Journal of Threatened Taxa |
www.threatenedtaxa.org | 26 May 2023 | 15(5): 23147–23163
ISSN 0974-7907 (Online) | ISSN 0974-7893
(Print)
https://doi.org/10.11609/jott.8145.15.5.23147-23163
#8145 | Received 11 August 2021 | Final
received 07 April 2023 | Finally accepted 05 May 2023
Impact of human activities on wild ungulates in Nagarjunsagar
Srisailam Tiger Reserve, Andhra Pradesh, India
K. Ashok Kumar 1
, Qamar Qureshi 2 & Yadavendradev
V. Jhala 3
1 WWF India, SBH
Colony, Domalguda Hyderabad, Telangana 500029, India.
2,3 Wildlife Institute of
India, Chandrabani, Dehradun, Uttarakhand 248001,
India.
1 ashok.elephas@gmail.com
(corresponding author), 2 qnq@wii.gov.in, 3 yvjhala@gmail.com
Editor: David Mallon, Manchester Metropolitan
University, Manchester, UK. Date of
publication: 26 May 2023 (online & print)
Citation: Kumar, K.A., Q. Qureshi & Y.V. Jhala (2023). Impact of human activities on wild ungulates in Nagarjunsagar Srisailam Tiger
Reserve, Andhra Pradesh, India. Journal of Threatened Taxa 15(5): 23147–23163. https://doi.org/10.11609/jott.8145.15.5.23147-23163
Copyright: © Kumar et al. 2023. Creative Commons Attribution 4.0
International License. JoTT allows unrestricted use, reproduction, and
distribution of this article in any medium by providing adequate credit to the
author(s) and the source of publication.
Funding: National Tiger Conservation Authority (NTCA).
Competing interests: The authors declare no competing interests.
Author details: Ashok Kumar
(AK): wildlife biologist with 15 years of field experience working on tigers, ungulates, and population estimation from the Wildlife Institute of India. Currently working as, a senior project officer
at World
Wide Fund for Nature- India (WWF-India). Qamar Qureshi (QQ):
senior professor at Wildlife Institute of India with more than 30 years of experience in wildlife research, specializing in RS & GIS applications to natural resource management and quantitative ecology. Y.V. Jhala (YVJ): retired senior professor and Dean Wildlife Institute of India, carnivore and ungulate ecologist, having more than 35 years of experience in wildlife research.
Author contributions: Concept, Design & Supervision: YVJ & QQ; Field work, data curation, and analysis: AK; Procuring Funding: YVJ & QQ; Manuscript writing AK & YVJ; MS Review and Comments: AK, YVJ, QQ.
Acknowledgements: We thank the Chief Wildlife Warden of Andhra
Pradesh and the Field Directors Mr. Rahul Pandey and Mr. Sarvannan
Nagarjunsagar Srisailam
Tiger Reserve for permissions and logistic support for the study. We thank
Deepan Chakravarthy, Naitik Patel, Ranjana Pal, Riddhima Solanki, Roshan Puranik,
and Vineet Dubey and our field assistants Kishore, Ashraf, Deva, and Baiyana for their help in field data collection and the
front line staffs of Nagarjunsagar Srisailam Tiger Reserve for accompanying us during field
visits. We also thank Anant Pande, Ujjwal Kumar, Neha
Awasthi, Muthu Veerapan, Shikha Bisht, and Vishnupriya Kollipakam, for their inputs in analysis and also Ninad Mungi, Swati Saini, Adarsh
Kulkarni and Dhruv Jain for GIS inputs. We also thank State Director WWF-
India, Hyderabad office for their support during the manuscript preparation and
Akbar Sharif for assisting in Telugu translation.
Abstract: Human activities
affect wildlife in several ways, ungulates tend to avoid areas of high human
use and alter their behavior to avoid human activity. We used remote camera
traps to quantify the relative abundance and activity of wild ungulates in high
and low human use areas within Nagarjunasagar Srisailam Tiger Reserve (NSTR). Major human activity in
NSTR included collection of forest produce and fuel wood, and livestock
grazing. Poaching for bush-meat and the use of hunting dogs was also prevalent,
but could not be quantified. The relative abundance of wild ungulates was high
in low human-use areas except for chital and wild pigs, which require flat
terrain and water found in prime areas for settlements. Diurnal ungulates like
Chital and Nilgai substantially altered their activity in response to human
activity, as did nocturnal species like Sambar and Mouse Deer. The demographic
response of ungulates in NSTR has been poor compared to other tiger reserves
that have been made free of human use. Our research highlights the importance
of having human-free protected areas so as to achieve the desired conservation
objectives of harbouring viable populations of large
carnivores that require high prey abundance.
Keywords: Activity pattern,
camera traps, human impacts, NSTR, relative abundance.
Global biodiversity declines are being driven
by the direct and indirect effects of anthropogenic actions (Hooper et al.
2012). India supports an extremely high diversity of wildlife (inside and
outside designated PAs); most of these species are found in higher densities
here than elsewhere across their range (Srivathsa et
al. 2023). Remarkable species richness can be found among herbivores, which are
primary consumers at the base of many food chains (Putman 1989). Human
activities including fuelwood extraction, fodder collection, cattle grazing,
consumption of bush meat, and infrastructure development in natural areas can
influence herbivore populations, habitat, behaviour, and relationships
negatively (Meyer et al. 2013; Frey et al. 2017). In places where wild animals
co-occur with humans and space is limiting, animals may minimize contact with
humans by separating themselves in time and/or space (Kronfeld-Schor
& Dayan 2003), often at a cost to their fitness. These activity shifts in
wild animals have been studied using advanced monitoring tools such as
GPS-satellite collars (Berger et al. 2003; Ungar et al. 2005) and camera traps
(Edwards et al. 2020).
