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Item Conservation of red junglefowl Gallus gallus in India : final report(Wildlife Institute of India, Dehradun, 2012) Sathyakumar, S.; Fernandes, Merwyn; Mukesh; Kaul, R.; Kalsi, R.S.The Red Junglefowl (RJF) is believed to be the wild ancestor of all domestic chicken in the world. there still exist a strong ethno-cultural bond where the wild males are used to invigorate the domestic stock in order to enhance the first generation individuals that are used in the context of cultural and religious relevance. Concerns were raised on the genetic endangerment of RJF due to introgression of domestic genes into the wild population. There needs to address these concerns and maintain uncontaminated RJF population in wild and captivity. keeping this in view, the Wildlife Institute of India, carried out a research project from 2006 to 2011 in two phases that dealt with status, distribution, genetic diversity, interactions between wild RJF and domestic chicken and introgression of domestic genes into the wild and captive stocks. The RJF listed in the “Least Concern” category of IUCN with an extent of occurrence of about 5,100,000 km2. One of the subspecies G g murghi has its distribution within India. In order to address the issues of status and distribution we resorted to using presence-only models. These models overcome the cost and time constraints when dealing with a large ranging species. Species site locations were all collated by using primary field data, network of field biologist, literature records, museum specimens and archived databases. A total of 500 georectified data points were used along with predictable variables such as bioclimatic factors, digital elevation model and forest cover. These variables were used to run maximum entropy models using the product function, the test data has an AUC score of 0.979, the jackknife test for variable importance was annual precipitation and precipitation of the driest quarter that contributed 46% to the model. The total predicted probability suitable area in India is approx 354,978 km2. There are three distinct landscapes within India namely north (12%), central (52%) and northeastern (36%).The central landscape is isolated and does not connect either to the north or northeastern landscape. The north and northeastern landscape is connected to each other through the forest patches in Bhutan and Nepal. PA network accounts for nearly 13% of the area with the National Parks (34) representing 4.32% and the Wildlife Sanctuaries (135) representing 8.52%, while nearly 90% of the area lies outside the purview of the PA network system. The species is still reported from 205 districts out of the 270 districts in range 21 states. Genetic diversity, population differentiation and phylogenetic analysis of RJF populations were assessed in 19 RJF range states of India. In total, 385 samples (306 RJF & 79 domestic chickens) were collected and genotyped with 26 microsatellite markers. Altogether, 628 alleles were observed across five RJF and one domestic chicken population. Observed and effective number of alleles ranged from 9 to 49 and 2.96 to 12.40 with mean (± s.e.) number of alleles 24.15 (± 8.31) and 6.50 (± 2.71), respectively. Effective number of alleles was less than the observed number of alleles for all the loci. The overall observed heterozygosity ranged from 0.23 and 0.79, with mean value of 0.52 ± 0.13, while expected heterozygosity ranged 0.62 to 0.92 with mean value of 0.82 ± 0.08. PIC value ranged from 0.56 to 0.91 with mean value 0.80 (±0.09) and therefore all microsatellite markers were informative in the present study. Mean observed number of alleles & mean observed heterozygosity was highest in Northern RJF population, i.e. Na 21.12 ±7.14 & Ho 0.61 ±0.17 and lowest in central RJF population, i.e. Na 1.92 ±0.89 & Ho 0.35 ±0.42, respectively. Total number of private alleles ranged from 1 to 179 in South-Eastern and Northern RJF population, respectively while no private was found in Central RJF population. The analysis of molecular variance (AMOVA) revealed a total of 6% variation was attributed to among populations while 94% variance was within population. The minimum population differentiation or maximum gene flow was between Northern and Eastern RJF population (Nm 10.846) while maximum population differentiation or minimum gene flow was between Central and Eastern RJF population (Nm 0.911). The overall, Nm values were quite high, suggesting the high gene flow among RJF populations. Nei's genetic distance indicated that the Central Indian RJF population is least similar or most distant (DA= 0.942) with domestic chicken, while the northeastern RJF population is most identical or least genetically distant (DA = 0.255) with domestic chicken. The UPGMA dendrogram was generated based on Nei’s genetic distance. The RJF populations in India formed three clusters: (i) central and southeastern, (ii) northern and eastern, and (iii) northeastern and domestic chicken. The multi-factorial correspondence analysis also revealed the similar pattern of clustering the RJF