A STUDY ON FAUNAL DIVERSITY OF DABKA AND KHULGAD WATERSHED AREAS OF KUMAON HIMALAYAS, UTTARAKHAND, INDIA

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KALEEM AHMED

CONSERVATION MONITORING CENTRE DEPARTMENT OF WILDLIFE SCIENCES ALIGARH MUSLIM UNIVERSITY AUGARH (INDIA) 2010 ^^v.; ICA^ EXECUTIVE SUMMARY

India has an estimated 8.1% of the world's total biological diversity contained within about 2.4% of the earth's area. India is perhaps better characterized as a "continent" rather than a "country", in terms of the biodiversity and biogeography of its floral and faunal resources, being one of the 12 mega-diversity countries of the world. There are innumerable species, the potential of which is not yet known. It would, therefore, be prudent to not only conserve the species we already have information about, but also species we have not yet identified. The greatest damage to natural habitat and wildlife today is due to ever increasing exploitation of land and natural resources. The ever increasing exploitation is resulting in damage, loss and fragmentation of natural areas in all continuously inhabited parts of the world- be it desert region, temperate or tropical regions. Himalayas too suffer with similar trend in resource use. Himalayas hold a significant unit in the Indian subcontinent and are being utilized as supplier of natural resources by humans since the start of the civilization in this region. Later the origin and settlements in and around the valleys depleted the biodiversity values of the entire region.

Kumoan Himalayas which hold 4.70% of land of the Himalayas within the Indian limits, extend from lower to higher Himalayas, and it can be considered as representative unit possessing all climatic conditions experienced by entire Himalayan region. The forest ecosystem in Uttaranchal (now Uttarakhand), which is part of western Himalayas, shares the biological richness of the Himalayas. The region is densely populated by human beings and is well connected with road transport through its range. The easy approach to most parts of the region has led to the development of the area, as is being happening in other parts of the country. Consequently, random forest clearings were observed for the purpose and most parts of the region are facing severe threats in terms of loss of biodiversity values. Keeping the importance of bio-diversity of the area, the present study was under taken in two watershed areas of Himalaya's viz. Dabka Watershed Area (DWA) and Khulgarh Watershed Area (KWA) with the following prime objectives:

•^ To assess population status and community attributes of birds and mammals in Dabka and KWA ^ To ascertain the vegetation composition in Dabka and KWA •^ To carry out intensive ecological studies on large mammalian community in Dabka and KWA •^ To carry out intensive ecological studies on avian community structure in Dabka and KWA •^ To carry out ecological studies on herpetofauna in Dabka and KWA •^ To study food habit of large carnivores of Dabka and KWA

The present study was carried out in DWA and KWA. The KWA lies between 29° 34" 31' to 29° 41" N latitudes and 79° 32" 15' and 79° 37" E longitudes in Almora district of Kumaon Himalayas, Uttarakhand. The study area spreads over 32 sq. km. and represents middle Shiwaliks. The most dominating tree species in the study area is Pinus roxburghii both in forested and outside forest areas. The other major tree species found in the area are Quercus incana and Lyonia ovalifolia. DWA has an area of 69.06 sq. km and lies between 29° 30' 19" to 29° 24' 09" N latitudes, 79° 17' 53" to 79° 25' 38" E longitudes, in the region of lesser Himalayas of Uttarakhand. DWA is protected as a reserved forest with two forest ranges Vinaiyak and Naina. Most of the study area comes under Vinaiyak forest range of Kumaon

PHD THESIS, EXECUTIVE SUMMARY 1 division with dominating Quercus leucotricophora and few patches of Pinus roxburghii. Taxus baccata and Cedrus deodara are also present as other associates. The Rhododendron arborium is very common throughout the study area.

The sampling was carried out with a range of sampling techniques for mammals, birds, reptiles and amphibians and also for vegetation. Direct and indirect methods were employed for mammalian population estimation. The direct methods comprised trail counts and vantage points scanning. Circular plots of radius 10 meters were established in order to collect indirect evidences and for vegetation composition and structure. Fixed radius Point Counts (r - 20 m) and Species Richness Counting Methods were employed for birds while Adaptive Cluster Sampling (5 m X 5 m) and Stream Transect (5 m X 1000 m) searches were used to sample herpetofauna. The plots and sampling units were laid in proportion to the land use/land cover units. To ascertain food habits of the large carnivores scat analysis techniques were used. The sampling was done from September 2007 to June 2009 in all seasons except monsoons.

Overall 150 sampling points, 65 in Khulgarh and 85 in Dabka were established to know the vegetation composition of both the watersheds. A total of 52 trees species were recorded in both the study sites, of which 34 tree species were identified in DWA and 30 species in KWA. The overall tree density was higher (710.93/ha ± 56.86) in KWA as compared to DWA (246.96/ha ± 6.11) and difference was found to be significant (Z = 6.581, P = 0.000). The overall tree diversity, richness and evenness in DWA was 1.296 ± 0.09, 1.024 ± 0.08 and 0.748 ± 0.04, respectively. Overall diversity, richness and evennes in KWA was 0.645 ± 0.08, 0.731 ±0.10 and 0.444 ± 0.05, respectively. Total mean shrub density in DWA was (4600.88/ha ± 843.27) and in KWA it was (4397.94/ha ± 719.64). Overall herb density in DWA was 39.32/m^ ± 2.75 and in KWA 62.57/m^ ± 12.02. Overall grass density was 154.09/m^ ± 17.55 in KWA while in DWA 93.43/m^ ± 6.02. Q. leucotrichophora was the most dominant tree species with IVI = 128.80 in DWA and in KWA P. roxburghii was most dominant with IVI = 155.

A total of 55 sampling points were established in KWA and 75 in DWA. Each point was monitored at least once in a season. A total of 157 birds in DWA and 102 species in Khulgarh were listed by species listing method. Jackknife 1 was used for stabilization of the number of species observed in watershed areas. In Dabka and Khulgarh watershed areas species turnover reached asymptote at 165 and 110 birds, respectively. In terms of bird diversity rarefaction showed that DWA was more diverse as compared to KWA. Bird density was highest in DWA (29.97 ± 1.79/ha) than in KWA (28.35 ± 1.79/ha). Two-way analysis of variance with seasons (winter, summer) and habitat as a main effect showed that there was no significant difference in bird density between seasons in (Fi,4 = 1.87, P = 0.34) and also there was no significant difference in bird density across different habitats (F4_4 = 1.21, P = 0.26) in DWA. Whereas in KWA there was highly significant difference in bird density between seasons (Fi,4 = 8.57, P = 0.004) and there was also significant difference in bird density across different habitats (F4,4 = 9.90, P = 0.02). Bird density, diversity and richness showed steep decline along the ahitudinal gradient in both the Watersheds. Based on guild structure Dabka bird community was more complex as compared to KWA watershed area because of variation in altitude and complex vegetation structure.

A total of 12 species of mammals were recorded in DWA while 7 species from KWA. A total of 3737 individuals with 588 groups were counted in DWA and 7339 individuals with 410 groups in KWA. In DWA mean group size was recorded highest for rhesus macaque (15.09 ±

PHD THESIS, EXECUTIVE SUMMARY 2 0.67) followed by langur (9.33 ± 0.70), chital (6.35 ± 0.50), sambar (1.35 ± 0.10), muntjac (1.12 ± 0.05) and serow (1.06 ± 0.66). Analysis of variance shows group size varied significantly among different species (F = 85.103, df = 6, P = 0.000). In KWA the highest mean group size was recorded for Rhesus (24.70 ± 0.96), followed by Langur (16.77 ± 0.89) and muntjac (1.44 ± 0.05) and difference was found to be significant (F = 83.500, df = 2, P = 0.000). In DWA encounter rate of chital was highest among all the mammalian species (6.51 animals/km) followed by rhesus macaque (4.35 animals/km) and langur (1.56 animals/km). The encounter rate of all the mammalian species was recorded highest in summer as compared to winter and difference was not found to be significant. In KWA encounter rate of rhesus macaque was highest (9.52 animals/km) among all other mammalian species followed by langur (4.99 animals/km) and wild boar (0.14 animals/km). In KWA, encounter rate of all the mammalian species was also highest in summer as compared to winter though the difference was not found to be significant. The encounter rate of goral using scan technique was higher (1.94 ± 0.30) in Kunjakharak as compared to other vantage points. Across different seasons encounter rate was higher in winter as compared to summer.

Habitat use and overlap studies were carried out on five ungulate species, sambar (Cerviis unicolor), goral (Nemorhaedus goral), muntjac (Muntiacus muntjak), chital {Axis axis) and serow (Capricornis sumatraensis) in DWA and muntjac {Muntiacus muntjak) in KWA. Mean pellet group density (ha ± SE) was recorded highest for sambar (41.56 ± 3.51) followed by goral (23.31 ± 3.45), chital (19.21 ± 3.51), barking deer (7.43 ± 1.21) and serow (1.02 ± 0.10) and difference was found to be significant (Mann Whitney U Test, P = 0.033). Across different habitats, the mean pellet group density of sambar was in dense forest (85.33 ± 12.52) followed by chital (54.34 ± 19.23), barking deer (15.23 ± 6.44). Two Way Analysis of variance showed a significant different between pellet group density of different ungulate species across different habitats (F = 6.38, df = 4, P = 0.027). In KWA, overall mean pellet group density of muntjac was (26.87 ± 5.55). It was found highest in dense forest (81.39 fc 11.57) followed by moderate forest (39.81 ± 7.96) and open forest (2.27 ± 1.28) and difference was found to be significant (F = 54.410, df = 2, P = 0.000). The highest overlap was found between sambar and muntjac (65%) and no overlap was found between chital and goral and chital and serow. Altitude, aspect, slope and vegetation parameters were found important factors for niche overlap analysis of four sympatric ungulate species. The Availability-Utilization (AU) of various habitat parameters showed that goral preferred areas with low tree cover (0-25%) and avoided areas of high tree cover (51-75%), {j^- 87.36, df = 2, P = 0.01) and usually avoided dense forest and showed preference towards open areas in the study area {y^ = 55.67, df = 3, P = 0.01). Chital used wide range of tree cover and shrub cover with preference towards moderate cover (26-50%) in the study area (x^ = 18.57, df = 3. P = 0.01) and (x^ = 25.48, df = 2, P = 0.01), respecfively and also preferred areas of moderate forest and used other habitat according to their availability (x^ = 72.41, df = 4, P = 0.01). Sambar in the study area used less tree cover (0-25%) and used in proportion to availability other higher tree cover categories (x^ = 22.89, df = 3, P = 0.01) and seemed to avoid open forest and showed their preference towards dense forest (x^ = 34.05, df = 2, P = 0.01). Muntjac used both tree cover and shrub cover in proportion to their availability in the study area (x^= 5.85, df = 2, P = 0.01) and (x^= 25.04, df = 2, P = 0.01), respectively while showed preference towards dense forest and seemed to avoid open forests (x^ = 55.97, df = 3, P = 0.01). The AU of tree cover categories showed that serow preferred high tree cover >75% and used other categories in proportion to their availability (x^ = 8, df = 2, P = 0.01). It preferred dense forest and appeared to avoid open forest and used moderate forest in proportion to their availability {y^= 10.28, df- 2, P = 0.01).

PHD THESIS, EXECUTIVE SUMMARY 3 For food habit analysis of carnivores 55 scats of tiger in Dabka and 91 and 118 scats of leopard were analyzed in Dabka and Khulgarh watersheds, respectively. The overall diet diversity of tiger in DWA was 2.923. In total 13 food items were found in the scats (n = 55). Chital constituted (30.91%) of the diet of tiger followed by sambar (21.82%), cow (13.64%) and buffalo (10.00%). The remaining prey items contributed less than (5%) in the diet of tiger. The wild prey constituted 77.36% of the diet of tiger where as domestic prey constituted 23.64% of its diet. In terms of relative biomass consumed sambar and chital are the two most important diet items for tiger in the study area, making up 29.45% and 19.04% of total biomass consumed, respectively. In terms of domestic prey, cow and buffalo constituted 19.04% and 19.99% of the total biomass consumed respectively. Comparison of observed and expected frequencies of occurrence of prey species in tiger scats found that sambar, wildboar and muntjac were utilized more than their availability. Chital was utilized in proportion to its availability while langur and rhesus macaque were found to be utilized less than their availability. Niche overlap between tiger and leopard in Dabka Watershed Area was (a = 0.65). The overall diet diversity of leopard in DWA was 3.003. In total 11 food items were found in the scats (n = 91). Sambar constituted bulk of its diet 27.47% followed by dog 21.98%, rodents 8.79%, goral 7.14% and muntjac 6.59%. In terms of biomass, sambar constituted 54.39% of the total biomass consumed by the leopard in Dabka followed by dog 13.41% and wildboar 5.63%. Sambar and langur were found to be utilized more than their availability. Muntjac, goral and serow were found to be utilized less than their availability. A total of 12 prey species were identified (n = 118) with diet diversity of 2.982 in KWA. Dogs constituted bulk of the diet of leopard 29.66%. In terms of relative biomass consumed, dog contributed major portion of its diet 29.90% followed by muntjac 14.31%, rodents (14.12%), langur 12.06% and macaque 7.55%. Rhesus macaque and muntjac were found to be used more than their availability, whereas langur was found to be utilized in proportion to its availability and wildboar was utilized less than its availability.

During the study period 15 species of reptiles were recorded in DWA and 11 in KWA. Similarly, 7 species of amphibians were recorded in DWA while 4 species in KWA. In total 22 species of reptiles were recorded and 6 species of amphibians. Forest floor density of reptiles in DWA was 87.52 animals/ha and in KWA 77.71 animals/ha. Reptilian diversity of DWA and KWA was 1.519 and 1.227, respectively. Richness in KWA (1.797) was more than DWA (0.932). In both the watersheds, density of reptiles was highest in summer as compared to winter. Diversity, richness and evenness of reptiles were also highest in summer as compared to winter. Reptilian density, diversity, richness and evenness were found to be decreasing with increasing elevation in both the watersheds. In different habitats in DWA, density of reptiles was highest 144.21 animals/ha in moderate forest and lowest (80 animals/ha) in open forest and difference was not found to be significant (F = 1.056, df = 2, P = 0.05). Among different habitats in KWA, density of reptiles was highest 214.44 animals/ha in open forest and lowest (57.14 animals/ha) in dense forest and difference was found to be significant (F = 12.56, df = 4, P = 0.05). Density of amphibians in DWA was 9.38 individuals/ha while diversity and richness were 0.426, 0.674, respectively. Amphibian density in KWA was 5.23 individuals/ha. Diversity and richness values were 0.234 and 0.174, respectively. Among different amphibians species, the density of skittering frog was found highest in both the watersheds. Comparison between the two sites shows that DWA was more dense, diverse and rich than KWA. Jacard's measure for similarity between two areas was 0.725.

PHD THESIS, EXECUTIVE SUMMARY The present study was aimed to study the faunal diversity of both the watersheds and to prepare conservation strategies for them. As there is complete interdependence in nature, change in a habitat affects the diversity of species contained in it. Conversely, any change in the number and assembleges of species also affects the nature of habitat. So there is a need to conserve biodiversity because of interdependence of species in nature for survival demands conservation of all elements of biodiversity. The first step of most conservation planning is to identify areas that want protection. The main criteria used to identify such areas are biodiversify, rarify, population abundance, environmental representativeness and site area. In past the protection of individual, usually rare species was used to select the site for protection but this approach to reserve selection has its strength and weakness. There are only two Wildlife Sanctuaries existing in Kumoan i.e Ashok Wildlife Sanctuary (Pithoragarh district, area = 600 km^) and Binsar Wildlife Sanctuary (Bageshwer district, area = 45.59 km^). The percent protected area is too small as compared to the whole geographical area of Kumoan (2,1032 km^). Both the sanctuaries are facing severe threats. Binsar sanctuary has limited conservation potential by having only approximately 4 km^ of Oak {Quercus sp.) patch. So, it is strongly recommended the creation of DWA as sanctuary based on the overall biodiversity assesment. The area holds maximum biodiversity and is relatively less disturbed. The area still also have higher density of certain ungulates species when compared to other PAs of Himalayas. Moreover, sighting of a rare species i.e. serow which was thought to be wiped out from China Peak enhance the importance of study site to be declared as sanctuary. The creation of this sanctuary and the buffer zone of Corbett Tiger Reserve will act as a corridor between them. These corridors would allow faunal and floral diversity to disperse from one reserve to another, facilitating gene flow and colonization of suitables sites. They would also help to preserve mammals and birds that migrate seasonally among a series of different habitat altitude and habitat to obtain food. The DWA is a river catchment and can serve as a potential biodiversity hotspot for conservation.

PHD THESIS, EXECUTIVE SUMMARY A STUDY ON FAUNAL DIVERSITY OF DABKA AND KHULGAD WATERSHED AREAS OF KUMAON HIMAUYAS, UTTARAKHAND, INDIA

kl^/ THESIS ;^-A /' SPBMITTED FOR THE AWARD OF THE PEQREE OF

Mottox of $I)Uo£(opl)p

WILDLIFE SQIENCE

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BV KALEEM AHMED

CONSERVATION MONITORING CENTRE DEPARTMENT OF WILDLIFE SCIENCES ALIGARH MUSLIM UNIVERSITY AUGARH (INDIA) 2010 0 8 M-1 /i •-

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T7839 Jamal A. Khan Ph. D. Oepartmcfit of WXdlfc Sdcncei Conservidofl M«lboriiT| Centfe i Professor, Department of Wildlife Sciences, A.M.U. Al^rli M

CERTIFICATE

This is to certify that the thesis titled ^*A Study on Faunal Diversity of

Dabka and Khulgad Watershed Areas of Kumaon Himalayas,

Uttaraichand, India" submitted for the award of Ph.D. degree in Wildlife

Science, of the Aligarh Muslim University, Aligarh is the original work of

^ Mr. Kaieem Ahmed. This work has been done by the candidate under my

supervision.

x^ ^^^•\^^^^ Jamal A. Khan, Ph. D.

Date: 5 February 2010 Acknowledgements vn List of Tables x List of Figures ^''v

CHAPTER 1 INTRODUCTION

1.1 The Himalayas 1 1.2 The Diversity 4 1.3 Indian Scenario 8 1.4 Rationale 9

CHAPTER 2 STUDY AREA

2.1 Historical Background 12 2.2 Watershed 14

2.3 Khulgarh Watershed Area (KWA) 15 2.3.1 Location and Extent 15 2.3.2 Climate 15 3.3.3 Physiography 16 2.3.4 Topography and Drainage 16 2.3.5 Geology 16 2.3.6 Natural Vegetation 17 2.3.7 Fauna 17 2.3.8 Human habitation and dependency on forests 18

2.4 Dabka Watershed Area (DWA) 18 2.4.1 Location and Extent 18 2.4.2 Topography 19 2.4.3 Climate 19 2.4.4 Human Habitation 20 2.4.5 Dependency on forest 20 2.4.6 Flora 21 2.4.7 Fauna 21 2.5 Habitat Categories of both Watersheds 21

CHAPTER 3 VEGETATION COMPOSITION

3.1 Introduction 28

3.2 Methodology 30 3.3 Analysis 31

Contents 3.4 Results 32 3.4.1 Trees 32 3.4.2 Shrubs 33 3.4.3 Herbs 35 3.4.4 Grasses 36 3.4.5 Sapling and Seedling 36 3.4.6 Human habitation/ Hamlets 37 3.4.7 Tree species dominance 37

3.5 Discussion 49

CHAPTER 4 BIRD COMMUNITY STRUCTURE

4.1 Introduction 54 4.2 Literature Review 55 4.2.1 Bird habitat-relationship 55 4.2.2 Foraging studies 57 4.2.3 Environmental influence 58 4.2.3 Disturbance studies 58 4.2.4 Comparison of methods for assessing bird abundance 59 4.2.5 Management studies 60 4.2.6 Overview of bird studies in the Indian Himalayas 61 4.2.7 Overview of bird studies in Kumoan Himalayas 61

4.3 Methodology 62 4.3.1 Guild Structure 62 4.4 Analysis 63

4.5 Results 65 4.5.1 Accuracy of sample size 65 4.5.2 Comparison of watershed areas in terms of bird diversity 66 4.5.3 Comparison of bird density 66 4.5.4 Comparison of diversity and richness 67 4.5.5 Other aspect of comparison 67 4.5.6 Guild structure comparison 77 4.5.7 Bird habitat relationship 77 4.5.8 Effect of density on disturbance pattern 77 4.6 Discussion 82

Contents W CHAPTER 5 STATUS AND POPULATION STRUCTURE OF MAMMALS

5.1 Introduction 89

5.2 Methodology 92 5.2.1 Scanning technique for goral 92 5.2.2 Trail count for all other mammalian species 93 5.3 Analysis 93

5.4 Results 94 5.4.1 Population structure 94 5.4.1.1 Group Size 94 5.4.2 Sex ratio 99 5.4.2.1 Langur 99 5.4.2.2 Rhesus Macaque 99 5.4.2.3 Muntjac 100 5.4.2.4 Sambar 100 5.4.2.5 Serow 100 5.4.2.6 Goral 101 5.4.2.7 Chital 101 5.4.2.8 Wild boar 101 5.4.3 Encounter rate 101 5.4.4 Scanning 102

5.5 Discussion 109 5.5.1 Encounter rate 109 5.5.2 Group size 109 5.5.3 Age and sex composition 112

CHAPTER 6 HABITAT USE OF UNGULATES

6.1 Introduction 114

6.2 The Himalayan ungulates 116 6.3 Introduction to Himalayan ungulates 116 6.3.1 Serow {Capricornis sumatrenesius) 116 6.3.1 GoxQ.\{Nemorheduss^^.) 117 6.3.3 Sambar {Rusa unicolor) 118 6.3.4 Muntjac {Muntiacus muntjak) 119 6.3.5 Chital (Axis axis) 119

6.4 Methodology 120

Contents 6.5 Statistical analysis 121

6.6 Results 123 6.6.1 Habitat use of ungulates 123 6.6.2 Dabka Watershed Area 123 6.6.2.1 Ordination technique 124 6.6.2.2 Use of AU data of goral in DWA 126 6.6.2.3 Use of AU data of chital in DWA 126 6.6.2.4 Use of AU data of sambar in DWA 127 6.6.2.5 Use of AU data of muntjac in DWA 127 6.6.2.6 Use of AU data of serow in DWA 128

6.6.3 Khulgarh Watershed Area 128 6.6.3.1 Use of AU of muntjak in KWA 128 6.6.4 Overlap between ungulates in DWA 129

6.7 Discussion 154 6.7.1 Goral 154 6.7.2 Chital 155 6.7.3 Sambar 156 6.7.4 Muntjac 157 6.7.5 Serow 158 6.7.6 Ecological separation 158

CHAPTER 7 FOOD HABIT OF TIGER AND LEOPARD

7.1 Introduction 160 7.2 Importance of big cat 161

7.3 Materials and Methods 165 7.3.1 Collection and preservation of scats 165 7.3.2 Identification of prey remains from scats 166 7.3.3 Sample size estimation for minimum number of hair 167 7.3.4 Sample size estimation for the minimum number of scats 167 7.3.5 Estimation of biomass 168 7.3.6 Analysis of prey selection 169 7.3.7 Niche overlap 170

7.4 Results 170 7.4.1 Sample Size 170 7.4.1.1 Sample size estimation for tiger 170 7.4.1.2 Sample size for leopard in Dabka 170 7.4.1.3 Sample size estimation for leopard in Khulgarh 171

Contents 7.4.2 Diet diversity in tiger in DWA 171 7.4.3 Biomass consumed 172 7.4.4 Prey selectivity for tiger 172 7.4.5 Diet diversity of leopard in DWA 172 7.4.6 Prey selectivity of leopard in DWA 173 7.4.7 Diet diversity of leopard in KWA 173 7.4.8 Prey selectivity of leopard in KWA 174

7.5 Discussion 184 7.5.1 Food habit of tiger 185 7.5.2 Food habit of Leopard 187 7.5.3 Prey selectivity 189

CHAPTER 8 HERPETOFAUNA

8.1 Introduction 190

8.2 Methodology 193 8.2.1 Reptiles 193 8.2.2 Amphibians 194 8.3 Analysis 194

8.4 Results 195 8.4.1 Reptiles 195 8.4.1.1 Dabka Watershed Area (DWA) 195 8.4.1.2 Khulgarh Watershed Area (KWA) 196 8.4.2 Amphibians 207

8.5 Discussion 211 8.5.1 Reptiles 211 8.5.2 Amphibians 213

CHAPTER 9 CONSERVATION THREATS AND MANAGEMENT

9.1 Introduction 215

9.2 Conservation Threats 216 9.2.1 Fire 216 9.2.2 Fuel wood collection 220 9.2.3 Fodder 220 9.2.4 Timber 221

Contents 9.2.5 Medicinal plant extraction 221 9.2.6 Pine seed and Rhododendron flower extraction 221 9.2.7 Poaching 221 9.2.8 Tourism 222

9.3 Conservation Strategy 223 9.3.1 Protected Area coverage and management of forest 223

Bibliography 227 Appendix 262

Contents ACKNOWLEDGEMENTS Thanks to the Almighty Allah who gave me the power and strength to complete this document.

As an average student I would never have been able to complete this work had I not got the support of various persons. Amnesia is an asset while writing acknowledgement otherwise the list of these gentlemen and women would be voluminous than the actual work.

I sincerely thank NRDMS Division, Department of Science and Technology, Government of India, for funding this research project under Ecological Modeling for Himalayas for Uttaranchal (now Uttarakhand) Transect. I thank R. Siva Kumar, Head, NRDMS, Department of Science & technology and Dr. Nisha Mendiratta, Addl. Director & Scientist 'E', NRDMS Division for their interest in this research.

I place on record my sincere gratitude to Prof. Jama/ A. Khan my supervisor and teacher for showing faith and introducing me first to the terai forest for my M.Phil and then to the Himalayas for Ph.D thesis. His constructive and perpetual guidance and support helped me a lot in streamlining the study

I am thankful to Dr. Affifullah Khan, Chairman Department of Wildlife Science for his valuable help and guidance throughout the compilation of the thesis. I am equally thankful to Professor H.S.A. Yahya, Dr. Satish Kumar (Reader) and Dr. Orus Ilyas and Dr. Faiza Abbasi faculty at Department of Wildlife Sciences for their timely help and guidance.

I thank Prof J.S. Rawat (Head, Department of Geology, Kumoan University, Nainital) for providing maps of Khulgarh and allowing me to use their GIS lab. I also thank Dr S. Sreekesh (Asso. Prof JNU) for providing boundary map of Dabka and Prof Charu C. Pant (Deptt. Of Geology, KU, Nainital) for providing toposheets of the Dabka I also thank Director WII (Wildlife Institute of India) for allowing me to use the library for literature survey and Dr. S.A. Hussain for arranging the accommodation.

My special thanks are due to local forest staff of Dabka and Khulgarh watersheds for being cooperative and providing support during fieldwork.

Contents vii / thank my field assistants Raju, Chotu (Khulgarh), Vijay (Dabl

I specially thank Mr. Akhlaq Khan (Property Incharge) and the security guard and his family for treating me as their family member at Ardee Estate In Ranikhet that was used as base camp during entire study period.

I also thank non teaching staff of DWS specially Mrs. Anjum, Rafat Yasmeen, and Mr. Mustafa Kamal, Chhotte Khan, Gaffar, Arshad, Azim, Tanveer, Nadeem and Vir Singh for their support.

Special thanks are due to Tanweer A. Dar (Dy. SP J&K police) and Dr. Bllal Habib (Scientist C) for their help in data analyses. Both of them were constant source of my inspiration whenever I lost my temper. Their critical comments not only helped in the preparation of this draft but also helped me in my personal life to get rid of difficult situations. I specially thank Mr. Junaid Nazir (RA, EADA, Abu Dhabi) and Khursheed Ahmed (Asst. Prof. 5KUAST, University) for his continuous support and guidance throughout the study.

My lot of love and special thanks to Athar, Shamshad and Mehraj in finalizing the thesis, especially Athar for proof reading, discussions and very constructive comments on the draft of this manuscript.

I am also thankful to my classmates Nasser, Kamlesh, Rohit, Zaibin, Vyom, Vijayan for their advice and support. Many thanks to my friends Javed, Neha Mid ha and Shipra Verma. I am also thankful to my seniors Mr. Usham, Mr. Sharad, my juniors Andaleeb, Tanushree, Tabassum, Bushra, Puja, Azram, Shallnl, Saraj, Tawqeer, Aftab, Shah Nawaz.

Special thanks to my friend NIsa (Project Officer WWF, India) for checking the bird checklist and Masood Khan and Shah Bllal for checking the final references.

I am also thankful to my friends In Aligarh Muslim University especially Dr. Manzoor, Sajad, Kaiser Ha mid and at home Dr. Javid, Suhall, Asif, Tahir, Irfan and Iftlkhar.

Contents viii Special thanks to my Uncles Mr. M. Y. Prince, Mr. Abdul Rahman and Mr. Ajmal Dar for their continuous support and encouragement throughout the study. I am also thankful to my Mamus especially Mr. Gulzar Ahmed Mir and Mr. Qayyoom Ahmed Mir for their continuous encouragement and support from my childhood till now for shaping my career in right direction.

I specially thank Mr. Farooq Shah (Assistant Commisioner Rajouri) for his encouragement and showing interest in my research work.

I am lucky enough to be born in a family who despite certain limitations value education very high. I got financial help, when I did not deserve it and emotional support when I needed it the most. I am here because of my family otherwise the battle would have been lost long back. I thank my father and mother for their love, affection and care. I thank you for bringing me into this world and bringing me up. I also thank my brothers Saleem, Sadaqet and Khalil, my sisters Nasreen, Rabia, my bhabi Fareena and all the kids especially Dilbar, Himaal, Naina, Sharayar, Aleem and Azeem. Special thanks to my two niece Umar and Nashra.

If I had to dedicate this thesis, it would have been my friend Dr. Saima. Thanks dear for accepting me the way I am with all my faults and weakness. Thanks for being with me in my ups and downs. Your presence around gives me reasons to smile.

V^too*4i

n<^aleem Ahmed)

Contents LIST OF TABLES PAGE NO

CHAPTER 2

Table: 2.1 Changes in the human population during 19"^ and 20"^ century in 13 Kumoan Himalayas Table: 2.2 Mean temperature and rainfall in different climatic zones of Kumoan 22 Himalayas Table: 2.3 Forest cover categories of Dabka and Khulgarh Watershed Area 23

CHAPTERS

Table: 3.1 Tree density, diversity, richness and evenness in different habitats in 38 DWA Table: 3. 2 Tree density, diversity, richness and evenness in different habitats in 38 KWA Table: 3.3 Shrub density, diversity, richness and evenness in different habitats in 38 DWA Table: 3.4 Shrub density, diversity, richness and evenness in different habitats in 38 KWA Table: 3.5 Herb density, diversity, richness and evenness in different habitats in 38 DWA Table: 3.6 Herb density, diversity, richness and evenness in different habitats in 39 KWA Table: 3.7 Grass density, diversity, richness and evenness in different habitats in 39 DWA Table: 3.8 Grasses density, diversity, richness and evenness in different habitats in 39 KWA Table: 3.9 Mean sapling and seedling density in different habitats in DWA 39 Table: 3.10 Mean sapling and seedling density in KWA 39 Table 3.11 Tree density (ha) in both watershed areas of Kumoan Himalayas 40

Contents CHAPTER 4

Table: 4.1 Review of bird studies conducted in Kumoan Himalayas 59 Table: 4.2 Variation of Bird Density (D), Density of Clusters (DS) Encounter Rate 71 (n/K) and Average Cluster Size across different seasons in DWA Table: 4.3 Variation of Bird Density (D), Density of Clusters (DS) Encounter Rate 71 (n/K) and Average Cluster Size across different habitats in DWA Table: 4.4 Variation of Bird Density (D), Density of Clusters (DS) Encounter Rate 71 (n/K) and Average Cluster Size across different seasons in KWA Table: 4.5 Variation of Bird Density (D), Density of Clusters (DS) Encounter Rate 72 (n/K) and Average Cluster Size across different habitats in KWA Table: 4.6 Mean diversity and richness of birds in Dabka and Khulgarh Watershed 72 Area Table: 4.7 Spearman rank correlation coefficients between bird species diversity 81 and richness with habitat parameters in DWA Table: 4.8 Spearman rank correlation coefficients between bird species diversity 81 and richness with habitat parameters in KWA Table: 4.9 Overall bird density in disturbed and undisturbed areas in Dabka and 81 KWA

CHAPTER 5

Table: 5.1 Characteristics of scanning areas in Dabka Watershed Area 92 Table: 5.2 Overall mean group size of different mammalian species in DWA 97 Table: 5.3 Mean group size of different mammalian species in winter in DWA 97 Table: 5.4 Mean group size of different mammalian species in summer in DWA 97 Table: 5.5 Overall mean group size of different mammalian species in KWA 98 Table: 5.6 Mean group size of different mammalian species in winter in KWA 98 Table: 5.7 Mean group size of different mammalian species in summer in KWA 98 Table: 5.8 Encounter rate (animals/hour ± SE) of goral in different vantage points in no DWA Table: 5.9 Percentage Sex ratio of mammals in Dabka Watershed Area 110

Contents XI Table: 5.10 Percentage sex ratio of mammais in Khulgarh Watershed Area 110 Table: 5.11 Encounter rate (animals/km) of mammals in Dabka Watershed Area 104 Table: 5.12 Encounter rate (animals/km) in Khulgarh Watershed Area 104

CHAPTER 6

Table: 6.1 Mean pellet group density (/ha) of ungulates species in DWA 133 Table: 6.2 Mean pellet group density (/ha) of ungulates across different habitats in 133 DWA Table: 6.3 Pair wise niche overlap between sympatric ungulate species in DWA 133 Table: 6.4 Percentage overlap between all combinations of pairs of species of 134 ungulates in their association with altitude, aspect, slope, tree cover, shrub cover and habitat in DWA Table: 5.5 Principal Component Analyses of animal and random plots of muntjac in 140 DWA Table: 6. 6 Principal Component Analyses of animal and random plots of goral in 142 DWA Table: 6.7 Principal Component Analyses of animal and random plots of sambar in 144 DWA Table: 6.8 Correlation between pellet group density of chital, sambar, serow, goral 146 and muntjac with different habitat variables in DWA Table: 6.9 Correlation between pellet group density of muntjac with different 147 habitat variables in KWA Table: 6.10 Availability-utilization of tree cover, shrub cover, slope, altitude, habitat 148 and aspect by goral in DWA Table: 6.11 Availability-utilization of tree cover, shrub cover, slope, altitude and 149 habitat by chital in DWA Table: 6.12 Availability-utilization of tree cover, shrub cover, slope, altitude, habitat 150 and aspect by sambar in DWA Table: 6.13 Availability-utilization of tree cover, shrub cover, slope, altitude, habitat 151 and aspect by muntjac in DWA Table: 6.14 Availability-utilization of tree cover, shrub cover, slope, altitude, habitat 152

Contents xii and aspect by serow in DWA Table; 6.15 Availability-utilization of tree cover, shrub cover, slope, altitude, habitat 153 and aspect by muntjac in KWA

CHAPTER 7

Table: 7.1 Prey represented in 55 tiger scats in DWA 175 Table: 7.2 Prey represented in 91 scats of leopard in DWA 176 Table: 7.3. Prey represented in 118 scats of leopard in KWA 177 Table: 7.4 Frequency of occurrence of major prey species in tiger Panthera 186 tigris tigris scats from different areas of the Indian subcontinent

CHAPTER 8

Table: 8.1 Diversity, richness and evenness of reptiles in different seasons in DWA 199 Table: 8.2 Reptiles density, diversity, richness and evenness in different habitats in 199 DWA Table: 8.3 Density, diversity, richness and evenness of reptiles in DWA 199 Table: 8.4 Correlation of reptile density with different microhabitat factors in 199 Dabka and KWA Table: 8.5 Amphibians density in Dabka and Khulgrah Watershed Areas 209 Table: 8.6 Density of amphibians on different stream transect in Dabka and KWA 209 Table: 8.7 Correlation of amphibian density with different microhabitat variables 209 in Dabka and KWA

CHAPTER 9

Table: 9.1 Proportion available {?io). Proportion dead (P/e) and 95% Bonferroni 218 confidence limits for dominant plant species in Dabka. Table: 9.2 Mean number of cut trees, lopped trees and cattle dung piles (/ha) in 226 Dabka and KWA

Contents xiu LIST OF FIGURES PAGE NO

CHAPTER 2

Figure: 2.1 Monthly Meteorological data of KWA during the study period 23 Figure: 2.2 Location Map of the Study Area 24 Figure: 2.3 Drainage map of Dabka Watershed Area 25 Figure: 2.4 Road map of Dabka Watershed Area 25 Figure: 2.5 Settlements map of Dabka Watershed Area 26 Figure: 2.6 Drainage map of Khulgarh Watershed Area 26 Figure: 2.7 Road map of Khulgarh Watershed Area 27 Figure: 2.8 Settlements map of Khulgarh Watershed Area 27

CHAPTER 3

Figure: 3.1 Diversity, richness and evenness of trees on different aspects in DWA 42 Figure: 3.2 Density of trees on different aspects in DWA 42 Figure- 3 3 Diversity, richness and evenness of shrubs on different aspects in 42 DWA Figure: 3.4 Density (/ha) of shrubs on different aspects in DWA 43 Figure: 3.5 Herbs and grasses density (/m^) on different aspects in DWA 43 Figure: 3 6 Diversity, richness and evenness of herbs on different aspects in 43 DWA Figure: 3.7 Diversity, richness and evenness of grasses on different aspects in 44 DWA Figure: 3.8 Density (/ha) of trees on different aspects in KWA 44 Figure: 3.9 Diversity, richness and evenness of trees on different aspects in KWA 44 Figure: 3.10 Density (/ha) of shrubs on different aspects in KWA 45 Figure: 3.11 Diversity, richness and evenness of shrubs on different aspects in 45 KWA Figure: 3. 12 Herbs and grasses density (/m^) on different aspects in KWA 45 Figure: 3.13 Herb diversity, richness and evenness on different aspects in KWA 46 Figure: 3.14 Grass diversity and richness on different aspects in KWA 46

Contents xiv Figure: 3.15 Tree, cut tree and lopped trees density(/ha) in relation to human 46 habitation in DWA

Figure: 3.16 Tree, cut tree & lopped tree density(/ha) in relation to human 47 habitation in KWA

Figure: 3.17 Tree diversity, richness and evenness in relation to human 47 habitation in DWA

Figure: 3.18 Tree diversity and richness in relation to human habitation in KWA 47 Figure: 3.19 Shrub density (/ha) in relation to human habitation in DWA 48 Figure: 3.20 Shrub density (/ha) in relation to human habitation in KWA 48

Figure: 3.21 Shrub diversity in DWA and KWA in relation to human habitation 48

CHAPTER 4

Figure: 4.1 Performance of Jackknife 1 estimator for DWA 73 Figure: 4.2 Performance of Jackknife 1 estimator for KWA 73 Figure: 4.3 Rarefaction Curves for Dabka and Khulgarh Watershed Areas 73 Figure: 4.4 Density (/ha) of bird along altitudinal gradients in DWA 74 Figure: 4.5 Diversity of bird along altitudinal gradients in DWA 74

Figure: 4.6 Bird richness along altitudinal gradients in DWA 74 Figure: 4.7 Bird evenness along altitudinal gradients in DWA 75

Figure: 4.8 Bird density (/ha) along altitudinal gradients in KWA 75

Figure: 4.9 Bird diversity along altitudinal gradients in KWA 75 Figure: 4.10 Bird richness along altitudinal gradients in KWA 76

Figure: 4.11 Bird evenness along altitudinal gradients in KWA 76 Figure: 4.12 Cluster analysis of bird community based on feeding niche in DWA 79 Figure: 4.13 Cluster diagram of bird community based on feeding niche in KWA 80

CHAPTER 5

Figure: 5.1 Group size of goral in different group sizes in DWA 105 Figure: 5.2 Group size of chital in different group sizes in DWA 105 Figure: 5.3 Group size of muntjac in different group sizes in DWA 105

Contents xv Figure: 5.4 Group size of sambar in different group sizes in DWA 106 Figure: 5.5 Group size of serow in different group sizes in DWA 106 Figure: 5.6 Group size of langur in different group sizes in DWA 106 Figure: 5.7 Group size of rhesus macaque in different group sizes in DWA 107 Figure: 5.8 Group size of muntjac in different group sizes in KWA 107 Figure: 5.9 Group size of langur in different group sizes in KWA 107 Figure: 5.10 Group size of rhesus macaque in different group sizes in KWA 108

CHAPTER 6

Figure: 6.1 Ordination of animal and random plots of muntjac in DWA 141 Figure: 6.2 Ordination of animal and random plots of goral in DWA 143 Figure: 6.3 Ordination of animal and random plots of sambar in DWA 145

CHAPTER 7

Figure: 7.1 Standardization of minimum number of hair required per scat 178 to know the food habit of tiger in DWA Figure: 7.2 Number of prey items detected in tiger scat (n = 55) in DWA 178 Figure: 7.3 Standardization of minimum number of hair required per scat to 179 know the food habit of leopard in DWA Figure: 7.4 Number of prey items detected in leopard scat (n = 91) in DWA 179 Figure: 7.5 Standardization of minimum no of hairs required per scat to 180 know the food habit of leopard in KWA Figure: 7.6 Number of prey items detected in leopard scat (n = 118) in KWA 180 Figure: 7.7 Food habit of tiger in DWA (n=55) from December 2007 to June 181 2009, Uttarakhand, India, 95% boostrap confidence interval Figure: 7.8 Food habit of leopard in DWA (n=91) from December 2007 to 181 June 2009, Uttarakhand, India 95% boostrap confidence interval Figure: 7.9 Food habit of leopard in KWA (n = 118) from September 2007 to 182 June 2009, Uttarakhand, India, 95% boostrap confidence interval Figure: 7.10 Comparison of observed and expected proportions of prey consumed 182

Contents xv\ in scats based on encounter rate of prey species of tiger in DWA. Figure: 7.11 Comparison of observed and expected proportions of prey consumed 183 in scats based on encounter rates of prey species of leopard in DWA. Figure: 7.12 Comparison of observed and expected proportions of prey use in 183 scats based on encounter rates of prey species of leopard in KWA

CHAPTER 8

Figure: 8.1 Comparison of snake density (/ha) with rest of reptiles in different 200 seasons in DWA Figure- 8 2 Reptilian diversity, richness and evenness in different seasons in 200 DWA Figure: 8.3 Percentage of network of clusters of reptiles in DWA 200 Figure: 8.4 Percentage of clusters with different species of reptiles in DWA 201 Figure: 8.5 Percentage of clusters with different number of species of reptiles 201 in winter and summer seasons in DWA Figure: 8.6 Percentage of clusters with number of reptiles in DWA 201 Figure: 8.7 Percentage of clusters with number of reptiles in winter and 202 summer seasons Figure: 8.8 Reptile density (/ha) along altitudinal gradients in DWA 202 Figure: 8.9 Reptile diversity, richness and evenness along the altitudinal 202 gradients in DWA Figure: 8.10 Comparison of snake density with rest of reptiles in different 203 seasons in KWA Figure: 8.11 Reptiles diversity, richness and evenness in different seasons in KWA 203 Figure: 8.12 Percentage of network of cluster of reptiles in KWA 203 Figure: 8.13 Percentage of Clusters with different species of reptiles in KWA 204 Figure: 8.14 Percentage of clusters with different number of species of reptiles 204 in winter and summer seasons in KWA Figure: 8.15 Percentage of clusters with number of reptiles in KWA 204 Figure: 8.16 Percentage of clusters with number of reptiles in winter and 205 summer seasons in KWA Figure: 8.17 Reptiles density along altitudinal gradients in KWA 205

Contents xvii Figure: 8.18 Reptiles diversity, richness and evenness along altitudinal 205 gradients in KWA Figure: 8.19 Comparison of reptile density in Dabka and KWA 206 Figure: 8.20 Figure Comparison of reptiles diversity and richness of Dabka and 2O6 KWA Figure: 8.21 Diversity, richness and evenness of amphibians in DWA 210 Figure: 8.22 Diversity, richness and evenness of amphibians in KWA 210

CHAPTER 9

Figure: 9.1 Percentage of dead trees in different GBH categories 219 Figure: 9.2 Percentage of dead trees in different height categories in DWA 219

Contents xviii LIST OF APPENDIX PAGE NO

Appendix: I Density, diversity, richness and evenness of bird guilds in 262 different habitats in DWA Appendix: If Density, diversity, richness and evenness of bird guilds in 263 different habitats in KWA Appendix: III Checklist of birds recorded in Dabka Watershed Area 264 Appendix: IV Checklist of birds recorded in Khulgarh Watershed Area 270 Appendix: V Checklist of mammalian species recorded in Dabka Watershed Area 274 Appendix: VI Checklist of mammals recorded in Khulgarh Watershed Area 274 Appendix: VII Checklist of reptile species recorded in Dabka Watershed Area 275 Appendix: VKI Checklist of reptile species recorded in Khulgarh Watershed Area 275 Appendix: IX Checklist of Amphibian species recorded in Dabka Watershed Area 276 Appendix: X Checklist of Amphibian species recorded in Khulgarh Watershed 276 Area

Contents XIX CHAPTER 1 INTRODUCTION l.lThe Himalayas The Himalayas embrace the complex system of nearly parallel ranges of tertiary mountains.

