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Journal of Resources and Ecology >

2023 , Vol. 14 >Issue 3: 604 - 615

DOI: https://doi.org/10.5814/j.issn.1674-764x.2023.03.015

Plant and Animal Ecology

Attitude of People towards Relief Fund as Human-Wildlife Conflict Management Strategy: A Case Study of Shivapuri-Nagarjun National Park, Nepal

  • RAI Pratap , 1 ,
  • JOSHI Rajeev , 2, * ,
  • NEUPANE Bijaya 3 ,
  • POUDEL Bishow 1 ,
  • KHANAL Sujan 4
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  • 1. The School of Forestry and Natural Resource Management, Institute of Forestry, Tribhuvan University, Kirtipur 44618, Nepal
  • 2. Department of Forestry, Amity Global Education (Lord Buddha College), Kathmandu 44600, Nepal
  • 3. Faculty of Agriculture and Forestry, University of Helsinki, Helsinki 00014, Finland
  • 4. Federation of Community Forestry Users Nepal, Bhaktapur 44800, Nepal
*JOSHI Rajeev, E-mail:

RAI Pratap, E-mail:

Received date: 2022-01-20

  Accepted date: 2022-06-10

  Online published: 2023-04-21

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Abstract

The present study aimed to assess if the people are satisfied with the relief fund scheme in the three different user committees belonging to 10 Buffer Zone User Group (BZUG) of Shivapuri-Nagarjun National Park (SNNP) in the situation with the higher incidents of conflict on those areas. Differences in local people’s attitudes and the effect of socio-economic factors like age, education, economic status, the quantity of crop damage, and their influence on the satisfaction level of people towards the prevailing relief scheme were mainly captured using a semi-structured questionnaire survey of the households. A total of 162 households (HHs), comprising 40.5% of the total 377 households, were surveyed using a purposive sampling method. People’s attitude towards relief schemes was measured at three levels (positive, negative, or neutral) while the Chi-square test at 5% level of significance was used to determine whether people’s attitudes and relief schemes were dependent or not. Similarly, Chi-square test was used to determine the dependency of different socioeconomic factors and people’s attitudes towards the relief scheme. The results showed that the majority of respondents i.e. 56% were not satisfied (negative attitude) with the relief scheme, 26% were neutral and only 18% of respondents were positive towards the relief fund (satisfied). A mere 41.93 USD was provided as relief against the crop loss of 101 USD at an average in the study area. Similarly, 73 USD was the relief amount for livestock loss (goat) of 124 USD per case. Owing to inadequate and delayed payment, the relief fund scheme was unable to bring a satisfactory change in the attitudes of people. Thus, the regular amendments of relief guidelines to address insufficient and delayed payment are recommended. Additionally, further studies on the wildlife damage relief schemes and its cost-effectiveness and appropriate measures to manage the drawback of this scheme are required.

Key words： attitude; conservation; crop raiding; depredation; livestock

Cite this article

RAI Pratap , JOSHI Rajeev , NEUPANE Bijaya , POUDEL Bishow , KHANAL Sujan . Attitude of People towards Relief Fund as Human-Wildlife Conflict Management Strategy: A Case Study of Shivapuri-Nagarjun National Park, Nepal[J]. Journal of Resources and Ecology, 2023 , 14(3) : 604 -615 . DOI: 10.5814/j.issn.1674-764x.2023.03.015

