Status of in Forest Division Arc Landscape, , CONTENTS

ACKNOWLEDGEMENTS 6 SUMMARY 7 CHAPTER 1: INTRODUCTION 8 CHAPTER 2: STUDY AREA 10 2.1 Location 2.2 Physical features 2.3 Flora & fauna CHAPTER 3: METHODS 14 3.1 Pre-field work 3.2 Reconnaissance survey 3.3 Data collection 3.4 Analytical details 3.4.1 Mark-Recapture approach 3.4.2 Inverse Prediction Method for density estimation 3.4.3 Maximum Likelihood method for density estimation CHAPTER 4: RESULTS 21 4.1 Capture Dynamics 4.2 New Capture Saturation 4.3 Closure Test and Model selection 4.4 Population (N-hat) 4.5 Tiger Density (D-hat) CHAPTER 5: DISCUSSION 28 5.1 Capture Dynamics 5.2 New Capture Saturation 5.3 Closure Test and Model selection 5.4 Tiger Population (N-hat) 5.5 Tiger Density (D-hat) Citation: Anwar, M., Kumar, H., Vattakaven, J., 2010. Status of Tigers in Pilibhit Forest Division, Terai Arc Landscape, CHAPTER 6: MANAGEMENT IMPLICATIONS AND 30 Uttar Pradesh, India. WWF-India. RECOMMENDATIONS

Copyright © 2010- All rights reserved REFERENCES 31 WWF-India 172-B, Lodi Estate New Delhi 110 003, India Tel. +91-11-4150 4797 Website: www.wwfindia.org

Published: August 2010

Tiger Population In Pilibhit Forest Division 2010 page 2 © JOSEPH VATTAKAVEN/WWF-INDIA ANNEXURES 34 Annexure 1 Annexure 2 Annexure 3 Annexure 4 Annexure 5 Annexure 6 Annexure 7 Annexure 8 Annexure 9 LIST OF FIGURES Figure 2.1: Location map of Pilibhit forest division and adjoining Protected Areas Figure 3.1: Location of trap stations over Landsat image of Pilibhit forest division Figure 3.3: Camera trap locations with minimum convex polygon, ½ MMDM and MMDM buffers (a) and with habitat masking (b) Figure 4.1: Percentage of captures of males and females in different quarters of total occasions Figure 4.2: Photographs of individual tigers (Right & Left flanks) with a map of capture sites Figure 4.3: Rate of tiger photographs and cumulative number of new captures in Pilibhit Forest Division LIST OF TABLES Table 3.1: X-matrix of individual tigers (11) in Pilibhit forest division for 40 occasions and 73 captures used in Capture, CloseTest and MARK 4.1 Table 3.2: Matrix used in Density 4.4.5 Table 3.3: Trap location file used in Density 4.4.5 Table 4.1: Selected model and tiger population with other statistics in the study area Table 4.2: Tiger density and other statistics in the study area ACKNOWLEDGEMENTS SUMMARY

We would like to thank the following organizations and associated individuals for their Tigers are a flagship and conservation dependant help and inputs in carrying out the present study successfully. species

Forest Department, Uttar Pradesh, for permission, logistic support, secondary © JOSEPH VATTAKAVEN/WWF-INDIA information, and assistance in data collection. Mr. B. K. Patnaik, (PCCF), Mr. V. K. Singh (DFO-Pilibhit), Mr. S. R. Singh (S.D.O.), Mr. R. P. Yadav (Range Officer (RO)-Mahof), Mr. Alijaan Ansari (R.O.-Mala), Mr. Imtiyaz Siddiqui (R.O.- Barahi), Mr. Mobin Arif (Forester), Mr. Navneet Singh (Forester), Mr. M. Arif (Forester), Mr. P. P. Singh (Forester), forest guards, beat watchers and rest house care takers.

Wildlife Institute of India, Dehradun, for technical inputs, guidance in data analysis, and assistance in data collection Mr. Qamar Qureshi (Scientist-F), Dr. Y.V. Jhala (Scientist-G), Mr. Manas P. Manjrekar (Research Fellow), Mr. Dipankar Lakhar (Research Fellow), Mr. Awanish K. Rai (Research Fellow), Mr. Wasi Azmi (Volunteer), Mr. Anant Pandey (Research Fellow ), Mr. Chitranjan Dave (Research Fellow), Ms. Swati, Mrs. Babita and Mr. Ved P. Ola.

WWF- India (Pilibhit Field Office), for accounts management and smooth running of data collection. Mr. Anil Srivastva (Accounts officer), Mr. Kandhai lal (Asst. Project Officer), Mr. Virendra (Driver), Mr. Prem (Driver).

WWF- India (Ramnagar Field Office), for accounts related tasks and coordination. Mr. Hem Tewari (Landscape Coordinator), Mr. Neeraj Pant (Accounts Officer), Mr. Prem (Office Attendant). Estimating the density of tigers in an area provides crucial information to conserve and manage tigers, its prey base and habitat. The population and density of tigers WWF- India (Secretariat-New Delhi) in Pilibhit forest division was estimated in a systematic scientific framework using We wish to thank Mr. Ravi Singh, SG & CEO, WWF-India. Dr. Sejal Worah, Programme the camera trapping technique. Thirty best sites were selected as camera trap Director, & Dr Dipankar Ghose, Director, Species and Landscapes for their timely stations on the basis of occurrence of tiger signs. A total of 174 photographs were inputs and help with logistics and coordination. Thanks are also due to Copal Mathur, captured in 1200 trap days over 40 occasions with 76.7% tiger photo capture success Sonali Nandrajog and Anil Cherukupalli for designing and editing this report. rate per trap station. Eleven individual adult tigers were identified on the basis of unique strip patterns. The capture curve for new tigers reached an asymptote on the A special thank you to Mrs. V. K. Singh, for regularly motivating the team in the field. 13th occasion. Population of tigers was estimated to be 12±1.50 (N-hat±SE) by the We are also thankful to the local stakeholders (villagers) for restraining themselves selected model (Mh jackknife) and it could range between 12 and 19 (95% Confidence from the study area during data collection and making the study disturbance free Interval). Density of the tigers in the Pilibhit Forest Divison was estimated to be without any loss of camera traps. 3.86±1.20 per 100 km² (D-hat±SE) using Maximum Likelihood method (Half normal, AIC=804.64) ranging between 2.13 to 7.00 (95% Confidence Interval) and -Sd. 4.95±1.2 per 100 km² using ½ MMDM method with habitat masking and ranging (Authors) between 4.58 and 8.00 per 100 km².

Considering the biodiversity rich habitat of Pilibhit Forest Division, including breeding tigers, and its connectivity to other critical forest blocks in this landscape, we recommend enhancing the protection and status of this reserve forest and declaring it as a Tiger Reserve at the earliest.