The time and activity budgets of species
under different ecological conditions can provide insights into factors that
influence predation, competition, metabolic requirements, and others (Aschoff 1989; Hayward & Hayward 2012; Kasiringua et al. 2017). Camera traps have been used as a
tool for animal population estimation (Karanth
&
Nichols 1998; Rowcliffe & Carbone 2008),
inventorying rare and elusive species (O’Brien et al. 2003), monitoring illegal
activities (Jenks 2012; Hossain et al. 2016), and studying animal behaviour (Wegge et al. 2004). For species where direct observation is
difficult, camera trap data has been used to study animal activity patterns (Rowcliffe & Carbone 2008; Frey et al. 2017). For
species that cannot be individually recognized from coat patterns, camera
trap-based encounter rates are used to compute a relative abundance index (RAI)
that is often correlated with independent density estimates (Carbone et al.
2001; Rovero & Marshall 2009).
Nagarjunsagar Srisailam Tiger
Reserve (NSTR) forms part of the Nallamala Hills of
the Eastern Ghats in Andhra Pradesh. Despite being the largest tiger reserve in
the country (area 3,728 km2; Jhala et al.
2015), there is little ecological data available from the reserve (Srinivasulu 2001). Two forest-dwelling communities, the Lambadas and Chenchus, inhabit
the core area of the Tiger Reserve.
Impacts of humans and their animals on wild ungulates can be due to: 1)
direct hunting, 2) hunting by free-ranging dogs, 3) competition with livestock,
and 4) disturbance/competition caused by extraction of forest produce. These
impacts may influence the demography of ungulates (decreased abundance and slow
growth rates) changes in habitat use, and behavioural changes in time-activity
patterns to avoid human activity periods (Madhusudan & Karanth
2002; Karanth et al. 2009; Dave & Jhala 2011; Ohashi et al. 2013; Ritchie at al. 2013).
Due to human-related activities, the animal
density in NSTR seems to be low (Srinivasulu 2001).
Yet, earlier studies from this site indicates that ungulate sightings were
common in the early morning hours close to waterbodies (Bhargav et al. 2009).
But due to livestock grazing and hunting pressure the detection of prey was
very low and hence proper density estimates were not obtained (Bhargav et al.
2009; Jhala et al. 2011, 2015, 2020).
Due to the presence of armed militant groups
in NSTR until recently, few studies could be conducted and therefore
information on ungulate densities in this area were lacking. The objective of
tiger reserves in India is to use the charismatic tiger as an umbrella species
to protect ecosystems. A demographically viable tiger population requires space
for a minimum of 20 breeding female tigers (Chapron
et al. 2008; Bisht et al. 2019) which translates to an area of about 1,000 km2
with an average of 50 km2 as a female breeding territory in Indian
forests. This area should support ~450 medium sized ungulates per tiger, and
the minimum requirement for a breeding population of tigers is around 34,000 (Jhala et al. 2021). The All India Tiger Estimation Report (Jhala et al. 2020) reports that there were 38 unique tigers
captured in the study area resulting in a density estimate of 0.91 tigers per
100 km2 (SE ± 0.14) and due to low prey sighting on transects the
prey density was not estimated (Jhala et al. 2020).
NSTR is the only tiger reserve in the state of Andhra Pradesh that has a
reasonable number of tigers, and when combined with the tiger reserve of Amrabad in the state of Telangana can potentially
accommodate more tigers in the future.
High-density tiger populations and humans do
not mix well. To create space for a source population of tigers while providing
better livelihoods for forest-dwelling people, a scheme of incentivized
voluntary relocation of human settlements from the core areas of tiger reserves
is implemented by the National Tiger Conservation Authority (Jhala et al. 2021). The relocation incentive scheme
(currently INR 15,00,000 or ~ 20,000 US$ per adult) was not applicable to the
tribal communities of Lambadas and Chenchus since their presence in NSTR was not considered to
be detrimental for tiger conservation due to the perception that tribal
communities lived in harmony with nature and for the utilitarian reason that
they were useful as labour for reserve maintenance and management (E.g.,
patrolling & protection, habitat management activities, and forest fire
management activities) since bringing labour from outside is expensive. Also,
owing to presence of armed militant groups, the implementation of human
resettlement scheme was difficult as militants depended on local forest dwellers
for resources and did not permit them to relocate. Now that militancy in the
area has been subdued, the administration can initiate incentivized voluntary
relocation of all interior settlements to outside of the tiger reserve for
better livelihood options and for creating space for wildlife (Pandey et al.
2013; Jhala et al. 2021).
The present study is a first of its kind in
the Eastern Ghats landscape that evaluates relative abundance of wild
herbivores, their activity patterns, and their behavioural responses to
human-related activities. Our study was constrained by the large size of the
protected area and the low abundance of ungulates (Kothari et al. 1995; Karamsi 2010; Jhala et al. 2015),
making traditional robust approaches like distance sampling impractical due to
the large amount of effort required, compounded by low detections of skittish
ungulates. Under conditions where ungulates are traditionally hunted, the use
of line transect-based distance sampling can be biased, since wild ungulates are
extremely vigilant and would likely detect the observer before they can be
detected and flee, thus potentially be unavailable for sampling.
