I remember you; Experimental evidence of true acoustic individual recognition in a wild passerine.

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I remember you; Experimental evidence of true acoustic individual recognition in a wild passerine.

https://doi.org/10.21203/rs.3.rs-3376567/v1

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True individual recognition refers to an animal's ability to recognise at least one unique feature of another individual. Demonstrating this in animals equivocally can be difficult, as it requires confounding variables such as location, kinship or familiarity to be carefully controlled. This is problematic, as a poor understanding of how individual recognition operates limits our understanding of pathways that shape intelligence, sociality, and cooperation in taxa. Noisy miners (Manorina melanocephala) are a highly social bird that exhibits multiple cooperative behaviours accompanied by functionally referential vocal signals, providing an ideal model for studying recognition. We employed an adapted habituation-discrimination paradigm to experimentally demonstrate true individual recognition in miners, as a receiver’s habituation to a calling individual transferred across different social contexts. This was observed in wild birds that were not subject to any additional training, and exhibited even by receivers exposed to novel signallers. These findings have significant implications for understanding the mechanisms underlying avian cooperation and cognition in complex animal societies, and indicate that recognition in this species is likely based on individual vocal characteristics.

Earth and environmental sciences/Ecology/Behavioural ecology

Earth and environmental sciences/Ecology/Evolutionary ecology

Biological sciences/Evolution/Social evolution

Cooperation can often seem counterintuitive, as individuals may sacrifice their own fitness to support the offspring of others (McDonald et al. 2009) or to alert neighbours of threats (Kokolakis et al. 2010). The benefits that arise from cooperative interactions, both direct (Rutte & Taborsky 2007) and indirect (Clutton-Brock 2009), are believed to come at a cost - they likely favour the selection of larger brains that are metabolically expensive (Ashton et al., 2020). Consequently, most hypotheses proposed to explain cooperative behaviour share a commonality: potential donors would maximise their fitness benefits by reliably discriminating between different groups of potential recipients and adjusting their level of aid provided accordingly (Komdeur 2006). For instance, donors may choose to aid a reliable neighbour over one that has failed to cooperate in recent interactions, as observed in pied flycatchers (Ficedula hypoleuca, Krams et al. 2008).

Differentiation has been successfully studied in a range of taxa, from social spiders such as the amblypygid (Damon diadema, Walsh & Rayor 2008), to mammals like primates (Seyfarth & Cheney 1990) and odontocets (Kershenbaum et al. 2013). However, in cooperative systems, true individual recognition (TIR) is required to maximise benefits from a given level of help (Tibbetts & Dale 2007). This is particularly relevant in complex societies where social relationships can change rapidly (Rios & Kraenkel 2017) or within fission-fusion systems where the composition of the group frequently changes (Parra et al. 2011), precluding simpler mechanisms of discrimination such as familiarity being used to identify favourable groups to aid.

Despite the expected benefits of TIR, controversy has arisen regarding the exact definition and detection of TIR in animals (Steiger & Müller 2008). For instance, the capability of individual recognition was once believed to exist in over 27 species of songbirds that could discriminate between different classes of individuals (Stoddard 1996). However, a refined definition of TIR (Tibbetts & Dale 2007) suggests that these results can be explained as a form of "class-recognition" rather than true recognition of a specific individual (Ward & Webster 2016).

To further understanding of TIR in complex social species, we investigated communication in the noisy miner (Manorina melanocephala) a honeyeater endemic to Australia that is known for the negative impact of its cooperative mobbing behaviour on other bird populations (Maron et al. 2013). Noisy miners occur in relatively large colonies, comprising up to 100 individuals (Dow 1970), engaging in cooperative activities that include social foraging, mobbing (facilitated by terrestrial alarm calls), and aerial alarm call signalling to warn of overhead predators (Holt et al. 2017). Therefore, noisy miners provide an opportunity to investigate true individual recognition, as they possess a complex vocal repertoire with functionally referential alarm calls (Farrow et al. 2017) that are individually distinctive allowing individuals to differentiate between individuals for both terrestrial (McDonald 2012) and aerial alarm calls (Farrow et al. 2020). This makes them an ideal species for testing whether this differentiation extends to true individual recognition.

