SINGING COMPLEXITY OF THE BANDED WREN (THRYOTHORUS PLEUROSTICTUS): DO SWITCHING RATE AND SONG-TYPE DIVERSITY SEND DIFFERENT MESSAGES?
Molles, Laura E
ABSTRACT.-
Most species of songbird possess repertoires of song types or variations that allow singers to vary how they present their songs. “Complexity,” or the amount of variation in a singing performance, has several distinct components that include the number of song types used, variation within song types, and rate of switching between song types. Because singers can control each factor somewhat independently, different components may encode different kinds of information. In a series of interactive playbacks, I presented Banded Wrens (Thryothorus pleurostictus) with stimuli that altered song-type diversity and switching rates independently. My results show that switching rates affect males’ aggressive approach responses, with lower switching rates eliciting stronger responses. By contrast, song-type diversity does not appear to affect males’ approach responses when switching rates are held at a high and constant level. Although focal male switching rates and song-type diversity are not strongly influenced by playback type, males frequently respond to high-diversity playback with delayed matches. Delayed matching entails using one or more of the same song types from the playback, without immediate song-type matching. Although delayed matches occurred at levels above chance during high-diversity playbacks, focal males appeared to avoid them during other types of playback; immediate matches were rare and repertoire matches frequent for all playback treatments. Overall, males’ responses to the three playback stimuli suggest that switching rate and song-type diversity encode different messages.
Received 8 November 2004, accepted 8 November 2005.
Key words: Banded Wren, repertoires, song-type diversity, song-type matching, switching, Thryothorus pleurostictus.
Complejidad del Canto de Thryothorus pleurostictus: ¿Envian Diferentes Mensajes las Tasas de Cambio y la Diversidad de Tipos de Canto?
RESUMEN.-La mayoría de las aves canoras poseen repertories con diferentes cantos o variaciones que les permiten variar la presentación de sus cantos. La “complejidad” o la cantidad de variación en un canto tiene varios componentes que incluyen el número de tipos de canto usados, la variaciín dentro de los tipos de canto y la tasa de cambio entre tipos de canto. Debido a que las aves que cantan pueden controlar cada factor de manera relativamente independiente, cada componente podría codificar diferentes tipos de información. En una serie de reproducciones de canto interactivas, sometí a individuos de Thryothorus pleurostictus a estímulos que alteraron de manera independiente la diversidad de los tipos de canto y sus tasas de cambio. Mis resultados muestran que las tasas de cambio afectan las respuestas de acercamiento agresivo, siendo las tasas de cambio más bajas las que producen las respuestas más fuertes. De modo contrario, la diversidad de tipos de canto no parece afectar las respuestas de acercamiento, al mantener las tasas de cambio altas y constantes. A pesar de que las tasas de cambio y diversidad de canto de los machos focales no están influenciadas por el tipo de reproducción, los machos respondieron frecuentemente a reproducciones de alta diversidad con cantos equivalentes desfasados. Los cantos equivalentes desfasados implican el uso de uno o más de los mismos tipos de canto reproducidos en la grabación, sin hacer coincidir el tipo de canto de manera inmediata. A pesar de que los cantos equivalentes desfasados ocurrieron más de lo esperado por azar durante la reproducción de cantos de alta diversidad, los machos focales parecieron evitarlos durante otro tipo de reproducciones. Las equivalencias inmediatas fueron raras y las equivalencias de repertorio fueron frecuentes para todos los tratamientos de reproducción. En general, las respuestas de los machos a los tres estímulos reproducidos sugieren que las tasas de cambio y la diversidad de tipos de canto codifican diferentes mensajes.
SONGBIRDS DIFFER WIDELY in their singing styles. These styles vary between species, within species, and even through a day in the life of an individual bird. Song-type repertoires, or sets of song types sung by individual males, are the basis for much variation in singing behavior. About 72% of species in which singing behavior has been examined sing more than one song or syllable type; most species, then, have the potential to communicate by varying the “complexity” of their singing performances (MacDougall-Shackleton 1997). “Complexity” can be measured in several ways, and components include the rate of switching among two or more song types, number of different song types used in a bout, and levels of within-song-type variation (Kroodsma and Verner 1978, 1987; Podos et al. 1992; Nowicki et al. 1994; Trainer and Peltz 1996). How male singers use complexity has been studied in a number of species (Catchpole and Slater 1995). Often, however, only one component of complexity is examined, and many analyses do not address the possibility that different components of singing complexity may encode different messages.
