tigers status of tigers in sundarban biosphere reserve...
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982.56 sq km+20
+1080 1682 sq km
TIGERS
STUDY AREA
AREA OF 24-PARGANAS (SOUTH)FOREST DIVISION
WORK DAYS TO COMPLETETHE STUDY
STATUS OF TIGERS IN , WEST BENGAL, INDIA
SUNDARBAN BIOSPHERE RESERVE, 24-PARGANAS (SOUTH) FOREST DIVISION
Status of Tigers in , West Bengal, India
Sundarban Biosphere Reserve24-Parganas (South) Forest Division ®
Status of Tigers in Sundarban Biosphere Reserve
, West Bengal, India24-Parganas (South) Forest Division
THIS REPORTHAS BEEN PRODUCED INCOLLABORATIONWITH:
REPORTIND
2013
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AuthorsSunit Kumar Das, Pankaj Kumar Sarkar, Ratul Saha, Pradeep Vyas, A. Anurag Danda and Joseph Vattakavan
CitationDas, S. K., Sarkar, P. K., Saha, R., Vyas, P., Danda, A. A., and Vattakavan, J. (2012). Status of Tigers in 24-Parganas (South) Forest Division, West Bengal, India. World Wide Fund for Nature-India, New Delhi.
Cover PhotoPradeep Vyas
MapsAbhijit Choudhury
IllustrationsArnab Roy
Processing & PrintingYES
Revised Edition, February 2013© WWF-India, 2013
Sundarban Biosphere Reserve,
Status of Tigers in Sundarban Biosphere Reserve 24-Parganas (South) Forest Division, West Bengal, India
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Status of Tigers in 24-Parganas (South) Forest Division
Sundarban Biosphere Reserve, West Bengal, India
PREFACEDespite 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.
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Ravi Singh Secretary General and CEO WWF-India
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ACKNOWLEDGEMENTSThis 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.
CONTENTSPreface ii
Acknowledgements iv
Executive Summary vi
Executive Summary in Bangla vii
1. INTRODUCTION 11.1 Indian Sundarbans 1
1.2 Tiger estimation in Sundarbans 2
2. STUDY AREA 52.1 Location 5
2.2 Physical features 6
2.3 Flora 8
2.4 Fauna 9
2.5 Human population 9
3. METHOD 103.1 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 174.1 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 27A. 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
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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EXECUTIVE SUMMARY
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The Sundarbans in its entirety in India and Bangladesh is the biggest tract of estuarine mangrove forest in the world. The forest 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)
1and has been identified as Level I (18) Tiger Conservation Unit (TCU) (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).
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) 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 matters in water, temperature and density of sea water and freshwater (Khan, 2011).
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 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 (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 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.
1.1 Indian Sundarbans
1 Level 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.
40% OF 10,000 SQ KM OF SUNDARBANS
MANGROVE FOREST IS IN
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1. INTRODUCTION
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1.2 Tiger estimation in Sundarbans
The inc
Studies
ology with the involvement of other institutions.
lusion 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.
on the Bengal tiger in the Indian Sundarbans date back to 1972. The then DFO of undivided 24-Parganas Forest Division, A. B. Chaudhuri carried out ecological studies and estimated the tiger population to be 112. Later in 1973, under the Indian Governments’ Project Tiger, an area of 2585.10 sq km from the total mangrove area of 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 method
Earlier tiger estimates were based on pugmark methods,
attacks on humans, and interviews with local
community
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None of the said studies or attempts to estimate tiger numbers was carried out in 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 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 coveri
lities 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).
ng tiger habitat outside the Protected Area. The SBR Director welcomed the idea and expressed that camera trapping exercise be initiated at 24-Parganas (South) Forest Division and subsequently at Sajnekhali Wildlife Sanctuary through a collaboration between SBR and WWF-India.
This report presents the findings of the first attempt to estimate the tiger population 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 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 estimate population parameters for fish, birds and small mammals which cannot be easily counted using distance sampling methods, such as point and line transects (Buckland et al. 1993). Recent analytical advances and the use of cameras make it possible to model biologically important factors like capture probabi
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ATTEMPT TO ESTIMATE TIGER
POPULATION USING PHOTOGRAPHIC
CAPTURE-RECAPTURE TECHNIQUES
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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.). 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 describing his experiences and includes many 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 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 biological relevant information such as abundance (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).