Social context of vocalisations broadcast did not impact receiver performance

Responses of subjects receiving aerial alarm call exemplars during the habituation

phase did not significantly differ from responses from subjects hearing terrestrial alarm call exemplars during the habituation phase (χ²_2.3 = 604.94, p = 0.1255). Consequently, analyses combined responses of subjects across both social contexts for simplicity. Across all Groups (A-D), subjects demonstrated habituation to Signaller A through a significant decrease in responsiveness from Call 1 to Call 23 across the Habituation Phase (Groups A & B; z-score = 3.93, p = 0.002: Groups C & D; z-score = 5.52, p < 0.001). However, upon hearing the Discrimination test call (call 24) all subjects resumed exhibition of a response towards the speakers, indicating through dishabituation that birds in Groups A and B were successfully differentiating between Signaller A and Signaller B (z-score = -1.191, p = 0.90), as well as between Groups C and D (z-score = 0.784, p = 0.987). Habituation to Signaller A was not lost following dishabituation, with all subjects maintaining habituation (i.e. lowered responses statistically similar to final call in Habituation Phase) upon hearing the Rebound call (Groups A & B; z-score = 3.292, p = 0.172: Groups C & D; z-score = -1.005, p = 0.953).

Noisy Miners demonstrated true individual recognition

Once individual differentiation was tested in the paradigm, subjects received

exemplars of a new context (Groups A & C = aerial: Groups B & D = terrestrial) to that used during the Habituation Phase, Test and Rebound calls. In Groups A and B habituation to Signaller A was maintained regardless of the Transference call context, with subjects having significantly lower responses to when they heard Signaller A’s Call 1 in the Habituation Phase (z-score = -7.702, p < 0.001; Figs. 1a & 1b). Conversely, when subjects in Groups C and D heard the Transference call from Signaller B they responded statistically similar to Call 1 in the Habituation Phase (z-score = -0.737, p = 0.990; Figs. 3c & 3d) indicating they were yet to assign a reliability status to Signaller B and therefore continued responding.

Groups A and B dishabituated during the Attending test call (z-score = 3.292, p = 0.172), as well as Groups C and D (z-score = -1.005, p = 0.953; Figs. 1c & 1d) thus indicating that birds were still attending to the vocalisations and had instead ceased responding (Groups A & B) due to the perceived unreliability of Signaller A.

In this study, we have demonstrated the ability of noisy miners to exhibit true individual recognition (TIR) by assessing their responses to referential signals in an experimental setting without the need for a training phase. We observed that the reliability status of a signaller can be transferred from one vocalisation type to another, even when the receiver is naïve to the identity of the signaller and has not previously heard any vocalisations from that particular bird. Further, consistent with previous findings, our test subjects were able to differentiate between different signallers producing the same vocalisation type. These results highlight two important aspects of the noisy miner signalling system. First, noisy miners are capable of discriminating between individuals based solely on the spectral features of their calls across at least two vocalisation contexts, suggesting that the species does not rely on learned vocal templates. Second, our experiment provides empirical evidence that the species habituates to the signaller rather than the signal alone, as receivers did not simply habituate to all aerial alarm call signallers once habituated to that call type of a given individual, but rather showed habituation to the specific individual producing the alarm calls used in the habituation sequence, maintaining this habituation across into a different social context. This occurred in the absence of any real threat being observed, and included transitions from terrestrial to aerial alarms calls and vice versa, despite aerial alarms calls typically indicating an increased threat level in the miner system that provokes a fleeing response (Farrow et al. 2017). Our experimental demonstration of habituation transfer from one call type to another from the same signaller suggests that receivers may reduce their attention to signallers that exhibit poor reliability, given that all alarm calls in this experiment were broadcast in the absence of a predator. Collectively, these results provide unequivocal evidence that noisy miners possess the capacity for true individual vocal recognition among the acoustic signals tested, which is the first demonstration of this ability in an avian species (see Brecht & Nieder 2020 for a review).

The ability to utilise TIR is likely a highly adaptive trait that enables individuals to maximise their fitness within the social system of noisy miners. It facilitates cooperative behaviour being preferentially directed towards individuals that offer the greatest fitness returns to a receiver (Clutton-Brock 2009. The bell miner (Manorina melanophrys), a congener of the noisy miner, has been shown to preferentially provide help to kin based on increasing levels of relatedness and call similarity (McDonald & Wright 2011). Similar decision-making processes involving TIR may operate in the noisy miner system, and further exploration of this possibility is warranted now that we have established the species' ability to attend to individual information encoded in vocal signals.

