Keywords

1 Introduction

Elephant (Elephas maximus) is the largest land mammal and though occur in low numbers, contribute considerably to the total biomass of the system due to its large size. The population of wild elephants in India is about 30,000 (MoEF&CC 2018). Due to habitat fragmentation, elephants move out to agricultural land parcels leading to man–elephant conflict (Sukumar 2006; MoEF&CC 2017). Project Elephant is a conservation scheme of the Government of India launched to plan at landscape-scale for long-term viability of the elephant habitats and populations (MoEF&CC 2018). There are about 30 Elephant Reserves in India. Monitoring of elephant populations and their demographic characteristics such as age structure and sex ratio across landscapes is an important task for sustainable conservation and management of elephants. Commonly used methods to assess the abundance of wild elephants include Total count, Sample block count, Waterhole count, Line transect sampling and Dung survey.

Based on the recommendation of the State Wildlife Advisory Board, Government of Kerala took a policy decision in 1993, to estimate the wildlife population periodically for the purpose of monitoring. The estimation results of wildlife population in Kerala State have been published from time to time covering major mammals of Kerala Forests (KFRI 1993; Easa and Jayaraman 1998; Easa et al. 2002; Sivaram et al. 2013), exclusively elephants as part of All India Synchronized Population Estimation of Elephants (Sivaram et al. 2006, 2007, 2010) and tigers, co-predators, prey and their habitat (Jhala et al. 2008, 2011). The present chapter elaborates the sampling methods employed for estimating elephant population in different Elephant Reserves of Kerala in 2011.

2 Materials and Methods

2.1 Sample Block Count Method—Direct Sighting

The forest area of each Protected Area/Territorial Forest Division in each Elephant Reserve (Fig. 1) was divided into number of small blocks based on identifiable physical features in forests such as stream, hill, etc., utilizing the toposheets of the Survey of India. In the present study, all the blocks were demarcated on geographic information system (GIS) platform and area of the individual blocks was measured. A systematic random sample of blocks was chosen in each Protected Area/Territorial Forest Division for enumeration. The total number of blocks sampled across different Elephant Reserves of Kerala is presented in Table 1.

Fig. 1
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Map showing Elephant Reserves of Kerala

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Table 1 Total number of sampled blocks and their area
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In the present population estimation, in each of the selected sample blocks, search was made for the presence of selected wild animals including elephants by perambulation from 06.00 to 18.00 h. The search team for each blocks consisted of a trained volunteer, a forest staff and a tribal tracker. The animals sighted while traversing the area were counted in each block. Other details recorded were habitat type(s) of the sample blocks and the age–sex distribution of the animals sighted. The estimated elephant population in ith Elephant Reserve \( \widehat{{(N_{i} )}} \) is given by Lahiri-Choudhury (1991) as:

$$ \widehat{{N_{i} }} = A_{i } \widehat{{D_{i} }},\quad i = 1,2, .. p $$

The sum of the estimates across Elephant Reserves provided state-level estimate.

Standard error (SE) of \( \widehat{{N_{i} }} \) is

$$ {\text{SE(}}\widehat{{N_{i} }}) = \sqrt {\frac{{A_{i}^{2} }}{{n_{i} \left( {n_{i} - 1} \right)}}\sum\limits_{j = 1}^{{n_{i} }} {\frac{{\left( {y_{ij } - y_{i} } \right)^{2} }}{{\left( {x_{ij } - x_{i} } \right)^{2} }}} } $$

95% confidence limit for \( \widehat{{N_{i} }} = \widehat{{N_{i} }} \pm 1.96\,{\text{SE}}(\widehat{{N_{i} }}) \)

where

  • \( \widehat{{D_{i} }} \) = Estimated density of animals (No. of animals/km2) in the ith Elephant Reserve

  • \( A_{i } \) = Total area under effective elephant habitat of the ith Elephant Reserve (after accounting for area devoid of elephants)

  • \( n_{i} \) = Number of blocks sampled in the ith Elephant Reserve

  • \( y_{ij} \) = Number of elephants sighted in the jth block of the ith Elephant Reserve

  • \( y_{i} \) = Total number of elephants in sample blocks of the ith Elephant Reserve

  • \( x_{ij} \) = Area of jth sample block of the ith Elephant Reserve

  • \( x_{i} \) = Total area of the sample blocks in the ith Elephant Reserve

  • p = Number of Elephant Reserves.

