Ecological and anthropogenic covariates ... - GANGAPEDIA

Ecological and anthropogenic covariates influencing gharial 

Gavialis gangeticus distribution and habitat use in 

Chambal River, India 

A Thesis 

Submitted to the 

Tata Institute of Fundamental Research 

for the degree of 

Master of Science 

in 

Wildlife Biology and Conservation 

By 

Tarun Nair 

2010 

National Centre for Biological Sciences 

Tata Institute of Fundamental Research 

Bangalore, India

EXECUTIVE SUMMARY 

The critically endangered gharial (Gavialis gangeticus), endemic to the Indian sub- 

continent, was common in the river systems of Pakistan, northern India, Bangladesh, 

Myanmar, Bhutan and Nepal. They are now restricted to a few, scattered locations in 

India and Nepal (Whitaker, 2007), having become increasingly rare due to land-use 

changes, reduction in water flow, modification of river morphology, loss of nesting 

sites, increased mortality in fishing nets, egg-collection for consumption (Whitaker, 

2007; Hussain, 2009). Information on the effects of habitat attributes; biotic factors 

and human disturbances on gharial distribution and abundance are either scant or 

completely lacking, and thus are an impediment to effectively understand the 

conservation needs of the species. 

In this regard, the objectives of my study were specifically, 

1) What is the extent of potential gharial habitat within the study area? 

2) How do different habitat attributes and conditions determine gharial distribution 

and abundance? 

3) How do different environmental and human activities influence gharial distribution 

and habitat site use/preference within available potential gharial habitat? 

The 75 km stretch of the Chambal was divided into thirty 2.5 km segments and each 

segment was sampled once across four sampling occasions, between February and 

May, 2010, by row-boat, with a total survey effort of 300 km. These four sampling 

occasions cover the gradient from late winter to mid-summer. Boat survey and 

stationary bank observations at basking sites were used to collect data. Habitat 

i

variable data like river discharge, water depth, channel width, air and water 

temperatures, shoreline substratum and presence of basking sites were recorded for 

each of the 2.5 km segments at a scale of 0.5 km. 

On the basis of the depth profile and shoreline substratum data, one-fifth of the study 

area qualified as preferred gharial habitat. Availability of undisturbed basking sites in 

conjunction with deep water segments emerged as the main variable explaining 

gharial occurrence. All human activities appeared to negatively influence the use of 

areas by gharials. Sand mining and cultivation around the banks negatively impacted 

the use of such sites for basking. Gharials were seen less often and in fewer numbers 

in areas where fishing was high. Similar results were seen with movement of people 

and livestock along the river stretch. This study indicates the importance of inviolate 

areas that satisfy the bio-physical requirements of the gharial. 

I also describe a robust and easily replicable protocol for estimating gharial 

population size using photo-capture of basking animals. I demonstrate the conceptual, 

technical and logistic feasibility of applying photographic capture-recapture 

techniques for estimating gharial abundance in the wild. 

ii

ACKNOWLEDGEMENTS 

I thank the National Centre for Biological Sciences, Tata Institute of Fundamental 

Research, Centre for Wildlife Studies and Wildlife Conservation Society-India 

Program for support. I thank the Department of Science and Technology (DST) for 

providing financial support for the project. 

I would like to thank the Rajasthan, Madhya Pradesh and Uttar Pradesh Forest 

Departments for permissions. The staff of the Madhya Pradesh Forest Department 

(Ambah and Deori Ranges) was very co-operative, and I'd like to particularly thank, 

Mr. S.C. Badoria, Dr. R.K. Sharma, Vijay Singh Tomar, Jyothi, Lokinder, Satyapal, 

Daulat Ram, Tejpal and Ramveer. Rakesh Singh, Officer, Ram Awatar, the residents 

of Kuthiana, and the Baba at Ehsa were kind enough to host me, more than once. 

Thanks to the core group who first helped me conceptualize the idea - Rom Whitaker, 

late John T., Jeff Lang and Patrick Aust. And thanks to the team at the Madras 

Crocodile Bank too – Nikhil, Samir, (Doc) Gowri and co. 

I thank my guide- Dr. Jagdish Krishnaswamy, my co-guides Patrick Aust and late Dr. 

John Thorbjarnarson, for being very patient and supportive at all times; and my field 

assistants - Kaptan Singh, Jagdish, Rajveer, Shyam Singh. 

I am grateful to my local hosts - Rajeev Tomar and Family (Dholpur) and Col. 

Ramesh (Gwalior). And to Mr. Rakesh Vyas who introduced me to vital local 

contacts. 

Thanks to V. Srinivas for help with the GIS analyses, Krishnapriya Tamma, Nachiket 

Kelkar, Umesh Srinivasan in coming to terms with my data; my seniors from the 

Course, my batchmates and co-ordinators Veena P.G. and Divya Panicker for all their 

help. 

iii

Table of Contents 

EXECUTIVE SUMMARY ...................................................................................... i 

ACKNOWLEDGEMENTS ................................................................................... iii 

GENERAL INTRODUCTION ............................................................................... 1 

CHAPTER 1 ECOLOGICAL AND ANTHROPOGENIC COVARIATES 

INFLUENCING GHARIAL DISTRIBUTION AND HABITAT USE IN THE 

CHAMBAL RIVER, INDIA ................................................................................... 4 

ABSTRACT .......................................................................................................... 4 

INTRODUCTION ................................................................................................. 6 

METHODS ........................................................................................................... 9 

STUDY AREA .................................................................................................. 9 

FIELD METHODS.......................................................................................... 11 

DATA ANALYSIS ......................................................................................... 16 

RESULTS ........................................................................................................... 23 

ASSESSING CHANGES IN HABITAT AVAILABILITY AND RELATIVE 

ABUNDANCE OF GHARIALS ACROSS THE LOW-WATER SEASON ..... 24 

ACTIVITY PATTERNS OF GHARIAL WITH PROGRESS OF DRY SEASON 

........................................................................................................................ 27 

REGRESSION TREES.................................................................................... 27 

DISCUSSION ..................................................................................................... 32 

REFERENCES .................................................................................................... 37 

CHAPTER 2 PHOTOGRAPHIC IDENTIFICATION OF WILD GHARIALS 

(Gavialis gangeticus GMELIN 1789) FOR ASSESSING FEASIBILITY OF 

CAPTURE-RECAPTURE TECHNIQUES FOR POPULATION ESTIMATION 

................................................................................................................................ 44 

ABSTRACT ........................................................................................................ 44 

INTRODUCTION ............................................................................................... 45 

METHODS ......................................................................................................... 48 

STUDY AREA ................................................................................................ 48 

SAMPLING METHODOLOGY ..................................................................... 50 

IDENTIFICATION METHODS ...................................................................... 52 

ESTIMATING POPULATION SIZE .............................................................. 55 

RESULTS ........................................................................................................... 55 

DISCUSSION ..................................................................................................... 57 

LITERATURE CITED ........................................................................................ 59 

GENERAL CONCLUSION .................................................................................. 64 

APPENDIX 1 ......................................................................................................... 64

GENERAL INTRODUCTION 

Humans have preferentially settled along freshwater resources, and subsequently, 

freshwater ecosystems and species have suffered from multiple and on-going stresses 

from use by humans (Revenga et al 2005). Consequently, species diversity of inland 

waters is among the most threatened of all ecosystems and global freshwater 

biodiversity is declining at far greater rates than is true for even the most affected 

terrestrial ecosystems (Sala, 2000). 

The gharial (Gavialis gangeticus, Gmelin, 1789), endemic to the Indian subcontinent, 

was once common in the river systems of Pakistan, northern India, Bangladesh, 

Myanmar, Bhutan and Nepal (Whitaker and Basu, 1983; Whitaker, 1987, 2007; 

Hussain, 1999, 2009). However, they are now restricted to a few, scattered locations 

in India and Nepal (Whitaker, 2007). The gharial, is becoming increasingly rare due 

to land-use changes, reduction in water flow, modification of river morphology, loss 

of nesting sites, increased mortality in fishing nets and egg-collection for consumption 

(Whitaker, 2007; Hussain, 2009); and is especially at risk from flow regulation 

because it prefers fast-flowing river habitats, which are prime sites for dams 

(Dudgeon, 2000). 

The Chambal river population is the largest contiguous and most viable population 

and has been the focus of conservation and restocking programmes. In recent times it 

has suffered from increasing disturbance from extractive activities and is under severe 

threat from hydrological modifications due to dam and reservoirs and diversion of 

river water for irrigation. 

1

In the face of increasing proposals for water extraction and impoundments on the 

Chambal, and nation-wide river linking aspirations, it is critical that species 

requirements be understood and flow regimes be restored. Bunn & Arthington (2002), 

illustrate how flow is a major determinant of physical habitat in streams, which in turn 

is a major determinant of biotic composition; that aquatic species have evolved life 

history strategies primarily in direct response to the natural flow regimes; that 

maintenance of natural patterns of longitudinal and lateral connectivity is essential to 

the viability of populations of many riverine species; and that the invasion and 

success of exotic and introduced species in rivers is facilitated by the alteration of 

flow regimes. 

Information on the effects of habitat attributes (availability and profile of basking and 

nesting sites; water flow and quality; channel depth and width, etc.); biotic factors 

(prey density and diversity, co-predators, etc) and human disturbances (impact of 

dams, barrages, canals, pollution, excessive water extraction, fishing, sand-mining, 

riverbed cultivation, livestock presence, etc.) on gharial distribution and abundance 

are either scant or completely lacking, and thus are an impediment to effectively 

understand the conservation needs of the species. 

Literature Cited 

Bunn, S.E. and A.H. Arthington, Basic principles and ecological consequences of 

altered flow regimes for aquatic biodiversity, Environ. Manage. 30 (2002), pp. 492– 

507. 

2

Dudgeon, D. 2000. Large-scale hydrological changes in tropical Asia: Prospects for 

riverine biodiversity. Bioscience 50:793-806. 

