Patterns and correlates of human–elephant conflict around a south Indian reserve

Patterns and correlates of human–elephant conflict around a south Indian reserve

Biological Conservation 148 (2012) 88–95 Contents lists available at SciVerse ScienceDirect Biological Conservation journal homepage: www.elsevier.c...

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Biological Conservation 148 (2012) 88–95

Contents lists available at SciVerse ScienceDirect

Biological Conservation journal homepage: www.elsevier.com/locate/biocon

Patterns and correlates of human–elephant conflict around a south Indian reserve Sanjay Gubbi ⇑ Wildlife Conservation Society – India Program and Centre for Wildlife Studies, 1669, 31st Cross, 16th Main, Banashankari 2nd Stage, Bengalooru 560 070, India

a r t i c l e

i n f o

Article history: Received 5 September 2011 Received in revised form 18 January 2012 Accepted 23 January 2012 Available online 22 February 2012 Keywords: Human–elephant conflict Spatio-temporal patterns Crop loss Compensation Nagarahole National Park India

a b s t r a c t Success stories in Indian conservation also carry opportunity costs in the form of human–wildlife conflicts, especially to people living in close proximity with wildlife. In India, human–wildlife conflict is a serious challenge to wildlife conservation, which needs a much-improved scientific and social understanding. In this study, I assess the patterns and correlates of human–elephant conflicts around Nagarahole National Park, southern India. I hypothesised that human and livestock demographic variables, and factors such as cropping patterns, availability of irrigated land around the national park, and protected area frontage to be the underlying correlates of conflict. Using applications and documents filed with the wildlife department by affected farmers during the period 2006–2009, I analysed crops affected, compensation payments made by the Government, spatio-temporal patterns of conflict and identified the key correlates of human–elephant conflict. 98.8% of the conflict incidences occurred in villages that lie within 6 km from the national park boundary. Of the 26 crop types affected by elephants, finger millet, maize, cotton, paddy and sugarcane formed 86.34% of the total crop losses. Conflict frequencies were highest during August–November, a period when there was a decrease in rainfall and important crops such as finger millet, maize and paddy were ripening. Multiple linear regression results suggest that villages with higher protected area frontage and unirrigated land were key variables underlying conflict frequency. However, results from this study suggests that there are other probable factors such as elephant behaviour, movement patterns and/or maintenance of physical barriers which could be more important determinants of conflict. Ó 2012 Elsevier Ltd. All rights reserved.

1. Introduction India holds the largest population of wild Asian elephants (Elephas maximus) with nearly 27,000–29,000 animals found in the country (MOEF, 2010). In the early 1980s, due to the stringent protection offered by law-enforcement agencies, some of the protected areas (PAs) in southern India recovered from poaching and other threats, resulting in high densities of elephants (AERCC, 1998). These results are laudable considering India’s rapidly increasing human population. However, this conservation success story also has opportunity costs including economic losses in production landscapes and human fatalities for communities living in close proximity with conflict-prone wildlife species such as the elephant. Today, managing human–wildlife conflict is one of the greatest challenges for conservation agencies in India. Across the world, it is generally accepted that conflict erodes public support and builds animosity against wildlife conservation (Madhusudan, 2003; Naughton-Treves and Treves, 2005; Ogra and Badola, 2008). Further, debates on conflict are now increasingly becoming more ⇑ Address: Nature Conservation Foundation, 3076/5, IV Cross, Gokulam Park, Mysore 570 002, India. Tel.: +91 80 26932516. E-mail address: [email protected] 0006-3207/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.biocon.2012.01.046

