Setting recovery targets for a charismatic species in an
iconic protected area complex: The case of tigers
(Panthera tigris) in Chitwan–Parsa National Parks, Nepal
Bhagawan Raj Dahal
| Rajan Amin
| Babu Ram Lamichhane
Sailendra Raj Giri
| Haribhadra Acharya
| Hem Raj Acharya
Zoological Society of London Nepal
Office, PO Box 5867, Kathmandu, Nepal
Zoological Society of London, Regent's
Park, London, UK
National Trust for Nature Conservation,
Khumaltar, POB 3712, Lalitpur, Nepal
Department of National Parks and
Wildlife Conservation, Kathmandu, Nepal
Panthera, New York, New York
Nature Conservation Foundation,
Mysore, Karnataka 570002, India
Bhagawan Raj Dahal, Zoological Society
of London Nepal Office, PO Box 5867,
Babu Ram Lamichhane, National Trust
for Nature Conservation, Khumaltar, POB
3712, Lalitpur, Nepal.
The Global Tiger Recovery Program has identified enhancing prey populations
as a crucial component in achieving its target of doubling wild tiger (Panthera
tigris) numbers, as prey density is a key determinant of tiger density. We esti-
mate prey abundance and ecological carrying capacity (ECC) of tigers in the
Chitwan–Parsa source site complex within a globally significant tiger
conservation landscape in south-central Nepal. Surveying 605.1 km of line
transects in the Terai plains and Chure hills of Chitwan–Parsa, we estimated
an overall density of 55.43 (36.98–83.45) ungulates/km
, and a biomass of
244,630 (151,520–334,270) kg/100 km
of five abundant ungulates. Chitwan
supports 71.58 (49.02–104.71) and Parsa 30.91 (18.70–51.19) ungulates/km
The prey base can support 177 (119–263) adult tigers based on energetic
requirement models. The tiger ECC was 3.5higher in Chitwan than in
Parsa at a park level. Although opportunities for further recovery of tiger and
prey through targeted habitat management exist, the current population of
170 tigers indicates that this population has likely reached its current ECC. We
recommend that policymakers and park managers change focus from increas-
ing tiger numbers to developing pre-emptive conflict mitigation strategies to
allow the site to retain the successes it has realized.
distance sampling, ecological carrying capacity, line transects, prey density, recovery target
Ensuring the effective conservation and management of
endangered species requires accurate and timely informa-
tion on their populations' distribution, size, and limits.
This is particularly critical for large terrestrial carnivores
that naturally occur at low densities in human-
dominated environments and rely on conservation mea-
sures to secure and recover their populations (Estes
et al., 2011; Ripple et al., 2014). Tigers, Panthera tigris,
Received: 10 November 2021 Revised: 31 January 2023 Accepted: 9 February 2023
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided
the original work is properly cited.
© 2023 The Authors. Conservation Science and Practice published by Wiley Periodicals LLC on behalf of Society for Conservation Biology.
Conservation Science and Practice. 2023;5:e12930. wileyonlinelibrary.com/journal/csp2 1of8
typify the problems faced by most large carnivores. With
around 4000 wild tigers occupying a mere 6% of their
historical range and 70% of the global population concen-
trated within 40 “source sites,”the protection and effective
management of these populations constitute the cornerstone
of global tiger conservation strategies (Goodrich et al., 2022;
Walston et al., 2010). Therefore, site-specific assessments of
these source sites' current and potential population sizes are
necessary to guide conservation investment and actions
(Harihar et al., 2018).
In 2010, the governments of tiger range countries com-
mitted to doubling wild tiger numbers across the range.
Although countries such as India and Nepal have been
making significant progress (DNPWC and DFSC, 2022;
Jhala et al., 2020), there is an urgent need to estimate
tigers' Ecological Carrying Capacity (ECC) at sites to
ensure that conservation goals are defined on site-specific
ecological parameters. This need is acutely felt in Nepal,
which supports 355 adult Bengal tigers (P. t. tigris, hereaf-
ter referred to as the tiger) and has exceeded its initial
commitment to increasing its population to 250 individuals
from a baseline of 121 (100–191) individuals in 2010
(DNPWC and DFSC, 2022;GTRP,2010). In addition, man-
agement agencies are increasingly concerned about the
escalating human-tiger conflict with limited habitat and
prey availability (Aryal et al., 2016; Thapa et al., 2016).
The maximum number of individuals of a species
(tigers, in this case) supported by the resources in a speci-
fied area refers to the site's ECC. Among terrestrial carni-
vores, population density is positively correlated with prey
availability (Carbone & Gittleman, 2002).Inthecaseof
tigers, populations within well-protected reserves are pri-
marily regulated by prey availability, given that they are
socially dominant obligate carnivores (Karanth et al., 2004).
