Using the population-based monitoring method, the observed population density indicates that it is apparent that the House sparrow was prevalent in damp weather compared to clear weather. The increase in the population of house sparrows during the North East monsoon season might be due to the availability of insect larva for its nestlings. Similarly, Rajashekar and Venkatesha 2008, has reported an increase in the number of birds during the South West monsoon (June–September) followed by the North-East monsoon (October–November) in Bangalore. Figures 4, 5 & 6, represents the number of male population against the female population in the study area using Scatter plot, Joint Plot and Box Plot respectively. In the Joint plot (Fig. 5), both the male and female population showed right-skewed distribution with outliers. The densest area of population distribution was in the range of -10 to 45 scale units.The Boxplot (Fig. 6) Clearly illustrates the variation in the occurrence of male and female population between different study sites. This shows that the sampling was not similar, but extensively varied. The correlation matrix (Fig. 7) Indicates that the status of the house sparrow, no. of male, no. of female, weather and habitat are highly correlated with one another. Choudhary S et al. 2019, stated that habitat variables like the presence of old buildings, residential areas, vegetation, water, grocery shops, food provision, open drainage system and open household waste dump influenced the selection of habitat by house sparrows.The population of male and female house sparrow is highly correlated with one another; hence a decline in male population would be directly reflected in the occurrence of the female population and vice versa (Fig. 13). In the statistical interpretation (Fig. 14) it was evident that the number of male house sparrow was more than the female in a given location. Despite the statistical interpretation, it was scientifically proven that variation in the primary sex ratio in house sparrow population was potentially influenced by seasonal variation in parental quality where good quality mother were more likely to produce, when bred late in the breeding season (Trivers and Willard 1973).
Habitat plays a vital role in the survival of an organism. House sparrows have been spotted in both rural and urban habitats. In the present study, Fig. 15 illustrates the correlation between house sparrow population and the type of habitat (rural, semi urban and urban). Based on the above results it could be stated that the house sparrow population was more dominant in the rural habitat, followed by the semi urban habitat. A study emphasized that though sparrow showed least preference to urban habitats, the introduction of artificial nesting boxes could be a suitable measure to increase the house sparrow population in the urban habitat (Balaji et al. 2014).
The correlation between weather and population density of house sparrow in the study area was signified in Fig. 16,. The number of sparrows counted in sunny weather was 81, while in clear and rainy weather conditions, the number of sparrows was 46 and 41 respectively. The data clearly show the preference of house sparrow towards sunny weather condition. Among the 13 study blocks surveyed in Madurai district, the maximum number of house sparrow count was recorded in Madurai West followed by Thiruparankundram, Madurai East, Thirumangalam, T.Kallupatti and Alanganallur (Fig. 17).
The average house sparrow count of the Madurai West block was 12.92. In the Kendall and Spearman correlation the endpoint was a set of clusters, where each cluster is distinct from other cluster, but broadly similar data are clustered together. The Kendall Correlation Matrix illustrates that the number of male, the number of female, status of house sparrow was found to be influenced by the habitat and weather of the study area. Based on the data points obtained from the cluster analysis, Cluster 0, indicated that during clear weather, the male and female population count lies within 1–25 and were seen predominantly in rural areas compared to urban habitat. In Cluster 1, the data were grouped with reference to sunny weather, wherein the population count ranged from 1–35.Lastly in Cluster 3, rainy weather was taken into consideration, with the population ranging from 1–35. Performance evaluation of clustering indicated that a 100% precision and recall score was obtained and the data points correctly fall under the three clusters (Fig. 18).
Based on the computational analysis, the population of house sparrow in an area, was found to be directly influenced by the block location, habitat and weather conditions of the region. Hence, by further monitoring of these parameters, the decline in house sparrow population can be revived using suitable revocation strategies. Principle Component Analysis has selected five major features (Block, Habitat, Weather, No. of the female and No. of male) which plays a vital role in the prevalence of a house sparrow was explained in Fig. 12. Various studies were performed to obtain strong evidence that temperature, it acts as a cue for this plasticity in breeding timing, the exact nature of the cue and response remain unexplained. Matthysen et al. 2021 investigated that small-scale variation in egg laying date, explained by local tree phenology, tree species composition around its habitat. Hence such study can be incorporated for further clarification with response to species of trees and insect diversity with house sparrow population.