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Quantitative Analysis of Ecological Distribution of House Sparrows in Asansol

Roy Archisman*, Banerjee Tushar

Department of Science, Asansol Old Station High School, Asansol, India

Abstract: The world has witnessed many species on the way of getting endangered during the last few decades. It has become modern to ultramodern leaving no space to the homeland for different animals as well as plants. For various reasons, there are also many birds streaming down the lane of extinction and one of them is house sparrows. The house sparrows are declining in numbers rapidly. In this piece of article, we are intending to find the current ecological distribution of house sparrows in the specific areas of the southern parts of Asansol. We preferred direct photogenic tracking for roosting sites and used new instrumentation for measuring home ranges and density calculation. The data of the birds' distribution is very much needed to focus on their rapidity of getting endangered. Currently, the house sparrow density per square meter is 0.0161315. Every element of an ecological niche plays a crucial role in maintaining nature, similarly does the sparrow. This paper directly points out the causes of the decreasing rate of frequency of the house sparrows to make sense among the common people as well as, focuses on the hamper caused by the Electromagnetic pressure which is not endurable for the thin skulled species. Finally, this write-up encounters a new and intriguing way of counting the number of birds with better precision as well as it produces unbiased data regarding their ecological importance, distribution, home ranges, and, activation hours, which eventually infers the foremost causes of extinction leading to possible researches in different subsections. The piece of the article also reflects on future management and planning regarding the safety of these species.

Keywords: house sparrow, rural area, electromagnetic radiation, greenery, tower, house-type

Received September 12, 2020; Revised October 14, 2020; Accepted October 22, 2020

Citation: Roy Archisman, Banerjee Tushar, Quantitative Analysis of Ecological Distribution of House Sparrows in Asansol. Applied Ecology and Environmental Sciences, 8 (6). 485-498. January 2020. doi:10.12691/aees-8-6-22

1. Introduction

Passer, a genus of sparrow family Passeridae, is commonly referred to, as the true sparrows, was introduced by the French zoologist Mathurin Jacques Brisson around 1760 [1,2,3]. The Eurasian tree sparrows, house sparrows, and various common species of sparrows are also included in this genus, passer [4]. Their possession of body colors is very ordinary which is either brown or grey, there also exists Palae-Arctic black-bibbed sparrows which are supposed to be the result of origination from radiations [5] and hence their color [6,7]. These birds are featured with thick bills to eat seeds, their main fodder. Being one of the oldest natives of the world, some new species have been triggered out as well as a few old species are on the verge of extinction, and house sparrows are the least concerned species but gradually it is likely to get endangered mostly due to industrialization.

The common name for Passer is house sparrow, generated of Latin origin [8], with which we are going to deal in this section. Open habitats are the preferred places to be the inherency of most of the species, especially in the warmer climates of Africa as well as southern Eurasia. As evolutionary studies reveal, the genus is likely to be originated in Africa [6]. Several species have chosen close association with humans that enabled them to extend well beyond its original home Eurasia, of the Middle East [8]. Baring the process of natural habitation, the true sparrows have been artificially implanted in many new climates of the Americas, including sub-Saharan Africa, and Australia. The artificial introduction of the Eurasian sparrow species was not up to a mass scale, rather it was limited to a few populations in Australia, remotely in Missouri and Illinois within the U.S. [10]. It has amazingly extended its home range in Eurasia since the 1850s [10] and goes on to do so, at least as shown by its colonization in the 1990s of Iceland and Japan [11,12]. The huge extent of its home range makes it the most far-ranging and colonized wild bird of this planet [13].