Wild ungulates, ranging in body size from 10 to 250 kg,
compose the principal prey (Hayward et al., 2012). How-
ever, over 50% of ungulate species that tigers prey upon are
threatened, and over 80% of these species have declined due
to habitat loss and degradation, overhunting, and/or con-
flict with agriculturalists (Wolf & Ripple, 2016,2017).
Therefore, estimating prey abundance constitutes a crucial
first step in evaluating a site's potential to function as a
source site, identifying recovery targets, and informing
In this study, we estimate prey densities and biomass
in the Chitwan–Parsa source site complex within a glob-
ally significant tiger conservation landscape in south-
central Nepal to determine the tiger ECC recognizing
that prey densities themselves may possibly be below car-
rying capacity. Nonetheless, given the known relation-
ship between prey abundance and tiger density, prey
availability provides a strong foundation for determining
a realistic goal for tiger densities (Karanth et al., 2004;
Miquelle et al., 2010). Using data from line-transect sur-
veys we conducted in 2019, we estimate species-specific
densities of five of the most abundant ungulates, which
are also the primary prey of tigers within this complex.
We then calculate the potential tiger population size that
can be supported. As the source site complex is managed
as two protected areas, we provide reserve-specific esti-
mates of ungulate densities and tiger ECC. Finally, con-
sidering the debates on whether to manage for continued
growth or enact appropriate management interventions
to conserve and manage the population effectively, we
assess the potential for increasing prey and/or tiger popu-
lation size, and what potential conservation interventions
may be needed for effective species conservation.
2.1 |Chitwan–Parsa complex
Chitwan–Parsa is comprised of two national parks (NP),
together encompass 1579 km
(Chitwan 952 km
) embedded within the eastern section of the trans-
boundary Terai Arc Landscape (TAL) of northern India and
southern Nepal. This source site complex is critical for sus-
taining tiger population recovery in 5000 km
tiger habitat in the region (DNPWC & DFSC, 2018;
Seidensticker et al., 2010; Wikramanayake et al., 2010).
The plains of east Rapti and Narayani rivers support
alluvial grassland habitats comprising the genera Sac-
charum,Themeda,andImperata, and riverine forests domi-
nated by Acacia catechu,Dalbergia sissoo,Trewia nudiflora,
and Bombax ceiba. The Chure (Shivalik) hills (ranging up to
900 m) comprise Shorea robusta and Terminalia-Anogeissus,
with seasonal streams draining these slopes. Although the
habitat types are similar across the two protected areas,
Parsa is hillier (63%) with plains (37%) along the northern
and southern boundaries. In contrast, Chitwan comprises
48% of Chure hills and 52% plains (PNP, 2018;Thapa&
Kelly, 2017). The region experiences a subtropical climate
with a monsoon period from June to September, followed
by a cool, dry season from October to February and a hot,
dry summer from March to May (Carter et al., 2015;Karki
et al., 2015).
Chitwan–Parsa supports an ungulate assemblage of
10 species comprising red muntjac Muntiacus muntjac,
Himalayan goral Naemorhedus goral, hog deer Axis porci-
nus, wild pig Sus scrofa, spotted deer A. axis, Himalayan
serow Capricornis thar,sambarRusa unicolor, nilgai Bosela-
phus tragocamelus,gaurBos gaurus and the greater one-
horned rhinoceros Rhinoceros unicornis (DNPWC &
DFSC, 2018;Karkietal.,2015). However, given that the
goral, serow, nilgai, gaur and rhino either occur at low
2of8 DAHAL ET AL.
densities and/or are not significant prey for tigers, we did
not include these species in this study.
Chitwan NP, established in 1973, is Nepal's oldest NP
and has been a site of significant research and conserva-
tion attention. Parsa NP was, first established as a Wild-
life Reserve in 1984, then was upgraded to a NP in 2017.
Since 2012, Parsa has received increased management
attention leading to the relocation of villages and the sub-
sequent recovery of tigers. In 2018 it was estimated that
there were 93 (89–102) tigers in Chitwan and 18 (16–24)
in Parsa (with a total of 111 adult tigers) (DNPWC &
DFSC, 2018), while in the most recent survey (DNPWC
and DFSC, 2022), tiger estimates are now 128 (121–40)
and 41 (38–50) in Chitwan and Parsa, respectively (total-
ing 170 adult tigers).