1 Introduction

The wildlife conservation approach in Nepal started with the formulation of National Parks and Wildlife Conservation (NPWC) Act 1973 (Wagle, 2009). The establishment of the protected areas began with this act and at present Nepal harbors an extensive network of protected areas (PAs) spread over 23.39% of the area of the country (Lamichhane et al., 2020). These PAs are established to protect and conserve the wild flora and fauna but have met with numerous challenges such as livestock depredation, damage to crops and properties, attacks on humans by several wildlife species that undermine the conservation effort (Ogra and Badola, 2008; Acharya et al., 2016; Lamichhane et al., 2018). Human-wildlife conflict (HWC) is a major conservation issue of increasing interest to conservationists (Woodroffe et al., 2005) especially in and around these protected areas (Nepal and Weber, 1995; Thapa, 2016; Lamichhane et al., 2018). Farming and animal husbandry in close proximity to protected areas acts as an easy source of food for wildlife resulting in their frequent visit to these areas (Pandey and Bajracharya, 2015; Lamichhane et al., 2019) causing a negative impact on human safety through animal attack; health through disease transmission and livelihoods through crop, property damage and livestock depredation (Ogada et al., 2003; Woodroffe et al., 2005; Pandey and Bajracharya, 2015; Lamichhane et al., 2018).
The loss incurred by the local people due to wildlife damage is one of the major issues that triggers park-people conflict and may compromise the sustainability of protected areas (PAs) (Lamsal, 2012; Dhakal and Thapa, 2015). Similarly, the spill-over population of wildlife as a result of successful conservation (Studsrød and Wegge, 1995) and the shrinkages of their habitat (Sukumar, 1991) are other reasons for such conflict. The negative impact of these wildlife damages frequently encourages retaliatory killings of wildlife (Woodroffe et al., 2005; Ripple et al., 2014; Ripple et al., 2015; Nyhus, 2016) and may lead to extirpations of endangered species (Bulte and Rondeau, 2005; Treves et al., 2011) and more importantly cause diminished support for conservation among the locals (Woodroffe et al., 2005; West et al., 2006). For example, Dhungana et al. (2016) reported four retaliatory killings of tigers by locals in Chitwan National Park (CNP) from 2007 to 2014.
Several studies in Nepal have identified HWC as major issue in wildlife conservation. For example, Acharya et al. (2016) reported 2.9 fatalities from 7.7 attacks per month by the major wild animal species such as bear (Ursus spp.), leopard (Panthera pardus), elephant (Elephas maximus), tiger (Panthera tigris), rhinoceros (Rhinoceros unicornis), etc. in Nepal. Lamichane et al. (2018) reported tiger and leopard to be the main depredator of livestock where an annual average of 122.94 incidents of livestock depredation occurred around CNP of Nepal. A study by Studsrød and Wegge (1995) in Bardia National Park reported a loss of 112.04 USD per year per household from the damage of crops like paddy, maize, lentil, and wheat.
Studies in Shivapuri-Nagarjun National Park (SNNP) has identified crop raiding and livestock depredation as the major type of HWC. Several species like wild boar (Sus scrofa) (major), monkey (Rhesus spp.), barking deer (Muntiacus muntjak), porcupine (Hystrix spp.), rats, and birds commonly raided paddy, wheat, maize, millet, potato, mustard and root crops in SNNP (Purkait, 2008; Pandey and Bajracharya, 2015). Pandey and Bajracharya (2015) reported that households living in Bidur Municipality of Nuwakot and Tokha Municipality of Kathmandu faced severe economic losses (10238 USD yr-1) due to these raiding wild animals. Studies showed leopard (Panthera pardus), jungle cats (Felis chaus), and jackals (Canis aureus) as the major predators for livestock (mainly goat and cattle) in SNNP (Purkait, 2008; Pandey and Bajracharya, 2015). Since the conflicts between humans and wildlife may incite retaliation, it is mandatory to develop effective prevention and mitigation strategies (Woodroffe et al., 2005; Treves et al., 2009; Dhungana et al., 2016; Nyhus, 2016).
