Journal of Threatened
Taxa | www.threatenedtaxa.org | 26 December 2022 | 14(12): 22293–22308
ISSN 0974-7907 (Online) | ISSN 0974-7893
(Print)
https://doi.org/10.11609/jott.8010.14.12.22293-22308
#8010 | Received 15 May 2022 | Final received
06 October 2022 | Finally accepted 04 December 2022
Avifaunal diversity
in Indian Institute of Technology Guwahati Campus, Assam, India
Umang H. Rathod
1 & Rupam Bhaduri 2
1 Department of
Mechanical Engineering, 2 Centre for the Environment,
Indian Institute of
Technology Guwahati, North Guwahati, Assam 781039, India.
1 umang174351003@iitg.ac.in
(corresponding author), 2 bhadurirupam@gmail.com
Editor: P.A. Azeez, Sálim
Ali Centre for Ornithology and Natural History, Coimbatore, India. Date of publication: 26 December
2022 (online & print)
Citation: Rathod, U.H. &
R. Bhaduri (2022). Avifaunal diversity in Indian Institute of
Technology Guwahati Campus, Assam, India. Journal of Threatened
Taxa 14(12): 22293–22308. https://doi.org/10.11609/jott.8010.14.12.22293-22308
Copyright: © Rathod & Bhaduri 2022. Creative Commons
Attribution 4.0 International License.
JoTT allows unrestricted use, reproduction, and distribution of this
article in any medium by providing adequate credit to the author(s) and the
source of publication.
Funding: No funding agencies
involved.
Competing interests: The authors declare no
competing interests.
Author details: Umang H. Rathod is a PhD student of Mechanical Engineering at
Indian Institute of Technology Guwahati (IITG), besides being a member of Assam
Bird Monitoring Network (ABMN). His research interests cover bio-inspired
engineering designs, wind turbines, soft computing, and avifauna; and has
authored several research articles in these topics. Rupam
Bhaduri is a PhD student from Centre for the Environment, Indian
Institute of Technology Guwahati, besides being a member of Assam Bird
Monitoring Network. His research interests cover analyzing climate dynamics in
infrastructure decision making process with a lens of political ecology. He is
an avid birder with large interest in understanding avifauna, their behavior
and impact of climate change on avian migration.
Author contributions: Documentation, data
analysis, structure and overall preparation of the manuscript, and
communication are done by UHR. RB has contributed in terms of documentation,
data analysis, and manuscript structure.
Acknowledgements: We would like to
thank all the members of IIT Guwahati birding group ‘Parindey’, especially Ms.
Akshita Jain, Mr. Aniruddha Mahagaonkar, Dr. Arun Dhillon, Mr. Atharva Amdekar,
Mr. Dhiren Huzuri, Dr. Jayakrishnan U, Mr. Ojing Siram, Mr. Pulakeswar
Basumatary, Dr. Sree Krishna Palaparthi, Dr. Smruti Ranjan Dash, Dr. Sounak
Bera, Dr. Srikanth Katla, Dr. Vimalathithan Devaraj, Ms. Vishaka Gulati for
contributing to the documentation process. We would also like to thank IIT
Guwahati administration for their support by letting us conduct the birding
events without any restrictions. We would also like to thank Assam Bird
Monitoring Network (ABMN) for providing us technical expertise and suggestions.
Abstract: Indian Institute of
Technology - Guwahati (IITG), Assam, is an ecologically rich campus hosting
different species of birds, butterflies and mammals. It accommodates several
migratory and resident species of birds across different seasons. However,
information is scanty on avian diversity with respect to the different habitats
of the campus. Therefore, the present study attempts to gain insight into avian
diversity with respect to habitat heterogeneity by considering the species
presence-absence dataset collected for three years (2017–2020). A multivariate
Beta (β) diversity analysis is carried out for the IITG
campus constituted of five primary habitats, viz., secondary growth,
eco–forest, water bodies, swampy-marshy area, and constructions. Of 152
bird species observed in the IITG campus, the highest number is reported from
secondary growth, followed by eco-forest. The multivariate analysis shows that
the average β–diversity for the IITG campus is approximately equal to
79%, which is in accordance with another published study. These observations
are examined in light of hypotheses and phenomena documented in the literature,
such as habitat heterogeneity hypothesis, niche-based hypothesis and anthropogenic
impact on habitats. The study also establishes that the IITG is among the
educational institutes and campuses that host many migratory bird species.
Lastly, based on the outcomes of β–diversity analysis, it is suggested
that the conservation effort for avian species in the campus should be directed
towards individual habitats uniformly.
Keywords: Campus avian
diversity, habitat heterogeneity, presence-absence dataset, multivariate β
‒ diversity.
Abbreviations: 2D—Two dimensional | a—Number
of species shared between two habitats | AR—Richness
agreement | b,c—Number of species present in one habitat but absent in
another | CBC—Campus Bird Count | DR—Richness difference |
IBA—Important bird and biodiversity area
| IITG—Indian Institute of Technology Guwahati | Ns—Species
nestedness | PAST—Paleontological Statistics software package for education and
data analysis | RS—Species replacement | SJ—Jaccard’s
similarity index | x̅—Mean index | α—Alpha diversity, diversity
of individual habitat | β—Beta diversity | β+—Additive
beta diversity | β×—Multiplicative beta diversity | βJ—Jaccard’s
dissimilarity index or Beta diversity | β̅J—Mean of all
multivariate beta diversity values | βJ, avg—Average of
multivariate beta diversity of one habitat | βS—Sorenson’s
index | γ—Gamma diversity, the total number of species in an area
encircling all the habitats.
INTRODUCTION
The state of Assam,
situated in the northeastern part of India, is home to over 700 avian species
(BirdLife-International 2022). The bird and biodiversity hotspots of Assam
include 55 IBAs (Important bird and biodiversity areas), which also cover the
state’s National Parks and Wildlife Sanctuaries (Rahmani et al. 2016). However,
the presence of avian species is not limited to the aforementioned designated
sites. It extends to lesser-known birding areas such as a city, a remote
wetland, a college campus or even an individual’s backyard. Among them, the
university campuses are distinctive because they can possess heterogeneous
habitats along with continuous anthropogenic influences. Moreover, Liu et al.
(2021) reviewed the campus biodiversity surveys of at least 300 universities
and colleges worldwide since 1940. They found that each campus contains an
average of 66 bird species, including threatened species, offering a major
refuge for birds in nearby urban areas. It was then proposed that the campuses
with high diversity should be protected for research, conservation, and
biodiversity education. Further, to implement more bio-diversity-friendly
designs, the suggested primary step is to monitor and investigate the
biodiversity of university campuses. Similarly, from the perspective of the
Indian academic campuses, Guthula et al. (2022) found an average of 88 bird
species per campus based on the survey conducted on total of 335 Indian
academic campuses. These observations and suggestions motivated the present authors
to study the avian diversity of the Indian Institute of Technology, Guwahati
(IITG) campus.
