# Mammalian diversity and prey population density of Gautala Autramghat Wildlife Sanctuary, Maharashtra, Western India

Pandurang Pawar, Mahadeo Mule

<figure><img src="image_1.png" /></figure>

## To cite this version:

Pandurang Pawar, Mahadeo Mule. Mammalian diversity and prey population density of Gautala Autramghat Wildlife Sanctuary, Maharashtra, Western India. Journal of Biology and Nature, 2025, 17 (1), pp.49-62. 10.56557/joban/2025/v17i19182. hal-04997301

HAL Id: hal-04997301

https://hal.science/hal-04997301v1

Submitted on 19 Mar 2025

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_3.png" /></figure>

# Mammalian Diversity and Prey Population Density of Gautala Autramghat Wildlife Sanctuary, Maharashtra, Western India

Pandurang Pawar a* and Mahadeo Mule a

a Department of Environmental Science, Dr. Babasaheb Ambedkar Marathwada University, University Campus, Near Soneri Mahal, Jaisingpura, Aurangabad, Maharashtra, 431004, India.

## Authors' contributions

This work was carried out in collaboration between both authors. Both authors read and approved the final manuscript.

## Article Information

DOI: https://doi.org/10.56557/joban/2025/v17i19182

## Open Peer Review History:

This journal follows the Advanced Open Peer Review policy. Identity of the Reviewers, Editor(s) and additional Reviewers, peer review comments, different versions of the manuscript, comments of the editors, etc are available here: https://prh.ikprress.org/review-history/12894

Received: 13/01/2025

Accepted: 16/03/2025

Published: 19/03/2025

## Original Research Article

## ABSTRACT

This study aimed to assess mammalian species within Gautala Autramghat Wildlife Sanctuary (GAWLS) to understand prey-predator dynamics and guide conservation strategies. The research used line transect surveys, camera trapping, and sign surveys, documenting 22 mammal species. The four-horned antelope, sloth bear, Indian leopard, striped hyena, and tiger are classified as threatened. A total of 30 random line transects were laid across the sanctuary to estimate prey species densities. Northern plain grey langur (19.96/km²) and wild boar (9.02/km²) were the most abundant species, with density estimates of 1.11/km² for blackbuck, 2.29/km² for Indian hare, 8.82/km² for nilgai, and 3.14/km² for peafowl. The encounter rate was highest for Northern plain grey langur (0.18), followed by nilgai (0.17) and wild boar (0.11). Among prey species, adults were

<footnote>*Corresponding author: E-mail: pandurangpawar82@gmail.com;</footnote>

<footnote>Cite as: Pawar, Pandurang, and Mahadeo Mule. 2025. "Mammalian Diversity and Prey Population Density of Gautala Autramghat Wildlife Sanctuary, Maharashtra, Western India". Journal of Biology and Nature 17 (1):49-62.
https://doi.org/10.56557/joban/2025/v17i19182.</footnote>
most prevalent, especially in peafowl (95.33%), blackbuck (91.82%), spotted deer (85.71%), and
wild boar (78.40%). Blackbuck showed the largest average cluster size (7.48), followed by Northern
plain grey langur (6.74), nilgai (5.19), and wild boar (5.69). Critically low sightings of four-horned
antelope and spotted deer suggest these species are nearing local extinction. The study
recommends improving water availability through man-made water holes and mitigating
anthropogenic pressures such as cattle grazing, human encroachment, and deforestation.
Strengthening enforcement measures, community engagement, and focused monitoring efforts are
critical for increasing the populations of these vulnerable species. The findings showed the adverse
effects of habitat degradation, water scarcity, and human interference, advocating for intensified
conservation and monitoring initiatives.

Keywords: Blackbuck; deer; distance sampling; four-horned antelope; line transect; predator; ungulate.

# 1. INTRODUCTION

Effective conservation management relies on
understanding the abundance and distribution
patterns of wildlife, particularly large carnivores
(Wang & Macdonald, 2009). These patterns are
shaped by a complex interaction of natural and
human-induced factors, making it essential to
study how ecosystems respond to changes in
species composition, abundance, and habitat
dynamics (Selvan et al., 2014). Diverse habitats,
which support a wide range of species, are often
subject to ongoing changes due to factors such
as vegetation succession, human activity, and
environmental variations. Such fluctuations can
profoundly impact species richness, population
densities, and the spatial distribution of wildlife,
ultimately affecting the overall biodiversity of a
region (Clark et al., 2001; Foley et al., 2005).
Prey species are fundamental to maintaining
ecological balance, and their availability is a key
determinant of carnivore populations (Carbone &
Gittleman, 2002; Karanth et al., 2004a).
Herbivores, as primary prey for many predators,
not only support predator populations but also
influence ecosystem structure and functioning.
Through their effects on vegetation patterns,
nutrient cycling, and soil composition, herbivores
play a vital role in sustaining habitat health and
stability (Augustine & McNaughton, 1998;
McNaughton, 1985). The biomass of these
herbivores often reflects the prey base available
in a habitat, serving as an indicator of the area's
carrying capacity and its potential to support
diverse predator species (Gordon & Prins, 2008).
In semi-arid regions like Maharashtra, where
human populations are dense and natural
resources are scarce, monitoring prey species is
particularly critical. These ecosystems are highly
vulnerable to disturbances, with fragmented
forests and limited water resources leading to
heightened competition among wildlife, livestock,

and humans, especially during the dry season
(Foley et al., 2005; Hobbs, 2001).

