Status of Tigers in Sundarban Biosphere Reserve

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20 This report was printed on 100% recycled paper, in order to reduce the ecological impact and minimise paper wastage. WWF-India, 172 B Lodhi Estate, New Delhi 110 003, India Tel. +91 11 4361 6248 Fax. +91 11 4150 4779. For contact details and further information, please visit our website at www.wwfindia.org TIGERS 24-Parganas (South) Forest Division (South) Forest 24-Parganas + Status of Tigers in of Tigers Status SUBHRO SEN

Status of Tigers in Sundarban Biosphere Reserve 24-Parganas (South) Forest Division, West Bengal, India

Authors Sunit Kumar Das, Pankaj Kumar Sarkar, Ratul Saha, Pradeep Vyas, A. Anurag Danda and Joseph Vattakavan

Citation Das, S. K., Sarkar, P. K., Saha, R., Vyas, P., Danda, A. A., and Vattakavan, J. (2012). Status of Tigers in Sundarban Biosphere Reserve, 24-Parganas (South) Forest Division, West Bengal, India. World Wide Fund for Nature-India, New Delhi.

Cover Photo Pradeep Vyas

Maps Abhijit Choudhury

Illustrations Arnab Roy

Processing & Printing YES

Revised Edition, February 2013 © WWF-India, 2013 Status of Tigers in Sundarban Biosphere Reserve 24-Parganas (South) Forest Division, West Bengal, India PREFACE

Despite multiple challenges and demands on its resources, India's efforts to preserve its wildlife and its tigers are exemplary; yet, tigers remain in a precarious existence in India. Faced with threats of habitat loss and organised poaching, tiger populations need scientific monitoring, protection and trans-boundary cooperation among other things to ensure their long term survival. In this context, 'Status of Tigers in Sundarban Biosphere Reserve: 24-Parganas (South) Forest Division' is an important publication that looks into the development of a landscape specific tiger monitoring protocol. It is the first such publication from the Sundarbans.

Sundarbans is an important biodiversity area that spans across India and Bangladesh, well known for its unique and rich variety of flora and fauna as well as the scenic landscapes. Parts of Sundarbans in the two countries are listed as World Heritage Sites by UNESCO, underlining their importance as conservation landscapes. The Sundarbans is also the only mangrove habitat in the world to be home to tigers.

This report provides an overview of the first tiger monitoring study undertaken outside the Sundarban Tiger Reserve using camera traps and the resultant tiger population estimate. Besides tigers, the study has also highlighted the presence of other felids such as fishing cat, jungle cat, leopard cat, and possibly the first reported melanisitic leopard cat. It also looks at the challenges facing the Sundarbans.

I hope that this report will highlight the critical importance of scientific monitoring for better management of our wildlife. The efforts of the Sundarban Biosphere Reserve Directorate in putting in place the framework of cooperation between state and other partner entities are to be highly commended. Their success, as evidenced by this report’s contents and progress in the field, I hope will spur trans-boundary cooperative efforts, between India and Bangladesh. For it is only through such concerted efforts that our Protected Areas and the incredible diversity of flora and fauna they harbour, will find a safe and secure future and continue to thrive in the years to come.

Our thanks go out to all those who have helped put this study together; to those who care and support the cause of the tiger and its habitat.

Ravi Singh Secretary General and CEO WWF-India

ii PRADEEP VYAS

iii ACKNOWLEDGEMENTS

This exercise is supported by WWF-Sweden.

We are grateful to Mr. S.B. Mondal, PCCF & Chief Wildlife Warden, West Bengal, Mr. Samir Chandra Pal, ADFO and Mr. Ashis Mondal, RFO: 24 Parganas (South) Forest Division for the collaboration and logistic support.

Despite time constraints Dr. Somenath Bhattacharyya and Dr. Kakoli Sen Sarma, Institute of Environmental Studies and Wetland Management (IESWM) extended technical support in terms of chemical analysis of soil and water samples from all the camera trap stations as a contribution to this project. We are also grateful to the Director of IESWM, Mr. Arijit Banerjee for the whole hearted cooperation extended to the project.

We would like to thank the following Forest Department personnel in carrying out the study successfully.

Ramganga Range: Arup Kumar Maity (Forest Guard), Phonibhusan Maity (Forest Guard), Tapas Kumar Maity (Forest Guard), and Bhagirath Singh (Forest Guard)

Raidighi Range: Uttam Biswas (Deputy Ranger), Braja Nath Halder (Forest Guard), Subal Mondal (Boatman), Dilip Kumar Ganguli (Forest Guard), Dulal Mondal (Banshramik), Dibakar Das (Majhi), Madan Mohan Das (Forest Guard), Prithvi Raj Maity (Forest Guard)

Baruipur Range: Abu Jafar Molla (Forest Guard), Mujibar Rahaman Molla (Forest Guard), Joydeb Adhikari (Forest Guard)

Matla Range: Kajal Biswas (Beat Officer), Paresh Kulu (Banshramik), Monu Patra (Banshramik)

We would also like to thank the boat crew of MB Sundari, Sreedham Gayen, Ishwar Chandra Shaw, Dinanath Mondal and Ananta Mondal for their excellent services and on board hospitality.

Abishek Harihar and Dr. Jimmy Borah reviewed the report at very short notice for which we are grateful. Their comments have strengthened this report.

Special thanks are due to Dr. Bivash Pandav for his initial encouragement and guidance to undertake tiger monitoring study in the Sundarbans.

Last but not the least, we remain grateful to Mr. Ravi Singh, SG & CEO, WWF-India; Dr. Sejal Worah, Programme Director, WWF-India; and Dr. Dipankar Ghose, Director, Species and Landscapes Programme, WWF-India for their inputs.

iv CONTENTS Preface ii Acknowledgements iv Executive Summary vi Executive Summary in Bangla vii 1. INTRODUCTION 1 1.1 Indian Sundarbans 1 1.2 Tiger estimation in Sundarbans 2 2. STUDY AREA 5 2.1 Location 5 2.2 Physical features 6 2.3 Flora 8 2.4 Fauna 9 2.5 Human population 9 3. METHOD 10 3.1 Pre-field work 10 3.2 Reconnaissance survey 10 3.3 Data collection 13 3.4 Analytical details 14 3.4.1 Mark-Recapture approach 14 3.4.2 Method for density estimation 14 4. RESULTS 17 4.1 Capture dynamics 17 4.2 New capture saturation 19 4.3 CloseTest and model selection 20 4.4 Tiger population (N-hat) 21 4.5 Tiger density (D-hat) 21 4.6 Activity pattern of tigers 22 4.7 Anthropogenic pressures 23 5. MANAGEMENT IMPLICATIONS 24

REFERENCES 25 ANNEXURES 27 A. List of birds sighted 27 B. Captures of tigers 29 C. Captures of other felids 34 D. Captures of other mammals 35 E. Captures of birds 36 F. Fringe villages adjoining the study area 37 EXECUTIVE SUMMARY

The Sundarbans is the only mangrove forest in the world where the tiger is at the apex of the food chain. The Sundarbans ecosystem is subjected to variable salinity, periodic high tides and tidal inundations, occasional tidal surges and frequent flooding. The terrestrial fauna inhabiting this ecosystem is significantly different from their counterparts inhabiting other ecosystems. The tiger being an umbrella species, effective tiger conservation enhances survival prospects for other forms of biodiversity. Earlier tiger estimates in Sundarbans were based on pugmark methods, attacks on humans, interviews with local community, and radio telemetry based extrapolation. This study presents the findings of the first attempt to estimate the tiger population in the 24-Parganas (South) Forest Division of the Sundarban Biosphere Reserve using photographic capture-recapture analysis. As part of Phase-IV monitoring protocol to obtain minimum tiger numbers in the Indian Sundarbans, WWF-India in collaboration with the Sundarban Biosphere Reserve Directorate carried out the camera trapping study.