The introduction of house sparrows has been a fine success in most parts of the world which also bore a significant role in the later stages of the ecological succession of a few locals. The reason for rapid adaptation is mostly the correlation set up between these species and humans from an earlier stage, including their adaptability of getting associated with human habitation and cultivation, although some of these birds are occasionally found to prefer distancing from humans [14,15,16]. The robust immune system is one of the ruling factors for their adaptation. It is not an obligate commensal of humans as some have suggested: birds of the migratory central Asian subspecies usually breed away from humans in open countries [17] yet birds elsewhere can occasionally be found away from humans. The house sparrows are imperceptible only in the tundra biomes and dense forests. Since they are greatly adapted to live with humans, very often they are seen living and breeding indoors, building their nests. Windows of factories, corners of warehouses, and even some zoos have been their traditional cum preferred zone of indoor habitats. An English coal mine, 640m below ground [18,19], has witnessed the awkward breeding of some house sparrows which continued to feed on the empire state buildings observation deck at night [14,20,21].

Although being tolerant of a variety of climates it prefers mostly dry regions followed by tropical regions [14,22]. A high salt tolerance along with an ability to survive in a waterless condition [23] by ingestion of berries [24] are few instances of several adaptations they have brought as a result of living in dry areas. In most of eastern Asia, the house sparrows are absent, replaced by the Eurasian tree sparrow.

The house sparrow has evolved with humane culture, known only to live in close contact with humans, instead of forests. For years it has peacefully co-existed with us in our buildings and gardens but in the last two decades, their population is on the decline in almost every city. Modernization of rapidly developing cities are no longer able to provide the required habitat type of house sparrows as well as the electromagnetic (EM) pressure of EM waves, mostly microwaves radiated by the towers, affect their physical responses, even if pollution caused by pesticides, concrete construction over the green places are pledging the sparrows to lose their foraging grounds which are considered to be the most valid reasons of their continual ecological declination [25,26,27].

House sparrow populations have waned by over 8.5% between 1966 to 2015, resulting in a cumulative reduction of 84%, according to the North Americans Breeding Bird Survey. The species rate 8 out of 20 on the scale of continental concerns. As a nonnative species, it is not included in the 2016 state of the birds’ report. After becoming common in North American cities, house sparrow moved out to colonize in farmyards and barns in the course of the twentieth century. As the firms are rapidly getting industrialized, house sparrows seem to be dwindling in most of their home ranges. During the early 1970s, the population took its peak in Great Britain, [28] although it faced a rapid fall-off of 68 % overall [29], and almost 90% in some locals [30,31]. According to the RSPB list, the condition of Sparrows in the United States has been red marked [32]. India is one of the oldest habitats of the house sparrows. The birds can be designated as the least concerned but recent statistics have changed the view. It is recently, an endangering species [33] in most of the urban areas including Paschim Burdwan, the district of our study area, India. Most of the advanced cities of India like Bangalore and New Delhi have already come across a rapid deterioration in the number of house sparrow’s habitat [34,35]. Our arena of research, Asansol faced a rapid but recent lessening in the sparrow-count, whose complete details are being placed in the following sections [viz calculated data]. Our paper is thus craving to evaluate the current density of the house sparrows, along with exploring the details of their roosting sites and its thorough apodictic study. Consistently, our research is also objected to analyze the extent of their home ranges, activation period and most indispensably the reason behind their gradual extinction. Hence forth, the article is intended to study in to-to about the passer’s current status in Asansol.

2. Study Site and Study Period

In the selected wards of the south part of Asansol, four distinct seasons are observed. A hot summer from March to May (temperature varies from 33°C to 45°C), a short monsoon in the months of June-July (rainfall varies from 710mm-776mm), magnificent autumn from September to October (temperature varies from 20°C to 25°C), and a cold winter from November to January (temperature varies from 7.2°C-7.8°C). A prodigious range of temperature (from 45°C in summer to 5°C in winter) has been observed in our study.

2.1. Study Period

Observation is continued from July 2016 to July 2019, except short breaks of 2-7 days per month for library consultation, various records from different public and private offices, and public opinions, additionally, half of a month had been used for analyzing and formatting the data after data collection is done in a specific area. The daily observation schedule was divided into morning shift (5 a.m. to 9 a.m.) and afternoon shift (3 p.m. to 7 p.m.). Observations were continued from 6 a.m. to 12 p.m. and 2 p.m. to 6 p.m. during the bout of counting the birds but, almost a full day was provided when activation hours were tracked.