The Gautala Autramghat Wildlife Sanctuary (GAWLS) in Maharashtra is one such sensitive ecosystem, recognized as an eco-sensitive zone by the government (Ministry of Environment Forest and Climate Change Notification, New Delhi, the 9th December, 2016). With its varied habitats, including grasslands, scrublands, and mixed forests, the sanctuary supports a diverse range of flora and fauna, encompassing many key mammalian prey and predator species. Regular monitoring of prey abundance trends in such habitats is crucial for effective conservation. It aids in assessing the impacts of habitat changes, whether due to invasive species or human activities on prey populations and, consequently, on predator species. Additionally, pressures from livestock grazing add further complexity to ecosystem dynamics, potentially creating conflicts between wildlife conservation and human livelihoods (Sankaran et al., 2005). This study aims to offer a detailed assessment of mammalian diversity within GAWLS, focusing on the population status of prey species. Key population metrics such as cluster size, cluster density, group size distribution, encounter rates, age structure (adult, subadult, young), detection probability, estimated animal density, and biomass are examined. By comparing these current findings with historical data from other protected areas, the research seeks to provide insights into how factors like resource availability during dry seasons, human disturbances, and grazing pressures influence wildlife populations in this region. Understanding these dynamics is vital for formulating effective conservation strategies that will support the long-term sustainability of both prey and predator species in this ecologically sensitive landscape.
## 2. MATERIALS AND METHODS

### 2.1 Study Area

Gautala Autramghat Wildlife Sanctuary (GAWLS) covers an area of 260 km² and spans across Chhatrapati Sambhajinagar (Aurangabad) and Jalgaon districts in Maharashtra, Western India (Fig. 1). The sanctuary is intersected by the Sathmala and Ajanta hill ranges of the Western Ghats, along with small plateaus and plains that characterize the landscape. It is geographically located at 20.33250000 N and 75.14083333 E. The main habitat types found within GAWLS include dry deciduous forests, grasslands, and scrublands, with dominant flora such as teak (Tectona grandis), Indian Sandalwood (Santalum album), Palash (Butea monosperma), Tembhurni/Tendu (Diospyros melanoxylon), and Dhamorda (Anogeissus latifolia) (Champion & Seth, 1968). Although a variety of mammal species inhabit the sanctuary, there has been no comprehensive scientific study documenting them to date. Agricultural lands border the sanctuary, and local communities depend on its resources for grazing, timber, and grass collection, as well as using the area for transportation. The region is drought-prone, leading to frequent water scarcity during the summer months. In 2016, the sanctuary was

designated as an eco-sensitive zone by the Ministry of Environment, Forest and Climate Change, covering an extended area of 483.45 km², including a one-kilometre boundary around GAWLS. This eco-sensitive zone encompasses approximately 70 villages within and around the sanctuary (Ministry of Environment Forest and Climate Change Notification, New Delhi, the 9th December, 2016).

### 2.2 Mammalian Species Richness

We compiled a checklist of mammalian prey and predator species, excluding rodents, shrews, and bats. However, we have included the three-striped squirrel and Indian-crested porcupine. We also included an Indian peacock as a prey species. Direct and indirect sign surveys, line transect methods, and camera trap records were used for the assessment. The random camera traps were deployed across three sites, covering 20 locations ranging from 1 to 7 days. The camera trap images were used for the identification of the species. For the sign surveys, the study area was divided into 46 grids, each measuring 3x3 km, and 28 of these grids were surveyed (Fig. 2). We conducted three replicate surveys within each selected grid along 3 km transects, resulting in a total survey effort of 9 km per sampling grid.

<figure><img src="image_4.png" /><figcaption>Fig. 1. Study area and line transect at Gautala Autramghat Wildlife Sanctuary</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Fig. 2. Sign survey sampling grids (3x3 km) and camera trap locations</figcaption></figure>

## 2.3 Estimation of Prey Species Density and Population Structure

Sign surveys and camera trapping were conducted between November 2022 and March 2023 to evaluate the presence of predator species. Line transect surveys were carried out during May and June 2023 to estimate the prey population. The line transect method was employed to estimate the density of various prey species, including barking deer (*Muntiacus muntjak*), nilgai (*Boselaphus tragocamelus*), wild boar (*Sus scrofa*), spotted deer (*Axis axis*), four-horned antelope (*Tetracerus quadricornis*), chinkara (*Gazella bennettii*), blackbuck (*Antilope cervicapra*), Indian hare (*Lepus nigricollis*), peafowl (*Pavo cristatus*), and Northern Plain Gray Langur (*Semnopithecus entellus*). A total of 30 line transects, each ranging from 1.6 to 2 km in length (Fig. 1), were randomly distributed across the 260 km² study area, amounting to a combined transect length of 54.8 km. Each transect was repeated six times, except for one, which was repeated three times, resulting in 177 surveys and a total survey effort of 318.60 km across the 30 transects. Surveys were conducted by two observers walking each transect in the

early morning hours, from 6:30 am to 8:30 am, recording direct observations on both sides of the transect lines. Data collected during observations included species identification, time, total counts of adults, sub-adults, and young, transect and animal bearings (θ), distance (r) from the observer, habitat type, forest terrain, and GPS location of the observer. Prey species were recorded as encountered. Equipment used included a Suunto KB 20 / 360R Compass for angle bearings, Garmin GPS Map 76CSx for location data, and a Nikon Prostaff 1000 rangefinder for distance measurements. The authors conducted the surveys with a trained team of 30 frontline personnel from GAWLS, adhering to the sampling methods outlined in the All-India Tiger Monitoring Program (AITM) (Jhala Y.V. et al., 2021) for collecting data on prey species abundance.

## 2.4 Statistical Analysis

The line transect survey data were analysed using the Distance 7.5 program, adhering to established protocols for distance sampling analysis (Thomas et al., 2010). Field data, including species detections, perpendicular
distances, and group sizes, were manually entered into the Distance 7.5 program. Several candidate detection functions, such as Half-Normal, Hazard Rate, and Uniform models, were fitted to the data. The suitability of each model was evaluated based on the shape of the detection function and its fit to the observed distance data. Truncation distances were applied to exclude outlier detections that might skew the estimation of the detection function. To increase the flexibility of the detection functions, adjustment terms like cosine and polynomial series were tested and incorporated if they significantly enhanced the model fit without leading to overfitting.