Hussain, S. A. 1999. Reproductive success, hatchling survival and rate of increase of 

gharial Gavialis gangeticus in National Chambal Sanctuary, India. Biological 

Conservation 87:261-268. 

Hussain, S. A. 2009. Basking site and water depth selection by gharial Gavialis 

gangeticus Gmelin 1789 (Crocodylia, Reptilia) in National Chambal Sanctuary, India 

and its implication for river conservation. Aquatic Conservation-Marine and 

Freshwater Ecosystems 19:127-133. 

Revenga, C., I. Campbell, R. Abell, P. de Villiers, and M. Bryer. 2005. Prospecting 

for monitoring freshwater ecosystems towards the 2010 targets. Philosophical 

Transactions of the Royal Society B 360:397–413. 

Sala, O. E., F. S. Chapin, J. J. Armesto, E. Berlow, J. Bloomfield, R. Dirzo, E. Huber- 

Sanwald, L. F. Huenneke, R. B. Jackson, A. Kinzig, R. Leemans, D. M. Lodge, H. A. 

Mooney, M. Oesterheld, N. L. Poff, M. T. Sykes, B. H. Walker, M. Walker, and D. H. 

Wall. 2000. Biodiversity - Global biodiversity scenarios for the year 2100. Science 

287:1770-1774. 

Whitaker, R., 1987. The management of crocodilians in India. In: Webb, G.J.W., 

Manolis, S.C., Whitehead, P.J. (Eds.), Wildlife Management: Crocodiles and 

Alligators. Surrey Beatty and Sons, Sydney, pp. 63-72. 

Whitaker R, Basu D. 1983. The gharial (Gavialis gangeticus): A review. Journal of 

Bombay Natural History Society 79: 531–548. 

Whitaker et al. 2007. The Gharial: Going extinct again. Iguana. 14, 1: 24 – 33. 

3

Chapter 1 

Ecological and Anthropogenic Covariates Influencing Gharial Distribution And 

Habitat Use In The Chambal River, India. 

Abstract 

The critically endangered gharial (Gavialis gangeticus Gmelin 1789), endemic to the 

Indian sub-continent, was common in the river systems of Pakistan, northern India, 

Bangladesh, Myanmar, Bhutan and Nepal. However, they are now restricted to a few, 

scattered locations in India and Nepal. The Chambal river population is the largest 

contiguous and most viable population and has been the focus of conservation and 

restocking programmes. In recent times it has suffered from increasing disturbance 

from extractive activities and is under severe threat from hydrological modifications. 

In addition, the Chambal River population is reported to have suffered a severe 

decline between 1998 and 2006, and was also affected by the mystery die-off between 

late 2007 and early 2008. Inspite of its global endangered status, rigorous studies of 

the gharial have been limited. The goal of the current study is to identify the 

environmental and anthropogenic factors that influence habitat use and distribution by 

the Gharial in the Chambal. Row-boat survey and stationary bank observations were 

undertaken to sample a 75 km stretch of the Chambal River, divided into thirty 2.5 km 

segments. Each segment was sampled once across four sampling occasions between 

February and May, 2010, with a total survey effort of 300 km. Encounter rates of 

gharial (basking and non-basking) and corresponding environmental (e.g. water depth, 

air and water temperature) and anthropogenic disturbance factors were measured for 

each segment. I used scatter plots, Classification and Regression Trees (CART) and 

4

egression models to identify factors affecting the encounter rates of gharials in each 

of the segments. A comparison of gharial counts across the 4 sampling occasions 

shows a peak in February, followed by similar relative abundances in March, April 

and May across sites, although there was a shift in activity from basking to increased 

submergence (basking : submerged gharial :: 2.28: 1 (in Occasion 1) to 1.36 : 1 (in 

Occasion 4). However, marked changes in river discharge and temperature through 

the study period imply that different ecological covariates may be influencing gharials 

at different periods. 

We used Bayesian spatial count regression models for analyzing the effects of two 

ecological covariates (sandbank availability and depth profile) and spatial adjacency 

on habitat-use (encounter-rates). Total Gharial abundance and habitat-usage in 

segments was positively influenced by presence of basking sites and greater water 

depth. Depth measurements were extrapolated for the entire river stretch, at 5 m 

intervals, using the Kriging function in a Geographical Information System. 

Keywords: gharial, distribution, habitat use, ecological covariates, anthropogenic 

covariates, CART, kriging. 

5

Introduction 

Humans live disproportionately near waterways and extensively modify riparian 

zones (Sala, 2000). Consequently, species diversity of inland waters is among the 

most threatened of all ecosystems and global freshwater biodiversity is declining at 

far greater rates than is true for even the most affected terrestrial ecosystems (Sala, 

2000). Habitat partitioning and microhabitat preferences may be evident among 

crocodilians, especially when multiple species cohabit (Magnusson, 1985; Herron, 

1994). Territoriality during the breeding season (Rootes and Chabreck 1993a); 

reducing intraspecific competition (Hutton, 1989); or predator avoidance (Cott, 1961) 

contribute to differential habitat use (Tucker et al 1997). Between 1997 and 2006, the 

gharial population reportedly experienced a 58% drop across its range; and its total 

breeding population was estimated to be less than 200 individuals, making it a 

critically endangered species (IUCN, 2007). The gharial, is becoming increasingly 

rare due to land-use changes, reduction in water flow, modification of river 

morphology, loss of nesting sites, increased mortality in fishing nets and egg- 

collection for consumption (Whitaker, 2007; Hussain, 2009); and is especially at risk 

from flow regulation because it prefers fast-flowing river habitats, which are prime 

sites for dams (Dudgeon, 2000). The gharial (Gavialis gangeticus, Gmelin, 1789), 

endemic to the Indian subcontinent, was once common in the river systems of 

Pakistan, northern India, Bangladesh, Myanmar, Bhutan and Nepal (Whitaker and 

Basu, 1983; Whitaker, 1987, 2007; Hussain, 1999, 2009). However, they are now 

restricted to a few, scattered locations in India and Nepal (Whitaker, 2007). The 

gharial, is becoming increasingly rare due to land-use changes, reduction in water 

flow, modification of river morphology, loss of nesting sites, increased mortality in 

fishing nets and egg-collection for consumption (Whitaker, 2007; Hussain, 2009); and 

6

is especially at risk from flow regulation because it prefers fast-flowing river habitats, 

which are prime sites for dams (Dudgeon, 2000). 

The few remaining breeding populations of the gharial in India occur in the Girwa 

River along the India-Nepal border in Uttar Pradesh, the Chambal River along the 

border of Uttar Pradesh, Madhya Pradesh and Rajasthan (Whitaker, 1987; Hussain, 

1999), the Ramganga and Palain Rivers (Corbett Tiger Reserve), Uttarakhand and the 

Son River (Son Gharial Sanctuary), Madhya Pradesh (Thorbjarnarson, pers. comm.). 

Since 1978, these river stretches have been protected as wildlife sanctuaries, and in 

1979 a captive reared restocking programme was undertaken in these areas. 

However, between 1997 and 2006, the gharial population reportedly experienced a 

58% drop across its range; and its total breeding population was estimated to be less 

than 200 individuals, making it a critically endangered species (IUCN, 2007). Very 

little information exists on the status of the gharial population in these protected areas; 

and gharial habitats and populations continue to be threatened. The Chambal river 

population is the largest contiguous and most viable population and has been the 

focus of conservation and restocking programmes. In recent times it has suffered from 

increasing disturbance from extractive activities and is under severe threat from 

hydrological modifications due to dams and reservoirs, and diversion of river water 

for irrigation. 

7

Despite the release of over 5000 young gharial into various Indian rivers, as part of 

the re-stocking programmes, only about 200 breeding adults still survive 

(http://www.gharialconservation.org/). No information on their recovery in these 

rivers exists and the reasons for their low survival rate remain unknown. The 

restocking programmes lacked monitoring of survival and dispersal of released 

animals and hence the efficacy of this programme could not be scientifically 

evaluated. Information on habitat use and preference; the effects of habitat attributes 

(availability and profile of basking and nesting sites; water flow and quality; channel 

depth and width, etc.); biotic factors (prey density and diversity, co-predators, etc) and 

human disturbances (impact of dams, barrages, canals, pollution, excessive water 

extraction, fishing, sand-mining, riverbed cultivation, livestock presence, etc.) on 

gharial distribution and abundance are either scant or completely lacking, and thus are 

an impediment to effectively understand the conservation needs of the species. 

For effective conservation and management of gharials within their natural habitats, it 

is important to be able to assess species distribution and abundance, and the influence 

of habitat attributes and human disturbances on them. This will indicate the 

population dynamics of the species and is vital to determine the status of gharial 

populations and the success of conservation efforts. Moreover, the ability to identify, 

quantify and map the limiting factors for a species will enable the prediction of the 

abundance of that species based on these factors. Population studies are essential to 

determine the status of gharials in the wild, assess the success and validity of 

conservation measures, make management recommendations and design conservation 

strategies. 

8

In this regard, I will investigate – 

1) What is the extent of potential gharial habitat within the study area? 

2) How do different habitat attributes and conditions determine gharial distribution 

and abundance? 

3) How do different environmental and human activities influence gharial distribution 

and habitat site use/preference within available potential gharial habitat? 