public and political. Similarly, chronic conflict has a profound impact on wildlife and their habitat (Woodroffe et al., 2005a; Gubbi, 2010). It may affect wildlife at the species, population and individual levels through processes of extinction, range contraction, population suppression and behavioural changes (Woodroffe et al., 2005a). The elephant is one of the most conflict-prone wildlife species in India, causing large-scale damage to crops and human lives. Each year, nearly 400 people and 100 elephants are killed in conflict related instances in India, and nearly 500,000 families are affected by crop damage (MOEF, 2010). Several reasons including habitat fragmentation, degradation of habitat quality, loss of forest cover, laxity in management of physical barriers and other causes have been cited for the human–elephant conflict (HEC) in the country (Sukumar, 1990, 1991; Johnsingh and Joshua, 1994; Williams et al., 2001; Jeyasingh and Davidar, 2003; Gubbi, 2009; MOEF, 2010). One of the methods followed by several Governments to offset economic losses imposed by human–wildlife conflict is by providing monetary compensations to affected people. Nevertheless, this scheme has come under severe criticism as compensation payments are often too meagre, delayed and the procedures to avail of these compensations are time-consuming. Hence, compensation has had little or no effect in some parts of the world to reduce

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anti-wildlife sentiments (Madhusudan, 2003; Naughton-Treves et al., 2003; Bulte and Rondeau, 2005). In India, especially in the south, a better scientific assessment of HEC and compensation payments is required. There is little quantitative understanding on spatio-temporal patterns, intensity, extent of damage and determinants of HEC (Ogra, 2008; Gubbi, 2009; MOEF, 2010) that could help managers, although notable exceptions exist (Kumar et al., 2010; Bal et al., 2011; Varma et al., 2011). However such studies have been previously carried out in Africa (Naughton-Treves, 1998; Hoare, 1999; Sitati et al., 2003). Hence, in this study, I attempt to quantify HEC and attempt to identify the correlates of conflict around Nagarahole National Park (NNP), southern India. I hypothesised that demographic factors such as human and livestock density, agricultural cropping patterns and availability of irrigated land around NNP to be among the key factors underlying conflict. These variables were picked as key correlates of conflict based on literature review (Hoare, 1999; Madhusudan, 2004, 2005; Linkie et al., 2007; Maclennan et al., 2009; Dar et al., 2009; Bal et al., 2011), personal observations and claims in grey literature that recent increases in conflict were due to improved irrigation facilities around PAs (Kulkarni et al., 2007). I hope results of this study will help in conservation planning and management plan development.

2. Study area NNP is recognised among the prime habitats for Asian elephant, tiger (Panthera tigris), Asiatic wild dog (Cuon alpinus), leopard (Panthera pardus), gaur (Bos gaurus) and other large mammals. It is contiguous with Bandipur National Park, Mudumalai and Waynaad Wildlife Sanctuaries, and with reserved forests where wildlife do occur but receive a lesser degree of protection compared to PAs. This forms one of the largest blocks of elephant habitat in the country spread over an area of nearly 5000 km2. Karanth and Sunquist (1992) estimated elephant densities in the western region of NNP to be 1.9/km2. NNP mostly consists of dry and moist deciduous forests, teak (Tectona grandis) plantations and low-lying swampy grasslands locally called as ‘hadlus’ forming an ideal habitat for large herbivores. It receives an average rainfall ranging between 1000 and 1500 mm. It has high human population density (265 people/ km2) around the national park (DeFries et al., 2010). Anthropogenic forest fires, livestock grazing, illegal timber felling, wildlife poaching and human–wildlife conflict are some of the serious conservation problems in NNP (Karanth, 2002). The western part of NNP abuts coffee plantations, while Waynaad Wildlife Sanctuary lies on its the south–western flank. Along its northern and eastern boundary are reserved forests, and stretches of dryland, rainfed agriculture which is the key production system in this region. The reserved forests outside NNP also host elephant populations. The Kabini River and a large reservoir built across it forms the southern boundary of NNP, and Bandipur National Park lies on the southern bank of the reservoir. Raagi or Finger millet (Eleusine coracana) is the staple food crop of the people in the drier regions outside the national park. Cotton, sugar cane, maize and coffee are some of the important crops grown in the farmlands abutting NNP. Pigeon pea and horse gram are the main legumes grown as intercrops. The wildlife department has primarily employed physical barriers such as elephant proof trenches and electric fences as the key measures to reduce conflict. However, these barriers are effective only if they are maintained around the year. In addition, farmers around the PA use private electric fences and also guard crops at night as their main means of averting crop losses. When crop

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losses occur despite these measures, the farmers, in desperation, retaliate against crop raiding elephants using live electric wires and gunfire, which have claimed the lives of 33 elephants during the period January 2008–May 2009 (Gubbi, 2009).

