Journal of Threatened
Taxa | www.threatenedtaxa.org | 26 December 2023 | 15(12): 24321–24330
ISSN 0974-7907
(Online) | ISSN 0974-7893 (Print)
https://doi.org/10.11609/jott.7647.15.12.24321-24330
#7647 | Received 04 September 2021 | Final received 31 August 2023 |
Finally accepted 23 September 2023
Diversity of wintering avifauna
throughout the heterogeneous aquatic habitats of Bankura District, West Bengal,
India
Biplob Kumar Modak
1, Subha Shankar Mukherjee 2, Susobhan Mondal 3, Mainak
Sarkar 4 & Asif Hossain 5
1.2.3.4 Department of Zoology, SKB
University, Purulia, West Bengal 723104, India.
2,5 Department of Zoology, The
University of Burdwan, Golapbag, Burdwan, West Bengal
713104, India.
1 bkmodak09@gmail.com, 2 msubhashankar@gmail.com,
3 susobhan.sm@gmail.com, 4 mainakbios@gmail.com, 5 asifhossain.bu@gmail.com (corresponding
author)
Editor: S. Balachandran, Bombay Natural History
Society, Mumbai, India. Date of publication: 26 December
2023 (online & print)
Citation: Modak, B.K., S.S. Mukherjee, S. Mondal, M. Sarkar
& A. Hossain (2023). Diversity of wintering avifauna throughout the
heterogeneous aquatic habitats of Bankura District, West Bengal, India. Journal of Threatened Taxa 15(12): 24321–24330. https://doi.org/10.11609/jott.7647.15.12.24321-24330
Copyright: © Modak et al. 2023. 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: Financial assistance provided by WBBB (Memo no. 51./5k(Bio)-3/2018 dt 09/01/2019).
Competing interests: The authors declare no competing interests.
Author details: Biplob Kumar Modak is a professor in Department of Zoology, Sidho-Kanho-Birsha University, Purulia. Subha Shankar Mukherjee is a
senior research fellow (UGC) in Department of Zoology, The University of Burdwan. Susobhan Mondal is a
research scholar in Department of Zoology, Sidho-Kanho-Birsha University. Mainak Sarkar is a
research scholar in Department of Zoology, Sidho-Kanho-Birsha University. Asif Hossain is an assistant professor in Department of Zoology, The University of Burdwan.
Author contributions: BKM conceptualised the idea, helped in data collection and drafting the manuscript. SSM contributed in data collection and analyses. SM helped in field survey and data analyses. MS helped in field survey and data analyses. AH helped data collection, analyses and drafting manuscript.
Acknowledgements:
The authors thankfully
acknowledge the head, Department of Zoology, SKB University, Purulia, India,
and Head, Department of Zoology, The University of Burdwan, Golapbag,
Burdwan, India, for the facilities provided. The authors thankfully acknowledge
the critical comments of the anonymous reviewers and the suggestions of the
respected chief editor that helped in transforming the manuscript into the
present form. Financial assistance provided by WBBB (Memo no. 51./5k(Bio)-3/2018 dt 09/01/2019)
is thankfully acknowledged.
Abstract: Birds play various crucial roles
in the ecosystem including pollination, seed dispersal, and pest control.
Assemblages of bird species in a particular landscape are useful predictors in
various ecosystem services, this is evident from studies of forest bird
assemblages, aquatic bodies and agro ecosystems. For
developing conservation strategies, information on bird species assemblages in
a particular geographical area is important. Diversity in aquatic ecosystem
support a diversity of water bird species. In the present study, around 45 bird
species were recorded in 21 aquatic bodies in Bankura, West Bengal, India, in
which two species, namely, Leptoptilos javanicus and Aythya
ferina declared ‘Vulnerable’ and three species
such as Mareca falcata, Threskiornis
melanocephalus, and Limosa
limosa considered as ‘Near Threatened’ according
to the IUCN Red list. Dendrocygna javanica and Nettapus
coromandelianus were found to be the most
abundant. In those 21 study areas, site6 has the highest species richness and
site2 has the lowest. The dominance index was highest for site2 and lowest for
site6. Pielou’s index of evenness was highest for
site20. The rarefaction curve showed species abundance was highest for site1.
