Journal of Threatened Taxa |
www.threatenedtaxa.org | 26 October 2019 | 11(13): 14643–14654
Habitat
suitability modeling of Asian Elephant Elephas
maximus (Mammalia: Proboscidea: Elephantidae) in Parsa National
Park, Nepal and its buffer zone
Puja Sharma 1, Hari
Adhikari 2, Shankar Tripathi 3, Ashok Kumar Ram 4 &
Rajeev Bhattarai 5
1,3 Faculty of Forestry, Agriculture
and Forestry University, Hetauda, Nepal.
2 Earth Change Observation
Laboratory, Department of Geosciences and Geography, University of Helsinki,
Finland.
2 Institute for Atmospheric and
Earth System Research, Faculty of Science, University of Helsinki, Finland.
4 Conservation Officer, Department
of National Parks and Wildlife Conservation Nepal.
5 Tribhuvan University, Institute
of Forestry, Pokhara, Nepal.
1 oujasharma@gmail.com
(corresponding author), 2 hari.adhikari@helsinki.fi, 3 stripathi@afu.edu.np,
4 ashokrink11@gmail.com, 5 bhattarairajeev@gmail.com
doi: https://doi.org/10.11609/jott.4467.11.13.14643-14654
Editor: L.A.K. Singh, Bhunaneswar,
Odisha, India Date of publication: 26
October 2019 (online & print)
Manuscript
details: #4467 | Received 02 August 2018 | Final received 27 June 2019 | Finally
accepted 18 September 2019
Citation: Sharma, P.,
H. Adhikari, S. Tripathi, A.K. Ram & R. Bhattarai (2019).Habitat suitability modeling of Asian Elephant Elephas maximus
(Mammalia: Proboscidea: Elephantidae)
in Parsa National Park, Nepal and its buffer zone. Journal of
Threatened Taxa 11(13): 14643–14654; https://doi.org/10.11609/jott.4467.11.13.14643-14654
Copyright: © Sharma et
al. 2019. Creative Commons Attribution 4.0 International License. JoTT allows
unrestricted use, reproduction, and distribution of this article in any medium
by adequate credit to the author(s) and the source of publication.
Funding: None.
Competing interests: The authors declare no competing interests.
Author details: Puja Sharma is doing MSc in Tropical and International Forestry
at University of Gottingen, Germany. She has completed BSc in forestry from
Agriculture and Forestry University and worked in the field of Natural Resource
Management and wildlife. Hari
Adhikari defended his PhD
at University of Helsinki, Finland. He has international working
experience on wildlife and
forestry in Nepal,
India, Philippines, Kenya, Germany
and Finland. Shankar Tripathi is young faculty member
of Faculty of Forestry at AFU, who have involve in lecturing and research on
forest measurement and application of Remote sensing and GIS in the field of
nature conservation. He has accomplished
post graduate degree in Forestry from Tribhuvan
University. Ashok Kumar Ram holds MSc on Forestry
from Institute of Forestry Pokhara, Nepal and studying his PhD on Wildlife
Science from Wildlife Institute of India. He is an IUCN Species survival
commission members for Asian Elephant specialist group. Rajeev
Bhattarai is a graduate student in School of Forest Resources,
University of Maine with a undergraduate degree in forestry from Tribhuvan
University, Nepal.
Author
contribution: PS planned and conducted this
research, HA and ST
supervised this research.
HA, PS and ST
together worked on manuscript. HA and PS collected RS and GIS
data. PS, RB and ST collected field data. AKR supervised PS during field data
collection.
Acknowledgements: Permission for the study was
acquired from the Department of National Park and Wildlife Conservation, the
government of Nepal. We would like to
thank Hari Bhadhra Acharya (Chief Conservation
Officer, Parsa National Park (PNP) for his support
during this study. This article is based on the bachelor thesis submitted to
Agriculture and Forestry University, Faculty of Forestry, Hetauda,
Nepal in partial fulfillment of the requirements for
the degree of Bachelor of Forestry Science. Anonymous reviewers and the Journal
Editor are thanked for useful insights and comments that helped improve this
work.