3. Materials and methods I collected applications of compensation claims made by farmers from the state wildlife department for the period 2006–2009. Since the wildlife department offices are well spread around NNP and has a good road network, I assume that distance or accessibility not being constraints to submit conflict applications. Documents such as initial application, survey reports of wildlife officials, details of affected land, final compensation paid and other records were collected. From these documents, I tabulated information such as area of landholding, types and extent of crops lost to depredation, losses to property such as fence post, electric fencing, water pipes, damages to structures, wildlife species responsible for conflict, location of farmland and approximate distance of the farmland from NNP boundary. I also collated information about date of conflict, date of application submitted by the claimant, date of survey carried out by the wildlife officials, date of granting of compensation to assess the number of days taken to settle compensation claims and the final amount paid as compensation. Compensation claims were converted to US$ by taking the average value of currency conversion from Indian Rupees to US$ for that particular year. Some farmers grow multiple crops in their farmland leading to losses of different crops to various degrees during elephant crop raids. Hence I analysed damages based on the extent of loss to diverse crop types and tabulated them as primary, secondary, tertiary, quaternary and quinary crop losses based on the intensity of loss for each crop type. The wildlife species responsible for conflict was also gathered from the documents. I obtained monthly rainfall figures from the Government statistical department that monitors rain gauges in different parts of the state. Data from seven different rainfall monitoring stations around NNP were collected and the mean of the various stations were used for data analysis. I correlated the number of conflict incidences against monthly rainfall data using Pearsons two-tailed correlation. Demographic and other information about the affected villages such as human population, area of the villages, forest area within the villages (if any), area of irrigated and unirrigated farmlands were collected from the Rural Development and Panchayat Raj Department (RDPR, 2011). I also triangulated these data with other Government electronic databases (TORGCCI, 2001; NRSC, 2011). I obtained village level livestock data from the database of the Animal Husbandry Department (DAHDF, 2011). I computed the shortest path from the boundary of a given village to the nearest NNP boundary, and also computed ‘PA frontage’ as the length of village boundary abutting NNP (km). Both measures were computed using computer GIS software ArcView 3.2 (ESRI, CA).

3.1. Correlation between conflict incidences and other variables I used Pearson correlations to assess bivariate relationships between HEC incidences in the affected villages with: (i) livestock population; (ii) human population; (iii) area of affected villages (sq km); (iv) forest area, if any, in affected villages (ha); (v) area of unirrigated croplands (ha); (vi) area of irrigated croplands (ha); (vii) nearest distance of the village boundary to the PA boundary (km) and; (viii) PA frontage (km).

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Further, I evaluated the relative importance of all these variables simultaneously by entering them as independent variables into the model to explain variation in the response variable, i.e., HEC frequency in that village. Before running the multiple regression, I identified variables showing multicollinearity, i.e. having a tolerance value 60.1 (Tabachnick and Fidell, 2007). After dropping the variables that showed significant multicollinearity, stepwise multiple linear regression was carried out with the remaining variables to build the final model. Given the fine spatial scale of the study, I did not attempt to build spatial autocorrelation terms in the regression model. All statistical tests were conducted using SPSS v.17.0 (IBM Corporation, 2010). 4. Results During 2006–2009 the wildlife department paid compensation for a total of 1955 crop loss incidences (Table 1). Of the total claims, 99.9% of the incidences were attributed to elephants while on two incidences, elephants and gaur were implicated in crop losses. Hence elephants were considered as the primary species for conflict in this study area.

to housing, household items, water pipes, water sprinklers, water storage ponds and stored rice. A total of 26 crop types were damaged or consumed by elephants of which five crop types Finger millet (20.61%), maize (Zea mays, 20.51%), cotton (Gossypium spp., 19.43%), paddy (Oryza sativa, 14.17%) and sugarcane (Saccharum officinarum, 11.61%) formed 86.34% of the total crop losses (Fig. 1). 4.3. Temporal distribution of conflict The temporal distribution of conflict frequencies was uniform during all the 3 years with crop raiding incidences peaking during August and November and the temporal patterns of loss of five primary crop species that were most preferred by elephants had similar peak periods (Fig. 2). NNP received a mean of 1113 mm of rainfall during the study period with maximum rainfall recorded during the month of July and with very little or no rainfall during the months of December, January and February. Conflict incidences had negative correlation with rainfall, with conflict incidences increasing with decrease in rainfall (rp = .628, p = 0.029). 4.4. Spatial distribution of conflict