Classical cluster analysis for species abundance showsthat
site20, site21, site3, site8, site4, site19, site5, site14, site12, site15,
site7, site 10 site11, and site13 are closely related. This paper is aimed to
generate interest among people to conserve aquatic birds and their habitats and
to document baseline information for further study.
Keywords: Abundance, conservation,
diversity, evenness, Near Threatened, richness, Vulnerable, winter birds.
Introduction
Birds are one of the most popular
life forms on the planet and their diversity contributes to life’s richness and
beauty. Birds are important components of the ecosystem contributing
substantively toecosystem function, especially
pollination, seed dispersal, pest control, nutrient cycling, and others (Whelan
et al. 2008; Sekercioglu 2012). Information on bird
assemblages in forests (Aich & Mukhopadhyay 2008;
Roy et al. 2011; Chatterjee et al. 2013), aquatic bodies (Kumar et al. 2006;
Kumar & Gupta 2013), agricultural and otherlandscapes
are useful tools in understanding the various ecosystem health (Dhindsa & Saini 1994; Borad
et al. 2001; Basavarajappa 2006; Gopi Sundar 2011; Gopi Sundar & Kittur 2013; Hossain & Aditya 2014) and to develop
strategies for conservation and further monitoring of ecosystem conditions and
functions (Bradford et al. 1998; Browder et al. 2002). Millions of people rely
on aquatic ecosystems for a better living through fishing, agricultural
irrigation and other purposes. Birds can be found almost everywhere on the
planet, in almost every climatic condition and at nearly every altitude. Birds
are excellent environmental indicators because they respond quickly to changes
in habitat structure, composition and other environmental factors (Hossain
& Aditya 2014). Besides their aesthetic role, they also hold a unique
position in the food chain. Aquatic ecosystems are highly productive ecosystems
on Earth and provide people a source of food, animal farming, fisheries,
aquaculture and also as a refuge for rare and endangered plant and animal
species. The assemblage of foraging bird species is dependent on habitat type
and stable condition of food resources. Migratory birds also play an important role
in maintaining ecosystem health by influencing nutrient cycling during the
migratory season. The present study deals with the documentation of avifauna in
Bankura and similar areas in the Chota Nagpur
Plateau. The study sites are heterogeneous in habitat structure as some of the
aquatic bodies are in plains area while others are from hilly terrains, and
forested areas while some from agricultural areas and a few of them are within
the human settlements. The climate of the Bankura District is characterized by
excessive heat in summer and highly humid throughout the year. The average
daily maximum temperature varies 26–39 0C during summer and during
winter temperature ranges 12–25 0C. The relative humidity is high
throughout the year. Damodar, Dwarakeswar,
Silabati, and Kangsabati
are the four major rivers of Bankura District. These rivers constitute the main
drainage system of this district. The Kangsabati dam
is a major dam constructed on the river at Mukutmanipur
of Bankura District to arrest flood and to provide irrigation facilities. There
are many threats to the water bodies of Bankura that include pollution due to
domestic sewage, pesticides, fertilizers, farming agriculture along the
exposing periphery, eutrophication/blooms of surface water, partial reclamation
of wetland, residential & commercial development, and sedimentation that
are the primary factors for reducing species diversity including birds.
The current study’s goal was to
assess the diversity of wintering aquatic birds and create an avifauna
checklist for the district of Bankura, West Bengal, India, which will aid in
future aquatic bird management with appropriate conservation strategies.
Materials
and Methods
Study Area
The survey was carried out at 21
water bodies and adjoining landscapes in Bankura, West Bengal, India, namely Mukutmanipur Dam (Site 1), Lal Bandh (Site 2), Jamuna Bandh
(Site 3), Krishna Bandh (Site 4), Kulaijurir Bandh
(Site 5), Sal Bandh (Site 6), Kadam Deuli Dam (Site
7), Sutan Dam (Site 8), Gangdua
Dam (Site 9), Bonkati Bandh (Site10), Bagjobra Bandh (Site11), Kesiakol
Bandh (Site 12), Talberia Dam (Site 13), Kakila Daha (Site 14), Jhilimili Bandh (Site 15), Poabagan
Bandh (Site 16), Chattna Bandh (Site 17), Nityanandapur Dam (Site 18), AmbikanagarBandh
(Site 19), Saheb Bandh (Site 20), and Ranir Bandh
(Site 21). All of the sites’ coordinates are plotted in a raster plot (Figure 1a,b,c). The following are the specific characteristics of
these aquatic bodies:
Mukutmanipur dam: This is a reservoir type of
aquatic body, with rain water and streams as the primary sources of water. This
body of water covers approximately 38.4 ha and has a maximum depth of 11 m.
