Successful conservation translocation: Population dynamics of tiger recovery in Panna Tiger Reserve, Central India
收藏NIAID Data Ecosystem2026-05-02 收录
下载链接:
http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.qbzkh18qz
下载链接
链接失效反馈官方服务:
资源简介:
Tiger (Panthera tigris) is an indicator species of ecological health and conservation efforts. Due to excessive poaching, the tiger was locally extinct in Panna Tiger Reserve, central India. Subsequent successful reintroduction efforts have brought the species back from the verge of extinction and have demonstrated the success of conservation translocations in response to such critical situations.
To understand the demographic characteristics of the tigers reintroduced to Panna Tiger Reserve, we used an ensemble approach of different sampling techniques and direct observations from a long-term data-set spanning more than 10 years. We evaluated different demographic indicators (population status, growth rate, mean litter size, inter-birth interval, and survival probability).
Since reintroduction in 2009, 18 females have recruited 120 cubs from 45 litters. This led to 59 individuals in 2021 with a growth rate of ~26%. The mean litter size was 2.66 (SE 0.1), and the inter-birth interval was 19.16 months (SE 0.5). The high survival rate of the reintroduced population (0.82±0.2) helped to achieve the success of reintroduction. We observed non-constant mortality trajectories for both sexes (higher survival probabilities for females) with a moderately higher risk of death in younger (<1 year) and older (>10 years) individuals.
Our results showed the effectiveness of translocation and conservation efforts. The recovered population can be used as a founder for augmentation in other recovering tiger populations. A long-term tiger-centric management plan should be implemented in the area adjacent to Panna Tiger Reserve to conserve and secure the habitat of the entire landscape for the long-term survival of the reintroduced population in a metapopulation framework.
Methods
Data Collection
Radio telemetry
A total of 25 tigers (7 males and 18 females; Table S1) were radio-collared between March 2009 and June 2020 as a part of the long-term project entitled “Tiger Reintroduction and Recovery Programme in Panna Tiger Reserve, Madhya Pradesh.” Animals were captured and collared under the permission of the Madhya Pradesh Forest Department (MPFD Letter No./Exp./2009/1205 dated 31/8/09) following the capture rule and regulation of the Wildlife Protection Act, 1972 Section 11 (1A). Animals were tracked and immobilized, using a ‘Hellabrunn mixture’ (125 mg xylazine + 100 mg ketamine/ml) (Hafner et al., 1989) injected through a Tele-inject projector (Model 4V.31). The target individuals were chemically immobilized. The entire process took place under the supervision of a veterinarian. Tigers were fitted with Very High Frequency transmitters (15 individuals; Telonics® Inc) and VHF/ GPS/ UHF collars (10 individuals; African Wildlife Tracking® Inc and Vetronic Aerospace®). All collared tigers were monitored very intensively with UHF and satellite tools. Staff and researchers jointly monitored VHF collared individuals and tracked the animals 24 hours per day, 7 days per week for the duration of the study.
Camera trapping
Grid-based systematic camera trap sampling was carried out from 2012-2016 in a 4km2 grid cell size; a more intensive effort took place from 2017-2021 with a 2km2 grid cell size (Jhala et al., 2019). The entire PTR was sampled systematically by placing a pair of camera traps (531 locations) on either side of dirt roads, animal trails, or dry river beds to maximize the chances of capturing tigers on camera. Camera traps were active for at least 30 days during the winter season. In addition to the double-sided camera traps, a single-sided continuous camera trap monitoring system (CCMS) was adapted to monitor the movement of non-collared tigers throughout the year. We used a grid-based approach (same 2km2 grid cell size) for CCMS to sample throughout PTR. Simultaneously, camera traps were also placed opportunistically at vantage points, kills, and nearby den sites. Cameras were checked every 5-7 days. Individually identifiable tiger pictures, including both flanks, were updated every year. Newly captured tiger images were compared manually by using their respective unique stripe patterns.
The intensive use of radio-telemetry and camera trapping helped us to document the emigration of tigers from PTR. As there are no other source populations around PTR, we did not record any immigration events during 2009-2021. Routine patrolling with elephants, camera traps, and intensive radio-telemetry helped us to quantify the IBI, initial litter size and cub survival.
Analytical methods
Population status and growth rate
All adult and sub-adult tigers were radio-collared during the initial days after reintroduction. With a growing tiger population, all individuals were not radio-tagged; therefore, the camera trap-based survey method was adapted to understand the movement of non-collared animals. To calculate the growth rate of tigers, we used the software Vortex version 10 (Lacy & Pollak, 2014) with 100 iterations. Vortex is appropriate for modelling species with low fecundity and long life spans and is the most commonly used software in published reintroduction models (Armstrong & Reynolds, 2012). The growth rate (r) of r > 0 indicates the population grows, while r < 0 indicates a population decline. Similarly, the annual multiplicative growth rate (λ) indicates a positive population growth if λ > 1.0 (Nt+1 > Nt), while λ < 1.0 (Nt+1 < Nt) indicates a population decline.
Litter size and inter-birth interval
Tiger individuals were identified by their unique stripe patterns (McDougal, 1977; Karanth, 1995) on their left and right flanks. Recording and documenting actual litter size at birth for any free-ranging elusive large carnivores is difficult; therefore, we determined the litter size of the tiger at the first sighting. Once the first sight or photo captured of the female with cubs was recorded, the approximate date of birth of the cubs was estimated by deducting two months from the first appearance (Smith et al., 1987). However, for collared females, the litter size or date of birth of cubs was confirmed by the direct sighting, using radio-telemetry tracking. The IBI was calculated when the same female produced second or consecutive successful litters. We assumed the cubs were dead, if not photo captured or found to be moving with mothers for more than six months. Usually, females conceive and give birth to another litter within 4-10 months after losing all cubs of the previous litter; such instances were discarded for IBI calculations (Singh et al., 2013). Since our monitoring was intensive, we had a high detection of tigers during the study period, except for when the individuals dispersed outside the PTR.
Survivorship
The detection non-detection matrix was prepared by compiling camera trap, CCMS, and radio-telemetry (to ensure whether the individual was within the PTR or not) data, and data were analyzed in the Capture-Mark-Recapture (CMR) framework (Table S1); since the detection probability of an animal within its home range was not involved in our study, imperfect detection was intentionally not addressed in our analysis. We used the Cormack-Jolly-Seber (CJS; Pledger et al., 2003) method to estimate the survival rate from one sampling period to the next; the survival rate is calculated as a proportion of animals alive at time ti versus time ti+1. Survival (ϕ) and recapture probability (p) depend on marked individuals' re-observation. Sex of each tiger, an intrinsic factor, and time (extrinsic factor) were included as covariates in the model of survival rate. As males and females have different life history traits, their survival probabilities might differ (Smith, 1993). Males show a lower survival probability than females in most mammalian species (Krebs, 1972). We modelled the survival probability using the ‘marked’ package (Laake et al., 2013) in R Core Team (2022). The Akaike Information Criterion (AIC) value was calculated for every model to determine the best fit model.
创建时间:
2024-05-16



