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Social foraging in vampire bats is predicted by long-term cooperative relationships

['Simon P. Ripperger', 'Department Of Evolution', 'Ecology', 'Organismal Biology', 'The Ohio State University', 'Columbus', 'Ohio', 'United States Of America', 'Smithsonian Tropical Research Institute', 'Balboa']

Date: 2021-09

Stable social bonds in group-living animals can provide greater access to food. A striking example is that female vampire bats often regurgitate blood to socially bonded kin and nonkin that failed in their nightly hunt. Food-sharing relationships form via preferred associations and social grooming within roosts. However, it remains unclear whether these cooperative relationships extend beyond the roost. To evaluate if long-term cooperative relationships in vampire bats play a role in foraging, we tested if foraging encounters measured by proximity sensors could be explained by wild roosting proximity, kinship, or rates of co-feeding, social grooming, and food sharing during 21 months in captivity. We assessed evidence for 6 hypothetical scenarios of social foraging, ranging from individual to collective hunting. We found that closely bonded female vampire bats departed their roost separately, but often reunited far outside the roost. Repeating foraging encounters were predicted by within-roost association and histories of cooperation in captivity, even when accounting for kinship. Foraging bats demonstrated both affiliative and competitive interactions with different social calls linked to each interaction type. We suggest that social foraging could have implications for social evolution if “local” within-roost cooperation and “global” outside-roost competition enhances fitness interdependence between frequent roostmates.

Funding: This study was funded by grants of the National Science Foundation (Integrative Organismal Systems #2015928; GGC; https://www.nsf.org/ ), of the Deutsche Forschungsgemeinschaft ( https://www.dfg.de/ ) within the research unit FOR-1508, a Smithsonian Scholarly Studies Awards grant (GGC, SPR; https://www.si.edu/ ), and a National Geographic Society Research Grant WW-057R-17 (GGC; https://www.nationalgeographic.com/ ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

To evaluate evidence for these scenarios, we tested whether nightly foraging departures and encounters were predicted by kinship, roosting associations based on 2 levels of proximity (during the previous day or over the whole study), and rates of social grooming, food sharing, and co-feeding in captivity. To document roosting associations and foraging encounters, we analyzed social encounter data from proximity sensors placed on 50 free-ranging common vampire bats. As additional predictors for 23 of these bats, we used published long-term rates of social grooming and food sharing [ 23 ] and co-feeding rates from when these bats were captive. Using simultaneous ultrasonic recording and infrared (IR) video, we also describe a distinct new type of vampire bat call only observed during hunting interactions. Multiple lines of evidence show that cooperative relationships in vampire bats extend outside the roost. More generally, our findings illustrate how social relationships and networks can both extend and vary across contexts.

For the same roosting association networks, each scenario predicts different outcomes for how preferred within-roost relationships correlate with co-departures or encounters during foraging. Preferred roostmates (shown as pair of light brown and dark brown bats) might either (A) not coordinate their behavior outside the roost, (B) coordinate only their departures, (C) depart independently and reunite during foraging, (D) coordinate departures and foraging, or (E) avoid foraging together. Alternatively, the bats could (F) depart and forage as a large group.

Here, we assessed the relative evidence for a range of hypothetical scenarios that vary in degree of coordination of social foraging among socially bonded bats ( Fig 1 ). In the simplest case, preferred roostmates might not coordinate their behavior outside the roost. If instead bats optimize individual foraging efficiency by preferentially departing, following, or foraging with their preferred roostmates, then within-roost networks should predict co-departures or foraging encounters. Alternatively, to maximize their collective search area, bats might prefer to forage with bats outside their network of cooperative relationships and actually avoid foraging with their frequent roostmates. If so, within-roost and outside-roost networks should be negatively correlated. Finally, if entire roosting groups forage together, then we expect similarly dense and highly correlated within-roost and outside-roost networks.

Social foraging can take many forms, from mere aggregations of individuals attracted to a common resource to coordinated foraging groups with differentiated roles. Socially hunting species can be placed on a spectrum of resource sharing from individual foragers competing to group-level sharing [ 3 ]. The form of social foraging and the scale of competition over resources outside the roost can have implications for the evolution of food-sharing relationships. Several evolutionary models of vampire bat food sharing as multilevel selection view them as foraging individually then sharing food at the group level [ 18 – 20 ], but this view contrasts with evidence that food-sharing relationships within groups are reciprocal and highly differentiated [ 11 , 21 ]. An alternative possibility is that individualized relationships drive both within-roost resource sharing and social hunting. This hypothesis is not mutually exclusive with group hunting, because even if individuals forage in groups, specific pairs could be more likely to compete or share a wound or host [ 14 – 16 , 22 ].

