Hung et al 2012
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Molecular Phylogenetics and Evolution xxx (2012) xxx–xxx
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Molecular Phylogenetics and Evolution
journal homepage: www.elsevier.com/locate/ympev
Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus)
Chih-Ming Hung a,b,c,⇑, Sergei V. Drovetski d, Robert M. Zink a,b
a
Bell Museum, University of Minnesota, St. Paul, MN 55108, USA Department of Ecology, Evolution and Behavior, University of Minnesota, St. Paul, MN 55108, USA c Department of Life Science, National Taiwan Normal University, Taipei 116, Taiwan d Tromsø University Museum, NO-9037 Tromsø, Norway
b
a r t i c l e
i n f o
a b s t r a c t
A previously published phylogeographic analysis of mtDNA sequences from the widespread Palearctic common rosefinch (Carpodacus erythrinus) suggested the existence of three recently diverged groups, corresponding to the Caucasus, central-western Eurasia, and northeastern Eurasia. We re-evaluated the mtDNA data using coalescence methods and added sequence data from a sex-linked gene. The mtDNA gene tree and SAMOVA supported the distinctiveness of the Caucasian group but not the other two groups. However, UPGMA clustering of mtDNA UST-values among populations recovered the three groups. The sex-linked gene tree recovered no phylogeographic signal, which was attributed to recent divergence and insufficient time for sorting of alleles. Overall, coalescence methods indicated a lack of gene flow among the three groups, and population expansion in the central-western and northeastern Eurasia groups. These three groups corresponded to named subspecies, further supporting their validity. A species distribution model revealed potential refugia at the Last Glacial Maximum. These three groups, which we hypothesized are in the early stages of speciation, provided an opportunity for testing tenets of ecological speciation. We showed that the early stages of speciation were not accompanied by ecological niche divergence, consistent with other avian studies. Ó 2012 Elsevier Inc. All rights reserved.
Article history: Received 3 December 2011 Revised 8 September 2012 Accepted 14 September 2012 Available online xxxx Keywords: Coalescence Simulation Species distribution model Niche divergence Phylogeography
1. Introduction Quaternary climatic fluctuations repeatedly shifted the distributions of species, presumably resulting in multiple cycles of retraction into refugia during glacial advance and subsequent expansion during interglacial periods (Hewitt, 2000, 2004). These fluctuations in range could have had at least three consequences: (1) initiation of divergence among populations, (2) continued maintenance of already distinct populations, or (3) merging of once-differentiated populations. Phylogeographic studies can provide a description of the current geographic deployment of genetic variation and yield inferences about which of these potential histories was experienced by a particular species (Avise, 2000). For example, the discovery of three phylogroups in an extant species implies the existence of at least three glacial refugia at the Last Glacial Maximum (LGM; 21,000 years ago), assuming that the groups evolved prior to the last glacial period. A species distribution model (SDM), often referred to as an ecological niche model (Peterson et al., 1999), can be used to determine the sizes and locations of
⇑ Corresponding author at: Department of Life Science, National Taiwan Normal University, Taipei 116, Taiwan. Fax: +1 612 624 6777. E-mail address: [email protected] (C.-M. Hung).
1055-7903/$ - see front matter Ó 2012 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ympev.2012.09.012
LGM refugia and then relate them to the current population structure (Carnaval et al., 2009; Knowles and Alvarado-Serrano, 2010). One could also discover whether these intraspecific groups have diverged ecologically, providing a test of the tenets of ecological speciation (Schluter, 2009; McCormack et al., 2010). Peterson et al. (1999) suggested that ecological divergence only occurred after speciation; however, there are relatively few tests of niche divergence early in the speciation process. The common rosefinch (Carpodacus erythrinus) inhabits various types of woodlands and grasslands, spanning much of the Palearctic. During the past century, its range has expanded westward into Scandinavia, France, Spain and England (Cramp and Perrins, 1994; Payevsky, 2008), although persistent breeding is limited to Scandinavia. Pavlova et al. (2005) surveyed mtDNA variation and postulated the existence of three taxa corresponding to the Caucasus (CA), northeastern Eurasia (NEE), and central-western Eurasia (CWE, Fig. 1). However, the geographic limits of the groups were unclear and maximum likelihood estimates of migration suggested a low level of gene flow among groups. In this study, we reexamined the conclusion of Pavlova et al. (2005) by (1) using robust coalescence methods and adding a Z-linked gene, (2) using a SDM to reconstruct the current and LGM distributions of the common rosefinch, to search for sites of potential refugia, and to
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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C. e. grebnitskii MAG DOR TÖV
KUR
MEZ YEK MED MOS KRD
C. e. erythrinus GOR TYV
KRY IRK KHA
ANA KAM
ALM C. e. ferghanensis
SAK
C. e. kubanensis
Fig. 1. Breeding range of the common rosefinch (Carpodacus erythrinus) with four subspecies indicated and location of sample sites (re-drawn from Fig. 1 in Pavlova et al. (2005). Gray area indicates breeding range. Large solid circles indicate sample sizes of 10 or more individuals. Dotted lines partition the population into three groups as indicated by the pairwise mtDNA UST analysis (Pavlova et al., 2005) and the UPGMA tree based on a matrix of mtDNA UST values (Fig. 4 in this study). ALM is Almaty, ANA is Anadyr’, DOR is Dornod, GOR is Gorno-Altay, IRK is Irkutsk, KAM is Kamchatka, KHA is Khabarovsk, KRD is Krasnodar, KRY is Krasnoyarsk, KUR is Kursk, MAG is Magadan, MED is Medvedevo, MEZ Mezen’, MOS is Moscow, SAK is Sakhalin, TÖV is Töv, TYV is Tyva, and YEK is Yekaterinburg.
