How free-ranging Indian Flying Fox (Pteropus medius) forage in urban areas? A study from Kolkata, India

Abstract

Foraging behaviour plays a significant role in the fitness of animals and is influenced by habitat quality. Habitat change due to rapid urbanization often results in altered behaviour and resource use patterns in animals thriving in such changed habitats. Bats play a crucial role as tree pollinators, seed dispersers and forest regenerators. Particularly in urban areas they are among the few pollinators that help regenerating the urban green spaces. Therefore, it is crucial to understand their foraging patterns in these human-dominated landscapes. Loss and degradation of roost and foraging resources threatens the survival of many bat species, including Indian Flying Foxes (IFF). Still, very few studies have been carried out on their feeding behaviour and ecology. Hence, we carried out this study to (i) identify the foraging sites of IFF, (ii) find out the urban land cover features influencing their foraging site selection and (iii) to identify the foraging trees used by them in urban areas. IFFs were observed to forage on 16 species of trees belonging to 10 families in four different sites in urban areas, of which Ficus species are most important. Amongst various urban land covers, the area of tree cover in the foraging sites were found to significantly influence the number of foraging IFFs. Our findings strongly advocate for the protection of the trees preferred by IFFs along with overall urban tree canopy covers, as these are essential resources for the survival of bats, as well as many other species in urban areas.

Introduction

Foraging in any animal is considered to be an important biological phenomenon that significantly contributes to physical fitness (Schoener 1971; Pyke 1984; Colwell 2010; Schloesing et al. 2020), and such foraging behaviour is often influenced by the habitat quality (Robinson and Holmes 1982; Lobo, Green, and Millar 2013). In recent times, several anthropocentric developmental activities have turned out to be the major driver of habitat change (Lindenmayer and Fischer 2013). Animals are often compelled to alter their behaviour and resource use pattern to thrive in such changed habitat (Sol, Lapiedra, and González-Lagos 2013; Roy, Saha, and Mazumdar 2020). Likewise, foraging pattern of animals usually vary in urban landscapes as compared to their natural habitats (Lowry, Lill, and Wong 2013). Animals thriving in urban areas often come across novel food resources and/or encounter the dearth of their traditional food (Páez et al. 2018). However, studies on the foraging resources of several wild faunas in such areas are limited. With the rapid increase in urbanization over last few decades across the globe, it is increasingly becoming crucial to understand the foraging patterns of various fauna living in these human-dominated landscapes.

Nearly 200 species of Old World fruit bats (Chiroptera: Pteropodidae) are known to forage on a combination of wild fruit, nectar and pollen in areas with regular and predictable availability of such resources (Constantine 1970; Simmons 2005) playing an important role in pollination and seed dispersal (Fujita and Tuttle 1991; Mickleburgh, Hutson, and Racey 1992; Eby 1996; Banack 1998). Through pollination and seed dispersal they also play crucial ecological role in regeneration, reforestation and maintaining plant community diversity in urban green spaces (Chan et al. 2021; Russo et al. 2023). However, many frugivorous chiropteran species may not be able to thrive in metropolitan environments, as their foraging grounds are frequently turned into urban infrastructures (Mickleburgh, Hutson, and Racey 2002; Rainho and Palmeirim 2011). As a consequence, about half of the living bat species are either suffering from population decline or threatened with extinction (Voigt and Kingston 2016), mainly due to the large-scale transformation of their natural habitats leading to loss and degradation of roost and foraging resources (Lane, Kingston, and Lee 2006; Kingston 2010).