This study used remotely triggered camera traps and the capture-recapture framework to estimate the minimum population and density of tigers in two ranges of 24-Parganas (South) Forest Division. A total of 41 camera trap pairs were used in two ranges to cover about 982.56 sq km area. A total sampling effort of 600 trap days (20 camera trap stations, each operating for 30 occasions) at Ramganga range yielded 28 photographs (both flanks) of tigers. In Raidighi range, a total sampling effort of 714 trap days (21 camera trap stations, each operating for 34 occasions) yielded 71 photographs (both flanks) of tigers. Population is estimated to be 8.0±0.2 (N-hat±SE) individuals for Ramganga range and 13±3.5 (N-hat±SE) individuals for Raidighi range. Tiger density is estimated as 4.3 individuals/100 sq km at Ramganga range with an effective trapping area of 184.5 sq km and 7.08 individuals/100 sq km at Raidighi range with an effective trapping area of 141.3 sq km. In MLSECR (Maximum Likelihood Spatially Explicit Capture Recapture) analysis, estimated tiger density was 3.8 (±SE 1.5) individuals/100 sq km for Ramganga range and 5.2 (±SE 1.7) individuals/100 sq km for Raidighi range.

In addition to tigers, the study also photo captured cats viz. fishing cat, jungle cat and leopard cat, as well as prey and other species. Apart from this, melanistic leopard cat was also photo captured. It is the first photographic evidence of its presence in the Sundarbans. These results provide insights into the richness and diversity which imply that the 24-Parganas (South) Forest Division is a rich landscape. The study results justify the assertion that the landscape is crucial for the future of tigers, and management of biodiversity should extend beyond the borders of Protected Areas.

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vii `D ARNAUD BAUMANN

viii The Sundarbans in its entirety in India and Bangladesh is the biggest tract of estuarine mangrove forest in the world. The forest 1. INTRODUCTION spreads over the lower Gangetic delta which is flat and alluvial, and is intersected from north to south by several wide rivers and numerous winding creeks. Mangrove forest is a highly productive ecosystem and maintains a high standing biomass, comparable to many other forests of wet tropics (Alongi, 2009). The Sundarbans is considered as one of the seven most important wetlands globally (Junk et al. 2006) and is a Ramsar site in Bangladesh. Portions of the mangrove forest in India and Bangladesh are designated as UNESCO World Heritage Site in recognition of their high biodiversity as well as the occurrence of threatened species including the only population of royal Bengal tigers (Panthera tigris tigris) found in a mangrove habitat. This mangrove forest has been recognised as a wildlife conservation area of regional and international importance (Khan, 2011) and has been identified as Level I (18) Tiger Conservation Unit (TCU)1 (Wikramanayake et al. 1998). As mangrove habitat is naturally inaccessible, the region offers a protected environment with the potential for long term preservation of tigers (Seidensticker, 1987; Khan, 2011). Since the tiger is considered as a flagship species, effective tiger conservation enhances survival prospects of the unique biodiversity in the Sundarbans (Karanth et al. 2003).

1.1 Indian Sundarbans

The Sundarbans ecoregion in India spreads over an area of about 9630 sq km and is situated within 21°40'04”N and 22°09'21”N latitude, and 88°01'56”E and 89°06'01”E longitude, under the jurisdiction of the two 24-Parganas districts (South and North) of West Bengal. It lies at the apex of the Bay of Bengal and includes the areas bordering the rivers Hooghly, Muriganga, Saptamukhi, Thakuran, Gosaba, Bidya, Matla and Harinbhanga, known as the Hooghly-Matla estuarine complex. This ecosystem comprises about 55% forest land and 45% water spread area.

The Sundarbans ecosystem is subjected to tides twice a day. Change in water level determines the biological diversity of this ecosystem. A combination of (a) daily tidal water fluctuation, (b) variation in tidal amplitude induced by lunar cycle, and (c) 40% change in water flow and level during seasons, results in temporary inundation of the land; some areas daily, some areas only during spring tide, and other areas just during the monsoon season. The mangrove ecosystem also depends on components such as salt content in water and soil, duration of sunlight, contents of sediments and organic OF 10,000 SQ KM matters in water, temperature and density of sea water and freshwater (Khan, 2011).

OF SUNDARBANS The Sundarban forest in its entirety in India and Bangladesh is about 10,000 sq km, of which 60% lies in the southwest Bangladesh and the other 40% in southeast West Bengal in India (Hussain and Acharya, 1994). In India, the mangrove forest covers an MANGROVE area of about 4267 sq km which is administratively divided into Sundarban Tiger Reserve (STR; 2585 sq km w.e.f. 23.12.1973) and 24-Parganas (South) Forest Division FOREST IS IN (1682 sq km). Rest of the area is spread over parts of two districts viz. North 24- Parganas and 24-Parganas (South), covering 19 community development blocks with human settlements. Within 2,585 sq km of Tiger Reserve area, about 1,330.12 sq km INDIA of mangrove forest are demarcated as Core Area and declared as National Park since 1984, which is under strict management practices and kept free from all types of human interference. An area of 124.40 sq km within the Core Area is preserved as primitive zone in accordance with the United Nations Educational Scientific and Cultural Organization (UNESCO) World Heritage Site to act as gene pool. About 1,255 sq km of the Tiger Reserve area serves as the buffer zone, where limited fishing activities are permitted with prior permission of the Forest Department. Since 1989, the Indian Sundarbans as described in the preceding sentences, has been declared as 'Sundarban Biosphere Reserve' under the UNESCO Man and Biosphere Reserve (MAB) program.

1Level I Tiger Conservation Units (TCUs) offer the biggest probability of persistence of tiger populations over the long term and are essential components of a global tiger conservation strategy. Level I TCUs share the following attributes: large blocks of habitat suitable for tigers and prey with adequate core areas and low to moderate poaching pressure on tigers and prey species as a result of either remoteness or vigilant protection.

1 1.2 Tiger estimation in Sundarbans

The inclusion of the royal Bengal tiger to the list of endangered species in 1969 and later into the Red Data Book of the International Union for the Conservation of Nature and Natural Resources (IUCN) was due to an alarming decrease in numbers of free living tigers (Perry 1964, Gee 1964 and Seshadri 1968). Official reclamation of Sundarbans (O' Malley, L.S.S., 1914) might have threatened the tiger habitat and its numbers. Acting on recommendation of Guy Reginald Mountfort who led an expedition in 1967, IUCN and World Wildlife Fund (WWF) decided to sponsor an ecological and ethological survey of the situation in Sundarbans to assess the requirements of a viable tiger population without undermining the human utilisation of forest.

Studies on the Bengal tiger in the Indian Sundarbans date back to 1972. The then DFO Earlier tiger estimates were of undivided 24-Parganas Forest Division, A. B. Chaudhuri carried out ecological based on pugmark methods, attacks on humans, and studies and estimated the tiger population to be 112. Later in 1973, under the Indian interviews with local Governments’ Project Tiger, an area of 2585.10 sq km from the total mangrove area of community 4267 sq km was demarcated as the Sundarban Tiger Reserve. The tiger population increased from 181 in 1976, to 205 in 1979, and to 264 in 1983 (Chowdhury and Sanyal, 1985). Attempts and studies to estimate tiger numbers were mostly based on pugmark methods, attacks on humans, and interviews with local community (Karanth et al. 2003). The estimates were neither reliable total counts nor statistical samples and prone to human errors (Karanth, 1995). It has been believed that Sundarbans is the most difficult area to count tigers due to its thick vegetation, tides twice a day, and the danger of supposedly the most aggressive tigers in the world (Tilson, 2010). As more reliable tools like remote photography emerged as a key tool in wildlife research, Karanth et al. (2000) carried out the first camera trap survey in the Indian Sundarbans and estimated fewer than 100 tigers. This study had limitations as the camera traps were set up around sweet water ponds because no trails or roads were available due to the thick mangrove vegetation. Other studies in the Indian Sundarbans have been based on extrapolation from radio telemetry studies carried out by Jhala et al. (2011) at Sundarban Tiger Reserve estimating tiger population to be around 70. On this study, the Principal Chief Conservator of Forests of West Bengal expressed reservation regarding the methodology and sought refinement in the methodology with the involvement of other institutions.