2.2. Study Site

The entire work was carried out in the South part of Asansol city, under Paschim Bardhaman district of West Bengal, India. The exact study places are listed in Table 1. Figure 2 illustrates a map of the study area, and Table 1 provides the present as well as previously noted ward numbers. The Map of the study site has been issued from Asansol Municipal Corporation.

Study area: 29869 sq. m.

Area of Asansol: 152.23 sq. km.

Geographical Coordinates:

Optimum temperature: 29-30°C

Climate type: Tropical

Greenery type: Mostly deciduous trees.

The Ph of soil: 7.6

Elevation: 100 m from sea level with an uncertainty of 2%.

Figure 1. A radar diagram of the sparrow density per sq. m. versus ward number

Figure 2. A map of the study site, Asansol (Paschim Bardhaman). [A clearer image is attached as supplementary file, Asansol Municipal Corporation Model 1]

3. Materials and Methods

3.1. Instrumental Works

The direct counting of birds by clicking photographs [40] induces enough uncertainty so, we planned to count the birds in such a way that once a bird is counted, it should not again appear in some another set of observations. That’s why, for better accuracy, we worked out an electrical instrument. The objective of it is to color the birds. Only the freshly colored birds have been reported. The instrument sprayed a bit of spirited color over them which stays maximum up to 2 months and then it gets evaporated in presence of sunlight. Here the description of the instrument is given. The three main components of it are a passive infrared sensor (PIR), a solar panel, and an electronic paint sprayer. Whenever a bird passes by the PIR motion sensor (fixed in the nesting trees), it gets activated within a response time of 98 milliseconds. After that, the circuit is activated drawing 230 volts output across the solar panel which makes the sprayer, spray paint. Once the bird is colored, we take it in the count. The entire functioning of the instrument has been illustrated in the circuit diagram shown in Figure 3.

Figure 3. The circuit diagram of the described instrument

3.2. Numbering of Birds

Time duration of approximately 1.5 months had been settled to observe each area. Around the observation site, we took only the colored birds into account. But this process enabled us to count those birds which, built their nests in the trees. House sparrows do not tend to migrate over large distances especially those who have nestled in houses, warehouses, or factories [36]. For counting them, we had issued a request letter to the individuals wherever we noticed any nest. The letter urged them not to produce any harm to the nests at least throughout the stretch of observation. We had checked for, if the birds had been hampered, at the last of our perpetuated survey. A few damages were reported to be calculated in the uncertainty introduced. So, bearing all the measures we have set the data of the numeral values.

3.3. Area Calculation

We used a handheld Magellan GPS tracker to precisely locate all sightings of the birds which was then plotted in the google map satellite version to determine the shape of the area under observation following the coordinates of the leading points. With the correct precision, coordinates up to seven digits after a point, have been considered. All the areas were approximated as a polygon. Each polygon is a composite structure of triangles. So, by determining the coordinates of corner points, lengths of sides and diagonals were calculated. With Haversine formulation [37,38] to calculate large circle distance between two points, the distances are determined, with an uncertainty of 2%, which is enough minor. The formulation can be given by,

[picture] | (1)

where R is the radius of the Earth, 6371-kilometers and

[picture] | (2)

One can use C++ programming or java type for computation to measure the distance between two points using haversine formulation. The computing used in our workshop was based on the C++ program. For instance, two corner points in the Talkuri area, Point-1: 23.648597N, 86.977757E; Point-2: 23.646324N, 86.979614E implies an approximated side length of 0.3157 km. The recorded areas have been enlisted in Table 1.