4.1. Compensation payments A total of US$52,026 was paid as compensation to damages by elephants around NNP during the study period (Table 1). The mean number of days to receive compensation from the day of conflict was 114.4 days (19–523, SD = 60.58) and an average of US$30.8 (4.55–170.73, SD = 17.93) was paid as compensation by the wildlife department. 4.1.1. Human deaths and injuries Elephants were responsible for all the 10 human deaths, and eight people were injured around NNP during 2006–2009 due to elephants. A total of US$ 35,788 was paid as compensation towards human deaths (mean = 3521.3) and US$ 2562 towards injuries by elephants (mean = 207.2). Other species that caused injuries to people were tiger (one incidence), gaur (one incidence) snakes (species unknown, three incidences) and bonnet macaque (Macaca radiata, one incidence) for which a total of US$ 1257 was paid as compensation. 4.2. Crop losses Farmers who suffered conflict held an average of 1.12 hectares of cropland (0.03–8.09 ha, SD = 0.65). Of the total claimants, 15.80% (n = 309) experienced loss of a secondary crop, 5.11% (n = 100) lost a tertiary crop, 2.40% (n = 47) lost a quaternary crop and 0.51% (n = 10) experienced a quinary crop loss. About 2.14% (n = 42) claimed losses on infrastructure such as electric fence, damages

A total of 79 villages spread over an area of 468.7 km2 were affected by HEC during the study period (Fig. 3). The mean distance of the affected villages to NNP boundary was 1.62 km (range 0– 9.81 km, SD = 2.36). Amongst these villages 98.8% of the conflict incidences occurred in villages that lie within 6 km from the NNP boundary. A total of 163 villages lie within 6 km from NNP boundary and 49.1% of these villages were affected by HEC. In the affected villages, 49.3% suffered 1–10 conflict incidences, with 36.7% suffering 11–50 incidences, 7.6% villages suffered 51– 100 incidences and 6.3% villages had P101 incidences of HEC. 4.5. Distance of farmland to NNP boundary I was able to analyse distance of farmland from NNP boundary for 650 applications (33.2% of the total applications filed). The mean distance of cropland from NNP boundary that suffered conflict was 1.47 km (Range 0.0–7.0 km, SD = 1.44). Farmland at a distance of 0–1.0 km from NNP boundary experienced 24.6% conflict incidences, farmland at 1.1–3.0 km experienced 32.3% conflict incidences, the highest conflict incidences (43.0%) were recorded at 3.1–5.0 km distance and the least conflict incidences (0.1%) were recorded in farmland 5.0 km and above. I correlated distance of the farmland to NNP boundary as surrogate to check if farmlands closer to PA boundary suffered heavier losses due to elephant conflict. It was found that croplands upto a distance of 5 km from NNP boundary did suffer heavier losses (rp = .204, p = <0.00, n = 575).

Table 1 Details of crop loss due to elephants around Nagarahole National Park during 2006–2009. Year 2006– 2007 2007– 2008 2008– 2009 Total a

Number of villages affected

Area of villages affected (km2)

Total compensation paid for crop and other damages (US$)

689

45

280.5

11,638

957

67

428.22

31,492

309

56

331.31

8896

1955

79a

468.67a

52,026

Number of conflict incidences

Some villages are repeated during different years.

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Fig. 1. Different types of crops lost to elephant conflict around Nagarahole National Park during 2006–2009 (n = 1955).

