Introduction
Human–wildlife conflict (interactions between people and wildlife that result in negative outcomes for one or both) is one of the most challenging issues for effective management and conservation of biodiversity (Nyhus, Reference Nyhus2016; Mekonen, Reference Mekonen2020). Generally it occurs through spatial overlap of people and wildlife species, and it often results in either damage to habitats or resources, or direct threats to individual animals (both wildlife and livestock) or people (Sillero-Zubiri et al., Reference Sillero-Zubiri, Sukumar, Treves, Macdonald and Service2006; Dickman, Reference Dickman2010). Such conflict is often most intense in areas affected by habitat loss and fragmentation or where there is a high density of megafauna (leading to resource competition between wildlife and people) or fear of large mammals (particularly predators; Weber & Rabinowitz, Reference Weber and Rabinowitz1996; Schwerdtner & Gruber, Reference Schwerdtner and Gruber2007).
Nepal is a hotspot for biodiversity and home to several species of megafauna, including the Endangered Bengal tiger Panthera tigris tigris, which inhabits lowland forests (Smith et al., Reference Smith, Ahearn and McDougal1998; Carter et al., Reference Carter, Gurung, Viña, Campa, Karki and Liu2013). These regions are also areas of expanding human settlements (Wikramanayake et al., Reference Wikramanayake, McKnight, Dinerstein, Joshi, Gurung and Smith2004). In recent decades, tiger populations have decreased as a result of conflict with humans (mostly because of habitat fragmentation and illegal hunting), prompting the Government of Nepal to formulate laws, policies and institutional arrangements for conserving tigers (Ghimire, Reference Ghimire2022). Conservation efforts have relied on both government and local communities, and resulted in the substantial recovery of tiger populations (Budhathoki, Reference Budhathoki2004; Thapa et al., Reference Thapa, Wikramanayake, Malla, Acharya, Lamichhane and Subedi2017). These initiatives have included designating protected areas for tigers, regular population monitoring, and implementing community-based conservation approaches by promoting tourism and its associated economic benefits. According to the 2022 tiger census there are estimated to be 355 tigers in Nepal, a nearly three-fold increase since the 2009 census (Department of National Parks and Wildlife Conservation, 2022). As tiger numbers increase, support for tiger conservation from local communities residing within tiger-inhabited areas becomes even more critical for ensuring long-term persistence of the species (Treves & Karanth, Reference Treves and Karanth2003; Chanchani et al., Reference Chanchani, Noon, Bailey and Warrier2016). However, increases in both tiger and human populations also increase the likelihood of conflict, potentially undermining conservation efforts (Goodrich, Reference Goodrich2010; White et al., Reference White, Ward, White and Ward2010; Struebig et al., Reference Struebig, Linkie, Deere, Martyr, Millyanawati and Faulkner2018).
Bardiya National Park and the Khata Corridor form an area of prime tiger habitat in Nepal (Bhattarai et al., Reference Bhattarai, Wright, Morgan, Cook and Baral2019). The forests of the Khata Corridor serve as a connection for tigers between Bardiya National Park in Nepal and Katarniaghat Wildlife Sanctuary in India. The corridor supports both resident and transient tigers but is subject to high levels of human disturbance (Kanagaraj et al., Reference Kanagaraj, Wiegand, Kramer-Schadt, Anwar and Goyal2011). This area supports low densities of wild tiger prey, and consequently tigers in the Khata Corridor supplemented their diet with livestock (Wegge et al., Reference Wegge, Yadav and Lamichhane2018). However, during 1998–2014, tiger predation on livestock significantly decreased because of improvements in herding practices and reductions in forest degradation. This area has experienced dramatic growth in the resident tiger population, from 18 individuals in 2009 to 125 in 2022 (Department of National Parks and Wildlife Conservation, 2022; Ojha, Reference Ojha2022). Coincident with more tigers and an increasing human population, there have been increases in encounters with tigers (Wegge et al., Reference Wegge, Yadav and Lamichhane2018; Rauniyar, Reference Rauniyar2021).