2 None of the said studies or attempts to estimate tiger numbers was carried out in ST 24-Parganas (South) Forest Division which is also a tiger habitat. As a part of the Phase-IV tiger estimation in Sundarbans, WWF-India proposed to the Sundarban 1 Biosphere Reserve (SBR) Director that a larger area (24-Parganas [South] Forest Division and Sundarban Tiger Reserve) be covered under camera trapping exercise, for a more holistic estimate covering tiger habitat outside the Protected Area. The ATTEMPT TO SBR Director welcomed the idea and expressed that camera trapping exercise be initiated at 24-Parganas (South) Forest Division and subsequently at Sajnekhali ESTIMATE TIGER Wildlife Sanctuary through a collaboration between SBR and WWF-India. This report presents the findings of the first attempt to estimate the tiger population POPULATION USING in the 24-Parganas (South) Forest Division. As a part of Phase-IV tiger estimation in the Indian Sundarbans, WWF-India in collaboration with the Sundarban Biosphere PHOTOGRAPHIC Reserve carried out camera trapping exercise and estimated population using photographic capture-recapture analysis (Otis et al. 1978; Pollock et al. 1990). Traditionally, capture-recapture techniques (Seber, 1982) have been employed to CAPTURE-RECAPTURE estimate population parameters for fish, birds and small mammals which cannot be easily counted using distance sampling methods, such as point and line transects TECHNIQUES (Buckland et al. 1993). Recent analytical advances and the use of cameras make it possible to model biologically important factors like capture probabilities being heterogeneous among individual animals in a population, a result of social structure and behavioural response to trapping or temporal variation for rare and elusive species such as the tiger (Karanth and Nichols, 1998). Availability of various softwares such as CAPTURE (Rexstad and Burnham, 1991), MARK (Cooch and White, 2006) and Density (Efford, 2009) makes this technique statistically precise for estimation of populations (Nichols, 1992).

3 REMOTE PHOTOGRAPHY IN AID OF CONSERVATION

Wildlife photography for scientific studies dates back to the period 1872–1876 when C. Newbold, a corporal with the Royal Engineers on an oceanographic voyage by the English vessel HMS Challenger, photographed rookeries of rockhopper penguins (Eudyptes chrysocome) and breeding albatrosses (Diomedia sp.). GEORGE SHIRAS / NATIONAL GEOGRAPHIC STOCK In the late 1890s, George Shiras, for the first time, employed trip wires and a flash bulb to photograph numerous animals free from human presence. His photographs won a gold medal at the 1900 Paris World Exhibition and were published in National Geographic Magazine (Guggisberg, 1977; Shiras 1906, 1908, 1913).

The first purely scientific use of camera traps was in the 1920s, when Frank M. Chapman surveyed the big species on Barro Colorado Island in Panama using a trip-wire camera trap. Later in 1926, William Nesbit published the first detailed guide to outdoor photography or more specifically flashlight trap photography which includes brief biographies and literature citations of “Who's who in nature photography”. The book provided detailed descriptions of camera equipment, baits to attract different animals, high-speed flash apparatus and trip wires to release the shutter. This book had the first photograph of a tiger (P. tigris) from the wild by F. W. Champion of the Indian Forest Service. The photograph was captured with Nesbit's equipment. Champion (1928, 1933) published several books George Shiras photographs wildlife in natural environment at night. describing his experiences and includes many Location: Whitefish Lake, Michigan, USA. photographs of tigers and other animals such as the leopard (P. pardus), leopard cat (Felis bengalensis), jungle cat (F. chaus), fishing cat (F. viverrinus), striped hyena (H. hyaena), sloth bear (U. ursinus), and ratel (Mellivora capensis).

Gysel and Davis (1956) mention a photographic unit

GEORGE SHIRAS / NATIONAL GEOGRAPHIC STOCK designed to be housed in a wooden box powered by a 6-V battery. The unit operates when an animal pulls the bait attached to a string. Since then, technological advances have led to modern camera traps, automated digital devices with built in infrared sensor.

Camera traps have been used across a broad range of mammals and have been extremely effective in identifying individual species like tigers. Karanth (1995) and Karanth and Nichols (1998) developed a method to estimate tiger population using photographic capture-recapture analysis using camera traps in Nagarhole National Park in India which has been widely accepted. This approach has also been employed to estimate vital rates such as survival and recruitment in long-term open model capture- recapture sampling study to gain a full understanding of tiger population dynamics (Karanth et al. 2006). Besides individual identification or population estimation, camera trapping also provides other A doe and her fawns are caught by a remote camera. biological relevant information such as abundance Location: Michigan, USA (Carbone et al. 2001; O'Brien et al. 2003; Rowcliffe et al. 2008), temporal variation, distance of travel, activity pattern, habitat use and reproductive status of cryptic carnivores (Trolle and Kery, 2003).

4 2.1 Location 2. STUDY AREA The study area is spread over deltaic forested islands of Ramganga, Raidighi and Matla range of 24-Parganas (South) Forest Division and covers a land area of about 982.56 sq km (Fig 1). This forest is under Reserve Forest status and falls under 24-Parganas (South) district of West Bengal, India. The western part of the forest division is flanked by villages. In the eastern side of the forest division, Sundarban Tiger Reserve is located across river Matla.

Fig 1: Sundarban Biosphere Reserve

5 2.2 Physical features

The study area is characterised by a web of water channels. Three rivers dominate the study area, from west to east these are the Thakuran, Matla and Bidya. There are also a number of smaller rivers and channels. These rivers are tidal with some freshwater influence. The study area has diversity of habitats such as beaches, mangrove swamps and tidal flats. Most of the physical parameters of the water in the Sundarbans are governed by seasonal variability, with high salinity, pH and nutrient loads during the pre-monsoon period and the converse pattern during the monsoon.

The observed water pH (January) is generally between 7.38 and 8.31 in the two ranges of 24-Parganas (South) Forest Division. Water salinity is not uniform across the study area. Ajmalmari forest compartments bordering Kultali community development blocks are less saline relative to the Ajmalmari forest compartments lying alongside river Matla and Dhulibasani forest compartments. Chulkati forest compartments show a high salinity range relative to Ajmalmari and Dhulibasani forest compartments. The salinity during the study period was found to be in the range between 26.4 mg/kg and 31.2 mg/kg (Fig 2).

Nitrogen, phosphorus and potassium levels are not uniform. Dhulibasani and Chulkati forest compartments are rich in nitrogen as compared to the Ajmalmari forest compartments bordering the Kultali community development block. The nitrogen levels observed in the study area range between 110 mg/kg and 247 mg/kg (Fig 3). The southern part of the study area is rich in potassium relative to the northern part with levels between 351 mg/kg and 1346 mg/kg (Fig 4). From east to west, the level of phosphorus has been noticed to be in the range between 7 mg/kg and 18 mg/kg (Fig 5).2

Fig 2: Level of Water Salinity in the study area Note: Green pin: 26.4 mg/kg, Blue pin: 29.2 mg/kg, Red Pin: 31.2 mg/kg

2The Institute of Environmental Studies and Wetland Management under the Dept. of Environment, Govt. of West Bengal, as a contribution to this project, analysed water and soil samples from all camera trap stations.

