Journal of Threatened Taxa |
www.threatenedtaxa.org | 26 March 2022 | 14(3): 20703–20712
ISSN 0974-7907
(Online) | ISSN 0974-7893 (Print)
https://doi.org/10.11609/jott.6178.14.3.20703-20712
#6178 | Received 17
May 2020 | Final received 20 January 2022 | Finally accepted 27 February 2022
Distribution and habitat-use of
Dhole Cuon alpinus
(Mammalia: Carnivora: Canidae) in Parsa National
Park, Nepal
Santa Bahadur Thing 1,
Jhamak Bahadur Karki 2, Babu Ram Lamichhane 3,
Shashi Shrestha 4 , Uba Raj Regmi 5 & Rishi Ranabhat
6
1,4 Ministry of Forests, Environment
and Soil Conservation, Lumbini Province, Nepal.
2 Kathmandu Forestry College
(KAFCOL), Amarawati Marga, Koteshwor, Kathmandu, P.O. Box 1276, Nepal.
3 National Trust for Nature
Conservation, Lalitpur, POB 3712, Kathmandu, Nepal.
5 Former Joint Secretary at
Department of National Parks and Wildlife Conservation, Babarmahal,
P.O. Box 860, Kathmandu, Nepal.
6 Department of National Parks and
Wildlife Conservation, P.O. Box 860, Kathmandu, Nepal.
1 sonam.lama200@gmail.com
(corresponding author), 2 jbkarki@gmail.com, 3 baburam@ntnc.org.np,
4 shrestha.shashi2015@gmail.com, 5 ubrajregmi@hotmail.com,
6 ranabhatrishi@gmail.com
Editor: Mewa Singh, University of Mysore,
Mysuru, India. Date of publication: 26 March
2022 (online & print)
Citation: Thing, S.B., J.B. Karki, B.R. Lamichhane, S. Shrestha, U.R. Regmi
& R. Ranabhat (2022). Distribution and habitat-use of
Dhole Cuon alpinus
(Mammalia: Carnivora: Canidae) in Parsa National
Park, Nepal. Journal of
Threatened Taxa 14(3): 20703–20712. https://doi.org/10.11609/jott.6178.14.3.20703-20712
Copyright: © Thing et al. 2022. 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: (1) National Trust for Nature Conservation, Biodiversity Conservation Center,
Sauraha, Chitwan; (2) ZSL
Nepal and Panthera; (3) WWF
Nepal, Hariyo Ban Program, Baluwatar,
Kathmandu.
Competing interests: The authors
declare no competing interests.
Author details: Santa Bahadur Thing—recently involving in the Provincial level
Forest and Wildlife conservation related policy formulation activities. He is
Interested in Wildlife Management outside the Protected areas and its
bottlenecks, Sustainable Tropical Forest management. Habitat suitability
modeling of threatened group of flora and fauna. Jhamak Bahadur
Karki, PhD—interested in Habitat (Grassland wetland) management of tiger
and prey base, Ramsar convention implementation in
Nepal focusing Himalayan wetland.
Involved in Policy formulation process for conservation. Babu Ram Lamichhane, PhD—in-charge of the NTNC's Biodiversity
Conservation Center, Chitwan. He is interested in study of large mammals and
human-wildlife interactions. Mrs. Shashi Shrestha—completed her B.Sc.
Forestry degree in 2016 from Institute of Forestry, Hetauda
under Tribhuvan University, Nepal. Currently, involving in the Provincial level
Forest and Wildlife conservation policy formulation activities. She is
interested in Community Based Sustainable Forest Management, Gender equality
and social inclusion (GESI) in forestry sector.
Mr. Uba
Raj Regmi—the former Joint secretary under the
Ministry of Forests and environment. He is recently involving in community
based conservation practices. He is interested in studying Wildlife ecology and
Protected area management. Rishi Ranabhat—Member
of Asian rhino specialist group, Species survival commission of IUCN. He is
interested in Rhino conservation and habitat management, also Involving in
Wildlife conservation policy formulation.
Author contributions: SBT, JBK & BRL designed the
survey; SBT & BRL analysed the data, SBT wrote
the first manuscript and all authors revised the manuscript.