2.2 |Estimating tiger prey densities and
Past national tiger surveys were conducted only in the
plains due to logistic constraints (Dhakal et al., 2014;
Karki et al., 2009). However, Thapa and Kelly's (2017)
survey of prey in the Chure hills of Chitwan suggested
that the region retains prey densities capable of
supporting tiger recovery. Therefore, we carried out line-
transect surveys covering the plains and hills to assess
prey status and estimate the ECC for tigers across this
complex. A total of 320 line transects were laid across
Chitwan (106 in the Terai plains and 101 in the Chure
hills) and Parsa (63 in the plains and 50 in the Chure)
(Figure 1). We surveyed between April 29, 2019 and May
25, 2019, after controlled burning had removed much of
the understory and increased visibility, covering a dis-
tance of 372.3 km (270.5 km in the plains and 101.8 km
in the hills) in Chitwan and 232.8 km (160.9 km and
71.9 km in the plains and hills, respectively) in Parsa.
The transects were laid out systematically with a random
start point and north–south or east–west orientation in
the plains, while in the hills, a random start point was
chosen, but the direction was decided based on the ter-
rain. Given the extreme ruggedness of the Chure hills,
some areas in the central parts of the PAs were not cov-
ered. The transects in the plains were surveyed from ele-
phant back, while the transects in the hills were surveyed
on foot (Lahkar et al., 2020; Thapa & Kelly, 2017; Wegge &
Storaas, 2009). The surveys were conducted in the morn-
ings (0630–0930 h) and/or afternoons (1530–1830 h) by
10 survey teams. Each team had two observers, with one
recording observations with the species name, group size,
FIGURE 1 Location of Chitwan–Parsa source site in south-central Nepal, with the 302 line transects distributed across the Terai plains
and Chure hills of the two protected areas.
DAHAL ET AL.3of8
angular distance (using a digital laser range-finder) and
sighting bearing using a compass following standard
protocols used in previous national assessments (Dhakal
et al., 2014;DNPWC&DFSC,2018).
We estimated the population densities of ungulates
from the detection data using the program DISTANCE
(Thomas et al., 2010). We expected two primary sources
of heterogeneity in detection probability: one related to
species and the other to the two habitat types sampled
(also corresponding to the survey method). So, we con-
ducted two sets of analyses to accommodate these varia-
tions while obtaining management-relevant estimates of
ungulates in the two protected areas. Given that body size
and grouping behavior influence detectability (Table S1),
we first constructed species-specific detection models in
the Conventional Distance Sampling (CDS) engine and
derived PA-specific and habitat-specific density estimates
through post-stratification. Second, a combined species
dataset was analyzed for each habitat type using species
as observation covariate within the multiple covariate
distance sampling (MCDS) engine in the program DIS-
TANCE. Here, we modeled species to influence the scale
of the detection function but not its shape. Both global
and separate species detection function estimation was
also selected in the analysis, and PA-specific density esti-
mates were derived through post-stratification. For all
analyses, the smooth function of perpendicular distance
from line transects was modeled using uniform, half-nor-
mal, and hazard rate key functions. Cosine, simple poly-
nomial, and Hermite polynomial adjustment terms were
included where necessary to ensure the detection func-
tion was monotonically decreasing for the CDS analyses.
No adjustment terms were used in MCDS analyses.
Model selection among candidate models was performed
by comparing AIC (Akaike information criterion) values.
Model fit was assessed using the Chi-square test statistic.
Finally, the estimated prey densities were converted to
biomass by multiplying estimated prey densities with 3
of average prey body weight estimates derived from the
literature (presented in Table S1) following (Hayward
et al., 2007).
2.3 |Estimating tigers ecological
To estimate the ECC, we reviewed and used two estab-
lished relationships. The first is based on prey density
(Karanth et al., 2004), and the second is on prey biomass
(Carbone & Gittleman, 2002). First, assuming tigers crop
10% of available prey with a kill rate of 1 per week,
ECC was estimated from prey density (individuals/km
Then, following the generalized scaling relationship
between prey biomass and population density across the
order Carnivora, which suggests that 10,000 kg of prey
biomass supports 90 kg of a given carnivore species, ECC
was estimated from prey biomass (kg/100 km
). In our
estimates, we assumed that one adult tiger would weigh
180 kg in Nepal (Carbone & Gittleman, 2002). Therefore,
20,000 kg could support one adult tiger.