These mountains are one of the youngest formations and are mainly having a northwest to southwest orientation. The main range of the Himalayas comprises of three zones; the outer

Himalayas (up to 1500m) the middle Himalayas (up to 5000m) and the greater Himalayas, the highest mountain range in the world, with peaks such as Everest exceeding 8800m

(Wadia 1966, Jhingran 1981). The Shiwaliks run parallel to the outer Himalayas on the southern side and to the north of the Indo-gangetic plains. The fold mountains, the Himalayas had originated as a result of tectonic movements of continental plates and are believed to be still growing (Vinod 1999). The formation of the Himalayas resulted in new barriers and corridors which influenced the dispersal of flora and fauna. Being the meeting point of two biogeographic realms, viz., the Oriental and the Palaearctic (Mani 1974), the Himalayas provide various habitats that are occupied by many primitive as well as newly evolved species (Vinod 1999).

The location, climate and topography of the Himalayas have endowed it with rich and diverse life forms. Of the 372 mammalian species found in India, as many as 241 species (65%) are recorded in the Himalayas and as many as 29 (37%) mammalian species listed under

Schedule I of Indian Wildlife (Protection) Act (1972) occur in the Himalayas (Ghosh 1996).

However, scientific information on many of these species is still lacking. With the exception of a few ecological studies which have been carried out in recent past (Green 1985, Kattel

1990, Chundawat 1992. Sathyakumar 1994, Bhatnagar 1997, Manjrekar 1997), all other information is based on status survey (Schaller 1977, Gaston et al. 1981, 1983, Fox et al.

CHAPTER 1 INTRODUCTION 1 1988, 1991 & 1992, Cavalllni 1990, 1992, Gaston and Garson 1992, Levari and Appollonio

J 993. Sathyakumar 1993) and short term studies (Mishra 1993 and Pendharkar 1993).

The Indian Himalayas are also inhabited by about 51 million (about 6%) of Indian population

(Anon. 1993). The human population in the area has increased over 170% since 1951

(Moddie 1981). Alterations in cropping patterns and development activities in the Himalayas have led to the shrinkage of many prime wildlife habitats. The existing and proposed network of protected areas in the Indian Himalayan region covers ca. 9.2% of the total range (Rodgers andPanwar 1988).

Biogeographically, the Himalayas are divisible into four provinces viz., northwestern, western, central and eastern (Rodgers and Panwar 1988), each characterized by distinctive flora and fauna. In the west, the Sutlej River makes a boundary between the western and northwestern Himalayas (Mani 1974). The Himalayan mountain ranges have an area of about

236,300 km^ in India which is approximately seven percent of the country's total land surface. However, their value in terms of natural resources is much greater than their area implies. The most important resoorce must be water. Over 300 million people in the Indo- gangetic plain are totally dependent on Himalayan waters for drinking, irrigation, sewage disposal, electricity and industry. This resource is not, unfortunately, infinite and has been depleted for the last couple of decades. Dry season waterflow is shrinking, monsoon floods are increasing, and reservoirs silt up even more rapidly. All of these problems are squarely the result of inadequate conservation of forest cover and hence, soil and water resources.

The steep slopes, unconsolidated soils and intense rainfall all make the Himalayan ecosystem one of extreme fragility. And yet, one can see more and more evidence of cultivation on

CHAPTER 1 INTRODUCTION 2 excessively steep slopes, livestock densities way in excess of carrying capacities, and forests under ever-mounting pressures of demand for timber and firewood. The Himalayas must rank as one of the most actively degraded ecosystems on earth (Rodgers and Panwar 1988a).

These environmental pressures have taken their toll of biological resources, plant and animal species. There are more endangered taxa in the Himalayas than anywhere else in India

(Rodgers and Panwar 1988).

The extremes of climate and vegetation types, and overall low productivity of cold, high altitude areas, means that most animal species require large areas to maintain adequate viable populations. For bears, snow leopard, leopard, wolves, tahr, ibex, markhor, serow, musk dear, takin etc. their requirements may be hundreds rather than tens of square kilometers which encompass both summer and winter dispersal areas (Rodgers and Panwar 1988a).

Indian wildlife management has learnt how to conserve the resources of deciduous forests and grasslands. We are learning how to tackle the problems of the evergreen forests and the deserts. But no real effort has been directed at the Himalayas, there is still a woeful lack of accurate information on the distribution, abundance and ecological needs of all Himalayan wildlife. These parameters are essential prerequisites of good management and rational conservation planning.

Uttarakhand is very rich in biodiversity and is represented by biogeographic zones 2B western Himalayas and 78 shiwaliks in the region. Different forest types can be identified in the state that spread over 34,661 km^. The forest department controls about 23,988 km^

(64.81%). About 18.7% of the total area under the forest department has been clearly

CHAPTER 1 INTRODUCTION 3 earmarked for biodiversity conservation, which resulted in the creation and management of twelve Protected Areas (PAs) in the state, which harbor's a great diversity of faunal and flora! species, distributed in a variety of topography types and climatic conditions.

The state of Uttarakhand is divided into two regions, Garhwal and Kumoan (Rodgers and

Panwar 1988). The state holds populations of all species characteristic of this zone, although many populations are now so fragmented and their habitats so degraded that they have doubtful viability. Wildlife information for this region is usually subjective and mainly based on hearsay, there is a paucity of direct precise quantitative data on distribution and abundance

of even quite conspicuous species.

1.2 The Diversity

The destruction of natural forest has led to severe reduction, fragmentation and degradation

of forest cover. As a consequence, a large number of plant and animal species, communities

and unique vegetation/habitat types have been subjected to drastic decline in abundance,

distribution and coverage. This loss is reflected in a number of faunal and floral species being

regarded as either extinct or near extinct, highly endangered, threatened and vulnerable.

Measuring biodiversity of a habitat or community has been central issue of ecology and

conservation biology (Ganeshaiah et al. 1997). Biodiversity can be measured in terms of

genetic diversity and the identity and number of different types of species, assemblages of

species, biotic communities and biotic processes and the amount (e.g. abundance, biomass,

cover, and rate) and structure of each. It can be observed and measured at any spatial scale

ranging from micro sites and habitat patches to entire biosphere (Delong 1996). Biodiversity

CHAPTER 1 INTRODUCTION 4 does not equate with richness (Koford et al. 1994, Noss and Corperinder 1994) or diversity

(Pielou 1975), both are the components of biodiversity. Diversity is either considered as number and relative abundance of all of the species within a given area (Art 1993) (Species diversity view) or all of the diversity and variability in nature (Spellerberg and Hardes 1992)

(Ecological diversity view).

Biological resources are not uniformly distributed over space resulting into global biological riches, pockets and countries. There is an increasing gradient of species richness towards equator and concentration of Phyla diversity in the marine systems (Ganeshaiah and Shankar

2003). The geographical distribution of species is a result of the action of both historical and ecological factors in time and space (Vuilleumier and Simberloff 1980). The number of species present at a given locality can be viewed as a variable that responds to the influence of several (local) ecological factors, while (largely temporal) historical factors are responsible for the biogeographic species pool from which the local community is derived (Wiens 1991).

Simpson (1964) and Cook (1969) attributed the high diversity of mammals and birds in the tropics to the availability of both tropical and temperate niches resulting in greater diversity of vegetation.

Many explanations for diversity pattern have been proposed, higher diversity has been attributed to temperature (MacArthur 1964, Root 1967), energy supply (Wright et al. 1993) and productivity (Owen 1988), intense competition which forces niche restriction

(MacArthur and Wilson 1967). Ironically Harper (1969) argued for reduced competition resulting from predation. Margalef (1969) found diversity negatively correlating with productivity. The question it seems is far from settled (Huston 1979).

CHAPTER 1 INTRODUCTION 5 The environment heterogeneity hypothesis is the only diversity supported by convincing evidence, with the exception of some cases of predation (Cornell 1975). Habitat structural complexity has been correlated with diversity in birds (MacArthur and MacArthur 1961.

MacArthur et al. 1966), in planktons (Richerson et al. 1970), in marine gastropods (Kohn

1968), in small mammals (Rozenzweig and Winakur 1966) and in lizards (Pianka 1967). In most of these cases the heterogeneit)' is based on the physical structure of the plant serving as the substrate for the animals. The environment stability, predictability and productivity hypothesis are closely related, since these parameters increase together from temperate to tropical regions (Cornell and Orias 1964, Pielou 1975).

Whittaker (1965) indicated a gradient of increasing diversity from the cooler to the warmer climates, but the trend was not a simple one. Indeed, different plant communities may show different trends in diversity. There is no simple trend of increasing or decreasing diversity along some stress gradient such as moisture. Some deserts have higher species diversity than temperate forests (Buzas 1972). Lloyd et al. (1968) made an extensive study of the diversity of reptiles and amphibians species in a Borneo rainforest. As might be expected, species diversity was high but equitability was relatively low.

Biodiversity loss and climate change are two of the greatest global environment challenges we face this century. Annually 6-10 million hectare of tropical rain forests are destroyed, harboring some of the planet's most biologically diverse and abundant flora and fauna

(Watson et al. 2000). Not only contributing to atmospheric carbon dioxide but also directly undermining the world's biological resources, ultimately precipitating species extinction and biodiversity loss (Motten et al. 2003).

CHAPTER 1 INTRODUCTION 6 A recent report of International Union for Conservation of Nature and Natural resources

(lUCN) global amphibian assessment indicates that as many as a third of amphibians, now estimated at over 5700 species have undergone several decline or extinction (Stuart et al.

2004). There is also general bird decline around the world (Lane and Alonso 2001).

Hughes et al. (1997) argued that there are about 220 genetically distinct populations for each extinct species. Their emphasis on the population rather than the species level dramatically increases the magnitude of the current global extinction crisis, with a possibility of 16 x 10^ of population being lost annually owing to habitat destruction.

The word biodiversity carries considerable political freight, as there can be no doubt that the general public's widespread concern about the current extinctions crisis provide a political spur to getting 161 countries to ratify a convention on biological diversity

Myers (1996) noted that on a planet that is increasingly overcrowded with humans the survival of biodiversity will ultimately hinge on utilitarian, particularly economic imperatives. Clearly environmental services are enormously important to human welfare even though the economic values of these services are poorly quantified and largely unappreciated by mainstream politicians. Given the rapidity of global environmental change, there is an increasing need to manage ecosystem to maintain planetary wealth. Maintaining high biodiversity has been linked to ecosystems resilience in the face of common climatic change related shocks such as storms, floods, fires and drought (Abramonitz 2001). Ecosystems that have more diversity provide more alternatives for transferring energy and nutrients and have greater capacity for resisting and reacting resiliently to such shocks compared to systems with

CHAPTER 1 INTRODUCTION 1 low biodiversity which are more likely to decline or even collapse and not recover (Folke et al. 2002). Evans (1976) stated that in the long run probably the most important aspect of the conservation of ecosystems is the preservation of biological system which might meet needs as yet unforeseen.

Biological diversity is being viewed as the potential resource capital of a state or region that possesses it. Preserving and protecting it requires clear knowledge and understanding of what we have and where they exist (Ganeshaiah and Shankar 2003)

1.3 Indian Scenario

Myers (1996) identified areas of exceptional species richness and endemicity on the global scale and referred them as hot-spots of diversity and considered India as one of the 12 mega- diversity centers of the world. Within India, two major centers of biodiversity have been identified. Western Ghats and Eastern Himalayas are considered two 'hot-spots' of diversity

in India (Platnick 1991). Rajmani (1998) believes that though not 'hot-spots', there are also a number of 'warm-spots' that need attention.

India is known for its genetic and species richness in a wide variety of ecological zones (Roy and Tomar 2000). India harbors an estimated 500,000 out of 10 to 30 million species of living organisms. It homes about 75,000 species of animals, including 5000 species of insects, 4000 species of mollusks, 2000 species offish, 140 species of amphibians, 420 species of reptiles,

1200 species of birds and 410 species of mammals (Anonymous 1994). However, increasing human intervention and excessive exploitation of resources have resulted in great changes and provide alarming signals of accelerated biodiversity loss (Roy and Tomar 2000).

CHAPTER 1 INTRODUCTION 8 Himalayas which cover 6.4% area of the Indian subcontinent constitute a significant unit for the conservation of biodiversity. It harbors a great diversity of flora and fauna distributed in variety of topographic types and climatic conditions (Rodgers et al. 2000). The forest ecosystem in Uttarakhand, which is part of western Himalayas, shares the biological richness of the Himalayas.

1.4 Rationale

The large scale exploitation and clearance of the forest for commercial as well as agricultural purposes, during the last two centuries and also due to unprecedented increase in human population and settlements in the last few decades in Uttarakhand, has brought about considerable changes in land use pattern. The large scale exploitation of forests has brought misery to not only to the local people, as extensive forest is no longer able to satisfy their fuelwood and fodder requirements on sustainable basis, but also to the people from plains due to annual flooding of major rivers. One of the major consequences of this continuous exploitation of forest in the Himalayas has been the loss of wildlife habitat and today's survival of several wildlife species is becoming extremely difficult due to tremendous shrinkage and degradation of their habitat.

The conservation of forested areas is vital for the very survival of people in Himalayas. It is well documented fact that the forest resources are the first to suffer if ill conceived unsustainable economic development policies are implemented. Since, Uttarakhand state is a newly created state and overall development is long overdue for the welfare of local people.

It is therefore, desirable that development activities are envisaged which are not only

CHAPTER 1 INTRODUCTION sustainable on long term basis, but are also compatible with the conservation interests of this region.

For preserving the ecological balance between natural resource development and conservation, the concept of watershed is assumed to be very important land unit, particularly in fragile and heterogeneous hilly ecosystems (Sharma et al. 1992). To ensure sustainable development a strong database is required that shall lead to conservation and regeneration of all the resources - natural (land, water, plant and wildlife) and human within a watershed.

Fauna along with flora and hydro-geo-morphology is considered an important aspect of the creation of such a database. Being essential component in the forest ecosystems, fauna plays crucial role in ecosystem functioning and its dynamics. Faunal elements act as an indictor of the health of the ecosystem. Despite their important role, animals are exploited directly or indirectly leading to extinction as a result of ill planned developmental activities and land use practices.

Understanding the spatial distribution of biodiversity is the foremost prerequisite for the meaningful conservation of natural ecosystems. The construction of strong database for biodiversity conservation reflecting the spatial distribution would serve several purposes such as locating the hot-spots of diversity, assigning conservation values for different areas etc.

Since, such type of database are rare there is therefore critical need to document the diversity pattern of fauna in India (Ganeshaiah and Shanker 2003). Though, Uttarakhand part of

Himalayas is well studied, yet such crucial information is lacking on the biodiversity of watersheds.

CHAPTER 1 INTRODUCTION 10 This thesis is an outcome of the Department of Science and Technology (DST), Govt, of

India, funded project under Nature Resource Data-Base and Management System entitled

"Documenting pattern of fauna! diversity in Dabka and Khulgarh Watershed Areas of

Kumoan Himalayas for augmenting Bio-Geo Data Base for sustainable use of Uttarakhand

Transect". Keeping the importance of faunal diversity of the area, the study was taken up with following main objectives:

^ To asses population status and community attributes of birds and mammals in Dabka

and Khulgarh Watershed Areas

>^ To carry out intensive ecological studies on large mammalian community in Dabka

and Khulgarh Watershed Areas

^ To carry out intensive ecological studies on avian community structure in Dabka and

Khulgarh Watershed Areas

*^ To carry out ecological studies on herpetofauna in Dabka and Khulgarh Watershed

Areas

^ To study food habit of large carnivores of Dabka and Khulgarh Watershed Areas

CHAPTER 1 INTRODUCTJON 11 CHAPTER 2 STUDY AREA 2.1 Historical Background Historically, the Kumoan Himalayas used to be a part of Oudh Province. Gorkhas ruled

Kumoan before the British annexed the area in 1815, thus, from 1815 to 1947, the area remained under British colonial rule. During the British period this area was declared as

"Non Regulated Area" hence, the rules and regulations implemented here were quite different from those of plains (Mittal 1990)

Very little is known about the agricultural condition and its development during the 19' century. Kumoan from ancient times seems to have been agricultural area. (Pate Ram 1916) but practising was difficult job. For, there were factors like occasional floods, hailstorms, landslides, the ravage of wild animals and a high degree of mortality among both the people and the cattle, were some of the obstacles, which made the cultivation in the hills difficult. It was observed and written by Sample (1921) during the British period that sustenance was very severe, yet, agriculture flourished well till the beginning of the 19**^ century. Great decline in agricultural practices was observed on account of the barbarous rule of Gorkhas

(1700-1815). After the British took control in 1815, cultivation got increased by one third and since then there was steady progress (Kennedy 1884). The net cultivable area in the Kumoan during 1842-1846 was 10.08% of the total area of Kumoan which was further increased upto

15.16% during^the years 1872-1873, and it was further extended to 17.06% in the year 1886

(Mittal 1990). The cultivable area increased upto 25.28% of the total area of Kumoan in the year 1978.

A steady increase in agricultural land was observed through out the Kumoan. This increase was due to increase in human population. The commissioner of Kumoan observed an increase

CHAPTER 2 STUDY AREA 12 of 12.8% in the agricultural production due to policy of encouragement within twenty years from 1815-1935 (Pant 1935). The region was recorded increase in total human population from 1,64,000 to 8,07,213 individuals during the years 1821-1921 and the human population

further increased from 8,60,588 to 29,43,199 individuals during the years 1931-1991 (Table

2.1).

Table 2.1 Changes in the human population during 19"" and 20"" century in Kumoan Himalayas

Year Human Population 1821 1,64,000 1852 3,60,011 1881 7,01,007 1911 8,49,149 1941 9,79,147 1971 19,55,281 1991 29,43,199 2001 35,64,049

Industrialization, agricultural expansion and development of the area in terms of road

establishment degraded the forested area. The contract arrangements for felling trees

continued until 1858 and as a consequence no conservation measure could be introduced.

From 1855 to 1861, due to tremendous demand of railway sleepers, uncontrolled felling of

Sal (Shorea robusta) tree was attempted in more accessible forests. The increased human

population during the 1900s exerted more pressure on Oak {Quercuses sps.) forest because

they provided them cheap fuel, leafage and fodder while Sal {Shorea robusta) and Deodar

{Cedrus deodara) tree species provided wood for timber and agriculture implements. The

reckless destruction"of valuable forests in the quest of railway sleepers and exploitation for

other human needs depleted the national timber resource. Ramsay the first conservator of

forests 1868 recognized the gravity of the situation and took immediate measures to stop this wanton destruction of forests, and from this time forests progressed with vigor.

CHAPTER 2 STUDY AREA 13 The forest department of this region got organized for the first time in 1868 with a conservator of forests as its head. For several decades forest department remained engaged more in conservation than exploitation. And this essential conservation, which was the keynote of the forest administration, then created a sufficient discontent among people of

Kumoan (Pant 1921). There was a widespread feeling of discontent and the forest policy of the government was criticized and condemned all over the area. In 1917, a fresh settlement was made which divided forests into the following categories.

•^ Reserved forests (Old reserves and new reserves), and

«^ Protected forests or civil forests

Recent assessment showed that 25.28% of the total area of Kumoan was under cultivation in the year 1978. Total forest cover which was 44.3% in 1972 of the reported area (18631.80 km^) of Kumoan, was increased a little up to 48.4% in the year 1979-80. But the recent forest cover of Kumoan was 35.61% in the year 1991 (Anonymous 1991). The drastic decline in the forest cover was observed in whole of Kumoan after independence.

2.2 Watershed

A watershed is a natural hydrological entity, defined as the drainage basin or catchment area of a particular stream or river. Simply put, it refers to the area from where the water to a particular drainage system, like a river or stream, comes from. According to Integrated

Mission for Sustainable Development (IMSD 1995) guidelines, watersheds are further classified into sub-watershed (± 30-50 km^), mini-watershed (± 10-30 km^) and micro watershed (± 5-10 km^). The present study was carried in two sub-watersheds of the middle

Himalayas.

CHAPTER 2 STUOYARBA 14 2.3 Khulgarh Watershed Area (KWA)

2.3.1 Location and Extent

The Khulgarh watershed lies between 29° 34" 31' to 29^ 41" N latitudes and 79° 32" 15' and

79° 37" E latitude in Almora distrist of Kumaon Himalayas, Uttarakhand (Figure 2.2). The area spreads over 32 km^ and represents middle Shiwaliks. It is situated 15 km west to

Almora town and inhabited by 34 villages.

2.3.2 Climate

There are three distinct seasons, summer, winter and monsoon. The monsoon starts at the end of June and ceases by the middle of September (Singh 1987). The average annual temperature of the KWA is 19.8 °C during summer, the average temperature of the watershed is 20 °C. which varies between 25.2 °C and 13.6 °C. During winter the average mean temperature of the watershed is 16.3 °C which varies between 19 °C and 11.1 °C. The average annual rainfall in the watershed was found to be 950 mm but within this small watershed there was a variation in the distribution of summer, winter and annual rainfalls (Figure 2.1).

The watershed received maximum (164.5 mm) rainfall during August which accounts for

26.01% of the total annual rainfall. The minimum rainfall occurred in November which accounts for only 1.02% of the total annual rainfall.

The average annual humidity of the basin was recorded at 66.12% which varied between

73.50% (in the forested) and 61% (in the barren land). During summer, the average humidity of the watershed rose to 71.82% with the forested Sitlakhet area registering 77.14%. In winter, the average humidity of the KWA was 70.04% with the north facing forested area of

Sitlakhet having the maximum humidity of 75.68% and agricultural lands 68.86%.

CHAPTER 2 STUDY AREA 15 The average annual evaporation of the watershed was recorded at 331 mm varying from 393 mm at south facing Jyoli agricuUural area to 226 mm at north facing Sitlakhet forested area.

During summer, the average evaporation of the watershed is 149.06 mm and in winter season it was 59.36 mm.

3.3.3 Physiography

KWA area represents highly folded and faulted chain of Kumaon hills with general elevation ranging from 1200 to 2200 m above mean sea level (msl). South-east and south-western hills relatively have more altitude than the north-eastern and northern hills. North-eastern facing hills are mostly convex in shape while south-western hills are concave in shape.

2.3.4 Topography and Drainage

The topography is extremely hilly and rolling. The relief is excessive except in piedmont

slopes and valley where it is somewhat excessive to flat. The watershed is drained by

Khulgarh stream, a tributary of Kosi River which merges with Ramganga River in the plains

of Uttar Pradesh. Drainage pattern in the watershed varies with the geology, slope and land

use/land cover. The area was mostly hilly with majestic terrain dominated mostly by pine

{Pinus spp.) forest. The general elevation varies from 1100 m to 2100 m above msl.

2.3.5 Geology

The Khulgarh watershed is situated on the north-east dipping southern limb of the synclinal

Almora Nappe- a thick folded sheet of precambrain metamorphic rocks and associated granites that has been considerably dislocated southwards from its original place in the north.

The Almora group that constitutes the Almora Nappe is made up of predominantly

CHAPTER 2 STUDY AReA 16 gametiferrous, mica-schists interbedded witii micaceous quartzites intimately associated with augen gneisses and subordinate phyllites and metagreywackes (Valdiya 1980, 1988).

2.3.6 Natural Vegetation

Natural vegetation comprise of Himalayan moist sub-temperate and mixed forest. The vegetation of the dip-slopes in the southern part of the watershed was covered by dense oaks forests, dense coniferous forests with scrubs, regenerated pine forests mostly in the mid- crestal zones and south facing slopes covered by scattered trees, but carpeted with grasses.

The vegetation of Kumoan Himalayas has been divided into four different zones (Champion

and Seth (1968). The most dominating tree species in the study area was Pinus roxburghii

both in forested and outside forest areas. The other major tree species found in the area were

Quercus incana and Lyonia Ovalifolia. A total of 30 species of trees, 30 species shrubs and

21 species of herbs were recorded in the study area. The area was divided into five major

habitat categories based on the density of forest cover, detail of which is given at the end of

this chapter.

2.3.7 Fauna

The Kumoan Himalayas hold rich oriental faunal composition (Mani 1974). The area still

holds some of the rare, endangered mammal and bird species. The main mammal species

recorded during the study period, were Sambar Cervus unicolor, Muntjac Muntiacus muntjak.

Wild boar Sus scrofa and Leopard Panthera pardus. A total of 103 bird species were

recorded prominent among them were Koklass Pucraasia macrolopha, Kalij Lophura

leucomelana. White-crested laughing thrush Garrulax leucolophus and many species of

finches, raptors, woodpeckers, laughing thrushes, tits, leaf warblers and flycatchers. Among

reptiles. Common Indian krait Bungarus caerruleus, Indian cobra Naja naja, Rat snake

CHAPTER 2 STUDY AREA 17 Elaphe obsolete, the Himalayan pit viper Ancistrodon himalayams were also recorded.

Among butterflies the notable species were Indian cabbage Pieris canidia indica. Common sailor Neptis hylas varmona. Painted lady Cynthia cardui. Great Mormon Princeps memnon agenor and Oak leafKaHima inachus inachus were recorded.

2.3.8 Human Habitation and Dependency on Forests

About 25 thickly populated villages in KWA, depend on forest resources for fuel wood and

fodder. Agriculture forms the major occupation of the people as 80 percent of the population

depends upon it. The crop production of this area is limited due to poor soil fertility,

dependence of agriculture on rains, poor socio-economic condition and absence of soil

conservation measures. The major crops grown in the rabi season are wheat, toria, lentil and

barley while mandua, bhatt and paddy are main kharif crops mostly cultivated as rainfed

crops. Vegetables such as potato and chillies are also grown. Fruit crops such as pear, citrus,

walnut, plum, apple and peach are also grown in the area. Figure 2.6, 2.7 and 2.8 shows the

drainage, road and settlement maps of KWA respectively.

2.4 Dabka Watershed Area (DWA)

2.4.1 Location and Extent

The DWA is situated in the south-west region of the Kumoan Himalayas in Nainital district

of Uttarakhand. The DWA lies between two rivers Dabka and Kosi, while the Dabka

originates from DWA. Dabka has several water catchments and several small streams

arising from these catchments meet to form the Dabka, a seasonal river. Dabka watershed

area is a reserved forest. Although Dabka watershed area is not under the protected area

category but still harbours a rich diversity of fauna and flora.

CH/^PTER 2 STUDY AREA 18 2.4.2 Topography

DWA has an area of about 69.06 km' and lies between 79" 17' 53" to 79*" 25' 38" longitude.

29° 30' 19" to 29° 24' 09" latitudes in the region of lesser Himalayas in the state of

Uttarakhand (Figure 2.2). It is situated in the lesser Himalayan mountains in the close proximity of main boundary thrust-the major Himalayan fault that makes tectonic boundary between lesser Himalayas in the north and shiwaliks in the south. The entire area is therefore, tectonically alive and ecologically fragile and therefore very prone to several kinds of mass movements and slope failure processes, particularly landslides, making it vulnerable to a variety of natural risks.

2.4.3 Climate

The climate of the area is cold temperate with the temperate vegetation. The monsoon starts at the end of June and ceases by the middle of September (Singh 1987). This area falls in different altitudinai ranges from 700 - 2600 m. In the lower elevations (600 -900 m) near

Kotabagh, the mean annual temperature varies from 18.9 "C to 21.1 °C with mean annual rainfall of 2860.33 mm. In warm temperate zone (900 - 1800 m), the mean annual temperature varies from 13.9 "C to 18.9 °C with mean annual rainfall of 3623.33 mm. In cold temperate zone (1800 - 2500 m), the mean annual temperature varies from 10.3 ''C to 13.9 °C with annual rainfall of 1750 mm (Sultana 2002). The microclimatic condition usually differs from valley to valley and from locality to locality according to the direction of ridges, degree of slopes, sunny or shady aspects of slope, intensity of forest cover and nearness to glaciers

(Sultana 2002). The region can be divided into seven broad climatic zones, primarily based on altitude (Saxena et al. 1985, Singh 1987) (Table 2.2).

CHAPTER 2 STUDY AREA 19 2.4.4 Human Habitation

The study area, though a reserve forest, comprises 33 villages under the category of revenue villages except Kotabagh, a town situated in the foothills. All villages have around 8 to 20 houses each. The human population of this area is very less and livestock population is also not much. Poaching of wildlife is by far the biggest threat to mammals in the DWA. As a consequence, a number of animal species have been subjected to drastic decline in abundances, distribution and coverage. This loss is reflected in a number of mammal as well as other species being perpetually becoming extinct, highly endangered, and threatened. The nature and magnitude of this illegal activity varies from poaching for personal consumption to organized poaching for commercial purposes. Illegal hunting has wiped out a number of species from certain areas of Kumaon e.g. serow from China peak of Nainital (Young and

Koul 1987). Figure 2.3, 2.4 and 2.5 shows the drainage, road and settlement map of DWA respectively.

2.4.5 Dependency on Forest

DWA being a reserve forest is divided into forest ranges Vinayak and Naina. The villages which are thickly populated are deficient in their fodder requirements. This has resulted into various human activities in the area and anthropogenic pressures on the natural resources.

The local people depend on forests for fodder, fuel and minor forest products. Oak trees are usually lopped for fodder. This has led to the stunted growth of Oak trees around the villages.

During summer people also harvest berry of Myrica kaffal, a kind of berry. The bark of

Grewia oppositifolia (Bhimal) is used to make ropes. The newly constructed road from

Nainital to Khunjakharak has led to mass level of mining and quarrying in these two forest ranges.

CHAPTER 2 STUDY AREA 20 2.4.6 Flora

The most of the study area comes under Vinayak forest range of Kumaon division with

dominating Oak Quercus leucotricophora and few patches of Chir pine Pinus roxburgii,

Taxus baccata, and Cedrus deodara trees are also present. The Rhododendron arborium

trees are common throughput the area. In lower elevations near Kotabagh one can find a

few patches of Sal Shorea robusta forest with Lantana camara and Colebrookia

oppositifolia being the more widespread shrub species. A total of 34 species of trees, 24

species of herbs, 27 species of shrubs with Berberis aristata and Rubus elipticus as most

dominant plants were reported from the study area. In herbaceous layer Hedychium

spicatum was the most dominant herb species.

2.4.7 Fauna

The area has the rich wealth of mammalian fauna that includes Rhesus macaque Mucucaca

mulata, Langur Presbytis entellus. Golden Jackal Canis aureus. Red Fox l^ulpus vulpus,

Indian Porcupine Hysterix indica, Sambar Cervus unicolor, Muntjak Muntiacus muntjak,

Wild Boar Sus scrofa, Goral Nemorhaedus goral, Serow Capricornis sumatraensis,

Yellow-throated Martin Martes flavigula and Leopard P anther a par dus. A total of 155

species of birds. 10 species of reptiles and amphibians were recorded. Among butterflies,

the notable species were Common Mormon Princeps polytes. Common Tiger Danaus

genutia. Common blue bottle Graphium sarpedon sarpedon, Paris Peacock Princeps pans pans were also found.

2.5 Habitat Categories of both Watersheds

The Forest Cover map of Dabka and Khulgarh Watershed Areas were prepared by Forest

Survey of India (FSl) by geo-referenced toposheet no. 530/7 and 530/10 in polyconic

CHAPTER 2 STUDY AREA 21 projection, respectively. Imageries (Land SAT 1988, 1994, LISS and PAN 1998, 2002) were geo-referenced on the basis of toposheets of the two watersheds. The FSI analyzed multidated satellite images to prepare the classified thematic maps by various digital image- processing techniques. The visual interpretation was carried out at 1:50,000 scale. They classified forest cover of both the watersheds into five categories viz. Very dense forest

(>70%), moderately dense forest (40-70%), open forest (10-40%), cropland, and barren area. The forest cover of both the watersheds show that in DWA's 53% area was forested,

16% was barren area and remaining 31 % was under cultivation. However, in KWA only

35% area was forested, 25% was barren and 39% was under cultivation (Table 2.3).

Table: 2.2 Mean temperature and rainfall in different climatic zones of Kumoan Himalayas (Source Singh 1987) Climatic zone Altitude range(m) Temperature ("C) Rainfall (mm)

Mean Annual Annual mean Tropical zone 300-900 18.9 21.1 2860.33 Warm temperate zone 900-1800 13.9 18.9 3623.33 Cool temperate zone 1800-2400 10.3 13.9 1750.00 Cold zone 2400-3000 4.5 10.4 335.00 Alpine zone 3000-4000 3.0 4.5 - Glaciar zone 4000-4800 Ten months below zero - Two months between 2.2 and 3.9 Perpetually frozen zone >4800 Cold desert no vegetation -

CHAPTER 2 STUDY AREA 22 Table: 2.3 Forest cover categories of Dabka and Khulgarh Watershed Area

Dabka Watershed Area Khulgarh Watershed Area Habitat Categories Area in (ha) % of Area Area in (ha) % of Area Dense forest 622 9.01 207 6.26 Moderate forest 880 12.74 392 11.85 Open forest 2200 31.86 552 16.69 Barren Area* 1106 16.02 858 34.79 Agriculture 2098 30.38 1299 25.94 Total Area 6906 3308 39.27 ^Barren Area includes scrub and grasslands

30.0 300.0

25.0 250.0

u 20.0 ' 200.0 oOJ w 3 (5 15.0 . 150.0 w 01 a \-( E 10.0 V I 100.0 0) */ " 5.0 50.0

0.0 0.0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

^••Maximum Minimum ----Rainfall(mm) Humidlty(%)

Figure: 2.1 Monthly Meteorological data of KWA during the study period (Source Kumoan University Almora Campus, Dept. of Geology)

CHAPTER 2 STUDY AREA 23 OS U KS -a 3

o a. C3 c _o %-» oKS o

3 BO

>. Q e HI i 3 ~yjitrE 79'»(rE 79-3?[rE TS-:4tr^

1 N

S ^••'•'"y^s

I

^^ '^^ •' "^^^^

•^^^^^'-^Tlii-ii^^ W [/ 1- •^ <7^ },

'V^jr-^ 1^ J NWatershed boundary Drainage p~- XJ/ Jr^^'^-v^ 0 0,5 I 2 3 4

Figure: 2.3 Drainage map of Dabka Watershed Area

79 1S0-E 7.Wt 79 2>-D-E T9-3*irE

S """-zlf^

i )

-'-'

i Road j_ J watershed boundary S / ) ^X 0 05 1 2 3 4 ^-^ ->^

Figure: 2.4 Road map of Dabka Watershed Area

CHAPTER 2 STUDY AREA 25 S y-+N. •^' /y ^-.- •- X-W,-^ / \ ^A

/• \ I' .-: • -. • ' • *. ' / * \.^^^ v /• • . \ / • ^ ••'. • :v-...... \ / ' • • ' • ."••- .. • • • • •--.. \ , '•••''• ' '•••' *_. . ;•;• ~N \.- .. • ':. " . ,'''•'. •••• " '•

/ • /.... •• '- * ••'*'. "• '. / /•/ . .

/»-. •••• ....

/ """'•*' '"••' 1 /-^-^-'' / • • '>;.: r-^'^" 1 '"' ' •' f •" { Settlement ' 1 / [ 1 Watershed boundary J \_>''"^<,. ••.• •• ^-^ 0 05 1 2 3 4

—— I 1 • . , 1 - -• 1 • 1 ' 1 1

Figure: 2.5 Settlements map of Dabka Watershed Area

79J32. 79J37.

(.\\ •^\\

y . y '1 1 1 * , • >» ^—s jL 29' 38'

i\ 29* •\* s 1 1 •* V / 37'

29° 36'

29° 35' [li^y '"••' Drainage

i ; 0 : h p 29° 34'

Figure: 2.6 Drainage map of Khulgarh Watershed Area

CHAPTER 2 STUDY AREA 26 79*^32' 19hj ^JW^ « 79''35' 79J36. 79J37' N 29° 38'

29° 37'

29° 36' M^ ~^-w.'^*^

29° 35' A' Road TSinta»%ji p 3 : 0 J <> 29° ^^tii. 1 :o£iOJ 34'

Figure: 2.7 Road map of Khulgarh Watershed Area

79J32. 79J33'

29° 38'

_29° 3?

_29° 36'

J9° 35' * Settlements

J9° 34'

Figure: 2.8 Settlements map of Khulgarh Watershed Area

CHAPTER 2 STUDY AREA 27 CHAPTER 3 VEGETATION COMPOSITION 3.1 Introduction Himalayas, the youngest mountain system of the world, constitute an important link between the vegetation of the southern peninsular India on the one hand, the eastern Malaysian, the north-eastern Sino-Japanese and the northern Tibetan areas on the other (Puri et al. 1983).

Several studies have described the vegetation of Kumaon (Dhar et al. 1997, Rikhari et al.

1989a, Singh et al. 1984, Singh and Singh 1984, Singh and Singh 1987, Singh et al. 1987,

Tiwari and Singh 1985, Upreti et al. 1985) and Garhwal Himalayas (Anthwal et al. 2006,

Kumar and Bhatt 2006, Nautiyal et al. 2004). Some of the studies described altitudinal variation in vegetation (Adhikari et al. 1992, Saxena et al. 1985) and reported that vegetation types differ with change in altitude. Some pioneering contributions on phytosociology

(Ralhan et al. 1982, Saxena and Singh 1982) and population structure (Saxena et al. 1985,

Singh et al. 1987) of certain central Himalayan forest types have already been reported.

The Himalayan mountains from Kumoan to Kashmir are with considerable variation between the outer and the inner valleys (Hussain et al. 2008). The vegetation is divided into altitudinal zones, such as sub-montane zone up to 1500 m, a temperate zone from 1500 - 3300 m, and alpine zone above the snowline (Sultana 2002). The altitudinal zonation of different types of vegetation is not restricted and it has been found that geology and soils exercise a far greater influence on the distribution of vegetation than altitude or climate does (Puri et al. 1983). The other important feature in the Himalayas is the role of man in delimiting the vegetation zones

(Sultana 2002).

Vegetation in the Himalayas is rich and diverse due to varied climatic, altitudinal, geological

CHAPTER 3 VEGETATION COMPOSITION 28 and topographical conditions. Being a source of primary production, vegetation plays a major role in determining animal abundance and distribution by providing essential habitat components i.e., food and cover.

A useful study is that where vegetation data are collected and analyzed with the aims of providing information of relevance to some ecological problems, often to do with environmental conservation and ecosystem management. The forest resources of the country are under great pressure owing to the increased demands from human and animal populations resulting in degradation of forest ecosystem. This has led to poor productivity and

regenerative capacity. Hence, monitoring of our forest resources is of great importance

(MOE«&F 1994, FAO 1995, MOE&F 1997). The collection and organization of existing

scattered information with a provision to synthesize and update without much additional

effort is needed for optimal resources management (Mukund Rao et al. 1994, Mukund Rao

and Jayaraman 1995, Rajan 1991).

The monitoring of vegetation forms an essential component of the management of wildlife

areas, since change in vegetation influences the distribution and abundance of animal species

(Khan 1996). Long term monitoring of vegetation, such as in Serengeti National Park, Africa

(Sinclair and Norton-Griffiths 1979), has demonstrated the utility of a habitat-oriented

approach to wildlife management. Such studies have been useful particularly in

understanding the dynamics of animal population distribution, abundance and habitat use

(Dinerstein 1980). The present study was conducted to understand the vegetation

characteristics of the two watershed areas. It was presumed that the vegetation characteristics

govern the community structure in an ecosystem.

CHAPTER 3 VEGBTA TION COMPOSITION 29 The data pertaining to vegetation were collected with the following main objectives:

^ To evaluate density, diversity and richness of all the three vegetation layers i.e. trees.

shrubs and ground layer in both the watershed areas.

^ To understand the organization of plant communities in relation to slope and aspect.

•^ To describe different dominating communities of the trees of both the watersheds.

3.2 Methodology

Overall 150 sampling points, 65 in Khulgarh and 85 in Dabka were established to know the vegetation composition of both the watersheds. The sampling points were laid randomly and also on existing forest trails. A distance of at least 250 meters was maintained between two sampling points. These sampling points covered almost all the habitat types of the study area.

Sampling points on trails were taken 10 m inside on either side of the trail to avoid sampling the relatively disturbed vegetation along it (Sultana 2002).

Sampling plot method following Dombois and EUenberg (1974) was used for vegetation sampling. At each sampling point, a 10 m radius circular plot was established. Trees > 4 m height were considered as mature trees and different species and their individuals were recorded for the estimation of density, species diversity and species richness. Shrub layer was quantified in 3 m radius concentric circular plot within the existing 10 m radius sampling plot. Shrub species and their numbers were recorded for the estimation of density, diversity and species richness. Shrub height was measured using measuring tape and ocular estimation was made for shrub cover. Shrub cover was categorized in to four categories 0 - 25%, 25 -

50%, 50 - 75% and > 75%. To calculate tree species dominance GBH (Girth at Breast

Height) in cm, was also recorded in each plot. Regeneration was quantified in terms of

CHAPTER 3 VEGETATION COMPOSITION 30 seedling and saplings in 3 m radius circular plot within the existing 10m radius circular plot.

Tree species up to 0.50 m was considered as seedling while 0.51 m to 4.0 m was taken as sapling (Sultana 2002).

Ground vegetation (herbs and grasses) was estimated in 0.5 m x 0.5 m quadrate in four

directions within the 10m radius circular plot. The species and their numbers were recorded

for the estimation of density, diversity and species richness. The ground cover was also

estimated by point intercept method (Canfield 1941). One meter long stick was marked at an

interval of 5 cm. The stick was randomly laid in four directions and any intercepting material

touching the mark was recorded. At any sampling plot, ground cover was calculated by

taking the averages of all the frequencies.

Tree cover was measured by using gridded mirror of 10 x 10 inches dimension, divided into

25 equal grids. The mirror was placed horizontally at 1.25 m above the ground touching the

body of the observer. Tree cover was measured at 5 m distance from the sampling point in

four different directions. Grids covered with more than 50% foliage were counted and

expressed in terms of percentage. Average of four recordings was taken for tree cover in each

sampling plot. Data pertaining to habitat disturbance such as lopping of trees, fallen trees

cattle dung and presence of fire were also recorded in 10 m radius circular plot. Data were

also collected on different slope and aspect categories.

3.3 Analysis

Density of trees, shrubs, herbs and grasses and of individual species was calculated for each

sampling plot using the formula:

CHAPTER 3 VEGETATION COMPOSITION 31 D = Number of individuals / area

Density in each plot was pooled into different habitats and mean density and standard error was calculated. Species diversity, richness and evenness was calculated for trees, shrubs. herbs and grasses. Shannon-Weiner Diversity Index (H') was used for diversity, Margalef s

Index (RI) for richness and Simpson's Diversity (D) was used for calculating evenness following Magurran (1988).

Shannon-Weiner Index

H' = I pi In pi.

Margalef s Diversity Index

RI = (S-l)/lnN

Simpson's index

D = Ip/'

Where, S is the number of species recorded, and

N = the total number of individuals summed over all the S species.

The quantity pi is the proportion of individual found in the /th species.

Man-Whitney U Test was used and One Way-Analysis of Variance was used to know the significant difference of density, diversity and richness within the area and between different habitat types in both the watershed.

3.4 Results

3.4.1 Trees

A total of 52 tress species were recorded in both the study sites, of which 34 tree species were identified in DWA and 30 species in KWA. The overall tree density (710.93/ha ± 56.86) was higher in KWA as compared to DWA (246.96/ha ± 6.11) and difference was found to be

CHAPTER 3 VEGETATION COMPOSITION 32 significant (Mann-Whitney U Test, Z = 6.581, P = 0.000). In different habitats in DWA, tree density was found to be highest in moderate forest (264.23/ha ± 6.55), lowest in open forest

(210/ha ± 16.23) and difference was found to be significant (ANOVA, F = 3.002, df = 3, P =

0.059) (Table 3.1)

The overall tree diversity, richness and evenness in DWA was 1.296 ± 0.09, 1.024 ± 0.08 and

0.748 ± 0.04 respectively. Among different habitats in DWA, tree diversity (F = 65.27, df =

2, P = 0.000), richness (F = 36.87, df = 2, P = 0.000) and evenness (F = 34.16, df = 2, P =

0.000) were found to be highest in dense forest but difference was not found to be significant

(Table 3.1). Tree diversity, richness and evenness were higher in eastern aspects and density in western aspects in DWA (Figure 3.1 and 3.2).

Overall diversity, richness and evennes in KWA was 0.645 ± 0.08, 0.731 ±0.10 and 0.444 ±

0.05 respectively. Tree density was highest in moderate forest (915.61/ha ± 157.60) and lowest in open forest (505.57/ha ± 72.20) and the difference was found to be significant

(ANOVA, F = 3.63, df = 2, P = 0.034). Among different habitat of KWA, tree diversity (F =

2.028, df = 2, P = 0.14), richness (F = 2.052, df = 2, P = 0.14) and evenness F = 0.694, df = 2,

P = 0.504) was found highest in dense forest but difference was not found to be significant

(Table 3.2). Density of trees was found highest in eastern aspect (Figure 3.8) and diversity, richness in western aspect (Figure 3.9).

3.4.2 Shrubs

A total of 27 shrub species were identified in DWA. Total mean shrub density was found to be (4600.88/ha ± 843.27). Overall diversity, richness and evenness was 1.097 ± 0.05, 0.777 ±

CHAPTER 3 VEGETATION COMPOSITION 33 0.04 and 0.861 ± 0.02, respectively. Moderate forest had highest density (5914.94/ha a:

1424.62) followed by dense forest (3981.05/ha ± 1309.08) but the difference was not found to be significant. Diversity in different habitats in DWA was found highest in moderate forest

(1.175 ± 0.14) and lowest in open forest (1.087 ± 0.06) and here too, the difference was not found to be significant. Richness and evenness was found to be highest in dense and moderately dense forests, respectively, while the lowest values recorded for richness and evenness were both from open forests (Table 3.3). Shrub density was found highest in southern aspect (Figure 3.3) and diversity richness and evenness in northern aspect (Figure

3.4).