Tiger Population In Pilibhit Forest Division 2010 page 7 Chapter 1

Tigers are a conservation ©JOSEPH VATTAKAVEN/WWF-INDIA dependent species. They require 1.0 protection from poaching, an adequate prey base, and adequate INTRODUCTION habitat. While the tiger as a species may not go extinct within the next two decades, the current trajectory may cause wild populations to disappear in many places, or shrink to the point of “ecological extinction”-where their numbers are too few to play their role as the top predator in the ecosystem (Sanderson et al. 2006). Conflict with humans, prey depletion, poaching, habitat loss and habitat fragmentation remain the most obvious threats to tigers in the wild, underscoring the need for political will to confront these challenges (Seidensticker et al. 1999a; Johnsingh & Negi 2003; Graham et al. 2005; Wang & Macdonald 2006).

India harbors a reasonably large proportion of the world’s tiger population. This is mainly attributed to a good forest cover (158,373 km2, 4.82% of total geographical area) under a Protected Area network (660) of 99 National Parks, 514 Wildlife Sanctuaries, 43 Conservation Reserves and 4 Community Reserves (NWDC, W.I.I. 2010) including 38 Tiger Reserves with an area of 32137.14 km2 (NTCA 2010). In India, conservation efforts such as Project Tiger have, since 1973, been attempting to save the nations declining population of tigers, their prey and habitats. Yet, about 26% of their range has been lost in the recent past (Qureshi et al. 2006). One such landscape, the Terai Arc Landscape, encompassing the Shivalik hills and the Terai flood plains running parallel to the outer Himalayas are considered one of the most threatened and fragile ecosystems in the Indian subcontinent. This productive landscape (Wikramanayake et al. 2004) is most prone to human disturbances (Johnsingh et al. 2004). The tiger has become locally extinct in 29% of the districts of this landscape where it was historically recorded. Currently, the tiger occupies 5080 km2 of forested habitats (Jhala et al. 2008). Protection cover for tigers diminish rapidly in the areas outside declared Protected Areas where boundaries of land use by humans and core tiger habitat are often blurred. These areas also witness human-wildlife conflict frequently. Therefore, estimating the population and density of wild tigers in such areas is of prime importance to ecologists and managers.

In most situations the goals of managing natural animal populations are expressed in terms of population size. The use of capture-recapture theory (Otis et al. 1978; Pollock et al. 1990) and remotely triggered cameras to capture individually identifiable Tiger in Sal forest habitat animals has resulted in their use for estimating demographic parameters (Karanth 1995; Karanth and Nichols 1998; Karanth et al. 2006). Owing to its applicability in The present study was carried out in Pilibhit forest division in Uttar Pradesh, which is a reserve forest a wide variety of habitats (Karanth et al. 2004) and ability to provide information in a human dominated landscape matrix. This study was the first of its kind in this forest division and was on activity pattern, habitat use and reproductive status of cryptic carnivores, camera well supported by the Forest Department. Local villagers restricted their movement in a manner to collect the trapping has in the recent past gained popularity (Griffiths 1993; Karanth 1995; data efficiently without a single loss of camera trap unit during the study period. Karanth and Nichols 1998; O’Brien et al. 2003; Trolle and Kery 2003). Availability of The objectives of the study were as follows: various softwares such as CAPTURE (Rextad & Burnham 1991), MARK 4.1 (Cooch & 1.To identify individual tigers and other fauna in the study area using camera traps. White 1995) and Density 4.4.5 (Efford 2009) etc. makes this technique hassle free and 2.To estimate population and density of tigers in the study area of Pilibhit forest division by photographic statistically highly precise for estimation of populations. capture-recapture modeling approach.

Tiger Population In Pilibhit Forest Division 2010 page 8 Chapter 2

The present study was carried out Topography of most of the forest area is plain and the general aspect is south-west. The in Pilibhit forest division in Uttar slope falls 2-3 m per km distance. The altitude ranges from 200 to 145m a.m.s.l. This 2.0 division looses the characteristics of bhabar areas in the south and forms flat alluvial Pradesh, which is a reserved plains of terai. Lower water table and swampy areas are peculiar features of terai. forest in a human dominated Small ditches, ponds and perennial rivers such as Sharda, Mala, Khannot, Chuka and landscape matrix. Gomti are the major sources of water. Main Sharda canal and other canal channels STUDY AREA pass through the different forest areas of the FD, providing water for wildlife even during peak summer season. Seepage of water from these canal system forms swampy areas and many small ditches, providing good habitat for swamp deer, rhinos and 2.1 Location Lower water table and tigers too. Sharda Sagar dam was built during 1953-57. This 22 km long water reservoir Pilibhit Forest Division covers an area of 712.88 km2 and is situated between 28º52’- swampy areas are peculiar also acts as a water source for the FD. Most of the areas remain inundated during the 28º46’ N Latitude and 79º55’-82º15’ E Longitude in the foothills of Himalaya features of terai monsoon. adjoining Shukla Phanta Wildlife Reserve, Nepal (Figure 2.1). Administratively, this forest division is managed under five forest ranges namely Barahi, Haripur, Deoria, 2.3 Flora & Fauna Mala and Mahof, which comprises of 52 Forest Beats (management units). This Pilibhit FD is a part of Terai Arc Landscape and according to the recent classification division is very important for long term conservation of wildlife in the Terai Arc proposed by Wikramanayake et al. (1999, 2002) that takes into consideration both Landscape (TAL) owing to its contiguity with the terai-bhabar forests of Surai range biogeography and conservation values, the landscape corresponds to three ecoregions of Terai East Forest Division (FD) in the north-west and with the Kishanpur Wildlife – (i) Upper Gangetic Plains moist deciduous forest, (ii) Terai-Duar savanna and Sanctuary (WLS) in the south-east. This division also provides connectivity to the grasslands and (iii) Himalayan subtropical broadleaf forest. The vegetation in the Shukla Phanta Wildlife Reserve with Kishanpur Wildlife Sanctuary in India through The vegetation in the area area is a mosaic of dry and moist deciduous forests, scrub savannah and productive Lagga-Bagga forest block, Tatarganj area of North Kheri FD and across Sharda river, is a mosaic of dry and moist alluvial grasslands, which harbour a rich fauna including several endemic and Haripur range of Pilibhit FD. At places, this division shares its legal boundary with the deciduous forests, scrub globally endangered species. Prominent among such species are the Royal Bengal savannah and productive human dominated matrices. In the east of the FD, North Kheri and South Kheri FDs Tiger (Panthera tigris), Asian elephant (Elephas maximus), one-horned rhinoceros alluvial grasslands, which are situated. harbour a rich fauna (Rhinoceros unicornis) and swamp deer (Cervus duvaucelli). Other endemic and obligate species found in this landscape are the hog deer (Axis porcinus), hispid 2.2 Physical features hare (Caprolagus hispidus), Bengal florican (Houbaropsis bengalensis) and swamp Figure 2.1 francolin (Francolinus gularis). Many of these species, surviving in small populations, Location map of Pilibhit have their last home in this landscape (Johnsingh et al. 2004). The Asian elephant and forest division and adjoining one-horned rhinoceros are migratory species in the division. Protected Areas

Tiger Population In Pilibhit Forest Division 2010 page 10 Tiger Population In Pilibhit Forest Division 2010 page 11 ©JOSEPH VATTAKAVEN/WWF-INDIA Chapter 3

