Urban fruit bats give birth earlier in the season compared to rural fruit bats

Abstract

Background

Urbanization is rapidly altering our ecosystem. While most wild species refrain from entering urban habitats, some flourish in cities and adapt to the new opportunities these offer. Urban individuals of various species have been shown to differ in physiology, morphology, and behavior compared to their rural counterparts. While several studies have suggested that urban dwelling alters the reproductive cycle in birds, such evidence currently has not been shown for mammals. Egyptian fruit bats are highly flexible mammals that roost and forage in both urban and rural habitats. Urban-dwelling fruit bats encounter higher average temperatures and a richer supply of food (mainly fruit) during winter.

Results

Here, we set out to determine whether urban-dwelling fruit bats take advantage of urbanization and reproduce earlier in the annual cycle than rural fruit bats. We sampled ten fruit bat colonies located in different urbanization levels, over 3 years. We monitored the bats’ reproductive state and the size of the pups following parturition. Indeed, we found that urban fruit bats gave birth ~ 2.5 weeks earlier in spring than rural fruit bats. We also found that roosting in urban colonies did not decrease the bats’ reproductive success, in contrast to what has been suggested for some urban birds.

Conclusions

Our study provides new insights into the adaptation to urban living and its exploitation by one of the most common mammalian groups found in cities worldwide—bats.

Background

Urbanization is one of the most significant processes of land use change and has substantially altered the habitats and landscapes available to wildlife [1]. The ongoing expansion of urban areas has led to a decline in natural habitats worldwide [2]. Numerous studies indicate that urbanization can adversely affect animals due to, among others, habitat loss, fragmentation, barrier effects, road mortality, high density of syntrophic predator species, exposure to chemical and physical pollutants, anthropogenic noise, artificial illumination, and direct human interference [3,4,5,6]. Moreover, animals roosting in urban environments have been suggested to be more vulnerable to disease outbreaks and suffer from higher parasite loads than rural animals [7, 8], albeit not for all species of hosts or parasites [9]. Despite these challenges, urbanization can benefit those species that are able to adapt to anthropogenic changes [10]. Some of the advantages of dwelling in the city include (1) elevated temperatures that result from the “urban heat island” phenomenon, (2) access to food, and (3) a refuge from predators [2, 11, 12]. The ability of a species to thrive in an urban area is closely tied to its life history and ecology [11]. Species are commonly categorized as either “urban exploiters” (able to exploit urban benefits), “urban avoiders” (highly sensitive to urban disturbances), or “urban adapters” (able to adapt to moderate urbanization levels) [13, 14]. Studies have in general demonstrated that omnivores, frugivores, and opportunistic nectar-feeders adapt more successfully to urban environments than insectivores or carnivores, due to the abundance of ornamental fruit trees and numerous artificial roosting sites [15, 16]. Moreover, increasing scientific evidence has shown that urban exploiters and adapters exhibit various behavioral modifications to city life [17,18,19,20,21,22,23].

Urbanization has also been shown to affect the reproduction of various taxa in both positive and negative ways [24]. For example, increased urbanization has been suggested to drive smaller clutch sizes in amphibians, birds, and reptiles. Several urban bird species have been shown to initiate breeding earlier in the season than their rural counterparts [25, 26]. And there is an ongoing debate as to whether urban environments reduce reproductive success and nullify the benefits of earlier breeding [1]. For example, urban white-winged choughs (Corcorax melanorhamphos) were shown to initiate breeding earlier than their non-urban counterparts but were also more likely to suffer from nest failures [17].

Studies on mammals in urban areas are much scarcer than those on birds [24], and the reproduction of urban mammals compared to rural ones has hardly been studied. While bats (order: Chiroptera), which account for more than 20% of mammalian species, exhibit a relatively high sensitivity to environmental changes [27], certain bat species can be found and even thrive in human settlements [4, 22]. Among the factors affecting the prevalence of bat presence in urban settings are the availability of suitable roosting sites, foraging habitats, and the bats’ morphological characteristics (e.g., wing morphology) [4, 11, 28].