A total of 30 species of shrubs were identified in KWA. Mean shrub density was found to be

(4397.94/ha ± 719.64). Overall diversity, richness and evenness was 0.488 ± 0.06, 0.523 ±

0.07 and 0.411 ± 0.05, respectively. Density was recorded highest in moderate forest

(5657/ha ± 1224), lowest in open forest (2213/ha ± 628) and the difference was not found to be significant. The diversity (0.603 ± 0.11) and richness (1.670 ± 0.36) was found to be maximum in the moderate forest in KWA, where as evenness was maximum (0.533 ± 0.11) in the dense forest. Contrary to this the dense forest was also found to least rich (0.412 ±

0.13) in shrubs among all the habitats. On the other hand, shrubs were found to be highly evenly distributed in the dense forest (Table 3.4). None of the comparisons among the habitats types yielded any significant difference. In different aspects shrub density, diversity, richness and evenness was found highest in southern aspects (Figure 3.10 and 3.11). Myrcine qfricana (5510.21/ha), Vrtica diaca (4321.21/ha), Athyrium sps. (3321.43/ha), Arundinella nepalensis (1819.32/ha), Scetullaria scandeis (1732.45/ha), Crisium uerutum (1865.86/ha) and Berberu lyceum (1342/ha) were more dominant shrub species in both the sites.

CHAPTER 3 VEGETATION COMPOSITION 34 3.4.3 Herbs

A total of 24 species of herbs were identified in DWA. Overall herb density in DWA was

39.32/m^ ± 2.75. Overall diversity, richness and evenness was 0.978 ± 2.75, (0.576 ± 0.04 and 0.756 ± 0.04, respectively. Across different habitats density was found highest in moderate forest (40.12W ± 3.62) and lowest in open forest (36.80/m^ ± 5.98) and difFerence was not found to be significant. Moderate forest was found to have maximum herb diversity

(1.071 ± 0.30) and to have most evenly distributed herbs (0.781 ± 0.05) among the habitats.

While, dense forest was highly rich in herb (0.624 ± 0.18), the open forest was least rich

(0.551 ± 0.05) (Table 3.5). Herb density, diversity, richness and evenness on different aspects almost showed a uniform pattern (Figure 3.5 & 3.6)

In KWA, 21 species of herb were identified. Mean herb density was found to be 62.57/m ±

12.02. Overall diversity, richness and evenness was 0.518 ± 0.07, 0.802 ± 0.09 and 0.477 ±

0.06, respectively. Density of herbs was found highest in moderate forest (87/m^ ± 26.61) and lowest in open forest (50.36W ± 14.87) and the difference was not found to be significant.

Diversity too was found to be highest in moderate forest and the difference across habitats was significant (F = 3.431, df = 2, P = 0.04). Dense forest was found to be most rich in herbs

(1.453 ± 0.17), but the herbs were most evenly distributed in the moderate forest (0.581 ±

0.08), while dense forest was found to be least diverse (0.219 ± 0.09) in herbs (Table 3.6).

Herb density was highest in eastern aspect (Figure 3.12) and diversity, richness and evenness in southern aspects (Figure 3.13). Hedychium spicatum (29.21/m^), Berberis aristata

(25.54/m^), Rubus elipticus (23.43/m^), Eupitorium adinophorum (19.42/m^), Calanthe sp

(18.23/m^), Condrus crispus (17.87/m^), Sida cordata (11.12/m'^) and Satyrium nepaknse

(11.21/m^) were most abundant herbs species.

CHAPTER 3 VEGETATION COMPOSITION 35 3.4.4 Grasses

A total of 19 species of herb were identified in DWA. Overall grass densit>' was 93.43/m^ ±

6.02. The overall diversity richness and evenness was 0.544 ± 0.05, 0.239 ± 0.02 and 0.476 ±

0.05, respectively. In different habitats, density was fond to be highest in open forest

(129.64/m^ ± 12.06) and lowest in dense forest (56/m^ ± 7.37) and the difference across habitats was significant (F = 13.59, df = 2, P = 0.000). Though the dense forest had the least grass density (56.00 ± 7.37), the same forest type was found to have highest diversity (0.712

± 0.21), richness (0.297 ± 0.08) and evenness (0.682 ± 0.19), but difference was not significant (Table 3.7). Grass density was found highest in southern aspects (Figure 3.5) and diversity, richness and evenness in southern aspect (Figure 3.7).

In total 17 species of grass were identified in KWA. Overall density was found to be

154.09W ± 17.55. Overall diversity, richness and evenness was 0.919 ± 0.06, 0.653 ± 0.04 and 0.788 ± 0.04, respectively. In different habitats, density and diversity was highest in open forest, richness in dense forest and evenness in moderate forest and difference was not found to be significant (Table 3.8). Grass density was highest in northern (Figure 3.12) and diversity, richness and evenness in southern aspect (Figure 3.14). Scirpus comosus (99.36/m ) and Cynodon dactylon (9.87/m^) were found to be most abundant in grass.

3.4.5 Sapling and Seedling

The overall sapling and seedling density in DWA was 46.26/ha. ±6.16 and 27.64/ha ± 4.23, respectively. Sapling density was recorded highest in dense forest (51.36 ± 8.04) and lowest in open forest (13.94 ± 12.46), where as seedling density was found highest in dense forest

(30.81 ± 5.99) but lowest in moderate forest (22.48 ± 8.53). There was no significant

CHAPTBR 3 VEGETATION COMPOSITION 36 difference between sapling and seedling density in different habitats (Table 3.9).

The overall sapling and seedling density in KWA was 467/ha ± 70.84 and 479.97/ha ± 49.50. respectively. The mean densities of sapling and seedling were recorded highest in moderate forest (720/ha ± 255) and dense forest (493/ha ± 76), respectively. While the open forest recorded the lowest for both sapling (347/ha ± 67.96) and seedling (441/ha ± 110) densities

(Table 3.10)

3.4.6 Human Habitation/ Hamlets

Since thirty three and twenty five villages or hamlets resided within DWA and KWA, respectively, which predominantly depended on natural forest for fodder. As a result vegetation around hamlets showed certain features of anthropogenic pressures. Trees showed

stunted growth in and around villages. Tree density, diversity, richness and evenness showed

increasing pattern and cut tree lopped tree density showed decreasing pattern as one moves away from habitation (Figure 3.15, 3.16. 3.17, 3.18). Similarly, shrub density showed

negative relationship with hamlets in both the study sites (Figure 3.19 3.20). Whereas shrub

diversity was found highest near human habitation (Figure 3.21).

3.4.7 Tree Species Dominance

The Important Value Index (IVI) computed for different tree species to ascertain the

dominance and abundance patterns yielded that Q. leucotrichophora was the most dominant

species with IVI = 128.80 in DWA (Table 3.11). On the other hand in KWA, Pinus roxburghii was the most dominant species (IVI = 155). The individual tree species densities

and IVI of both the watershed areas is shown in Table 3.11.

BBBBaESHBaiaaBaaaaBaBaBaBBSBBBaBaaaaBaaaBSBi^ CHAPTER 3 VEGETATION COMPOSITION 37 Table: 3.1 Tree density, diversity, richness and evenness in different habitats in DWA

Habitat Density(/ha) Diversity Richness Evenness Open forest 210 ±16.23 1.538±0.14 I.302±0.17 0.857±0.03 Moderate forest 264 ±16.23 0.477±0.09 0.335±0.06 0.403±0.08 Dense forest 243 ±9.51 1.706±0.06 1.356±0.08 0.919±0.01

Table: 3. 2 Tree density, diversity, richness and evenness in different habitats iinKW A

Habitat Density(/ha) Diversity Richness Evenness Open forest 505.57±72.20 0.427±0.10 0.472±0.08 0.383±0.08 Moderate forest 915±61±157.60 0.543±0.18 1.640±0.21 0.366±0.12 Dense forest 769±80±79.90 0.641±0.13 0.928±0.17 0.504±0.07

Table: 3.3 Shrub density, diversity, richness and evenness in different habitats in DWA

Habitat Density(/ha) Diversity Richness Evenness Open forest 2480.21±1149.58 1.087±0.06 0.643±0.08 0.847±0.03 Moderate forest 5914.94±1424.62 1.175±0.14 0.777±0.04 0.936±0.01 Dense forest 3981.05±1309.08 1.092±0.10 0.815±0.08 0.866±0.05

Table: 3.4 Shrub density, diversity, richness and evenness in different habitats inKWA

Habitat Density(/ha) Diversity Richness Evenness Open forest 2213±628 0.431±0.09 0.528±0.53 0.364±0.08 Moderate forest 5657±1224 0.603±0.11 1.670±0.36 0.526±0.10 Dense forest 3547±848 0.497±0.13 0.412±0.40 0.533±0.11

Table: 3.5 Herb density, diversity, richness and evenness in different habitats in DWA

Habitat Density(/m1 ) Diversity Richness Evenness Open forest 36.80±5.98 0.972±0.08 0.55I±0.05 0.716±0.07 Moderate forest 40.12±3.62 0.1.071±0.30 0.606±0.07 0.781±0.05 Dense forest 38.58±5.37 0.958±0.11 0.624±0.18 0.719±0.18

CHAPTERS VEGETATION COMPOSITION 38 Table: 3.6 Herb density, diversity, richness and evenness in different iiabitats in KWA

Habitat Density(/m ) Diversity Richness Evenness Open forest 50.36±14.87 0.419±0.12 0.766±0.21 0.418±0.12 Moderate forest 87.00±26.61 0.676±0.10 0.953±0.12 0.581±0.08 Dense forest 59.50±27.65 0.219±0.09 1.453±0.17 0.278±0.12

Table: 3.7 Grass density, diversity, richness and evenness in different habitats in DWA

Habitat Density(/ni ) Diversity Richness Evenness Open Forest 129.64±12.06 0.619±0.42 0.266±0.18 0.537±0.36 Moderate forest 79.61±5.08 0.474±0.30 0.214±0.14 0.409±0.29 Dense forest 56.00±7.37 0.712±0.21 0.297±0.08 0.682±0.19

Table: 3.8 Grasses density, diversity, richness and evenness in different habitats in KWA

Habitat Density(/m ) Diversity Richness Evenness Open forest I77±41.41 1.047±0.09 0.650±0.03 0.789±0.09 Moderate forest 172±27.67 0.848±0.16 0.517±0.09 0.795±0.n Dense forest 134±22.98 0.875±0.09 0.704±0.06 0.785±0.07

Table: 3.9 Mean sapling and seedling density in different habitats in DWA

Habitat Sapling density(/ha) Seedling density(/ha) Open forest 13.94±12.46 28.08±24.87 Moderate forest 46.83±11.29 22.48±8.53 Dense forest 51.36±8.04 30.81±5.99 Overall 46.26±6.16 27.64±4.23

Table: 3.10 Mean sapling and seedling density in KWA

Habitat Sapling density(/ha) Seedling density(/ha) Open forest 347±67.96 441±110 Moderate forest 720±255 480±78 Dense forest 517.51±122 493±76 Overall 457±70.84 479±48

CHAPTER 3 VEGETATION COMPOSITION 39 Table: 3.11 Tree density (/ha) along with Important Value Index (IVI) in Dabka and Khulgarh Watershed Areas

Tree species DWA IVI KWA IVI Abies pindrow 13.23 7.03 - • - Acer oblongum 10.21 6.08 - - Adina cordifolia 7.81 12.72 - - Brassaiopsis mitis 0.60 1.08 - - Bridelia retura - - 2.38 0.92 Cedrus deodara 42.75 11.59 - - Cornus macrophyla - - 4.85 1.43 Cupressus torulosa 1.20 2.87 - - Cassia fistula 10.22 14.79 - - Euonymus sp. - - 14.54 3.11 Ficus benghalensis 3.00 5.34 - - Ficus religiosa 1.20 1.55 - - Ficus hispida 1.20 1.45 - - Grewia opiiva 0.60 0.87 0.80 0.95 Grewia asiatica - - 0.80 0.96 Ilex dyperina 13.87 10.37 1.01 1.34 Litsia umbrosa 23.32 11.98 12.65 5.35 Lyonia ovalifolia 11.21 9.08 45.54 9.54 Madhuca longifolia 3.61 3.95 3.98 4.16 Myrica esculenta 4.81 6.27 60.51 35.73 Machilutn odoratissima - - 17.52 - Malus sp. - - 2.11 2.98 Murrya sp. 4.81 6.28 - - Mallotus philippinensis 5.41 8.53 - - Magnifera indica 3.61 5.34 - - Millettia auriculata - - 1.59 1.22 Nerium indicum 0.60 0.56 - - Persea duthiei 9.21 2.34 8.43 7.23 Pinus roxbughii 4.40 3.85 531.01 155.23 Pinus wallichiana 10.41 7.58 21.23 20.21 Pyrus pashia - - 2.39 1.23 Pieris avalifolia - - 31.05 25.51 Phyllanthus indica 1.20 2.81 - - Premma latifolia - - 0.80 0.96 Phoebe lanceolata - - 0.80 0.92 Quercus incana - - 110.46 42,65 Quercus floribunda 13.82 17.04 - - Quercus leucotrichophora 117.77 128.80 23.46 13.23

CHAPTERS VEGETATIONCOMPOSTTION 40 Quercus semecarpifolia 18.43 - - - Rhododendron arboreum 20.43 29.79 44.59 23.63 Symplocos theifolia 4.31 1.22 - - Syzygium cumini 6.61 11.30 - - Sapiunt insigne 1.80 3.16 - - Shorea robusta 11.42 16.05 - - Swida oblonga - - 20.97 11.23 Taxus baccata 43.21 10.21 - - Viburnum cotinifolium 27.85 11.21 4.54 3.21 Villebrunea frutescens - - 2.39 2.91 Wrightia tomentosa - - 0.80 1.05 Unidentijiedl - - 3.00 3.45

CHAPTER 3 VEGETATION COMPOSITION 41 Figure: 3.1 Diversity, richness and evenness of trees on different aspects in DWA

Figure: 3.2 Density of trees on different aspects in DWA

North South East West

* Shrubdiv • Shrubric jt SMrubeve

Figure: 3.3 Diversity, richness and eveness of shrubs on different aspects in DWA

CHAPTER 3 VEGETATION COMPOSITION 42 3500 T . 3000 m ^ 2500 1 2000 -o 1500 E S 1000 - •^ son 0 - 1 North South East West

Figure: 3.4 Density (/ha) of shrubs on different aspects in DWA

140 1 120 100 80 60 . 40 A 20 0 North South East West

» He'bs U Grasses

Figure: 3.5 Herbs and grasses density (/m ) on different aspects in DWA

1.2 1.0 *,—-"—"""'^ 0.8 TZ^—•"'^ 0.6 0.4 1 0.2

North South East West

• Herb div • Herb ric —*—Herb eve

Figure: 3.6 Diversity, richness and evenness of herbs on different aspects in DWA

CHAPTERS VEGETATION COMPOSITION 43 North South East West

• Grass div U Grass ric —*—Grass eve

Figure: 3.7 Diversity, richness and evenness of grasses on different aspects in DWA

13 00 1000 y~- 800 ^"^ i 600 - ^^^^y^

1 400

200

0 (Nfortli Soulh Co 51 West

Figure: 3.8 Density (/ha) of trees on diiferent aspects in KWA

1.2

1.0

0.8

0.6

0.4

0.2

0.0 North South East West

Diversity Richness Evenness

Figure: 3.9 Diversity, richness and evenness of trees on different aspects in KWA

CHAPTER 3 VEGETATION COMPOSITION 44 12000

! 10000

8000

6000 -

4000

2000

0 —-1 North South Cost West

Figure: 3.10 Density (/ha) of shrubs on different aspects in KWA

1.2 ::i 0.6

0.4

0.2 t

0.0 i North South East Weil

•Diversity 'Richness —*—Evenness

Figure: 3.11 Diversity, richness and evenness of shrubs on different aspects in KWA

180 160 140 : 120 f h 100 -' 80 60 40 20 t 0 •-- SouLii Cost

-Herb den •Grdssden

Figure: 3. 12 Herbs and grasses density (/m ) on different aspects in KWA

CHAPTER 3 VEGETATION COMPOSITION 45 Figure: 3.13 Herb diversity, richness and evenness on different aspects in KWA

1.4 1.2 1.0 0.8 0.6 0.4 0.2 t 0.0 Morth South East West

-Grass Div. -Grass Rich.

Figure: 3.14 Grass diversity and richness on different aspects in KWA

300

250

200

150

100 -

50

0

—•—Tree den U Cut tree den —"* — loptrro den

Figure: 3.15 Tree, cut tree and lopped trees density (/ha) in relation to human habitation in DWA

CHAPTER 3 VBGBTATION CoMPOsmoN 46 1200

lOOO

800 \ ^

600 •

400 - • iOO - • 0 ^ 1km 1.5km <2km

» Tree Density —^i—Cuttrredcn —*— lop Iroe den

Figure: 3.16 Tree, cut tree & lopped tree density (/ha) in relation to human habitation in KWA

1.5 r

1 a.s

0 -t~ upto500 uplolkm

•—T'ce div. W Tree rich. —*—Tree even.

Figure: 3.17 Tree diversity, richness and evenness in relation to human habitation in DWA

1.6 T 1.4 H 1.2 1 -1 0.8 - 0.6 - 0.4 ^ 0.2

1km 1.5km <2km

* Tree div. M Troo rich.

Figure: 3.18 Tree diversity and richness in relation to human habitation in KWA

CHAPTER 3 VEGETATION COMPOSITION 47 3000

2S00 2000 • 1500 • 1000 • 500 i^^B 0 -. .• up to 500m up to 1km

Figure: 3.19 Shrub density (/iia) in relation to human habitation in DWA

8000

7000

6000

5000

4000 -

3000

2000

1000 1 0 -__.+- --• •^ 1km 1.5km <2km

Figure: 3.20 Shrub density (/ha) in relation to human habitation in KWA

1.4 -

1-2

1 -;

0.8 : 0.6 0.4 - 0.2 ~ 0 ' -+- up to 500IT1 up to 1km

-Dabkd • Khulgarh

Figure: 3.21 Shrub diversity in DWA and KWA in relation to human habitation

CHAPTER 3 VEGETATION COMPOSITION 48 3.5 Discussion The vegetation of KWA falls under temperate forest and DWA on the other hand is falls under both sub-tropical as well as temperate zone. Being small in area, no clearly distinct arrangement of tree species in space to form definite vegetation classes was present.

However, some poorly distinct classes can be recognized based on the relative dominance of tree species.

The subjective classification of vegetation into different habitat types seemed to be satisfactory in order to discriminate between patches within the mosaic of heterogeneous vegetation. Such classification may not be the best method, however the aim of this study was to work out vegetation ecology and structure, which may be helpful in explaining animal-habitat inter-relationships and inter-dependencies.

Tree species density was significantly different in both the sites. It was higher in Khulgarh as compared to Dabka. The tree density 715.93 in Khulgarh and 246.96 in Dabka recorded in this study are well within the range of values reported for other forests of different localities of Kumoan Himalayas (Saxena and Singh 1982, Tiwari and Singh 1985, Upreti et al. 1985,

Orus 2001). However Hussain et al. (2001) have shown higher tree density in Khunjakharik and Sitlakhet areas. The possible reason for higher tree density estimates could be due to small proportion of sampling area. Moreover, that study was conducted in 1998 and since then-onwards frequent fires and high anthropogenic pressure in both the areas have changed the forest composition. The tree diversity and richness found during this study, in both the areas, are similar to those reported by Sultana (2002). However, these values are quite low

(all values < 2.0) as compared to values (2.63 and 2.28) recorded by Saxena et al. (1985),

CHAPTER 3 VEGETATION COMPOSITION 49 who found maximum tree diversity in middle Himalayas concluding that harsh climate was responsible for the development of dominance while moderate climate i.e. high rainfall and moderate temperature for diversification closely supporting that tropical forests are more diverse than temperate ones (Khan 2004). Shrub density was low compared to values reported by Sultana (2002) and Hussain et al. (2008) in the same area. Shrub diversity range

(0.448 in Khulgarh and 1.097 in Dabka) reported was well within the range of (0.6 - 1.11 reported by Hussain et al. (2008) in the same area but lower (1.36) than what was reported b}

Dhar et al. (1997) in other regions of Kumoan Himalayas.

In our study, Oak (Q. leucotricophora) forest represented the elevation range 1800 - 2300 m

(1200 - 2300 m by Singh and Singh 1987, 1700 - 2100 m by Singh et al. 1994), while Q. semecarpifolia forest was present between 2200 - 3000 m altitude range (2400 - 3600 m by

Singh and Singh 1987, 2366 - 3000 m by Singh et al. 1994) and Shorea robusta forest reported below 900 m (<800 m by Ahmed et al. 2008). The diversity values were also similar to those reported by (Singh et al. 1994). These values were also similar to those reported for

temperate communities in adjacent Nepal Himalayas (Ohsawa et al. 1975) and elsewhere

(Monk 1967). As reported by Dhar et al. (1997), more than 50% species of this region are

non-native species. The area has received plant elements from adjoining regions of tropical

Asia (Indo-China and Indo- Malaya, Mani 1974) and Indo-Gangetic plains (Spate 1957).

Though, the data were not collected and analyzed keeping in mind native species but, the

distribution of non-native species is known from the Himalaya (Maheswari 1962). However,

the change in native flora because of non-native species could lead to long-term changes in

ecosystem processes (Ramkrishnan and Vitousek 1989).

SSBBBSBaBOBaBBBBamaBBamaSSBSSaBBBSBSmBBSBB^SBSSaB^^ CHAPTER 3 VEGETATION COMPOSITION 50 The P. roxburghii poses serious threat to native Oak {Q. leucotricophora and Q. floribunda) in whole of the Kumaon, as it has been reported earlier also (Singh and Singh 1987). The ecological nature of P. roxburghii does not allow other broad-leaf species to replace it, and P roxburghii will continue to hold a site indefinitely once it occupies it (Singh et al. 1984). All

Oak species are facing severe threats because of the demand for fodder and fire-wood. This has led to reduction in seed production (Saxena and Singh 1984). Other valuable tree species such as A. pindrow, T. baccata and C. deodara are felled because of their timber value. A pindrow and C. deodara had a good population size in Vinaiyak reserve forest falling under

DWA. Protection of this community is necessary. The density of regenerating species was highest in Khulgarh as compared to Dabka. In Dabka extensive summer forest fires are ver}

frequent which is perhaps responsible for low density of regenerating species. Shrub and herb

density was found highest in moderate forest indicating that open canopy provides better

opportunity for the recruitment of shrubs and herbs (Khera et al. 2001). Although, in open

forest these values were found to be lowest. The possible reason for this could be that the

open forest in the study area mainly consisted of pine forest, and the acidic nature of Pinus

roxburghii does not allow any broad-leaf species to survive (Singh et al. 1984).

The southern and eastern aspects are comparatively more dense and diverse than other

aspects. Low density and diversity in other aspects is due to high anthropogenic pressure on

these aspects. Khera et al. (2001) also found that low density and diversity of vegetation in

one or other aspects was due to anthropogenic pressure. In the complex Himalayan forest

ecosystem chronic form of disturbances exists in which people remove only a small fraction

of forest biomass in the form of grazing, lopping, surface burning and litter removal at a

given time. These disturbances are affecting the stability of the ecosystem and retarding the

CHAPTER 3 VEGETATION COMPOSITION 51 successional process in the area. Moreover, the broad overlapped scattered centers of species population along a gradient imply that most of the communities integrate continuously along environmental gradients, rather than forming clearly distinct zones (Mishra et al. 2000). The total number of species in any physiographic aspects reflects the adaptation potential of the community. The physiographic features such as aspects and elevation have profound influence on the distribution, growth, form and structure of vegetation, as result of which the individual species has different values for density at various aspects and altitudes (Wikum and Wall 1974). The diversity is also variable on different geographical locations (Baduni

1996).

The low tree and shrub density and highest lopped and cut tree density in and around villages

is the resuh of this human dependency on forest. Human interference causes great impact on

forest structure (Tyser and Worley 1992). In Kumoan, most of the lower altitude and middle altitude forests are densely populated as compared to high altitude forests (Sultana 2002). So. the chances of destruction of forest and invasion of non-native species are more as seen in

Quercus leucotricopphora and Quercus semecarpifolia forests. Disturbances may interact in

complex ways to affect composition (Collins and Barber 1985, Steuter et al. 1990, Noy-Meir

1995). The shrub diversity was found highest near human habitations, similar observation has also been made by Khan (1996) in Gir Lion Sanctuary, whereby controlling vegetation from

livestock grazing led to a considerable increase in shrub densities and decrease in species

richness and diversity. The high species diversity in shrubs near human habitation is contrary to expectations, as one would expect higher regeneration and species richness as we move away from habitation. While moderate grazing favors high species diversity in grasses (Mc-

Naughton 1983b), it needs to be empirically tested by enclosure experiments whether

CHAPTER 3 VEGETATION COMPOSITION 52 moderate grazing by domestic livestock leads to better regeneration and high species richness of trees and shrubs in Kumoan Himalayas. Pandey and Singh (1985) have also reported an

increase in species diversity in disturbed ecosystem of Kumoan Himalayas. While in alpine

meadows of the Himalayas, the impact of livestock grazing has been a subject of

considerable debate among ecologists (Ram et al. 1989, Negi et al. 1993, Rawat and Uniyal

1993, Kala et al. 1995, Sundriyal 1995, Kala et al. 1997). Based on intermediate disturbance

hypothesis, a few authors (Kumar and Joshi 1972, Rawat and Rodgers 1988) have argued that

moderate level of grazing may enhance herbaceous species diversity in alpine meadows.

While Singh (1991) and Kala et al. (1997) found higher species diversity in ungrazed sites as

compared to grazed sites indicating that livestock grazing may not be crucial for maintaining

species diversity but certain abiotic factors such as soil depth, snowfall, water movement,

wind and soil erosion seem to influence the structure and composition of alpine meadows

(Kala et al. 1995). Kala and Rawat (1999) also found that heavy grazing reduces the species

diversity, and promotes ruderal and weedy species.

The low regeneration of a plant species in Dabka is a topic of concern for managers. All the

species occur in extremely low densities in tree layer and large scale mortality in plant

population (Ahmed et al. 2008) would further affect their regeneration. The repeated fires in

Dabka cause retrogression in vegetation and reduction in tree cover. This area needs an

urgent attention as density of some ungulate species found in this area, was higher than other

protected areas of Kumoan Himalayas (Chapter 4).

CHAPTER 3 VEGETATION COMPOSITION 53 CHAPTER 4 BIRD COMMUNITY STRUCTURE 4.1 Introduction Temperate forests are complex habitats that support diversified communities (Sultana 2002).

Several aspects of the ecology of the birds inhabiting these factors, such as community structure (Keast 1988), population dynamics (Holmes et al. 1986, Leek et al. 1988), competition (Robinson and Holmes 1982) or habitat selection (Hespenheide 1971, Sherry and

Holmes 1985) have been investigated.

Many birds are restricted to certain types of habitats and their distribution patterns are thought to be strongly related to various structural and floristic aspects of the vegetation (Karr and Roth 1971, Noon 1981, Cody 1985, Terborgh 1971). Consequently, a structurally complex forest rich in plant species is likely to house a greater diversity of bird species than a nearby, structurally more simple vegetation type.

Species richness and community structure of birds vary from region to region (Recher 1969). as well as within a region, as abiotic and biotic factors vary from habitat to habitat. Several studies have identified the factors responsible for variations in avifauna from habitat to habitat outside India (Anderson 1970, Beedy 1981, Manuwal 1983) and within India (Beehler et al. 1987, Daniels 1989, Johnsingh et al. 1987, Katti 1989, Rai 1991).

Avian communities are the characteristics and properties of assemblage of species population

(Koromondy 1989) or the group of population that occur together (Ricklefs 1990). Major goals of avian community ecology are to identify recurrent pattern of species composition, guild structures, diversity and other parameters among co-occurring species and to understand the factors promoting those pattern (Wiens and Rotenberry 1981). Being

CHAPTER 4 BIRD COMMUNITY STRUCTURE 54 ecologically diverse and sensitive to various kinds of perturbations, avian community acts as a better predictor of the quality and health of the habitat than single species (Javed 1996).

The introduction of the avifauna of Indian subcontinent began in the first half of the 19'^ century with three main pioneers. Edward Blyth, Btain Hodgson and Thomas Jerdon. Jerdon

(1860) published a book named "Birds of India" which summarised what was known at that time about the avifauna of much of what is now the country of India (Grimett et al. 1998). In the 20* century, Late Dr. Salim Ali, the first Indian ornithologist carried out many surveys throughout the country and published relevent literature on birds. But still there is lack of information on the ecology of bird community in India and especially in the Himalayas.

4,2 Literature Review

The literature review on bird studies has been divided in five categaries such as

1. Bird-habitat relationship

2. Foraging studies , [ <^. '^Q ^H- '•

3. Environmental Influence M., ,'- 4. Comparison of Methods

5. Management studies

4.2.1 Bird Habitat-Relationship

Many surveys and studies have been conducted to know the status of birds. Crooks et al.

(2001) have surveyed the islands of USA to know the status of birds. They have also calculated the local extinction and colonization rate of birds. While in South America, Jacobs

and Walker (1999) estimated the density of birds inhabiting fragments of cloud forest in

Southeren Ecuador. Many checklist of birds have been published through out the world for

CHAPTER 4 BIRD COMMUNHY STRUCTURE 55 the status and distribution of birds but the main work has been done on bird habitat relationship.

Several authors (Lack 1933 & 1943, Hilden 1965) have theorized that bird selects habitat on

the basis of "sign stimulu" that convey information about ultimate factors such as food,

protection and nest site avaliability. Root (1967) has documented areas in which bird species

appear to be associated directly with ultimate factors. Other studies have described structural

and functional components of vegetation usually involving some form of symbolism denoting

items considered important to the avifauna present (Weins 1969). MacArthur and MacArthur

(1961) developed a technique to describe the layering of vegetation. Some authors showed

the availability of food in the habitat preference by birds (Connell and Orias 1964.

MacArthur 1965, Clout and Gaze 1984).

Bond (1957) and Anderson (1970a) studied that plant community succession have often been

associated with changing bird species composition. Robbins (1979) indicated the importance

of habitat size to maintain population of Neotropical migrants. Increased edge is a factor that

does attract species, as shown by Lay (1938) and Johnson (1947). MacArthur and MacArthur

(1961) were the first to suggest that structural complexity of vegetation measured by the

vertical layering of foliage. Later studies in temperate forest do support this (Erdelen 1984),

but studies on tropical forests have failed to prove this relationship (Pearson 1982, Weins

1983, Daniels 1989). Habitat diversity or spatial heterogeneity influence the diversity of birds

positively (MacArthur 1965, Rafe et al. 1985, Pyrovetsi and Crivelli 1988). Rotenberry

(1985) found that local assemblage of birds are determined by the floristc and not by the

physiognomy of the vegetation. Larger area of a habitat tends to increase the bird species

diversity (Terborgh 1973, Galli et al. 1976, Martin 1980, Blake 1983, Woolhouse 1983,

CHAPTER 4 BIRD CoMMUNnr STRUCTURE 56 Blake and Karr 1984). While small habitats when compared to larger habitats of the same biotope are found to have a higher proportion of the communities consisting of abundant

generalists that are often the smaller species (Terborgh et al. 1978, Howe 1979, Willis 1980.

Ambuel and Temple 1983, Nilsson 1986).

4.2.2 Foraging Studies

Studies comparing the foraging behavior of congeners have shown the familiar patteren of

resource partioning found in warblers and tits (MacArthur 1958, Hartley 1953, Cody 1974).

Other studies showed that closely related species show similar foraging strategies (Root

1967, Fitzpatrick 1980). In some studies it has been found that bird species show preference

for certain tree species and avoid others (Holmes and Robinson 1981, Peck 1989) as the

availability of prey varies from one tree species to another (Robinson and Holmes 1984).

Time budget suggest that birds do not spend more time in foraging during autumn and winter

than during spring and summer in temperate forest (Haylock and Lill 1988, Ford 1989).

Foraging behavior has been divided into guilds that define as functionally related group of

species (Kikawa and Anderson 1986). Root (1967) described guild as a group of species that

exploit the same class of resources in a similar way. Holmes et al. (1986) defined guild

structure as the patterens of resource use among co-existing species and with emphasis on

similarities and differences in how these species exploit resources. Recent researchers have

documented a mere objective analysis of the bird guild and exploration of the second level of

guild grouping based on foraging strategies (Holmes et al. 1979, Sabo 1980, Holmes and

Robinson 1981, Holmes and Recher 1986, Poulin et al. 1994).

CHAPTER 4 BIRD CoMMUNmr STRUCTURE 57 The study of relationships between bird despersed plants and fruigivorous birds in temperate regions have received attention (Snow 1971, Thompson and Willson 1979, Stiles 1980.

Herrera 1984, Herrera and Jordano 1981, Jordano 1982, Sorenson 1981, Stapanian 1982).

4,2.3 Environmental Influence

Ornithologists have noted change in avian activity with time of day for decades. During the

breeding seasons, activity and detectability of most bird species are maximum at dawn,

decrease to diurnal minimum at mid day (Robbins and Van Velzen 1967, Weber and

Theberge 1977, Sheilds 1977) and increase in late afternoon (Jarvinen et al. 1977a). Seasonal

changes were also studied by Best (1981) and Anderson et al. (1981). It was found in

Austarlia that the birds reach the highest levels of diversity in the zone of maximum rainfall

(Pianka and Schall 1981). Robbins (1981) also found effect on bird diversity by temperature,

wind speed, sky condition and winter condition. Some studies have also been conducted on

the limitation of sampling in the rugged terrain (Oberholser 1905, Wetmore 1939, Murray

1946, Tanner 1955, Dawson 1981).

4.2.3 Disturbance Studies

Human activities in an ecosystem result in restructuring of its communities through a variety

of means. However, the influence differs in different ecosystem (Brash 1987). Habitat loss

and fragmenation are known as causal agents of species extinction (Leek 1979, Brash 1987,

Whitten et al. 1987). Some authors compared samples of experimentally disturbed nests or

colonies with undisturbed controls (Anderson and Keith 1980, Cairns 1980). A number of

studies have shown the effects of disturbance on behavior, predation rate and other factors,

which are likely to affect overall reproduction (Hobson and Hallina 1981, Verbeek 1982).

Burger et al. (1982) found that ditching increased species diversity in salt marshes. Some

CHAPTER 4 BIRD COMMUNITY STRUCTURE 58 studies compared bird communities in undeveloped areas and areas used as campgrounds with different degree of developments for holiday cottages (Foin et al. 1977, Robertson and

Flood 1980, Clark et al. 1984, Blakesley and Reese 1988). All these studies found in general a higher species diversity in disturbed habitats. Fjeldsa (1999) also found similar results in

Tanzania. Madsen (1985) found that wintering geese avoided areas close to roads for grazing

and hunting a less significant problem (King 1978). Birds with endangered status over the world, 67.2% are forest birds, 16.8% are scrub and 12.7% are wetland birds (King 1978).

4.2.4 Comparison of Methods for Assessing Bird Abundance

A bird census technique that estimates the number of birds per unit area rather than relative

abundance is desirable when the objective is to estimate the number and species of birds in a

community for energetic considerations (Weins and Nussubaum 1975), for calculating

species diversity (MacArthur 1960, MacArthur and Mac Arthur 1961) or for enlightening the

effects of habitat disturbance on bird population (Bock and Lynch 1970). Some existing

methods require different amount of efforts and give resuhs of differing accuracy (Kendeigh

1944, Emlen 1971, Robinette et al. 1974, Best 1975, Franzreb 1976, Reynolds et al. 1980),

the choice of a suitable technique should be based on the species of interest, the season of the

year, time and personnel available, number and types of habitats to be censused, and accuracy

of the density estimate that is require (Sultana 2002).

Territorial or spot mapping methods (Williams 1936, Kendeigh 1944) require that the census

be conducted during the breeding season and involve considerable time and effort. Plots of

fixed size (Fowler and McGinnes 1973, Anderson and Shugart 1974), whether traversed by

transect or censued from a fixed point, are more easily censued since only bird occurrence

needs to be noted (Reynolds et al. 1980). O'Meara (1981) compared the line transect and spot

CHAPTER 4 BIRD CoMMUNnr STRUCTURE 59 mapping technique. DeSante (1981) compared the mapping and circular plot method while

Franzreb (1981) compared mapping and line transect methods. Edwards et al. (1981) compared sample plot, variable circular plot and transect method. Fjeldsa (1999) compared species richness counting method with point count and transect and found that this is highly time efficient and secures broad area coverage.

4.2.5 Management Studies

For management purpose evaluation and assessment of nature for conservation has been described and researched by several authors (Ratcliflfe 1971, Goldsmith 1975, Peat 1984.

Gotmaric et al. 1986). Spellerberg (1981) and Usher (1986) reviewed the wildlife conservation evaluation. Some studies have been conducted in relation to patch size for

management of birds. For temperate forest bird communities a general pattern appear to be

that total density is negatively correlated with patch size (Oelke 1966, Gromadzki 1970,

Helliwell 1976, Morse 1977, Nilsson 1977, Martin 1981). This correlation disappears when

species prefering forest edges are excluded (Gromadzki 1970, Morse 1977, Nilsson 1977,

Martin 1981, Nilsson 1986). However, for tropical islands this pattern does not exist. Here,

there are either no clear density trends on large islands (Cox and Ricklefs 1977, Terborgh et al. 1978), or the total density increase with patch size, especially on smaller islands (Diamond

1970a, Willis 1980, Wright 1979, 1981).

An early debate within conservation biology occurred over whether species richness is

maximized in one large nature reserve or several smaller ones 'SLOSS' (Single large or

several small) of an equal total area (Diamond 1975b, Simberloff and Abele 1976, Terborgh

1976). Opposing this viewpoint, other conservation biologist argue that well placed small

reserves are able to include a greater variety of habitat types and more population of rare

CHAPTER 4 BIRD CoMMUNny STRUCTURE 60 species than one large block of the same area (Jarvinen 1979, Simberloff and Gotelli 1984).

As suggested by Game and Peterkin (1984) and Soule and Simberloff (1986) strategy on reserve size depends on the group of species under consideration as well as scientific circumstances.

4.2.6 Overview of Bird Studies in the Indian Himalayas

Studies on overall bird community in the Indian Himalayas are few. However, species specific studies have been conducted in Western and Eastern Himalayas. Shankar-Raman

(1995) studied the impact of shifting cultivation on bird community in Mizoram while Singh

(1994) compiled a checklist of Arunchal Pradesh. Katti et al. (1990) conducted an ornithological survey in eastern Arunchal Pradesh. Katti (1989) studied the bird communities of lower Dhachigum valley in Kashmir. Garson et al. (1993) studied the ecology and conservation of cheer pheasant. Iqbal (1993) studied the pattern of habitat use by Kalij pheasant in the Indian Himalayas. Saklani et al. (1988 & 1989) worked on habitat utilization and behavioral ecology of Kalij in the Garhwal Himalayas. Sathyakumar et al. (1993) collected information on the ecology of Kalij and Monal in the Kedamath Wildlife Sanctuary.

Ahmed and Musavi (1993) studied the ecology of Kalij at Ranikhet in Kumoan. Asad et al.

(1994) surveyed Limber valley to study the Western Tragopan and its habitat. Khaling (1998) studied the ecology and conservation of Satyr Tragopan in Singhalila National Park,

Darjeeling. Datta (1998) studied the hombills in Arunchal Pradesh. Pandey (1993) conducted a pheasant survey in the Upper Beas valley, Himachal Pradesh.

4.2.7 Overvievv' of Bird Studies in Kumoan Himalayas

Britishers very well surveyed Almora and Nain Tal districts in terms of bird species in 19"' century. Though the reporting's mainly consisted new sightings, but all of them have great

CHAPTER 4 BIRD CoMMUNrrv STRUCTURE 61 importance in knowing the status of birds. A total of 62 studies were conducted on birds of

Kumoan Himalayas together with reporting of new sightings and compiled checklist of an area (Table 4.1). However no ecological study has been done except Sultana and Khan

(2000), Hussain et al. (2001) and Sultana (2002). Out of 62 studies, 40 were carried out in

Nainital and 22 in Almora.

4.3 Methodology

Avian community studies were conducted from September 2007 to June 2009 in Dabka and

Khulgarh Watershed Areas. Point count method (Reynolds et al. 1980) and species richness counting method (Mackinnon and Phillips 1993) were used for sampling birds in both the

Watersheds. Point count is a popular method for surveying the birds (Dawson 1981) and the method is used for extensive monitoring programs. During survey, birds were sampled by monitoring 55 points in Khulgarh and 75 points in Dabka with respect to the area. The sampling points were taken randomly. A distance of approximately 250 m was maintained between two sampling points. A 20 minutes field time duration was spent at each point in the morning hours between 0600-1030 hr with fixed radius of 20 m each. The duration on the point count is one of the most obvious factors influencing the detection probability of the bird species. Keeping the above-mentioned fact in mind, each point was monitored for 20 minutes. At each point station, data was recorded on the following variables: (a) species and number of individuals (b) perch height (c) stratum and height of tree and (d) activity.

4.3.1 Guild Structure

Root (1967 & 2001) defined guilds as group of species that exploit the same class of environmental resources (e.g., food, nest site) in a similar way. Guild studies are particularly valuable since they determine the function of avian communities and also how these

CHAPTER 4 BIRD CoMMUNmr STRUCTURE 62 communities are structured in a resource hyperspace used by a set of species. Coexistence of species in an area depends largely on various biological factors and most important being partitioning of resources (Holmes et al. 1979).

Guild studies are particularly valuable since they determine the function of avian communities and also how these communities are structured in a resource hyperspace used by a set of species. Composition of species within a guild in any area depends on the habitat related attributes like the foraging substrate, vegetation structure, vertical heterogeneity and other aspects of physiognomy (Robinson and Holmes 1982, Holmes and Recherl986). Bird species have been observed to show preferences for perch height and food sites (Landres and

MacMahon 1980). The data on such patterns was collected during the point counts, whenever a bird was encountered. Every time a bird was seen feeding on a substrate or making any attempt (e.g. canopy, tree trunk, branch or ground), foraging height and horizontal distance from the tree trunk were recorded following by Kratter et al. (2001). The data for all the

individuals across all the seasons was pooled on the assumption that there is very little or no

change in the foraging behavior of the birds during different time of the year. This pooling of

data was done separately for Dabka and Khulgarh. Data on 38 species was recorded in Dabka

and 35 species in KWA.

4.4 Analysis

Shannon-Weiner Index (H') was used for diversity and Margalef s Index (RI) for richness computations. To find out the correlation between the bird (density, diversity, richness and evenness) with the habitat parameters, Pearson's product moment correlation coefficient was used.

CHAPTER 4 BIRD CoMMUNnr STRUCTURE 63 For the statistical analysis with Biodiversity Pro Version 2 (Neil 1997), each species list was treated as a separate sample. Jacknife 1 (Bumham and Overton 1978, Heltshe and Forrester

1983, Smith and Van Belle 1984) was used to extrapolate species richness curves. Jacknife 1

is based on incidence of species in samples. Rarefaction was used to compare the species

diversity of two watershed areas.

The program DISTANCE 5.0 Release Beta 5 (Thomas et al. 2005) was used to compare

models, assess goodness-of-fit and determine estimates of bird density for the study period,

seasonally and across different habitats in both watersheds. The different models were

compared using Akaike's Information Criteria (AIC; Bumham and Anderson, 1998). By the

definition the best model is the one with the least AIC value for a given season; competing

models were those within 2 AIC values. When using AIC to select a particular model among

alternative candidate models of the detection function, it is not unusual to find that more than

one model have similar AIC scores (perhaps differing by AIC's of 2 or fewer). When this

happens, more reliable inferences can be obtained based on the final results on an AIC

weighted average of these plausible alternative models (Bumham and Anderson 2002).

Variations in bird density across different habitats and seasons was tested by using Two Way

Analysis of Variance. Two-way ANOVA technique allows us to estimate the effects of two

independent variables on a dependent variable (Fowler et al. 2006).

A matrix was formed of bird species and their mean perch height and horizontal distance from

tmnk for each species. This data set was used to generate guilds. Single linkage cluster

diagram were generated using nearest neighbour method. As no objective criteria is available

to use euclidian distance for separating groups, we considered midpoint of euclidian distance

CHAPTER 4 BIRD COMMUNOY STRUCTURE 64 as the separating point and clusters were groups separated by euclidian distance greater than

0.25 or the mid point value for cluster interpretation.

Guild diversity and richness across different habitats was also calculated. Based on field observations and prior knowledge of the diet of the birds. Birds were assigned into six different categories based on their food habits. This was done through following existing literature primarily Ali and Ripley (1987).

Omnivore: bird species that eat both flesh and vegetable for example common myna and crows.

Carnivore: Species who are flesh eaters for example, raptors.

Frugivore: Birds that eat the fruits like barbets.

Nectarivore: Birds that suck the nectar from flowers like sunbirds.

Granivore: Bird species who eat the seeds like parakeets.

Insectivore: Insect eating birds like drongos and flycatchers.

All the statistical tests were performed following Zar (1999) and using the statistical software

SPSS 17.0(Norussis, 1990).

4.5 Results

4.5.1 Accuracy of Sample Size

For Dabka 57 samples were used whereas for Khulgarh 49 samples were used for the analysis.

Jackknife Iwas used for stabilization of the number of species observed in watershed areas.

Figure 4.1 and 4.2 illustrates the performance of Jacknife 1 for 15 species lists respectively. A total of 157 birds in DWA and 102 species in Khulgarh were listed following species listing method. In Dabka and Khulgarh watershed area asymptote reaches after 165 and 110 birds, respectively.