The standard method of camera 3.3 Data Collection trapping in accordance with Capture- Data collection was carried out during 40 occasions from 22nd May to 30th June, 3.0 Recapture framework was followed to 2010. MOULTRIE (D-40, Moultrie Feeders, Alabama) passive camera units were collect and analyze the data for tiger initially tested and deployed in the field on 19th and 20th May, 2010. Moultrie digital population and density estimation passive units is activated by infrared sensors that detect animal presence by sensing in the study area in Pilibhit forest a moving heat source whose temperature is different than the ambient temperature. METHODS division. The unit has a 4.0 megapixel digital camera which has a quick trigger time, 45-ft flash and a reasonably good battery life. Spitting, smoking, tobacco consumption etc was discouraged near trap stations, though some grasses and shrubs were cleared to get 3.1 Pre-Field work obstruction free captures. Site clearing was done five days in advance before deploying A landsat image (Dated 19th November, 2009, Path 145, and Row 040) was of camera units in the field to allow animals to get acclimatized to the area. On each downloaded and processed for its use in the reconnaissance survey and thereafter. station, two camera units were placed on poles or tree trunks between 30 and 40 A copy of the management plan of the Pilibhit FD and blue print of the division was cm height from the ground in such a way so as to capture both flanks of the animal acquired from the Divisional Forest Office, Pilibhit. Secondary information about the simultaneously. The cameras were placed at a distance of 4 to 8 meters on both sides trails and dirt roads regularly used by tigers in the division was also acquired from the from the center of the trail to get good quality full frame pictures of animals on the Divisional Forest Officer, Forest Range Officers, Foresters, Forest Guards and Beat locations. The camera delay was kept at minimum to minimize the chance of missing Watchers of Pilibhit FD for selecting a suitable patch to carry out field data collection mating pairs or a female with cubs in case such an event occured. All of the cameras after verification. were regularly checked in the field for its proper functioning, orientation and status of the battery. Pictures were downloaded on alternate days and orientation of the cameras 3.2 Reconnaissance Survey were adjusted accordingly. Systematic downloading of the data from all the trap Reconnaissance survey was carried out from 4th May to 18th May, 2009. On the basis stations was also carried out after every 10th day. of secondary information and sign survey, 75 initial locations were selected for deploying trap stations. Geo-coordinates of the suitable sites were recorded using After examining the stripe pattern on the flanks, limbs, forequarters and sometimes a handheld Global Positioning System receiver (Garmin Etrex). These points were even tail (Schaller, 1967; McDougal, 1977; Karanth, 1995), every tiger captured was further monitored for considerable time for the signs of tigers and overlaid over given a unique identification number e.g. PMT001 & PFT005 where PMT and PFT gridded landsat image in Geographic Information System environment using ArcGIS stands for Pilibhit Male Tiger and Pilibhit Female Tiger with their individual numbers 9.2 and ERDAS Imagine 9.1. By further considering regular occurrence of tiger signs, respectively. Males were differentiated from females based on the presence of testicles. 30 suitable sites were selected as trap stations in a manner so that at least one station Print out of the captures were taken for ease in individual identification. fell in each grid of 5 km² and each station seperated by about 2 km away from other stations (Figure 3.1). 3.4 Analytical details Abundance & Density of the tigers in the study area was estimated by using software MARK 4.1, CAPTURE 2 and Density 4.4.5. Figure 3.1 Location of trap stations over Landsat image of Pilibhit 3.4.1 Mark-Recapture Data was analysed in Mark-Recapture framework which uses various suitable models forest division approach on the basis of basic assumptions of demographically and geographically closed population (Otis et al. 1978; Karanth 1995; Karanth & Nichols 1998). Probabilistic capture-recapture estimators can model capture probabilities being heterogenous among individuals in a population due to its social structure or due to effect of behavioural response to trapping and temporal variation in capture probability. Models are also available for combination of these biological factors i.e. heterogeneity, time and behaviour (Karanth 1995). To establish demographically closed population, closure test was performed using software CAPTURE 2 (Otis et al. 1978; White et al. 1982; Rexstad & Burnham 1991) and CloseTest (Stanley & Burnham 1999). It uses standard X-matrix where 1 signifies capture and 0 demonstrates no capture at a particular occasion of a session. In closure test, value of p≥ 0.05 favors the null hypothesis of population closure.

Analysis of X-matrix involves comparison between competing models using a series of hypothesis tests and the results of an overall discriminant function analysis, in order to select the most appropriate abundance estimation (N-hat) model for a given data set (Otis et. al. 1978).

Tiger Population In Pilibhit Forest Division 2010 page 14 Tiger Population In Pilibhit Forest Division 2010 page 15 Table 3.1 Tiger ID Occasions (40) 3.4.3 Maximum Likelihood Capture-recapture studies of animal populations with camera traps inevitably have X-matrix of individual tigers PMT1 0100001000111001100001000101100010000010 1; method for density a spatial component where animals close to traps are more likely to be caught than (11) in Pilibhit forest division estimation those far away. Conventional closed-population estimates of abundance do not for 40 occasions and 73 PMT2 1000110001100000001000001000001000100001 1; consider spatial components and therefore rigorous estimates of density often cannot captures used in Capture, PMT3 1000000000011100000001000000000000000001 1; CloseTest and MARK 4.1 be obtained. Maximum Likelihood method (ML) estimates of density use the capture PMT4 0000000000001000000000000000000000000000 1; locations to estimate animal locations and spatially-referenced capture probability. PFT5 0100001100010100000101101100100010000001 1; The models being likelihood-based, allow use of Akaike’s Information Criterion or PFT6 1001010000000001000010000101000000100000 1; other likelihood-based methods of model selection. Density is an explicit parameter, and the evaluation of its dependence on spatial or temporal covariates is therefore PFT7 0001000100000011010100001000000000001000 1; straightforward. Detailed methodology of ML can be accessed from Borchers & Efford PFT8 1000000000000000000000000000000010000001 1; 2007. Habitat mask option was used for density calculation using a shape file of the PFT9 0000000010000000100001001001000000000000 1; concerned area. It was performed with Density 4.4.5 software (Efford 2009). PFT10 1000000000000001100000000000001000000000 1; Two different files were used in Density 4.4.5 software, comprising capture recapture data along with trap ID (Table 3.2) where capture was recorded with geo-coordinates PFT11 1000000000000000000000000000000001000000 1; of trap stations (Table 3.3) to be used in calculation of capture probability (g0) and spatial functions (σ), respectively. The density (D-hat) of tigers in the study area was estimated by the conventional

method of estimated population size (N-hat) divided by the effective sampled area ©JOSEPH VATTAKAVEN/WWF-INDIA (A (W)), where A (W) was estimated by creating a polygon over the trapping stations (A) and a buffer width (W) estimated as half the Mean Maximum Distance Moved (½ MMDM) ‘d’ by recaptured tigers, added to the camera trap polygon (A) (Karanth and Nichols, 1998). The Minimum Convex Polygon (MCP) is usually formed by the outermost camera traps points using GIS domain. Some areas of human dominated matrices and water reservoir (Sharda Sagar) contributed to the MCP and buffers of MMDM and ½ MMDM were actually subtracted from the calculated areas (Fig 3.3).