assess the relative sizes of populations at each time, and (3) testing for ecological divergence between these groups to determine if niche differentiation has accompanied the early stages of lineage divergence (Warren et al., 2008). 2. Methods and materials 2.1. Genetic analyses We used the ND2 sequence data for 186 common rosefinches from Pavlova et al.’s (2005) study (Fig. 1 and Table S1, NCBI accession numbers AY703261-AY703446). In addition, one Z-linked intron, ADAMTS6 (Backström et al., 2006), was sequenced for 28 individuals from 15 localities (Table S1; 12, 7, and 9 individuals from the three mtDNA-defined groups, CWE, NEE and CA, respectively). Phases of sequences containing indels were sorted manually by subtracting chromatogram peaks upstream of the indel in the reverse primer sequences from the double peaks downstream of the indel in the forward primer sequences. This procedure was repeated in the alternative direction and allowed the two alleles of a heterozygous individual to be determined (Sousa-Santos et al., 2005; Dolman and Moritz, 2006). Alleles present in individuals with multiple heterozygous sites but no indel(s) were resolved using PHASE 2.1.1 (Stephens et al., 2001; Stephens and Scheet, 2005). 2.2. Detection of population division NETWORK 4.5.1.6 (fluxus-engineering.com) was used to generate minimum spanning networks (Polzin and Daneschmand, 2003) for mtDNA and ADAMTS6 data to detect geographic partitioning of haplotypes and alleles. Pairwise UST-values of mtDNA (but not ADAMTS6 due to small sample sizes) among populations were estimated using DnaSP 5 (Librado and Rozas, 2009). To determine the overall geographic pattern of population structure, we pooled individuals from each locality and then clustered the matrix of pairwise UST values using the unweighted pair-group method using arithmetic averages (UPGMA) implemented in MEGA 4 (Tamura et al., 2007). We combined the populations with sample sizes smaller than five with samples in the nearest and sufficiently large population to avoid bias in UST estimates. If the combination was not geographically reasonable, the samples were excluded from analyses. For example, the Sakhalin population was not combined with the Kamchatka or Magadan population because they are separated by a wide area of sea or a long geographic distance.
We also applied spatial analysis of molecular variance implemented in SAMOVA 1.0 (Dupanloup et al., 2002) to the mtDNA data to explore population division. Based on an F-statistic, SAMOVA uses a simulated annealing procedure to determine groups of populations that are geographically and genetically homogeneous and maximally differentiated from each other (i.e., the configuration has the largest UCT). We tested population partitions (K) ranging from 2 to 8 with 100 to 300 initial conditions each based on 105 annealing permutations. Given that populations with small sample sizes might be erroneously identified as isolated groups in SAMOVA (Dupanloup, pers. comm.), we combined the localities with small sample sizes according to the same rules we used for calculating the pairwise UST-values. 2.3. Estimates of demographic parameters A coalescence-based program, IMa (Hey and Nielsen, 2007), was used to estimate the effective population sizes of two current populations and their common ancestral populations (h1, h2, and ha; h = 4 Nel), migration rates (m1 and m2; m = m/l), and divergence times (t = t l) between groups of populations determined from the procedures outlined above. The UPGMA phenogram based on pairwise UST values and SAMOVA suggested two possible group structures, a three-group model and a two-group model (see Section 3.1). The three-group model included CA, CWE, and NEE. The two-group model consisted of a combined CWE and NEE (termed ME) and CA. We estimated the demographic parameters associated with the various groupings in the two alternative models. We did not use IMa2 (Hey, 2010) because we cannot specify a tree topology for the three groups. A minimum of two independent analyses of >2 Â 107 steps after a burn-in of 106 steps were performed for each pairwise comparison. Plots of trend lines and the effective sample size values (ESS > 250) were examined to assess convergence in parameter estimates. The IMa estimates were based on all available mtDNA and ADAMTS6 sequence data combined. To convert the scaled demographic parameters to absolute values, we calculated the geometric mean of the substitution rates of ND2 and ADAMTS6 by multiplying the sequence lengths by 4 Â 10À8 substitutions/site/ year for ND2 (Arbogast et al., 2006) and 1.62 Â 10À9 substitutions/ site/year for ADAMTS6 (Ellegren, 2007; given the mean divergence of Z-linked introns between chicken and turkey is 1.2 times higher than that of autosomal introns, which have an average rate of 1.35 Â 10À9 substitutions/site/year) and assumed a generation time of 2 years (Stjernberg, 1979). The substitution rate used in this study was higher than widely used rates for avian mtDNA (Lovette,