3.1 |Ungulate prey densities and
We recorded 7 ungulate species with 642 independent
detections/observations across the Chitwan–Parsa source
site. Spotted deer was the most sighted ungulate (34.6%;
222 independent detections), followed by Sambar (26.2%;
168), red muntjac (13.4%; 86), wild pig (12.5%; 80), and
hog deer (10.9%; 70). During our surveys, Nilgai (5) and
gaur (11) sightings were too few to include in further
analysis (Table 1). In Chitwan, we recorded 425 indepen-
dent detections of 6 ungulate species at an average
TABLE 1 The number of independent detections and individuals observed (in parentheses) of ungulate species recorded along line
transects in Terai plain and Chure hills of the Chitwan–Parsa source site, 2019.
Prey size Species
Terai plains Chure hills Total Terai plains Chure hills Total
Small Barking deer 43 (55) 7 (7) 50 (62) 33 (35) 3 (3) 36 (38)
Medium Hog deer 67 (173) 3 (4) 70 (177) –––
Spotted deer 153 (1354) 18 (262) 171 (1616) 45 (285) 6 (27) 51 (312)
Wild pig 20 (30) 7 (14) 27 (44) 49 (78) 4 (14) 53 (92)
Large Nilgai –––5 (18) –5 (18)
Gaur 6 (58) 4 (25) 10 (83) 1 (1) –1 (1)
Sambar 62 (108) 35 (74) 97 (182) 64 (126) 7 (11) 71 (137)
4of8 DAHAL ET AL.
encounter rate of 1.29 detections/km, while in Parsa, we
obtained 217 independent detections of 6 ungulates at an
encounter rate of 0.93 detections/km. Detections were
higher in the plains (85.4%) at an average encounter rate
of 1.27 detections/km than in the hilly Chure habitat
(14.6%, 0.54 detections/km).
From the species-specific CDS models, we estimated
an overall density of 55.43 (36.98–83.45) individuals/km
for the five ungulates in the Chitwan–Parsa source site,
with Chitwan supporting 71.58 (49.02–104.71) and Parsa
supporting 30.91 (18.70–51.19) individuals/km
Spotted deer was the most abundant prey (66.5% of over-
all density), followed by Sambar (11.8%), wild pig (9.8%),
hog deer (6.2%), and red muntjac (5.7%). The Terai plains
supported around twice the density (66.19 [44.41–99.09])
compared to the Chure hills (34.8 [23.3–52.2]) (Table S2).
The combined density for the five ungulates in the
Chitwan–Parsa source site from the MCDS analyses was
57.19 (26.93–102.79) individuals/km
, with the plains
supporting higher densities than the Chure hills (Terai
66.2 [31.18–118.95]; Chure 34.81 [16.35–62.65]; Table S3).
Although similar to our CDS analyses, confidence inter-
vals from the MCDS analyses were wider.
We used prey density estimates derived from species-
specific detection functions to estimate an overall prey
biomass density of 224,630 (151,520–334,270) kg/100 km
in the Chitwan–Parsa source site (Table 2). Spotted deer
contributed the highest proportion of biomass (53.1%),
compared to Sambar (36.2%), wild pig (5.4%), hog deer
(3.6%), and red muntjac (1.7%).
3.2 |Tigers' ecological carrying capacity
Based on our estimates of prey, we estimated ECCs of
177 (119–263) adult tigers based on prey biomass and
175 (117–264) adult tigers based on prey density across
the source site. The tiger ECC was 3.5higher in
Chitwan than in Parsa (Table 3).
Our study highlights that, given prey densities estimated
across the plains and hills, the Chitwan–Parsa source site
in south-central Nepal can support 177 (95% CI 119–263)
adult tigers, indicating that the population of 111 (105–
126) estimated in 2018 was below the carrying capacity
(DNPWC & DFSC, 2018). More specifically, Chitwan, with
apopulationof93(89–102) in 2018, could support an addi-
tional 40%, while Parsa can double its tiger population
from 18 (16–24) to 39 (24–64). More recently, national sur-
veys reported that populations have recovered at these two
TABLE 2 Estimated individual animal density (individuals/km
) and biomass density (kg/km
) and associated 95% confidence interval for the five abundant ungulates in the Chitwan–
Parsa source site in 2019.