Food-sharing relationships in vampire bats form as preferred associates escalate social grooming [ 13 ]. These preferred associations and cooperative interactions occur within the day roost. However, little is known about if or how cooperative relationships extend beyond the roost. For example, foraging with socially bonded roostmates might increase efficiency in searching for prey or feeding from wounds, but it remains unclear if or how vampire bats perform social hunting. Several authors provide anecdotal evidence for groups of females apparently flying together, adult females departing roosts in groups of 2 to 6, and groups arriving together at a pasture or approaching and circling prey [ 14 – 17 ]. There are also observations of up to 4 individuals feeding simultaneously from different wounds on the same cow [ 14 ] or pairs feeding on the same wound [ 14 , 16 ]. Wilkinson [ 16 ] described evidence that mother–daughter pairs co-forage and share wounds, but found no evidence that frequent roostmates forage together.

Socializing and foraging are 2 key determinants of reproduction and survival that can influence each other in several interesting ways. Preferred social relationships can drive foraging decisions (e.g., great tits [ 1 ]). Conversely, shared foraging behaviors might shape how relationships form (e.g., bottlenose dolphins [ 2 ]). Social relationships can determine access to food because closely affiliated individuals can peacefully co-feed at a food patch, hunt together [ 3 ], cooperatively defend food patches (e.g., [ 4 – 6 ]), or even give food to less successful foragers (e.g., chimpanzees [ 7 ]). Access to food is therefore one benefit of long-term cooperative relationships, i.e., stable preferred associations that involve cooperative investments such as grooming and food sharing. For example, grooming in chacma baboons promotes tolerance during foraging [ 8 ], and vervet monkeys strategically groom individuals that control access to food due to social dominance [ 9 ] or an experimentally manipulated ability to access food [ 10 ]. A particularly clear nonprimate example of cooperative relationships providing food occurs in common vampire bats where females regurgitate ingested blood to socially bonded kin and nonkin that failed to feed that night [ 11 , 12 ].

Methods

Subjects Subjects were common vampire bats (Desmodus rotundus) including 27 wild-caught adult females that were tagged and released and 23 previously captive females (17 adults and their 6 subadult captive-born daughters) that had spent the past 21 months in captivity and were then tagged and released back into their wild roost tree (see [13,23]). See S1 Text for details.

Kinship We assumed that known mother–daughter pairs had a kinship of 0.5. To estimate kinship for all other pairs, we genotyped bats at 17 polymorphic microsatellite loci (DNA isolated via a salt–chloroform procedure from 3- to 4-mm biopsy punch stored in 80 or 95% ethanol), then used the Wang estimator in the R package “related.” See S1 Text for details.

Past cooperative interaction rates in previously captive bats To measure cooperative relationships in the previously captive bats, we used previously published rates of social grooming and food sharing from experimental fasting trials [13]. See S1 Text for details. To assess tolerance while feeding, we also analyzed observations of co-feeding among the same captive vampire bats. Social interactions were observed at blood spout feeders while the bats were in captivity, including 1,300 competitive interactions and 277 cases of co-feeding where 2 bats were observed feeding from the same blood spout at the same time (from 1,050 hours of observation from 70 nights). In 201 of these cases, both bats were clearly identified. We used these to construct a co-feeding network of the number of dyadic co-feeding events (range = 0 to 6) for each pair. To test correlations between the captive co-feeding network and networks of food sharing or social grooming, we used Mantel tests. To test the same correlation while controlling for overlap in individual feeding times, we also used a custom double permutation test [24]. This procedure calculates an adjusted co-feeding rate for each pair as the difference between the observed co-feeding rate and the median expected co-feeding rate from 5,000 permutations of the co-feeding bat identities, permuted among the bats seen within each hour. To test for preferred captive co-feeding partners, we also used the same within-hour permutations to test if social differentiation in co-feeding (the coefficient of variation in co-feeding rates) was greater than expected from the null model.