The relationship between conflict frequency with human and livestock populations, village area, irrigated area and unirrigated area was non-linear. However, conflict frequencies were correlated with forest area within the village, distance of village to NNP boundary and PA frontage. Correlation results are given in Table 2. In the preliminary regression where all the variables were simultaneously entered into the model, the collinearity statistics showed that village area had significant collinearity with other independent variables with a tolerance value 0.173. Hence the village area was dropped from the final model. It was found in the final model that PA frontage and unirrigated land area were the two predictor variables that significantly influenced the frequency of HEC (Table 3). Of these two variables, PA frontage contributed 52% and unirrigated land area contributed 26% of the variability in the HEC frequency.

The preferred assessment method of HEC is via third party enumerators (IUCN-AfESG, 1999). However the research on conflict is seldom comprehensive though there is an ability to get it. Until such data is available official statistics remain the most reliable source. Despite the limitation that the methodology used in this study is a ‘passive’ process, such large-scale, continuous datasets on conflict are currently available only through Government records. Though this dataset is not exhaustive, I have made a valid assumption that it is a good sample, or at least a representative sample of the more serious incidents and provides us enough confidence to give robust results. Bal et al. (2011) report a total of 806 conflict incidences for NNP during a 12 year period (1996–2008), however they also note that it could be an underestimate due to farmers not claiming compensation. Comparing our data with Bal et al., 2011 there is a steep increase in claims by farmers depicting either an increase in conflict or increased awareness to claim compensation.

5. Discussion

5.1. Correlates of human–elephant conflict

There have been few studies about HEC in this area (Bal et al., 2011; Varma et al., 2011) despite holding one of the largest populations of Asian elephant and also suffer high levels of conflict. Hence studies such as these make an important first step to understand the spatio-temporal patterns of conflicts. I am aware of the limitation that all farmers suffering conflict incidences may not report and claim compensation. High levels of conflict reported by elephants and none reported by other species such as wild pig (Sus scrofa) or sambar (Cervus unicolor) clearly indicates a bias either by the reportees or compensation provided only for very obvious species such as elephants. The destruction to crops either through foraging and/or trampling by elephants is very high and the tell-tale signs of the species are very apparent. This makes it easier for farmers to demonstrate the species responsible for crop loss and claim compensation. Similarly, it is straightforward for wildlife department officials carrying out surveys to assess and confirm damages due to elephants.

Results of this study indicate a negative correlation between conflict incidences and rainfall pattern. Most villages around NNP depend on rainfed agriculture and the frequency of conflict shows an increase with crop maturity. Results of this study clearly shows that elephants were attracted to some cultivated food plants possibly due to their high protein or mineral value as demonstrated by Sukumar (1991). The timing of finger millet to inflorescence and threshing stage (August–November) correlates with higher conflict incidences. Plausibly elephants prefer to raid crops during this season for accessing sodium and minerals found in this crop. Similarly conflict was higher during the ripening of paddy which is in line with previous studies in the area (Bal et al., 2011). Maize also ripened during August–November providing opportunity for elephants to access nutritious fodder during this time of the year. It is very likely that elephants damaged cotton while passing through these fields to other croplands as cotton fruits are inedible. This is

4.6. Correlation between conflict incidences and other variables within affected villages

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Fig. 2. Temporal patterns of elephant crop raiding incidences (n = 1955) on various crop species and monthly rainfall from 2006 to 2009.

consistent with patterns seen in other studies from Africa and Asia where cotton and other crops were not consumed by elephants (IUCN-AfESG, 1999; Webber et al., 2011). Ripening of certain crops seems to hold the key reason for elephants to raid crops. In this study elephants have travelled nearly 10 km from NNP for crop raiding. Elephant’s possess highly developed olfactory organs which could be guiding them to ripened crops. Hence, as suggested by a study in Sri Lanka (Santiapillai and Read, 2010), developing substances that could be sprayed on crops that would mask the ripening smell of important crops such as finger millet, maize, paddy, needs to be developed. This would give time to farmers to harvest their crops and avoid conflict. It is also clear that sugarcane, a perennial plantation crop, had visitation right through the year though very small in number during February–September. Visitation to sugarcane fields was also higher during the same periods as crop raids to finger millet or