Some studies have suggested that urban life drives bats to adapt their ecology and behavior. Bats that roost in buildings form larger colonies than those roosting in natural roosts [29], and they may alter their roost-switching patterns in response to disturbance [30]. The presence of bats in urban habitats has also been tied to disease spread. For example, flying foxes roosting in the urban parks of Australia have been associated with pathogen outbreaks [31].

Egyptian fruit bats (Rousettus aegyptiacus) offer an interesting case study as they roost in both urban and rural areas and have been shown to adapt their behavior to urbanization [22, 32]. They enjoy a wide distribution range worldwide and exhibit flexibility in their reproductive patterns in different parts of the world, providing evidence of flexible reproduction adaptivity. Specifically, the species exhibits a bimodal annual reproductive cycle in several Mediterranean locations [33] and in central African rainforests [34], year-round breeding in captivity in Egypt [35], and a unimodal cycle on the South African savannah [14].

In this study, we set out to examine potential differences in the breeding timing and success of urban and rural Egyptian fruit bat colonies. Specifically, we hypothesized that urban fruit bats might benefit from the urban conditions and give birth earlier in the season.

Results

To test this hypothesis, we examined female reproduction in a total of five rural and five urban colonies over three consecutive years (Fig. 1A—spring of 2022, 2023, and 2024 and winter of 2022–2023, see Table 1 and Additional file 1: Table S1). In total, we sampled 561 mothers and 123 pups. We estimated the human population density at typical bat foraging ranges, i.e., a 5-km radius and a 15-km radius around each bat colony (Fig. 1B and Table 1 and see the “Methods” section). According to the estimated densities, we used a threshold of 3000 inhabitants per km² to distinguish between rural and urban bat colonies. We also tested all models using a categorical division of the colonies into urban and rural. We then used generalized linear mixed effect models (GLMMs) to examine the effect of urbanization on the reproductive cycle. Finally, we employed a categorical urban/rural model that best fit the data (based on the AIC) but also provided results for the human population density at a 15-km radius, which fits better than the 5-km density and was not significantly worse than the categorical model. The 15-km density indicated an almost continuous variability in human population density for our sampled colonies (see Y-axis values for the light-blue points in Fig. 1B). Unless stated otherwise, we also used the sampling year and date (days from December 1st of the relevant year) as fixed factors in all models and the colony ID as a random effect (see the “Methods” section). To identify the best time slots for sampling, we first sampled two colonies (one urban and one rural) approximately once a month over a full year (Additional file 1: Table S2). This revealed a clear bi-annual reproductive cycle (Fig. 1C), which had already been documented for this species in the region [36]. Accordingly, in the following years, we conducted one sample in December to determine pregnancy probability in the colonies and another sample in March–April to assess parturition dates. We focused on the spring reproduction peak as it is the first after winter, which is the most difficult time for these bats [36]. All the results below are reported for adult females or pups of both sexes.

Fig. 1

Fruit bat colonies in relation to human population densities. A A map depicting the sampled bat colonies’ locations (urban in brown and rural in green). Circles represent the 5-km radius (dark blue) and 15-km radius (light blue) around the bat colony. Red and brown areas represent urban cities and towns, respectively. Here, we define an urban colony as one with a human population of more than 3000 inhabitants per km². B Human population density (per km²) for a 5-km and 15-km radius around the colonies. The dotted line shows the cutoff between urban and rural colonies. C Seasonal fluctuations in reproduction. During 2021/2022, one urban colony (Herzliya) and one rural colony (Tinshemet) were sampled approximately once a month for 1 year. Dark green (Tinshemet) and brown (Herzliya) lines and dots represent the percentage of pregnant females out of the total adult females caught in each sampling event. Light green (Tinshemet) and brown (Herzliya) lines represent the percentage of females with pups out of the adult females that were caught in each sampling event. Gray areas represent the dates chosen for sampling in the following years, based on peaks in pregnancies and pup occurrence