Indian flying fox (Pteropus medius, Temminck, 1825) is one of the largest bat species of the world (Bates and Harrison 1998) and is an important pollinator and seed disperser of commercially important fruiting trees (Singaravelan, Marimuthu, and Racey 2009; Mahmood-Ul-Hassan et al. 2010). Additionally, Izhaki, Korine, and Arad (1995) asserted that passing through a bat's intestines enhances the level of seed germination. Through their pollination and seed dispersal activities, the bats also serve to balance the degraded tree cover, thereby enhancing reforestation (Fujita and Tuttle 1991), secondary succession as well as maintaining the compositional heterogeneity of tropical forests (Wang and Smith 2002). Therefore, considering the multifaceted ecological and economic roles of pteropodid bats like IFF in plant pollination, seed dispersion and reforestation, the conservation and management of the bats along with their roosting and foraging trees, must be considered crucial for sustainable urban development planning and to stop any potentially serious ecological consequences and economic disadvantages (Fujita and Tuttle 1991; Singaravelan, Marimuthu, and Racey 2009; Ali 2014). Despite being the most conspicuous and the largest amongst 14 fruit-eating bat species (Chiroptera; Pteropodidae) reported from India (Kumar et al. 2016), relatively few researches have so far been carried out on the feeding behaviour and ecology of this mega chiropteran species and the known information on this species are also fairly old (McCann 1934, 1941; Neuweiler 1969). Research has been carried out on roosting habitats of IFF in both rural (Pandian and Suresh 2021; Madala et al. 2022) and urban areas (Mishra, Dookia, and Bhattacharya 2020; Roy, Saha, and Mazumdar 2020) in India. Research on foraging behaviour of IFF has been conducted in other South Asian countries in the recent years (Win and Mya 2015; Javid et al. 2017), as well as in a few rural (Sudhakaran and Doss 2012; Prasad et al. 2014) and urban centres in India (Nathan et al. 2009; Rao 2017). Particularly, no studies have been carried out to locate the foraging sites of Indian flying fox around their roosting sites and data concerning the feeding behaviour of the Indian flying fox Pteropus medius in urban systems is limited. Thus, information of the dietary behaviour and ecology of Indian Flying Fox (IFF) including their foraging habitat and fruiting trees are very much essential to ensure their continued existence in urban areas. To address this research gap on the foraging behavior of bats in urban megacities, we carried out this study with the following null hypotheses:

Null hypothesis 1: No significant variation exists in the number of IFFs across different foraging sites

Null hypothesis 2: Land cover features of the foraging sites have no influence on the IFFs

Null hypothesis 3: No significant variation exists in the number of IFFs across different foraging trees in urban areas.

To test these hypotheses, we carried out the present study (i) to identify the foraging sites of IFF around a major urban diurnal roost of Kolkata, India, (ii) to find out the land cover features influencing their foraging site selection and (iii) to identify the foraging tree species used by the IFF. Our findings contribute to a further understanding of the foraging site selection and foraging ecology of Indian flying fox, and might be useful in the conservation of these megachiropterans in many other urban landscapes across the globe.

Methods

Study area

This study was done in Kolkata (22°33′N, 88°30′E, 1.5–9 m a.s.l.; Fig. 1), which is a major urban agglomeration in India covering an area of 206.08 km² and one of the most populated cities of the world with 4 496 694 residents (Census Organization of India 2011; Kolkata Municipal Corporation 2021). The city is linearly laid out along the banks of the Hooghly River in the lower deltaic plains of the Ganga-Bhagirathi River basin with younger alluvial soil made primarily of silty and clayey loams and comprises various low lying depressions that form marshes and lakes (or jhills) (CGWB 2007). The major land cover categories of this urban area comprise of urban built-up areas, agricultural land, bare land, fallow land, vegetation, homestead with plantation and natural water bodies (Ray et al. 2023). Along with 35 ornamental median strips (56 638 m), the city is also embellished with thousands of economically and ecologically important tree species interspersed in 93 parks, playgrounds, nurseries, gardens in 53 wards and several other green patches in and around the urban complex, contributing to a total 28.088 km² of tree cover (vegetation) area (Mukherjee 2015; Supplementary Table S1). Comprising of 16 boroughs, which together encompass 144 wards, the city is bounded by river Hooghly in the northwest, South 24 Parganas district in the south and southwest, Salt Lake City in the east and North 24 Parganas district in the north (Kolkata Municipal Corporation 2021). Encompassing 1 056 351 households a total area of 113.806 km² falls under urban built-up area (Supplementary Table S1; Kolkata Municipal Corporation 2021). The city is drained by the Hooghly River along its northwestern boundary and by several canals. These canals and 3777 other water bodies (lakes and ponds) cover a large area (12.6702 km²) of the city (Supplementary Table S1; Kolkata Municipal Corporation 2021; Bhattacharya et al. 2022). Among other land categories in Kolkata, 18.8766 km² falls under open ground, 6.1965 km² falls under crop fields and 2.0475 km² falls under barren land (Supplementary Table S1). Four distinct seasons are noted in Kolkata viz. summer (March–May), monsoon (June–August), post-monsoon (September–November) and winter (December– February) (Ghosh and Ghosal 2021).