Prey size Species
Individual animal density Biomass density
Chitwan Parsa Overall Chitwan Parsa Overall
Small Barking deer 3.5 (2.33–5.25) 2.69 (1.67–4.33) 3.18 (2.07–4.88) 55.12 (36.69–82.68 42.36 (26.30–68.19) 50.05 (32.56–76.93)
Medi-um Hog deer 5.67 (3.51–9.16) 3.42 (2.12–5.52) 182.85 (113.19–295.41) 110.24 (68.24–178.11)
Spotted deer 51.95 (36.14–74.68) 13.96 (8.07–24.13) 36.86 (24.99–54.61) 1831.23 (1273.93–2632.47) 492.09 (284.46–850.58) 1299.47 (881.03–1924.91)
Wild pig 2.81 (1.67–4.73) 9.44 (5.72–15.56) 5.44 (3.28–9.03) 67.44 (40.08–113.52) 226.56 (137.28–373.44) 130.62 (78.67–216.731)
Large Sambar 7.65 (5.37–10.89) 4.82 (3.24–7.17) 6.53 (4.52–9.41) 768.82 (539.68–1094.45) 484.41 (325.62–720.58) 655.88 (454.68–945.99)
Total 71.58 (49.02–104.71) 30.91 (18.7–51.19) 55.43 (36.98–83.45) 2905.49 (2003.6–4218.5) 1245.43 (773.67–2012.8) 2246.3 (1515.2–3342.70)
Note: Refer to Table S2 for distance analysis output.
DAHAL ET AL.5of8
sites to a total of 170 adults in the Chitwan–Parsa land-
scape and surrounding areas (DNPWC and DFSC, 2022),
suggesting that the landscape is now likely to be close to
The estimated prey density of 55.43 (37.05–83.58)
for Chitwan–Parsa is comparable to sev-
eral source sites in the TAL, such as Bardia (65.2) and
Shuklaphanta (59.98) NPs in Nepal, Rajaji (40.22), and
Corbett (59.03) NPs in India, and to other alluvial grass-
land and moist woodland habitats, such as Kaziranga
(58.1) and Manas (42.66) NPs in eastern India (Dhakal
et al., 2014; Harihar et al., 2014,2020; Karanth
et al., 2004; Lahkar et al., 2020). These sites either sup-
port some of the highest recorded tiger densities globally
(e.g., Corbett; 14/100 km
and Kaziranga; 13/100 km
et al., 2020) or are hosting rapid tiger population recoveries
(e.g., Bardia and Rajaji; DNPWC and DFSC, 2018;Harihar
et al., 2020). In our study site, Chitwan supports Nepal's
largest tiger population, while Parsa has rapidly recovered
in recent years (DNPWC and DFSC, 2022;Karkietal.,
2015; Lamichhane et al., 2018). Together, these results high-
light the critical role of sites with high prey density in sup-
porting high-density tiger populations. Therefore, ensuring
they remain secure is vital to sustaining population recovery
at landscape scales. However, the source site's linear shape
and the high human density surrounding the parks may
limit tigers' movements and territories.
Across the source site, Chitwan's higher ungulate
densities than Parsa are likely due to differences in avail-
able habitat and conservation legacy. Although forest
types across the source site are similar, Chitwan com-
prises more extensive plains with productive grasslands
and riverine forests than Parsa. In particular, 9.6% of
Chitwan comprises grasslands along three major river
systems and >80 permanent wetlands compared to 0.85%
of Parsa comprising alluvial grasslands along the river
Rapti towards the northern boundary (CNP, 2016;
PNP, 2018). Given that these habitats are preferred by
hog deer and spotted deer (Lamichhane et al., 2020;
Odden et al., 2005; Wegge et al., 2009), these differences
in the extent of the preferred habitat likely resulted in
>3.5higher densities of spotted deer in Chitwan, and
hog deer not being encountered in Parsa (Table 2). Also,
the Chure hills, where seasonally water is not available
and therefore supports lower prey densities (Thapa &
Kelly, 2017), make up over 63% of Parsa, in contrast to
48% of Chitwan. Additionally, because Chitwan is
Nepal's oldest NP and has received significant conserva-
tion attention for nearly five decades, ungulate densities
are likely closer to the carrying capacity. In contrast,
although established in 1984, Parsa was upgraded to a
NP in 2017. Consequently, efforts to reduce anthropo-
genic pressures such as poaching, livestock grazing, and
illegal natural resource extraction have occurred rela-
tively recently (Lamichhane et al., 2018). Therefore,
while recovering, prey densities are likely still not close
to the carrying capacity (Dhakal et al., 2014; DNPWC &
DFSC, 2018). Hence, we believe that the estimated poten-
tial density of tigers for Chitwan is probably close to the
ECC, while the continued recovery of prey in Parsa sug-
gests that the potential ECC for the tiger could still
increase over time. Collectively these two protected areas
constitute over 1500 km
of contiguous protected habitat,
making Chitwan–Parsa a quintessential source site that
can support a large tiger population with over 50 breeding
females, assuming a stable demographic structure and
support recoveries across the eastern TAL (Walston
et al., 2010; Wikramanayake et al., 2011).