Table 1 Detailed data of the sampled bat colonies. Numbers refer to female bats only, as captured males were immediately released

In winter, there was no significant difference in pregnancy proportion between rural and urban colonies (75% ± 19% [mean ± SD] of females in urban colonies were pregnant vs 84.5% ± 19.5% in rural colonies). The Null model with only the intercept as an explaining parameter had the best fit (binomial distribution GLMM null model, intercept p < 0.001, n = 197 adult female bats, see Table 2 in which we also provide the best non-null model). There was also no significant difference in the size (forearm; GLMM, p = 0.9, n = 197 bats) and fitness (represented by the body mass index (BMI), see the “Methods” section; GLMM, p = 0.77, n = 197 bats) of adult females in urban and rural colonies. Although there was no significant difference in the parasite load between urban and rural females, we did find a significant correlation between parasite load and reproductive state, with pregnant bats presenting a slightly higher parasite load than non-pregnant females (GLMM, p = 0.01 for reproductive state, n = 197 bats, Table 2). Winter BMI (a proxy for individual state) did not correlate with parasite infestation (GLMM, p = 0.3 for parasites, n = 197 bats, Table 2).

Table 2 Statistical GLMM results for adults and pups

Pups in urban colonies were born earlier in spring than in rural colonies, as was evident from their significantly longer forearms and heavier weight (Fig. 2B, C, urban average forearm was 10 mm longer and average weight was 7 gr heavier; GLMM, forearm: p < 0.001, n = 123 pups; weight: p = 0.03, n = 123 pups, Table 2). Translating forearm to age (see the “Methods” section) suggested that urban pups were born on average 2.5 weeks earlier than rural pups (GLMM, pup age: p < 0.001, n = 123 pups, Table 2).

Fig. 2

Pups are born earlier in urban colonies. For all parameters, data are presented on the left panel by colony type (A1–D1; lines represent the median and lower and upper quartiles. Circles represent individual data points for each colony type and a gray asterisk represents significance), and on the right panel by human population density for a 15-km radius around the colony (A2–D2; mean ± SE). Asterisks represent individual data points for each colony. A Pup estimated age. B Pup forearm length. C Pup weight. D Pup BMI

We rejected the possibility that urban pups are born at the same time as those in the wild but simply grow faster than rural pups, as there was no significant interaction between urbanization and time from the beginning of the season in explaining pup size. Pup size therefore did not increase differentially in the two environments (GLMM with pup forearm length as the response and colony type and time as fixed effects with an interaction between time and colony, p = 0.7 for the interaction, n = 208, Additional file 1: Table S3). Note that the spring sampling occurred over a span of ~ 4 weeks, enabling us to perform this analysis and assess the urban and rural growth rates. We additionally determined whether the size of the mother (forearm length) had any effect on the size of the pups, by adding the forearm length of the mother as a fixed factor in the pup size models (weight and forearm), but found no significant effect (GLMM, p > 0.5, n = 123 pups).

We also examined several alternative models (using the AIC to perform model selection). To account for the distribution of colonies—all urban colonies were near the coast and at lower elevations—we examined models that included ambient temperature (near the colony) as a fixed factor instead of or in addition to human density. Based on their AIC score, these models did not fit the data nor the urbanization level models (which were based on the human population density Additional file 1: Table S3). Adding bat population size to the model also did not improve model fit.

We only measured the temperature inside the colony in five colonies (four urban and one rural), so we could not compare these models to the models above. Interestingly, however, internal colony temperature in the urban colonies significantly correlated with pup age but not with the other pup measurements (p = 0.03, Additional file 1: Table S3).