REMOTE PHOTOGRAPHY IN AID OF CONSERVATION
George Shiras photographs wildlife in natural environment at night. Location: Whitefish Lake, Michigan, USA.
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A doe and her fawns are caught by a remote camera. Location: Michigan, USA
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2.1 Location
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.
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Fig 1: Sundarban Biosphere Reserve
2. STUDY AREA
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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
218 mg/kg (Fig 5).
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.
Note: Green pin: 26.4 mg/kg, Blue pin: 29.2 mg/kg, Red Pin: 31.2 mg/kgFig 2: Level of Water Salinity in study areathe
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Fig 4: Level of Potassium in the study areaNote: Green pin: 351 mg/kg, Red Pin: 1346 mg/kg
Fig 3: Level of Nitrogen in the study areaNote: Green pin: 110 mg/kg, White pin: 247 mg/kg
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2.3 Flora
Forests in India have been classified into six major groups based on factors 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 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 divided into several subgroups. The type groups have been classified into 202 forest types and subtypes based on location specific climate factors.
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) 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 4B/TS1, 4B/TS2, salt water type mixed forests 4B/TS3 and brackish type 4B/TS4 (Champion and Seth, 1968).
Tidal swamp forests are inundated during high tides and comprise the following 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.
such as
Fig 5: Level of Phosphorus in the study areaNote: White pin: 7 mg/kg, Red Pin: 18 mg/kg
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TIDAL SWAMP FOREST SUBDIVIDED INTO
MANGROVE,SALT WATER TYPE
MIXED FORESTS, AND BRACKISH WATER TYPE
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2.4 Fauna 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).
The area harbours 234 species of birds (Ghosh et al. in press). During the course of the camera trapping exercise, 61 species of birds were sighted (Annexure A). Three of
3these, as per the IUCN Red List , 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.
3 IUCN 2012. IUCN Red List of Threatened Species. Version 2012.1. <www.iucnredlist.org>. Downloaded on 19 September 2012.
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 (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 (South) Forest Division. The population density of these villages varied between 186 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.
White-bellied sea eagle [Juvenile] (Haliaeetus
leucogaster)
103768 PERSONS LIVE IN 22
ADJOINING VILLAGES
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Table 1: Critically Endangered and Vulnerable birds found in Sundarbans.
Common name Scientific name Status
White-rumpedvulture
Gyps bengalensisCriticallyEndangered
Lesser adjutant stork Leptoptilos javanicus Vulnerable
VulnerableGreater spottedeagle
Aquila clanga
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3. METHOD 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 analyse data.
the
(Fig 6)
with
3.1 Pre-field work
3.2 Reconnaissance survey
As 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.
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
4Ramganga and Raidighi range .
The team avoided the grids 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.
4 Herobhanga 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.
Fig 6: Reconnaissance survey with tracks laid over study area: 24-Parganas (South) Forest
Division (Ramganga and Raidighi range)
11
thN
ote
: T
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7:
Tid
al
flu
ctu
ati
on
du
rin
g s
am
pli
ng
per
iod
at
Ra
mg
an
ga
as
per
tid
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ble
5.05
5.09
4.81
5.06
4.95
4.78
4.53
4.24.1
14.2
64.5
14.7
64.9
55.0
35.0
24.9
34.6
54.8
14.6
64.4
94.2
53.9
43.5
93.5
13.7
44.0
84.4
4.71
4.97
5.15
5.22
5.18
5.07
5.02
4.76
4.42
4.01
3.81
3.95
4.26
4.56
4.77
4.88
4.89
4.84
4.76
4.71
4.63
4.49
4.26
3.98
0.89
0.82
0.83
0.82
0.86
0.96
1.13
1.35
1.55
1.58
1.42
1.18
0.98
0.85
0.81
0.85
0.89
0.94
11.1
11.2
91.5
41.8
12
1.91
1.65
1.36
1.07
0.81
0.59
0.47
0.36
0.3
60.4
70.6
70.9
61.3
11.6
21.6
81.4
61.1
70.9
30.7
90.7
4 0
.69 0
.690.7
0.74
0.85
1.06
1.33
Jan,10
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Sa
mp
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g p
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d
Hig
h
Lo
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6 5 4 3 2 1 0
12
Fig
8:
Tid
al
flu
ctu
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on
du
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g s
am
pli
ng
per
iod
at
Ra
idig
hi
as
per
tid
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thN
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5.o
7 m
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m.