The resurgence of large carnivore populations in their historical habitats can have both negative and positive impacts. Potential conflict with humans may be offset by enhancements in ecosystem services triggered by cascading ecological change, as seen with the reintroduction of the grey wolf Canis lupus to Yellowstone National Park, USA (Ripple & Beschta, Reference Ripple and Beschta2012). Additionally, recovery efforts for apex carnivores can benefit both people and wildlife, as exemplified by the successful recovery of the Eurasian lynx Lynx lynx coupled with economic benefits from tourism (Wilson, Reference Wilson2004). Similarly, conflict may not always be directly associated with increases in carnivores but rather with inequitable realization of environmental benefits (e.g. tourism revenue and access to local natural resources) and risks (e.g. human–wildlife conflict and pollution), as has been highlighted within an environmental justice framework (McInturff et al., Reference McInturff, Cannon, Alagona and Pellow2021). This framework aims to mitigate uneven allocations of both environmental benefits and risks by focusing on disadvantaged communities to ensure they do not bear an unfair burden of risk. Unequal distribution of benefits and risks create localized (i.e. settlement-specific) coexistence issues, which can lead to the intensification of conflicts for some residents but not for others (Fig. 1; Jordan et al., Reference Jordan, Smith, Appleby, van Eeden and Webster2020). This subsequently leads to disparate societal identities and descriptive norms amongst communities (Coria & Calfucura, Reference Coria and Calfucura2012; Marchini & Macdonald, Reference Marchini and Macdonald2012). When conflict results in negative economic outcomes, communities may rely more on forest resources, increasing the risk of further conflict (Braczkowski et al., Reference Braczkowski, O'Bryan, Lessmann, Rondinini, Crysell and Gilbert2023).
Fig. 1 Linkages between environmental justice, coexistence inequalities, human–tiger conflict and tourism (Jordan et al., Reference Jordan, Smith, Appleby, van Eeden and Webster2020; McInturff et al., Reference McInturff, Cannon, Alagona and Pellow2021). This framework highlights the unequal distribution of environmental benefits (tourism) and harm (human–tiger conflict) leading to inequalities amongst communities, which in turn cause human–tiger conflict. Unequal distribution of benefits of tourism across communities can create coexistence inequalities, but benefits also have potential to reduce human–tiger conflict if they are distributed equally.
The current situation in the Khata Corridor is challenging because, although tiger populations are increasing across the region, there are disparities amongst communities in how they experience such changes. These communities are located at varying distances from Bardiya National Park (Fig. 2), and experience an unequal distribution of tourism benefits, differential enforcement of forest use laws and varying intensities of human–wildlife conflict risk (Wegge et al., Reference Wegge, Yadav and Lamichhane2018; Sharma & Neupane, Reference Sharma and Neupane2023). These circumstances highlight several environmental justice issues (McInturff et al., Reference McInturff, Cannon, Alagona and Pellow2021; Van Horne et al., Reference Van Horne, Alcala, Peltier, Quintana, Seto and Gonzales2023). Following an environmental justice framework, here we explore the drivers of spatiotemporal overlap that increase the risk of conflict between people and tigers. Specifically, we examine whether human–tiger conflict risk is primarily a result of tigers encroaching into human habitat or because of increased human visitation in tiger forest habitat. To achieve this, we analyse forest visitation patterns of people, generate spatial data on tiger records around human settlements, and explore the connection between settlement-specific economic well-being, forest visitation and tiger encounters. We hypothesize that conflict risk is driven by the frequency with which people enter forested areas and the proximity of settlements to Bardiya National Park (H1). We also consider whether these factors are correlated with the economic status of each settlement and whether they are therefore driven by reliance on forest resources. This hypothesis would be supported by significantly distinct patterns of forest visitation based on the distance of settlements from the National Park and on their economic status. Alternatively, we hypothesize that conflict risk is primarily caused by tigers entering human settlements, regardless of the proximity of settlements to the National Park or reliance upon forest resources (H2). If this was the case, we would expect to find no significant differences in tiger records across settlement types and a greater probability of records near settlement boundaries than at the forest edge.
Fig. 2 The Khata Corridor connecting Bardiya National Park in Nepal and Katarniaghat Wildlife Sanctuary in India, and the locations of the four settlements selected for household surveys.
Methods
We conducted this work in Thakurbaba Municipality Ward 9 (Thakurdwara settlement) and Ward 3 (Neulapur settlement) and Madhuwan Municipality Ward 1 (Dalla and Pattharbhuji settlements) during December 2021 (Table 1). We selected these settlements on the basis of evident but unquantified differences in economic benefit received from tiger tourism (e.g. number of hotels, shops and homestays) and the unequal distribution of government subsidies correlated with distance from Bardiya National Park (Table 1).