Acoustic communication plays a crucial role in species inhabiting visually obstructed environments like the woodland patches (Debus 2008) and urban environments (Catterall 2004) that noisy miners occupy. In such environments, vocal communication is essential for facilitating activities among cooperative conspecifics (Perez et al. 2015). Additionally, dense vegetation or artificial structures, such as buildings, may select for increased vocal communication as a means of providing protection to signallers compared to open environments (Mays et al. 2006). Consequently, due to the regular distance between individuals throughout the day, acoustic communication is likely the most efficient means of transferring information for miners, although the possibility of TIR occurring through other sensory modalities such as olfactory or visual systems may also be possible.

The capacity to discriminate between individuals through TIR may also enable receivers to identify the number of individuals participating in vocal communication, as proposed by Blumstein (2004), benefiting the receiver in two ways. Firstly, the presence of multiple signallers producing the vocalisation presumably increases the reliability of the information being conveyed (Dutour et al. 2021). Secondly, in mobbing events, the more signallers present, the safer it is for the receiver to engage in vocal communication or mobbing behaviour (Wheatcroft & Price 2018). When only a single individual vocalises, the receiver's response is potentially based on the message being transferred (Cheney & Seyfarth 1988) and/or the perceived reliability and relationship (kin or non-kin) of the signaller to the receiver (Komdeur 1994).

Modulating responses to signallers based on a reliability assessment of the given signaller may initially incur costs for receivers (Blumstein et al. 2004). However, over the long-term, reducing responses to unreliable individuals may ultimately be the most efficient strategy, particularly when considering the costs associated with responding to unreliable signallers, such as the energetic requirements of locomotion or lost opportunities to feed (Giraldeau et al. 2002). As noisy miners maintain their own activity spaces within colonies (Dow 1979), they are regularly in visual isolation from conspecifics so facilitating cooperation through vocal interactions potentially fosters individual variation in vocal signals. When coupled with the ability of receivers to attend to individual vocal signatures, this signalling system greatly enhances an individuals' ability to maximise their fitness during cooperative interactions within a colony be selectively attending to a specific individual’s calls.

Although the social brain hypothesis has primarily been studied in primates, our findings suggest that increased sociality can also drive cognitive abilities in avian species. Previous research has primarily focused on corvids and parrots due to their tool use and vocal learning capacities, respectively (Olkowicz et al. 2016; Medina-García 2015). However, our study clearly demonstrates that noisy miners, a phylogenetically distant passerine species, possess a highly complex cognitive prowess associated with the observed TIR of vocal signals. This finding provides further evidence for the potential link between increased levels of sociality and the complexity of cognition, suggesting that the latter is not purely a by-product of phylogenetic relationships.

In conclusion, our study provides unequivocal evidence that noisy miners possess the ability for TIR mediated through acoustic variation in alarm signals, which imposes high cognitive demands not yet described in any other avian species and rarely demonstrated in other taxa groups. The presence of TIR in this system facilitates the reduction of costs associated with responding to unreliable signallers while enabling receivers to maximise the benefits associated with providing help in one of the most complex avian systems known.

Source of test subjects

Adult noisy miners (n = 32) were caught using mist nets from four locations near Armidale, New South Wales, Australia: Roumalla Creek TSR (30°25'28.56"S 151°11'37.14"E, n = 6), the University of New England Armidale campus (30°29'04.1"S 151°38'28.6"E, n = 8), Burying Ground Creek TSR (30°32'47.5"S 151°46'07.7"E, n = 7) and a privately owned property near Argyle (30°33'17.5"S 151°51'18.3"E, n = 10) from July 2020 – May 2021. These sites were selected to ensure naivety of test subjects as locations were a minimum of 14 km apart in linear distance (more than 100 times further than average home range of this species, Higgins et al. 2001). All sites consisted of dry, open woodland vegetation with a large eucalypt overstory and sparse understory vegetation, except for the privately-owned property where regeneration efforts have led to relatively dense understory vegetation (LF personal observations).

After capture, birds were transported back to the University of New England Armidale campus and housed individually in a 76- x 45- x 45-cm cage with 30 mL of Wombaroo Nectivore wet-mix (Wombaroo Food Products, Glen Osmond SA, Australia) and supplied twice daily in conjunction with ad libitum madeira cake and mealworms (Tenebrio molitor). All individuals were left overnight under natural light conditions to habituate to holding conditions prior to the commencement of trials. Experimental trials were conducted between 0800h – 1600h, with individuals housed for no longer than three consecutive nights prior to release. Individuals housed in the same room were always from the same colony and were therefore already familiar with each other. Birds housed together from the same colony were released as a group at their point of capture during periods of benign weather with at least two hours of daylight remaining.

