Cultural niche construction of repertoire size and learning strategies in songbirds
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- Creanza, N., Fogarty, L. & Feldman, M.W. Evol Ecol (2016) 30: 285. doi:10.1007/s10682-015-9796-1
Birdsong is a complex cultural and biological system, and the selective forces driving evolutionary changes in aspects of song learning vary considerably among species. The extent to which repertoire size, the number of syllables or song types sung by a bird, is subject to sexual selection is unknown, and studies to date have provided inconsistent evidence. Here, we propose that selection pressure on the size and complexity of birdsong repertoires may facilitate the construction of a niche in which learning, sexual selection, and song-based homophily may co-evolve. We show, using a review of the birdsong literature and mathematical modeling, that learning mode (open-ended or closed-ended learning) is correlated with the size of birdsong repertoires. Underpinning this correlation may be a form of cultural niche construction in which a costly biological trait (for example, open-ended learning) can spread in a population (or be lost) as a result of direct selection on an associated cultural trait (for example, song repertoire size).
KeywordsBirdsong Learning Niche construction Sexual selection Evolution Culture
Amid a cacophony of environmental sounds, juvenile songbirds can reliably learn a species-specific song. In general, male birdsong has the functions of territory defense and mate attraction, and learning these songs is a costly process (Catchpole and Slater 2003; Nowicki and Searcy 2004). The song control system in the brain of vocal learners is a network of discrete, interconnected neural circuits with two primary pathways, one for song learning and one for song production (Nottebohm et al. 1976, 1990; Scharff and Nottebohm 1991; Brenowitz et al. 1997). By decreasing the resources available for brain development, nutritional and developmental stress in the nest can lead to deficits in this song system (MacDonald et al. 2006; Schmidt et al. 2013) and thus in song learning. Therefore, learned song can be a reliable indicator of a male’s fitness potential (Nowicki et al. 1998a; Nowicki and Searcy 2004) and general cognitive capacity (Boogert et al. 2008, 2011; Templeton et al. 2014). Early-life stresses can lead to perceptible differences in song repertoire size (Nowicki et al. 2000), the amount of song produced (Buchanan et al. 2003), song complexity (Spencer et al. 2003, 2004; Soma et al. 2006), and learning accuracy (Holveck et al. 2008). The effects of early development on song can be reflected in sexual selection and fitness; for example, female swamp sparrows (Melospiza georgiana) prefer the songs of males that had exhibited faster growth as nestlings (Searcy et al. 2010).
Although songs are learned, birds often exhibit unlearned predispositions for the kinds of songs they learn. For example, swamp sparrows (M. georgiana), when raised in isolation and exposed to various recorded and manipulated songs, learned only songs composed of swamp sparrow syllables (Marler and Peters 1977). Further, juvenile white-crowned sparrows (Zonotrichia leucophrys) could be ‘tricked’ into learning the syllables of other species when the manipulated playbacks began with a white-crowned sparrow whistle, indicating that this initial syllable may act as a cue to alert the bird that the syllables that follow should be learned (Soha and Marler 2000). In a discussion of the unlearned aspects of this learned behavior, Peter Marler suggested that “[i]n the evolution of birdsong there is tension between selection pressures to develop along species-specific lines and pressures to systematically or opportunistically develop novel behaviors” (Marler 1984).
The balance between these pressures can differ dramatically from species to species. In certain species, more accurately learned songs (Melospiza melodia, Nowicki et al. 2002) or more species-typical songs (M. georgiana, Lachlan et al. 2014) elicited more mating displays from females. However, in other species, such as the great reed warbler (Acrocephalus arundinaceus), females in natural settings preferred males with larger repertoires (Catchpole 1986). Larger repertoire sizes have also been associated with larger song control areas in the brain (Devoogd et al. 1993; Szekely et al. 1996), with increased testosterone levels (Van Hout et al. 2012), with polygynous species compared to monogamous ones, and with increased migratory behavior across species (Read and Weary 1992). As well as general features of songs and song repertoires, specific elements of a song can also be under selection: in a long-term study of Savannah sparrows (Passerculus sandwichensis), certain syllable types were associated with reproductive success, and these increased in frequency over time (Williams et al. 2013). Further, the song features that are the least variable within a species might be salient cues for species recognition, although the level of support for this “invariant feature hypothesis” (Marler 1960) depends on the species studied (Emlen 1972; Nelson 1989; Dabelsteen and Pedersen 1992; Shackelton et al. 1992).