CHAPTER 4 BIRD COMMUNITY STRUCTURE 65 4.5.2 Comparison of Watershed Areas in Terms of Bird Diversity

Rarefaction plots the expected number of species against number of individuals. It provides a measure of species diversity which is robust to sample size effect, permitting comparison between communities. Steeper curves indicate more diverse communities. So, for both the watershed areas numbers of species were plotted against the number of individuals for comparing the diversity of the bird communities. Dabka was more diverse as compared to

Khulgarh watershed area. Figure 3 shows the rarefaction curves for the two watershed areas.

4.5.3 Comparison of Bird Density

In DWA a total of 157 (Appendix III) species were encountered during the study period.

Overall bird density (D) was 29.97 ± 1.79/ha, density of clusters (DS) was 9.53 ± 0.48/ha.

Encounter rate (n/K) was 1.87 ± 0.02 and the average cluster size (A(S)) was 3.14 ± 0.09

(Table 4.2). Across different habitat in Dabka Watershed Area, density was highest in dense forest 40.60 ± 4.73/ha and lowest in barren area 17.95 ± 2.73/ha (Table 4.3) and difference was found to be significant (P = 4.33, df == 4, P = 0.02). Two-way analysis of variance with seasons (Winter, Summer) and habitat as a main effect showed that there was no significant difference in bird density between seasons (F i^ = 1.87, P = 0.34) and also there was no significant difference in bird density across different habitats (F 4,4 = 1 -21, P = 0.26).

In KWA a total of 102 (Appendix IV) species were encountered during the study period.

Overall bird density (D) was 28.35 ± 1.79/ha density of clusters (DS) was 7.85 ± 0.39/ha.

Encounter rate (n/K) was 1.53 ± 0.02 and the average cluster size (A(S)) was 3.62 ± 0.14.

(Table 4.4). Across different habitat in KWA, density was highest in agriculture field 41.60/ha

±5.12 and lowest in barren area 13.81/ha ± 2.09 (Table 4.5) and difference was found to be significant (F = 5.66, df = 4, P = 0.001). In both the Watersheds density was found highest in

CHAPTER 4 BIRD COMMUNITY STRUCTURE 66 summer as compared to winter. Two-way analysis of variance with seasons (Winter and

Summer) and habitat as a main effect showed that there was highly significant difference in bird density between seasons (Fi,4 = 8.57, P = 0.004) and there was also significant difference in bird density across different habitats (F4,4 = 9.90, P = 0.02).

4.5.4 Comparison of Diversity and Richness

In DWA overall bird diversity was 5.51 and richness was 12.22. Bird species diversity and richness was almost uniform in all the four habitats. Mean bird diversity was highest in moderate forest (1.45 ± 0.20) followed by open forest (1.31 ± 0.22), dense forest (1.29 ± 0.29), barren area (0.75 ± 0.34) and agricultural field (0.46 ± 0.09) and difference was found to be significant (F = 33.26, df = 4, P = 0.000). Mean richness was also found to be highest in moderate forest (3.82 ± 1.30) and lowest in agriculture field (1.19 ± 0.65) and difference was also found to be significant (F = 11.69, df = 4, P = 0.000) (Table 4.6).

In KWA overall bird diversity was 4.95 and richness was 10.24. In KWA mean bird diversity was highest in agriculture field (1.89 ± 0.19) followed by moderate forest (1.79 ± 0.19), dense forest (0.89 ± 0.30), Open forest (0.83 ±0.11) and Barren area (0.65 ± 0.36) and difference was found to be significant (F = 2.85, df = 4, P = 0.03). Mean richness was found highest in agriculture field (2.73 ±0.10) and lowest in open forest (1.32 ± 1.14) and difference was not found to be significant (Table 4.6).

4.5.5 Other Aspect of Comparison

Bird density showed a regular decline along the altitudinal gradient in DWA. Bird richness, diversity and evenness showed decline with the increase in the altitude, though decline in diversity was more but in richness and evenness was less. In KWA bird density, diversity.

CHAPTER 4 BIRD COMMUNITY STRUCTURE 67 richness and evenness also showed decline along the ahitudinal gradient, though decline in diversity richness and evenness was more prominent than density. Figures 4.4, 4.5, 4.6 and 4.7 show the variation of density, diversity, richness and evenness along ahitudinal gradient in

DWA, respectively and Figures 4.8, 4.9, 4.10 and 4.11 shows variation of density, diversity,

richness and evenness along ahitudinal gradient in KWA, respectively.

CHAPTER 4 BIRD CoMMUNny STRUCTURE 68 Table: 4.1 Review of bird studies conducted in Kumoan Himalayas

Author Year Area of study Particular bird/group Lesson R.P. 1826 Almora Bird community Hardwicke T. 1827 Almora Cheer Pheasant Gray J.E. 1829 Almora Western tragopan Griffin E. 1829 Almora Koklass pheasant Gray J. E. and Hardwicke T. 1830 Almora Koklass pheasant Vigors N. A. 1830 Naini Tal Bird community Irby L. H. 1861 Almora, Naini Tal Bird community Brooks W. E. 1869 Almora, Naini Tal Bird community Hume A. 0. 1869 Naini Tal Bird community Hume A. O. 1870 Almora Bird community Sharpe R. B. 1890 Naini Tal Bird community Finn F. 1899 Naini Tal Funn's weaver Walton H. J. 1900 Almora Bird community Osmaston A. E. 1916 Almora, Naini Tal Woodpeckers Hartert E. 1917 Naini Tal Rallidae Kloss C. B. 1918 Naini tal Phasianidae and Eurylaemidae Field F. 1922 Almora H.T. creeper Hudson C. 1930 Naini Tal Bird community Kinnear N.B and Whistler H. 1930 Almora Nuthatch Brigg's F. S. 1931 Ranikhet (Almora) Bird community Whistler H. 1931b Naini Tal Bird community AliS. 1935 Naini Tal Finn's bay a Prater S.H. 1940 Almora Yellow billed flower pecker Smythies B.E 1943 Naini Tal Yellow-headed fantain warbler Koelz W. 1950 Naini Tal Bird community Abdulali H. 1952 Naini Tal Finn's weaver Ali S and Crook J.H 1959 Naini Tal Finn's baya Rao V.U.S 1965 Naini Tal Bird community Ganguli U. 1966 Almora Bird community Ambedkar V.C. 1969 Naini Tal Finn's baya Ambedkar V.C. 1970 Naini Tal Baya weaver Ambedkar V.C. 1972 Naini Tal Weavers Sridharan E. 1974 Naini Tal Bird community Smetacek V. 1975 Naini Tal Bird community Ghorpade K.D. 1976 (Pindari) Almora Bird community Narang M.L. and Lamba B.S 1979 (Jageshwer) Almora Nepal dark rosefinch Newsome J. 1979 Almora Bird community Singh S.R and Singh A. 1980 Naini Tal Bird community Rasool T.J. 1984 Naini Tal Cheer pheasant Rabnson C. 1985 Naini Tal Bird community Jepson P. 1987 Naini Tal Bird community Young L., Garson P.J and Kaul R. 1987 Naini Tal Cheer pheasant Young L. and Kaul R. 1987 Naini Tal Pheasants YahyaH.S.A 1990 Naini Tal Bird community Ahmed A. and Musavi A.H 1993 Naini Tal White-crested Kalij Tak P.C. and Sati J.P. 1994 (Ranikhet) Almora Bird community TakP.C 1995 Naini Tal Bird community Maheswaran G. 1996 Kumoan Bird community Robnson C. 1996 Naini Tal Scarlet finch

CHAPTER 4 BIRD COMMUNITY STRUCTURE 69 -a Ahmed A. 1997 Naini Tal Bird community Hussainetal. 1997 Naini Tal Galliformes Kazmierczak K. and Singh R. 1998 Naini Tal Bird community Naoroji R. and Silva CD. 1998 Ranikhet, Almora Red kite Sultana A. and Khan J.A. 1999 Almora, Naini Tal Bird community Sultana A. and Khan J.A 2000 Almora Nainai Tal Bird community Hussain M.S., Khan J.A. and Kaul R. 2001 Almora, Naini Tal Kalij and Koklass Sultana A. 2002 Almora, Naini Tal Bird community Mathur, et al. 2007 Kumoan Bird Diversity Ahmed K., Khan J.A and Zehra N. 2008 Almora, Naini Tal Bird community Ahmed K., Khan J.A and Zehra N. 2009 Almora, Naini Tal Bird community

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tj o 00 Tf O NO o ON "1 00 NO oi ^ ^ ^ ^ - NO +1 -H -H "H 1 1 1 1 ea NO IT) CN m ON 00 NO w CN NO m t--- m CN NO o m _; _; (Nj _;

m NO "Tl NO NO NO I o o o o o C/5 5 -H o o o" o o -H -H -H 4^ -H .^^ NO ON NO m 00 i-c Tt m t~~ NO Tj- (U NO ON '—1 ON CO rt > o O O -: o a -H 5 2 ON m 2ON -^<0 —' NO o^ J^^ 00 JS3 <-H^ t^ 00 00 vo Tt 00 tN <^ •a « oo m o _; o —; o o; o6 i: 2 o\ on ON t-~; ON —; r-^ O NO w CO

00 ON m 3 V r- o oo 00 C o o o o NO o vo in m -H -H -H •D >n m ON NO 00 ON o C 0^ od -^ do o ON rn C3 S +1 -H -4H -H 4) 00 o6 to t~~. (N ro ON «J 00 _ _ _ X) rn (N —' —^ Q r-- m NO NO ON o >o 00 o ON O CN ON -^ c CS CN O ro m v^ t^ CN ON o o o vo ro (N —' O S -H -H +1 o o CN V-) CN I

w La O u NO o •*-> 00 1^ R i I g I I V a © W Q S O <; CQ a SHHSSI r^e-iH^^ :5?r^ i ^Sr &• ^-

_l 1 1 1_

Figure: 4.1 Performance of Jackknife 1 estimator for DWA

^ ^ f

H 1 1 h"

Figure: 4.2 Performance of Jackknife 1 estimator for KWA

Rwef.Kfj

Dabka

Khulgarh

//

Figure: 4.3 Rarefaction Curves for Dabka and Khulgarh Watershed Areas

CHiKPXtR 4 BIRD COMMUNITY STRUCTURE 73 90,00 80.00 ;j» 70.00 60.00 50.00 40.00 ¥•• • 30.00 1f^~ 20.00 10.00 0.00 '-F •-•• 700 1330 1900 2500

Figure: 4.4 Density (/ha) of bird along altitudinal gradients in DWA

V= -0.00DX +0.983

7O0 1300 1900 2500 Altitude

Figure: 4.5 Diversity of bird along altitudinal gradients in DWA

700 13O0 1900 2500 Altitude

Figure: 4.6 Bird richness along altitudinal gradients in DWA

CHAPTER 4 BIRD COMMUNITY STRUCTURE 74 2.50

2.00 y -0.000x4. 1.067

700 1300 igoo 250O AHStude

Figure: 4.7 Bird evenness along altitudinal gradients in DWA

200.000 _^ • y- O.OOSx t 69.73 18O.0O0 ^ • • • • • 16O.00O 140.000 -••• • ipo.oon 100.000 80.000 60.000 „

Figure: 4.8 Bird density (/ha) along altitudinal gradients in KWA

1.200 T V = -0.000x +0.730

1000

0800

0.600

0.400

0.200

0.000 <-••-• ••4M»-i»f 1100 1300 1500 1700 1900 2100

Figure: 4.9 Bird diversity along altitudinal gradients in KWA

CHAPTER 4 BIRD COMMUNny STRUCTURE 75 3.500 y = -C.001x+2.615 3.000 2.500 2.000 1.500 1.000 0.500 0.000 ••+ --••••.-••••in *••<#* i'**!-*' i--«^t i i ••••- 1100 1300 1500 1700 1900 2100

Figure: 4.10 Bird richness along altitudinal gradients in KWA

1.200 y=-0.000x+ 1.180 1.000 : • • 0.800 ;

U.bOU •^ —•—^

0.400 • • ^^ -^ 0.200 •

o.ooo . -^^^^m-i .•4«>(^*i^»*-* •- -•-i '• i **• 1 i 110 0 1300 1500 1700 1900 2100

Figure: 4.11 Bird evenness along altitudinal gradients in KWA

CHAPTER 4 BIRD CoMMUNny STRUCTURE 76 4.5.6 Guild Structure Comparison

Guild 1 consists of species which forage on the ground. It includes Thrush, Pheasant and black bird in DWA and sparrow, lapwing, dove, pheasant and babbler in KWA.

Guild 2 consists of species like woodpecker, tree creeper nuthatch, niltava in DWA. In

Khulgarh Guild 2 includes species tit, minivet, barbet, warblers and occupy top canopy. This guild was dominated by insectivore birds.

Guild 3 consist of species which utilize top canopy like barbet, tit and warblers in DWA and bulbul, warbler, tree creeper and nuthatch which utilized tree trunk and top canopy in KWA.

Guild 4 consist of species which occupy middle and lower canopy in both the watershed areas and includes species like jaw, hum's warbler, grey bushchat, ultramarine flycatcher in

DWA and grey breasted prinia, black drango and brown fronted woodpecker in KWA.

Guild 5 includes species which utilized lower middle canopy like oriental turtle dove, red billed blue magpie, pale blue flycatcher in DWA and green bee-eater and blue capped rock thrush in KWA (Figure 4.12, 4.13). The density, diversity, richness and evenness of different guilds in both the watersheds is shown in Appendix I and II

4.5.7 Bird Habitat Relationship

Spearman rank correlation coefficient was used to test the relationship between bird species diversity and richness with vegetation attributes in both the Watersheds. The birds species diversity and richness in both the watersheds showed significant relation with tree density, tree diversity, shrub density, shrub diversity and foliage height diversity (Table 4.7 and Table

4.8)

4.5.8 Effect of Density on Disturbance Pattern

In order to know the effect of disturbance on bird species density, sampling plots with high

CHAPTER 4 BIRD COMMUNOY STRUCTURE 77 level of disturbance (close to human habitation with high level of tree cutting, lopping and cattle dung piles) were compared with that of undisturbed plots (in core areas of both watersheds). Densities were maximum in disturbed habitats in both the watersheds (Table

4.9). There was significant difference in disturbed and undisturbed habitats in KWA (X'^ =

7.81, P < 0.05), while no significant difference was observed in disturbed and undisturbed habitats of DWA (X^ - 0.02, P > 0.05)

CHAPTER 4 BIRD CoMMUNpy STRUCTURE 78 1^

li^ •SJ. Iflitii- < Q ililtltliltifilliliiifjiiiiii^e

si U u 60

c o w tn XI C 3 B B o o

o E K) I-, OB O •a" T3 C

3 op I a E

<

00 c '•3

C s3 s o o

o -5 S •Hi, e« x: 6i3 O T3 I C Q a <6 3

UJ I0: E

2 § 8 Q a: & a: 0. Table: 4.7 Spearman rank correlation coefficients between bird species diversity and richness with habitat parameters in DWA Habitat variables Bird species diversity Bird species richness Altitude -0.121 __ Canopy cover -0.223* 0.341 Grass density 0.013 -.0.031 Herb diversity 0.216 0.012 Tree density 0.371 0.351 Tree diversity 0.631* 0.421* Shrub density 0.411* 0.383 Shrub diversity 0.981* 0.742* Slope 0.123 0.142 Foliage height diversity 0.831* 0.752* "significant at P<0.01 level

Table: 4.8 Spearman rank correlation coefficients between bird species diversity and richness with habitat parameters in KWA

Habitat variables Bird species diversity Bird species richness Altitude 0.021 __ Canopy cover -0.453* 0.232 Grass density -0.115 -0.104 Herb diversity 0.156 -0.213 Tree density 0.414 0.572 Tree diversity 0.759* 0.537* Shrub density 0.626* 0.431* Shrub diversity 0.548* 0.631* Slope -0.023 0.219 Foliage height diversity 0.928* 0.811* *significantat P<0.01 level

Table: 4.9 Overall bird density in disturbed and undisturbed areas in Dabka and KWA

Disturbed Habitat Undisturbed Habitat Area D ± SE 95 % CL D±SE 95 % CL Dabka 13.81 ±2.03 10.42-16.23 8.22 ±1.27 6.41-11.64 Khulgarh 15.45 ±2.09 13.76-18.95 7.65 ±1.03 5.26-9.73

CHAPTER 4 BIRD COMMUNITY STRUCTURE 81 4.6 Discussion

During the period of this study, 157 in Dabka and 102 bird species in Khulgarh were recorded. No other ecological study on the avifauna in this area has been conducted so far except Sultana (2002). Only bird lists by other workers have been compiled on the basis of short survey in different districts such as in 19"^ century Atkinson (1882) documented >600 bird species from Western Himalayas, which include Kumoan also. Hudson (1930) documented 124 bird species occurring on seven hills around Naini Tal between 6000 ft to

8500 ft altitude range and Briggs (1931) documented 83 bird species in Ranikhet forest.

The species richness counting method is highly efficient compared with point count and lines transect method (Sultana 2002) and secure a broad coverage of the study area. The sub listing is in conflict with standard statistics for species richness estimation (e.g. Magurran 1998) but could be practical guideline for those who otherwise provide only a total list of bird species seen. The length of sub lists need to modify according to the circumstances, e.g. 10- species lists in species poor areas (see Poulsen et al. 1997). During this study, 15-species list were compiled to survey both the areas.

In terms of bird diversity DWA was more diverse as compared to KWA. Difference in bird species diversity and richness in the two watersheds of Kumoan Himalayas was probably due to a number of factors, including floristic and structural changes in the vegetation along the elevational gradient in Dabka. Both, general observation and field survey method confirmed that, as predicted, the more structurally diverse forest at low elevation contains the greatest number of species in Dabka. Moreover, location of Dabka is between the altitudinal gradient from 600 - 2500 m, which also attracts most of the birds of the lower altitudes.

CHAPTER 4 BIRD CoMMUNmr STRUCTURE 8 2 Food is an important limiting resource (Leek 1954, Cody 1974). Holmes et al. (1979) proposed that communities should be structured on the basis of how food is partitioned and that synoptic species should differ in physical or behavioral characteristics resulting in differential food utilization. Overall density was higher in Dabka as compared to Khulgarh.

Density was also found higher in summer than winter in both the watershed areas. Same pattern was also observed in other studies (Bell 1980, Osborne and Green 1992, Dar et al.

2008a). Since, winters are very cold in both the areas it is possible that insect population goes down subsequently reducing insectivore population. Less availability of insect in winter is in confirmation with the results of Anderson et al. (1982) and Dar et al. (2008a) and super availability in summer with Rosenberg et al. (1982). The difference in density pattern in

Dabka and Khulgarh was mainly because of their locations. During winter the less local migrants and migrants species were recorded in Khulgarh than in Dabka. Dabka is situated along the ridges and this forest is contiguous with the forests of Ramnagar Forest Division and Corbett National Park at lower altitude, which provides sub tropical and tropical conditions where as Khulgarh is an isolated forest patch. In extreme weather conditions

(snowfall), the birds find no suitable place to go for routine activities, whereas in Dabka, mixed tropical and sub tropical conditions supports extra activities. For example, the local migrants White-collared black bird were recorded in Dabka in early March and then disappeared from the area and again arrived in November and December. This point towards the importance of Dabka forest as wintering sites for local migrants and migrant species.

In both the watersheds bird species density, diversity, richness and evenness decrease with

increasing elevation. Decline in species number with elevation has been reported for many types of organisms (Rosenweig 1995), although peak species richness often is found at lowest elevation. The turnover in species composition occurs over relatively short distance in species

CHAPTER 4 BIRD COMMUNnrSwucTURE 83 composition (Sultana 2002). Changes in community composition from one elevation to the next reflect many factors that affect the distributional patterns of individual species. Such factors operate over various temporal and spatial scales. Many changes in species composition with elevation reflect changes in the type of vegetation (Sultana 2002).

Insectivorous species, for example, generally are less important at higher elevations

(Terborgh 1971). Some insectivores groups that are particularly common and important components of lowland avifauna and are rare or absent at higher elevations. Mostly omnivorous birds were found at higher elevations, so they are not selective feeders (Sultana

2002). Decline of bird species richness and density with elevation has also been attributed to decline in forest area at higher elevations, decline in abundance and size distribution of invertebrates, competition and changes in environment conditions (Terborgh 1971), local migration of birds along gradient (Stiles 1988), spatial variation in resources (Blake and

Loiselle 2000), reduced primary productivity (Lawton et al. 1987). Some studies believe that low density and diversity at higher elevations is since they act as ecological islands (Prodon et al. 2002, Kattan and Franco 2004, Diaz 2006).

Agriculture spreads over large area in KWA than DWA. In Khulgarh agriculture fields are present in mosaic with surrounding woodlands. These woodlands provide breeding sites, food sites or by potentially allowing the colonization by individual and species (Woodhouse et al.

2005, Buckingham et al. 2006). They may also provide roosting sites for the birds (Dar et al.

2008a).

Dense forest in Dabka have highest density, this may be due to the diverse vegetation stratification in Dabka. Older trees in dense forest provide more food availability for foliage and trunk gleaner as well as more breeding sites for birds nesting in tree holes (Thompson et

CHAPTER 4 BIRD CoMMUNny STRUCTURB 84 al. 1999, Keller et al. 2003). Avery and Charles Van Riper (1989) attributed the high relative density of birds in oak (dense forest) forests to greater complexity of habitats. Moreover, point count method gives us advantage over line transect in dense forest, because one of the major assumption of the distance method is that all birds at zero distance be detected

(Buckland 1993). This assumption is clearly violated to a greater degree in dense habitats

(Sultana 2002), where while walking the line, transect line is not visible ahead and birds being flushed before they could be seen. This may be the reason that densities calculated were higher in dense forest relative to open habitat and moderate forest in Dabka.

Among birds there are five major groups based on food eaten, insectivorous, omnivorous, carnivorous and frugivorous, nectivorous. The height and height related characteristics separate the ground foragers from the other species. There are three distinct foraging environments ground, plants and air. Plants (shrubs and trees) surfaces provided microhabitats such as foliage and trunk. Each of these regions (environment and microhabitats) was exploited by the bird species that have specialized morphology and behaviour necessary for foraging there (Sultana 2002). Distinction of ground and above ground (air, shrubs and trees) emphasized the importance of foraging opportunities on these environments. The availability of various plant forms (shrubs, short trees and trees) in the habitat not only increase dimensions of the vertical habitat and, as a consequence, the foliage layering and complexity, but also provide supporting substrates (twigs, trunk, main branches, foliage). In the present study, closely related species used the same basic searching methods indicating the importance of phylogenic and evolutionary process in determining patterns

(Robinson and Holmes 1982). However, adaptive radiation in certain groups provide facilities for them to diverse resource utilization using different methods. In most of the cases, guild was formed by a group of species, which are similar in their morphological,

CHAPTER 4 Brno COMMUNITY STRUCTURE 8 5 adaptation. For example, all the woodpeckers were chiefly wood gleaning and mostly on the trunk/main branches. But, species with different morphologies also utilize the same general searching mode and take the similar types of prey, suggesting that morphology does not necessarily predetermine the foraging behaviour or diet, as has been inferred by insectivorous birds (Ricklefs and Travis 1980).

Resource portioning reduces the effect of competition by decreasing the amount of overlap between the competing species (Weins 1969). So the incidence of overlap amongst potential competitors may be used to assess the extent of resource partitioning on the niche dimensions measured. All the birds in these habitats overlapped with others but only to a smaller extent.

Niche overlaps are shaped by several factors (Cody 1974, MacArthur 1968). The birds are evolved with special morphological adaptations to use specific method and exploit particular substrates for their prey and hence morphology of birds may constrain the usage of foraging methods and substrates (Rolando and Robotti 1985). Among the dimensions (foraging height, foraging substrate and foraging methods), prey largely depends on the substrate and thus, substrate determines what sort of prey it can support. Birds are evolved with special morphological adaptations to exploit particular substrates for particular prey and hence specialists were more in the substrates. It is frequently reported in the literature (Weins 1969,

James 1971, Anderson and Shugart 1974) that bird species select certain parts of habitat based on specific search images (Sultana 2002).

The habitat use data showed that birds species diversity correlated with foliage height diversity, shrub density and tree diversity, similar pattern were found by MacArthur and

MacArthur (1961), Karr (1968) and Recher (1969) but contrary to Javed (1996). In both the watersheds bird species diversity and richness depended on foliage height diversity. Diaz

CHAPTER 4 BIRD CoMMUNrrv STRUCTURE 86 (2006) and Dar et al. (2008a) found species richness increasing with shrub diversity in Oak forest. Bird species correlate with tree diversity was also demonstrated by Peck (1989) for british forest birds. Increase in structural complexity and floristic composition quite often are related to enrichment of associated bird communities since more heterogeneity allows more species to create niches (Poulsen 2002, Shochat et al. 2001, Laiola 2002, Machtans and

Latour 2003).

Margalef (1958) suggested sigmoid relation between diversity and cover. Grass layer adds slightly to the avian diversity. With the addition of the first shrub cover, diversity increases more rapidly. As more cover is added, diversity decreases as it restricts the mobility of the avifauna in the very dense foliage. This might explain the decrease or negative correlation of bird diversity and richness with dense cover although relation was not significant. These results were also in confirmation with Karr and Roth (1971). Henning's and Edge (2003),

Blair (1996) and Dar et al. (2008a) put similar argument that bird species richness and diversity peaked in areas with moderate canopy cover. Blair (1996) put similar argument that bird species richness and diversity peaked in areas with moderate canopy cover.

Bird species density was found highest in disturb habitat as compared to undisturbed areas.

Studies in other part of India, Daniels et al. (1992) in Western Ghats, Javed (1996) in terai regions. Sultana (2002) in Kumoan Himalayas, Dar et al. (2008a) also showed the same results. It rejected the null hypothesis that bird density was minimum in disturbed habitats.

Some studies (Haworth and Thompson 1990, Van Der Zande et al. 1980, Tuite 1981, Fraser et al. 1985, Lauila 1989) on water fowl showed that birds avoid different types of human disturbance e.g. pollution, mines, roads, construction etc. While other workers (Foin et al.

1977, Watson 1979, Robertson and Flood 1980, Burger et al. 1982, Storey 1987, Watson

CHAPTER 4 BIRD COMMUNITY STRUCTURE 87 1988b, Hill and Roiser 1989) showed preference in disturbed habitats by Passeriformes and showed that increase in bird density in disturbed areas was due to increase in common species.

Field ornithologists have long recognized that species select habitat for nest site, foraging, perching and other activities within certain specific habitats (Lack 1933, Lack and Venables

1939). The assumption was that birds respond to a complex pattern of stimuH rather than to simple variables (Svardson 1949, James 1971). Studies have shown birds to be disturbed along gradients e.g moisture (Smith 1977), altitude (Anderson 1970a), succession (Bond

1957) and competition (Cody and Walter 1976). Such findings appeared to be related to habitat gradients studies where forest species are characterized as associated with dense under story, heavy canopy or other variables that are part of the changing structure in forest succession.

CHAPTER 4 BIRD CoMMUnny STRUCTURE 88 CHAPTER 5 STATUS AND POPULATION STRUCTURE OF MAMMALS 5.1 Introduction Single species approach to conservation, management, and monitoring are insufficient to

combat the threat to overall biological diversity of an area. Multi species based monitoring

approaches are needed to provide reliable, timely, and informative measure of change in the

status of population, communities and biological diversity (Manley et al. 2005).

The conservation of the mammalian community is one of the important goals in wildlife

management of wildlife areas as it forms larger prey-predator system (Cairns and Tefler

1980). Understanding factors that govern species distribution is a central goal of ecology and

is of fundamental importance to conservation biologists and wildlife managers (Scott et al.

2002.

The Himalayas offer great challenges to wildlife biologists in studying aspects of ecology,

conservation and management of animals. The low density of animals and harsh climatic

conditions are the major reasons for this. The varied topography of the area does not allow

systematic sampling using the conventional methods. Due to which, status, distribution and

relative abundance of many of the Himalayan mammalian species are not fully known.

Density estimates for the Himalayan species have been sparsely reported. In western

Himalayas the existing information on mammalian species are mainly through base line

surveys (Schaller 1977, Gaston et al. 1981, Fox et al. 1988, Cavallini 1990, Gaston and

Garson 1992 and Sathyakumar 1993) and few systematic studies (Green 1985, llyas 2001.

Ilyas and Khan 2003 and Ahmed et al. 2009).

CHAPTER S STATUS & POPULATION STRUCTURE OF MAMMALS 89 Ungulates form a major component of Himalayan mammalian fauna. They form the major

prey base for large mammalian predators. Ungulates often modify their activity in response

to habitat differences, seasons and modify their activity pattern in response to habitat

differences. Seasons and disturbance factors, and their behavior could be a sensitive

indicator of habitat quality, protection and management. In total 19 ungulate species

belonging to four families viz., moschidae cervidae, bovidae and equidae, inhabit the

Himalayas (Bhatnagar 1993). The Himalayas and associated mountain ranges form the home

to 12 of 13 species (38.7%) of caprinae found worldwide, the richest in any part of the world

(Shakletonl997).

Himalayas also serve as distribution range of various rare and endemic species of flora and

fauna. There is a great need of conservation of mammalian species in most of the parts of

Himalayas having a rich diversity of mammalian fauna like Kumaon Himalayas. The

Kumaon Himalayas is home to many mammalian species including tiger, leopard, black

bear, chital, Indian muntjac, sambar and goats like goral etc. Over the years however,

poaching, habitat degradation and habitat loss has led to the drastic reduction in their

population.

Age composition although often difficult to determine accurately in field is generally a

reflection of the status of species in terms of its reproductive potential (Ahmed 2007). There

are two main hypotheses regarding the herding behavior of the ungulates. The first suggests

that, when in herds the animals can prevent or avoid the predation better than when alone

(Hamilton 1971). This could be done by a variety of methods including improved predator

detection, active group defense and predator confusion. The other hypothesis links the

CHAPTER S STATUS & POPULATION STRUCTURE OF MAMMALS 90 animal social organization with the distribution and availability of its food supply (Altman

1952, Lowe 1966, Jarman 1974). The small species, it is suggested, have high nutritional requirements and has to feed in a highly selective way, they therefore cannot live in large

groups. Larger species can afford to be less selective and can therefore, live in larger groups

(Mishra 1982). In species, which exhibh flexible social system, h is suggested that they will

form large groups when there is abundance of high quality forage but will be forced into

smaller groups when food supply is less abundant and dispersed in distribution.

Most members of the families cervidae and bovidae are highly gregarious and have been

studied in detail (Clutton-Brock et al. 1982, Geist 1971, Nievergeh 1981, Rice 1987,

Rodgers 1977 Schaller 1967, 1977, Soma 1987). Estes (1974) compiled data on social

organization and habitats of African bovids and suggested that species living in closed

habitats are usually primitive, solitary, small and cryptically coloured browsers which hide

from danger. Jarman (1974) indicated that grazers which are largely generalistic feeders,

may present in large groups in areas where grass is abundantly available, whereas, browsers

which are much more selective feeders, live in small groups or solitary. However,

information about the most primitive taxa of caprinae (rupicaprids) is mostly ancecdotal

(Cavallini 1992, Gaston et al. 1981, 1983, Gaston and Garson 1992, Mead 1989, Prater

1980, Roberts 1977 and Soma 1987).

The section of this chapter documents the variation in group size, composition of ungulates and status of mammalian fauna. The main objectives of the study were:

-^ To study variation in size and composition of groups of ungulates in two Watersheds

of Kumoan Himalayas

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 91 ^ To determine the sex ratio of ungulates in Dabka and Khulgarh watershed area

^ To know the encounter rate (ER) of the key mammalian species of two watershed

areas of Kumoan Himalayas.

5.2 Methodology

Based on recent literature and initial fieldwork, the following techniques were used.

5.2.1 Scanning Technique for Goral

The method involves careful scanning from vantage points using spotting scope or binoculars for a specified period of time. Gorals were scanned in DWA during winter and summer from three vantage points namely Khunjakharak, Sigri and Vinayak (Table 5.1). The scanning was done between 06:00 hr to 09:00 hr and 15:00 hr to 18:00 hr. Scan duration varied from one to three hours depending upon weather conditions. The number of animals seen, their age, sex and activity patterns were recorded for every sighting. The various habitat parameters were also recorded around 10 m radius of the animal sighted whenever possible. In order to increase the scanning efficiency, two people scanned independently from two comers of a vantage point. Recording the time of animal sightings helped in eliminating double counts.

This technique has already been used by Vinod (1999) in Great Himalayan National Park,

Sathyakumar (1994) in Kidamath Wildlife Sanctuary and Johnsingh (1992a) in the Shiwaliks.

Table: 5.1 Characteristics of scanning areas in Dabka Watershed Area

Vantage Points Altitude Range (m) Aspect Extent of Human Use No Scans Khungakharak 2200-2500 E Low 17 Sigri 2000-2200 E Middle 19 Vinayak 1700-2000 W High 22 /

CHAPTER S STATUS & POPULATION STRUCTURE OF MAMMALS 92 5.2.2 Trail Count For AH Other Mammalian Species

Trail count has evolved as a sound method of finding distribution and population index

(MaCaffery 1976). Trail count utilizes the direct sightings of the animals. Data on population structure and encounter rate of mammalian species were collected by regular monitoring of trails passing through various habitat types supplemented by instantaneous scan sampling

(Altman 1974). Four trails in DWA and three in KWA were identified, which covers almost all habitats of the area. These trails were walked 82 times in total covering a distance of 410 kilometers (250 km in DWA and 160 km in KWA), during the entire study period. These trails were walked in the morning, midday and in the evening hours, though majority of trails were walked in the morning. Distance of trail and total time taken in completing the trail were also recorded. Data on species, their number, age and sex were recorded. Sex and age of different individuals was identified based on the morphological features and their size.

Number of animals per group and time of sighting were noted for every sighting. Individuals were classified into five groups that is, adult male, adult female, sub-adult male and sub-adult female and fawn.

5.3 Analysis

Data on group size and age sex composition were summarized separately for both the watershed areas to know the population structure in each watershed. The encounter rate of all the animals in the all trails and vantage points were calculated using the following formula.

Animal Encounter rate = n/L. where n and L are the number of animals sighted and the length of trail walked or time spent on each vantage point, respectively.

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 93 Encounter rate was calculated (animal groups/km) both individually as well as seasonally.

Mann-Whitney U test and Kruskal-Wallis test were performed using SPSS/PC statistical computer package (Norusis 1990) to detect any difference in encounter rates in different areas and between seasons.

5.4 Results

5.4.1 Population Structure

During the study period 12 species of mammals were recorded in DWA and 7 species were recorded in KWA. Chital, sambar, serow, goral and yellow throated martin were absent in

KWA but present in DWA (Appendix V and VI).

5.4.1.1 Group Size

A total of 3712 individuals with 506 groups were counted in DWA. Eighty two of such groups were that of Chital with 521 individuals, 50 groups of sambar with 68 individuals, 3 groups of serow with 3 individuals, 54 groups of muntjac with 61 individuals, 144 groups of rhesus macaque with 2179 individuals, 84 groups of hanuman langur with 757 individuals, 10 groups of wild boar with 15 individuals and 59 groups of goral with 73 individuals. Rests of the 30 groups were that of Red fox, Jackal, leopard and yellow throated martin with 10, 9, 4 and 12 individuals, respectively.

In KWA a total 7325 individuals were counted in 393 groups. Largest number of groups was that of rhesus macaque (192) followed by hanuman langur (149), muntjac (31), jackal (8), wild boar (7) red fox (4) and leopard (2). In terms of total number of individuals rhesus

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 94 macaque was seen with higher no of individuals (4764) followed by hanuman langur (2499), muntjac (41), jackal (8), wild boar (7), red fox (4) and leopard (2).

In DWA mean group size (15.09 ± 0.67) was recorded highest for rhesus macaque followed by langur (9.33 ± 0.70), chital (6.35 ± 0.50), sambar (1.35 ± 0.10), muntjac (1.12 ± 0.05), and serow (1.00 ± 0.00) (Table 5.2). Analysis of variance showed group size varied significantly among different species (F = 85.10, df = 6, P = 0.000).

Mean group size of chital was highest in summer (7.57 ± 0.61) as compared to winter (6.35

± 0.50) and difference was found to be significant (F = 11.26, df = 1, P = 0.001). Mean group size of hanuman langur and rhesus macaque was also recorded highest in summer

and difference was found to be significant F = 4.19, df = 1, P = 0.04, F= 10.6, df = 1, P =

0.001, respectively. Although group size of muntjac and sambar was also highest in

summer but difference was not found to be significant (Table 5.3, 5.4).

In KWA the highest mean group size was recorded for rhesus macaque (24.70 ± 0.96)

followed by langur (16.77 ± 0.89) and muntjac (1.44 ± 0.05) and difference was found to be

significant (F = 83.50, df = 2, P = 0.000) (Table 5.5). Mean group size of langur and rhesus

macaque was highest in summer and difference was found to be significant (F = 12.403, df

= 1, P = 0.001, F = 89.81, df = 1, P = 0.000) respectively. Group size of muntjac was also

recorded highest in summer but difference was not found to be significant (Table 5.6, 5.7).

Sixty three percent of groups of goral were constituted single individuals and 36% consisted

of 2 to 5 individuals. There was no group found with membership exceeding more than 5

(Figure 5.1).

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 95 Six percent of groups of chital consisted of single individual and 47% groups consisted of 2

to 5 individuals. During winter single groups increased to 13% but came down to only 1%

during summer. In contrast, groups containing more than 10 individuals increased from 3% to

23% during summer (Figure 5.2).

Forty eight percent of muntjac in DWA were found in single member groups and 6% were

found in 2 to 5 member groups and in KWA 87% of groups were found in single and 12%

were found in 2 to 5 groups. There was not much variation in different season in the group

size (Figure 5.3, 5.8).

In sambar, 76% belonged to single member group and 23% to 2 to 5 member groups. There

was not much variation in the different seasons (Figure 5.4). Serow was seen as solitary in all

the observation (Figure 5.5).

Langur in KWA formed more gregarious groups (63% in more than 10 member groups),

whereas in DWA it showed almost equitable presence in all the four categories (Figure 5.6,

5.9). Rhesus also showed a gregarious pattern in both the watersheds with more than 10

individuals dominated in the grouping pattern (Figure 5.7, 5.10).

CHAPTER S STATUS & POPULATION STRUCTURE OF MAMMALS 96 Table: 5.2 Overall mean group size of different mammalian species in DWA

Species Number Minimum Maximum Mean ± SE Chital 82 22 6.35 ± 0.50 Sambar 50 4 1.35 ±0.10 Serow 3 2 1.00 ±0.00 Muntjac 54 3 1.12 ±0.05 Goral 59 2 1.25 ±0.63 Rhesus macaque 144 2 46 15.09 ±0.67 Langur 84 1 23 9.33 ± 0.70

Table: 5.3 Mean group size of different mammalian species in winter in DWA

Species Number Minimum Maximum Mean ± SE Chital 30 22 4.23 ± 0.75 Sambar 21 4 1.19±0.14 Serow 1 1 1.00±0.00 Muntjac 18 2 1.11 ±0.07 Goral 26 2 1.36±0.10 Rhesus macaque 50 2 30 12.18±0.83 Langur 33 1 20 7.57 ± 1.02

Table: 5.4 Mean group size of different mammalian species in summer in DWA

Species Number Minimum Maximum Mean ± SE Chital 52 18 7.57 ±0.61 Sambar 29 3 1.48 ±0.13 Serow 2 2 1.00 ±0.00 Muntjac 36 3 1.13 ±0.07 Goral 33 3 1.12 ±0.063 Rhesus macaque 94 2 46 16.64 ±0.89 Langur 51 1 23 10.47 ±0.92

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 97 Table: 5.5 Overall mean group size of different mammalian species in KWA

Species Number Minimum Maximum Mean±SE Muntjac 31 1 3 1.14 ±0.05 Rhesus macaque 192 1 55 24.70 ± 0.96 Langur 149 1 41 16.77 ±0.89

Table: 5.6 Mean group size of different mammalian species in winter in KWA

Species Number Minimum Maximum Mean±SE Muntjac To i 2 1.11 ±0.07 Rhesus macaque 87 3 35 16.43 ±0.76 Langur 27 1 21 10.33 ± 1.12

Table: 5.7 Mean group size of different mammalian species in summer in KWA

Species Number Minimum Maximum Mean ± SE Muntjac 21 i 3 1.16 ±0.08 Rhesus macaque 105 1 55 31.56 ±1.30 Langur 149 1 41 18.19 ±1.08

CHAPTER S STATUS & POPULATION STRUCTURE OF MAMMALS 98 5.4.2 Sex Ratio

5.4.2.1 Langur

Out of total number of 784 individuals of langur in DWA, adult males constituted 143

(18.24%). adult females numbered 452, constituting 57.65% of the population and infant attached to their mothers constituted 70 (8.93%) of the population (Table 5.9). Number of adult males to 100 adult females was 31.63 and sub aduh male: Sub aduh female ratio was

70:100 and about 15-16 fawns per 100 females.

In KWA 2499 individuals of langur were observed. Out of which 589 (23.57%) were adult males, 1104 (44.18%) were adult females, 163 (6.52%) were sub adult males, 260 (10.40%) were sub adult females, 311 (12.44%) were infants and 76 (3.04%) remained unidentified

(Table 5.10). Number of adult male to 100 adult female was 53.35 and sub adult male: sub adult females ratio was 62.69 males: 100 females. There were 28.17 fawns per 100 females.

5.4.2.2 Rhesus Macaque

A total of 2179 individuals of Rhesus were observed in DWA, out of which 572 (26.25%) were adult male, 1001 (45.94%) were adult female, 257 (11.79%) were fawns and 43 (1.97%) individuals could not be identified (Table 5.9). Adult male to adult female ratio was 57.14 males per 100 females and sub adult male to sub adult female ratio was 61.41:100 females.

Female to fawn ratio was 100:25.67.

In KWA, 4744 individuals of rhesus macaque were observed. Out of this 1136 (23.95%) were aduh male, 1761 (37.12%) were adult females, 285 (6.01%) were sub aduh male, 562

(11.85%) were sub aduh female, 603 (12.71%) were fawn and 104 (2.19%) individuals could

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 99 not be classified (Table 5.10). Adult male to adult female ratio was 64.50:100 and sub adult male: sub adult female ratio was 50.71:100. There were 34.24 fawns per 100 females.

5.4.2.3 Muntjac

In DWA, muntjac, female constituted 62.90% of the population while 27.42% was constituted by males, 8.06% were fawn and rest could not be identified (Table 5.9). Male: female ratio was

43.58:100 and there were 12.82 fawns per 100 females.

In KWA males constituted 23.64%, females 67.27%, Fawn 9.09% and 3.64% remained unidentified (Table 5.10). Male: female ratio was 35.13:100 and 13.51 fawns per 100 females.

5.4.2.4 Sambar

A total of 68 individuals of sambar were observed in DWA. Adult males constituted 12

(17.65%) of population. Adult females were 30 (44.12%) and fawns constituted only 4

(5.88%) of the population and only 2 (2.94%) remained unsexed (Table 5.9). Number of adult males per 100 adult females was 40 and Sub adult male: Sub adult female ratio was 90:100.

There were 13 fawns per 100 females.

5.4.2.5 Serow

Serow sightings were very few and only 3 individuals were observed. The results showed bias towards males. Adult males constituted 66.66% of the population whereas females constituted 33.33%. No sub adult and fawn was observed during the study period (Table 5.9).

The sex ratio favored males. There were 100 females per 200 males. Although sex ratio and population structure could not be drown on the basis of 3 sighting, but an attempt was made to structure the serow population in the present study.

CHAPTER 5 STATUS & POPULATION STPUCTUK OF MAMMALS 100 5.4.2.6 Goral

In DWA, goral population comprised of 31.51% females and 47.95% males. Fawn constituted 8.22% of the population and 13.70% of individuals remained unsexed (Table 5.9).

The sex ratio of goral too favored males. There were 152 males to 100 females. Number of

fawns per 100 females was 26.88.

5.4.2.7 Chital

In DWA, chital population comprised of 21.11% adult males, 40.69%o adult females and

fawns constituted 4.80% of the population (Table 5.9). Number of males to 100 females was

51.88 and number of fawns per 100 females was 26.88.

5.4.2.8 Wild Boar

In DWA, male, wild boar constituted 20% of the population and 50% was constituted b\ females while 30% remained unsexed (Table 5.9).

In KWA males constituted 14.29%, females 28.57% and 57.14% remained unidentified (Table

5.10). The sample size of wild boar, jackal, red fox, yellow throated martin and leopard was too small to calculate the sex ratio.

5.4.3 Encounter Rate

In DWA, encounter rate of chital was highest among all the mammalian species (6.51 animals

/km) followed by rhesus (4.35 animals/km) and langur (1.56 animals/km). The encounter rate of all the mammalian species was recorded highest in summer as compared to winter and difference was not found to be significant (Table 5.11).

CHAPTER S STATUS & POPULATION STRUCTURE OF MAMMALS 101 In KWA encounter rate of rhesus macaque was highest (9.52 individuals/km) among all other mammalian species followed by langur (4.99 animals/km) and wild boar (0.14 animals/km)

In KWA, encounter rate of all the mammalian species was also highest in summer as compared to winter and difference was also not found to be significant (Table 5.12).

5.4.4 Scanning

The ER of goral using scan technique was higher (1.94 ± 0.30) in Kunjakharak as compared to other vantage points (Table 5.8) Across different season ER was higher in winter as compared to summer. The ER across different seasons and vantage points was not found to be statistically significant.