other preferred crop species. Hence it is evident that despite sugarcane being a year round crop, it was not distinctly targeted as a standalone crop by elephants. Possibly elephants opportunistically raided sugarcane fields during their forays to finger millet, maize or paddy fields. In public discourse conflict increase is also attributed to cultivation of crops such as sugarcane, a better ecological understanding of this subject is very essential. Elephants also raid stacked finger millet before they are threshed when farmers stack harvested finger millet in the open with little or no physical barriers. This makes the harvested crop highly vulnerable for raiding by elephants. Installation of temporary physical barriers to harvested finger millet can reduce losses to farmers. Our initial hypothesis that demographic factors and cropping patterns played a major role in HEC was only partly borne out. The low coefficient of determination (R2) denotes that apart from the variables analysed in this study there could be other probable

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Fig. 3. Human–elephant conflict incidences around Nagarahole National Park during 2006–2009.

Table 2 Pearson Rank Correlations (rp) for association between independent variables and human–elephant conflict incidences in affected villages. Variable Livestock population Human population Village area Forest area within the village Area of unirrigated croplands Area of irrigated croplands Distance of the village from Nagarahole National Park Protected area frontage

rp

P

n

0.149 0.027 0.194 0.320 .014 0.011 0.344

0.192 0.821 0.086 0.004 0.901 0.927 0.002

79 78 79 78 78 78 79

0.389

<0.001

79

significant factors such as elephant movement, behaviour, maintenance of physical barriers and/or other factors which could be causes of conflict. The popular belief widely propagated in grey literature and soft publications, even by conservationists, that increase in irrigation facilities around elephant habitats has augmented HEC is possibly

overstated (Kulkarni et al., 2007). There are large-scale discussions about halting cultivation of crops such as sugarcane around elephant habitats to reduce conflict. Our study results clearly demonstrate that crops such as sugarcane or irrigated land around NNP did not contribute heavily to conflict. Cropping patterns are largely driven by local economics, food patterns and farmers might find it unfeasible to change the current patterns. Farmers will always rely on crops that would fetch them higher returns despite running the risk of conflict. Similarly, the opinion that elephants raid crops due to nonavailability of food and water within PAs during dry seasons is also incorrect. Conflict with elephants had seasonal peaks especially post-monsoons when there should be abundance of food sources within forests and not during summer seasons as popularly believed. This general impression has led to the argument that more surface water holes should be created, cultivation of fodder crops to be undertaken inside PAs and other similar unscientific suggestions. It is apparent from our results that elephant crop raids do not increase during summer, hence such suggestions have little scientific basis.

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Table 3 Results of multiple linear regression model that explains correlates of human–elephant conflict around Nagarahole National Park (n = 79). Regression model Linear regression