Vegetation covered 5% of the area, including submerged Hydrilla as well as
shrubs and reeds in the bank.
Lal Bandh:
Fresh water lake with 30% vegetation cover, including shrubs, reeds, Hydrilla, water hyacinth, and water lilies. The lake has a surface area of about 12 ha and a maximum depth of about 9 m.
Jamuna Bandh: This freshwater
lake covers an area of 22 ha, with vegetation covering 90% of the area. This
aquatic body has a maximum depth of approximately 8 m.
Krishna Bandh: Relying completely
on rainfall and local streams, this freshwater lake spans 10 ha in surface area
with a maximum depth of 5 m. Notably, 30% of the area hosts vegetation,
including submerged Hydrilla, free-floating water hyacinth, shrubs, and reeds
along the banks.
Kulaijurir bandh: This freshwater pond
covers an area of 18 ha and has a maximum depth of about 5 m; 56% of the area
is covered by vegetation, which includes various shrubs on the bank,
free-floating water hyacinth, and submerged Hydrilla.
Sal bandh: Sal bandh is a 3.5-ha
reservoir with a maximum depth of 3 m. It is dependent on local rain and is
only temporary in nature. Vegetation covered 20% of this area.
Kadam Deuli
dam: Featuring a 7 m maximum depth, this rainwater and stream-fed freshwater
pond spans a total area of 14.94 ha. Impressively, 86% of this expanse is
veiled by vegetation.
Sutan dam: This reservoir has a
surface area of 6.5 ha and a maximum depth of 4 m. It is primarily dependent on
rainfall and streams. Vegetation such as Hydrilla and various shrubs
covered 15% of the area.
Gangdua dam: This lake’s main source of
water is local rainfall and streams. This body of water has an area of about 18
ha and a maximum depth of 7.5 m. Hydrilla and water lily vegetation covered 35%
of the area.
Bonkati bandh:
The main sources of water for this freshwater lake are local rainand streams. This water body covers an area of11.92 ha and has a maximum depth of about 5 m. The
vegetation covered 66% of the land area.
Bagjobra bandh: This lake covers 5 ha,
and 86% of it is covered by vegetation such as shrubs and reeds growing on the
bank, free floating water hyacinth, submerged Hydrilla, and floating,
leaved-rooted water lilies.
Kesiakol bandh: This freshwater lake
covers 10.26 ha and has a maximum depth of 4.5 m. The lake is 10.26 ha in size,
with vegetation covering 38% of the area.
Talberia dam: Talberia
dam is a freshwater lake with a surface area of 12.30 ha and a maximum depth of
5 m. It is reliant on rainwater and streams, and vegetation covers 53% of the
area, including various shrubs in the bank, Hydrilla, water hyacinth,
and water lilies.
Kakila Daha:
Local rainwater and streams are the primary sources of water for this lake,
which has a maximum depth of 5 m. This lake took up 4.94 ha of land, accounting
for 39% of the total vegetation area.
Jhilimili bandh: This freshwater lake has
a surface area of 12.37 ha and a maximum depth of 5.5 m. It is entirely
dependent on rainwater and streams for its survival. The vegetation covered 66%
of the land area.
Poabagan bandh: Spanning an area of 4.514
ha, this site relies on local rainfall and streams for sustained existence.
Vegetation, encompassing shrubs, reeds, Hydrilla, and water hyacinth, blankets
46% of the area.
Chattna bandh:
This freshwater lake has an area of 11.30 ha, with vegetation covering
69%
of it. Its long-term survival is dependent on local rains and streams.