The best-fitting detection function was selected using the Akaike Information Criterion (AIC), with the model showing the lowest AIC chosen for its optimal balance between complexity and fit (Anderson & Burnham, 2004; Buckland et al., 2004). Additional diagnostics, such as Chi-square goodness-of-fit tests and visual inspection of detection function plots, were conducted to ensure that the selected model accurately represented the data. Detection probability was plotted against distance to visually verify the model's appropriateness. Based on the chosen detection function, species density estimates were calculated. The effective strip width (ESW) was determined to account for the reduction in detection probability with increasing distance from the transect line. The software calculated the density and abundance of prey species across the study area, and variance estimates were obtained using analytical methods within the Distance 7.5 program. These variance estimates were vital for evaluating the precision of the density and abundance figures and for making informed conservation and management decisions.

Encounter rates were calculated by dividing the number of observed objects or clusters by the total length of the transects (n/l). The mean group size was derived by dividing the sum of observed clusters by the total count of clusters. Each prey species was further classified into groups of five, and the percentage of each class for each prey species was calculated. Population structure was categorized by total adults, sub-adults, and young individuals, with their respective percentages computed. Key metrics such as the probability of detection (p) within a defined area, estimated animal numbers (N), effective strip width (ESW) in meters, estimated

density of clusters (DS), and estimated density of animals (D) were all determined based on the selected model. The biomass of individual prey species was estimated using their calculated density, with average weights sourced from prior peer-reviewed studies (Bagchi et al., 2004; Johnsingh & Manjrekar, 2013; Menon, 2014).

# 3. RESULTS

## 3.1 Mammalian Species Richness

In this study, 22 mammalian prey species were recorded within GAWLS (Table 1), marking the first comprehensive survey of mammals in the sanctuary. Among these, five species such as tiger, sloth bear, Indian leopard, striped hyena, and four-horned antelope are categorized as threatened. Additionally, eight species are protected under Schedule I of the Wildlife (Protection) Act, 1972, which affords the highest level of protection in India. These Schedule I species include the four-horned antelope, chinkara, blackbuck, sloth bear, Indian leopard, tiger, Indian grey wolf, and honey badger (Table 1). Notably, bats, shrews, and rodents were not the focus of this study, except the three-striped squirrel and Indian-crested porcupine.

## 3.2 Encounter Rate, Mean Cluster Size and Population Structure of Prey Species

The encounter rate in GAWLS was highest for grey langur (0.18), followed by nilgai (0.17), and wild boar (0.11) (Table 2). Blackbuck had the largest mean cluster size (8.54 ± 1.25), followed by grey langur (7.98 ± 0.52), nilgai (5.20 ± 0.77), and wild boar (4.62 ± 0.60) (Table 2). The frequency distribution of group sizes for prey species ranged from 28.33% to 83.33% for the smallest groups (1 to 5 individuals). Adult prey species were most abundant among peafowl (95.33%), followed by blackbuck (91.82%), spotted deer (85.71%), and wild boar (78.40%). In the sub-adult category, grey langur (17.62%) had the highest representation, followed by spotted deer (14.29%) and wild boar (13.58%). Among the young population, Indian hare (25.81%) was the most represented, followed by barking deer (25%) and nilgai (12.71%). Overall, the prey population in GAWLS consisted of 79.43% adults, 10.79% sub-adults, and 7.29% young individuals (Table 4).
<table><caption>Table 1. Species, IUCN status, and Wildlife (Protection) Act, 1972 (India) classification of prey species in GAWLS</caption><thead><tr><th>Species Name<br>Ungulates</th><th>Scientific Name</th><th>IUCN Status</th><th>WPA,1972 Status</th></tr></thead><tbody><tr><td>Barking Deer</td><td>Muntiacus muntjak</td><td>Least Concern</td><td>Schedule- III</td></tr><tr><td>Nilgai</td><td>Boselaphus tragocamelus</td><td>Least Concern</td><td>Schedule- III</td></tr><tr><td>Wild boar</td><td>Sus scrofa</td><td>Least Concern</td><td>Schedule- III</td></tr><tr><td>Spotted Deer</td><td>Axis axis</td><td>Least Concern</td><td>Schedule- III</td></tr><tr><td>Four-horned antelope</td><td>Tetracerus quadricornis</td><td>Vulnerable</td><td>Schedule- I</td></tr><tr><td>Chinkara</td><td>Gazella bennettii</td><td>Least Concern</td><td>Schedule- I</td></tr><tr><td>Blackbuck</td><td>Antilope cervicapra</td><td>Least Concern</td><td>Schedule- I</td></tr><tr><td colspan="4"><strong>Carnivores</strong></td></tr><tr><td>Sloth Bear</td><td>Melursus ursinus</td><td>Vulnerable</td><td>Schedule- I</td></tr><tr><td>Indian Leopard</td><td>Panthera pardus</td><td>Vulnerable</td><td>Schedule- I</td></tr><tr><td>Jungle Cat</td><td>Felis chaus</td><td>Least Concern</td><td>Schedule- II</td></tr><tr><td>Striped hyena</td><td>Hyaena hyaena</td><td>Near<br>Threatened</td><td>Schedule- III</td></tr><tr><td>Tiger</td><td>Panthera tigris</td><td>Endangered</td><td>Schedule- I</td></tr><tr><td>Indian Gray Wolf</td><td>Canis lupus pallipes</td><td>Least Concern</td><td>Schedule- I</td></tr><tr><td>Indian Fox</td><td>Vulpes bengalensis</td><td>Least Concern</td><td>Schedule- II</td></tr><tr><td>Indian Gray Mongoose</td><td>Urva edwardsii</td><td>Least Concern</td><td>Schedule- II</td></tr><tr><td>Honey Badger</td><td>Mellivora capensis</td><td>Least Concern</td><td>Schedule- I</td></tr><tr><td>Indian Jackal</td><td>Canis aureus indicus</td><td>Least Concern</td><td>Schedule- II</td></tr><tr><td>Common Palm Civet</td><td>Paradoxurus hemaphroditus</td><td>Least Concern</td><td>Schedule- II</td></tr><tr><td colspan="4"><strong>Primates</strong></td></tr><tr><td>Northern Plain Gray Langur</td><td>Semnopithecus entellus</td><td>Least Concern</td><td>Schedule- II</td></tr><tr><td colspan="4"><strong>Hares</strong></td></tr><tr><td>Indian Hare</td><td>Lepus nigricollis</td><td>Least Concern</td><td>Schedule- IV</td></tr><tr><td colspan="4"><strong>Rodents</strong></td></tr><tr><td>Three-Striped Squirrel</td><td>Funambulus palmarum</td><td>Least Concern</td><td>Schedule- IV</td></tr><tr><td>Indian-crested Porcupine</td><td>Hystrix indica</td><td>Least Concern</td><td>Schedule- IV</td></tr></tbody></table>

