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Journal of Resources and Ecology >

2024 , Vol. 15 >Issue 5: 1335 - 1343

DOI: https://doi.org/10.5814/j.issn.1674-764x.2024.05.020

Impact of Human Activities on Ecosystem

Users’ Participation in Community Forest Management: A Comparative Study

  • Sandeep TIMILSINA , 1, * ,
  • Gyan Bandhu SHARMA 1 ,
  • Prabin POUDEL 1 ,
  • Anjan TIMILSINA 2
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  • 1. Faculty of Forestry, Agriculture and Forestry University, Hetauda 44107, Nepal
  • 2. Faculty of Livestock Production and Management, Agriculture and Forestry University, Bharatpur 13712, Nepal
* Sandeep TIMILSINA, E-mail:

Received date: 2024-01-02

  Accepted date: 2024-04-22

  Online published: 2024-10-09

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Abstract

Local community participation in forest management is pivotal since they are familiar with the forest environment. In the successful management of community forestry (CF), both males and females along with the representation of poor and disadvantaged groups are of vital importance. This research compares the users’ perception in community forest management (CFM) activities, and socio-economic variables influencing participation in studied community forestry user groups (CFUGs). Primary data were collected through reconnaissance surveys, interviewing key informants, focus group discussions, and household surveys. Secondary data were collected from the division forest office, CFUGs’ operational plan (OP) and Constitution, internet, and authenticated websites. The chi-square (χ2) test was applied to test separately association variables like gender, caste, age class, education level, and wealth ranking with participation. Using ordered logit regression, the variables affecting participation in OP and constitution-making, Silvicultural activities, Forest products collection, and CF fund mobilization were quantified. Gender and Education were found to be the most promising factor influencing participation in Jagriti CFUG and Jhankrikhola CFUG respectively. In general, higher caste, older age, and rich people dominate the major decision-making activities. However, lower caste and poor people have been involved comparatively more in Forest product collection.

Key words： user groups; executive committee; socio-economic variable; Chi-square test; ordered logit regression

Cite this article

Sandeep TIMILSINA , Gyan Bandhu SHARMA , Prabin POUDEL , Anjan TIMILSINA . Users’ Participation in Community Forest Management: A Comparative Study[J]. Journal of Resources and Ecology, 2024 , 15(5) : 1335 -1343 . DOI: 10.5814/j.issn.1674-764x.2024.05.020

