Assessing the Economic and Ecological Costs of Human–Wildlife Conflict in Nuwara Eliya

Abstract

Human–wildlife conflict (HWC) is a growing concern in the Nuwara Eliya Divisional Secretariat Division (DSD) in the central highlands of Sri Lanka. This study investigates the nature and distribution of HWC, with particular focus on agricultural damage, livestock losses, infrastructure destruction, and human injuries. Data were collected through field surveys, expert opinions, satellite imagery, and census data, including interviews with 720 farmers (conducted between 2021 and 2022) and 25 online questionnaires, which provided expert insights on HWC. Animals such as wild boars, bandicoots, barking deer, toque macaques, porcupines, buffaloes, sambar, and leopards were found to be key to HWC, contributing to crop raiding, livestock predation, and infrastructure damage, and through the analytical hierarchy process (AHP), the wild boar was determined to have the greatest impact. Spatial analysis revealed conflict hotspots near forest and tea plantation boundaries, emphasizing the influence of land use and proximity to wildlife habitats. Mitigation strategies were explored; most farmers utilize multiple conflict reduction strategies, with varying efficacy. These findings underline the importance of developing region-specific strategies for HWC management, promoting sustainable agricultural practices, and fostering coexistence between wildlife and local communities.

1. Introduction

Human–wildlife conflict (HWC) is an ongoing problem resulting from disparity between the needs of wildlife and humanity, with negative effects on both parties. Many communities rely on natural resources, leading to conflicts with nearby wildlife. The destruction of wildlife habitats due to human activities has affected food security and the well-being of local people [1,2], and the growing human population, with its increasing demand for food and space, now encroaches on many species’ natural habitats [3]. Coexisting with wildlife becomes particularly complex when human lives and livelihoods are at risk; historical evidence indicates that HWC can lead to the local or, in extreme cases, complete extinction of some species. The effects of HWC extend beyond its immediate impacts on communities and wildlife, creating social and developmental issues alongside conservation concerns. The acceleration of climate change and habitat depletion due to deforestation amplify HWC’s adverse effects on human populations and wildlife, and many of the existing solutions are insufficient to address such issues. To foster harmonious coexistence between humans and wildlife, stakeholders must work together to effectively resolve HWC by demonstrating that the benefits of cohabiting with wildlife outweigh the associated costs [4]. HWC is a widespread issue which may create local, regional, and national challenges; however, it is particularly pronounced in tropical and developing countries, where agriculture and livestock are essential to rural communities. The competition for natural resources between wild animals and local communities significantly affects agricultural production and household income, especially for indigenous communities and agro-pastoralists [5]. HWC occurs worldwide; for example, in Kenya, wildlife faces numerous threats, including poaching, habitat loss, and competition with livestock. The most prevalent form of HWC in this region is crop raiding, with elephants (Loxodonta africana) and primates being the most common culprits [6,7]. In Brazil, HWC has increased and diversified significantly over the past decade, with notable conflicts including jaguars (Panthera onca) preying on livestock; confrontations between sea lions and fishermen; road accidents involving capybaras (Hydrochoerus hydrochaeris); pumas (Puma concolor) intruding in urban areas; and the spread of exotic species like wild boar [8]. In Colombia’s northern Andes, HWC is escalating in the cloud forests due to rapid agricultural expansion-related deforestation, with livestock predation and crop raiding becoming increasingly prevalent [9]. In Japan, conflicts have arisen between humans and Japanese macaques (Macaca fuscata) due to recent unprecedented population growth and environmental changes, which have led the macaque population to encroach on areas of human habitation [10]. In India, elephants (Elephas maximus) raid crops, causing tension with local farmers [11]; similarly, in Nepal, crop raiding by rhesus macaques (Macaca mulatta) and conflicts with elephants (Elephas maximus), among other interactions, are common [12]. HWC is widely studied around the world, with particular focus on its socioeconomic impacts and spatial–temporal dynamics [13,14,15,16,17,18]; ongoing research aims to reduce such conflicts and their effects on local communities.

In Sri Lanka, the species most commonly involved in HWC are elephants (Elephas maximus), leopards (Panthera pardus), monkeys (Macaca sinica/Semnopithicus prima/Semnopithicus vetulus), crocodiles (Crocodylus palustris/Crocodylus porosus) [19,20,21,22,23,24], peafowl (Pavo cristatus), wild boar (Sus scrofa), porcupines (Hystrix indica), and fruit bats (Pteropus medius) [25,26].