<table><caption>Table 2. Encounter rates and Mean Cluster Size of prey species in GAWLS</caption><thead><tr><th>No. of transect</th><th>30</th><th>SD</th></tr></thead><tbody><tr><td>Transect Length in km (mean)</td><td>1.8</td><td>0.33</td></tr><tr><td>Total Effort (km)</td><td>318.6</td><td>-</td></tr><tr><td><strong>Encounter rate</strong></td><td></td><td><strong>95 % CI</strong></td></tr><tr><td>Northern Plain Gray Langur</td><td>0.18</td><td>0.14-0.22</td></tr><tr><td>Barking Deer</td><td>0.04</td><td>0.02-0.06</td></tr><tr><td>Nilgai</td><td>0.17</td><td>0.13-0.21</td></tr><tr><td>Wild boar</td><td>0.11</td><td>0.08-0.15</td></tr><tr><td>Spotted Deer</td><td>0.02</td><td>0.007-0.04</td></tr><tr><td>Blackbuck</td><td>0.09</td><td>0.06-0.16</td></tr><tr><td>Indian Hare</td><td>0.07</td><td>0.04-0.11</td></tr><tr><td>Peafowl</td><td>0.08</td><td>0.05-0.12</td></tr><tr><td><strong>Mean Cluster Size</strong></td><td></td><td><strong>SE</strong></td></tr><tr><td>Northern Plain Gray Langur (mean)</td><td>7.98</td><td>0.52</td></tr><tr><td>Barking Deer</td><td>1.92</td><td>0.39</td></tr><tr><td>Nilgai</td><td>5.20</td><td>0.77</td></tr><tr><td>Wild boar</td><td>4.62</td><td>0.60</td></tr><tr><td>Spotted Deer</td><td>2.40</td><td>1.40</td></tr><tr><td>Blackbuck</td><td>8.54</td><td>1.25</td></tr><tr><td>Indian Hare</td><td>1.44</td><td>0.19</td></tr><tr><td>Peafowl</td><td>3.57</td><td>0.31</td></tr></tbody></table>
<table><caption>Table 3. The frequency of prey species detections is categorized by different group size classes in GAWLS</caption><thead><tr><th>Group Size</th><th>Langur (%)</th><th>Barking Deer (%)</th><th>Nilgai (%)</th><th>Wild boar (%)</th><th>Spotted Deer (%)</th><th>Blackbuck (%)</th><th>Indian Hare (%)</th><th>Peafowl (%)</th></tr></thead><tbody><tr><td>1-5</td><td>17(28.33)</td><td>12(100)</td><td>38(66.67)</td><td>25(71.42)</td><td>3(60)</td><td>14(45.16)</td><td>26(100)</td><td>25(83.33)</td></tr><tr><td>6-10</td><td>26(43.33)</td><td>0</td><td>9(15.79)</td><td>7(20)</td><td>1(20)</td><td>4(12.90)</td><td>0</td><td>5(16.67)</td></tr><tr><td>11-15</td><td>15(25)</td><td>0</td><td>10(17.54)</td><td>3(8.57)</td><td>1(20)</td><td>9(29.03)</td><td>0</td><td>0</td></tr><tr><td>16-20</td><td>2(3.33)</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1(3.22)</td><td>0</td><td>0</td></tr><tr><td>21-25</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>3(9.67)</td><td>0</td><td>0</td></tr></tbody></table>
**3.3 Estimation of Prey Species Density**

The 30 spatially replicated line transects resulted in a total survey effort of 318.60 km of walking. During these surveys, eight out of the ten prey species found in GAWLS were recorded, specifically barking deer (*Muntiacus muntjak*), nilgai (*Boselaphus tragocamelus*), wild boar (*Sus scrofa*), spotted deer (*Axis axis*), blackbuck (*Antilope cervicapra*), Indian hare (*Lepus nigricollis*), Northern Plain Gray Langur (*Semnopithecus entellus*), and peafowl (*Pavo cristatus*) (Table 4). The data collected was sufficient for the analysis of six prey species, while the sample sizes for barking deer and spotted deer were too low for reliable analysis (Table 4). The half-normal key function was selected to be the best-fitting model for most prey species (Table 5).

Among the six analysed species, grey langur was the most abundant with an estimated density of 19.96 ± 3.28 SD/km² in GAWLS. Among wild ungulates, wild boar was the most abundant (9.02 ± 2.40 SD/km²), followed closely by nilgai (8.82 ± 1.92 SD/km²) (Table 6). The overall density ranking of individual species from highest to lowest was grey langur > wild boar > nilgai > peafowl > Indian hare > blackbuck, while the biomass ranking was nilgai > wild boar > grey langur > blackbuck > peafowl > Indian hare. The estimated cluster density was highest for grey langur (2.96 ± 0.38 clusters/km²), followed by Indian hare (1.82 ± 0.55 clusters/km²), nilgai (1.69 ± 0.27 clusters/km²), and wild boar (1.58 ± 0.33 clusters/km²) (Table 6).

**4. DISCUSSION**

This study is the first scientific assessment of prey species including peafowl, providing a present diversity status and their population structure with density. Species like barking deer, four-horned antelope, spotted deer, and chinkara were found in minimal numbers. While four-horned antelope and chinkara were captured on camera traps, they were absent during line transect surveys. Notably, the four-horned antelope is listed as vulnerable on the IUCN Red List. Among the threatened carnivores, tiger, striped hyena, sloth bear, and Indian leopard were documented. Camera traps recorded a solitary male tiger, which has established its territory in GAWLS since 2021. This tiger, last reported in 1940, reappeared after migrating approximately 2000 km from the Eastern Vidarbha Landscape, as reported by the

Maharashtra Forest Department (The Economic Times, 2021). Indian leopards are more widespread compared to hyenas and Indian wolves. Increasing the density of prey species is crucial to enhancing the presence of these carnivores (Winnie & Creel, 2017). The availability and abundance of prey species directly affect predator populations, playing a crucial role in maintaining ecosystem balance and contributing to the stability and richness of mammalian diversity in the region (Chang & Todd, 2023) (Table 5).