Table 1 The four settlements (Fig. 1), with the number of households in each, the number of households surveyed, economic benefits received from tiger tourism, distance from Bardiya National Park, Nepal (Fig. 2), and enforcement of provisions on forest use, ordered by distance from the Park. Economic benefit is categorized based on the number of tourism-related businesses, including hotels, homestays, shops and other small-scale enterprises in each settlement, and designated as low (< 5 businesses), moderate (5–20) or high (> 20). We measured distance of each settlement from Bardiya National Park headquarters to the midpoint of the respective settlement. Enforcement of provisions on forest use indicates the extent to which laws and regulations are implemented to control and manage the use of forest resources near to the settlement, as observed by surveyors during field visits and whilst interacting with respondents. High enforcement refers to regular patrolling and well-maintained fences, moderate enforcement reflects no patrolling but some maintenance of fences, and low enforcement indicates no patrolling and no maintenance of fences.
The four settlements had a total of 1,720 households, from which we selected 177 (c. 10% of households in each settlement; Table 1), using systematic random sampling, for in-person surveys (i.e. we conducted a survey in every 9th or 10th house). Household surveys consisted of semi-structured questionnaires presented to any family member of > 18 years of age in each house. If the selected house was empty, we selected the next proximate house. The survey team comprised two individuals, including author BS, both of whom were external to the study area and early-career graduate students in the field of natural resource management. They had not previously conducted research focusing on tigers. We collected information on the demography and socio-economic condition of respondents, including age, gender, monthly family income, number of livestock owned, and frequency, purpose and duration of forest visitation (Supplementary Material 1). We also asked respondents to provide anecdotal information on their past experiences with tigers, including when and where they had seen a tiger within the last 5 years and whether they, their family members, their livestock or their neighbour or neighbour's livestock had experienced a negative interaction (attack or direct threat) with a tiger in the previous 5 years. We also asked them about the time (morning: 04.00–11.00; day: 11.00–16.00; evening: 16.00–21.00; night: 21.00–04.00) and season (winter: December–February; spring: March–May; summer: June–August; autumn: September–November) in which they usually visit the forest and experience interactions with tigers. We chose the most recent 5 years because the tiger population increased markedly during this time, there was minimal chance of significant land-use change and habitat alteration within the span of 5 years, and people are probably able to remember details of any encounters with tigers within this timeframe. For confirmation that respondents could distinguish a tiger from the Indian leopard Panthera pardus fusca (a congeneric species of large felid commonly found in the region and sometimes confused with tigers) we showed respondents images of both and asked them to identify them.
In addition to the household surveys we recorded the positions of tiger records using a GPS. We only collated records within the boundaries of human settlements, to assess the use of anthropogenic habitats by tigers. Records near households were identified by respondents after the household survey. For records far from households we used a map to allow respondents to identify these locations. Records of tigers within forests were all considered to be in tiger habitat. Within settlements we documented habitat type for each record (agricultural land, human habitation, water feature, grazing land and forest edge; the latter being a transition zone characterized by substantial husbandry).
Data analysis
For H1, we assessed the relative intensity of forest use with respect to multiple human demographic variables, using multinomial logistic regression. The dependent categorical variable was frequency of forest visitations, and the independent categorical variables were human settlement types, gender of respondent, age, monthly family income and livestock herd size owned by each household (Supplementary Table 1, Supplementary Material 2).
For H2, to assess the factors underlying the risk of a person encountering a tiger, we examined which independent variables were significantly associated with tiger records, using binary logistic regression. The dependent variable consisted of binary data in which we coded all 33 recorded tiger records as 1 and an equal number of pseudo-absences as 0. We generated pseudo-absence points using the create random points feature in ArcGIS 10.8 (Esri, 2022), distributing them equally amongst the three settlement wards (i.e. 11 in each ward; Barbet-Massin et al., Reference Barbet-Massin, Jiguet, Albert and Thuiller2012). We validated these by confirming that none of them overlapped with the presence data, and that all were within the same human settlement boundaries as the tiger records. Independent variables were human settlement as a categorical variable (to which settlement each presence and each random pseudo-absence was most proximate) and the nearest distance of each presence and pseudo-absence to the forest edge, water feature, grazing land, household and road (Supplementary Table 1). Given the strong positive correlations between nearest distance to the forest edge, grazing land and water feature (r > 0.5) and between nearest distance to the household and road (r > 0.4; Supplementary Fig. 1), we selected nearest distances to forest and household for the analysis.