1 Introduction

Globally, community forestry (CF) has emerged as a major paradigm of forest management addressing problems pertaining to environmental and social issues (Gilmour, 2016). Community forestry is one of the umbrella terms where local users are involved in both forest conservation and utilization. As an alternate to the state control model of forest management, CF has been established to reduce the loss of forests and improve the livelihoods of local communities through environmental governance amid increasing forest protection costs (Ojha et al., 2009; Gilmour, 2016).
As per Nepal’s Forest Act 2019, community forest, a part of state-controlled forests handed to local user groups for the purpose of conservation, management, utilization, and distribution of forest products by affixing prices as per the approved operational plan (MoFE, 2019). Moreover, community forest (CF) is a fellowship program between the state and local forest users in which government staff plays a role of mediator in identifying real user groups, operational plan and constitution preparation of user groups, and effective implementation of CF activities whereas local forest user groups are responsible in management, conservation and sustainable utilization of the forest. A total of 22266 community forest user groups (CFUGs) (Province No. (1)-3675, Madhesh Province-512, Bagmati Province-4464, Gandaki Province-3845, Lumbini Province-3960, Karnali Province-2686, and Sudur Paschim Province-3124) are formed, administering 2.23767×106 ha of forest lands as a community forest (Department of Forest of Nepal, 2018). Out of total forest area in Nepal, 35% is managed under community forests and approximately 62% are the inhabitants (Pandey and Pokhrel, 2021). Community forestry is not just a technology, but is a process of social change that involves continuous participation of whole communities in planning, problem identification, and formulating solutions.
The community forestry program is considered to be an effective model not only for conserving the forest but also for fulfilling the basic needs of locals. Due to immense deforestation in the nation-managed forest, a large area of the forest was destructed. In the late 1970s, considering the fact that the conservation of forest is only possible when local users feel connected to the forest, community forest user groups (CFUGs) were formed (Joshi and Singh, 2020). Currently, the community forestry program is represented as the most innovative participatory natural resource management model (Pokharel and Nurse, 2004). The CFUGs are provided with the right to access, utilize and manage the peripheral forest retaining ownership (Paudel, 2018). Community forestry programs have been initiated to realize communal benefits and increase local participation in decisions and their implementation (Adhikari et al., 2016).
Participation refers to the joint involvement of people and local government to promote and implement local government programs (Touchton et al., 2015). As per report published by FAO in 2012, participation refers to a collaborative mechanism that allows local people to control policy, investment choices, managerial decisions, and become a part of driving the local economy. In addition, Reed et al. (2009) noted that participation is inclusive of both conventional and non-conventional stakeholders in determining how initiatives will be scheduled, executed, and appraised.
In order to be effective, a natural resource management (NRM) program requires significant user’s participation. Moreover, participation means directly participating in decision-making and implementation or being represented by legitimate users (Graham et al., 2003). In addition, to helping solve environmental problems, community development and natural resource management programs, help improve local livelihoods (Ting et al., 2011).
In Nepal, despite the rise in community forests, the program has yet to determine whether people can effectively participate in the management and jurisdiction of these forests (Chhetri et al., 2013; Adhikari et al., 2014). The study of Maskey et al. (2006) and Chhetri et al. (2013) indicates various socio-economic factors influence community forestry participation. Community forest participation levels are affected by variables like sex, age, education, household size, and social groups (Oli and Treueb, 2015).
This study aimed at comparing Users’ perceptions in Community Forest Management (CFM) activities, to assess the relationship between socio-economic variables such as gender, caste, age, education level, wealth ranking, and participation level, and to determine factors affecting participation. The findings of this research were based on a case study and can be used as a reference for similar types of study in the near future.

2 Research methodology

2.1 Study area

Based on the criteria: 1) CF handed over at least 10 years before, for the reason that they will have a substantial degree of experience; 2) Accessibility; 3) CF managed under the same division forest office; 4) Male and female CFUG leader, two CFUG—Jagriti CFUG and Jhankrikhola CFUG of Kaski District were selected purposively (see Fig. 1).
The fieldwork was conducted from July-September, 2021. Both the primary and secondary data relevant to the study were collected using different community participatory tools to fulfill the set of objectives of the research. Primary data were collected through reconnaissance surveys, total enumeration of households, Key informant interview with five individuals including division forest officer (DFO) in Kaski, each CFUG head and elite person from each studied CFUG, and Focus group discussion with four groups; one with the executive committee and general users, in each CFUGs. Each discussion lasted for about 40-50 minutes. For the Secondary data collection, literature available in the form of journals, articles, thesis, publication, websites, forest user group (FUG) minute book, operation plan (OP) and Constitution of CFUGs, etc. were reviewed.