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 102 Table: 5.8 Encounter rate (animals/hour ± SE) of goral in different vantage points in DWA

Vantage Points Winter Summer Overall Kunjakahrak 2.25 ± 0.71 1.64 ±0.51 1.94 ±0.30 Sigri 1.21 ±0.73 0.89 ±0.31 1.05 ±0.56 Vinayak 0.73 ± 0.22 0.96 ± 0.45 0.38 ± 0.33 Overall 1.39 ±0.44 1.16±0.34 1.12 ±0.23

Table: 5.9 Percentage Sex ratio of mammals in Dabka Watershed Area

Species A. Male A. Female S. A .Male S. A. Female Fawn Unsexed Chital 21.11 40.69 13.82 19.58 4.80 0.00 Muntjac 27.42 62.90 0.00 0.00 8.06 3.23 Sambar 17.65 44.12 13.24 14.71 5.88 2.94 Serow 66.66 33.33 0.00 0.00 0.00 0.00 Goral 47.95 31.51 0.00 0.00 8.22 13.70 Wild boar 20.00 0.00 50.00 0.00 0.00 30.00 Langur 18.24 57.65 6.25 8.93 8.93 0.00 Rhesus macaque 26.25 45.94 5.19 8.44 11.79 1.97

Table: 5.10 Percentage sex ratio of mammals in Khulgarh Watershed Area

Species A. Male A. Female S. A. Male S. A. Female Fawn Unsexed Muntjac 23.64 67.27 0.00 0.00 9.09 3.64 Wild boar 14.29 28.57 0.00 0.00 0.00 57.14 Langur 23.57 44.18 6.52 10.40 12.44 3.04 Rhesus macaque 23.95 37.12 6.01 11.85 12.71 2.19

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 103 o

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70 Si Winter s Summer EI Total 60

50

a 40 c 9J S 30 a.

20

10

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Figure: 5.2 Group size of chital in different group sizes in DWA

100 90 SO a Winter ¥Summor EJTotal 70 So 60 iz £ 50 £ 40 30 • 20 10 ; 0 • 2-5 6-10 >10

Figure: 5.3 Group size of muntjac in different group sizes in DWA

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 105 __ S5Winter s Summer 0Total

2-5 6-10 >10

Figure: 5.4 Group size of sambar in different group sizes in DWA

120 •

100 S Winter R Summer 0 Total 80 •

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Figure: 5.5 Group size of serow in different group sizes in DWA

45 s Winter s Summer ElTotal 40

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30

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Figure: 5.6 Group size of langur in different group sizes in DWA

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 106 80 :

70 t s Winter a Summer 0Total 60 r a 50 j

£ 40 • I 30 J;

20 ;

10 ;

0 - 2-5 6-10 >10

Figure: 5.7 Group size of rhesus macaque in different group sizes in DWA

is Winter a Summer ETotal

2-5 6-10 >10

Figure: 5.8 Group size of muntjac in different group sizes in KWA

70

60 •& Winter ^Summer 13Total 50 40 30

20 • - 10 i5^Sr! n '"'••• t 2-5 6-10 >10

Figure: 5.9 Group size of langur in different group sizes in KWA

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 107 100 T 90 I 80 t 70 I sWiP'er a Slimmer QTotal 60 I 8 50 I I 40 S- 30 [ 20 t 10 t 0 i 2-5 6-10 ?10

Figure: 5.10 Group size of rhesus macaque in different group sizes in KWA

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 108 5.5 Discussion

5.5.1 Encounter Rate

The ER of goral in DWA was calculated both as animal seen/km and animal seen/hour. The

ER of goral was highest in winter as compared to summer. This could be attributed to the fact that goral do form bigger groups during winter due to low availability of snow free area to feed (Vinod 1999). Another reason for low ER may be due to the higher ambient temperature in summer, which would have made the animals to restrict to cooler valleys away from trails and vantage points. The higher ER in Kunjakharak, which is less disturbed area suggests that goral do respond adversely to human disturbance (Vinod 1999). The overall ER of 0.91/km in the study area was very close to the value of 1.10/km of Great Himalayan National Park. The overall ER in temperate pine-oak forest for goral in Kedamath Wildlife Sanctuary was

3.11/km walk (Sathyakumar 1994) which is much higher than the present estimate. However the ER in temperate scattered tree in Kedamath Wildlife Sanctuary and in Binsar Wildlife

Sanctuary was 0.50 and 0.08/kmwalk (Ilyas 2001), respectively, which is slightly lower than the present estimate. The encounter rate of muntjac in Dabka was 0.76 and in KWA it was

0.11, which is same to the value 0.11 in Binsar Wildlife Sanctuary (Ilyas 2001). Muntjac emerges as solitary animals as groups of one individual contributed more than 85% in population. These findings are in conformity with Barrette (1977) and Ilyas (2001) who recorded 64.5% and 80% respectively, of muntjac groups to be of single individual.

5.5.2 Group Size

The size of group is often considered as flindamental attribute of social organization of such species (Jarman 1974). Usually the observed group size is explained as arising from a balance between various advantage of group living and costs (Pulliam and Caraco 1984). In attempts

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 109 to understand why animals form group, biologists have focused on anti-predator benefits of increased group size, including shared vigilance (Lazarus 1979), dilution of risk (Foster and

Treheme 1981), predator swapping (Clark and Robertson 1979), confusion of predators

(Milinsk 1977) and an increased ability to mob predators (Curio 1978).

There are two main hypotheses regarding the herding behavior of the ungulates. The first suggests that when in herds the animals can prevent or avoid the predation better than when alone (Hamilton 1971). This could be done by a variety of methods including improved predator detection, active group defense and predator confusion. The other hypothesis links the animal social organization with the distribution and availability of its food supply

(Altman 1952, Lowe 1966, Jarman 1974). The small species, it is suggested, have high nutritional requirements and has to feed in a highly selective way, they therefore cannot live in large groups. Larger species can afford to be less selective and can therefore, live in larger groups (Mishra 1982). In species, which exhibit flexible social system, it is suggested that they will form large groups when there is abundance of high quality forage but will be forced into smaller groups when food supply is less abundant and dispersed in distribution.

Deer are also generally assumed to have reached firm sociality. This idea apparently originated from the descriptions given by Darling (1937) for Red deer in Scotland. However, recent studies revealed that grouping is largely dependent upon environment and changes in physiological functions.

The mean group sizes of chital (6.35) and sambar (1.35) are almost similar to the values reported by Karanth and Sunquist (1992) from Nagerhole Tiger Reserve, Mishra (1982) from

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 110 Chitwan National park and Khan et al. (1995) from Gir National Park. The smaller group size of sambar is explained on the habitat (closed forest) it occupies (structuralist explanation.

Barrette 1991) its solitary nature and anti-predator strategies (Johnsingh 1983).

Group size of muntjac in Dabka and KWA was 1.12 and 1.14 respectively. These values were similar to Ilyas (2001) in Kumoan Himalayas and Barrett (1977) but higher than Mishra and Johnsingh (1996) in Majhatal Wildlife Sanctuary. Serow and goral group size was 1.06 and 1.25, respectively. This was smaller than Green (1987) reported from Kedemath

Sanctuaty. Small group size other than anti-predator strategies can be explained on the feeding habit of the species, small body size, which results in higher basal metabolic rates suggests as the main factor which govern selective feeding on high quality food items available in the habitat (Jarman 1974). Small group size of muntjac is based on the fact that it is a solitary, forest dwelling ruminant and inhabits dense shrub cover in the broad leaved forest (Teng et al. 2004). Being a nibbler (Barrett 1977), it feeds on tender leaves, twigs, seed pods and shrub fruits. These items have higher protein and accessible plant cell content and tend to be small, distinct and spatially scattered foliage (Jarman 1974). Goral despite being a grazer, exploits comparatively more high quality grasses than low quality grasses (Ilyas and

Khan 2003), which too are scare and scattered will governing its small group size. But its ability to exploit cliffs or landscape not often liked by predators explains its higher group size than muntjac in the study area.

Group size was recorded highest in summer as compared to winter for all the species except goral. The seasonal variation in group size has been documented by others (Barrette 1991),

Dinerstein 1980). In an explanation for seasonal variation in group size, many factors have

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 111 been enumerated. Social organization of species (Rodgers 1977), open structure, food availability, rutting activity (Hamilton 1971, Khan and Vohra 1992). Sharatchandra and

Gadgil (1975) attributed the increase in group size during rainy season to high food availability. Dinerstein (1980) on the other hand, considered predation as the prime reason for bigger group size due to increase in plant cover and density. Khan et al. (1995) believed that increase in plant cover and density will cause the herds to fragment but also bigger group size increase the probability of predation as dense cover may help predators to stalk. For species like chital and barasingha as main factors responsible for seasonal changes (Khan et al. 1995.

Ahmed 2007).

5.5.3 Age and Sex Composition

Age composition although often difficult to determine accurately in field is generally a reflection of the status of species in terms of its reproductive potential. A high percentage of young generally indicate a growing and thriving population. In contrast a small population of young usually indicates a low reproductive or senile group.

Sex ratio of all the mammalian species in the study areas favored females, except goral, serow and wild boar. Since for serow and wildboar the small sample size could be the reason that reflects the male biasness. In case of goral large percentage of animals could not be classified due to monomorphism. Therefore, any likely explanation for skewed sex ratio would not be complete. Female biasness has already reported in many studies (Khan et al.

1995) for chital, Ahmed (2007) for swamp deer, Rahmani (1990) for Chinkara. The disparity in adult sex ratio in favor of females has been attributed to several factors such as misclassification of individuals (Sharatchander and Gadgil 1975, Mishra 1982, Ahmed et al.

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 112 2008) higher mortality of male fawns (Schaller 1967, Johnsingh 1983), selective predation on males (Schaller 1967 for sambar, Karanth and Sunquist 1992 for chital, sambar and wild boar). Karanth and Sunquist (1992) suggested that female bias may be due to male's solitary habits, proneness to injuries from intra-specific aggression, lack of alertness during rut and dispersal behavior may render them vulnerable to predation.

CHAPTER 5 STATUS & POPULATION STRUCTURE OF MAMMALS 113 CHAPTER 6 HABITAT USE OF UNGULATES 6.1 Introduction The basic requirement for the conservation and management of ungulates is the sound knowledge of their specific habitat requirements. In the western Himalayas, only a few recent studies have been focused on the association between ungulates and their habitat components

(Fox et al. 1988, Ben-Shahar 1990, Mishra 1993, Sathyakumar 1994, Bhatnagar 1997, Vinod

1999, Ilyas 2001). The selection of an area by a species depends on the availability of specific resources on that particular area, which can fulfill the requirement of the species. The identification of these specific resources are of utmost importance for the management of the area and the species.

The habitat use of species is generally detennined by factors such as food and water availability, shelter, escape, cover and extent of human use (Duncan 1983, Hanley 1984,

Putman 1986, Gordon 1989 Beirer and Mc Collough 1990 and Thigood 1995). In the

Himalayas altitude, aspect and slope determine the distribution of plant species and hence contribute a major role in determining the habitat use. Most seasonal variations in habitat use by ungulates have been associated with seasonal changes in the availability of food and protective cover. The abundance of predators and the anti-predator strategies are also important in determining prefered habitats by mountain ungulates (Mishra and Johnsingh

1997, Sathyakumar 1994).

India is remarkable for the variety of its large mammals, a richness in species exceeded by few countries in the world (Schaller 1967). The pioneering work of Schaller (1967) in the

Kanha National Park was the first ecological description of some of the common ungulate

CHAPTER 6 HABITAT USE OF UNGULATES 114 species found in India. Since then there have been several studies (e.g Eisenberg and

Lockhart 1972, Berwick 1974, Sharatchandra and Gadgil 1975, Dinerstein 1980, Mishra

1982, Johnsingh 1983, Green 1987, Barrette 1991, Khan 1993, Sathyakumar 1994, Vinod

1999, Ilyas 2001, Dar et al. 2008b, Ahmed 2007). However, information on ecological aspects is still far from satisfaction especially for mountain ungulates.

In Kumoan Himalayas virtually no information is avaialable on the habitat use patterens of ungulates. Only short-term studies were carried out on habitat use of ungulates except for goral and musk deer where long term studies were carried out (Ilyas 2001). So, through the present study, an attempt has been made to investigate the major factors that are affecting the habitat use by these ungulates in Kumoan with particular reference to the two watersheds.

The main objectives of this study are:

^ To study the habitat use by major ungulate species

*^ To study niche overlap among sympatric ungulate species

"^ To study the availability-utilization patterns of various factors by these ungulates

CHAPTER 6 HABITAT USE OF UNGULATES H5 6.2 The Himalayan Ungulates

Ungulates form a major component of the Himalayan mammalian fauna. They form major prey base for the large mammalian predators. Ungulates often modify their activity pattern in response to habitat differences, seasons and disturbance factors, and their behavior could be a sensitive indicator of habitat quality, protection and management. In total, 19 ungulate species belonging to four families, (moschidae, cervidae, bovidae and suidae) inhabit the

Himalayas (Bhatnagar 1993, Sathyakumar 1994). The sub-family Caprinae is represented by nine species in the Himalayas. Schaller (1977) and Bhatnagar (1993) have reviewed the origin and distribution of the Himalayan ungulates.

In the Western Himalayas, eight species of ungulates are present of which five species occur in the present study sites. They are serow (Capricornis sumatraemis), goral (Nemorhaedus goral), sambar (Cervus unicolor), muntjac (Muntiacus muntjac) and wild pig {Sus scrofd).

Although chital (Axis axis) was also present in DWA in lower altitude up to 750 m, above msl but it was totally absent from KWA.

6.3 Introduction to Himalayan Ungulates

6.3.1 Serow {Capricornis sutnatraensis)

The Himalayan serow is listed on Appendix I of CITES (Duckworth and MacKinnon (2008) and Near Threatened in the Red Data Book (lUCN 2009). In India, it is listed in Schedule I

(revised March 1987) of the Wildlife (Protection) Act (1972) and thus totally protected.

Within India, this species of serow occurs in a number of protected areas of Himachal

Pradesh, Uttarakhand, and Sikkim as well as few protected areas in Manipur, Meghalaya and

Mizoram (Duckworth and MacKinnon 2008). In total, it is present in over 50 Indian protected areas, ranging in size from 4 km^ to 1,800 km^ and totalling about 17,000 km"^

CHAPTER 6 HABITAT USE OF UNGULATES 116 (Duckworth and MacKinnon 2008). However, due to habitat alteration and hunting will continue to negatively affect serow populations throughout northern India, and because serow is apparently dependent on patches of dense vegetation associated with rugged terrain, the alteration or elimination of such vegetation will be highly detrimental to the species.

Management to control habitat alteration, prevention of overhunting outside the protected areas (PAs) and effective protection in national parks (NPs) and wildlife sanctuaries (WSs). will be required to maintain viable populations in the future. Queries on even basic information such as presence or absence of this species from many areas is yet to be answered. Information on serow in India is scanty (Dang 1962, Schaller 1977, Green 1985,

Tak and Kumar 1987, Katti et al. 1990, Johnsingh 1992b, Sathyakumar 1993, Mishra et al.

1994).

6.3.2 Goral {Nemorhedus spp.)

The Himalayan goral is represented by two sub-species viz.. Grey goral {Nemorhedus goral bedford) of the Western Himalayas and Brown goral {Nemorhedus goral goral) of the

Eastern Himalayas. The Red goral {Nemorhedus bailey) occurs in the trijunction of India,

Burma and China. The Himalayan goral {Nemorhedus goral) is listed in as 'Near threatened' in the Red Data Book of lUCN and Appendix I of CITES (Duckworth and MacKinnon

2008). In India, it is listed in Schedule I of the Indian Wildlife (Protection) Act (1972).

Goral is generally found in sparsely wooded slopes with open grassy patches. It occupies a wide range of habitats between Himalayan temperate forest, the alpine pastures, the tropical moist deciduous and subtropical pine forests in the outer Himalayas, the Shiwaliks, montane wet temperate and evergreen forests in its north eastern distributional range (Dang 1968,

Schaller 1977, Prater 1980, Gaston et al. 1981, 1983, Green 1985, Tak and Kumar 1987,

Johnsingh 1992a, Ilyas 2001). In India, the goral is found in the states of Jammu and

CHAPTER 6 HABITAT UsB OF UNGULATES 117 Kashmir, Himachal Pradesh, Haryana, Uttarakhand, Bihar, Sikkim, Arunachal Pradesh and

Mizoram. The goral is reported to occur in 46 Pas in the Himalayan and associated hills of

the north-east India.

Information on goral is mostly anecdotal (Dang 1968, Schaller 1977, Roberts 1977, Tak and

Kumar 1987, Mead 1989, Soma 1989). A few quantitive studies on goral have been

conducted on the ecology and behavior of goral. Green (1985) studied the ecological

separation of goral with other mountain ungulates in Kedarnath WS. Lovari and ApoUino

(1994) conducted a study on habitat use, group size and activity pattern of goral in Majhatal

WS, Himachal Pradesh. Ilyas (2001) conducted a study on feeding ecology and habitat use

of goral in Binsar WS. Mishra (1993) and Pendharkar (1993) studied habitat use by goral in

Majhatal WS and Simbalbara WS, Himachal Pradesh, Uttarakhand, Arunchal Pradesh and

Mizoram (Gaston et al. 1981, Gaston and Garson 1992, in Great Himalayan MP, Cavallini

(1992) in Himachal Pradesh, Mishra et al. 1994 in Mizoram, Sathyakumar 1994 in

Kedarnath WS and Dar et al. 2008b in Uttarakhand).

6.3.3 Sam bar (Rusa unicolor)

Sambar is the largest forest deer in South-East Asia (Sathyakumar 1994) listed as Vulnerable

in lUCN Red Data Book (Duckworth and MacKinnon 2008) and in Schedule III of the

Indian Wildlife (Protection) Act (1972). Sambar is well adapted to varied habitats ranging

from the sub-alpine scrub and alpine pastures of the Greater Himalayas (Green 1985,

Sathyakumar 1994) to the dry deciduous and thorn forests ofv the Peninsula (Prater 1980).

Sambar is reported to occur in 26 PAs in the Himalayan region (Sathyakumar 1994).

Rodgers (1988) has stated that information on the ecology of sambar in India is wanting.

Most of the existing information on sambar in India is either anecdotal or natural history

CHAPTER 6 HABn7»T USE OF t/NSUiATES 118 notes (Prater 1980, Schaller 1967). Aspects of population dynamics, habitat use, feeding and

ranging patterns of sambar in India have been discussed by Schaller (1967), Johnsingh

(1983), Karanth (1988), Haque (1990), Bhatnagar (1991), Johnsingh and Sankar (1991).

Khan (1993), and Sankar (1994).

6.3.4 Muntjac {Muntiacus ntuntjac)

The muntjac is classified as one of the seven species under sub-family Muntiacinae and

family Cervidae (Grubb, 1993). It is distributed in India, Sri Lanka, Nepal, Bhutan,

Bangladesh, North-east Pakistan, South China (Yunnan, Guangxi, Hainan Islands), South

through Indo China to Peninsular Malaysia, Sumatra, Borneo, Java, Bali, Lombok and many

other smaller Indonesian islands. The muntjac is listed as least concern according to lUCN

Red Data Book (lUCN 2009) and listed in Schedule III of the Indian Wildlife (Protection)

Act (1972) and Appendix II of CITES. It is widely distributed from the Himalayas (upto

2,800 m) to the Peninsular India. It is reported to occur in 34 PAs in the Himalayan region of

India. Information on muntjac in India is only anecdotal (Schaller 1967, Prater 1980).

Studies on some aspects of the ecology of muntjac have been done in Nepal (Seidensticker

1976, Dinerstein 1979) and Sri Lanka (Barrette 1977).

6.3.5 Chital {Axis axis)

The Chital is protected under Schedule III of the Indian Wildlife (Protection) Act (1972) and

listed as Least Concern (lUCN 2008), because it occurs over a very wide range within which

there are many large populations (Duckworth et al. 2008). Chital or spotted deer (Axis axis)

is the third largest deer inhabiting the plains and undulating terrain of India. A well-built

stag stands 90 cm at the shoulder and weighs about 85 kg (Prater 1980). Chital is an endemic

species of south Asia, occurring in India, Sri Lanka, Nepal and Bangladesh (Schaller 1967).

CHAPTER 6 HABITAT USE OF UNGULATES 119 Chital have declined drastically throughout their range, and are now only locally abundant within 123 PAs of India and some forest tracts (Source: National Wildlife Database). The

strongholds PAs of chital where they have been adequately studied are: Corbett (De and

Spillit 1966), Kanha (Schaller 1967), Bandipur (Johnsingh 1983), Nagarahole (Karanth and

Sunquist 1992), Sariska (Sankar 1994), Gir (Khan et al. 1995), Guindy (Raman 1997).

Pench (Biswas and Sankar 2002), Ranthambore (Bagchi et al. 2003) in India, Chitwan

(Mishra 1982) and Kamali-Bardia (Dinerstein 1980), in Nepal, and Wilpattu (Eisenberg and

Lockhart 1972) in Sri Lanka. Introduced chital populations occur in Russia, Yugoslavia.

USA, Argentina, Brazil, Uruguay, Australia, Hawaii and several private ranches in the

Western Cape, South Africa (Lever 1985). Chital form one of the important prey of top

carnivores as is evident from studies in Kanha (Schaller 1967), Bandipur (Johnsingh 1983),

Rajaji (Johnsingh et al. 1993), Sariska ( Sankar 1994), Pench (Biswas and Sankar 2002) and

Ranthambore (Bagchi et al. 2003). Chital is a species that is most amenable to wildlife

management practices, and just a little effort and care is required to increase the numbers of

this prolific breeder, in addition to maintaining the grassland-wood land interface (edge)

habitat so essential for the survival of this species;

6.4 Methodology

Larger mammalian population of the study areas was sampled by using a combination of

direct and indirect methods. Among the direct methods. Trail Count has evolved as a sound

method of finding distribution and population index (MaCaffery 1976) already described in

Chapter 5

The indirect methods relies on the quantification of the indirect evidences such as pellet groups, scats, pug-marks, hoof marks, dung piles etc. Pellet group count method was

CHAPTER 6 HABITAT USE OF UNGULATES 120 employed in quantification of indirect evidences. Pellet group count method was first described by Bennet et al. (1940) and has subsequently been used by a number of investigators (Eberhardt and Van Etten 1956). Permanent circular plots of 10m radius were established in different habitats. Plots were randomly laid maintaining an approximate distance of 250 meters followed Dar et al. (2008b). In addition circular plots were also laid on trails. These plots were taken 10 m inside on either side of the trail to avoid sampling the relatively disturbed vegetation along it (Sultana 2002).

The presence of pellets, indicate that the animal has used the area. The pellets of different species were distinguished from each other by their size, shape and color. Only fresh and well-shaped pellets were considered. Partially or completely disintegrated pellets were not included in the sample to avoid error. The sample plots were cleared of any pellet before the onset of season and pellets were allowed to compile till the next sampling.

6.5 Statistical analysis

The data matrix was transformed using log and arcsine transformation before performing any statistical test to improve normalcy in the data, following Zar (1999). The values of the mean pellet group were compared with different habitats to test for significant difference using one­ way ANOVA. Pearson's product moment correlation analysis was used to observe correlation between the pellet group densities of different sympatric ungulate species with habitat parameters. To reduce the dimensionality of variables and to extract maximum information from the variables principal component analysis (PCA) was conducted.

A variety of indices have been proposed, which can be calculated for field measurements of the ecological niche such as utilization of dietary components, microhabitat, or temporal or

CHAPTER 6 HABITAT USE OF UNGULATES 121 spatial activity. The indices typically range from 0 (no resources used in common between two species) to 1.0 (complete overlap in resource use). Niche overlap was estimated based on the pattern of usage of particular habitat, altitudinal range, aspect and diversity of shrubs and tree species. These aspects are crucial for co-existence of species. Sympatric species can only occur when they isolate themselves at spatial and temporal scale based on the availability and utilization of resources. Pianka index for species 1 and 2, with resource utilizations pij and

P2i, Pianka's (Pianka 1973) overlap index of species 1 on species 2 (O12) is calculated as:

X

Where, 1, 2 represent species 1 and 2 with utilization of this habitat micro-components P12 and P21. This index is similar to the original asymmetric (MacArthur and Levins 1967) index.

The denominator has been normalized to make it symmetric but the stability properties are unchanged (May 1975).

Randomized Algorithm RA3 was used, which opts for retained niche breadth and reshuffle zero states based on recommendation by (Winemiller and Pianka (1990). Various resources which govern overlap or isolation in sympatric ungulate species was set to equiprobable - which assumes every resource which govern isolation or overlap is equally abundant or unusable to all species. Equiprobable resource state based on recommendation from Gotelli and Graves (1996) was followed. If the resources are not equiprobable, the analysis will tend to over-estimate niche overlap because species will tend to use common resource state even if there is niche segregation.

CHAPTER 6 HABITAT USE OF UNGULATES 122 The number of pellet groups for each species in each plot was used to calculate pellet group density. The values were pooled together to calculate the mean pellet group density for each species vis-a-vis different habitat types. The values of the mean pellet group density were compared with different habitats to test for significant difference using One-Way ANOVA and Mann Whitney U Test. Variation of pellet group density across different habitats and species was tested by using Two Way Analysis of Variance. To compare availability- utilization of various habitat variables, a computer program PREFER (Prasad and Gupta

1992) based on Neu et al. (1974) and Byers et al. (1984) was used. All the statistical tests were performed following Zar (1999) and using computer program SPSS (Norussis 1990).

6.6 Results

6.6.1 Habitat Use of Ungulates

Habitat use and niche overlap studies were carried out on five ungulate species sambar

{Cervus unicolor), goral (Nemorhaedus goral), muntjac {Muntiacus muntjac), chital {Axis axis) and serow (Capricornis sumatraensis). Though wildlboar was also present in the study area but, because of insufficient data it was not included in the final analysis. PCA was not performed on muntjac in KWA, serow in DWA due to very low sample size. PCA was also not performed on chital in DWA, because their complete absence from high altitudes increased the frequency of absence plots and thus would not allow us to run the PCA.

6.6.2 Dabka Watershed Area

Pellet group were counted in summer and winter seasons for all the species in DWA (Table

6.1). Mean pellet group density (/ha ± SE) was recorded highest for sambar (41.56 ± 3.51) followed by goral (23.31 ± 3.45), chital (19.21 ± 3.51), muntjac (7.43 ±1.21) and serow (1.02

±0.10) and difference was found to be significant (Mann Whitney U Test, P = 0.033). One

CHAPTER 6 HABITAT Use OF UNGULATES 123 way ANOVA showed significant difference in the mean pellet group densities of sambar and goral for two seasons (F = 11.079, P = 0.04) and (F = 9.21, P = 0.03). However, no significant difference was found in the mean pellet group densities of serow (F = 0.422, P =

0.677), muntjac (F = 0.732, P = 0.132) and chital (F = 0.332, P = 0.132) across the two seasons.

Across different habitats, the mean pellet group density (/ha ± SE) of sambar was highest in dense forest (85.33 ± 12.52) followed by chital (54.34 ± 9.23) and muntjac (15.23 ± 6.44). In moderate forest pellet group density was also recorded highest for sambar (32.34 ± 10.21) followed by goral (23.23 ± 9.78) and chital (12.55 ± 8.33). In agricultural field only pellets of chital were observed. Serow was recorded only in dense and moderate forest (Table 6.2).

Two Way Analysis of variance showed a significant difference between pellet group density of different ungulate species across different habitats (F = 6.38, df = 4, P = 0.027).

6.6.2.1 Ordination Technique

For muntjac PC A extracted eight factors explaining 91.11% of variance in the habitat utilization pattern. The first two factors explained 48.29% of variance. The gradients for the first factor were tree richness, tree diversity, shrub diversity, shrub evenness, shrub richness, canopy cover, shrub cover and tree no. The gradients for second factor were herb height, grass height, litter, bare ground, herb diversity and herb richness being important factor for habitat utilization of muntjac. Table 6.5 gives PCA matrix. Figure 6.1 shows ordination of animal and random plots of muntjac.

For goral PCA extracted ten factors explaining 90.37% of variance in the habitat utilization pattern. The first two factors explained 33.18% of variance in data set. The gradients for the

CHAPTER 6 HABITAT USE OF UNGULATES 124 first factor were grass diversity, grass richness and grass evenness and cut tree, which were responsible for habitat use. The gradients for second factor were tree evenness, grass no, tree diversity, shrub richness and elevation. Table 6.6 gives PCA matrix and Figure 6.2 shows the ordination of animal and random plots of goral.

For sambar PCA extracted seven factors explaining 93.52% of variance in the habitat utilization pattern. The first two factors explained 51.05% of variance. The gradients for the first factor were herb evenness, litter, shrub diversity, bare ground, herb diversity, herb richness, shrub evenness, tree diversity and tree no. The gradients for second factor were elevation, distance from habitation, herb height, canopy cover, shrub height and shrub covers.

Table 6.7 gives PCA matrix. Figure 6.3 shows the ordination of animal and random plots of sambar.

Chital showed positive correlation with shrub height, grass number and showed negative correlation with elevation, distance from habitation, and slope.

Sambar showed positive correlation with tree number, tree diversity, grass evenness, distance from habitation and showed negative correlation with slope, terrain and cattle dung piles

(Table 6.8).

Serow showed positive correlation with shrub number, shrub diversity and litter while showed negative correlation with cut tree, cattle dung piles, lopped tree and grass evenness

(Table 6.8).

Goral showed positive correlation with grass number, aspect, elevation, slope and fire. It showed negative correlation with canopy cover, litter, shrub evenness, distance from

•B CHAPTER 6 HABITAT USB OF UNGULATES 125 habitation, shrub cover, shrub diversity and tree number (Table 6.8).

Muntjac showed positive correlation with tree number, canopy cover, shrub diversity, and litter. It showed negative correlation with terrain, slope, shrub height, and herb height (Table

6.8).

6.6.2.2 Use of tree cover, shrub cover, slope, altitude, habitat and aspect by goral in DW A

The Availability-Utilization (AU) of tree cover categories showed that goral preferred areas with low tree cover (0-25%) and avoided areas of high tree cover (51-75%) (x^= 87.36, df =

2, P =^ 0.01) (Table 6.10). They also preferred areas with low shrub understory and avoided all areas where shrub cover exceeded 26% (x^ = 61.04, df = 2, P = 0.01). Goral were mostly sighted in steep slopes in the study area and usually avoided flat areas {% = 37.58, df = 3, P =

0.01). Goral seemed to prefer > 2100 m altitudinal range and avoided low altitudinal range

(X^ = 11.21, df = 1, P = 0.01). Goral usually avoided dense forest and showed preference towards open areas in the study area (x^ = 55.67, df = 3, P = 0.01). They showed a tendency to occur more equitably among aspects in the study area but southern aspects were used relatively more than their availability (x^= 63.18, df = 3, P = 0.01) (Table 6.10).

6.6.2.3 Use of tree cover, shrub cover, slope, altitude and habitat by chital in DWA

Chital used wide range of tree and shrub covers with preference towards moderate cover range (26-50%) for tree cover (x^ - 18.57, df = 3, P = 0.01) and shrubs (x^ ^ 25.48, df = 2, P

= 0.01) in the study area (Table 6.11). Chital in the area preferred areas with low slope category (< 25) (x^ = 41.65, df = 1, P = 0.01) and usually avoided areas of high altitude {y^ =

58.51, df = 1, P = 0.01). They also preferred areas of moderate forest and used other habitats according to their availability (x^= 72.41, df = 4, P - 0.01) (Table 6.11).

CHAPTER 6 HABITAT USE OF UNGULATES 126 6.6.2.4 Use of tree cover, shrub cover, slope, altitude, habitat and aspect by sambar in DWA

Sambar in the study area used to avoid less tree cover (0-25) and used in proportion to availability the different tree cover categories (x^ = 22.89, df = 3, P = 0.01). Sambar did not show any preference for shrub cover categories but avoided (0-25%) cover and used in proportion the other categories (x^ = 35.92, df = 3, P = 0.01). It appeared to prefer the (26-

50°) slope category, but avoided (0-25*') slope and used in proportion (51-75°) slope categorj

(Table 6.12) (x^ = 48.92, df = 2, P = 0.01). Sambar were sighted in a wide altitude range from

600 m to >2100 m in the study area and preferred altitudes between 1600-2100 m and used all other altitudinal range in proportion to their availability (x^ = 18.61, df = 3, P = 0.01).

Sambar in study area seemed to avoid open forest and showed their preference towards dense forest (x^ = 34.05, df = 2, P = 0.01). They were mostly recorded in northern aspects and thus showed preference towards this aspects (x^= 55.67, df = 3, P = 0.01) (Table 6.12).

6.6.2.5 Use of tree cover, shrub cover, slope, altitude, habitat and aspect by muntjac in DWA

Muntjac used both tree cover (x^ = 5.85, df =^ 2, P = 0.01) and shrub cover (x^ = 25.04, df = 2,

P = 0.01) in proportion to their availability in the study area (Table 6.13). It seemed to avoid steeper slopes (51-75°) and used other slope ranges in proportion to their availability (x^ =

15.57, df = 2, P = 0.01). The muntjac used all elevation ranges in proportion to their availability in the study area (x^ = 14.5, df = 3, P = 0.01). In different habitat categories muntjac showed preference towards dense forest and seemed to avoid open forests (x^ =

55.97, df = 3, P = 0.01). The AU of aspects of muntjac indicate that it preferred the northern aspects and seemed to avoid southern aspects and used in proportion to their availability the eastern and western aspects (x^ = 22.69, df = 3, P = 0.01) (Table 6.13)

CHAPTSR 6 HABITAT USE OF UNGULATES 127 6.6.2.6 Use of tree cover, shrub cover, slope, altitude, habitat and aspect by serow in DWA

The AU of tree cover categories showed that serow preferred high tree cover >75% and used other categories in proportion to their availability (x^ = 8, df = 2, P = 0.01). It avoided low shrub cover (0-25%) and showed preference towards high shrub cover 51-75% but difference was not found to be significant (Table 6.14). Serow used both the slope categories in proportion to their availability in the study area but difference was not found to be significant.

Being a high altitude species it avoided low elevation range and utilized in proportion higher elevation > 2100 m (x^= 8.04, df = 1, P = 0.01). Serow preferred dense forest and appears to have avoided open forest and used moderate forest in proportion to their availability {% =

10.28, df = 2, P = 0.01). The AU data of serow indicate that it avoided northern aspects and used others in proportion to their availability (x^ = 10.80, df = 3, P = 0.05) (Table 6.14).

6.63 Khulgarh Watershed Area

In KWA, overall mean pellet group density of muntjac was (26.87/ha ± 5.55). It was found highest in dense forest (81.39/ha ± 11.57) followed by moderate forest (39.81/ha ± 7.96) and open forest (2.27/ha ± 1.28) and difference was found to be significant (F = 54.41, df = 2, P =

0.000). In KWA muntjac pellet group density showed highly positive correlation with canopy cover, shrub cover, tree diversity, tree richness, tree evenness, distance from water and shrub density. It showed negative correlation with distance from habitation, grazing, grass density and cattle dung density (Table 6. 9).

6.6.3.1 Use of tree cover, shrub cover, slope, altitude, habitat and aspect by muntjac in KWA

Muntjac avoided 0-25% and seems to preferred 51-75% tree cover categories (x^= 2.15, df=

2, P = 0.05) and used all shrub cover categories in proportion to their availability in the study

(X^ = 13.01, df = 2, P = 0.01) (Table 6.15). It seemed to avoid steeper slopes (51-75^) and

CHAPTER 6 HABITAT USE OF UNGULATES 128 used other slope range in proportion to their availability (x^ = 8.21, df = 2, P = 0.05). Muntjac preferred 1600-2100 m altitude range and used all elevation range in proportion to their availability in the KWA (x^= 4.57, df = 3, P = 0.05). In different habitat categories muntjac showed preference towards dense forest and used all other habitats in proportion to their availability (x^ = 45.32, df = 3, P = 0.01). The AU of aspects of muntjac indicate that it preferred the northern aspects and seemed to avoid southern aspects and used eastern and western aspect in proportion to their availability (x^= 33.29, df = 3, P = O.Ol) (Table 6.15)

6.6,4 Overlap Between Ungulates in DWA

The overall niche overlap between four sympatric ungulate species is shown in Table 6.3.

The highest overlap was between sambar and muntjac (65%) and no overlap was found between chital and goral and chital and serow. Altitude, aspect, slope and vegetation parameters were found important factors for niche overlap analysis of four sympatric ungulate species. The detailed pair wise niche overlap among five species in different habitat variable is shown in Table 6.4.

The niche overlap of chital and sambar along different altitude and slope was found to be significant at 600-900 m (r = 0.730, P = 0.01) and 0 - 25" slope categories (r = 0.612, P =

0.01). Among other altitudes and slopes no overlap was found between the two species. Both the species were present in all the aspects, but showed maximum overlap in southern aspect (r

= 0.812, P = 0.001). Among tree cover maximum overlap was found in dense tree cover

(>75) but different was not found to be significant. Significant overlap between two species among different tree cover (r = 0.320, P = 0.021) and shrub cover (r = 0.411, P = 0.013) categories was found between 0-25% cover categories. In different habitats maximum

CHAPTBR 6 HABITAT USE of UNGULATES 129 overlap was observed in dense forest and difference was also found to be significant (Table

6.4).

No overlap was found between chital and goral and chital and serow among different habitat variables, because both goral and serow are high altitude species and their pellets were found above 1600 m and chital pellet was not found above 900 m in the study area (Table 6.4).

Among different altitudes and slope categories, the overlap between chital and muntjac were found only in 600-900 m, and 0-25° slope categories, respectively and difference was found to be significant (r = 0.730, P > 0.01) for altitude. Both species showed some degree of overlap among different aspects but the difference was not found to be significant. The species competed for moderate tree and shrub cover and showed maximum overlap between

26-50 cover category and pattern was found to be significant for tree cover (r = 461, P =

0.001) (Table 6.4).

Both goral and sambar were almost absent from lower altitudinal category. As a result maximum overlap between goral and sambar occurred in high altitudes but correlation was not found to be significant. Maximum overlap between sambar and goral was found in northern aspects but pattern was not found to be significant. Overlap was observed maximum in medium slope category (25-50°) that decreased in high altitudes due to very low presence of sambar in steep slopes. Among different tree cover, maximum overlap between these two species was observed in (26-50) category and difference was found to be significant (r = 0.523, P = 0.01). Since goral prefer open areas and sambar forested areas, a negative correlation (r = -0.231, P = 0.01) was found with high shrub cover of >75% and

CHAPTBR 6 HABITAT USE OF UNGULATES 130 among different habitats except barren area where sambar was found completely absent and difference was not found to be significant (Table 6.4).

Serow being a high altitude species was found completely absent from lower altitude and showed maximum overlap with sambar above >2100 m with significant difference (r = 0.823.

P = 0.03). Both species showed maximum overlap on western aspects and difference was found to be significant (r= 0.631, P>0.001). Among different slope categories, maximum overlap was observed between (25-50") and difference was not found to be significant. Since, both sambar and serow prefer high tree (50-75%) and shrub cover (>75%) therefore, maximum overlap was seen between the two with significant difference. Among different habitats maximum overlap was observed in dense forest and difference was found to be significant (r = 0.581, P = 0.001). Since, serow was not found in lower altitude, so their overlap with goral was found only above >2100 m with significant difference (r = 0.432, P >

0.04). Among different aspects overlap was observed in almost all the categories, but difference was not found to be significant. Both goral and serow prefer steep slopes, so maximum overlap was observed between 51-75" and >75" slope categories and difference was found to be significant for 51-75° slope (r = 0.891, P = 0.001) and > 75° (r = 0.756, r =

0.013), respectively. In terms of tree cover, shrub cover and different habitat type's slight overlap was observed between the two species (Table 6.4).

Goral and muntjac showed overlap 1600- 2100 m and above >2100 m but difference was not found to be significant. Maximum overlap between the two species was found in northern aspects without any significant difference. Among different slope an overlap of (44%) was observed in (51 -75°) slope category. No significant overlap with respect to tree cover, shrub cover and different habitats was observed between the two species (Table 6.4).

CHAPTER 6 HABITAT USE OF UNGULATES 131 An overlap of (44%) was observed between serow and muntjac >2100 m and difference was found to be significant (r = 0.511, P = 0.010). Maximum overlap between two species was observed on western aspects and difference was found to be significant (r = 0.571, P = 0.011).

On different slope categories, no significant overlap was observed between the two species.

Since both species prefer high tree and shrub cover, so maximum overlap was found above

75% cover category and difference was found to be significant for tree cover (r = 0.431, P =

0.011) and for shrub cover (r = 0.921, P = 0.001). Among different habitats maximum overlap between the two species was observed in dense forest and difference was found to be significant (r = 0.211, P = 0.041) (Table 6.4).

CHAPTER 6 HABITAT USE OF UN6ULAT£S 132 Table: 6.1 Mean pellet group density (/ha) of ungulates species in DWA Species Winter Summer Overall Chital 23.21 ±6.65 19.13 ±3.75 19,21 ± 3.51 Sambar 60.34 ±7.23 25.29 ± 4.24 41,56 ±4.21 Serow 2.21 ±0.34 .001 ±0.00 1.02 ± 0.10 Muntjac 13.45 ±2.21 4.11 ±1.07 7.43 ±1.21 Goral 33.21 ±4.81 15.56 ±3.10 23.31 ±3.45

Table: 6.2 Mean pellet group density (/ha) of ungulates across different habitats in DWA Habitat Chital Sambar Muntjac Goral 'Serow Dense forest 54.34± 19.23 85.33±12.54 15.23±6.44 7.77±5.21 2.21±0.34 Moderate forest 12.55±8.33 32.34±10.21 5.78±2.61 23.23±9.78 1.02±0.10 Open forest 8.21±7.31 4.21±1.95 2.23±1.33 49.23±9.10 0.00 Barren Area 2.21±1.23 0.00 0.00 8.33±6.54 0.00 Agriculture 1.23±0.45 0.00 0.00 0.00 0.00

Table: 6.3 Pair wise niche overlap between sympatric ungulate species in DWA

Species Niche overlap rs P Chital*Sambar 50.6 0.536 0.001 ChitaI*Serow 0 - - Chital*Goral 0 - - Chital*Muntjac 10.4 -0.257 0.040 Sambar*Goral 35.5 0.261 0.010 Sambar*Serow 60 0.621 0.021 Sambar*Muntjac 65 0.417 0.000 Gora!*Serow 5 -0.315 0.021 Goral*Muntjac 12 -0.211 0.001 Serow*Muntjac 55 0.641 0.000

CHAPTER 6 HABITAT USE OF UNGULATES 133 Table: 6.4 Percentage overlap between all combinations of pairs of species of ungulates in their association with altitude, aspect, slope, tree cover, shrub cover and habitat, together with spearman's rank correlation coefficients (rs) and corresponding probability value (P) in DWA. Variable Variable Category Species 1Percen t Overlap h P

Altitude 600-900 m Chital*Sambar 55 0.730 0.01 Chital*Goral - - - Chital*Serow - - - Chital*Muntjac 22 0.234 0.192 Sambar*Goral - - - Sambar*Serow - - - Sambar*Muntjac 23 0.112 0.231 Goral*Serow - - - Goral*Muntjac - - - Serow*Muntjac - - -

900-1500 m ChitaPSambar - . . ChitaPGoral - - - Chital*Serow - - - Chital*Muntjac - - Sambar*Goral - - - Sambar*Serow - - - Sambar*Muntjac 68 0.453 0.03 Goral*Serow - - - Goral*Muntjac - - - Serow*Muntjac - - -

1600-2100 m Chital*Sambar - - - Chital*6oral - - - Chital*Serow - - - Chital*Muntjac Sambar*Goral 64 0.305 0.432 Sambar*Serow - - - Sambar*Muntjac 83 0.732 0.001 Goral*Serow - - - Goral*Muntjac 55 0.341 0.211 Serow*Muntjac - - -

>2100 Chital*Sambar - - - Chital*Goral - - - Chital*Serow - - - Chital*Muntjac - - - Sambar*Goral 17 0.666 0.11 Sambar*Serow 87 0.823 0.03 Sambar*l\/luntjac 77 0.523 0.06 Goral*Serow 65 0.432 0.04 Contd..

CHAPTER 6 HABITAT USE OF UNGULATES 134 Goral*Muntjac 12 0.312 0.121 Serow*Muntjac 44 0.511 0.010

Aspect East Chital*Sambar 45 -0.463 0.04 Chital*Goral - - - Chital*Serow - - - Chital*Muntjac 35 0.231 0.141 Sambar*Goral 25 0.331 0.231 Sambar*Serow 56 0.376 0.006 Sambar*Muntjac 32 -0.534 0.321 Goral*Serow 43 0.371 0.031 6oral*Muntjac 21 0.481 0.213 Serow*Muntjac 12 0.321 0.131

West Chital*Sambar 60 -0.211 0.312 Chital*6oral - - - Chital*Serow - - - Chital*Muntjac 33 0.261 0.111 Sambar*Goral 35 0.321 0.131 Sambar*Serow 85 0.631 0.001 Sambar*Muntjac 51 0.302 0.210 Goral*Serow 67 0.485 0.312 Goral*Muntjac 49 0.112 0.031 Serow*Muntjac 91 0.571 0.011

North Chital*Sambar 54 0.430 0.281 Chital*Goral - - - Chital*Serow - - - ChitaPMuntjac 21 0.229 0.142 Sambar*Goral 69 -0.271 0.342 Sambar*Serow 53 0.491 0.621 Sambar*Muntjac 21 0.391 0.231 6oral*Serow 71 0.342 0.081 Goral*Muntjac 55 0.111 0.213 Serow*Muntjac 38 0.371 0.175

South Chital*Sambar 65 0.812 0.001 Chital*Goral - - - Chital*Serow 8 0.111 0.281 Chital*Muntjac 10 0.265 0.354 Sambar*Goral 31 -0.451 0.031 Sambar*Serow 71 0.351 0.213 Sambar*Muntjac 47 0.376 0.021 Goral*Serow 59 0.258 0.132 GoraPMuntjac 23 0.341 0.245 Serow*Muntjac 13 0.234 0.121

Contd..