populations. In order to study interactions, observation were recorded from 13 sites with mixed groups all observations were in the pre-dawn hours. A total of 51 encounters were recorded. The interest was to elucidate whether an interaction between the wild and domestics fowls was mutualistic or agnostic during the breeding and nonbreeding season. From the 10 observation recorded during the breeding season there were no interaction between the wild and feral population suggesting that there might be a spatial segregation between these two populations. While interactions during the nonbreeding season suggest that that males are intolerable to each other when in close proximity, while the females are tolerated and move about freely within the groups. Genetic characterisation and maintaining studbooks is the key step towards formulating management action plan for conservation breeding or release program for any captive species. We collected 220 RJF samples (blood/feathers) from 14 captive centers and investigated population genetic structure and admixture analysis of RJF with domestic chicken using 23 highly polymorphic microsatellite markers. Bayesian clustering analysis revealed three distinct groups that indicated the genetic integrity among the birds of 14 centers. We presumed genetic integrity would have been resulted due to exchange of birds between zoos or the founders would have been introduced from the same wild population. The global performance of STRUCTURE assigning individuals was 169/220=76.81% while 8.63% individuals remained unassigned to any of three clusters. Each RJF stock was independently investigated for admixture analysis with a pooled domestic chicken population and ten birds were found to be hybrids out of 220 birds collected from 14 captive centers. based on the study, we recommend the following As this study could not survey all areas within RJF’s distribution range, we suggest that there is a need to increase efforts to understand whether the species is prevalent within forested tracts outside the PA network, especially Bihar, Haryana, Punjab, Sikkim and Uttar Pradesh where the present distribution is highly fragmented with growing pressures on the existing PA of these States. Similarly, in the States of Andhra Pradesh, Jammu & Kashmir and Maharashtra, extensive field surveys should be carried out to ascertain the presence/absence and exact distribution limits of RJF as these States encompass the limits or edges of the distribution range of this species. Special focus surveys/studies are required at range overlaps between G.g. murghi and G.g. spadiceus (northeastern States) and also between RJF and Grey Junglefowl (central India). Based on our samples collected from zoos/captive centres (Table 5.1), admixed bird were identified (Table 5.4). These admixed individuals (hybrids between RJF and domestic chicken) that are kept in zoos/captive centres should be removed from these captive stocks to avoid any further hybridisation. They should not be exchanged with any other zoos/captive centres and should not be released back into the wild. The list of individual birds in the zoos/captive centres that have been identified as ‘not admixed’ have been provided to these centres. For RJF individuals in zoos/captive centres that were not sampled during the study or born or added after the sampling, similar genetic analysis should be carried out. Such individuals should not be used /exchanged for any breeding programme. As there are chances of silent breeding between RJF and domestic chicken, hence the use of domestic hens as foster parents should be avoided.Item Identifying delineating and mapping areas with high conservation values and developing management recommendatons/plans for SECURE Himalaya landscapes in Himachal Pradesh(Wildlife Institute of India, Dehradun, 2021) Lyngdoh, Salvador; Sathyakumar, S.; Bhatnagar, Y.V.; Singh, N.; Yadav, S.N.High Conservation Value Areas (HCVAs) is an emerging concept used to identify important areas based on a variety of parameters including biodiversity, landscape context, threatened or endangered ecosystems, provisioning of basic ecosystem services, and dependence of local communities. The assignment aims to Identify High Conservation Value (HCV) categories of areas in the project landscape of Himachal Pradesh, delineate their boundaries and map them, and suggest relevant recommendations with respect to the potential threats prevalent in the areas, specific for each HCV category. The Ministry of Environment, Forest and Climate Change (MoEFCC), Government of India along with UNDP has implemented a GEF funded project: SECURE Himalaya (Securing livelihoods, conservation, sustainable use and restoration of high range Himalayan ecosystems). The project aims to promote sustainable land management in alpine pastures and forests in Indian Himalayan ecosystems for conservation of snow leopard and other endangered species and their habitats and sustaining ecosystem services. The project SECURE Himalayas would be implemented over a period of six years in the high-altitude trans-Himalayan region, which