Methods 

Study Area 

The 960 km long Chambal River rises in the northern slopes of the Vindhyan 

escarpment, 15 km West-South-West of Mhow in Indore District in Madhya Pradesh 

state, at an elevation of about 843 m (Jain et al. 2007). Lying between 24°55' and 

26°50'N, 75°34' and 79°18'E the Chambal flows first in a northerly direction in 

Madhya Pradesh(M.P.) for a length of about 346 km and then in a generally north- 

easterly direction for a length of 225 km through Rajasthan. It flows for another 217 

km between M.P. and Rajasthan (Raj) and further 145 km between M.P. and Uttar 

Pradesh (U.P.). It enters U.P. and flows for about 32 km before joining the Yamuna 

River in Etawah District at an elevation of 122 m, to form a part of the greater 

Gangetic drainage system (Jain et al. 2007). From the source down to its junction with 

the Yamuna, the Chambal has a fall of about 732 m. Out of this; around 305 m is 

within the first 16 km reach from its source. It falls for another 195 m in the next 338 

km, where it enters the gorge past the Chaurasigarh Fort. In the next 97 km of its run 

from the Chaurasigarh Fort to Kota city, the bed falls by another 91 m. In the rest of 

9

its 523 km run, the river passes through the flat terrain of the Malwa Plateau and later 

in the Gangetic Plain with an average gradient of 0.21 m/km (Jain et al. 2007). It is a 

typical anterior-drainage pattern river, being much older than River Yamuna and 

Ganga, into which it eventually flows (Mani, 1974). 

The area lies within the semi-arid zone of north-western India at the border of 

Madhya Pradesh, Rajasthan and Uttar Pradesh States (Hussain 1999, 2009), and the 

vegetation consists of ravine, thorn forest (Champion and Seth, 1968). Evergreen 

riparian vegetation is completely absent, with only sparse ground-cover along the 

severely eroded river banks and adjacent ravine lands (Hussain 1999, 2009). Ambient 

air temperatures range from 2 to 46 °C with a mean annual precipitation of 591.2mm, 

the bulk of which is received during the south-west monsoons (Hussain 1999, 2009). 

Figure 1: Map of the Study Area, River Chambal with important landmarks. 

10

A 600km stretch of the Chambal River, between Jawahar Sagar Dam and 

Panchhnada, has been protected as the National Chambal Sanctuary (Hussain 1999, 

2009). The study area comprises a 75 km stretch of river within the Sanctuary, 

between 26°32'22" N, 77°45'30" E (Daburpur Ghat, M.P.) and 26°48'37" N, 

78°10'18" E (Sukhdyan Pura Ghat, M.P.). The study area includes the river stretch, 

mid-channel islands, sand-bars, rocky outcrops and adjacent banks. The water depth 

ranges from 0.02 to 18.6 m; while the channel width ranges from 44 to 400 m. River 

discharge levels varied from 23.9 to 75 m 3 s -1. Sand occupies29.7% of the shoreline 

substratum, while gravel, clay-loam ad sandstone-rock occupied 16.6%, 20.5% and 

33.2% respectively. 

Anthropogenic influences are chiefly in the form of sand-mining; bank-side 

cultivation; domestic activities like bathing, defecating and water collection; gill-net 

and hook-line fishing; livestock herding; grass-soaking; river crossing and temple 

fairs. 

Field Methods 

Gharial Habitat Use and Distribution 

The 75 km stretch of the Chambal was divided into thirty 2.5 km segments and each 

segment was sampled once across four sampling occasions, between February and 

May, 2010, by row-boat, with a total survey effort of 300 km. These four sampling 

occasions cover the gradient from late winter to mid-summer. Boat survey and 

stationary bank observations at basking sites were used to collect data. The 

probability of basking gharial encounters was maximized by stationary bank counts at 

11

sites considered favourble based on the depth profile and basking site substrate. 

Digiscoping and digital photography were employed to observe and record basking 

animals. This was achieved using a Bushnell 20 - 60x Spotting Scope and a Casio 3x 

6 mega pixel digital camera. This was supported by a Sony Cybershot DSC-HX1 9.1 

mega pixel digital camera with 20x optical zoom and a 16 x 50 Porro-Prism 

Binoculars. The segments were sampled during periods of maximum basking activity 

(between 1000 – 1700 hrs during winter; and between 0630 – 1030 hrs and 1500 – 

1900 hrs during summer). All basking individuals were photographed, their location 

and size-class noted, and basking site characteristics measured. Location and position 

of all non-basking gharials were recorded and their sizes were approximated from 

snout length (Singh and Bustard, 1982a). Locations were determined from a Global 

Positioning system (Garmin GPS 72). Size-classes of basking gharials were 

determined by calibrating natural objects or landscape features at basking sites or by 

setting up measured reference markers at basking sites and then estimating gharial 

lengths from photographs using the public domain, image processing software 

'ImageJ' (Wayne Rasband, National Institute of Health). Alternately, gharial body 

lengths were also estimated from tail scute spoor (Bustard & Singh, 1977). 

Individuals < 90 cm long were considered to be yearlings, those between 90–180 cm 

as juveniles, and those between 180–300 cm as sub-adults, and those > 300 cm as 

adults. Basking site characteristics were measured as follows – 

1) Basking site substrate was categorized into clay, silt, sand, gravel and rock and 

these were determined using standard soil texture finger tests 

(www.cmg.colostate.edu). 

2) Basking site slope was recorded at 0, 1 and 2 meters from the water’s edge, using a 

Suunto MC-2 Compass/Clinometer. 

12

3) Depth was recorded at 5 m intervals from the basking site, upto a distance of 50 m, 

using a hand-held Hondex Digital Depth Sounder 3394. 

Explanatory variables 

Habitat variable data like river discharge, water depth, channel width, air and water 

temperatures, shoreline substratum and presence of basking sites were recorded for 

each of the 2.5 km segments at a scale of 0.5 km (See Table 1). Inorder to measure 

stage level and river discharge, I first set up a simple staff gauge at a convenient 

reference location to determine the water level at different stages of the study. 

Discharge was determined using the velocity-area approach, i.e. discharge = (cross- 

sectional area) X (average stream velocity). The location chosen for the purpose 

satisfied the following criteria – 

1) the cross section lay within a straight reach, and streamlines were parallel to each 

other 

2) velocities were greater than 0.15 m/s and depths greater than 0.15 m 

3) the streambed was relatively uniform and free of boulders and heavy aquatic 

growth 

4) flow was relatively uniform and free of eddies, slack water, and excessive 

turbulence. 

Channel width and depth were determined using a rangefinder (Nikon Monarch Laser 

800 6x) and depth sounder, respectively. Stream velocity was measured using 6 float 

measurements and a LYNX cup type water current meter with fish weight. The 

13

correction factor for the float measurements to convert these into stream velocity was 

determined from simultaneous flow meter readings. 

I recorded depth and width, along with GPS locations, at 0.5 km intervals along the 

length of the river and at 10 m intervals along the channel width at each of these 0.5 

km intervals. Air and water temperatures were recorded at 30 minute intervals using 

data loggers (HOBO Pendant Temperature Data Loggers - Part # UA-001-XX). Air 

temperatures were also collected from the National Informatics Centre 

(weather.nic.in/). Shoreline substratum was classified broadly into clay-loam, sand, 

gravel and sandstone-rock, based on standard soil texture tests. Presence of 

confluences, sand and spit bars, and mid-channel islands was recorded. 

Anthropogenic activities like sand mining, fishing, bankside cultivation, livestock 

presence, river crossing and miscellaneous activities (bathing, washing, defecation, 

grass soaking, temple fairs, etc) were recorded for each of the 2.5 km segments at a 

scale of 0.5 km (See Table 2). 

While the number of people, vehicles and livestock involved in each type of activity 

were recorded, only data on the extent of each activity type was analysed since this 

factor seemed to have greater influence on gharial distribution as compared to the 

number of people/ vehicles/ livestock per unit area. 

14

Variable 

(type) 

Stage Height 

(S) 

Discharge (S) 

Water depth 

(S) 

Equipment used 

Measurement 

Details 

Staff Gauge Daily (in) 

LYNX cup type 

water current 

meter; Float 

method 

Hondex Digital 

Depth Sounder 

3394 

Nikon Monarch 

Channel width 

Laser 800 6x 

(S) 

Range finder 

Temperature 

(S) 

Shoreline 

substrate type 

(C, D) 

Basking Site 

(S) 

HOBO Pendant 

Temp. Data 

Loggers (Part # 

UA-001-XX) 

Six 

measurements 

bet. Jan-May 

2010; m 3 /sec 

Measured every 

0.5 km; 

continuous (ft) 

Measured every 

0.5 km; 

continuous (m) 

Logged at 30 

min intervals 

Soil texture tests Observation 

Observation 

15 

Covariates 

Change in river 

level 

Depth at 10m 

intervals across 

channel width 

Mean channel 

width (m) 

Expected effects on 

gharial distribution/ 

activity 

Increased clustering of 

individuals within 

deeper sections with 

decrease in water level 

Correlated with stage 

height 

Size-related preference 

for depth; larger 

individuals (deep 

segments); smaller 

individuals (less deep 

segments) 

Correlated with depth 

(1) Air and water 

temperatures (2) 

Mean, maximum 

and minimum ( o Basking activity 

C) 

Types - Clayloam, 

Sand, 

Gravel, 

Sandstone-rock. 

Extent per 

segment 

Substrate; slope at 

0, 1, 2 m; depth at 

5m intervals 

inversely proportional 

to temp; reduced 

proportion of basking 

animals 

Preference for areas 

with greater sand 

extent 

Preference for areas 

with suitable basking 

sites. 

Table 1: Details of habitat covariates measured, Variable types: S - scalar, 

Categorical, D - Discrete

Variable (type) 

Measurement 

Details 

Sand mining (D) Observation 

Bankside Cultivation 

(D) 

Observation 

Fishing (C, D) Observation 

River crossing (C, D) Observation 

Livestock (D) Observation 

Miscellaneous (C, D) Observation 

16 

Covariates 

No. of people/ tractors; Extent 

per segment 

No. of people/ pump sets; Extent 

per segment 

Type - Gill net; Hook-line. No. of 

people; Extent per segment 

Type - People; Float; Tractor; 

Ferry. Number. Extent per 

segment 

No. of livestock. Extent per 

segment 

No. of people. Extent per 

segment 

Table 2: Details of anthropogenic covariates measured, Variable types: S - scalar, C- 

categorical, D – Discrete 

Data Analysis 

Assessing changes in habitat availability and relative abundance of Gharials 

across the low-water season 

Explanatory variables like water depth and channel width, and stage height and 

discharge, are riverine, geophysical factors, and often correlated to each other. 

