% 6% No 6.5% 62% 44% 12% 12% 6.5% 38% 19% 44% 12% Legend Y: Level of understanding about CF is high. Positive attitude towards existing management system and its sustainability. Y/N: Level of understudying is ok but not enough. There is some disagreement with existing management system and not sure about its sustainability. N/Y: Level of understanding is low but not against CF. Disagreement with existing management system is high and do not consensus about sustainability. N: Do not know about CF and its management mechanisms. Attitude is negative towards existing management system and do not think it is for the people. 80 APPENDIX Appendix 7: Data sheet for inventory data 2001 7.1: Majhau CFUG )/ha) )/ha) 3 /ha. 2 Evidences damage Sample plot plot Sample X coordinate Y coordinates % Slope Aspect Stand type % cover Crown * Seedling code) (species Seedling/plot Seedling/ha. Grass (kg)/plot ** Sapling/plot Sapling/ha. m area B. M. tree spp. spp. tree M. M. dbh (cm) (m) height M. Volume (m 1 482305 2948120 P 75 S, KH. 13 13000 50 17 850 10 KH 24 13.5 135 No 2 482405 2948269 <10 W P 70 F, IP 11 11000 40 30 1500 6 F 15 6 36 Sc 3 482672 2948754 <10 S P/N 70 F, IP 5 5000 30 21 1050 13 AR 11 12 156 Sc 4 482651 2948721 0 _ P 70 S, MO 6 6000 18 23 1150 9 S 16 11 99 Sc 5 482830 2949486 _ P/N 40 KI, SF 7 7000 30 8 400 11 CH 13 10 110 No 6 482968 2949994 30 E N 25 SF, KI 6 6000 35 14 700 8 KU 14 8 64 Ins 7 482984 2949734 50 E N 60 Sal, O 15 15000 12 32 1600 5 Sal 16.5 15 75 No 8 482914 2949388 0 _ N 15 KI, CH 8 8000 35 12 600 2 CH 10 7 14 No 9 482617 2949160 40 SE N 35 Sal, O 9 9000 30 15 750 5 Sal 12.5 13 65 No 10 482483 2948966 <10 ES N/P 75 Hal, O 6 6000 30 20 1000 13 S 13.6 13 169 No 11 482874 2949929 <10 N N 70 O 3 3000 0 25 1250 10 O 12 10 100 Se 12 482974 2950227 45 N N 50 Sal, O 13 13000 0 30 1500 8 O 20 10 80 C 13 482886 2950508 50 NE N 70 AM, SJ 11 11000 0 30 1500 8 KI 16 8 64 No 14 483081 2950181 40 SE N 15 Sal, O 11 11000 8 22 1100 3 Sal 13 8 24 Sc 15 482689 2949680 70 N N 40 Sal, KI 13 13000 8 25 1250 13 Sal 14 15 195 No 16 482286 2948394 0 _ P 75 _ 0 0 60 23 1150 16 S 14 13 208 Sc 17 482395 2948536 0 _ P/N 70 B, TA 12 12000 0 24 1200 13 S 19 10 130 No 18 482430 2948781 15 S N/P 80 F, TA 5 5000 50 30 1500 14 S 14 14 196 No 19 482361 2948836 10 N P/N 70 KI, O 5 5000 40 27 1350 6 Hal 11.5 10 60 Sc 20 482221 2948147 0 _ P 55 _ 0 0 50 19 950 6 S 14.8 9.5 57 Sc 21 482202 2948268 0 _ P 20 _ 0 0 50 9 450 4 KH 19 8 96 C 22 482427 2948412 <10 SE N/P 70 IP, O 5 5000 20 28 1400 12 TA 13 10 40 No 23 N 482787 2950124 25 W N 60 HA, O 18 18000 30 28 1400 8 HA 35 15 120 Sc 24 482771 2949915 <10 SE N 30 Sal 20 20000 30 23 1150 3 Sal 12 11 33 No 25 N 482628 2949416 25 W N 35 KI, O 22 22000 20 30 1500 4 KI 20 8 