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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2004; Weir and Schluter, 2008) but more appropriate for recent divergences (Ho et al., 2005; Arbogast et al., 2006; Herman and Searle, 2011; but see Emerson 2006). 2.4. Group delimitation using hypothesis testing We tested alternative population models using a coalescent simulation program, SIMCOAL 2.1.2 (Laval and Excoffier, 2004) to simulate ND2 sequences. The simulations were performed using the demographic parameters estimated from IMa based on mtDNA and ADAMTS6, i.e., current effective population sizes (the effective population size of mtDNA, Nef, was assumed to be half of the Ne of populations), migration rates, divergence times, exponential growth rates (calculated from the current and ancestral population sizes), a substitution rate of 4 Â 10À8 substitutions/site/year, and the generation time of two years. One two-group model and two three-group models were simulated (Fig. 2). In the latter case, two models were considered due to the uncertainty in gene flow from NEE to CWE based on the IMa analyses (see Section 3.1). One three-group model postulated no gene flow (Fig. 2a) and the other assumed a low level of gene flow (2 Â 10À6 per generation per individual; see Section 3.1) from NEE to CWE (Fig. 2b). Given that the dispersal distance of rosefinches is unlikely to span the entire geographic range, the widely distributed ME (in the two-group model; Fig. 2c) was not assumed to be panmictic. We simulated ME by connecting two subgroups with a substantial level of migration, 100 individuals per generation at present but decreasing exponentially backwards in time as the population size decreased (Fig. 2c). This level of migration is large enough to prevent population differentiation (Hudson and Coyne, 2002). The ratio of Ne for the two subgroups in ME was 12:1 (Fig. 2c) similar to that for CWE and NEE. We simulated 5000 datasets of 186 ND2 sequences (1041 bp) for each hypothesized model. The simulated datasets were analyzed using Arlequin 3.1 (Schneider et al., 2000) to calculate UST values (Excoffier et al., 1992) and the distribution and the upper and lower bounds of 95% ranges of these values were recorded. The UST values for simulated data were compared with the empirical UST to evaluate which model was most consistent with the observed data. 2.5. Species distribution modeling Online databases ORNIS and GBFI together with our own museum data resulted in 196 breeding localities (see Fig. S1), which we input into MAXENT v 3.2.2. (Phillips et al., 2006) to infer a SDM. Because the species has only colonized western Europe during the past few decades (Cramp and Perrins, 1994), we excluded
breeding records from Scandinavia, France, Spain and England. We obtained climatic data (19 layers) for present and LGM conditions from the Worldclim bioclimatic database (Hijmans et al., 2005). We ran MAXENT five times (using 30% of values for training) and examined the jackknifed contributions of each bioclimatic layer, picking seven layers (bioclim layers 1, 5, 9, 10, 11, 15 and 18) that contributed 5% or more to the total variation for the final analysis (Brown and Knowles, 2012). For the final model, we constructed a SDM from the average of 10 MAXENT runs using all locality points, which we displayed using DIVA-GIS ver. 7.1.7.2 (Hijmans et al., 2004). 2.6. Niche divergence tests We used the program ENMTools v.1.3 (Warren et al., 2010) to perform niche identity tests and background tests for whether taxa that were defined according to the genetic data (i.e., the CA, CWE and NEE groups) exhibit niche divergence or conservatism (or neither). The niche identity test assesses whether the similarity between ecological niches of two taxa is significantly different from a null distribution generated from random draws of pooled empirical occurrence points. The identity test often suggests that two taxa have significantly different niches (Godsoe, 2010; Warren et al., 2008). However, this inference is only true when the two groups tolerate the exact same set of environmental conditions and have the same suite of environmental conditions available to them (Warren et al., 2010). Because this is unlikely for allopatric populations that are distributed across environmental gradients, the background test determines whether two taxa are more or less similar than expected based on the differences in the environmental background where they occur. The background test determines whether an empirical niche similarity index between two taxa is significantly smaller (niche divergence) or greater (niche conservatism) than a null distribution of the niche similarity indices between one taxon and random points from the environment within the other taxon’s range; two null distributions result because the comparisons are done in both directions (Warren et al., 2010). For the background tests, we divided the large central area of rosefinch distribution into eastern (CWEE) and western (CWEW) groups to account further for the large geographic distance involved. 3. Results 3.1. Population structure The mtDNA network revealed that 9 of the 13 haplotypes from the Caucasus (CA) formed a clade, which was separated by a few steps from the remaining haplotypes (Fig. 3a). The haplotypes in