Changes in river discharge (m 3 /sec) and in mean, maximum and minimum, air and 

water temperatures (°C) across sampling occasions were plotted using box-and- 

whiskers plots (see figures 4 & 5). I also compared gharial counts across the sampling 

occasions to ensure that similar relative abundances were recorded across sites,

assuming closure and detection did not change as the dry season progressed (see 

figure 6). 

River discharge varied from an estimated 75 m 3 /sec at the start of Occasion 1 to 23.9 

m 3 /sec at the start of Occasion 4. The variations in mean, maximum and minimum air 

and water temperatures are summarized in Table 3— 

PARTICULARS RANGE 

Mean Daily Air Temperature 14.5 – 35.0 °C 

Maximum Daily Air Temperature 20.0 – 45.0 °C 

Minimum Daily Air Temperature 7.5 – 28.5 °C 

Mean Daily Water Temperature 14.8 – 34.1 °C 

Maximum Daily Water Temperature 16.6 – 46.3 °C 

Minimum Daily Water Temperature 13.4 – 28.1 °C 

Table 3: The variations in mean, maximum and minimum air and water temperatures 

Activity patterns of gharial with progress of dry season 

Observed differences in basking/non-basking behavior over 4 sampling occasions 

were represented using a bar plot (see figure 7). 

Mapping suitable habitat for Gharials 

I recorded depth and width, along with GPS locations, at 0.5 km intervals along the 

length of the river and at 10 m intervals along the channel width at each of these 0.5 

km intervals. Depth measurements were interpolated for the entire river stretch, at 5 m 

intervals, using the Kriging function in a Geographical Information System (GIS) 

(i.e., using the GIS software ESRI ArcGIS 9.2). Kriging is the method of 

17

interpolation deriving from regionalized variable theory, which depends on expressing 

spatial variation of the property in terms of the variogram, and it minimizes the 

prediction errors which are themselves estimated (Oliver & Webster, 1990). A 45 

degree directional variogram was used to fit to the following model 1.216759 Nug(0) 

+ 1.085575 Bessel(1000) + 1.035012 Spherical(5000). Gharial encounter rates and 

ecological covariates (depth values and sand bank extent) were measured at 0.5 km 

sub-segment level, and overlaid onto a raster. 

Sand Bank Profile 

Figure 2: Schematic Map of a section of the study area, representing the proportional 

extent of shoreline substratum (sand) 

2 0 2 4 Kilometers 

18 

High Sand 

Moderate Sand 

Low Sand 

No Sand

Identifying ecological and anthropogenic covariates affecting Gharial encounter- 

rates (habitat-use) 

To identify factors affecting the encounter rates of gharials in each of the segments, I 

used Classification and Regression Trees (CART) (Breiman, 1984). The CART 

method is highly simple, flexible, robust, nonparametric, and hence distribution free; 

and can accommodate a lack of statistical independence between explanatory 

covariates and nested nonlinearity (De’ath & Fabricius 2000). Heterogeneity within 

data is hierarchically partitioned such that variation within data is reduced to the 

extent possible at each split. Heterogeneity (deviance) refers to the lack of fit between 

the split in the tree model and the response variable values. Heterogeneity in the 

response variable is partitioned, at each level in the tree-building process, by selecting 

the covariates which minimize this variation at that level. I used models with the 

lowest Residual Mean Deviance and number of terminal nodes (tree complexity) as 

measures of model selection. Availability of basking sites emerged as the main 

variable explaining variability in Gharial use of river segments. We can conclude in 

general that wherever basking sites were present, gharials were able to use them in 

spite of other factors. However, subject to availability of basking sites, water depth 

emerged as important for Gharial use of river segments. 

Separating spatial and covariate effects 

The Poisson distribution is the most natural choice for modeling count data, such as 

gharial abundance per site. Rivers are also connected systems and habitat use by 

Gharials is likely to be influenced by attributes of adjacent sites or sampling units 

upstream or downstream of the sampling unit.. Therefore we need to take into account 

19

the effects of covariates measured at the site as well spatial continuity across sampling 

units or spatial adjacency. 

We used Bayesian spatial count regression models for analyzing the effects of two 

ecological covariates and spatial adjacency on habitat-use (encounter-rates). While 

frequentist methods treat model parameters as unknown constants, Bayesian analysis 

consider them as random variables (Ellison 1996). The Poisson distribution is the 

most natural choice for modeling count data, such as gharial abundance per site. 

Although the Poisson model is generally used for abundance, animals may not be 

distributed completely randomly in space, and as there are a large number of 

unoccupied sites (zeros) as well as clusters of animals at other sites. 

For site (i), gharial count [i] ~ Intercept + slope * basking site [i] + spatial effect 

term[i] 

Or gharial count [i] ~ Intercept + slope * depth [i] + spatial effect term[i] 

Here, gharial count (site-specific count) is assumed to come from a Zero-inflated 

Poisson or Negative Binomial distribution (negative binomial distribution can be used 

for clumped data). Intercept and slope follow uninformative or flat prior normal 

distributions with zero mean and low precision (high variance). The zeroes of the 

dataset are separately treated as Bernoulli outcomes with a probability p0 for the 

proportion of zeroes in the data. The remaining counts are treated as following a 

Poisson distribution, with overall mean of counts equal to 1 – prob(zero count) * site- 

specific count. 

Ecological datasets tend to contain a large proportion of zero values (Clarke & Green 

1988), and such data do not readily fit standard distributions (e.g. normal, Poisson, 

binomial, negative-binomial and beta). These are referred to as ‘zero inflated’ 

20

(Heilbron 1994). Zero inflation is often the result of a large number of ‘true zero’ 

observations caused by the real ecological effect of interest (Martin et al 2005). 

True zeros arises from a low frequency of occurrence, which can be the result of 

range of ecological processes and life-history strategies (Gaston 1994) or the result of 

a strong ecological effect that leads to sites having no organisms present; or because 

the species does not saturate its entire suitable habitat (Martin et al 2005). False zeros 

can be caused by a species not being present at the time of survey or that the observer 

does not detect the species, even when it was present. 

The Zero-Inflated Poisson (ZIP) model is especially useful in analyzing count data 

with a large number of zero observations, and the Zero-Inflated Negative Binomial 

(ZINB) model is more appropriate for cases where an upper bound exists for the 

response (Arab et al 2008). 

Figure 3: Zero-inflated nature of gharial abundance. 

Zero-inflated data (see figure 3) need to be analyzed using appropriate zero-inflated 

distributions that are variations of the Poisson and Negative Binomial distributions. 

21

We compared Zero-Inflated Poisson (ZIP) and Zero-Inflated Negative Binomial 

(ZINB) that accounts for over-dispersion which can account for both over-dispersed 

and under-dispersed counts. To these models I assumed a Conditional Auto- 

Regressive (CAR) normal distribution as an uninformative prior distribution for 

spatial random effects. The inverse of the precision parameter (spatial variance) for 

the CAR normal models was calculated and compared between models. The CAR 

prior provides spatial smoothing of parameter estimates. 

The value of Gharial count per segment is influenced by the probability that it takes a 

value conditional upon the gharial count in the neighbouring segment. The CAR 

model used here has four terms: the number of neighbours of each site, (2 for all 

segments except terminal sites which have only one neighbour), adjacency matrix 

based on the IDs of neighbouring sites and spatial weights which we assign as 1 for 

all areas. The spatial precision (1/variance) parameter tau is the important parameter 

for the model, as it gives us an estimate of spatial effect. Higher the parameter tau, 

lower is the spatial variation or spatial effect. 

We used the ZINB and ZIP models to estimate the slope and intercept parameters, as 

well as spatial variance parameter for relationship between Gharial abundance and 

basking site presence, as well as between abundance and depth of river channel in that 

segment. The parameters slope, intercept, spatial variability (variance of CAR 

Normal), over-dispersion parameters, and other parameters of the respective 

distributions (ZIP, ZINB) were estimated in each model. Deviance was compared for 

model selection. All statistical analyses were conducted using the software R 2.11.1 

(R Development Core Team 2010) and WinBUGS (Spiegelhalter et al. 2007). For 

22

Bayesian analyses, 100 000 MCMC simulations were carried out and a burn-in period 

of 10000 iterations was discarded for each model. 

Results 

Total Gharial abundance and habitat-usage was positively influenced by presence of 

basking sites and greater water depth (see table 4). 

Model Intercept 

(beta1) 

Slope (beta2) Spatial variance 

(1/tau) 

23 

Deviance 

~ basking site + Mean (SD) and Mean (SD) and Mean (SD) Mean (SD) 

spatial effect credible 

interval 

credible interval 

ZIP 0.25 (0.47) 1.75 (0.47) 2.1 (0.80) 250 (10.07) 

ZINB 0.29 (0.48) 1.73 (0.48) 2.385 (0.95) 250.9 (10.22) 

~ depth + spatial 

effect 

Mean (SD) Mean (SD) 

ZIP 0.31 (0.60) 0.92 (0.88) 0.85 (0.40) 304.2 (14.82) 

ZINB 0.55 (0.54) 0.90 (0.70) 1.09 (0.47) 312.1 (12.61) 

Table 4: Parameter estimates for the ZINB and ZIP models for gharial abundance and 

habitat usage influenced by basking site and depth availability. 

On the basis of the depth profile and shoreline substratum data, approximately one- 

fifth (29/150 sub-segments) of the study area qualified as preferred gharial habitat. 79 

out of 150 sub-segments had a mean depth of > 1m, while the extent of sandy 

shoreline was greater than 0.4 in 42 out of 150 sub-segments. Of these, only 29 out of 

150 sub-segments satisfied both criteria and were accordingly qualified as preferred 

gharial habitat.

Assessing changes in habitat availability and relative abundance of Gharials 

across the low-water season 

River discharge varied from 75 m 3 /sec at the start of Occasion 1 to 23.9 m 3 /sec at the 

start of Occasion 4. 