2.2 Research methodology

Based on Pearson’s Chi-square test, we analyzed if gender, caste, age, education, and wealth ranking affected participation in OP and Constitution making, Silvicultural activities, Forest products collection, and CF fund mobilization. As our dependent variable are ordinal in nature and cannot be accounted by multinomial logit and probit models, so ordinal logit regression model was used.
The equation for the model thus to be estimated is as follows:
y i * = β x + ε i
where yi* is the exact but unobserved dependent variable; x is the vector of independent variables; εi is the error term, and β is the vector of regression coefficients.
The level of agreement pertains to participation, ranging from 1 to 3, where 1 represents “agree” and 3 represents “disagree”. The dependent variable is structured as μj-1<yi*<μj, where j=1, 2, 3 and μ1<μ2<μ3. Cut points (constants) μi must be estimated. Based on the cut points, the distribution of yi* is divided into three categories, and y is a discrete realization of yi*, generated as per the given equation:
$y=\left\{\begin{array}{lc} 1, & \text { if } y_{i}^{*} \leqslant \mu_{1} \\ 2, & \text { if } \mu_{1}<y_{i}^{*} \leqslant \mu_{2} \\ 3, & \mu_{2}<\text { if } y_{i}^{*} \leqslant \mu_{3} \end{array}\right.$
Table 1 Studied CFUG details
Name Jhankrikhola CFUG Jagriti CFUG
Address Pokhara-33, Kaski Pokhara-32, Kaski
CFUG President Saraswati Bastakoti Baburam Mijar
CFUG head Female Male
Area (ha) 41.80 45.50
Household number 138 120
Household
population		 645 652
Main species Shorea robusta, Terminalia alata, Schima wallichi, Castanopsis indica Shorea robusta, Terminalia alata, Schima wallichi, Castanopsis indica
Slope 10°-40° 0°-40°
CF handover date 1996-06-24 2007-12-27
Recent OP duration 10 years (1996-2005) 5 years (2007/2008-2012)

Note: Source: respective CF OPs and Constitutions.

This same model is applied in case of all four community forest participation activities. However, to measure the perception of the users towards CFM activities, all responses were scaled according to the Likert 3 points scale (1= Agree, 2= Neutral and 3= Disagree) and the weighted mean ( x ¯) was calculated to find the average perception of the respondents using the given formula:
x ¯ = ∑ w i × x i ∑ w i
where, x ¯is the weighted mean; wi is respondents response in %; xi is value assigned to agree to disagree. Considering the Likert scale to be interval scale, the weighted mean of the respondent’s perception was further analyzed using Table 2.
Table 2 Perception level and its interval range
Level Scale Interval length Lower limit Upper limit Interval
Agree 1 0.67 1 1.67 [1, 1.67)
Neutral 2 0.67 1.67 2.33 [1.67, 2.33)
Disagree 3 0.67 2.33 3.00 [2.33, 3.00]

2.3 Description of the variables

Several socio-economic and demographic factors like household size, level of education, age class, sex, caste, and wealth status impacts the participation of users in forest management activities (Lise, 2000; Degeti, 2003; Salam et al., 2005; Dolisca et al., 2006; Chhetri et al., 2013; Getacher and Tafere, 2013; Subedi and Timilsina, 2016).
Household heads’ gender can affect involvement in CFM programs. Both males and females have varied capacities, impetus, and opportunities to participate in communal works. Females are more likely than males to be positive and generous about community based forest management (Ray et al., 2017). Therefore, a significant association between gender and participation level is expected.
Participation in CFM programs is strongly influenced by an individual’s age (Atmiş et al., 2007). Elderly people are more inclined to collect forest products, whereas younger people shows more penchant in making decision regarding forest activities (Dolisca et al., 2006). CFM programs are therefore likely to have a significant impact on participation based on age. In this paper, age class was divided into three classes: 1=18-35, 2=36-55, and 3= >55 years.
Forest management and conservation have been reported to be more or less influenced by education (Butler and Butler, 2016). A more educated user is more likely to take part in decision-making. Therefore, the significant influence of the education variable is expected. Here, the education levels of the respondents were measured in 3 classes: 1=illiterate, 2=Primary education (1-10 class), and 3= Higher education (> 10 class).
Caste is one of the most influencing socio-economic variables in participation. Community Forest User Executive Committee (CFUEC) has meaningful representation from all caste and the benefit distribution is targeted to disadvantaged and marginal groups as per Community Forestry Guideline, 2071 (Government of Nepal, 2014). Generally, higher caste people have more approach to the resources and opportunities in society. Therefore, higher caste people are expected to participate more in CF management. In the study, caste was classified into three categories: 1-higher, 2-indigenous, and 3-lower.
Wealth ranking in the CF is categorized by the users themselves based on the resource they own. As per the CF constitution respondents belonging to “Ka barga” are indicated as 1, “kha barga” are indicated as 2, and “ga” and “gha barga” are represented as 3. We hypothesized that the collection of forest products shows a significant difference among wealth classes. The socio-economic variables which are used to determine participation are depicted below:
In this paper, respondents varying from different gender, ethnic groups, educational strata, age classes, and wealth ranking were asked to categories their responses (Agree, Neutral, and Disagree) on participation of four community forestry activities; participation in op and Constitution-making, Participation in Silvicultural activities, Participation in collection of forest products”, and Participation in CF fund mobilization.