A wide range of different management tools like sport hunting (Peebles et al., 2013); guarding, noise-making, lighting, use of guard dogs (Markar et al., 2005; Linnell et al., 2012); fencing (Woodroffe et al., 2014), etc. are practiced worldwide to address HWC depending upon place and concerned animal. Some of the common methods practiced in Nepal includes tin hitting, group shouting, throwing flaming stick (Pandey and Bajracharya, 2015); trenching, watchtower (Thapa, 2010) and electric fencing (Sapkota et al., 2014). In addition to this, an economic incentive like compensation for damage caused by wildlife is also practiced around the world.
Wagner et al. (1997) recognized increasing human tolerance of wildlife by compensating for wildlife damages as one of the methods to mitigate these conflicts. Compensation schemes have been practiced in many countries including Nepal in an attempt to resolve the issues of HWC (Nyhus et al., 2005; Dhungana et al., 2016; Ravenelle and Nyhus, 2017). Nepal endorsed a compensation/relief scheme by formulation of the Wildlife Damage Relief Guideline in 2009 which was dismissed and a new guideline was formulated in 2013 with the aim of developing a harmonious relationship between people and parks (Silwal et al., 2013; Dhungana et al., 2016). This Compensation program (relief program in the case of Nepal) involves partial or full payment of the value of crops, property, or livestock lost by wildlife. This wildlife damage relief guideline has undergone amendments three times in the year 2015, 2017, and 2018 respectively to address the various shortcomings like inadequate and delayed payments, easy processing, and including more problematic wildlife species. The recent amendments have increased the number of problem wildlife species from 8 to 14, enabled the victim to process for and claim relief from their respective buffer zone user committee (BZUC), and insured relief payments as high as 8265 USD. SNNP has been running wildlife damage relief since 2017 (SNNP, 2017).
Increased level of tolerance towards offending wildlife and positive park people relationship can be achieved through timely, transparent, and equitable execution of such economic compensation (Ogra and Badola, 2008). Conversely, critics find compensation/relief schemes inefficient, prone to corruption, lacking transparency, low assistance, fail to account for transaction costs, and time-consuming (Nyhus et al., 2005; Maclennan et al., 2009; Watve et al., 2016). So, payment of compensation for damages does not ensure that affected people will display high tolerance towards the damage-causing species (Naughton-Treves et al., 2003). Numerous studies have examined attitudes toward wildlife (Naughton-Treves et al., 2003; Wang and Macdonald, 2006; Morzillo et al., 2010); however, few have examined the impact of compensation payment on peoples’ attitudes, especially in Nepalese scenarios, and have a poor understanding on how individual experiences, socio-economic and environmental factors shape people’s attitude towards relief scheme as a conflict management tool. Thapa (2016) and Lamichhane et al. (2019) reported that the majority of buffer zone people from Parsa National Park (PNP) and CNP respectively were not satisfied with the relief payment for wildlife damage as a conflict management tool.
Thus, the damages from wildlife are rising around SNNP as in other lowland protected areas (e.g., CNP) adding socio-economic burden (Pandey and Bajracharya, 2015; Pandey et al., 2016; Lamichhane et al., 2018). Thus, these parks conduct relief programs as one of the conflict management tools in order to develop the positive attitudes of local people that can ultimately contribute for the success of the conservation programs. And few studies about people’s attitude towards relief are conducted which are concentrated in lowland protected areas like CNP; therefore, we selected SNNP for this study. This study aimed to understand the satisfaction level of local people with the existing relief fund scheme. Besides, this study attempted to identify the impact of socio-economic factors of local people in shaping their attitudes. Assessing people’s satisfaction with the relief funds helps to determine if the program is likely to ease tension between humans and wildlife. Through this study, we hoped to gain a deeper understanding of the existing shortcomings of the relief scheme so as to bring desired changes that can help to resolve the conflicts.