To understand the ecology of a wild ungulate species, the factors that influence the dynamics of its population or the ecosystem it represents are crucial. Our a
priori hypotheses were that ungulate abundances would be lower in areas of high
human use, and that ungulates would adjust their activity to avoid periods of
high human activity. With this ecological understanding in mind, our
study aims to: a) estimate the relative abundance of wild ungulates in
the park using camera traps and b) quantify the impact of human activities on
the abundance & behaviour of wild ungulates. This study would help us to
better understand the low densities and slow recovery of ungulate populations
in NSTR and provide recommendations for management interventions.
NSTR is the largest tiger reserve in the
country (3,728 km2), demarcated as core and buffer administrative
units of 2,444 km2 and 1,284 km2, respectively. It is
located in the southern Eastern Ghats (15.88333-16.71666 N, 78.50000-79.46666
E) in the state of Andhra Pradesh. Our study area covered 2,500 km2
within two administrative units, namely, Markapur and
Atmakur divisions, including the extended Tiger
Reserve core area constituted by Gundala Brahmeswaram Wildlife Sanctuary (GBM), Velgode,
and Bairlutty ranges (Image 1).
The terrain of NSTR can broadly be classified
as hills, plateaus, valleys, gorges, and escarpments. The vegetation type is
southern tropical dry deciduous, tropical moist deciduous, and tropical thorn
forests (Champion & Seth 1968). Forest contributed to (84%) of land cover
in the study area which is mostly deciduous and scrub/degraded forest followed
by agricultural land (1%), waste land (12%), water bodies (2%), and built up
(1%). In total, forest covers 84% of the study area. These data were calculated
using Arc GIS (v.10.1) (ESRI 2011).
The major portion of rainfall is received
from the south-west monsoon that commences from the second half of June and
continues up to the first week of October. Then there is a short dry spell for
a month. The north-east monsoon is active from November to the first half of
December, mainly on the eastern slopes of Nallamala
Hills. The mean annual rainfall ranges from 590–760 mm (Jhala
et al. 2020). NSTR supports large carnivores like the Tiger Panthera
tigris, Leopard Panthera
pardus, Dhole Cuon
alpinus, Wolf Canis
lupus, Striped Hyena Hyena hyena, Golden Jackal Canis
aureus, and Sloth Bear Melursus ursinus. Wild ungulates found in NSTR are Chital Axis
axis, Sambar Rusa
unicolor, Blackbuck Antelope cervicapra,
Mouse Deer Moschiola meminna,
Nilgai Boselaphus tragocamelus,
Chousingha Tetracerus
quadricornis, and Wild Boar Sus scrofa (Pandey et al. 2013).
The study area encompasses 15 major villages
that were home to two scheduled tribes (Subramanyachary
2013), the Chenchus and Lambadas,
with few other scheduled castes and their livestock, mainly composed of cattle,
buffalos, and goats & sheep. Location of human settlements is mostly
determined by proximity to perennial water and productive flat lands, which are
also prime habitat for wildlife (pers. obs.).
Andhra Pradesh is home to 12 primitive tribal
groups (PTGs), with Chenchu being one of the PTGs
recognized by the Indian government. Later in 2006, the Indian government
proposed renaming the primitive tribal group as primitive and vulnerable for 75
tribal groups in India based on their dependency on hunting, gathering food
from the forest, growth of their population, and literacy level. The purpose of
this classification was to provide assistance so as to uplift the tribal
community in different sectors like education, health, livelihood, skilled
labour, agriculture, housing, while retaining their culture (Ministry of Tribal
Affairs 2015). These communities are mostly confined to the foothills and
low-lying areas of Nallamalla Hills covering Prakasam, Kurnool, Mahaboobnagar,
Rangareddy, Guntur Nalgonda districts of both Andhra
Pradesh and Telangana states (Raju et al. 2009).
Historically, Chenchus
were nomadic hunters and food gatherers inhabiting forested areas, where they
ate honey and tubers, and hunted wildlife for food (Murty
1981). Most Chenchus now live in permanent
settlements called gudem or pentas,
which are a cluster of huts made from bamboo and grass, however, they continue
to engage in collecting honey, grass, fruits, nuts, and leaves as supplements
to their livelihood (Suryakumari et al. 2008). Chenchus still carry traditional bows and arrows when they
move inside the forest that can be used for hunting.
Lambada tribes are called by different names,
such as Sugalis and Banjaras in other parts (Lal
2015). These tribes spread across Andhra Pradesh and Telangana states in
southern India (Vaditya 2019). They live in exclusive
settlements of their own called ‘Thandas’ (Shankar
2016). Present day occupation of majority of Lambadas
in general is cultivation and pastoralism (Karamsi
2010).
Inside the core area of NSTR, there are
around 5,650 households, with a total population of more than 25,000 people and
2,977 cattle, while another 69 villages with 1,26,000 cattle are present in the
buffer zone of the tiger reserve (Bhargav et al. 2009; Mathur et al. 2018). The
entire tribal population within the tiger reserve depends on forest resources
for survival, which are shared with wildlife (Srinivasulu
2001; Sudeesh & Sudhakar 2012).
The smallest administrative unit, i.e.,
forest beats, were used to systematically distribute line transects (n = 142)
to survey the study area. The length of each line transect was between 1.5 to 3
km. Each transect was walked once during the early morning (0600–0800 h)
between December to February of 2014 and 2016. All sightings of animals, the
group size, radial distance to the centre of the group and bearing were
manually recorded on a datasheet. Radial distances to animals were
measured using a hand-held range finder (Bushnell RX1000). Bearings were
recorded using a hand-held compass (Suunto KB 20).