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m 2
7 F
ebru
ary
to
ch
eck
th
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mer
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nd
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ed c
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rap
or
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3.59 3.5
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5.18
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4.42
4.01
3.81
3.95
4.26
4.56
4.77
4.88
4.89
4.84
4.76
4.71
4.63
4.49
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3.98
3.66
3.46
3.6
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4.36
4.73
5.03
5.24
5.32
5.37
5.29 5.0
6
4.71
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1.97
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0.72
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31.6
1.31
1.09
0.95
0.83
0.75
0.71
0.69
0.73
0.85
1.06
1.31
1.58
0123456
Feb,1
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Sa
mp
lin
g p
erio
d
13
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 (
, which may have inundated some o
the
et al.
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 ambient temperature.
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 trap stations at Ramganga and 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
th thwater mark of 9 February and 10 March
f 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 tiger with Extract Compare V1.08 (Hiby
2009) software as well as manually, e.g. T1 and onwards 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).
Camera trap being deployed in presence of forest department personell
Camera trap fitted with protective covering and fastened onto shrub/pole in mangrove habitat
Attractants being applied on vegetation at camera trap station
14
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.
5Data was analysed in Mark-Recapture framework which uses various suitable models 6under the basic assumptions of demographic and geographic closure (Otis
score value.
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.
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
10masking 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.
3.4.1 Mark-Recapture approach
3.4.2 Method for density estimation
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).
7CloseTest uses standard X-matrix (Table 2 and 3) where 1 signifies capture and 0 8denotes no capture at a particular occasion of a session . 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
9software Mark 6.1. The best fit model has the highest DF (Discriminant Function)
Hence, we consider minimum convex polygon as Effective Trapping Area (ETA). The MCP (Fig 9)
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
stin the area to be studied. At the beginning of the study (on 1 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
ndand unmarked animals to mix on the following day (2 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.
6 The 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.
7 A 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.
8 Session 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).
15
Tiger ID Occasions(30)
T1 010000000000000100000000000000 1;
T2 010000000000000000000000000000 1;
T3 010000000010000000010000000000 1;
T4 000000000100000000000000000000 1;
T5 000010010100000001000000000100 1;
T6 000000001000000000000000000000 1;
T7 000001000000000000000000000000 1;
T8 000000010000000000000000000000 1;
Tiger ID Occasions(34)
T9 1000100000000001000000000000000000 1;
T10 0000000001000000000000000000000001 1;
T11 0000000000000001000000000100000000 1;
T12 0001000000000000000000000000000000 1;
T13 0001001000100000100000000000100001 1;
T14 0010001000100011000000100000000001 1;
T15 0000100000000000000000000000000000 1;
T16 0000001000000000000000000000000000 1;
T17 0000001000000000000000000000000000 1;
T18 0000000000000000000100000000000000 1;
Raidighi range,24-Parganas (South)
Ramganga range24-Parganas (South)
Fig 9: Camera trap stations with minimum convex
polygon (MCP)
Table 3individual tigers (10) of
Raidighi range for 34occasions and 24 capturesused in Capture, CloseTest
and Mark 6.1
: X-matrix for
Table 2: X-individual tigers (8) of
Ramganga range for 30occasions and 15 captures
used in Capture, CloseTestand Mark 6.1
matrix for
16
Table 4: Capture h in Density 4.4 istory matrix used
Ramganga range
Session ID
Tiger ID
Occasion ID
Trap ID
1 T1 2 10
1 T1 16 10
1 T2 2 10
1 T3 2 7
1 T3 11 13
1 T3 20 11
1 T4 10 7
1 T5 5 18
1 T5 8 14
1 T5 10 14
1 T5 18 14
1 T5 28 7
1 T6 9 11
1 T7 6 2
1 T7 6 4
1 T8 8 2
Raidighi range
Session ID
Tiger ID
Occasion ID
Trap ID
1 T9 1 7
1 T9 5 5
1 T9 26 6
1 T10 10 8
1 T10 34 1
1 T11 16 20
1 T11 26 21
1 T12 4 10
1 T13 4 18
1 T13 7 9
1 T13 11 9
1 T13 17 9
1 T13 20 17
1 T13 29 9
1 T13 34 9
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
17
4.1 Capture dynamics
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 and Annexure B).1o
4. RESULTS
Fig 10: Capture and recapture of tigers at Ramganga
18
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 ( and Annexure B).Fig 11
Fig Capture and recapture of tigers at Raidighi11:
19
4.2 New capture saturation
At Ramganaga range, the number of new capture of tigers reached saturation level on ththe 10 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 sttigers reached the saturation level here on 21 occasion with 19 usable captures
(Fig 13).