Abstract: Asian Elephants Elephas
maximus in Nepal are known to have habitats and movement corridors in Parsa National Park (PNP) and its buffer zone (BZ), located
east of Chitwan National Park. A study
was conducted in this area to assess the suitability of PNP and BZ as elephant
use areas, and to determine factors relevant to the presence of elephants in
PNP. Field measurements were carried out
in 67 plots for vegetation analysis. Boosted Regression Tree (BRT) analysis was
used to examine the relationship of habitat suitability and variables including
topography (slope, aspect, altitude), climate (precipitation, temperature),
habitat preference, ground cover and crown cover. The results indicate that elephant habitat
suitability is mainly determined by the dominant plant species, temperature, altitude,
habitat preference and precipitation.
Slope, ground cover, crown cover and substrate have lesser effects. Elephants were recorded up to 400m in the
northeast and southeast aspects of the study area. Most suitable habitats were low slope forest
dominated by Acacia catechu and Myrsine
semicerate that received 300mm annual
precipitation. The model emphasizes
environmental suitability, and contributes to knowledge for conservation of
elephants in PNP and BZ by delineating sites that require specific planning and
management.
Keywords: Boosted Regression Tree,
corridor, elephant habitat suitability, important value index, vegetation.
The Asian Elephant was recognized as an endangered
species in 1975 after its inclusion in Appendix I of CITES (Convention on
International Trade in Endangered Species of Wild Fauna and Flora) (Bisht 2002)
and listed as “Endangered” on the IUCN Red List of Threatened Species (IUCN
2017). These elephants are found in a
variety of habitats that include grasslands, tropical evergreen, moist
deciduous, dry deciduous and dry thorn forests, as well as secondary forest,
scrublands, and cultivated areas (Sukumar 2003). Armbruster & Lande
(1993) stated that human encroachment of natural habitats is one of the most
critical issues facing elephant conservation.
In Asia, elephants have lost extensive habitat areas, and as a result,
conflicts with people have increased (Santiapillai
1997).
In Nepal, elephants are distributed throughout the
lowland Terai in four isolated populations ranging
over 10,982km2 of forest habitat (DNPWC 2008). The estimated number of resident wild
elephants in Nepal is between 107 and 145 (DNPWC 2008; Pradhan et al.
2011). The eastern population has 7–15
resident animals and 100 migratory animals from India. In central Nepal, 20–25 elephants reside
primarily in Parsa National Park (PNP) and Chitwan
National Park (CNP). The western and far
western populations consist of 60–80, and 15–20, wild elephants respectively
(DNPWC 2008; Pradhan et al. 2011).
Habitat conservation is an important aspect of
wildlife conservation, and habitat suitability analysis is an essential aspect
of management of wild animals such as elephants. Habitat suitability modeling
can predict the quality and suitability of habitats for given species based on
predictor variables such as topography (aspect, slope, altitude), climate
(temperature, precipitation) and other biotic and abiotic factors. Different methods of modeling
are used to determine suitable habitats for elephants. The boosted regression trees (BRT) method is
an ensemble tree-based species distribution modelling technique that
iteratively grows small/ simple trees based on the residuals from all previous
trees (Elith et al. 2008). BRT has proven useful for working with large
datasets of environmental variables and observations (Elith
et al. 2008). For example it has been
used to identify determinants of above ground biomass (Adhikari et al. 2017)
and fish species distribution (Elith et al. 2008; Trigal & Degerman 2015). BRT and geographic information have also
proven to be effective in the assessment of habitat quality.
The present study aims: 1) to assess the suitable
habitat of elephants, and 2) to determine which explanatory variables better
explain elephant presence in PNP and buffer zone. This study has assessed habitat suitability
in order to provide insights towards better management of elephant populations.
The study was conducted in Parsa
National Park (PNP) and its buffer zone (BZ), located in the sub-tropical zone
of the southern part of Nepal. It has an
area of 627km2. In 1984, PNP
was established to preserve the habitat of natural populations of Asian
Elephant Elephas maximus, Tiger Panthera
tigris, and Gaur Bos gaurus
(Rimal et al. 2018). The BZ of PNP was declared in 2005, which
covers an area of 285.17km2 encompassing three districts and 11
village development committees (VDC) (Figure 1). The region experiences four different
seasons: summer (April–June), rainy/monsoon (July–September), winter
(October–December), and spring (January–March).