Sampling using camera traps was done across
the study area between January to July 2014 in an area covering 713 km2.
A total of 345 camera locations were sampled, with a double camera unit (Cuddeback attack 1149, Cuddeback
ambush 1194) deployed at each location for about 40 days. Since this exercise’s
primary objective was to obtain a population estimate of tigers, camera
placement was mostly on game trails, dry stream beds, and dirt roads to
maximize photo captures of carnivores. However, we believe that the photo
capture data on ungulates to address our study’s objectives and comparisons
with other sites would remain unbiased as placement locations were similarly
selected across the study area and in other tiger reserves across India (Jhala et al. 2021). We checked cameras every 3–7 days to
download data and check battery status. All photographs were segregated to
species, and information on time, date, and coordinates, recorded for each
image.
Livestock were not free-ranging in NSTR, but
taken out to graze by herders from corrals in each settlement every morning and
brought back by dusk. Herders were often accompanied by dogs. Since livestock
movement was constrained by the distance they could move from their corrals and
from water sources, human, dog, and livestock activity was mostly concentrated
within a certain radius from settlements. Cattle, buffalo, goat, and sheep escorted
by herders were accompanied by the first author from early morning when they
left the corrals to late evening when they returned to their corrals. A
hand-held GPS unit was used by the first author to record the daily grazing
circuit from villages in the winter and summer of 2014 and 2015. The grazing
circuit was mapped using ArcGIS (v. 9.3), the average displacement distance of
livestock herds from settlements/villages was computed, and each settlement was
buffered by the 95% upper bound of this distance to delineate a zone of high
human use. A total count of all livestock in each season was done for each
village and cattle shed across NSTR at a time when livestock were corralled to
determine the total livestock population.
Analysis was done using the conventional
distance sampling approach in Program DISTANCE (v. 6.0) (Buckland et al. 2004).
Due to low detection of ungulate species in NSTR on line transects we pooled
observations from three sampling periods (Jhala et
al. 2011 & 2015 and sampled by first author in 2016) from NSTR and used
line transect observation data from seven other sites in the country (Table S1,
S2) which have the similar habitat type to NSTR for fitting species detection
functions in program DISTANCE to estimate effective strip width.
Shape criteria were examined for heaping, and any outliers were right-hand
truncated where necessary (Buckland et al. 2004). Three key functions (Half
normal and hazard rate all with cosine and Hermite polynomial series
adjustment) were considered for analysis. Model selection was evaluated using
Akaike’s information criteria (AIC), while Kolmogorov–Smirnov statistics were
used to assess the goodness of fit of each model (Buckland et al. 2004). Subsequently,
this pooled effective strip width was used to obtain year wise density
estimates of ungulate species in NSTR.
Relative abundances of the wild ungulates in
the study area were estimated from 2014 camera trap data, as photo capture
rates which were computed by summing independent photo-captures of each species
and dividing this sum by the camera trap operational days. We defined an
independent photo-capture event as follows 1) consecutive photographs of
different species or different individuals of the same species; 2) Consecutive
photographs of individuals of the same species taken more than 30 minutes apart
(O’Brien et al. 2003); and, 3) non-consecutive photos of individuals of the
same species.
We used independent photographs of species to
calculate relative abundance index (RAI) from camera trap images. RAI was
computed as the number of independent photo captures of a species in 100 trap
nights (Carbone et al. 2001). The total effort invested was determined by multiplying
total camera operation day. Camera traps were segregated into two strata based
on their location as i) within the high human - use
areas and ii) those outside this zone as low human impact areas. RAI of
ungulates was also computed separately for these two zones. We hypothesised
that RAI values of ungulates would be lower in high human impact areas and RAI
values of human disturbances (photocaptures of
humans, domestic dogs, and livestock) would be higher in high human impact
areas.
The RAI was computed for each camera trap
location for each species in both high and low human use zones, for testing if
RAI differed between high and low human use zones we used non-parametric
Mann-Whitney U-test (Zar 2022).
Camera trap-based data collection overcomes
biases induced by the skittish nature of wild ungulates which can result in
non-availability for sampling on line transects, but unfortunately RAI does not
allow for rigorous inference on absolute abundance. To test the hypothesis that
RAI is a reliable index of absolute density we regressed the RAI values of
Chital and Sambar (species with a reasonable sample size of observations) with
absolute density estimates of these species obtained from line transect
distance sampling from other similar forest types where absolute density
estimates from distance sampling were also available (Jhala
et al. 2020). A significant positive relationship between RAI and absolute
density would lend support to the hypothesis.
Temporal peak activity pattern
We used camera trap images and their
associated information from the metadata of the images like date, time of the
photograph to understand the temporal activity of six wild ungulate species in
NSTR. The time of the photo capture was used to create a 24-hour activity
pattern graph as well as analysis using Oriana software (v. 4.0). Oriana
uses circular statistics to enumerate the dispersions such as mean vector
length (r) along with confidence intervals. The mean vector has two properties:
direction and length of the mean or angle, and the mean vector length (r)
denotes the clusters of observation around the mean, which ranges from 0 to 1,
where 1 is the frequency of observations very close to the mean and 0 is when
observations are scattered across the study. In the rose plot the arc on the
outer edge extending to either side of the mean represents the 95% confidence
limits Oriana software (v.4). The output provided activity clustering
along with mean peak activity time for wild ungulates and human related activities
factors within a 24-hour cycle, facilitating a quantitative statistical
comparison of their temporal activity.