3.4. General Methods

The method of counting the numbers of roosting birds directly by photogenic tracking had been used in the roosting sites. Different species of trees were identified and reported in the roosting sites. Species density was determined using the transect design method. Around every tree, a transect was designed undertaking a radius of 5 meters. The area of the roosting site has been calculated using the following formula,

[picture] | (3)

And the nesting house sparrow density in the observed study area was determined by the formula,

[picture] | (4)

Table 1. Details of the study sites

Where is the ratio of the number of birds to the total area of observation. The general tools of mathematics used in further statistical counts are as followed,

1. to determine the standard mean or, the first-order moment of the data,

[picture] | (5)

2. to calculate the expectation value or, the second-order moment of the data,

[picture] | (6)

3. to find SD [standard deviation] of the parameters or, the statistical counts,

[picture] | (7)

4. to measure the standard error (SE) of the parameters or, the statistical counts,

[picture] | (8)

[picture] | (9)

Where x is the statistical count (data), f is the frequency of the data, p is the probability of occurrence with finite population size and E is the expectation value. N denotes the total population size and n is the sample size as considered during measurement of expectation value.

4. Results and Analysis

Collected data from various wards have been listed in Table 1, which provides details of the study area and specific locations along with the exact number of the species, of course with some uncertainty, as well as the density of species per square meter. The following discussion has been made based upon the observed house sparrow density. In recent times the density of this species sheltered in these areas is almost 0.0161315 per square meter. The results reflect a clear scenario about house sparrows.

The radar diagram in Figure 1 plots the house sparrow density per sq. m, where we have chosen all the areas or wards from wherever we got a minimum of 0.006 house sparrow density. The ward number 86 & 57 i.e. Talkuri & Narsamuda shows the highest number of house sparrow density of 0.03 or more; those areas show high contrast against the other wards. While the ward number 87, 58 & 85 shows next to the highest number of house sparrow rounding 0.025. Jamuria, Gopalpur New Colony, Railpar & Hutton Road comes next to the above-mentioned areas. The data reflects that the areas which consist of the lowest number of towers have the highest number of house sparrows. Similarly, the old architecture of the house is also a factor that affects the number of house sparrows. Court More & Master Para shows the lowest number of house sparrow with “>5” towers and modern houses.

The important factor is the abundance of green areas which is again categorized as high and low. The presence of green areas imparts in a higher number of house sparrows. Talkuri (ward no: 86) is a bit of a rural area. While collecting data from Talkuri, we had caught sight of song birds (rare today). The number of trees, the agricultural fields, water bodies, house types, and, mentality of people triggers the breeding of these birds whose quantitative description is available in Table 2. The overall out-view of all the wards with natural geographical features are recorded in Table 3.

Table 2. Abundance of the geographical factors needed for breeding and livelihood of the species

Table 3. The out-view of the wards surveyed

4.1. Roosting Site

The study on their roosting sites was carried from April to June of 2018. The house sparrows are typically not prone to separate roosting sites although a few birds were traced. It was noticed that the roosting sites are tended to either barren land or dense greenery. The roosting places have been segmented in two sites, the first one is Talkuri roosting site (RS-1) and the other one is Dhemo Colliery roosting Site (RS-2). The house sparrows used 6 different species of trees as the roosting places in RS-1 whereas, 2 different species of roosting trees were reported in RS-2. Table 4 provides the details of the trees and the roosting area with the reported number of birds.