Association rates in the wild using proximity sensors We placed custom-made proximity sensors on all 50 female common vampire bats (sensor mass: 1.8 g; 4.5% to 6.9% of each bat’s pre-feeding mass) that automatically documented dyadic associations among all 50 tagged bats when those come within the reception range of 5 to 10 m [23,25]. To log encounters, each proximity sensor broadcasted a signal every 2 seconds to update the duration of each encounter. We used 1 second as the duration of encounters that were shorter than 2 successive signals (i.e., encounters shorter than 2 seconds). The maximum signal strength of each encounter is used as an estimate for a minimum proximity between 2 tagged bats during the encounter by comparing the signal intensity to a calibration curve [23,25,26]. We collected association data on the free-ranging bats at Tolé, Panama (8° 12′ 03″ N 81° 43′ 46″ W), a rural area that is mainly composed of cattle pastures for meat production. Around 200 to 250 common vampire bats roosted inside a hollow tree on a cattle pasture that was about 15 ha in size. To create a stable food patch during part of our study, we corralled approximately 100 heads of cattle at a distance of approximately 300 m from the roost from 6 PM until 6 AM between the evening of September 21 until the morning of September 26, 2017 (days 1 to 5 in our study). Before and after that time period, the cattle were ranging freely. A neighboring, much larger pasture west of the roost had about 1,500 heads of cattle within a distance of 1 to 2 km (Fig A in S1 Text). To construct networks of roosting association rates during each daytime period within the roost, we relied on roosting association data that had been used in a previous study [23]. Based on the same 2 thresholds of signal strength as before, we defined 2 categories of proximity: “associations” (within approximately 50 cm) and “close contacts” (within approximately 2 cm). Roosting network edges were rates of within-roost association or close contact, i.e., the total time 2 bats spent in association per unit of time. See S1 Text for details. To help localize bats, we used base stations that can detect tagged bats at distances of about 150 m. We placed these stations at the roost and at 5 other locations in the surrounding cattle pastures to help localize individuals and encounters as inside or outside the roost. To identify departures from the roost, we found the points in time where each bat lost connection from the roost base station and almost all of the many tagged bats in the colony within communication range (i.e., a sudden drop in associations from many bats down to 0 to 3 bats; see [25]). Some departing bats also contacted base stations on the cattle pasture (Fig A in S1 Text). We used the same kind of data to infer the return times to the roost for each bat and night. Of the 629 dyadic encounters that occurred 1 minute after leaving the roost and 1 minute before arriving at the roost, we excluded 43 encounters from further analysis, because a proximity sensor contacted the roost base station, suggesting that those encounters occurred while bats were roosting at the entrance or on the outside of the roost tree. The remaining 586 encounters occurred farther away, outside the communication range of the roost base station, and we refer to these as “foraging encounters.”

Observing interactions of foraging vampire bats At Tolé, we only observed 2 occasions where 2 bats stopped at the monitored cattle pasture and were associated (for 3.5 and 4.6 minutes). When releasing the corralled cattle in the morning, we observed bite marks. However, to avoid changing their behavior, we did not get close enough to the cattle at night to record audio or video of bats interacting. To collect direct observations on foraging behavior, we therefore recorded simultaneous audio and video of bat foraging behavior at a different farm near La Chorrera, Panama (8° 52′ 42″ N 79° 52′ 05″ W) using an IR spotlight, IR-sensitive video camera (Sony AX53 4K camcorder), and an Avisoft condenser microphone (CM16, frequency range 1 to 200 kHz) and digitizer (Avisoft USG 116 Hbm, 1,000 kHz sampling rate, 16-bit resolution) connected to a notebook computer. One observer (SPR) moved with a herd of about 20 grazing cattle without visible light, only using the viewfinder of the IR camera. To compare social calls made during foraging with calls from inside a roost, we used the same recording equipment to record social calls from a roost only a few hundred meters from the foraging site at La Chorrera.