In many species, singers tend to increase complexity during male-male interactions (Vehrencamp 2000). Males of many wood-warbler (Parulidae) species typically increase switching rates or use more complex songs when interacting with other males (Staicer 1989, Spector 1992, Byers 1996). Male Western Meadowlarks (Sturnella neglecta) switch more often during chases and boundary interactions (Horn and Falls 1991), as do Song Sparrows (Melospiza melodia; Kramer and Lemon 1983), Northern Cardinals (Cardinalis cardinalis; Ritchison 1988), Tufted Titmice (Baeolophus bicolor; Duguay and Ritchison 1999), and Sedge Wrens (Cistothoms platensis; Kroodsma et al. 1999). Playback experiments have further demonstrated this tendency in Song Sparrows (Kramer et al. 1985, Stoddard et al. 1988, Nielsen and Vehrencamp 1995) and Carolina Wrens (Thryothorus ludovicianus; Simpson 1985). This increased complexity is predicted by several hypotheses: the “Beau Geste” (Krebs 1977), “habituation” (Hartshorne 1956), and “deceptive mimicry” hypotheses (Payne 1982). All three hypotheses predict roles for singing complexity in male-male competition. Although these theories predict that high complexity will give males a competitive edge, many species sing repetitively during singing bouts (Morton 1982). For example, bout length (which correlates with the number of repetitions of a song type before switching) increases in response to playback in Chaffinches (Fringilla coelebs; Riebel and Slater 2000). The key to resolving this apparent contradiction may lie in separating the components of singing complexity. Singing behaviors such as song-type diversity and switching rates can be altered independently in many species, and may send different messages to receivers. Additionally, both components of complexity may be affected by repertoire and song-type matching behavior, which can occur when part or all of the repertoire is shared among neighboring birds (Krebs et al. 1981, Simpson 1985, Morton and Young 1986, McGregor et al. 1992, Beecher et al. 1996, Duguay and Ritchison 1998, Burt et al. 2001, Otter et al. 2002).
Banded Wrens (T. pleurostictus) have songtype repertoires of moderate size (~20 song types per male) and alter switching rates and song-type diversity depending on context (Molles and Vehrencamp 1999). Banded Wrens also use unshared song types, repertoire matches, and immediate matches during territorial interactions (Molles and Vehrencamp 2001b). I used interactive playback to examine how Banded Wrens respond to changes in two components of singing complexity during a simulated male-male interaction. Switching rate and song-type diversity were varied independently to determine differences in males’ responses to each of these components. Male approach responses and singing behavior (switching rates; song-type diversity; and immediate, repertoire, and delayed matches) during playback periods were examined.
METHODS
Eighteen Banded Wren males in sector Santa Rosa of the Area de Conservation Guanacaste, Costa Rica, served as playback subjects. Habitat, neighborhoods, and methods for calculating repertoire size and overlap are described in Molles and Vehrencamp (1999). Focal males held territories in the Santa Rosa and Cerco de Piedra neighborhoods.
Songs for playback were recorded during dawn singing bouts using a Sennheiser MKH 816 or Audio-Technica AT 4071 directional microphone and a Tascam DA-Pl or Sony TCDD8 digital tape recorder. Songs were recorded from one territorial neighbor of each focal bird, to be played back from the shared boundary of the focal bird and the neighbor. I considered recordings suitable for use in playback if they were made within 15 m of the bird, if I did not hear the male noticeably interacting with a neighbor, and if there was minimal background noise. Suitable songs were digitized using the CANARY sound-analysis package (Charif et al. 1995) on an Apple PowerBook 1400. Unwanted noises (insects, other singers) were filtered out if necessary. In some cases, I amplified waveforms to ensure that all playback songs would be played at the same volume.
I conducted playbacks from 7 July to 21 August 1998, between 0615 and 0950 hours (post-dawn chorus). This period was during the breeding season, and males were at a variety of stages in the breeding cycle. All trials on a given bird were carried out within six days. Six of the 18 males heard two of their three treatments on the same day, separated by >30 min. All other males heard one treatment per day. Time of day varied for each subject’s three playbacks. Playback was performed interactively using SINGIT! (Bradbury and Vehrencamp 1994) on an Apple PowerBook 1400. Playback rate was approximately 1 song every 10 s, with an average of 18 songs played per trial; this rate is similar to that observed during natural singing bouts (L. E. Molles unpubl. data). Interactive playback allowed me to avoid overlapping focal birds’ songs, because overlapping may be an especially aggressive signal for some songbirds (Brindley 1991, Langemann et al. 2000). I did not alter playback diversity or switching rates in response to focal bird song. For all trials, the speaker was mounted in a parabola that was in turn placed on a tripod; this was done to minimize the volume of playback on the neighboring bird’s territory. I placed the speaker at the approximate territorial boundary between the focal bird and the test neighbor, to simulate a low-grade threat; playbacks that simulate invasions tend to trigger strong responses, regardless of the type of stimulus (Molles 1999). All trials consisted of a 3-min pre-playback monitoring period, 3 min of playback, and 6 min of post-playback monitoring. Playback began only when I knew the focal bird’s location, and when the boundarysharing neighbor (whose songs were being played) had been silent for at least one minute. I abandoned playback if the boundary-sharing neighbor sang during the playback period. Each male received three playback treatments in a randomly stratified order, so that each of the six possible presentation orders was represented at least twice among the males. All playback songs were recorded from the “appropriate” neighbor (the neighbor who shared the focal bird’s territorial boundary at the site of playback), and all song types were shared with the focal bird. Neighboring Banded Wrens have high levels of song-type sharing (Molles and Vehrencamp 1999), so most songs sung in natural bouts are shared types.
The trial types differed in song-type diversity and switching rate as follows.
High diversity-high switching (HD-HS) rate.-Playback consisted of six song types sung by the appropriate neighbor. I switched to a different song type after every song played (diversity = 0.333 types per song, switching rate = 1.0; Fig. 1).
Low diversity-high switching (LD-HS) rate.-Playback consisted of three song types, a subset of those used in the HD-HS playback. I switched to a different song type after every song (diversity = 0.167 types per song, switching rate = 1.0; Fig. 1).