In addition to this tension between selection for accurately learned or species-typical song and selection for complex songs, different learning programs are exhibited by different songbird species. Species with age-limited or closed-ended learning, such as zebra finches (Taeniopygia guttata, Zann 1990) and song sparrows (M. melodia, Marler and Peters 1987), crystallize their song repertoires at a relatively early age, whereas species with open-ended learning, such as northern mockingbirds (Mimus polyglottos, Howard 1974) and European starlings (Sturnus vulgaris, Buchanan et al. 2003), are capable of learning new song elements throughout their lives. In certain species, a larger repertoire size in males has been shown to correspond to earlier pairings and an increased number of offspring (e.g. Howard 1974; Catchpole 1980), indicating that repertoire size could be under strong sexual selection. In some cases, this earlier pairing allowed birds to produce an additional clutch of offspring (Price et al. 1988), corresponding to a dramatic fitness benefit.
Homophily (assortative mating) based on song type is also thought to play an important role in evolutionarily important processes such as pre-mating isolation, mate recognition, and speciation. This kind of homophily or mating preference is a different form of sexual selection in that it does not involve one song type (such as a complex or a simple song); instead females may favor a familiar song based on early experience (Laland 1994). In two subspecies of captive zebra finches (T. guttata guttata and T. guttata castanotis), cross-fostered females preferred the song of the foster father’s subspecies, demonstrating assortative mating according to song type (Clayton 1990). For example, the songs of male medium ground finches (Geospiza fortis) resemble their fathers’, and their songs differ quantitatively from songs of the sympatric species, the cactus finch (G. scandens). In the former species, females avoid mating with males that sing a heterospecific song, with very rare exceptions that generally have a behavioral explanation, such as the death of the father before song learning can take place (Grant and Grant 1996). In other species of Darwin’s finches, Grant and Grant (1989) observed similar patterns of transmission from fathers to sons, with females showing a preference for their fathers’ song types in potential mates. Grant and Grant (1989, 1992, 1996) concluded that song type was an important factor in species recognition and mate choice, with rare mistakes potentially leading to interspecific hybridization.
Evolutionary feedback between learning strategies and repertoire size may have been facilitated by sexual selection and homophily in songbirds. To study this possibility, we develop an age-structured model of gene-culture niche construction that is based on a model described by Creanza et al. (2013). This framework produces feedback between homophily, sexual selection, and learning strategies when song learning is costly. We are particularly interested in whether the presence of a costly cognitive ability for open-ended learning can increase in frequency in a population through sexual selection for the increase in song repertoire size that this learning can facilitate. Conversely, if sexual selection favors small repertoire size and effective learning, we may see the fixation of closed-ended learning, or selection may favor an extra chance to learn the correct song accurately. This represents a form of cultural niche construction whereby a costly biological trait (open-ended learning) can hitchhike to high frequency (or be removed from the population) due to an associated cultural trait that is under direct selection (Rendell et al. 2011).
To investigate the relationship between repertoire size and open- or closed-ended learning programs in songbirds, we performed a quantitative review of the literature on birdsong learning and adapted the model described by Creanza et al. (2013) to account for unique features of songbird learning, such as sexual selection favoring either accurate learning of species-typical songs or large song repertoires and song complexity (Howard 1974; Catchpole 1986; Nowicki et al. 2002a; Lachlan et al. 2014).
