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Elephant Crop Raiding and Railways Traffic: Temporal Determinants of Elephant-train Collisions in Eastern Karbi Anglong, India

Rekib Ahmed

Department of Geography, Gauhati University, Guwahati, India

Abstract: Asian elephant is one of the endangered species in the world. Of late, India witnesses elephant-train collision incidences frequently that resulted in more than 200 elephant deaths in last three decades. As most of the accidents occurred during dusk-night-dawn time period, this study assessed a case of elephant-train collision incidences in reference to diurnal and monthly patterns of elephant crop raiding and railways traffic volume during September-November, 2016 in eastern Karbi Anglong, a hill district of Assam. It evidenced that there was a significant variation of traffic volume (Skewness = -0.89; kurtosis = -0.04; W = 0.86, P<0.05) during dusk-night-dawn (DND) time period. Particularly, a significant difference of traffic volume was observed between day time and DND time {t (13) = 2.35, P<0.05} in the collision incidence month September, 2016. The regression models indicated that distance from crop depredation incidents to the railway line (distance) and the size of damaged crop fields (SDCF) were the strong determinants of elephant-train collisions in the given area. The study provides a crucial insight on elephant-train collisions to develop mitigation strategies for such incidences.

Keywords: elephant-train collisions, traffic volume, crop damage, kurtosis, skewness

Received March 09, 2020; Revised April 12, 2020; Accepted April 22, 2020

Citation: Rekib Ahmed, Elephant Crop Raiding and Railways Traffic: Temporal Determinants of Elephant-train Collisions in Eastern Karbi Anglong, India. Applied Ecology and Environmental Sciences, 8 (3). 81-86. January 2020. doi:10.12691/aees-8-3-2

1. Introduction

Transportation infrastructure in wildlife home ranges affects wildlife habitat through habitat fragmentation, acts as a barrier to wildlife movement and exacerbates wildlife mortality through wildlife vehicle/train collisions [1,2]. Temporal variations in wildlife-train collisions is often determined by seasonal and diurnal variations in traffic volume, weather conditions and animal activities such as foraging, mating or breeding behaviour [3,4,5]. Railway transportation is far more effective for potent as an agent of direct mortality of wildlife due to collisions than road way transportation [6]. More importantly, the Asian elephant (Elephas maximus) has itself been a frequent victim of train collisions [7,8,9], resulting in more than 200 elephant deaths between 1987 and 2015 [10]. Most of the accidents (80%) occurred during the dusk-night-dawn time period, which was significantly higher than during the day time [10].

High mishap incidences at dusk-night-dawn time reflects the nocturnal foraging behaviour of wild mammals living in human-disturbed areas, forcing them to change their foraging activities to night time when human disturbances are least [11,12,13]. The surrounding land cover around the railway line such as agricultural fields, forest covers, water bodies, settlements etc have influenced elephant train collisions elsewhere in India [14]. At the same time, increased traffic intensity of railway within the elephant’s habitat was one of the causal factors of increased mortality of elephant in Rajaji National Park, India [7]. The variation of traffic intensity significantly influenced amphibian mortalities of the Kouchibouguac National Park in south-western New Brunswick, Canada [15]. It was brought to light that crop depredation of elephant was determined by different attributes such as nature of habitat, climate, foraging strategies and behaviour ecology of elephants [16]. It was envisaged that the growth of agricultural activities along the railway lines had resulted in increased crop depredation by elephants and pushed elephants close to railway lines [14]. In Assam, the hill districts of Karbi Anglong and Dima Hasao are important elephant areas. Of these, the former is considerably more important. This is due to the elevated volume of elephant activity from the adjacent Kaziranga National Park during the monsoon months when rising floodwaters force numerous wildlife species, including elephants, to seek higher ground and enter the hill district.

Figure 1. The map of the study region

The present study assessed a case of elephant-train collisions on 27th September, 2016 to understand railway’s traffic behaviour and crop raiding strategies of elephants around the railway line. The objectives of the study were (1) to understand temporal patterns of elephant crop depredation around the railway line and (2) to understand the temporal variation of traffic volume during September, October and November, 2016.

2. Methodology

2.1. Study Area

The study area comprised of three fringe villages of Nagaland border along the 3 km long railway line between Khatkhati railway station and Laharijan Crossing Gate No-ST/58KM 263/2-3 in eastern Karbi Anglon. This railway line is surrounded by a mosaic of forests, low flat hillocks, river, wet lands, crop lands, tea gardens, livestock grazing pastures and settlements. The river Dhansiri flows south-west to north-east along with the railway line. The meandering course of the river formed an ox-bow lake in this area; the latter serving as natural watering holes. The distance of this waterhole from the nearest point of the railway line is 121 metres. The climatic condition and daily weather of the area is determined by the leeward position of the Karbi plateau (locally called 'Chenge-Arnam'), the altitude of landforms and vegetation cover [17]. The vegetation cover ranges from semi evergreen forest, tropical deciduous forest, mixed deciduous forest to grassland forest. The area surrounded by three important elephant habitats viz. Nambar Reserve Forest, Kaliani Reserve Forest and the Nambar & Garampani wildlife sanctuaries.