Low diversity-low switching (LD-LS) rate.-Playback consisted of the same three song types as were used in the LD-HS playback, but each song type was repeated four to seven times before switching to a new song type (diversity = 0.167 types per song, switching rate = 0.118; Fig. 1).
All three stimuli can be considered representative of Banded Wren singing behavior under natural conditions, which ranges from bouts with high switching rates and song-type diversity during the dawn chorus to repetitive singing during and after close territorial interactions (Molles and Vehrencamp 1999; Fig. 2). Order of initial song-type presentation was equivalent for LD-HS and LD-LS playbacks and was randomly determined. For HD-HS playbacks, the three song types not used in the other two treatments were presented first (in random order), followed by the three remaining songs.
I did not attempt an HD-LS playback. The playback rate-one song every 10-11 s to approximate natural singing rates-allowed for broadcast of only three types within 3 min during LD-LS playbacks. An HD-LS playback would have required either a faster and unnatural song rate or a much longer playback. Neither compromise was considered desirable, as I wished to present a natural-sounding stimulus, and long playbacks greatly increase the probability of interference by the boundary-sharing neighbor. When boundary-sharing neighbors interfere during a playback, the trial must be abandoned and repeated at a later date; repeated playbacks may lead to habituation by focal birds and greatly complicate interpretation of results. Additionally, comparing behaviors between long HD-HS and other treatments would be complex, because the level of song-type diversity would be “revealed” to focal birds on very different time scales. In the three treatments presented, all song types to be used were revealed to the bird within the first 70 s of playback; whereas in an HD-LS playback, several minutes would elapse before all song types appeared. Analyzing responses to playback would then be complicated by an additional factor-the delay between the start of playback and the point at which total diversity was revealed. Aside from the difficulties in interpretation, any changes in behavior triggered by such late-appearing diversity would need to be of great magnitude to be detected, because they would be apparent only for a very short proportion of the total playback period.
Throughout the pre-playback, playback, and post-playback periods, I recorded focal birds’ vocalizations and location. Because several post-playback periods were interrupted by the approach or singing of a boundary-sharing neighbor, I examined variables measured only during the playback period. I measured seven response variables. As an indicator of aggressive response, I recorded the amount of time the focal bird spent within 10 m of the playback speaker during the playback period. Approach responses by Banded Wrens are stronger in more aggressive contexts; playbacks from within a bird’s territory trigger stronger responses than playbacks from boundary positions (L. E. Molles unpubl. data), and birds approach playback of unfamiliar birds much more strongly early in the breeding season than during the nonbreeding season (Molles 1999).
To examine focal-bird singing complexity, I measured the number of songs sung during playback, the ratio of song types used to number of songs sung, and the rate of switching between song types (measured as the number of switches divided by the maximum possible number of switches). Additionally, I measured three kinds of matching behavior: immediate matches (use of the same song type as the most recent playback song), repertoire matches (use of any song-type shared with the playback neighbor, but not an immediate match), and delayed matches (use of a shared and recently sung song-type, but not an immediate match).
I measured the frequency of immediate song-type matches to the playback as the ratio of immediate song-type matches to the total number of songs sung by the focal bird. Chance levels of immediate song-type matching were calculated as 1 divided by the repertoire size of the focal bird.
Repertoire matches occur when a focal bird sings a song type shared with the opponent, excluding immediate matches (Beecher et al. 1996). I measured the proportion of focal songs that were shared with the playback opponent, and I defined the level of repertoire matching by chance alone as the repertoire overlap between the focal bird and the neighbor whose songs were played back (repertoire overlap = 2N^sub S^/(R^sub 1^ + R^sub 2^), where N^sub s^ is the number of shared song types and R^sub 1^ and R^sub 2^ are the total number of song types in the two males’ repertoires) (McGregor and Krebs 1982). Because song-type sharing among Banded Wrens is high (Molles and Vehrencamp 1999), repertoire matches are highly likely to occur by chance alone during countersinging bouts.
I defined delayed matches as use of a song type that matches any type used during the playback but does not match the most recently played song (Fig. 2). Delayed matching involves using a song type from the same subset of song types as the opponent. For example, if playback (or a live opponent) is alternating between song types A, B, and C out of a repertoire of 20 different song types, a responding singer can choose to sing one of those three types while avoiding an immediate match. This is a more specific choice of song type than a general repertoire match when repertoire sizes are moderate or large. Chance levels for delayed matches were defined as the number of playback song types used (six for HD-HS playbacks, three for the other two playback types) divided by the repertoire size of the focal bird. I did not count a song as a delayed match if the focal bird sang it before the matching song type was used by the playback. Rates for repertoire and delayed matches were defined as the number of repertoire or delayed matches divided by the total number of songs sung by the focal bird during the playback period. The two types of matches are not independent, because delayed matching is a form of repertoire matching.