2 Study area

The study was conducted in Shivapuri-Nagarjun National Park (SNNP) (Fig. 1), located in the Kathmandu Metropolitan City, initially established as Shivapuri Mountain Range and later declared Shivapuri Watershed Conservation Area in 1976 in order to protect the watershed of Holy Rivers Bagmati and Bishnumati from heavy deforestation and encroachment. Geographically Shivapuri Forest Block is located within 27°45′ to 27°52′N and 85°16′ to 85°45′E longitude and the Nagarjun Forest Block is located within 27°43′ to 27°46′N latitude and 85°13′ to 85°18′E. Elevation of the park ranges from 960 m to 2732 m at Shivapuri Peak (SNNP, 2017). The climate of Shivapuri has a subtropical to warm temperate climate with an average maximum temperature of 19.9 ℃ and an average minimum temperature of 11.15 ℃. The mean annual precipitation is 236.5 mm mostly occurring during the monsoon period (SNNP, 2017).
Fig. 1 Location of study area in SNNP based on the administrative division

Note: Map in upper left corner shows the network of protected areas in Nepal along with the location of Shivapuri-Nagarjun National Park in Nepal. User committee in the legend means the 3 buffer zone user committee of SNNP in which the study was conducted.

SNNP is surrounded by high human settlements and most of these people are dependent on agriculture (about 70%) for their subsistence needs. Due to this kind of extensive farming in close proximity to park areas, wild animals from the park are attracted to these easy sources of food (Wagner et al., 1997) causing great economic loss to crops as well as livestock. The study reported crop raiding and livestock depredation as major HWC in all three-study sites of SNNP. Wild boar, monkey, porcupine, bear, etc. were the major crop raider causing damage to maize, millet, paddy, mustard, etc, which is supported by the results of Pandey and Bajracharya (2015). Likewise, Pandey and Bajracharya (2015) reported that farmers have abandoned their farmland in SNNP to avoid the losses. The land use pattern in and around SNNP is predominated by forest followed by shrubland, cultivated land, and grassland respectively. Floral diversity is quite high in SNNP due to its location, altitudinal and climatic variations and it harbors a total of 1402 plant species. Similarly, about 129 species of mushrooms and nearly 22 species of macrofungi have been reported. There are more than 1114 flowering plants including 16 endemic species. Schima wallichii, Castanopsis indica, Alnus nepalensis, Pinus roxburghii, Quercus semicarpifolia, Quercus lanuginose, and Rhododendron arboretum are the dominant vegetation in this park. In addition to this, the park has a record of 9 species of amphibians, 20 species of reptiles, 124 species of butterflies, and 320 species of avifauna (SNNP, 2017).

3 Data collection and analysis

3.1 Key informant interview (KII)

Key informant interviews (KII) were conducted by interviewing the park managers. They were asked to share their understanding of HWC and the associated relief scheme. Four officials from the park office were included in the study. Apart from park managers and officials, representatives from BZUC (3 from Sundarijal-Shivapuri, 2 from Sindhu-Shivapuri, and 1 from Goldhunga Jitpur) were also interviewed. They were asked about the ground-level realities of wildlife conflict (crop and property damage, livestock depredation, human injury or casualty), associated animals, and subsequent relief disbursement.

3.2 Household questionnaire survey

After taking information about the Buffer Zone User Groups (BZUCs) of SNNP and depending upon most conflict-prone areas, 3 BZUCs consisting of 10 BZUGs were purposively selected. The selection criteria were based on the information regarding the crop damage, livestock damage, human casualties, and relief fund obtained from key informants (SNNP office, BZMC, Division Forest office (DFO), and local leaders). Altogether 10 BZUG consisting of 6 villages: Panchmane, Thulogaun Aanpchaur, Okhreni, Mulkharka, Jyotish Gaun, and Gurung Gaun from three Buffer Zone User Committees (BZUC were included in the household survey out of which BZUG from Shivapuri Sundarijal BZUC is located inside SNNP while the rest are located in the periphery of the park. A total of 162 (9 had a poor responses, so the final number is 153) households (HHs), comprising 40.5% of the total of 377 households (Table 1), were surveyed using a purposive sampling method. The field study was carried out during the winter season between December 2019 to February 2020. Semi-structured questionnaire was designed for the survey and prior to implementation, questions were pre-tested in some households of Shivapuri Sundarijal BZUC, and necessary modifications were made for data reliability. The household questionnaire consisted of three parts which included questions related to i) socio-economic background of the household, landholding, livestock holding, livelihood strategies, and source of income ii) type of problems the household faced due to wild animals, the quantity of damage, estimated monetary value of losses iii) attitude towards relief fund scheme for determining the relation of socio-economic factors and attitude of people towards relief scheme. The attitude of respondents was measured in three response patterns: positive, negative, or neutral in order to reduce the confusion among respondents between the same categories of attitude i.e. strongly agree, agree, and so on.

3.3 Data analysis

Descriptive analysis was done for the socio-economic characteristics of the respondents and interpreted in the form of frequency and percentage. Similarly, no of conflict cases, species involved in the conflict, relief amount distributed were analyzed and interpreted in the tabular form. Besides, responses were first analyzed using frequencies and percentages to ascertain a general trend of the attitudes towards the relief fund schemes. People’s attitude towards the relief schemes was measured at three levels (positive, negative, or neutral). Chi-square test was used to determine whether people’s attitudes and relief scheme were dependent or not using R (R Core Team 2018). Similarly, Chi-square was used to determine the dependency of different socio-economic factors and people’s attitudes towards relief schemes. The economic status of the respondents was categorized based on the annual income of the family. Family with an annual income of less than approximately USD 991 were categorized as the low, medium for income of approx. USD 991 to USD 2479 and rich for income more than USD 2479.