The study of birdsong often faces a “unit problem,” since different researchers define “repertoire size” by different criteria. For example, repertoire size has been defined as the number of song types, strophe or phrase types, syllable types, or note types, taking account of the features of particular songs that are most salient for the specific species studied (Macdougall-Shackleton 1997). For this study, we used syllable repertoire size as the unit because it is relevant both for birds with short songs of few repeated elements and for birds with long strings of variable elements.
We performed a literature search for data on repertoire size and learning programs using the terms “syllable repertoire” and “syllable repertoire size” combined with “bird,” “birdsong,” “song,” or “oscine.” This yielded the individual papers cited in Appendix 1 as well as two papers that compiled data on syllable repertoire size (Moore et al. 2011 and Szekely et al. 1996). We then performed another literature search for those species with available syllable repertoire size data, combining the Latin or common species names with the key terms “open-ended,” “closed-ended,” “adult learning,” “song plasticity,” “sensitive period,” “crystallization,” and “crystallized song” to determine the learning mode for each species. The resulting papers were categorized according to features of the studies and species they described. For example, some studies that reported open-ended learning recorded the difference in repertoire size between first-year birds and second-year or older birds, but did not record further changes in repertoire size throughout the life of the birds. These studies, noted in Appendix 1, could not eliminate the possibility that these birds crystallized their song after their second year and so might have experienced a kind of extended learning that may or may not have been truly open-ended.
We also reviewed studies on species that were known to “overproduce” song elements (Marler and Peters 1982; Nelson et al. 1996). Juveniles in these species learn more song elements than necessary and crystallize one particular song, which may follow the local song dialect or match their neighbor’s song after migration and before mating. Species with this type of closed-ended learning are also noted in Appendix 1.
To account for phylogenetic relationships when analyzing repertoire size and learning mode, we sampled 1000 trees for the subset of species listed in Appendix 1 from the avian phylogeny assembled by Jetz et al. (2012, data available at birdtree.org), rooted with Sayornis phoebe as an outgroup. We generated a consensus topology with the ‘consense’ function in PHYLIP (Felsenstein 1989). We then performed a phylogenetic ANOVA (Garland et al. 1993) implemented with the ‘phytools’ R package (Revell 2012) to compare the distribution of repertoire sizes between the two groups (open-ended and closed-ended learners) while controlling for the phylogenetic relationships between species. This test determines the significance of the ANOVA with an empirical null distribution, generated by simulating 100,000 times the evolution of (log10-transformed) syllable repertoire size along the tree with a Brownian motion algorithm.
To investigate possible evolutionary mechanisms that may facilitate or explain an association between repertoire size and learning mode, we analyzed a mathematical model that treats repertoire size as a selectively advantageous culturally transmitted trait and investigated a possible cultural niche-constructive relationship between learning mode, song homophily (assortative mating), and this repertoire size. With this modeling framework, we tracked the spread of the repertoire size trait denoted by T, with alternative forms, T, representing a relatively large, complex repertoire, and t, representing a relatively limited or simple repertoire. Two other dichotomous traits influence the evolution of T: a trait, S, that determines the learning program used by an individual, with S representing open-ended learning and s representing closed-ended learning, and a trait, M, that determines the rate at which females preferentially mate with males of a certain repertoire size, with M representing a preference for a song she heard early in life (i.e. the T state she inherited from her father) and m representing random mating. Haploid genetic structure is modeled for simplicity.
To investigate the evolution of a simple and idealized system of open- or closed-ended learning, we introduced an age-structured model in which there are two available learning opportunities: one as a juvenile and one as an adult. Individual birds can learn from their parents as juveniles only (closed-ended learning) or can learn from their parents and continue to learn, after they mature, from the population as a whole (a simplified version of open-ended learning). These learning differences depend on the form of the S trait. Here, we represented learning early in life as occurring primarily from parent to offspring, although it is known that a juvenile’s repertoire is often influenced by other nearby adults (Baptista and Morton 1988; Williams 1990; Beecher et al. 2007). This vertical transmission represents learning of repertoire size, not necessarily particular syllables, so it could also be conceptualized as a form of imprinting in which the juvenile learns from the father the length of a species-typical song.
