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Item Preliminary assessment of tigers, co-predators and prey in Pranhita Wildlife Sanctuary, Maharashtra, India for exploring options for conservation translocation(Wildlife Institute of India, Dehradun, 2020) Habib, B.; Nigam, P.; Joshi, K.; Panwar, P.As part of the project “Preliminary assessment of tigers, co-predators and prey species in Pranhita Wildlife Sanctuary, Maharashtra, India for exploring options for conservation translocation”, the study was carried out in Pranhita Wildlife Sanctuary in Gadchiroli district of Maharashtra. The fieldwork was carried from January 2019 to June 2019 covering an area of 418.85 km2 in southern Gadchiroli. The Eastern Vidarbha Landscape (EVL) holds a high density of carnivores both inside and outside protected areas leading to an increase in human-wildlife interactions. Pranhita Wildlife Sanctuary (PWLS) is a part of EVL and could be an important corridor. To explore new habitats for carnivore species, we conducted a preliminary assessment of tigers, co-predators, and prey in PWLS. The sanctuary mainly is dominated by Southern Tropical Dry Deciduous forest. We conducted carnivore and ungulate sign surveys and deployed camera traps (n=25) in 40 km2 area in Bahmni range. The area was divided into different 1.42 × 1.42 km2 grids and at least one pair of camera trap was placed in each 2.0164 km2 grid at 20 sites and operated for 24-27 days in Bahmni range. Apart from that random camera traps were placed at 5 sites in Kamlapur and Pranhita ranges for 1 to 7 days during the study period. The camera traps sampling effort was 1030 trap nights and around 33000 images were captured. For prey species density estimation, 24 line transects of 2 km length were walked in 43 beats with 5-7 replicates. For vegetation quantification, we laid a total of 144 circular plots of a 10-meter radius and recorded 43 trees, 37 shrubs, and 13 grass species. We used both spatial and temporal data for occupancy estimation. Data were analyzed using the software Presence for occupancy estimation and Distance 7.2 for density estimation. A total of 10 carnivore species were recorded directly or indirectly during the study period. According to the IUCN Red List of threatened species, 2 are Endangered and Near Threatened, and 2 are vulnerable. The major carnivore species are leopard, Asiatic wild dog, sloth bear, Indian grey wolf, jungle cat, Indian fox, and rusty-spotted cat. The occupancy estimate (ψ) of leopard in the null model was 0.20 while for other carnivore species like sloth bear, jungle cat and wild dog were 0.70, 0.74, and 0.68 percent respectively. A total of 14 prey species were recorded during the line transect and sign survey. The major prey species are sambar, Indian gaur, chousingha, Indian giant squirrel, chital, wild pig, nilgai, barking deer, langur sp., rhesus macaque, and Indian peafowl. Among these, 3 species are listed as Vulnerable and 1 as Near Threatened by IUCN Red List. Overall density estimation of major ungulate species was 14.82/km2. The encounter rate of cattle was 0.17/km, nilgai 0.039/km, chital 0.059/km, chousingha 0.016/km, and wild pig 0.022/km. Individual density estimate of major ungulate species like chital 2.27/km2, wild pig 11.55/km2, nilgai 0.72/km2, langur 0.55/km2, Indian hare 1.78/km2, peafowl 0.44/km2, grey jungle fowl 1.87/km2, chousingha 0.28/km2 and cattle were 28.61/km2. Occupancy estimate of ungulate species like sambar 0.27%, chital 0.44%, chousingha 0.51%, Indian gaur 0.07% and nilgai were 0.59%. The major threats in the sanctuary areas are hunting for local consumption, tree cutting, livestock grazing, forest fire, roadkill, and electrocution. We have got 28 % usable images of cattle grazing and 4 % of hunting. Other administrative lacunas are impractical beat boundaries, unequipped frontline staff, lack of legal action against the guilty, inadequate infrastructure, lack of training and capacity building. There is a consistent trepidation of left-wing extremism in the minds of locals and forest officials. It prevents or demotivates them from working efficiently in the PWLS. These activities directly or indirectly affect wildlife conservation and management in PWLS. This was the first-ever scientific study conducted to document prey and predator presence in PWLS. Further detailed and long-term studies are required for a better understanding of species ecology and their habitat. Such studies will help not only in better management and conservation of species in the area but also in decision-making on conservation translocations. Based on the preliminary study and SWOT analysis following are measures to be taken before translocation of any large carnivore species to Pranhita Wildlife Sanctuary: 1. Capacity building of local staff for effective wildlife management.2. Enhancement of protection measures in the Sanctuary to reduce poaching, hunting, and other illegal activities. 