3 Results

In Jagriti CFUG, 54 (45%) of the respondents were female and 66 (55%) were male, highly dominated by lower caste people. In Jhankrikhola CFUG, 79 (57%) of the respondents were female and 59 (43%) were male with dominancy of higher caste population.
Effective participation of users in different forest management activities determines the success or failure of the community forestry program. Four statements related to the participation of users in the management of community forest were made. Thereafter, the respondents were asked to rate these statements on a 3-point Likert scale providing their degree of satisfaction and their weighted mean was calculated in both Jhankrikhola and Jagriti CFUGs (see Table 3). Since the data for all four activities lies in the range [1.67, 2.33) (see Table 2). So, users’ perceptions of both CFUGs can be considered neutral. Neutral perception indicates the need for active involvement of users in all sorts of community forestry activities. Great leadership and users’ awareness can lead to a more vested interests and stronger opinions.
Table 3 Perception of users’ in community forest management
Statements Weighted mean
Jhankrikhola CFUG Jagriti CFUG
OP and constitution making 1.94 2.13
Silvicultural activities 1.99 2.05
Forest products collection 2.03 2.00
CF fund mobilization 1.82 2.00
As a means of evaluating the relationship between categorical variables and CF participation, Chi-square tests of independence were used. Table 4 and Table 5 presents the association between independent variables with participation in different activities in Jagriti and Jhankrikhola CFUG respectively (Table 6 and Table 7).
Table 4 P-value showing association between a socio-economic variable with 4 statements of participation in Jagriti CFUG
Statements Gender Age Education Caste Wealth ranking
OP and Constitution making 0.011* 0.6 0.001** 0.014* 0.002**
(9.052) (9.064) (18.297) (12.475) (16.73)
Silvicultural activities 0.005** 0.464 0.172 0.007** 0.597
(10.732) (3.595) (6.391) (14.219) (2.77)
Forest products collection 0.00001** 0.523 0.00001** 0.002** 0.227
(15.398) (3.209) (20.375) (16.744) (5.654)
CF fund mobilization 0** 0.836 0.001** 0.007** 0.362
(15.202) (1.449) (18.992) (14.095) (4.338)

Note: *, ** mean the significance level at 5% and 1%, respectively; the values in parentheses represent χ2 value.

Table 5 P-value showing association between a socio-economic variable with 4 statements of participation in Jhankrikhola CFUG
Statements Gender Age Education Caste Wealth ranking
OP and Constitution making 0.1 0.227 0** 0.018* 0.241
(9.291) (5.645) (20.983) (11.873) (5.481)
Silvicultural activities 0.159 0.246 0.274 0.029* 0.074
(3.681) (5.432) (5.136) (10.782) (8.536)
Forest products collection 0.00001** 0.16 0.00001** 0.00001** 0.006**
(17.168) (6.585) (25.092) (28.745) (14.436)
CF fund mobilization 0.181 0.046* 0.014* 0.029* 0.375
(3.42) (9.708) (12.498) (10.829) (4.234)

Note: *, ** mean the significance level at 5% and 1%, respectively; the values in parentheses represent χ2 value.