Using prey availability to estimate ECC inherently
suggests that ECC for tigers will be altered with prey den-
sity/biomass changes. Given that tigers prefer prey
approximately their own size (Hayward et al., 2012), it is
worth considering management options that will support
populations of large prey and hence more tigers. Recent
studies suggest some grasslands are successioning into
forests, which could adversely affect ungulate densities
(DNPWC, 2020). Habitat management, such as controlled
burns, may effectively maintain grasslands and increase
prey abundance. Targeted habitat improvement measures
to increase gaur densities, which are low in this land-
scape, could also benefit the tiger population at the site.
An unintended negative consequence of recovering
predator and prey species is increased human-wildlife
conflict. Past research documents how tiger recovery in
Chitwan has led to increased conflict with buffer zone com-
munities and highlights conservation actions that have
helped mitigate and reduce loss (Bhattarai et al., 2019;
Gurung et al., 2008; Lamichhane et al., 2018). Given that
TABLE 3 The ecological carrying capacity of tigers (ECC
) based on prey biomass density (kg/100 km
) and ECC
based on individual animal density (individuals/km
), Chitwan–Parsa source site, 2019.
Site Biomass density (kg/100 km
Individual density (ind/km
Chitwan NP (952 km
) 290,549 (200,360–421,850) 138 (95–200) 71.58 (49.02–104.71) 136 (93–199)
Parsa NP (627 km
) 124,543 (77,367–201,280) 39 (24–63) 30.91 (18.7–51.19) 39 (23–64)
Chitwan–Parsa (1579 km
) 244,630 (151,520–334,270) 177 (119–263) 55.43 (36.98–83.45) 175 (117–264)
6of8 DAHAL ET AL.
our analyses suggest that the ECC for tigers has essentially
been reached in Chitwan (while small gains are still likely
as prey populations recover [recovered both in Chitwan
and Parsa based on recent survey]), policymakers and park
managers need to change focus from increasing tiger num-
bers to developing pre-emptive conflict mitigation strategies
to allow the Chitwan–Parsa source site to retain the suc-
cesses it has realized.
In conclusion, estimating the carrying capacity of
tigers in any given landscape provides defensible and
quantifiable recovery goals. Basing estimations on prey
biomass also allows considerations as to what may influ-
ence their abundance and how management actions may
induce increases in prey species, thereby increasing the
ECC of tigers. Managers should recognize that there is
inherent fluctuation in tiger populations; however, by
setting clearly defined recovery goals based on the ecolog-
ical capacity of the landscape, managers can prioritize
conservation investment and action towards recovery in
a timely and adaptive manner.
Bhagawan Raj Dahal https://orcid.org/0000-0003-
Babu Ram Lamichhane https://orcid.org/0000-0003-
Aryal, A., Lamsal, R. P., Ji, W., & Raubenheimer, D. (2016). Are
there sufficient prey and protected areas in Nepal to sustain an
increasing tiger population? Ethology Ecology and Evolution,28,
Bhattarai, B. R., Wright, W., Morgan, D., Cook, S., & Baral, H. S.
(2019). Managing human-tiger conflict: Lessons from Bardia
and Chitwan National Parks, Nepal. European Journal of Wild-
Carbone, C., & Gittleman, J. L. (2002). A common rule for the scal-
ing of carnivore density. Science,295, 2273–2276.
Carter, N., Levin, S., Barlow, A., & Grimm, V. (2015). Modeling
tiger population and territory dynamics using an agent-based
approach. Ecological Modelling,312, 347–362.
CNP. (2016). Grassland habitat mapping. Chitwan National Park.
Dhakal, M., Karki (Thapa), M., Jnawali, S. R., Subedi, N.,
Pradhan, N. M. B., Malla, S., Lamichhane, B. R., Pokheral, P. C.,
Thapa, G. J., Oglethorpe, J., Subba, S. A., Bajracharya, P. R., &
Yadav, H. (2014). Status of tigers and prey in Nepal. Kathmandu,
DNPWC. (2020). Conservation action plan of gaur for Nepal (2020–
2024). Kathmandu, Nepal.
DNPWC & DFSC. (2018). Status of tiger and prey in Nepal.
DNPWC and DFSC. (2022). Status of tigers and prey in Nepal 2022.
Estes, J., Terborgh, J., Brashares, J., Power, M., Berger, J.,
Wardle, D. A. (2011). Trophic downgrading of planet earth.
Goodrich, J., Wibisono, H., Miquelle, D., Lynam, A. J.,
Sanderson, E., Chapman, S., Gray, T. N. E., Chanchani, P., &
Harihar, A. (2022). Panthera tigris. The IUCN Red List of
Threatened Species 2022: e. T15955A214862019.