The campus of IITG is
beautifully manicured in the proximity of many IBAs located nearby Guwahati
city viz, ‘Dadara-Pasara-Singimari’, ‘Deepor Beel’ (Assamese: lake) bird
sanctuary, ‘Amchang’ hills, ‘Chandubi’ lake, and adjoining areas, ‘Jengdia
Beel-Satgaon’ and ‘Pabitora’ wildlife sanctuary (Rahmani et al. 2016). The
campus is composed of diverse habitats such as forest patches, hillocks,
wetlands, bushes, and a few lakes, making it perfectly suitable for
accommodating a wide range of bird species. The diverse vegetation found in
such habitat heterogeneous sites decides the overall rich avifaunal composition
of the area (MacArthur & MacArthur 1961) . The campus with diverse habitats
hosts not only resident birds but also many migratory species. However, no
scientific documentation of the avifauna inside the IITG campus was conducted
in the past. Thus, a study addressing the avian diversity within the IITG campus
was deemed necessary. This investigation is an attempt to document the avian
species of the IITG campus for three years (2017–2020) and to perform a
diversity analysis of the bird species among different habitats of the campus
using multivariate Beta (β) diversity analysis. This has
been one of the most prevalent techniques to compare the diversities of
different species assemblages (Anderson et al. 2011; Schmera et al. 2020),
especially where the field data are collected only as the presence or absence of
species. This study is particularly important to highlight the richness of
avian species on the campus besides quantitative comparison of diversity among
the different campus habitats. In the literature, there are many documented
campus-based avian studies, but only as species checklists (Gupta et al. 2009;
Surasinghe & Alwis 2010; Ali et al. 2013; Kabir et al. 2017; Manohar et al.
2017; Sailo et al. 2019), without thorough and quantitative habitat-wise
diversity analysis. On the other hand, Chakdar et al. (2016) & Trivedi
& Vaghela (2020) conducted a diversity & abundance analysis based on
the dataset of species-wise number of individual birds. The overall trend
suggests that most campus-based diversity analyses are checklists or
abundance-based and are not based on a presence-absence dataset. To address
this skewness, the present study is aimed to carry out a diversity analysis
based on the presence-absence dataset. Moreover, this technique can emphasize
the individual identity of the species rather than its abundance (Anderson et
al. 2011). This technique is elaborated in the Methodology section, followed by
results, discussion, and a brief conclusion emphasizing the threats and
conservation measures.
METHODS
Study Area
The present study has
been carried out in the IITG campus located at 26.1850N and 91.6880E,
nearby Guwahati, Assam. The campus
spanning over 2.8 km2 of area is situated on the northern banks of
the river Brahmaputra. The campus was established in 1995, and since then, the
habitat has been significantly changed due to infrastructural development. The
climate of the campus area is warm and humid, with an average annual rainfall
of 1,752 mm. The temperature of the site ranges between maximum and minimum
temperatures of 32.60 (August) and 11.00 (January) (Govt.
of India 2021). The campus is surrounded by marshy areas to the east and north,
human settlements to the west, and the ‘Brahmaputra’ river and sandy riverbanks
in the south. Moreover, in the proximity of the campus, the hilly areas ‘Kali
Pahar’ (Assamese: hill) in the north and ‘Nilanchal’ hills in the south are
located.
The campus area is
divided into multiple habitat types, as depicted in Image 1 in the form of a
map based on their topology and vegetation type. The approximate area of each
habitat type is estimated by Google Earth and listed in Table 1 in ascending
order. The eco-forest habitat, spread mainly over a hilly and uneven
campus area, is the remains of the wooded forest that was present before the
establishment of the campus. The highest peak in the eco-forest habitat is the
‘view-point’, with the lowest human disturbance compared to other habitats. The
dominant tree species and other plants in this habitat are Tectona grandis,
Dipterocarpus sp., Eucalyptus maculata, Acacia auriculiformis, Bombax
ceiba, Erythrina stricta, Butea monosperma, Ficus hispida, Ficus racemosa,
Artocarpus heterophyllus, Ailanthus excelsa, Neolamarckia cadamba, Aegle
marmelos, Aglaia spectabilis, Toona ciliata, Holmskioldia sanguinea, Aporosa
octandra, Nyctanthes arbor-tristis, Costus speciosus, and Areca catechu
among others (Kar et al. 2012). The aquatic habitat of the campus is of two
major categories: water bodies & swampy-marshy habitats. The
water bodies are a combination of large lakes & ponds, viz.,
‘Tihor’, Serpentine, and IITG lakes, as delineated in the form of blue location
icons in Image 1. These lakes were present before the establishment of the
campus and are not yet landfilled. Among the lakes, Serpentine contains
island-type small patches, providing safe shelter to the aquatic birds. The
water bodies are surrounded by trees such as Roystonea sp., Cassia
javanica, Delonix regia, Lagerstroemia speciosa, and Michelia champaca
for campus beautification. Most of the patches of the swampy-marshy habitat are
a result of rainwater accumulation over the sites from which the vegetation was
removed and then abandoned with no construction. Some of them have been present
before the establishment of the campus. The aquatic species include Canna
indica, Colocasia esculenta, Nymphaea rubra, Eichhornia crassipes,
Hymenachne sp., and some species of ferns are abundant in this habitat. The
scattered distribution of tree species such as Cocos nucifera, Ziziphus
jujuba, Syzygium cumini, Ailanthus integrifolia, Dillenia indica, Mimusops
elengi, Ficus religiosa, Lantana sp., and Bambusa sp. can be
observed on the fringes of the Swampy-marshy habitat. The secondary growth
habitat consists of shrubs, bushes, grassy meadows, and sparsely distributed
trees. This area usually remains disturbed by construction activities,
transportation, and human activities. Additionally, the playgrounds having
grass/lawns are also included in this habitat. This habitat is dominated by
tree species such as Alstonia scholaris, D. regia, Dalbergia sissoo, Acacia
farnesiana, Eucalyptus hybrida, Albizia lebbeck, Gmelina arborea, Psidium
guajava, Terminalia bellirica, Samanea saman, Monoon longifolium, Terminalia
arjuna, Phyllanthus emblica, Mangifera indica, Polyalthia longifolia, Cassia
fistula, Azadirachta indica, M. elengi, Ficus benghalensis, and others.