Table 6 Summary statistics for independent variables (N=120) in Jagriti CFUG
Variables Minimum Maximum Mean
Statistic Std. error
Gender 1 2 1.45 0.046
Age 1 3 2.08 0.068
Educational status 1 3 1.87 0.064
Caste 1 3 2.21 0.08
Wealth Ranking 1 3 1.88 0.065
Table 7 Summary statistics for independent variables (N=138) in Jhankrikhola CFUG
Variables Minimum Maximum Mean Std. error
Gender 1 2 1.57 0.042
Age 1 3 2.16 0.063
Educational status 1 3 1.99 0.05
Caste 1 3 1.74 0.069
Wealth Ranking 1 3 2.23 0.073
Ordinal logit regression model analyzed likely and unlikely nature of independent variables, their empirical findings are shown in Table 8 and Table 9. The Chi-square values are found to lower than 0.05 in all the four cases. This regression model consequently features a high caliber of explanatory power, to the extent that it provides insights into the dependent variables. In evaluating each model log-likelihood, the data are found to be fitted and accounted well for them. In the standardized normal distribution, the threshold points are ancillary parameters for every point of the dependent variable.
Table 8 Empirical results using ordinal logit regression of participation of four different activities in Jagriti CFUG
Variables Variables
(Compared to) Reference		 OP and
constitution-making		 Silvicultural activities Forest products
collection		 CF fund mobilization
Coefficients Std. error Coefficients Std. error Coefficients Std. error Coefficients Std. error
Gender (1= Male) 2 = Female 1.363*** 0.424 -1.365*** 0.412 -1.520*** 0.411 1.461*** 0.429
Age in years (1= 18-35]
3= >55		 -0.387 0.575 -0.140 0.533 -0.368 0.546 -0.420 0.561
Age in years (2= 36-55] 0.692 0.446 0.880** 0.441 0.572 0.450 -0.777* 0.467
Education (1= illiterate)
3= >10th		 -1.311** 0.584 -1.486** 0.592 1.808*** 0.605 -2.109*** 0.633
Education (2= 1-10th grade) 0.114 0.531 -1.457*** 0.548 0.397 0.534 -1.062* 0.558
Ethnicity (1= Higher)
3= Lower		 1.372*** 0.485 1.713*** 0.489 -1.121** 0.463 1.647*** 0.499
Ethnicity (2= Indigenous) 1.089** 0.550 1.058** 0.514 -1.324** 0.541 0.303 0.550
Wealth ranking (1= Rich) 3= Poor 1.858*** 0.620 -0.965 0.593 -0.241 0.600 -1.320** 0.598
Wealth ranking (2= Medium) 1.713*** 0.563 -0.004 0.508 -0.467 0.506 -0.905* 0.521
Threshold (3) 1.991 0.872 -2.317 0.858 -1.957 0.859 -2.757 0.899
Threshold (2) 4.271 0.954 0.284 0.835 0.339 0.832 0.506 0.853

Note: *, **, *** mean the significance level at 10%, 5% and 1%, respectively.

Table 9 Empirical results using ordinal logit regression of participation of four different activities in Jhankrikhola CFUG
Variables Variables
(compared to) reference		 OP and constitution
making		 Silvicultural activities Forest products
collection		 CF fund mobilization
Coefficients Std. error Coefficients Std. error Coefficients Std. error Coefficients Std. error
Gender (1= Male) 2 = Female 0.415 0.395 -0.232 0.407 -0.491 0.413 0.540 0.393
Age in years (1= 18-35) 3= >55 -0.777 0.573 -0.953 0.579 -1.684*** 0.641 0.273 0.548
Age in years (2= 36-55] -0.153 0.389 -0.535 0.399 0.120 0.389 0.820** 0.394
Education (1= Illiterate 3= >10th -2.090*** 0.726 0.561 0.694 2.723*** 0.772 -0.860 0.655
Education (2= 1-10th grade) -1.422*** 0.529 0.610 0.517 -0.126 0.521 0.295 0.488
Ethnicity (1= Higher) 3= Lower 0.437 0.499 -0.250 0.496 -1.687*** 0.535 0.614 0.490
Ethnicity (2= Indigenous) 0.446 0.487 0.756 0.506 -1.386** 0.555 0.382 0.491
Wealth ranking (1= Rich) 3= Poor 0.843* 0.468 1.163** 0.494 -1.078** 0.481 0.362 0.455
Wealth ranking (2= Medium) 0.589 0.445 0.647 0.458 0.336 0.466 0.457 0.439
Threshold (3) -2.060 0.721 -0.902 0.682 -2.715 0.759 -0.238 0.659
Threshold (2) 0.428 0.702 1.839 0.701 -0.215 0.707 1.895 0.679

Note: *, **, *** mean the significance level at 10%, 5% and 1%, respectively.