Data collection

Single observer (KR) followed the direction of all the flight lines of the fruit bats emerging from the diurnal roosting site in February 2017 during dusk (between 05:30 and 06:30 pm) with the help of compass, which subsequently led us to the location of their communal foraging sites in the study area. Each flight path of the IFFs were followed for 10 ± 3 days and during the efforts of following the bats from ground, even if one bat went out of sight, the next bat and subsequent bats were followed from ground to move further towards their foraging site. Emergence time of the first and last IFF from their diurnal roosting site after sunset and geographical position of these foraging sites were recorded using a handheld GPS (Garmin eTrex 30x) and plotted on the Google Earth^® imageries of Kolkata (Fig. 1).

According to Mathur et al. (2012), the IFF population maintains stability from March until the onset of their second mating season (from early August). So, the present study to assess the foraging activities of these fruit bats were carried out between March–May, 2017, in order to avoid counting non-residential immigrating males in the colony (Mathur et al. 2012). To determine the number of IFFs in each of the foraging trees, single- observer fixed radius (50 m) point sampling method (Petit et al. 1995; Masing, Lutsar, and Lotman 2005; Sutherland 2006) was carried out from a fixed observation point on ground in four different foraging sites, as all the foraging trees in each foraging site were found to be present within 50 m radius of the present observation point (Bibby et al. 2000; McCallum 2005). Each observation point was surveyed twice in a month in the evening hours (between 06:30 and 08:30 pm) of days with calm weather conditions, in absence of rain and/or strong wind. Therefore, total 24 surveys (i.e. three months* four foraging sites* two surveys per month per foraging site) were carried out where the number of foraging IFFs were recorded for 10 min following Hutto, Pletschet, and Hendricks (1986). Within this 10 min count duration the IFFs foraging in groups in a particular tree was counted. This method was repeated for all the trees present in a particular foraging site. These counts finally yielded the total number of IFF in each foraging tree species of that foraging site. Each day three such sessions of 10-min point count method were conducted between 06:30 pm to 08:30 pm in all the foraging sites. These bats were observed using red filtered torchlight (Prasad et al. 2014) and a pair of binoculars (Nikon 8 × 40) (Bonthoux and Balent 2012) causing minimum disturbance to the foraging IFFs. Also, different foraging trees used by the IFF were identified using field guides (Mukherjee 1983; Sahni 1999).

Occurrences of anthropocentric activities like numbers of pedestrian, bi-cycle, rickshaw, two-wheeler, three-wheeler, light motor vehicle (LMV) and heavy motor vehicle (HMV) were recorded in the study area between March–May, 2017, following a separate single-observer point count method (Bibby et al. 2000; Sutherland 2006). For this purpose, three random locations were selected within 250 m radius buffer area keeping the foraging sites at the centre. Then the number of these anthropocentric activities within 50 m radius around each of those randomly selected points were recorded for 10 min. Each observation point was surveyed twice in a month in the evening hours (between 05:30 and 06:00 pm).