Although spotted deer and four-horned antelope were captured on camera traps during the survey, they were not observed during line transect surveys, indicating their minimal presence. High-biomass prey species such as sambar (*Rusa unicolor*) and gaur (*Bos gaurus*) are absent. Preferred prey species for tigers, including spotted deer, nilgai, wild boar, barking deer, four-horned antelope (Karanth et al., 2004b) and chinkara, are present within the sanctuary. Their densities could be increased through effective wildlife management practices. The study area is located in the drought-prone Marathwada region of Maharashtra, India, GAWLS faces significant water scarcity during the summer months, a critical factor for wild prey species that rely heavily on nearby water sources (Grewal & Srinivasan, 2024). The densities of wild boar and nilgai are comparable to those in other protected areas across India. However, spotted deer, typically the most abundant prey species in protected areas (Lamichhane et al., 2020), are nearing extinction in GAWLS (Table 7). As a key prey species, spotted deer significantly contribute to the overall prey biomass, supporting a healthy predator population (Ranjan et al., 2024).

Our findings lead to several key recommendations for conserving and managing prey species in GAWLS. First, addressing water scarcity by creating man-made water holes, especially in drought-prone areas, is crucial for improving prey habitats during summer. Second, managing anthropogenic pressures such as cattle grazing, human encroachment, and deforestation is essential to reduce interspecific competition and prevent habitat degradation. Strict regulations and community engagement programs can help control these activities and restore ecological balance. Efforts should also focus on monitoring and bolstering populations of critical species like spotted deer and four-horned antelope, which are nearing local extinction.
<table><caption>Table 4. Population structure of prey species in GAWLS</caption><thead><tr><th>Species</th><th>Total recorded Individuals</th><th>Total adults</th><th>Adults (%)</th><th>Total Sub-adult</th><th>Sub-adult (%)</th><th>Young</th><th>Young (%)</th></tr></thead><tbody><tr><td>Barking Deer</td><td>24</td><td>16</td><td>66.67</td><td>1</td><td>4.17</td><td>6</td><td>25.00</td></tr><tr><td>Blackbuck</td><td>269</td><td>247</td><td>91.82</td><td>1</td><td>0.37</td><td>2</td><td>0.74</td></tr><tr><td>Indian Hare</td><td>31</td><td>19</td><td>61.29</td><td>0</td><td>0.00</td><td>8</td><td>25.81</td></tr><tr><td>Langur</td><td>488</td><td>349</td><td>71.52</td><td>86</td><td>17.62</td><td>37</td><td>7.58</td></tr><tr><td>Nilgai</td><td>291</td><td>228</td><td>78.35</td><td>33</td><td>11.34</td><td>37</td><td>12.71</td></tr><tr><td>Peafowl</td><td>107</td><td>102</td><td>95.33</td><td>4</td><td>3.74</td><td>0</td><td>0.00</td></tr><tr><td>Spotted Deer</td><td>28</td><td>24</td><td>85.71</td><td>4</td><td>14.29</td><td>0</td><td>0.00</td></tr><tr><td>Wild boar</td><td>162</td><td>127</td><td>78.40</td><td>22</td><td>13.58</td><td>12</td><td>7.41</td></tr><tr><td>Total</td><td>1400</td><td>1112</td><td>79.43</td><td>151</td><td>10.79</td><td>102</td><td>7.29</td></tr></tbody></table>

<table><caption>Table 5. Details of detection, selected detection functions, and model selection for prey species in GAWLS</caption><thead><tr><th colspan="3">Detection</th><th colspan="5">Detection functions and model selection</th></tr><tr><th>Species</th><th>n</th><th>n/l</th><th>N</th><th>TW (m)</th><th>p</th><th>ESW (m)</th><th>Selected Model</th><th>Min. AIC</th></tr></thead><tbody><tr><td>Barking Deer</td><td>12</td><td>0.03</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Blackbuck</td><td>30</td><td>0.094</td><td>286</td><td>0</td><td>0.47</td><td>319.92</td><td>Half-normal</td><td>51.87</td></tr><tr><td>Indian Hare</td><td>23</td><td>0.072</td><td>595</td><td>3</td><td>0.48</td><td>19.94</td><td>Half-normal</td><td>40.97</td></tr><tr><td>Langur</td><td>57</td><td>0.18</td><td>5190</td><td>8.19</td><td>0.51</td><td>30.28</td><td>Uniform</td><td>438.78</td></tr><tr><td>Nilgai</td><td>54</td><td>0.17</td><td>2291</td><td>40.83</td><td>0.42</td><td>49.94</td><td>Half-normal</td><td>112.03</td></tr><tr><td>Peafowl</td><td>30</td><td>0.09</td><td>885</td><td>0</td><td>0.44</td><td>43.98</td><td>Half-normal</td><td>65.85</td></tr><tr><td>Spotted Deer</td><td>5</td><td>0.016</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Wild boar</td><td>34</td><td>0.11</td><td>2343</td><td>15.68</td><td>0.45</td><td>33.73</td><td>Half-normal</td><td>56.97</td></tr></tbody></table>