The forests of PNP consist of tropical and subtropical
tree species. Sal Shorea
robusta forests compose about 90% of the park’s
vegetation. The riverine forests are
found along the banks of rivers entailing species like Sisso
Dalbergia sisoo,
Silk Cotton Tree Bombax ceiba, and Khair Acacia
catechu. Grass including Siru Imperata cylindrica and Kans Saccharum spontaneum
are in the park. PNP and BZ support
various endangered animal species including wild Asian Elephant, Royal Bengal
Tiger Panthera tigris,
and Sloth Bear Melursus ursinus. Mammals including Blue Bull Boselaphus tragocamelus,
Sambar Rusa unicolor, Hog Deer Axis porcinus, Barking Deer Indian muntjac, Rhesus
Macaque Macaca mulatta,
and Palm Civet Paradoxurus hermaphrodites
are also found in the park.
Anthropogenic pressures like sand extraction, shifting cultivation and
domestic cattle grazing are high in PNP and BZ (CHEC Nepal 2012).
Field work was conducted during the morning hours of
May–June 2017. In reconnaissance, the
habitats preferred by elephants were identified in consultation with local
people. Questions concerned areas where
elephants were frequently sighted, places where indirect signs of elephants
were found, and availability of water. Reconnaissance field visits were made
with the help of elephant rides, on foot and by vehicle, and areas were
allocated into blocks according to habitat types. Sample plot centers
were positioned using hand-held Garmin global positioning system (GPS) with a
2–5 m accuracy.
Nested quadrats of different size were purposively
assigned in the study area (Figure 2).
Total 67 plots were assigned and used to assess the status of tree, pole
and regeneration condition. Quadrats of
10m × 10m were set in the study area to calculate the intensity for tree
species. All plant species within each
quadrat were identified and counted. For
trees, trunk diameter at breast height (DBH; 1.3m) and height was
measured. Quadrats of 5m × 5m were
allocated randomly for shrubs. Herbs and
regeneration were recorded from nesting sampling of 1m × 1m quadrate within the
5m × 5m quadrate.
Tree diameter, height, dominant species, crown cover
and ground cover were measured, poles and regeneration were counted and in
cases of grasses, clumps were counted within each quadrat. Plant species were identified by a local
para-taxonomist, field guide and also based on literature related to plant
identification in Nepal (Rimal et al. 2018). Leaves
of unidentified tree species were brought to the faculty of forestry at
Agriculture and Forestry University (AFU) and were identified.
To assess the habitat, important value index (IVI) and
prominence value (PV) of vegetation available in the habitat range is
crucial. The vegetation data collected
in the field were used to calculate IVI, density, relative density, frequency,
and relative frequency of the tree species by using equations 1–8 explained in
Greig-Smith (1983). The IVI of a species signifies its dominance and ecological
success, its good power of regeneration and greater amplitude. The IVI was calculated by using three
measures including relative frequency, relative density, and relative
dominance. Vegetation data were calculated
following the broad principle described by Mishra (1968) and Mueller-Dombois & Elienberg
(1974). Basal area helps to determine
the dominance and nature of the community and it refers to the actual ground
covered by the stems. Density is
generally used for large plants that have discrete individuals (Zobel et al.
1987). Frequency and relative frequency
give an index on the spatial distribution of a species (Krebs 1978). To calculate the prominence value, the
percentage cover of each species is estimated in each quadrate and recorded in
classes as follows, for high coverage = > 50%, medium= 26–50% and low =
0–25%. Prominence value is used to
calculate the availability of plants in the research sites (Jnawali
1995).
1. Density of species = (Total number of individuals
of a species) / (Total number of quadrats sampled × area of a quadrate)
2. Relative density of species (RD) = (Total
individuals of species) / (Total individual of all species)
3. Frequency of species = Number of plots in which a
particular species occurs / Total number of plots sampled × 100
4. Relative frequency of species (RF) = Frequency
value of a species / Total frequency of all species × 100
5. Relative dominance of species = Total basal area of
a species / Total basal area of all species × 100
6. Basal area = π d2/4
7. Important value index (IVI) = Relative density +
Relative frequency + Relative dominance
8. PVX = MX (√FX)
(where, d = diameter at breast height (1.3 m) of tree,
PVX = prominence value of species X; MX = mean percentage cover of species X;
FX = Frequency of occurrence of species X)
A range of explanatory variables was derived from
geospatial data sets for modeling habitat
suitability. Table 1 presents the
complete list of variables. The slope,
aspects, and altitude were derived from the Japan Aerospace Exploration Agency
(JAXA) digital elevation model (dem). Precipitation and temperature were downloaded
from WorldClim data.
