Download Ecological speciation in Darwin`s finches

Current Zoology
59 (1): 8–19, 2013
Ecological speciation in Darwin’s finches: Parsing the effects
of magic traits
Jeffrey PODOS1*, Rie DYBBOE2, Mads Ole JENSEN3
1
2
3
Department of Biology, University of Massachusetts, Amherst MA 01003, USA
Department of Biology, University of Copenhagen, The August Krogh Bldg., Universitetsparken 13, DK-2100, Copenhagen,
Denmark
Horsens Statsskole, Studentervænget 2, 7000 Horsens, Denmark
Abstract Many recent studies of ecological speciation have focused on “magic trait” scenarios, in which divergent selection on
viability traits leads inextricably to corresponding divergence in mechanisms, especially mate recognition systems, that facilitate
assortative mating. Speciation however may also proceed via other scenarios, such as when populations experience directly selected or random divergence in mate recognition systems. The relative contributions of magic trait versus other scenarios for
speciation remain virtually unexplored. The present study aims to test the relative contribution of the magic trait scenario in the
divergence of populations of the medium ground finch Geospiza fortis of Santa Cruz Island, Galapagos. First, we assess differences in G. fortis song between a northern population (Borrero Bay) and a southeastern population (El Garrapatero), differences
that we propose (along with other within-island geographic song variations) have arisen via scenarios that do not involve a magic
trait scenario. Pairwise comparisons of raw and composite (PC) song parameters, as well as discriminant functions analyses, reveal significant patterns of song divergence between sites. Second, we test the ability of territorial males at Borrero Bay to discriminate songs from the two sites. We find that G. fortis males can discriminate within-island song variants, responding more
strongly to local than to “foreign” songs, along 3 raw and 1 composite response measures. Third, we compare these findings to
prior data sets on song divergence and discrimination in Santa Cruz G. fortis. These comparisons suggest that song divergence and
discrimination are shaped less strongly by geographic sources than by morphological (beak-related) sources. We thus argue that
interpopulation song divergence and discrimination, fundamental elements of assortative mating in Darwin’s finches, can be fostered in early stages of divergence under magic trait as well as alternative scenarios for speciation, but with more emphasis on the
magic trait scenario, at least for this species on this island [Current Zoology 59 (1): 8–19, 2013].
Keywords
Galapagos, Bird song, Geographic variation, Acoustic communication
Ecological speciation occurs when divergent natural
selection among isolated or partly isolated populations
drives the evolution of their reproductive isolation
(Dobzhansky, 1951; Mayr, 1963; Rice and Hostert, 1993;
Schluter, 2001). One scenario for ecological speciation
that has garnered particular attention in recent years
involves so-called “magic traits” (Gavrilets, 2004). The
magic trait scenario proceeds when two functionally
distinct types of traits -- (i) traits subject to disruptive
natural selection and (ii) traits that govern patterns of
mating -- are either the same or share the same genetic
loci. When either condition is met, disruptive natural
selection should lead inexorably, as if by magic, to
non-random, within-type mating and thus enhanced
reproductive isolation (Gavrilets 2004). The “classic”
scenario for magic trait speciation, on which the present
paper focuses, occurs when divergent selection on viReceived June 26, 2012; accepted Oct. 26, 2012.
∗ Corresponding author. E-mail: [email protected]
© 2013 Current Zoology
ability traits (e.g., on body size, color pattern, feeding
morphology) leads to necessary, correlated divergence
in cues or signals that mediate mate selection (Schluter,
2001; Servedio et al., 2011).
An emerging empirical question about the classic
magic-trait scenario concerns its actual contributions to
reproductive isolation, relative to other possible speciation mechanisms. Such mechanisms include differential mutation patterns under uniform selection regimes,
hybridization, polypoloidy, or drift (Schluter, 2001;
Coyne and Orr 2004). As noted by Servedio et al. (2011,
p. 392), “the importance of magic traits in speciation
depends on the degree to which they cause an increase
in reproductive isolation, i.e. their ‘effect size’.” In
many cases, speciation surely proceeds independently of
the magic trait scenario. Moreover, for systems even in
which magic traits can be identified, such traits might,
PODOS J et al.: Ecological speciation in Darwin’s finches
in certain times or places, be trivial. For instance, magic
traits should no longer influence reproductive isolation
if and when divergent selection pressures are relaxed
(Haller et al., 2012), or if and when preferences in specific populations come to rely on mating cues or signals
unlinked to divergent selection. Under such scenarios,
speciation will hinge on the evolution of other factors
such as divergence in mate recognition systems via drift,
or direct selection on mate recognition systems unrelated to viability selection. What then is the relative
contribution of the magic trait scenario versus other
scenarios for signal divergence and the evolution of
reproductive isolation (Haller et al., 2012; Servedio et
al., 2012)?
