WII Technical Reports
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Item Patterns of Human-Wildlife Conflict in Chandrapur, Maharashtra, India(Wildlife Institute of India, Dehradun, 2022) Habib, B.; Nigam, P.; Praveen, N.R.; Ravindran, A.Human-wildlife conflict (HWC) is the negative interaction between human or human property and wildlife and is a growing cause for concern among conservationists and scientists globally. Although HWC is a global phenomenon, there are certain differences in its manifestation as well as magnitude in developed versus developing nations. Developed regions of the world exhibit lower levels of direct dependence on forest ecosystems and their resources, as well as exclusionary management of the wildlife habitats. India, being a developing nation, is witness to an increasing intensity of human-carnivore conflict due to the fast-shrinking percentage of forest cover, that act as natural habitats of many carnivore species, due to a combination of factors including human population explosion, agricultural expansion, and large-scale developmental activities, leading to fragmentation and destruction of forest cover all across the country. The Central Indian Landscape (CIL) is one of the regions of high tiger populations and density in India with 6 Tiger Reserves featuring heavily as source populations, including Tadoba Andhari, Pench, Kanha, Satpura, and Melghat Tiger Reserves. But there is a disproportionate decline in forest cover as well as quality, which means that even though the populations of large carnivores are thriving, there isn’t enough pristine forest to support their growing numbers. This eventually leads to a spill-over of the carnivores into surrounding human-dominated landscapes (HDL). This acts as one of the major reasons for the burgeoning number of conflict cases between humans and large carnivores. The Vidarbha Landscape (VL) of the state of Maharashtra is facing a similar decline in forest cover leading to an increase in conflict cases. Records of conflict incidents were collected from the Greater Tadoba Landscape (GTL) which covers the divisions of Brahmapuri, Chandrapur & Central Chanda, along with the Tadoba Andhari Tiger Reserve (TATR), in the Chandrapur Circle. Using these records, hotspots of livestock depredation and attacks on humans were mapped using a hotspot analysis tool in ArcGIS. Various scientific and non-scientific methods continue to be tested to slow down the increasing rate of HWC across the world. One of the major hurdles in the implementation of a universal mitigation method to curb the number and impact of HWC is the heavy influence of local factors including topography, vegetation, and human demography of the region. This requires an intensive study of the patterns and causes of conflict in a given region. Studying conflict hotspots and understanding the emerging spatial and temporal patterns is a quintessential step in the process of mitigating the HWC of any landscape. An important step in that direction is the establishment of a comprehensive database, which can be used for trend analysis and predictions. The hot spot analysis of human-carnivore conflict for tigers, leopards, and sloth bears enables visualization of the spatial distribution of events of attacks on humans as well as livestock depredation by each species, hence aiding in the development of site-specific management strategies to mitigate the effects of human-carnivore conflictItem Status of tigers, co-predator and prey in Akola Wildlife Division, Maharasthra, India 2021(Wildlife Institute of India, Dehradun, 2022) Habib, Bilal Habib, B., Nigam, P., Banerjee, J., Reddy, M. S., Nimje, A., Khairnar, M. N., Patil, J. and Ray, S. (; Nigam, P.; Banerjee, J.; Reddy, M.S.; Nimje, A.; Khairnar, M.N.; Patil, J.; Ray, S.Phase IV monitoring for Akola Wildlife Division was conducted from February – May 2021 covering an area of 300 sq. km. as a part of the project “Long-term Monitoring of Tigers, Co-Predators and Prey in Tiger Reserves and other Tiger bearing areas of Vidarbha, Maharashtra”. The objective of the 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. A total of 103 camera traps (pairs) were placed in the 4 wildlife sanctuaries (viz. Dnyanganga WLS, Katepurna WLS, Karanja-Sohol WLS and Lonar WLS) of Akola Wildlife Division following a sampling grid of 2 sq. km. In each wildlife sanctuary, camera traps were active for 25-30 days. During 90 days of camera trapping survey with a sampling effort of 3,090 trap nights, 42 adult individual leopards were photographed in Akola Wildlife Division. 28 adult individual leopards were photographed in Dnyanganga WLS and population size (N) based on the best fit (SECR Heterogeneity) model was 28 (SE ± 1.0). 9 adult individual leopards were photographed in Katepurna WLS and population size (N) based on the best fit (SECR Null) model was 10 (SE ± 1.27). 