We estimated the proportion of time active
and activity pattern of ungulates across the day from camera trap data using
the Activity package (v1.3.1) (Rowcliffe 2022)
in Program R (v. 1.4). This provided information on how much time an
ungulate species remains active in a day while the activity pattern describes
the distribution of activity across the 24-hour period. Analysis of data was
done separately for the two human impact strata. We hypothesised that ungulates
in high human impact zones would alter their active behaviour and activity to
avoid peak human associated activity periods (human, dog, and livestock
activity peaks). Temporal overlap of ungulate activity with anthropogenic
disturbances using different packages like Overlap (v. 0.3.3) (Ridout & Linkie 2009) and
ggplot2 (v 3.3.3) in Program R (v 1.4.) software was estimated. We used
the overlap coefficient (Δ), ranging from 0 – no overlap to 1 – complete
overlap (Ridout & Linkie
2009) to estimate the overlap for each wild ungulate species in both high and
low human-use areas with human related activities. Since samples used for
overlap analysis were more than 75 independent photo-captures for most of the
wild ungulate species in both high and low human impact areas we used D-hat 4
estimator for all species (Ridout & Linkie 2009).
Results
The total livestock population in NSTR was
4,403 in summer and 3,934 in winter. The livestock population comprised of
44.5% goats, 31.4% cattle, & 24.0% buffalo during summer and 35.8% goats,
35.4% cattle, & 28.8% buffalo during winter. Average livestock grazing
circuit was 4.0 (SE ± 0.12) km. Livestock ranged more in summer 4.6 (SE ± 0.22)
km than in winter 3.5 (SE ± 0.23) km. The average foraging radius combined for
both seasons was 1.8 (SE ± 0.07) km. The 99% upper bound on the foraging radius
was 2.01 km. Camera traps within a buffer of this maximum foraging radius (2.01
km) around each human settlement / cattle shed were considered to be within
high human activity zone (Image 1).
We obtained 35,306 usable photographs with an
effort of 10,681 trap nights. Humans were photo-captured the most (Table 2).
Wild ungulates constituted 37% of this data. The highest number of captures
were of Sambar (38%) followed by Chital (26%), Wild Boar (18%), Chousingha (9%), Mouse Deer (5%), and Nilgai (4%). RAI was
highest for Wild Boar (10.0), while it was lowest was for Nilgai (1.5) (Table
2). Human impact was recorded throughout NSTR (in the form of human, livestock,
and domestic dog photo-captures), and was similar across the reserve for humans
and domestic dogs since RAIs of humans and domestic dogs were not significantly
different near settlements and away from settlements (Table 2, Figure S1).
Livestock RAI was significantly higher in the proximity of settlements (Figure
S1). Amongst wild ungulates only Chousingha and
Nilgai had significantly higher RAI in low human use areas while Wild Boars had
significantly higher RAI in high human use areas (Table 2, Figure S1).
In support of our hypothesis, the regression
between absolute density and RAI was asymptotically linear with a reasonably
good fit for both Chital (Table S1, Figure S2; R2 = 0.86; P =
<0.001) and Sambar (Table S2, Figure S6; R2 = 0.69; P =
<0.01).
All wild ungulates except Chousingha
showed bimodal activity. Chousingha were diurnal,
Chital and Nilgai were crepuscular and diurnal, Sambar and Mouse Deer were
primarily nocturnal, while Wild Boars showed activity at night and in the
forenoon (Figure S3). All human related activity (humans, domestic dogs, and
livestock) were diurnal, beginning late mornings and extending into late
evening (Figure 1, Figure S3). In agreement with our a priori hypothesis,
within the constraints of some ungulates being diurnal, wild ungulates avoided
all forms of human activities (Figure 1; Figure S3). The 95% confidence
intervals of wild ungulate activities (except Chital) did not overlap any of
the human related activities (humans, livestock, and domestic dogs; Figure S3).
Chital activity in low human use areas overlapped only with the 95% confidence
intervals of livestock active periods (Table 3, Figure S3). Overlap of ungulate
activity with anthropogenic activities within the high-human impact zone was
found to be higher for Chousingha (63%) and the
lowest for Sambar (15%) (Figure S4). For species like Chital, Chousingha, and Nilgai in the low human impact zone, the
overlap with various anthropogenic disturbance factors, such as humans, dogs,
and livestock activities combined, was found to be more than (60%) for Chital
and least for Mouse Deer (18%), respectively (Figure 1).
Discussion
In the Anthropocene, exclusive space for
biodiversity is one of the most limiting factors for conservation (Kipkeu 2014). Many protected areas set aside for wildlife
conservation have people residing within them (Kothari et al. 1995). NSTR has
15 villages with human population of 5,650 families with a population of
~18,000 (Lal 2015), and a livestock population of ~4,500 within the tiger
reserve. In addition to the resident settlements, NSTR is also used by humans
and their livestock from peripheral villages (Image 1). Human and livestock
photo-captures outnumber all other species in NSTR (Table 2), which should be
reason for concern.
Human-related activities contributed 63% of
total independent photo-captures. Photo-captures of humans were high, followed
by livestock and domestic dogs which were all primarily restricted to daylight
hours. However, except for livestock, the presence of humans and domestic dogs
was recorded across the protected area, suggestive of high impacts of human
activities within NSTR and not limited to near the settlements. Though we found
that wild ungulates avoided active periods of humans we found no statistical
differences in relative abundance or activity for most wild ungulates between
areas closer to human settlements (high human use) and further from settlements
(low human use) suggesting a pernicious impact of humans across NSTR.