Vertical transmission probabilities for T, S and M
Second, open-ended learners (S, represented by the frequencies x1, x2, x5, and x6) have another chance to learn T or t as adults, through horizontal or oblique learning from randomly chosen members of the population at large (see Eq. 3 below). Closed-ended learners (s, represented by the frequencies x3, x4, x7, and x8) do not have the opportunity to change their T state after the initial vertical learning step. Note that a smaller repertoire (t) can be transmitted by oblique learning, depending on its frequency in the parental generation. We used numerical iteration to explore the dynamics of the evolutionary system across a wide range of parameter values.
Large repertoire favored: σT > 0
TSM, TSm, TsM, Tsm
tSM, tSm, tsM, tsm
Small repertoire favored: σt > 0
TSM, TSm, TsM, Tsm
tSM, tSm, tsM, tsm
Using initial pheno-genotype frequencies near fixation of tsm (x1 = 0.011, x2 = 0.012, x3 = 0.013, x4 = 0.01, x5 = 0.015, x6 = 0.014, x7 = 0.016, x8 = 0.909), we introduced large repertoires (T), open-ended learning (S), and homophily (M) at low frequency, and the system was numerically iterated for 100,000 timesteps or until the pheno-genotype frequencies (xi) reached equilibrium, which almost always occurred in many fewer timesteps. Finally, we made the assumptions that there can be cultural mutation between T and t when bT→T and bt→t are not equal to 0 or 1 (Table 1) and that a short or simple repertoire (t) can be more easily learned by a juvenile bird than a long or complex repertoire (T): bt→t > bT→T. In other words, a juvenile whose father or tutor has a smaller repertoire (t) will only rarely produce a larger repertoire (T), perhaps through copy error, improvisation, or eavesdropping (Beecher et al. 2007; Sober and Brainard 2012). However, a juvenile whose father/tutor has a large repertoire (T) might, with a larger probability (1– bT→T > 1– bt→t), learn a smaller repertoire (t) than his tutor, perhaps because of the challenges of learning a large repertoire or because he was not exposed to his father’s entire repertoire (Botero et al. 2008). Since some closed-ended learners are known to learn song elements obliquely early in life (e.g. Baptista and Morton 1988; Liu and Nottebohm 2007), we note that the vertical transmission here denotes repertoire size learning, not necessarily transmission of particular syllables, and so could represent a form of imprinting where a juvenile vertically learns characteristics of a species-typical song.
There is a clear relationship between the mode of learning employed by a bird species and the size of its reported syllable repertoire. In Fig. 1, the repertoire sizes from the review of published data described above are plotted on a log scale and grouped by learning program. We found a significant difference in repertoire size distributions between open- and closed-ended learners even when accounting for phylogenetic relationships (phylogenetic ANOVA, F = 52.97, p = 4 × 10−5). Thus there is an association between open-ended learning and large repertoire sizes, warranting further investigation into the effects of, for example, phylogenetic distance and life history traits.
When σt was positive and σT = 0, individuals with t had higher fitness than their T counterparts with larger complex repertoires. It is useful to imagine that larger repertoires here represent a collection of new or learned sounds picked up through mistakes in learning or in song recognition. In this case, a small set of specific song elements (t) was favored. When open-ended learning allowed a second chance to learn and was not too costly (σt > 0, ε = 0.05), S was driven to high frequency along with the favored song, t, when selection (σt) and oblique transmission (γ) were both strong (Fig. 3c). However, if continuing to learn was more expensive (ε = 0.1), S did not rise in frequency even when selection (σt) and oblique transmission (γ) were both strong, and a smaller repertoire (t) was found at high frequency along with closed-ended learning (s) for all values of σt and γ (Fig. 3d); this was also the case if bt→t = 1. These results suggest that if continuing to learn is very costly, we should expect to see that sexual selection for a trait that is relatively easy to learn as a juvenile should lead to the fixation of closed-ended learning (Fig. 3d). Conversely, if a trait is relatively difficult to learn initially but strongly favored, selection for the trait should facilitate the spread of open-ended learning (Fig. 3a–b).