Acknowledgements: I deeply appreciate and would
like to thank to Prof. Balram Bhatta (PhD) and Prof. Basudev Pokharel for their
intellectual guidance, constructive comments and supports. I also acknowledge
DNPWC and PNP for providing me permission to conduct this research and also for
providing relevant data for this study. I would like to express gratitude to
National Trust for Nature Conservation, Biodiversity Conservation Center, Sauraha, Chitwan, ZSL
Nepal/Panthera and WWF Nepal, Hariyo
Ban Program, Kathmandu for the financial support. I also would like to thank ZSL Nepal and Panthera for providing me camera trap records. I heartily
would like to thank Dr. Kanchan Thapa, Mr. Sujan Khanal and Mr. Gopal Khanal for their help in data collection, processing and analyzing.
Abstract: Dhole Cuon
alpinus is one of the top predators in Asian
forests but is one of the least studied species of carnivores. We surveyed an
area of 499 km2 of Parsa National Park
(PNP) during the winter (November–January) of 2016–17 using camera-traps to
determine the spatial distribution and habitat-use patterns of Dhole. We overlaid 2 x 2 km2 grid cells
(n= 126) across the study area and set up a pair of motion sensor cameras in
each grid cells for 21 days. We modeled the habitat-use by Dholes as a function of sampling
covariates and fine-scale habitat covariates using single species single season
occupancy models. We estimated the parameters in two steps. First, we defined a
global model for probability of habitat-use and modeled
detection probability (p) either as an intercept-only model or as a
function of covariates. Second, we modeled the habitat-use probability (Ψ)
incorporating the top-ranked model for probability of detection (p) in
the first step. A total effort of 2,520 camera-trap-nights resulted in 63
independent detections of dholes at 27 locations in PNP. The naïve occupancy
estimate of Dholes in PNP was 0.21. The estimated probability of habitat-use (Ψ)
and detection (p) were 0.47±0.27 and 0.24±0.05, respectively. Grassland
availability (βG= 8.00±3.09), terrain ruggedness index (βTRI=
0.73±0.34), and Sambar (prey) presence (βS= 1.06±0.51) strong
positive association, whereas, stream/exposed surfaces (βSES=
-0.45±0.43) had negative association with the habitat use by Dholes. Similarly,
detection probability was positively associated with presence of Sambar (βS=
2.44±1.02) but negatively associated with streams/exposed surfaces (βSES=
-0.99±0.32) and terrain ruggedness (βTRI= -0.09±0.23). Our study
provides quantitative information on the ecology of Dholes with potential
applications for improving their conservation efforts in Nepal.
Keywords: Asiatic Wild Dogs, camera-traps,
conservation, ecology, occupancy, social carnivores, spatial scale.
Introduction
Patterns of spatial distribution
and fine-scale habitat-use by species are important aspects to understand their
ecology and to initiate conservation measures to ensure population stability
(Law & Dickman 1998; Phillips et al. 2004; Abrahms
et al. 2016; Massara et al. 2018). Habitat components
such as topography, canopy cover, water sources, prey species availability,
proximity of habitat edges, and anthropogenic activities have significant roles
in shaping the occurrence of a species (Durbin et al. 2004; Grassman
et al. 2005; Jenks et al. 2012; Srivathsa et al.
2014; Aryal et al. 2015; Ferreguetti
et al. 2016; Ferreguetti et al. 2017; Punjabi et al.
2017). Some species are habitat specialists with narrow niche requirements in
specific habitats while others are habitat generalists occurring in a variety
of habitats (Thorpe & Thorpe 2019). Within this behavioural diversity, it
is hard to manage any species without information on its distribution and
ecology (Aryal et al. 2015). Such information is a
prerequisite for planning and developing species conservation strategies (Guisan & Zimmermann 2000; Halstead et al. 2010; Aryal et al. 2014, 2012; Lee et al. 2012).
