Egyptian fruit bats (Rousettus aegyptiacus) manage to survive and flourish in a large geographic range despite the variability of natural and anthropogenic conditions in this range. To examine the challenges faced by free-ranging R. aegyptiacus living at the northern edge of their distribution, we performed a retrospective analysis of ~1500 clinical cases reported by a bat rescue NGO over 25 months, from all over Israel. All cases of injured or stranded bats were evaluated and categorized according to date, place, sex, age, and etiology of the morbidity. The analysis of the data showed an increase in all types of morbidity during the wintertime, with more than twice the number of cases in comparison with the summertime, over two consecutive years. Moreover, we found that the number of abandoned pups peaks during spring till autumn when adult morbidity is minimal. We characterize two prominent types of previously undescribed morbidity in R. aegyptiacus, one in the form of bacterial illness, and the other associated with feet deformation which affects bats in addition to major anthropogenic-related threats related to synanthropic predators. We analyze the reasons driving winter morbidity and conclude that winter weather and specifically low temperature best explains this morbidity. We hypothesize that R. aegyptiacus, a fruit-bat of tropical origin is facing major seasonal difficulties near the northern edge of its distribution, probably limiting its further spread northward.

For decades, researchers have speculated how echolocating bats deal with masking by conspecific calls when flying in aggregations. To date, only a few attempts have been made to mathematically quantify the probability of jamming, or its effects. We developed a comprehensive sensorimotor predator-prey simulation, modeling numerous bats foraging in proximity. We used this model to examine the effectiveness of a spectral Jamming Avoidance Response (JAR) as a solution for the masking problem. We found that foraging performance deteriorates when bats forage near conspecifics, however, applying a JAR does not improve insect sensing or capture. Because bats constantly adjust their echolocation to the performed task (even when flying alone), further shifting the signals' frequencies does not mitigate jamming. Our simulations explain how bats can hunt successfully in a group despite competition and despite potential masking. This research demonstrates the advantages of a modeling approach when examining a complex biological system.

To examine the challenges faced by free-ranging Rousettus aegyptiacus living at the northern edge of their distribution, we performed a retrospective analysis of 2196 clinical cases reported by a bat rescue NGO over a period of 36 months, from throughout Israel. All cases of injured bats were evaluated and categorized according to date, place, sex, age, and etiology of the morbidity. The data analysis revealed an increase in all types of morbidity during the wintertime, with more than two-fold the number of cases per week compared to in the summer, over three consecutive years. Moreover, we found that the number of abandoned pups peaked during spring and summer, when adult morbidity is minimal. We characterized two prominent types of previously undescribed morbidities in R. aegyptiacus. We also employed GPS tracking to monitor the movement and foraging of dozens of bats, and to examine the potential correlates of elevated winter morbidity. Our results suggest that it is mainly harsh weather that drives the observed winter morbidity, with food limitations playing a minor-role. We hypothesize that R. aegyptiacus, of tropical origin, is facing major seasonal survival difficulties near the northern edge of its distribution, probably limiting its spread further northwards still.

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6For decades, researchers have speculated how echolocating bats deal with acoustic 7 interference created by conspecifics when flying in aggregations. It is thus surprising that 8 there has been no attempt to quantify what are the chances of being jammed, or how such 9 jamming would affect a bat's hunting. To test this, we developed a computer model, 10 simulating numerous bats foraging in proximity. We used a comprehensive sensorimotor 11 model of a hunting bat, taking into consideration the physics of sound propagation and bats' 12 hearing physiology. We analyzed the instantaneous acoustic signals received by each bat, and 13 were able to tease apart the effects of acoustic interference and of direct resource 14 competition. Specifically, we examined the effectiveness of the spectral Jamming Avoidance 15 Response -a shift in signal frequencies -which has been suggested as a solution for the 16 jamming problem. As expected, we found that hunting performance deteriorates when bats 17 forage near conspecific. However, applying a Jamming Avoidance Response did not improve 18 hunting, and our simulations clearly demonstrate the reason: bats have adequate natural 19 signal variability due to their constant adjustment of echolocation signals to the task. The 20 probability to be jammed is thus small and further shifting the frequencies does not mitigate 21 spectral jamming. Our simulations reveal both negative and positive insight: they show how 22 bats can hunt successfully in a group despite potential sensory interference and they suggest 23 that a Jamming Avoidance Response is not useful. 24 A: One Bat Scenario B: Five Bats Scenario Figure 1: Examples of individual and group hunting of the simulated bats (also see 85 supplementary movie). (A)A single simulated bat flying in the arena with 5 prey items. The 86 bat detects two prey items and decides to pursue the closest one (moth a). Panel 1 shows the 87 trajectories of the bat (black) and the moths (blue), the positions of each emitted signal (green 88 dots), and the location of the capture (black cross). Panel 2 shows the bat's velocity (gray), 89 the distance (black) and relative angle (blue) to target. Panel 3 shows the bat's received 90 acoustic scene for the section marked by a gray dashed line, including the envelopes of the 91 following signals: the transmitted signals (black), the received prey echoes (green), and the 92 received masking signals (red). Panel 4 shows a spectrogram of the same segment as in panel 93 3. Note how the signals' frequency drops at the final terminal buzz. (B) Three bats (out of five 94 in the arena) hunting in an environment with 10 moths. Bat 1 detects and pursues a moth, 95 while conspecifics (bats 2 and 3) fly nearby, emitting echolocation signals some of which mask 96 (or jam) the echoes received by bat 1. Instances of jamming are marked with red diamonds in 97 (3) (2)