I analyzed response variables separately because I was interested in how playback diversity and switching rates affected each focal-bird behavior measured. Additionally, techniques such as principal component analysis that combine response variables were deemed inappropriate because individuals were tested repeatedly (violating the assumption of independence of data). Time spent within 10 m of the speaker and three playback-period song variables (number of songs, types per song, and switching rate) were analyzed separately using a mixed-model analysis of variance (ANOVA) procedure with restricted maximum-likelihood (ML) estimation of model parameters. This technique accommodates repeated measures from individuals; male was included as a random effect in all models. Response variables and potential covariates were transformed when necessary. For each response variable, I began with a full model that included playback type, date, time of day, and playback response variables (other than the variable being modeled, and excluding the three matching behaviors) as fixed effects. Initial models for singing variables also included the corresponding measure for the pre-playback period as a fixed effect. I examined the resulting ANOVA and removed the effect with the highest P value. Sequential pairs of models were rerun using ML parameter estimation (necessary because of changes in fixed-effects structure), and compared with an ML ratio test. If this test was not significant, the simpler model was retained (Crawley 2002, Venables and Ripley 2002). I repeated this process until only significant effects (P
Playback-type contrasts were specified a priori to examine the two complexity measures of interest. To compare responses to high-diversity and low-diversity playbacks with equal switching rates, I specified a contrast between HD-HS and LD-HS treatments. To compare responses to high- and low-switching-rate playbacks with equal song-type diversity, I specified a contrast between LD-HS and LD-LS treatments. The HD-HS and LD-LS playbacks were not directly compared, because both components of complexity (switching rate and song-type diversity) differed between the treatments.
It was necessary to use nonparametric analyses for the three song-matching measures (immediate, repertoire, and delayed matching rates). All analyses were performed using R for Macintosh OSX (R Development Core Team 2005). Results are presented as means ± SE, followed by a range showing minimum and maximum values; all P values are two-tailed.
RESULTS
Average repertoire size for the focal males was 23.01 ± 0.411 (range: 18-29), and average repertoire overlap among adjacent neighbors was 0.791 ± 0.011 (range: 0.731-0.860).
Approach responses.-Focal birds spent significantly more time
Singing responses: Diversity and switching.Each singing variable (number of songs, song-type diversity, and switching rate) was analyzed separately, because I was interested in determining whether different aspects of singing behavior changed in relation to the playback stimuli.
Birds that sang only once during a playback period were excluded from analyses, because switching rate and diversity could not be measured. Playback type did not explain a significant amount of variation in any of these singing measures and was not included in the final model for either number of songs or types per song (Table 1). Playback type could not be removed from the final model for switching rate, but was not significant for either treatment comparison. The three singing variables were intercorrelated, and both switching rate and song-type diversity during playback correlated with corresponding pre-playback measures. Switching rate during the playback period also correlated positively with time of day. This result contrasts with those found in a descriptive study (no playback) where switching rates declined with time of day (Molles and Vehrencamp 1999).
Rather than altering switching rates per se, focal birds may alter song-type matching behavior that, in turn, affects switching rates. To determine whether the trends seen in switching rates might be attributable to song-type matching, I calculated an adjusted switching rate by subtracting all switching rates that involved a songtype match. When the analysis was redone using this corrected switching rate, playback type dropped from the final model and only number of songs and song-type diversity remained as significant effects on switching rate.
Singing responses: Song-type matching.-In 12 of 54 playback trials, focal birds sang at least one immediate match (HD-HS = eight birds, LD-HS = three birds, LD-LS = one bird). Immediate song-type matches were more common during HD-HS than LD-HS playbacks (Wilcoxon signed-rank test: W= 190, P = 0.02, n = 16). There was no difference between rates of song-type matches between LD-HS and LD-LS playbacks (Wilcoxon signedrank test: W = 152, P = 0.32, n = 16). However, rates of immediate song-type matching were at or below chance levels for all playback types (Wilcoxon signed-rank tests: HD-HS: W = 144, P > 0.9, n = 16; LD-HS: W = 54, P
In contrast to immediate matches, repertoire matches were at or above chance levels for all playback types (Wilcoxon signed-rank tests: HD-HS: W = 144.5, P = 1, n = 16; LD-HS: W = 223, P 0.09, n = 15) or between LD-HS and LD-LS treatments (Wilcoxon signed-rank test: W = 104, P > 0.70, n = 15).
Delayed matches during HD-HS playbacks also exceeded chance levels (Wilcoxon signedrank test: W = 211, P = 0.02, n = 16). However, levels of delayed matching were significantly below chance levels for the other two playback types (Wilcoxon signed-rank tests: LD-HS: W = 18, P
DISCUSSION
In this experiment, Banded Wrens responded differently to two aspects of singing complexity. When song-type diversity was low, Banded Wrens spent more time close to playback with low switching rates than to playback with high switching rates. Previous playback studies in Banded Wrens have illustrated that such escalated approaches correspond to high-threat situations (Molles 1999; Molles and Vehrencamp 2001a, b). By contrast, high levels of playback song-type diversity did not affect approach responses but did elicit frequent delayed matches. Other aspects of focal-bird singing behavior (song rates, levels of song-type diversity, rates of switching between different song types, and use of immediate song-type matches) did not differ among the playback treatments. Time of day significantly affected two response variables: time spent
In the absence of an HD-LS stimulus (not performed because it would have required a longer or rapidly paced playback), it could be argued that focal birds were responding to combinations of diversity and switching levels, rather than to separate components. However, several lines of evidence suggest that the additional treatment would be unlikely to reveal an interaction effect. In this experiment, approach responses to high versus low song-type diversity did not differ when switching rates were high; would responses to high and low diversity differ when switching rates were low? Probably not. Most birds that approached LD-LS playbacks did so within 66 s. At the corresponding point in an HD-LS playback, only three song types would have been used. Furthermore, birds moved away from playback after approaching to within 10 m in only 5 of 54 trials (this happened at least once for each playback type), so it is unlikely that a late increase in playback song-type diversity would reduce the total time spent close to the speaker. Would responses to high versus low switching rates differ in high-diversity conditions? Again, probably not. With four to seven repeats per song type and a natural song rate, an HD-LS playback would be virtually identical to the performed LD-LS treatment and would present only one additional song type, late within the playback period.