Nityanandapur dam: With a surface area of 24
ha and a maximum depth of 7 m, this reservoir relies on rainfall and local
streams. About 90% of its area features vegetation, including various shrubs,
Hydrilla, and water lilies.
Ambikanagar bandh: This freshwater lake, fed
by local rain and streams, spans an area of 18 ha with a maximum depth of 12 m.
Approximately 90% of the area is covered by vegetation
Saheb bandh: A freshwater lake
with a surface area of 9.2 ha and a depth of 6 m. It is mainly dependent on
local rainfall and stream flow. The area is covered by vegetation, accounting
for 49% of the total area. This vegetation includes primarily shrubs growing
along the banks, as well as submerged and free-floating aquatic plants.
Ranir bandh: This lake is seasonal in
nature and relies on water from streams. It spans an area of 3 ha and has a
maximum depth of 5 m. Vegetation covers 20% of the total area surrounding the
lake.
Data Collection
The survey spanned from November
to January in both 2018 and 2019, involving monthly visits to study sites from
0700 h to 1200 h and 1230 h to 1700 h with the participation of nine
individuals. Transportation primarily relied on bicycles and motorcycles to
cover the extensive distances. Executed through the point count method, the
survey focused on cataloging bird species around water bodies and their
environs. Birds were observed using Olympus 7 X 21 PS III binoculars and
documented via Nikon Coolpix P600 camera. Identification of avian species
utilized relevant keys from Grimmett et al. (1998), Kazmierczak & van Perlo
(2000), and Ali (2002)
Statistical Analyses
Three biological indices are
employed to compute species richness, species dominance, and evenness: the
Shannon-Wiener index (Shannon & Wiener 1963), the Berger-Parker index
(Berger & Parker 1970), and Pielou’s index (Pielou 1969; Biswas et al. 2019; Mukherjee et al. 2021).
The Shannon-Wiener index (Shannon & Wiener 1963) serves as a valuable
statistical metric for determining the species richness within a community.
This index can yield low values due to the contribution of rare species with
small populations. The calculation is expressed as Hs = -Ʃpi
ln pi, where Hs represents the Shannon index value and pi signifies the
proportion of the ith species within the community.
The Berger-Parker index (Berger & Parker 1970) is derived as d = max(pi),
where d indicates dominance and pi denotes the proportion of the ith species in the community. Higher values of
the Berger-Parker index imply greater dominance by one or a few species. Pielou’s index of species evenness (Pielou
1969) gauges how evenly species are distributed numerically within the
community. The following formula quantifies it: E = Hs / Hmax,
where E signifies evenness, Hs signifies the Shannon index value, and Hmax represents ln(S), where S signifies the number of
species in the community. Pielou’s evenness index
ranges from 0 to 1, with values closer to 1 indicating higher species evenness
in the community. All three indices underwent one-way ANOVA to assess the
significance of differences in their means. Subsequently, the
species-habitat-evenness (SHE) analysis was employed to interpret the
relationship between species richness (H) and evenness (E) of the samples. This
analysis was carried out to understand the log series distribution of species
in the community. Furthermore, principal component analysis (PCA) was performed
on the Shannon-Wiener index of species richness, Pielou’s
index of evenness, and the Berger-Parker index of dominance to elucidate the
relationships between these three variables. For the species abundance across
all 21 sites, classical clustering using the UPGMA algorithm (based on the
Brey-Curtis index) was executed (Mukherjee & Mondal 2020). All analyses
were conducted using PAST 3.14 (Hammer et al. 2001) and R-Studio 3.6.3 (R
Studio Team 2020).