3 and 2 adult individual leopards were photographed in Karanja-Sohol WLS and Lonar WLS respectively. Leopard density per 100 sq. km. based on the Spatially Explicit Capture-Recapture (SECR) model was 13.42 (SE ± 2.56) and 25.61 (SE ± 8.85) for Dnyanganga WLS and Katepurna WLS respectively. To estimate prey density in Dnyanganga WLS, 42 line transects were sampled times 6-7 during the sampling period, with a total walking effort of 513 km. Overall during the sampling, 336 animal/bird observations were made. The overall density of major prey species (Wild Boar 14.90/sq. km., Nilgai 12.51/sq. km., Peafowl 2.79/sq. km., Chinkara 1.40/sq. km. and Four Horned Antelope 1.33/sq. km.) as estimated using distance sampling was 24.19 /sq. km. A basic understanding of sympatric carnivore ecology with asymmetric competition enables us to hypothesize that to coexist and not just co-occur there must be niche segregation on at least one of the three axes: space, time, and/or diet. To understand how large sympatric predators co-occur in space and in time, camera trapping was carried out. Temporal activity overlaps were derived by using kernel density. Leopards were found in all 4 wildlife sanctuaries. There was a distinct difference in the space-use pattern observed for all three carnivores and a strong spatial segregation pattern found between Leopards, Hyenas and Dholes. It showed significant segregation and avoidance of each other’s space. While leopards show a strong, bimodal, nocturnal activity pattern, Hyenas have a strong, unimodal activity pattern in Dnyanganga WLS. In Katepurna WLS, leopards show a strong unimodal, nocturnal activity pattern and dholes show a bimodal, crepuscular activity pattern.Item Status of Tigers, Co-Predator and Prey in Pench Tiger Reserve (PTR) 2021(Wildlife Institute of India, Dehradun, Maharashtra Forest Department, 2022) Habib, Bilal; Nigam, P.; Ramanujam, M.; Pathak, A.; Shukla, P.; Dabholkar, Y.; Bhowmick, I.The 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 Pench Tiger Reserve was conducted from January 2021-July 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 January 2021. 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. Among all the prey species highest density was recorded for Chitals 24.28 (±4.83)/km2 in the core. The density of other species are as follows Sambar 6.08 (±0.98), and Gaur 1.56 (±0.39)/km2, Wild pig 4.31 (±0.90), Langur 17.02 (±3.56), Nilgai 1.91 (±0.41), Barking Deer 0.59 (±0.15), Hare 0.81 (±1.12), Peafowl 2.49 (±0.60). In the buffer area, the density of Chital was 8.63 (±4.15) and of Sambar was 1.36 (±0.40). 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 the trapping was completed in a single block with 311 camera stations resulted in 8415 trap nights during May 2021-June 2021. The minimum number of individual tigers captured was 44 along with 60 leopards. Tiger density based on the Spatially Explicit Capture-Recapture framework was 4.78(±0.7)/100km2 and the density of leopard was 7.55 (±1.02)/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 population.Item Status of Tigers, Co-Predator and Prey in Pandharkawada Forest Division (Territorial) 2021(Wildlife Institute of India, Dehradun, Maharashtra Forest Department, 2022) Habib, Bilal Status of Tigers, Co-Predator and Prey in Pandharkawada Forest Division (Territorial) 2021; 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, copredator and prey in Tadoba Andhari Tiger Reserve (TATR) 2021(Wildlife Institute of India, Dehradun, Maharashtra Forest Department, 2022) Habib, Bilal Habib, B., Nigam, P., Ramgaokar, J., Guruprasad, G., Kale, N., Bhagwat, S. S., Krishnan, A., Hushangabadkar, P., Sheikh, S. (2022): Status of Tigers, Co-Predator and Prey in Tadoba Andhari Tiger Reserve (TATR) 2021; Nigam, P.; Ramgaokar, J.; Guruprasad, G.; Kale, N.; Bhagwat, S.S.; Krishnan, A.; Hushangabadkar, P.; Sheikh, S.Phase IV monitoring for the Tadoba Andhari Tiger Reserve (TATR) core and buffer was conducted from February – May 2021 covering an area of 1315 sq. km. as a part of the project “Long-term Monitoring of Tigers, Co-predators and Prey in Tiger Reserves and other Tiger bearing areas of Vidarbha, Maharashtra”. The objective of Phase IV Monitoring is to estimate the minimum number of tigers in the reserve using Spatially Explicit Capture-Recapture Sampling and density estimation of prey base using Distance Sampling. Camera traps were placed in 621 grids of 2.01 sq. km. area each in the core and buffer area of TATR in two blocks. In each sampling block, camera traps were active for 27 - 44 days. During 83 days of camera trapping survey with a sampling effort of 20,965 trap nights, 85 adult individual tigers were photographed in the sampled area of TATR. Estimated population (N) of tigers based on the best fit (SECR Heterogeneity) model was 86 (SE ± 0.71). Tiger density per 100 sq. km. based on the Spatially Explicit Capture-Recapture (SECR) model was 6.31 (SE ± 0.70). Along with tigers 114 adult individual leopards were photographed in the sampled area of TATR and estimated population (N) based on the best fit (SECR Heterogeneity) model was 118 (SE ± 2.17). Leopard density per 100 sq. km. based on the Spatially Explicit Capture-Recapture (SECR) model was 7.07 (SE ± 0.67). To estimate prey density, 133 line transects in core and buffer of TATR were sampled 7 times during the sampling period, with a total walking effort of 1862 km. During the sampling, a total of 1163 animal/bird observations were made. The overall individual density per km2 of