Figure 3.3 Camera trap locations with minimum convex polygon, ½ MMDM and full MMDM buffers (a) and with habitat masking (b)

Legend MMDM 1/2 MMDM MCP Trap Stations

3.4.2 Inverse Prediction Density was also calculated by using computer-intensive method from trapping data Method for density (Efford 2004; Efford et al. 2004) using the software Density 4.4.5 (Efford 2009). estimation This method relates the probability of catching an animal to the distance between its home range centre and a particular trap. The parameters of this relationship can be jointly estimated from conventional capture-recapture data by statistical procedure of simulation and inverse prediction. These calculations were performed using software Density 4.4.5 (Efford 2009). The key advantages of this method are that it removes the need to calculate the Effective trapping area, and that it provides reliable confidence intervals (Efford 2004). Habitat masking was done to subtract the human dominated matrices in calculation of density using software Density.

Tiger Population In Pilibhit Forest Division 2010 page 16 Tiger Population In Pilibhit Forest Division 2010 page 17 Table 3.2 Session ID Animal ID Occasion ID Trap ID Session ID Animal ID Occasion ID Trap ID Matrix used in Density 4.4.5 1 1 2 19 1 5 22 8 1 1 7 21 1 5 23 8 1 1 11 18 1 5 25 4 1 1 12 18 1 5 25 8 1 1 13 18 1 5 26 5 1 1 16 17 1 5 29 8 1 1 17 19 1 5 33 4 1 1 22 19 1 5 40 6 1 1 22 23 1 5 40 11 1 1 26 17 1 6 1 11 1 1 28 22 1 6 4 12 1 1 29 18 1 6 6 11 1 1 33 17 1 6 16 12 1 1 39 22 1 6 21 11 1 2 1 17 1 6 21 8 1 2 1 18 1 6 21 12 1 2 5 17 1 6 26 10 1 2 6 17 1 6 28 12 1 2 10 17 1 6 35 11 1 2 11 17 1 7 4 23 1 2 19 17 1 7 8 21 1 2 19 18 1 7 15 22 1 2 25 18 1 7 16 24 1 2 31 17 1 7 18 22 1 2 35 17 1 7 20 22 1 2 40 17 1 7 25 30 1 3 1 16 1 7 37 22 1 3 12 10 1 8 1 2 1 3 12 7 1 8 33 3 1 3 13 2 1 8 33 2 1 3 14 4 1 8 40 3 1 3 22 7 1 9 9 19 1 3 40 3 1 9 17 17 1 4 13 16 1 9 22 19 1 5 2 4 1 9 25 19 1 5 7 8 1 9 18 18 1 5 8 4 1 10 17 15 1 5 12 4 1 10 17 16 1 5 12 8 1 10 17 13 1 5 14 8 1 10 31 13 1 5 14 7 1 11 1 1 1 5 20 8 1 11 34 2

Tiger Population In Pilibhit Forest Division 2010 page 18 Tiger Population In Pilibhit Forest Division 2010 page 19 Chapter 4

Table 3.3 Camera ID Longitude Latitude Trap location file used in 1 394861.1529 3171674.5940 Density 4.4.5 2 396322.2588 3169300.7560 4.0 3 398115.6845 3169463.4840 4 399881.4857 3170211.5190 5 397469.5474 3171325.1160 RESULTS 6 397144.9451 3173180.8770 7 399855.5346 3172249.2990 4.1 Capture Dynamics 8 400849.3990 3172613.2300 The total sampling effort of 1200 trap days, over 40 occasions, yielded 174 photographs 9 398742.4338 3176290.9670 (both flanks) of tigers at 23 out of the 30 trap stations (76.7% tiger photo capture 10 400707.9077 3176714.1790 success rate for trap stations) strategically placed in the 5 km² grids. 17.5% occasions 11 398897.2895 3174122.7740 harvested no captures of tigers. Number of tiger captures increased by 4% in the second quarter of the total occasions and afterward decreased by 5% and 6% in third 12 401965.4610 3175250.7620 and fourth quarter, respectively (Figure 4.1). A total of 11 tigers (> 1.5 years) were 13 404811.3456 3173491.2530 individually identified, comprising 4 males and 7 females (Figure 4.2). A tiger cub (<1 14 407313.7250 3173147.9150 year) with mother (PFT5) and another lactating female (PFT6) were also captured. In 15 405901.7232 3176766.4540 the standard X-matrix (Table 3.1), 73 photographs were used, which were contributed by 13 captures of PMT1 (Pilibhit Male Tiger no. 1) and PFT5 (Pilibhit Female Tiger no. 16 406036.1405 3177956.4960 5) each, 10 captures of PMT2, 8 captures of PFT6 and PFT7 each, 6 captures of PMT3, 17 407365.6787 3180700.5060 5 captures of PFT9, 4 captures of PFT10, 3 captures of PFT8, 2 captures of PFT11 and 18 408578.6089 3178000.8770 a single capture of PMT4 which might be a floating/transient tiger. Average trapping 19 408273.9377 3176864.4790 effort was 16.4 trap days per usable capture. In the capture file for Density 4.4.5 software, 84 photographs were used (Table 3.2) 20 408737.7754 3180652.7190 21 410716.7537 3176269.9380

22 411738.4632 3176822.3070 Caption 23 410782.0261 3174872.1180 24 413830.1340 3174587.5630 25 414609.3027 3175742.1430 26 413350.6762 3172879.8800 27 414933.7949 3172240.3600 28 416011.6060 3173780.6520 29 417698.9068 3173288.4890 30 417792.9770 3169689.9690

Tiger Population In Pilibhit Forest Division 2010 page 20 Tiger Population In Pilibhit Forest Division 2010 page 21 Figure 4.1 Percentage of captures of male and female in different quarters of total occasions

PMT1 (R) PMT1 (L) PMT4 (R) PMT4 (L)

PMT1 PMT2 PFT5 (R) PFT5 (L)

PMT2 (R) PMT2 (L) PFT5 PFT6

Figure 4.2 Photographs of individual tigers (Right & Left flanks) with a map of capture sites

PMT3 (R) PMT3 (L) PFT6 (R) PFT6 (L)

PMT3 PMT4 PFT7 (R) PFT7 (L)

Tiger Population In Pilibhit Forest Division 2010 page 22 Tiger Population In Pilibhit Forest Division 2010 page 23 PFT7 PFT8 PFT11 (R) PFT11 (L)

PFT8 (R) PFT8 (L) PFT11

PFT9 (R) PFT9 (L)

PFT9 PFT10

PFT10 (R) PFT10 (L)

Tiger Population In Pilibhit Forest Division 2010 page 24 Tiger Population In Pilibhit Forest Division 2010 page 25 Table 4.1 Model p-hat (c-hat) N-hat SE LCI UCI %CV DF Score 4.2 New Capture Saturation Selected model and tiger th M(h) jackknife 0.15 12 1.50 12 19 12.48 1 The number of new captures of tigers reached an asymptote on the 13 occasion of population with other study duration of 40 occasions with 27 usable photographic captures. First and second statistics in the study area M(h) Chao 0.15 12 1.32 11 19 11.02 1 occasion contributed 54.4% and 72.7% of new captures respectively while 7th occasion M(o) 0.17 11 0.09 11 11 0.01 0.91 yielded 81.8% of new captures of tigers. The total no. of captures are well distributed M(bh) 0.13 (0.25) 11 0.03 11 11 NA 0.89 along a linear trend line (R²=0.99). Figure 4.3 shows rate of tiger photographs and M(b) 0.31 (0.15) 11 0.00 11 11 NA 0.81 cumulative number of new captures in Pilibhit FD.