Responses to switching rates.-The playback results in response to changing switching rates reflect natural countersinging interactions between Banded Wrens, which often involve a repetitive mode of singing (Molles and Vehrencamp 1999). However, Banded Wren switching rates can be both high and low during both countersinging and solo singing, which indicates that additional factors may influence this measure (Trillo et al. unpubl. data). Switching rates are commonly linked to context. Red-winged Blackbirds (Agelaius phoeniceus; Searcy and Yasukawa 1990), Dunnocks (Prunella modularis; Langmore 1997) and Chaffinches (Riebel and Slater 2000) exhibit a reduction in switching rates during real or simulated male-male interactions. By contrast, for many species with discrete song-type repertoires of small to moderate size, high switching rates are associated with aggression (d’Agincourt and Falls 1983, Kramer and Lemon 1983, Schroeder and Wiley 1983, Kramer et al. 1985, Simpson 1985, Ritchison 1988, Stoddard et al. 1988, Horn and Falls 1991, Nielsen and Vehrencamp 1995, Duguay and Ritchison 1998, Kroodsma et al. 1999, Vehrencamp 2000). In other species, such as Bobolinks (Dolichonyx oryzivorus), switching rates appear to play no role in aggressive interactions (Capp 1992).
There are several potential costs to repetitive singing that could help explain why repetitive singing might elicit aggressive responses. Repetitive singing may place greater demands on the muscles involved in song production than switching among several song types (Lambrechts and Dhondt 1988, Lambrechts 1996). If this is true, low switching rates during male-male interactions may signal male condition or strength and will constitute a high threat level. In bird species where each song type consists of one rapidly repeated syllable, such a link seems especially reasonable. However, I do not believe that this can explain the use of repetitive singing as an aggressive signal in Banded Wrens. Each Banded Wren song type consists of a wide variety of note types. This wide variety of notes may mean that repetitively singing one song type may not be significantly more tiring than alternating among several song types. Additionally, the fact that numerous species use increased alternation rather than repetition as an aggressive signal suggests that muscle fatigue does not always represent a critical cost.
Alternatively, repeating a single song type several times may also allow opponents to more accurately estimate the location of a singer through ranging (Morton 1982), entailing a risk to the singer. Repetitive singing is also logically linked to song-type matching, which appears to be an especially aggressive signal for Banded Wrens (Molles and Vehrencamp 2001b) and several other species (Krebs et al. 1981, Simpson 1985, McGregor et al. 1992, Duguay and Ritchison 1998, Burt et al. 2001, Vehrencamp 2001, Otter et al. 2002, Peake et al. 2005). Birds locked in mutual, persistent song-type matching necessarily sing repetitively (Nielsen and Vehrencamp 1995), so low switching rates may be associated with aggressive intentions even in the absence of actual song-type matching.
Responses to song-type diversity. -In contrast to switching rates, song-type diversity does not appear to affect Banded Wrens’ aggressive responses to playback, at least among established neighbors. When switching rate was held at a constant and high level, male approach responses to playbacks of high and low diversity were indistinguishable. High song-type diversity may not be a useful signal during most male-male interactions. Song diversity may serve to reveal repertoire size (a possible correlate with male quality), but the brevity of interactions among even unfamiliar males may render the overall repertoire size meaningless in the context of territorial disputes. For example, when it is impossible for a male to present his entire arsenal of song types during a confrontation, a male with 10 song types may appear to be as competitive or motivated as a male with 20 song types who only has time to present 10. Most Banded Wren territorial conflicts, including the establishment of boundaries with new neighbors, are probably settled in a series of short encounters over a period of hours or days. Large repertoires might give a competitor an advantage over the course of several interactions; these kinds of long-term interactions have not yet been examined in Banded Wrens. It is also likely that initial interactions among unfamiliar birds will involve costly signals (such as very close approaches, chases, and direct attacks) that are less vulnerable to potential bluffers than either switching rates or shortterm song-type diversity (Enquist et al. 1998).
The playback trials here involved established neighbors who were familiar with the simulated opponents and their repertoires. Once neighbors are familiar with one another, use of song-type diversity as a means of revealing repertoire size becomes irrelevant: overall repertoire size is known. Instead, short-term changes in song-type diversity may be used as a conventional signal of aggressive intentions. Few studies have specifically investigated whether song-type diversity associates with aggressive response. In one such study of Carolina Wrens, the number of song types used per 100 songs rose as the distance between (real or simulated) opponents decreased; the focal birds’ increases in song-type diversity occurred in tandem with increases in switching rate and song-type matching rate (Simpson 1985). By contrast, the number of different syllable types in a playback (values ranged from two to 55) did not affect aggressive responses of male Sedge Warblers (Acrocephalus schoenobaenus; Catchpole 1988).