In urban areas, availability of suitable habitat features at local level like trees (White et al. 2005), canopy cover (Alberti and Marzluff 2004; MacGregor-Fors and Schondube 2011), green spaces (Ortega-Álvarez and MacGregor-Fors 2009), presence of water-bodies (Baschuk et al. 2012) and buildings (Germaine et al. 1998) and other urban structures (Ortega-Álvarez and MacGregor-Fors 2009) are known to potentially influence the faunal communities present there. Such habitat features can well be assessed from high resolution Google Earth satellite images (Buchanan et al. 2008; Clark and Aide 2011), as these are relatively up-to-date, freely available in digital format and give a synoptic view (Hu et al. 2013). Hence, the land-cover features like build-up area, water cover and tree cover present within 250 m radius of the sampling point in the foraging sites were assessed from the cloud free high-resolution satellite image of Kolkata (Image acquisition: 24.11.16) obtained from Google Earth Pro software (ver. 7.3.3.7699) which were used as land-cover features of each foraging site of the IFF.

Data analysis

Non-parametric tests were performed for data analysis as Shapiro-Wilk’s tests revealed that the number of foraging IFF (W = 0.84364, df = 24, P < 0.05) followed non-normal distribution, over-dispersed and negatively skewed (variance > mean). Three separate Kruskal–Wallis ANOVA with subsequent post hoc Dunn’s tests were applied to find out if the number of foraging IFF showed any significant variation between (i) the foraging sites, (ii) the foraging trees and (iii) the study months. Using number of IFF, foraging on particular fruiting trees, agglomerative hierarchical clustering (AHC) was performed based on the similarity (Pearson’s r) and aggregated on the basis of un-weighted pair group average (UPGA). Thus, a dendrogram was prepared to classify 16 different foraging trees used by IFF, observed during the study. We tested multi-collinearity between variables (i.e. built-up area, water area, tree cover and anthropogenic disturbances) using variance inflation factor (VIF) method (Zuur, Hilbe, and Ieno 2013) and only included the predictor variables with a VIF value < 5 (Montgomery and Peck 1992) to ensure that no variables were strongly correlated. Then, Generalized Linear Mixed Models (GLMMs) with negative binomial distribution and log-link were carried out considering number of foraging IFF as response variables against the land-cover features (fixed factors) and foraging sites (random factor) as predictor variables. Then another GLMM with negative binomial distribution and log-link were carried out considering number of foraging IFF as response variables against the foraging trees (fixed factors) and foraging sites (random factor) as predictor variables. Statistical tests were performed using SPSS software (ver. 20) and R Studio (ver. 4.1.1). Significance was tested at P < 0.05 and data were presented as mean ± standard error.

Finally, we carried out land cover change detection analyses to understand how the land cover features changed over a decade (corresponding to 2010 and 2020) in each of the foraging sites as well as the entire urban agglomeration of Kolkata Municipal Corporation area. Landsat 7 and 8 satellite images with minimum cloud cover (24 January 2011, 20 January 2020) were downloaded from USGS Earth Explorer (https://earthexplorer.usgs.gov). We then prepared past (2010) and present (2020) land cover maps of the study area (with 30 m resolution) in QGIS through supervised ‘minimum distance classification’ (Abburu and Golla 2015) using Semi-Automatic Classification Plugin (Congedo 2014, 2016). We prepared error ‘matrix’ for accuracy estimation of the land cover layers of 2010 and 2020 land cover maps, both of which showed very good to excellent overall accuracy (Supplementary Table S2; Cohen 1960; Anderson et al. 1976; Landis and Koch 1977).