GTRP. (2010). Global Tiger recovery program. Washington, DC.
Gurung, B., Smith, J. L. D., McDougal, C., Karki, J. B., &
Barlow, A. (2008). Factors associated with human-killing
tigers in Chitwan National Park, Nepal. Biological Conserva-
Harihar, A., Chanchani, P., Borah, J., Crouthers, R. J.,
Darman, Y., Gray, T. N. E., Mohamad, S., Rawson, B. M.,
Rayan, M. D., Roberts, J. L., Steinmetz, R., Sunarto, S.,
Widodo, F. A., Anwar, M., Bhatta, S. R., Chakravarthi, J. P. P.,
Chang, Y., Congdon, G., Dave, C., …Vattakaven, J. (2018).
Recovery planning towards doubling wild tiger Panthera tigris
numbers: Detailing 18 recovery sites from across the range.
PLoS One,13, e0207114.
Harihar, A., Pandav, B., Ghosh-Harihar, M., & Goodrich, J. M.
(2020). Demographic and ecological correlates of a recovering
tiger (Panthera tigris) population: Lessons learnt from 13-years
of monitoring. Biological Conservation,252, 108848.
Harihar, A., Pandav, B., & MacMillan, D. C. (2014). Identifying
realistic recovery targets and conservation actions for tigers in a
human-dominated landscape using spatially explicit densities
of wild prey and their determinants. Diversity and Distributions,
Hayward, M. W., Jędrzejewski, W., & Jedrzejewska, B. (2012). Prey
preferences of the tiger Panthera tigris. Journal of Zoology,286,
Hayward, M. W., O'Brien, J., & Kerley, G. I. H. (2007). Carrying
capacity of large African predators: Predictions and tests. Bio-
logical Conservation,139, 219–229.
Jhala, Y. V., Qureshi, Q., & Nayak, A. K. (2020). Status of tigers,
copredators and prey in India, 2018. New Delhi & Dehradun.
Karanth, K. U., Nichols, J. D., Kumar, N. S., Link, W. A., & Hines, J.
(2004). Tigers and their prey: Predicting carnivore densities from
prey abundance. Proceedings of the National Academy of Sciences
of the United States of America,101,4854–4858.
Karki, J. B., Jnawali, S. R., Shrestha, R., Pandey, M. B.,
Gurung, G., & Karki (Thapa), M. (2009). Tiger and their prey
base abundance in Terai arc landscape, Nepal. Kathmandu.
Karki, J. B., Pandav, B., Jnawali, S. R., Shrestha, R.,
Pradhan, N. M. B., Lamichane, B. R., Khanal, P., Subedi, N., &
Jhala, Y. V. (2015). Estimating the abundance of Nepal's largest
population of tigers Panthera tigris. Oryx,49, 150–156.
Lahkar, D., Ahmed, M. F., Begum, R. H. R. H., Das, S. K.,
Harihar, A., Ahmed, F. M., Begum, R. H. R. H., Das, S., &
Harihar, A. (2020). Responses of a wild ungulate assemblage to
anthropogenic influences in Manas National Park, India. Bio-
logical Conservation,243, 108425.
Lamichhane, B. R., Persoon, G. A., Leirs, H., Poudel, S., Subedi, N.,
Pokheral, C. P., Bhattarai, S., Thapaliya, B. P., & de
Iongh, H. H. (2018). Spatio-temporal patterns of attacks on
human and economic losses from wildlife in Chitwan National
Park, Nepal. PLoS One,13, e0195373.
Lamichhane, B. R., Pokheral, C. P., Poudel, S., Adhikari, D.,
Giri, S. R., Bhattarai, S., Bhatta, T. R., Pickles, R., Amin, R., &
Acharya, K. P. (2018). Rapid recovery of tigers Panthera tigris
in Parsa wildlife reserve, Nepal. Oryx,52,16–24.
DAHAL ET AL.7of8
Lamichhane, S., Khanal, G., Karki, J., 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.
Miquelle, D. G., Goodrich, J. M., Smirnov, E. N., Stephens, P. A.,
Zaumyslova, O. Y., Chapron, G., Kerley, L., Murzin, A. A.,
Hornocker, M. G., & Quigley, H. B. (2010). The Amur tiger: A
case study of living on the edge. In Biology and Conservation of
Wild Felids (pp. 325–339). Oxford University Press.
Odden, M., Wegge, P., & Storaas, T. (2005). Hog deer Axis porcinus
need threatened tallgrass floodplains: A study of habitat selec-
tion in lowland Nepal. In Anim. Conserv. Forum (pp. 99–104).