For other species, song-type diversity may play a role in aggressive interactions, but songtype diversity and switching rates have not been examined separately. Speaker-replacementplayback experiments have demonstrated that song-type repertoires are more effective territorial signals than single song types in Great Tits (Parus major) and Red-winged Blackbirds (Krebs et al. 1978, Yasukawa 1981), though switching rate differences in stimuli may also have played a role. Similarly, Duguay and Ritchison (1998) found that Tufted Titmice sang with higher versatility when neighboring males were nearby, whereas the proximity of the mate had no apparent effect. However, because both songtype diversity and switching rates entered the versatility measure, it is unclear whether there were separate or interactive effects of the two components (Duguay and Ritchison 1998).
Song-type matching behaviors.-In the present study, playback diversity during high-switchingrate playbacks appeared to influence one aspect of focal birds’ song responses, the use of delayed matches. Delayed matches were remarkably common during HD-HS playbacks, occurring an average of four times per playback and in 14 of 18 trials. During these playbacks, 12 of 14 focal birds increased their rates of delayed matching to levels higher than chance alone, whereas focal birds appeared to actively avoid delayed matches during the other two kinds of playback.
Delayed matches and single immediate matches may indicate attentiveness or serve to “direct” the signal to a particular opponent without increased aggression (Falls 1984, McGregor et al. 1992, Todt and Hultsch 1996). Both of these behaviors are more reminiscent of dawn-chorus song bouts than song bouts during interactions. During dawn-chorus singing, birds often match several different neighbors in rapid succession, using different song types for each match (Burt and Vehrencamp 2005). The low switching rates and repetitive immediate matches characteristic of escalated interactions do not occur, because several singers are interacting simultaneously. Delayed matches may occur deliberately or as a result of several birds using a subset of shared song types.
In contrast to the frequent use of delayed matches, immediate matching occurred only in 12 of 54 trials, and in 10 of these, only one or two immediate song-type matches were performed. Repertoire matching, however, occurred more frequently than expected by chance in two of three playback types; similar results have been observed in several species, including Song Sparrow (Beecher et al. 1996), Tufted Titmouse (Schroeder and Wiley 1983), and Rock Wren (Salpinctes obsoletus; Kroodsma 1975). Although the degree of repertoire matching did not significantly differ among playback treatments, the overall high occurrence is not surprising; in Banded Wrens, avoiding repertoire matches (by singing unshared song types) may signal willingness to de-escalate an interaction (Molles and Vehrencamp 2001b). Because the playback simulated an opponent that neither retreated nor altered its singing behavior, I would not expect frequent use of unshared types unless a focal bird had been dominated by the playback neighbor in previous interactions. Only one male consistently avoided repertoire matches; this male used only unshared types during two of his three playback treatments and did not approach to within 10 m of the playback speaker during any of his trials. Although I do not have data on pre-playback interactions between this bird and his playback neighbor, his unusual behavior in relation to other focal males may be related to unmeasured social effects.
Overall, the treatments presented here showed little effect on focal-bird singing responses. As in previous studies on this species (Molles and Vehrencamp 2001 a, b), behavioral discrimination among playback treatments was apparent in approach responses rather than singing responses. Ongoing studies of natural countersinging interactions on a neighborhood scale may help explain why such differences are rare in Banded Wren playback studies and may suggest useful refinements to playback techniques.
The costs underlying all components of singing complexity are still unclear. However, it appears that all sources of complexity may not be equal; rather, each component may send different kinds of information. Switching rates, song-type diversity, syllable and song-type repertoire sizes, and within-song-type variation are all sources of complexity that may be used to encode information. Re-examining singing complexity in other species, with these separate components in mind, could further elucidate the role of the repertoire in male-male interactions.
ACKNOWLEDGMENTS
Logistical support was provided by the staff of the Area de Conservation Guanacaste, in particular R. Blanco. For field assistance, I thank K. Doordan and J. Willis. J. Burt, S. Vehrencamp, J. Waas, and anonymous reviewers provided helpful comments on the manuscript. This study was supported by the Jeanne Messier Memorial Fund, the Animal Behavior Society, the American Museum of Natural History, the American Ornithologists’ Union, the Los Angeles Audubon Society, and a National Insitutes of Health traineeship.
LITERATURE CITED
BEECHER, M. D., P. K. STODDARD, S. E. CAMPBELL, AND C. L. HORNING. 1996. Repertoire matching between neighbouring Song Sparrows. Animal Behaviour 51:917-923.
BRADBURY, J. W., AND S. L. VEHRENCAMP. 1994. SINGIT!: A program for interactive playback on the Macintosh. Bioacoustics 5:308-310.
BRINDLEY, E. L. 1991. Response of European Robins to playback of song: Neighbour recognition and overlapping. Animal Behaviour 41:503-512.
BURT, J. M., S. E. CAMPBELL, AND M. D. BEECHER. 2001. Song type matching as threat: A test using interactive playback. Animal Behaviour 62:1163-1170.
BURT, J. M., AND S. L. VEHRENCAMP. 2005. Dawn chorus as an interactive communication network. Pages 320-343 in Animal Communication Networks (P. K. McGregor, Ed.). Cambridge University Press, Cambridge, United Kingdom.
BYERS, B. E. 1996. Messages encoded in the songs of Chestnut-sided Warblers. Animal Behaviour 52:691-705.