Darwin’s finches of the Galápagos Islands are a potentially useful study system within which to address
this question. In a recent literature review, Darwin's
finches were identified as one of 18 taxa in nature for
which available evidence suggests that ecological speciation proceeds via the classic magic trait scenario
(Servedio et al., 2011). This scenario seems applicable
to Darwin's finches because a principal locus of adaptive divergence, beak form and function, also influences
the expression of vocal mating signals. To elaborate,
Darwin's finches are known to adapt readily to their
feeding environments, i. e., food availability and interspecific competition, via rapid evolution in beak morphology and function (Gibbs and Grant, 1987; Herrel et
al., 2005; Grant and Grant, 2006). Beak divergence is
thought to drive, as an incidental consequence, divergence in the acoustic structure of songs, given the functional role of beak morphology and dynamics in vocal
production (Nowicki, 1987; Podos, 2001; Podos and
Nowicki, 2004a, b; Podos et al., 2004; Huber and Podos,
2006; Herrel et al., 2009). Divergence in song structure,
in turn, likely drives within-type assortative mating,
Table 1
9
consistent with two main observations: isolating
mechanisms among Darwin's finch populations and
species (as with many other island songbird species) are
primarily pre-mating (Grant and Grant, 1992); and, in
these birds, song is the key mating signal in mate selection (Ratcliffe and Grant, 1985; Grant and Grant, 1997,
see also Grant et al., 2000).
This magic trait scenario must, however, be weighed
against other factors that shape finch song evolution and
divergence (Table 1). One such factor for bird song
evolution is selection for transmission efficacy, in which
signal structure evolves to minimize song degradation
and attenuation, or to enhance detectability or distinctiveness against background noise (e. g., Morton, 1975;
Ryan and Brenowitz, 1985; Wiley 1991; Seddon, 2005;
Tobias et al., 2010). In Darwin’s finches, adaptations for
minimizing degradation and attenuation appear to play
some role in interspecies song divergence (Bowman,
1979), although that role is relatively minor given that
many populations and species inhabit the same or
acoustically similar habitats. A case of song evolution
for distinctiveness in response to background noise has
been recently reported for Darwin's finches of Daphne
major island, in which a newly established population of
the large ground finch, Geospiza magnirostris, which
sings songs with slow trill rates, appears to have driven
the evolution of songs of the other resident species, G.
fortis and G. scandens, towards higher trill rates (Grant
and Grant, 2010). Selection for transmission efficacy in
either context (minimizing degradation, maximizing
detectability) can be considered as adaptive and ecologically-driven, yet would not fall under the classic
magic-trait scenario because evolutionary change in the
vocal phenotype results from direct selection rather than
emerging as a secondary correlate of divergent selection
on viability traits.
Mechanisms of song divergence considered in this study
Mechanism of song divergence
Classic magictrait scenario?
Scale for divergence
Morphological adaptation, correlated song evolution
Yes
Between morph
Acoustic adaptation for signaling efficacy
No
Between site
Random drift (including cultural evolution)
No
Citations for study species
Podos 2001, Huber and Podos 2006
Bowman 1983, Grant and Grant 2006
Between site (and morph) Grant and Grant 1996, Goodale and Podos 2010
The first two mechanisms are adaptive, resulting in song x ecology correlations, yet only the first corresponds to the classic magic trait scenario
(Servedio et al. 2011). Acoustic adaptation does not fit under the classic magic trait scenario because it is driven directly by local acoustic ecology,
rather than as an indirect byproduct of selection on a correlated viability trait. The present study considers two scales of song divergence -- between
morph and between site -- and also asks how these variations correspond to the strength of birds' perceptual discrimination. Our between-morph
comparison removes the effects of acoustic adaptation, given that the morphs occupy the same acoustic environments. Between morph differences
can thus be viewed as driven largely by the classic magic-trait scenario, with perhaps some contributions from drift. Our between-site comparisons
remove the effects of the classic magic-trait scenario, by being limited to a single morph class.
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Current Zoology
Another factor that can shape song evolution is drift.
Song divergence by drift occurs as fully or partly isolated populations undergo distinct trajectories of random
evolution, either in genes that underlie the song phenotype, or in vocal memes in taxa such as Darwin's finches
that learn to sing through imitation (genetic or cultural
evolution, e. g., Jenkins, 1978; Slater, 1986; Payne,
1996; Irwin et al., 2008). Drift likely accounts for moderate to strong degrees of structural variation within and
across Darwin's finch populations, as suggested by
analyses of song divergence within sites over time
(Grant and Grant, 1996; Goodale and Podos, 2010) and
across sites within islands (Snodgrass and Heller, 1904;
Bowman, 1979, 1983; Ratcliffe, 1981; Podos, 2007; see
also Podos and Warren, 2007). Song evolution by drift
also does not fit the magic-trait scenario, because it can
occur independently of patterns of adaptive evolution.