Detailed research on this topic is still lacking, and the wider socioeconomic effects of these conflicts on local communities, livelihoods, and overall well-being have yet to be fully elucidated. Most existing studies focus on conflicts with elephants in the dry zone, while other human–wildlife interactions remain understudied. Therefore, this manuscript will focus on HWC in the Nuwara Eliya Divisional Secretariat Division (DSD) in the mountain wet zone and will address the existing knowledge gaps in this area, with the aim of improving capacity-building efforts and suggesting strategies for ameliorating HWC at the community level.

2. Materials and Methods

2.1. Study Area

This study focuses on the Nuwara Eliya DSD in the central highlands of Sri Lanka, which is located in the country’s middle plateau, with coordinates ranging from latitude 7°02′ N to 6°46′ N and longitude 80°34′ E to 80°52′ E and an altitude that varies between 900 and 2523 m above sea level. The central highlands of Sri Lanka are global biodiversity hotspots. The Nuwara Eliya DSD is divided into 72 Grama Niladhari divisions (GNDs) and covers 478 km². It is under the administrative control of the Nuwara Eliya district (Figure 1).

2.2. Data Collection

This study employed a mixed-methods approach, incorporating both primary and secondary data to ensure comprehensive coverage. A pilot survey was conducted in selected GNDs within the study area to enhance the reliability and accuracy of the data, and the feedback this survey provided was essential for refining the final questionnaire, amending errors, and enhancing the overall survey process. Adjustments were made to scheduled interviews, sampling techniques, geographic data collection, and the structured approach needed to address the complex nature of HWC in the region.

Following the pilot survey, a comprehensive questionnaire survey was carried out in agricultural areas using random sampling techniques. The survey focused on key aspects of HWC, such as crop damage, livestock loss, and safety concerns, while assessing the mitigation measures employed to reduce HWC. A total of 720 farmers from 72 GNDs were surveyed between 2021 and 2022. This included farmers from large-, medium-, and small-scale agricultural operations. The geographic coordinates of the survey locations were recorded using the Global Positioning System (GPS) to ensure spatial accuracy and analysis.

To supplement the primary data collection, two online surveys were conducted to gather expert opinions on HWC. The first survey was completed by 25 experts, a mixed cohort of wildlife professionals, agricultural experts, plantation managers, researchers, and administrators who provided insights into the relevant criteria and aspects of HWC. In the second survey, 25 experts identified the animal species involved in HWC within the Nuwara Eliya DSD. Both surveys utilized the Analytic Hierarchy Process (AHP), a structured decision-making tool for analyzing complex issues. These findings were supplemented by unstructured formal interviews with government representatives, including wildlife, forest, and agricultural officers, and three informal group interviews involving 20 participants who had experienced HWC for an extended period. These interviews provided valuable qualitative insights into the local context and challenges of HWC.

Secondary data were sourced from multiple authoritative databases. Census data were obtained from the Department of Census, while land use data were derived from Google Earth Pro imagery captured in 2022. Additional spatial data were collected from the Department of Survey and the United States Geological Survey (USGS) Landsat imageries. The diverse range of data sources provided a robust foundation for spatial analysis and contributed to a holistic understanding of HWC in the region.

2.3. Satellite Image and Field Data Collection

The Nuwara Eliya DSD exhibits complex land use patterns. Google Earth Pro satellite images were downloaded, processed, and georeferenced to digitize the land use map. Using ArcGIS Pro 3.1.3, land use was digitized with an accuracy of 3–5 m. GPS sampling was implemented to validate the created maps.

2.4. Data Analysis

A Google Earth Pro image (2022) was used to digitize polygons representing different areas. These Keyhole Markup Language (KML) polygons were then converted into a shapefile (shp) using ArcMap. Various ArcGIS Pro tools were applied to extract and mosaic these areas. The land use shapefiles were converted to the raster format and used for raster overlay. The scheme classification was developed based on ancillary information from field surveys conducted in 2021 and 2022 (

Table 1. LULC class.

Class	Description
Road	National roads (category A and B, estate roads, and other minor roads)
Tea	Tea plantation
Abandoned Land	Abandoned tea and agricultural lands
Animal Husbandry	Animal Husbandry farms
Park and Golf Club	Botanical gardens, parks, walkways, and golf courses
Agriculture	Lands used for cultivation
Water	Lakes, ponds, rivers, and streams
Built-up area	Residential areas, industrial areas, sports complexes, etc.
Forest	National parks, conservation forests, strict nature reserves, and other forest areas

), and involved visual image interpretation and local knowledge of the study area. Nine distinct land cover types were identified. Digital maps were created, and primary data were used to identify conflict-affected areas, assess the damage, and classify it accordingly. Hotspot and cold spot analyses of GPS location data were used to identify spatial patterns of HWC in terrestrial spaces. The spatial distribution of these hotspots and cold spots was analyzed using the Inverse Distance Weighted (IDW) interpolation method and natural breaks classification. This highlighted the spatial patterns of HWC hotspots and cold spots within the Nuwara Eliya DSD. To examine the relationship between crop damage, livestock loss, infrastructure damage, animal attacks on humans, and the extent of tea plantation and forest coverage, the IDW interpolation method with natural breaks classification was used.