6 Fig 3: Level of Nitrogen in the study area Note: Green pin: 110 mg/kg, White pin: 247 mg/kg

Fig 4: Level of Potassium in the study area Note: Green pin: 351 mg/kg, Red Pin: 1346 mg/kg

7 Fig 5: Level of Phosphorus in the study area Note: White pin: 7 mg/kg, Red Pin: 18 mg/kg

2.3 Flora

Forests in India have been classified into six major groups based on factors such as climate, soil, vegetation and biotic interference (Champion and Seth, 1968). These major groups are (i) moist tropical forests (ii) dry tropical forests (iii) montane sub tropical forests (iv) montane temperate forests (v) sub alpine forests and (vi) alpine 4 B forests. These major groups have been further divided into 16 type groups based on temperature and moisture content. A few of these type groups have been further TIDAL SWAMP divided into several subgroups. The type groups have been classified into 202 forest types and subtypes based on location specific climate factors. FOREST SUBDIVIDED INTO The mangrove forest of Sundarbans falls under the category of Group 4: littoral and swamp forests. This type group is further sub divided into (a) littoral forest and (b) MANGROVE, tidal swamp forest. The forest at 24-Parganas (South) Forest Division is classified under the sub group 4B tidal swamp forest, with sub-divisions namely, mangrove type SALT WATER TYPE 4B/TS1, 4B/TS2, salt water type mixed forests 4B/TS3 and brackish type 4B/TS4 MIXED FORESTS, AND (Champion and Seth, 1968). Tidal swamp forests are inundated during high tides and comprise the following BRACKISH WATER TYPE mangrove forest types and species:

Mangrove forest mostly comprises Acanthus ilicifolius, Aegialites rotundifolia, Avicennia alba, Brownlowia lanceolata, Bruguiera conjugata, Ceriops decandra, C. tagal, Excoecaria agallocha, Kandelia candel, Lumnitzera racemosa, Phoenix paludosa, Rhizophora sp., Sonneratia apetala, Xylocarpus granatum and X. mekongensis.

Saltwater mixed forest mostly comprises Aegialites rotundifolia, Amoora cucullata, Avicennia officinalis, Bruguiera conjugata, Ceriops decandra, Excoecaria agallocha, Heritiera fomes, Nypa fruticans and Xylocarpus mekongensis.

Brackish water mixed forest comprises Acanthus ilicifolius, Acrostichum aureum, Amoora cuculata, Avicennia officinalis, Brownlowia lanceolata, Bruguiera conjugata, Ceriops decandra, Excoecaria agallocha, Heritiera fomes, Phoenix paludosa, Nypa fruticans, Sonneratia apetala, S. caseolaris and Xylocarpus mekongensis.

8 2.4 Fauna

SUNIT KUMAR DAS The fauna of Sundarbans exhibit adaptability to this ecosystem subjected to adversities, significantly different from their counterparts inhabiting other ecosystems. The forests at 24-Parganas (South) Forest Division harbours four felid species viz. Bengal tiger (Panthera tigris), fishing cat (Prionailurus viverrinus), jungle cat (Felis chaus) and leopard cat (Prionailurus bengalensis). Diurnal smooth Indian otter (Lutra perspicillata) and the nocturnal small-clawed otter (Aonyx cinereus) are often sighted along the creeks. The only ungulates are spotted deer (Axis axis) and wild pig (Sus scrofa). The spotted deer are quite often seen in association with rhesus macaque (Macaca mulatta). Aquatic mammals that frequent the tidal waters include Indo-Pacific hump-backed dolphin (Sousa chinensis) and Irrawaddy dolphin (Orcaella brevirostris).

White-bellied sea eagle The area harbours 234 species of birds (Ghosh et al. in press). During the course of [Juvenile] (Haliaeetus the camera trapping exercise, 61 species of birds were sighted (Annexure A). Three of leucogaster) these, as per the IUCN Red List3, are Critically Endangered or Vulnerable (Table 1). The brown-winged kingfisher (Halcyon amauroptera) was commonly sighted during the exercise but is considered Near Threatened due to habitat destruction globally; it is also rarely sighted in Chilika.

Table 1: Critically Endangered and Vulnerable birds found in Sundarbans.

Common name Scientific name Status Critically White-rumped Gyps bengalensis vulture Endangered

Lesser adjutant stork Leptoptilos javanicus Vulnerable

Greater spotted Aquila clanga eagle Vulnerable

2.5 Human population

Open access to biological resources play an important role in supporting the livelihood of the burgeoning human population with an average density of 925 persons/sq km 103768 (2001 census) in the Indian Sundarbans. The dependence on biodiversity resource ranges from subsistence to commercial exploitation. A total of 22 villages with a population of 103768 (Annexure F) are situated adjoining the fringe of 24-Parganas

PERSONS LIVE IN 22 (South) Forest Division. The population density of these villages varied between 186 ADJOINING VILLAGES to 814 persons/sq km, with an average density of 557 person/sq km (2001 census). Fishing is the mainstay for the local communities dwelling here. The businesses in fringe villages deal in fish, crab, shrimp, and prawns. A total of 3793 Boat Licence Certificates (BLCs) have been issued by 24-Parganas (South) Forest Division to access fish resources from the forest.

3IUCN 2012. IUCN Red List of Threatened Species. Version 2012.1. . Downloaded on 19 September 2012.

9 The standard method of camera trapping in accordance with Capture-Recapture framework (Otis et al. 1978; Pollock et al. 1990) was followed to collect and 3. METHOD analyse data.

3.1 Pre-field work

As the Sundarbans ecosystem is subjected to tides twice a day with varying tide levels, there is high risk of the camera traps being inundated. The first step was to analyse the tidal fluctuation from the data available through tide tables (Survey of India, 2011) (Fig 7 and Fig 8). A high resolution image of the study area was also procured and processed for its use in the reconnaissance survey and thereafter. The study area was divided into grids of four sq km each, so as to systematically divide the area and help the team plan during reconnaissance survey and also to decide on the sites and minimum distance between camera trap stations.

3.2 Reconnaissance survey

Reconnaissance survey was carried out in different grids for potential camera trap locations. Geo-coordinates of the survey and suitable sites were recorded using a handheld Global Positioning System receiver (Garmin 72 H). These tracks and points were laid over gridded high-resolution image in Geographic Information System environment using MapInfo 8.5. The grids were selected based on the following criteria: (i) tiger pugmarks and (ii) comparatively high elevation areas unlikely to get submerged even during high tides. A total of 41 grids were selected at Ramganga and Raidighi range4 (Fig 6).

Fig 6: Reconnaissance survey with tracks laid over study area: 24-Parganas (South) Forest Division (Ramganga and Raidighi range)

The team avoided the grids with dense vegetation which made access difficult as well as those with excessive human disturbance. Considering the above criteria, a total of 20 suitable grid locations out of possible 51 grids across Ramganga and 21 suitable grid locations out of 48 grids across Raidighi range of 24-Parganas (South) Forest Division, were selected as trap stations.

4Herobhanga in Matla range was also surveyed at a later date and four camera trap stations were established. However, the session was aborted due to inclement weather and high water level.

9 2 Feb,

1.33 3.98

8 2 Feb,

1.06 4.26

7 2 Feb,

High

0.85 4.49

26 Feb,

0.74 4.63

25 Feb,

0.7

4.71

24 Feb,

0.69 4.76

23 Feb, Low

0.69 4.84

22 Feb,

0.74 4.89

21 Feb,

0.79 4.88

20 Feb,

0.93 4.77

19 Feb,

1.17 4.56

18 Feb,

1.46 4.26

17 Feb,

1.68 3.95

16 Feb,

1.62 3.81

15 Feb,

February which may have inundated the cameras.