CAPP, M. S. 1992. Tests of the function of the song repertoire in Bobolinks. Condor 94: 468-479.
CATCHPOLE, C. K. 1988. Responses of male Sedge Warblers to playback of different repertoire sizes. Animal Behaviour 37:1046-1047.
CATCHPOLE, C. K., AND P. J. B. Slater. 1995. Bird Song: Biological Themes and Variations. Cambridge University Press, Cambridge, United Kingdom.
CHARIF, R., S. MITCHELL, AND C. CLARK. 1995. CANARY 1.2 User’s Manual. Cornell Laboratory of Ornithology, Ithaca, New York.
CRAWLEY, M. J. 2002. Statistical Computing: An Introduction to Data Analysis Using S-Plus. John Wiley and Sons, Chichester, United Kingdom.
D’AGINCOURT, L. G., AND J. B. FALLS. 1983. Variation of repertoire use in the Eastern Meadowlark, Sturnella magna. Canadian Journal of Zoology 61:1086-1093.
DUGUAY, J. P., AND G. RITCHISON. 1998. A contextual analysis of singing behavior in male Tufted Titmice. Journal of Field Ornithology 69:85-94.
ENQUIST, M., S. GHIRLANDA, AND P. L. HURD. 1998. Discrete conventional signalling of a continuous variable. Animal Behaviour 56: 749-754.
FALLS, J. B. 1984. Song matching in Western Meadowlarks. Canadian Journal of Zoology 63:2520-2524.
HARTSHORNE, C. 1956. The monotony-threshold in singing birds. Auk 73:176-192.
HORN, A. G., AND J. B. FALLS. 1991. Song switching in mate attraction and territory defense by Western Meadowlarks (Sturnella neglecta). Ethology 87:262-268.
KRAMER, H. G., AND R. E. LEMON. 1983. Dynamics of territorial singing between neighboring Song Sparrows (Melospiza melodia). Behaviour 85:198-223.
KRAMER, H. G., R. E. LEMON, AND M. J. MORRIS. 1985. Song switching and agonistic stimulation in the Song Sparrow (Melospiza melodia): Five tests. Animal Behaviour 33: 135-149.
KREBS, J. R. 1977. The significance of song repertoires: The Beau Geste hypothesis. Animal Behaviour 25:475-478.
KREBS, J. R., R. ASHCROFT, AND K. VAN ORSDOL. 1981. Song matching in the Great Tit Parus major L. Animal Behaviour 29:918-923.
KREBS, J., R. ASHCROFT, AND M. WEBBER. 1978. Song repertoires and territory defence in the Great Tit. Nature 271:539-542.
KROODSMA, D. E. 1975. Song patterning in the Rock Wren. Condor 77:294-303.
KROODSMA, D. E., J. SANCHEZ, D. W. STEMPLE, E. GOODWIN, M. L. DA SILVA, AND J. M. E. VIELLIARD. 1999. Sedentary life style of Neotropical Sedge Wrens promotes song imitation. Animal Behaviour 57:855-863.
KROODSMA, D. E., AND J. VERNER. 1978. Complex singing behaviors among Cistothorus wrens. Auk 95:703-716.
KROODSMA, D. R., AND J. VERNER. 1987. Use of song repertoires among Marsh Wren populations. Auk 104:63-72.
LAMBRECHTS, M. M. 1996. Organization of birdsong and constraints on performance. Pages 305-320 in Ecology and Evolution of Acoustic Communication in Birds (D. E. Kroodsma and E. H. Miller, Eds.). Cornell University Press, Ithaca, New York.
LAMBRECHTS, M. M., AND A. A. DHONDT. 1988. The anti-exhaustion hypothesis: A new hypothesis to explain song performance and song switching in the Great Tit. Animal Behaviour 36:327-334.
LANGEMANN, U., J. P. TAVARES, T. M. PEAKE, AND P. K. McGREGOR. 2000. Response of Great Tits to escalating patterns of playback. Behaviour 137:451-471.
LANGMORE, N. E. 1997. Song switching in monandrous and polyandrous Dunnocks, Prunella modularis. Animal Behaviour 53: 757-766.
MACDOUGALL-SHACKLETON, S. A. 1997. Sexual selection and the evolution of song repertoires. Pages 81-124 in Current Ornithology, vol. 14 (V. Nolan, Jr., E. D. Ketterson, and C. F. Thompson, Eds.). Plenum Press, New York.
McGREGOR, P. K., T. DABELSTEEN, M. SHEPHERD, AND S. B. PEDERSEN. 1992. The signal value of matched singing in Great Tits: Evidence from interactive playback experiments. Animal Behaviour 43:987-998.
McGREGOR, P. K., AND J. R. KREBS. 1982. Song types in a population of Great Tits (Parus major): Their distribution, abundance, and acquisition by individuals. Behaviour 79: 126-152.
MOLLES, L. E. 1999. Use of song-type repertoires by Banded Wrens. Ph.D. dissertation, University of California-San Diego, La Jolla.
MOLLES, L. E., AND S. L. VEHRENCAMP. 1999. Repertoire size, repertoire overlap, and singing modes in the Banded Wren (Thryothorus pleurostictus). Auk 116:677-689.