How then do song variations driven indirectly by the
divergence of beaks (magic trait scenario) compare to
song variations driven by direct selection for signaling
efficacy in divergent habitats, and random song variations generated by drift (alternative scenarios) in their
influence on reproductive isolation?
We here address this question for Geospiza fortis, the
medium ground finch, of Santa Cruz Island, Galapagos.
G. fortis shows unusually extensive variation in beak
morphology across the archipelago (Grant et al., 1985),
and different populations across Santa Cruz exhibit distinct beak size distributions (Hendry et al., 2006).
Moreover, two Santa Cruz populations, one currently
(El Garrapatero) and one historically (Academy Bay),
show beak size distributions that are distinctly bimodal,
Fig. 1
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with small morphs and large morphs separated by a size
gap (Hendry et al. 2006, see Fig. 1 for site locations). At
El Garrapatero, the songs of the two morphs differ in a
manner consistent with a vocal constraint hypothesis,
which predicts that large-beaked morphs should sing
with lower vocal performance (Huber and Podos, 2006).
Furthermore, the two morphs are favored by disruptive
selection (Hendry et al., 2009), and mate assortatively
by morph (Huber et al., 2007). It thus seems reasonable
to ascribe song differences among morphs, and its consequences, to ecological divergence and the magic trait
scenario (as in Podos, 2001; Servedio et al., 2011) as
well as, to some extent, the effects of drift. By contrast,
given that the morphs at El Garrapatero live and nest in
the same habitat, often side by side in the same trees and
feeding flocks (S. K. Huber, L. DeLeon, A. Hendry, and
J. Podos unpublished data), song differences between
morphs could not be attributed to divergence in acoustic
ecology. Overall, variations that occurs within-island
(our focus here) likely represent early stages of divergence, with ready opportunity for gene flow among
populations. By contrast, between-island comparisons
are more likely to illuminate later stages of divergence,
given that gene flow between islands is restricted, and
ecological separation typically more extensive.
We present tests of song variation between Borrero
Bay and El Garrapatero, and behavioral responses of
birds at Borrero Bay to playback of song from both localities. This latter component of our study is the reciprocal of an analysis in Podos 2010, in which birds at El
Garrapatero were played these same songs. We also
revisit published data on variations in song structure,
Map of Galápagos and Santa Cruz Island, showing the three locations featured in this paper
New data introduced here compares song structure of male G. fortis between Borrero Bay and El Garrapatero, and also includes playback trials in
which territorial males at Borrero Bay were presented with song stimuli from their local site and from males recorded at El Garrapatero. These data
are evaluated, in the discussion section, together with prior analysis of (i) song variation between El Garrapatero and Academy Bay (Podos, 2007)
and between beak-size morphs at El Garrapatero (Huber and Podos 2006), (ii) previously reported playback data with birds at El Garrapatero on
song discrimination by site (Podos 2007, Podos 2010) and beak-size morph (Podos 2010), and (iii) reported genetic differences by site and morph
(Huber et al., 2007, de Leon et al., 2011).
PODOS J et al.: Ecological speciation in Darwin’s finches
song playback, and genetic data within and across Santa
Cruz sites (Fig. 1, Huber and Podos, 2006; Hendry et al.,
2006; Podos, 2007, 2010; de Leon et al., 2010). These
approaches together allow a first assessment of the relative contributions of magic trait versus alternative scenarios in finch speciation. More specifically, we propose
that magnitudes of song variation between morph and
between site will roughly parallel the relative contributions of magic trait versus alternative scenarios, respectively, in song divergence (Table 1). If, for instance, we
find that songs vary much more between morphs than
between sites, we could infer a greater role for the magictrait scenario in song divergence. Moreover, comparing
birds’ abilities to discriminate between-morph versus
between-site song variants provides context for interpreting the functional importance of those signal variations. If, for instance, birds show greater facility in discriminating spatial versus morph-associated song variants, we would infer a greater effective role for the
speciation scenarios alternative to that of magic traits.