thFig 12: Camera trap exercise attains saturation point on 10 occasion at Ramganga range
0
2
4
6
8
10
12
14
16
Ne
w c
ap
tur
e
Trap occasion
Totalcapture
Newcapture
To
tal
ca
ptu
re
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 301 2 3 4 5 6 7 8 9
9
8
7
6
5
4
3
2
1
0
stFig 13: Camera trap exercise attains saturation point on 21 occasion at Raidighi range
12
10
8
6
4
2
0
30
25
20
15
10
5
0
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33
Ne
w c
ap
tur
e
Trap occasion
Totalcapture
Newcapture T
ota
l c
ap
tur
e
Table 6: Comparison of model and tiger population in the study area
20
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
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.
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.
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.
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
Table 5: Test of models for different aspects in capture probability
Model Aspects
Discriminant FunctionScore (DF)
Ramganga Raidighi
Mo vs Mh To see the heterogeneity incapture probability
0.77 1
Mo vs Mb To see the behaviouralresponse after initial capture
0.94 0.78
Mo vs Mt
To see the time specificvariation
0.00
0.00
Raidighi (at 95% confidence interval)
Mh 10 0.06 13 3.5 10.5 28.7 1
Model p-hat (c-hat)
Mb 0.18 8 0.2 8.0 0.94 8 8.9
N-hat SE LCI DF Score
Mt+1 UCI
Ramganga (at 95% confidence interval)
21
4.4 Tiger population (N-hat)
4.5 Tiger density (D-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 individuals
but the data was not sufficient to estimate the range and density.
Density estimation for tigers in the study area was performed using Effective
(Table 7).
tiger (one male and one female) were captured,
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: Density estimation of tigers in 24-Parganas (South) Forest Division, Sundarban Biosphere Reserve
Estimation Standard Error Estimation
EffectiveTrapping Area
184.5 sq km - 141.3 sq km
Camera points 20 - 21
No. of trapnights 600 - 714
Density Estimatewith ETA 4.3
sq kmindividuals/100 - 7.08 individuals/100
sq km
Density Estimatewith total landmass
3.9 individuals/100sq km
- 5.2 individuals/100sq km
Density estimatesin MLSECR 3.8 individuals/100
sq km 1.5 5.2 individuals/100
sq km
Standard Error
-
-
-
-
-
1.7
Ramganga
Raidighi
Total land mass 204 sq km - 192 sq km -
Variables
22
4.6 Activity pattern of tigers
Information on temporal activity pattern of
served 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 ).
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 ob
14
Fig t 24-Parganas (South) Forest Division during January-March, 201214: Activity pattern of tigers a
01:
00
o2
:00
03
:00
04
00
:
05
00
:
06
00
:
07
00
:
08
00
:
09
00
:
100
0:
110
0:
120
0:
130
0:
140
0:
150
0:
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0:
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0:
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0:
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0:
20
00
:
21
00
:
22
00
:
23
00
:
24
00
:
Ac
tiv
ity
pa
tte
rn
%
Time (Hours)
25
20
15
10
5
0
Tiger (N=107)
Spotted deer (N=367)
Wild pig (N=702)
23
4.7 Anthropogenic pressures
.
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.
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)
Honey
Garan poles
Fuel wood
Dhudul
Pasur
Fig Proportion of illegal extraction
Source: Forest Department offence records (2001-2007)
15:
Note: (i) Pasur - Xylocarpus sp. (ii) Dhudul - Xylocarpus sp. (iii) Garan - Ceriops decandra
0 5 10 15 20 25 30 35
24
5. MANAGEMENT IMPLICATIONS
Monitoring of an ecosystem is an important tool for the forest administration to assess the outcomes of prevailing 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 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.