The Dhole Cuon
alpinus is a habitat generalist and a social
carnivore that lives in packs of 3–20 adults (Valkenburgh
1991; Iyengar et al. 2005; Reddy et al. 2019). Dholes
occur in a variety of habitats, occupying a wide distribution range across
central Asia, southern Asia, and southeastern Asia (Lekagul & Mc Neely 1977; Johnsingh
1985; Srivathsa et al. 2014; Kamler
et al. 2015). They are also found on the islands of Sumatra and Java (IUCN
2015). In Nepal, they are distributed from southern lowland protected areas of Bardia, Chitwan, and Parsa
national parks (Thapa et al. 2013; Yadav et al. 2019) to the northern high
mountain protected areas of Kanchanjunga Conservation
Area, Makalu Barun National Park, and Dhorpatan Hunting Reserve (Jha 2003; Khatiwada
2011; Aryal et al. 2015). Despite their wide
geographical distribution, they are endangered because of low population
density and continued population decline caused by prey depletion, disease,
habitat loss, and persecution (Kamler et al. 2015;
Reddy et al. 2019). The Dhole is categorized as ‘Endangered’ in the IUCN Red
List and placed in Appendix II of CITES (Kamler et
al. 2015; CITES 2017). In spite of its endangered status, there have been
relatively few quantitative studies throughout its range (Khatiwada
2011; Aryal et al. 2015) and very little is known
about its distribution and ecology in Nepal (Thapa et al. 2013). Our study
documents the influence of various ecological factors on the habitat-use
patterns of dholes at a fine spatial scale in Parsa
National Park Nepal. This study generates baseline information about dholes in Parsa with potential applications for improving dhole
conservation efforts in Nepal.
Materials and Methods
Study Area
The study was conducted between
2016 and 2017 in Parsa National Park (PNP) in
south-central Nepal (27.25–27.55 N, 84.68–84.96 E) covering an area of 499 km2
(area of PNP before extension). PNP was established in 1984 as a wildlife
reserve, which was extended eastward to 627.37 km2 in 2015 (Figure
1), and was upgraded to a national park in 2017. Parsa
is the easternmost protected area of the trans-boundary Terai
Arc Landscape (Lamichhane et al. 2018). The park was
established primarily to preserve the unique sub-tropical dry ecosystem and to
protect habitats of resident Asian Elephant Elephus
maximus populations. However, it also provides good habitat for Dholes as
they have been frequently recorded in camera-traps (PNP 2020) and directly
sighted (Thapa et al. 2013). The reduced anthropogenic pressure, improved
security and good prey base (Thapa et al. 2013; Thapa & Kelly2016; Lamichhane et al. 2018) have made the landscape suitable
for Dholes.
PNP has many carnivore species
including the Tiger Panthera tigris, Leopard Panthera
pardus, Striped Hyaena Hyaena
hyaena, Clouded Leopard Neofelis
nebulosa, and Golden Jackal Canis
aureus. The park also supports populations of a wide range of herbivore
species such as Greater One-horned Rhinoceros Rhinoceros
unicornis, Gaur Bos gaurus,
Sambar Rusa unicolor, Nilgai Boselaphus tragocamelus,
Spotted Deer Axis axis, Barking Deer Muntiacus vaginalis, and Wild Pig Sus scrofa (Thapa et al. 2013). Parsa
has a fragile geology and highly porous alluvial substrate. The streams running
off the Churia Hills permeate the porous sediment and
flow underground, reappearing south of the park and restricting water
availability in >70% of PNP throughout the dry months (Lamichhane
et al. 2018). Besides its biodiversity conservation value, PNP also serves the
vital needs of the large human population living south of the park by
conserving water sources and reducing the soil erosion in the Siwalik Hills
(Bhattarai et al. 2018). PNP includes mainly sub-tropical forests of the
Siwalik and Bhabar physiographic regions of Parsa, Makwanpur, and Bara
districts. The vegetation is mainly dominated by Sal Shorea
robust forest (90%). However, the forests are
dominated by Khote salla Pinus
roxburghii on the southern slope of the Siwalik
Hills (60%). The riverbeds and flood plains are covered by riverine species
including Khair Acacia catechu, Simal Bombax ceiba, Kans Saccharum spontaneum,
and Cogon Grass Imperata cylindrica (Chhetri 2003; PNP 2020).
Field Survey
We overlaid 2 x 2 km2
grid cells on 499 km2 area of PNP and set up a pair of automatic
motion sensor digital cameras (Panthera V4 and V5) in
each grid cell selecting the best possible locations. The paired cameras were
positioned 45 cm above ground, perpendicular to, and 5–7 m apart, on either
side of game trails, grassland, forest roads and riverbeds with higher
probability of detecting carnivores (Figure 1). The camera-traps were kept for
21 days within each grid cell. Camera-traps were installed in the field during
the winter season (November–January) of 2016–17. Due to limited camera-traps
availability, the entire area was divided into two blocks and surveyed
sequentially. The camera-traps pictures were sorted species-wise, and all the
Dhole photographs were obtained in a separate folder. Dhole photographs
obtained from a location at 30 minutes apart were considered as independent
detections (Silver et al. 2004; Di Bitetti et al.