1.31 4.01 th

14 Feb,

0.96 4.42

13 Feb,

0.67 4.76

12 Feb,

0.47 5.02

1 1 Feb,

0.36 5.07

10 Feb,

0.36 5.18

9 Feb,

period

5.22 0.47

8 Feb,

i 0.59 5.15

7 pl Feb,

0.81 4.97

6 Feb, am

1.07 4.71 February to check the status of camera traps and if required change height

S 5 Feb, th

4.4 1.36

4 Feb,

1.65 4.08

3 Feb,

1.91 3.74 Feb,2

3.51 Feb,1

1.81 3.59

31 Jan,

1.54 3.94

30 Jan,

1.29 4.25

29 Jan,

1.11 4.49

28 Jan,

4.66

27 Jan,

0.94 4.81

26 Jan,

0.89 4.65

25 Jan,

0.85 4.93

24 Jan,

0.81 5.02

23 Jan,

0.85 5.03

22 Jan, at Ramganga as per tide table

0.98 4.95

21 Jan,

1.18 4.76

20 Jan,

1.42 4.51

19 Jan,

1.58 4.26

18 Jan,

1.55 4.11

17 Jan,

4.2 1.35

16 Jan,

1.13 4.53

15 Jan,

0.96 4.78

14 Jan,

0.86 4.95

13 Jan,

0.82 5.06

12 Jan,

0.83 4.81

1 1 Jan,

0.82 5.09 Jan,10 0.89 5.05 6 5 4 3 2 1 0 the camera trap or select comparatively high elevation sites within same grid. This was due to water mark of 5.22 m on 9 Fig 7: Tidal fluctuation during sampling period Note: The high tidal mark ranges between 5.22 m and 3.51 m. Monitoring was carried out from 5

,30 ar M

1.58 3.94 ,29 ar M

1.31 4.17 ,28 ar M

4.4

High 1.06 ,27 ar M

4.6

0.85 ,26 ar M

0.73 4.74 ,25 ar M

0.69 ,24 ar M

0.71 4.814.81

,23 ar M Low

0.75 4.76 ,22 ar M

0.83 4.77 ,21 ar M

0.95 4.73 ,20 ar M

1.09 4.62 ,19 ar M

1.31 4.42 ,18 ar M

1.6

4.15 ,17 ar M

1.83 3.86 ,16 ar M

1.8

3.72 ,15 ar M

3.9

1.45 14 , ar M

March which may have inundated the cameras. 4.3

1.04 th ,13 ar M

0.66 4.71 ,12 ar M

0.35 5.06 ,11 ar M

5.29

0.16 ,10 ar M

5.37

0.12 9 , ar M

0.23 5.32 8 , ar M

0.47 5.24 7 , ar M

0.72 5.03 6 , ar M

1.03 4.73 5 , ar M

1.38 4.36 4 , ar M

February to check the status of camera traps and if required change height

1.73 3.96 ,3 ar M th

3.6

1.97 ,2 ar M

1.89 3.46 ,1 ar M

1.62 3.66 Feb,29

1.33 3.98 Feb,28

period 1.06 4.26 Feb,27

0.85 4.49 ng i Feb,26

0.74 4.63 Feb,25

0.7 4.71 ampl Feb,24

S 4.76 Feb,23

0.690.69 4.84 Feb,22

0.74 4.89 Feb,21

0.79 4.88 Feb,20

0.93 4.77 Feb,19

1.17 4.56 Feb,18

1.46 4.26 Feb,17

1.68 3.95 Feb,16

1.62 3.81 at Raidighi as per tide table Feb,15

1.31 4.01 Feb,14

0.96 4.42 Feb,13

0.67 4.76 Feb,12

0.47 5.02 Feb,11

5.07 Feb,10

0.360.36 5.18 9 Feb,

0.47 5.22 8 Feb,

0.59 5.15 7 Feb,

0.81 4.97 6 Feb,

1.07 4.71 Feb,5

4.4 1.36 Feb,4

1.65 4.08 Feb,3

1.91 3.74 Feb,2 2

Tidal fluctuation during sampling period

3.51 Feb,1 : 3.59 1.81 Note: The high tidal mark ranges between 5.o7 m and 3.46 m. Monitoring was carried out from 27 Fig 8 of camera trap or select comparatively high elevation sites within same grid. This was due to the water mark 5.37 m on 10 6 5 4 3 2 1 0

12 3.3 Data collection

Data collection was carried out on 30 occasions (days) at Ramganga range (23 January-21 February, 2012) and on 34 occasions at Raidighi range (11 February-16 March, 2012). Cuddeback (Attack) Digital Scouting cameras with heat-motion sensors were deployed to capture tigers and other fauna. The camera trap unit gets activated by the sensor that detects animal presence by sensing a moving heat source whose temperature is different than the Camera trap fitted with protective covering and ambient temperature. fastened onto shrub/pole in mangrove habitat The distance between two camera trap stations was kept at a minimum of 1 km to maximise the capture probability. At each station, two camera units were tied around tree trunks between 40 and 50 cm height from the ground in such a way that both flanks of the animal are captured. The camera delay was minimised to ensure photo captures of tigresses with cubs in case such an event occurred.

To maximise both tiger captures as well as recaptures, an olfactory lure was applied. All the camera Camera trap being deployed in presence trap stations at Ramganga and of forest department personell Raidighi range were monitored periodically to check the status of camera traps and if required change the height of camera trap or select comparatively high elevation sites within the same grid. This was due to the high water mark of 9th February and 10th March, which may have inundated some of the camera trap units. Every tiger captured in the camera traps was given a unique identification number after examining the stripe pattern on the flanks, limbs, forequarters and sometimes even tail of the tiger with Extract Compare V1.08 (Hiby et al. 2009) software as well as Attractants being applied on vegetation manually, e.g. T1 and onwards at camera trap station where T stands for tiger with their individual numbers respectively. Males were differentiated from females based on the presence of testicles. Prints of the captures were taken for ease of individual identification. Apart from tigers (Annexure B), the camera traps also photographed other felids (Annexure C), other mammals (Annexure D), and birds (Annexure E).

13 3.4 Analytical details

Abundance and Density of the tigers in the study area were estimated by using software MARK 6.1, CAPTURE 2, and Density 4.4.

3.4.1 Mark-Recapture approach

Data was analysed in Mark-Recapture framework5 which uses various suitable models under the basic assumptions of demographic and geographic closure6 (Otis et al. 1978; Karanth 1995; Karanth and Nichols 1998) at each forest range, given the unique habitat condition and dataset. To establish demographically closed population, closure test was performed using software CAPTURE 2 (Otis et al. 1978; White et al. 1982; Rexstad and Burnham 1991) and CloseTest (Stanley and Burnham 1999). CloseTest uses standard X-matrix7 (Table 2 and 3) where 1 signifies capture and 0 denotes no capture at a particular occasion of a session8. In closure test, value of p (detection probability) ≥ 0.05 favours the null hypothesis of population closure. The most appropriate population estimation (N-hat) model for a given data set (Otis et al. 1978) is selected after analysis of X-matrix using a series of hypothesis tests in software Mark 6.1. The best fit model has the highest DF9 (Discriminant Function) score value.

3.4.2 Method for density estimation

The density (D-hat) of tigers in the study area is estimated by the conventional method: estimated population size (N-hat) divided by the effective sampled area (A), where A is estimated by creating a buffer over the minimum convex polygon (MCP) over the camera trapping stations (A). However, since the area outside the camera trap polygon was either wide channels of water or disturbed area, it is assumed that the animals have not used this area. Hence, we consider minimum convex polygon as Effective Trapping Area (ETA). The MCP (Fig 9) is usually formed by joining the outermost camera traps stations on an Arc GIS platform. These calculations were performed using software Density 4.4. Effective trapping area without habitat masking10 at Ramganga and Raidighi range is 184.5 sq km and 141.3 sq km respectively. Density was also estimated through spatially explicit maximum likelihood methods (MLSECR) and compared with conventional estimate.

5 Mark-recapture is a method, for estimating population size that is based on ratios of marked to unmarked individuals. Following is a typical field experiment: A number of traps are positioned in the area to be studied. At the beginning of the study (on 1st day [j] =1), a sample size of n1 is taken from the population; the animals are marked for future identification, and then returned to population usually at same point where they were trapped. After allowing time for the marked and unmarked animals to mix on the following day (2nd day [j=2]), a second sample of n2 animals is then taken. The second sample normally contains both marked and unmarked animals. The unmarked animals are marked and all captured animals are again released back into population. This procedure continues for t (sampling period) periods where t≥2.

6The assumption of closure is reasonable, if the total number of individuals in a population has not changed through births, deaths, immigration or emigration over the time period of the study. The interval among sampling events is assumed to be short for the said events to happen.