Results
In Bankura, 45 species of aquatic
birds were recorded during winter in 21 different locations (Table 1). The
results of one-way ANOVA for the Shannon-Wiener index (F = 11.06, p <0.001)
(Table 2), Berger-Parker index of dominance (F = 6.519, p <0.001) (Table 2)
and Pielou’s index of evenness (F = 27.92, p
<0.001) (Table 2) demonstrated that there was a significant difference in
the mean of all the indices present in all of the study sites. The
Shannon-Wiener index, or species richness, was highest at site 6 (2.280±0.10)
and lowest at site 2 (0.82±0.015) (Figure 2). These findings indicate that the
community at site 6 is a natural one with high species richness. As the
dominance index increases, species richness decreases because the highest
dominance index recommends the predominance of one or a few species in an
ecosystem. Site 2 has the highest dominance index (0.84±0.13) and Site 6 has
the lowest (0.32±0.04) (Figure 3). The highest species evenness (0.91±0.06) is
found at Site 20 (Figure 4). The results of SHE analysis show a log-series
distribution of bird species in the studied area (Figure 5). Individual
rarefaction analysis of taxa plotted at the 95 percent confidence level shows
that the highest specimen is more likely to be found in site 1, followed by
site 2 (Figure 6). PCA results show that dimension 1 has an Eigen value of
2.04390180, followed by dimension 2 with a value of 0.92147965; in terms of
percent variance, dimensions 1 and 2 contribute 68.130060 and 30.715988,
respectively (Table 3). The PCA scree plot shows that dimensions 1 and 2
contribute the majority of the percent variance (Figure 7). In terms of species
abundance, classical cluster analysis using the Brey-Curtis index reveals that
sites 20-site 21, site 3, site 8, site 4, site 19, site 5, site 14, site 12,
site15, site7, site 10 and site 11, site 13 are closely related (Figure 8).
Discussion
During the current study, 45 bird
Species of 13 families such as Accipitridae, Alcedinidae, Anatidae, Ardeidae, Charadriidae, Ciconiidae, Jacanidae, Motacillidae, Phalacrocoracidae, Podicipedidae, Rallidae, Scolopacidae, and Threskiornithidae
were recorded in aquatic bodies in the Bankura district, including two
‘Vulnerable’ species Leptoptilos javanicusand Aythya farina, three ‘Near Threatened’ species
Mareca falcata, Threskiornis
melanocephalus and Limosa
limosa as listed under Dendrocygna
javanica and Nettapus
coromandelianus are the most abundant. This is
the first report of its kind on birds in 21 aquatic bodies and their
surroundings in Bankura. Birds are vulnerable to changes in the landscape,
pollution, hunting and other factors, so proper precautions must be taken to
protect them. The Shannon-Wiener index is highest at site 6 and lowest at site
2, and the Berger-Parker index is highest at site 2 and lowest at site 6. Site
20 has the highest level of evenness. The results of SHE analysis show that the
distribution of bird species in the studied area is a log series. The
rarefaction curve depicts the likelihood of finding the most specimens at site
1, followed by site 2. The richness value observed during the current survey is
higher than the values reported in 2000 for Purulia Saheb bandh (24 species) (Nandi
et al. 2004), Santragachi lake in Howrah District,
West Bengal (22 species) (Roy et al. 2011), Bakreswar
and Hinglo reservoirs and Adra
Saheb bandh lake (24 species) (Khan et al. 2016), but lower than the Kolkata
surroundings (48 species) (Sengupta et al. 2013), Purulia town and its
outskirts (115 species) (Mahato et al. 2021),
agricultural landscape in Burdwan (Hossain & Aditya 2014). The Shannon
index (2.28) in Sal Bandh (Site 6), which was the highest during the current
survey, was lower than the Mukkali moist deciduous
forest (3.45) and Purulia town and its outskirts (3.66) (Jayson & Mathew
2000; Mahato et al. 2021). In 2018 it was reported
that the species richness of Mukutmanipur dam (81
species) (Singh et al. 2018) was much higher than the richness value in this
dam during the present survey (36 species). The richness value for Jamuna bandh
(12 species), Krishna bandh (11 species), and Kulaijurir
bandh (6 species) was lower, but the Lal bandh (15 species) richness value was
higher than the previous survey that was conducted in 2000 (Nandi et al. 2007).
Apart from this, it was also found during the present survey Sal bandh (site
6), Kadam Deuli Dam (Site 7), Sutan
Dam (Site 8), Gangdua Dam (Site 9), Bonkati Bandh (Site 10), Bagjobra
Bandh (Site 11), Kesiakol Bandh (Site 12), Talberia Dam (Site 13), Kakila Daha (Site 14), Jhilimili Bandh
(Site 15), Poabagan Bandh (Site 16), Chattna Bandh (Site 17), Nityanandapur
Dam (Site 18), Ambikanagar Bandh (Site 19), Saheb
Bandh (Site 20) and Ranir Bandh (Site 21) contain 19,
16, 15, 14, 12, 12, 10, 10, 8, 6, 6, 5, 6, 5, 5, and 5 species, respectively.