Lastly, the habitat type named ‘Constructions’ (their locations marked by black
icons in Image 1) is the only habitat which is non-contiguous and dispersed
within the range of other aforementioned habitats. This area is scarcely
populated with tree species such as D. sissoo, A. lebbeck, M. longifolium,
M. elengi, N. cadamba, A. scholaris and P. longifolia, along with
other floral species planted for campus beautification. It is important to note
that sparse construction sites (their locations marked by gray icons in Image
1) are still present in all other habitats; however, they are not as congested
as the construction habitat.
Data Collection
To collect species
presence-absence datasets for the diversity analysis, methodologies described
in Hill et al. (2005) are implemented, as discussed in this section. As this
task involves mobile species, the line/strip transect survey method is
preferred, in which the surveyor walks along the line and records the
presence/absence of individual species. The line transect method has been
widely implemented in many avian surveys (Surasinghe & Alwis 2010; Devi et
al. 2012; Kottawa-Arachchi & Gamage 2015; Chakdar et al. 2016; Pragasan
& Madesh 2018; Singh et al. 2020; Trivedi & Vaghela 2020). Other
attributes of this survey method, such as the number of individuals and their
perpendicular distances from the line, are omitted here since the aim of the
present survey does not include density and detectability parameters.
Additionally, some of the merits of the line transect method are the ability to
cover a large distance, address the common, and elusive species, low bias,
versatility, and efficiency (Hill et al. 2005). Considering this, the line
transect method is applied especially over the well-defined fixed routes,
trails, bridle paths, and roads in the IITG habitats and boundaries around the
habitats, water bodies, and swampy-marshy areas. Other documented studies have
also adopted a similar methodology (Gupta et al. 2009; Ali et al. 2013; Kabir
et al. 2017).
To standardize this technique, timed search
type method is intertwined with the same, especially while surveying for the
presence-absence of the species. Therefore, the line transect surveys were
usually made in the early morning (06:00–09:00) and sometimes at night for
nocturnal species such as owls (Ali et al. 2013). Such surveys were conducted
weekly for three years (2017–2020) in all the seasons of a year (viz, winter,
summer, and monsoon), and the data were tabulated habitat-wise (Appendix 1).
Sometimes, the point counts method and opportunistic sightings of the birds
were also used along with line transects for the habitats (Pragasan &
Madesh 2018). It is important to clarify that birds in flight are included in
the dataset only when the particular species is found using the particular
habitat; for example, any raptor hovering or soaring in search of prey, the
swifts or swallows hawking in proximity to the habitat or transects.
Instruments such as
cameras (Nikon Coolpix P510 and Canon Powershot S×50 hs) and field binoculars
(Solognac 500 dpi, 8 × 40) were used to record the observations. Audio records
were also used to identify the bird species by listening to the call on the
spot or recording it in an audio recorder (Zoom H4n) and later analyzing it.
Every identified species was cross-checked with the help of bird guides and
handbooks (Grimmett et al. 2016), besides referring to the eBird database
(ebird 2021). The abundance code is qualitative; for example, if an individual
of a species is found slightly less than 10 times out of 10 different visits
for birding, it is assigned as C―common, and, similarly, species were assigned
as U―uncommon and R―rare, if recorded roughly for five times & 1─2 times
out of 10 visits, respectively. These abundance codes, along with residency
status & migratory status for each species, are provided in Appendix 1.
Mathematical
Formulation for Data Analysis
As mentioned in the
data collection section, the data of avian species in the aforementioned
habitats are collected in the form of a presence-absence matrix. In this
method, the presence & absence of a given species for each habitat are
recorded in binary values 1 & 0 (Appendix 1), respectively. Usually, this
approach is preferred when the difference/variations of species
numbers/identities among assemblages, communities, habitats, and along spatial
or temporal gradients are emphasized (Magurran 1988). Moreover, a focus on the
identities of species (especially the role of rare species) rather than their
abundance (individual numbers) is necessary for conservation and biodiversity
studies (Anderson et al. 2011). Since the present investigation opted for a comparison
of diversity between habitats of the IITG campus, the presence-absence dataset
is sufficient.
As per the
literature, the β – diversity is one of the most prevalent techniques
used to compare the diversities of different assemblages whenever the species
presence-absence data is available (Koleff et al. 2003; Anderson et al.
2011). Historically, the concept of β
– diversity and its mathematical formulation in the form of β –
diversity indices were proposed by R.H. Whittaker in 1960, and thereafter, ecologists
have derived many indices for different applications. Some of these indices can
even facilitate the use of abundance and presence-absence data. Basically, the β
– diversity quantifies the dissimilarity or variation between habitats and
assemblages in terms of varieties of species. Ecologists have classified the
broad range of β – diversity indices into two major classical
categories, viz., multiplicative & additive indices, as expressed in
Equations 1 & 2, respectively.
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(1) |
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(2) |
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The latter is more
popular since it has the same dimension and unit as its independent variables (γ,
α); hence, they can be directly compared. Therefore, the additive approach
of β – diversity is chosen for the present investigation. It is
important to note that the present study uses the measure of multivariate
additive β – diversity instead of classical additive β –
diversity. This approach facilitates the comparison of β – diversity of
a given assemblage/habitat with all of the other habitats available in the
given area in the form of their pairs which is not possible in the classical
approach (Anderson et al. 2011). Moreover, the value of β – diversity
depends on the value of γ; therefore, it should be normalized by the
value of γ as per equation 3 (Ricotta & Pavoine 2015).
|
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(3) |
One common usage of β
– diversity is to study the change of species diversity along an environmental
gradient (i.e., elevation, latitude, longitude, temperature, upstream to downstream
of a river, and others) (Legendre & Legendre 2012). On the other hand, the
same index can also be used to compare species diversity & highlight
dissimilarity in species compositions of different assemblages or habitats
(Magurran 1988). As the multivariate β – diversity analysis deals with
the dissimilarity between two assemblages (mentioned in the last paragraph), it
is necessary to define an index which can quantify the same. In the literature
on numerical ecology, more than 24 types of different types of β –
diversity indices are available for the purpose (Koleff et al. 2003). Among
them, Jaccard’s dissimilarity index is mathematically less vigorous yet
intuitive. To understand the index, the notions of shared and unshared species
between two assemblages/habitats have to be clarified, as shown in Figure 1.
The species shared between both the assemblages/habitats are marked as ‘a’.
The species present in Habitat―1 but not in Habitat―2 are marked as ‘b’.