25
REFERENCESAlongi, D. M. (2009). 'Paradigm Shifts in Mangrove Biology', In: Perillo, G., Wolanski, E., Cahoon, D. and Brinson, M. (eds) Coastal
Wetlands: An Integrated Ecosystem Approach; London, Elsevier.
Buckland, S. T., Anderson, D. R., Burnham, K. P. and Laake, J. D. (1993). Distance sampling: Estimating Abundances of Biological Populations. Chapman and Hall, London. 446 p.
Burnham, K. P., Anderson, D. J. and Laake, J. L. (1980). Estimation of density from Line Transect sampling of biological populations. Wildlife Monographs, 72. The Wildlife Society, Washington D. C.
Carbone, C., Christie, S., Conforti, K., Coulson, T., Franklin, N., Ginsberg, J. R., Griffiths, M., Holden, J., Kinnaird, M., Laidlaw, R., Lynam, A., MacDonald, D. W., Martyr, D., McDougal, C., Nath, L., O'Brien, T., Seidensticker, J., Smith, J. L. D., Tilson, R. and Wan Shahruddin, W. N. (2002). The use of photographic rates to estimate densities of cryptic mammals: response to Jennelle et al. Animal Conservation, 5: 121–123.
Champion, H. G. and Seth, S. K. (1968). A Revised Survey of Forest Types of India. Natraj Publishers, Dehradun. 404 p.
Champion, F. W. (1928). With a camera in tiger-land. Chatto and Windus, London, England
Champion, F. W. (1933). The jungle in sunlight and shadow. Chatto and Windus, London, England.
Chowdhury, M. and Sanyal, P. (1985). Use of electroconvulsive shocks to control tiger predation on human beings in Sundarbans Tiger Reserve. Tigerpaper, 12 (2):1-5.
Gee, E. (1964). The Wildlife of India. Collins, London.
Ghosh, A., Sanchez-Triana, E. and Joshi, A. eds. (in press). State of Art Report on Biodiversity in Indian Sundarbans. World Wide Fund for Nature-India, New Delhi.
Gompper, M., Kays, R., Ray, J., Lapoint, S., Bogan, D. and Cyan, J. (2006). A comparison of Noninvasive Techniques to Survey Carnivore Communities in northeastern North America. Wildlife Society Bulletin, 34: 1142–1151.
Guggisberg, C. A. W. (1977). Early wildlife photographers. Taplinger Publ. Co., New York, NY.
Gysel, L. W. and Davis, E. M. (1956). A simple automatic photographic unit for wildlife research. Journal of Wildlife Management, 20:451–453.
Huapeng, C., Freng, L., Huai, W., Jianzhang, M., Xibo, J. and Chunmei, L. (1997). Assessment of Three Methods for Estimating Abundance of Ungulate Populations. Journal of Forestry Research, Vol.8, No. 2.
Hussain, Z. and Acharya, G. (1994). (eds.) Mangroves of the Sundarbans. Volume two : Bangladesh. IUCN, Bangkok, Thailand. 257 p.
Jhala, Y. V., Qureshi, Q., Gopal, R. and Sinha, P. R. (eds.). (2011). Status of the Tigers, Co-predators, and Prey in India. National Tiger Conservation Authority, Govt. of India, New Delhi, and Wildlife Institute of India, Dehradun. 302 p.
Junk, W. J., Brown, M. T., Campbell, I-C., Finlayson, M., Gopal, B., Ramberg, L. and Warner B. G., (2006). The comparative biodiversity of seven globally important wetlands: a synthesis. Aquatic Science, 68: 400–414.
Karanth, K. U. (1991). Ecology and Management of the tiger in tropical Asia. In: Maruyama, N., B. Bobek, Y. Ono, W. Reglin, L. Bartos and R. Ratcliffe (eds.),. Wildlife Conservation: Present Trends and Perspectives for the 21st Century, Tokyo, Japan Wildlife Research Center. 156 p.
Karanth, K. U. (1995). Estimating tiger (Panthera tigris) populations from camera-trap data using capture-recapture models. Biological Conservation, 71, 333–338.