Figure 4: Box-and-whiskers plot showing reduction in discharge(m 3 /sec) across 

occasions. 

Reduced discharge and water level can mean a reduction in the extent of available 

habitat, in terms of preferred water depth. Decreasing water levels, through the dry 

season, was expected to cause increased clustering of individuals, within the deeper 

sections of the river. However, this did not manifest during the course of this study, 

probably because the dry season – reduced flow pattern had already set in at the start 

of the study and the clustering of gharials observed on all 4 occasions was an artefact 

of gharial response to reduced flow regimes. 

24

Figure 5: Box-and-whiskers plots showing increase in mean daily air and water 

temperatures (°C) respectively, across occasions. 

25

Figure 6: Box-and-whiskers plots comparing gharial counts across sampling 

occasions. 

The abundance of gharials in a segment on either banks were plotted against (a) 

Extent of sand mining on the corresponding bank (b) extent of cultivation on the 

corresponding bank (c) extent of human presence on the corresponding bank (d) 

extent of livestock presence on the corresponding bank. The plots (Refer Appendix 1) 

suggest that gharial abundance drops sharply when disturbance levels are present. 

Most plots show that gharial abundance is heavily clumped at zero values of 

disturbance. 

A comparison of gharial counts across the 4 sampling occasions shows that similar 

relative abundances were recorded across sites, assuming closure and detection did 

not change as the dry season progressed. However, marked changes in river discharge 

and temperature within the same period imply that different ecological covariates may 

be influencing gharials at different periods. Site-specificity may also suggest the 

26

influence of a combination of interacting covariates on gharial habitat use and 

preference. 

Activity patterns of Gharial with progress of dry season 

No. of Gharials 

300 

250 

200 

150 

100 

50 

0 

Figure 7: Observed differences in basking/non-basking behavior over 4 sampling 

occasions are represented using a bar plot. Gharials are ‘thermoconformors’, avoiding 

extreme temperatures and that explains the decreased intensity of basking, as the dry- 

season progressed (Lang, 1987a, b). 

Regression Trees 

To identify factors affecting the encounter rates of gharials in each of the segments, I 

used Classification and Regression Trees (CART). Models with the lowest Residual 

Mean Deviance and number of terminal nodes (tree complexity) were used, as 

measures of model selection. 

Comparison of Basking and Non-Basking Gharials across the dry 

season 

1 2 3 4 

Occasion 1 2 3 4 

Basking 274 211 167 136 

NonBasking 120 88 94 100 

27

Occasion 1: Residual mean deviance = 29.05 

Figure 8: Regression Tree explaining variation in gharial encounter rates for Occasion 

1. Numbers at terminal nodes indicate mean gharial encounter rates influenced by 

mean channel depth. 

Encounter rates were modelled as a function of the extent of sandy shoreline substrate 

(preferred basking site), mean and maximum daily air temperatures, river depth, and 

all anthropogenic variables. From these, only basking site and mean channel depth 

were used in the actual tree construction. 

28


Figure 9: Regression Tree explaining variation in gharial encounter rates for Occasion 

2. Numbers at terminal nodes indicate mean gharial encounter rates influenced by 

different combinations of ecological covariates. Here, availability, mean channel 

depth and mean depth positively influence gharial encounter rates, while the extent of 

sandstone –rock shoreline substrate negatively influences gharial encounter rates. 

Encounter rates were modelled as a function of all habitat and anthropogenic 

variables. From these, only extent of sandy shoreline substrate (preferred basking 

site), channel width, mean channel depth and the extent of sandstone-rock shoreline 

substrate were used in the actual tree construction. 

29

Occasion 3: Residual mean deviance: = 11.04 

Figure 10: Regression Tree explaining variation in gharial encounter rates for 

Occasion 3. Numbers at terminal nodes indicate mean gharial encounter rates 

influenced by different combinations of ecological covariates. Here, availability, 

mean daily temperature, mean channel width and mean depth positively influence 

gharial encounter rates, while the extent of livestock negatively influences gharial 

encounter rates. 



site), channel width, mean channel depth, maximum daily air temperature and the 

total disturbance index were used in the actual tree construction. 

30


Figure 11: Regression Tree explaining variation in gharial encounter rates for 

Occasion 4. Numbers at terminal nodes indicate mean gharial encounter rates 

influenced by different combinations of ecological covariates. Here, availability, 

mean daily temperature, extent of sandy shoreline substrate and mean depth positively 

influences gharial encounter rates, while the extent of livestock negatively influences 

gharial encounter rates. 



site), mean channel depth and mean daily air temperature were used in the actual tree 

construction. 

31

Discussion 

Humans have preferentially settled in close proximity of freshwater resources and 

subsequently, freshwater ecosystems and species have suffered from multiple 

historical and on-going stresses from use by humans (Revenga et al 2005). These 

stresses are often interrelated and endangered species, like the gharial (Gavialis 

gangeticus), are highly susceptible to these combined pressures (Malmqvist & Rundle 

2002). The gharial, a charismatic flagship species of freshwater ecosystems, is 

increasingly threatened due to human induced disturbances. Land-use changes, 

reduction in water flow due to dams, modification of river morphology, loss of 

nesting sites, mortality in fishing nets and egg-collection for consumption (Whitaker, 

2007; Hussain, 2009) are some of the factors affecting gharial populations. The 

gharial is especially at risk from change in factors like water flow because it prefers 

fast-flowing river habitats, which are prime sites for dams (Dudgeon, 2000). 

Information on the effects of habitat attributes (availability and profile of basking and 

nesting sites; water flow and quality; channel depth and width, etc.); biotic factors 

(prey density and diversity, co-predators, etc) and human disturbances (impact of 

dams, barrages, canals, pollution, excessive water extraction, fishing, sand-mining, 

riverbed cultivation, livestock presence, etc.) on gharial distribution and abundance 

are either scant or completely lacking, and thus are an impediment to effectively 

understand the conservation needs of the species. 

My study describes gharial habitat use in terms of river depth -channel width profile 

and basking site characteristics. Previous studies, using a non-mapping technique, on 

basking site selection and water depth preferences of the gharial have reported 

preference for sandy basking sites, and size-related preference for different water 

depths (Hussain, 2009). My study also showed a similar pattern of habitat use by 

32

gharial, within my study area. Gharial encounter rates and habitat-usage were higher 

in areas where large sandy banks were adjacent to deep pools of water, indicating that 

such locations were favoured for basking. I observed that gharial aggregations tend to 

cluster at sites which had greater water depth – channel width profile. Further, all 

anthropogenic activities like sand mining, bankside cultivation, human and livestock 

presence, fishing and people crossing the river, had a negative impact on gharials 

using an area. This pattern of habitat use was seen consistently in observations across 

all occasions. 

Gharial encounter rates and site occupancy were expected to be influenced by 

seasonality of river discharge and temperature, both of which showed marked changes 

across the duration of the study. Ambient air and water temperature increased from 

February to May, and river flow and discharge showed a decrease during this period. 

In a comparison of gharial counts across the 4 sampling occasions, we see a peak in 

February, followed by similar relative abundances in March, April and May, 

assuming closure and detection did not change. February is a period of intensive 

basking frequency, due to low temperatures, and this greatly increases detection of 

gharials. This period also coincides with the aggregation of large gharials for 

breeding. We also see similar relative abundances in March, April and May. 

However, marked changes in river discharge and temperature within the same period 

imply that factors other than discharge and temperature are influencing gharial 

encounter rates in this period. This indicates that other variables may be influencing 

spatial distribution of gharials along the river stretch at different periods. Site- 

specificity may also suggest the influence of a combination of these variables on 

gharial habitat use and preference. 

33

Tucker et al. (1997) report that primary change in habitat use was related to maturity 

status, evident by the habitat differences between immature and adult Crocodylus 

johnstoni. When water levels subside, crocodiles become restricted to the available 

aquatic habitats and social interactions become more frequent, particularly during 

mating and breeding seasons. Divergent foraging patterns, intraspecific behavioural 

interactions, thermal preference, predator avoidance or social displacement are known 

to influence habitat associations in crocodilians (Tucker et al 1997). Decreasing water 

levels, through the dry season, was expected to cause increased clustering of 

individuals, within the deeper sections of the river. However, this did not manifest 

during the course of this study, probably because the dry season – reduced flow 

pattern had already set in at the start of the study and the clustering of gharials 

observed on all 4 occasions was an artefact of gharial response to reduced flow 

regimes. However, water levels and discharge are critical factors that are regarded to 

be the key driver of river and floodplain wetland ecosystems, and hence need to be 

monitored continually, across different seasons. Also, low water levels lead to 

increased anthropogenic disturbances, especially along shallow stretches (pers. obs.). 

Higher incidences of river-crossing and sand mining at these sites were observed. 

Large scale nest predation (of turtles, skimmers, black-bellied terns, etc) was observed 

following reduced water levels, and easy access to mid-river islands and sand-spits. 

Human induced disturbances were seen to have tangible impacts on the spatial 

distribution of gharials along the river. The presence of people at a site was seen to 

have a negative impact on gharials using the area. Segments which had people 

presence, recorded much lower gharial numbers. I observed that gharials took evasive 

action and submerged themselves when they spotted people, even as far as 200m 

away. They were seen to be particularly affected by the presence of people if they 

34

were on the same bank as the animals. Similarly, the presence of livestock in the 

vicinity also appears to have a negative influence on use of a site. In addition, gharials 

were unable to use mid river sand spits exposed in shallow areas because such 

locations would be frequently used by people to cross the river. This implies that in 

spite of additional available habitat for basking, gharials were unable to use them 

because of humans using the same resource. 