Similarly, the species present in Habitat―2 but not in Habitat―1 are defined as
‘c’. The summation of these quantities gives γ – diversity. The
species absent from both the habitats, but present in other habitats, are
excluded while calculating multivariate indices, i.e., exclusion of joint
absences is implemented in multivariate analysis (Anderson et al. 2011). Using
the definitions of a, b and c, the Jaccard’s similarity
& dissimilarity (β – diversity) in the normalized form can be
calculated using Equations 4 & 5. βJ
emphasizes species b & c, which are not shared by both
habitats, clearly quantifying the dissimilarity between the two habitats. The
summation of βJ & SJ results in unity.
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(4) |
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(5) |
The dissimilarity (βJ)
between two habitats can be divided into two parts, namely the species
replacement (RS) & richness difference (DR),
as depicted in Figure 1. When a particular number of species in focal Habitat –
1 is replaced by different but the same number of species in Habitat – 2, then
the phenomenon is known as species replacement (RS) and the number of species participated is
known as replaced species (Podani & Schmera 2011; Legendre 2014). It is
important to clarify that the term ‘replacement’ or ‘variation’ is used for
heterogeneous habitats-based studies, while the alternative term ‘turnover’ is
more prevalent for gradient-based studies (Anderson et al. 2011). The number of
dissimilar species not part of the replacement phenomenon is marked as the
difference in richness (DR). Both these quantities are
defined in Equations 6 & 9, respectively. The (1 – component) of both the
quantities are known as species nestedness (NS) and richness
agreement (AR) as expressed by Equations 7 & 8,
respectively. Whenever the species of Habitat – 1 is a subset of Habitat – 2,
it can be stated that both habitats have pure nestedness between them. It is
also observed that the higher the value of βJ, the higher the
anti-nested characteristics for the artificial presence-absence dataset (Podani
& Schmera 2011). The species nestedness (NS) &
species agreement (AR) can clearly be visualized in Figure 2.
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(6) |
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(7) |
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(8) |
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(9) |
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(10) |
The above indices can
be calculated using PAST (Paleontological Statistics software package for
education and data analysis) software (Hammer et al. 2001). It is important to
note that all the indices cannot be calculated directly by PAST software; however,
William’s index (Koleff et al. 2003) & Jaccard’s similarity index can be
estimated directly by the software. Using the estimated values of both indices,
the remaining indices are calculated by equations 4 through 10. It is important
to note that the normalization using the denominator (2a+b+c) can also
be implemented in the form of Sorenson’s index (βS).
Nevertheless, the Jaccard’s index (βJ) is chosen since it
gives an amplified value because of the lower value of (a+b+c), i.e.,
βJ > βS.
To visualize the
numerical values of indices intuitively, the simplex approach of visualization
is implemented since the summation of SJ, RS
and DR result in a value equal to 1 as per equation 10 (Podani & Schmera 2011). A graphical
depiction of the 2D (two-dimensional) simplex approach in the form of a Ternary
plot is shown in Figure 3. The apices of the equilateral triangle in the
ternary plot represent 100% values of RS, SJ
& DR. Their values decrease along their respective
simplices and result into 100% values of their (1 ‒ component), creating apices
of the inner equilateral triangle. The apices of this inner triangle represent
100% values of NS, βJ, and AR.
The dotted sides of the inner triangle denote 50% values of RS,
SJ, and DR. Any point inside a ternary plot
possesses values of RS, SJ and DR
corresponding to a pair of dissimilar habitats/assemblages. Thus, the 2D
simplex approach in the form of a ternary graph is used to represent indices
for present investigations.
In multivariate
analysis, the aforementioned indices are calculated for different pairs of
habitats; therefore, if there are m number of habitats in a given area,
the total number of such pairs would be mC2 as per
equation 11. Hence, the average value of these indices from these pair values
can be calculated using Equation 12.
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(11) |
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(12) |
RESULTS
AND DISCUSSION
Species
Richness
In
total, 152 species of birds belonging to 108 genera, 50 families and 14 orders
were recorded on the IITG campus (Appendix 1). Among them, 35 species are
winter migrants (including altitudinal migrants), four summer migrants, and
others are resident and local migrants (Choudhury 2000; Grimmett et al. 2016).
The highest number of species is found in secondary growth (83 species),
followed by eco-forest (68 species), swampy-marshy area (57 species),
constructions (38 species), and water bodies (33 species), as shown in Figure
3. In the case of species that are specific to a habitat type, the highest
numbers are recorded in eco-forest followed by swampy-marshy areas, secondary
growth, water bodies and, constructions. The highest difference between the
aforementioned numbers (total number of species found in a habitat and the
number of species that can only be found in the same habitat) is found in
secondary growth, which clearly indicates that most of the species are
generalists. The lowest difference is found for water bodies indicating a major
share of specialist species.
Approximately 36%, 35%, and 33% of the total species are specialists in
species composition of water bodies, swampy-marshy areas, and eco-forest
habitats, respectively. On the other hand, the values are 17% & 13%
(approximately 1/3rd of previous values) for habitats like secondary
growth & construction habitats, which clearly indicate that the percentage
of specialist species decreases due to construction work & associated
disturbances. These results are also supported by similar findings for the
Assam University Campus (Chakdar et al. 2016).
Approximately
49% of species belong to only one habitat type, i.e., nearly half of the total
species are specialists (Table 2). Five species are found in all of the five
habitats; Black Kite Milvus migrans, Asian Barred Owlet Glaucidium
cuculoides, Spotted Owlet Athene brama, Black Drongo Dicrurus
macrocercus, and Red-vented Bulbul Pycnonotus cafer. Similarly,
species namely the Spotted Dove Streptopelia chinensis, Cattle Egret Bubulcus
ibis, Shikra Accipiter badius, Taiga Flycatcher Ficedula
albicilla, and White Wagtail Motacilla alba are recorded in four
habitats (different habitats for each species) out of the total five habitats.
The qualitative abundance of each species is tabulated in Appendix 1.
Variation
in Species Compositions Among Different Habitats of IITG Campus
Following
the methodology discussed in the section on mathematical formulation for data
analysis, multivariate values of Jaccard’s similarity index (SJ)
& William’s index are estimated (Table 3). After that, other indices such
as βJ, RS, DR, NS,
and AR are calculated. As per Table 4, all of the
multivariate βJ values are more than 50%, clearly showing
high β – diversity of all the habitats in the IITG campus. The high β
– diversity values can be explained by the habitat heterogeneity
hypothesis, which states that an increase in the number of distinct habitats
leads to an increase in β – diversity and hence the overall diversity in
a landscape (MacArthur & MacArthur 1961). Because of habitat heterogeneity,
a successful adaptation of a particular species to one habitat leads to its
inferior competitiveness for another habitat. As a tradeoff between both,
distinct habitats in an area may be distinct in terms of species composition,
resulting in higher β – diversity among them (Cramer & Willig 2005;
Soininen et al. 2007). Additionally, the number of partitionable niche
dimensions is expanded due to habitat heterogeneity. The maximum value of βJ
= 94.8% is obtained between eco-forest & water bodies habitats.
