Journal of Threatened
Taxa | www.threatenedtaxa.org | 26 March 2024 | 16(3): 24949–24955
ISSN 0974-7907
(Online) | ISSN 0974-7893 (Print)
https://doi.org/10.11609/jott.8865.16.3.24949-24955
#8865 | Received 01 December 2023 | Final received 05 February 2024 |
Finally accepted 21 February 2024
Species distribution modelling of
Baya Weaver Ploceus
philippinus in Nagaon District of Assam, India: a
zoogeographical analysis
Nilotpal Kalita
1, Neeraj Bora 2, Sandip Choudhury 3 & Dhrubajyoti Sahariah 4
1 Department of Geography, Nowgong Girls’ College, Uttar Haibargaon,
PO - Haibargaon, P.S. Sadar,
Assam 782001, India.
2,3 Department of Zoology, Nowgong Girls’ College, Uttar Haibargaon,
PO - Haibargaon, P.S. Sadar,
Assam 782001, India.
4 Department of Geography, Gauhati University, Gopinath Bordoloi
Nagar, Jalukbari, Guwahati, Assam 781014, India.
1 nilotpalkalita4@gmail.com
(corresponding author), 2 neerajbora15@gmail.com, 3
csandip2016@gmail.com, 4 dhrubajyoti@gauhati.ac.in
Editor: H. Byju,
Coimbatore, Tamil Nadu, India. Date of publication: 26 March 2024
(online & print)
Citation: Kalita, N., N. Bora, S. Choudhury & D. Sahariah (2024). Species distribution modelling of Baya Weaver Ploceus philippinus in Nagaon District of Assam, India: a
zoogeographical analysis. Journal of
Threatened Taxa 16(3):
24949–24955. https://doi.org/10.11609/jott.8865.16.3.24949-24955
Copyright: © Kalita et al. 2024. 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: None.
Competing interests: The authors declare no competing interests.
Author details: Dr. Nilotpal Kalita is currently working as assistant professor in the department of Geography, Nowgong Girls’ College, affiliated
to Gauhati University. His specialization is geoinformatics and fluvial geomorphology and currently working on phytogeography and zoogeography of selected flora and fauna from northeastern India. Dr. Sandip Choudhury is currently working as assistant professor and head in the department of Zoology, Nowgong Girls’ College, affiliated to Gauhati University. His specialization is in cell and molecular biology and currently working on molecular phylogenetics, ethnozoology and zoogeography of selected fauna from northeastern India. Neeraj Bora is currently working as assistant professor in the department of Zoology, Nowgong Girls’ College and he has a keen interest in wildlife biology and ornithology. Dr. Dhrubajyoti Sahariah is currently working as professor and Head in the Department of Geography, Gauhati University. His specialization is fluvial geomorphology and geoinformatics and currently working on phytogeography and zoogeography of selected flora and fauna from northeastern India.
Author contributions: Geographical work is contributed by first and fourth author and Zoology part is contributed by second and third author. Equal contributions of all authors in preparation of the manuscript.
Abstract: Identification and mapping of the
spatial distribution of species is an important aspect of zoogeographical
enquiry. The habitats of many species are facing the threat of depletion in
increasingly human-influenced environments. This has already led to the extinction
of many species in different localities, making understanding the linkages
between anthropogenic threats and species distribution of utmost importance. A
GIS-based model was applied to gain an overall picture of the potential
distribution of Ploceus philippinus (Baya
Weaver) in and around Nagaon District in Assam. The used maxent model in the
GIS environment gives a highly significant Area Under Curve (AUC) validation
statistic of 0.99. Out of the total area of 3,975 km2, 596.86 km2
(15%) is demarcated as a high-potential area. Such predictions are highly
useful in assisting in the conservation of threatened species under current and
future climatic conditions.
Keywords: AUC, birds, environment, GIS,
habitat, mapping, Maxent, potential, northeastern India, spatial distribution.
Introduction
The Baya
Weaver Ploceus philippinus,
is distributed throughout the Indian subcontinent and southeastern Asia. There
are five species in the Ploceus clade: P.
philippinus, P. manyar,
P. benghalensis, P. hypoxanthus, and P. megarhynchus
(De Silva et al. 2019). The Baya
Weaver has a unique courtship display involving the nest-building that it is
known for, and has multiple adaptations to its
ecological niche. The male weaver bird puts a lot of effort and time into
making a beautiful hanging nest and then invites a female bird by flapping its
wings to choose it as their nesting place (Arigela et
al. 2021). The weaver selects various trees, bushes, and other sites for
building its nests, showing a preference for thorny acacias and specific palm
species. The avian population in a particular region tends to favor a distinct
type of nesting location (Davis 1974). Indian Baya
Weavers have been observed to establish colonies on a remarkable range of
plants. They have also been known to choose unconventional structures such as
house eaves (Davis 1971), telegraph and power lines (Ambedkar 1970), and the
sides of irrigation wells (Ali 1931; Crook 1960, 1963) as occasional sites for
suspending their nests (Davis 1972). Over 84 percent of the colonies in the
Assam region were on Areca palm (Davis 1972).