2.2 Line Transect Sampling (Direct Sighting)

Line transect sampling technique has been in use for estimating the size of the biological populations such as deer (White et al. 1989), ungulates (Forcard et al. 2002), primates (Buckland et al. 2010a, b, 2015) and elephants (Easa et al. 2002). It is preferred over the other methods as it has a scientific basis to develop estimates of animal density based on detection probabilities of animals even without encountering all the animals in the study area (Burnham et al. 1980; Buckland et al. 2001). In line transect sampling, the observer(s) perform a standardized survey along a series of lines with total line length of L, searching for animals (clusters/herds/troop/groups) of interest (Fig. 2). The radial distance (r) from the observer to the geometric center of the animal herds along with the angle of sighting (θ) are recorded and perpendicular distances (x) are worked out; x = r sin(θ). Animal density is estimated by using the formula \( \widehat{D} = \frac{{n\hat{f}(0)}}{2L} \) (Buckland et al. 2015).

Fig. 2
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Method of line transect sampling—direct sighting

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where

$$ \hat{f}(0) = \frac{1}{{\mathop \smallint \nolimits_{0}^{w} g(x)}} $$

  • g(x) = the probability density function of detecting an animal (herd) in the survey area

  • x = perpendicular distance (m)

  • L = transect length (km)

  • w = perpendicular distance to animals.

The approximate variance of \( \widehat{D} \) is

$$ \widehat{\text{Var}}\left( {\widehat{D}} \right) = \widehat{D}^{2 } \left\{ {\frac{{\widehat{\text{var}}(n)}}{{n^{2} }} + \frac{{\widehat{\text{var}}\left[ {\widehat{E}(s)} \right]}}{{\left[ {\widehat{E}(s)} \right]^{2} }} + \frac{{\widehat{\text{var}}\left[ {\hat{f}(0)} \right]}}{{\left[ {\hat{f}(0)} \right]^{2} }}} \right\} $$

where

  • n = number of herd/troop/groups encountered

  • s = expected herd/troop/group size.

An approximate 100(1 − 2α)% confidence interval is given by

$$ \widehat{D} \pm Z\alpha \sqrt {\widehat{V}\left( {\widehat{D}} \right)} $$

  • (z = z0.025 = 1.96 for a 95% confidence level).

Some of the functional forms of g(x) considered include uniform, half normal, negative exponential and hazard rate. In order to improve the fit of the model, especially, the tail part of the detection curves, series expansion such as simple polynomial or higher-order polynomial is added with the key detection function. One among the functional forms is chosen based on fit statistics/model selection criterion such as Chi-square test, Akaike information criterion (AIC) and Bayesian information criterion (BIC) (Buckland et al. 2001, 2004).

In the present study, the line transect sampling was adopted in the selected sample blocks. In each block, a transect of about 2 km length was laid. These transects were covered on foot recording the sighting distance (r) and the sighting angle (θ) to the elephant or geometric center of the elephant herds. Ocular estimation of the sighting distance was made. The sighting angle was measured with a compass. These measurements formed the input data for the estimation of elephant density. The details of line transects employed for the population estimation are presented in Table 2.

Table 2 Number of line transects, total length and number of detections in direct sightings
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The radial distances (r) to the elephant herds and angle of sighting (θ) formed the input data for the estimation of elephant density.

The density estimates were obtained by using the software DISTANCE 6.0 developed by Thomas et al. (2010). The univariate half-normal distribution with the series expansion of simple polynomial was used for estimating the elephant density. A 5% truncation of the largest distance values was adopted to improve the precision of the density estimates. The density estimates were developed after adjusting for herd size bias. The herd size estimation was done by regressing distance function g(x) on logarithm of herd size. Whenever the regression approach was not possible, mean/median herd size was used.