Note: n - Number of observed objects (single or clusters of animals) after truncation, p - Probability of observing an object in a defined area, ESW - Effective strip width in meters, N - Estimate of number of animals in specified area, n/l - Encounter rate per kilometre, TW - Truncation Width, - could not be analysed due to low sample size
<table><caption>Table 6. Estimated density of prey species in GAWLS</caption><thead><tr><th rowspan="2">Species</th><th colspan="3">Cluster Size</th><th colspan="3">Density/km<sup>2</sup></th><th colspan="2">Biomass</th></tr><tr><th>E(S)</th><th>SE</th><th>% CV</th><th>DS</th><th>SE</th><th>D</th><th>SE</th><th>BW (Kg)</th><th>BM (kg/km<sup>-2</sup>)</th></tr></thead><tbody><tr><td>Blackbuck</td><td>7.48</td><td>1.67</td><td>22.42</td><td>0.15</td><td>0.04</td><td>1.11</td><td>0.41</td><td>35</td><td>38.85</td></tr><tr><td>Indian Hare</td><td>1.26</td><td>0.11</td><td>9.48</td><td>1.82</td><td>0.55</td><td>2.29</td><td>0.73</td><td>2</td><td>4.58</td></tr><tr><td>Gray Langur</td><td>6.74</td><td>0.68</td><td>10.11</td><td>2.96</td><td>0.38</td><td>19.96</td><td>3.27</td><td>8</td><td>159.68</td></tr><tr><td>Nilgai</td><td>5.19</td><td>0.76</td><td>14.77</td><td>1.69</td><td>0.27</td><td>8.82</td><td>1.92</td><td>180</td><td>1587.6</td></tr><tr><td>Peafowl</td><td>3.18</td><td>0.37</td><td>11.88</td><td>1.07</td><td>0.23</td><td>3.41</td><td>0.85</td><td>5</td><td>17.05</td></tr><tr><td>Wild boar</td><td>5.69</td><td>0.90</td><td>15.87</td><td>1.58</td><td>0.33</td><td>9.02</td><td>2.40</td><td>27</td><td>243.54</td></tr></tbody></table>

Note: E(S) - Estimate of the expected value of cluster size, CS - Mean Cluster size, DS - Estimate of density of clusters, D - estimate of density of animals, % CV - Percentage of coefficient of variations, BW - Average weight of individual (Kg), BM - Biomass of individual

<table><caption>Table 7. Comparison of prey species estimated density in other protected areas of India</caption><thead><tr><th>Location</th><th>Wild boar</th><th>Spotted Deer</th><th>Hanuman langur</th><th>Nilgai</th><th>Barking Deer</th><th>Chinkara</th><th>Blackbuck</th><th>Peafowl</th></tr></thead><tbody><tr><td>Anamalai (Kumaraguru et al., 2011)</td><td>NA</td><td>20.54</td><td>NA</td><td>AB</td><td>0.28</td><td>AB</td><td>AB</td><td>NA</td></tr><tr><td>Bandipur (Karanth & Nichols, 2000)</td><td>NA</td><td>20.1</td><td>NA</td><td>AB</td><td>0.7</td><td>AB</td><td>AB</td><td>NA</td></tr><tr><td>Bhadra (Jathanna et al., 2003)</td><td>NA</td><td>4.51</td><td>22.6</td><td>AB</td><td>3.64</td><td>AB</td><td>AB</td><td>NA</td></tr><tr><td>BRT (Kumara et al., 2012)</td><td>NA</td><td>13.96</td><td>6.34</td><td>AB</td><td>3.7</td><td>AB</td><td>AB</td><td>NA</td></tr><tr><td>Gir (Khan et al., 1996)</td><td>2.1</td><td>50.8</td><td>NA</td><td>0.4</td><td>AB</td><td>2.1</td><td>AB</td><td>NA</td></tr><tr><td>Kanha (Schaller, 1967)</td><td>2.5</td><td>49.7</td><td>NA</td><td>NA</td><td>0.6</td><td>AB</td><td>AB</td><td>NA</td></tr><tr><td>Keoladeo (Haque, 1990)</td><td>2.24</td><td>9.8</td><td>AB</td><td>7</td><td>AB</td><td>AB</td><td>0.76</td><td>NA</td></tr><tr><td>Keoladeo</td><td>3.21</td><td>52.37</td><td>AB</td><td>13.68</td><td>AB</td><td>AB</td><td>AB</td><td>NA</td></tr><tr><td>KMTR (Ramesh et al., 2012)</td><td>NA</td><td>NA</td><td>9.9</td><td>AB</td><td>NA</td><td>AB</td><td>AB</td><td>NA</td></tr><tr><td>Mudumalai (Varman, 1995)</td><td>NA</td><td>25.03</td><td>NA</td><td>AB</td><td>NA</td><td>AB</td><td>AB</td><td>NA</td></tr><tr><td>Nagarhole (Karanth & Sunquist, 1992)</td><td>NA</td><td>50.6</td><td>23.8</td><td>AB</td><td>4.2</td><td>AB</td><td>AB</td><td>NA</td></tr><tr><td>Pench (Biswas & Sankar, 2002)</td><td>2.6</td><td>80.7</td><td>NA</td><td>0.4</td><td>NA</td><td>AB</td><td>AB</td><td>NA</td></tr><tr><td>Ranthambore (Bagchi et al., 2002)</td><td>9.8</td><td>31</td><td>21.75</td><td>11.41</td><td>AB</td><td>5.6</td><td>AB</td><td>NA</td></tr></tbody></table>
<table><thead><tr><th>Location</th><th>Wild boar</th><th>Spotted Deer</th><th>Hanuman langur</th><th>Nilgai</th><th>Barking Deer</th><th>Chinkara</th><th>Blackbuck</th><th>Peafowl</th></tr></thead><tbody><tr><td>2004)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ranthambore (Kumar, 2000)</td><td>3.61</td><td>38.4</td><td>NA</td><td>6.6</td><td>NA</td><td>1.2</td><td>AB</td><td>NA</td></tr><tr><td>Sariska (Avinandan et al., 2008)</td><td>1.64</td><td>27.62</td><td>14.13</td><td>5.19</td><td>AB</td><td>AB</td><td>AB</td><td>NA</td></tr><tr><td>NNTR (Habib, Nigam, Shrotriya, et al., 2016b)</td><td>12.71</td><td>11.12</td><td>57.71</td><td>4.77</td><td>1.34</td><td>AB</td><td>AB</td><td>NA</td></tr><tr><td>TATR(Habib, Nigam, Chatterjee, et al., 2016a)</td><td>9.82</td><td>8.73</td><td>28.52</td><td>5.91</td><td>3.62</td><td>AB</td><td>AB</td><td>4.18</td></tr><tr><td>Gautala Autramghat (Present study)</td><td>9.02</td><td>NA</td><td>19.96</td><td>8.52</td><td>NA</td><td>NA</td><td>1.11</td><td>3.41</td></tr></tbody></table>