The total area of the three fringe village viz. Laharijan Basti (Old), Khatkhati Pacca Field and Khatkhati Tila Basti was 3.6 km². The total population of these villages was 6,459 persons with a literacy rate of 46.60% [18], which is generally par in many rural areas of Assam. The infrastructure network prevailing on both sides of the railway line comprise the NH 39, Old Numaligarh-Dimapur road (which is a secondary road) and unpaved roads. The Old Numaligarh-Dimapur road was previously used as a highway at the time of India-China War of 1962. The road is frequently damaged by Dhansiri River and presently serves as a village road linking Dimapur with nearby villages. During the 1970s and 1980s, this area experienced severe elephant poaching, logging and encroachment of forest due to Assam-Nagaland border problem [19]. Border areas between states in India are commonly sources of friction with states covertly encouraging occupation by villagers and later laying claim to such areas on the basis of such settled huts and hamlets. Often forest patches are cleared of vegetation and subsistence agriculture initiated along with a smattering of huts; these are later palmed off as 'evidence' of settlement and occupation by one/either of the state actors.

2.2. Data Collection and Analysis

Information was collected from both primary and secondary sources. The information relating to elephant mortalities along with date, time, sex and age group information of the elephants were collected from the Divisional Forest Office of Karbi Anglong East Division and West Division, Government of Assam and previously published news reports. Railway traffic data for the months of September - November, 2016 were acquired from the Khatkhati railway station and the Laharijan railway crossing gate. The data included daily information regarding the types, time and number of trains traversing the railway segment. The information gathered followed a similar study [20] elsewhere. A total of 14 consecutive days of the each month was selected to analyse variation of traffic volume in the section. A sample size of 297 households was surveyed to understand elephant’s crop damages as well as socio economic structure of the villages, following a previous study [21].

Table 1. Description of parameters and their characteristics

Data on crop damage was acquired through the use of questionnaires and monitoring the area around the railway line on a monthly basis. The data included crop type, the size of crop fields and damaged crop fields, distance from the damaged crop field to the centre point of the railway line, number of elephants responsible for crop damage and details pertaining to the type and extent of damage. A single day from 7 a.m. to 5 p.m. was taken for collecting data on crop damage for each month. An independent incidence of crop depredation was treated as having occurred during a single foray occasion [22]; this tends to enable a conservative estimate of crop-raiding frequency [22]. Damaged crop fields were classified into two types, i.e. trail damage (elephant having walked through the crop fields) and area of damage (widespread damage) [23]. The size of the damaged crop fields were measured through the responses given by farmers and a measuring tape if possible. Responses on size of crop fields and damaged crop fields (SDCF) were given by farmers in different local units of measurement e.g. 1 bigha of a rice field: ½ katha of vegetable field, 3 pura of mustard plot etc. Pura, bigha, and katha are local measurements of land, roughly measuring 57,600, 14,400 and 2880 feet² respectively. All these terms were converted into a standardized value (hectare). The numbers of elephants responsible (RE) for crop damage were counted through direct observations of elephant’s signs such as dung, foot marks, feeding signs and responses of farmers. The location points of all the parameters were recorded with a hand-held global positioning system (GPS) Garmin GPS MAP 64s device.

Coordinate points of crop damage incidents were imported into a geographic information system (GIS) to analyse the data. ArcGIS 10.2 (www.esri.com) was used in order to measure the distance of each crop damage site to the centre point of the railway line. The projection WGS 1984 and UTM Zone 46N were preferred. The parameters of types of damage (trail and widespread damage) and elephants (single and group) were converted as grouping variables. Mann Whitney U test (non-parametric) was used to determine the difference between types of crop damage and distance to the railway line. Multiple linear regression models were employed for each month separately in order to determine the impact of distance and responsible elephants on the size of damaged crop fields [24]. Railway traffic data were divided into two time periods, i.e. day time (6a.m. - 6p.m.) and dusk-night-dawn (DND) time (6p.m. - 6a.m.). Paired sample t test was used to detect the difference of traffic volume between day time and dusk-night-dawn time. Skewness and kurtosis were used to study the variation of traffic volume between the time series data for each month. Skewness and kurtosis can be used for testing the variation of a phenomenon and stipulate as powerful tools for validating models [25]. The Shapiro-Wilk test was used for each time period of the months. The test and measures of skewness and kurtosis using Shapiro-Wilk test provides good power properties and graphical checks [26]. All the statistical analysis was carried out using SPSS V23 [27].