Pups in rural colonies had significantly higher BMIs (Fig. 2D and Table 2; GLMM, p < 0.001, n = 123 pups). However, a model of the change in pup BMI over time (Methods) suggested that, for the relevant ages of the sampled pups, the BMI decreases by 0.0001 g/mm² per day, making this difference likely a result of the urban pups being older rather than being due to some resource deficiency in cities.

There was no correlation between parasite load and pup BMI (GLMM, p = 0.54, n = 95 pups). Spring adult parasite load was significantly positively correlated with adult BMI (GLMM, BMI: p < 0.001, n = 244; weight: p < 0.001, n = 244, Table 2) and also with reproductive status, with lactating bats suffering from higher parasite loads than both pregnant and non-pregnant bats and no difference between the two latter groups (GLMM, p < 0.001 for lactating, n = 244 bats, lactating vs. non-pregnant, p < 0.001 and lactating vs. pregnant, p = 0.003). There was also no difference in the parasite load of urban and rural bats in spring. The continuous model showed a significant difference in parasite load but the effect size was negligible and the categorical model with the same AIC did not show a significant difference (continuous—by density, p = 0.03; categorical—by type, p = 0.12, n = 244 bats).

There was no significant effect of urbanization on the reproductive yield, which was defined as the proportion of adult females in the colony that were actively reproductive (i.e., either pregnant/lactating/with pup; GLMM, null model, intercept p < 0.001, n = 364 adult female bats, Table 2). This measurement sought to validate the hypothesis that urban bats giving birth earlier does not result in lower overall reproduction rates due to more miscarriages or higher pup mortality.

Discussion

Approximately 55% of the global human population resides in urban areas, and projections indicate a rise to 68% by 2050 [37]. Urbanization has been shown to affect animals in many different dimensions [24]. Its effect on animal reproduction is still unclear and under debate, especially in mammals [1, 4, 25]. Here, we show that urban-dwelling fruit bats give birth ~ 2.5 weeks earlier in spring than rural fruit bats. Among the parameters that we examined, urbanization explained this shift in reproduction time better than other environmental or colony parameters. Moreover, a categorical urban/rural classification of the colonies explained the data better than ambient temperature, suggesting that the earlier birth in cities is not merely a result of the spatial spread of the colonies we sampled, because temperature changed gradually between colonies while we observed a categorical difference.

We suggest that the conditions found in cities, specifically the elevated ambient temperatures outside [38] and the relatively easier access to food [22], allow fruit bats to give birth earlier in the season than rural bats. The winter temperate in Israel poses severe difficulties for fruit bats, which suffer from a major increase in morbidity due to the low temperatures, and to some extent also due to the sparseness of food resources during winter [36]. Indeed, the ambient temperature outside the colonies significantly correlated with pup weight (but not with pup forearm length). However, human population density explained pup size and age better than ambient temperature, suggesting that temperature per se is not the sole driver of early season parturition and that additional urban features drive this phenomenon. One obvious factor is the higher prevalence of food (fruit trees), which are available year-round in the city because they are watered and because cities host many ornamental trees whose seasonality does not coincide with the local climate.

Another possible explanation for the earlier parturition is the more protected environment that city bats experience inside their roost in winter. Indeed, the positive correlation between pup age and temperature inside the urban colonies suggests that city microclimate can also have an effect, advancing parturition when the temperature is higher. The Dizengoff Center colony, for example, offers a unique case in which the bats roost in an active suppliers’ (truck) parking lot where the temperature is always much higher than the ambient temperature outside. On average, the pups in this colony were born earlier than in all other colonies. However, more sampling is required to confirm this observation.

What is the advantage of reproducing earlier? Egyptian fruit bats have been globally shown to adapt their reproductive cycle to the local weather, sometimes reproducing once a year and sometimes twice [33, 39]. In Israel, they reproduce twice a year, with reproduction peaking around March–April and August–September, at the beginning of spring and the end of summer, thus avoiding rearing pups in winter.