Cambridge University Press.
PNP. (2018). Parsa National Park and its buffer zone management
plan, FY 2075/76–2079/80. Aadhavar, Bara.
Ripple, W. J., Estes, J. A., Beschta, R. L., Wilmers, C. C.,
Ritchie, E. G., Hebblewhite, M., Berger, J., Elmhagen, B.,
Letnic, M., Nelson, M. P., Schmitz, O. J., Smith, D. W.,
Wallach, A. D., & Wirsing, A. J. (2014). Status and ecological
effects of the world's largest carnivores. Science,343, 1241484.
Seidensticker, J., Dinerstein, E., Goyal, S. P., Gurung, B.,
Harihar, A., Johnsingh, A. J. T., Mandandhar, A.,
McDougal, C. W., Pandav, B., Shrestha, M., Smith, J. L. D.,
Sunquist, M., & Wikramanayake, E. (2010). Tiger range col-
lapse and recovery at the base of the Himalayas. In D. W. Mac-
donald & A. J. Loveridge (Eds.), Biological and Conservation of
Wild Felids (pp. 305–323). Oxford University Press.
Thapa, K., & Kelly, M. J. (2017). Density and carrying capacity in
the forgotten tigerland: Tigers in the understudied Nepalese
Churia. Integrative Zoology,12, 211–227.
Thapa, K., Malla, S., Thapa, G. J., Wikramanayake, E., &
Wikramanayake, E. (2016). Yes, Nepal can double its tiger pop-
ulation. A reply to Aryal et al. Ethology Ecology and Evolution,
Thomas, L., Buckland, S. T., Rexstad, E. A., Laake, J. L.,
Strindberg, S., Hedley, S. L., Bishop, J. R., Marques, T. A., &
Burnham, K. P. (2010). Distance software: Design and analysis
of distance sampling surveys for estimating population size.
Journal of Applied Ecology,47,5–14.
Walston, J., Robinson, J. G., Bennett, E. L., Breitenmoser, U., da
Fonseca, G. A. B., Goodrich, J., Gumal, M., Hunter, L.,
Johnson, A., Karanth, K. U., Leader-Williams, N.,
MacKinnon, K., Miquelle, D., Pattanavibool, A., Poole, C.,
Rabinowitz, A., Smith, J. L. D., Stokes, E. J., Stuart, S. N., …
Wibisono, H. (2010). Bringing the Tiger Back from the brink—
The six percent solution. PLoS Biology,8, e1000485.
Wegge, P., Odden, M., Pokharel, C. P., & Storaas, T. (2009). Preda-
tor-prey relationships and responses of ungulates and their
predators to the establishment of protected areas: A case study
of tigers, leopards and their prey in Bardia National Park,
Nepal. Biology Conservation,142, 189–202.
Wegge, P., & Storaas, T. (2009). Sampling tiger ungulate prey by the
distance method: Lessons learned in Bardia National Park,
Nepal. Animal Conservation,12,78–84.
Wikramanayake, E., Dinerstein, E., Seidensticker, J., Lumpkin, S.,
Chestin, I., Sunarto, S., Thinley, P., Thapa, K., Jiang, G.,
Elagupillay, S., Kafley, H., Pradhan, N. M. B., Jigme, K., Teak, S., …
Than, U. (2011). A landscape-based conservation strategy to double
the wild tiger population. Conservation Letters,4, 219–227.
Wikramanayake, E., Mandandhar, A., Bajimaya, S., Nepal, S.,
Thapa, G., & Thapa, K. (2010). The Terai arc landscape: A tiger
conservation success story in a human-dominated landscape.
In R. Tilson & P. J. Nyhus (Eds.), Tigers of the world: Science,
politics and conservation of Panthera tigris (pp. 161–172).
Wolf, C., & Ripple, W. J. (2016). Prey depletion as a threat to the
world's large carnivores. Royal Society Open Science,3, 160252.
Wolf, C., & Ripple, W. J. (2017). Range contractions of the world's
large carnivores. Royal Society Open Science,4, 170052.
Additional supporting information can be found online
in the Supporting Information section at the end of this
How to cite this article: Dahal, B. R., Amin, R.,
Lamichhane, B. R., Giri, S. R., Acharya, H.,
Acharya, H. R., & Harihar, A. (2023). Setting
recovery targets for a charismatic species in an
iconic protected area complex: The case of tigers
(Panthera tigris) in Chitwan–Parsa National Parks,
Nepal. Conservation Science and Practice,5(6),
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