Results

During the present study it was observed that the IFFs started their foraging flight 30 ± 12 min after sunset mostly in a group of 2 to 4 (sometimes solitary flights were observed) in different directions from their colonial roosting site at Alipore Zoological Garden (22.538115°N, 88.332210°E) which harbours around 945.33 ± 50.96 IFF individuals (Roy, Saha, and Mazumdar 2020) in 17 different tree species (n = 27) like Ficus benghalensis, Ficus glomerata, Terminalia catappa, Tamarindus indica, Madhuca longifolia, Manikara hexandra, Putranjiva roxburghii, Albizia procera, Alstonia scholaris, Pterygota alata, Terminalia arjuna, Casaurina equisetifolia, Delonix regia, Couroupita guianensis, Dalbergia sissoo, Pterospermum acerifolium and Toona ciliate (pers. observation). Four different foraging sites were discovered in four different directions from the roosting site of IFFs viz. foraging site 1 (henceforth FS1), foraging site 2 (henceforth FS2), foraging site 3 (henceforth FS3) and foraging site 4 (henceforth FS4) (Fig. 1; Supplementary Table S3). All the foraging sites were found to be within 1.27 (±0.094) km (Mean ± SE) from the roosting site.

Kruskal–Wallis test revealed that the number of foraging IFF significantly varied across different foraging sites (Hc = 19.472, df = 3, P < 0.05; Dunn’s post hoc test: P < 0.05) and their number in FS4 (414 ± 7.56 individuals) was significantly higher than FS2 (119 ± 9.27 individuals) and FS3 (118 ± 7.32 individuals) except for FS1 (263 ± 3.21 individuals) as shown in Fig. 2a. However, no significant variation was noticed in their number between FS1, FS2 and FS3 (P > 0.05; Fig. 2a).

The number of foraging IFFs in different foraging sites was positively influenced only by tree cover area (GLMM: F_1,19 = 43.054, P < 0.05) (Table 1). However, the other variables, i.e. built-up area (GLMM: F_1,19 = 1.199, P > 0.05), water body area (GLMM: F_1,19 = 1.702, P > 0.05) and anthropogenic disturbances (GLMM: F_1,19 = 0.246, P > 0.05) did not influence the abundance of foraging IFF in different foraging sites (Table 1).

The IFFs were observed to forage on 16 species of foraging trees belonging to 10 families within the four foraging sites of the study area (Table 2). Kruskal–Wallis test revealed that the number of foraging IFF significantly varied across different foraging trees (Hc = 117.35, df = 15, P < 0.05; Dunn’s post hoc test: P < 0.05; Fig. 2b). Number of IFF foraging on Ficus bengalensis was highest (85.2 ± 5.70 individuals) followed by Ficus religiosa (34.4 ± 7.26 individuals) and others (Fig. 2b). Dendrogram further revealed that 16 different foraging trees used by IFF, fall under three different clusters (Fig. 3).

Presence of different tree species (GLMM: F_{15, 368} = 2.156, P = 0.007) significantly influenced the number of IFF in the major foraging sites during the present study (Table 3). Out of 16 different foraging trees used by IFF, presence of only two species viz. Ficus benghalensis (GLMM: FBE = 2.259 ± 0.757, t = 2.985, P = 0.003) and Ficus religiosa (GLMM: FRE = 1.541 ± 0.757, t = 2.036, P = 0.043) showed significant positive influence on the number of foraging IFF (Table 3).

Number of foraging IFF was 221 ± 44.58 individuals in March, 229.8 ± 47.23 individuals in April and 234.1 ± 47.91 individuals in May (Fig. 2c). However, no significant variation in the number of foraging IFF was observed across three different months of the present study (Kruskal–Wallis test: Hc = 0.65432, df = 2, P = 0.721; Dunn’s post hoc test: P > 0.05).

LULC change detection analysis revealed a 4–6% decrease in tree cover area in all the foraging sites, except for FS4 over a decade (2010–2020) (Table 4). Built-up area in all the foraging sites increased by 1–4% whereas FS1 had a 2.28% decrease in built-up area during 2010 and 2020 (Table 4). Waterbody area increased by 2–8% and open ground increased by 1–8%. whereas barren land decreased by 1–4% along with crop fields which also decreased by 0.4–4% in all the foraging sites over a decade (2010–2020) (Table 4). In addition, LULC change detection analysis in the entire Kolkata Municipal Corporation (KMC) area over a decade (2010–2020) also revealed a decrease in tree cover area, crop fields and barren land by 4.66%, 4.15% and 8.54% respectively and an increase in built-up area, waterbody area and open ground by 8.37%, 1.70% and 7.27% respectively (Supplementary Table S1).