In a comparative scenario, in Kuno Wildlife Sanctuary with similar dry deciduous forest
like NSTR, the Chital population was found to recover from a density of 4.6 km-2
(Banerjee 2005) to ~40 km-2 (Jhala et al.
2015) after human habitations were relocated from Kuno
and protection from poaching enhanced. Subsequent to the data collection for
this study, we obtained photo-capture of local communities indulging in hunting
activities (Image S1). Wild Boar abundance was not in agreement with our a
priori predictions since they had higher abundance in high human use areas.
This was likely since human habitations were located in flatter productive
terrain (Image 1) which is also the only habitat for Chital and Wild Boars as
these species tend to avoid hilly areas.
Earlier studies on temporal activity of
sambar in India (Schaller 1967; Shea et al. 1990; Lahkar et al. 2020) and on greater mousedeer from Borneo (Ross
et al. 2013) report these species to be nocturnal. Our data confirm these
inherent biological patterns of Sambar and Mouse Deer becoming active well
after darkness and continuing their activity into dawn hours (Lahkar et al. 2020). By being nocturnal, both species avoid
periods of high human activities. However, in human-free areas, Sambar are
recorded to show activity during daylight hours as well (Griffiths & Schaik
1993). Though there were no totally human free areas in NSTR, we did observe
greater daytime activity for Sambar in low human impact zone (Figure 1).
More significantly, the overall active period
of Sambar reduced in high human use areas (Table 2), thereby reducing the
duration available for foraging and other vital activities. At NSTR, chital
were reported to be widely dispersed and to form small herds (Srinivasulu 2001), which contrasts with our observations,
since we found all ungulates to be very skittish, Chital in particular, were at
very low densities and mostly observed as solitary or in very small groups, a
major deviation from observations in other protected areas where chital tend to
be the most abundant wild ungulate, often occurring in large herds. Chital have
been reported as being diurnal with a bimodal activity at dawn and dusk
(Schaller 1967) our results conform to this pattern.
A shift in the activity of Chital (though not
statistically significant) was observed between high and low human-use areas of
NSTR (Figure 1), with the evening peak of activity being less pronounced and
more spread out into the late evening and early night in high human-use areas.
High and low human-use areas actually differed only in terms of livestock use,
with human and domestic dog usage being recorded across NSTR with no
statistical difference across zones.
Livestock is sympatric with wild ungulates in
most forested areas of India (Kothari et al. 1989), where they potentially
compete for essential resources like food and water. Even though livestock
grazes Indian forests to varying extents, their impact on wild native ungulates
is less understood (Madhusudan 2004). Understanding the interaction between
wild ungulates and livestock is complex and varied under different ecological
conditions (Sankar 1994; Dave & Jhala 2011). Though we segregate our camera traps into high
and low human impact zones we caution that human activity was recorded across
NSTR and therefore we find little differences between low and high human impact
zones in terms of timing of activity as well as active duration, these differences
would likely have been more pronounced if compared between total human impact
free areas and human use areas.
More importantly, our data show that all
ungulates across NSTR avoided time periods having high human activities. Often
diseases like foot and mouth can get transmitted between livestock and sambar (Johnsingh & Manjrekar 2015). NSTR has a large resident
cattle population and during the monsoon an additional large number of cattle
migrate from nearby villages to graze (Bhargav et al. 2009).
Presence of domestic dogs in protected areas
shifts wildlife temporally or permanently from the available space they have
(Banks & Bryant 2007). Our results show that domestic dogs were very active
(41%) in high human use areas and domestic dogs usually accompanied humans
(Table 2). Domestic dogs have been traditionally used by forest dwelling
communities to hunt bushmeat. Even the odour of dog urine or faeces can trigger
wild animals to avoid an area (Hennings 2016). Since
domestic dogs occur at densities higher than natural predators, the frequency
of attacks on wild prey species is also likely high, especially in and around
protected areas (Ritchie et al. 2013).
We found that free-ranging dogs often
accompany tribesmen armed with bow and arrows who move around unhindered inside
the protected area on the pretext of collecting non-timber forest products.
While conducting fieldwork AK witnessed incidents where dogs accompanied by
local tribal communities chased Chital. Temporal activity pattern revealed that
activity of dog’s overlap more than 60% of the activity of Chital, Nilgai, and Chousingha. These ungulates being diurnal are limited in
their ability to change their activity to avoid dog activity periods (that are
only diurnal). Thus human impacts and predation through dogs would affect these
diurnal species the most. Domestic dogs were often used for hunting wildlife by
local tribal communities and their impact were likely significant in depressing
ungulate densities as also reported (Madhusudan & Karanth
2002).
Many wildlife species face extinction because
of human impacts; therefore, a prevailing belief is that many species cannot
co-exist with people (Carter et al. 2012). Any human-related activity can
disturb wildlife; one such significant depressant is hunting. Carnivore
assemblages may be affected by direct poaching or through poaching of their
prey. Diverse methods, including domestic dogs, bow and arrows, traps, and
smoking of fossorial mammals, were traditionally used for hunting (Datta & Naniwadekar 2019). It
is recognized that continued overhunting lowers animal densities and
subsequently leads to local, regional, and overall species extinction (Diamond
1989; Rabinowitz 1995). A study from Nagarahole Tiger
Reserve mentions that 78% of local communities interviewed preferred to hunt
Mouse Deer by using domestic dogs (Madhusudan & Karanth
2002).