Notably, only some bats manage to reproduce twice a year, as we observed in captivity and as concluded from our observation that 70–80% of adult females are pregnant during each reproductive cycle (Fig. 1C). To manage a second reproductive cycle in late summer, females would benefit from giving birth as early as possible in spring. Because we only sampled two colonies during the summer reproduction season, we could not test this prediction.

Notably, there was no significant difference between urban and rural colonies in the proportion of females with pups and pregnant females out of the total number of adult females in mid-spring. This suggests that, unlike some other species for which the city seems to be an ecological trap that attracts individuals to forage in it but reduces reproductive success [17], Egyptian fruit bats do not suffer from reduced reproductive success in cities. More research is needed to determine whether urban bats copulate earlier in the season, or whether they are able to control their gestation period, as some bat species do [40].

Due to previous reports of increased parasite loads in urban areas and a connection between parasite load and reproduction [41, 42], we examined these two questions focusing on Nycteribiid flies, which are the most common ectoparasites of our studied bat species [43]. We did not find a significant difference in parasite load between urban and rural bats in spring or winter. We found that reproductive state correlated with parasite load, and specifically that pregnant females in winter and lactating (and pregnant) females in spring host more parasites than non-pregnant females, although we note that our spring counts comprised mothers and pups together. BMI also positively correlated with parasite load in spring, but this could be an artifact of the bats’ being pregnant (and thus exhibiting high BMI).

Conclusions

Urbanization significantly impacts the reproductive timing of Egyptian fruit bats, with urban female fruit bats giving birth approximately 2.5 weeks earlier in spring compared to rural females. Factors such as higher urban ambient temperatures, abundant food resources, and more protected roost environments probably contribute to this shift in timing. Although urban bats exhibit similar reproductive success rates to those of rural bats, early birth timing may enable females to undergo a second reproductive cycle in late summer. Parasite loads did not differ significantly between urban and rural bats, though reproductive states influenced parasite prevalence. Further research is needed to clarify the mechanisms driving the earlier parturition and urban-specific adaptations.

Methods

Bat sampling

We conducted a sampling of five rural and five urban bat colonies (see the “Environmental parameters” section) during three consecutive years (2021–2024). During the first year, we sampled two colonies, one rural and one urban, once a month, to document the breeding cycle. Following our initial findings, over the next 2 years, we sampled ten colonies twice a year in winter (mid-December to mid-January) when females are pregnant and in spring (mid-March to mid-April) when some of them have already given birth (see Table 1 and Fig. 1 for the exact colony locations and sampling dates). Because all the colonies sampled in this experiment are inhabited by bats year-round, we can assume that copulation can occur at all times. We selected colonies that cover a range of urbanization levels, from deep inside the city through more suburban areas and to completely rural environments. To reduce potential environmental and colony-based confounds, all colonies were located in central Israel (same latitude) with relatively little altitude variation (all < 350 m), and all held hundreds to thousands of individuals. Urban colonies are naturally closer to each other as the density of colonies in the city is higher (there are more colonies per km²). To account for biases resulting from the spatial distribution of the colonies, we incorporated potential confounds such as temperature in the models (see the “Statistics” section). The population of each colony was approximately assessed by counting the bats in a sector of the colony and extrapolating.

The sampling was conducted under permits from the ISNNPPA (Israeli Nature and National Park Protection Authority)—permit numbers 2021/42760, 2022/43219, 2023/43373, and 2024/43583. We used a combination of mist and hand nets to capture the bats. Data collection took place on the site immediately post-capture. All measurements were conducted by experienced bat handlers and performed under veterinary supervision. During the first 2 years, all bats from the Herzliya and Tinshemet caves were PIT-tagged (LID540-FDXB by Trovan®). Sixteen female bats, out of 150 tagged, were recaptured during this experiment, all in the Herzliya cave.