For both the multinomial and binary logistic regression we first built a single-effect model for each predictor variable, in R 4.2.0 (R Core Team, 2023) using the glm() (binary) and multinom() (multinomial) functions in the nnet package (Ripley & Venables, Reference Ripley and Venables2023). We compared all single-effect models based on the Akaike information criterion corrected for small samples sizes (AICc) and identified the most influential variable based on the lowest AICc value (variable human settlement types in the multinomial logistic regression and nearest distance to forest edge in the binary logistic regression; Supplementary Table 2). Subsequently, we developed additional models by combining these influential variables with other predictor variables. In addition, we constructed models that included either no predictor variables (null model) or all variables. After developing candidate models we considered the models with ΔAICc values ≤ 2 as the best competing models. We chose the model with the lowest AICc value but highest Akaike weight as the best explanatory model. We also performed χ 2 goodness-of-fit tests to assess whether responses to survey questions were statistically different considering in which season and at which time respondents visited forests, sighted a tiger or witnessed a tiger attack or the killing of either a person or livestock.
Results
Forest visitation by people
Frequency of forest visitation varied, but all respondents indicated they visit the forest at least occasionally. Some respondents visited the forest only once per year (37%), followed by weekly (25%) and monthly (22%), with daily visits uncommon (16%). The frequency of forest visitation correlated strongly with economic benefit from tourism, with the majority of respondents from Pattharbhuji (low benefit) visiting the forest daily, whereas respondents from Thakurdwara (high benefit) visited forests only annually, and respondents from Dalla and Neulapur (moderate benefit) reported a medium frequency of visits (Fig. 3). Based on the AICc values in the multinomial regression, no single variable best explained forest visitation. The best-fitting model for explaining the frequency of forest visitations included settlement type, age, gender and livestock herd size (Supplementary Table 2). A model including settlement type, age and livestock herd size was also well supported but was less parsimonious based on its slightly higher AICc and lower Akaike weight values than the best-fit model. The best-fit model indicated that frequency of forest visits (using yearly visits as the baseline for comparison with more frequent visit categories) was significantly dependent on settlement economic category (greater frequency of visits with lower economic category). For example, numbers of people from Pattharbhuji visiting the forest on a daily, weekly and monthly basis were 1,042, 27 and nine times higher, respectively, than yearly compared with people from Thakurdwara (Supplementary Table 3). We observed a similar pattern for the Dalla and Neulapur settlements in comparison to Thakurdwara. However, other variables in the best-fit model did not provide a clear explanation for the pattern of forest visitation. For instance, number of livestock did not influence daily or weekly forest visitation patterns, but it affected visitation frequency when comparing monthly with yearly visitation. We observed similar irregular patterns in the age and gender categories.
Fig. 3 Percent of respondents visiting the forest for resource collection daily, weekly, monthly and yearly in four settlements in the Khata Corridor in Nepal (Fig. 1), with the degree of economic benefit from tourism (Table 1) indicated in parentheses. (Readers of the printed journal are referred to the online article for a colour version of this figure.)
In terms of seasonality and time of day, forest visitation was significantly highest in the winter and during the daytime, respectively (Supplementary Figs 2, 3). The primary reasons for forest visitations included grass harvesting for thatch and hut construction (khar khadai in Nepali), collecting lianas (lahara in Nepali) and fruits (especially plums, bayer, in Nepali) and for grazing livestock. Duration of visits was 3–7 h.
Tiger records in settlements
A total of 33 tiger records were documented within the boundaries of settlements and georeferenced during field visits. These included 24 sightings, six locations of tiger attacks and three observations of pugmarks. Respondents in only 24 of 177 households had seen a tiger within a settlement's boundary, and no household reported more than one sighting. These sightings occurred across all seasons and at various times of the day (Supplementary Figs 2, 3). Tigers were most commonly seen in winter and in the evening, although there were no significant differences amongst seasons or times of day. Thirty-seven of 177 respondents had experienced negative tiger interactions: the six attacks within the settlements and 31 additional interactions in the forest. Tiger attacks did not differ between seasons but were significantly higher during day and night than in the early morning or evening (Supplementary Fig. 3). The attacks in the forest occurred whilst people grazed livestock or collected forest products, and included attacks on both people and livestock. The six attacks within a settlement were on livestock, in sheds in Pattharbhuji. In all of these cases, the livestock sheds were open and within 10–30 m of the forest edge.