4 Discussion

Regardless of socioeconomic status, users participate in a wide range of CF management work moderately (Chhetri et al., 2013). The minority of users participate at a higher level or never participate. The majority of respondents to this study reported a neutral level of perception towards CF management activities. As seen in this study, the weighted means of perception in both CFUGs are close to the “agree” state when it comes to participating in CF fund mobilization than other management activities. This supports a study by Kimengsi et al. (2019) who found the economic motivation to be an influencing factor in people’s participation in various community activities.
Gender plays a pivotal role in participation. All four CF activities are statistically significant at the 1% level for gender within Jagriti CFUG. There is a positive sign associated with this coefficient (Table 8) indicating that men shows more likeliness towards participation. This is in line with study by Oli and Treueb (2015) found males to be involved more in extra household activities than females. Moreover, Getacher and Tafere (2013) reported women in northern Ethiopia to be rarely engaged in community forest management, as they were impacted by childcare responsibilities, fetching water, and cooking for themselves and their families. Similarly, Coulibaly-Lingani et al. (2011) in southern Burkina Faso also found that community participation was impeded by women’s personal and household chores. In the case of Jhankrikhola CFUG, according to Chi-square testing of independence, participation in forest product collection and CF fund mobilization were significantly associated with gender (Table 5). But the regression analysis (Table 9) didn’t reveal any significant association with participation. However, the negative sign indicates men shows less likeliness to involve in forest product collection than women in Jhankrikhola CFUG as females are the principal user of forest products (Dhimal, 2012; Chhetri et al., 2013; Subedi and Timilsina, 2016).
Participants’ age is also an important variable determining participation level. Regression analysis indicates a significant relationship between ages (36-55 years) with participation in Silvicultural activities (at 5%) and CF fund mobilization (at 10%) in Jagriti CFUG (Table 8). Negative coefficients in age groups concerning participation in CF activities indicates participation is less likely among the young and middle aged in reference to >55 years. The possible reason is elderly population possess significant time available for communal activities, which is also supported in study by Subedi and Timilsina (2016). Age (18-35 years) is significant at a 1% level of significance in the Jhankrikhola CFUG, negative coefficient indicating a lower likelihood of participating in forest product collection (Table 9). In a study by Beach et al. (2005), elderly farmers were found to be gathering more forest resources. However, Chhetri et al. (2013) reported reduction in participation with increasing age. Middle age groups (36-55 years) in Jhankrikhola CFUG is found to be significant at P value less than 0.05 with participation in CF fund mobilization and are more likely to participate (Table 9). However, Zhang (2001) and Coulibaly-Lingani et al. (2011) found no evidence to suggest that age impacted forestry activities.
A number of scholars argue that education spurs forestry participation (Lise, 2000; Dolisca et al., 2006; Torgler et al., 2011), while a few claim, increment in household education contends engagement in forestry activities (Agrawal and Gupta, 2005). Based on the findings of Carreira et al. (2016), education level only influences users; participation in public policies and perceptions, but not necessarily in CFM programs. But in this study, the Chi-square test of independence of both Jhankrikhola and Jagriti CFUG showed significant association with participation in 3 CF management activities: OP and Constitution preparation, collection of forest product, and fund mobilization. Regression analysis in Jagriti CFUG reveals, illiterate people are less likely to participate in all CF activities except Forest product Collection (Table 8). Likewise, Chhetri et al. (2013) study reported less participation of illiterate people in decision making process and resource utilization. In case of Jhankrikhola CFUG, the higher the education lesser is the participation in physical work requiring activities (Table 9).
Among all participation sorts (meetings, aliments, bulwark, and inspection), Naidu (2011) found a positive and statistically consequential impact of caste. As the results of this study indicate, caste has a significant association with participation in OP and Constitution-making, Silvicultural activities, Forest products collection, and CF fund mobilization in both CFUGs. Ordinal logistic regression (Table 8) (Table 9) shows that higher caste so-called Brahmin/ Chhetri and Indigenous castes are more inclined to participate in all CF activities indicated by positive coefficient except in Forest product collection. This study is in consistent with findings of Agrawal and Gupta (2005), Maskey et al. (2006), Naidu (2011), Chhetri et al. (2013), Oli and Treueb (2015), and Subedi and Timilsina (2016) who also documented less participation of lower caste forest users in forestry activities. This has been attributed to their involvement in daily labor to support their living.
In the study conducted by Oli and Treueb (2015), participation and wealth status did not show a statistically significant difference. In Jagriti CFUG, both the Chi-square test (Table 4) and regression analysis (Table 8) is significant at a 1% level in OP and Constitution-making. Rich and medium economic status people are found to be dominating in decision-making activities indicated by positive regression coefficient while poor people participate in physical work requiring activities. In Jhankrikhola CFUG, regression analysis (Table 9) shows the wealth ranking (1-rich) to be significant at a 5% level with participation in Silvicultural activities and Forest product collection and at a 10% level with OP and Constitution making. The negative Coefficient in Wealth ranking (1-rich) indicates less likely to participate in Forest product collection (Table 9). Poor households mainly depend on forest resources to sustain their living.