2.5. Land Use Classification of the Area

Table 2. The extent of land use categories after classification.

No.	Name of the Land Use Type	Area (km2)	Percentage (%)
1	Road	5.17	1.0%
2	Tea	197.03	40.0%
3	Abandoned land	3.28	0.7%
4	Animal Husbandry	8.01	1.6%
5	Park and Golf Club	0.73	0.1%
6	Agriculture	29.92	6.1%
7	Water	3.33	0.7%
8	Built-up area	18.48	3.7%
9	Forest	226.92	46.0%

Source: data generated based on the analysis presented in Figure 2.

provides a comprehensive summary of the land cover classification results, while Figure 2 acts as a visual representation of the LULC data. Forest areas dominate the study region, accounting for 46% of the total land cover. Tea plantations occupy 40% of the area, followed by agricultural land, which comprises 6.1%. Most agricultural land is located adjacent to forest or tea plantations.

Multi-Criteria Decision Analysis (MCDA) is a structured decision-support process that can facilitate dialog between groups with differing interests and incorporates both human and environmental conflict. It can be used to simplify complex problems with multiple objectives. The study utilized MCDA and the AHP to evaluate HWC. MCDA supports transparent decision-making and can be used to effectively address the challenges associated with conflict management. However, the methodological choices and limitations must be considered before this approach can be applied in conflict situations [27]. In this study, MCDA employed AHP weights to identify instances of HWC. The identification and prioritization of animals were based on a farmer survey and expert consultations collected with the AHP, as is standard practice [27,28,29].

2.6. Developing a Pairwise Comparison Matrix and Calculating the Weight Using the AHP

Pairwise comparison is commonly used to establish trade-off relationships between criteria and factors [30]. The AHP expresses the comparative importance of the criteria through pairwise comparison and assigns priority values based on these comparisons. In our study, the fundamental AHP scale proposed by Thomas L. Saaty (1980) (

Table 3. Fundamental AHP scale (Thomas L. Saaty, 1980).

Intensity of Importance	Definition	Explanation
1	Equal importance	Two activities contribute equally to the objective
3	One is moderately more important than the other	Experience and judgment strongly favor one activity
5	Strong importance	Experience and judgment strongly favor one activity
7	Very strong importance	An activity is strongly favored, and its dominance is demonstrated in practice
9	Extreme importance	The evidence favoring a particular activity is of the highest possible order of affirmation

) was employed to collect pairwise comparisons from selected experts through an online survey, using a relative preference scale ranging from 1 to 9. Weighted values were calculated, and the reciprocal condition was satisfied when the number of alternatives was (−1)/2 [31]. Users compared factors by answering questions about their relative strengths. This information was used to create a direct-relation matrix (A) in the form of an n × n matrix, where each element (aij) represents the degree to which the I th criterion affects the jth criterion [31,32]. The animals involved in HWC and the factors influencing these conflicts were identified and used for pairwise comparison analysis.

Weight overlay analysis was conducted using the priority weights assigned by field experts, and layers were classified according to the priority weights of the AHP on HWC in

Table 4. Priority weights obtained for HWC using AHP.

Category	Priority Weight	Rank
(WB) Wild boar	26%	1
(BA) Bandicoot	20%	2
(BD) Barking deer	17%	3
(MA) Toque macaque	16%	4
(PO) Indian crested porcupine	13%	5
(BU) Buffalo	9%	6
(SA) Sambar	7%	7
(LE) Sri Lankan leopard	7%	7

. The priority weights were calculated as follows:

The HWC density (D) can be defined as follows:

$$d=\sum _{i=1}^{i=7}{w}_i{x}_i$$

• d = composite density score
• x_i = conflict animal score (cells)
• w_i = weight assigned by each animal

The factors contributing to HWC in the study area were identified through an extensive review of the relevant literature and collected baseline information. Building upon the critical drives, pressures, and impacts described by Eva M. Gross in 2021, potential influencing factors contributing to HWC in the Nuwara Eliya DSD were identified, validated, and refined through an online survey completed by experts in the field.