Sand mining along the banks of the Chambal appeared to have a severe negative 

impact on gharial use of sites for basking. Continuous human activity in the mining 

areas precluded the gharials from using these sites. Gharial numbers were consistently 

lower in areas with mining operations, except one location where the height of the 

sand bank excluded the mining from view of the animals. What is also significant is 

the fact that mining usually takes place in large stretches of sand, areas that are 

preferred by the gharial for basking and nesting. Sand mining therefore, not only 

reduces the availability of sites for basking, but also poses a severe threat to the 

reproductive success of gharials. In addition, sand mining also affects a suite of other 

riverine species like turtles and ground nesting birds by excluding their use of sand 

banks. 

Land use changes along the river also appear to have a negative impact on habitat use 

by gharials. Agriculture along the banks in all seasons, except when banks were 

inundated due to flooding, was also viewed as a disturbance by the animals. I found 

gharial numbers to be much lower in areas proximate to cultivations. Fishing 

activities were another anthropogenic factor influencing the use of areas by gharials. 

Again, gharial numbers were seen to be lower in areas where the intensity of fishing 

activities was high. Gillnet fishing poses the danger of entanglement in the nets, 

especially with smaller size-classes. Anecdotal reports mention that animals that are 

35

once caught in the net are wary of reusing areas where they were caught. As gharials 

are obligate piscivores, their exclusion from parts of the river might negatively impact 

their foraging success. People and gharial seem to select similar resources (fish and 

sand), and this could suggest competition between them. Studies from the 

Vikramshila Gangetic Dolphin Sanctuary in Bihar (Kelkar et al. 2010), investigated 

the effects of fishing on prey intensity on fish availability to the Ganges river dolphin, 

and estimated 85% spatial and 75% prey-resource overlap between fisheries and 

dolphins, suggesting a high level of competition. 


is important to be able to assess the impacts of various habitat attributes on species 

distribution and abundance. This will help understand population dynamics of the 

species and is vital to determine the status of gharial populations and the success of 

conservation efforts. The impact of human disturbances on the behaviour and habitat 

use by animals also needs to be understood and quantified, especially in the face of 

increasing human intrusion into most ecosystems. The overall picture that emerges 

from my study appears to indicate that gharials avoided areas with anthropogenic 

activities. Irrespective of the type of the disturbance, spatial distribution of gharials 

appeared to be negatively affected by the presence of people. 

In the face of increasing proposals for water extraction and impoundments on the 

Chambal, and nation-wide river linking aspirations, it is critical that species 

requirements be understood and flow regimes be restored. Bunn & Arthington (2002), 

illustrate how flow is a major determinant of physical habitat in streams, which in turn 

is a major determinant of biotic composition; aquatic species have evolved life history 

strategies primarily in direct response to the natural flow regimes. Maintenance of 

natural patterns of longitudinal and lateral connectivity is essential to the viability of 

36

populations of many riverine species. Alteration of flow regimes may also change the 

dynamics of the success of native and introduced species. 

The ability to identify, quantify and map the limiting factors for a species will enable 

the prediction of long term changes in the behavioural responses and population 

dynamics of the species. The long term changes in behavioural dynamics of gharials 

and response of the species to anthropogenic disturbance factors merit further study. 

Robust quantitative estimates of gharial populations are needed to objectively 

determine the status of gharials in the wild. This is vital to assess the success and 

validity of conservation measures, make management recommendations and design 

future conservation strategies for this highly endangered and charismatic species of 

freshwater riverine systems. 

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43

Chapter 2 

Photographic identification of wild gharials (Gavialis gangeticus Gmelin 1789) 

for assessing feasibility of capture-recapture techniques for population 

estimation. 

Abstract 

The Gharial is a critically endangered crocodilian, endemic to the Indian 

subcontinent, and with populations facing severe declines across its range from both 

direct and indirect causes. Available population estimates of gharials have been based 

on direct ‘total counts’ and do not address uncertainty due to biological or 

observation-related factors, especially detectability. The Chambal River in Northern 

India is thought to have one of the last viable populations of the Gharial, and robust 

estimates of population size, that incorporate uncertainty are necessary for informing 

management and conservation decisions of this last surviving population. Individual 

identification of Gharial, if demonstrated under wild conditions, can enable 

abundance estimation within a capture-recapture frame-work, a technique that has 

never been used for crocodiles anywhere. It will also enable regular monitoring of 

their critically endangered populations. Photographic identification of individuals 

offers several advantages employed within the sampling framework of capture- 

recapture for estimating capture (detection) probabilities and population size. Photo- 

identification has the advantages of being a non-invasive technique, with fewer 

economic and logistic constraints of capture, handling, capture and post-capture 

stress, tracking, altered behaviour and the demand for large sample sizes. Although 

photographic identification of individual young gharials has been used in captive 

44

conditions, based on tail markings and scute structures, this technique has not been 

adapted to field conditions. I describe a robust and easily replicable protocol for 

estimating gharial population size. Row-boat surveys and stationary bank 

observations were undertaken to sample thirty 2.5 km segments over 4 sampling 

occasions in the dry season of 2010, in the National Chambal Sanctuary, Chambal 

River, India. I also explain in detail the field challenges, precautions and methodology 

for conducting photo-identification of gharials. 

Keywords: gharial, uncertainty, individual identification, capture-recapture, detection 

probabilities, non-invasive. 

Introduction 

Humans live in high densities near waterways and extensively modify riparian zones 

(Sala, 2000). Consequently, species diversity of inland waters is among the most 

threatened of all ecosystems and global freshwater biodiversity is declining at far 

greater rates than is true for even the most affected terrestrial ecosystems (Sala, 2000). 

The Gharial (Gavialis gangeticus Gmelin 1789) is a river crocodilian endemic to the 

Indian subcontinent. It is one of the main fish predators of the north Indian riverine 

floodplains. Between 1997 and 2006, the gharial population reportedly experienced a 

58% drop across its range; and its total breeding population was estimated to be less 

than 200 individuals, making it a critically endangered species (IUCN, 2007). The 

gharial, is becoming increasingly rare due to bank land-use changes, reduction in river 

flows, modification of river morphology, loss of nesting and basking sites, increased 

mortality in fishing nets and egg-collection for consumption (Whitaker, 2007; 

45

Hussain, 2009); and is especially at risk from flow regulation because it prefers fast- 

flowing river habitats, which are prime sites for dams (Dudgeon, 2000). 

Although previous assessments report population trends and document the fall in 

gharial numbers, censuses based on total counts do not take into account detection 

probabilities and lack any measure of uncertainty in their estimates. Additionally, the 

lack of quantitatively robust population estimates for three generations in the past 

makes the calculation of exact rates of decline over the period problematic (IUCN, 

2007). Despite the release of over 5000 young gharial into various Indian rivers, as 

part of the re-stocking programmes, only about 200 breeding adults still survive 

(http://www.gharialconservation.org/). No information on their recovery in these 

rivers exists and the reasons for their low survival rate remain unknown. The 

restocking programmes lacked monitoring of survival and dispersal of released 

animals and hence the efficacy of this programme could not be evaluated. 

Population studies are essential to determine the status of gharials in the wild, assess 

the success and validity of conservation measures, make management 

recommendations and design conservation strategies. Magnusson (1982) and Bayliss 

(1987) reviewed survey methods and techniques for crocodilian population 

estimation. Although several survey techniques have been used to ascertain 

crocodilian populations worldwide, they vary greatly in terms of applicability, cost- 

effectiveness, the species involved, and the socio - political and administrative 

environment. For instance, the widely used spot light counts are often affected by the 

presence of vegetation, size-related wariness to approaching observers, time and 

expenses required, and the dangers involved (Bayliss et al 1986). Similarly, 

conventional mark-recapture techniques, besides being affected by the above, also 

suffer from tag loss and unequal catchability (Bayliss 1987); altered natural behaviour 

46

(Gauthier-Clerc 2004), and ethical and welfare issues arising from the application of 

tags or marks (Wilson & McMahon 2006, McMahon et al 2006). 

Individual identification of rare and endangered species enable the counting and 

monitoring of threatened populations, provide the detailed knowledge of the life 

histories of individual animals used in a new generation of predictive models, and 

help understand differences between animals within a population in terms of 

behavioural strategies, differential habitat use and reproductive success (McGregor & 

Peake, 1998). The use of natural markings to distinguish between individuals has 

been used for the identification of chimpanzees from facial characteristics (van 

Lawick Goodall, 1971); dolphins from dorsal fin cuts and nicks (Mazzoil et al 2004); 

Nile crocodiles (Swanepoel, 1996); African wild dogs from coat markings (Creel & 

Creel, 1995); tigers from strip patterns (Karanth, 1995; Karanth & Nichols, 1998), and 

the use of pattern recognition software to identify cheetahs (Kelly, 2001) and whale 

sharks (Arzoumanian et al. 2005) from spot patterns. 

Capture-Recapture models provide a statistical framework for estimating p (detection 

or capture probability) and quantities of biological interest such as population size 

(Nichols, 1992). Since gharials are individually identifiable (Singh & Bustard, 1976), 

it may be possible to estimate population sizes by using individual identity within the 

sampling framework of capture-recapture (Otis et al., 1978). The underlying principle 

of the capture-recapture framework is that several samples consisting of individually 

identifiable gharials are drawn from a population of unknown size (N = abundance). 

This sampled population consists of individual gharials, with unique markings, that 

are counted across two or more sampling occasions. The detection probability is then 

estimated from the capture histories of the individual gharials, following which, the 

unknown abundance and density can be estimated. Multi-season capture-recapture 

47

data also enables the estimation of various demographic parameters, vital rates and 

state variables (e.g. Karanth 1995; Karanth & Nichols 1998; Karanth et al. 2006). 

Although photographic identification of individual young gharials has been used in 

captive conditions, this technique has not been adapted to field conditions. The goal 

of this study is to demonstrate the feasibility (conceptual, technical and logistic) of 

applying photographic capture-recapture techniques for estimating gharial abundance 

in the wild. I describe a robust and easily replicable protocol for estimating gharial 

population size using photo-capture of basking Gharials in the wild. Row-boat 

surveys and stationary bank observations were undertaken to sample thirty 2.5 km 

segments over 4 sampling occasions in the dry season from February to May, 2010, in 

the National Chambal Sanctuary, Chambal River, India. I also explain in detail the 

field challenges, precautions and methodology for conducting photo-identification of 

Gharials. 