Karanth, K. U. and Nichols, J. D. (1998). Estimating tiger densities in India from camera trap data using photographic captures and recaptures. Ecology, 79 (8): 2852-2862.
Karanth, K. U. and Nichols J. D. (2000). Ecological Status and Conservation of Tigers in India. Final Technical Report to the Division of International Conservation, US Fish and Wildlife Service, Washington DC and Wildlife Conservation Society, New York. Centre for Wildlife Studies, Bangalore, India.
Hiby, L., Lovell, P., Patil, N., Kumar, N. S., Gopalaswamy, A. M., and Karanth, K. U. (2009). A tiger cannot change its stripes: using a three-dimensional model to match images of living tigers and tiger skins. Biology Letters, 5(3): 383–386.
26
Karanth, K. U., Nichols, J. D., Seidensticker, J., Dinerstein, E., Smith, J. L. D., McDougal, C., Johnsingh, A. J. T., Chundawat, R. S. and Thapar, V. (2003). Science deficiency in conservation practice: the monitoring of tiger populations in India. Animal Conservation, 6: 141–146.
Karanth, K. U., Nichols, J. D., Kumar, S. and Hines, J. E. (2006). Assessing tiger population dynamics using photographic capture-recapture sampling. Ecology, 87(11): 2925-2937.
Khan, M. (2011). Tigers In The Mangroves: Research and Conservation of the Tiger in The Sundarbans of Bangladesh. Aranyak Foundation. 189 p.
Long, R. A., Mackay, P., Zielinski, W. J. and Ray, J. (eds.) (2008). Non-invasive Survey Methods for Carnivores. Island Press, Washington, 400 p.
Meyer, W. B. and Turner II, B. L. (1992). Human population growth and global land-use/cover change. Annual Review of Ecology and Systematics, 23, 39–61.
Margules, C. R. and Pressey, R. L. (2000). Systematic conservation planning. Nature, 405: 243-253.
Nichols, J. D. (1992). Capture-recapture models: using marked animals to study population dynamics. Bioscience, 42, 94–102.
O'Brien, T. G., Kinnaird, M. F. and Wibisono, H. T. (2003). Crouching tigers, hidden prey: Sumatran tiger and prey populations in a tropical forest landscape. Animal Conservation, 6:131–139.
O' Malley, L. S. S., (1914). Bengal District Gazetteers, 24 Parganas. The Bengal Secretariat Book Depot, Calcutta.
Otis, D. L., Burnham, K. P., White, G. C. and Anderson, D. R. (1978). Statistical inference from capture data on closed animal populations. Wildlife Monograph, 62: 1–135.
Perry, R. (1964). The world of the tiger. Cassell & Company Ltd., London. 263 p.
Pollock, K. H., Nichols J. D., Brownie, C. and Hines, J. E. (1990). Statistical inference for capture-recapture experiments. Wildlife Monographs, 107.
Rexstad, E. and Burnham, K. P. (1991). User's guide for interactive program CAPTURE. Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins.
Rowcliffe, J. M., Field, J. S., Turvey, T. and Carbone, C. (2008). Estimating animal density using camera traps without the need for individual recognition. Journal of Applied Ecology, 45(4):1228–1236.
Stanley, T. R. and Burnham, K. P. (1999). A closure test for time specific capture–recapture data. Environmental and Ecological Statistics, 6: 197–209.
Seber, G. A. F. (1982). The estimation of animal abundance and related parameters. Second Edition. MacMillan, New York,
New York, USA.
Seidensticker, J. (1987). The Bangladesh Sundarbans as wildlife habitat: looking ahead. In: J. Seidensticker, R. Kurin, and A. Townsend, eds. The Commons of South Asia: Societal Pressure and Environmental Integrity in the Sundarbans. The International Center, Smithsonian Institution, Washington, D. C.
Seshadri, B. (1968). The Indian tiger fights for its survival: Animals, London. pp-414-419.
Shiras, G. (1906). Photographing wild game with flashlight and camera. National Geographic Magazine, 17:366–423.
Shiras, G. (1908). One season's game bag with a camera. National Geographic Magazine, 19:387–446.
Shiras, G. (1913). Wild animals that took their own pictures by day and by night. National Geographic Magazine, 24:763–834.