1
Materials and Methods
1.1 Geographic variation in song structure
Songs of male G. fortis were recorded at Borrero Bay
(Fig. 1) during 4–5 day visits in February and March of
2004, 2005 and 2007, using Sony TCD-5M cassette
recorders or Marantz PMD660 digital recorders, and
Sennheiser omnidirectional microphones (K6/ME62 or
MKH20) mounted in 55.9 cm Telinga Pro Universal
parabolas. None of the birds recorded were banded but,
as in all Darwin’s finches, males sing a single, acoustically distinct and highly stereotyped song type, which
allowed us to confirm later that no individual bird was
included twice in our analyses. Songs from our second
site, El Garrapatero, were the same used in a prior
analysis of geographical variation in song structure
(Podos, 2007). Our sampling at El Garrapatero has
been long-term and comprehensive, and all birds recorded at that site had been banded, measured, and
categorized to morph class (small or large, see Hendry
et al., 2006, Huber et al., 2007). In the present analysis
we only included songs from El Garrapatero of
small-beaked morphs. This is because large morphed
birds are very rare at Borrero Bay (Hendry et al., 2006),
and characterizing the contributions to song variations
of non-beak related factors requires that we limit our
comparisons to within the same beak-size classes, i. e.,
to eliminate from consideration contributions to song
variation of the magic-trait scenario. Our sample size
for statistical analysis was 17 males from Borrero Bay
11
and 19 males from El Garrapatero.
For the El Garrapatero sample, we analyzed up to 10
songs from each singer, and calculated mean values for
four acoustic parameters: song duration, trill rate,
minimum frequency, and maximum frequency (as described in Podos, 2007). A fifth parameter, frequency
bandwidth, was calculated as the difference between
maximum and minimum frequency. The same parameters were calculated from a single high quality song
from each of our Borrero Bay sample. As in Podos
(2007), we compared values of acoustic parameters between sites using Mann-Whitney U tests, to test for spatial variation by site. Also as in Podos (2007), we calculated, across the pooled sample, Principal Component
Analysis (PCA) on the correlation matrix for these five
raw song parameters (see Table 2 for factor loadings),
and compared PC factors by site using Mann-Whitney
U tests. These statistical analyses were conducted using
the R statistics platform (http://www.r-project.org/).
Finally, we performed Discriminant Functions Analysis
(DFA), first on the raw song parameters and then on PC
factors 1−3, to assess how well these parameters or factors predicted the geographical locality (Borrero Bay or
El Garrapatero) at which songs were recorded. The
DFA was conducted in Systat 11 (SPSS, Chicago, IL,
USA).
Table 2
site
PC loadings for the analysis of song variation by
Song parameter
PC1
(40.3%)
PC2
(35.0%)
PC3
(20.8%)
Trill rate
0.308
0.634
0
0.694
Duration
0.644
-0.286
Minimum frequency
0.028
0
0.176
Maximum frequency
0.648
-0.284
-0.698
Frequency bandwidth
-0.263
-0.659
0
Proportion of variance explained by each PC factor is indicated in
parentheses. The two most strongly weighted values for each factor
are indicated in bold.
1.2 Playback study
Subjects
Playback trials were conducted with 9 male G. fortis
at Borrero Bay. We ran trials during four days, 26 February through 01 March 2007. Each morning we located
males that were actively defending a territory, recorded
songs from each, and ran playback trials. All males were
defending nests, some of which contained eggs or
chicks.
Playback stimuli
We here used the same playback stimuli from the
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geographic song discrimination component of Podos
(2010). In brief, we identified high-quality versions of
songs recorded during our 2004 and 2005 visits to Borrero Bay (see above for recording methods). We assumed that all of our Borrero Bay singers were smallmorphed, based on annotations taken during recording
and also given that large-morphed birds at Borrero Bay
are rare (Hendry et al., 2006). Following Podos (2010),
and as with our analysis of geographical variation in
song structure (see above), we accounted for the presumed small-morph bias in our Borrero Bay playback
stimuli by restricting our selection of playback songs
from El Garrapatero to small-morphed singers from that
site. For each of 18 playback stimuli (2 sequences for
each of the 9 subjects), we prepared a playback sequence consisting of 18 repetitions of each song, played
every 10 s for 3 min.
Playback trials
One local song sequence and one foreign song sequence were played to each subject during separate trials. Each playback sequence was presented only once
during the entire experiment, so as to avoid pseudoreplication (Kroodsma et al., 2001). For each trial, a
portable playback speaker (Mineroff SME-AFS) was
placed on the ground within the subject’s territory, facing a nest the male was seen to be defending. The same
speaker location was used for each bird for playback of
both local and foreign song stimuli. Playback stimuli
were played from an Apple iPod, saved in uncompressed ‘.wav’ format at a 44.1 kHz sample rate. The
maximum amplitude of all sequences was standardized
to a constant value, 90 dB at 1 m, using test tones and a
Radio Shack sound level meter.