3. Results

Two elephants were killed by up Rajdhani Express (12436) during the study period (27th September, 2016; 12.20 a.m.; 93°44′22.608′′ E - 25°56′22.918′′ N). The train struck two female elephants, one was a calf of about 5 years and the other was a sub-adult about of 15 years in age. The collision also caused the damage of a signal post of the railway line. In Karbi Anglong district of Assam, 58 elephants have been killed due to train accidents, gunshot, poisoned, electrocution and other reasons since 1990, among which 43% elephant mortality had resulted by train accidents. According to recorded data of elephant population of the Forest Department under the Karbi Anglong East Division, a total of 480 elephants were variously sighted in 2011. The highest elephant density was found in the Kuthori and Rongmongwe USF (Unclassified State Forest), the North Karbi Anglong Wildlife Sanctuary, the Dolamara PRF (Proposed Reserved Forest), the Haithapahar DCRF (District Council Reserved Forest) and the USF of Kakochang, Lokhojan, Deithor and Rangsali within the Northern Dolamara Range (Figure 2).

Figure 2. Elephant density around the study area

The values of skewness and kurtosis of the traffic volume in September (DND) were --0.89 and -0.04 (Table 2) respectively (W=0.86, P<0.05). There was a significant variation of traffic volume at the time period. High normality of kurtosis value indicated a mesokurtic distribution. This implied that traffic volume was increasingly concentrated at higher ranges (negatively skewed or left skewed). There was no significant deviation of both the values of skewness (-0.21) and kurtosis (-0.15) from normality during the day time (Table 2). Variation of traffic volume was not significant (W=0.89, P>0.05) at DND in the month of October. On the contrary, the values of skewnes (-0.54) and kurtosis (0.25) of day time (Table 2) indicated that there was an approximate normal distribution of mean traffic volume as the both values were found close to zero. The traffic volume in the month of November (DND) was positively skewed (0.61) and the value of kurtosis was negative (-0.23). There was no significant variation (W=0.95, P>0.05) of traffic volume during the period. However, traffic volume at day time exhibited a distribution with fairly skewed (0.31) patterns and the value of kurtosis were -0.65. The results of paired samples t-test showed that there was a significant difference of traffic volume between day time and DND {t (13) =2.35, P>0.05}. Traffic volume of DND between September and October {t (13) = .47, p= .64} and between September and November {t (13) = -.11, P>0.05} did not differ significantly.

A total of 32% (n=95) of households depended on agriculture. According to the respondents, they faced a variety of problems in crop production. Among these, households 46% ranked as crop raiding, 32% ranked as drought, 9% (rodents), 8% (insects) and 5% (diseases) as being problematic. Two major crops were grown in the area. These were winter paddy (June/July-November/December) and Mustard (October/November-February/March). Besides these, various vegetables such as okra (Abelmoschus esculentus), cabbage (Brassica oleracea), potato (Solanum tuberosum), Indian bean (Lablab purpureus), pumpkin (Cucurbita moschhata), and bottle gourd (Lagenaria siceraria) were grown. About 10.1% (n=30) of the total households faced crop depredation by elephants. Among these, 4 households had to content with crop raiding by almost continuously. A total of 38 incidents of crop raiding occurred during the three months covered by the survey. The total size of damaged crop fields and the total area under cultivation were estimated to be about 1.62 ha and 30.55 ha respectively. Meanwhile, the estimated size of damaged rice fields was 1.37 ha and the size of other crop fields damaged was 0.25 ha of the total cultivated area. Most of the farmers who suffered from crop depredation were tenant farmers of which 53.3% were migrants from the state of Bihar, India.

Crop damage was slightly more of widespread damage (57.9%) compared to trail damage (42.1%). Incidence of trail damage increased significantly with a reduction in distance from the railway line in September (Mann-Whitney U= 4.0, P<0.05), October (U=2.0, P<0.05) and November (U=1.0, P<0.01). The regression models for each month (R 0.84, 0.77 and 0.87) showed that there was a strong positive relationship between the SDCF as the dependent variable and distance and RE as independent variables (Table 3). Moreover, the coefficient of determination values for September (R² = 0.71), October (R² = 0.60) and November (R² = 0.75) indicated the adequacy of the models (Table 3). Thus 71%, 60% and 75% of the proportion of the variation of damaged crop fields were explained by both distance and RE (elephant’s group size). The coefficient of distance in September was negative (b= -.12) and significant (P<0.01), suggesting that larger sizes of crop damage were related to proximity to the railway line (Table 4).