Methods 

Study Area 

The 960 km long Chambal River rises in the northern slopes of the Vindhyan 

escarpment, 15 km West-South-West of Mhow in Indore District in Madhya Pradesh 

state, at an elevation of about 843 m (Jain et al. 2007). Lying between 24°55' and 

26°50'N, 75°34' and 79°18'E the Chambal flows first in a northerly direction in 

Madhya Pradesh(M.P.) for a length of about 346 km and then in a generally north- 

easterly direction for a length of 225 km through Rajasthan. It flows for another 217 

km between M.P. and Rajasthan (Raj) and further 145 km between M.P. and Uttar 

48

Pradesh (U.P.). It enters U.P. and flows for about 32 km before joining the Yamuna 

River in Etawah District at an elevation of 122 m, to form a part of the greater 

Gangetic drainage system (Jain et al. 2007). It is a typical anterior-drainage pattern 

river, being much older than River Yamuna and Ganga, into which it eventually flows 

(Mani, 1974). The area lies within the semi-arid zone of north-western India at the 

border of Madhya Pradesh, Rajasthan and Uttar Pradesh States (Hussain 1999, 2009), 

and the vegetation consists of ravine, thorn forest (Champion and Seth, 1968). 

Evergreen riparian vegetation is completely absent, with only sparse ground-cover 

along the severely eroded river banks and adjacent ravine lands (Hussain 1999, 2009). 

Ambient air temperatures range from 2 - 46 °C with a mean annual precipitation of 

591.2mm, the bulk of which is received during the south-west monsoons (Hussain 

1999, 2009). 

Figure 1: Map of the Study Area, River Chambal with important landmarks. 

49

A 600km stretch of the Chambal River, between Jawahar Sagar Dam and 

Panchhnada, has been protected as the National Chambal Sanctuary (Hussain 1999, 

2009). The study area comprises a 75 km stretch of river within the Sanctuary, 

between 26°32'22" N, 77°45'30" E (Daburpur Ghat, M.P.) and 26°48'37" N, 

78°10'18" E (Sukhdyan Pura Ghat, M.P.). The study area includes the river stretch, 

mid-channel islands, sand-bars, rocky outcrops and adjacent banks. The water depth 

ranges from 0.02 to 18.6 m; while the channel width ranges from 44 to 400 m. 

Sampling Methodology 

The 75 km stretch was divided into thirty 2.5 km segments and each segment was 

sampled once across four sampling occasions by row-boat. Boat survey and stationary 

bank observations at basking sites were used to collect data. The probability of 

basking gharial encounters was maximized by stationary bank counts at sites 

considered favourble based on the depth profile and basking site substrate. 

Digiscoping and digital photography were employed to observe, record and identify 

basking individual gharials. This was achieved using a Bushnell EXCURSION FLP 

20 - 60x - 80mm Spotting Scope, coupled with a Casio EX-Z110 6 mega pixel digital 

camera with 3x optical zoom using a Bushnell Universal Digiscoping Bracket. This 

was supported by a Sony Cybershot DSC-HX1 9.1 mega pixel digital camera with 

20x optical zoom and a 16 x 50 Porro-Prism Binoculars. The segments were sampled 

during periods of maximum basking activity (between 1000 – 1700 hrs during winter; 

and between 0630 – 1030 hrs and 1500 – 1900 hrs during summer). At each of these 

basking sites, all basking individuals were photographed, their location and size-class 

noted, and basking site characteristics measured. 

50

The sampling protocol was followed in order to meet the basic assumptions of 

capture-recapture models, as follows: 

1) All individuals have an equal probability of being captured: 

Although crocodilian population surveys are affected by biases against smaller size 

classes, I ensured that all zones within the study area, which included the river stretch, 

mid-channel islands, sand-bars, rocky outcrops and adjacent banks, were observed 

with equal effort. I used powerful optics (a Bushnell EXCURSION FLP 20 - 60x - 

80mm Spotting Scope and 16 x 50 Porro-Prism Binoculars) to ensure that were no 

‘holes’ where an individual could have zero capture probability. 

2) Capture does not affect subsequent recapture: 

This technique did not involve physical capture and restraint of gharial; and data 

collection through stationary bank observations were being carried out from 

concealed locations to minimize disturbance and observer influence. Moreover, a time 

period of at least three weeks between subsequent occasions was considered sufficient 

to aid recovery from any possible stress or disturbance arising from the study. 

3) Marks are not lost: 

The tail of the gharial is laterally compressed, and on its sides, it has black markings 

on a base of light to dark brown. Proximally, the tail has a double crest of projecting 

scutes and, distally, a single crest. Individual identification of gharial were made, 

primarily, by comparing natural permanent blotches and markings on the lateral 

scutes on the tail, and by using additional cues like size classes, injuries and scars. 

These markings are not known to change and are individually unique. 

4) Marked and unmarked individuals have the same probability of survival: 

51

Marked animals were accorded no exclusive treatment, since captures and subsequent 

recaptures through photo-identification is a non-invasive technique. 

5) Geographic and demographic closure: 

Since the timing of this study preceded the gharial hatching season, the likelihood of 

the demographic closure assumption being violated was low. Similarly, since the 

study coincided with the dry-season (low-water level), the likelihood of animals 

moving in and out of the study area was low, supporting the assumption of geographic 

closure. 

Identification Methods 

Individual identification of gharial were made, primarily, by comparing natural 

blotches and markings on the lateral scutes on the tail, and by using additional cues 

like size classes, injuries and scars. Each of these encounters was photographed, given 

a unique identity number and geo-tagged using a Global Positioning System (Garmin 

GPS 72). Group composition data (number of animals in aggregations and size-class) 

were collected. Gharial size-classes were determined by calibrating natural objects or 

landscape features beforehand and by setting up measured reference markers at 

basking sites and then estimating gharial lengths from photographs using the software 

'ImageJ' (Wayne Rasband, National Institute of Health). Alternately, gharial body 

lengths were also estimated from tail scute spoor (Bustard & Singh, 1977). 

Individuals < 90 cm long were considered to be yearlings, those 90–180 cm as 

juveniles, those 180–300 cm as sub-adults, and those > 300 cm as adults. 

The tail of the gharial is laterally compressed, and on its sides, it has black markings 

on a base of light to dark brown. Proximally, the tail has a double crest of projecting 

52

scutes and, distally, a single crest. The scutes will be numbered serially from the 

junction -- proximally in the double-crested region and distally in the single-crested 

region. In the above case, only the markings present on the first row of lateral scutes 

immediately below the first five scutes of the single- and double- crested regions will 

be used for individual identification (see figure 2). 

In the first filter, only the presence or absence of marking on a particular scute will 

noted. If these match consistently for 2 or more individuals, then the second filter will 

take into account the position of the marking on the scute, i.e. anterior/ posterior/ 

base/ fully black. 

Here, the entire scute 1 is marked. Denoted as ‘F’ for fully black. 

Here only the posterior side of scute 1 is marked and will be denoted 

‘P’. The adjoining scute will be denoted ‘B’ to indicate that only base of the scute is 

marked. (Adapted from Singh & Bustard, 1976), 

53

Single-crested region 

Figure 2: Lateral view of the gharial tail showing distinguishing patterns. 

Identification of individual in Fig 2 - 

Filter 1 

RS 5 RS 4 RS 3 RS 2 RS 1 RD 1 RD 2 RD 3 RD 4 RD 5 

No Yes No No Yes No No Yes No Yes 

Filter 2 

Junction of double-crested region. 

Single crests posterior of this point. 

3 

2 

1 1 2 

Double-crested region 

RS 5 RS 4 RS 3 RS 2 RS 1 RD 1 RD 2 RD 3 RD 4 RD 5 

--- A --- --- PB --- --- PB --- A 

A = Anterior B = Base P = Posterior 

R = Right side S = single-crested region D = double-crested region 

3 

54 

Fig. 2

Estimating population size 

To estimate abundance using capture-recapture methods, a capture history matrix for 

each identified individual will be constructed, in the standard ‘X’ matrix format (Otis 

et al., 1978) such that each entry assumes the value ‘1’ for being captured in that 

particular sampling occasion, or the value ‘0’ for not being captured in the same 

sampling occasion. Thus, a capture-history of 1001 would mean that a gharial was 

captured (photographed) on the first and fourth sampling occasions but not on the 

second and third occasions. Capture histories will be constructed separately for either 

side since most captures were obtained of only one side, and the side with most 

captures will be used in the analysis. Capture – Recapture data analysis and the 

estimation of abundance will be carried out using the software MARK or CAPTURE. 

Closure will also be tested statistically using MARK or CAPTURE. 

Results 

Over 400 usable photographs were obtained during the 4 sampling occasions. 

Preliminary analysis of the photographs suggests site fidelity, especially among 

individuals of the adult and sub-adult size classes which seem to favour particular 

basking sites. 

55

A B 

C 

Capture: 07.02.2010 Figure 1. 

Recapture: 04.03.2010 Figure 2. 

A – Black blotch on the single scute number 5, 6 (Posterior to Junction of doublecrested 

region) 

B - Black blotch on the single scute number 2, 3 (Posterior to Junction of doublecrested 

region) 

C- Black blotch below double scute 1, 2 

Figure 1 refers to the ‘photo-capture’ of an adult gharial during Occasion 1 on 

07.02.2010, while Figure 2 refers to the ‘photo-recapture’ of the same adult during 

Occasion 2 on 04.03.2010, after a period of 26 days. The two photographs have been 

matched on the basis of the presence and position of natural blotches on the lateral 

scutes and on the single-crested caudal scutes. 

This demonstrates that photographic identification of wild gharial is a feasible 

technique for identifying individuals, in order to estimate population size in a capture 

– recapture framework. 