Field measurements, dominant species, habitat preference, segment type,
crown and ground cover and substrate conditions were derived. All topographic, climatic, and land use data
available for the study area were resampled to 30m resolution and UTM 45N, WGS
84 projection system. For each absence
and presence of GPS location, these variables were extracted. The correlation co-efficient between the
explanatory variables and presence-absence data of elephant is shown in
Appendix 1.
Boosted regression tree (BRT) (Elith
et al. 2008) was used for examining the habitat preference area for elephant.
BRT handles different types of predictor variables and accommodates missing
data (Elith et al. 2008). Besides these, there is no need for prior
data transformation or elimination of outliers.
This is an advanced form of regression methods, which consists of two
component—regression trees and boosting.
BRT analysis was done using the ‘dismo’
package in R. The Bernoulli error
distribution was used. Furthermore, the minimum predictive error was achieved
when using a learning rate of 0.001, tree complexity (interaction depth) of 5,
bag fraction of 0.75 and tolerance method “fixed”. All predictor variables were used as BRT can
handle multi-collinearity among variables.
Results
IVI was calculated to find out the dominant tree
species (Appendix 2) and prominence value was observed in the case of shrubs
and herbs (Appendix 3 & 4). We
calculated the species diversity of the study area for trees. Fifty-seven species were present in the
quadrates; among them, 10 tree species were the dominant tree species present
in the study area. In the study area, Sal
(IVI–50.7753) was found most dominant and Careya
arborea (IVI–5.2802) as least dominant. The species including Mallotus
philipinensis, Dillenia pentagaina, and Careya arborea have the highest IVI among all, and they are
the most preferred species of the elephant.
To determine the preferred habitat used by elephant,
we calculated the PV of shrubs and herbs.
Among 40 species, each of shrubs and herbs was present in the study
area. Among the shrub species, Eupatorium
spp. (PV–306.25) was the most abundant species and Bauhinia vahilli (PV–53.07) was the least abundant. Among the herb species, Imperata
cylindrica (PV–317.66) was the most abundant and Piper
longum (PV–29.48) the least abundant. The shrub species including Eupatorium odoratum, Leea macrophylla, and Cleroden dronviscosum and
herb species including Imperata cylindrica, Saccharum spontaneum, and Fritillaria camschatcensis
have the highest PV among all species found in the study area as well as, they
are the most preferred species of the elephant in the study area.
The total deviance explained by the BRT model was
0.16. The correlation between different
variables, including presence-absence, altitude, land cover of the plot,
segment type, substrate condition, dominant species, ground cover, crown cover,
habitat preference, precipitation, temperature, slope, and aspect is shown in
Appendix 1. The relative influence of
each predictor variables is shown in Figure 3.
Each predictor variable has different relative contributions for the BRT
model. Dominant species, temperature,
and altitude have higher relative influence, whereas ground cover, crown cover
and substrate condition have a lower relative influence.
Prioritized dependence plots visualize the effect of a
single variable on the model response, holding all other variables
constant. Model results vary the most
with dominant species as seen in the first left plot (Figure 3). Dominant
species (34%), temperature (15.3%), altitude (12.4%), habitat preference
(11.1%) and precipitation (8.8 %) have the highest relative influence
percentage and play a crucial role in the elephant distribution based on these
plots. For more details on how they were
calculated and model parameters used, see Sharma (2017).
On the basis of partial dependence plots, the elephant
was more available at the altitude of 250–350 m with precipitation 310mm. The suitable habitat for the elephant was at
the temperature of 28.5°C, a slope of 0–5° and in the northeastern
and southeastern regions. Dominant species shows that Acacia catechu
(AcC) and Myrsine
semicerata (MyS) forest
are more suitable for the elephant. Species including Dillenia
pentagaina (DiP), Saccharum spontaneum (SaS), and Pennnisetum
purpureum (PeP) are the most preferable species
of the elephant. Elephants dwelled in
forest dominated by Mallotus philipinensis followed by Syzigiym
cumini.
Thus areas having these species were the most suitable habitats.
The weighted mean of discrete data was not available,
whereas the weighted mean of continuous data was altitude (264m), precipitation
(310mm), temperature (28.6 °C), slope (5.6°) and aspect (190°). Elephants were found mostly around the fire
line and river, at an altitude of 150–350 m with temperature around 28.6 °C,
crown cover 40–70 and slope below 0–5° (Figure 4).
The correlation between elephant presence-absence and
temperature is 0.24, that implies a slight positive relationship between them,
the elephant is mostly found in increasing temperature (Appendix 1). Whereas there is almost no linear association
between presence-absence, and slope, dominant species, land cover of the plot,
crown cover and ground cover. The
relationship of altitude with temperature is negative, i.e., 0.84, the
temperature of the area increases with a decrease in altitude and vice versa.
The elephant distribution prediction map based on
altitude, slope, aspect, precipitation, and temperature only using boosted
regression tree model is presented in Appendix 5. Other predictor variables were based
specifically on field data and their extrapolation to spatial scale was not
possible.
Discussion
The elephant population in Nepal is restricted to the Terai and Siwalik regions, where there have been
large-scale conversion of forest and expansion of agricultural lands (Koirala
et al. 2015). This has resulted in
negative human-elephant interactions in many parts of Nepal. Movement of elephants outside the national
park and wildlife reserve could have been the result of unsuitable habitat,
reduced supply of food and water, and encroachment by human beings. Assessing habitat suitability of elephants
assists in the preparation of sustainable management plans. PNP and BZ has been the habitat of elephant
for long time, but habitat suitability studies are rare in this area. This research examines habitat suitability of
the elephant in PNP and BZ based on different variables including dominant
species, temperature, altitude, habitat preference, precipitation, segment
type, aspect, slope, ground cover, crown cover and substrate condition.
Based on the BRT model, PNP and BZ are suitable
habitats for elephants. We witnessed the
outcome of parameters as per the physical, biological and climatic features of
the area like slope, aspect, altitude, precipitation, temperature, habitat
preference, crown cover and ground cover.
The result shown by Koirala et al. (2016) posits that species like Spatholobus parviflorus,
Saccharum spontaneum,
Shorea robusta,
Mallotus phillippensis,
Garuga pinnata,
Litsea mono-petala
contributed the highest proportion of diet for an elephant in the PNP. In consent with our result, similar species
of trees, shrubs, and herbs have the highest IVI and PV and distributed in the
lower part of the area. This result
concludes that the study area is the most suitable for elephant to dwell. Our study revealed that the habitat is suitable
in the Northeast and Southeast region of the study area, which is similar to
the result of Shamsuddoha & Aziz (2015).
Rood et al. (2010) studies have
found that the elephant’s habitat use in a tropical forest is depicted by areas
of high forest cover. Our analysis,
however, found no marked relationship between ground cover, crown cover, and
presence of elephants. Our findings
revealed that in the study area, slope 0–5° and altitude 400m is suitable for
elephants which are almost similar to the result of Areendran
et al. (2011). In accordance with the
studies of Douglas et al. (2006), Lin et al. (2008) and Ochieng (2015),
suitable habitat for elephants was found to be limited by augmentation of both
altitude and slope. There is no
abundance of elephants’ presence sign with the increment of the altitude and
slope in PNP. In order to preserve their
energy needs, Ntumii et al. (2005) mention that
elephants avoid the height and steeply sloped area.
Variability in results might
have occurred due to the differences in sampling methods, variance in forest
condition, composition, and sampling area, etc.
The research outcome was concluded based on only one season field work;
however, taking all the results of four seasons might produce more effective
result. Data of precipitation and
temperature were extracted from Worldclim; the data
taken from the nearest metrological station of Samara could be better with more
accuracy. The outcomes from this study, linked
to slope, and elevation are valid for PNP only, and cannot be generalized to
the habitat of an elephant in other countries.
Further research should focus on creating map of elephant distribution,
habitat suitability, and threats to elephant from invasive species.
Conclusion
BRT was applied to assess
elephant habitat suitability in PNP. In
this study, we analyzed the distribution of elephant
using a combination of biotic and abiotic environmental variables, including
the topographic and climatic factors.
The model emphasizes on environmental suitability and contributes to
knowledge for conservation of elephant in PNP.
It provides a basis for habitat analysis. Elephants were recorded up to 400m and in northeastern and southeastern
aspects. Its presence could not be
related to forest cover and substrate condition. The result from the modeling
may become useful to plan and delineate areas for management of elephant. It presents scope to minimize HEC through
precautionary measures.
Table 1. Predictor variables used to model the habitat
of Elephant.
|
Predictor variables |
Format (Source) |
Description |
|
Temperature (× 10 °C) (1km × 1km) |
Raster (WorldClim)
1* |
The temperature of June was used |
|
Precipitation (mm) (1km × 1km) |
Raster (WorldClim)
1* |
Precipitation of June was used |
|
Slope (°) (30m × 30m) |
Raster (Jaxa
DEM) 2* |
|
|
Aspect (30m × 30m) |
Raster (Jaxa
DEM) 2* |
|
|
Altitude (30m × 30m) |
Raster (Jaxa
DEM) 2* |
|
|
Habitat preference |
Field measurement |
Species preferred by elephant, including
Mallotus philipinensis,
Imperata cylindrica, Dillenia pentagina, Saccharum spontaneum, Careya arborea, and Pennisetum purpureum |
|
Dominant Species |
Field measurement |
Area dominated by species like Acacia
catechu (AcC), Bombax ceiba (BoC), Dillenia pentagaina (DiP),
Albizzia procera (AlP),
Lagerstroemia parviflora (LaP),
Terminalia chebula (TeC),
Trewia nudifolia
(TrN), and Myrsine
semicerata (MyS) |
|
Segment type |
Field measurement |
Divides the area into the segment by
fire line, foot trail, pond, river, and railway |
|
Crown and ground cover |
Field measurement |
Cover (%) of forest crown and ground |
|
Substrate condition |
Field measurement |
The condition of the soil, including
hard soil, soft soil, and leaf litter |
1*—www.worldclim.org | 2*—www.global.jaxa.jp/press/2015/05/20150518_daichi.html.
For figures
& appendices – click here
Adhikari, H., J. Heiskanen, M. Siljander, E.
Maeda, V. Heikinheimo & P.K.E. Pelikka (2017). Determinants of aboveground
biomass across an Afromontane landscape mosaic in Kenya. Remote Sensing
9(8): 827. https://doi.org/10.3390/rs9080827
Areendran, G., K. Raj, S. Mazumdar, M. Munsi, H. Govil & P.K. Sen
(2011). Geospatial
modelling to assess elephant habitat suitability and corridors in northern
Chhattisgarh, India. Tropical Ecology 52: 275–283.
Armbruster, P. & R. Lande (1993). A population viability analysis for African Elephant
(Loxodonta africana):
how big should reserves be? Conservation Biology 7(3): 602–610. https://doi.org/10.1046/j.1523-1739.1993.07030602.x
Bisht, S.S. (2002). An overview of elephant
conservation in India. Indian Forester 128(2): 121–136
CHEC Nepal (2012). An assessment of Tiger (Panthera tigris)
and its habitat in Bara forest, Nepal. A report submitted to District Forest
Office, Simara, Bara.
DNPWC (2008). The Elephant Conservation Action
Plan for Nepal. Ministry of Forest and Soil Conservation, Department of
National Parks and Wildlife Conservation, Kathmandu, Nepal, 30pp.
Behavioural reactions of elephants towards a
dying and deceased matriarch. Applied Animal Behaviour Science 100: 87–102. https://doi.org/10.1016/j.applanim.2006.04.014
Elith, J., J.R. Leathwick
& T. Hastie (2008). A working guide to boosted regression trees, (Ml),
802–813. https://doi.org/10.1111/j.1365-2656.2008.01390.x
Greig-Smith (1983). Quantitative
Plant Ecology. University of California
Press, Berkeley, CA, xiv+359pp.
IUCN (2017). The IUCN Red List of Threatened
Species. Version 2017-1.https://www.iucnredlist.org
Jnawali, S.R. (1995). Population ecology of greater
one horned rhinoceros (Rhinoceros unicornis)
with particular emphasis on habitat preference, food ecology and ranging behavior of a reintroduced population in Royal Bardiya National Park in Low land Nepal (A Doctor Scientiarum Thesis 1995: 4), i-vii,
128pp.
Koirala, R.K., W. Ji, A. Aryal, Jessica Rothman & D. Raubenheimer
(2015). Dispersal
and ranging patterns of the Asian Elephant (Elephas maximus) in relation
to their interactions with humans in Nepal. Ethology Ecology & Evalution 28(2): 221–231. https://doi.org/10.1080/03949370.2015.1066872
Koirala, R.K., D. Raubenheimer, A. Aryal, M.L. Pathak
& W. Ji (2016). Feeding preferences of the Asian Elephant (Elephas maximus) in
Nepal. BMC Ecol., 16 (1): 54. https://doi.org/10.1186/s12898-016-0105-9
Krebs, C.J. (1978). Ecology: The Experimental
Analysis of Distribution and Abundance. 2nd Ed. Harper & Row
Publishers, 678pp.
Lin, L., L. Feng, W. Pan, X.
Guo, J. Zhao, A. Luo & L. Zhang (2008). Habitat selection and the change in
distribution of Asian elephants in Mengyang Protected Area, Yunnan, China. Acta Theriologica 53:
365–374. https://doi.org/10.1007/BF03195197
Mishra, R. (1968). Ecology Work Book. Oxford
and IBH Publishing Company, Calcutta, 244pp.
Mueller-Dombois, D. & H. Elienberg (1974). Aims and Methods of Vegetation
Ecology. John Wiley & Sons, New York, 547pp.
Ntumi, C.P., R.J. van Aarde, N. Fairall & W.F. de Boer (2005). Use of space and habitat use by elephants (Loxodonta
africana) in the Maputo Elephant Reserve,
Mozambique. South African Journal of Wildlife Research 35(2): 139–146.
Ochieng, E.O. (2015). Characterizing the spatial
distributions of elephants in Mpala, Kenya. MSc
Thesis, University of Twente, 53pp.
Pradhan, N.M.B., A.C. Williams & M. Dhakal (2011). Current status of Asian elephants in Nepal. Gajah 35: 87–92.
Ram, A.K. (2008). Impact of Mikania micrantha on Rhinoceros unicornis
habitat in Chitwan National Park, Chitwan Nepal (Bachelor thesis submitted to Tribhuwan University), 79pp. https://doi.org/10.13140/RG.2.1.1756.8244
Rimal, S., H. Adhikari & S.
Tripathi (2018). Habitat
suitability and threat analysis of Greater One-horned Rhinoceros Rhinoceros unicornis
Linnaeus, 1758 (Mammalia: Perissodactyla: Rhinocerotidae) in Rautahat
District, Nepal. Journal of Threatened Taxa 10(8): 11999–12007.
https://doi.org/10.11609/jott.3948.10.8.11999-12007
Rood, E., A.G. Abdullah & V.
Nijman (2010). Using
presence-only modelling to predict Asian Elephant habitat use in a tropical
forest landscape: implications for conservation. Diversity and Distributions 16: 975–984. https://doi.org/10.1111/j.1472-4642.2010.00704.x
Santiapillai, C. (1997). The Asian Elephant conservation:
a global strategy. Gajah 18: 21–39.
Shamsuddoha, M. & M.A. Aziz (2017). Raiding pattern of migratory
elephants in a human dominated landscape in
northern Bangladesh. Ecoprint 24:
21–27. https://doi.org/10.3126/eco.v24i0.20643
Sharma, P. (2017). Habitat suitability modeling of Asian wild elephant and its interaction with
people in Parsa National Park and its Buffer Zone.
Submitted to Agriculture Forest University, Faculty of Forestry, Hetauda, Nepal in partial fulfilment of the requirement for
the degree of Bachelors’ in forestry, i-xi, 46pp.
Sukumar, R. (2003). The living elephants:
evolutionary ecology, behavior, and conservation.
Oxford University Press, New York, 478pp.
Trigal, C. & E. Degerman
(2015). Multiple
factors and thresholds explaining fish species distributions in lowlands
streams. Global Ecology and Conservation 4 589–601. https://doi.org/10.1016/j.gecco.2015.10.009
Zobel, D.B., U.K. Yadav, P.K. Jha
& M.J. Behan (1987). A practical manual for ecology. Rani Printing Press, Kathmandu, Nepal.