Cultural niche construction occurs when one or more cultural traits can alter the evolutionary pressures on other cultural or genetic traits; models of cultural niche construction can incorporate, for example, fitness effects, mating preferences, cultural transmission differences, and age-structured learning (Odling-Smee et al. 2003; Ihara and Feldman 2004; Creanza et al. 2012, 2013; Fogarty et al. 2013). The literature on niche construction in birds has focused primarily on foraging and nest-building behaviors (Tebbich et al. 2001; Odling-Smee et al. 2003; Jones et al. 1996; Harrison and Whitehouse 2011). Previous models have explored various aspects of avian song learning and its evolution: the origin (Aoki 1989) and maintenance (Lachlan and Slater 1999) of vocal learning itself, the preservation of dialects (Planqué et al. 2014), the restrictiveness of “innate learning preferences” (sensu Marler 1990; modeled in Lachlan and Feldman 2003), and the effect of the song learning program on song divergence and male dispersal (Ellers and Slabbekoorn 2003). Other theoretical work has investigated the influence of song learning on evolutionary processes, including the link between learned song and male quality (Ritchie et al. 2008; Lachlan and Nowicki 2012), as well as the effects of song learning on the evolution of brood parasitism (Beltman et al. 2003), on speciation after colonizing a new niche (Beltman et al. 2004), and on population divergence in allopatric and sympatric contexts (Lachlan and Servedio 2004; Olofsson and Servedio 2008; Olofsson et al. 2011; Rowell and Servedio 2012). Here, we have proposed a model for the interactions between three traits that may be important in songbird evolution: the culturally transmitted trait of song repertoire size, the capacity for song learning in adulthood, and mating preference for a song heard early in life. These traits can indeed influence one another in this theoretical evolutionary framework, sometimes in complex ways.
First, we explored the association between sexual selection for a large repertoire size and the spread of open-ended learning. Maintaining the neural circuitry for song learning into adulthood can allow a bird to increase its repertoire size but is hypothesized to be costly; we observed a tradeoff in the effect of this cost. The rate of adult song learning (γ), which can help a bird acquire an attractive repertoire, had a nonlinear relationship with the fitness advantage (σT) necessary for open-ended learning to spread in a population. In other words, if adult song learning is very effective (large γ) at increasing repertoire size, the sexual selection pressure on large repertoires (σT) does not need to be as strong for the benefits of open-ended learning to outweigh its costs (Fig. 3).
The fidelity of transmission of a large repertoire to juveniles (bT→T). and the sexual selection for a large repertoire (σT) also interacted in a nonlinear way to shift the balance of costs and benefits of open-ended learning (Fig. 5). As juveniles learn more effectively (increased bT→T), the benefits of open-ended learning outweigh the costs under weaker selection for a large repertoire (decreased σT) and open-ended learning (S) approaches fixation in the population; however, if birds can very easily learn a large repertoire as juveniles, open-ended learning ceases to have an advantage. The benefit of being able to learn as an adult seems most likely to outweigh its cost when a large repertoire is favored by sexual selection but cannot be easily learned as a juvenile. Juveniles have been tutored by an adult tutor in captivity in only a few species of open-ended learners; European starlings (S. vulgaris) learned 62–76 % of their tutor’s repertoire with twelve weeks of exposure, and canaries (S. canarius) raised with a tutor from the juvenile stage until sexual maturity learned 76–91 % of their tutor’s repertoire. In contrast, in the closed-ended learners studied (e.g. T. guttata, M. georgiana), juveniles are assumed to be capable of imitating the complete syllable repertoire of the tutor, and learning accuracy can be measured by comparing the fine-scale properties of sound spectrograms from full pupil and tutor songs (Tchernichovski et al. 2001; Nowicki et al. 2002b). For both open- and closed-ended learners studied, tutoring with few syllables led the pupil to have a very limited repertoire, but birds tutored with abnormally large repertoires only learned species-typical repertoire sizes (Kroodsma and Canady 1985; Clayton 1989; Airey et al. 2000; Tchernichovski et al. 2001). The exception to this pattern is open-ended learners that improvise most of their syllable repertoire (Kroodsma et al. 1997; Leitner et al. 2002); these species are capable of producing a species-typical repertoire in isolation and are not within the scope of the current model.