Of the 33 tiger records within settlements, 36% were within 100 m of a river or stream bank. The next most frequent location was in open grassland (21%), followed by proximal to roads (18%). There were few records of tigers at the forest edge (9%) or in areas of human habitation (15%). Tiger records were a mean of 50.5 ± SD 39.1 m from the nearest forest edge and 414.7 ± SD 423.7 m from the nearest household (Fig. 4), indicating that tigers mostly limit their movements to within forests and rarely enter settlements. Mean distances from grazing land (280.9 ± SD 250.4 m), water features (279.3 ± SD 262.1 m) and roads (236.5 ± SD 296.2 m) were intermediate and comparable (Fig. 4). The binary logistic regression model that included settlement type and distance to the nearest forest was the most strongly supported based on its low AICc value (Supplementary Table 2). A similar model but with the addition of distance to nearest household had a ΔAICc of 2.28 but included a higher number of variables. Compared with Thakurdwara (high economic benefit), records of tigers were significantly higher in both Pattharbhuji (low economic benefit) and Dalla (medium economic benefit). Records of tigers in Pattharbhuji and Dalla were 119 and 18 times higher than in Thakurdwara, respectively (Supplementary Table 4). With respect to distance to the nearest forest, there was a 1% decrease in tiger records with every 100 m. Similarly, probability of tiger records increased with proximity to grazing land and water features but decreased with proximity to households and roads (Fig. 5).
Fig. 4 Variation in distances of the 33 tiger records (sightings, pugmarks and attacks) within the three settlements from forest, grazing land, households, roads and water features in the Khata Corridor. The y-axis shows the distance from each record to the nearest landscape feature. The horizontal spread of the data points facilitates visualization of the density and distribution of the distances, with wider sections indicating distances at which tiger records are concentrated. (Readers of the printed journal are referred to the online article for a colour version of this figure.)
Fig. 5 Probability curves for recording a tiger with respect to the shortest distance from tiger record locations (consisting both presence and pseudo-absence points; N = 66) to forest, grazing land, households, roads and water features within human settlements in the Khata Corridor. The curves illustrate how proximity to these features influences the probability of encountering a tiger, accounting for both confirmed records and areas where tigers are likely absent. (Readers of the printed journal are referred to the online article for a colour version of this figure.)
Discussion
We aimed to investigate the dynamics of human–tiger conflict risk and provide insights for potential solutions to this ongoing problem in the Khata Corridor, to help maintain a robust tiger population and meet the needs of the poor and marginalized communities of this region. Although we acknowledge the possibility that the unique perspectives of each surveyor could have influenced their approach to data collection (Jafar, Reference Jafar2018), our findings highlight that (1) forest visitation by people differed across settlement types, and the frequency of forest visits was higher in settlements farther from Bardiya National Park, (2) tiger records within settlements varied across settlement types and were positively associated with proximity to forests and negatively associated with proximity to households, and (3) tiger attacks on livestock in settlements occurred more frequently in households near to the forest edge and with an open livestock shelter. Taken together, these findings support our primary hypothesis (H1) that human–tiger conflict risk in the Khata Corridor is driven by the dependency of people on forest resources to meet their needs, which is higher for those living farther from Bardiya National Park. In addition, we reject our secondary hypothesis (H2) that conflict risk is associated with tigers entering human habitation. These findings are probably shaped by a combination of factors, including an unequal distribution of benefits from tiger tourism and unequal access to forest resources, all of which are related to the geographical proximity of settlements to Bardiya National Park.
From an environmental justice perspective, effective mitigation of human–tiger conflict risk must ensure that human communities and tigers can coexist in a balanced and equitable manner. This perspective also emphasizes the need to ensure that marginalized communities are not disproportionately burdened by conflict risk and that they have equal access to environmental resources and benefits (McInturff et al., Reference McInturff, Cannon, Alagona and Pellow2021). When there are disparities in the distribution of environmental costs and benefits associated with human–tiger coexistence, coexistence inequalities can arise that further increase conflict risk (Jordan et al., Reference Jordan, Smith, Appleby, van Eeden and Webster2020). Our study suggests this is the case within the Khata Corridor. People in the settlement farthest from the National Park (Pattharbhuji) had the highest frequency of forest visitation, received lower economic benefits from tourism and faced a higher risk of conflicts with tigers than the settlement nearest to the National Park (Thakurdwara). Furthermore, people's forest use patterns were driven more by the economic category of their settlement than the monthly income of their family. This suggests there is an unequal distribution of both environmental benefits and costs, resulting in inequalities and divergent societal identities and norms amongst settlements because of differential access to the National Park and its resources.