7A capture-recapture matrix or a "frequency" format is in which each row represents a distinct capture history and is followed by an integer denoting how many individuals had that particular history.

8Session is the sampling period, where occasion is the sampling day of a sampling period.

9Discriminant function determines the variables discriminating between two or more groups.

10Habitat masking is done to subtract an area presumed as not being used by the subject in calculation of density using Density Software. It is presumed that the tiger used the channels within the two ranges (Ramganga and Raidighi).

14 Table 2: X-matrix for

individual tigers (8) of Tiger ID Occasions(30) Ramganga range for 30 T1 010000000000000100000000000000 1; occasions and 15 captures used in Capture, CloseTest T2 010000000000000000000000000000 1; and Mark 6.1 T3 010000000010000000010000000000 1; T4 000000000100000000000000000000 1; T5 000010010100000001000000000100 1; T6 000000001000000000000000000000 1; T7 000001000000000000000000000000 1; T8 000000010000000000000000000000 1;

Table 3: X-matrix for Tiger ID Occasions(34) individual tigers (10) of Raidighi range for 34 T9 1000100000000001000000000000000000 1; occasions and 24 captures used in Capture, CloseTest T10 0000000001000000000000000000000001 1; and Mark 6.1 T11 0000000000000001000000000100000000 1;

T12 0001000000000000000000000000000000 1; T13 0001001000100000100000000000100001 1;

T14 0010001000100011000000100000000001 1; T15 0000100000000000000000000000000000 1; 0000001000000000000000000000000000 1; T16 T17 0000001000000000000000000000000000 1;

T18 0000000000000000000100000000000000 1;

Fig 9: Camera trap stations Raidighi range, Ramganga range with minimum convex 24-Parganas (South) 24-Parganas (South) polygon (MCP)

15 Table 4: Capture history matrix used in Density 4.4

Ramganga range Raidighi range Session Tiger Occasion Trap ID Session Tiger Occasion Trap ID ID ID ID ID ID ID 1 T1 2 10 1 T9 1 7 1 T1 16 10 1 T9 5 5 1 T2 2 10 1 T9 26 6 1 T3 2 7 1 T10 10 8 1 T3 11 13 1 T10 34 1 1 T3 20 11 1 T11 16 20 1 T4 10 7 1 T11 26 21 1 T5 5 18 1 T12 4 10 1 T5 8 14 1 T13 4 18 1 T5 10 14 1 T13 7 9 1 T5 18 14 1 T13 11 9 1 T5 28 7 1 T13 17 9 1 T6 9 11 1 T13 20 17 1 T7 6 2 1 T13 29 9 1 T7 6 4 1 T13 34 9 1 T8 8 2 1 T14 3 14 1 T14 7 9 1 T14 11 14 1 T14 15 14 1 T14 16 14 1 T14 23 14 1 T14 34 14 1 T15 5 15 1 T16 7 9 1 T17 7 9 1 T18 20 18

16 4.1 Capture dynamics 4. RESULTS Ramganga range A total sampling effort of 600 trap days (20 camera trap stations, each operating for 30 occasions) at Ramganga range yielded 28 photographs (both flanks) of tigers. A total of eight out of 20 camera trap stations recorded the photographs. There were no tiger captures for 63.3% occasions. A total of eight tigers were individually identified from the trapping polygon in Ramganga. In the standard X-matrix (Table 4) of the software Density 4.4, 15 captures and recaptures of the tigers were used. The photographs represent five captures of T5, three captures of T3, two captures of T1 and single capture by T2, T4, T6, T7, and T8. (Fig 1o and Annexure B).

Fig 10: Capture and recapture of tigers at Ramganga

17 Raidighi range

A total sampling effort of 714 trap days (21 camera trap stations, each operating for 34 occasions) at Raidighi range yielded 71 photographs (both flanks) of tigers. A total of 13 out of 21 camera trap stations recorded the photographs. There were no tiger captures on 52.9% occasions. A total of 10 tigers were individually identified. In the standard X-matrix (Table 4) of the software Density 4.4, 26 captures and recaptures were used. This included seven captures of T13, seven captures of T14, three captures of T9, two captures of T10, two captures of T11 and single capture by T12, T15, T16, T17, and T18 (Fig 11 and Annexure B).

Fig 11: Capture and recapture of tigers at Raidighi

18 4.2 New capture saturation

At Ramganaga range, the number of new capture of tigers reached saturation level on the 10th occasion with 11 usable photographic captures over a sampling period of 30 days (Fig 12). The sampling period of Raidighi range was for 34 days. Captures of tigers reached the saturation level here on 21st occasion with 19 usable captures (Fig 13).

16 9

8 14

7 12

6 e 10

ur Total 5 capture pture capt

8 ca l a 4 w ot New Ne T 6 capture 3

4 2

2 1

0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Trap occasion

Fig 12: Camera trap exercise attains saturation point on 10th occasion at Ramganga range

30 12

25 10

e 20 8 Total

ur capture

apture capt

c l 15 6 a w New ot Ne T capture 10 4

5 2

0 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 Trap occasion

Fig 13: Camera trap exercise attains saturation point on 21st occasion at Raidighi range

19 4.3 CloseTest and model selection

The capture saturation at the two ranges was different. The capture dynamics might have been impacted by wide array of factors. For example, change in weather or tidal cycle or human presence or prey base activity might impact the activity of the tiger. The capture probabilities vary by individual animal and its behavioural response towards the camera trap. The probabilities might have also been impacted due to the animals' accessibility to camera traps (influenced by individual home ranges), its social dominance or difference in age or sex. It might also happen that the behaviour of the animal altered after its initial capture (Otis et al. 1978).

To estimate the population accurately, models based on unequal probabilities of capture were used. CloseTest was carried out using the capture-recapture matrix data of Ramganga and Raidighi ranges using the Program CAPTURE 2. Null hypothesis model Mo was tested against the models such as Mh (heterogeneity), Mb (behaviour) and Mt (time specific variation) [Table 5] to see the different aspects in capture probabilities in the capture-recapture dataset.

Table 5: Test of models for different aspects in capture probability

Discriminant Function Score (DF) Model Aspects Ramganga Raidighi

To see the heterogeneity in Mo vs Mh 0.77 1 capture probability

To see the behavioural Mo vs Mb 0.94 0.78 response after initial capture

To see the time specific Mo vs Mt 0.00 0.00 variation

On the basis of highest score of DF, the best fit model for Ramganga and Raidighi is Mb and Mh respectively. The details of the selected models are mentioned in the Table 6.

Table 6: Comparison of model and tiger population in the study area

Ramganga (at 95% confidence interval)

Model Mt+1 p-hat (c-hat) N-hat SE LCI UCI DF Score

Mb 8 0.18 8 0.2 8.0 8.9 0.94

Raidighi (at 95% confidenc e interval)

Mh 10 0.06 13 3.5 10.5 28.7 1

Note: p-hat= Capture probability, N-hat= Population size, SE= Standard Error, LCI= Lower value of 95% confidence interval, UCI= Upper value of 95% confidence interval, Mt+1= Number of animals captured, DF Score= Discriminant function.

20 4.4 Tiger population (N-hat)

Behaviour effect model (Mb) is the best fit model on the basis of highest DF probability value after analysis of the capture-recapture matrix through software Mark 6.1. It indicates the presence of behavioural response among the individuals generated from the matrix. Population is estimated to be 8.0±0.2 (N-hat±SE) individuals per 100 sq km for Ramganga range; it ranges between 8.0 and 8.9 at 95% confidence interval (Table 6). The average capture probability per occasion was found to be 0.18 (p-hat). At Raidighi range, population is estimated to be 13±3.5 (N-hat±SE) individuals per 100 sq km ranging between 10.5 and 28.7 at 95% confidence interval (Table 6). The average capture probability per occasion was found to be 0.06 (p-hat). At Herobhanga reserve forest, two tiger individuals (one male and one female) were captured, but the data was not sufficient to estimate the range and density.