Figure 4.3 M (t+1)= No. of individuals, n= No. of captures, p-hat= Capture probability, c-hat= Recapture probability, Rate of tiger photographs and N-hat= Estimated tiger population, SE= Standard error, LCI= Lower value of 95% confidence interval, UCI= Upper value of 95% confidence interval, %CV= % coefficient of variation, DF= discriminant function, M (t+1)= cumulative number of new 11, Occasions= 40, Capture #= 73 captures in Pilibhit FD

4.5 Tiger Density (D-hat) Density of the tiger in the sampled area of Pilibhit FD was estimated to be 3.86±1.20 per 100 km² (D-hat±SE) using Maximum Likelihood method (Half normal, AIC=804.64) and it ranges 2.13-7.00 (95% Confidence Interval). Estimated density and their % CV, by available models in Density 4.4.5, were similar. Half normal model was selected as best fit on the basis of lowest coefficient of variation (31.09). Percent coefficient of variation (%CV) of estimated density by uniform model using Inverse Prediction (IP) method was found to be lowest (32.60) while % CV of estimated density by half normal (38.96) and negative exponential (36.10) models were higher. Estimated density by these three models was similar. Tiger density estimated by uniform model was found to be 3.29±1.01 per 100 km² (D-hat±SE) ranging between 1.77 and 6.14 (95% CI).

Using the conventional method of Mean Maximum Distance Moved (with habitat 4.3 Closure Test and Model selection masking), density was estimated to be 3.82±0.91 per 100 km² (3.53-6.18, 95% CI) with The closure test performed using Capture 2 supported the null hypothesis and an effective trapping area of 314.13 km². Tiger density was found to be 4.95±1.2 per assumes population closure (z= 2.96, p= 0.998). Closure test performed using 100 km² estimated by ½ MMDM method with habitat masking and it ranges between the software CloseTest (Stanley & Burnham 1999) also supported the population 4.58 and 8.00 per 100 km². Effective trapping area (minus non habitat) was estimated closure assumption with Stanley & Burnham test (χ= 11.81, df= 6, p=0.06). Test for to be 242.54 km². Percent coefficient of variation for estimated density by both the heterogeneity of trapping probabilities in population could not reject null hypothesis methods was almost same. of model M(o) vs. alternate hypothesis of model M(h) (χ²= 4.73, df=3, P= 0.19) and vs. M(t) in the test for time specific variation in trapping probabilities (χ²= 26.05, df= Estimated values of density by different methods and other statistics are summarized 39, P= 0.94). In the test for behavioral response after initial capture, null hypothesis in table 4.2. of model M(o) vs. alternate hypothesis of model M(b) was rejected (χ²= 3.72, df= Table 4.2 1, P= 0.05). In the goodness of fit test, null hypothesis of model M(h) vs. alternate Density Dens SE LCI UCI g0 SE σ SE % CV W SE ETA Tiger density and other hypothesis of model M(h) was not rejected (χ²= 52.24, df= 39, P= 0.08). M(h) model estimation statistics in the study area method was selected as the best fit model having highest value (1) in model selection criterion and it was followed by M(o), the null model, rated second with a value 0.91. Table 4.1 ML-nh (Half 3.86 1.20 2.13 7.00 0.07 0.01 2161.40 182.27 31.09 normal) summarizes selected model and criteria scores of individual models. IP-nh 3.29 1.07 1.77 6.14 0.04 0.01 4328.24 426.60 32.60 (Uniform) 4.4 Tiger Population (N-hat) MMDM 2.11 0.50 1.95 3.40 23.90 5.37 1.11 570.20 Population was estimated to be 12±1.50 (N-hat±SE) by the selected model and it MMDM-nh 3.82 0.91 3.53 6.18 23.90 5.37 1.11 314.13 ranges between 12 and 19 (95% Confidence Interval). This result (N-hat) was close to ½ MMDM 3.42 0.83 3.17 5.53 24.28 2.69 0.56 350.56 the number of individuals identified (Mt+1). Jackknife estimator for Mh model was selected to estimate N-hat (table 4.1). The average capture probability per occasion was ½ MMDM- 4.95 1.20 4.58 8.00 24.28 2.69 0.56 242.54 nh found to be 0.15 (p-hat).

Dens= density /100 km², SE= Standard error, LCI= Lower value of 95% confidence interval, UCI= Upper value of 95% confidence interval, g0= Capture probability function, σ= Spatial function, %CV= % coefficient of varia- tion, W= Buffer width in Km, ETA= Effective trapping area in km², ML-nh= Maximum likelihood-non habitat (with masking), IP-nh= Inverse prediction-non habitat, MMDM= Mean maximum distance moved – non habitat, ½ MMDM= ½ Mean maximum distance moved

Tiger Population In Pilibhit Forest Division 2010 page 26 Tiger Population In Pilibhit Forest Division 2010 page 27 Chapter 5