Environmental justice issues resulting from the geographical location of settlements with respect to protected areas are widespread (Inskip & Zimmermann, Reference Inskip and Zimmermann2009). In general, economically disadvantaged and marginalized settlements tend to lose a significantly greater number of livestock to large carnivores compared to wealthier settlements, resulting in greater economic burdens and forest dependency and higher conflict risk coupled with lower ability to cope with conflict (Saberwal et al., Reference Saberwal, Gibbs, Chellam and Johnsingh1994; Agrawal & Redford, Reference Agrawal and Redford2009; Carter & Linnell, Reference Carter and Linnell2016). In Nepal, the establishment of protected areas has been successful in terms of increasing population densities of tigers, but conflict risk in these regions has consequently increased. Of even greater concern is that increased conflict risk is disproportionately experienced by settlements that exist within protected areas but beyond jurisdictional oversight, as is the case for the settlements in the Khata Corridor.
Settlements in closer proximity to the National Park experience both advantages and disadvantages (Budhathoki, Reference Budhathoki2004; Lamichhane et al., Reference Lamichhane, Persoon, Leirs, Poudel, Subedi and Pokheral2019). The National Park brings tourism opportunities but imposes restrictions on forest use (Adams & Hutton, Reference Adams and Hutton2007). In Bardiya and other national parks in Nepal, participation by local people in community-based tourism has been praised as a beneficial offset to restrictions on forest use (Stræde & Helles, Reference Stræde and Helles2000; Dhungana et al., Reference Dhungana, Savini, Karki and Bumrungsri2016; Bhattarai et al., Reference Bhattarai, Wright, Poudel, Aryal, Yadav and Wagle2017; Ghimire, Reference Ghimire2022; Woli, Reference Woli2022). The village of Thakurdwara highlights these dynamics. It lies close to the National Park, and residents of this village are strictly prohibited from using National Park resources, enforced through regular patrolling and well-maintained fencing, except for during a single visit to forests each year (during winter) for 3 days. These restrictions are adhered to given that the people of Thakurdwara have diverse opportunities to generate income through tourism, reducing their dependency on forest resources and subsequently increasing their support for the conservation of national forests. However, other settlements do not experience the same level of benefit. Neulapur is within the buffer zone, an area designated as a transitional space surrounding a protected area to promote natural resource conservation through local participation, and as such receives some government subsidies but does not receive benefits from tourism and has only moderate law enforcement (no patrolling but some maintenance of fences), together leading to a greater need for and utilization of forest resources. Dalla is bordered by both buffer zone forest and national forest, and has successful homestay operations for tourists, and consequently, despite only moderate law enforcement of forest restrictions, forest visitation is relatively low. Pattharbhuji, farthest from the National Park, does not receive many economic benefits from tourism and has little enforcement of restrictions on forest use (no patrolling and no maintenance of fences), together leading to daily reliance on restricted forest resources. The daily use of forest resources in Pattharbhuji could be attributed to several factors. It is possible that the community forest, an area of a national forest for the community to use, manage and conserve, is of inadequate size to meet community needs or that a lack of law enforcement facilitates the use of restricted forest areas even if the assigned community forest is large enough to meet local needs. Alternatively, it is possible that high conflict with tigers in this settlement and perceived risk of attack have resulted in residents degrading forest habitats to drive tigers from the region. However, there is little support for this latter hypothesis. Despite Pattharbhuji having a high incidence of tiger records, being the most isolated and forest-bound settlement and experiencing more tiger attacks on livestock than the other settlements, there is general community support for tiger conservation amongst its residents (Sharma & Neupane, Reference Sharma and Neupane2023). Therefore, enforcement of restrictions on forest access and use alone probably cannot mitigate conflict risk if there is a lack of economic opportunity to overcome the reliance on forests (Colchester et al., Reference Colchester, Boscolo, Contreras-Hermosilla, Gatto, Dempsey and Lescuyer2006). Within an environmental justice framework it is evident that uniform solutions to complex issues can result in unfair outcomes for communities that are already bearing costs. These communities are highly dependent on the forest for their livelihoods, relying on its resources for sustenance, shelter and income generation. Even with the application of strict enforcement measures it is likely that people from such communities would still visit the forest to fulfil their livelihood needs. A more inclusive approach is needed to reduce forest visitation and conflict risk (Carter & Linnell, Reference Carter and Linnell2016).