Survey of India. (2011). Hugli River Tide Tables for Sagar, Gangra, Haldia, Daimon Harbour, Mayapur and Garden Reach. Geodetic and Research Branch of Survey of India, Dehradun. 175 p.
Tilson, R. and Nhyus, J. P. (2010). Tigers of the world: The Science, Politics and Conservation of Panthera tigris. Elsevier,
U.S.A.: 552 p.
Trolle, M. and Kery, M. (2003). Estimation of Ocelot density in the Pantanal using capture-recapture analysis of camera-trapping data. Journal of Mammalogy, 84: 607-614.
White, G. C., Anderson D. R., Burnham, K. P. and Otis, D. L. (1982). Capture recapture and removal methods for sampling closed populations. LA-8787-NERP, Los Alamos Nat. Lab., Los Alamos, New Mexico, USA.
Wikramanayake, E. D., Dinerstein, E., Robinson, J. G., Karanth, U., Rabinowitz, A., Olson, D., Mathew, T., Hedao, P., Conner,
M., Hemley, G. and Bolze, D. (1998). An ecology-based method for defining priorities for large mammal conservation: the tiger as case study. Conservation Biology, 12 :865–878.
Web references:
Cooch, E. and White, G. C. (2006). Program MARK: A gentle introduction. 4th edition. Available at http://www.phidot.org/software/mark/docs/book/ [Accessed 28 August 2012].
Efford, M. G. (2009). DENSITY 4.4: software for spatially explicit capture–recapture. Department of Zoology, University of Otago, Dunedin, New Zealand. Available at http://www.otago.ac.nz/density/ [Accessed 28 August 2012].
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Common English Name Species
Lesser whistling-duck
Common shelduck
Gadwal
Fulvous breasted woodpecker
Common flameback
Common hoopoe
Indian roller
Common kingfisher
Brown winged kingfisher
White-throated kingfisher
Black-capped kingfisher
Collared kingfisher
Pied kingfisher
Green bee-eater
Rose-ringed parakeet
Asian palm swift
Spotted owlet
Spotted dove
Whimbrel
Eurasian curlew
Common greenshank
Common sandpiper
Little stint
Grey plover
Little ringed plover
Grey-headed lapwing
Red-wattled lapwing
Brown-headed gull
Black-headed gull
Common tern
Sterna hirundo
Larus ridibundus
Larus brunnicephalus
Vanellus indicus
Vanellus cinereus
Charadrius dubius
Pluvialis squatarola
Calidris minuta
Actitis hypoleucos
Tringa nebularia
Numenius arquata
Numenius phaeopus
Streptopelia chinensis
Athene brama
Cypsiurus balasiensis
Psittacula krameri
Merops orientalis
Ceryle rudis
Todiramphus chloris
Halcyon pileata
Halcyon smyrnensis
Halcyon amauroptera
Alcedo atthis
Coracias benghalensis
Upupa epops
Dinopium javanense
28
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
Osprey
Black kite
Brahminy kite
White-bellied sea eagle
White-rumped vulture
Crested serpent e agle
Shikra
Greater spotted eagle
Peregrine falcon
Darter
Indian cormorant
Intermediate egret
Grey heron
Purple heron
Little heron
Black-crowned night heron
Black bittern
Lesser adjutant stork
Long-tailed shrike
Black-hooded oriole
White-throated fantail
Black drongo
Asian paradise-flycatcher
Common iora
Common starling
Great tit
Oriental white-eye
Jungle babbler
Purple-rumped sunbird
Forest wagtail
White wagtail
Pandion haliaetus
Milvus migrans
Haliastur indus
Haliaeetus leucogaster
Gyps bengalensis
Spilornis cheela
Accipiter badius
Aquila clanga
Falco peregrinus
Anhinga melanogaster
Phalacrocorax fuscicollis
Mesophoyx intermedia
Ardea cinerea
Ardea purpurea
Butorides striatus
Nycticorax nycticorax
Dupetor flavicollis
Leptoptilos javanicus
Lanius schach tricolor
Oriolus xanthornus
Rhipidura albicollis
Dicrurus macrocercus
Terpsiphone paradisi
Aegithina tiphia
Sturnus vulgaris
Parus major
Zosterops palpebrosus
Turdoides striatus
Nectarinia zeylonica
Dendronanthus indicus
Motacilla alba
Sr.