Discussion

The emergence time of IFFs after sunset from their colonial roosting site, multidirectionality of their flights and distance covered to reach the nearby foraging grounds observed in the present study are in consistent with earlier reports (Bates and Harrison 1998; Kumar, Prasad, and Elangovan 2019; Pandian and Suresh 2021; Murugavel et al. 2023). Using different foraging sites reduce intraspecific foraging competition thereby optimizing spatial resource partitioning (Nicholls and Racey 2006; Prasad et al. 2014; Tayiba Latif 2014). This might be a plausible reason for the selection of four different foraging sites by the IFFs in four different directions in the present study. Predictability of food are known to influence the spatial memory of bats (Genzel, Yovel, and Yartsev 2018). Availability and predictability of food in urban habitats also impact the foraging patterns (Egert-Berg et al. 2021), optimize foraging activities and thereby improve the fitness and survival of a species (Krebs 2009; Boardman et al. 2021). Possibly for these reasons the IFF in our study followed distinct flight lines from their roost to the foraging sites.

We noticed that foraging site selection of IFF was significantly influenced by the tree cover present within 250 m of the foraging site. Bat species thriving in urban areas are known to depend on various tree species present along the roads, as well as inside parks, gardens and private premises for food and also for safe dispersal between their diurnal roost and foraging sites (Van Zyll de Jong 1985; Duchamp, Sparks, and Whitaker 2004; Duchamp and Swihart 2008; Dixon 2012; Moretto et al. 2019). Therefore, in urban areas, tree cover is emphasized to be an important habitat feature for bat communities as they provide various important resources for their survival (Fenton et al. 1992; Medellín, Equihua, and Amin 2000; Schulze, Seavy, and Whitacre 2000; Harvey et al. 2006). It has also been suggested that tree cover mitigates the negative effects of artificial light at night (ALAN) on foraging bats by shielding areas against light scatter in urban landscapes (Straka et al. 2019). Various research studies advocate for the protection of different urban tree canopy covers in both public lands, roadside trees and trees present inside public premises (Zipperer et al. 1997; Jones, Davis, and Bradford 2013; Clark, Ordóñez, and Livesley 2020; Wood and Esaian 2020).

Spatio-temporal distribution of foraging resources is known to influence behavior, biology and distribution of individuals (Marshall 1985). Bat forages from the tree canopies (Evelyn, Stiles, and Young 2004; Bhatnagar 2014) and the availability of nectar and fruit bearing trees are particularly beneficial for them (Nakamoto, Kinjo, and Izawa 2007, 2012; Wood and Esaian 2020). The influence of tree size (height, DBH, canopy spread etc) and resource density, on the food and foraging preferences of several pteropodid bat species including IFF, have been documented in several studies in India (Nathan et al. 2009; Sudhakaran and Doss 2012) and all around the globe (Walton and Trowbridge 1983; McDonald‐Madden et al. 2005; Krivek 2017; Krivek et al. 2020). In present study, IFF were seen to forage on 16 species of foraging trees (Table 2). Rao (2017) found IFF to forage on nectar and petals of flowers and fruits of 24 species and Mahmood-Ul-Hassan et al. (2010) reported 20 species of foraging trees of IFF, both of which include eight species of foraging trees in common to those observed during the present study. In lower Brahmaputra valley of Assam, individuals of P. medius have been observed to forage on 51 plant species of 35 genera and 24 families (Ali 2014) which include 15 species of foraging trees in common to those observed during the present study. Sudhakaran and Doss (2012) observed IFF to forage on unripe fruits of Mangifera indica, Psidium guajava, Bassia latifolia, Ficus religiosa, F. benghalensis, as also noticed during the present study. Similar tree species were also used for food by another species of bat under genus Pteropus (P. livingstonii) (Trewhella et al. 2001; Ibouroi et al. 2018).