2.3 Dung Survey Using Line Transect Sampling

Population estimation methods based on direct sightings of animals especially elephants suffer due to scattered occurrence, group behavior and its vast home range (Jachmann 1991). The indirect evidences of animals such as droppings (pellets and dung) present in the area survive for a considerable time period which can be used for the estimation of animal density (Marques et al. 2001). Standing crop and clearance plot methods are the possible indirect methods for estimating the elephant population. The clearance plot method involves clearing dung from marked plots at regular intervals, counting the dung piles, and correcting the counts by the defecation rate (Staines and Ratcliffe 1987). The standing crop method is the most commonly used method. One of the assumptions of this method is that there is a stable relationship between the amount of dung present and the number of elephants (Barnes and Barnes 1992). The elephant density using the method involves one-time survey of dung for estimating dung density which is corrected by defecation and decay rate. Estimated density of elephants, \( \widehat{{D_{\text{e}} }} \) is given by

$$ \widehat{{D_{\text{e}} }} = \frac{{{\text{Dung}}\,{\text{density }}}}{{{\text{Defecation}}\,{\text{rate}}}} \times {\text{Dung}}\,{\text{decay}}\,{\text{rate}} $$

Dung density (number of dung per unit area) is usually estimated through dung surveys using quadrat sampling, strip transect sampling or line transect sampling. Defecation rate (number of dung piles defecated per day per animal) can be estimated by monitoring captive elephants or by placing a known number of elephants in an enclosure previously cleared off dung and estimating the number of dung produced over a fixed time period. The dung decay rate is defined as the number of dung decayed per day and is expressed as the reciprocal of the estimated mean time to decay (Barnes and Barnes 1992). The literature on dung decay experiments are available (Barnes and Jenson 1987; Barnes and Barnes 1992; Laing et al. 2003; Sivaram et al. 2016).

In this study, the technique of line transect sampling was adopted in the sampled blocks for estimating the dung density of elephant. In each block, the transects were covered on foot recording the perpendicular distance to the geometric center of the dung piles of elephant. The perpendicular distance was measured using a tape. The number of line transects and total transect length used for the estimation are presented in Table 3.

Table 3 Number of line transects for the estimation of dung density
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The perpendicular distances to dung piles formed the input data for the estimation of dung density of elephants. Univariate half-normal distribution with the series expansion of simple polynomial was used as detection function for estimating the dung density. A 5% truncation of the largest perpendicular distance values was adopted to improve the precision of the density estimates. The defecation rate of 16.33 per day, as obtained from wild elephants in Mudumalai by Watve (1992), was used in the above formula. As far as dung decay rate is concerned, the rate 0.0102 per day, obtained from dung decay experiments conducted in Wayanad Elephant Reserve in the year 2005 was used. The elephant population in each Elephant Reserve was estimated by multiplying density estimates with their respective extent of elephant habitat.

3 Results

3.1 Sample Block Count

The estimated elephant population based on sample block count method for various Elephant Reserves is given in Table 4 (also depicted in Fig. 3). The total number of elephant sightings using sample block count method was 1357 in 2011 and 1911 in 2010 while using total count method it was 2296 in 2002. The extrapolated number of elephants for the State was 1958 in 2011 against 3520 in 2010. The population estimation in 2010 was exclusively for elephants. In the year 2011, the focus was for all the major mammals including elephants and thus lesser number of detections and decrease in the estimate of total elephant population. The area sampled also varied from 4474 km2 in 2010 to 5515 km2 in 2011. In 2011, all the block maps were digitized and exact area statistics was calculated using GIS, to work out area sampled. Due to the use of digitized maps, there was an upside revision in the area sampled and thus affecting the estimation of elephant density and elephant population. Besides above, the variations in weather and field conditions might have also contributed to the differences in number of detections.

Table 4 Estimated elephant population using sample block count method
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Fig. 3
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Density of elephants using sample block count method

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The highest elephant density is usually found in Wayanad Elephant Reserve. On the contrary, in 2011, the highest was in Anamudi Elephant Reserve followed by Wayanad, Periyar and Nilambur Elephant Reserve (Table 4). In terms of total number of elephants, Anamudi Elephant Reserve ranked first followed by Periyar, Wayanad and Nilambur Elephant Reserve. The population characteristics of the elephants sighted in different Elephant Reserves of Kerala are presented in Table 5. Lower confidence limit (LCL) and upper confidence limit (UCL) were worked out at 5% level of significance for all the methods.

Table 5 Population characteristics of elephants using sample block count method
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3.2 Line Transect Sampling—Direct Sighting

The herd and elephant density are presented in Table 6. The highest elephant density was in Anamudi followed by Wayanad, Periyar and Nilambur.