32 No 26 482427 2948827 10 _ N/P 30 Si, O 10 10000 25 22 1100 3 HA 11 7 21 No 27 482542 2948561 0 _ P 80 IP, TA 7 17000 40 29 1450 12 S 26 16 192 L 28 482435 2948353 0 _ P 70 IP, TA 8 18000 50 48 2400 13 AR 18 13 169 No 29 482503 2948307 0 _ P 30 _ 0 0 55 21 1050 0 _ 0 0 0 Sc 30 482495 2948397 0 _ P/N 70 TA, O 9 9000 15 16 800 13 S 26.5 15 195 Sc Average: 54 8.6 9267 29 23 1168 8.4 15.8 10.6 97.8 Species: AM= Amala (Emblica officinalis), AR= Badahar (Artocarpus spp.), B= Simal (Bombax cieba), CH= Chamre, F=Nibaro (ficus spp.) HR= Harde , IP= Ipil Ipil (Leucaena leucocephala), KH= Khair (Acacia catachu), KR= Karma (Adina cordifolia), Man= Anp (Mengifera indica), MO= Kimbu (Morus alba) NE= Neem (Azadiracta indica), O= Other (local fuel wood spp), S= Sissoo (Dalbergia sissoo), Sal= Sal (Shorea robusta), SI= Siris (Albizia spp.), TA= Tanki (Bauhinia spp.) Evidence of damage: C= Cutting, L= Lopping, Sc= Seedling cut, Se= Soil erosion M. species= Median tree species; M. dbh = Median diameter; and M. height = Mean height Plot radius: *seedling and grass = 1.78m; ** Sapling and trees = 7.98m 81 APPENDIX 7.2: Jiva CFUG 2 M. tree spp. M. tree spp. M.dbh (cm) (m) ht. Mean Volume/ha. Evidences damage S. Plot X coordinate Y coordinate Slope % Aspect Stand type cover Crown Seedling code) (species Seedling/plot Seedling/ha. Grass(kg) /p Sapling/plot Sapling/ha. B.area/ha.m 31 426368 2969543 0 _ N/P 70 O 4 4000 0 30 1500 10 S 19 14 140 G/c 32 426123 2969620 0 _ P 10 MAN. 1 1000 20 0 0 0 _ 0 0 0 No 33 426111 2970215 20 S N 45 O 3 3000 0 32 1600 3 BE 15 7 21 G/c 34 426637 2969751 <10 S P 90 O 5 5000 0 50 2500 16 S 27 17 272 G 35 426931 2970638 25 S N 90 O 1 1000 0 30 1500 8 KR 12 8 64 C 36 425493 2969160 0 _ P 40 O 4 4000 0 15 750 10 S 14 12 120 G 37 425284 2969443 <10 W P 50 O 2 2000 0 21 1050 11 S 19.5 15.5 170 No 38 425317 2970212 48 W N 60 KR, O 7 7000 16 26 1300 9 KR 10.5 6 54 Se 39 425421 2970359 42 SE N 20 KR, O 6 6000 20 20 1000 4 KR 13 7 28 Se 40 425587 2970617 45 SE N 10 TA, BE 10 10000 0 80 4000 2 KR 12 8 16 No 41 425454 2970292 30 E N 60 HR 10 10000 0 60 3000 8 KH 18.5 9 72 C 42 425552 2969712 <10 SE P 70 NE, O 3 3000 0 11 550 7 KH 17 9 63 G 43 425399 2969695 0 _ P 60 _ 0 0 0 16 800 13 S 16.5 14 182 De 44 425550 2969894 25 S-E N 50 NE, O 8 8000 10 11 550 5 HR 23 11 55 No 45 425788 2969986 35 E N 60 - 0 0 0 48 2400 5 KH 16 7 35 No 46 426118 2969985 <10 SE N 90 - 0 0 0 28 1400 9 BE 21 10 90 C/l 47 426219 2969860 <10 SE P 65 - 0 0 0 64 3200 15 S 26.5 16 240 No 48 426263 2969198 0 _ P 55 - 0 0 0 10 500 22 S 27 20 440 G 49 426025 2969364 <10 E P 50 - 0 0 0 36 1800 11 KH 23 13 143 G 50 425296 2969167 0 _ P 10 MAN. 1 1000 50 0 0 6 S 24 10 60 No 51 424986 2969377 <10 SW N/P 20 _ 0 0 0 3 150 5 KH 14 8 40 G 