Although both the habitats are contiguous, these habitat types have very
contrasting characteristics, i.e., the former is a hilly wooded forest and the
latter is aquatic. A similar trend is reported for contrasting habitats even in
a gradient-based study (Goettsch & Hernández 2006). The lowest value of βJ
= 57.1% is found between eco-forest & swampy-marshy areas.
Average β – diversities (βJ, avg) (e.g., for habitat –
1 of the present case, βJ for pairs 12, 13, 14,
and 15 are averaged) of each habitat is more than 70%. The overall β̅J
calculated using Equation 12 is approximately 79%, showing very high β –
diversity for the overall IITG campus area.
The
authors of the present paper implemented the current approach of β –
diversity analysis in another documented research article (Surasinghe &
Alwis 2010) to gain more insight into the species variation in different
habitats of college campuses besides the present study. The study recorded 145
species distributed into seven different habitats of the ‘Sabargamuwa’
university campus (area ≈ 0.5 km2, established in 1990); however, β
– diversity analysis and species variation along habitats were not
analyzed. Authors of the present paper calculated β̅J ≈ 82%
for ‘Sabargamuwa’ university campus, which is close to the β̅J
≈ 79% of the IITG campus area (area ≈ 2.8 km2, established in 1995).
The
results of the multivariate analysis are presented in a graphical ternary plot
(Figures 5,6) using the values of RS, DR,
and SJ listed in Tables 3 & 5. As discussed, the ternary
plot provides a better understanding of the relative composition of richness
difference (DR) & species replacement (RS)
constituting βJ. Figure 4 shows that most of the multivariate
data points are enclosed by β- – triangle (depicted in Figure 2) and are
leaning towards the left side of the equilateral triangle, indicating high βJ
values. A similar type of trend is also observed in Figure 5. Further, the
majority of the points (circular & solid red markers) are congregated in
the top 1/3rd portion of a quadrilateral (depicted in Figure 2) with
a propensity towards replacement (RS apex) rather than the
richness difference (DR apex). Therefore, species replacement
is dominating factor behind the high β- – diversity of IITG habitats.
The reason might be that the specialist species of one habitat are replaced by
those of another habitat without much relative difference between them in terms
of species numbers. This can also be explained by the niche-based hypothesis,
which states that the difference in habitat compositions drives species
turnover between different locations along a gradient or species variation
through replacement among different habitats in a given area (Anderson et al.
2011; Lorenzón et al. 2016).
On
the other hand, the points are equally dispersed towards RS
apex (circular markers) & DR apex (solid circular
markers) for Figure 5. Hence, the species replacement and richness difference
are equally responsible for the high β- – diversity of ‘Sabargamuwa’
university campus. Graphically, the points of Figure 4 are distributed along R
– simplex, while they are along S- – simplex for Fig. 6 while
maintaining inclination towards high β-J values. The habitat
pair of secondary growth and constructions yields the highest value of
nestedness (NS ≈ 88.5%) among IITG habitats, indicating a
subset relationship between them. The dispersed and non-contiguous nature of
the constructions habitat inside the secondary growth habitat might be
the reason for such species composition. A corresponding multivariate point
(red square marker) is also located towards the triangle’s lower side, clearly
showing a prominent nestedness behavior. Likewise, the nestedness is observed
between dry-mixed semi-evergreen forest and residential habitat in Figure 5
(red solid square marker at point 45). A similar trend of high β- –
diversity is observed for the Colorado fish dataset (Smith 1978), involving six
different sites and 26 fish species in the ternary plot (Podani & Schmera
2011). The high β- – diversity was constituted by DR
as a major factor and RS as a minor factor. The reason behind
this trend was believed to be many extinctions and a few successful
colonization.
Therefore,
it can be concluded that the habitats in IITG habitats proclaim high β –
diversity due to habitat heterogeneity. The main factor behind high β –
diversity is species replacement rather than species richness differences. Most
importantly, habitat heterogeneity is also a result of anthropogenic impacts.
The β – diversity is observed to increase during the initial stage of
the anthropogenic impacts due to the extinction of rarer specialist species and
the establishment of invasive generalist species (considering the campus a
biogeographic island) (Socolar et al. 2016). Gradually, the invasive generalist
species become more dominant while eradicating native specialist species.
Hence, the entire process gives a momentary increment in β-diversity followed
by a simultaneous drop in β-diversity and overall species richness.
Therefore, the high β-diversity of the IITG campus indirectly indicates
the initial phase of anthropogenic impact.
It
is noteworthy to clarify that the present analysis only emphasizes
presence-absence data, not the abundance data, providing equal weightage to
both rare and abundant species. Nevertheless, the species list with qualitative
abundance code is provided in Appendix 1 for further insights.
THREATS
AND CONSERVATION MEASURES
Not
much past documented data are available in the literature about the avian
diversity of the IITG campus; nevertheless, a checklist from a web source is
available from July 2000─February 2002 (Praveen 2002). The documentation was
done during that time of the year when most of the area within the campus was a
part of the wetland on which the autonomous institute was built. As eBird was
launched only in 2014 in India, the earlier historical records of species
within campus could not be found in the portal. Hence, the authors had to rely
on the website on which the aforementioned documentation had been uploaded. The
checklist listed 120 species, most of which had been observed during the period
of the present study (2017─2020). The exceptions are Eurasian Wryneck Jynx
torquilla, Little-ringed Plover Charadrius dubius, Osprey Pandion
haliaetus, Eurasian Marsh Harrier Circus aeruginosus, and Common
Kestrel Falco tinnunculus that were not observed during the period.
These species are common in nearby wetlands and water bodies. The reason behind
their disappearance from the campus could be the deterioration of water bodies
and marshy areas besides the peripheral vegetation that came up due to
construction activities.
During
the 2017─2020 timeframe, one critically endangered, one endangered, two
vulnerable and three near threatened species were recorded as per IUCN Red List
norms as enlisted in Table 6. Both the migratory aquatic species, viz., Common
Pochard Aythya ferina and Ferruginous Duck Aythya nyroca can be
observed in the water bodies of the campus during winter in small numbers
(10─20); however, their presence have become less frequent with each winter as
per the observations of the authors. Another important observation by the
authors is that both the species, besides other duck & pochard species, are
mostly found in Serpentine and ‘Tihor’ lakes, and not in the IITG lake.