Designation of the Khata Corridor as a governmental protected region has mostly been successful in terms of biodiversity conservation (Wegge et al., Reference Wegge, Yadav and Lamichhane2018). However, unequal access to benefits associated with the National Park is ultimately related to forest dependency and increased conflict risk. Providing opportunities that align with the principles of environmental justice amongst settlements is likely to minimize conflict risk (Boillat et al., Reference Boillat, Gerber, Oberlack, Zaehringer, Ifejika Speranza and Rist2018). It is important to ensure that all communities, regardless of their geographical location or socio-economic status, have equal opportunities to benefit from conservation and experience reduced risk. Such benefits could be economic aid from tourism, community-focused infrastructure development such as road access to markets, medical facilities such as health posts, and schools and livelihood improvement initiatives (Bookbinder et al., Reference Bookbinder, Dinerstein, Rijal, Cauley and Rajouria1998; Coria & Calfucura, Reference Coria and Calfucura2012; Das & Chatterjee, Reference Das and Chatterjee2015; Stronza et al., Reference Stronza, Hunt and Fitzgerald2019). This approach would provide communities with infrastructure support and knowledge to prevent and respond to conflict risk or tiger attacks. Furthermore, integrating the entire Khata Corridor into the buffer zone of Bardiya National Park would align with the principles of environmental justice (Bhatt et al., Reference Bhatt, Castley, Sims-Castley, Baral and Chauvenet2023). Extending the responsibilities of the National Park through the Khata Corridor and up to the international border would facilitate transboundary wildlife movement and ensure that all communities, regardless of location, receive equal environmental benefits and have similar costs. An immediate short-term solution to mitigate conflict risk could involve implementing community-focused education programmes to increase local knowledge of human–tiger interactions, emphasizing that tigers are highly unlikely to enter human habitations except for those that are close to the forest boundary. Instead of relying solely on physical barriers such as fences to prevent tigers from entering settlements and people from entering forests, a common conflict mitigation action in tiger-inhabited areas, it could be more effective in the Khata Corridor to focus on raising awareness of tiger behaviour and knowledge of the relative risks associated with community activities.
This local study, conducted with limited financial resources, demonstrates the value of such research in providing potentially valuable insights into spatial use by tigers in human settlements. As most conflicts between tigers and people arise from direct encounters during periods of overlapping activity, reducing this overlap would enhance coexistence. Our incorporation of residents' knowledge was effective in improving knowledge of risks associated with tigers. However, use of camera trapping and/or tracking of tiger movements would further improve this knowledge. As a first step, we recommend that the appropriate authorities initiate the recording of georeferenced and time-stamped records of tigers within settlements, potentially involving citizen participation. Although access to such data should be monitored, to prevent misuse, they could be invaluable for modelling spatial use by tigers, particularly in landscapes where both human and tiger populations are increasing rapidly. This approach aligns with the need for targeted, cost-effective strategies to mitigate conflict and promote coexistence between people and tigers.
Author contribution
Study design: BS, DN; fieldwork: BS; data analysis: BS, AGH; writing: all authors.
Acknowledgements
We thank Nepal Open University for providing BS with an opportunity to complete a master's degree in Natural Resources and Development; the Resources Himalaya Foundation, Lalitpur, Nepal, for providing a dissertation grant (grant number: 01-RHF-2078); and Gokarna Dhakal for assistance in the field.
Conflicts of interest
None.
Ethical standards
This research abided by the Oryx guidelines on ethical standards. The fieldwork was permitted through the Department of National Parks and Wildlife Conservation (permit number: 078/79-109), the governing authority for wildlife research and conservation in Nepal. The household survey was initiated only after obtaining the verbal consent of the respondents to participate in the survey. All participants were approached respectfully, and their personal information, including names and household locations, was treated with confidentiality. Our analysis used only general demographic and socio-economic information.
Data availability
The dataset used for the analysis is available in the Supplementary Materials. The georeferenced locations of tiger records have been omitted from the dataset to prevent any potential misuse of this information but are available upon reasonable request to the corresponding author (BS).
Open access