Mangifera Indica, Ficus benghalensis, Litchi chinensis, Acacia acuminate, Psidium guajava, and different hedges were identified as the roosting trees in RS-1, among them Mangifera Indica hosts the maximum number of birds reportedly with 13 individual trees, followed by Litchi chinensis with 6 individual trees and Ficus benghalensis with 3 individual ones. Only 2 roosting trees were identified in RS-2 such as Mangifera Indica, Psidium guajava. In this site, the guava trees hold the maximum number of house sparrows with 5 individuals. Table 4 also registers the haystacks as the roosting element, which separately provides a roosting place to 6 house sparrows. Approximately, it is seen that RS-1 happens to occupy a bigger area of 1884.96 square meters, and RS-2 to occupy 785.39 square meters. In the RS-1 roosting site the total colony size was almost 213 in April, 223 in May and, 323 in June followed by, 183 in April, 173 in May and, 203 in June reported in Dhemo Colliery roosting site. Figure 4 illustrates both the roosting sites. A few house sparrows were also observed to roost in the nests of the white storks in RS-1, which was congruent to the report [39]. Counting of these birds in the roosting site was assessed through direct counting and photogenic method with the use of binoculars [40].

4.2. Open Space Study

Computer programming SPSS version 11.0 was used in the case of statistical analysis. Spearman’s Rho test has been carried out for measuring the association at the ordinal level. In an open space study, we prefer to observe three birds in an individual area. On average, four days were spent to observe each bird. Mann Whitney U test was applied to calculate the deviation of annuity and seasonal home ranges. Approximately, each bird traverses 1.2 kilometers on average. The detention of each bird from its mean trajectory did not exceed a radius of 0.9 kilometers with an approximation of 92%.

Table 5 illustrates the active region of each bird’s flight consisting of four recording times. During the Rainy season, the range of mean deviation as well as the total trajectory is greater than the other seasons. Although the separate values listed do not result in an average of 1.2 km. which was detained from more values that are not listed in the illustration. The calculation of frequency of birds has been executed mostly by the early dawn (4.30-6.00 am), noon (1.00-2.00 pm), or by dusk (7.00-7.30 pm). The whole day long PIR sensors always kept continuation on the sensation of birds. The preferred stretches of time were selected in such a way that, mobility of the birds should be the least. Since, the total count of the species, in almost every segment exceeded 10, it was not possible to follow their activation ranges simultaneously. For that reason, a random sample of birds was chosen statistically without replacement and kept under observation. The least and maximal coordinates were determined by highly focused drones with an uncertainty of (3-4) %. The coordinates were put to find an approximated polygonal geometry. By computation through AutoCAD 2007 version, areas were determined.

To execute the circular statistics, we defined the nests as the mid-point and based upon it, the angels were measured. For, >1 rotation, steradians were used as a measure of the angels. Table 5 contains the angular statistics where the angels have been reported in degrees. Movement patterns were recorded to be random. In a few cases, the buzzing sounds have induced some unfairness by increased entropy with a precision of 90%. R series denotes the measurement of Rayleigh test scales applied over circular statistics. The home ranges as well as circular statistics have been shown in the same Table. We are not addressing all the locations rather, only those areas are enlisted which has been thoroughly observed. From the study of the home ranges, it is observable that the birds of house or gardens do not bother much distancing rather, their preference is centrally tended. From the total count, few birds rely upon different habitat distribution. The frequency and their habitat distribution have been monitored as well as plotted in Figure 5. This distribution ponders over their tendency to build nests mostly in green gardens.

Table 4. Table showing the number of roosting trees at the sites

Figure 4. Illustrates the satellite-tracked mode of the first roosting site, the Talkuri area, and the second roosting site, Dhemo Colliery. As mentioned in the figure legend, the observed area has been highlighted with yellow color

Table 5. The home ranges of the birds and their circular statistics

Figure 5. The frequency of the number of birds is plotted against some particular homeland areas

Now, the home ranges shown in Table 5 are sample means drawn from a finite series of population. It is a statistical count, not a parameter, that’s why this is quite typical to produce a better accuracy rate. So, we preferred a completely random sampling under SRSWR such that SE can be defined upon the sampling means. The sampling means prefer to follow the Normal Gaussian distribution. So, a measure of the SE of the sample means gives an understanding of the uncertainty introduced.