Acoustic analysis of calls in foraging bats We used Avisoft SASLab Pro (Raimund Specht, Avisoft Bioacoustics, Glienicke/Nordbahn, Germany; version 5.2.13) to measure acoustic parameters of the social call types. Start and end of calls were determined manually, based on the oscillogram. Subsequently, 5 acoustic parameters were measured automatically: 1 temporal (duration) and 4 spectral parameters (peak frequency at maximum amplitude, minimum and maximum frequency, and bandwidth). Acoustic parameter extraction was restricted to the fundamental frequency. Spectrograms were created using a Hamming window with 1024-point fast Fourier transform and 93.75% overlap (resulting in a 977 Hz frequency resolution and a time resolution of 0.064 ms). To estimate the frequency curvatures of the different call types, we measured the spectral parameters at 11 different locations distributed evenly over the fundamental frequency of each call. To compare call structure from different contexts (roosting versus foraging and antagonistic versus affiliative behavior) in multivariate space, we plotted the first 2 principal components after entering these measures into a principal component analyses with varimax rotation (using the “foreign” package in R).

Statistical analysis of foraging behavior To estimate foraging bouts, we calculated the periods when each bat was distant from the roost tree (S1 Fig). Then, to test whether the previously captive bats and never-captive control bats differed in their departure times and foraging bout durations, we fit linear mixed-effect models (LMMs) with type of bat and day as fixed effects and bat as a random intercept. We calculated p-values using Satterthwaite degrees of freedom method with the R package lmerTest. To compare consistency of onsets and durations, we measured the unadjusted repeatability (intraclass correlation coefficient or ICC) for each type of bat. To count how often tagged bats departed together, we counted and inspected cases where bats departed the roost within 1 minute of each other.

Preferred associations during foraging To test if repeated foraging encounters occurred among the same bats more than expected by chance, we used a permutation test that compared observed and expected social differentiation while controlling for overlap in foraging times. For social differentiation, we used the coefficient of variation in co-foraging rates, which increases when some pairs have more repeated encounters than others and decreases when all pairs have similar encounter rates. We first used a simple and conservative measure of co-foraging: counting the presence or absence of an encounter during each hour outside the roost over 9 days. These counts varied from 0 to 15. If 2 bats met twice in the same hour, this is still one encounter. We used this method because all bats were sampled evenly within each night and most foraging encounters were brief (median = 1 second). These present versus absent observations in each hour were swapped to randomize the data. Specifically, we permuted one bat in every dyad to a random possible partner that was also outside the roost during that same day and hour. By randomizing the data this way 5,000 times, we generated a null distribution of social differentiation values expected by chance.

Predictors of social foraging To test predictors of social foraging, we constructed foraging encounter networks where edges were based on either duration of total encounter time outside the roost (seconds) or number of days with foraging encounters (0 to 9 days). The latter response variable is far more conservative because it only counts repeats across different days. We included the following predictors: kinship, within-roost association rate, within-roost close contact rate, social-grooming rate, and food-sharing rate. We also tested the effect of dyad type (i.e., both bats previously captive, both bats never captive, one bat previously captive, or both bats captive-born juveniles). We did not use number of nights with foraging encounters as a response for tests that only included the previously captive bats, because 9 of these bats (including all captive-born bats) left the roost during the study period [23]. To test the effect of predictor networks on a response network, we used regression quadratic assignment procedure (QAP) for single predictors or multiple regression quadratic assignment procedure with double semi-partialling (MRQAP) for 2 predictors (using the “asnipe” R package [27]). To create null models, we used constrained (within-day) node label permutations. This approach is necessary for preserving the daily and nightly network structure (e.g., distribution of edges and edge weights) and for controlling for the presence or absence of bats in the roost each day. To control for foraging bout overlap in each pair, we included that measure as a covariate. We also used QAP to test whether the within-roosting association on each day predicted the subsequent foraging network that night. We then bootstrapped the mean of the slopes across the 8 days to test for an overall paired day–night effect.

Consistency of individual social traits To test whether bats that are more socially connected within the roost are also more connected in foraging networks, we tested if the nodes’ degree centrality was correlated between roosting and foraging networks. We measured degree centrality independently within each day or night network when the bat was present and then took the mean for each bat. Bats with no encounters in that day or night were considered missing for that day (i.e., not counted as zero degree). We fit general linear mixed effect models with foraging network centrality as the response variable, roosting network centrality (either association and close contact) as fixed effect, and bat as random intercept. p-Values were calculated from 5,000 permutations of the bat’s foraging centralities within each night (i.e., constrained node label permutations (within night) control for the fact that foraging and roosting network centralities could be correlated simply by some bats being present at the site longer). Throughout the results, we use “p-null” to indicate p-values that come from a null model where permutations were constrained within day. All data and R code are available on Figshare [28].

[END]

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