3. Habitat improvement by grassland management and eradication of lantana and other invasive species. 4. Reducing threats due to electrocution by illegal power fences used for local hunting and protection of crop fields by local farmers. 5. Special forest protection force for Gadchiroli considering extremism issues.6. Augmentation of the prey base to enhance fast recovery of prey species.7. Maintaining full-strength dedicated forest staff across all range offices of the division.8. Building infrastructure such as patrolling roads, forest chowkis etc., across the sanctuary.9. Involving local people in conservation measures across the sanctuary.10. Establishment of local ecodevelopment committees. 11. Wildlife-oriented management across the Gadchiroli forest division.12. The special financial package for Gadchiroli for enhancing wildlife-oriented management.13. Mitigation measures on the existing roads through the sanctuary and other critical wildlife corridors across the division.14. Implementation of Shyamaprasad Mukherjee Jan Van Vikas Scheme for development of villages across the forested landscape of Gadchiroli to achieve sustainable development of these villages and reduce the man-animal conflict.15. Identification of potential areas within the district for designation as Sanctuary, National Park, Conservation Reserve, Community Reserve.Item Status of tigers, copredator and prey in Bor Tiger Reserve, Maharashtra, India 2021(Wildlife Institute of India, Dehradun, 2022) Habib, Bilal ; Nigam, P.; Govekar, R.; Ramanujam, M.; Gawai, R.; Dabholkar, Y.; Bhowmick, I.SummaryThe Phase IV monitoring exercise as a part of the project “Long Term Monitoring of Tigers-predators and prey in tiger reserves and other bearing areas of Vidarbha, Maharashtra, for Bor Tiger Reserve was conducted from December 2020-May 2021. This exercise, having three main objectives, the status of prey, estimation of minimum tiger and leopard numbers, and capacity building among staff flagged off with a capacity-building workshop in December 2020. Line transects surveys aimed to estimate the density of prey species were carried out in two blocks with an effort of 7 days for each transect line. In the core area among all the prey species, the highest density was recorded for Chitals 7.14 (±4.44)/km2 followed by Sambar 6.45 (±2.26)/km. sq. and Nilgai 2.53(±0.67)/km2.In the buffer area, the highest density was recorded for wild pigs 5.75 (±1.26)/km2 among all the ungulate species. The density of other species includes Chital 0.81 (±0.22), Sambar 0.40 (±0.15), Nilgai 4.72 (±0.58), Peafowl 2.56 (±0.54), Langur 19.09 (±2.49).Camera trapping based on the spatial capture-recapture framework was conducted on the same locations of the same grids (2 km2) similar to the previous cycle (2020) which were selected based on a rigorous sign survey that provided sign encounters of tiger, leopard, and other co-predators. This year both core and buffer areas were covered in two blocks with 211 active camera trap stations during February 2021-May 2021. The effort resulted in 7572 trap nights. The number of individual tigers captured was 9 along with 46 leopards. Tiger density based on the Spatially Explicit Capture-Recapture framework was 1.10(±0.37)/100km2 and the density of leopard was 6.68 (±0.80)/100km2. To study space use and activity patterns we have used camera-trapping data from both core and buffer areas of Pench Tiger Reserve. Higher activity overlap was recorded between tigers and leopards (Dhat1=0.88) among predators. Camera trap locations with the number of captures of each species were modeled in a GIS domain using IDW (Inverse distance weighted) interpolation technique to generate spatially explicit capture surfaces. The times recorded on camera trap photos provide information on the period during the day that a species is most active. Species active at the same periods may interact as predator and prey, or as competitors. Sensors that record active animals (e.g. camera traps) build up a record of the distribution of activity over the day. Records are more frequent when animals are more active and less frequent or absent when animals are inactive. The area under the distribution of records thus contains information on the overall level of activity in a sampled populationItem Status of Tigers, Co-Predator