Note: NA - Not analysed, AB - Absent, NNTR - Navegaon-Nagzira Tiger Reserve, TATR - Tadoba-Andhari Tiger Reserve, MTR - Kalakad-Mundanthurai Tiger Reserve; BRT - Biligiri Rangaswamy Temple Wildlife Sanctuary
Habitat enrichment, anti-poaching measures, and potential reintroduction programs could help. Increasing the density of key prey species, including nilgai and wild boar, is vital to support larger predator populations, such as tigers and leopards while maintaining overall biodiversity (Shah et al., 2024). Globally, the decline in mammalian species abundance highlights the importance of regular assessments of prey and predator populations to track changes in abundance and distribution (Bagchi et al., 2004). Wildlife managers can easily follow the techniques using scientific methods like line transect sampling, camera trapping, and sign surveys. This study will benefit them for consistent monitoring and informed decision-making.

This research provides a foundational understanding of the current status of mammalian prey species and serves as a baseline for future conservation strategies. Implementing these measures can strengthen GAWLS's role as a critical habitat for biodiversity, contribute to the conservation of threatened species, and support ecosystem stability.

## 5. CONCLUSION

This study represents the first comprehensive assessment of mammalian prey species richness, population structure, and density within the GAWLS Sanctuary. A total of 22 mammalian prey species were documented, including eight species protected under Schedule I of the Wildlife (Protection) Act, 1972, highlighting the sanctuary's importance as a critical habitat for threatened and legally protected species. Notably, large mammals such as the Indian leopard, tiger, and sloth bear were recorded, while smaller taxa like bats, shrews, and most rodents were excluded from the scope of this research. The encounter rates revealed that grey langur, nilgai, and wild boar are the most frequently observed prey species. Group size analysis indicated that blackbuck forms the largest clusters, while the overall prey population is dominated by adult individuals, suggesting a relatively stable and mature prey base. The density estimation further confirmed grey langur as the most abundant species, followed by wild boar and nilgai among ungulates. These three species also accounted for the highest cluster densities, reflecting their significant contribution to the prey biomass available for large carnivores in the region. The findings emphasize the ecological value of GAWLS as a refuge for a

diverse range of prey species, supporting both common and threatened fauna. The high density of key prey species, particularly wild ungulates and primates, provides a crucial food base for large carnivores, including the Indian leopard. This study offers a baseline for future monitoring efforts and underscores the need for continued conservation initiatives to protect the sanctuary's rich biodiversity from ongoing threats.

## DISCLAIMER (ARTIFICIAL INTELLIGENCE)

Author(s) hereby declare that NO generative AI technologies such as Large Language Models (ChatGPT, COPILOT, etc.) and text-to-image generators have been used during writing or editing of this manuscript.

## ACKNOWLEDGEMENT

We sincerely thank the Maharashtra Forest Department for their support in this study. Special thanks to the Divisional Forest Officer (DFO), Assistant Conservator of Forests (ACF), forest guards, and Vanmajur of GAWLS for their invaluable efforts and cooperation during fieldwork.

## COMPETING INTERESTS

Authors have declared that no competing interests exist.

## REFERENCES

- Anderson, D., & Burnham, K. (2004). *Model selection and multi-model inference* (2nd ed.). Springer-Verlag.

- Augustine, D. J., & McNaughton, S. J. (1998). Ungulate effects on the functional species composition of plant communities: Herbivore selectivity and plant tolerance. *Journal of Wildlife Management*, 62, 1165.

- Avinandan, D., Sankar, K., & Qureshi, Q. (2008). Prey selection by tigers (*Panthera tigris tigris*) in Sariska Tiger Reserve, Rajasthan, India. *Journal of the Bombay Natural History Society*, 105.

- Bagchi, S., Goyal, S. P., & Sankar, K. (2004). Herbivore density and biomass in a semi-arid tropical dry deciduous forest of western India. *Journal of Tropical Ecology*, 20, 475-478.

- Biswas, S., & Sankar, K. (2002). Prey abundance and food habit of tigers (*Panthera tigris tigris*) in Pench National Park, Madhya
Pradesh, India. *Journal of Zoology*, 256, 411-420.

Buckland, S. T., Anderson, D. R., Burnham, K. P., & Laake, J. L. (2004). *Advanced distance sampling: Estimating abundance of biological populations*. Oxford University Press.

Carbone, C., & Gittleman, J. L. (2002). A common rule for the scaling of carnivore density. *Science*, 295, 2273-2276.

Champion, H. G., & Seth, S. K. (1968). *A revised survey of the forest types of India*. Government of India Publication.

Chang, C., & Todd, P. A. (2023). Reduced predation pressure as a potential driver of prey diversity and abundance in complex habitats. *njp Biodiversity*, 2(1), 1-5.

Clark, J. S., Carpenter, S. R., Barber, M., et al. (2001). Ecological forecasts: An emerging imperative. *Science*, 293, 657-660.

Foley, J. A., DeFries, R., Asner, G. P., et al. (2005). Global consequences of land use. *Science*, 309, 570-574.

Gordon, I., & Prins, H. (Eds.). (2008). *The ecology of browsing and grazing* (1st ed.). Springer Berlin Heidelberg.

Grewal, V., & Srinivasan, V. (2024). Why do parts of Maharashtra experience different water stress levels? *The Hindu*.

Habib, B., Nigam, P., Chatterjee, N., et al. (2016a). Status of tigers, co-predators, and prey in Tadoba Andhari Tiger Reserve (TATR). Wildlife Institute of India.

Habib, B., Nigam, P., Shrotriya, S., Govekar, R., Phatak, A., & Sawant, U. (2016b). Status of prey in Navegaon-Nagzira Tiger Reserve (NNTR) (Winter & Summer 2016). Wildlife Institute of India.