Bat parameters

The female bats were processed, and the male bats were immediately released. The reproductive status (when no pup was present) was assessed using palpation by a bat-specialist veterinarian to detect pregnancy. Sub-adults that had never reproduced before were identified based on size and nipple state and were excluded from further analysis as we only focused on mature reproductive females. Forearm length was measured using a Carbon Fiber Composites Digital Caliper (resolution ± 0.1 mm). Weight was measured on a digital scale (resolution ± 0.3 g). The body mass index (BMI) was calculated by dividing the bat’s weight by the square of the forearm length. Nycteribiidae is a family within the true fly superfamily Hippoboscoidea. Along with their close relatives, the Streblidae, they are commonly referred to as “bat flies.” These flies are parasitic and are known to infest Egyptian fruit bats [43]. Individual parasite load was determined by counting the blood-sucking Nycteribiidae flies found on the bats during a 10-s systematic body search. When a pup was present, the parasite load was assessed for both mother and pup together. Each bat was also examined for major unexpected conditions (injuries, diseases) before prompt release. Pup weight and forearm length were measured, and their age was estimated based on a polynomial fit developed by the lab to fit forearm to age. The fit was based on a previous large data-set, including measurements collected daily from dozens of pups born in captivity to mothers that had been caught just prior to parturition to minimize the effects of captivity [34, 44]. Our forearm-to-age captive measurements are compatible with data collected in the wild [45]. We similarly used another polynomial model to predict changes in BMI (calculated as noted above) with age.

Environmental parameters

The average ambient temperature around the colonies was determined using data from the Israeli Meteorology Service (IMS)—for each colony, we took data from the nearest IMS station. Temperatures were noted for the relevant sampling year and sometimes varied between neighboring colonies. The average temperature inside the colonies was measured for five of the ten colonies, using either a PurpleAir PA-II-SD sensor (Dizengoff and Soncino) or a PATS + sensor (Jaffa, Bridge, Beit Guvrin), deployed inside the colonies (Additional file 1: Table S4). There was a significant linear correlation between human population density and environmental temperature (outside the colony). A linear regression model suggested an average increase of 0.3 °C in ambient temperature for every population density increase of 500 human inhabitants per km².

The Human Population Density Index (HDI) was estimated by combining data from the Central Bureau of Statistics (CBS) for the Israeli population (updated to 2021) [46] with Palestinian Authority population data (updated to 2017) [47]. Population density estimates (used as a proxy for urbanization) were made within a 5-km and 15-km radius around each colony using the QGIS software (QGIS 2023 Version 3.16). Areas in the Mediterranean Sea were excluded. We chose these two ranges (5 and 15 km) because they represent typical foraging ranges of urban and rural bats, respectively [22]. Moreover, there was a high correlation (Pearson correlation R > 0.92; see Additional file 1: Table S5) between the two parameters, making it likely that any other radius in between would yield similar results. Extending the radius to the maximum foraging range of these bats (~ 50 km) would simply equalize the density of colonies (which were within 50 km from each other).

Statistics

We combined data from all sampling years together in the models. We tested the differences in female parturition times and pup growth in urban and rural colonies using generalized linear mixed effect models (GLMMs with fit method of Maximum Pseudo-likelihood). The bat colonies were characterized both categorically (urban vs. rural) and according to the human population density at a 5-km radius and a 15-km radius around the bat colony. We fitted GLMMs, testing all three urbanization parameters (separately), and found that while the models with human population density at 15 km had the best fit for most tests according to the Akaike information criterion (AIC), this was only slightly better than the categorical urban/rural model. We therefore present the results for both the 15-km density model and the urban/rural categorical model. To account for differences in sampling time in the different colonies along the season, we added the sampling date—defined as the number of days from December 1 (irrespective of year) as a fixed factor. The sampling year was another fixed factor. The colony’s ID was included as a random effect. We additionally compared all models to their null model (with only the intercept) and found that for the two reproductive status parameters (reproductive state and reproductive yield), the null model had the best fit. All analyses were performed in MATLAB R2021b.