In NSTR mousedeer has the least overlap with
domestic dog activity (Figure S5) possibly to avoid predation. Hunting also
changes the behaviour of wildlife as seen in Sika Deer in Bialowieza
National Park where they became more diurnal once the park management
restricted tourism and hunting (Kamler et al.
2007). Hunting influenced Wild Boar
activity patterns where it was more diurnal during the non-hunting season in
central Japan (Ohashi et al. 2013). The NSTR management acknowledges that the
resident Chenchu tribals,
who always carry a bow and arrows and are accompanied by domestic dogs whenever
they move inside the forest, do hunt birds and monitor lizards (Pandey et al.
2013). The Lambada tribe, are reported to occasionally hunt small mammals
during festive season (Bhargav et al. 2009). Despite the fact that we were
unable to quantify ungulate poaching as a cause of their low densities, based
on observations and camera trap photographs of such actions, poaching, combined
with high livestock densities, and domestic dog related stress was most likely
to be responsible for NSTR’s low wild ungulate densities.
Our findings suggest that RAI estimates can
help index abundance and can be used to estimate trends in wild ungulate
populations. Our data and inferences show that impacts of human activities
alter wild ungulate abundance and behaviour, as also demonstrated previously
(Gaynor et al. 2018) The tropical dry deciduous forests are among the most
impacted habitats by anthropogenic activities and are vulnerable to degradation
(Chundawat et al. 1999). The forests near human
settlements were more disturbed than those away from settlements. In the short-term,
we recommend active removal of free-ranging dogs, control of poaching, and
minimizing livestock grazing, for wildlife population revival.
Most forest dwellers prefer to relocate when
given a genuine opportunity, since living within protected areas is difficult
due to limited access to basic amenities like electricity, roads, health care,
education, and markets. While within protected areas, their crops are raided by
wild ungulates, and large carnivores often kill their livestock and sometimes
humans (Madhusudan & Mishra 2003; Chapron et al.
2008). However, people rights activists argue that human resettlement from
protected areas is unethical and is not required since forest-dwelling
communities live in harmony with nature and forest resource use by them is
sustainable (Rangarajan & Shahabuddin
2006; Dattatri 2010). In certain instances,
relocation results in transformation of the ‘way of living’ since relocation
usually results in changing nomadic hunter-gatherer or pastoral communities to
a more settled livelihood based on agriculture or labour.
Several communities such as Gujjars in
Uttarakhand, Sahariyas in Madhya Pradesh, and Maldharis in Gujarat face a challenging transition that is
often difficult to make (Rangarajan & Shahabuddin 2006). In line with this argument, the
forest-dwelling tribes of NSTR (Chenchus and Lambadas) have not been offered the NTCA incentive of
voluntary relocation. Thus, without any genuine feasible option to move out of
the core area of NSTR, human settlements continue to grow within the tiger
reserve, and their impact on forest resources remains unabated and increasing
with time. To achieve the conservation objectives of the tiger reserve, i.e.,
to establish a long-term viable population of tigers that act as a flagship and
umbrella species for the conservation of the ecosystem, higher abundance of
wild ungulates is required, for this it seems important to mitigate the current
human impacts in NSTR.
We propose that the incentivized voluntary
relocation package of INR 1.5 million per adult (~ USD 20,000) (NTCA 2021) be
made available to the forest-dwelling communities of NSTR. This would open an
option for potentially better livelihoods and lifestyles to these people
outside of the tiger reserve and benefit both people and wildlife
simultaneously. Future studies should be carried out by camera trap based
monitoring each year, keeping the present study as a baseline, to understand
the status and trends of carnivore and herbivore abundance after human impacts
are reduced/removed within NSTR. Such monitoring should conclusively prove the
depressant effects of humans on wildlife and document the recovery of the wild
ungulate populations (Anonymous 2009).
Table 1. Density
estimates of ungulates in Nagarjunsagar Srisailam Tiger Reserve based on line transect distance
sampling.
|
Species |
Observations |
Model |
Density (SE) |
%CV |
Group density (DS)-
(S.E) |
%CV |
ESW |
Detection
probability (P^) |
Chi P-value |
|
Chital |
22 |
Hazard rate/Hermite
polynomial |
1.80 (0.52) |
29 |
0.52 (0.13) |
26.46 |
50.9 |
0.42 |
0.66 |
|
Sambar |
17 |
Hazard rate/Hermite
polynomial |
0.72 (0.24) |
33 |
0.49 (0.15) |
31.82 |
41.9 |
0.41 |
0.72 |
|
Wild Boar |
13 |
Uniform/Cosine |
0.48 (0.15) |
33 |
0.37 (0.10) |
28.36 |
41.7 |
0.41 |
0.90 |
DS—Group density |
ESW—Effective strip width | SE—Standard error | %CV—Coefficient of variation.