Ethics statement

Ethics approval was granted by the University of New England’s Animal Ethics Committee (AEC20-032), with no injuries or deaths recorded during the experiment. Banding of caught individuals was conducted under license SL100314 provided by the National Parks and Wildlife Service, using bands supplied by and in accordance with protocols approved by the Australian Bird and Bat Banding Scheme (authority A2259).

Playback procedure

Calls used during the playback procedure were obtained by Farrow et. (2020) with all call exemplars used being unfamiliar (temporally separated) to subjects in order to avoid past experience impacting responses. Vocalisations from signallers used in experiments were recorded from colonies located at Dumaresq Dam (30°30’S, 151°40’E) and the University of New England Newholme Field Research Station (30°25’24’’S; 151°38’38’’E). Only signallers that had been fitted with unique leg colour band to allow for identification were used, ensuring that recordings could be assigned to a specific signaller without ambiguity. Additionally, only those signallers that had a minimum of 25 different calls from each call type were used in the playback experiment to avoid pseudo-replication impacting results. Consequently, this allowed for 11 signallers at Dumaresq Dam and 10 signallers from Newholme Field Research Station.

Subjects were placed within a 76- x 45- x 45-cm cage located within a sound booth (Acoustical Design PL, Blackburn South, Australia) to ensure subjects were reacting to broadcast sounds only. The sound booth was regulated at temperatures between 18–25℃, with each cage having a single wooden perch to control the orientation of perched birds. Wet food (Nectivore wet mix, Wombaroo, Glen Osmond, South Australia) and madeira cake were supplied ad libitum during the experimental trials, with feeders washed and replenished between test subjects. Vocalisations were played via one of two speakers (Advent AV570, Advent, Cambridge, MA) connected to an iMac (2015 model, EL Capitan, Apple Inc, Cupertino, CA) and placed at either end of the holding cage perpendicular to the single perch. This ensured that all individuals were a similar distance from either speaker, with playback randomly assigned to each side to account for any hearing biases (McDonald 2012).

Each subject heard the same number of stimuli, with calls presented at 30 second intervals. Subjects were monitored via an overhead camera (Panasonic HC-V270) placed on a Manfrotto tripod (MKCOMPACTLT – BK Compact Light 4 Section Tripod) that allowed an observer in the adjacent room to monitor real-time behaviour without disturbing subjects. Any birds deemed to be exhibiting behaviours linked to high stress levels, such as excessive movement or gular fluttering, were planned to be excluded from the experiment and treated accordingly, however this was not required. Subject responses during the experimental period were recorded and this footage used to score responses as outlined below.

Playback method consisted of a given subject being exposed to a new call exemplar broadcast at natural volume (89dB, Holt et al. 2017) every 30s following the procedure depicted in Fig. 2. Rarely, if a subject was distracted when a call was due to be broadcast, for example moving in the cage, playback of that specific exemplar was delayed slightly until the subject was back in a stationary position on the central perch. This was assessed by viewing video footage in real time, and only involved a delay or several seconds at most.

Broadly, playback involved a “Habituation Phase” where the subject was exposed to 23 different exemplars of the same call type (either aerial or terrestrial contexts) from the same signaller (Signaller A). A 24th “Test” call of the same call type as in the Habituation Phase was then played, however this time the exemplar broadcast was from a new signaller (Signaller B). Call 25 in the series was the “Rebound” call, which was used to control for any false-positive responses potentially observed in the Test call exemplar (McDonald 2012) and, as such, was a new exemplar of the same context as the Habituation Phase from Signaller A. The 26th call in the series was the “Transference” test and was of the alternate context to the call used in the habituation phase (i.e. if terrestrial calls were played during habituation phase, call 26 would be of aerial alarm context). Importantly, to confirm that responses seen to these transferred calls were true indications of transferred status of the signaller (and thus TIR), half the subjects received the transference call from the signaller to which they had habituated (Signaller A; Groups A & B) and half received the transference call from the signaller to which they had not habituated (Signaller B; Groups C & D). Doing so, we reasoned that if subjects in Groups A and B maintained habituation when hearing the transference call from Signaller A in a new context, and subjects in Groups C and D dishabituated if hearing Signaller B in a new context, this would be empirical evidence of TIR. Finally, the 27th call was the “Attending” test call, which was of a new context (fledgling begging “chip” call) also from a new signaller (Signaller C). The Attending test call was used to ensure subjects were still attending to calls and any lowered responses observed in prior signals were part of the experimental procedure and not a change in the subject’s attention. As such, any subjects not dishabituating when hearing this call would have been dropped from the analysis, however again this was not necessary as all subjects responded to the Attending test call exemplar.