2006; Thapa et al. 2013).
Data Analysis
The estimated home-range of dhole
is ~85 km2 (Srivathsa et al. 2017) which
exceeded our sampling unit 4 km2, so we described occupancy as a
measure of ‘habitat-use’ instead of ‘true occupancy’ (Sunarto
et al. 2012; Srivathsa et al. 2014; Thapa & Kelly
2016). We constructed the detection history of dholes in each grid. We
considered 24 hours as a sampling occasion, so that each grid had 21 sampling
occasions. We then grouped five consecutive sampling occasions to obtain four
temporal replicates in each location (discarding first camera-trap day) to
avoid redundancy in data transformations that might arise from zero counts (Kafley et al. 2016; Wolff et al. 2019). The final
detection history of Dholes in each grid therefore included four independent
sampling occasions (replicates). We coded detection of Dholes in each replicate
as ‘1’ and non-detection as ‘0’. We estimated the detection probability and
habitat-use following MacKenzie et al. (2002). We
estimated the probability of detection, p based on the two possible
outcomes for each survey occasion, namely, (1) the animal was detected, p,
and (2) the animal was not detected, 1–p. Consequently, the probability
of habitat-use based on the detectability was translated as follows: (1) the site
was occupied and the species was detected, Ψxp;
(2) the species was present but not detected, Ψx(1-
p); or (3) the species was not present and, hence, not detected, (1-Ψ).
We used single season single species occupancy models (MacKenzie
et al. 2006) to estimate the relative effect of land cover (forest cover,
grassland and streams/exposed surfaces), terrain ruggedness index, distance to
the nearest settlement, and prey species covariates at a fine-scale on the
probability of Dholes habitat-use and distribution. We used the prey species
(Sambar) captured on the same camera-traps as sample covariate and others as
site covariates (Karanth & Sunquist
1995; Andheria et al. 2007; Punjabi et al. 2017).
Areas of different habitat types, i.e., forest cover, grassland, and
stream/exposed surfaces were obtained from supervised classification of Landsat
satellite images and were used as site covariates (Lillesand et al. 2004).
Similarly, we calculated average terrain ruggedness index (TRI) values for each
grid cell from the digital elevation model (DEM) of ASTER Global DEM at 30 m
resolution by using a “DOCELL” command in ArcGIS 10.3. We calculated the
distance of each grid from its center to the nearest
settlements using ArcGIS 10.3 and used this as a surrogate of disturbance
index. We assumed farther the distance from settlements, lower is the
disturbance and higher is the occupancy and vice-versa. All predictor variables
were standardized (z-transformations) so that the model coefficients could be
directly interpreted as effect sizes. We tested auto-correlation between the
predictor variables using Pearson’s coefficients. We constructed covariate
combinations such that highly correlated predictors (Pearson’s |r| >0.70)
did not appear in the same model. For example, grassland and streams/exposed
surfaces were not used together within the same model due to high correlation
between the variables (Pearson’s |r|= 0.74). We performed all analyses
on program PRESENCE Version v2.12.32 and selected the best model based on minimum
Akaike Information Criteria (Burnham & Anderson 2002). We estimated
parameters in two steps. First, a general structure for habitat-use was defined
as a function of forest cover Fc, grassland G, streams/exposed surfaces SES,
terrain ruggedness index TRI, distance to the nearest settlements D and prey
species S i.e. Ψ (Fc+G+SES+TRI+D+S) as global
model Ψ (Global) and modeled detection
probability (p) either as an intercept-only modelor
as a function of individual covariates and their combinations (Table 1).
Second, the habitat-use probability (Ψ) was modeled
incorporating the top ranked model for probability of detection in the first
step (Table 2). Influence of different covariates on habitat-use was again modeled either individually or additively combining
covariates in different biologically plausible combinations. Models with ΔAIC
of <2 were considered to be strongly supported by the data. We used
estimated β-coefficients to assess the strength of association of each
covariate with habitat-use probability. Model fit was assessed for
over-dispersion in the global model by running 1,000 bootstrap iterations
(Burnham & Anderson 2002). The global models with c-hat>4 were
considered structurally inadequate (Burnham & Anderson 2002) and excluded
from further analyses. A total of seven candidate models (Table 2) were run for
determining factors influencing habitat-use by Dholes.