4 Results

4.1 General socioeconomic characteristics

On average 71% were illiterate or had lower level of education whereas 29% had higher or at least secondary level of education. Around 39% belonged to very low economic status while the rest had in medium and high economic status. Sundarijal Shivapuri had the highest proportion of people in low economic status (55%). Around one-third were agriculturists. Other occupations include daily wage worker, government jobs and businesses. The highest number of agriculturists was from Sindhu Shivapuri. Despite being engaged in other occupations, most of the people were involved in agriculture production too (Table 2).
Table 2 Socioeconomic characteristics of respondents
Socio economic characteristics Indicators Goldhunga Jitpur (n=55) Sindhu Shivapuri (n=43) Sundarijal Shivapuri (n=55) Grand total (n=153)
Age <40 12 22% 3 7% 17 31% 32 21%
40-60 33 60% 24 56% 30 55% 87 57%
>60 10 18% 16 37% 8 15% 34 22%
Education Higher 20 36% 13 30% 11 20% 44 29%
Low or illiterate 35 64% 30 70% 44 80% 109 71%
Economic status Medium to high 43 78% 25 58% 25 45% 93 61%
Low 12 22% 18 42% 30 55% 60 39%
Occupation Agriculture 36 66% 35 81% 37 67% 108 71%
Others 19 34.5% 8 19% 18 33% 45 29%

4.2 Relief fund scheme in SNNP

4.2.1 Relief support for wildlife damage

SNNP commenced a relief program under wildlife damage relief guidelines (2013) in 2017/18 (SNNP, 2017). This program covers damages caused by 14 species listed in the guidelines except for SNNP where there is no restriction. Similarly, maximum cap on the relief amount ranges from 82 USD to 8265 USD depending upon the type of damage. Similarly, the guideline has developed a certain mechanism for making claims for relief. First, there is damage assessment based on photographic shreds of evidence and field visits. This is followed by the economic valuation of the damage, verification recommendation, and approval for relief payment (Carson et al., 2003).
A total of 24874 USD was disbursed by SNNP in the fiscal year 2017/18 for three kinds of damage; human injury, livestock depredation, and crop-raiding (Table 3). An average of 59 USD was paid for crop damage, 71 USD for livestock depredation, and 223 USD for human injury. Similarly, a total of 34875.38 USD was disbursed by SNNP in the fiscal year 2018/19 (Table 3). An average of 37 USD was paid for crop damage, 61 USD for livestock depredation, and 398 USD for human injury. There was an overall increase in total payment but average pay for crop and livestock depredation decreased.
Fig. 2 A flow diagram showing the workflow of the relief fund scheme adopted by SNNP

Note: Source: Based on informal discussion with park officials and stakeholders.

Table 3 Relief disbursed by SNNP in the fiscal year 2017/2018 and 2018/2019
Serial number Conflict type Involved wildlife Relief provided for damage caused by wildlife in the fiscal year 2017/2018 Relief provided for damage caused by wildlife in the fiscal year 2018/2019
Number of cases Relief amount (USD) Relief per case (USD) Number of cases Relief amount (USD) Relief per case (USD)
1 Human injury Snake and wild boar 1 223.03 223.03 2 795.09 397.55
2 Livestock depredation Common leopard and others* 48 3392.56 70.68 88 5358.68 60.89
3 Crop raiding Wild boar 360 21258.68 59.05 643 24503.43 37.30
Monkey - - - 97 3180.99
Others - - - 30 1037.19
Total 409 24874.27 352.76 860 34875.38 495.74

Note: *Jackal, Yellow throated marten.

Similarly, records of relief recipients were also collected from the HHs survey and tallied with the relief disbursement data from respective BZUC and SNNP. Out of 153 respondents, 35 (22%) received relief payment since it was initiated. A total of 44 cases (41 crop damage and 3 livestock depredation) among the respondents were provided with relief funds at an average of 41.9 USD per case for crop damage and an average of 73 USD per case for livestock respectively from 2017 to the time of field survey (Table 4). A total of 16 (21 cases) respondents from Sindhu Shivapuri were provided relief for wildlife damage (880.99 USD). Goldhunga Jitpur had the least number (23%) of relief recipients among the respondents (350.54 USD). Most of the relief payment was for wild boar causing damage to maize. The relief received by respondents is given in Table 4.
Table 4 Total relief disbursed among the respondents in both fiscal years
HWC BZUC Sundarijal Shivapuri Sindhu Shivapuri Goldhunga Jitpur Total
Crop loss Recipient 11 16 6 33
No. of cases 12 21 8 41
Raided crop Maize Maize Maize -
Raider Wild boar (10 cases) - Wild boar (2 cases) -
Monkey (1 case) Wild boar Monkey (6 cases) -
Porcupine (1 case) - -
Raided quantity 2157 kg 5925 kg 1850 kg -
Received relief fund (USD) 482.64 880.9 355.37 1719.01
Relief fund per case (USD) 40.22 41.95 44.42 41.93
Livestock depredation Recipients 1 - 1 2
No. of cases 1 - 2 3
Predator/Predated animal C. Leopard/Goat - Leopard/Goat -
Received relief fund (USD) 66.16 - 152.9 219.01
Relief fund per case (USD) 66.10 - 76.44 73