major prey species in TATR was Gaur 2.16 (SE ± 0.39), Sambar 1.71 (SE ± 0.29), Chital 2.65 (SE ± 0.55), Wild Boar 3.73 (SE ± 0.84), Langur 3.35 (SE ± 0.71), Barking Deer 0.42 (SE ±0.08), Nilgai 1.04 (SE ± 0.25), Black-naped Hare 0.68 (SE ± 0.15) Peafowl 1.79 (SE ± 0.25) and Grey Jungle Fowl 8.19 (SE ± 1.02). A basic understanding of sympatric carnivore ecology with asymmetric competition enables us to hypothesize that to coexist and not just co-occur there must be niche segregation on at least one of the three axes: space, time, and/or diet. To understand how three large sympatric predators co-occur in space and in time, camera trapping was carried out. Temporal activity overlaps were derived by using kernel density. All the sympatric predators were found to co-occur in the sampled area of TATR. There was a distinct difference in the space-use pattern observed for all three carnivores and a strong spatial segregation pattern found between Tigers, Dholes, and Leopards. It showed significant segregation and avoidance of each other’s space. There was a significant overlap between the temporal activity pattern of tigers and leopards. While tigers and leopards show a strong, unimodal, nocturnal activity pattern, dholes show a bimodal, crepuscular activity pattern.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.Item Spatial mapping of important marine habitats of Malvan Coast for re-organization of boundary of the Malvan Marine Sanctuary(Wildlife Institute of India, Dehradun, 2023) Shinde, N.; Bayana, S.; Sarkar, D.; Pande, A.; Sivakumar, K.; Talukdar, GautamMalvan Marine Sanctuary is a Marine Protected Area located in the Sindhudurg district of Maharashtra state. Known for its rich biodiversity, it is grappling with increasing anthropogenic pressure necessitating a comprehensive study to assess its habitats and threats. Management Effectiveness Evaluation (MEE) of 2017-2018 team had suggested for boundary reorganization to exclude areas of human intervention and to include important habitats and areas with high biodiversity for the better management of biodiversity off the coast of Malvan. The project has undertaken because high tourism zone are areas with high anthropogenic pressure within the core zone of the sanctuary. Coral reefs and its associated fish fauna were surveyed at nine sampling sites. The total hard coral cover was observed to be 28% while the seagrass cover was observed to be 3% in 21 sampling sites. 19 genera of corals were identified. Favites sp.was observed to be the most abundant (19.18%). Within the sanctuary, Seagrass patches were identified at five sampling sites namely King’s Garden 1, King’s Garden 2, King’s Garden 3, Dharan and Donor site. 122 species of fish belonging to 38 families were observed during underwater surveys. Fish-market surveys were conducted to study the species composition and size-class of fish species caught around the sanctuary. A total of 44 different fish species were observed during market surveys. Beach litter surveys were conducted to assess the anthropogenic stress along the Malvan coastline. Debris in the form of polythene was the major contributing litter type at all three sections of the beach. The rocky outcrops along the coast were observed to be roosting sites for avifaunal species namely, White-bellied Sea Eagles, Pigeons, Swiftlets, etc. Spatial prioritization of the marine habitats revealed potential PA’s include Kawda, 7 rocks, Lighthouse area, covering an area of 29.07 sq.km; conservation priority areas comprising Chiwla, and Sargassm covering a total area of 19.21 sq. km and King’s garden (3.534 sq km) as sensitive area. Strategies to conserve these areas for long term conservation. should be planned. Spatial mapping of important marine habitats of Malvan coast for re-organization of boundary of the Malvan Marine SanctuaryItem Tracking the nearshore and migratory movement of Olive Ridley sea turtles occurring in the coastal waters of Maharashtra(Wildlife Institute of India, Dehradun, 2024) Mudliar, Mohit M.; Kumar, R. SureshThis tracking study has been successful in creating awareness about olive ridley sea turtles through extensive media coverage on tagging and movement updates. Even with a small number of tagged turtles, it also provided crucial information on the movement and diving ecology of this lesser-studied population. Most importantly, the patterns of movement from this study suggests that turtles nesting on the Maharashtra coast comprise two foraging populations. Firstly, those that are resident to the Arabian Sea and the others from the Sri Lankan waters or from the Bay of Bengal. Further tracking efforts are recommended where the turtles are tagged early in the nesting season to understand their inter-rookery movements and find nesting frequencies per season. More tracking efforts from Maharashtra and elsewhere along the West coast of India are suggested to be taken up. This will help understand how the turtles from different nesting areas move and forage. Moreover, this will help identify the overlap between fishing zones and critical breeding and foraging areas along the West Coast to better manage and conserve the species through appropriate interventions.