5.1 Capture Dynamics Capture dynamics revealed that 41% photographs were and overall probability of missing an individual was low (8.3%). The interval estimated contributed by four males and remaining 7 females by M(0), Mb and M(bh) models are likely to be an artifact of disparity in individual 5.0 contributed 59% of the total usable captures. In the capture rate which are influenced by age, sex, size and position of ranges in relation sampling grids, males having comparatively larger to traps among other ecological factors. These sampling uncertainties are often the territories are more likely to encounter at least one of cause of assumption violations. The estimated population in Pilibhit, when compared the trap stations. Same trend was reported by Azlan & to other reserves in the Terai Arc landscape, was lower than that of Kishanpur Wildlife DISCUSSION Sharma (2003), where a single male tiger contributed Sanctuary (18±4.2 per 100 km², N-hat±SE) and it was similar to that estimated in 66% of the total usable photographs. Increase in the and Katerniaghat WLS (14±1.2, 14±2.73, respectively) while number of captures in second quarter of total occasion it was also lower than that estimated in Corbett National Park, 19±0.54 (Jhala et al. may be an artifact of slight shifting of the traps on the basis of previous captures 2008). Tiger population estimated in Pilibhit FD was higher than that of Valmiki Tiger and encountered signs while decrease in number of captures in the third and fourth Reserve, at 3±1.1 per 100 km² (Jhala et al. 2008). quarter could probably be an artifact of trap shyness (Wegge et al. 2004; Sharma et al. 2009). Movement of villagers in the study area was restricted with the help of 5.5 Tiger Density (D-hat) Forest Department staff from the beginning of the reconnaissance survey to minimize Density estimation of tigers in the wild is critically important for scientific and the risk of camera unit theft and to increase robustness in data collection. The overall management purposes. Density estimated for tigers in the study area by different probability of capturing a tiger present in the study area (Mt+1 / N-hat) was high methods was more or less similar. Inverse Prediction (IP) method’s estimate was (91.7%), which is comparable with that reported by Sharma et al. (2008) in Kanha higher than that estimated by conventional Mean Maximum Distance Moved (MMDM National Park. Only one cub with mother and one lactating female was captured as without habitat masking) and lower than that estimated by ½ MMDM (without and young cubs are confined to a small area and rarely accompany mothers (Chundawat, with masking) and MMDM (with masking). The conventional parameterization of 2004). closed population models in terms of N (population) and p (capture probability) often remains incomplete due to negligence of space used. IP method uses an 5.2 New Capture Saturation alternative and different approach to fit a model to the trapping data that includes The curve of the cumulative number of new tiger captures stabilized on the 13th both density D and a spatial model of the trapping process (Efford, 2004). The basic occasion, suggesting the minimum number of trap days (13) required to capture all of concept is that if a trap is moved from an animals’ home range centre, it becomes the individual tigers in similar habitat. Wegge et al. (2004) reported stabilization of less likely to catch the animal. The relationship is based on the detection function the curve of cumulative number of new captures on the 5th day in the lowland area of with parameters g(0), which is the probability of capture in a trap at the home range Bardia National Park in intensive sampling. In the high tiger density area of Corbett centre and σ (the spatial scale over which capture probability declines). The search National Park in the western side of Terai Arc Landscape, this curve was stabilized only for parameter estimates (D, g(0), σ) that best match the field data is formalized in on the 40th occasion (Contractor, 2007). a procedure called Inverse Prediction (Pledger & Efford 1998; Efford, 2004). While density estimated by Maximum Likelihood method is higher than that estimated by IP 5.3 Closure Test and Model selection method it is similar to that estimated by conventional MMDM (with masking) method. Closure test supported the null hypothesis of population closure. Single capture of Spatially explicit Maximum Likelihood method estimates of density use the capture PMT4 which might be a floater and occasions with no harvesting were excluded from locations to estimate animal locations and spatially-referenced capture probability. the matrix for closure test in the software CloseTest 3.0, though capture history of The models being likelihood-based, allow use of Akaike’s Information Criterion or PMT4 was used for further analysis as this individual was present in the sampling other likelihood-based methods of model selection. Density is an explicit parameter, area during the study duration. Population was assumed closed geographically and and the evaluation of its dependence on spatial or temporal covariates is therefore demographically considering that the sampling area was the biggest forest patch of straightforward. Additional (nonspatial) variation in capture probability was modelled the division and also considering the social organization land tenure system of tigers as in conventional capture-recapture. The method can also test by simulation, using (Sunquist 1981; Smith 1993). Tigers less than 1 year of age were not included in the a model in which capture probability depends only on location relative to traps analysis. (Borchers & Efford, 2007). Density estimated by ML method may be considered most close to natural density of the tigers as it was almost equal to that estimated by After comparison with alternate models, Mh model was selected as it had the highest MMDM (with masking). Density estimated by MMDM method for tigers in Kanha generated score followed by null model. There was no effect of time (Mt) on the capture (Sharma et al. 2009), for jaguars Panthera onca (Soisalo & Cavalcanti 2006) and as probability for the study duration. White et al. (1982) cautions against the use of null reported by Dillon & Kelly (2008) for oceolots Leopardus pardalis was found close to model (Mo) if individual heterogeneity and trap response may be present. actual densities. These studies compared results obtained by MMDM method with that estimated using radio-telemetry. 5.4 Tiger Population (N-hat) Tiger population estimated by the models was similar (11-12) and their ranges are Tiger density estimated in Pilibhit FD by ½ MMDM (with masking) method was comparable. Although, percent coefficient of variation was slightly lower for the higher than that of (1.49±0.52 per 100 km², D-hat±SE) and estimate given by Mh (Chao), but owing to the robustness of the Mh (jackknife) Dudhwa National Park (4.91±0.31) and it was comparable with that of Kishanpur WLS estimate, it was used for other parameters (Karanth & Nichols 2002; Karanth et al. (6.23±0.76) and Katerniaghat WLS (5.01±0.52), while it was much lower than that 2004; Sharma et al. 2009). Average capture probability per occasion was fairly high estimated in Corbett National Park, 19±0.54 per 100 km² (Jhala et al. 2008).

Tiger Population In Pilibhit Forest Division 2010 page 28 Tiger Population In Pilibhit Forest Division 2010 page 29 Chapter 6 ©JOSEPH VATTAKAVEN/WWF-INDIA This report provides the first MANAGEMENT baseline estimates of tigers from Pilibhit and recommends IMPLICATIONS AND enhancing the protection and RECOMMENDATIONS status of this critical forest patch. This study provides a good estimate of the tiger density in the study area of Pilibhit forest division, which is also comparable with some of the better . This breeding population in Pilibhit is also likely to be serving as a source for the Surai range of Terai East FD in state, forests of North Kheri and South Kheri FDs. Decrease in anthropogenic pressure on this forest and an increase in protection level in this division would ensure the long term survival of this tiger population. Preservation and restoration of the corridor area between Shuklaphanta in Nepal and Kishanpur Wildlife Sanctuary via Laggabagga block and Haripur range of this division would facilitate movement of tigers between these reserves and exchange of genes. This study accounted for the presence of various ungulates in the study area such as chital, sambar, muntjac, hog deer, swamp deer, nilgai, wild pig and even four horned antelope (Annexure 2). The presence of four horned antelope was uncertain before this study and is probably the first record for the area (Krishna et al. 2009). Six random sightings of swamp deer (total 13 individuals) in the study duration show that Pilibhit harbours a small population of this endangered deer. These ungulates which serve as a prey base for tigers needs protection to proliferate and survive as a viable population in this division. Camera trapping was successful in producing photographic records of 11 individual tigers along with its co-predators, lesser carnivores, primates, ungulates, reptiles and birds. The study also recorded and obtained the first photographs of rusty spotted cat from Pilibhit, extending its distributional range. We suggest periodic monitoring of tigers and co-predators using such robust techniques in Pilibhit and more such potential areas in this landscape. Considering the biodiversity rich (Annexure 1, 2, 3 & 4) habitat of Pilibhit FD, fairly good tiger density, including breeding tigers, and its connectivity to other critical forest blocks in this landscape, we recommend enhancing the protection and status of this reserve forest at the earliest.

Tigress with cubs

Tiger Population In Pilibhit Forest Division 2010 page 30 Karanth K.U., Nichols J.D., Kumar S. & J.E. Hines. 2006. Assessing tiger population dynamics using photographic capture-recapture sampling. Ecology 87(11): 2925-2937. REFERENCES Krishna Y.C., Clyne P.J., Krishnaswamy J. & S.K. Narayanarao. 2009. Distributional and ecological review of the four horned antelope, Tetracerus quadricornis. Mammalia 73: 1-6. Annon. 2010. National Authority. http://www.projecttiger.nic.in/yearofcreation.asp McDougal C. 1977. The Face of the Tiger. Rivington Books, London. Annon. 2010. National Wildlife Data base Cell, Wildlife Institute of India. http://oldwww.wii.gov.in/nwdc/index.html Moultrie Feeders, Alabama. http://www.moultriefeeders.com

Azlan M.J. & S.K. Sharma. 2003. Camera trapping the indochinese tiger, Panthera tigris corbetti, in a secondary O’Brien T.G., Kinnaird M.F. & H.T. Wibisono. 2003. Crouching tigers, hidden prey: Sumatran tiger and prey forest in peninsular malaysia. The Raffles Bulletin of Zoology 51(2): 421-427. populations in a tropical forest landscape. Animal Conservation 6: 131–139.