3. Results

3.1. HWC in the Study Area

Figure 3 depicts the frequency of different types of damage caused by HWC. Crop damage was the most prevalent, followed by livestock damage. Infrastructure damage and human attacks were also impactful; however, they were less frequent.

The wild boar was identified as the primary cause of crop damage, followed by the bandicoot, Indian crested porcupine (Hystrix indica), buffalo (Bubalus bubalis), sambar deer (Rusa unicolor), toque macaque, barking deer (Muntiacus muntjak), black-naped hare (Lepus nigricollis), and Sri Lankan junglefowl (Gallus lafayettii) (Figure 4). The Sri Lankan leopard (Panthera pardus kotiya) and the jackal (Canis aureus naria) were responsible for livestock predation in the area; however, in some instances, the specific predator could not be determined. Damage to livestock and human injuries have been recorded, particularly in the tea estate and margins of the agricultural land. The species involved in attacks on humans include the toque macaque, wild boar, Sri Lankan leopard, buffalo, and giant honeybee (Apis dorsata). Wild animals damaged infrastructure across the study area, with the toque macaque and buffalo causing most of the damage (

Table 5. Infrastructure damage and the involved animals.

Infrastructure Damage	Involved Animal
Damage to houses and home appliances and stealing food	Toque macaque
Damage to security cameras, electric bulbs, and others	Toque macaque
Damage to garbage bins	Toque macaque
Damage to vehicles	Toque macaque and buffalo
Damage to fences and gates	Toque macaque and buffalo

).

3.2. Distribution of the HWC

The spatial distribution of HWC incidents in the Nuwara Eliya DSD during 2021–2022 is shown in Figure 5. The map depicts widespread crop damage across the region, with fewer incidences in urban areas and large-scale farms. Livestock damage was concentrated near forest and tea plantation boundaries. Infrastructure damage and human attacks frequently occurred near forest edges and tea lands.

Figure 6 illustrates the spatial distribution of the four main types of damage caused by HWC in forest and tea plantation areas. The results presented in (a) show the spatial distribution of wildlife-induced crop damage, with hotspots where crop damage is most severe highlighted in red, while cooler spots with less significant damage are depicted in blue. Regions circled in yellow sustained minimal crop damage; these areas encompass the city limits and large-scale commercial farms where the impact of wildlife on crops is relatively low. Meanwhile, (b) represents the livestock damage resulting from HWC. The red circle pinpoints areas that suffer from significant livestock predation or attacks. In (c), red circles indicate locations where direct animal-on-human attacks have occurred (predominantly identified as tea estates), while (d) highlights the spatial distribution of infrastructure damage resulting from HWC in the study area.

3.3. Analytical Hierarchy Process for Overall HWC

Table 4 ranks animal species based on their impact on HWC, as determined by AHP analysis. The wild boar, with a priority weight of 26%, was the most significant contributor to HWC, followed by the Sri Lankan leopard and sambar deer, which shared 7% priority weight.

Figure 7 illustrates the spatial distribution of HWC risk within the study area, as determined by the AHP and MCDA. The map categorizes the risk level as low, moderate, or high, with red indicating the highest risk and green indicating the lowest. Most of the area is classified as moderate-risk, while small high-risk areas are identified in the northwest and southeast corners. Lower-risk areas are concentrated in the northeast and southwest quarters.

3.4. Factors Influencing HWC in Nuwara Eliya DSD

Based on the frequency and severity of HWC in the region, seven key contributing factors were identified: the distance to forests or plantations, encroachment and forest fragmentation, varying land use changes, the cultivation of palatable and high-yielding crops, infrastructure development, climate change, and the level of investment allocated for mitigation efforts. Each factor plays a critical role in shaping the intensity and distribution of HWC within the study area.

3.5. Mitigation Methods Used to Minimize HWC in Nuwara Eliya DSD

The mitigation methods used in the study area are listed in Figure 8. The majority of the farmers, 30%, reported installing natural fencing, utilizing plants, shrubs, or trees to create barriers around farmland, while 23% of respondents stated that they use fencing methods involving barbed wire, walls, and mesh. Moreover, 14% of farmers practice guarding, actively monitoring and protecting their crops from animals. Less popular deterrents include electrical fencing (used by 3% of respondents), firecrackers (used by 9%), air rifles (4%), and poisoning (3%), as well as nets or barriers, such as the traditional “Saree Wata,” which consists of multiple colorful 1 × 6 m sections of recycled cloth; 3% of respondents reported using such barriers to cover their agricultural plots. Additionally, 5% of farmers use dried corn seeds to prevent bandicoot damage, as local people have observed that bandicoots do not return to farmland areas for several days after consuming dry corn seeds. Many farmers use multiple safeguarding methods, and their choice of mitigation technique often depends on the type of animal involved.