The present study investigates that the reduction in richness value may be due
to pollution by domestic sewage, pesticides, fertilizers, eutrophication and
residential & commercial development in the bank of these aquatic bodies.
The loss of avian diversity can have a significant impact on species
interactions and ecosystem functions. Changes in avian diversity have an impact
on the food chain (Hossain & Aditya 2014). Assessing avifauna assemblages
to govern foraging behaviour and habitat preferences
is critical for determining their importance in ecosystem services (Lawton et
al. 1998; Sekercioglu 2006). It was observed that
species richness values were lower for the Mukutmanipur
dam, Jamuna bandh, Krishna bandh, and Kulaijurir bandhbut richness value was higher for Lal bandh than the
previous survey (Nandi et al. 2004). A survey of sixteen new aquatic bodies was
conducted that had not previously been done (Nandi et al. 2004). So, to begin
the assessment of ecological services in a specific landscape, a document of
species richness and composition of birds must be created and maintained as
present study. This document aids in the comparison of aquatic bird diversity for
future research. The primary step in the conservation of bird species and the
maintenance of ecosystem services is the species-specific ecological role,
which is far from complete in the Indian context (Dhindsa
& Saini 1994; Singh &Banyal 2013; Sengupta et
al. 2013; Sundar & Kittur
2013). This report can pique people’s interest in conserving aquatic birds and
their habitats and conservation of this avifauna is necessary for long-term
development.
Table 1. List of aquatic and migratory birds
observed in Bankura district during thestudy period,
2018–2019. W —Winter Migratory | R—Resident | L—Local migratory | VU—Vulnerable
| LC—Least Concern | NT–Near Threatened.
|
Common name |
Scientific name |
Family |
IUCN Red List status |
Migratory status |
Abundance |
|
Lesser Whistling-Duck |
Dendrocygna javanica |
Anatidae |
LC |
W |
2125 |
|
Cotton Pygmy-Goose |
Nettapus coromandelianus |
Anatidae |
LC |
W |
3351 |
|
Common Teal |
Anas crecca |
Anatidae |
LC |
L |
62 |
|
Northern Pintail |
Anas acuta |
Anatidae |
LC |
W |
62 |
|
Falcated Duck |
Mareca falcata |
Anatidae |
NT |
W |
19 |
|
Garganey |
Spatula querquedula |
Anatidae |
LC |
W |
12 |
|
Tufted Duck |
Aythya fuligula |
Anatidae |
LC |
L |
7 |
|
Common Pochard |
Aythya ferina |
Anatidae |
VU |
L |
85 |
|
Gadwall |
Mareca strepera |
Anatidae |
LC |
W |
60 |
|
Red-crested Pochard |
Netta rufina |
Anatidae |
LC |
W |
34 |
|
Indian PondHeron |
Ardeola grayii |
Ardeidae |
LC |
R |
209 |
|
Cattle Egret |
Bubulcus ibis |
Ardeidae |
LC |
R |
182 |
|
Purple Heron |
Ardea purpurea |
Ardeidae |
LC |
R |
23 |
|
Great Egret |
Ardea alba |
Ardeidae |
LC |
R |
38 |
|
Little Egret |
Egretta garzetta |
Ardeidae |
LC |
R |
47 |
|
Yellow Bittern |
Ixobrychus sinensis |
Ardeidae |
LC |
L |
32 |
|
Cinnamon Bittern |
Ixobrychus cinnamomeus |
Ardeidae |
LC |
R |
18 |
|
Little Cormorant |