Otis D.L., Burnham K.P., White G.C. & D.R. Anderson. 1978. Statistical inference from capture data of closed Borchers D.L. & M.G. Efford. 2007. Spatially explicit maximum likelihood methods for capture-recapture studies, populations. Wildlife Monographs 2: 1- 13. Biometrics online early doi: 10.1111/j.1541-0420.2007.00927.x Pledger, S. & M. Efford. 1998. Correction of bias due to heterogeneous capture probability in capture–recapture Chundawat R.S. 2004. The life of tiger. Territorial changeover. In Tiger: the ultimate guide: 46–78. Thapar V. studies of open populations. Biometrics 54: 888–898. (Ed.).New York: CDS Books. Pollock, K.H., Nichols J.D., C. Brownie & J.E. Hines. 1990. Statistical inference for capture-recapture experiments. Contractor D. 2007. Evaluating the effect of design and sampling intensity on estimating tiger population and Wildlife Monographs 107. density. M. Sc. Dissertation, Saurashtra University, Gujarat. 69 pp. Qureshi Q., Gopal R., Kyatham S., Basu S., Mitra A. & Y.V. Jhala. 2006. Evaluating tiger habitat at the tehsil level. Cooch E. & G.C. White. 2006. Program MARK: A gentle introduction.4th edition. TR-06/001, Project tiger directorate, Govt. of India and Wildlife Institute of India, India. www.phidot.org/software/mark/docs/book/ Rexstad E. & K. P. Burnham. 1991. User’s guide for interactive program CAPTURE. Colorado Cooperative Fish and Dillon A. & M.J. Kelly. 2008. Ocelot home range, overlap and density: comparing radio telemetry with camera Wildlife Research Unit, Fort Collins. trapping. Journal of Zoology 275: 391–398. Sanderson E., Forrest J., Loucks C., Ginsberg J., Dinerstein E., Seidensticker J., Leimgruber P., Songer M., Heydlauff Efford M.G. 2004. Density estimation in live-trapping studies. Oikos 106: 598-610. A., O’Brien T., Bryja G., Klenzendorf S. & E. Wikramanayake. 2006. Setting Priorities for the Conservation and Recovery of Wild Tigers: 2005–2015. The Technical Assessment., Wildlife Conservation Society, World Wildlife Efford M.G. 2009. DENSITY 4.4: software for spatially explicit capture–recapture. Department of Zoology, Fund, Smithsonian, and Save the Tiger Fund, Washington, D.C. University of Otago, Dunedin, New Zealand. http://www.otago.ac.nz/density. Schaller G.B. 1967. The deer and the tiger. University of Chicago Press, Chicago. Illinois.U.S.A. Efford M.G. Dawson D.K. & C.S. Robbins. 2004. Density: software for analysing capture-recapture data from passive detector arrays. Animal Biodiversity and Conservation 27: 217-228. Seidensticker, J., Christie S. & P. Jackson. 1999. Preface. In Riding the tiger: tiger conservation in human-dominated landscapes: xv–xix. Seidensticker, J., S. Christie and P. Jackson. (Eds). Cambridge: Cambridge University Press.

Graham K., Beckerman A.P. & S. Thirgood. 2005. Human–predator–prey conflicts: ecological correlates, prey Sharma R.K., Jhala Y.V., Qureshi Q., Vittakaven J., Gopal R. & K. Nayak. 2009. Evaluating capture-recapture losses and patterns of management. Biological Conservation 122: 159–171. population and density estimation of tigers in a population with known parameters. Animal Conservation 2009: 1-10. Griffiths M. & C.P. van Schaik. 1993. The impact of human traffic on the abundance and activity periods of Sumatran rainforest wildlife. Conservation Biology 7: 623-626. Smith J.L.D. 1993. The role of dispersal in structuring the Chitwan tiger population. Behaviour 124: 165-195.

Jhala Y.V., Gopal R. & Q. Qureshi (Eds). 2008. Status of tigers, copredators and prey in India. Dehradun: National Soisalo M.K. & S.M.C. Cavalcanti. 2006. Estimating the density of a jaguar population in the Brazilian Pantanal Tiger Conservation Authority & Wildlife Institute of India. TR08/001. 164pp. using camera-traps and capture-recapture sampling in combination with GPS radio-telemetry. Biological Conservation 129: 487-496. Johnsingh A.J.T. & A.S. Negi. 2003. Status of tiger and leopard in Rajaji-Corbett Conservation Unit, northern India. Biological Conservation 111: 385-393. Stanley T.R. & K.P. Burnham. 1999. A closure test for time specific capture–recapture data. Environmental and Ecological Statistics 6: 197–209. Johnsingh A.J.T., Ramesh K., Qureshi Q., David A., Goyal S. P., Rawat G.S., Rajapandian K. & S. Prasad. 2004. Conservation status of tiger and associated species in the Terai Arc Landscape, India. Wildlife Institute of India, Sunquist M.E. 1981. Social organization of tigers (Panthera tigris) in Royal Chitwan National Park, Nepal. India. Smithsonian Contributions to Zoology 336: 1-98

Karanth K.U. 1995. Estimating tiger (Panthera tigris) populations from camera trapping data using capture- Trolle M. & M. Kery. 2003. Estimation of Ocelot density in the pantanal using capture-recapture analysis of recapture models. Biological Conservation. 71: 333-338. camera-trapping data. Journal of Mammalogy 84: 607-614.

Karanth K.U. & J.D. Nichols. 1998. Estimation of tiger densities using Photographic captures and recaptures. Wang S.W. & D.W. Macdonald. 2006. Livestock predation by carnivores in Jigme Singye Wangchuck National Ecology 79(8): 2852-2862. Park, Bhutan. Biological Conservation 129, 558–565.

Karanth K. U. & J.D. Nichols. 2002. Monitoring tiger and their prey: A Manual for Researchers, Managers and Wegge P., Pokheral C. & S. R. Jnawali. 2004. Effects of trapping effort and trap shyness on estimates of tiger Conservationists in Tropical Asia. Centre for Wildlife Studies, India. abundance from camera trap studies. Animal Conservation 7: 251-256.

Karanth K.U. & J.D. Nichols. 1998. Estimation of tiger densities in India using photographic captures and White G.C., Anderson D.R., Burnham K.P. & D.L. Otis. 1982. Capture recapture and removal methods for sampling recaptures. Ecology 79: 2852–2862. closed populations. LA-8787-NERP, Los Alamos Nat. Lab., Los Alamos, New Mexico, USA.