5 Conclusions and recommendation

5.1 Conclusions

Community forestry, one of the mediums to link-local users to the forest for forest protection, management, and utilization has been practiced for the last 5 decades. The majority of the respondents shared a neutral perception towards community forest management activities. The findings of the study cautiously conclude that the socio-economic variables are responsible for affecting the participation level.
Empirical analysis suggests that gender, caste, and education are the most influencing factors in participation with regards to all community forest management activities in Jagriti CFUG. In Jhankrikhola CFUG education is found to be the most promising factor among all under consideration. Given their substantial availability of time for communal activities, older people’s active participation in community forestry activities seems to be a deliberate choice rather than a result of compulsion. Moreover, higher caste people dominate in decision-making activities and the poor and lower caste people are confined to participate in physical work requiring more energy. The forest products collection drive is found to be a significant source of livelihood for poor and low caste people. Household wealth ranking, nevertheless, did not seem to influence participation levels more significantly.
The provision made by the government about the inclusion of at least 50% women in the executive committee representing poor, lower caste, and janajati’s should be strongly implemented into action. Activities intended to change the perception of users towards forest conservation and management must be focused on. Long-term technical, as well as advisory assistance from the DFO, FECOFUN, and other external organizations for the empowerment of women, poor, Dalits, and marginalized groups is highly recommended.

5.2 Limitations

The findings from the two CFUGs may not be fully representative of the broader national context. Different geography, socio-economy, and governance mechanisms can make subtle differences in the findings. Moreover, social data remains always crucial in understanding people’s behavior towards community forestry activities. The Covid pandemic also delayed the data collection process. So, the methods used in this study may not be enough to apprehend people’s perceptions.

Acknowledgment

It is with great pleasure and gratitude that we acknowledge the help of Mr. Ganashyam Khanal and Mr. Dinanath Adhikari; Ban rakshak at Sdfo Lekhnath for providing valuable support during data collection. We are thankful to Mr. Kedar Baral, Division Forest Officer, Kaski for his invaluable support and guidance. Our sincere cordial thank goes to Professor Yajna Prasad Timilsina, Assistant Professor Deepak Gautam, IOF, Pokhara for their technical assistance. We are equally indebted to both the studied CFUGs for their unbroken coordination throughout the survey.

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