Haque, N. (1990). Study on the ecology of wild ungulates of Keoladeo National Park Bharatpur, Rajasthan.

Hobbs, R. J. (2001). Synergisms among habitat fragmentation, livestock grazing, and biotic invasions in southwestern Australia. *Conservation Biology*, 15, 1522-1528.

Jathanna, D., Karanth, K. U., & Johnsingh, A. J. T. (2003). Estimation of large herbivore densities in the tropical forests of southern India using distance sampling. *Journal of Zoology*, 261, 285-290.

Jhala, Y. V., Qureshi, Q., & Gopal, R. (2021). *Field guide: Monitoring tigers, co-predators, prey and their habitats* (5th ed.). Technical Publication of National Tiger Conservation Authority, New Delhi & Wildlife Institute of India, Dehradun.

Johnsingh, A., & Manjrekar, N. (2013). *Mammals of South Asia* (Vol. 1 & 2). University Press (India) Private Limited.

Karanth, K. U., & Nichols, J. D. (2000). Ecological status and conservation of tigers in India. Final Technical Report (February 1995 to January 2000).

Karanth, K. U., & Sunquist, M. E. (1992). Population structure, density and biomass of large herbivores in the tropical forests of Nagarahole, India. *Journal of Tropical Ecology*, 8, 21-35.

Karanth, K. U., Nichols, J. D., Kumar, N. S., Link, W. A., & Hines, J. E. (2004a). Tigers and their prey: Predicting carnivore densities from prey abundance. *Proceedings of the National Academy of Sciences U.S.A.*, 101, 4854-4858.

Karanth, K. U., Nichols, J. D., Kumar, N. S., Link, W. A., & Hines, J. E. (2004b). Tigers and their prey: Predicting carnivore densities from prey abundance. *Proceedings of the National Academy of Sciences*, 101, 4854-4858.

Khan, J. A., Chellam, R., Rodgers, W. A., & Johnsingh, A. J. T. (1996). Ungulate densities and biomass in the tropical dry deciduous forests of Gir, Gujarat, India. *Journal of Tropical Ecology*, 12, 149-162.

Kumar, N. S. (2000). Ungulate density and biomass in the tropical semi-arid forest of Ranthambore, India (MSc thesis). Salim Ali School of Ecology and Environmental Sciences, Pondicherry University.

Kumara, N. H., Rathnakumar, S., Sasi, R., & Singh, M. (2012). Conservation status of wild mammals in Biligiri Rangaswamy Temple Wildlife Sanctuary, the Western Ghats, India. *Current Science*, 103, 933-940.

Kumaraguru, A., Saravanamuthu, R., Brinda, K., & Asokan, S. (2011). Prey preference of large carnivores in Anamalai Tiger Reserve, India. *European Journal of Wildlife Research*, 57, 627-637.

Lamichhane, S., Khanal, G., Karki, J. B., Aryal, C., & Acharya, S. (2020). Natural and anthropogenic correlates of habitat use by wild ungulates in Shuklaphanta National Park, Nepal. *Global Ecology and Conservation*, 24, e01338.

McNaughton, S. J. (1985). Ecology of a grazing ecosystem: The Serengeti. *Ecological Monographs*, 55, 259-294.

Menon, V. (2014). *Indian mammals: A field guide* (latest ed.). Hachette India Pvt. Ltd.
MoEFCC. (2016). *Ministry of Environment Forest and Climate Change Notification*. The Gazette of India, New Delhi, the 9th December, pp. 1–29.

Ramesh, T., Sankar, K., Qureshi, Q., & Kalle, R. (2012). Group size, sex and age composition of chital (*Axis axis*) and sambar (*Rusa unicolor*) in a deciduous habitat of Western Ghats. *Mammalian Biology*, 77, 53–59.

Ranjan, V., Hussain, S. A., Badola, R., Vashistha, G., & Dhakate, P. M. (2024). Feeding dynamics of sympatric large carnivores in an anthropogenic landscape of the Indian Terai. *Journal of Threatened Taxa*, 16, 25791–25801.

Shah, S. K., Karki, J. B., Bhatta, B., et al. (2024). Recovery of tigers (*Panthera tigris*): Assessing ecological carrying capacity in Bardia-Banke Complex, Nepal. *Global Ecology and Conservation*, 56, e03326.

Sankaran, M., Hanan, N. P., Scholes, R. J., et al. (2005). Determinants of woody cover in African savannas. *Nature*, 438, 846–849.

Schaller, G. (1967). *The deer and the tiger: Study of wildlife in India*. University of Chicago Press.

Selvan, K. M., Lyngdoh, S., Habib, B., & Gopi, G. V. (2014). Population density

and abundance of sympatric large carnivores in the lowland tropical evergreen forest of Indian Eastern Himalayas. *Mammalian Biology*, 79, 254–258.

The Economic Times. (2021, March). Tiger seen in Guatala Autramghat sanctuary, a first after 1940.

Thomas, L., Buckland, S. T., Rexstad, E. A., et al. (2010). Distance software: Design and analysis of distance sampling surveys for estimating population size. *Journal of Applied Ecology*, 47, 5–14.

Varman, K. (1995). The line transect method for estimating densities of large mammals in a tropical deciduous forest: An evaluation of methods and field experiments. *Journal of Bioscience*, 20, 273–287.

Wang, S. W., & Macdonald, D. W. (2009). The use of camera traps for estimating tiger and leopard populations in the high-altitude mountains of Bhutan. *Biological Conservation*, 142, 606–613.

Winnie, J., & Creel, S. (2017). The many effects of carnivores on their prey and their implications for trophic cascades, and ecosystem structure and function. *Food Webs*, 12, 88–94.

**Disclaimer/Publisher's Note:** The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of the publisher and/or the editor(s). This publisher and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

© Copyright (2025): Author(s). The licensee is the journal publisher. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

### Peer-review history:

The peer review history for this paper can be accessed here:

https://prh.ikprress.org/review-history/12894