The reason can be the small island type patches and bushes on the fringes of
the lakes, except that of the IITG lake, which provides safe roosting places
for the aforementioned species (as the majority of them are nocturnal feeders)
(Ali & Ripley 1978) away from the reach of feral cats, dogs, and Indian
Jackal Canis aureus indicus. Over time, vegetation on the fringes of the
IITG lake has been removed due to constant construction work, fencing, and
campus beautification by planting Bottle palm tree species. This would be one
of the probable reasons behind their less frequent presence. Preservation of
the small island patches and vegetation on peripheral fringes can be an
important step to maintain the Water bodies undegraded for the critically
endangered and near threatened aquatic species besides other species.
The
Red-breasted Parakeet usually prefers forest and wooded habitats. Therefore, it
is recorded in eco-forest and wooded areas of secondary growth. It nests
in the cavities of trees and is mainly frugivorous. Therefore, it is advisable
to conserve already present teak wood patches and other trees along with
fruit-bearing ones like Gular Tree Ficus racemosa.
As
mentioned in the ‘Results and Discussion’ section, the IITG campus has a high
value of β – diversity, with species replacement as a dominating factor.
It is reported in the literature that the replacement across multiple habitats
in a given area (or turnover for gradient-based study) implies the focus to be
on conservation efforts over multiple habitats rather than any single habitat
(Socolar et al. 2016). Hence, the conservation effort for the avian community
of the IITG campus should be directed towards each habitat uniformly. Moreover,
the species richness of the campus is 152 species, which is way over the
average species richness (by considering the dataset of 300 plus campuses),
equal to 66, as per the review conducted by (Liu et al. 2021). For such avian
(or overall) diversity-rich campuses, different key steps were suggested
(Kobori & Primack 2003; Colding & Barthel 2017; Liu et al. 2021). It is
recommended that a―certain parts of the campus should be protected with minimal
scraping and disturbance | b―diversity of university campuses should be
monitored thoroughly to plan more diversity-friendly designs, | c―provide
nature-based education and awareness to campus residents, especially the
students as they are the next generation of potential birders/naturalists |
d―restoration of biodiversity in the surrounding area with biodiversity
protected in campus | e―implement primary biodiversity educational courses. In
this direction, different activities are being carried out in the IITG campus,
as narrated in the following paragraph.
Awareness
of the avifauna within the IITG campus was restricted only to the birders with
experience. Therefore, the authors, with support from the IITG population
(refer to acknowledgement), tried to spread the message of the presence of
birds within the campus by organizing ‘Bird Walk’ events frequently. During
these events, participants were provided with the necessary support to identify
and understand the importance of birds. These events have been organized as a
part of the ‘Campus Bird Count (CBC)’ and ‘Bihu Bird Count’ projects every year
since 2017 & 2020, respectively. The CBC, conducted under the banner of
‘Great Backyard Bird Count’ by Bird Count India (https://birdcount.in/about/),
has further accelerated the process of counting the species and the number of
birds in a given time frame within various campuses across the country. Other
Campuses within Assam have also participated in CBC since its inception in
2014, with IITG recording one of the highest numbers of species yearly. ‘Bihu
Bird Count’ is a regional citizen science project hosted by Assam Bird
Monitoring network and Bird Count India, integrating with the celebration of
‘Bihu’ festivals (celebrated three times a year) with documentation of avifauna
since its initiation in the year 2020. Especially for water bodies and
swampy-marshy habitats, the ‘Asian Waterbird Census’ (by Bird Count India and
International Waterbird census – IWC) has also been organized in the IITG
campus to record migratory waterbirds. Plantation drives are also being
organized from time to time in the eco-forest, secondary growth and periphery
of the water bodies, which will be beneficial, especially for IITG lake, to
address the concerns mentioned earlier. Further, a pictorial guide on birds in
the form of a coffee table book (Bhaduri et al. 2020) is also launched by the
IITG to inform visitors and students about avian diversity.
Table 1. Area of
different habitats.
|
Habitat type |
Area (km2) |
|
Water bodies |
0.235 |
|
Swampy-marshy |
0.307 |
|
Secondary growth |
0.456 |
|
Eco-forest |
0.783 |
|
Constructions |
1.019 |
|
Total |
2.8 |
Table 2. Number of
species found in the given number of habitats.
|
Number of total
habitats |
Number of species |
|
1 |
74 |
|
2 |
46 |
|
3 |
22 |
|
4 |
5 |
|
5 |
5 |
Table 3. Values for
Jaccard’s similarity index-SJ (upper triangle) and William’s index (lower
triangle).
|
Habitats* |
1 |
2 |
3 |
4 |
5 |
|
1 |
‒– |
0.052 |
0.096 |
0.428 |
0.235 |
|
2 |
0.291 |
‒– |
0.304 |
0.105 |
0.111 |
|
3 |
0.403 |
0.173 |
‒– |
0.241 |
0.160 |
|
4 |
0.219 |
0.211 |
0.267 |
‒– |
0.367 |
|
5 |
0.200 |
0.412 |
0.296 |
0.057 |
‒– |
|
*Habitats are
tagged as: 1—Eco-forest | 2—Water bodies | 3—Swampy-marshy area | 4—Secondary
growth | 5—Constructions. |
|||||
Table 4. Values for
Jaccard’s dissimilarity index (βJ) (upper triangle) and
Nestedness index (NS) (lower triangle).
|
Habitats* |
1 |
2 |
3 |
4 |
5 |
βJ, avg |
β̅J |
||
|
1 |
‒– |
0.947 |
0.903 |
0.571 |
0.764 |
0.796 |
|
||
|
2 |
0.416 |
‒– |
0.695 |
0.894 |
0.888 |
0.856 |
|
||
|
3 |
0.192 |
0.652 |
‒– |
0.758 |
0.835 |
0.799 |
0.789 |
||
|
4 |
0.561 |
0.576 |
0.464 |
‒– |
0.632 |
0.714 |
|
||
|
5 |
0.600 |
0.174 |
0.407 |
0.885 |
‒– |
0.781 |
|
||
|
* Habitats are
tagged as: 1—Eco-forest | 2—Water bodies | 3—Swampy-marshy area | 4—Secondary
growth | 5—Constructions. |
|||||||||
Table 5. Values for
Species replacement index (RS) (upper triangle) and Richness
difference index (DR) (lower triangle).
|
Habitats* |
1 |
2 |
3 |
4 |
5 |
|
1 |
‒– |
0.583 |
0.807 |
0.438 |
0.400 |
|
2 |
0.364 |
‒– |
0.347 |
0.423 |
0.825 |
|
3 |
0.096 |
0.347 |
‒– |
0.535 |
0.592 |
|
4 |
0.133 |
0.471 |
0.223 |
‒– |
0.114 |
|
5 |
0.364 |
0.063 |
0.246 |
0.517 |
‒– |
|
* Habitats are
tagged as: 1—Eco-forest | 2—Water bodies | 3—Swampy-marshy area | 4—Secondary
growth | 5—Constructions. |
|||||
Table 6. List of
recorded species under the IUCN Red List.