4.2.2 Participation in relief fund

Out of 153 respondents, 70 (46%) reported some kind of wildlife damage and applied for relief while 83 (54%) had never participated in this program, and 35 respondents were reported to have received relief while 35 failed to secure the payment. The main reasons for their failure were the inability to show proof and incomplete documentation. Despite suffering loss only 9 (26%) non-recipients applied for the second time while 26 (74%) recipients reapplied for relief. Decreases in the number of these applicants were reported to be due to doubt created from failure to receive relief, frustration over the cumbersome procedure, etc.
Chi-square test revealed variables like age, education and economic status of respondents were not dependent on participation rate in the relief scheme. While the participation in the relief fund was dependent on the status of crop damage (χ2=9.1465, df=1 and P=0.002492) (Appendix 1). Respondents with high crop damage had high participation in the relief funds. 54% of respondents who suffered severe crop damage (>50%) participated in relief fund while the rest 46% did not participate.

4.3 Attitude of respondents towards relief fund scheme

The overall attitude of respondents towards the relief fund scheme was negative (56%) i.e., more people were unsatisfied with the role of the relief scheme in reducing people’s suffering from wildlife damage. The attitude of respondents to the relief scheme was dependent on relief recipient status (χ2=7.11, df=2, P=0.03) (Appendix 2). A higher proportion of non-recipients (61%) of relief funds disagreed that relief funds reduce suffering from wildlife damage than that of recipients of relief (40%). The overall attitude of respondents towards willingness to accept relief was positive (89%) while 8% were unwilling to accept relief funds and 6% were neutral.

4.4 Effect of different socio-economic variables on attitude towards the relief fund

In the case of economic status, respondents across all economic status were more negative toward the relief fund schemes (χ2=6.0071, df=2, P=0.04961) (Appendix 3). The education level of the respondents was dependent on their attitude towards the relief fund schemes (χ2=21.013, df=2, P =0.00002736) (Appendix 3). The respondents with higher education had less negative attitudes as 68% of respondents with lower level education were negative towards relief fund scheme comparison to secondary level educated respondents (27%). Similarly, the attitude of the respondent towards relief fund was dependent on the status of crop damage (χ2=7.5245, df=2, P=0.02323) (Appendix 3). 61% of respondents with higher crop damage were highly negative towards the relief fund scheme. If the status of crop damage was found to be greater than 50% then it was considered high damage, while damage less than 50% was considered low damage. Similarly, attitudes of respondents towards the relief schemes and age group were dependent (χ2=9.6, df=4, P=0.048) (Appendix 3). Comparatively, older respondents were less satisfied with the relief scheme. 74% of respondents in the old age group disagreed that relief reduces the suffering of people while only 38% of young (<40) respondents disagreed with the statement.