Microcarbo niger |
Phalacrocoracidae |
LC |
R |
283 |
|
Great Cormorant |
Phalacrocorax carbo |
Phalacrocoracidae |
LC |
R |
41 |
|
Pheasant-tailed Jacana |
Hydrophasianus chirurgus |
Jacanidae |
LC |
R |
35 |
|
Bronze-winged Jacana |
Metopidius indicus |
Jacanidae |
LC |
R |
48 |
|
Asian Openbill |
Anastomus oscitans |
Ciconiidae |
LC |
R |
31 |
|
Lesser Adjutant |
Leptoptilos javanicus |
Ciconiidae |
VU |
L |
28 |
|
White-brested
Kingfisher |
Halcyon smyrnensis |
Alcedinidae |
LC |
R |
17 |
|
Common Kingfisher |
Alcedo atthis |
Alcedinidae |
LC |
R |
91 |
|
Pied Kingfisher |
Ceryle rudis |
Alcedinidae |
LC |
R |
18 |
|
Stork-billed Kingfisher |
Pelargopsis capensis |
Alcedinidae |
LC |
R |
21 |
|
Common Sandpiper |
Actitis hypoleucos |
Scolopacidae |
LC |
W |
55 |
|
Green Sandpiper |
Tringa ochropus |
Scolopacidae |
LC |
W |
11 |
|
Common Greenshank |
Tringa nebularia |
Scolopacidae |
LC |
W |
15 |
|
Common Redshank |
Tringa totanus |
Scolopacidae |
LC |
W |
2 |
|
Black-tailed Godwit |
Limosa limosa |
Scolopacidae |
NT |
W |
9 |
|
Little Grebe |
Tachybaptus ruficollis |
Podicipedidae |
LC |
L |
316 |
|
Ruddy--breasted Crake |
Zapornia fusca |
Rallidae |
LC |
R |
4 |
|
Purple Swamphen |
Porphyrio poliocephalus |
Rallidae |
LC |
R |
8 |
|
Common Moorhen |
Gallinula chloropus |
Rallidae |
LC |
R |
105 |
|
Common Coot |
Fulica atra |
Rallidae |
LC |
L |
19 |
|
White-breasted Waterhen |
Amaurornis phoenicurus |
Rallidae |
LC |
R |
86 |
|
Western Marsh-Harrier (Eurasian
Marsh-Harrier) |
Circus aeruginosus |
Accipitridae |
LC |
R |
25 |
|
Yellow-wattled
Lapwing |
Vanellus malabaricus |
Charadriidae |
LC |
R |
4 |
|
White Wagtail |
Motacilla alba |
Motacillidae |
LC |
W |
2 |
|
Western Yellow Wagtail |
Motacilla flava |
Motacillidae |
LC |
W |
9 |
|
Citrine Wagtail |
Motacilla citreola |
Motacillidae |
LC |
W |
12 |
|
Black-headed Ibis |
Threskiornis melanocephalus |
Threskiornithidae |
NT |
L |
41 |
|
Red-naped
Ibis |
Pseudibis papillosa |
Threskiornithidae |
LC |
L |
8 |
Table 2. Result of one------way ANOVA of
Shannon-Wiener index, Berger-Parker index and Pielou’s
index of evenness of 21 sampling sites. F values are significant at p <0.001
level.
|
Index |
|
Df |
Sum Sq |
Mean Sq |
F value |
Pr (>F) |
|
Shannon-Wiener index |
Sites |
20 |
8.712 |
0.4536 |
11.06 |
<0.001 |
|
Residuals |
42 |
1.655 |
0.0394 |
|
|
|
|
Berger- Parker index |
Sites |
20 |
0.9414 |
0.04707 |
6.519 |
<0.001 |
|
Residuals |
42 |
0.3033 |
0.00722 |
|
|
|
|
Pielou’s index of evenness |
Sites |
20 |
2.2621 |
0.11311 |
27.92 |
<0.001 |
|
Residuals |
42 |
0.1701 |
0.00405 |
|
|
Table 3. Results of Principal component
analysis showing that dimension 1 has the highest eigenvalue and percent
variance followed by dimension 2.
|
Dimensions |
Eigen value |
Percent variance |
Cumulative percent variance |
|
Dim.1 |
2.04390180 |
68.130060 |
68.13006 |
|
Dim.2 |
0.92147965 |
30.715988 |
98.84605 |
|
Dim.3 |
0.03461855 |
1.153952 |
100.00000 |
For
figures - - click here for full PDF
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