No. Common English Name Species
29
ANNEXURE B
T3
T4
T1
T2
CAPTURES OF TIGERS
30
T7
T8
T6
T5
31
T9
T10
T11
T12
32
T13
T14
T15
T16
33
T17
T18
T19
T20
34
ANNEXURE CCAPTURES OF OTHER FELIDS
Fishing cat ( viverrinus)Prionailurus
Jungle cat (Felis chaus)
Leopard cat (Prionailurus bengalensis)
Melanistic leopard cat ( )Prionailurus bengalensis
35
ANNEXURE DCAPTURES OF OTHER MAMMALS
Rhesus macaque (Macaca mulatta)
Spotted deer (Axis axis)
Small Indian civet (Viverricula indica)
Wild pig (Sus scrofa)
36
ANNEXURE ECAPTURES OF BIRDS
Eurasian curlew (Numenius arquata)
Oriental magpie robin (Copsychus saularis)
White-breasted waterhen (Amaurornis phoenicurus)
Coucal (Centropus sinensis)
37
ANNEXURE F FRINGE VILLAGES ADJOINING THE STUDY
AREA
Community
Development
Block
Village Area (sq km)
Kultali
Deulbari Debipur
Purba Gurguria
Madhya Gurguria
Debipur Gurguria
Bhubaneshwari
Maipit
Binodpur
Baikuntapur
Kisorimohanpur
Bhubaneshwari
Char
Ambikanagar
Patharpratima
Purba
Sripatinagar
Sridhar Nagar
Upendra Nagar
Rakhalpur
Daspur
Uttar
Surendranagar
Dakshin
Surendranagar
Indrapur
Sitarampur
Gobardhanpur
Basanti Lot No 126
Total
7.5991
7.0507
6.1801
13.0606
8.5641
5.7878
6.5596
8.8416
7.6485
1.2322
1.1273
6.5188
9.4995
8.9052
9.3878
0.829
5.558
6.1338
7.6983
6.2489
6.4305
45.5839
186.4453
No of
Household
939
849
682
1885
1068
724
808
1079
975
169
72
599
1109
752
986
68
570
654
759
772
213
2604
18336
Population
5622
4733
3975
10015
6201
4712
4849
6711
5889
833
451
3587
6694
4311
5348
395
3038
3882
4591
4090
1193
12648
103768
Populationdensity/sq km
740
671
643
767
724
814
739
759
770
676
400
550
705
484
570
476
547
633
596
655
186
277
557
THE TEAM
Field team at Ramganga range
Field team at Nolgora Beat
Field team at Bonnie Camp
38
2. Study area with four sq km
grids
3. Selection of comparatively high elevation zones
4. Presence of tiger pugmarks 5. Grids with human presence were avoided
6. Clearance around camera trap station
7. Camera testing 8. Deployment of camera traps 9. Attractants being applied
10. Monitoring during high tide 11. Forest Department personnel check camera trap station
12. Camera traps being checked and data downloading
13. Closed Capture 14. Density 4.4 15. Program Capture 16. Program Mark
STUDY AT A GLANCE
39
1. Tide analysis
40
DEMYSTIFYING CAMERA TRAPPING1. What is camera trapping?
Camera trapping or 'remote photography' is the use of motion triggered cameras that automatically capture images ofwhatever moves in front of these. The cameras record data non-invasively without the subject being captured or theresearcher being present. These are used in pairs to record both flanks of the individual and estimate population parametersusing capture-recapture studies.
2. What is capture-recapture?In capture-recapture studies, population is estimated based on ratios of marked to unmarked individuals. The individualsthat can be easily identified from photographs are taken up in capture-recapture studies. Animals are captured and markedon several trapping occasions. The number of marked individuals that are recaptured allows the researcher to estimate thetotal 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 onscientific scrutiny has been found to be error prone. With technological advances in photography, automated digitaldevices 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 andcovers a land area of about 982.56 sq km. The study was carried out in phases between 23 January and 21 February 2012 atRamganga 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 that24-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 Distance betweentwo camera trap stations was at least one km so as to maximise capture of new individuals.
four sq km grids.
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 wasmaintained at a height of about 40-50 cm. The minimum distance maintained between two opposite cameras was three to fivemeters.
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 basesuch 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 andwild 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.