Karanth K.U., Chundawat R.S., Nichols J.D. & N.S. Kumar. 2004. Estimation of tiger densities in the tropical dry Wikramanayake E., McKnight M., Dinerstein E., Joshi A., Gurung B. & D. Smith. 2004. Designing a conservation forests of Panna, Central India, using photographic capture–recapture sampling. Animal Conservation 7: 285–290. landscape for tigers in Human-Dominated environments. Conservation Biology 18: 839-844. Pictures of other important carnivores Activity Pattern of tiger and captured in camera traps leopard in Pilibhit forest division ANNEXURE 1 ANNEXURE 2 from Camera trap captures

The activity periods of tigers and leopards as indicated by their capture in camera trap stations during 22nd May to 30th June, 2010 was also analyzed. Data was filtered on the basis of date, time and camera ID imprinted on the photographs. A total of 97 and 15 photographs of tiger and leopard, respectively, were used. Leopards were captured more during the early hours of morning and peaks around 06:00 hours while movement of tiger peaks at 04.00 hours and then decreases. Leopards were also captured more in the early evening hours. An increase in tiger movement probably resulted in a decrease in leopard activity level between 19:00-23.00 hours. There were no captures of tigers or leopards during 08:00-17:00 hours. (Fig.1)

Leopard Fishing cat

Fig. 1: Activity pattern of tiger and leopard in Pilibhit FD during 22nd May to 30th June, 2010 from camera trap captures.

Jungle cat Sloth bear

Rusty spotted cat Otters

Tiger Population In Pilibhit Forest Division 2010 page 34 Pictures of ungulates captured in Pictures of birds captured in camera ANNEXURE 3 camera traps ANNEXURE 4 traps

Chital Hog Deer Muntjac

Lesser adjutant stork Indian peafowl

Swamp deer Wild pig Sambar

Red jungle fowl Red vented bulbul

Nilgai Four horned antelope

Green bee-eater Oriental magpie robin

Tiger Population In Pilibhit Forest Division 2010 page 36 Tiger Population In Pilibhit Forest Division 2010 page 37 Pictures of some of the mammals and ANNEXURE 5 reptile captured in camera traps

Hanuman langur Rhesus macaque Ratel Jackal

Common palm civet Small Indian civet Grey mongoose Monitor lizard

Indian porcupine Rufus tailed hare

Tiger Population In Pilibhit Forest Division 2010 page 38 Tiger Population In Pilibhit Forest Division 2010 page 39 Geo-coordinates of trap stations in Scientific names of carnivores, Pilibhit forest division ungulates, reptile, birds and other ANNEXURE 6 (Datum: WGS 84) ANNEXURE 7 mammals captured in camera traps

Camera ID Latitude (ddmmss) Longitude (ddmmss) Species Scientific name IUCN status WPA (Schedule) 1 28 40 05.0 79 55 20.5 (Carnivores) 2 28 39 00.5 79 56 17.0 Common leopard Panthera pardus Lower risk I 3 28 38 52.2 79 57 20.0 Common palm Paradourus hermaphroditus Lower risk II 4 28 39 20.8 79 58 29.4 civet 5 28 39 55.0 79 56 56.9 Fishing cat Prionailurus viverrinus Vulnerable I 6 28 40 54.7 79 56 45.3 Rusty spotted cat Prionailurus rubiginosus Vulnerable I 7 28 40 24.6 79 58 24.1 Jackal Canis aureus Lower risk II 8 28 40 47.4 79 59 12.1 Jungle cat Felis chaus Lower risk II 9 28 42 36.0 79 57 41.7 Ratel Mellivora capensis Lower risk I 10 28 42 51.6 79 58 53.8 Sloth bear Melursus ursinus Vulnerable I 11 28 41 25.6 79 57 48.0 Small Indian civet Viverricula indica Lower risk II 12 28 42 00.3 79 59 44.0 Smooth coated Lutrogale perspicillata Vulnerable I otter 13 28 41 07.0 80 01 26.6 (Others) 14 28 40 56.3 80 02 34.9 Indian porcupine Hystrix indica Lower risk IV 15 28 42 53.2 80 02 10.8 Grey mongoose Herpestes edwardsii 16 28 44 10.9 80 02 21.5 Hanuman langur Semnopithecus entellus Lower risk II 17 28 44 58.4 80 02 59.8 Rhesus macaque Macaca mulata Lower risk II 18 28 43 34.3 80 03 44.5 Rufus tailed hare Lepus nigricollis 19 28 42 57.5 80 03 33.1 (Ungulates) 20 28 44 09.7 80 04 29.2 Chital Axis axis Lower risk III 21 28 42 38.4 80 05 03.6 Four horned ante- Tetracerus quadricornis Vulnerable I 22 28 42 57.1 80 05 41.1 lope 23 28 41 49.6 80 05 07.0 Hog deer Axis porcinus Lower risk III 24 28 41 59.4 80 06 42.1 Muntjac Muntiacus muntjak Lower risk III 25 28 42 22.5 80 07 26.9 Nilgai Boselaphus tragocamelus Lower risk III 26 28 40 47.9 80 06 41.7 Sambar Cervus unicolor Lower risk III 27 28 40 28.7 80 07 40.0 Swamp deer Cervus duvaucelii Vulnerable I 28 28 41 20.3 80 08 18.3 Wild pig Sus scrofa Lower risk III 29 28 41 02.9 80 09 24.4 (Reptile) 30 28 39 54.9 80 08 27.6 Monitor lizard Varanus bengalensis Endangered I Scientific names of carnivores, ungulates, reptile, birds and other Study at a glance ANNEXURE 8 mammals captured in camera traps ANNEXURE 9 continued...

Common name (Birds) Scientific name Black francolin Francolinus francolinus Lesser adjutant Leptoptilos javanicus Indian peafowl Pavo cristatus Red jungle fowl Gallus gallus Red vented bulbul Pycnonotus cafer Camera testing Tiger pugmark Tiger Scat Tiger Rake marks Green bee-eater Merops orientalis Oriental magpie robin Copsychus saularis Indian nightjar Caorimulgus affinis Rufous treepie Dendrocitta vagabunda Lesser racket-tailed drongo Dicrurus remifer Emerald dove Chalcophaps indica

Black-rumped flameback Dinopium benghalense GPS Point Collection GIS work Grid map Pole fitting

Station clearing Deployed camera Spider web in lens Disturbed camera

Regular monitoring FD support Final downloading Visual documentation

Using Capture 2 CloseTest 3 MARK 4.1 Density 4.4.5

Tiger Population In Pilibhit Forest Division 2010 page 43 ©JOSEPH VATTAKAVEN/WWF-INDIA

Tiger Population In Pilibhit Forest Division 2010 page 44 STATUS OF TIGERS IN PILIBHIT FOREST DIVISION IND WWFINDIA.ORG 11 tigers Rusty spotted cat Study recorded the first of photos the smallest wildcat-rusty spotted cat Arc from the Terai Landscape extending its distributional range The number of individual of number The tigers identified in sampled the area 2

4.95/100 km

Number of camera of Number trap stations setup a for total1200 trap of days estimate to the tiger population in sampled area Pilibhit of Forest Division 30 camera trap stations trap 30 camera Estimated density tigers of in the sampled area © 1986 Panda Symbol WWF-World Wide Fnd For Nature (Formerly World Wildlife Fund) World Wide Fnd For Nature (Formerly © 1986 Panda Symbol WWF-World WWF-India Secretariat 172-B Lodi Estate New Delhi 110003 4150 4779 4150 4814 Fax: 011 011 Tel: