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Geology, Ecology, and Landscapes
ISSN: (Print) (Online) Journal homepage: www.tandfonline.com/journals/tgel20
Elevation gradients and environmental variables
shaping tree diversity and composition in
Srivilliputhur Wildlife Sanctuary, Western Ghats
Neha Jaiswal & S. Jayakumar
To cite this article: Neha Jaiswal & S. Jayakumar (21 Nov 2024): Elevation gradients
and environmental variables shaping tree diversity and composition in Srivilliputhur
Wildlife Sanctuary, Western Ghats, Geology, Ecology, and Landscapes, DOI:
10.1080/24749508.2024.2430051
To link to this article: https://doi.org/10.1080/24749508.2024.2430051
© 2024 The Author(s). Published by Informa
UK Limited, trading as Taylor & Francis
Group on behalf of the International Water,
Air & Soil Conservation Society(INWASCON).
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RESEARCH ARTICLE
Elevation gradients and environmental variables shaping tree diversity and
composition in Srivilliputhur Wildlife Sanctuary, Western Ghats
Neha Jaiswal and S. Jayakumar
Department of Ecology and Environmental Sciences, School of Life Sciences, Pondicherry University, Puducherry, India
ABSTRACT
Srivilliputhur Wildlife Sanctuary holds signicant value being a part of Western Ghats, which
remains unexplored in terms of vegetation. The current study is the rst quantitative assess-
ment of tree distribution along an elevation gradient combined with environmental variables.
Sampling was conducted from December 2020 to April 2021 in six elevation zones (Z1 to Z6). A
total of 135 plots of 20m × 20m size were established, and the stems were measured (>30 cm
GBH). Across a 5.4 ha studied area, 2157 individuals representing 188 tree species and 48
families were documented. Tree density (348-473 ind. ha
−1
), basal area (21.71-36.59 m
2
ha
−1
),
and species richness (84-122) were highest at mid-elevations. One-way ANOVA result high-
lighted the signicant inuence of elevation on species richness (p < 0.05). Canonical
Correspondence Analysis revealed a good correlation between environmental variables and
elevation. Furthermore, beta diversity showed intermediate dissimilarity between zones, ran-
ging from 0.30 to 0.61. Z1 and Z6 exhibited the most dissimilarity (60%). Our study revealed
tree diversity was least at higher elevations, suggesting good evidence of elevation and
environmental ltering in shaping the overall tree diversity. Besides, the scarcity of a few
species showed a point of concern. Hence, the current study suggests the implementation of
strategic conservation plans to conserve species diversity in this area.
ARTICLE HISTORY
Received 24 April 2023
Accepted 12 November 2024
KEYWORDS
Elevation gradient; Western
Ghats; species richness; beta
diversity; canonical
correspondence analysis
1. Introduction
As a society, we unknowingly harm our vital means of
survival, such as clean air and a healthy environment,
every day due to development and excessive consump-
tion (Feng et al., 2021). Among the natural resources,
forest ecosystems have been one of the major contri-
butors to maintaining biodiversity as they support all
living organisms by providing food and fodder (Dar &
Parthasarathy, 2022b; Hebbar & Krishnaswamy,
2024). According to a recent report from the Forest
Survey of India (FSI), India covers >24% of its geogra-
phical area under forest and consists of 80.9 million
hectares (ha) of forest cover (ISFR, 2021). Among
various forest ecosystems, tropical mountain ecosys-
tems are home to 50% of global biodiversity hotspots
and support more than one-quarter of terrestrial bio-
logical diversity on the Earth (Thakur et al., 2022),
despite covering <10% of the area (Sharma et al.,
2023). However, forests are subject to loss and frag-
mentation, a primary cause of ecosystem degradation
worldwide (Hansen et al., 2020; Pujiono et al., 2023).
Historically, mountain forests were untouched, and
the loss was limited as the elevation and steep slopes
were the main barriers to human interference (da Silva
et al., 2014). However, as the 21
st
century began, these
forests were increasingly exploited and reshaped their
existing pattern of plant diversity remarkably (Yang
et al., 2022). Between 2001 and 2018, mountainous
regions experienced a decline in forest cover, amount-
ing to a global relative gross loss of 7.1% since 2000
(He et al., 2023). Therefore, from a conservation point
of view, phytosociological explorations in mountain
ecosystems are essential and highly recommended
(Hansen et al., 2020; Kishore et al., 2024; Rahman
et al., 2022).
Western Ghats, on the other hand, is one of the
major tropical forests of India, with a unique flora and
faunal diversity (Schmerbeck et al., 2024; Subashree
et al., 2021). However, it is highly vulnerable to various
threats (Jaiswal & Jayakumar, 2024), a situation that
needs to be addressed and improved (Pragasan, 2023).
In this context, human disturbance is one of the major
concerns that reshapes species composition in multi-
ple ways. Studies revealed that the increase in human
population leads to increased land use and climate
change (Dhyani et al., 2023; Gebeyehu & Hirpo,
2019; Kapitza et al., 2021; Sarvade et al., 2016), result-
ing in the loss of biodiversity (Gupta et al., 2024; Raha,
2023; Farooqi et al., 2022). These disturbances can also
affect the environment and change the interaction
CONTACT S. Jayakumar s.jkumar1@gmail.com; s.jkumar1@pondiuni.ac.in Department of Ecology and Environmental Sciences, School of Life
Sciences, Pondicherry University, R Venkat Raman Nagar, Kalapet, Puducherry 605014, India
Supplemental data for this article can be accessed online at https://doi.org/10.1080/24749508.2024.2430051
GEOLOGY, ECOLOGY, AND LANDSCAPES
https://doi.org/10.1080/24749508.2024.2430051
INWASCON
© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the International Water, Air & Soil Conservation Society(INWASCON).
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which
permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been
published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
between plant species and their composition (Lolila
et al., 2023; Sahoo et al., 2020). In general, the inten-
sive use of forest products may put pressure on the
forest, which could lead to changes in species’ survival
and restrict the necessary migration for them to adjust
to new circumstances (Elsen et al., 2020). To under-
stand the detailed consequences of anthropogenic
development on forests, it is essential to understand
the natural – or as close to natural as possible – struc-
tural pattern of these systems.
Diversity patterns and structural compositions are
two major prioritized factors that should be consid-
ered to improve our understanding of ecosystem con-
servation and management (Altaf et al., 2022; Wani
et al., 2022). Several research has been conducted on
floristic compositions based on different parameters,
such as topographical (elevation, slope, aspect, etc.)
and environmental variables (e.g., temperature, preci-
pitation, etc.), explaining the importance of mountain
forests in the world (Báez et al., 2022; Cheng et al.,
2023; Li et al., 2020; Monge‐González et al., 2020) and
in India (Ahmad et al., 2020; Buragohain et al., 2023;
Dar & Parthasarathy, 2023; Murthy et al., 2016).
Recently, the investigation of plant species richness
based on elevation gradient has become one of the
most popular topics (Khadanga et al., 2023; Noroozi
et al., 2018; Thakur et al., 2021). Such as variations in
the distribution and richness of species along elevation
gradients are among the most well-documented types
of vegetation patterns for tropical forests (Nohro &
Jayakumar, 2020; Oishi, 2021; Sekar et al., 2023).
For example, Bhatt et al. (2024) explained that the
elevation gradient significantly influences plant diver-
sity and spatial biodiversity distribution in mountain
forests. The preservation of habitats across their entire
elevational gradient is essential to the conservation of
species. Similarly, Vetaas (2021) highlighted the
importance of elevation gradients in comprehending
the broad patterns in biodiversity, composition, and
conservation of these forests.
However, several factors affect the elevation pattern
of tree diversity including environmental variables
(Song et al., 2021). Other significant factors that can
explain variation in species compositions across eleva-
tional gradients are biotic factors, such as vegetation
structure, resource availability, or competition
(Santillán et al., 2020). Overall, the deterministic pro-
cesses of changes in plant community composition are
mostly driven by variations in environmental condi-
tions in the mountain forests (Krishnadas & Osuri,
2021; López-Calvillo et al., 2023; Victorero et al.,
2018). And it has been proved that temperature and
precipitation are two of the most significant environ-
mental variables influencing vegetation, growth (Ali
et al., 2023), and the development of plants (Dar &
Parthasarathy, 2022a; Pan et al., 2023). According to
the research, both temperature and precipitation need
to be considered when understanding the tree species
pattern in the tropical forest of mountains (Báez et al.,
2022).
Moreover, it is believed that tree species richness
and diversity decrease with elevation, proving to be
highest at mid-elevations (López-Angulo et al., 2018;
Salazar et al., 2015), while tree density and tree basal
area may increase with elevation in tropical forests of
mountains (Clark et al., 2015). Usually, in tropical
forests, two patterns of plant diversity are found: one
is a hump-shaped curve (Willinghöfer et al., 2012),
and the other is a sharp decline in diversity along
with the elevation (Brambach et al., 2017).
Specifically, a study clarified that there is an inverse
relationship between elevation with species composi-
tion and diversity distribution in tropical mountain
forests (Rahman et al., 2022). However, many studies
cited the hump-shaped diversity pattern with peaks at
mid-elevations (Dani et al., 2023; Malizia et al., 2020;
Manish et al., 2017), mainly due to the mid-domain
effect and alterations in environmental variables in
both animals and plants (Ferreira & Perbiche-Neves,
2021; Montañez-Reyna et al., 2023). The mid-domain
effect asserts that the overlap of each species’ distribu-
tion is maximized as they approach the center of the
shared domain of the geographical distribution area
due to the constraints of the geometric distribution
limit and the average points of the species (Du et al.,
2024).
Several recent advancements in the direction of
current studies provide a better understanding, for
example, elevation and environmental variables are
considered the key parameters in determining the
species richness and composition in the mountains
(Abbasi et al., 2023). The combination of elevation
and environmental variables provides extremely com-
plex environmental variety, which in turn promotes
high species diversity (Perrigo et al., 2020). Elevation
change can change the environmental and site condi-
tions by significantly influencing the plant commu-
nities (Mariano et al., 2020; Tito et al., 2020). In this
context, the diversity of plant species in various envir-
onmental conditions is identified as a crucial subject
for ecological research and has been explored in con-
nection to productivity, biomass, biotic interaction,
history, climate, and habitat heterogeneity (Bisht
et al., 2022; B. M. Kumar & Balasubramanian, 2024).
Furthermore, concerning studies on elevation,
beta diversity is crucial (Baselga, 2010). The
Sorensen dissimilarity index is one of the common
methods used to assess beta diversity (Krishnadas &
Osuri, 2021; Wani et al., 2022) based on presence-
absence data (Koleff et al., 2003). Based on the
Sorensen (β
sor
) and Simpson (β
sim
) indices, the over-
all spatial dissimilarity is partitioned into two parts
(nestedness and turnover). The species turnover
(explains species replacement between the zones) is
2N. JAISWAL AND S. JAYAKUMAR
represented by β
sim
, whereas the nestedness-related
gain or loss of species is indicated by β
sne
, which is
the difference between β
sor
and β
sim
(Haq et al.,
2021). Hence, beta diversity helps to understand
the species pattern and compositional changes
along the elevation gradient by understanding the
nestedness (β
sne
) and turnover (β
sim
) (Baselga &
Orme, 2012). According to Coelho et al. (2018),
higher turnover shows that diversity is determined
by species replacement between sites and plays
a significant role in organising spatial patterns of
variety in tropical forests. In contrast, nestedness is
the presence of subsets of species that only occur in
more speciose sites, maybe due to environmental
filtering or sporadic changes in species abundance
(Fu et al., 2019).
It is clear from our understanding that the
importance of mountain forests can be explained
by comprehending the pattern and composition of
plants in their environment. Elevation gradient, in
general, is one of the determining factors (Beck
et al., 2017) and is often a primary focus of studies
related to the diversity and distribution of vegeta-
tion (Khadanga et al., 2023; Zheng et al., 2024).
Also, the combined effects of different variables
(temperature, precipitation, soil, etc.) are crucial in
exploring the same along the elevation gradient,
which is understudied in some parts of tropical
forests (Guclu et al., 2024).
This is the first quantitative study conducted in
Srivilliputhur Wildlife Sanctuary (SWLS), currently
known as Srivilliputhur-Megamalai Tiger Reserve. It
is located in parts of the Western Ghats in Tamil Nadu
state and is rich in flora and fauna diversity. Being rich
in composition and one of the hotspot regions, the
study area lacks baseline information on its flora com-
position; hence, the present study was carried out to
fill the gap and strengthen the information on phyto-
sociological data for the present study area. In detail,
this study aims to enumerate the abundance and dis-
tribution of trees along the elevation gradient across
this sanctuary, which determines the overall tree
diversity of the forest ecosystem and helps understand
the structural composition of the forest. Conversely,
trees support habitats and provide resources to all
related species in the forest (Naidu et al., 2018;
B. Gupta et al., 2015).
Specifically, our study addresses the following
research questions:
(1) What is the role of elevation and environmental
variables (temperature and precipitation) in
tree diversity and distribution?
(2) How do tree density, basal area, and species
richness correlate along the elevation zones?
(3) Does beta diversity show a significant differ-
ence between all the zones?
(4) Do all elevation zones have the same dominant
species throughout?
2. Materials and methods
2.1. Study area
The present study was conducted in SWLS, located
between geographical coordinates of 9° 21’to 9° 48’
N latitude and 77° 21’to 77° 46’ E longitude (Figure 1).
The sanctuary is primarily situated in the
Virudhunagar district, especially in Srivilliputhur,
and extends partly into the Madurai district in western
Tamil Nadu, India. It borders the Periyar Tiger
Reserve on the southwest and the Megamalai Reserve
Forest on the northwestern side (Kumar et al., 2014).
The total area of this sanctuary is 485 km
2
, and it was
established in 1989 to protect and safeguard the giant
grizzled squirrel Ratufa macroura, a vulnerable species
(Tamil Nadu Forest Department, 2007). It encom-
passes various types of forests, primarily dry decid-
uous with patches of tropical evergreen forests, semi-
evergreen forests, moist mixed deciduous forests, and
grassland. The elevation ranges from 100 m in the
plains to 2010 m amsl (above mean sea level) at the
highest peak. The monthly average temperature varies
from 36°C to 39°C in summer and 26°C to 30°C in
winter. The annual average precipitation in this sanc-
tuary is 849 mm and ranges from 700–3000 mm,
a cumulative of five years. Seventy percent of the rain-
falls in September, October, and November originate
from the northeast monsoon. January to April is typi-
cally dry, though there may be occasional showers.
The SWLS is adjacent to a town, and residents
utilize resources such as water and wood. Cattle graz-
ing is also observed in the area, with minimal distur-
bance at the periphery of the forest.
2.2. Field sampling and measurements
Survey of India (SOI) toposheets (numbers C43R6,
C43R7, C43R9, C43R10, and C43R14) and maps
from the forest department were utilized during field
surveys to confirm the elevation gradient of this
region. Shuttle Radar Topography Mission (SRTM)
Digital Elevation Data (DEM) was downloaded from
the USGS website (https://earthexplorer.usgs.gov/)
and processed to obtain elevation data and divided
into six elevation zones (Z1, 200–400 m; Z2,
400–600 m; Z3, 600–800 m; Z4, 800–1000 m; Z5,
1000–1200, and Z6, 1200–1400 m) at intervals of 200
m. Environmental variables such as temperature and
precipitation were retrieved with field geo-coordinates
for established sample plots from the WorldClim
(http://www.worldclim.org/) database using the
getData() package in R (Hijmans, 2018).
GEOLOGY, ECOLOGY, AND LANDSCAPES 3
Phytosociological sampling was conducted from
December 2020 to April 2021, and the plot study was
carried out using the standard quadrat method (Curtis
& Mcintosh, 1950) with plots measuring 20 m × 20 m
in size. Sampling locations were distributed randomly
using a stratified random sampling technique with the
help of ArcGIS.
The number of plots in each elevation zone was
25 plots per hectare with a minimum intraplot
distance of 100 m. However, due to inaccessibility
and undulant terrain at higher elevations, only 20
plots in Z5 (0.8 ha) and 15 plots in Z6 (0.6 ha)
could be achieved. In the remaining four zones
(Z1, Z2, Z3, and Z4), all 25 plots were established.
Hence, a total of 135 sampling points were laid
randomly across six elevation zones, covering
a total of 5.4 ha of the study area. In each of
these sample plots of 0.04 ha, all trees with
a Girth at Breast Height (GBH > 30 cm) were
identified to species level, number of individuals
counted, and girth measured using measuring
tape. And then used to compute the Basal Area
(BA) as BA = 0.00007854 × DBH
2
for their DBH
(1.37 m above ground level). Samples were col-
lected, and a herbarium of trees was prepared and
identified with the help of experts (plant taxono-
mists and field ecologists in the respective region),
keys (Pascal & Ramesh, 1987), and available
literature. An online database, World Flora Online
(https://www.worldfloraonline.org/), was used to
assign the currently accepted names for each iden-
tified tree species. Topographic variables such as
elevation, coordinates, and slope were recorded for
each plot. The elevation and geo-coordinates of the
plots were recorded using a Global Positioning
System (GPS Trimble Juno 3B), having an accuracy
of ±10 m.
For buttressed trees, measurements were made
above ground level, avoiding the buttresses.
Multistems were measured separately. In each zone,
we calculated the basal area (m
2
ha
−1
), species rich-
ness, and tree density (ind. ha
−1
) of trees. Trees in
relation to elevation gradient from all the recorded
zones were used to analyse the abundance and dom-
inance of tree species.
2.3. Diversity analysis
2.3.1. Data analysis
Species diversity indices, such as Shannon-Weiner
(1948), Simpson (1949), and Evenness (Pielou, 1969)
were calculated using the PAST software ver.3.14
(Hammer & Harper, 2001). Phytosociological charac-
ters (tree density, frequency, and importance values)
were used to calculate the data from each elevation
zone (MS Excel, 2016). The Importance Value Index
Figure 1. A study area map with all the sample point locations in Srivilliputhur Wildlife Sanctuary, Western Ghats, India.
4N. JAISWAL AND S. JAYAKUMAR
(IVI) of tree species was calculated as a result of
relative density, relative dominance, and relative fre-
quency (Curtis & Mcintosh, 1950), and similarly, the
Family Importance Value (FIV) was determined
(Mori et al., 1983). The species with higher importance
values were considered dominant tree species and
families, and the top three dominant species were
identified and listed for all the zones. A girth class
analysis was also performed to analyse the structural
composition of all the zones (Sahu et al., 2019) to
understand the growth of the forest using MS Excel,
2016. The top five abundant tree species for all the
zones were examined to assess their distribution along
the elevation in each zone.
2.3.2. Statistical analyses
Individual-based rarefaction and extrapolation curves,
using “vegan” package, were employed to estimate
species richness within the elevation zones for
sampled trees (Gotelli & Colwell, 2001). Rarefaction
curves were used to assess how well species diversity
was sampled along the elevations, and they are con-
sidered to be less biased.
One-way analysis of variance (ANOVA) test fol-
lowed by post-hoc Tukey’s HSD test procedures were
performed to test the significant differences between
tree basal area, species richness, and tree density with
elevation among all the six zones. Linear regression
analysis was also utilized to assess the interrelations
between species richness, basal area, and tree density.
We further used Spearman’s ranks correlation coeffi-
cient (rho) to analyse the relationships between tree
density, basal area, species richness, elevation, and
environmental variables based on species composition
along elevation gradients (Sokal & Rohlf, 1995).
We performed Canonical Correspondence Analysis
(CCA) to understand the effects of different topogra-
phical variables (aspect N, W, S, and E, slope, and
elevation) and environmental variables (temperature
and precipitation) on the distribution of tree species
abundance. Multicollinearity was performed between
all variables with the help of the variance inflation
factor (VIF). CCA was performed using species occur-
rence data from all sample plots across the study area
with the help of “vegan” package (Ter Braak, 1987).
This test elucidates the associations among different
sets of variables. A permutation test (Monte Carlo)
was done to measure the significant contribution of all
the considered variables for the model.
We employed the beta diversity approach to exam-
ine the differences in species composition between all
the elevation zones (Baselga & Orme, 2012).
According to Baselga (2010), this method divides
total dissimilarity (β) into two parts: nestedness
(β
sne
), loss or gain in species, and turnover (β
sim
),
species replacement between zones, using the
Sorensen (β
sor
) (Sorensen, 1948) and Simpson (β
sim
)
(Koleff et al., 2003) indices. The Sorensen dissimilarity
index is theoretically equivalent to the total beta diver-
sity, and the turnover component is technically analo-
gous to the Simpson dissimilarity index. Since species
turnover and nestedness add up to overall beta diver-
sity, the nestedness component is determined by sub-
tracting the Simpson dissimilarity index from the
Sorensen dissimilarity index. The total beta diversity
among the six zones was computed using the “beta-
part” package (http://cran.r-project.org/web/
packages/betapart/), based on the Sorensen dissimilar-
ity (β
sor
) measure (Haq et al., 2021). The data accepted
by all the functions in the package is a matrix (x)
represented as the presence (1) or absence (0) of all
the tree species (columns) in six elevation zones
(rows).
All the statistical analyses were done in R.4.2.2.
software (R Core Team, 2021) and log-
transformation of data was done if necessary.
3. Results
3.1. Species diversity and composition
In the present study, 2,157 individual trees belonging
to 188 species were distributed among 48 families and
123 genera along the elevation gradient (Table 1). Out
of the 188 tree species, three tree species were identi-
fied only to the genera level and one remains uniden-
tified. The top three most diverse families based on
species richness were Fabaceae (16 species), Moraceae
(14 species), and Annonaceae (12 species) across the
study area.
Zone-wise, a total of 89 tree species were recorded
in Z1 with 32 families, 113 species in Z2 with 38
families, 122 species and 41 families in Z3 and Z4,
104 in Z5 with 35 families, and 86 species with 38
families in Z6. We observed that the richness in tree
species and family composition was highest at mid-
elevations, particularly in Z3 and Z4. We observed that
the mid-elevation zones (Z3 and Z4) supported higher
species richness which may be due to moderate cli-
matic conditions and environment heterogeneity
which means middle elevations tend to be greater,
offering a variety of microhabitats that can support
more species (Jiang et al., 2022). The presence of
species from both the lower and higher zones signifi-
cantly and uniquely adapted to the intermediate
conditions.
Based on abundance, the top five dominant tree
species were Ixora pavetta (60), Streblus asper (58),
Celtis philippensis (49), Drypetes sepiaria (46), and
Albizia amara (43) across the studied area. Whereas,
zone-wise, the top three dominant tree species include
Streblus asper, Ixora pavetta, and Lepisanthes tetra-
phylla in Z1, Albizia amara, Schleichera oleosa, and
Streblus asper in Z2, Celtis philippensis, Streblus asper,
GEOLOGY, ECOLOGY, AND LANDSCAPES 5
and Ixora pavetta in Z3, Celtis philippensis, Mallotus
philippensis, and Dimorphocalyx beddomei in Z4,
Anogeissus latifolia, Psydrax dicoccus, and Mallotus
philippensis in Z5 and Cullenia exarillata, Atalanatia
monophylla, and Litsea floribunda in Z6 were
documented.
3.2. Family composition and family importance
value index (FIVI)
The total number of families recorded for all the tree
species in the study area was 48. The most important
family in terms of tree species were Fabaceae with 16
species, followed by Moraceae, with 14 species, and
Annonaceae, with 12 species across the study area. On
the other hand, density-wise, Fabaceae had the highest
number of individuals (213), followed by Rubiaceae
(169) and Moraceae (164). However, the most impor-
tant families in terms of Family Importance Value
(FIV) were Fabaceae, Rubiaceae, Moraceae,
Sapindaceae, and Annonaceae, which together
accounted for 38% of all the trees recorded all over
the study area.
Zone-wise, Fabaceae had the maximum number of
species (55) in Z1. Similarly, Z2 was also dominated by
Fabaceae (13 species). Z3 and Z4 revealed Moraceae (10
species) had the highest number of species. Z5 and Z6
showed similar results as Moraceae was the dominant
family with eight species in both the zones. Additionally,
the maximum FIVI was observed for Fabaceae in Z1
(15.06%) and Z2 (45.76%), Annonaceae in Z3 (28.33%),
Moraceae (29.89%) in Z4, Rubiaceae (25.92%) in Z5 and
Moraceae in Z6 (28.93%). Zone-wise, the top five values
of FIVI for families are shown in Table 2. A single family,
Daphniphyllaceae, was only found in Z3, whereas
Tetramelaceae was the only family recorded in two
zones (Z2 and Z4).
3.3. Importance value index (IVI)
The top five most important species in terms of IVI
were Tamarindus indica (IVI = 9.45), Ixora pavetta
(6.50), Ficus microcarpa (6.35), Celtis philippensis
(5.97), and Drypetes sepiaria (5.88) across the study
area. However, zone-wise, the values changed slightly
(Table 3). Tamarindus indica was a significantly
important species with the highest IVI value, which
shows that the relative dominance of this species is
higher compared to other species. Whereas,
Tamarindus indica continued to be significant,
Streblus asper was the most prevalent species across
the study area.
3.4. Stand structure heterogeneity
3.4.1. Girth class-wise distribution
Lower girth classes (30–60 cm) contributed to the
higher number of individuals in all the zones. Tree
individuals and diversity continuously decreased with
Table 1. Summary of structural, diversity and topographic features across six elevation zones in Srivilliputhur Wildlife Sanctuary,
Western Ghats.
Z1 Z2 Z3 Z4 Z5 Z6 Landscape Scale (mean per 5.4 ha)
Forest Attributes
Sample plots 25 25 25 25 20 15 135
Tree density (ind. ha
−1
) 365 430 457 394 378.75 348.3 399.44
Basal Area (m
2
ha
−1
) 23.56 36.58 27.55 24.79 27.27 21.7 27.28
Diversity
Tree species richness 89 113 122 122 104 84 188 (per 5.4 ha)
Shanon diversity (H’) 4.134 4.41 4.45 4.52 4.38 4.18 4.13–4.52
Simpson diversity (D) 0.978 0.984 0.984 0.986 0.98 0.98 0.97–0.986
Pielou evenness 0.92 0.933 0.92 0.942 0.945 0.944 0.92–0.94
Spatial and topographic parameters
Elevation (m)(mean) 301.4 497.2 677.6 897.4 1073 1320.8 301–1321
Slope (°) (mean) 16.3 24.6 25.8 27.0 22.9 32.5 16.3–32.5
Table 2. The top five families of tree species
recorded in each zone based on the Family
Importance Value Index (FIVI) along the eleva-
tion gradient in Srivilliputhur Wildlife
Sanctuary, Western Ghats.
Elevation Zone Family FIVI
Z1 Fabaceae 45.23
Sapindaceae 26.21
Rubiaceae 23.08
Rutaceae 18.56
Putranjivaceae 18.25
Z2 Fabaceae 137.28
Moraceae 70.11
Rubiaceae 69.02
Sapindaceae 68.05
Annonaceae 61.82
Z3 Annonaceae 85.00
Moraceae 83.18
Rubiaceae 76.26
Fabaceae 74.25
Ebenaceae 71.33
Z4 Moraceae 89.68
Rubiaceae 84.99
Euphorbiaceae 80.81
Anacardiaceae 60.65
Ebenaceae 60.20
Z5 Rubiaceae 77.76
Phyllanthaceae 76.85
Euphorbiaceae 68.60
Rutaceae 63.42
Moraceae 50.65
Z6 Moraceae 86.81
Lauraceae 74.34
Oleaceae 70.68
Rutaceae 64.90
Phyllanthaceae 64.86
6N. JAISWAL AND S. JAYAKUMAR
increasing girth classes of stems (Figure 2), revealing
that small-stemmed trees dominated the area. Almost
half of the trees were in the lowest girth class for all
zones. For example, the lowest size of girth classes
(30–60 cm) captured 57.53%, 49.06%, 52.41%,
43.14%, 42.24%, and 51.19% of tree densities in Z1,
Z2, Z3, Z4, Z5, and Z6, respectively. More or less, all
species showed a reverse J-shaped curve. Notably, the
highest girth class (>300 cm) captured the highest
basal area in Z3 and Z5.
3.4.2. Tree density, species richness, and basal area
Across a 5.4 ha area, 2157 individuals of trees were
recorded. This revealed that the tree density was most
significantly higher in Z3 (457 ind. ha
−1
), while the
mean tree basal area was highest in Z2 (36.58 m
2
ha
−1
).
Tree density (209 ind. ha
−1
) and basal area (21.71 m
2
ha
−1
) were lowest in Z6. However, the species richness
was similar for Z3 and Z4. Besides, genera with a large
number of species, including Ficus (10), Diospyros (9),
and Terminalia (5), were observed across the area.
Tree density and species richness first increased
and then sharply decreased with elevation which
showed hump-shaped patterns, whereas basal area
did not show any trend (Table 1). Linear regression
suggested a non-significant weak relation (p > 0.05)
between species richness, basal area, and tree density
with elevation across the study area. The result also
suggested that tree density showed a moderate signifi-
cant relation (R
2
= 0.35, p < 0.05) with the basal area
(Figure 3b) and a strong significant relation with spe-
cies richness (R
2
= 0.57, p < 0.05; Figure 3a). On the
other hand, the species richness and basal area showed
a weak significant relationship (R
2
= 0.09, p < 0.05;
Figure 3c).
However, a Spearman correlation (rho) test con-
ducted between tree density and basal area showed
a moderately positive correlation (rho = 0.59, p <
0.00). While tree density and species richness showed
a very strong positive correlation (rho = 0.72).
Similarly, the one-way ANOVA test showed that the
overall difference in species richness among the six
elevation zones was statistically significant (p = 0.04;
Figure 3d) while in terms of basal area and tree den-
sity, it was non-significant. The Tukey’s HSD test
further revealed that a significant relationship of spe-
cies richness was only found between Z1 with Z3.
3.5. Rarefaction curve
Visual inspection of the species–accumulation curves
(Figure 4) helped analyse the differences in tree species
richness within all zones. For trees, area-based accu-
mulation curves showed that the two elevation zones,
i.e., Z2 and Z3, had much higher species richness than
the other four zones. The analysis of the rarefaction
curve also showed that the observed richness was less
than the estimated richness and did not reach an
asymptote, indicating that the species richness may
be greater than that of the sampled (Figure 4). In
addition, Z1, Z4, and Z5 had intermediate richness
levels, while Z6 was extremely species-poor
(Figure 4b). The reason may include less sampling
because of inaccessibility to the higher elevation.
However, with individual-based accumulation curves,
the picture changed slightly (Figure 4a).
3.6. Tree species assemblage based on the
selected variables along the elevation gradient
In terms of environmental variables (temperature
and precipitation), spearman correlations suggested
a negative correlation of elevation with temperature
(rho = −0.56 p < 0.001) while a positive correlation
with precipitation (rho = 0.40, p < 0.001) across the
study area. We found that the temperature (R
2
=
0.40; Figure 5a) decreased with elevation, while
precipitation (R
2
= 0.28; Figure 5b) increased with
elevation based on linear regression. This explains
that elevation has a significant role in the health
and growth of plants as elevation changes the
quantity of sunlight, water, and nutrients available
in the soil (Zhu et al., 2019). However, based on
the Spearman correlation, temperature showed
a non-significant negative correlation with basal
area, density, and species richness. In contrast,
precipitation showed non-significant positive
Table 3. The top five tree species, based on the importance
value index (IVI) across six elevation zones in Srivilliputhur
Wildlife Sanctuary, Western Ghats.
Elevation Zone Tree species IVI
Z1 Lepisanthes tetraphylla 11.47
Tamarindus indica 11.33
Streblus asper 11.31
Ixora pavetta 11.29
Drypetes sepiaria 11.24
Z2 Tamarindus indica 26.32
Ficus virens 9.52
Holoptelea integrifolia 9.40
Schleichera oleosa 8.89
Albizia lebbeck 8.31
Z3 Ficus microcarpa 15.12
Celtis philippensis 10.99
Albizia lebbeck 7.50
Streblus asper 8.88
Ixora pavetta 7.83
Z4 Mallotus philippensis 8.95
Celtis philippensis 8.03
Tetrameles nudiflora 7.38
Ficus microcarpa 7.32
Vitex altissima 7.30
Z5 Ficus microcarpa 12.57
Anogeissus latifolia 11.41
Bischofia javanica 8.42
Mesua ferrea 9.65
Mallotus philippensis 8.61
Z6 Litsea floribunda 15.29
Canarium strictum 13.84
Cullenia exarillata 13.63
Albizia amara 9.10
Bischofia javanica 8.52
GEOLOGY, ECOLOGY, AND LANDSCAPES 7
correlations with tree density, species richness, and
basal area. This suggests that the role of these
variables as important parameters and the combi-
nation of elevation with these variables significantly
contributes to shaping the overall diversity of trees.
3.6.1. Canonical correspondence analysis (CCA)
Among all the studied variables (elevation, tempera-
ture, precipitation, slope, and aspect), the CCA
results retained two significant axes, CCA 1 and
CCA 2. CCA 1 (eigenvalue = 0.39) and CCA 2
(eigenvalue = 0.22) represented considerable var-
iance in the species–environment relationship, as
shown in Table 4 (Permutation test for all canonical
axes: F = 1.53, p = 0.001). The CCA 1 was mainly
related to elevation, thus separating low-elevation
tree species (for example, Butea monosperma) from
high-elevation (for example, Euonymus crenulatus),
and the CCA 2 was mainly related to temperature
and precipitations. The result of CCA indicated that
all the species are evenly distributed along the gra-
dients, and the Variance Inflation Factor (VIF) for
all the variables was less than 10, explaining there
was no redundancy in data (Table 4). The result
revealed that the species extremely influenced by
elevation were Euonymus crenulatus, Drypetes
wightii, Glochidion ellipticum, Mallotus tetracoccus,
Memecylon umbellatum, etc. on CCA 1 and
Turpinia cochinchinensis on CCA 2. Regarding
aspect variables, the southern aspect was negatively
correlated with temperature and positively corre-
lated with precipitations. The species favored
Figure 2. Girth class-wise distribution of tree density and basal area across the elevation zones (Z1 to Z6) in Srivilliputhur Wildlife
Sanctuary.
8N. JAISWAL AND S. JAYAKUMAR
precipitations compared to the elevation and
temperature.
Overall, in the upper right corner on CCA 1
Ailanthus triphysa was extremely correlated with
temperature, whereas, on CCA 2, Mangifera indica
was closely related to temperature (permutation test
for significance of first axis: F = 3.041, p = 0.001 and
for second axis: F = 1.725, p = 0.001). Hence, the tree
species influenced by temperature were Ailanthus
triphysa, Butea monosperma, Hardwickia binnata,
while with precipitations Cullenia exarillata,
Phoebe wightii, and Ligustrum perrottetii were asso-
ciated with CCA1. However, on CCA2, dominant
trees associated with temperature were Mangifera
indica, Euonymus crenulatus, and Memecylon umbel-
latum. Whereas, with precipitation, Syzygium lan-
ceolatum, Litsea glutinosa, and Phoebe wightii were
associated (Figure 6). The variation inflation factor
(VIF) in CCA revealed that aspect (1.7), elevation
(1.3), slope (1.4), temperature (5.6), and precipita-
tion (5.3) had no redundancy (Table 4). In detail,
VIF was less than 10, which suggests that no multi-
collinearity was found in CCA and can be consid-
ered (Oksanen, 2011).
3.6.2. Beta diversity
Total beta diversity, calculated based on the Sorensen
dissimilarity index (β
sor
), ranged from 0.30–0.61, sug-
gesting considerable variation between all the zones.
The species replacement rate between zones inclined
as elevation increased and tended to be intermediate
as the Sorensen index reached 60% (0.60). The result
reflects two clusters between the zones; the species
turnover (β
sim
) showed similarity between Z6 and Z4
to Z5 while showing extreme dissimilarity to Z3, Z1,
and Z2 (Figure 7).
Nestedness (β
sne
) showed two clusters as well. One
is Z5 with Z2 (0.02), and the other is Z6 with Z1 (0.01).
This nestedness pattern that Z1 shows the least nest-
edness with Z6, as the difference in species composi-
tion was dominated by species turnover (β
sim
= 0.60).
Z5, on the other hand, is clustered with Z2, which may
Figure 3. Linear regression between (a) tree density (ind. ha
−1
) and species richness , (b) tree density and basal area (m
2
ha
−1
) and
(c) species richness and basal area (m
2
ha
−1
), across all the elevation zones and (d) one-way analysis of variance test between
species richness and elevation zone in Srivilliputhur Wildlife Sanctuary. Tukey pair-wise test shows a significant difference between
Z1 and Z3 (p = 0.04) based on 95% confidence interval.
GEOLOGY, ECOLOGY, AND LANDSCAPES 9
be attributed to the high elevation difference between
these zones. However, Z4 and Z3 showed no nested-
ness (β
sne
= 0%), as there is no difference in species
composition for the zones Z3 and Z4. Compared to
species loss by nestedness, tree species in Z6 were least
clustered with those in Z1 (0.01). How species compo-
sition changes along the elevation can be a significant
attribute in understanding the pattern of species dis-
tribution by calculating beta diversity. For example, by
focusing on regions with high beta diversity,
conservation efforts can protect multiple unique spe-
cies assemblages.
4. Discussion
To the best of our understanding and knowledge,
this study represents the first attempt in SWLS
regarding tree species distribution pattern and com-
position, along the elevation gradient, indicating
healthy forest growth based on the results. Elevation-
Figure 4. (a) Rarefaction and (b) species–area curve for trees
across the elevation zones based on 95% confidence intervals.
Figure 5. Linear regression relationship between (a) elevation
and temperature (°C) and (b) elevation and precipitation (mm)
in Srivilliputhur Wildlife Sanctuary.
Table 4. Summary of canonical correspondence analysis (CCA).
Variation inflation factor Eigen values for constrained axis (%)
Aspect N Aspect S Aspect W Elevation Temp Prec Slope CCA1 CCA2
1.64 1.64 1.72 1.65 5.6 5.3 1.24 0.4 0.22
Permutation test for testing significance of CCA-axis Permutation test for CCA model
Axix χ
2
F P χ
2
F P
CCA1 0.398 3.041 0.001 1.4061 1.5331 0.001
CCA2 0.2261 1.7259 0.001
Permutation test for CCA model Biplot scores for constraining variables
Variables χ 2 F P Variables CCA 1 CCA2
Aspect 0.44 1.13 0.02 Slope −0.38 −0.17
Slope 0.1516 1.1569 0.079 Elevation −0.95 0.24
Elevation 0.276 2.11 0.001 Temp. 0.8 0.5
Temp. 0.1925 1.469 0.001 Precip. −0.7 −0.69
Precip. 0.1977 1.5089 0.001 Aspect N 0 −0.07
Aspect S −0.09 −0.1
Aspect W 0.13 0.07
10 N. JAISWAL AND S. JAYAKUMAR
wise, this study aligns with the trends observed in
other parts of Western Ghats, India (Rawat et al.,
2021; Swamy et al., 2010) and other parts of moun-
tain forests (Bhatta et al., 2021). A high number of
tree species were found in the middle elevations
compared to lower and higher elevations, a pattern
consistent with similar studies in tropical forests
(Dani et al., 2023; Khadanga et al., 2023; Liang
et al., 2020; Zhang et al., 2016). According to
Thakur et al. (2022) and Gómez-Díaz et al. (2017),
the lower species richness at higher elevations is
attributed to harsh environmental factors that stress
plants physiologically, such as cold temperatures and
limited rainfall, inhibiting plant development and
regeneration.
4.1. Tree density, basal area, and species richness
Comparing this study to others conducted in the
Western Ghats, we found similar results (Giriraj
et al., 2010; Kumar et al., 2010; Reddy et al., 2007;
Sathish et al., 2013; Swamy et al., 2010). For instance,
the mean tree density ranged from 348 to 457 ind.
ha
−1
, which aligns with studies from the tropical forest
region, such as 313 to 330 ind. ha
−1
in tropical forest of
Nagaland (Ao et al., 2021), 110 to 406 ind. ha
−1
at
Mudumalai Wildlife Sanctuary (Reddy et al., 2008),
and 352 to 748 ind. ha
−1
at Kodayur (Sundarapandian
et al., 2005). Further studies showed a slightly higher
tree density of 527 to 665 ind. ha
−1
at Kalakad National
Park (Parthasarathy, 1999) and 435 to 705 ind. ha
−1
at
KMTR (Giriraj et al., 2010). This leads to the conclu-
sion that the observed decrease in the number of trees
over time is perhaps due to anthropogenic and natural
disturbances. Species richness, on the other hand,
explains the importance and uniqueness of species in
an area, and in ecological research, it is generally
acknowledged that species richness decreases with
elevation (Malik & Nautiyal, 2016; Sinha et al., 2018).
This study witnessed the highest value of tree species
richness in the middle elevation zone and the lowest in
the higher elevation zone, aligning with other studies
suggesting that middle elevations exhibit higher spe-
cies richness than lower and upper elevations (Bhat
et al., 2020; Dani et al., 2023; Khadanga et al., 2023;
Rawat et al., 2021) in mountain forests. Numerous
studies suggest a mid-domain effect, which arises
from biotic exchange with nearby communities (Sun
et al., 2020). The mid-domain effect explains that the
species distribution ranges overlap along elevation
gradients, with the greatest overlap intensity occurring
at middle elevations, which forms a hump-shaped
pattern (Gao et al., 2021). In terms of overlap intensity,
the elevations between low and high are rather mod-
erate; nonetheless, species diversity peaks at inter-
mediate elevations (Xu et al., 2021). These patterns
of species richness are also connected with environ-
mental factors such as precipitation and temperature
regimes. For instance, there are nearly always strongly
collinear environmental gradients found (elevation,
temperature, etc.) when the observed richness is cor-
related with the mid-domain effect (Currie & Kerr,
2008).
This study found that the mean basal area ranged
from 23 to 38.5 m
2
ha
−1
, which remains within the
range with similar studies (Ayyappan & Parthasarathy,
1999; Osuri et al., 2020; Sathya, 2017; Subashree et al.,
2021; Swamy et al., 2010) in the Western Ghats.
Whereas, Rawal et al. (2023) and Davidar et al.
(2007) reported comparatively higher basal areas of
60 to 70 m
2
ha
−1
and 36 to 94 m
2
ha
−1
, respectively.
We also found an increase in basal area with elevation
which was consistent with a similar study in the
Figure 6. Canonical correspondence analysis for tree species
with the selected variables (elevation, aspect, temperature and
precipitation) along the elevation gradient in Srivilliputhur
Wildlife Sanctuary. The six-letter code with a yellow colour
circle represents the name of the tree species, with the first
three letters corresponding to the genus name and the sub-
sequent letters the species name. Refer to the supplementary
data (Table S1) for scientific names of all the letter codes for
tree species.
Figure 7. Beta diversity between six elevation zones based on
the Sorensen dissimilarity index (spatial turnover; β
sim
and
nestedness; β
sne
) along the elevation gradient in
Srivilliputhur Wildlife Sanctuary.
GEOLOGY, ECOLOGY, AND LANDSCAPES 11
Western Ghats region (Bhatt et al., 2024). Numerous
researchers have also examined how elevation influ-
ences floristic diversity, species composition variation,
and forest structure, revealing that about half of these
studies find a negative association between elevation
and species richness (Rezende et al., 2015).
Also, species richness showed a high correlation
with tree density and basal area, reflecting the good
shape of the forest. On the one hand, a non-significant
relationship was reported between tree species rich-
ness, density, and basal area with elevation. On the
other, a significant relationship was observed between
temperature and precipitation with elevation. This
indicates that the combined effect of elevation and
environmental variables is crucial in tree diversity
assessment in the mountain forest (Sharma & Kala,
2022).
4.2. Diversity indices
The highest Shannon-Weiner diversity index (4.52)
and Simpson index (0.986) were observed in Z4,
while the lowest Shannon-Weiner diversity (4.13)
and Simpson index (0.978) were recorded in Z1,
respectively. These indices ranged from 4.13 to 4.52,
indicating high diversity in the area compared to pre-
vious observations in the Western Ghats (Murthy
et al., 2016). For example, the values are much higher
compared to similar studies conducted by Devagiri
et al. (2020) and Chandran et al. (2010). The trend of
the Shannon-Weiner index in the present forest can be
depicted as Z4 > Z3 > Z2 > Z5 > Z6 > Z1. Recently,
a similar study suggested a higher Simpson index
value at middle elevations in a mountain forest of the
Himalayas (Negi et al., 2024). The reason for this
difference between lower and higher elevation zones
may include the vulnerability of the lower zones to
various anthropogenic activities, such as grazing, etc.
In a similar context, using the resources from the
forest can affect the species composition and create
pressure on the forest leading to unidentified conse-
quences. According to research, the intensity of graz-
ing should be considered to identify the potential
threat to the forest, and grazing management should
be monitored (Dainese et al., 2015).
4.3. Zone-wise distribution of tree species and
family
Species-wise, IVI showed that the dominance of
species differed for each zone. For example,
Lepisanthes tetraphylla in Z1, Tamarindus indica
in Z2, Ficus microcarpa in Z3, Mallotus philippensis
in Z4, Ficus microcarpa in Z5 and Litsea floribunda
in Z6 shared the dominance. On the one hand, out
of the 188 identified species, only 13 species were
commonly present in all six zones, including
Albizia lebbeck, Atalantia monophylla, Chloroxylon
swietenia, Drypetes sepiaria, Grewia tiliifolia, Ixora
pavetta, Miliusa eriocarpa, Psydrax dicoccos,
Scolopia crenata, Stereospermum tetragonum,
Syzygium cumini, Tamarindus indica, and Tectona
grandis.
While on the other hand, few species were unique
to specific zones. For example, six species- Ailanthus
triphysa, Butea monosperma, Ficus racemosa,
Hardwickia binata, Pterospermum diversifolium,
and Strychnos nux-vomica, were restricted to Z1.
Two species- Diospyros saldanhae and Terminalia
catappa, were restricted to Z2. Five species- Blachia
umbellata, Daphniphyllum species, Syzygium lanceo-
latum, Allophylus serratus, and Atalantia wightii,
were found in Z3 alone. Grevillea robusta was the
only species recorded in Z4. Drypetes wightii and
Elaeocarpus variabilis were the only species found
in Z5, and a single species, Turpinia cochinchinensis,
was restricted to Z6 alone. Hence, the study area
showed uniqueness with some distinct species pre-
sent in specific zones, which, on the other hand, also
need to be maintained and conserved due to their
scarcity.
In addition, the increasing threats to biodiversity
conservation, particularly the fluctuation of tem-
perature due to climate change, can highly impact
the species distribution and richness in a natural
forest. One of the most significant aspect to inves-
tigate the conservation requirements for a concer-
ened species is taking into account the spatial
distribution of threats. And we observed that the
current study area having a scarcity of few tree
species ensures the degree of threats, which are
crucial in setting priorities for conservation
management.
However, we observed a marginal difference in
terms of family composition in each zone. For
example, Fabaceae had the highest FIVI in Z1 and
Z2, Annonaceae in Z3, Moraceae in Z4 and Z5, and
Rubiaceae in Z6, respectively. Rubiaceae was com-
monly observed in all the zones which is in line
with a similar study in mountain ecosystems
(Sanjeewani et al., 2024), contrary to
Phyllanthaceae, which was only seen in Z5 as one
of the top three FIVIs. Giriraj et al. (2010) and
Subashree et al. (2021) also reported Rubiaceae as
one of the top three dominant families in the
Western Ghats. Overall, we witnessed the highest
FIVI for Fabaceae (87.47), indicating that the area
was highly dominated by Fabaceae, with
a significant difference in FIVI compared to all
other recorded families. Fabaceae was found to be
the dominant family across the study area, which is
in line with studies conducted in tropical forests of
northern India (Patel et al., 2022; Sharma et al.,
2023).
12 N. JAISWAL AND S. JAYAKUMAR
4.4. Role of elevation and environmental
variables
The combination of environmental variables (tem-
perature and precipitation) with elevation is important
in shaping the species distribution and ecological pro-
cess. Given that the environmental variables had
a significant correlation with elevation, our findings
suggested that temperature and precipitation were key
influencing factors in tree diversity and distribution. It
is believed that more benign biotic or abiotic factors
may have an impact on plant communities at lower
elevations, while at higher elevations environmental
variables come into the picture by having an impact on
the form and distribution of plant communities
(Sánchez‐González & López‐Mata, 2005). Whereas,
precipitation supports the rich growth of plants at
higher elevations in the forest-like Western ghats
(Joseph et al., 2012). Cold temperatures may shift the
species distribution to higher elevations because of
climate change, competition, etc. based on the criteria
for species survival.
Numerous species have already shifted their ranges
to higher latitudes and elevations in response to the
changing climate. On the contrary, several species may
respond to the shifting in the changing climate
because of biotic interactions (Neuschulz et al.,
2018). Research indicates that, for plant establishment
at high elevations, biotic interactions are frequently
just as significant as abiotic variables (Liang et al.,
2016).
Combined effects of these variables were observed
using the beta diversity approach. Beta diversity is
comparing two sets of species, where the proportion
of unshared species is directly proportional to the
dissimilarity in species composition, and was assessed
using presence-absence data of the species (Wu et al.,
2023). The present study emphasizes that beta diver-
sity is highly significant for this area, falling within the
range of considerable difference as the Sorensen index
(SI) is close to one (Haq et al., 2021). The dissimilarity
among the zones may be due to the high difference in
elevation, a key driver for this study, which is consis-
tent with other studies (Hilmers et al., 2018; Swenson
et al., 2011), while in their studies, they have also
suggested that age and time can also be a reason for
the changes in species turnover. For example, in our
study, we have observed that based on the partitioning
of β
sor
, turnover (β
SIM
) contributed more compared to
nestedness (β
SNE
) to overall dissimilarity for all the
zones, which aligns with similar studies (Viana et al.,
2016; Wani et al., 2022; Yao et al., 2020). A significant
contribution of the turnover component could point
to a natural process of species replacement (Soininen
et al., 2018). Moreover, when the number of species is
the same in two zones (β
sor
and β
sim
are the same), any
differences between them are entirely the result of
spatial rotation (turnover) because nestedness cannot
exist (Dalmaso et al., 2020). In our study, Z3 and Z4
showed no nestedness (0.00), while species turnover
(0.60) dominated in measuring the total beta diversity
(Figure 7), which may be explained by the high species
richness for both zones. In addition, a study
(Victorero et al., 2018) suggested that nestedness
often results from the processes of ordered extinctions
or colonisations along gradients or spatial patterns of
declining resource or habitat availability. Conversely,
turnover in species composition may reflect species
sorting by the environment, or dispersion restrictions
may impose stronger selective pressures, increasing
species turnover (Conradi et al., 2017). However, the
turnover rate increased as elevational dissimilarity
increased, which may also imply that plots are more
homogeneous at lower and nearby elevations.
According to Sreekar et al. (2020), environmental
variables can also play a major role in species compo-
sitional changes based on beta diversity. Similarly,
Cordeiro et al. (2023) suggested that extreme environ-
mental factors, such as strong winds, low temperature,
etc., along the elevation, may also be responsible for
the high rates of spatial turnover seen. These factors
favor more specialized species – that is, better
adapted – to the unique conditions found in each
elevation zone. Climate change and human activities
further complicate these dynamics, highlighting the
importance of monitoring and conserving elevation-
diverse ecosystems.
The influence of elevation and environmental vari-
ables on tree species distribution was also explained by
Canonical Correspondence Analysis (CCA). In our
result, CCA 1 and CCA 2 retained two significant
axes, representing the considerable variance of the
species–environment relationship. We observed that
elevation was mainly related to CCA 1, which aligns
with a study conducted in tropical forests (Khadanga
et al., 2023). The result also revealed that the max-
imum number of species was influenced by tempera-
ture and elevation compared to precipitation, and
a positive correlation was found between them. The
result is consistent with similar studies, which showed
elevation (Méndez‐Toribio et al., 2016; Ramos et al.,
2020) and environmental variables (Ilyas et al., 2018)
were important factors influencing the species distri-
bution based on CCA. However, based on regression
analysis, elevation was significantly related to tem-
perature and precipitation, suggesting a considerable
role of these two variables in tree species distribution.
4.4.1. Pattern of dominance in relation to elevation
Out of 123 genera, the three most dominant genera
with a high number of species, Ficus (10 species),
Diospyros (9 species), and Terminalia (6 species),
were observed across the study area. We then
compared all three genera at the zonal level and
GEOLOGY, ECOLOGY, AND LANDSCAPES 13
found that Z2 was the highest contributor of these
genera and Z1 was the lowest (Figure 8). With few
exceptions, Z3, Z4, and Z5 showed intermediate
dominance. Furthermore, where Z3 and Z6
encountered only one species of Terminalia,
Diospyros contributed the highest number of spe-
cies in Z2. However, zone-wise, the pattern
revealed a different result. For example, Z1 and
Z2 dominated with Polyalthia & Albizia (4 species
each) and Diospyros (8 species), respectively, while
Ficus was dominant in Z3 (6 species), Z4 (7 spe-
cies), Z5 (7 species), and Z6 (5 species). Besides
these three genera, Polyalthia (5 species), Syzygium
& Albizia (4 species each), and Atalantia, Celtis,
Litsea, & Mallotus (3 species each) also dominated
the area. Some of these genera have also been
reported as higher in similar studies by
Sanjeewani et al. (2024) and Parthasarathy (1999).
Hence, the zone-wise distribution was important to
assess, showing a good pattern of elevational
changes across the landscape (Figure 8).
Similar to genera, we also observed the top five
abundant tree species (Ixora pavetta, Streblus asper,
Celtis philippensis, Drypetes sepiaria, and Albizia
amara) for the entire plots and then compared all
those species in each elevation zone (Figure 9).
This revealed that each species differed in each
zone. For instance, the most abundant species,
Ixora pavetta, gradually decreased with zones, as
shown in Figure 9. However, Streblus asper,
the second most abundant species across the area,
was absent in Z5. Therefore, the interpretation of
abundance data suggests that the overall dominant
species from all the plots varied within each zone,
providing strong evidence of elevation change in
terms of species richness. The dominance for all
five species was also observed to be highest in Z2
and Z3.
5. Conclusion
This study investigated for the first time how elevation
gradients and environmental variables influence the
structural composition of various tree species in the
Srivilliputhur Wildlife Sanctuary. The comprehensive
taxonomic analysis of the flora, examination of eleva-
tion patterns, and exploration of correlations between
species richness, basal area, and tree density provided
insights into the area’s diverse and even ecosystem.
Temperature and precipitation were identified as cru-
cial factors influencing the distribution of tree species
remarkably.
The study identified 188 tree species belonging to
123 genera and 48 families across the elevation gradi-
ent, with notable diversity concentrated in mid-
elevations, which form a hump-shaped pattern. The
dominance of certain families and genera varied
across zones, reflecting the delicate ecological
dynamics. Fabaceae emerged as the most dominant
family, underscoring its ecological importance
throughout the study area. However, challenges in
accessing higher elevation plots limited comprehen-
sive sampling. Despite this, mid-elevation zones, par-
ticularly Z3 and Z4 (600–1000 m), showcased
considerable species richness, indicating robust forest
growth. Tamarindus indica, Ixora pavetta, and
Streblus asper were found as the prevalent species in
the study area. Furthermore, the analysis of environ-
mental variables using CCA highlighted the influence
of temperature and precipitation on tree species dis-
tribution along the elevation gradient. The identified
key species associated with specific variables provides
valuable information for understanding the impacts of
climate on tree species.
Besides, beta diversity analysis, using the Simpson
and Sorensen dissimilarity index, underscored the sig-
nificant impact of elevation on species diversity and
composition. The observed dissimilarities in species
composition between zones indicate the sensitivity of
Figure 8. Top three dominant genera (Ficus, Diospyros, and
Terminalia) with a large number of species for the entire plot
across the study area in Srivilliputhur Wildlife Sanctuary.
Figure 9. Top five dominant tree species (Ixora pavetta,
Streblus asper, Celtis philippensis, Drypetes sepiaria and,
Albizia amara) based on abundance data across the study
area in Srivilliputhur Wildlife Sanctuary.
14 N. JAISWAL AND S. JAYAKUMAR
the forest ecosystem to elevation-related environmen-
tal factors. Meanwhile, species turnover dominated
the overall contribution based on beta diversity, sug-
gesting that diversity plays a major role here.
The distinct distribution pattern of woody stems
across elevation zones became evident in this study.
However, the presence of only a few species in certain
zones raises concerns about biodiversity loss and
emphasizes the urgency of conservation efforts.
Immediate action is required to safeguard the unique
species in specific zones and protect the forest ecosys-
tem. The study also identified areas of concern, such as
the presence of exotic species like Lantana camara
throughout the elevation range. The findings empha-
size the importance of conservation efforts, especially
in light of potential threats from anthropogenic activ-
ities and invasive species.
Overall, the findings of this study contribute to the
broader understanding of forest ecology, particularly
in the Western Ghats region. However, future research
may include human disturbance as a significant vari-
able in tree species diversity and gamma diversity can
also be calculated as this was beyond the scope of the
current study. Future research and conservation initia-
tives should consider the identified ecological degrees
to ensure the sustained health and resilience of the
forest ecosystem in the face of environmental changes.
Acknowledgments
The authors thank the Tamil Nadu Forest Department for
carrying out the fieldwork. The authors also thank
Dr. S. Sossairaj, Prof. N. Parthasarathy, Dr. Santhan
Ponnutheerthagiri, Dr. J. Naveenkumar for the plant iden-
tification, and Dr. Ashaq Ahmad Dar during the data ana-
lysis part.
Disclosure statement
No potential conflict of interest was reported by the
author(s).
Funding
NJ received financial support from the University Grant
Commission through a National Fellowship [UGC NO.
F. 44-1/2018 - SA-III].
ORCID
S. Jayakumar http://orcid.org/0000-0002-9917-2106
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