5 Discussion

The finding of this study is consistent with that of other studies that the leopard (Panthera pardus) was the main livestock depredator in Sundarijal VDC (Purkait, 2008). Livestock depredation by a leopard, jungle cat, yellow-throated marten, and jackals are reported in the study area. Shivapuri Sundarijal is reported to have the highest-level livestock unit (goat) and the depredation too where the attacks occurred in household areas and corral too. So, grazing livestock in forests is not the only issue but the corral system in the study area because most of the corral systems were fragile and open type due to which livestock depredation was easy for the predator (SNNP, 2017). People in the Goldhunga area have reported that they have decreased the livestock numbers to avoid the loss from depredation and encouraged towards the stall-feeding system. SNNP (2017) reported following severe damage to the wall in the 2015 earthquake caused easy access for animals to nearby areas causing damage. In addition to this, lack of comprehensive preventive measure was also responsible. Similarly, the respondents believed occasional release of elsewhere captured monkeys in the parking area closest to the settlement has also elevated the human-monkey conflict in the recent years.
The effectiveness of mitigation measures declines with time as the wild animals become more adapted to it (Udmale et al., 2014). The mitigation measures adopted in SNNP were the same old technique practiced long times back which were effective for a very short interval of time. Crop guarded by constructing temporary houses was the most effective method to control loss but it required intensive labor and time. Park has been constructing fences at different places in the park boundary but was not satisfactory enough to halt wildlife damage. Similarly, the BZUC allocates very less budget for human-wildlife conflict mitigation. On the other hand, wildlife populations are on the rise which may lead to the intensification of human-wildlife conflict in SNNP. High conflict may overpower the benefit of the park, thus causing diminished tolerance (Woodroffe et al., 2005) and questioning the co-existence of humans and wildlife in the human-dominated landscapes.
Based on the secondary data, SNNP made payments for the wildlife damage in two fiscal years 2017/18 and 2018/19. In 2018/19 SNNP paid an average of 37 USD per case for crop damage, 61 USD for livestock depredation and 398 USD per case of human injury. This payment is slightly less than the payment made in India in 2012-2013 where an average of 47 USD for crop and property damage, 74 USD for livestock, and 103 USD for human injury (Karanth et al., 2018). This kind of low amount of payment is not likely to solve the misery of people facing loss. According to field data, a mere 41.93 USD was disbursed as relief against crop damage of 101.45 USD at an average in the study area. Similarly, 73 USD was disbursed for livestock depredation of 124 USD per case.
Our findings mirror other studies, where participation in relief scheme is very low despite a majority of respondents suffering from wildlife damage (Karanth et al., 2012) and the major reasons being lengthy and difficult procedures, uncertainty about relief, and inadequate payment (Rohini et al., 2016). Past experience with relief schemes plays a vital role in participation (Patt et al., 2009). Silwal et al. (2013) suggested wildlife victims suffer mentally, physically, and financially for nominal relief. The finding of this study contradicts those of other studies in that participation in the scheme was shaped by wealth (Ogra and Badola, 2008). Participation in relief schemes in SNNP was neither dependent on economic standing, education and age but on the intensity of damage to crops. People either educated or not; well-off or not; young or old did not bring any interests on these kinds of inadequate relief payments unless great damage was done. The difference in attitudes towards relief recipients and non-recipients was slightly significant. Shibia (2010) reported similar findings where differences in wildlife benefits and attitudes on conservation were significant. In addition to this, Wang et al. (2006) reported an apparent positive attitude derived from the expectation of significant economic benefit from park management.
In our case, the overall attitude of respondents towards the relief scheme was negative. The finding of this study is consistent with other studies mentioning respondents were not satisfied with the relief scheme due to being inadequate and delayed payment, uncertainty, and time consuming (Distefano, 2005; Nyhus et al., 2005; Bhattarai, 2009; Kgathi et al., 2012; Rohini et al., 2016; Thapa, 2016; Lamichhane et al., 2019). In addition to this, very low proportions of people have been compensated (partial) causing unrest and a negative attitude towards the other half. Respondents with higher education were more likely to have a positive attitude towards the relief schemes in the study area. These findings concur with the findings of other studies that education induces a positive attitudes (Shibia, 2010; Bhattarai and Fischer, 2014; Megaze et al., 2017). Similarly, a study in Makalu Barun National Park of Nepal reported that educated people can better comprehend the importance of the conservation area by developing positive attitudes (Mehta and Heinen, 2001). Carter et al. (2014) reported negative attitudes among low-income and marginalized people towards tigers in Chitwan National Park (CNP) since they were unable to fully utilize the means of formal education. Thus, it can be inferred that higher education will induce higher awareness and minimize hostility resulting in a positive attitude. Younger respondents were more likely to have a positive attitude towards relief than their counterparts. This finding contrast with those of study conducted in Makalu Barun National Park where conservation attitude is independent of age. On the other hand, Shibia (2010) reported younger respondents were more educated due to better access to education. Shibia (2010) further reported older respondents were exposed to adverse effects of wildlife and restriction on use associated with reserve for a longer periods thus resulting in a negative attitude towards reserves.
Similarly, higher crop damage produced a more negative attitude towards the relief fund schemes. Similar findings were reported by studies where wildlife damage is associated with negative attitudes (Wang and Macdonald, 2006; Shibia, 2010). A study in SNNP reported that high crop-raiding develops more negative attitudes than those with fewer crop raiding (Air, 2015). Wildlife conflicts tend to threaten people’s ability to secure sustainable livelihoods (Nepal and Weber, 1995; Studsrod and Wegge, 1995) while relief amount barely covers the damage resulting in negative attitude among the people. In the case of economic status, generally people had negative attitude toward the relief fund schemes but well off respondents were slightly positive than the poor ones. This is in line with the findings that greater affluence is linked with positive attitudes (Infield, 1988; Shrestha and Alavalapaty, 2006). People with single livelihood strategies who lack alternative income strategies are more vulnerable to wildlife damage and tend to have negative attitudes (Dickman, 2010). On the other hand, well off people generally have alternative source of income. So, they can somewhat cope with the wildlife damage and generally posses positive attitude.