CHAPTER 6 HABITAT USE OF UNGULATES 135 Variable Variable Category Species Percent Overlap rs P

Slope (0-25'') ChitaPSambar 68 0.612 0.01 Chital*Goral - - - Chital*Serow - - - Chital*Muntjac 75 0.562 0.121 Sambar*Goral - - - Sambar*Serow - - - Sambar*Muntjac 23 -0.353 0.211 Goral*Serow - - - Goral*Muntjac - - - Serow*Muntjac - - -

(25 - 50">) Chital*Sambar - . - ChitaPGoral - - - Chital*Serow - - - Chital*Muntjac - - - Sambar*Goral 54 0.032 0.183 Sambar*Serow 22 0.243 0.011 Sambar*Muntjac 95 0.671 0.001 Goral*Serow 45 0.421 0.187 Goral*Muntjac 30 0.278 0.289 Serow*Muntjac 24 0.356 0.145

(51 - 75°) ChitaPSambar - - - ChitaPGoral - - - Chital*Serow - - - Chital*Muntjac - - - Sannbar*Goral 43 0.432 0.023 Sambar*Serow 28 0.241 0.143 Sambar*Muntjac 14 0.321 0.111 6oral*Serow 97 0.891 0.001 Goral*Muntjac 44 0.342 0.132 Serow*Muntjac 25 0.213 0.211

(>75<') Chital*Sambar _ _ - Chital*Goral - - - Chital*Serow - - - Chital*Muntjac - - - Sambar*Goral 36 0.367 0.143 Sambar*Serow 24 0.222 0.144 Sambar*Muntjac 20 0.287 0.245 Goral*Serow 86 0.756 0.013 Goral*Muntjac 35 0.269 0.213 Serow*Muntjac 45 0.456 0.121 Tree Cover 0-25% Chital*Sambar 40 0.320 0.021 Chital*Goral - - - Chital*Serow 5 0.478 0.001 Chital*Muntjac 20 0.111 0.276 Sambar*Goral 18 0.289 0.452 Contd

CHAPTER 6 HABITAT USE OF UNGULATES 136 Sambar*Muntjac 10 0.021 0.211 Sambar*Serow 5 0.343 0.031 Goral*Muntjac 30 0.143 0.421 Goral*Serow 15 0.111 0.213 Serow*Muntjac 8 0.254 0.011

26- 50 % Chital*Sambar 63 0.048 0.823 Chital*Goral - - - Chital*Serow 56 0.167 0.172 Chital*Muntjac 70 0.461 0.001 Sambar*Goral 55 0.523 0.010 Sambar*Muntjac 40 0.212 0.132 Sambar*Serow 60 0.321 0.110 Goral*Muntjac 52 0.132 0.121 Goral*Serow 35 0.341 0.212 Serow*Muntjac 50 0.351 0.041

51-75% Chital*Sambar 30 0.254 0,313 Chital*Goral - - - Chital*Serow 15 0.251 0.165 Chital*Muntjac 20 0.345 0.162 Sambar'Goral 5 0.141 0.191 Sambar*Muntjac 80 0.712 0.012 Sambar*Serow 75 0.521 0.001 Goral*Muntjac 15 0.121 0.211 Goral*Serow 10 0.213 0,312 Serow*Muntjac 65 0.476 0.072

>75% Chital*Sambar 65 0.320 0.331 Chital*Goral - - - ChitaPSerow 30 0.241 0.312 Chital*Muntjac 35 0.376 0.111 Sambar*Goral 16 0.254 0.283 Sambar*Munt]ac 90 0.841 0.010 Sambar*Serow 85 0.662 0.046 Goral*Muntjac 10 0.241 0.241 Goral*Serow 15 0.352 0.211 Serow'Muntjac 78 0.431 0.011

Shrub Cover 0-25% Chital*Sambar 60 0.411 0.013 Chital*6oral - - - Chital*Serow 15 0.256 0.211 Chital*Muntjac 35 0.314 0.111 Sambar*Goral 25 0.111 0.213 Sambar*Muntjac 30 0.314 0.176 Sambar*Serow 5 0.226 0.213 Goral*Muntjac 30 0.282 0.111 Goral*Serow 10 0.140 0.341 Serow*Muntjac 5 0.191 0.212

26-50% Chital*Sambar 65 0.342 0.061 Chital*Gora( - - - Chital*Serow 30 0.231 0.121 Contd.,

CHAPTER 6 HABITAT USE OF UNGULATES 137 Chital*Muntjac 40 0.367 0.0761 Sambar*Goral 35 0.431 0.121 Sanfibar*Muntjac 64 0.585 0.012 Sambar*Serow 55 0.368 0.121 Goral*Muntjac 20 0.218 0.111 Goral*Serow 10 0.212 0.212 Serow*Muntjac 45 0.367 0.121

50-75% Chital*Sambar 65 0.245 0.410 Chital*Goral - - - Chital*Serow 20 0.312 0.121 Chital*Muntjac 39 0.291 0.312 Sambar*Goral 8 -0.316 0.212 Sambar*Muntjac 70 0.521 0.001 Sambar*Serow 95 0.777 0.011 Goral*Muntjac 10 0.151 0.451 Goral*Serow 5 0.161 0.215 Serow*Muntjac 65 0.451 0.001

>75% Chital*Sambar 40 -0.215 0.421 Chital*Goral - - - Chital*Serow 15 0.231 0.211 Chital*Muntjac 25 0.321 0.431 Sambar*Goral 55 -0.231 0.012 Sambar*Muntjac 60 0.555 0.001 Sambar'Serow 70 0.478 0.03 Goral*Muntjac 10 0.321 0.231 Goral*Serow 0 -0.471 0.021 Serow*Muntjac 90 0.921 0.001

Habitat Dense Chital*Sambar 55 0.283 0.480 Chital*Goral - - - Chital*Serow 40 -0.389 0.012 Chital*Muntjac 10 -0.111 0.519 Sambar*Goral 15 -0.231 0.214 Sambar*Muntjac 80 0.581 0.014 Sambar*Serow 90 0.621 0.001 Goral*Muntjac 17 -0.214 0.241 Goral*Serow 0 -0.211 0.321 Serow*Muntjac 65 0.211 0.041

Moderate Chital*Sambar 70 0.431 0.032 Chital*Goral - - - Chital*Serow 45 0.111 0.231 Chital*Muntjac 55 0.218 0.021 Sambar*Goral 30 -0.411 0.211 Sambar*Serow 60 0.434 0.121 Goral*Muntjac 10 -0.217 0.321 Goral*Serow 5 -0.321 0.071 Serow*Muntjac 40 0.411 0.181 Contd

CHAPTER 6 HABITAT USE OF UNGULATES 138 Open Chital*Sambar 30 0.338 0.229 Chital*Goral - - Chital*Serow 20 -0.311 0.211 Chital*Muntjac 10 0.211 0.312 Sambar*Goral 15 -0.361 0.151 Sambar*Muntjac 5 0.211 0.421 Sambar*Serow 0 -0.231 0.153 Goral*Muntjac 20 0.381 0.321 Goral*Serow 0 -0.211 0.211 Serow*Muntjac 5 0.231 0.212

Agriculture Chital*Sambar 2 0.117 0.421 Chital*Goral - - Chital*Serow - - Chital*Muntjac 5 0.132 0.219 Sambar*Goral - - Sambar*Muntjac - - Sambar*Serow - - Goral*Muntjac - - Goral*Serow - - Serow*Muntjac - -

Barren Area Chital*Sambar - - Chital*Goral - - Chital*Serow - - Chital*Muntjac 10 0.180 0.341 Sambar*Goral - - Sambar*Muntjac - - Sambar*Serow - - Goral*Muntjac 15 0.231 0.421 6oral*Serow - - Serow*Muntjac ~

• "

CHAPTER 6 HABITAT USE OF UNGULATES 139 Table: 6.5 Principal Component Analysis of animal and random plots of muntjac in DWA

Variable PCI PCII ~ Elevation -0.065 0.885 Terrain -0.402 -0.229 Slope -0.147 -0.422 Aspect -0.324 -O.lll Distance from water -0.340 0.894 Distance from ttabitation 0.451 -0.181 Canopy cover 0.797 -0.104 Slirub cover 0.797 -0.154 Tree no 0.726 -0.323 Tree diversity 0.888 0.066 Tree richness 0.924 -0.054 Tree evenness 0.787 0.164 Tree height 0.531 -0.413 Shrub no 0.622 -0.341 Shrub diversity 0.857 -0.126 Shrub richness 0.826 -0.118 Shrub evenness 0.844 -0.094 Shrub height 0.712 -0.247 Herb no 0.640 -0.016 Herb diversity 0.764 0.471 Herb richness 0.735 0.453 Herb evenness 0.687 0.649 Herb height 0.424 0.793 Grass no -0.483 0.047 Grass diversity -0.058 -0.115 Grass richness 0.008 -0.073 Grass evenness 0.246 -0.081 Grass height 0.127 0.688 Litter 0.614 -0.529 Bare ground -0.437 -0.573 Lopped tree 0.366 0.165 Cut tree 0.093 0.131 % of Variance 33.76 14.53 Cumulative % 33.76 48.29

CHAPTER 6 HABTTAT USE OF UNGULATES 140 1.0- DW Eleval on o o grassM Herbht O O Herbeve ° Herbdiv 0.5- ^ Herbric

Grassno Srassric Gr'sseve ^reeeve O Grassdiv "rassric - „,^H.r«. ° f'^eediv Aspect °Fi,cuttree °^ Herbno ^^^^ic 0.0" O CanopyCover'^ Q Terrain ShrubCover ^shrutadiv Sope ShrubM^ Shrubric O n Treeno O BareGr TreehtAverage QShrubno •0.5- O Litter

1.0- i 1 -1.0 -0.5 0 0 0.5 1.0

Figure: 6.1 Ordination of animal and random plots of muntjac in DWA, Uttarakhand

CHAPTER 6 HABITAT USE OF UNGULATES 141 Table: 6.6 Principal Component Analysis of animal and random plots of goral in DWA Variable PCI PCII Elevation 0.480 0.448 Terrain -0.060 -0.205 Slope 0.374 -0.076 Aspect -0.229 -0.094 Distance from water 0.262 0.257 Distance from habitation 0.141 0.475 Canopy cover -0.093 0.064 Shrub cover 0.012 -0.303 Tree no -0.222 0.115 Tree diversity -0.319 0.507 Tree richness -0.224 0.771 Tree evenness -0.084 0.146 Tree height -0.442 -0.097 Shrub no -0.438 -0.264 Shrub diversity 0.303 -0.555 Shrub richness 0.411 -0.678 Shrub evenness 0.266 -0.051 Shrub height 0.287 -0.409 Herb no -.0381 0.017 Herb diversity 0.494 -0.250 Herb richness 0.687 -0.430 Herb evenness 0.514 0.027 Herb height 0.191 -0.157 Grass no 0.066 0.515 Grass diversity 0.801 0.417 Grass richness 0.857 0.229 Grass evenness 0.919 0.136 Grass height 0.072 0.118 Litter -0.267 -0.623 Bare ground 0.267 -0.211 Lopped tree -0.497 0.239 Cut tree -0.735 0.275 Fire 0.262 0.27 Vo of Variance 19.64 19.64 Cumulative % 13.54 33.18

CHAPTER 6 HABITAT USE OF UNGUIATES 142 1.0- Treeric O Fire O. TreecSv DH Elevation 0.5- Grassdiv Grass no O O ^;f-'^^ Loppedtree Grassric " O Tre leve '^asseve Treeno i ssht O C o Herbeve Herbno n Shrutaeve _Q 0.0- AspeqCane tyCeter ^^^ OSIope TreehtAverageO O Terr an Shrubno ° OeareOr ^^^ O uHerbht JhfubCover ^'•'*" Hertaric O Shritodlv -0.5- Litter Shrubric O O

-1.0- —T— —r- -0.5 0.0 0.5 1.0 -1.0

Figure: 6.2 Ordination of animal and random plots of goral in DWA, Uttarakhand

CHAPTER 6 HABITAT Use OF UNGULATES 143 Table: 6.7 Principal Component Analysis of animal and random plots of sambar in DWA Variabte PCI PCII Elevation -0.064 -0.722 Terrain 0.407 0.321 Slope -0.540 0.031 Aspect 0.347 -0.685 Distance from water -536 -0.149 Distance from habitation 0.367 -0.868 Canopy cover 0.386 0.612 Shrub cover 0.185 0.572 Tree no 0.709 0.344 Tree diversity 0.742 -0.127 Tree richness 0.497 -0.225 Tree evenness 0.710 -0.324 Tree height 0.565 0.412 Shrub no 0.388 0.150 Shrub diversity 0.839 -0.176 Shrub richness 0.598 -0.059 Shrub evenness 0.742 -0.191 Shrub height -0.095 0.646 Herb no -0.042 -0.044 Herb diversity 0.766 -0.144 Herb richness 0.752 -0.189 Herb evenness 0.909 0.030 Herb height -0.468 0.766 Grass no -0.553 -0.348 Litter 0.857 0.344 Bare ground -0.808 0.220 Lopped tree 0.614 0.371 Cut tree 0.557 0.583 % of Variance 33.36 17.68 Cumulative % 33.36 55.05

CHAPTER 6 HABITAT USE OF UNGULATES 144 1.0- Herbht O Shrub It CanopyCover Shi jbCoverO o o 0.5- Fire TreeWAverage'^""''ee Terrain O- Treeno Litter BareGr o ° o o O Shrutino Slope O Loppedtree n^^jeve J2 Hei ano 0.0- Shfubric C DW ? .. _ Hofbdiy O ShrubeweS' J^^'"'^^" Herbnc Grassno O O Treeeve -0.5- Elev^lon Aspect O O DH

-1.0- _j— -1.0 -0.5 0.0 0.5 —r- 1.0

Figure: 6.3 Ordination of animal and random plots of sambar in DWA, Uttarakhand

CHAPTER 6 HABITAT USE OF UNGULATES 145 Table: 6.8 Correlation between pellet group density of chital, sambar, serow, goral and muntjac with different habitat variables in DWA

Habitat variables Chital Sambar Serow Goral Muntjac Elevation -0.750** 0.329** 0.018 0.309** 0.247** Terrain 0.281** -0.331** -0.162* -0.223** -0.335** Slope 0.252** -0.422** -0.078 0.351* -0.468** Aspect -0.247** 0.172* 0.049 0.335** 0.395** Distance from water -0.247** 0.268** -0.142 0.118 -0.025 Distance from -0.359** 0.335** 0.009 -0.491** 0.122 habitation Canopy cover -0.085 0.277** 0.177* -0.709** 0.501** Shrub cover 0.214** 0.147 0.069 -0.480** 0.190* Tree no. -0.098 0.419** 0.081 -0.437** 0.544* Tree diversity 0.216** 0.387** 0.047 -0.210** 0.314** Tree richness 0.284** 0.344** -0.027 -0.228** 0.283* Tree evenness 0.172* 0.319** 0.144 -0.274** 0.275** Tree height -0.015 0.099 0.177* -0.377** 0.245** Shrub no. -0.096 0.024 0.582** -0.225** 0.281** Shrub diversity -0.026 0.411** 0.336** -0.448** 0.400** Shrub evenness 0.168* 0.231** 0.150* -0.586** 0.276** Shrub height 0.704* 0.311** -0.147 -0.297** -0.310** Herb no 0.053 -0.171* 0.005 -0.157* 0.122 Herb diversity -0.025 0.266** 0.184* -0.283** 0.137 Herb richness -0.054 0.278** 0.178* -0.332** 0.150* Herb evenness -0.006 0.212** 0.169* -0.217 0.070 Herb height 0.551** -0.323** -0.181* -0.372** -0.342** Grass no. 0.511 -0.184* -0.141 0.633** -0.209** Grass diversity -0.037 0.027 -0.025 -0.013 0.007 Grass richness -0.223** 0.301** 0.086 0.162* 0.060 Grass evenness -0.212** 0.339** -0.211* 0.120 0.085 Litter 0.124 0.039 0.216** -0.655** 0.371** Bare ground -0.051 -0.059 -0.140 0.018 -0.093 Fire -0.115 0.236** -0.144 0.300** -0.160* Lopped tree -0.036 -0.063 -0.268** -0.091 0.195* - Cut tree -0.056 -0.148 -0.444** 0.049 0.002 Cattle dung piles -002 -0.385** -0.383* -0.141 -0.041 •Significant at P = 0.01

CHAPTER 6 HABITAT USE OF UNGULATES 146 Table: 6.9 Correlation between pellet group density of muntjac with different habitat variables in KWA Habitat variables Muntjac Terrain -.060 Slope .237 Aspect .066 Fire -.055 Grazing -.320* Distance from water -.471 * * Distance from habitation .592** Canopy cover .692** Shrub cover .501** Tree density .060 Tree diversity .580** Tree rich ness .511** Tree evenness .504** Tree height .029 Shrub density .403** Shrub diversity .013 Shrub evenness .035 Shrub height .229 Herb no -143 Herb diversity .040 Herb richness .130 Herb evenness .057 Grass density -402** Grass diversity -.116 Grass richness .204 Grass evenness -.080 Litter .068 Bare ground -.225 Grass -.157 Lopped tree -.042 Cut tree .320** Cattle dung piles -.323**

•Significant at P = 0.01

CHAPTER 6 HABrrAT USE OF UNGULATES 147 Table: 6.10 Availability-utilization of tree cover, shrub cover, slope, altitude, habitat and aspect by goral in DWA Categories Expected Prop Confidence Limits Intensity of Use Usage Lower Upper Tree Cover (%) 0-25 0.740 0.755 0.925 Preferred

26-50 0.120 0.045 0.195 Used in prop

51-75 0.040 0.00 0.035 Avoided

Shrub Cover (%) 0-25 0.747 0.646 0.847 Used in prop.

26-50 0.213 0.119 0.208 Avoided

51-75 0.040 0.00 0.035 Avoided

Slope 0.25 0.047 0.000 0.034 Avoided

26-50 0.200 0.108 0.292 Used in prop

51-75 0.320 0.405 0.635 Preferred

>75 0.253 0.153 0.354 Used in prop.

Altitude <1600 0.307 0.200 0.300 Avoided

>1600 0.693 0.697 0.800 Preferred

Habitat Dense 0.040 0.000 0.035 Avoided

Moderate 0.067 0.009 0.124 Used in prop.

Open 0.280 0.296 0.483 Preferred

Barren 0.613 0.501 0.726 Used in prop

Aspect North 0.120 0.045 0.115 Avoided

South 0.467 0.481 0.682 Preferred

East 0.320 0.212 0.428 Used in prop.

West 0.093 0.026 0.161 Used in prop

CHAPTER 6 HABITAT Use OF UNGULATES 148 Table: 6.11 Availability-utilization of tree cover, shrub cover, slope, altitude and habitat by chital in DWA

Categories Expected Prop Confidence Limits Intensity of Use Usage Lower Upper Tree Cover (%) 0-25 0.286 0.151 0.421 Used in prop.

26-50 0.629 0.281 0.576 Preferred

51-75 0.214 0.092 0.337 Used in prop.

>75 0.071 0.00 0.148 Used in prop

Shrub Cover (%) 0-25 0.286 0.178 0.394 Used in prop.

26-50 0.600 0.483 0.717 Preferred

51-75 0.194 0.038 0.190 Used in prop.

Slope >25 0.806 0.810 0.962 Preferred

<25 0.124 0.038 0.110 Avoided

Altitude >900 0.957 0.909 1.006 Used in prop.

<900 0.043 0.000 0.031 Avoided

Habitat Dense 0.071 0.007 0.123 Used in prop

Moderate 0.216 0.239 0.463 Preferred

Open 0.557 0.389 0.624 Used in prop

Barren 0.071 0.007 0.123 Used in prop.

CHAPTER 6 HABITAT USE OF UNGULATES 149 Table: 6.12 Availability-utilization of tree cover, shrub cover, slope, altitude, habitat and aspect by sambar in DWA

Categories Expected Prop. Confldence Limits Intensity of Use Usage Lower Upper Tree Cover (%) 0-25 0.028 0.035 0.142 Avoided

26-50 0.221 0.143 0.299 Used in prop.

51-75 0.398 0.306 0.490 Used in prop

>75 0.292 0.206 0.378 Used in prop

Shrub Cover (%) 0-25 0.013 0.015 0.047 Avoided

26-50 0.239 0.159 0.319 Used in prop.

51-75 0.451 0.358 0.545 Used in prop.

>75 0.257 0.174 0.339 Used in prop.

Slope 0-25 0.575 0.482 0.568 Avoided

26-50 0.481 0.189 0.372 Preferred

51-75 0.044 0.006 0.083 Used in prop

Altitude 600-900 0.115 0.055 0.175 Used in prop. 900-1500 0.221 0.143 0.299 Used in prop.

1600-2100 0.165 0.182 0.349 Preferred

>2100 0.398 0.306 0.490 Used in prop.

Habitat Dense 0.475 0.482 0.668 Preferred

Moderate 0.381 0.289 0.472 Used in prop.

Open 0.044 0.006 0.033 Avoided

Aspect North 0.449 0.455 0.642 Preferred

South 0.204 0.128 0.279 Used in prop.

East 0.124 0.062 0.186 Used in prop.

West 0.124 0.062 0.186 Used in prop

CHAPTER 6 HABITA T USE OF UNGULATES 150 Table: 6.13 Availability-utilization of tree cover, shrub cover, slope, altitude, habitat and aspect by muntjac in DWA

Categories Expected Prop Confldence Limits Intensity of Use Usage Lower Upper Tree Cover (%) 0-25 0.239 0.138 0.341 Used in prop.

26-50 0.296 0.187 0.404 Used in prop.

51-75 0.465 0.346 0.583 Used in prop.

Shrub Cover (%) 0-25 0.056 0.002 0.111 Used in prop.

26-50 0.437 0.319 0.554 Used in prop.

51-75 0.507 0.388 0.626 Used in prop.

Slope 0-25 0.310 0.200 0.420 Used in prop.

26-50 0.535 0.417 0.654 Used in prop.

51-75 0.155 0.069 0.141 Avoided

Altitude 600-900 0.183 0.091 0.275 Used in prop.

1000-1500 0.141 0.058 0.223 Used in prop.

1600-2100 0.437 0.319 0.554 Used in prop.

>2100 0.239 0.138 0.341 Used in prop.

Habitat Dense 0.493 0.514 0.712 Preferred Moderate 0.310 0.200 0.420 Used in prop.

Open 0.127 0.008 0.186 Avoided

Barren 0.028 0.00 0.017 Avoided

Aspect North 0.465 0.476 0.683 Preferred

South 0.070 0.000 0.031 Avoided

East 0.211 0.114 0.308 Used in prop.

West 0.254 0.150 0.357 Used in prop.

CHAPTER 6 HABITAT USE OF UNGULATES 151 Table: 6.14 Availability-utilization of tree cover, shrub cover, slope, altitude, habitat and aspect by serow in DWA

Categories Expected Prop. Confidence Limits Intensity of Use Usage Lower Upper Tree Cover (%) 25-50 0.143 0.000 0.296 Used in prop.

51-75 0.238 0.052 0.424 Used in prop.

>75 0.619 0.687 0.931 Preferred

Shrub Cover (%) 0-25 0.143 0.000 0.106 Avoided

26-50 0.333 0.128 0.539 Used in prop.

51-75 0.524 0.586 0.842 Preferred

Slope >50 0.286 0.089 0.483 Used in prop.

<50 0.714 0.517 0.911 Used in prop.

Altitude <2100 0.190 0.000 0.162 Avoided

>2100 0.810 0.638 0.981 Used in prop.

Habitat Dense 0.619 0.677 0.931 Preferred

Moderate 0.333 0.128 0.539 Used in prop.

Open 0.048 0.000 0.041 Avoided

Aspect North 0.048 0.000 0.034 Avoided

South 0.286 0.039 0.532 Used in prop.

East 0.143 0.000 0.334 Used in prop.

West 0.524 0.251 0.796 Used in prop.

CHAPTER 6 HABITAT USE OF UNGULATES 152 Table: 6.15 Availability-utilization of tree cover, shrub cover, slope, altitude, habitat and aspect by muntjac in KWA

Categories Expected Prop Confidence Limits Intensity of Use Usage Lower Upper Tree Cover (%) 0-25 0.139 0.038 0.111 Avoided.

26-50 0.261 0.147 0.314 Used in prop.

51-75 0.214 0.331 0.412 Preferred.

Shrub Cover (%) 0-25 0.067 0.022 0.101 Used in prop.

26-50 0.237 0.211 0.341 Used in prop.

51-75 0.417 0.288 0.593 Used in prop.

Slope 0-25 0.110 0.231 0.370 Used in prop.

26-50 0.135 0.087 0.182 Used in prop.

51-75 0.192 0.031 0.136 Avoided

Altitude 600-900 0.183 0.091 0.275 Used in prop.

1000-1500 0.141 0.058 0.223 Used in prop.

1600-2100 0.217 0.279 0.337 Preferred.

>2100 0.151 0.258 0.299 Used in prop.

Habitat Dense 0.311 0.491 0.611 Preferred

Moderate 0.327 0.221 0.411 Used in prop.

Open 0.127 0.162 0.186 Used in prop.

Barren 0.038 0.00 0.015 Avoided

Aspect North 0.514 0.596 0.714 Preferred

South 0.282 0.132 0.223 Avoided

East 0.041 0.000 0.045 Used in prop.

West 0.121 0.146 0.216 Used in prop.

CHAPTER 6 HABITAT USE OF UNGULATES 153 6.7 Discussion Coexistence of ecologically similar species in sympatric suggests tlie occurrence of differential use of resources. Separation along any dimension potentially might reduce inter­ specific competition and promote coexistence. Habitat is a complex resource which includes food availability, predation risk, and competitor density. Habitat choice and its use is therefore, the tradeoff between these factors evaluated by the animal.

6.7.1 Goral

Goral used areas with low or nil tree and shrub cover as its favored habitats are usually steep slopes with open grassy patches (Sathyakumar 1994). The use of vegetation cover by goral is similar to the observations made by other studies. Green (1985) reported that goral used 0% tree cover. Mishra (1993) reported similar choice of shrub cover by goral in Majhatal WS, where goral avoided higher shrub cover categories. Goral in Simbalbara WS preferred low shrub cover categories in winter and summer (Pendharkar 1993). Goral in DWA preferred steep slopes and avoided gentle areas. The use of steep areas is an anti-predatory strategy

(Sathyakumar 1994). Mishra (1993) reported that goral in Majhat WS preferred >30'' slope categories and avoided the lower slope categories. Goral in Simbalbara WS Preferred >51 slope in winter (Pendharkar 1993). Sathyakumar (1994) stated that 47% and 38% of total goral sightings in Kedamath WS were in >60*' and 41-50° slope categories, respectively.

Goral in the study area preferred >1600 m altitudinal range and avoided the altitudinal range below 1600 m. Mishra (1993) also reported that the best habitat in terms of goral abundance was above 1600 m in Majhatal WS. Green (1985) reported that goral used altitudes up to

3600 m, where as Sathyakumar (1994) reported 1900-2000 m range as preferred habitat for goral in Kedarnath WS. The preferred altitude range for goral in DWA was similar to the earlier studies. Goral preferred open and moderate forest, because they provide food in terms

CHAPTER 6 HABITAT USE OF UNGULATES 154 of open grassy patches, low tree cover, interspersion of densely forested nullahs or fringes for resting and adequate shelter and escape terrain. Goral showed preference towards southern aspects in the study area. The south facing slopes provide warmer areas with open grassy slopes (Sathyakumar 1994). Goral seems to avoid the northern aspects. Green (1985) reported that goral used south and south-western aspects more whereas Sathyakumar (1994) reported the preference of eastern, south-eastern and southern aspects at the lower altitudes and the avoidance of the same at the middle altitudes in Kedamath WS. Mishra (1993) and Mishra and Johnsingh (1997) reported the use of south-eastern aspects more than expected by gorai in Majhatal WS. Pendharkar (1993) reported the preference of south-east and south-west aspects in winter and summer. Sathyakumar (1994) reported the preference of southern aspects. In the present study it was also seen that goral utilized southern aspects more than their availability in DWA. Response to slope steepness, altitude, aspect, tree cover, shrub cover and habitat types may be related to factors such as visibility, forage availability and proximity to escape terrain.

6.7.2 Chital

Chital was mostly encountered in moderate tree and shrub cover. Moderate tree and shrub and tree cover offers escape cover and shelter to chital in the study area (Sathyakumar 1994).

Chital is present in all the habitats in the study area and used mostly gentle slopes and lower altitudes in the study areas (Dar et al. 2008b). The pellet density of chital was recorded highest in dense forest. The results are in agreement with Barrette (1991) and Chakrabarty

(1991). Chital is primarily a grazer (Mishra 1982) however, Hofmann (1985) considered chital as an intermediate feeder, feeding on a mixture of browse and grass. Schaller (1967) and Mishra (1982) consider chital as species adapted to ecotones. Since dense forest in the study area is at the interface of moderate forest and agricultural fields, therefore it may be the

CHAPTER 6 HABITAT USE OF UNGULATES 155 reason for observing higher density of chital. Moreover, dense forest has many plant species which are exploited by rhesus macaque and langur and chital follows the troops for getting fi-esh leaves and fallen fruits. It is equally important that chital was present in all the habitats including agricultural and barren areas indicating that it also goes for night crop raiding and thus prefer dense forest for the rest of the time.

6.7.3 Sam bar

Sambar showed positive correlation with tree density and shrub diversity. Its pellet density was also found highest in dense forest. Its preference for structured forests is already known.

Schaller (1967) believed that since sambar has an oriental origin therefore, it is adapted to forested habitats. Sambar which is predominantly a browser (Schaller 1967, Mishra 1982) and its affinity for shrubs can be explained on the basis of its feeding habits. Sambar was mostly encountered in dense and moderate tree and shrub cover areas. Moderate shrub and grass cover offer escape and shelter to sambar (Sathyakumar 1994). The results are in confirmation with Green (1985) who reported sambar sighting in >75% tree cover but in contrast to Bhatnagar (1991) who reported that sambar in the Shiwaliks showed preference for low tree and shrub cover in winter and summer. Sambar preferred moderate slopes categories as the habitats they used were predominantly in these categories (Sathyakumar

1994). Green (1985) reported that sambar in the subalpine region used mostly the 21-40° slope range. Sambar has a wide altitudinal range extending from the lower altitude to almost the tree line (Sathyakumar 1994). Most of the sambar sightings in the study area were in the range (1600-2100 m and >2100 m) and the present results were in confirmation with

Sathyakumar (1994) who recorded more that 75% of sighting in this range.

CHAPTER 6 HABITAT USE OF UNGULATES 156 6.7.4 Muntjac

Although muntjac used all tree and shrub cover categories in proportion to their availability but most of their sightings were in high tree and shrub cover categories. Small forest ungulates like muntjac choose to inhabit and hide in thick cover to avoid predation (Geist

1974, Chapman et al. 1993. McCuUough et al. 2000). Seeking dense canopy cover by muntjac is an important thermal strategy in winter (Mysterud and Ostbye 1995) and provides a means to avoid heat stress during summer (Sargeant et al. 1994). Since temperature is an important factor in temperate forest like Dabka, this may explain the preference of muntjac for high tree and shrub cover. Muntjac occurred in medium slope categories and seems to avoid steeper slopes 51-75'' which is similar to the observations made by Sathyakumar

(1994). Muntjac preferred moderate slopes categories as the habitats they used were predominantly in these categories (Sathyakumar 1994). Muntjac did not show preference towards any altitudinal range in DWA, but preferred altitude between 1600-2100 m in KWA.

Muntjac preferred the lower altitudes because its favored habitat lies in these altitudinal ranges (Sathyakumar 1994). Green (1985) reported that it occurred up to 2,740 m. Muntjac, therefore seems to be an ungulate inhabiting only the temperate zones particularly oak dominated forests. Muntjac showed preference for dense forest and seems to avoid open forest in the study area, which is due to the combination of its preferred altitudinal range and aspect in this habitat. Mostly dense forest in the study area is of oak trees. Ilyas and Khan

(2003) analyzed food quality in Binsar WS and found that crude protein values in oak forest were comparatively higher thus, arguing for the use of oak forest. Muntjac were encountered mostly in northern and western aspects and showed preference towards northern aspects, which is similar to the observations made by Sathyakumar (1994). The muntjac seems to avoid southern aspects, because these aspects are warmer and hence, they were not preferred

(Sathyakumar 1994).

CHAPT£R 6 HABITAT USE OF UNGULATES 157 6.7.5 Serow

Limited data on serow suggests that it prefered high tree and shrub cover with steep slopes and higher ahitudinal ranges. Green (1985) studied the ecological separation between ungulates in Kedamath WS based on field survey and dietary analysis and found that serow always occurred in dense tree and shrub cover and in very steep rugged slopes.

6.7.6 Ecological Separation

The differential use of altitude by ungulates is one of the major reasons for their ecological separation. This is substantiated by avoidance of altitudes >900 m by chital and <2100 m by serow. All the species occupied similar kinds of habitat, namely forest or scrub, with the exception of goral which preferred more open areas.

Though, Muntjac is similar to goral in size and in being solitary and a forest dweller they are considered to be allopatric and thus, the differential forest cover has been a major reason for their ecological separation. Sambar with its wide altitudinal range was more sympatric with muntjac and serow than goral. Green (1985) in Kedamath WS also concluded that sambar was sympatric to musk deer, goral and serow in subalpine habitats. Sambar by nature of its body size and preference for middle altitudes and being a grazer and browser (Sathyakumar

1994) was ecologically separated from muntjac, a small, solitary, intermediate feeder preferring lower altitudes. Moreover, browse inaccessible for muntjac is available for sambar as body size is an advantage. There was overlap between sambar and chital in the study area.

Sambar and chital were ecologically separated by their use and preference for different altitudinal zones and food preference. They seemed to avoid direct competition by adapting to different feeding habits. Johnsingh and Sankar (1991) in Mundanthrai plateau found that

CHAPTBR 6 HABITAT USE OF UNGULATES 158 with the advancement of summer chital shifts to grass and sambar to shrub for the fulfillment of their nutritional requirements once herbs either dry out or come into flowering phase.

Sambar and serow were sympatric as they shared similar habitats and both were browser and solitary. Green (1985) studied the ecological separation between ungulates in Kedamath WS.

The ecological separation between serow and sambar may be achieved by their differential preference for slope categories. Data though very limited, show that serow always occurred in dense tree and shrub cover and in very steep slopes, where as sambar showed preference towards intermediate tree, shrub and slopes.

Potential competition between herbivores can be avoided, therefore, by reduction in overlap either in habitat use or diet during periods of critical food shortage (Green 1987). It is known that African herbivores often overlap less in their diets during dry seasons, when resources are in short supply, than the wet season (Eltringham 1979).

CHAPTER 6 HABITAT USE OF UNGULATES 159 CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 7.1 Introduction The disappearance of large carnivores in the tropical belt may be next biological insult of the global extinction crises. Large predators and their prey are at particular risk in Asia, where they are threatened by poaching and habitat loss. Large mammalian predators and large herbivores exert a strong influence on community structure within the diverse range of habitat they occupy (Owen-Smith 1988, Dinerstein 1992), so their extirpation from an ecosystem is of grave ecological concern. Protecting wide range mega fauna requires taking the "representation" approach designed for habitat conservation and adapting it to species conservation, so that not only individual population be conserved but also the suite of adaptations and ecological interactions associated with them.

The members of the mammalian order carnivore number about 226 species, almost all of which are predators. As a group, carnivores exert a profound influence on biological communities via predation and interspecific competition (Treves and Karanth 2003).

Carnivores often regulate or limit the numbers of their prey, thereby altering the structure and function of entire ecosystem (Schaller 1972, Estes et al. 1998, Berger et al. 2001). As a result, carnivore management is of central concern to conservation biologists.

Increasingly, it is being realized that the decline of these large cats is global conservation concern (Weber and Rabinowitz 1996). Effective conservation of large predators requires the assessment of a complex mix of ecological, ethical and symbolic inter-relationships (Keller et al. 1996).The rate at which the tiger {Panthera tigris) and leopard {Panthera pardus) is losing its range, is a sure indication that these magnificent species are racing towards

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 160 extinction. The conservation status of the tiger is worrying even in India, which has about half the total population in the wild (Jackson, 1997, Thapar 1999). The reason for this is the unprecedented increase in human population, which in India, for example, was 361 million in

1951 and now stands at more than one billion, one sixth of the world's human population

(Johnsingh and Negi 2003). This much human mass and its growing requirements put enormous pressure on wildlife habitats. Another reason is the special requirement of tiger, which as species needs large undisturbed habitats with abundant ungulate prey (Johnsingh and Negi 1998).

Food availability and its utilization is one of the most important factors influencing the distribution of free ranging animals. Formulation of any management strategy for the given species in the question necessarily requires information on the food habits of the species

(Martin 1955, Wilkins 1957). Prey population controls the distribution and population of predator but at the same time predator checks the drastic increase in the population of prey species and help in maintaining the equilibrium. Understanding of predator-prey dynamics is crucial for the conservation of top order predators and the functioning of the forest ecosystems. The knowledge of diet spectrum and feeding habits provides requisite information to understand complex relationship of predator and prey. It means understanding of feeding ecology of these predators are essential for the formulation of better management strategies for management and conservation of big cats within their distributional ranges.

7.2 Importance of Big Cat

Big cats, being on the apex of food chain, play an important role in the homeostasis of the forests ecosystem and are the indicator of health and integrity of environment. lUCN defines

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 161 the big cats as Pantherine, including clouded leopard Neofelis nebulosa, snow leopard Uncia uncia, Panthera species and the marbled cat Pardofelis marmorata. In India, big cats are represented by five species- tiger Panthera tigris, Asiatic lion Panthera leo, leopard Panthera pardus, clouded leopard Neofelis nebulosa, and snow leopard Uncia uncia.

Ecologists who study the earth ecosystems and try to model their dynamics argue that the plant and animal communities that share our planet contribute to the stability and functioning of biological and chemical cycles that make life possible for us on this planet. Big cats, as tiger and leopard are an integral part of these complex ecosystems (Karanth 2001). Tiger and leopard is at the apex of these ecosystems and, therefore is the indicator of health of these ecosystems. So the conservation of tiger and leopard is necessary for the proper flinctioning of these ecosystems.

Although ecological studies of large carnivores within a modem scientific framework began forty years ago with George Schaller's pioneering work in Kanha National Park (Schaller

1967) and have advanced tremendously thereafter as a result of research by other scientists, much of this new knowledge appears to have escaped the notice of wildlife managers and conservationists in the Indian subcontinent (Karanth 2003). Major scientific advances in understanding tiger ecology were made in the 1973-1985, through radio telemetry studies in

Chitwan, Nepal, under the Smithsonian Tiger Ecology Project (Seidensticker 1976, Sunquist

1981, Smith et al. 1987, Sunquist and Sunquist 1989, Smith 1993, Seidensticker and

McDougal 1993). During the 1990s, long-term ecological studies in Nagarahole (Karanth and

Sunquist 1992, 1995, 2000), Panna (Chundawat et al. 1999) and other areas of India and

Nepal (Karanth and Nichols 1998, 2000, Biswas and Sankar 2002, Karanth 2003, Khan et al.

CHAPTER 7 FBEDING ECOLOGY OF TIGER AND LEOPARD 162 2004, Karanth et al. 2004, Wegge et al. 2004, Musavi et al. 2006, Ahmed 2007) that employed modem techniques such as radiotelemetry, camera trapping, dietary analyses and prey density estimation, generated substantial new knowledge about wild tigers.

The leopard P anther a pardus was one of the least studied animals till the 1970s in the wild.

Behavioral studies have been conducted on leopard by Chambers and Santipillai (1983) in

Srilanka, work on density estimation from camera trapping and scat counts has been carried out by Khorozyan (2003) in Armenia. Genetic level work was conducted for phylogeographic subspecies recognition of 27 subspecies of leopard by Miththapala et al. (1995) and the same work was carried out by Spong et al. (2000) on Tanzanian leopard. First intensive study was carried out by Hamilton (1976) on movements using radio-telemetry equipment. Zuberbuhker and Jenny (2002) studied leopard predation in Tai National Park and Ososky, leopard diet in

Ndoki National Park, Congo in 1998. Henschel et al. (2005) studied leopard food habit in

Lop National Park, Gabon. Mizutani (1999) studied impacts of leopard on working ranch in

Lakapia Ranches, Kenya. Stander et al. (1997) studied ecology of Namibian leopard in

Kaudom National Park, Namibia. Wright (1960) studied leopard predation in Serengeti

National Park, Tanzania. Kruuk and Turner (1967) studied comparative predation of lion, leopard, cheetah and wild dog in Serengeti. Schaller (1972) studied food habit and Bertram

(1982) studied leopard ecology by radio tracking in Serengeti. Mitchell et al. (1965) studied leopard predation in Kufi National Park, Zambia. Hart et al. (1996) studied diet, prey selection and ecological relationship of leopard and golden cat in the Ituri forest, Zaire.

Wilson in (1975) studied leopard diet in Wankie (Hwange National Park, Zimbabwe.

Eisenberg and Lockhart (1972) studied some ecological aspects of leopard in Wilpattu

National Park. Like other areas detailed study on leopard has been carried out in South

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 163 Africa, Whateley and Brooks (1985) studied leopard ecology along with other carinvores in

Hluhluwe-Umfolozi National Park. Mills (1990) studied comparative behavioral ecology of

Kalahari hyeana and leopard. Bothnia and le Riche (1984) and Bothma (1997) studied leopard behavioral ecology in Kalahari desert. Pienaar (1969) studied prey-predators relationship in Kruger National Park and Kruger (1988) studied inter-relationship of leopard with other large carnivores in Klaseria Private Nature Reserve. Bailey (1993) studied ecology and behavior and Mills and Biggs (1993) studied ecological relationship of leopard with other large carnivores in Kruger National Park. Walker (1999) studied ecological aspects of leopard in Phinda Game Reserve. Hirst (1969) studied leopard and other carnivores predation as limiting factor for large ungulate population in Timbavati Game Reserve and Grimbeek

(1992) studied ecology of leopard in Waterberg-Melk River.

In India leopard is one of the least studied animals than any other big cat like lion and tiger.

The main focus has remained on conflict with human at Sanjay Ghandhi National Park, Baria

Forest Divison, Gujarat and Garhwal Himalayas. Of course the species is more involved in conflict with human than any other large cat but the ecology and biology should be known and very important for long term conservation. Although, work on feeding ecology through scat analysis and standardization has been done by Mukherjee et al. (1994), Sankar and

Johnsingh (2002) Biomass consumption and scat produced in captive leopards and lion was studied by Mukherjee et al. (2004). Johnsingh (1983) and (1992) studied food habit and prey selection of leopard in Bandipur. Karanth and Sunquist (1995) studied prey selection of leopard, dhol (Cuon alpinus) and tiger in Nagarhole National Park. Other studies on leopard in Indian range (Johnsingh 1983, 1992a, Rice 1986., Karanth and Sunquist 1995, Sankar and

Johnsingh 2002, Ahmed 2007, Ahmed and Khan 2008) were conducted to know their prey

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 164 abundance and food habits. Hayward et al. (2006) reviewed the 29 published and four unpublished studies from 25 different conservation areas of 13 countries describing the diet

of leopard and prey preferences. The long term ecological study on leopard in India was

initiated in 2002 (Khan et al. 2004) with modem technique of radio-telemetry to understand

leopard movement pattern, food habit and social organization in Gir forest ecosystem. In

spite of advancement of research on different species of wildlife in India, the research on this

species is lacking. Still there is no knowledge about the ecology, breeding biology and social

structure of this secretive and elusive predator in the wild.

7.3 Materials and Methods

Scat analysis is an indirect, non-destructive and cost effective method (Schaller 1967,

Sunquist 1981, Johnsingh 1983) for recording frequency of occurrence of prey items in the

diet of a carnivore.

7.3.1 Collection and Preservation of Scats

Scats were collected at regular time intervals, generally every week, or more often in

frequently traveled areas throughout the entire study period. The forest roads and trails

known to be used for scat deposition by large carnivores (Sunquist 1981, Johnsingh 1983,

Karanth and Sunquist 1995, Ahmed and Khan 2008) were searched. During monsoon it was

not possible to collect the scats due to excessive rains in the study area. Scats were also

collected opportunistically during bird and herpetofaunal surveys in the study area. The scats

were collected in polythene bags, labeled and sun-dried in the field. Information on habitat

parameters, substratum where scat was found and its GPS location were also recorded. These

scats of leopard and tiger were differentiated based on associated signs and tracks, size and

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 165 appearance of each scat. The scats of leopard have higher degree of coiling than tiger and relatively lesser distance between the two successive constrictions within a single peace of scat. Although tiger sacts were found only in Kotabagh area of DWA below 800 m. Scats which could not be identified were excluded from the analysis.

7.3.2 Identification of Prey Remains From Scats

Standard methods for scat analysis from time to time were followed which have been used by various workers (Koppiker and Sabnis 1976, 1979, Leopold and Krausman 1986, Johnson et al., 1993, Reynolds and Aebischer 1991, Mukheijee et al., 1994, Spaulding et al., 1997,

Ahmed and Khan 2008).

1. Scats were crushed and carefully observed for the presence of indigestible macro

components such as bones, claws, feathers, beaks, scales, hooves and other indigestible

vegetable matter.