Maxent (Maximum entropy model) is
a machine learning technique that can be used for SDM (Species distribution
modelling) due to its use of maximum entropy to determine the probability of a
species’ presence and absence in each area. This method combines a variety of
independent regional climate, land-use, topography, and other environmental and
ecological variables into a single model of species’ distributions. It then
applies the principle of maximum entropy to the dataset. It is an increasingly
popular machine learning algorithm used in SDM, which is a technique that can
be used to predict the locations where species may occur, by examining the
potential environmental, ecological, and socioeconomic factors associated with
their distribution. Maxent is a machine learning algorithm that has become an
increasingly popular choice for SDM (Phillips & Dudik
2008).
Several works have been done on
species distribution model and habitat suitability analysis using Maxent model
in India and across the world. The works of Reside et al. (2010), Syfert et al. (2013), Booth et al. (2014), Fourcade
et al. (2014), Padalia et al. (2014), Jathar et al. (2015), Sarma et
al. (2015), Moya
et al. (2017), Bradie & Leung (2017), Rhoden et
al. (2017), Palacio & Girini (2018), Nameer & Sanjo (2020) are
worth mentioning as they have found the Maxent model has the ability to provide
accurate predictions with different species and with different environmental
variables .
The current paper analyzes the
distribution or range of Baya Weaver in Nagaon
District of Assam, India. Through the use of geographic information systems,
species distribution modelling and remote sensing data, the habitat suitability
classes like least potential, moderate potential, good potential and high
potential classes for the Baya Weaver is identified.
The Maxent (Phillips & Dudik 2008) model is
popular among many scientists in investigating the potential distribution of
floral and faunal species. Through this analysis we will gain insight into the
bird’s current and probable habitat and hopefully be able to provide
recommendations for management and conservation efforts suitable for this
species.
Materials
and Methods
Study Area
The present Nagaon and Hojai districts (Figure 1)are situated
in the middle part of Assam between 25.72 & 26.75 0N and 93.42
& 93.33 0 E. It is surrounded by Sonitpur
District in the north, Karbi Anglong
and North Cachar hills in the south, Karbi Anglong and Golaghat districts in the east, and Morigaon
District in the west. The mighty river Brahmaputra flows along the northern
periphery of the district. Three Important Bird Areas (IBA) fall within
Nagaon District: Deobali Jalah
(IN-AS-11), Kaziranga National Park and Tiger Reserve
(IN-AS-25) and Laokhowa-Burhachapori WS (IN-AS-28) (Rahmani et al. 2016). Nagaon District also falls under the
range state of central Asian flyway.
Methods
The field survey was conducted
randomly at several locations in Nagaon District of Assam to cover both summer
(March to August) and winter seasons (January to February) and GPS points were
collected using handheld GPS devices. While surveying the locations, local
residents were interacted with to gather information about nesting sites of Baya Weaver. During the surveys, opportunistic sightings of
nesting sites of Baya Weaver were also recorded.
After that, the maxent model (Phillips & Dudik
2008) was used for predicting the habitat suitability of Baya
Weaver in Nagaon District of Assam. During the run, six presence records were
used for training and two for testing, 10,006 points were used to determine the
Maxent distribution (background points and presence points). Regularized
training gain is 5.245, training AUC is 0.999, unregularized training gain is
6.310. Unregularized test gain is 5.668. Test AUC is 0.999.
Nineteen environmental variables (BIO1 =
Annual Mean Temperature, BIO2 = Mean Diurnal Range (Mean of monthly (max temp -
min temp)), BIO3 = Isothermality (BIO2/BIO7) (×100),
BIO4 = Temperature Seasonality (standard deviation ×100), BIO5 = Max
Temperature of Warmest Month, BIO6 = Min Temperature of Coldest Month, BIO7 =
Temperature Annual Range (BIO5-BIO6), BIO8 = Mean Temperature of Wettest
Quarter, BIO9 = Mean Temperature of Driest Quarter, BIO10 = Mean Temperature of
Warmest Quarter, BIO11 = Mean Temperature of Coldest Quarter, BIO12 = Annual
Precipitation, BIO13 = Precipitation of Wettest Month, BIO14 = Precipitation of
Driest Month, BIO15 = Precipitation Seasonality (Coefficient of Variation),
BIO16 = Precipitation of Wettest Quarter, BIO17 = Precipitation of Driest
Quarter, BIO18 = Precipitation of Warmest Quarter, BIO19 = Precipitation of
Coldest Quarter) with a spatial resolution of 30 arc second (Fick & Hijmans 2017) were downloaded from worldclim.org along with
slope, elevation and aspects raster and a multicolinearity
test was conducted (Mehmud et al. 2022). Variables
with a cross correlation of ±8 or more were excluded from the model to reduce the data
redundancy and improve the performance of the model (Figure 2). The Shuttle
Radar Topography Mission (SRTM) (Rodrıguez et al.