Homophily, incorporated here as a female’s preference (α) for males that sing a song of the type she remembers hearing as a juvenile, can also shift the balance between the cost (ε) of adult learning and the benefit (σT) of learning a selectively advantageous song, thus enhancing the spread of open-ended learning with a smaller fitness advantage of large repertoire size, reduced effectiveness of adult learning, increased open-ended learning cost, and a larger range of juvenile learning rates (Fig. 6). In these simulations (Figs. 3, 4, 5, 6, 7 and 8), the populations displayed variation in repertoire size (both T and t present) but approached fixation for either S, open-ended learning, or s, closed-ended learning (except in certain cases with very high homophily); this is consistent with field and laboratory studies of songbird species.
In at least some species, song is a reliable indicator of male fitness, and different aspects of song are thought to be under sexual selection pressure in different species (Macdougall-Shackleton 1997; Nowicki et al. 1998b). Examining the broad phylogenetic distribution of both large and small repertoires, Macdougall-Shackleton noted that “selection has probably acted both to increase and to decrease repertoire size to different degrees in different lineages” (1997). Likewise, while less well studied, open- and closed-ended learning may appear in closely related branches of the oscine songbird lineage (Appendix 1).
Evidence that repertoire size is under selection is somewhat inconsistent. Under laboratory conditions, females offered the choice between two songs will often pick the more complex one, but this preference does not necessarily hold in a natural setting (Searcy and Marler 1984; Searcy 1992). Evidence from field tests of song repertoire size preference in female birds has not pointed to a consistent effect of repertoire size (Searcy 1992; Byers and Kroodsma 2009; Soma and Garamszegi 2011). However, one source of these apparent conflicts may be that the learning program of the species studied was not taken into account. For example, species surveyed by Searcy (1992) that showed earlier pairing dates for males with larger repertoires were open-ended learners (Howard 1974; Catchpole 1980), and species that showed no relationship between pairing date and repertoire size were closed-ended learners (Krebs et al. 1978; Searcy 1984; but see Reid et al. 2004). Thus, sexual selection based on repertoire size might interact with learning programs and learning modes in natural populations.
With this in mind, it may be necessary to take account of these learning modes and the length of the sensitive period for learning in studies of mate choice, honest signaling, and species recognition. Our model hints at an evolutionary interaction that can be tested in future field studies and evolutionary analyses. In addition, this model could be extended to account for more learning scenarios. For example, in the case of avian species that are capable of prolific mimicry, the oblique learning step of a juvenile or adult would not be constrained to members of its own species. This learning step would therefore depend not only on the repertoires of conspecifics but also on the diversity of ambient sounds. Further, our current framework of open- and closed-ended learning does not discriminate between species that can increase their repertoire size throughout life and species that are capable of adult learning only until their second year. In future work, our model could be modified to include mimicry of interspecific sounds and additional learning steps.
The model presented here is, of course, a simplified representation of a very complex process, but it demonstrates that culturally transmitted song can be a niche-constructing trait, influencing the spread of other traits that are likely to have genetic underpinnings, such as those that affect neural development and mating preferences. The niche-constructed selection pressures on a bird’s song can shift the balance between the costs of maintaining the neural architecture for adult song learning and the benefits of increasing repertoire size with age and experience.
This work was supported in part by the Morrison Institute for Population and Resource Studies, the John Templeton Foundation to N.C. and M.W.F., and a 2020 Science Fellowship at UCL to L.F. We thank the organizers and participants of the Frontiers in Niche Construction workshop at the Santa Fe Institute for stimulating discussions.
|Funder Name||Grant Number||Funding Note|
|John Templeton Foundation|
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