2. After identification of macro components the hair remains were washed in warm water

over a sieve to remove soil and calcium present in the scat.

3. The washed scats were dried for further collection of hair and their microscopic

examination to identify prey species.

4. Hairs were thoroughly mixed and randomly picked for slide preparation. Before slide

preparation hair were also treated with Xylol (50 % Ethyl Alcohol and 50 % Xylene)

when they carried more dirt or undigested food particles.

5. Reference slides for cuticular pattern and medulla were prepared for all potential prey

species occurring in the study area.

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 166 6. The combination of hair characteristics such as medullary and cuticular pattern, were

primarily used for identification of most of the mammalian species from the tiger and

leapord scats.

7. Slides of hair picked up randomly from scats were prepared in DPX mounting medium

for examining cuticular and medullary characteristics. All these characteristics were

compared with permanent slides to identify different prey species (Keogh, 1983).

7.3.3 Sample Size Estimation for Minimum Number of Hair

A total of 50 hair from a scat were picked up randomly and the prey species detected by scanning a hair for each additional hair. Then the cumulative proportions of prey species detected from all the hair scanned from a scats were recorded. This procedure was repeated for a total of 47 scats picked up randomly for the analysis. The cumulative proportions of total prey items in a scat were plotted against number of hair scanned. Ninety five percent lower bounds were computed for all the cumulative proportions. The purpose of this analysis was to ascertain the minimum number of hair that need to be scanned per scat for detection of all prey species and the whole method was repeated for all the scats collected from both the study areas. This was done only for leopard in both the watersheds and for tiger in DWA.

Quantification of the diet was based on both frequency of occurrence (proportion of total scats in which an item was found) and percent occurrence (number of times a specific items was found as a percentage of all items found) following Ackerman et al. (1984).

7.3.4 Sample Size Estimation for the Minimum Number of Scats

To determine the minimum number of scats that needs to be analyzed for an accurate estimate of food habits of leopard, Observation Area-Curve (Odum and Kuenzler 1955) was

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 167 used for a reliable estimate of leopard diet. Percent occurrence of each prey species in scats was calculated in increment of 5 - 10 scats and was plotted against the number of scats. This was continued until all the scats in the sample was analyzed. The cumulating frequency of occurrence of different prey species in the leopard scats over successive randomly drawn scats were then assessed to infer effect of sample size on the final resuUs. Diet diversity for tiger and leopard scats were calculated using Shannon Weiner Index (H')

H' =^ -Zp/ X logp/ where pi is the proportion of individual prey species.

7.3.5 Estimation of Biomass

Although frequency of occurrence of mammalian prey species in carnivore scats is most frequently used parameter in predation studies (Karanth and Sunquist 1995), but if prey sizes

are highly variable, frequency of occurrence can considerably distort the relative numbers of different prey types in the diet. Therefore, a method developed for mountain lions (Puma concolor), by Ackerman et al. (1984) was used to calculate the total biomass consumed of each prey species, assuming that the digestive system and feeding habits of leopard and mountain lion are comparable. Ackerman et al. (1984) conducted feeding trials and found a

linear relationship between ingested biomass per deposited scats (Y) and the live weight of prey species (X). The resulting linear relationship Y = 1.98 + 0.035X, was then applied in the

form of a correction factor, to convert frequency of occurrence to relative biomass consumed.

The live weights of individuals of wild prey species were taken from Karanth and Sunquist

(1995), Khan et al. (1996), and Henschel et al. (2005) and that of domestic livestock from

Schaller (1967). To calculate the relative biomass consumed, a corrected frequency of occurrence was used to take account of multiple prey species occurring in a single scat because the quantity of meat consumed for a given species will decrease as the number of

BaaBaaEBaBsaaBsasaBaBBBaBasaBBSiaaBg^si^H^ CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 168 prey species per scat increase (Henschel et al. 2005). The corrected frequency of occurrence was obtained by counting each prey item as 1/2, if two prey items occurred in one scat and

1/3, if three species occurred and so on (Karanth and Sunquist 1995, Ahmed and Khan 2008).

7.3.6 Analysis of Prey Selection

Selectivity for principal prey species was tested using x^ goodness-of-fit test (Zar 1999) based on null hypothesis of random or non selective prey killing by predators. Predation was selective in nature when proportion represented by potential prey species in scats differed from expected proportion in the community of prey species at a 95% level of significance (p

= 0.05).

The program SCATMAN (developed by J.E. Hines and W.A. Link, Link and Karanth 1994) was utilized to calculate the expected proportion of prey species in scats. Density estimates of both individuals and groups of individuals of wild prey species was used to calculate expected scat frequencies based on the assumption of non-selective predation by tiger. Scats having more than one prey species were given equal weight to each species following

Karanth and Sunquist (1995). If there was a pattern of overall prey selection, use of each prey species as calculated by the program inspected, Link and Karanth (1994) suggested that variability in the density estimates of each prey species and number of scats produced from a particular kill of any species is the potential source of inflation of type I error. Thus, program also incorporates the effect of such variability (Link and Karanth 1994) and reduces the inflation of type I error to produce an unbiased probability value. To overcome this problem parametric bootstrap procedure of the program for 1000 times suggested by Link and Karanth

(1994) was also implemented.

B!iBSBBBaBBSBSBBaBBa9BBaa9BaaBaaaBSB9BBBa^ CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 169 Karanth and Sunquist (1995) used density of groups of individual to determine the selectivity in prey selection while the Biswas and Sankar (2002) used both density of individuals and groups to make conclusion about the selectivity in predation. In this study encounter rate of individual to calculate the prey selectivity was used, because line transect method was not feasible in the study sites due to highly undulating topography and low animal sightings. So, instead of transect method trail monitoring were used.

7.3.7 Niche Overlap

The food niche overlap was calculated using the total number of items using the total number of items identified in scats among different species.The Pianka index between different species was calculated with discussed in detail in chapter 6.

7.4 Results

7.4.1 Sample Size

7.4.1.1 Sample Size Estimation for Minimum Number of Hair/Scat for Tiger in Dabka

The number of hair needed to be scanned per scat to detect 100 % of the mammalian prey species in a particular scat with 95% certainty was between 11-17 hair whereas 95% of the

mammalian prey species were detected by analyzing 10-12 hairs per scat (Figure 7.1).

Maximum scats (n = 38) were found with only one prey species (70.37 %) where as very few

scats (n = 10) were found containing two (18.52 %), three (7.41 %) and four prey species

(3.70%) (Figure 7.2).

7.4.1.2 Sample Size Estimation for Minimum Number of Hair/Scat for Leopard in Dabka

The hair needed to be scanned per scat to detect 100% of the mammalian prey species in a

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 170 particular scat with 95% certainty was between 8-9 hair whereas 95% of the mammalian prey

species were detected by analyzing 9 hairs per scat (Figure 7.3). Maximum scats (n =41)

were found with only one prey species (45.05%) whereas very few scats (n = 29) were found

containing two (31.87 %), three prey species (15.38%) and four species (7.69 %) respectively

(Figure 7.4).

7.4.1.3 Sample Size Estimation for Minimum Number of Hair/Scat for Leopard in Khulgarh

In KWA the number of hair needed to be scanned per scat to detect 100% of the mammalian

prey species in a particular scat with 95% certainty was between 9-10 hairs whereas 95% of

the mammalian prey species were detected by analyzing 8 hairs per scat (Figure 7.5).

Maximum scats (n = 73) were found with only one prey species (61.86 %) where as very few

scats (n = 30) were found containing two (25.42%) and three prey species (n = 15, 12.71%)

(Figure 7.6).

7.4.2 Diet Diversity in Tiger in DWA

The overall diet diversity of tiger in DWA (Shannon-Wiener Index H') was 2.923. In total 13

food items were found in the scats (n = 55). Chital constituted (30.91%) of the diet of tiger

followed by sambar (21.82%), cow (13.64%) and buffalo (10.00%). The remaining prey

items contributed less than 5 % in the diet of tiger. The wild prey constituted 77.36% of the

diet of tiger whereas domestic prey constituted 23.64% of their diet (Figure 7.7). Niche

overlap between tiger and leopard in Dabka Watershed Area was (a = 0.65). The overlap was

calculated by using Pianka's index on the relative percent frequency of occurrence of different prey species in the scats of tiger and leopard. The overlap was statistically

significant at the 95% level after 5000 randomizations.

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 171 7.4.3 Biomass Consumed

In terms of relative biomass consumed sambar and chital were the two most important diet items for leopards in the study area, making up 29.45% and 19.04% of total biomass consumed, respectively. In terms of domestic prey cow and buffalo constitited 19.04% and

19.99% of the total biomass consumed, respectively. Nilgai, wild pig and muntjak contributed 2.65%, 2.44% and 1.69% respectively. Together domestic livestock made up

39.03% of the biomass of tiger diet (Table 7.1).

7.4.4 Prey Selectivity for Tiger

Comparison of observed and expected frequency of occurrence of prey species in tigers scats indicated significant difference in utilization of prey species by tigers and rejected the hypothesis of non selective predation by tigers (x^ = 73.35, df = 12, P < 0.01). Comparison of observed and expected proportions of prey species (wild prey) in tigers scats based on their encounter rate, indicated the selection of prey species. It was found that sambar, wildboar and muntjak were utilized more than their availability. Chital was utilized in proportion to their avalability and langur and rhesus macaque were found to be utilized less than their availability (Figure 7.10).

7.4.5 Diet Diversity of Leopard in Dabka Watershed Area

The overall diet diversity (Shannon-Wiener Index H') of leopard in DWA was 3.003. In total

11 food items were found in the scats (n = 91). Sambar constituted bulk of diet (27.47%) of leopard followed by dog (21.98%), rodents (8.79%), goral (7.14%) and muntjak (6.59%). The remaining prey itmes contributed less than (5%) in the diet of leopard in DWA (Figure 7.8).

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 172 In terms of biomass sambar constituted (54.39%) of the total biomass consumed by the leopard in the entire study period followed by dog (13.41%) and wildboar (5.63%).

Remaining prey items contributed less than (5%) in the diet of leopard in DWA (Table 7.2).

7.4.6 Prey Selectivity of Leopard in DWA

Comparison of observed and expected frequency of occurrence of prey species in leopard scats indicated significant difference in utilization of prey species by leopard and rejected the hypothesis of non selective predation by leopard (x^== 67.37, df = 10, P < 0.01).

Comparison of observed and expected proportions of prey species (wild prey) in leopard scats based on their encounter rate in survey area indicated the selection of prey species and pointed preference or avoidance of prey species by leopard. Sambar and langur were found to be utilized more than their availability, while muntjak, goral and serow were found to be utilized less than their availability (Figure 7.11).

7.4.7 Diet Diversity of Leopard in Khulgarh Watershed Area

A total of 12 prey species were identified (n =118) with diet diversity (Shannon-Wiener

Index H') of 2.982. Dog constituted bulk of the diet of leopard (29.66%) in Khulgarh

Watershed Area followed by rodents (16.95%), langur (12.71%), muntjak (12.71%) and rhesus macaque (8.47%) (Figure 7.9).

In terms of relative biomass consumed dog contributed major portion of their diet (29.90%) followed by muntjak (14.31%), rodents (14.12%), langur (12.06%) and rhesus macaque

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 173 (7.55%). Remaining prey items contributed less than (5.00%) of the total biomass consumed by the leopard in the Khulgarh Watershed Area (Table 7.3).

7.4.8 Prey Selectivity of Leopard in Khulgarh Watershed Area

Comparison of observed and expected frequency of occurrence of prey species in leopard scats indicated significant difference in utilization of prey species by leopard and rejected the hypothesis of non selective predation by leopard (x^= 113, df = 11, P < 0.01).

Comparison of observed and expected proportions of prey species (wild prey) in leopard scats based on their encounter rate in survey area indicated the selection of prey species and pointed preference or avoidance of prey species by leopard from 2007-2009 in KWA. Rhesus macaque and muntjak were found to be utilized more than their availability whereas langur was found to be utilized in proportion to its avaliabilty and wildboar was utilized less than its availability (Figure 7.12).

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80.00

70.00

50,00

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40.00

30,00

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Figure: 7.2 Number of prey items detected in tiger scat (n = 55) in DWA

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 178 O O O O-O'O O-O-O'-O-O-O 0 O O 'O O'«>'O'0'<3>-O'O 0"0"0 OO

11 1? 15 17 19 21 23 25 27 29 31 33 35 57 35

Figure: 7.3 Standardization of minimum number of hair required per scat to know the food habit of leopard in D WA

50,00 45.00 40.00 : 35.00 ^ 30.00 ^ 25.00 20,00 15.00 10.00 5.00 000 IPrey 2 Prey 3 Prey 4 Prey

Figure: 7.4 Number of prey items detected in leopard scat (n =^ 91) in DWA

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20.00

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Figure: 7.6 Number of prey items detected in leopard scat (n =^ 118) in KWA

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 180 35 30.91 30

25 21.82 HFrequency of Occuaence DPercentage Oourence 20 13.64 15 10.00 10 4.55 4.55 5 3.64 2.73 ^_ 1-82 2.73 1.82 0.91 0.91 E^ I i ^^ I—i. •p^J~1 ^#^ s^ ;^ A..4'* #,#.^* " ~r^

Figure: 7.7 Food habit of tiger in DWA (n=55) from December 2007 to June 2009, Uttarakhand, India, 95% boostrap confidence interval

35

30 27 47 m 25 •- Frequency of occurrence D Percentage occurrence 20 -

15

10 8.79 8.79 6.59 7.14 7.14 4.40 5 1.65 1.65 0 ..N^ .

Figure: 7.8 Food habit of leopard in DWA (n=91) from December 2007 to June 2009, Uttaraichand, India 95% boostrap confidence interval

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 181 35 .66 30 25 -' 20 - jyf-95 12.71 12.71 Si] 15 8.47 10 - 4.24 5.51 2.12 2.97 5 [ 1.27 2.12 1.27 0 -: HM. 1

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0 Frequency of occurrence D Percentage Occurrence

Figure: 7.9 Food habit of leopard in KWA (n = 118) from September 2007 to June 2009, Uttarakhand, India, 95% boostrap confidence interval

18 a Used B Availability 16

8 •

5 \

4 ' 2 ; 0 ^ IrF L dl J Cliital Sanibar Wildboar Muntjac Langur Rhesus macaque

Figure: 7.10 Comparison of observed and expected proportions of prey consumed in scats based on encounter rate of prey species of tiger in DWA. Expected proportions of prey species in tiger scats calculated from encounter rates of prey species.

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 182 DAvaliability BUsed

30

25

20

10 n Hi L^ Serow iLangu r Sdinbar Muntjac Goral

Figure: 7.11 Comparison of observed and expected proportions of prey consumed in scats based on encounter rates of prey species of leopard in DWA. Expected proportions of prey species in leopard scats were calculated from encounter rates of prey species

DAvaliability •Used

30

25

20

10

Muntjac Wild Boar Langur Rhesus Macaque

Figure: 7.12 Comparison of observed and expected proportions of prey use in scats based on encounter rates of prey species of leopard in KWA. Expected proportions of prey species in leopard scats were calculated from encounter rates of prey species.

CHAPTER 7 FCEDING ECOLOGY OF TIGER AND LEOPARD 183 7.5 Discussion

Several investigators have investigated feeding ecology of carnivores (Johnsingh 1983,

Norton et al. 1986, Palmer and Fairall 1989, Windberg and Mitchell 1990, Karanth and

Sunquist 1995, Sankar and Johnsingh 2002, Biswas and Sankar 2002, Bagchi et al. 2003,

Kumar et al. 2004, 2007) by scat analysis technique. However, only few studies investigated the minimum number of scats and hairs required per scats to examine the feeding habits of carnivore species (Windberg and Mitchell 1990, Mukherjee et al. 1994 a,b, Biswas and

Sankar 2002, Bagchi et al. 2003, Jethva and Jhala 2003, Habib 2007, Ahmed 2007, Ahmed and Khan 2008) The present study, which was conducted in Dabka and Khulgarh watershed area, has also standardized the minimum number of hair that need to be scanned per scat in order to detect the presence of 95% and 100% of the prey species occurring in the diet of tiger and leopard. The results indicated that for determining the 95% of the prey items per scat 10-12 hair for tiger in Dabka, 10-11 hair for leopard in Dabka and 8-10 hairs of leopard in Khulgarh were needed to be analyzed, whereas for determining 100% of the food items 17-

18 hairs for tiger, 12-13 hair for leopard in Dabka and 10-11 hair of leopard in Khulgarh were sufficient. Since 70% of tiger scats in Dabka and 45% and 61% of scats in Dabka and

Khulgarh, respectively contained a single prey item, so picking up and scanning 1 or 2 or 10 hairs from such scats, which contain single prey item will produce the same results. Addition of each new hair in the scats will not have any effect in determining the mammalian prey species found in the scats showed by these results, since the majority of the scats contained only one prey species in both the Watersheds. Similar results were also reported by Harihar et al. (2006) in Rajaji National Park (77.27%), Bagchi et al. (2004) in Ranthambore National

Park (58%) and Ahmed (2007) in Dudhwa National Park (67%). Multiple prey items were also reported in other studies of large carnivores (Biswas and Sankar 2002, Bagchi et al.

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 184 2003, Mukheijee et al. 1994a, Ahmed 2007, Ahmed and Khan 2008) and common in smaller carnivores (Reynolds and Aebischer 1991).

7.5.1 Food Habit of Tiger

Large prey species (sambar, chital, wild pig, cow and buffalo) were found to be favored by tigers in comparison to smaller prey species. Preference for large prey species by predators in

Dabka can be considered in light of the hypothesis related to foraging theory (Stephens and

Krebs, 1987), which states that "predators may select prey species containing the most profitable prey as measured by the ratio of energy gain to handling time" (Scheel 1993,

Karanth and Sunquist 1995).

The comparison of frequency of different prey species in scats of tiger in different areas of

Indian sub-continent revealed that, if predation on chital is high then the contribution of sambar is relatively low or vice-versa suggesting strong preference towards chital and sambar over its range (Table 7.4).

When compared to other areas, the predation rate on livestock species (cow and buffalo) by tiger was found to be relatively high. All the studies, where predation rate on livestock was low, were conducted in protected areas, where entry of livestock is restricted by forest department. However present study was conducted in Reserve forest, where local people regularly graze livestock and high availability of livestock species gives rise to high rate of predation on livestock species by tiger in comparison to other areas.

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 185 Table: 7.4 Frequency of occurrence of major prey species in tiger Panthera tigris tigris scats from different areas of the Indian subcontinent

Species Dabka Corbett Pench Kanha Bandipur Nagahole Chitwan Bardia Bandipur Chital 17 40 53.01 52.2 39 31.2 33.3 77.7 145 Sam bar 12 23.2 13.78 10.4 30.5 24.9 29.3 - 99 Muntjak 2 1.9 5.34 - 6.1 4.1 - 11 Barasingha - N.P N.P 8.6 N.P. N.P. N.P. 1.4 - Hog deer - - N.P N.P N.P. N.P. 15.4 7.7 - Wild pig 2.5 6.5 8.88 0.8= 5.5 9.4 10.6 8.8 40 Gaur - N.P - 8.3 5.5 17.4 N.P. N.P. 106 Nilgai 1 4.8 - - N.P. N.P. - 1.9 - Chowsingha - N.P 2.67 - - - N.P. N.P. - Langur 1.5 1.9 3.65 6.2 - 3.9 5.7 2.3 10 Cow 7.5 9.2 4.34 5.9 5.5^ - - - -

Buffalo 5.5 5.6 2 1.7 - - - • - 2 Others 5 6.9 6.33 6.1 14 7.1 1.6 5.2 9 Dabka, Present study; Corbett, Kumar (2009); Pench, Biswas and Sankar (2002); Kanha, Schalier (1967); Bandipur, Johnsingh (1983); Nagarhole, Karanth and Sunquist (1995); Chitwan, McDougal (1977); Bardia, Stoen and Wegge (1996); Bandipur, Andheria et al. (2007), NP- Not Present

Result from prey selectivity (Scat analysis) analysis indicated that selective predation by

tigers was directed towards prey species with large body mass in DWA. Karanth and

Sunquist (1995) reported similar selective predation of tigers towards large bodied prey in

Nagarhole. Chital in terms of number of individual eaten, contributed maximally to the diet

of tiger in the study area and was utilized in proportion to its availability. The present results

are in conformation with Biswas and Sankar (2002), who also reported prey utilization

proportion to its avaliabilty. But in contrast with Johnsingh (1983), Karanth and Sunquist

(1995), Stoen and Wegge (1996), who reported under use of chital as compared to its

availability. Sambar and wild pig were consumed more than their availability in the study

area. Similar pattern of over-utilization of sambar and wild pig by tiger was also reported

from Pench (Biswas and Sankar 2002) which indicates habitat overlap between tiger and wild

pig. Selective predation on muntjak by tiger in the study area might be considered rare event

since this species is too small to be profitable prey for tigers. It occurs in very low density

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 186 and preferred hiliy terrain was very quick to disappear in the bushes. It becomes very difficult for tigers to prey on muntjak. Langur was under utilized by tigers because of its arboreal nature. Langur spends most of their time on the tree, so it is not possible for tigers to prey on them and hence they represent small portion of tiger's diet. Nilgai prefered flat areas and found rarely in study area could be the reason for its very small portion in the diet of tiger.

7.5.2 Food Habit of Leopard

The analysis of 91 and ! 18 scats in Dabka and Khulagarh revealed the presence of ten and eleven prey species in the dietary spectrum of leopard, respectively. The principal prey item in Dabka was sambar and dog, while in Khulgarh it was dog and rodents. The present findings confirm with that of Shah et al. (2009) who also found dog as a principal prey item in Dachigam National Park. The Dabka and Khulagarh both inhabited with 33 and 25 villages, respectively, contain a sizeable population of dogs and thus provide easy targets for leopard. Johnsingh (1983) although identified chital sambar, langur, cattle and hare as leopard prey items from scats but also reported killing of village dogs in Bandipur.

Rodents as a whole were the second most important group in Khulgarh, contributing 17.54% to diet of leopard and 14.12% of the total biomass consumed. The occurrence of rodents in scats of leopard in India has been documented by Ahmed and Khan (2008) Sankar and

Johnsingh (2002) and outside India (Grobler and Wilson 1972, Henschel et al. 2005).

Rodent's contribution in leopard diet was found to be 29.86% in Dudhwa and 45.6% in

Sariska, which was 17.35% and 23.1%, respectively of the overall biomass consumed

(Ahmed and Khan 2008, Sankar and Johnsingh 2002). The reason for high percentage in the diet of leopard may be the nocturnal habit of rodents which makes them more vulnerable to

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 187 leopard predation (Ahmed and Khan 2008, Grobler and Wilson 1972). The low percenatge of rodents, muntjak and goral in Dabka may be due the presence of large body weight prey species like sambar and may be considered in the light of hypothesis related to foraging theory (Stephens and Krebs 1987), which suggests that predator may select species containing the most profitable prey as measured by the ratio of energy gain to handling time

(Scheel 1993)

Sambar contributed 27.47% of the diet of leopard in Dabka and 54.39% of the total biomass consumed. The higher predation of leopard on sambar was also reported by Rice (1986) in

Eravikulum National Park and their contribution in leopard diet in other studies (Ahmed and

Khan 2008, Andheria et al. 2007, Sankar and Johnsingh 2002, Karanth and Sunquist 1995,

Johnsingh 1983). The forest of Khulgarh is in continuity with Ranikhet forest division, which has very good population of sambar (Habib 2002) that could be the reason for the presence sambar hair in scats of leopard.

The predation on langur and muntjak in Khulgarh was almost same 13.16% and 12.06% and

14.31% of the total biomass consumed. Shah et al. (2009) also reported langur as the principal prey items of leopard in Dachigam National Park. Since, leopards are known to prefer small to medium size prey within a weight range of 10-40 kg (Henschel et al. 2006) and such species are considered to be the energetically most profitable prey for the leopard

(Sunquist and Sunquist 1989). The low percentage of wild pig in both the study area may be attributed to inability to handle the aggressive prey of comparable weight (Karanth and

Sunquist 1995).

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 188 The results from both the study sites appear to support the prediction of Griffiths (1975), that

"vertebrate predators would be selective "energy" maximizers in prey rich habitat, but would be non selective where large prey were scarce".

The presence of birds, porcupine and jackal showed flexibility of leopard diet in both the study sites that they have enough behavioral plasticity to take advantage of a wide variety of prey species like neotropics felids (Rabinowitz and Nottingham 1986, Emmons 1987) because prey choice will be influenced by prey availability, abundance and vulnerability

(Emmons 1987, Nunez et al. 2000).

7.5.3 Prey Selectivity

Leopard's selectivity towards different prey species which was observed in Dabka and

Khulgarh, may be related to several factors. Leopard selectivity of sambar in Dabka indicates a preference for large prey size that is strong enough to override the possible risk of injury during prey capture (Karanth and Sunquist 1995). The comparatively higher degree of predation on langur in both in Dabka and Khulgarh and on rhesus macaque in Khulgarh by leopard may be linked to the leopard's greater arboreality and crypticity (Karanth and

Sunquist 1995). The under representation of muntjak, goral and serow may be due to their low avaliabilty in Dabka (Ahmed and Khan 2009). The selectivity towards muntjak in

Khulgarh may link to leopard preference to small to medium sized prey ranging around their own weight (45kg), and such species are considered to be energetically most profitable prey for the leopard (Sunquist and Sunquist 1989). However, confronted with the low abundance of medium size prey in Dabka, large ungulate prey became an important prey item for leopard (Bodendorfer et al. 2006).

CHAPTER 7 FEEDING ECOLOGY OF TIGER AND LEOPARD 189 CHAPTER 8 HERPETOFAUNA 8.1 Introduction Biodiversity supports life on earth, and human beings frequently depend on biodiversity to satisfy basic needs like food, refuge, medicine, combustibles, and industrial products (Dirzo et al. 2003). Amphibians and reptiles are essential components of the Earth's biodiversity because they play integral roles in food webs as herbivores, predators, and prey, as well as connecting aquatic and terrestrial ecosystems (Schenider et al. 2001). There are currently

6347 amphibian and 8863 reptilian species reported worldwide (Frost 2008, Uetz 2008) of these, 32.5% of all known amphibians and 22% of reptiles are endangered, and close to 122 amphibians and 22 reptile species currently have become extinct from the wild (Dirzo et al.

2003, Baillie et al. 2004, Stuart et al. 2004, Gascon et al. 2007).

Herpetofauna face numerous challenges coexisting with an urbanizing world. Some of the most important factors that have affected herpetofauna during the last three decades are: land use change (habitat deforestation, fragmentation and deterioration), emerging infectious diseases (such as the fungus that causes Chytridiomycosis), toxin release into the environment

(toxin-accumulation in trophic chains), over exploitation (by illegal trafficking or unmeasured scientific collecting), exotic species introduction (competitors or predators), and

synergetic interactions with climatic change (Dodd 1987, Semlitsch 2003, Young et al. 2004,

Hedges 2006, Tolson and Henderson 2006). In response to habitat changes and the

combination of this threat with other factors, some amphibian and reptile species have

undergone fluctuations in the duration of reproductive periods, loss of reproduction sites, loss of genetic diversity, changes in home ranges, population isolation due to the incapacity to

cross anthropogenic matrix habitats, changes in individual growth rates and activity patterns, •BBBOBiBBBBBBiaBa^siBBBaiBBaaaaaBaaaBBasaBaaBaaBasB^ CHAPTER 8 HERPETOFAUNA 190 and changes in microhabitat use (Crump 2003, Gardner et al. 2007). In fragmented environments, species with a greater degree of habitat specialization are more prone to extinction, as they are neither able to tolerate abrupt microclimatic changes nor move between patches of native forest (Schlaepfer and Gavin 2001, Urbina-Cardona et al. 2006).

Natural landscapes have been converted into semi-natural landscapes reducing habitat quality and resulting in the loss of connectivity between patches of suitable habitats, reduced size of native habitat fragments, and edge effects (Urbina-Cardona et al. 2006, Saunders et al. 1991,

Fischer and Lindermayer 2007). This in turn causes the extinction of individual species and functional groups (i.e. defaunation) which may precipitate extinction cascades throughout the food chain (Saunders et al. 1991, Fischer and Lindermayer 2007). It is known that habitat loss is the principal cause of species extinction. In spite of being at high risk of extinction, amphibians and reptiles are the terrestrial vertebrate groups least studied in the world, with only 5 and 2.5% respectively, of the total number of studies conducted on vertebrates and the effects of habitat loss (Lawler et al. 2006, Gardner et al. 2007). There are also a reduced number of studies on consequences of anthropogenic effects and land use changes on herpetofauna.

Amphibians and reptiles (collectively called "herps") are two distinct but important classes of vertebrates (Zug et al. 2001). Reptiles and amphibians are a major constituent of the fauna inhabiting tropical forests.

Reptiles are highly diverse in their morphology and ecology. They have a wide distribution though avoiding extreme environments. Reptiles are cold blooded therefore, go for hibernation during winter and aestivation during very hot temperatures.

CHAPTER 8 HERPETOFAUNA 191 Amphibians on the other hand are poikilothermal vertebrates having smooth or rough glandular skin and lacking fur (Daniel 2002). Amphibians have successfully exploited humid environments in most areas of the world while remaining closely tied to water or moist microhabitats for propagation (Zug et al. 2001).

Structure and composition of herpetofauna assemblage has been studied in different habitats

(Pianka 1973, Ross et al. 2000). The most commonly studied, to describe spatial structure of reptilian community, however is vegetation (Pianka 1967). Resource portioning along food, time, temperature, altitude and habitat gradient has also been documented (Pianka 1973.

Heatwole 1982). Heyer (1967) in a study on herpetofauna concluded that, although the distribution of some species was limited by climatic factors, that of some other correlated with specific microhabitats The precise requirement of herpetofauna with regard both to terrestrial and freshwater habitats are poorly understood (Beebee 1983). However, unlike birds and mammals, herpetofauna has not been studied in detail in India (Vasudevan et al.

2001).

Gibbons et al. (2000) enumerated six causes of global decline in herpetofauna. The causes included habitat loss and degradation, introduction of invasive species, environmental pollution, disease, unsustainable use and global climatic changes. As these causes are still present it is clear that herpetofauna is getting lost even before it gets recorded. Most people however, have come to recognize the value of both reptiles and amphibians as an integral part of natural ecosystems and as heralds of environment quality (Gibbons and Stangel 1999).

Despite high endemism, herpetofauna in India has received poor attention. Only few studies including Inger et al. (1984), Bhupathy and Kannan (1997) and Kumar et al. (2001) have

CHAPTER 8 HERPETOFAUNA 192 been carried out in India. Even these studies were restricted to rainforests of Western Ghats.

No such study has been initiated in the Kumaon Himalayas. The present study was carried out with the following objectives:

•^ To find the status and distribution of reptiles of Dabka and Khulgarh Watershed

Areas.

•^ To find the status and distribution of amphibians along the streams of the two

Watershed Areas,

v^ To find the diversity and richness of the herpetofauna of both the study sites

8.2 Methodology

8.2.1 Reptiles

Reptiles were sampled using the "Adaptive Cluster Sampling" as described by Ishwar et al.

(2001). The method was supposed to give better estimates of the density of animals. The basic sampling unit used was 5 m x 5 m randomly laid quadrates. If a reptile was sighted in one of these quadrates (called primary quadrates), additional quadrates (called secondary quadrates) of the same dimension were searched on the four sides of the primar> quadrate.

There was a gap of one meter between the primary and secondary quadrates. If any of these quadrates had animals, further quadrates were laid around them until the quadrate with reptile was surrounded by the quadrates without animals. The whole network of quadrates with animals then becomes a cluster. If the primary quadrate did not have any animal, the sampling was carried out in the next, randomly selected quadrate. In order to minimize the chances of missing animals during search efforts, two observers searched the quadrate from opposite sides towards the center. In each quadrate data was collected on (a) name of species, and (b) their number following Ishwar et al. (2001).

CHAPTER 8 HERPETOFAUNA 193 In addition to adaptive cluster sampling method, three quadrates of 5 m X 1000 m along the streams were established. Stream was considered as "centre of quadrate" and sampling was carried on both sides of the stream simultaneously. Loose rocks and leaf litter was carefully turned and cavities were prodded for reptilian species. In DWA, 40 permanent quadrates were laid and monitored for two seasons (summer and winter), amounting to 300 quadrates

(both primary and secondary). In KWA 30 permanent quadrates were laid amounting to 250 quadrates (both primaty and secondary) in two seasons (summer and winter). The data on herpetofauna was collected from September 2007 to June 2009.

8.2.2 Amphibians

The amphibian community was sampled using the methods described by Vasudeven et al.

(2001). Amphibians were sampled using a combination of adaptive cluster sampling and visual encounters. Opportunistic records were also maintained. The adaptive sampling was done along streams on the forest floor. Quadrates of 5 m X 1000 m along the streams were established. Stream was considered as "centre of quadrate" and sampling was carried on both sides of the stream simultaneously. Loose rocks and leaf litter was carefully turned and cavities were prodded for amphibian species.

In Dabka and KWA, four and three stream transects were established and monitored, respectively during the study period. During monsoon the stream got flooded therefore, sampling was abandoned.

8.3 Analysis

Data was summarized and density was calculated for each species. Shannon-Weiner Index

CHAPTER 8 HERPETOFAUNA 194 (H') was used for measuring diversity, Simpson's diversity index (D) was used for calculating evenness and Margalefs diversity index (Rf) was used to measure richness of species on different transects and in different seasons. Pearson's Product Moment Correlation

Coefficient was used to loiow the correlation of reptile and amphibian density with different micro habitat variables.

8.4 Results

8.4.1 Reptiles

8.4.1.1 Dabka Watershed Area (DWA)

In the DWA 15 species of reptiles were recorded during the study period (Appendix VII).

Overall reptile density in Dabka watershed was 87.52/ha. Overall diversity, richness and evenness of reptiles were 1.519, 0.932 and 0.759, respectively. Density of reptiles was highest in summer (127/ha) as compared to winter (50.4/ha). The diversity, richness and evenness of reptiles was highest in summer as compared to winter (Table 8.1)

Density of snakes was highest in summer (43.2/ha), followed by winter (21.21/ha). Combined densities of rest of the reptiles during the summer and winter seasons was 64.11/ha, 14.21/ha, respectively. Figure.8.1 shows the comparison of snake density with rest of the reptiles in different seasons. In stream transects, density of reptiles was 7.67^a. Diversity, richness and evenness in all the three stream transects were 1.607, 2.364 and 0.986, respectively.

Diversity, richness and evenness of reptiles were also highest in summer as compared to winter (Figure 8.2).

Sixty eight percent of the quadrate laid in DWA was single followed by 23% single clusters

CHAPTER 8 HERPETOFAUNA 195 and 8% double clusters (Figure 8.3). Overall clusters with single species was highest (34%)

followed by three species and about (23%) of clusters were found without any species (Figure

8.4). In summer, the cluster with single species was highest (38%) than winter (31%) and clusters with three and four species was highest in winter as compared to summer (Figure

8.5). About 8% of quadrate was found empty, 24.5% of quadrate contained species between 1 to 3, 47% of quadrate contained species between 4 to 7 and 16.5% were found to contain more than seven species (Figure 8.6). The comparison of species with their number in different seasons is shown in Figure 8.7. Reptilian density, diversity, richness and evenness were found to be decreasing with respect to increasing elevation in DWA (Figure 8.8 and

8.9).

Density of G'mther Mubaya ladacemishimalayanus was recorded highest (43.75/ha) followed by brahminey skink Mubaya carinata (27.22^a), kashmir Agama Laudakia tuberculata

(25/ha), common garden lizard Calotes versicolor (12.5/ha) and little skink Mubaya macularia (12.5/ha) in DWA.

In different habitats density of reptiles was highest (144.21/ha.) in moderate forest and lowest

in open forest (80/ha). Diversity (1.108), richness (1.797) and evenness (0.901) was found highest in dense forest and lowest was recorded in open forest (Table 8.2).

8.4.1.2 Khulgarh Watershed Area (KWA)

In the KWA 11 species of reptiles were recorded during the study period (Appendix VIII) with overall density of 77.71/ha. Overall diversity, richness and evenness of reptiles were

CHAPTER 8 HERPETOFAUNA 196 1.227, 0.733 and 0.659, respectively. Among different habitats density of reptiles was highest

214.44/ha in open forest and lowest 57.14/ha in dense forest and difference was found to be significant (F = 12.56, df = 4, P = 0.05). Diversity 1.689 and richness 1.251 were highest in dense forest, but lowest were recorded in agricultural area (Table 8.3).

Density of snakes was highest in summer (32.2/ha), followed by winter (7.21/ha.). Combined densities of rest of reptiles during the summer and winter seasons was 38.1!/ha & 11.31/ha, respectively (Figure 8.10). In stream transects density of reptiles was 21.67 animals per hectare. Diversity, richness and evenness in all the stream transects were 1.817, 2.554 and

1.011, respectively. Diversity, richness and evenness of reptiles were also higher in summer as compared to winter in KWA (Figure 8.11 and Table 8.1). Fifty nine percent of the quadrate laid in KWA was single followed by 29% single clusters and 12% double clusters

(Figure 8.12). Overall clusters with single species was highest (26%)) followed by three species and about (30%) of clusters were found without any species (Figure 8.13). In winter the clusters with no species was highest (34%) than summer (27%) and clusters with one species was highest in summer than winter (Figure 8.14). About eleven percent of quadrates were found to be empty, 26.5% of quadrate contained species between I to 3, 46.5% of quadrates contained species between 4 to 7 and 16.5% were found to contain more than seven species (Figure 8.15). The comparison of species with their number in different seasons is shown in Figure 8.16. Reptilian density, diversity, richness and evenness were found to be decreasing with respect to increasing elevation in KWA (Figure 8.17 and 8.18). The density of Snake skink Lygosoma punctatus was highest in KWA (110.37^a) followed by Little skink Mabuya macularia (35.57/ha), Kashmir agama Laudakia tuberculata (30.76/ha) and

Common garden lizard Calotes versicolor (10.12/ha).

CHAPTER 8 HBRPETOFAUNA 197 Comparison between the two sites show that Dabka watershed was more dense, diverse and rich than Khulgarh watershed (Figure. 8.19 and 8.20). Jacard's measure for similarity index for the two watershed areas was 0.725.

There was weak correlation of reptilian density with different microhabitat features. Density was positively correlated with all the factors except slope in DWA while negatively correlated with herb cover and presence of logs and rocks. The relation was significant with respect to litter cover, litter depth and moisture in both the watersheds. Table 8.4 enumerates the correlation values for both the sites.

CHAPTBK 8 HERPETOFAUNA 198 Table: 8.1 Diversity, richness and evenness of reptiles in different seasons in Dabka and KWA Index bWA KWA Winter Summer Winter Summer Diversity 0.413 0.981 0.213 0.589 Richness 1.325 2.513 1.542 1.653 Evenness 0.931 1.431 0.831 1.00

Table: 8.2 Reptiles density, diversity, richness and evenness in different habitats in DWA Habitat Density(/ha) Diversity Richness Evenness Dense forest 53.5 1.108 1.797 0.901 Moderate forest 94 0.455 0.764 0.691 Open forest 47.22 0.231 0.531 0.423

Table: 8.3 Reptile density, diversity, richness and evenness in different habitats in KWA Habitat Density Diversity Richness Evenness Dense Forest 57.14 1.689 1.25 0.948 Moderate Forest 62.62 1.00 .558 1.00 Open Forest 82.44 1.157 .869 .690 Barren area 43 .981 0.698 .884 Agriculture area 34.56 0.930 0.108 ,996

Table: 8.4 Correlation of reptile density with different microhabitat factors in Dabka and KWA Microhabitat variables DWA KWA Slope -0.026 0.030 Moisture 0.122* 0.160* Canopy cover 0.018 0.089 Shrub cover 0.085 0:068 Herb cover 0.020 -0.098 Presence of logs 0.414 -0.049 Presence of rocks 0.052 -0.147 Litter cover 0.216* 0.330* Litter depth 0.318* 0.536* ^Significant at 0.01 level

CHAPTER 8 HeRPeroFAUNA 199 80 -

•S 40

20

Winter Summer

• Snakes D Other Reptiles

Figure: 8.1 Comparison of snake density (/ha) with rest of reptiles in different seasons in DWA

3 2.5 3 2 5 S 1-5 u 1 1 0.5 -! 0 Diversity Richness Eveness

nWinter •Summer

Figure: 8.2 Reptilian diversity, richness and evenness in different seasons in DWA

80 70 -f 60 M 50

5 30 20 10 0 Single quadrate Single cluster Double cluster

Figure: 8.3 Percentage of network of clusters of reptiles in DWA

CHAPTER 8 HERPETOFAUNA 200 40 i 35 * 30 re '•^ ^" ph g 20 u r^ « 15 : -i-i a -S-, 10 5 1 -t ( 0 no species 1 species 2 species 3 species 4 species

Figure: 8.4 Percentage of clusters with different species of reptiles in DWA

no species 1 species 2 species 3 species 4 species

a Winter D Summer

Figure: 8.5 Percentage of clusters with different number of species of reptiles in winter and summer seasons in DWA

60

50

v 40 bs 4-re> c 30 u o\-r a 20 10 n lto3 4 to 6 >7

Figure: 8.6 Percentage of clusters with number of reptiles in DWA

CHAPTER 8 HERPETOFAUNA 201 60 50

00 S 30 f u S. 20 =[jJI^ 11 1 to 3 4 to 6 >7

I Winter D Summer

Figure: 8.7 Percentage of clusters with number of reptiles in winter and summer seasons

100 90 80 -f _ 70 ra £. 60 i ^ 50 £ 40 ° 30 20 10 0 + 600-900 901-1200 1201-1500 1501-1800 >1800

Figure 8.8 Reptile density (/ha) along altitudinal gradients in DWA

1.8 1.6 -t 1.4 I S 1.2 -t

g 0.8 I 1 0.6 0.4 0.2 -^ 0 600-900 901-1200 1201-1500 1501-1800 >1800

• Diversity •Richness Eveness

Figure: 8.9 Reptile diversity, richness and evenness along the altitudinal gradients in DWA

CHAPTER 8 HERPETOFAUNA 202 50

40

30

g 20

10 f

0 Winter Summer

• Snakes D Other Reptiles

Figure: 8.10 Comparision of snake density with rest of reptiles in different seasons in KWA

1.5 n > vt 1 0) ••• •a c 0.5 J Diversity Riciiness Eveness

DWinter R Summer

Figure: 8.11 Reptiles diversity, richness and evenness in different seasons in KWA

70

60

50 V «0 S 40 c a 30 a. 20 10 0 Single quadrate Single cluster Double cluster

Figure: 8.12 Percentage of network of cluster of reptiles in KWA

CHAPTER 8 HERPETOFAUNA 203 35

30 25 w OS S 20 c V a 15 a. 10 5 0 no species 1 species 2 species 3 species 4 species

Figure: 8.13 Percentage of Clusters with different species of reptiles in KWA

40

30

20 -

10 -

no species 1 species 2 species 3 species 4 species

a Winter D Summer

Figure: 8.14 Percentage of clusters with different number of species of reptiles in winter and summer seasons in KWA 60

50

a 40

Hi a 20 10 0 n 1 to 3 4 to 6 >7

Figure: 8.15 Percentage of clusters with number of reptiles in KWA

CHAPTER 8 HERPBTOFAUNA 204 60 T 50

ba 40 re *^c 30 i u01 a. 20 - 10 n -[ 1 la c -4- c 1 to 3 4 to 6 >7

I Winter D Summer

Figure: 8.16 Percentage of clusters with number of reptiles in winter and summer seasons in KWA

90 80 70 ™ 60 > 50 "I 40 Q 30 20 10 4 0 1100-1400 1401-1800 >1800

Figure: 8.17 Reptiles density along altitudional gradients in KWA

1.6 1.4 Ia. 1-2' S 0.8 ^ 0.6 -t c " 0.4 -t 0.2 4 0 + 1100-1400 1401-1800 >1800

• » Diversity • Richness —ir- Evenness

Figure: 8.18 Reptiles diversity, richness and evenness along ahitudional gradients in KWA

CHAPTER 8 HERPETOFAUNA 205 100 -i 90 T 80 i T 70 - i 60 - 50 - 40 J : I 30 - 20 : 10 0 - J __i_.__ Dabka Khulgarh

Figure: 8.19 Comparison of reptile density in Dabka and KWA

I 1.5

•o c 0.5 - L D Diversity H Richness

Figure: 8.20 Comparison of reptiles diversity and richness of Dabka and KWA

CHAPTER 8 HERPETOFAUNA 206 8.4.2 Amphibians

In Dabka seven and in Khulgarh four species of amphibians were recorded during the study period (Appendix IX, X). Four species recorded in Khulgarh were also present in Dabka. In total seven species of amphibians were recorded from the this study.

Overall amphibians density in Dabka was 9.38 individuals/ha. Diversity, richness and evenness of amphibians in DWA were 0.426, 0.674 and 0.278, respecyively (Figure 8.21).

In total, 221 individuals encompassing seven species were encountered in DWA. In Baghjala transect, 111 individuals contributing to six species were encountered with a density of 22.21 individuals/ha followed by 61 individuals from three species in Mahadev, 29 individuals from two species in Gugukhan and 20 individuals from two species in Chand transect (Table

8.6)

Among different amphibian species in DWA, the density of Skittering frog Euphlystic cyanophlyc was found highest 23.34 individuals/ha followed by Himalayan torrent frog

Amolops marmoratus 10.22 individuals/ha and common Indian toad Bufo melanostictus

2.22individuals/ha (Table 8.5).