52 424884 2969685 0 _ N 50 O 20 20000 0 25 1250 5 HR 18 8 40 C/l 53 426155 2971088 41 N N 65 O 10 10000 0 20 1000 17 CH 20 8 136 No 54 426272 2971157 65 W N 75 O 5 5000 0 35 1750 9 KR 12 7 63 No 55 426165 2971157 <10 E N 60 CH, O 20 20000 0 20 1000 13 Sal 19 8 104 C 56 426354 2970579 55 SW N 75 KR, O 8 8000 0 36 1800 8 KR 16 8 64 Se 57 426595 2970489 <10 W N 80 O, BE 8 8000 0 33 1650 8 KR 20 10 80 No 58 426598 2970306 0 _ N 80 O 8 8000 0 35 1750 10 BE 21 12 120 G/c 59 426742 2970096 0 _ N 10 SC 0 0 0 0 0 0 _ 0 0 0 60 426530 2969528 0 _ P 80 _ 0 0 0 20 1000 16 S 28 25 400 G Average: 55 4.8 4800 3.9 55 1358 8.8 17.4 10 110 Species: B= Simal (Bombax cieba), BE= Bell (Aegle marmelos), CH= Chamre, HR= Harde, JH= Jhakadnedi (Glycosmis pentaphylla), KH= Khair (Acacia catachu), KR= Karma (Adina cordifolia), Man= Anp (Mengifera indica), NE= Neem (Azadiracta indica), O= Other (local fuel wood spp), S= Sissoo (Dalbergia sissoo), Sal= Sal (Shorea robusta), SC= Scrub area. Evidence of damage: C/L= Cutting/lopping, De= debarking, G= Grazing, Se= Soil erosion, Wed= weeding 82 APPENDIX Appendix 8: Data sheet for inventory data 1998 Majhau Jiva ) cm ( ) ) y /ha /ha) /ha /ha) 2 3 2 3 rown rown ean height ean ensit asal area asal area iameter iameter m m) m Crown C Growing stock stock Growing (m Plot number number Plot Seedling (no/ha) Sapling (no/ha). Slope (%) type Forest Plot number number Plot Seedlings (no/ha) Sapling (no./ha) Slope (%) type Forest D B ( M ( Density M d B ( Mean height height Mean Mean Mean diameter (cm) stock Growing (m 1 0 2000 0 KS 3 20 17 11 220 1 500 0 0 SK2 30 18 17 306 2 1000 800 0 KS 1 17 23 14 238 2 15000 0 22 SK2 32 18 12 216 3 2000 1200 0 KS 2 15 11 11 165 3 10000 0 0 SK2 22 16 15 240 4 3000 900 11 KS 2 13 18 11 143 4 8000 0 22 SK1 13 7 5 35 5 3000 1300 0 S 1 5 17 8 40 5 0 0 0 SK2 15 14 9 126 6 0 1333 11 S 1 7 13 10 70 6 0 500 11 TH1 20 9 3 27 7 0 1500 0 S 1 8 16 14 112 7 0 500 22 SK2 15 8 9 72 8 0 1100 0 S 2 9 11 12 108 8 0 500 0 SK2 14 14 16 224 9 0 900 0 S 1 8 12 13 104 9 800 0 22 M 1 12 7 4 28 10 0 1100 0 S 2 9 13 12 108 11 0 1000 100 M 1 28 11 9 99 11 11000 856 22 S 1 3 14 9 27 12 0 1500 100 M 1 14 8 6 48 12 9500 300 33 M 1 3 12 7 21 13 0 1000 66 M 1 15 5 2 10 13 19000 550 44 S 1 3 17 11 33 14 5200 2500 50 M 1 24 7 3 21 14 10500 900 0 S 2 7 14 9 63 15 8500 1500 100 M 2 14 7 9 63 15 14000 500 78 Sal 1 5 13 8 40 16 4000 2500 100 M 2 13 7 13 91 16 21000 400 66 K 1 4 16 13 52 17 8000 500 78 M 2 18 8 9 72 17 17000 700 0 M 2 6 18 8 48 18 8000 2000 22 M 2 13 6 7 42 18 31000 550 0 M 1 3 18 11 33 19 10500 1500 33 M 1 12 10 3 30 19 22500 700 44 M 1 2 13 7 14 20 5000 500 22 M 2 15 9 7 63 20 15500 300 78 M 2 4 15 11 44 21 2000 2000 22 M 2 14 7 10 70 21 15500 560 66 M 3 8 12 12 96 22 4000 