Out of 16 different foraging trees recorded during the present study, Ficus benghalensis and Ficus religiosa were found to positively influence the number of foraging IFF, which clearly indicate figs to be an important foraging resource for IFFs in our study area. Ficus benghalensis and Ficus religiosa bear small-sized fruits which were foraged on the same tree (in situ foraging) by P. medius (Prasad et al. 2014). Fig trees (Ficus spp.) are consumed by several species of frugivorous or omnivorous vertebrates, particularly birds and mammals (Shanahan et al. 2001; Sreekar, Le, and Harrison 2010). Even when other foods are abundant, the frugivores show a clear preference towards figs (O'Brien et al. 1998). A number of volant, arboreal and terrestrial species particularly forage on the fruits and edible inflorescences (syconia) of these Ficus trees, which are not only easily accessible and easy to handle, but are also with high nutritive values (Shanahan et al. 2001; Sreekar, Le, and Harrison 2010; Prasad et al. 2014). Fig fruits are calcium rich (Nelson et al. 2000) and contain three-times more calcium than other fruits (O'Brien et al. 1998). Higher amount of calcium plays vital role in the development and maintenance of bones (Barclay 1994, 1995; Palmer, Price, and Bach 2000). Figs are favorite food of many species of flying foxes (Tayiba Latif 2014; Lee et al. 2017) and more than half of the chiropteran diet is obtained from the trees falling under family—Moraceae (Mahmood-Ul-Hassan et al. 2010; Ray 2014). Several species of pteropodid bats in subtropical and tropical regions of Australia and Asia, including P. medius, are known to consume the fruits from more than 30 species of fig trees throughout the year (Marshall and McWilliam 1982; Thomas1984; Fujita and Tuttle 1991; Bhat 1994; Javid et al. 2017). Also, the bat density is reported to be high in areas with greater relative density of total figs (Mahmood-Ul-Hassan et al. 2010). We found that the number of IFFs were highest in Ficus bengalensis followed by Ficus religiosa. This clearly indicates figs to be an important foraging resource for IFFs in our study area. Earlier researchers reported these species to serve as staple food of P. medius (Wendeln, Runkle, and Kalko 2000; Mahmood-Ul-Hassan et al. 2010; Sudhakaran and Doss 2012). Besides, these species are ubiquitous and fruits are available throughout the year with predictable food resources (Mickleburgh, Hutson, and Racey 1992; Bhat 1994).

We did not find any significant variation in the number of foraging IFF across three different months of the present study (March–May). This is possibly because the population of P. medius shows mass copulation and increases exponentially, reaches its peak during February in the first mating season (mid- January to early March- spring) and then maintains stability from March until the onset of their second mating season (early August to end of September—autumn) (Mathur et al. 2012).

Most of the land area in major urban metropolitan cities across the globe is dominated by buildings or paved areas, and any vegetation is primarily ornamental (Blair 1996; Germaine et al. 1998). Kolkata is not an exception where urban built-up area comprises the maximum land cover (Supplementary Table S1; Dinda, Chatterjee, and Ghosh et al. 2021; Das and Angadi 2022). With the accelerated rate of urbanization and industrialization along with rapid expansion of real-estate business, natural habitats with green patches like parks, playgrounds, gardens, wetlands and old urban buildings (with backyard gardens) are converted to public and commercial urban infrastructures (roads, metros, flyovers, water pumping stations, gas stations, shopping malls, hotel complexes etc) and multistoried office and residential buildings (without any tree cover) which leads to disturbances and negative impacts on several faunal species (Pena et al. 2017). The urban greenspace of Kolkata supports around 414 avifaunal species and 13 species of mammals, including frugivorous bat species like Indian flying fox (Pteropus medius), Greater short-nosed fruit bat (Cynopterus sphinx) and Indian pipistrelle (Pipistrellus coromandra) (Basu Roy et al. 2022; Lepage 2023). Tree cover area of this city has been declining at an alarming pace with rapid increase in built-up area in the past few decades (Ramachandra, Aithal, and Sowmyashree 2014; Rahaman et al. 2019; Sen 2020; Ray et al. 2023), which is in accordance with our findings (Table 4; Supplementary Table S1). This trend is not only potentially detrimental for IFF, but are also equally harmful for many other urban wildlife depending on urban tree cover for their refuge and/or resource utilization.