R2

R 0.454

SE

0.206

29.68

Variable

Regression coefficient

SE

b

Protected area frontage Unirrigated land area Constant

6.310 0.040 19.038

1.430 0.013 4.160

The study results are similar to patterns in Sumatra where conflict was lesser around PAs that had a buffer of multiple use areas and agroforestry (Nyhus and Tilson, 2004). Hence the few multiple use forest areas bordering NNP such as Devamachi, Anechowkur, Mavukal should be made part of NNP buffer and conserved against activities incompatible with elephant conservation. Bal et al. (2011) present qualitative data based on interviews with farmers that HEC has become a year-round phenomenon unlike in earlier times. However findings from this study illustrates that HEC is seasonal and is absent during certain periods of the year. This makes a strong point for more quantitative assessments of HEC to assist improved conflict management. As in other studies (Sukumar, 1990; Hoare, 1999) it was found that croplands with higher PA frontage could expect higher probability of crop raiding. This result should build a strong case study for strengthening and maintenance of physical barriers in an efficient manner. It is well demonstrated in civil society initiatives that efficient maintenance of physical barriers will certainly reduce crop raiding by elephants and also improve people’s livelihoods (Sankaran and Madhusudan, 2010). Alternative arrangements to compensation such as direct payments, payments for eco-system services, private insurance, consumptive and non-consumptive use of wildlife have been suggested (Bulte and Rondeau, 2005; Leader-Williams and Hutton, 2005; Nyhus et al., 2005; Woodroffe et al., 2005b). In fact there are few projects that have been successfully implemented either by civil society institutions or through community-based programs at real-world scales to reduce conflict (Nyhus et al., 2003; Mishra et al., 2003). It is now important to scale up such experimental initiatives to larger areas to reduce conflict levels. While such programs take root and be accepted by the communities, improved Governmental efforts are very much necessary especially in installing and efficiently maintaining physical barriers that would spatially segregate wildlife and people. However fencing has to factor in ecological issues such as facilitating corridors for elephants to move from NNP to other areas. Spatial segregation of people and wildlife through displacement has been suggested as an option to reduce conflict (Karanth, 2002; Karanth and Karanth, 2007; Ogra and Badola, 2008) which is one of the conservation models carried out at NNP. 280 families were relocated to the north–eastern boundaries of NNP (Nagaapura) during the period 1999–2006 with families being provided agricultural land. It is important to note that high incidences of conflict are reported from this area. The location to where the families would be shifted needs better planning or else despite providing substantial Governmental support in the form of housing and agricultural land it will prove futile in helping forest dwelling communities to practice agriculture as a livelihood option. Similarly these areas were till recently covered with forests and formed part of the elephants natural home range. Hence relocation into this area has also shrunk the elephant’s habitat. HEC goes much beyond PA boundaries wherever there is an interface between conflict-prone wildlife species and humans. Hence mitigation of conflict needs broad-based approaches. In NNP effective reduction of HEC will depend on effective maintenance of

t 0.52 0.26

F

p

9.721

<0.0001

p 4.407 3.093 4.577

0.001 0.003 <0.001

physical barriers, community guarding and vigilance by farmers. Recently the wildlife department due to the heightened HEC, pressure from farmers, political leaders and media have installed new electric fences around the neighbouring Bandipur National Park. This new installation has led to reduction in crop raids according to villagers (personal communication). Conflict incidences are likely to reduce for a couple of years now. However the continuity and sustainability of this will largely depend on the efficient maintenance and interests of field officers. A study post these installations will quantitatively demonstrate the effectiveness and long-term sustainability of these installations. Ultimately fewer losses and fewer elephants killed due to retaliation will be a true measure of ecological, economic and social success of mitigation measures. The mean number of days taken to disburse compensation at NNP was 114 days depicting high delays in processing the claims. Compensation even as a partial strategy to reduce animosity and support aggrieved farmers needs large-scale improvement. The lengthy process of obtaining meagre payments, largely due to delay in fund disbursal from the Government is a serious issue that needs resolution. As wildlife conservation is a non-priority sector for the Government, budget allocations and flow of funds takes longer periods which need to be addressed. Shortage of administrative staff has also been cited as an important constraint in effective processing and disbursal of compensation claims. The average compensation paid in the study area was US$ 30 which is very low for the losses undergone by farmers. Meagre payments have been an important factor in creating animosity amongst farmers against wildlife. Even if the compensation does not match the actual losses, timely payment can help in reducing retaliation if verification of losses and final disbursal is quick. If the humiliation that farmers experience in chasing their claims to finally receive measly payments is reduced, it would help improve relationships between communities and wildlife department. The Government of Karnataka has recently been pro-active in increasing compensation payments for crop loss and human fatalities due to wildlife conflicts (GOK, 2011) and is currently one of the highest in the country. However this still needs improvement to meet the market value of crops lost. Land use around NNP is changing at a large-scale level due to several factors including infrastructure development leading to elephant habitat fragmentation. In the future these changes can lead to higher conflict resulting in greater damages to farmers. Hence Government and conservationists should ensure that policies that regulate these land use changes are compatible with wildlife conservation. Villages that are affected by conflict should be given priority for future investments of improved HEC mitigation strategies. I also recommend a state wide study about HEC to give a broader scale picture of the problem for effective management strategies. Cultural tolerance to human–wildlife conflict is reducing and the losses suffered by poor farmers may have long-lasting social impacts (Karanth and Madhusudan, 2002). Nevertheless as long as large-bodied, conflict-prone species share their boundaries with people, conflict is bound to happen. However conflict needs to be brought down to tolerable limits to ensure friendly neighbours

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