Figure 6. Plotting of the activated birds to different time span

Table 8 records the tracked activation hours of the birds whose observation was continued from 6.00 A.M. to 8.00 P.M. Each two hours long incumbency is divided into four segments whose mid value has been denoted by 'x'. The number of birds active in flight during the observed period serves as the frequency of the data (time). A total of 476 birds were recorded, out of which maximum birds were active during 8.00-10.00 A.M. and 5.00-7.00 P.M. Considering the frequency distribution as the principle data, a first-order moment is also produced in the table. The moment takes its peak around 8.00-10.00 A.M. and 4.00-6.00 P.M. with the values 23.643 and 23.768 respectively. The mean and the median give an understanding of the central tendency of the observable time. The virtual plotting of the moment of the frequency concerning the mean or medium gives an analyzable sense about the birds active through different runs of time, refer to Figure 6.

4.3. Captive Study

By captive study, we meant the study of the required specimens through imprisonment. Here, we captivated one specimen, that is randomly chosen. For international ecological interest, the species although being least concerned was not hampered a bit and was set free after observation of 1.5 months. During this period, the physiological structures were observed. Table 6, produces all the recorded physiological features in adherence to [41,42].

4.4. Measurement of Uncertainty

Mostly in three sections measuring the uncertainty is crucial. As earlier been mentioned, the calculation of home ranges is one of them. Table 7 shows the measurement of uncertainty. The home ranges are statistical means of some samples. Since the population is quite large, we can use an approximation to calculate the SE of sampling means (). By taking an average of the SE we conclude that the uncertainty of measurement is 5.807753438 Table 7 also includes the data regarding the SE of each sample.

Table 6. Biophysical features of the species

Table 7. Standard errors of the sampling means (home ranges)

Table 8. Observed activation period, frequency of birds, and their means

The section, activation hours, also bears some amount of uncertainty. The frequency distribution has been provided in Table 8. From that specific frequency distribution, a probability distribution has been charted out. A measure of SD is enlisted in Table 9. Now, this is the case of SRSWOR with a finite amount of population size. Although this population bears a very short number of members, by random sampling, of sample size 4 again the SE of sampling means can be calculated which gives the precise figure of uncertainty, almost up to 1.99743642. Table 9 shows the SE and a measure of uncertainty. One major section is the probability distribution of species and their ranges of finding. Since intuitively it is very much pellucid that the probability of finding a bird around its nest is the maximum, we used the Gaussian distribution taking a mean of 1.2 km. and SD of 0.08 with origin as the nest.

Table 9. Expectation Value, Standard Errors, and measurement of the uncertainty of the number of birds during the activation period

Figure 7. Graph of various geographical features versus, the corresponding wards

According to our survey, the house sparrow density per square meter depends upon house architecture, presence of mobile towers, amount of green areas, increased predation from domestic or feral cats, and sparrow hawks (Accipiter nisus), EM radiation from dipole antennae. We noticed that they construct their nests in the thatched roofs of old typical houses, in ventilator holes, and even in the electricity meter boxes of the old houses. Most of the nests were situated at a height of 8-9 feet from the ground level in the study sites. Nest material is grass, straw, jute threads, leaves, weeds, feathers, etc. In the city areas, sparrows in small groups were usually found resting on electric wires, and pipelines of the building. These observations show that there was no place for house sparrow to build its nest in the urban areas. The distribution of house sparrows amongst rural and urban areas varies widely. Urban areas are readily lacking the presence of these birds which is following the report of [43,44,45]. The effecting geographical features and their distribution according to each ward have been plotted in Figure 7, to illustrate the preceding description.