500 100 M 1 25 9 2 18 22 10000 350 100 M 2 12 17 10 120 23 5500 1000 33 M 1 16 7 5 35 23 5500 867 0 M 2 4 11 11 44 24 2500 2500 78 M 2 20 9 10 90 24 20000 1120 55 M 2 10 19 12 120 25 3000 0 100 M 2 20 12 6 72 25 21000 975 44 M 3 14 25 13 182 26 5000 15000 44 M 1 27 8 4 32 26 17000 1100 33 M 1 5 14 8 40 27 4000 0 55 M 1 14 7 4 28 27 11000 1345 44 M 1 4 11 6 24 Avg 10370 897 1.59 7.7 15.2 10.4 85.5 Avg. 4212 1423 23 1.5 18 9.54 8 83 K= Khair, KS= Khair/ Sissoo, S= Sissoo, M= Mixed (planted +natural), Sal= Sal Appendix 9: Data sheet for inventory data 1995 Data 1995 were adopted from forest inventory done for prefeasibility study of Churia Forest Development Project (ChFDP) in 1995. Inventory was done to obtain reliable data on the actual status of the forest resources in the district of Saptari, Siraha and Udayapur. Although, this data is not exactly fit with this study, it has been used as an indicator of forest status in two districts Siraha and Saptari. To make those data more reliable, out of the total 26 and 31 sample plots, only 15 and 24 plots that were somewhat similar with the case studies’ condition were selected and averaged. Database was taken from the ChDFP project. Because of not from exactly same areas, data 1995 has not been tested with data 1998 and 2001. It has been used only to visualize the trend. 83 APPENDIX Data table 1995 Variables Saptari Siraha Stand variables Mean Mean Crown Cover (%) NA NA Seedling (no/ha) 2415 1563 Sapling (no/ha) NA NA B. Area (m2/ha) 5.1 4.61 Mean dbh (cm) NA NA Mean height (m) NA NA Volume (m3/ha) 25.66 25.118 Grass (ton/ha) NA NA Human damage (%) 79.25 80.25 NA= Not available Appendix 10: Measuring basal area using Relascope Relascope is a basal area measuring equipment. Among different models of Relascope, Spiegel Relascope ® made in Austria was used for this research. Basal area is determined by counting all trees in a full circle (dbh>=10 cm.), which fill the gap of the Relascope at breast height. The measurement is started from a certain point and advanced clockwise until the full circle is completed. Every stem should be aimed at and checked if it fills the gap. A tree is inside the Relascope plot if the distance from the plot center to the tree (m) is less than half the diameter of the tree (cm). A tree is on the plot border (borderline tree) if the distance (m) to the tree from the plot center is exactly half of the diameter (cm) of the tree. Boarder line trees should be checked measuring the distance and diameter and their status re-assessed (in/out). It is not recommended to use the Relascope inventory in very steep slopes. However, if individual plot is located in a steep slope, the final basal area is calculated by multiplying the