Before a given trial, four observers (all authors plus
an assistant) positioned themselves around the subject’s
territory, and annotated information about subject location and behavior, using portable digital recorders. Each
trial consisted of the 3 minutes of song playback, and
was only initiated when the focal bird was in sight and
within ~ 20 m of the speaker. The vocal behavior of
subjects during trials was recorded using a Marantz
PMD660 digital recorder (44.1 kHz sampling rate, uncompressed “.wav” files) and a Sennheiser omnidirectional microphone mounted in a Telinga parabola. Behavioral patterns noted were flights, songs, and horizontal distance to the speaker, in terms of position when
perched and when flying over the playback speaker.
After each trial distance estimates were confirmed or
refined using a tape measure. The second trial for each
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bird was conducted on the same morning as the first
trial, after an interval of at least one hour so as to minimize habituation. As in many prior studies of responses
to geographic song variants by territorial male songbirds,
we predicted that birds would respond more strongly to
local, familiar song variants.
Analysis of playback responses
Upon return to the laboratory, audio recordings of
each trial were visualized using spectrograms, generated
via the “StripChart” function of Signal 4.0 (Beeman,
2002). This enabled us to annotate all relevant response
behaviors and note their timing to the nearest second.
Quantification of response behaviors followed the
methods in Podos (2007) and Podos (2010). To account
for possible correlations among raw response parameters and to generate composite response indexes, we
conducted Principal Component Analysis on the raw
response parameters (see Table 3 for factor loadings),
using the R statistical platform. Raw response parameters and PC factors 1–3 were compared among local and
foreign sites, using Wilcoxon signed-rank tests.
Table 3 PC loadings of response parameters from playback trials
Response parameter
PC1
(41.8%)
PC2
(28.9%)
PC3
(12.3%)
minimum distance (perched)
-0.558
0.011
-0.309
minimum distance w/overflights)
-0.535
0
-0.407
latency to first flight
-0.203
-0.595
0.494
flights/min
0.453
0.37
-0.211
latency to first song
0.314
-0.527
-0.107
songs/min
-0.242
0.482
0.662
2 Results
2.1 Geographic variation in song structure
Representative songs from Borrero Bay are illustrated in Fig. 2. As can be seen, song structure across
birds in this population is highly variable, an observation also reflected in the wide scatter among points in
PCA summary plots (Fig. 3). Three lines of evidence
indicate that Borrero Bay songs are structurally distinct
from their El Garrapatero counterparts. First, visual
inspection of spectrograms (representative samples of G.
fortis songs from El Garrapatero can be found in Huber
and Podos, 2006; Podos, 2007) reveals differences by
site in song type structure. That is, most song types at
each site have no obvious counterparts at the other site.
Second, songs from the two sites are seen to diverge
statistically in three parameters: trill rate (faster at Bor-
PODOS J et al.: Ecological speciation in Darwin’s finches
Fig. 2
13
Representative songs from the Borrero Bay population of Geospiza fortis
Broad variation in song structure within this population is evident, consistent with observations of song variation within other G. fortis populations.
Several of these songs are similar in structure to songs recorded at El Garrapatero (e.g., Fig.1 in Podos, 2007), although most do not appear to have
a specific El Garrapatero counterpart. A statistical analysis of raw song parameters revealed two differences in song by population, in trill rate (with
Borrero Bay birds singing faster songs) and in minimum frequency (with Borrero Bay birds singing lower minimum frequencies, see text, Table 4).
rero Bay), minimum frequency (lower at Borrero Bay,
Table 4), and PC3, which mainly represents maximum
frequency and duration (Table 2, Fig. 3). All three of
these results retain significance after sequential Bonferroni corrections. Third, our DFA revealed significant
separation of songs according to site (for raw acoustic
parameters, Wilk’s lambda = 0.404, F1, 34 = 11.44, P <
0.001; for PC factors, Wilk’s lambda = 0.448, F1, 34 =
13.13, P < 0.001). DFA was also able to classify the
majority of songs to their correct locations (for raw parameters, 16 of 17 Borrero Bay songs and 15 of 19 El
Garrapatero songs; for PC factors, 17 of 17 Borrero
Bay songs and 16 of 19 El Garrapatero songs).