Response scoring

Final Cut Pro version 10.5.2 (Apple Inc., Cupertino, CA) was used to strip audio from the footage and cut samples into smaller videos of a single playback call and its response (using the audio waveform to identify when each exemplar was broadcast). These edited sequences were renamed randomly using the inbuilt Mac OS Finder tool and saved without audio to ensure that observers were blind to the exemplar context when scoring sequences.

Due to the difficulty of determining gaze direction, we used the method deployed in past experiments that investigated differentiation of signallers (McDonald 2012; Farrow et al. 2017; Farrow et al. 2020) to measure the most informative responses in playbacks to this species, which were: 1) initial time to first respond (a head turn > 5 ° without the body moving) to the signal (measured in 24 frames per second), 2) degree to which the head moved in response to the signal and 3) duration of this initial head turn (fps). Degree of head turn was measured by Pixel Stick version 2.16.2 (Plum Amazing Software LLC).

Statistical Analyses

All statistical analyses were conducted in R (Version 4.0.3 for Mac OS X GUI, R Core Team 2021), with the measured responses log-transformed to generate normal distributions before they were reduced with a principal component analysis (PCA). Only one component had an eigenvalue above 1 (PC1 = 1.61), and this component accounted for 79% of the variance in the data set. PC1 loaded most heavily and positively on the measures “response time” (0.591) and “duration of the initial head-turn” (0.351). Consequently, PC1 was treated as the dependent variable in a generalised linear mixed model (GLMM), with a Gaussian link function using the package “lme4” to assay the fixed effect of “Stimulus type”, a seven-level factor that corresponded to the playback stages of interest; the first (call 1), middle (call 12) and last call within the Habituation Phase (call 23), the Test call (call 24), the Rebound test (call 25), the Transference test (call 26) and the Attending test (call 27). The fixed factors of “context” (aerial or terrestrial alarm call) and treatment (whether call 26 was from the Habituation Phase Signaller A or the Test call Signaller B) were also tested. All two-way and the three-way interactions between stimulus type, context and treatment were also included. Additionally, two random terms were included as potentially confounding covariates: 1) source colony (3 levels) of the subject and 2) subject identity to account for repeated measures of a subject.

Likelihood Ratio Tests (LRT; package “lme4”, Bates et al. 2015) were used to determine the significance of dropping terms from the model, starting with the three-way interaction. Planned post-hoc comparisons comparing individual levels of interest in main effect of stimulus type were then carried out using Estimated Marginal Means (emmeans and emmip; using package “emmeans”, Lenth 2021). No formal adjustments were made to alpha levels to account for multiple testing, with p values presented unaltered instead for the reader to assess.