measured basal area by a slope correction factor. Slope correction factors for Relascope (adopted from Seppanen &Wikberg, 1995). Slope (%) Degrees C. Factor 10 6 1.00 20 11 1.02 30 17 1.04 40 22 1.08 50 27 1.12 60 31 1.17 70 35 1.22 80 39 1.28 90 42 1.35 IN OUT BORDRE 100 45 1.41 Aiming with Relascope 84 APPENDIX Appendix 11: Sample point’s distribution Majhau Jiva i ii i i ii - - - i i i i - - i - - i - - - i - - ii - i i -- i - - i i - - - - i ii - ii - - i i - ii - - - - - Appendix 12: Accuracy assessment (confusion matrix) of classified images 2001 Majhau 2001 Dense Open Degraded Sand Open field forest forest forest Dense forest 6 1 0 0 0 0.86 Open forest 1 5 0 0 0 0.83 Degraded 0 1 2 0 0 0.67 Sand 0 0 0 0 0 ? Open field 0 0 0 0 0 ? Reliability 0.86 .071 1.00 ? ? Average Accuracy = 78.57 % Average Reliability = 85.71 % Jiva 2001 Overall Accuracy = 81.25 % Dense Open Degraded Sand Open field Accuracy forest forest forest Dense 5 0 1 0 0 0.83 Open forest 0 4 1 0 0 0.80 Degraded 0 1 2 0 0 0.67 Sand 0 0 0 0 0 ? Open field 0 0 0 0 0 ? Reliability 1.00 0.80 0.5 ? ? Average Accuracy = 76.67 % Average Reliability = 76.67 % Overall Accuracy = 78.57 % 85 APPENDIX Appendix 13: Trend in forest cover classes in the study sites Change in forest cover classes Change in forest cover classes in Jiva 80 Majhau 250 70 200 60 50 DGF 150 DGF 40 OF OF DF 100 Area (ha) Area Area (ha) 30 DF 20 50 10 Year0 0 1992 1999 2001 Year 1992 1999 2001 Where, AG = Agricultural field/open field DGF = Degraded forest DF = Dense forest OF = Open forest S = Sand Example of Rehabilitation in slope Majhau. Heavily grazed area in Jiva consists no regeneration. Researcher is approaching sampling point. 86 APPENDIX Appendix 14: Histogram of classified images (surroundings) Surroundings: Majhau 2001 1999 1992 800 800 600 600 600 400 400 400 area (ha) : area (ha) : area (ha) : 200 200 200 0 0 A S A S A S DF DF OF RA OF RA DF OF RA DGF DGF DGF Class : class : class : AG DGF DF OF S Year (ha) (ha) (ha) (ha) (ha) 1992 369 437 160 334 151 1999 236 475 136 513 91 2001 291 282 207 595 76 Surroundings: Jiva 2001 1999 800 800 800 600 600 600 400 400 400 : (ha) area area (ha) : area (ha) : 200 200 200 0 0 0 A S A S A S DF OF RA DF RA OF DF OF RA DGF DGF DGF class : class : class : Ag DGF DF OP Sand (ha) (ha) (ha) (ha) (ha) 1992 304 450 302 340 46 1999 246 537 370 268 21 2001 365 282 418 368 9 87 APPENDIX Appendix 15: Feature space of training sample Majhau Majhau 2001 Majhau,1999 Majhau 1992 S S S S S AG AG AG AG AG DGF DGF DGFDGF DGF OF DF DF OF DF OF DF OF OF DF Jiva: Jiva 2001 Jiva 1999 Jiva 1992 S S S AG AG AG DGF DGF DGF OF OF DF OF DF DF AG = Agricultural field/open field DGF = Degraded forest DF = Dense forest OF = Open forest S = Sand 88