2.2 Playback study
Playback trials for two subjects were interrupted by
neighboring birds, and data from these subjects were
thus excluded from further analysis. In both cases, interruptions occurred during playback of local song, and
consisted of a neighbor either responding strongly to the
playback stimulus itself, or engaging with the focal
male in a chase. Responses of the remaining birds,
sorted by category, are illustrated for raw response parameters in Fig. 4. Three of these parameters, all related
to flight, showed significant differences by stimulus
class, in terms of uncorrected p-values (minimum approach distance, perched, Z = -2.152, P = 0.031; latency
to first flight, Z = -2.032, P = 0.042; flight rate, Z =
1.960, P = 0.050). PC1, which corresponded to flight
behavior (closer approaches, quicker latency to fly,
higher flight rate) also showed significant differences by
condition, with stronger responses to local song stimuli
than to foreign song stimuli (PC1, Borrero Bay stimuli =
0.830 ± 0.512 SE, El Garrapatero stimuli = -0.830 ±
0.587 SE, Z = 2.366, P = 0.018). Statistical values for
non-significant response parameters were as follows:
minimum approach distance w/ overflights, Z = -1.638,
P = 0.101; latency to first song, Z = -1.270, P = 0.204;
song rate, Z = 0.255, P = 0.799; PC2, Borrero Bay stimuli = 0.360 ± 0.695 SE, El Garrapatero stimuli = -0.360
± 1.804 SE, Z = 1.183, P = 0.237.
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Fig. 3 Multivariate analysis of song variation between Borrero Bay (closed circles) and El Garrapatero (open squares)
Shown are PC2 and PC3 plotted as a function of PC1. PC loadings are
shown in Table 2: PC1 represents, roughly, duration and maximum
frequency; PC2 varies positively with trill rate and negatively with
frequency bandwidth; and PC3 varied positively with duration and
negatively with maximum frequency. Differences by population in
PC3 were statistically significant (see Table 4, text).
3
Discussion
Our first main finding is that songs of Geospiza fortis
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have diverged in structure across two Santa Cruz populations ~25 km distant, Borrero Bay and El Garrapatero.
Other instances of within-island song divergence in
Darwin's finches have been reported (Snodgrass and
Heller, 1904; Bowman, 1979, 1983; Ratcliffe, 1981;
Podos, 2007), but the present case seems especially
pronounced. Statistically significant differences were
identified in two song parameters, trill rate and minimum frequency, as well as in one composite measure of
song structure, PC3. These differences are more extensive than those reported in a similar comparison of
songs between El Garrapatero and Academy Bay, sites
separated by ~11 km (Podos, 2007; Fig. 1). Songs between those sites were found to differ in only one raw
song parameter (minimum frequency), not two, although they did also differ in a PC factor (Podos, 2007).
Also, discriminant functions analysis was able to categorize songs to site with greater accuracy in the Borrero
Bay x El Garrapatero comparison (86.1% and 91.7%
for raw and PC factor data, respectively) than for the El
Garrapatero x Academy Bay comparison (78.9% and
70.2%, Podos, 2007).
This pattern of greater differences in song between
the more distant sites might be best explained by drift,
by clinal variation in acoustical ecology, or by some
combination of the two. Random variations in song
should accumulate over increasing distances (e.g., Slater,
1986), as in ‘isolation by distance’ models of genetic
divergence. Ecologically speaking, the two study sites in
the present comparison present roughly similar vegetation profiles (both populations are low-elevation arid
zone with landscapes featuring Opuntia echios, Acacia
macracantha, Cordia lutea, and Bursera graveolens),
although they still might exert slightly differential pressures for song adaptations that minimize song degradation. The sites probably also differ in available acoustic
Table 4 Summary statistics (mean ± SD) for five song parameters and three PC factors from two sites, Borrero Bay and El
Garrapatero. Significant uncorrected P-values are shown in bold
Locality
Song parameter
Between-site comparison
Borrero Bay
El Garrapatero
Mann-Whitney U scores
Z approximation
Uncorrected P value
Trill rate (Hz)
2.52±0.56
2.08±0.35
Duration (s)
0.78±0.21
0.85±0.14
240.5
2.5
0.012
186.5
0.79
0.428
Minimum frequency (kHz)
1.98±0.23
2.31±0.20
278
3.69
<0.001
Maximum frequency (kHz)
4.93±1.21
4.73±0.95
174
0.39
0.692
Frequency bandwidth (kHz)
2.95±1.13
2.42±0.97
209
1.51
0.132
PC1
0.42±1.50
-0.37±1.27
208.5
1.49
0.136
PC2
0.33±1.60
-0.30±0.96
189.5
0.89
0.375
PC3
-0.68±0.84
0.61±0.75
285
3.91
<0.001
PODOS J et al.: Ecological speciation in Darwin’s finches
Fig. 4
15
Results from playback trials, means ± SE for the 6 raw response parameters shown
Significant differences were found in 3 of the 4 flight response parameters, with birds responding more strongly to local songs (Borrero Bay) than
foreign songs (EI Garrapatero, * uncorrected P < 0.05). A parallel stronger response to local song was also documented for PC1, which loaded most
strongly with flight response (see Table 3, text).
space (Luther, 2009; Grant and Grant, 2010), especially
given the relative paucity of large-morphed G. fortis at
Borrero Bay. As such, Borrero Bay birds might be free
to occupy a broader acoustic space with their songs than
they would be able to in the presence of large-morphed
acoustic competitors. Indeed, birds from Borrero Bay
sing songs with relatively low minimum frequencies
and high trill rates, patterns which at El Garrapatero
appear characteristic of large-morphed birds (Huber and
Podos, 2006).