5. Conclusion

In this study two roosting sites, the Talkuri area and the Dhemo Colliery area, of the house sparrows were observed in South Asansol. The total population size of the roosting birds was around 523 with an expanse of 2670.36 square meters. RS-1 and RS-2 host 323 and 203 roosting house sparrows respectively. The study reveals six different roosting trees in RS-1 such as Mangifera Indica, Ficus benghalensis, Litchi chinensis, Acacia acuminate, Psidium guajava, and different hedges but, contrary to that RS-2 holds only two species of roosting trees. The loss of roosting places due to the felling of these trees for industrial purposes and commercial issues is pushing the birds towards the verge of getting endangered. Apart from the birds as mentioned the nesting house sparrows bear an approximated density of 0.0161315 over the observed area of 29869 sq. meters whereas, the rural (in a weaker sense) ward like Talkuri (86) bears a density, 0.03173 over an area of 2300 sq. meters. But the highly modernized study sites, Court More and such else hardly shelter any house sparrow, registering with a sparrow density of 0.006 per meter squared. This analysis also assesses that the EM pressure of mostly microwaves radiated, exerts huge pressure on their blood vessels. As per home ranges are concerned its detailed discussion has been provided earlier. The mean home range of the passer is approximately 1.2 km. and the SE of sampling means is 5.807753438 The maximum home range is 0.8 km. in summer, 1.44 km. in monsoon, and 1.1 km. in winter. The R series value associated with it is roughly 0.0626. The birds were reported to be active with different frequencies throughout the day which is being referred to the activation hours. Active hours of the passer domesticus bear maximal point during 8.00 - 10.00 A.M. and 4.00-6.00 P.M. with 1st order moments of the frequency as, 23.643, 23.768 respectively. One of the most important factors of this quantitative measure is the uncertainty introduced by the PIR motion sensor, which is calculated to be 1.99743642 along with a precision of 94-95 % accurate work function of the PIR sensor. So, viz data are consulted it can be noted that the study sites in Talkuri & Narsamuda, rural areas consist of cultivated fields. Moreover, in these areas, bushes of various plant species, shrubs were also very common. So, it is perspicuous that the availability of diverse food sources for house sparrows in rural areas is more when compared to urban areas. Food sources near the nests mainly play a crucial role in the increased breeding of house sparrows under a population. The field study suggests that the old type buildings in the city are necessary for retaining the house sparrow population density to a fine number. Obliterate of old type buildings severely affect the sparrow population. In the modern architecture of buildings, the kitchen waste is directly transported into the drain and there is no availability of food waste for these sparrows in the urban areas, but in rural areas, the people are cleaning the food making pots in front of their houses which provides better accessibility of fodder morsels. There is a loss of habitat for the house sparrow population due to the increasing globalization and large areas of land being transformed into modern cities.

Acknowledgments

The entire funding of the research project was lugged by personal investment. This work was appreciably supported by Sanghamitra Roy, with her supervision and guidance in editing. We would like to extend our gratitude to those people who succored us to bring this Paper to fruition. First, we would like to thank Tushar Banerjee for giving us the opportunity and admirable guidance in paving up to fulfillment as well as showing us the process of this paper’s publication. Finally, author Archisman Roy is eagerly expressing his due regards with the warmest and hearty gratefulness for his parents to aid a great deal in the paper’s publication, for his father’s lucrative advice, and especially thanks to his mother who helped throughout the whole process by all means. From all the co-authors an exuberant salutation is being delivered to dear, Prof. Asim Kumar Mukherjee, for his aid in the formulation of mathematics and combining all these to the physical world of instrumentation. In the case of computation one of our friends aided us wildly, so we are also cordially paying our gratitude to Jaidip Patra for his profound help. We are especially grateful to Mr. Nilratan Halder for his appreciable assistance during the fieldwork at different study sites. This is our prime ethical responsibility to acknowledge one of our dearest partner Prof. Raja Mukherjee for his appreciable assistance in field study.

Statement of Competing Interests

The authors have no competing interests.

List of Abbreviations

PIR: Passive Infrared Sensor.

SD: Standard Deviation.

SE: Standard Error (of the sampling means).

SRSWR: Standard Random Sampling With Replacement.

SRSWOR: Standard Random Sampling Without Replacement.

MOF: Moment of Frequency.

EM: Electro-magnetic.

RS: Roosting Site.

References

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