MOLLES, L. E., AND S. L. VEHRENCAMP. 2001a. Neighbour recognition by resident males in the Banded Wren, Thryothorus pleurostictus, a tropical songbird with high song type sharing. Animal Behaviour 61:119-127.
MOLLES, L. E., AND S. L. VEHRENCAMP. 2001b. Songbird cheaters pay a retaliation cost: Evidence for auditory conventional signals. Proceedings of the Royal Society of London, Series B 268:2013-2019.
MORTON, E. S. 1982. Grading, discreteness, redundancy, and motivation-structural rules. Pages 198-212 in Acoustic Communication in Birds, vol. 1 (D. E. Kroodsma, E. H. Miller, and H. Ouellet, Eds.). Academic Press, New York.
MORTON, E. S., AND K. YOUNG. 1986. A previously undescribed method of song matching in a species with a single song “type,” the Kentucky Warbler (Oporornis formosus). Ethology 73:334-342.
NIELSEN, B. M. B., AND S. L. VEHRENCAMP. 1995. Responses of Song Sparrows to song-type matching via interactive playback. Behavioral Ecology and Sociobiology 37:109-117.
NOWICKI, S., J. PODOS, AND F. VALDES. 1994. Temporal patterning of within-song type and between-song type variation in song repertoires. Behavioral Ecology and Sociobiology 34:329-335.
OTTER, K. A., L. RATCLIFFE, M. NJEGOVAN, AND J. FOTHERINGHAM. 2002. Importance of frequency and temporal song matching in Black-capped Chickadees: Evidence from interactive playback. Ethology 108:181-191.
PAYNE, R. B. 1982. Ecological consequences of song matching: Breeding success and intraspecific song mimicry in Indigo Buntings. Ecology 63:401-411.
PEAKE, T. M., G. MATESSI, P. K. McGREGOR, AND T. DABELSTEEN. 2005. Song type matching, song type switching and eavesdropping in male Great Tits. Animal Behaviour 69: 1063-1068.
PODOS, J., S. PETERS, T. RUDNICKY, P. MARLER, AND S. NOWICKI. 1992. The organization of song repertoires in Song Sparrows: Themes and variations. Ethology 90:89-106.
R DEVELOPMENT CORE TEAM. 2005. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
RIEBEL, K., AND P. J. B. SLATER. 2000. Testing the flexibility of song type bout duration in the Chaffinch, Fringilla coelebs. Animal Behaviour 59:1135-1142.
RITCHISON, G. 1988. Song repertoires and the singing behavior of male Northern Cardinals. Wilson Bulletin 100:583-603.
SCHROEDER, D. J., AND R. H. WILEY. 1983. Communication with shared song themes in Tufted Titmice. Auk 100:414-124.
SEARCY, W. A., AND K. YASUKAWA. 1990. Use of the song repertoire in intersexual and intrasexual contexts by male Red-winged Blackbirds. Behavioral Ecology and Sociobiology 27:123-128.
SIMPSON, B. S. 1985. Effects of location in territory and distance from neighbours on the use of song repertoires by Carolina Wrens. Animal Behaviour 33:793-804.
SPECTOR, D. A. 1992. Wood-warbler song systems: A review of paruline singing behaviors. Pages 199-238 in Current Ornithology, vol. 9 (D. M. Power, Ed.). Plenum Press, New York.
STAICER, C. A. 1989. Characteristics, use, and significance of two singing behaviors in Grace’s Warbler (Dendroica graciae). Auk 106:49-63.
STODDARD, P. K., M. D. BEECHER, AND M. S. WILLIS. 1988. Response of territorial male Song Sparrows to song types and variations. Behavioral Ecology and Sociobiology 22: 125-130.
TODT, D., AND H. HULTSCH. 1996. Acquisition and performance of song repertoires: Ways of coping with diversity and versatility. Pages 79-96 in Ecology and Evolution of Acoustic Communication in Birds (D. E. Kroodsma and E. H. Miller, Eds.). Cornell University Press, Ithaca, New York.
TRAINER, J. M., AND B. S. PELTZ. 1996. Song repertoire of the Bobolink: A reassessment. Ethology 102:50-62.
VEHRENCAMP, S. L. 2000. Handicap, index, and conventional signal elements of bird song. Pages 159-182 in Animal Signals: Signalling and Signal Design in Animal Communication (Y. Espmark, T. Amundsen, and G. Rosenqvist, Eds.). Tapir Publishers, Trondheim, Norway.
VEHRENCAMP, S. L. 2001. Is song-type matching a conventional signal of aggressive intentions? Proceedings of the Royal Society of London, Series B 268:1637-1642.
VENABLES, W. N., AND B. D. RIPLEY. 2002. Modern Applied Statistics with S, 4th ed. SpringerVerlag, New York.
YASUKAWA, K. 1981. Song repertoires in the Redwinged Blackbird (Agelaius phoeniceus): A test of the Beau Geste hypothesis. Animal Behaviour 29:114-125.
Associate Editor: K. Yasukawa
LAURA E. MOLLES1
Department of Biology, University of California at San Diego, 9500 oilman Drive, La Jolla, California 92093, USA
1 Present address: Bio-Protection and Ecology Division, P.O. Box 84, Lincoln University, Canterbury, New Zealand. E-mail: mollesl@lincoln.ac.nz
Copyright American Ornithologists’ Union Oct 2006
Provided by ProQuest Information and Learning Company. All rights Reserved