Turning then to the central question raised in this paper, how do drift and/or acoustic adaptation (alternative
scenarios for speciation) compare to morphology
(magic-trait scenario) as drivers of song divergence?
The relationship between song divergence and morphology has been assessed for beak-size morphs at El
Garrapatero (Huber and Podos, 2006), a comparison
that minimized the potentially confounding effects of
acoustic environment, given that these birds nest and
sing in the same habitats. In that study, morph songs
showed divergence in all parameters assessed: minimum
and maximum frequencies, frequency bandwidth, trill
rate, and "vocal deviation", the latter being a composite
measure of vocal performance that considers trill rate
16
Current Zoology
and frequency bandwidth together relative to the species' putative performance boundary (Podos, 2001; Huber and Podos, 2006). Direct comparison of the Huber
the and Podos (2006) morphological divergence data set
to the geographic divergence data sets (here and in Podos, 2007) is hindered by the fact that not all of the
same song parameters were measured across studies,
and that Huber and Podos (2006) did not include a discriminant functions analysis. Nevertheless, different
patterns of trait variation are apparent. Minimum frequency is seen to vary by both morph and site, being
higher in small-morphed birds and at El Garrapatero as
compared to Borrero Bay and Academy Bay. Similarly,
trill rate also varies by morph and one of the site
comparisons, El Garrapatero and Borrero Bay (Table 4),
being higher at Borrero Bay and in large- beaked
morphs. Yet divergence in other song parameters assessed is predicted only by morph designation; these parameters include maximum frequency, frequency bandwidth, and vocal deviation. The greater breadth of parameters that vary with morph designation suggests to
us that morphology has the more pronounced influence
on song divergence. This finding in turn tentatively
supports a greater role for the magic trait scenario than
the alternative scenarios in song divergence.
Ultimately, however, sorting magic trait from alternative scenarios for speciation requires attention not just to
signal structure but also to signal discrimination. To
illustrate, certain signal parameters might diverge as a
correlated effect of morphological divergence, but have
no effect on mating patterns (and thus the evolution of
reproductive isolation) if those signal parameters are not
recognized or used in mate assessment. In many bird
groups including Darwin's finches, reproductive isolation is principally pre-mating in nature, which means
that females’ perception, discrimination, and preferences
for certain signal features are the key determinants of
speciation. The ideal test for magic trait versus alternative scenario effect sizes in Darwin's finches would thus
compare female preferences for song traits linked to
morphology versus song traits explained by acoustic
adaptation or drift. However, studies of song preferences in female Darwin's finches have so far proven
intractable (S. K. Huber and J. Podos, unpublished data),
and the majority of published studies on song function
in Darwin's finches have focused instead on responses
to song playback in territorial males (e. g., Ratcliffe and
Grant, 1985; Grant and Grant, 2002a, b). Typically we
expect males to be less discriminating than females in
Vol. 59
No. 1
their reactions to song, because of lower costs associated with false positives (Searcy and Brenowitz, 1988;
Ratcliffe and Otter, 1996). Indeed, in two studies of
sparrows in the same family as Darwin’s finches (Emberizidae), females were seen to respond positively to a
narrower range of song stimuli than did males (Searcy
et al., 2002; Danner et al., 2011). We thus expect any
discriminations males make among stimulus classes to
also occur in females, whereas a lack of discrimination
among song categories by males is less likely to tell us
anything about how females would respond. Thus, we
presume that any perceptual discriminations (by morph
or site) we can document for males would translate into
patterns of assortative mating (by morph or site) in females, and as such inform the likelihood of magic-trait
versus alternative scenarios for speciation.