|
IUCN Red List
status |
Species name |
Taxonomic name |
|
Critically
Endangered |
Slender-Billed
Vulture |
Gyps tenuirostris |
|
Endangered |
Greater Adjutant |
Leptoptilos dubius |
|
Vulnerable |
Common Pochard |
Aythya ferina |
|
Lesser Adjutant |
Leptoptilos
javanicus |
|
|
Near Threatened |
Ferruginous Duck |
Aythya nyroca |
|
Himalayan Griffon |
Gyps himalayensis |
|
|
Red-Breasted
Parakeet |
Psittacula
alexandri |
|
|
Oriental Darter |
Anhinga
Melanogaster |
For figures &
images - - click here for full PDF
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Appendix 1. Checklist
of avian species recorded in IITG during 2017–2020.
|
|
Name |
Scientific name |
Presence-Absence
data for different habitats |
Abundance code |
Residency code |
IUCN Status |
||||
|
Eco-forest |
Water bodies |
Swampy -marshy
area |
Secondary growth |
Constructions |
||||||
|
1 |
Common Pochard |
Aythya ferina |
0 |
1 |
0 |
0 |
0 |
U |
WM |
VU |
|
2 |
Cotton Pygmy-Goose |
Nettapus
coromandelianus |
0 |
1 |
0 |
0 |
0 |
R |
R |
LC |
|
3 |
Eurasian Wigeon |
Anas penelope |
0 |
1 |
0 |
0 |
0 |
R |
WM |
LC |
|
4 |
Ferruginous Duck |
Aythya nyroca |
0 |
1 |
0 |
0 |
0 |
U |
WM |
NT |
|
5 |
Fulvous
Whistling-Duck |
Dendrocygna bicolor |
0 |
1 |
1 |
0 |
0 |
U |
WM |
LC |
|
6 |
Gadwall |
Mareca strepera |
0 |
1 |
0 |
0 |
0 |
U |
WM |
LC |
|
7 |
Green-Winged Teal |
Anas crecca |
0 |
1 |
0 |
0 |
0 |
U |
WM |
LC |
|
8 |
Lesser
Whistling-Duck |
Dendrocygna
javanica |
0 |
1 |
1 |
0 |
0 |
C |
R |
LC |
|
9 |
Tufted Duck |
Aythya fuligula |
0 |
1 |
0 |
0 |
0 |
U |
WM |
LC |
|
10 |
Yellow-Footed
Green-Pigeon |
Treron
phoenicopterus |
1 |
0 |
0 |
1 |
0 |
C |
R |
LC |
|
11 |
Spotted Dove |
Streptopelia
chinensis |
1 |
0 |
1 |
1 |
1 |
C |
R |
LC |
|
12 |
Red Collared-Dove |
Streptopelia
tranquebarica |
0 |
0 |
0 |
1 |
0 |
U |
R |
LC |
|
13 |
Eurasian
Collared-Dove |
Streptopelia
decaocto |
1 |
0 |
0 |
1 |
0 |
C |
R |
LC |
|
14 |
Rock Pigeon |
Columba livia |
0 |
0 |
0 |
1 |
0 |
C |
R |
LC |
|
15 |
Asian Koel |
Eudynamys
scolopaceus |
1 |
0 |
0 |
1 |
1 |
C |
R |
LC |
|
16 |
Common Hawk-Cuckoo |
Hierococcyx varius |
1 |
0 |
0 |
1 |
0 |
C |
R |
LC |
|
17 |
Banded Bay-Cuckoo |
Cacomantis
sonneratii |
1 |
0 |
0 |
0 |
0 |
R |
R |
LC |
|
18 |
Greater Coucal |
Centropus sinensis |
1 |
0 |
1 |
1 |
0 |
C |
R |
LC |
|
19 |
Lesser Coucal |
Centropus
bengalensis |
0 |
0 |
1 |
1 |
0 |
C |
R |
LC |
|
20 |
Green-Billed
Malkoha |
Phaenicophaeus
tristis |
1 |
0 |
0 |
0 |
0 |
U |
R |
LC |
|
21 |
Plaintive Cuckoo |
Cacomantis
merulinus |
1 |
0 |
0 |
0 |
0 |
R |
R |
LC |
|
22 |
Pied Cuckoo |
Clamator jacobinus |
1 |
0 |
0 |
0 |
0 |
U |
SM |
LC |
|
23 |
Indian Cuckoo |
Cuculus micropterus |
1 |
0 |
0 |
1 |
0 |
C |
SM |
LC |
|
24 |
Asian Palm-Swift |
Cypsiurus
balasiensis |
1 |
0 |
0 |
1 |
0 |
C |
R |
LC |
|
25 |
House Swift |
Apus nipalensis |
0 |
0 |
0 |
0 |
1 |
C |
R |
LC |
|
26 |
Brown-Cheeked Rail |
Rallus indicus |
0 |
0 |
1 |
0 |
0 |
R |
WM |
LC |
|
27 |
Slaty-Breasted Rail |
Lewinia striata |
0 |
0 |
1 |
0 |
0 |
R |
R |
LC |
|
28 |
Eurasian Moorhen |
Gallinula chloropus |
0 |
1 |
1 |
0 |
0 |
C |
R |
LC |
|
29 |
White-Breasted
Waterhen |
Amaurornis
phoenicurus |
0 |
1 |
1 |
1 |
0 |
C |
R |
LC |
|
30 |
Eurasian Coot |
Fulica atra |
0 |
1 |
0 |
0 |
0 |
C |
R |
LC |
|
31 |
Grey-Headed
Swamphen |
Porphyrio
poliocephalus |
0 |
0 |
1 |
0 |
0 |
R |
R |
LC |
|
32 |
Red-Wattled Lapwing |
Vanellus indicus |
0 |
0 |
1 |
1 |
1 |
C |
R |
LC |
|
33 |
Bronze-Winged
Jacana |
Metopidius indicus |
0 |
1 |
1 |
0 |
0 |
C |
R |
LC |
|
34 |
Pheasant-Tailed
Jacana |
Hydrophasianus
chirurgus |
0 |
1 |
0 |
0 |
0 |
R |
R |
LC |
|
35 |
Asian Openbill |
Anastomus oscitans |
0 |
1 |
1 |
0 |
0 |
C |
R |
LC |
|