Results
Distribution
of Dholes
With a total survey effort of
2,520 trap-nights at 126 camera-traps locations, we obtained 63 independent
pictures of Dholes in PNP. Dholes were photographed at least once in 27
different locations (21.43% of the surveyed grids) with the naïve occupancy estimate
of 0.21. Dholes were recorded primarily in the Churia
hill forest (59.26%) followed by the forest in plains (29.63%), grassland
(7.41%), and stream/exposed area (3.70%). Most photo-captures were in the
western and northwestern part of the park bordering
Chitwan National Park with a few records on the southern border (Figure 2).
Detection
probability of Dhole
Streams/exposed surfaces (SES),
terrain ruggedness index (TRI), and Sambar (S) affected the detection
probability (p)in the top ranked model (Table 1, Figure 3). The
estimated detection probability (p) was found to be 0.24±0.05. The top
model indicated that dhole detection probability was positive for prey species
Sambar (βS= 2.44±1.02) but was negative for streams/exposed surfaces
(βSES= -0.99±0.32) and terrain ruggedness index (βTRI=
-0.09±0.23) as shown in the Table 1.
Probability
of habitat-use
We used top ranked model for
detectability, Ψ (Global) p (SES+TRI+S) to model fine-scale
habitat-use (Ψ). Among a set of seven candidate occupancy models, the
model with Ψ as a function of grassland and terrain ruggedness index, Ψ
(G+TRI) and p as a function of stream/exposed surfaces, terrain
ruggedness index and Sambar, p (SES+TRI+S) best fit the data. Our model
estimate of the probability of habitat-use (Ψ) was 0.47±0.27, more than
double the naïve occupancy estimate. The model indicated that the habitat-use
was strongly associated with grassland availability (βG= 8.00±3.09),
terrain ruggedness index (βTRI= 0.73±0.34) and prey species (Sambar)
presence (βS= 1.06±0.51) but had strong negative association with
streams/exposed surfaces (βSES= -0.45±0.43) as shown in Table 2. We
model averaged across a set of models for estimating probability of habitat-use
(Figure 4).
Discussion
Our study provides insights into
the factors affecting spatial distribution and habitat-use by Dholes at a fine
spatial scale in PNP, Nepal using camera-trap data. The survey was conducted
primarily to monitor Tigers. Hence, probable bias in camera-traps placement
towards Tigers cannot be denied. However, the camera-traps also produced a good
number of Dhole detections (n= 63), which were used in this study. It provides
an opportunity to obtain information on Dhole but our results may have
underestimated the probability of habitat-use and detection of Dholes in PNP
due to the bias in the placement of camera traps. Positive association of
Dholes with grassland can be explained by the availability of prey species in
higher density and ease of predation in grasslands. Prey populations of large
carnivores occur in a wide range of habitats including grasslands (Karanth et al. 2009; Wegge et al.
2000; Dinerstein 1980, 1979; Schaller 1967). Our
findings are similar to those reported by Jenks et al. (2012) and Grassman et al. (2005) in Thailand. The inter-specific
competition like tigers and leopards, both of which typically prefer lowland
areas, may have pushed the dholes in rugged areas in Siwalik hills (Reddy et
al. 2019; Dhakal et al. 2014; Venkataraman 1995; Johnsingh 1983; Wood 1929). Another reason may be due to
year-round availability of their preferred prey species (Sambar) in these hills
(Thapa & Kelly 2016; Shrestha 2004; McKay & Eisenberg 1974). Moreover,
the rugged areas (Churia hills) of Parsa are generally distant from settlements and hence
there is comparatively less disturbance. We also found strong positive
association between Dhole habitat-use and Sambar presence similar to the
findings of Jenks et al. (2012). This is probably because Sambar is one of the
most preferred prey species of Dholes (Hayward et al. 2014; Acharya et al.
2007). In Parsa, there are many streams flowing from
the Siwalik hills towards south with large amount of sediments deposited in the
streambeds. The streambeds are wide and remain dry most of the time (except
flash floods during rainy season). Avoiding these streambeds and exposed
surfaces by dholes can be linked to the low density of prey species and
difficulty in predation as prey species can easily spot Dholes from a distance.