This leads to the second main finding from our study,
which is that males responded more strongly to local
songs (Borrero Bay) than to foreign songs (El Garrapatero, see Fig. 4). This finding parallels those in two prior
studies of geographic song discrimination: for El Garrapatero males played local songs and songs from
Academy Bay (Podos, 2007); and less strongly, in a
reciprocal study to the present one, for birds at El Garrapatero played local songs and songs from Borrero
Bay (Podos, 2010). Returning the central question of
this paper, how do these geographical discriminations
compare to the discrimination of morphologicallylinked song variations? Does a greater degree of linked
divergence in song parameters translate into a higher
effect size for a magic-trait scenario versus alternative
scenarios? An informal ranking of the four available sets
of playback data is illuminating. As illustrated in Table
5, we find that the overall discrimination of morphological variants was stronger than in the three tests of
geographic variant discrimination. This result suggests a
comparatively large role for the magic-trait scenario in
the song divergence and discrimination. As a side note,
within the geographic discrimination data sets, the
strongest discrimination was in the El Garrapatero x
Academy Bay discrimination, and the two weakest discriminations were in the Borrero Bay x El Garrapatero
comparisons. This latter result is at odds with our song
divergence data, which documented greater (not less)
divergence in the Borrero Bay x El Garrapatero comparison versus the El Garrapatero x Academy Bay
comparison. This outcome is puzzling given that song
sets that have diverged more in structure should be easier to discriminate.
PODOS J et al.: Ecological speciation in Darwin’s finches
Table 5
17
Ranking of song discrimination scores across 4 playback data sets
Playback study
closest approach
(perched)
closest approach
(w/overflights)
latency to
first flight
flight rate
PC1
PC2
Average
Rank
Geographic 1: Males at El Garrapatero, local
vs Academy Bay songs (Podos 2007)
2
1
3
3
1.5
4
2.42
Geographic 2: Males at El Garrapatero, local
vs. Borrero Bay songs (Podos 2010)
4
4
4
1
4
1
3.00
Geographic 3: Males at Borrero Bay, local vs.
El Garrapatero songs (this study, Fig. 4)
3
3
2
4
3
2
2.83
Morphological: Males at El Garrapatero, same
vs. other morph songs (Podos 2010)
1
2
1
2
1.5
3
1.75
For each data set, responses to treatment (geographic or morph) were evaluated by 4 raw and 6 PC response variables, and the strength of the differences by treatment indicated by Wilcoxon signed-rank test values. Here we ranked those values by strength, via comparison of uncorrected p-values
from Wilcoxon values across the studies. Scores were ranked from 1−4, for strongest to weakest discrimination. Two additional response parameters,
song rate and latency to first song, did not differ by condition in any of the four experiments, and are thus not considered here. Average rank is
shown in the last column. The overall strongest discrimination was to the morph treatment.
Needless to say, much remains to be learned about if
and how spatial and morphological song variations
translate into actual mechanisms and patterns of population divergence. The present study and analysis is best
considered as only preliminary, given the limited number and arbitrary selection of sites used in our study.
However, we can view our results to date within the
context of the work of de Leon et al. (2010), who
documented patterns of genetic divergence both across
sites and between morphs for Santa Cruz Geospiza fortis. A main finding from de Leon et al. (2010) is that
genetic divergence among morphs substantially outweighs genetic divergence by site (the same sites studied here), typically by at least an order of magnitude
(e.g., FST value for El Garrapatero large vs. small
morph = 0.016, FST values for El Garrapatero small
morph vs. Borrero small morph = <0.001). Once again
the direction is consistent with a magic-trait divergence
scenario, but to a much greater degree for the song data.
How do we account for the greater disparity (between
morph and site) in genetic data than in song data? Perhaps females show disproportionately stronger realworld discriminations than we detected in territorial
males, in a way that accentuates the differences in male
discriminations that we report. Exploring this possibility
in more quantitative terms will require additional research, ideally incorporating data on female preferences
for morphological versus geographical axes of song
divergence.
To summarize, our focal species, Geospiza fortis, exhibits extensive song divergence across Santa Cruz island sites, as indicated by statistical comparisons of
song structure across three sites and within one site with
a bimodal distribution. Variation in the relative strength
of song differences suggest that song divergence is more
pronounced when it is linked to morphological divergence than when it occurs via alternative mechanisms of
divergence, including acoustic adaptation or drift.
Likewise, available evidence from playback data, admittedly limited, suggests that discrimination is stronger
for morphologically- mediated than geographicallymediated song divergence. Together, these data offer a
first suggestion that the magic trait scenario outweighs
alternative scenarios in the evolution of inter-population
reproductive isolation, at least for this species on this
island.
Acknowledgements We thank the Galápagos National Park
Service and Charles Darwin Research Station for logistical
support, and Morten Harboe Kirkegaard, Andrew Hendry, and
Luis Fernando de Leon for assistance in the field. Jenny
Boughman, Sarah Goodwin, Jofre Carnicer, and an anonymous referee offered insightful comments on prior drafts.
Supported by NSF grants IBN-0347291 and IOS-1028964 to
JP, and awards from the Hede Nielsen Foundation and the 3rd
Galathea expedition to MOJ.
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