Arnold, K. E., Owens, I. P., & Goldizen, A. W. (2005). Division of labour within cooperatively breeding groups. Behaviour, 142(11-12), 1577-1590.
Ashton, B. J., Kennedy, P., & Radford, A. N. (2020). Interactions with conspecific outsides as drivers of cognitive evolution. Nature Communications, 11(1), 1-9.
Barati, A., Andrew, R. L., McDonald, P. G. (2021). Nestling sex does not influence provisioning effort of parents or helpers in a cooperative bird with a male-biased helper contingent, Behavioral Ecology and Sociobiology, 75(6), 1-11.
Barrickman, N. L., & Lin, M. J. (2010). Encephalization, expensive tissues, and energetics: an examination of the relative costs of brain size in strepsirrhines. American Journal of Physical Anthropology, 143(4), 579-590.
Bates, D., Maechler, M., Bolker, B., Walker, S. (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1-48. doi: 10.18637/jss.v067.i01.
Blumstein, D. T., Verneyre, L., & Daniel, J. C. (2004). Reliability and the adaptive utility of discrimination among alarm callers. Proceedings of the Royal Society of London. Series B: Biological Sciences, 271(1550), 1851-1857.
Bogonovich, M. (2011). Intelligence's likelihood and evolutionary time frame. International Journal of Astrobiology, 10(2), 113.
Brecht, K. F., & Nieder, A. (2020). Parting self from others: individual and self-recognition in birds. Neuroscience & Biobehavioral Reviews.
Catterall, C. P. (2004). Birds, garden plants and suburban bushlots: where good intentions meet unexpected outcomes. Urban Wildlife: more than meets the eye, 21-31.
Cheney, D. L., & Seyfarth, R. M. (1988). Assessment of meaning and the detection of unreliable signals by vervet monkeys. Animal Behaviour, 36(2), 477-486.
Clark, J. A., & Leung, J. (2011). Vocal distinctiveness and information coding in a suboscine with multiple song types: eastern wood-pewee. The Wilson Journal of Ornithology, 123(4), 835-840. doi:10.1676/11-059.1
Clarke, M. F., & Oldland, J. M. (2007). Penetration of remnant edges by noisy miners (Manorina melanocephala) and implications for habitat restoration. Wildlife Research, 34(4), 253-261.
Clutton-Brock, T. (2009). Cooperation between non-kin in animal societies. Nature, 462(7269), 51-57.
Debus, S. J. (2008). The effect of noisy miners on small bush birds: an unofficial cull and its outcome. Pacific Conservation Biology, 14(3), 185-190.
Dow, D. D. (1970). Communal behaviour of nesting Noisy Miners. Emu-Austral Ornithology, 70(3), 131-134.
Dow, D. D. (1979). Agonistic and spacing behaviour of the noisy miner Manorina melanocephala, a communally breeding honeyeater. Ibis, 121(4), 423-436.
Dutour, M., Kalb, N., Salis, A. & Randler, C. (2021). Number of callers may affect the response to conspecific mobbing calls in great tits (Parus major). Behavioral Ecology and Sociobiology, 75(2), 1-8.
Englert, A. C., & Greene, M. J. (2009). Chemically-mediated roostmate recognition and roost selection by Brazilian free-tailed bats (Tadarida brasiliensis). PLoS One, 4(11), e7781.
Farrow, L. F., Barati, A., & McDonald, P. G. (2020). Cooperative bird discriminates between individuals based purely on their aerial alarm calls. Behavioral Ecology, 31(2), 440-447.
Farrow, L. F., Doohan, S. J., McDonald, P.G. (2017). Alarm calls of a cooperative bird are referential and elicit context-specific antipredator behavior. Behavioural Ecology, 28(3), 724-731.
Giraldeau, L. A., Valone, T. J., & Templeton, J. J. (2002). Potential disadvantages of using socially acquired information. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 357(1427), 1559-1566.
Higgins, P. J., Peter, J. M. & Steele, W. K. (eds) 2001. Handbook of Australian, New Zealand and Antarctic Birds. Volume 5. Tyrant-Flycatchers to Chats, pp. 626–650, Melbourne, Australia: Oxford University Press.
Holt, J., Barati, A., McDonald, P. G. (2017). The complex acoustic repertoire of a highly social species, the noisy miner, Manorina melanocephala. Emu, 117(1), 19-30.
Jacobs, I. F., Osvath, M., Osvath, H., Mioduszewska, B., von Bayern, A. M., & Kacelnik, A. (2014). Object caching in corvids: incidence and significance. Behavioural processes, 102, 25-32.
Kershenbaum, A., Sayigh, L. S., & Janik, V. M. (2013). The encoding of individual identity in dolphin signature whistles: how much information is needed? PLoS ONE, 8(10).
Komdeur, J. (1994). The effect of kinship on helping in the cooperative breeding Seychelles warbler (Arcocephalus sechellensis). Proceedings of the Royal Society of London. Series B: Biological Sciences, 256(1345), 47-52.
Komdeur, J. (2006). Variation in individual investment strategies among social animals. Ethology, 112(8), 729-747.