Extreme urbanization decreases the species richness of various birds, mammals, reptiles, amphibians, invertebrates and plants triggering biotic homogenization which can lead to the extinction and loss of many native species (McKinney 2006, 2008; Pal et al. 2019). Therefore, adequate and appropriate planning and management of the urban vegetation is urgently needed emphasizing on both aesthetic and utilitarian view of the urban afforestation process ensuring the availability of resources for native fauna. Decisions must take into consideration how effectively the urban landscape and the green elements integrate together (Pena et al. 2017). Policies and punishments also need to be strongly implemented to prevent destruction of ecologically important trees in any private, public or commercial urban spaces and mandatory prior permission must be obtained along with producing genuine and relevant justification, even if any tree needs to be removed from these urban spaces (Miller, Hauer, and Werner 2015; Moretto et al. 2019). Moreover, generating awareness for the urban citizens and providing them with rewards and incentives for protecting trees within any private, public or commercial urban premises may not only be useful for various tree-dwelling urban wildlife (including IFF), but will also foster many other benefits that the urban trees offer (Roy, Byrne, and Pickering 2012; Sen 2020). In his book Design with nature Ian McHarg wrote “We need nature as much in the city as in the countryside” (McHarg 1969). Thus, preserving and maintaining large trees, and planting adequate amount of native tree species in private, public and commercial urban spaces, are to be urgently implemented. This initiative will not only increase biodiversity and ecosystem functionality within the urban matrix, but will also alleviate the negative effects of urbanization and thereby improve our own wellbeing and quality of life (Pena et al. 2017). Finally, we advocate to include fig trees in urban afforestation programs, which will not only serve as a good foraging resource for IFF, but will equally be useful for other frugivores thriving in urban habitats.

Acknowledgements

We appreciate the support of Sri. M.S. Roy, Smt. Nilanajna Roy and Sri. Suvrajyoti Chatterjee in implementing the field work. We would especially like to thank Ms Sweta Bhattacharya for her consistent field support during data collecting and data entry. Special thanks are due to Mr Souvik Barik and Ms Antara Sarkar for their valuable assistance with GIS mapping and manuscript improvement. Infrastructural support extended by the Head, Department of Zoology, University of Calcutta and the Principal, Shibpur Dinobundhoo Institution (College) are gratefully acknowledged. Special thanks are due to Dr Anandarup Biswas, Associate Professor of the Department of English for improving the language of this manuscript. We also thank the Director of the Zoological Garden for his gracious permission. Finally, we would like to express our gratitude to the anonymous reviewers for their suggestions in improving the manuscript.

Author contributions

Kanad Roy (Conceptualization [supporting], Data curation [equal], Investigation [lead], Writing—original draft [equal], Writing—review & editing [equal]), Goutam Kumar Saha (Conceptualization [supporting], Project administration [equal], Supervision [supporting], Writing—review & editing [equal]), and Subhendu Mazumdar (Conceptualization [lead], Formal analysis [lead], Supervision [lead], Writing—original draft [equal], Writing—review & editing [equal])

Funding

The expenses during the research were borne by the authors and not funded by any external agency.

Conflict of interest statement

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Supplementary data

Supplementary data are available at JUECOL online.

Data availability

The datasets used in the present study can be made available upon authentic and reasonable request.

Ethical statement

This paper contains findings of our original research. Applicable national and/or international guidelines for animal ethics were followed and no animal was harmed during the study. We adhered to the ethical standards in this study and in production of this manuscript.

Consent for publication

The article submitted herewith contains the findings of our original research, is not under consideration for publication elsewhere, and is approved by all authors of this manuscript.

References

Author notes