Table 2. Relative
abundance of wild ungulates, livestock, domestic dogs, and humans in Nagarjunasagar Srisailam Tiger
Reserve as estimated from relative abundance index (RAI) from camera trap data.
|
Species |
Total number of
photographs |
Total number of
independent photographs |
Overall RAI |
RAI in the high human- use zone |
RAI in the low human- use zone |
Overall % time
active |
% Time active
in high human- use zone |
% Time active
in low human- use zone |
|
Sambar |
5003 |
923 |
8.6 |
6.7 |
9.2 |
45 |
37 |
47 |
|
Chital |
3443 |
859 |
8.0 |
12.1 |
6.9 |
29 |
28 |
28 |
|
Wild Boar |
2356 |
1073 |
10.0 |
14.4 |
8.7 |
47 |
53 |
41 |
|
Chousingha |
1152 |
383 |
3.6 |
1.9 |
4.1 |
30 |
31 |
30 |
|
Mouse Deer |
665 |
380 |
3.6 |
1.5 |
4.1 |
36 |
23 |
35 |
|
Nilgai |
387 |
158 |
1.5 |
0.5 |
1.8 |
43 |
28 |
36 |
|
Humans |
14033 |
4117 |
38.5 |
50.1 |
35.2 |
38 |
34 |
36 |
|
Livestock |
7127 |
821 |
7.7 |
13.3 |
6.1 |
36 |
28 |
27 |
|
Domestic dog |
1140 |
264 |
2.5 |
2.4 |
2.5 |
39 |
41 |
34 |
Table 3. Temporal
activity pattern of wild ungulates, livestock, domestic dogs, and humans in Nagarjun Sagar Srisailam Tiger Reserve. Mean vector length (r) denotes the
clusters of observation around the mean, which ranges from 0 and 1 where 1 is
the frequency of observations very close to the mean and 0 is when observations
are scattered. The 95% confidence limit of the mean, overlap between HDZ (high
human use zone) and LDZ (low human use zone) 95% CI signifies no statistical
shift in peak activity between the two zones.
|
Species/zone |
No. of observations |
Mean vector (µ) |
Length of mean
vector (r) |
SE mean |
95% C.I |
|
Chital HDZ |
1569 |
10:37 |
0.143 |
00:28 |
09:41–11:32 |
|
Chital LDZ |
1881 |
11:57 |
0.343 |
00:10 |
11:36–12:18 |
|
Sambar HDZ |
664 |
01:38 |
0.659 |
00:08 |
01:22–01:54 |
|
Sambar LDZ |
4085 |
00:47 |
0.51 |
00:04 |
00:38– 00:56 |
|
Chousingha HDZ |
121 |
09:45 |
0.601 |
00:21 |
09:02– 10:27 |
|
Chousingha LDZ |
981 |
10:27 |
0.581 |
00:08 |
10:11–10:42 |
|
Mouse Deer HDZ |
50 |
22:19 |
0.612 |
00:33 |
21:14– 23:24 |
|
Mouse Deer LDZ |
615 |
00:51 |
0.556 |
00:10 |
00:30–01:12 |
|
Wild Boar HDZ |
839 |
02:12 |
0.134 |
00:41 |
00:50– 03:33 |
|
Wild Boar LDZ |
1515 |
08:41 |
0.115 |
00:36 |
07:30– 09:52 |
|
Livestock HDZ |
3257 |
12:14 |
0.697 |
00:03 |
12:07– 12:21 |
|
Livestock LDZ |
3863 |
12:22 |
0.624 |
00:03 |
12:15– 12:29 |
|
Humans HDZ |
4096 |
13:22 |
0.689 |
00:03 |
13:16– 13:28 |
|
Humans LDZ |
9597 |
13:04 |
0.619 |
00:02 |
12:59– 13:08 |
|
Domestic dogs HDZ |
469 |
12:34 |
0.597 |
00:11 |
12:12–12:56 |
|
Domestic dogs LDZ |
668 |
13:48 |
0.693 |
00:07 |
13:33– 14:03 |
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Table S1. Distance
sampling based density estimates for Chital and relative abundance index (RAI) Jhala et al. (2020) obtained from camera trap data for
habitats similar to Nagarjunasagar Srisailam Tiger Reserve.
|
Site |
Density #/ km2 (SE) |
RAI |
|
Nagarjunsagar Srisailam Tiger Reserve |
|
8.0 |
|
Panna Tiger Reserve |
13.78 (2.77) |
20.89 |
|
Achanakmar Tiger Reserve |
12.62 (1.78) |
4.54 |
|
Nawegaon Nagzira Tiger Reserve |
5.16 (1.16) |
2.74 |
|
Pench Tiger Reserve
(Maharashtra) |
20.87 (4.36) |
22.84 |
|
Ranthambore Tiger Reserve |
21.66 (3.34) |
39.90 |
|
Bandhavgarh Tiger Reserve |
41.36 (4.09) |
57.30 |
|
Kanha Tiger Reserve |
38.14 (5.04) |
43.46 |
Table S2. Distance
sampling based density estimates for Sambar and relative abundance index (RAI)
(Jhala et al. 2020) obtained from camera trap data for
habitats similar to Nagarjunasagar Srisailam Tiger Reserve.
|
Site |
Density #/ km2 (SE) |
RAI |
|
Nagarjunsagar Srisailam Tiger Reserve |
|
8.6 |
|
Panna Tiger Rserve |
4.97 |
26.58 |
|
Achanakmar Tiger Reserve |
0.64 |
2.15 |
|
Nawegaon Nagzira Tiger Reserve |
2.81 |
8.51 |
|
Pench Tiger Reserve
(Maharashtra) |
5.41 |
13.98 |
|
Ranthambore Tiger Reserve |
13.95 |
29.43 |
|
Bandhavgarh Tiger Reserve |
3.85 |
10.89 |
|
Kanha Tiger Reserve |
6.95 |
17.14 |