4.5 Tiger density (D-hat)

Density estimation for tigers in the study area was performed using Effective Trapping Area (ETA), without habitat masking by using software Density 4.4. Density is estimated as 4.3 individuals/100 sq km at Ramganga with an effective trapping area of 184.5 sq km and 7.08 individuals/100 sq km at Raidighi range with 141.3 sq km.

It is expected that the captured individuals within the minimum convex polygon were also present outside. Density was calculated conventionally considering the total land mass of the study area. To reduce the possibility of overestimation, density was also calculated through Spatially Explicit Maximum Likelihood Methods (MLSECR) (Table 7).

Table 7: Density estimation of tigers in 24-Parganas (South) Forest Division, Sundarban Biosphere Reserve

Variables Ramganga Raidighi

Estimation Standard Error Estimation Standard Error

T otal land mass 204 sq km - 192 sq km -

Effective 184.5 sq km - 141.3 sq km - Trapping Area

Camera points 20 - 21 -

No. of trap - 714 - nights 600

Density Estimate 4.3 individuals/100 - 7.08 individuals/100 - with ETA sq km sq km

Density Estimate 3.9 individuals/100 - 5.2 indiv iduals/100 - with total land sq km sq km mass

De nsity estimates 3.8 individuals/100 1.5 5.2 indiv iduals/100 1.7 in MLSECR sq km sq km

21 4.6 Activity pattern of tigers

Information on temporal activity pattern of tigers was obtained through captured photographs using camera traps (Gompper et al. 2006; Long et al. 2008). The activity pattern of tigers, spotted deer, and wild pigs were studied through 107 captured photographs of tigers, 367 captured photographs of spotted deer and 702 captured photographs of wild pigs. Data was filtered with date and time imprinted on captured images. Tigers were found more active with a bimodal peak during morning (06:00 hrs-09:00 hrs) and late evening (18:00 hrs-20:00 hrs). Activity is less in midday hours (11:00 hrs- 16:00 hrs). The peak of tiger activity was observed at the same period as of spotted deer and wild pig activity peaks during the first morning hour peak. This is along expected lines as they are the primary prey of tigers in the Sundarbans (Fig 14).

25 Tiger (N=107) Spotted deer (N=367)

20 Wild pig (N=702)

% 15 rn patte 10 ity Activ

0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 : : : : : 00 : : : : : : : : : : : : : : : :

01:00 o2:00 03:00 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Time (Hours)

Fig 14: Activity pattern of tigers at 24-Parganas (South) Forest Division during January-March, 2012

22 4.7 Anthropogenic pressures

There are 22 forest fringe villages adjoining part of the study area with a population of more than one hundred thousand. These villages are rather remote and isolated and are beset with problems such as limited livelihood opportunities, high proportion of people belonging to backward communities, low levels of irrigation and cropping, and 63 per cent unemployment rate. The average poverty ratio in these villages is close to twice as much as compared to other villages away from the forest. All of these combine to exert significant pressure on the ecosystem due to high dependence on natural resources. In the 24-Parganas (South) Forest Division, of which the study area is a part, over 3700 boat licenses have been issued for fishing. Often, the licensees overstay or extract other resources in addition to fish. Illegal extraction of natural resources is in the form of honey, fuel wood beyond immediate requirement during fishing trips, and timber, all of which have a significant bearing on the habitat (Fig 15).

Sundarbans does not lend itself well to enforcement due to lay of the land and thus elimination of illegal anthropogenic pressure is difficult unless significant investments are made in information technology for remote monitoring. The other option to reduce this pressure is to make concerted investment in infrastructure development along with skill and capacity enhancement of the forest fringe population.

Pasur

Dhudul

Fuel wood

Garan poles

Honey

0 5 10 15 20 25 30 35

Fig 15: Proportion of illegal extraction Source: Forest Department offence records (2001-2007) Note: (i) Pasur - Xylocarpus sp. (ii) Dhudul - Xylocarpus sp. (iii) Garan - Ceriops decandra

23 Monitoring of an ecosystem is an important tool for the forest administration to assess the outcomes of prevailing 5. MANAGEMENT management practices. In a complex ecosystem like the Sundarbans – an active delta with erosion and accretion, and exhibiting impacts of climate change – monitoring is a challenge for any institution due to the fact that a significant portion of the landmass gets inundated twice a day during high tide. In the IMPLICATIONS Sundarbans, tigers are known to swim across rivers and have the ill repute of being man-eaters. These attributes pose additional challenges not only to monitor the tiger population but also to monitor all components of this mangrove ecosystem. Camera trapping emerged as a relatively safer and more scientific method for monitoring despite the many challenges.

The camera trap exercise in the Sundarbans is important for the forest administration as it provides key information about population size, density, dynamics and other important factors related to conservation of tigers and other associated species. Camera trap monitoring at regular intervals will provide valuable information about the effectiveness of management practices and enable corrective measures.

Over time, a larger sampled area comprising the Sundarban National Park and Basirhat range, and a better understanding of the ecosystem will help improve the outcome of the camera trap monitoring study. The database on tigers thus created will help in deciding on release site of a captured strayed individual tiger with scientific rigour. Also, over a period of time, insight can be gained as to why certain animals stray into the villages and from which compartments, enabling suitable proactive action. All these are envisaged to help in managing human tiger conflict over the long term.

The results of this camera trap study provide the first ever estimate of tiger density in 24-Parganas (South) Forest Division. Tiger density here is similar to that of the Sundarban Tiger Reserve despite the protection regime being dissimilar in the two forest units. Tiger density in Sundarban Tiger Reserve has been estimated to be 4.3/100 sq km (Jhala et al. 2011) while the density estimated from this study outside the Tiger Reserve is 4.5/100 sq km. The reasons for similar tiger density in both the forest units may be attributed to similar habitat characteristics along the latitude and probably similar prey densities which need to be further investigated. The outcome of this study has helped the forest administration in its decision to declare about 556 sq km of West Sundarban Reserve Forest as the West Sundarbans Wildlife Sanctuary. The protection regime is being upgraded as a consequence. Decrease in anthropogenic pressure and an increase in protection level followed by systematic monitoring in this forest division would help ensure the long term survival of this tiger population.

Earlier experience of establishing wildlife sanctuaries in the Sundarbans reflects the attempt to decrease anthropogenic pressures through exclusion of humans in the designated space. Offence records reflect that maintaining this exclusion is a challenge. However, on the other hand, if pre-existing resource extraction rights are not extinguished but on the contrary reinforced and regulated, it is likely that the beneficiary population would act as co-custodians akin to populations that maintain common property rights over certain spaces and resources by excluding others not considered as co-owners.

Given the precarious existence of tigers, besides scientific monitoring and protection, ensuring their long term survival in Sundarbans will require trans-boundary cooperation as ecosystems and species are not confined by political boundaries. Towards this end, a protocol on Conservation of Royal Bengal Tiger of the Sundarban was signed on 6 September 2011 between India and Bangladesh, to undertake bilateral scientific and research projects to promote the understanding and knowledge of the Sundarbans Royal Bengal Tiger and its habitat. Building on the protocol, bilateral initiatives like knowledge sharing, application of common protocol for estimation of tiger population, research and enhanced collaboration in forest protection need to be pursued.