and Prey in Pandharkawada Forest Division (Territorial) 2021(Wildlife Institute of India, Dehradun, Maharashtra Forest Department, 2022) Habib, Bilal ; Ramarao, S.V.; Jagtap, K.P.; Nigam, P.; Koley, S.The Phase IV monitoring for the Pandharkawada Forest Division (Territorial) was conducted from March –April (2021) as part of the project “Long Term Monitoring of Tigers, Co-Predators and Prey species in Vidarbha Landscape, Maharashtra, India”. The exercise aimed to cover an area of 655.336 km2 of the forested area of the entire division. The objective of the Phase IV Monitoring is to estimate the minimum number of tigers in the Pandharkawada Forest Division using Spatially-Explicit-Capture-Recapture Sampling and density estimation of prey species using Line transect based Distance Sampling. 110 pairs of camera traps were placed in the forested area of Pandharkawada Forest Division following a sampling grid of 2 km2 in all four blocks. The camera traps were active for average 30 days in each block yielding a sampling effort 3508 of trap nights of data which is used for further analysis. From the camera trap photographs 11 tigers (unique to Pandharkawada Forest Division) and 10 leopards have been identified. Tiger density per 100 km2 based on the Spatially Explicit Capture-Recapture (SECR) model was 2.356 (SE ± 0.727) in the forest division while that of leopards based on the same method was 2.99 (SE ±1.03). To estimate prey density, 84 line-transects were laid randomly all over the division and were sampled 7 times during the sampling period, with a total walking effort of 1176 km was invested. The observations include chital (Axis axis), nilgai (Boselaphus tragocamelus), chousingha (Tetracerus quadricornis), langur (Semnopithecus sp), wild boar (Sus scrofa), chinkara (Gazella bennetii), Indian hare (Lepus nigricollis) and peafowl (Pavo cristatus). As per the observations, Nilgai (n=278) is the most observed species followed by Wild boar (n=77), Peafowl (n= 54), Indian hare (n=45) and Chital (n=44). The overall prey density of Pandharkawada Forest Division is 10.977 (SE± 1.19). Due to very low observations (n<20) densities of chousingha and chinkara could not be estimated. To study the activity, we used the camera trap images. The times recorded on camera trap photos provide information on the period during the day that a species is most active. Species active at the same periods may interact as predator and prey, or as competitors. Sensors that record active animals (e.g. camera traps) build up a record of the distribution of activity over the day. Records are more frequent when animals are more active and less frequent or absent when animals are inactive. The area under the distribution of records thus contains information on the overall level of activity in a sampled population. We used IDW (Inverted distance weighted) to map the intensive area used by different animal species.Item Status of Tigers, Co-Predator and Prey in Tipeshwar Wildlife Sanctuary 2021(Wildlife Institute of India, Dehradun, Maharashtra Forest Department, 2022) Habib, B.; Nigam, P.; Banerjee, J.; Puranik, S.; Jagtap, K.; Koley, S.Phase IV monitoring for the Tipeshwar Wildlife sanctuary was conducted from March –April (2021) as part of the project “Long Term Monitoring of Tigers, Co-Predators and Prey species in Vidarbha Landscape, Maharashtra, India”. The exercise aimed to cover an area of 148.63 km2 of the entire sanctuary. The objective of Phase IV Monitoring is to estimate the minimum number of tigers in the Tipeshwar WLS using Spatially-Explicit-Capture-Recapture Sampling and density estimation of prey base using Distance Sampling. 62 pairs of camera traps were placed in the forested area of Tipeshwar WLS following a sampling grid of 2 sq. km. in one block. The camera traps were active for 30 days yielding a sampling effort of 2206 trap nights of data which is used for further analysis. Tiger density per 100 km. sq. based on the Spatially Explicit Capture-Recapture (SECR) model was 7.07 (SE ± 0.218) in the sanctuary while that of leopards based on the same method was 3.86 (SE ±0.165). To estimate prey density, 13 line-transects were laid randomly all over the division and were sampled 7 times during the sampling period, with a total walking effort of 182 km was invested. The observations include chital (Axis axis), sambar (Rusa unicolor), nilgai (Boselaphus tragocamelus), chousingha (Tetracerus quadricornis), langur (Semnopithecus sp), wild boar (Sus scrofa), chinkara (Gazella bennetii), Blackbuck (Antilope cervicapra), Indian hare (Lepus nigricollis) and peafowl (Pavo cristatus). As per the observations, Nilgai (n=50) is the most observed species followed by Chital (n=27). The overall prey density of Tipeshwar WLS is 17.82 (SE± 3.81). Due to low number of observations densities of chousingha, chinkara, blackbuck, langur, Indian hare, peafowl, sambar, wild boar could not be estimated. To study the activity, we used the camera trap images. The times recorded on camera trap photos provide information on the period during the day that a species is most active. Species active at the same periods may interact as predator and prey, or as competitors. Sensors that record active animals (e.g. camera traps) build up a record of the distribution of activity over the day. Records are more frequent when animals are more active and less frequent or absent when animals are inactive. The area under the distribution of records thus contains information on the overall level of activity in a sampled population.Item Status of tigers, co-predator and prey in Navegaon Nagzira Tiger Reserve (NNTR) - 2021(Maharashtra Forest Department and Wildlife Institute of India, 2022) Habib, Bilal Habib, B., Nigam P., Ramanujam, M., Pate, P., Singh, K., Bhalavi, S. B., Bhandari, A. and Akshay, J. Kanishka; Nigam, P.; Ramanujam, M.; Pate, P.; Singh, K.; Bhalavi, S.B.; Bhandari, A.; Kanishka, Akshay J.The Phase IV monitoring for the NNTR core and buffer was conducted from December 2020 – March 2021 as part of the project “Long term Monitoring of Tiger, Co-predator and their Prey in Tiger Reserves and other Tiger Bearing Areas of Vidarbha Maharashtra”. The field site for this exercise was Navegaon-Nagzira Tiger Reserve. The core and buffer areas of the tiger reserve were covered under this exercise. The objective of Phase IV Monitoring is to estimate the minimum number of tigers in the reserve using Capture-Recapture Sampling and density estimation of prey base using Distance Sampling.518 camera traps were placed in the core and buffer area of NNTR following a sampling grid of 2.01 sq. km in two blocks. An average camera trapping survey of 33 days in each block (Nagzira and Navegaon) with a sampling effort of 15,692 trap nights yielded data used for further analysis. Tiger density per 100 km2 based on the Spatially Explicit Capture-Recapture (SECR) model was 0.64 in the Navegaon-Nagzira Tiger Reserve while that of leopards based on the same method was 8.21. To estimate prey density, 172 line-transects were sampled 7 times during the sampling period, with a total walking effort of 2382 km. The individual densities in Nagzira and Navegaon Core for Sambar, Chital, Nilgai, Wild pig, and Gaur were estimated to be 1.26 ± 0.39, 8.89 ± 1.77, 9.14 ± 1.94, 8.27 ± 4.85, 5.50 ± 1.08 and 0.56 ± 0.25, NA, 10.42 ± 2.61, NA, 5.93 ± 1.68 respectively whereas the individual density estimates for Nagzira and Navegaon buffer for Sambar, Chital, Nilgai, Wild pig, and Gaur were 0.15 ± 0.13, 10.29 ± 1.96, 7.13 ± 1.43, 13.92 ± 8.29, NA and 0.49 ± 0.18, 7.61 ± 2.15, 11.75 ± 1.97, 12.03 ± 8.12, NA respectively. To study space use patterns and activity we used camera-trapping data from both core and buffer areas of Navegaon-Nagzira Tiger Reserve. Camera trap locations with the number of captures of each species were modeled in a GIS domain using IDW (Inverse distance weighted) interpolation technique to generate spatially explicit capture surfaces. The times recorded on camera trap photos provide information on the period during the day that a species is most active. Species active at the same periods may interact as predator and prey, or as competitors. Sensors that record active animals (e.g. camera traps) build up a record of the distribution of activity over the day. Records are more frequent when animals are more active and less frequent or absent when animals are inactive. The area under the distribution of records thus contains information on the overall level of activity in a sampled population. Species distribution was mapped seasonally using direct sighting data of wild ungulates from all the three seasons i.e. from winter 2019 to monsoon 2020 that was collected through regular patrolling using the MSTrIPES, a patrolling protocol mandated by NTCA to use in tiger reserves. MaxEnt, ArcGIS software was used for data preparation and final analysis. Factors that influence species distributions and habitat selection are of great importance to researchers and managers of wildlife. Here we used habitat variables namely: Land use Land cover (LULC), Digital Elevation Model (DEM), slope, aspect, stream delineation (Distance to streams), distance to the village, distance to road, distance to the railway line, and distance to the waterhole.