4. Discussion

Wild boar and bandicoots create significant conflict within the study area, as forest and tea land collectively covering 86% of the Nuwara Eliya DSD are their primary habitats. Tea land, as an evergreen plantation, provides a highly desirable habitat for various species [33,34]. Farmland is typically situated at the boundary between tea and forest lands. However, within tea plantations, fodder availability is limited due to weed control practices and pesticide usage. Conflict arises when wildlife, searching for easily accessible food, encroaches on farmland, threatening agricultural activities. Moreover, toque macaques, which are endemic and threatened in Sri Lanka, and leopards, which are also classified as threatened, are significant contributors to HWC. The IUCN (2023) highlights that some of the species causing conflict are also threatened on a global level. This situation underscores two critical issues: the conflict between wildlife and farmland and the adverse impacts on threatened species within the study area.

The nature of the environment is another significant factor that influences HWC, particularly in light of human encroachment and the fragmentation of natural habitats, which have intensified these conflicts. Leopards, for instance, are often attacked by domestic pets such as dogs. Similarly, livestock predation by species like the Sri Lankan leopard and jackal poses a serious concern. Additionally, crop damage by wildlife predominantly occurs at night, particularly in misty and cloudy weather, making it challenging for farmers to detect raiding animals. The region’s typically cloudy and rainy climate has exacerbated this issue. This study has identified various types and levels of crop damage caused by different wild animals, which are active at different times of day or night. This issue is commonly observed in areas where the natural habitat has been disrupted by human encroachment [9].

Various researchers have identified factors affecting HWC around the world. The land use type in the area significantly influences habitat suitability and its effect on HWC [35]. Our study highlights that understanding these factors is essential for developing effective management strategies to mitigate the impacts of these conflicts and promote coexistence between humans and wildlife. Addressing these factors is critical for designing targeted interventions that support harmonious human–wildlife interactions.

Khan et al. [36] revealed that local communities have adopted various management strategies; however, these conflict mitigation measures remain largely ineffective due to a lack of proper training and insufficient funding. Most farmers in the Nuwara Eliya DSD use natural plant-based fencing for land protection, while others employ barbed wire and walls. Others rely on human guards, firecrackers, air rifles, and electric fencing. Additionally, local methods such as colorful recycled cloth nets and dried corn seeds are used for pest control. Farmers often combine these techniques on a case-by-case basis, depending on the animal involved.

Some of the suggested mitigation measures from the study align with those identified by other scholars, who emphasized the importance of conservation awareness and education which, in turn, will help to minimize HWC. However, the study also highlighted key challenges, including a low income, which hinders the effective implementation of mitigation strategies.

5. Conclusions

In this study, we explored the complex dynamics of HWC in the Nuwara Eliya DSD and highlighted significant economic and social challenges within local communities, particularly with regard to agriculture, livestock, infrastructure, and human safety. Wild boars were identified as significant contributors to crop raiding, alongside other species like the toque macaque and buffalo. The most severe damage was observed in close proximity to forests and tea plantations, and was driven by factors such as land use changes and the cultivation of crops that attract wildlife. Using surveys, we identified the locations most affected by HWC, enabling more targeted interventions, and noted the various mitigation strategies farmers use to protect their land, including natural fencing and active guarding. However, the effectiveness of these methods varies depending on the species involved and area-specific conditions. Furthermore, the challenges faced by threatened species, such as the Sri Lankan leopard and toque macaque, highlight the importance of balancing ecosystem conservation with community needs. Promoting coexistence through habitat restoration, community awareness, and sustainable agricultural practices is essential. HWC requires a collaborative approach in which farmers, conservationists, and local authorities work together to safeguard wildlife and agricultural livelihoods. This study highlighted vulnerable areas and the most affected areas, and these findings will facilitate the development of policy-integrated, community-based solutions that combine traditional methods with innovative strategies, such as early warning systems, damage compensation schemes, and habitat restoration to mitigate human–wildlife interactions. Continued research on HWC in the Nuwara Eliya DSD is crucial, as the existing studies were conducted in the short-term. Long-term monitoring is needed to assess agricultural losses caused by wild animals. Key strategies include raising awareness about wildlife conservation, providing farmers with resources such as fencing and financial support, offering insurance to cover agricultural losses, enforcing strict penalties for poaching and hunting, establishing a monitoring program for crop damage reports, and conducting ongoing behavioral studies.