36 |
Greater Adjutant |
Leptoptilos dubius |
0 |
0 |
1 |
0 |
0 |
U |
R |
EN |
|
37 |
Lesser Adjutant |
Leptoptilos
javanicus |
0 |
0 |
1 |
0 |
0 |
U |
R |
VU |
|
38 |
Oriental Darter |
Anhinga
melanogaster |
0 |
0 |
1 |
0 |
0 |
R |
R |
NT |
|
39 |
Little Cormorant |
Microcarbo niger |
0 |
1 |
1 |
0 |
0 |
C |
R |
LC |
|
40 |
Great Cormorant |
Phalacrocorax carbo |
0 |
1 |
0 |
0 |
0 |
R |
R |
LC |
|
41 |
Cinnamon Bittern |
Ixobrychus
cinnamomeus |
0 |
0 |
1 |
1 |
0 |
C |
R |
LC |
|
42 |
Indian Pond-Heron |
Ardeola grayii |
0 |
1 |
1 |
0 |
0 |
C |
R |
LC |
|
43 |
Black-Crowned
Night-Heron |
Nycticorax
nycticorax |
0 |
0 |
1 |
0 |
0 |
U |
R |
LC |
|
44 |
Purple Heron |
Ardea purpurea |
0 |
1 |
1 |
0 |
0 |
U |
R |
LC |
|
45 |
Striated Heron |
Butorides striata |
0 |
0 |
1 |
0 |
0 |
U |
R |
LC |
|
46 |
Cattle Egret |
Bubulcus ibis |
0 |
1 |
1 |
1 |
1 |
C |
R |
LC |
|
47 |
Little Egret |
Egretta garzetta |
0 |
1 |
1 |
1 |
0 |
C |
R |
LC |
|
48 |
Intermediate Egret |
Ardea intermedia |
0 |
0 |
1 |
0 |
0 |
U |
R |
LC |
|
49 |
Yellow Bittern |
Ixobrychus sinensis |
0 |
0 |
1 |
0 |
0 |
R |
R |
LC |
|
50 |
Booted Eagle |
Hieraaetus pennatus |
1 |
0 |
0 |
0 |
0 |
U |
WM |
LC |
|
51 |
Crested
Serpent-Eagle |
Spilornis cheela |
1 |
0 |
0 |
0 |
0 |
R |
R |
LC |
|
52 |
Short-Toed
Snake-Eagle |
Circaetus gallicus |
0 |
0 |
0 |
1 |
0 |
R |
R |
LC |
|
53 |
Oriental
Honey-Buzzard |
Pernis
ptilorhynchus |
1 |
0 |
0 |
0 |
0 |
R |
R |
LC |
|
54 |
Black Kite |
Milvus migrans |
1 |
1 |
1 |
1 |
1 |
C |
R |
LC |
|
55 |
Black-Winged Kite |
Elanus caeruleus |
0 |
0 |
0 |
1 |
0 |
R |
R |
LC |
|
56 |
Shikra |
Accipiter badius |
1 |
0 |
1 |
1 |
1 |
C |
R |
LC |
|
57 |
Himalayan Griffon |
Gyps himalayensis |
1 |
0 |
0 |
0 |
0 |
R |
WM |
NT |
|
58 |
Slender-Billed
Vulture |
Gyps tenuirostris |
0 |
0 |
0 |
1 |
0 |
R |
R |
CR |
|
59 |
Asian Barred Owlet |
Glaucidium
cuculoides |
1 |
1 |
1 |
1 |
1 |
C |
R |
LC |
|
60 |
Spotted Owlet |
Athene brama |
1 |
1 |
1 |
1 |
1 |
C |
R |
LC |
|
61 |
Barn Owl |
Tyto alba |
0 |
0 |
0 |
1 |
1 |
U |
R |
LC |
|
62 |
Brown Hawk-Owl |
Ninox scutulata |
0 |
0 |
1 |
1 |
1 |
C |
R |
LC |
|
63 |
Oriental Scops Owl |
Otus sunia |
1 |
0 |
0 |
0 |
0 |
R |
R |
LC |
|
64 |
Eurasian Hoopoe |
Upupa epops |
0 |
0 |
0 |
1 |
0 |
C |
R |
LC |
|
65 |
Oriental Pied
Hornbill |
Anthracoceros
albirostris |
1 |
0 |
0 |
0 |
0 |
R |
R |
LC |
|
66 |
Stork-Billed
Kingfisher |
Pelargopsis
capensis |
0 |
0 |
1 |
0 |
0 |
U |
R |
LC |
|
67 |
White-Throated
Kingfisher |
Halcyon smyrnensis |
0 |
1 |
1 |
1 |
0 |
C |
R |
LC |
|
68 |
Common Kingfisher |
Alcedo atthis |
0 |
1 |
1 |
0 |
0 |
R |
R |
LC |
|
69 |
Pied Kingfisher |
Ceryle rudis |
0 |
1 |
0 |
0 |
0 |
R |
R |
LC |
|
70 |
Green Bee-Eater |
Merops orientalis |
1 |
0 |
0 |
1 |
0 |
C |
R |
LC |
|
71 |
Chestnut-Headed
Bee-Eater |
Merops leschenaulti |
1 |
0 |
0 |
0 |
0 |
U |
SM |
LC |
|
72 |
Blue-Tailed
Bee-Eater |
Merops philippinus |
0 |
0 |
0 |
1 |
0 |
U |
SM |
LC |
|
73 |
Indo-Chinese Roller |
Coracias affinis |
0 |
0 |
0 |
1 |
1 |
C |
R |
LC |
|
74 |
Coppersmith Barbet |
Psilopogon
haemacephalus |
1 |
0 |
0 |
1 |
0 |
U |
R |
LC |
|
75 |
Blue-Throated
Barbet |
Psilopogon
asiaticus |
1 |
0 |
0 |
1 |
0 |
C |
R |
LC |
|
76 |
Lineated Barbet |
Psilopogon lineatus |
1 |
0 |
0 |
1 |
0 |
C |
R |
LC |
|
77 |
Fulvous-Breasted
Woodpecker |
Dendrocopos macei |
1 |
0 |
0 |
1 |
0 |
C |
R |
LC |
|
78 |
Black-Rumped
Flameback |
Dinopium
benghalense |
1 |
0 |
0 |
1 |
0 |
C |
R |
LC |
|
79 |
Greater Flameback |
Chrysocolaptes
guttacristatus |
1 |
0 |
0 |
1 |
0 |
C |
R |
LC |
|
80 |
Rufous Woodpecker |
Micropternus
brachyurus |
1 |
0 |
0 |
0 |
0 |
R |
R |
LC |
|
81 |
Peregrine Falcon |
Falco peregrinus |
0 |
0 |
0 |
1 |
||||