24 REFERENCES

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26 Common English Name Species

Lesser whistling-duck Common shelduck Gadwal Fulvous breasted woodpecker Common flameback Dinopium javanense Common hoopoe Upupa epops

Indian roller Coracias benghalensis Common kingfisher Alcedo atthis Brown winged kingfisher Halcyon amauroptera White-throated kingfisher Halcyon smyrnensis Black-capped kingfisher Halcyon pileata

Collared kingfisher Todiramphus chloris Pied kingfisher Ceryle rudis

Green bee-eater Merops orientalis Rose-ringed parakeet Psittacula krameri Asian palm swift Cypsiurus balasiensis Spotted owlet Athene brama Spotted dove Streptopelia chinensis

Whimbrel Numenius phaeopus Numenius arquata Eurasian curlew Common greenshank Tringa nebularia Common sandpiper Actitis hypoleucos Little stint Calidris minuta Grey plover Pluvialis squatarola Little ringed plover Charadrius dubius

Grey-headed lapwing Vanellus cinereus Red-wattled lapwing Vanellus indicus Brown-headed gull Larus brunnicephalus Black-headed gull Larus ridibundus Common tern Sterna hirundo

27 Sr. Common English Name Species No.

31 Osprey Pandion haliaetus

32 Black kite Milvus migrans

33 Brahminy kite Haliastur indus 34 White-bellied sea eagle Haliaeetus leucogaster 35 White-rumped vulture Gyps bengalensis 36 Crested serpent eagle Spilornis cheela

37 Shikra Accipiter badius 38 Greater spotted eagle Aquila clanga

39 Peregrine falcon Falco peregrinus 40 Darter Anhinga melanogaste r 41 Indian cormorant Phalacrocorax fuscicollis

42 Intermediate egret Mesophoyx intermedia 43 Grey heron Ardea cinerea

44 Purple heron Ardea purpurea

45 Little heron Butorides striatus 46 Black-crowned night heron Nycticorax nycticorax 47 Black bittern Dupetor flavicollis 48 Lesser adjutant stork Leptoptilos javanicus

49 Long-tailed shrike Lanius schach tricolor 50 Black-hooded oriole Oriolus xanthornus 51 White-throated fantail Rhipidura albicollis 52 Black drongo Dicrurus macrocercu s 53 Asian paradise-flycatcher Terpsiphone paradisi 54 Common iora Aegithina tiphia 55 Common starling Sturnus vulgaris

56 Great tit Parus major 57 Oriental white-eye Zosterops palpebrosus 58 Jungle babbler Turdoides striatus 59 Purple-rumped sunbird Nectarinia zeylonica 60 Forest wagtail Dendronanthus indicus

61 White wagt ail Motacilla alba

28 ANNEXURE B CAPTURES OF TIGERS

29 T5

30 T9

T10

T11

T12

31 T13

T14

T15

T16

32 T17

T18

T19

T20

33 ANNEXURE C CAPTURES OF OTHER FELIDS

Fishing cat (Prionailurus viverrinus)

Jungle cat (Felis chaus)

Leopard cat (Prionailurus bengalensis)

Melanistic leopard cat (Prionailurus bengalensis)

34 ANNEXURE D CAPTURES OF OTHER MAMMALS

Spotted deer (Axis axis)

Wild pig (Sus scrofa)

Rhesus macaque (Macaca mulatta)

Small Indian civet (Viverricula indica)

35 ANNEXURE E CAPTURES OF BIRDS

Eurasian curlew (Numenius arquata)

Oriental magpie robin (Copsychus saularis)

White-breasted waterhen (Amaurornis phoenicurus)

Coucal (Centropus sinensis)

36 ANNEXURE F FRINGE VILLAGES ADJOINING THE STUDY AREA

Community No of Population Development Village Area (sq km) Population Household density/sq km Block

Deulbari Debipur 7.5991 939 5622 740 Purba Gurguria 7.0507 849 4733 671 Madhya Gurguria 6.1801 682 3975 643

Debipur Gurguria 13.0606 1885 10015 767 Kultali Bhubaneshwari 8.5641 1068 6201 724 Maipit 5.7878 724 4712 814 Binodpur 6.5596 808 4849 739 Baikuntapur 8.8416 1079 6711 759 Kisorimohanpur 7.6485 975 5889 770 Bhubaneshwari 1.2322 169 833 676 Char Ambikanagar 1.1273 72 451 400 Purba 6.5188 599 3587 550 Sripatinagar Sridhar Nagar 9.4995 1109 6694 705 Upendra Nagar 8.9052 752 4311 484 Rakhalpur 9.3878 986 5348 570 Daspur 0.829 68 395 476 Patharpratima Uttar 5.558 570 3038 547 Surendranagar Dakshin 6.1338 654 3882 633 Surendranagar Indrapur 7.6983 759 4591 596 Sitarampur 6.2489 772 4090 655 Gobardhanpur 6.4305 213 1193 186 Basanti Lot No 126 45.5839 2604 12648 277 Total 186.4453 18336 103768 557

37 THE TEAM

Field team at Ramganga range

Field team at Nolgora Beat

Field team at Bonnie Camp

38 STUDY AT A GLANCE

1. Tide analysis

2. Study area 3. Selection of comparatively with four sq km high elevation zones grids

4. Presence of tiger pugmarks 5. Grids with human presence were 6. Clearance around avoided camera trap station

7. Camera testing 8. Deployment of camera traps 9. Attractants being applied

10. Monitoring during high tide 11. Forest Department 12. Camera traps being checked and data downloading personnel check camera trap station

13. Closed Capture 14. Density 4.4 15. Program Capture 16. Program Mark

39 DEMYSTIFYING CAMERA TRAPPING

1. What is camera trapping? Camera trapping or 'remote photography' is the use of motion triggered cameras that automatically capture images of whatever moves in front of these. The cameras record data non-invasively without the subject being captured or the researcher being present. These are used in pairs to record both flanks of the individual and estimate population parameters using capture-recapture studies.

2. What is capture-recapture? In capture-recapture studies, population is estimated based on ratios of marked to unmarked individuals. The individuals that can be easily identified from photographs are taken up in capture-recapture studies. Animals are captured and marked on several trapping occasions. The number of marked individuals that are recaptured allows the researcher to estimate the total population size based on the samples' overlap.

3. Why is camera trapping considered an improvement over the traditional method of tiger estimation? Traditionally tigers have been estimated through pugmark census. The pugmark impression method on scientific scrutiny has been found to be error prone. With technological advances in photography, automated digital devices with built in infrared sensor have been used to estimate tiger population. As tigers have unique stripe patterns, population estimated through capture-recapture studies is more reliable.

4. Where was this study carried out and when? The study area is spread over two ranges of 24-Parganas (South) Forest Division in Sundarban Biosphere Reserve and covers a land area of about 982.56 sq km. The study was carried out in phases between 23 January and 21 February 2012 at Ramganga range, and between 11 February and 16 March 2012 at Raidighi range.

5. Is the study area under Sundarban Tiger Reserve? The study area is outside the Sundarban Tiger Reserve.

6. Are there earlier studies or estimates for tigers available for this area? This is the first attempt to estimate tiger population in this area using camera traps. However, it was believed that 24-Parganas (South) Forest Division had 20-25 tigers.

7. What type of camera has been used? Cuddeback Attack (1149) cameras have been used. These are automated remote cameras with heat-motion sensors.

8. Were the cameras deployed at random? No, the cameras were deployed using grid based sampling. The total area was divided into four sq km grids. Distance between two camera trap stations was at least one km so as to maximise capture of new individuals.

9. Where and how were the cameras deployed and positioned? The cameras were deployed in comparatively high elevation areas. The distance of the camera from the ground was maintained at a height of about 40-50 cm. The minimum distance maintained between two opposite cameras was three to five meters.

10. What were the determining factors for deploying the cameras? The cameras were deployed depending on the indirect signs of tigers such pugmarks, and indirect signs of its prey base such as hoofmarks and pellets. The areas with high anthropogenic pressure and dense vegetation were avoided.

11. How many cameras were deployed in each range? In Raidighi and Ramganga ranges respectively, 21 and 20 pairs of camera traps were deployed.

12. What other species were camera trapped apart from tigers? Apart from tigers, felids like fishing cat, jungle cat and leopard cat were camera trapped. Ungulates like spotted deer and wild pig along with avifauna were also camera trapped. Apart from this, a melanistic leopard cat was also photo captured. This is the first photographic evidence of its presence in the Sundarbans.

13. “Melanism in Leopard cat”- What is it? Is it common? The cat family exhibits a wide diversity of coat colour and pattern, including melanism. Melanism occurs as a common polymorphism and is a development of dark coloured pigment in skin.