In Khulgarh, overall ambhibian density was 5.23 individuals/ha. Diversity, richness and eveness in KWA was 0.234, 0.174 and 0.025, respectively (Figure 8.22). Density in the

Kovodov transect was found highest 10.22 individuals/ha foUwed by Kosi 5.10 individuals and Sayhedevi 2.43 individuals/ha (Table 8.6) Overall density of skittering frog Euphlystic

CHAPTER 8 HERPETOFAUNA 207 cyanophlyc was found highest 11.23 individuals/ha followed by Himalayan toad Bufo himalayanusgiinther 1.04 individuals/ha. (Table 8.5)

A total of four species with 151 individuals were encounterd in KWA. Of these 84 individuals of three species were encountered in Kovodov transect with a density of 10.22 individuals/ha followed by 36 individuals of two species in Kosi transect and 31 individuals of two species in Sayhedevi transect (Table 8.6).

Amphibian density also showed weak correlation with different microhabitat features except moisture in both the watersheds. Density was positive with all the factors canopy cover and presence of logs, slope and herb cover. The relation was significant with respect to moisture, litter cover and litter depth (Table 8. 7).

Cmmn 8 HERPETOFAUNA 208 Table: 8.5 Amphibians density in Dabka and Khulgrah Watershed Areas Amphibian Species DWA KWA Density/ha Density/ha Common Indian toad 2.22 0.023 Himalayan toad 1.11 1.04 Skittering frog 23.34 11.23 Indian Bull Frog 0.24 - Jerdons Bull Frog 1.21 - Himalayan Bull Frog 2.23 0.87 Indian Cricket Frog 0.91 - Himalayan Torrent Frog 10.22 -

Table: 8.6 Density of amphibians on different stream transect in Dabka and KWA DWA KWA Stream Transect Density/ha Stream Transect Density/ha Chand 1.21 Sayhedevi 2.43 Mahadav 4.12 Kosi 5.10 Baghjala 22.21 Kovodov 10.22 Gugukhan 3.11

Table: 8.7 Correlation of amphibian density with different microhabitat variables in Dabka and KWA Microhabitat variables DWA KWA Slope 0.019 -0.360 Moisture 0.621* 0.485* Canopy cover -0.077 -0.015 Shrub cover 0.175 0.149 Herb cover -0.067 -0.044 Presence of logs -0.061 0.061 Presence of rocks 0.017 0.061 Litter cover 0.170* 0.299* Litter depth 0.202* 0.316*

CHAPTBR 8 HERPETOFAUNA 209 0.8 0.7 ; 0.6 2 0.5 n $ 0.4 i 1 0.3 0.2 0.1 -f 0 Diversity Ricliness Evenness

Figure: 8.21 Diversity, richness and evenness of amphibians in DWA

0.25 • T i * 0.2 TB T > 1 S 0.15 i u £ 0.1

0.05 , 0 - ,™_j . rTL_. -^ Diversity Richness Evenness

Figure: 8.22 Diversity, richness and evenness of amphibians in KWA

CHAPTER 8 HERPETOFAUNA 210 8.5 Discussion

8.5.1 Reptiles

The overall reptilian density in Dabka and Khulgarh Watershed was 87.52/ha and 77.71/ha, respectively during the whole study period. This was much lower than 154/ha recorded by

Ingler (1980) in Panama and 108/ha by Kumar et al. (2001) in KMTR in Western Ghats and almost similar to 66.45/ha recorded by Dar et al, (2008c) in Garhwal Himalayas. The higher density in Panama and Western Ghats could be that these studies were conducted in tropical rainforests whereas, present study was conducted in sub-tropical areas of middle Himalayas and confirms with the study of Garhwal Himalayas. Kumar et al. (2001) reported 54 species from KMTR and Ingler et al. (1984) reported 33 species and Dar et al. (2008c) reported 10 species in Garhwal Himalyas. In this study 15 species were recorded. Low percentage of species in the two study sites may be because of two reasons, first the study area was small and second the study was conducted in sub-tropical areas of Kumoan Himalayas with confirmation from the results of Dar et al. (2008c) who conducted study in similar region and also reported lower species.

In both the study sites density of reptiles was highest in summer as compared to winter.

Lower density in winter may be due to harsh climatic conditions in both the sites. However, the high density in summer is also due to high density of non snake reptiles including geckos, agamids etc. as compared to their density during winter (Dar et al. 2008c).

Species in reptile assemblages are not randomly distributed in space either horizontal or vertically, but occupy discrete microhabitats (Heatwole 1982). There were some differences in abundance among the major taxa in both the watershed. Overall more species were

^ CHAPTER 8 HERPETOFAUNA 211 recorded in Dabka with more diversity and ricliness than Khulgarh, this may be the general

topographical condition of DWA starting from 500 to 2300 m above msl thus, representing

the species of both lower as well as higher altitudes. Together with skinks, agamids formed

dominant taxa in both the watersheds. Snakes were more abundant in Dabka in comparison to

Khulgarh, but contributed a small portion of forest floor reptiles in both the sites. Low

abundance of snakes could be due to their mobile nature and thus escape detection during

sampling (Dar et al. 2008c).

Change in reptilian abundance along altitudinal gradient has been documented earlier (Fauth

et al. 1989, Bhupathy and Kannan 1997, Dar et al. 2008c). The results of both the study sites

showed decline of density with altitude. Porter (1972) believes that it might be primary due to

decline in temperature. It seems logical since, reptiles are ectothermic, temperature plays

important role in their ecology.

Reptiles showed positive correlation with leaf litter cover depth and soil moisture. This was

particularly demonstrated by skinks and agamids. There was also preference for certain

structural diversity in the ground vegetation characters. This association of geckos, skinks has already been shown by Heatwole (1977), Kumar et al. (2001) and Dar et al. (2008c).

Agamids which were dominated by calotes preferred more rocky and open canopy than skinks. The specific habitat features are essential for leaf litter reptiles as they can meet the conflicting demands of thermoregulation, predator avoidance and participation in other activities (Lima and Dill 1990). It might also be possible that cool and humid environment below litter provide good microclimatic conditions for arthropods, which is a major prey base for the forest floor reptiles (Dar et al. 2008c). This fact was also observed by (Kumar et

CHAPTER 8 HERPETOFAUNA 212 al. 2001) in KMTR. Since snakes are predatory in nature, therefore, their local distribution might be influence by distribution of their prey abundance (Dar et al. 2008c).

8.5.2 Amphibians

Amphibians in both the areas show positive correlation with litter cover and litter depth. Com

(1994) noted positive association of Enstaina (an amphibian) with litter depth and grass cover. Litter depth may provide a wider range of microhabitat, allowing more individuals and species to coexist in the litter microhabitat (Fauth et al. 1989) or provide refuge from predation (Liberman 1986). Libermasn and Dock (1982) argued that litter may sustain large arthropod prey population. Block and Morrison (1998) believed that litter depth is an important factor in habitat selection in amphibians and reptiles. Amphibians are soft skin and sensitive to temperature and precipitation and also showed a positive correlation with moisture in both the watersheds.

Baghjaia in Dabka and Sayadevi in Khuigarh were found with highest density of amphibians.

It might be due to presence of water till late winter, less rocky and width of the stream. In addition to these, streams were wide as compared to others as a result slowing the flow and creating stagnant pools for species like Scittering frog to flourish. Density of amphibians was recorded low in Kosi and Sayadevi stream in Khuigarh and Gugukhan and Mahadav in

Dabka. Although, these streams were perennial, but quite deep. Amphibians though like water but seem to avoid deep water (Dar et al. 2008c). Hecnar and M'Closkey (1998) also found negative correlation of amphibians with deep water. Low density in Chand stream may be due to the fast flowing of water as amphibian's were recorded to avoid fast flowing streams (Dar et al. 2008c)

•BBBBaasBBBBBBaBBgaBaaBBBaaaBaBBaa^aaBBaaag^^ CHAPTER 8 HERPETOFAUNA 213 Comparison between two sites shows that reptilian density is higher in DWA. Diversity and richness values are also higher for Dabka as compared to KWA. The more density and diversity values in Dabka might be the general topography of the area starting from 550 to

2300 m above msl thus, representing the species of both Himalayan foothills as well as middle Himalayas. Another reason may be the fewer disturbances and large area of Dabka as compared to Khulgarh. Dabka is 69 km^ where as Khulgarh is only 32 km^. It therefore, seems probable that high density and diversity values are in Dabka. It is therefore, imperative from the above results that DWA is more diverse and richer with respect to reptiles and amphibians than KWA.

CHAPTER 8 HERPETOFAUNA 214 CHAPTER 9 CONSERVATION THREATS AND MANAGEMENT 9.1 Introduction The greatest damage to natural habitat and wildlife today is due to ever increasing exploitation of land and natural resources. The ever increasing exploitation is resulting in damage, loss and fragmentation of natural areas in all continuously inhabitated parts of the world; be it desert region, temperate region or tropical (Pyne 1981). Himalayas too, suffer with similar trend in resource use. Himalayas hold a significant unit in the Indian subcontinent and are perpetually being utilized as supplier of natural resources by human since the start of the civilization in this region. Later the origin and settlements in and around the valleys depleted the biodiversity values of the entire region. The overcrowding led to resource crunch and compelled them to move and expand up to the higher elevation in the difficult and remote areas. In due course of time the newly inhabited areas experienced similar threats as the previous ones at lower elevations.

Kumoan Himalayas which holds 4.70% of land of the Himalayas within the Indian limits, extend from lower to higher Himalayas, and it can be considered as representative unit possessing all climatic conditions experienced by entire Himalayan region. The region is densely populated by human beings and well connected with road transport through its range.

The easy approach to most parts of the region lead to the development of the area, as is being happening in other parts of the country. Consequently, random forest clearings were observed for the purpose and most parts of the region are facing severe threats in terms of loss of biodiversity values.

CHAPTER 9 CONSERVATION THREATS AND MANAGEMENT 215 The present study was conducted for assessment of various threats on biodiversity conservation. It was observed that this region too possesses threats on biodiversity as rest of the human inhabited regions of the Himalayas. The data on threats were collected during vegetation sampling (discussed in Chapter 3) as well as personal observation during the entire study period. The percent mortality of trees in different girth and height class categories were calculated. 95% Bonferroni confidence intervals was calculated following Byers et al. (1984) to find out the significant difference in mortality among various tree species.

9.2 Conservation Threats

9.2.1 Fire

Fire has been considered as one of the major threats particularly in DWA. According to the reports of forest department the maximum wide spread fire event with an affected area of 460 km^ was observed during 1984 in whole of the Kumoan and again after a span of 10 years i.e. in 1995, the affected area under fire was 309 km^. The great damage was observed due to fire during the years 1916, 1931, 1948, 1972, 1974, 1980-81 in Naini Tal forest division

(Working plan Naini Tal Forest Division 1988-1998) and more recently in 2008 widespread forest fire was also observed in this region (Pers. Obser.). Khulgarh (in Almora district was found to be degraded with maximum dependent human and a sizeable livestock populations.

The houses were situated very close and in the vicinity of the forest and locals extend great help to cease forest fire that's why this site did not experience extensive fire in the recent past years.

It has been observed that wild forest fire events on a large scale occur usually within a gap of

3 or 4 years (Sharma and Rikhari 1997). During the present study, fire was recorded from

CHAPTBR 9 CONSERVATION THREATS AND MANAGEMENT 216 Dabka. The fires at this place occurred during the summer season (April-May). This was owing to availability of low water content, highly inflammable ignition material (Sharma and

Rikhari 1997), high surrounding temperature and accumulation of oak leaf and conifer litter, low humidity in the same period (Rawat and Singh 1989). The low density values of sapling and seedling (Chapter 3) in Dabka also confirm this, those vegetation layers are found to be badly affected. Secondary layers mostly the shrub and tree species at the sapling stages are found dead. Many workers (Heinselman 1981, Bond and Van Wilgen 1996) have documented that post fire conditions have many advantages for seedlings. Space is freed by burning of established plant, resource (light, water and nutrients) increased and seed and seedling predation declines. A total of 990 plant species belonging to different species were sampled, of which 270 (27.27%) trees were found dead due to fire. The individual tree mortality was different between different species and it was significantly higher than expected in Viburnum cotinifolium, wheras it was significantly less than expected in Lyonia ovalifolia, Rhododendron arboreum and Shorea robusta. The mortality in rest of the species was in proportion to their availability. Figure 9.1 and 9.2 provide percentage mortality of different tree girth and height classes. The percentage mortality was higher in girth class 0-25 cm and 26 - 50 cm and it was found less in > 50 cm girth classes. The percentage mortality of plant in different height classes increased with height, it was found highest in 8-16 m and 16-

32 m classes. Fire showed heavy mortality in mature trees, as 25% of trees were found dead during vegetation sampling. This is attributed to the high intensity of fire and topography of the area. Trees at slope are more susceptible, as fire sweeping through slopes can bum a tree at various elevations. Smaller trees on slope usually get engulfed even by ground fire and have low chance of survival. The resistance of trees to fire varies greatly among different species, depending upon the tree size, physiological condition, site quality and season of

CHAPTER 9 CONSERVATION THREATS AND MANAGEMENT 217 burning (Kalbokidis and Wakimoto 1992). Martin (1989) suggested that bark thickness may

be the single attribute that best characterizes a species adaptation to fire. It follows that

smaller individuals are at greater risk of mortality due to their thin bark as compared to larger

individuals.

There is general consensus that fire is responsible for enormous levels of direct faunal

mortality, fire size and seasonality influence animal survival. During the assessment of fire,

no dead mammal, herpetofauna or birds was encountered. Part of the reason is that it is

difficult to pinpoint cause and eflFect relationship between the action of fire and the response

of animals. This might be due to the cause that sudden and drastic modification of habitat due

to fire at these sites created inhospitable habitats.

Table: 9.1 Proportion available (Pio), Proportion dead (Pie) and 95% Bonferroni confidence limits for dominant plant species in Dabka. (0 = mortality proportion to availability, - = significantly lower mortality & + = significant higher mortality). Tree species Pio Pie Bonferroni C.I Significant mortality Cedrus deodara 0.003 0.008 0.019

CHAPTER 9 CONSERVATION THREATS AND MANAGEMENT 218 70

50

is • •D so ^HH m ^^H 40 «*M. H o ^H 01 30 1. H sc ^^^1H 20 w ^1 ^ 10 - 1 • 0 ^ 1 I .1.1 0-25 26-50 51-100 101-200 201-400 >400

GBHfcm)

Figure: 9.1 Percentage of dead trees in different GBH categories

50 45

%mt> •o 35 •; IZ 32m

Height Categaries (m)

Figure: 9.2 Percenatge of dead trees in different height categories in DWA

CHAPTER 9 CONSCRVATION THREATS AND MANAGEMENT 219 9.2.2 Fuel Wood Collection

Villagers are totally dependent on existing forest of DWA. They fulfill their requirements of fuelwood from this area only. Survey for the fuelwood was based on requirement of eight identified villages inside the study area. An average requirement of fuel wood for each familj was found to be 30 kg/day. Villagers of distant villages mostly use pine wood, while villagers near the oak forest use oak wood. All the villagers prefer (75%) Quercus sp. as the fuel wood.

Other species used by villagers are Rhododendron arboreum, Shorea robusta. Viburnum sp. and Pinus sp.

9.2.3 Fodder

Oak leaves are considered to be the best fodder for miltching cattle. Each household owns a cattle population and it is predominently dependent on oak and other forest patches of the area. Villagers mostly prefer oak leaves, grasses and herbs for fodder. The collection for oak leaves start from mid November and it lasts til end of March. Villagers approximately collect

4567 kg of oak leaves per day. Collection of grasses and herbs starts from April and lasts till

September and each head load of grass weights 25 kg approximately. Overall 2550 kg/day grasses and herbs are extracted out for the cattle by all the surveyed villages. Green grasses are available only in September and collection of dry grasses starts in October and November for the winter season as it becomes difficult to collect grass after the snowfall. Grasses and herbs collection becomes low in July and August due to heavy rain. Arundinaria sp. mainly grow in oak forest as under-story. Some villagers collect this to make baskets as this is one of the partial source of income. Extraction of Arundinaria sp. starts from October and lasts till

March, because in this season grasses become mature and hard and are available in large quantities.

CHAPTER 9 CONSERVATION THREATS AND MANAGEMENT 220 9.2.4 Timber

Villagers also depend upon Naina and Kosi forest ranges for their timber requirements, which comes under Dabka Watershed Area. Usually, forest Department allots some trees to Gram

Pradhan who distributes timber to the villagers according to their requirements. The precious timber like Cedrus deodara and Abiespindrow are cut illegally by the villagers.

9.2.5 Medicinal Plant Extraction

People of the area do not use medicinal plant except Viburnum sp. So, no such pressure is there as far as medicinal plant extraction is concerned. Very few and old people of the area

know about traditional medicinal plants and they do not want to share their knowledge with

others. Moreover, people normally use allopathic medicine, which are cheap and easly

available due recent development of the area.

9.2.6 Pine Seed and Rhododendron Flower Extraction

Villagers collect Pine seed and Rhododendron flowers. Children in the age group of 13-22

are expert in climbing trees and collect the pine cones for the collection of seeds. They sell

the edible seeds in the market, cost of it varies from Rs. 150 to 200/kg. It is a partial source of

income to them. Rhododendron flowers are used for squash, some collect them for their own

consumption too.

9.2.7 Poaching

Poaching of the wildlife is by far the biggest threat to entire biodiversity of Kumoan

Himalayas. The nature and magnitude of this illegal activity varies from poaching for

personal consumption to organised poaching for commercial purposes. The high poaching

CHAPTER 9 CONSERVATION THREATS AND MANAGEMENT 221 pressure was noticed in entire forest. Although, Sultana (2002) found that the Vinaiyak area, falling under DWA, free from poaching and trade of wild animals. In this forest stretch, poaching is mostly done by visitors from Ramnagar, Ranikhet, Bhawali, Kotabagh, Bareily and nearby areas. There is nexus of some locals, who collaborate with poachers by providing logistic help and offering their services as guides. Poaching of tiger and leopard take place in forest areas outside Corbett Tiger Reserve near Ramnagar and Kotabagh Forest Division falling under DWA. All commercial poachers of tiger and leopard either operate from

Ramnagar, Nanital or Ranikhet. The road connecting Ramnagar and Khaima bridge through

Betalghat is frequently used by the poachers. They came out into the plains either via Khaima or Ranikhet. The road from Ramnagar to Khaima does not have an effective forest check post and is therefore, is a safe passage. In this area sambar, barking deer, goral, serow and pheasants are also subject to extensive poaching. This illegal hunting has already wiped out a number of species from certain areas of Kumoan e.g serow {Capricornis sumatraensis) from china peak near Nainital (Young and Kaul 1987) and from Binsar Wildlife Sanctuary (Ilyas

2001).

9.2.8 Tourism

Heavy tourism pressure in Dabka causes great disturbance to animals. Moreover, the construction of new metalic road from Pangot to Kunjakharak destroy the precious habitat of serow, sambar, barking deer and other wildlife of the area. Builders from Ramnagar, Nanital and Delhi hire the land of locals and tents make on that thus, promoting tourism in the area.

They also conduct night safaris, which cause great disturbance to the wildlife of the area.

Heavy tourism pressure coincides with the breeding period of the birds in summer season.

CHAPTER 9 CONSERVATION THREATS AND MANAGEMENT 222 9.3 Conservation Strategy

9.3.1 Protected Area Coverage and Management of Forest

The present study was aimed to study the faunal diversity of both the Watersheds and to prepare conservation strategies for them. For conservation strategies to implemented first the

two primary questions. What to conserve and where to conserve.

The barking deer, sambar, goral and serow in Kumoan Himalayas are important faunal

elements of the biodiversity of Himalayan landscape and some of these species are major prey item for leopard which is the top most predator and is widely distributed throughout the

area. Moreover, these temperate forests supports a relatively high proportion of species with

restricted distribution, notably the white throated tit (Aegithalos niveogularis), which

frequents bushes in mixed forest and dwarf shrub berries near the tree line in the breeding

season (Grimmet et al. 1998). This bird was frequently sighted in Dabka (Vinaiyak reserve

forest). Another endemic bird Pied thrush (Zoothera wardii), which breeds in open broad

leaved forest in the Himalayas and hills of North East India (Sultana 2002). This bird was

seen thrice in Vinaiyak Reserve Forest (VRF). Sulatna (2002) also observed this twice in this

area. Birdlife International has identified eight centres of endemism in the Indian

subcontinent and Western Himalayas is one of them (Grimmet et al. 1998). The 11 species

endemic to the western Himalayas include the probably extinct Himalayan quail, which was

once distributed in Nainital (Vinaiyak, Kunjakharak) and Cheer pheasant {Catreus wallichii)

is thought to be at the risk of extinction sighted in Vinaiyak forest of the study area.

Therefore, the conservation of these is of paramount importance. Since, in nature no

organism lives in isolation, each species is dependent on other species as also an ecological

system. As there is complete interdependence in nature, change in a habitat affects the

CHAPTER 9 CONSERVATION THREATS AND MANAGEMENT 223 diversity of species contained in it. Conversely, any change in the number and assembleges of species also affects the nature of habitat. So, there is a need to conserve biodiversity because of interdependence of species in nature for survival demands conservation of all elements of biodiversity.

The first step of most conservation planning is to identify areas that want protection. The main criteria used to identify such areas are biodiversity, rarity, population abundance, environmental representativeness and site area (Sultana 2002). Where distribution data are both comprehensive and accurate, it is possible to identify areas of high species richness for certain taxa, focussing on threat level (e.g. endangered species) or biogeographical status

(e.g. endemic species) (Diamond 1986, Myers 1990, Prendergast et al. 1993). In the past the protection of individual, usually rare species was used to select the site for protection but this

approach to reserve selection has its strength and weakness (Prendergast et al. 1999).

There are only two Wildlife Sanctuaries existing in Kumoan i.e. Ashok Wildlife Sanctuary

(Pithoragarh district, area = 600 km^) and Binsar Wildlife Sanctuary (Bageshwer district, area

= 45.59 km^). The percent protected area is too small as compared to the whole geographical area of Kumoan (2,1032 km^). Both the sanctuaries are facing severe threats. Binsar

sanctuary has limited conservation potential by having only approximately, 4 km^ of oak patch (Sultana 2002).

Thus, in order to conserve faunal diversity more areas have to be brought under the network of protected areas. Sultana (2002) have already suggested creation of two protected areas in

Nainital and Almora districts based on their avian survey. The protected area in Nainital

CHAPTEK 9 CONSERVATION THREATS AND MANAGEMENT 224 district will include Kilbury, Vinaiyak and Kunjakharak. It is strongly recommended the creation of this sanctuary based on the overall biodiversity assesment of this study. The area holds maximum biodiversity and is relatively less disturbed. This area also has higher density of certain ungulate species when compared to other protected areas of Himalayas (discussed in chapter 5 and 6). Moreover, sighting of a rare species i.e. serow which was thought to be wiped out of China Peak (Young and Kaul 1987), 10 km away from study sites enhance the importance of study site to be declared as sanctuary. The creation of this sanctuary and the buffer zone of Corbett Tiger reserve and National Park will act as a corridor between them.

These corridors would allow faunal and floral diversity to disperse from one reserve to another, facilitating gene flow and colonization of suitable sites. This would also help mammals and birds that migrate seasonally fi-om different altitudes and habitats to obtain food. Since, Dabka is a river catchment therefore, it has a potential of being considered as biodiversity hot spot for conservation ( Samant et al. 1993).

The situation of KWA (Sitlakhet) is worse. Most of the area is highly degraded and surrounded by pine forest. Being close to Almora, it is densely populated with human and livestock populations and is well connected with road network all around. It is devoid of any dense oak patch. So, people mostly depend on the degraded oak forest to meet their needs of fuel wood and fodder. Moreover, if we compare the anthropogenic pressure of both the sites, the cut tree, lopped tree as well as cattle dung density is approximately 5-6 times higher in

Khulgarh as compared to Dabka (Table 9.2)

Though, it is not possible to prevent habitat loss in nearby towns but the extent of dependency can be reduced.

CHAPTEH 9 CONSERVATION THREATS AND MANAGEMENT 225 Table: 9.2 Mean number of cut trees, lopped trees and cattle dung piles (/ha) in Dabka and KWA Cut tree density Lopped tree density Cattle dung density Dabka 25.24 ±4.56 27.04 ± 4.80 25.83 ±4.20 Khulgarh 250.99 ± 28.03 123.60 ± 10.33 53.83 ±11.66

Apart from giving status of sanctuary to Naina and Vinaiyak Reserve forests for the conservation of biodiversity of the area, it is also recommended that the following steps be taken to reduce the dependency of people on the forest in Kumfoan Himalayas.

1. All ridges and barren lands should be afforested with native tree species, particularl>

in KWA. Not only forest department but local people should also be engaged for this.

2. Some of the land under cultivation, in both the areas is of poor quality and on such

steep gradients forestry practices would be a proper use of those lands.

3. Opportunity should be offered to landholders to surrender their land to the

government for afforestation against adequate compensation. Conservation of entire

biodiversity will not be possible without addressing the local needs.

4. The existing as well as the areas which are going to be conserved by Govt, should be

brought under Eco-tourism. Through this scheme locals also would get employment

and the awareness for environment or wildlife conservation could be spread amongst

the dependents of forest.

5. The task of conservation can not be initiated and made feasible to work untill and

unless locals are involved and are benefited. So, the locals should be made the

stakeholders and are army for conservation. People-private partnership (PPP) model

would be the best suited strategy to give it a start.

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BiBUOGRAPHY 261 APPENDIX Appendix: I Density, diversity, richness and evenness of bird guilds in different habitats in DWA Habitat Guild Density Diversity Richness Evenness Dense forest Omnivore 8.60 3.910 4.228 0.982 Dense forest Granivore 2.58 1.614 1.204 0.796 Dense forest Carnivore 0.21 00 00 00 Dense forest Frugivore 3.87 2.816 2.422 0.959 Dense forest Insectivore 5.37 3.543 4.039 0.968 Dense forest Nectarivore 1.07 1.371 1.243 0.840 Moderate forest Omnivore 3.99 2.462 1.054 0.987 Moderate forest Granivore 2.99 1.382 1.361 0.821 Moderate forest Carnivore 00 00 00 00 Moderate forest Frugivore 3.91 1.211 0.923 0.211 Moderate forest Insectivore 1.94 1.352 0.893 0.672 Moderate forest Nectarivore 3.95 2.765 2.111 0.891 Open forest Omnivore 1.70 1.231 2.111 0.132 Open forest Granivore 0.56 0.987 1.231 0.561 Open forest Carnivore 00 00 00 00 Open forest Frugivore 1.70 0.918 0.918 0.889 Open forest Insectivore 1.70 1.241 1.820 1.00 Open forest Nectarivore 1.13 0.671 0.829 0.212 Agriculture Omnivore 25.33 1.875 1.688 0.758 Agriculture Granivore 14.47 1.739 1.335 0.775 Agriculture Carnivore 00 00 00 00 Agriculture Frugivore 7.23 0.971 0.434 0.960 Agriculture Insectivore 1.44 0.918 0.910 0.889 Agriculture Nectarivore 00 00 00 00

APPENDIX 262 Appendix: II Density, diversity, richness and evenness of bird guilds in different habitats in KWA Habitat Guild Density Diversity Richness Evenness Dense forest Insectivore 13.69 2.750 2.885 0.984 Dense forest Frugivorous 00 00 00 00 Dense forest Granivore 00 00 00 00 Dense forest Omnivore 0.076 00 00 00 Dense forest Carnivore 00 00 00 00 Moderate forest Insectivore 21.06 3.013 2.762 0.950 Moderate forest Granivore 7.61 1.295 0.869 0.950 Moderate forest Omnivore 10.50 1.914 1.559 0.858 Moderate forest Frugivorous 3.84 1.0000 0.721 1.0000 Open forest Insectivore 12.73 2.62 2.288 0.090 Open forest Frugivorous 5.54 1.189 0.805 0.729 Open forest Granivore 3.50 0.961 0.390 0.947 Open forest Omnivore 1.65 1.224 0.910 0.741 Open forest Carnivore 0.079 00 00 00 Agriculture Insectivore 23.15 2.954 2.588 0.853 Agriculture Granivore 19.42 1.723 1.108 0.853 Agriculture Frugivorous 7.57 00 00 00 Agriculture Omnivore 14.31 2.927 2.768 0,951

APPENDIX 263 Appendix: III Checklist of birds recorded in Dabka Watershed Area S. No. Common Name Scientific Name Accipitridae 1 Black kite Milvus migrans 2 Black shouldered kite Elanus caeruleus 3 Creasted serpent eagle Spilornis cheela 4 Mountain hawk eagle Spizaetus nipalensis 5 Tawny eagle Aquila rapax 6 Shikra Accipiter badius 7 Eurasian sparrowhawk Accipiter nisus 8 Himalayan giffron Gyps himalayensis

Falconidae 9 Orientel hobby Falco severus

Phasianidae 10 Black francolin Francolinus francolinus 11 Grey francolin Francolinus pondicerianus 12 Kalij pheasant Lophura leucomelanos 13 Indian peafowl Pavo cristatus 14 Red jungle fowl Gallus gallus

Charadriidae 15 Red wattled lapwing Vanellus indicus

Columbidae 16 Eurasian collard dove Streptopelia decaocto 17 Oriental turtle dove Streptopelia orientalis 18 Red collarad dove Streptopelia tranquebarica 19 Spotted dove Streptopelia chinensis 20 Speckled wood pigeon Columba hodgsonii 21 Rock pigeon Columba livia 22 Wedge tailed green pigeon Treron sphenura

Psittacidae 23 Plum headed parakeet Psittacula cyanocephala 24 Rose ringed parakeet Psittacula krameri 25 Slaty headed parakeet Psittacula himalayana

Cuculidae 26 Indian cuckoo Cuculus micropterus

Strigidae 27 Brown wood owl Strix leptogrammica

APPENDIX 264 Alcedinidae 28 White throated kingfisher Halcyon smyrnensis

Meropidae 29 Blue tailed beeater Merops philippinus 30 Green bee eater Merops orientalis

Coraciidae 31 Common hoopoe Upupa epops

Capitonidae 32 Blue throated barbet Megalima asiatica 33 Brown headed barbet Megalaima zeylaniea 34 Golden throated barbet Megalaimafranklinii 35 Great barbet Megalaima virens 36 Lineated barbet Megalaima lineata

Picidae 37 Brown fronted woodpecker Dendrocopos auriceps 38 Fulvous breasted woodpecker Dendrocopos macei 39 Grey capped pygmy woodpecker Dendrocopos canicapillus 40 Himalayan flameback Dinopium shorii 41 Himalayan woodpecker Dendrocopos himalayensis 42 Lesser yellownape Picus chlorolophus 43 Rufous belleid woodpecker Dendrocopos hyperythrus 44 Striped breasted woodpecker Dendrocopos atratus

Eurylaimidae 45 Long tailed broadbill Psarisomus dalhousiae

Hirundinidae 46 Bam swallow Hirundo rustica 47 Nepal house martin Delichon nipalensis 48 Red rumped swallow Hirundo daurica

Laniidae 49 Bay backed shrike Lanius vittatus 50 Long tailed shrike Lanius schach

Oriolidae 51 Maroon oriole Oriolus traillii

Dicruridae 52 Ashy drongo Dicrurus leucophaeus 53 Black drongo Dicrurus macrocercus 54 Bronzed drongo Dicrurus aeneus

APPENDIX 265 55 Crow billed drongo Dicrurus annectans 56 Lesser racket tailed drongo Dicrurus remifer

Sturnidae 57 Asian pied starling Sturnus contra 58 Brahminy starling Sturnus pagodarum 59 Chestnut tailed starling Sturnus malabaricus 60 Common myna Acridotheres tristis 61 Jungle myna A cridotheres fuscus 62 Spot winged starling Saroglossa spiloptera

Corvidae 63 Black headed jay Garrulus lanceolatus 64 Eurasian jay Garrulus glandarius 65 Red billed blue magpie Urocissa erythrorhyncha 66 House crow Corvus splendens 67 Large billed crow Corvus macrorhynchos 68 Grey treepie Dendrocittaformosae

Campephagidae 69 Bar winged flycatcher shrike Hemipus picatus 70 Long tailed minivet Pericrocotus ethologus 71 Scarlet minivet Pericrocotus flammeus White throated fantail Rhipidura albicolis

Irenidae 72 Orange bellied leafbird Chloropsis hardwickii

Pycnonotidae 73 Ashy bulbul Hemixos Jlavala 74 Black bulbul Hypsipetes leucocephalus 75 Black creasted bulbul Pycnonotus melanicterus 76 Himalayan bulbul Pycnonotus leucogenys 77 Red vented bulbul Pycnonotus cafer 78 Red wiskered bulbul Pycnonoyus jocosus 79 Grey breasted prinia Prinia hodgsonii 80 Plain prinia Prinia inornata 81 Straited prinia Prinia criniger

Muscicapidae Subfamily Timaliinae . 82 Black chined babbler Stachyris pyrrhops 83 Chestnut capped babbler Timalia pileata 84 Jungle babbler Turdiodes striatus 85 Large grey babbler Turdoides malcolmi

APPENDIX 266 86 White browed shrike babbler Pteruthius flaviscapis 87 Rufous sibia Heterophasia capistrata 88 Chestnut crowned laughing thrush Garrulax erythrocephalus 89 Plain backed thrush Zoothera mollissima 90 Straited laughing thrush Garrulax striatus 91 Streaked laughing thrush Garrulax lineatus 92 Tickell's thrush Turdus unicolor 93 White creasted laughing thrush Garrulax leucolophus 94 White throated laughing thrush Garrulax albogularis 95 Whiskered yuhina Yuhina flavicollis Sub family Muscicapinae 96 Asian brown flycatcher Muscicapa dauurica 97 Asian paradise flycatcher Terpsiphone parodist 98 Blue throated flycatcher Cyornis rubeculoides 99 Dark sided flycatcher Muscicapa sibirica 100 Grey headed canary flycatcher Culicicapa ceylonensis 101 Little pied flycatcher Ficedula westermarmi 102 Pale blue flycatcher Cyornis unicolor 103 Ultramarine flycatcher Ficedula superciliaris 104 Verditer flycatcher Eumyias thalassina 105 Rufous bellied niltava Niltava sundara Subfamily Sylviinae 106 Aberrent bush warbler Cettia flavolivacea 107 Ashy throated warbler Phylloscopus maculipennis 108 Golden speckeld warbler Seicercus burkii 109 Greenish warbler Phylloscopus trachiloides 110 Grey hooded warbler Seicercus xanthoschistos 111 Hume's warbler Phylloscopus humei 112 Large billed leaf warbler Phylloscopus magnirostris 113 Tickell's leaf warbler Phylloscopus affinis 114 Common tailer bird Orthotomus sutorius 115 Mountain chifchaf Phylloscopus sindianus Sub family Turdinae 116 Indian robin Saxicoloides fulicata 117 Orientle magpie robin Copsychus saularis 118 White tailed robin Myiomela leucura 119 Black redstart Phoenicurus ochruros 120 Blue capped redstart Phoenicurus coeruleocephalus 121 Plumbeous water redstart Rhyacornis fuliginosus 122 White throated redstart Phoenicurus schisticeps 123 Blue capped rockthrush Monticola cinclorhynchus 124 Blue whisling thrush Myophonus caeruleus 125 Pied thrush Zoothera wardii 126 Grey winged blackbird Turdus boulboul

APPENDIX 267 127 White-collared black bird Turdus albocinctus 128 Common stone chat Saxicola torquata 129 Grey bushchat Saxicolaferrea 130 Jerdon's bushchat Saxicola jerdoni 131 Pied bushchat Saxicola caprata 132 Little forktail Enicurus scouleri 133 Spotted forictaiJ Enicurus maculatus 134 Grey bellied tesia Tesia cyaniventer

Paridae 135 Black lored tit Parus xanthogenys 136 Black throated tit Aegithalos concinnus 137 Great tit Parus major 138 Green backed tit Parus monticolus 139 Rufous vented tit Paras rubidiventris 140 White-throated tit Aegithalos niveogularis

Sittidae 141 Chestnut bellied nuthatch Sitta castanea 142 White tailed nuthatch Sitta himalayensis

Certhidae 143 Eurasian treecreeper Certhiafamiliaris 144 Rusty flanked treecreeper Certhia nipalensis

Motacillidae 145 Grey wagtail Motacilla cinerea

Zosteropidae 146 Oriental white-eye Zosterops palpebrosus

Nectariniidae 147 Crimson sunbird Aethopyga siparaja 148 Purple sunbird Nectarinia asiatica Ploceidae Sub Family Passerinae 149 House sparrow Passer domesticus 150 Russet sparrow Passer rutilans Sub family Estrildinae 151 Scaly breasted munia Lonchura punctulata 152 White rumped munia Lonchura straita

Fringillidae 153 Common rosefmch Carpodacus erythrinus 154 Plain mountain finch Leucosticte nemoricola

APPENDIX 268 155 Vinaceous rosefinch Carpodacus vinaceus 156 Yellow breasted green finch Carduelis spinoides

Emberizidae 157 Creasted bunting Melophus lathami

APPENDIX 269 Appendix: IV Checklist of birds recorded in Khulgarh Watershed Area

S.No Common Names Scientific Names Accipitridae 1 Black eagle Ictinaetus malayensis 2 Crested serpent eagle Spilornis cheela 3 Black kite Milvus migrans 4 Shikra Accipiter badius

Phasianidae 5 Grey francolin Francolinus pondicerianus 6 Khalij Pheasent Lophura leucomelanos 7 Red Jungle fowl Gallus gallus

Charadriidae 8 Red wattled lapwing Vanellus indicus

Columbidae 9 Eurasian collard dove Streptopelia decaocto 10 Oriental turtle dove Streptopelia orientalis 11 Spotted dove Streptopelia chinensis 12 Rock pigeon Columba livia 13 Wedge tailed green pigeon Treron sphenura

Psittacidae 14 Rose ringed parakeet Psittacula krameri 15 Plum headed parakeet Psittacula cyanocephala

Cuculidae 16 Greater coucai Centropus sinensis 17 Eurasian cuckoo Cuculus canorus 18 Indian cuckoo Cuculus micropterus

Strigidae 19 Collared owlet Glaucidium brodiei

Alcedinidae 20 Common kingfisher Alee do atthis

Meropidae 21 Blue tailed beeater Merops philippinus 22 Green bee eater Merops orientalis

Upupidae 23 Common hoopoe Upupa epops

APPENDIX 270 Capitonidae 24 Blue throated barbet Megalima asiatica 25 Great barbet Megalaima virens

Picidae 26 Grey capped pygmy woodpecker Dendrocopos canicapillus 27 Brown fronted woodpecker Dendrocopos auriceps 28 Great slaty woodpecker Mulleripicus pulverulentus 29 Lesser yellownape Picus chlorolophus 30 Scaly bellied woodpecker Picus squamatus 31 Streak throated woodpecker Picus xanthopygaeus

Alaudidae 32 Oriental skylark Alauda gulgula

Hirundinidae 33 Bam Swallow Hirundo rustica 34 Red rumped swallow Hirundo daurica

Laniidae 35 Bay-backed shrike Lanius vittatus 36 Brown Dipper Cinclus pallasii

Dicruridae 37 Black drongo Dicrurus macrocercus 38 Spangled drongo Dicrurus hottentottus

Sturnidae 39 Bank myna Acridotheres ginginianus 40 Common myna Acridotheres tristis

Corvidae 41 Black headed jay Garrulus lanceolatus 42 Eurasian jay Garrulus glandarius 43 Grey treepie Dendrocitta formosae 44 Rufous treepie Dendrocitta vagabunda 45 Large billed crow Corvus macrorhynchos

Campephagidae 46 Small minivet Pericrocotus cinnamomeus 47 Scarlet minivet Pericrocotus flammeus

Pycnonotidae 48 Black bulbul Hypsipetes leucocephalus 49 Himalayan bulbul Pycnonotus leucogenys 50 Red vented bulbul Pycnonotus cafer

APPENDIX 271 51 Grey breasted prinia Prinia hodgsonii

Muscicapidae Sub family Timaliinae 52 Jungle babbler Turdiodes striatus 53 Chestnut-capped babbler Timalia pileata 54 White browed scimitar babbler Pomatorhinus schisticeps 55 Yellow-eyed babbler Chrysomma sinense 56 Streaked laughing thrush Garrulax lineatus 57 Chestnut-crowned laughingthrush Garrulax erythrocephalus 58 Variegated laughingthrush Garrulax variegatus 59 White throated Laughingthrush Garrulax albogularis Sub Family Muscicapinae 60 Asian brown flycatcher Muscicapa dauurica 61 Asian Paradise Flycatcher Terpsiphone paradise 62 Grey headed canary flycatcher Culicicapa ceylonensis 63 Pale-blue flycatcher Cyornis unicolor 64 Rusty-tailed flycatcher Muscicapa ruficauda 65 Slaty blue flycatcher Ficedula tricolor 66 Verditer flycatcher Eumyias thalassina 67 Common woodshrike Tephrodornis pondicerianus Sub family Sylviinae 68 Aberrent bush warbler Cettia flavolivacea 69 Greenish warbler Phylloscopus trachiloides 70 Grey hooded warbler Seicercus xanthoschistos Sub family Turdinae 71 Rusty-bellied shortwing Brachypteryx hyperthra 72 White browed shortwing Brachypteryx montana 73 Blue-fronted redstart Cinclidium frontalis 74 Common stone chat Saxicola torquata 75 Grey bushchat Saxicola ferrea 76 Pied bushchat Saxicola caprata 77 Blue capped rockthrush Monticola cinclorhynchus 78 Blue whisling thrush Myophonus caeruleus 79 Mistle Thrush Turdus viscivorus 80 Orientle magpie robin Copsychus saularis 81 Spotted forktail Enicurus maculatus 82 White-rumped shama Copsychus malabaricus

Paridae 83 Black lored tit Parus xanthogenys 84 Black throated tit Aegithalos concinnus 85 Great tit Parus major 86 Green backed tit Parus monticolus

272 Sittidae 87 Chestnut bellied nuthatch Sitta castanea

Certhiidae 88 Bar-tailed tree-creeper Certhia himalayana 89 Eurasian treecreeper Certhiafamiliaris

Motacillidae 90 Olive backed pipit Anthus hodgsoni 91 Upland pipit Anthus sylvanus 92 White-browed wagtail Motacilla maderaspatensis

Dicaeidae 93 Thick billed flowerpecker Dicaeum agile

Zosteropidae 94 Oriental white-eye Zosterops palpebrosu.

Nectariniidae 95 Purple sunbird Nectarinia asiatica

Ploceidae Sub family Passerinae 96 House sparrow Passer domesticus 97 Russet sparrow Passer rutilans Sub family Estrildinae 98 Red avadavat Amandava amandava 99 Scaly breasted munia Lonchura punctulata

Fringiliidae Sub family Fringillinae 100 Beautiful rosefinch Carpodacus pulcherri

Emberizidae 101 Creasted bunting Melophus lathami 102 White-capped bunting Emberiza stewarti

APPENDIX 273 Appendix: V Checklist of mammalian species recorded in Dabka Watershed Area Common Names Scientific Names Rhesus macaque Rhesus macaque Common langur Presbytis entellus Jackal Canis aureus Red fox Vulpus vulpus Sambar Cervus unicolor Serow Capricornis sumatraensis Goral Nemorhaedus goral Barking deer (Muntjac) Muntiacus munjak Yellow Throated Marten Martes flavigula Indian wild boar Sus scrofa Indian porcupine Hysterix indica Leopard Panther a pardus Tiger Panthera tigris

Appendix: VI Checklist of mammals recorded in Khulgarh Watershed Area Common names Scientific names Rhesus Macaque Presbytis entellus Barking Deer Macaca mulatto Red fox Vulpes vulpes Indian Porcupine Muntiacusmuntjak Leopard Hystrix indica Jackal Panthera pardus Common Langur Canis aureus

APPENDIX 27A Appendix: VII Checklist of reptile species recorded in Dabka Watershed Area

Common Names Scientific Names Brahminy skink Mubaya carinata Common garden lizard Mubaya ladacensishimalayanus Giinther Calotes versicolor Kashmir agama Laudakia tuberculata Little skink Mubaya macularia Northern house gecko Hemidactylus flaviviridis Buff striped keel back Amphiasma stolata Indian Gamma or Cat snake Bioga trigonata Vine snake Ahaetulla nasuta Indian cobra Naja naja Russels viper Daboia russelii Common Indian krait Bungarus caeruleus Himalayan Pit Viper Ancistrodon himalayanus Trinket snake Elaphe Helena Indian Python Python molurus

Appendix: VIII Checklist of reptile species recorded in Khulgarh Watershed Area Common Names Scientific Names Kashmir agama Laudakia tuberculata Forest calote Calotes rouxi Common garden lizard Calotes versicolor Peninsular rock agama Psammophilus dorsalis Little Skink Mabuya macularia Snake skink Lygosoma punctatus Common Indian Krait Bungarus caeruleus Rat snake Ptyas mucossus Pit viper Daboia russelii Indian cobra Naja naja Common kukri snake Oligodon arnensis

APPENDIX 275 Appendix: IX Checklist of Amphibian species recorded in Dabka Watershed Area

Common Names Scientific Names Common Indian toad Bufo melanostictus Himalayan toad Bufo himalayanusgiinther Skittering frog Euphlystic cyanophlyc Himalayan Torrent Amolops marmoratus Jerdon's bull frog Hoplobatrachus crasssus

Appendix: X Checklist of Amphibian species recorded in Khulgarh Watershed Area Common Name Scientific Name Skittering Frog Euphlystic cyanophlyc Common Indian toad Bufo melanostictus Himalayan toad Bufo himalayanusgiinther Indian bull frog Hoplobatrachus tigerinus

APPENDIX 276