56

Discussion 

One issue that needs to be addressed is the fact that only one side of the gharial is 

visible at any one time, and that unless both sides are photographed, an individual’s 

identity remains unknown when presented with only the unrecorded side. However, 

this can be dealt with by identifying basking sites in advance and positioning oneself 

before these animals emerge to bask. Thereafter, the sequence of events that 

accompany most basking episodes provide a way to bypass the issue. Gharials emerge 

head first onto basking sites, providing an opportunity to ‘capture’ one side and then 

re-orient themselves so as to face the river. This allows for the other side to be 

captured too. 

Other factors that could complicate the implementation of this technique are poor 

weather conditions, animals lying at odd angles or congregating in a way such that 

individuals are blocking the observers’ view of other individuals, disturbances that 

drive basking gharials into the water. 

Although the use of natural markings is non-invasive and is advantageous over 

applied tags in specific cases, issues relating to uncertainty in the level of 

identification, misidentification or misclassification, and unmarkable animals must be 

considered (Yoshizaki, 2007). Since conventional methods for analysis of capture– 

recapture data do not account for identification errors, special capture-recapture 

models that incorporate unmarkable animals (Da Silva et al., 2000, 2003) or models 

that incorporate the misidentification mechanism (Yoshizaki, 2007; Yoshizaki et al. 

2009) will have to be used. 

Capture-Recapture models provide a statistical framework for estimating p (detection 

or capture probability) and quantities of biological interest such as population size 

57

(Nichols, 1992). Since gharials are individually identifiable (Singh & Bustard, 1976), 

it may be possible to estimate population sizes by using individual identity within the 

sampling framework of capture-recapture (Otis et al., 1978). Population studies are 

essential to determine the status of gharials in the wild, assess the success and validity 

of conservation measures, make management recommendations and design 

conservation strategies. 

To obtain life-history parameters of animals and to be able to determine critical 

resource requirements, it is essential to monitor individuals for extended periods of 

time. Identifiable individuals are thus invaluable in the investigation of survival, 

movement, competition, behavioural strategies and reproductive strategies. 

Knowledge of the life histories of individual animals used in a new generation of 

predictive models (Sutherland, 1995) may prove vital to the conservation of those 

species that are especially vulnerable to human disturbance and for which predictive 

measures may be of more importance than reactive measures (McGregor & Peake, 

1998). Individuals use habitat differently (e.g., Peake, 1997), employ different 

behavioural strategies (e.g., Rohner, 1996), and have different reproductive success 

(Newton, 1995); and therefore, individuals should be assumed to have different 

conservation values unless there is evidence to the contrary (McGregor & Peake, 

1998). 

58

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63

GENERAL CONCLUSION 

Humans have preferentially settled in close proximity of freshwater resources and 

subsequently, freshwater ecosystems and species have suffered from multiple 

historical and on-going stresses from use by humans. Freshwater ecosystems are 

increasingly threatened by human modifications of riverscapes. These stresses are 

often interrelated and endangered species like the gharial (Gavialis gangeticus), are 

highly susceptible to these combined pressures. Understanding the habitat 

requirements of species in such systems is vital for effective conservation planning. 

My study describes gharial habitat use in terms of river depth -channel width profile 

and basking site characteristics; and the effect of anthropogenic activities on the use 

of habitats by the gharials. 

On the basis of the depth profile and shoreline substratum data, approximately one- 

fifth (29/150 sub-segments) of the study area qualified as preferred gharial habitat. 

I quantified the habitat attributes of areas used by the species. The results corroborate 

existing qualitative information on the subject. Gharials appear to prefer areas where 

deep pools are in proximity of large sandy banks. The banks are used for basking and 

the pools are an important refuge from danger, and also offer more stable temperature 

regimes. 

I also examined the effect of anthropogenic activities on the use of habitats by the 

gharials. All human activities appeared to negatively influence the use of areas by 

gharials. Sand mining and cultivation around the banks negatively impacted the use of 

such sites for basking. Gharials were seen less often and in fewer numbers in areas 

64

where fishing was high. Similar results were seen with movement of people and 

livestock along the river stretch. 

I also attempted to test the feasibility of capture-recapture methods for quantitative 

estimation of gharial numbers. I was able to identify individuals based on natural 

blotches on the lateral sides of the gharials tail and along the caudal scutes. Nicks, 

scars and injuries can also be used as a second line of identification. Hence, I propose 

that individual identification, used within a capture recapture framework, can provide 

an effective way for robust estimation of gharial abundances. 


is important to be able to assess species distribution and abundance, and the influence 

of habitat attributes and human disturbances on them. This will help understand 

population dynamics of the species and is vital to determine the status of gharial 

populations and the success of conservation efforts. Moreover, the ability to identify, 

quantify and map the limiting factors for a species will enable the prediction of the 

abundance of that species based on these factors. Population studies are essential to 

determine the status of gharials in the wild, assess the success and validity of 

conservation measures, make management recommendations and design conservation 

strategies. 

65

APPENDIX - 1 

Figure 1: Scatter plots representing the effects of various disturbance factors on 

gharial counts during Occasion 1, in the National Chambal Sanctuary in 2010. Bank 1 

indicates the Rajasthan (left) bank, and Bank 2 indicates Madhya Pradesh (right) 

bank. 

No. of gharials along Raj. bank 


Total No. of gharials 

60 

50 

40 

30 

20 

10 

0 

0.0 0.2 0.4 0.6 0.8 1.0 

Proportion of segment used by people for crossing 

30 

25 

20 

15 

10 

5 

0 

30 

25 

20 

15 

10 

5 

0 

0.0 0.2 0.4 0.6 0.8 1.0 

Proportional extent of sand mining on Raj bank 

0.0 0.2 0.4 0.6 0.8 1.0 

Proportional extent of livestock on Raj bank 


66 



60 

50 

40 

30 

20 

10 

0 

0 5 10 20 30 

30 

25 

20 

15 

10 

5 

0 

0.0 0.2 0.4 0.6 0.8 1.0 

Intensity of fishing 

0.0 0.2 0.4 0.6 0.8 1.0 

Proportional extent of cultivation on Raj bank 

0.0 0.2 0.4 0.6 0.8 1.0 

Proportional extent of people on Raj bank

No. of gharials along MP bank 


30 

20 

10 

0 

0.0 0.2 0.4 0.6 0.8 1.0 

Proportional extent of sand mining on MP bank 

30 

20 

10 

0 

0.0 0.2 0.4 0.6 0.8 1.0 

Proportional extent of livestock on MP bank 

67 



0 10 20 30 

30 

20 

10 

0 

0.0 0.2 0.4 0.6 0.8 1.0 

Proportional extent of cultivation on MP bank 

0.0 0.2 0.4 0.6 0.8 1.0 

Proportional extent of people on MP bank




bank. 




30 

25 

20 

15 

10 

5 

0 

0.0 0.2 0.4 0.6 0.8 1.0 


15 

10 

5 

0 

0.0 0.2 0.4 0.6 0.8 1.0 


15 

10 

5 

0 

0.0 0.2 0.4 0.6 0.8 1.0 


68 




0 5 10 15 

30 

25 

20 

15 

10 

15 

10 

5 

0 

5 

0 

0.0 0.2 0.4 0.6 0.8 1.0 


0.0 0.2 0.4 0.6 0.8 1.0 


0.0 0.2 0.4 0.6 0.8 1.0 




15 

10 

5 

0 

0.0 0.2 0.4 0.6 0.8 1.0 


15 

10 

5 

0 

0.0 0.2 0.4 0.6 0.8 1.0 


69 



0 5 10 15 

15 

10 

5 

0 

0.0 0.2 0.4 0.6 0.8 1.0 


0.0 0.2 0.4 0.6 0.8 1.0 





bank. 




30 

25 

20 

15 

10 

5 

0 

0.0 0.1 0.2 0.3 0.4 0.5 0.6 


12 

10 

8 

6 

4 

2 

0 

12 

10 

8 

6 

4 

2 

0 

0.0 0.2 0.4 0.6 0.8 1.0 


0.0 0.2 0.4 0.6 0.8 1.0 


70 




0 2 4 6 8 10 

30 

25 

20 

15 

10 

5 

0 

12 

10 

8 

6 

4 

2 

0 

0.0 0.2 0.4 0.6 0.8 1.0 


0.0 0.2 0.4 0.6 0.8 1.0 


0.0 0.2 0.4 0.6 0.8 1.0 




14 

12 

10 

8 

6 

4 

2 

0 

14 

12 

10 

8 

6 

4 

2 

0 

0.0 0.2 0.4 0.6 0.8 1.0 


0.0 0.2 0.4 0.6 0.8 1.0 


71 



0 2 4 6 8 10 14 

14 

12 

10 

8 

6 

4 

2 

0 

0.0 0.2 0.4 0.6 0.8 1.0 


0.0 0.2 0.4 0.6 0.8 1.0 





bank. 




30 

20 

10 

0 

0.0 0.1 0.2 0.3 0.4 


3.0 

2.5 

2.0 

1.5 

1.0 

0.5 

0.0 

3.0 

2.5 

2.0 

1.5 

1.0 

0.5 

0.0 

0.0 0.2 0.4 0.6 0.8 1.0 


0.0 0.2 0.4 0.6 0.8 1.0 



72 



30 

20 

10 

0 

3.0 

2.5 

2.0 

1.5 

1.0 

0.5 

0.0 

0.0 1.0 2.0 3.0 

0.0 0.1 0.2 0.3 0.4 0.5 0.6 


0.0 0.2 0.4 0.6 0.8 1.0 


0.0 0.2 0.4 0.6 0.8 1.0 




15 

10 

5 

0 

0.0 0.2 0.4 0.6 0.8 1.0 


15 

10 

5 

0 

0.0 0.2 0.4 0.6 0.8 1.0 


73 



0 5 10 15 

15 

10 

5 

0 

0.0 0.2 0.4 0.6 0.8 1.0 


0.0 0.2 0.4 0.6 0.8 1.0

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