Table 2. Descriptive statistics of traffic volume in the months of September, October and November

Table 3. Regression model summary

Table 4. Coefficients of regression models

4. Discussion

The estimated values of skewness and kurtosis demonstrate that increasing deviation of mean traffic volume from normality (either positively or negatively skewed) with high normality of kurtosis significantly influences elephant train collisions. Although a consistent platykurtic (negative) kurtosis was found during all three months (DND), kurtosis in September was almost zero (-0.04) and it can be considered as mesokurtic kurtosis. Very low and negative kurtosis reflects the lower variation of traffic volume in October and November. Low negative skewness of mean traffic volume of day time changed into high negative skewness during DND and these oscillated either positively or negatively between day and DND throughout September-November. Variation of traffic volume also influenced speed limits [28] and speed limits were correlated with moose-vehicles collision rates in Sweden [29]. Variation of traffic volume particularly at night time affects the movement of wildlife [15], as their foraging activities mainly occurred at night due to high human disturbance during the day [11,12,13]. In Assam, a majority of the mishap incidents of elephants-trains occurred between 6 p.m. and 5 a.m. [8]. Railway traffic of express and superfast passenger and goods trains were primarily depend on a single track [30]. Moreover, goods traffic comprising cement, sleepers, bamboo cuttings, logs, military stores, stone, firewood, dry fish and tea through the traffic interchanging nodes of Chongajan and Lumding also prevailed on a single track [30].

The nearest point of the Dhansiri River from the railway line was 121 metres. Increased incidence of trail damage with proximity to the railway line indicates that elephants crossed the railway line due to seasonal migration and diurnal search for water [16]. The river Dhansiri is only the perennial river of eastern Karbi-Anglong [17]. The tributaries of the Dhansiri, namely Kaliani, Doigurung, Nambar, Depone, Lain and Della are non-perennial rivulets that shrink during winter [17]. Elephants mostly prefer to stay close to major rivers when water becomes scarce during the dry season because they need to consume about 80-160 litres of water/day [16,31]. The best supported model of underlying drivers of elephant-train collision was determined by distance of damaged crop fields to the centre point of the railway line. Parameter estimates in September showed that larger sizes of crop damage occurred when distances of crop fields from the railway line decreased. Previous studies indicated that the level of crop damage increases due to increase abundance of the wildlife and such abundance along the railway line is an important factor in wildlife-train collisions [6]. Differences in distances of damaged crop fields from the railway line in September, October and November was probably affected by the variation of traffic intensity during these months. Variation of traffic volume influenced the behavioural response of wildlife and affected the spatio-temporal movement patterns of moose in Sweden [32]. Traffic intensity of vehicles and trains lead to unusual behavioural changes in elephants of the Rajaji National Park and created human-elephant conflict in the form of crop raiding and manslaughter around the park [33].

Most of the affected farmers of the villages did not claim compensation for crop damage because they were migrant tenant farmers. Moreover, farmer’s tolerance levels to crop damage by elephants were rapidly declining. Crop raiding and elephant tolerance levels are a delicate issue in many contexts. Farmers and forest encroachers in neighbouring Sonitpur district of Assam were responsible for poisoning some 22 odd elephants in 2001-02 [34,35]. A suitable compensation scheme [23,31,36,37,38] and community-based crop protection [39] could increase tolerance levels of farmers as well as increase positive interaction between elephants and villagers [23].

Three elephant warning signs were found along the railway line segment during the field survey. These signs were 3 feet long and 2 feet wide in size. The colours of symbol and background were black and yellow. When standard warning signs are not effective to prevent accidents, oversize warning signs might be helpful in such cases. Moreover, the locations of installed warning signage are important because clear visibility and noticeability could be distracted by various obstructions such as speed and other types of signs/objects [40]. Installation of the signage at the nearest railway station would be helpful to increase noticeability to train drivers. In the absence of any protective measures, beyond limited signage, elephant deaths will continue and exacerbate as human numbers and agricultural intensification occur.

5. Conclusion

There is no alternate railway line to shift railway traffic to in the study area. Therefore, it is necessary to diagnose variation of train’s traffic volume as well as its impact on elephant train collision. The study provides a crucial insight on the incidence of accident but additional information and more sampling is required across different railway segments of Assam to develop mitigation strategies for such incidences. There is a need for a continuous monitoring of elephant’s movement and behaviours around the railway lines to understand the spatio-temporal pattern of crop raiding and to predict and minimize elephant-train collisions. While, reduction of trains speed could prevent train’s strikes but it is economically cost prohibitive [6] and particularly so when traffic volumes rely entirely on a single track.

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