Previous studies documented the Dhole habitat use increasing with an increasing
distance from forest edge but we did not find the effect of distance to forest
edge (Durbin et al. 2004; Punjabi et al. 2017; Aryal
et al. 2015; Srivathsa et al. 2014; Khatiwada 2011). In a nutshell, our results show that
dholes prefer rugged areas with grasslands and prey (Sambar). In addition to
these findings, obtaining information on their population size and viabilities
in the Terai Arc Landscape (that PNP is a part of) would
be important from a conservation standpoint.
Table 1. Summary of β-coefficient parameter
estimates and associated standard errors (SE) of covariates from top models
used to explain Dhole detection (p) in PNP. Given are intercept (Int.),
stream/exposed surfaces (SES), terrain ruggedness index (TRI), Sambar presence
(S), grassland availability (G), distance to the nearest settlements (D),
Akaike Information Criteria (AIC), relative difference in AIC(∆AIC), and AIC
model weight (W).
Model (M) |
βInt.±SE |
βSES±SE |
βTRI±SE |
βS±SE |
βG±SE |
βD±SE |
AIC |
∆AIC |
W |
Ψ (Global),p(SES+TRI+S) |
-2.29±0.15 |
-0.99±0.32 |
-0.09±0.23 |
2.44±1.02 |
- |
- |
256.03 |
0 |
0.46 |
Ψ (Global),p(TRI+S) |
-1.29±0.11 |
- |
-0.25±0.16 |
0.47±0.21 |
- |
- |
257.42 |
1.39 |
0.23 |
Ψ (Global),p(S) |
0.31±0.14 |
- |
- |
0.50±0.25 |
- |
- |
257.64 |
1.61 |
0.21 |
Ψ (Global),p(SES) |
0.51±0.78 |
-0.30±0.13 |
- |
- |
- |
- |
260.53 |
4.50 |
0.05 |
Ψ (Global),p(G+S+TRI+D) |
1.13±0.71 |
- |
-0.22±0.17 |
0.41±0.11 |
-0.48±0.16 |
-0.19±0.13 |
261.23 |
5.20 |
0.03 |
Ψ (Global),p(.) |
2.13±1.45 |
- |
- |
- |
- |
- |
262.20 |
6.17 |
0.02 |
Table 2. Summary of β-coefficient parameter
estimates and associated standard errors (SE) of covariates from top models
used to explain dhole habitat use (Ψ) in PNP. Given are intercept (Int.),
grassland availability (G), terrain ruggedness index (TRI), Sambar presence
(S), stream/exposed surfaces (SES), Akaike Information Criteria (AIC), relative
difference in AIC(∆AIC), and AIC model weight (W).
Model (M) |
βInt.±SE |
βG±SE |
βTRI±SE |
βS±SE |
βSES±SE |
AIC |
∆AIC |
W |
Ψ (G+TRI),p(SES+TRI+S) |
0.91±0.37 |
8.00±3.09 |
0.73±0.34 |
- |
- |
251.54 |
0.00 |
0.49 |
Ψ (G+S),p(SES+TRI+S) |
-1.19±0.23 |
0.21±0.09 |
- |
1.06±0.51 |
- |
252.56 |
1.02 |
0.29 |
Ψ (G),p(SES+TRI+S) |
0.63±0.09 |
0.29±0.16 |
- |
- |
- |
254.86 |
3.32 |
0.09 |
Ψ (Global),p(SES+TRI+S) |
-0.61±0.47 |
8.78±2.81 |
-3.70±1.15 |
2.31±1.20 |
-3.70±1.151 |
254.97 |
3.43 |
0.09 |
Ψ (SES+S),p(SES+TRI+S) |
-1.26±0.24 |
- |
- |
0.39±0.51 |
-0.45±0.43 |
258.09 |
6.55 |
0.02 |
Ψ (S),p(SES+TRI+S) |
-1.19±0.22 |
- |
- |
0.38±0.51 |
- |
260.70 |
9.16 |
0.01 |
Ψ (.),p(.) |
0.29±0.16 |
- |
- |
- |
- |
262.20 |
10.66 |
0.00 |
For figures &
image - - click here
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