covers an area of about 184,823 km2 representing 5.62 percent of the total geographic area of the country. The selected landscape for the project is Lahaul-Pangi & Kinnaur Landscape in Himachal Pradesh. The Himalayan ecosystem in India is of critical importance for its immense biological, sociocultural, and hydrological values. The biodiversity and ecosystems that it harbours form an important life-support system for a large number of agro-pastoral communities that depend on it. However, these natural ecosystems are under severe threat from high dependence of local communities on natural resources. The major threats as identified in the landscape are intensive grazing of the pasturelands by domestic livestock, inter-specific competition between wild ungulates and domestic livestock, human-wildlife conflict resulting in crop destruction and depredation of livestock, over-harvesting and illegal extraction of medicinal and aromatic plants by intruders, over-exploitation of natural resources and uncontrolled conventional tourism interfering with the fragile ecosystems and the wildlife of the area. The current assignment identifies and delineate the potential high conservation value areas in the landscape through a knowledge-based approach i.e. data compilation, remote sensing & GIS approach, and ground truthing. The information is presented through the appreciation and understanding of the study sites by short-listing of areas of high conservation value and their management regimes. We reviewed 101 documents (74 peer reviewed and 27 unpublished) pertaining to the subject, and concept of high conservation value forests. Remote sensing and GIS data was used to generate various layers like digital elevation model (DEM), land-use land cover (LULC), drainage network, road network, protected areas network, distribution, occupancy maps of species, forest cover, slope and maps of villages in the landscape in concern. With the help of the secondary data and various GIS layers, potential high conservation value areas were identified and mapped in the remote sensing and GIS environment. Through ‘ground truthing’ of the available data and stakeholder consultations followed by field visits to the potential areas, 28 villages were visited, 13 in Lahaul and 15 in Pangi valley. Village level meetings were organized and data were collected using semi-structured open-ended questionnaire, for validation of potential high conservation value areas (HCVAs). Key informants were identified and interviewed for further validation and verification for HCVAs. A presence survey was conducted in the landscape to understand mammalian species distribution by using a combination of direct and indirect methods. Direct methods were based on visualencounters of animals whereas indirect methods relied on quantification of indirect evidences such as animal feces (pellet groups, scats, droppings), tracks (pug marks, hoof marks, scrapes) and other signs (feeding/ digging). Since all the areas surveyed were located at higher altitudes on steep and uneven terrain, the trails in the forests and alpine regions were surveyed. A total of 79 trails (1 km each), were surveyed, 25 in Lahaul, and 54 in Pangi. A total of 17 areas with high potential for conservation were identified in the entire landscape, 11 in Lahaul valley, namely, Miar valley, Naingar & Neelkanth lake, Billing-Istingri, Darcha-Jispa, Koksar, Kuruched, Hadsar, Chandratal lake, Mrikula Mata temple, Trilokinath temple, Kardang monastery; and 6 areas in Pangi, Sural Bhatori & Sural Gompa, Hudan bhatori, Kadu nallah, Sechu Tuan, Luj and Mindhal. Consequent upon these consultations and ground verification, biodiversity values and associated threats to these biodiversity values have been identified for each of the short-listed area of high conservation value and relevant recommendations prepared. It is proposed that in order to conserve the integrity of each HCVA type the status of the land in concern needs to be ascertained. The key recommendations towards this end include- 1) Demarcation of critical areas within the short-listed areas of high conservation values to serve as important livelihood source for herder communities; 2) Integrated pastureland management regimes to reduce the pressure on the pastures, and provide some time for restoration; 3) Anti-predatory livestock management through fences and other barriers, human-accompanied herding of livestock to reduce livestock losses is recommended; also, the strategies suggested by the SECURE-HWC (human-wildlife conflict) project in Lahaul-Pangi landscape, shall be followed. 4) Enhanced training to the key stakeholders concerning the extraction, harvesting and sustainable use of medicinal and aromatic plants; 5) Enhanced collaboration between the enforcement agencies (like the forest department and security forces) for improved surveillance to identify, monitor and prevent illegal activities. 6) Policy harmonization for potential HCVAs in the form of recognizing such areas as Community Conservation Reserve, Biodiversity Heritage Sites or Medicinal Plant Conservation and Development Areas.