2005) elevation raster and the Terra and Aqua combined Moderate Resolution
Imaging Spectroradiometer (MODIS), MCD12Q1 (Friedl
& Sulla-Menashe 2019) land cover type was also used in the study and LULC
map is prepared. The products give yearly intervals of global land cover
categories (2001-2018). In the study, a classification scheme based on the leaf
area index (Friedl & Sulla-Menashe 2019) was
applied. Leaf area index in a classification scheme for categorizing land cover
types based on the amount of leaf area per unit ground area. It also measures
the density and structure of vegetation which affects the exchange of energy,
water and carbon between the land surface and the atmosphere.
Results
and Discussion
Habitat
In our study, it was observed
that the Baya Weaver prefers to make nests in trees
located near grasslands and wet plains where there is standing water or small
pools to forage for food. They also thrive in wetlands and cultivated areas.
During the field visits, it was observed that this species mostly occupies
trees in agricultural fields and even few pockets of urban settings (Figure 3).
It is common to observe the bird creating huge loosely woven, roof-like nests
made of dried leaves, grass, and coconut fronds out of its environment (Davis
1974). The nests are usually located in shrubs, trees, and other tall
vegetation. These nests (Image 1) provide ideal shelter for them and also help
in attracting a mate. The Baya Weaver also has a preference for nesting near other birds, which helps
in its defense if it comes under attack by predators (Street et al. 2022). They
are also found in large flocks during migratory season, due to their
go-it-alone personalities.
Spatial modelling
Identifying and charting the
spatial distribution of species is a critical element of any zoogeographical
investigation. It gives us a great insight into the current habitats of species
many of which are now facing severe threats from a human-altered harsh environment.
Owing to human activities and the growing pressure of human populations put on
habitats, many species are becoming threatened. As such, a GIS based study has
been applied to gain an understanding of the potential distribution of species
in and around the Nagaon District of Assam. The habitat suitability map
generated by Maxent in GIS was based on selected environmental parameters. The
results showed by the maxent model suggest that among these environmental
variable number 17 (Precipitation of Driest Quarter), 14 (Precipitation of
Driest Month), slope and land use have 38.3,21.6, 24.7, and 5.7 percent
contribution. Pearson’s correlation coefficient (r) was used to conduct
multicollinearity test (Mehmud et al. 2022) for the
region of Assam. The test AUC and training AUC of the maxent model is 0.99. The
importance of environmental variable can be identified by looking at the
Jackknife test (Figure 4). Maximum iteration was set to 1,000 for the analysis.
The potential habitat (Figure 3) suitable for
the nesting sites of Baya Weaver is estimated
from the model within the periphery of the availability of water sources. The
model also suggests that the rainfall in the driest quarter and rainfall in the
driest month are a significant role in the spatial distribution of the said
bird species. Out of the total area of 3,975 km2, 596.86 km2
(15%) area is demarcated as a good and high-potential area. Using the map as a
guide, another field visit was conducted and discovered a few colonies in and
around the areas identified as suitable. One of the observations was that, in
one location, it was found nesting in banyan trees, rather than the more common
tree species of Areca Palm.
Conclusion
The zoogeographical analysis of Baya Weaver in Nagaon District of Assam was aimed to detect
the optimum environment for its favorable distribution and viable long-term
conservation. The study showed that anthropogenic land-cover such as
agriculture, water bodies and infrastructure play significant roles in
determining the potential range of the bird species. In addition, precipitation
of driest quarter (bio 17) and precipitation of driest month (bio 14) were also
found to be suitable for the species. The associated vegetation cover of the
habitat played an important role in the increased number of individuals and
their distribution area as observed from the Land use and land cover map and
field visits. These findings clearly demonstrate the importance of robust
species conservation models for Baya Weaver in
Nagaon. Therefore, this study provides a useful perspective on determining
landscape features in order to conserve this species in the future. This study
represents the first zoogeographical investigation into habitat suitability
mapping of Baya Weaver in the Nagaon region of Assam.
It provides researchers with valuable insights into the potential locations of
said bird species in the area, utilizing bioclimatic variables. Subsequent
research endeavors can build upon this habitat mapping to explore the reasons
behind the low geographical coverage (15 % geographical area) of Baya Weaver population in the region.
For figures
& images -
- click here for full PDF
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