6 Conclusions

HWC is on the rise especially crop-raiding which constituted nearly 53% loss in the average annual income of a HH in the study area where over 70% of the people were subsistence agriculturists which could affect their livelihood. Further, livestock depredation intensified the conflict. In contrast to the high losses, the relief payment was found to be inadequate and time-consuming. The gaps of proper knowledge about processing for relief, uncertainty about getting relief were the other causes of low participation. Though the relief scheme was widely accepted, respondents were not satisfied with it, developing a negative attitude towards it. Socio-economic factors like age, education, and status of crop damage were good predictors of attitude towards relief fund schemes. Thus, integrating relief with a proper mitigation strategy is desirable. The findings indicate that monetary losses of crops and livestock by wildlife along with the drawback of the relief scheme are the priority issues to be addressed to win the support of buffer zone people towards wildlife conservation.

Appendix 1 Chi square test results of participation in relief fund scheme
Socio-economic variable Category Applied for relief Grand total Test statistics
No (n=83) Yes (n=70) χ2 df P
Age class <40 18 56% 14 44% 32 0.15 2 0.93
>60 19 56% 15 44% 34
40-60 46 53% 41 47% 87
Education of respondents Higher 23 52% 21 48% 44 0.0175 1 0.895
Lower or illiterate 60 55% 49 45% 109
Economic status High 48 52% 45 48% 93 0.4205 1 0.517
Low 35 58% 25 42% 60
Status for crop damage High (>50%) 49 46% 58 54% 107 9.15 1 0.0025
Low (<50%) 34 74% 12 26% 46
Gender of respondents Female 19 49% 20 51% 39 0.38 1 0.54
Male 64 56% 50 44% 114
Appendix 2 Chi square test results of attitude towards relief fund scheme and subsequent tolerance to wildlife
Responses Received relief? Does relief fund reduce suffering from wildlife damage? Grand total Test statistics
No (n=118) Yes (n=35) χ2 df P
Agree 16 14% 11 31% 27 18% 7.11 2 0.03
Disagree 72 61% 14 40% 86 56%
Neutral 30 25% 10 29% 40 26%
Appendix 3 Chi square test results of attitude towards relief fund scheme and various socio economic variables
Socio economic variable Category Response Total Test statistics
Agree (n=27) Disagree (n=86) Neutral (n=26) χ2 df P
Economic status of the
respondent		 High 20 22% 45 48% 28 30% 93 6.0 2 0.0496
Low 7 12% 41 68% 12 20% 60
Education of the respondents Higher 13 30% 12 27% 19 43% 44 21.0 2 2.74E-05
Lower or illiterate 14 13% 74 68% 21 19% 109
Status of crop damage High (>50%) 13 12% 65 61% 29 27% 107 7.5 2 0.023
Low (<50%) 14 30% 21 46% 11 24% 46
Age group <40 (Young) 7 22% 12 38% 13 41% 32 9.6 4 0.048
40-60 (Med.) 15 17% 49 56% 23 26% 87
>60 (Old) 5 15% 25 74% 4 12% 34

The authors would like to express sincere gratitude to Prof. Santosh Rayamajhi, PhD and Associate Prof. Jhamak Bahadur Karki, Ph.D. for their noble guidance and supervision of the field and for the drafting of the manuscript. We are very much thankful to the Department of National Parks and Wildlife Conservation (DNPWC) and Shivapuri-Nagarjun National Park (SNNP) for providing us permission to do this research work and other necessary information. We would like to provide special thanks to Mr. Dil BahadurPurja Pun (Chief Conservation Officer-SNNP), Ms. Kanti Kandel (Assistant Conservation Officer-SNNP), Mr. Suman Bhandari (Ranger-SNNP), Mr. Keshav Dhodari (Ranger-SNNP), Anish KC (Ranger-SNNP), and all the buffer zone user committee members who helped us during data collection.

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