Table 6 Estimates of elephant density using line transect sampling—direct sightings
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3.3 Line Transect Sampling—Dung Survey

The dung density estimates for various Elephant Reserves are presented in Table 7. The estimated density and population of elephants in various Elephant Reserves are presented in Table 8 and Fig. 4. The highest elephant density was in Wayanad followed by Anamudi, Periyar and Nilambur. Anamudi had the highest elephant population followed by Periyar, Wayanad and Nilambur.

Table 7 Estimated dung density using line transect—dung survey
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Table 8 Density and population of elephant based on dung density estimates
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Fig. 4
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Density of elephants using line transect sampling—dung survey

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4 Discussion and Conclusions

The population estimation in 2011 covered major mammal species including elephants, while the estimation in 2010 was exclusively for elephants. The possible reason for the decrease in elephant population in 2011 is given in Sect. 3.1. We have not used line transect sampling—direct sighting for estimating the elephant population as it provided inflated population figures. The estimated elephant population using dung survey was 7490.

The sample block count method which is based on elephants sighted while traversing the sample block area may suffer from under counting and repetitive counting of elephants. A sampling frame of blocks was formed based on identifiable physical features in forests such as stream, hill, etc. Some of the sample blocks chosen were large in size and have difficult terrains and thus lesser geographical coverage while traversing. This might lead to under estimation of the population. The solitary elephants behind the bushes could not have been counted. The elephants have large home range and move across the blocks. This might lead to repetitive counting across the chosen blocks. The sample block count method may not be acceptable for the population estimation as it is not based on detection probability of the animals. Nonetheless, the sample block count method provides information on the characteristics of the population such as sex ratio among adults and sub adults, % tuskers and number of makhnas.

The line transect sampling—direct sighting has greater advantages than the sample block count method (Sivaram et al. 2016, 2018). However, there are many practical difficulties. Line transect may pass through different local forest conditions and thus may provide imprecise estimates. Detection probability of elephants varies across forest types, therefore, in thick forests (say, evergreen forests), the visibility of elephants at longer distance may lead to under estimation. The key assumptions of line transect sampling are that the detection probability g(x) is the same for all the animals and that 100% of the animals are detected along the transect line, i.e., g(0) = 1 (Buckland et al. 2001). In the case of elephants, these assumptions are likely to be violated as there could be instances in which sighting of elephants on the transect line and closer to the line may danger to the enumerator. Such difficulties may produce imprecise estimates. Though line transects are cut before the estimation exercise, the enumerators are likely to deviate from walking on the line when elephants are sighted for personal security reasons. The elephant density using line transect sampling—direct sighting was overestimated when compared with the other methods and thus affecting the estimate of the total elephant population.

The estimation of elephant population using dung survey involves three estimates viz., dung density, decay rate of dung piles and defection rate. Estimation of each of these involves their own assumptions and practical difficulties (Barnes and Barnes 1992; Laing et al. 2003). The presence of dung piles and detection probability depend on the level of rain fall preceding the date of dung survey (Sivaram et al. 2016; Barnes et al. 1997). Dung decay rate varies across sites (Varman et al. 1995; Sivaram et al. 2018). The dung decay rates are mostly borrowed from other studies for the population estimation. For example, the present exercise used the dung decay rate estimated in parts of Wayanad Elephant Reserve during the year 2005 (Sivaram et al. 2006). It is advisable that the dung decay experiments be conducted during every population estimation across Elephant Reserves for obtaining reliable estimates. Similarly, the defecation rate used in the formula of elephant density was from Watve (1992) based on his observations in Mudumalai Sanctuary.

In the computation of confidence intervals for the population estimate, the standard errors of dung density alone were used. If the standard errors of the other parameters are included, the confidence intervals of the population estimates would be to an unacceptable range. This limits to reach any conclusion on population trends as to whether the elephant population is on increase or decrease (Fig. 5).

Fig. 5
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Trends in estimated elephant population using line transect—dung survey

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The estimates of the three methods need not agree with each other due to assumptions and limitations associated with each of the methods. The validation of the methods for elephants at landscape level is not possible as the elephants are long-ranging animals. Among the three methods used for the estimation of population of elephants, the dung survey appeared to be better method than the other two methods. However, more studies to obtain defecation rates and decay rates in varying climatic conditions will help improving the accuracy of the elephant density estimates. Proper training to field officers will also greatly improve the estimates. Despite several limitations of the methods, efforts in accurately estimating the population estimation should be continued for policy making and effective wildlife management.