Lenth, R. V. (2021). emmeans: Estimated Marginal Means, aka Least-Squares Means. R package version 1.6.1. https://CRAN.R-project.org/package=emmeans
Maron, M., Grey, M., Catterall, C. P., Major, R. E., Oliver, D. L., Clarke, M. F., Loyn, R. H.,
MacNally, R., Davidson, I. & Thomson, J. R. (2013). Avifaunal disarray due to a single despotic species. Diversity and Distributions, 19(12), 1468-1479.
Mays, H. L., Yao, C. T., & Yuan, H. W. (2006). Antiphonal duetting in Steere’s liocichla (Liocichla steerii): male song individuality and correlation between habitat and duetting behavior. Ecological Research, 21(2), 311-314.
McDonald, P. G., Kazem, A. J., & Wright, J. (2009). Cooperative provisioning dynamics: fathers and unrelated helpers show similar responses to manipulations of begging. Animal Behaviour, 77(2), 369-376.
McDonald, P. G., & Wright, J. (2011). Bell miner provisioning calls are more similar among relatives and are used by helpers at the nest to bias their effort towards kin. Proceedings of the Royal Society B: Biological Sciences, 278(1723), 3403-3411.
McDonald, P. G. (2012). Cooperative bird differentiates between the calls of different individuals, even when vocalizations were from completely unfamiliar individuals. Biology Letters, 8(3), 365-368.
McDonald, P. G., Rollins, L. A., & Godfrey, S. (2016). The relative importance of spatial proximity, kin selection and potential ‘greenbeard’ signals on provisioning behaviour among helpers in a cooperative bird. Behavioral ecology and sociobiology, 70(1), 133-143.
Medina‐García, A., Araya‐Salas, M., & Wright, T. F. (2015). Does vocal learning accelerate acoustic diversification? Evolution of contact calls in Neotropical parrots. Journal of Evolutionary Biology, 28(10), 1782-1792.
Olkowicz, S., Kocourek, M., Lučan, R. K., Porteš, M., Fitch, W. T., Herculano-Houzel, S., & Němec, P. (2016). Birds have primate-like numbers of neurons in the forebrain. Proceedings of the National Academy of Sciences, 113(26), 7255-7260.
Parra, G., Corkeron, P., & Arnold, P. (2011). Grouping and fission-fusion dynamics in Australian snubfin and Indo-Pacific humpback dolphins. Animal behaviour, 82(6), 1423- 1433.
R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/
Rios, V. P., & Kraenkel, R. A. (2017). Do I know you? How individual recognition affects group formation and structure. PloS one, 12(1), e0170737.
Rolando, A., & Zunino, M. (1992). Observations of tool use in corvids. Ornis Scandinavica, 23(2), 201-202.
Rutte, C., & Taborsky, M. (2007). The influence of social experience on cooperative behaviour of rats (Rattus norvegicus): direct vs generalised reciprocity. Behavioral Ecology and Sociobiology, 62(4), 499-505.
Seyfarth, R. M., & Cheney, D. L. (1980). The ontogeny of vervet monkey alarm calling behavior: a preliminary report. Zeitschrift fur Tierpsychologies, 54(1), 37-56.
Seyfarth, R., & Cheney, D. (1990). The assessment by vervet monkeys of their own and another species alarm calls. Animal Behaviour, 40(4), 754-764.
Steiger, S., & Müller, J. K. (2008). ‘True’ and ‘untrue’ individual recognition: suggestion of a less restrictive definition. Trends in Ecology & Evolution, 23(7), 355.
Stoddard, P. K., (1996). Vocal recognition of neighbors by territorial passerines. In: Ecology and evolution of acoustic communication in birds (Kroodsma DE, Miller EH, eds). Ithaca, New York: Cornell University Press; 356-374.
Tibbetts, E. A., & Dale, J. (2007). Individual recognition: it is good to be different. Trends in ecology & evolution, 22(10), 529-537.
Walsh, R. E., & Rayor, L. S. (2008). Kin discrimination in the amblypygid, Damon diadema. The Journal of Arachnology, 36(2), 336-343.
Ward, A., & Webster, M. (2016). Mechanisms: social recognition and social organisation. In Sociality: The Behaviour of Group-Living Animals (pp. 9 – 27). Springer, Cham.
Wheatcroft, D., & Price, T. D. (2018). Collective action promoted by key individuals. The American Naturalise, 192(4), 401-414.

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I remember you; Experimental evidence of true acoustic individual recognition in a wild passerine.

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Abstract

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Introduction

Results

Social context of vocalisations broadcast did not impact receiver performance

Noisy Miners demonstrated true individual recognition

Discussion

Methods

Source of test subjects

Ethics statement

Playback procedure

Response scoring

Statistical Analyses

References

Additional Declarations

Status:

Version 1