(a)
t= 39,200
Na = 63,000
(b)
t= 39,200
Na = 63,000
(c)
t =33,200
Na = 72,000
m= 2 × 10 -6
NCA = 83,000 NCWE = 3,516,000 NNEE = 308,000 NCA = 83,000 NCWE = 3,516,000 NNEE = 308,000 NCA = 72,000 NME = 3,990,000 + 333,000
Fig. 2. Outline of two three-group models (a and b) and one two-group model (c) developed to test hypothesized demographic histories for the common rosefinch. Na, NCA, NCWE, NNEE and NME indicate effective population sizes of ancestral, CA, CWE, NEE and ME groups, respectively. t indicates time of divergence in units of generations from present. Arrows indicate gene flow. The immigration rate (m) in the (b) model is shown in the figure. The dashed lines indicate that the groups are connected to each other with substantial levels of gene flow.
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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Fig. 3. Network of (a) mtDNA and (b) a Z-linked intron (ADAMTS6) haplotypes of the common rosefinch by the minimum spaning criterion. Colors on the network indicate the locations at which each haplotype was detected. Black circles indicate central-western Eurasian (CWE) haplotypes, white circles indicate northeastern Eurasian (NEE) ones, and gray circles indicate Caucasian (CA) ones. Open triangles indicate unsampled or extinct haplotypes. Sizes of circles are proportional to haplotype frequencies. Short lines indicate one mutation step.
northeastern Eurasia (NEE) were not separated from those in central-western Eurasia (CWE). Thus, the mtDNA network revealed limited geographic structure. The allele network for ADAMTS6 showed no geographic structure (Fig. 3b). The UPGMA phenogram based on the matrix of mtDNA pairwise UST values (see Table S2 for the UST values) clustered rosefinch populations into three distinct groups corresponding to CA, NEE, and CWE groups (Fig. 4). The SAMOVA supported a two-group structure, CA and all remaining populations (i.e., CWE plus NEE). The UCT value was highest when K = 2 (UCT = 0.349) and decreased as K increased. IMa analyses based on mtDNA, and mtDNA plus ADAMTS6, suggested recent isolation with little or no gene flow followed by population expansion (except for CA), for both the three-group and two-group models. In addition, the IMa analyses revealed that the values of demographic parameters for the two datasets differed in magnitude, with the combined data (i.e., mtDNA plus ADAMTS6) suggesting longer divergence times, greater effective population sizes and lower migration rates (Table S3). We used results based on the combined dataset in our simulations. For the three-group model, IMa revealed that the current population sizes of CWE (7,032,000; 95% credibility interval [CI] = 4,130,000 to 17,303,000) and NEE (616,000; 95% CI = 334,000–1,839,000) are significantly larger than that of the ancestral population (136,000; 95% CI = 58,000–240,000), whereas the current population size of CA
Fig. 4. UPGMA phenogram showing relationships among rosefinch population samples. The tree is reconstructed based on the matrix of UST values. The three clades correspond to the central-western Eurasian (CWE), northeastern Eurasian (NEE), and Caucasian (CA) groups. Populations with sample sizes smaller than five were combined with samples in the nearest and sufficiently large population. Therefore, DOR + TÖV is the combination of Dornod and Töv’s samples, IRK + KRY is that of Irkutsk and Krasnoyarsk, MED + MEZ is that of Medvedevo and Mezen, and MOS + KUR is that of Moscow and Kursk.
(167,000; 95% CI = 80,000–438,000) was not significantly larger than that of the ancestral population (Fig. 5a and b). There was little if any migration between any pair of groups (Fig. 5c–e). There could
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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Fig. 5. The marginal posterior probabilty distribution of the IMa parameters under the three-group model. The three groups are Caucasus (CA), central-western Eurasia (CWE) and northeastern Eurasia (NEE). The IMa analyses were based on mtNDA and a Z-linked gene (ADMATS6) combined. Effective population sizes, h, for CA, CWE, NEE and their ancestral populations are shown in (a and b). Migration rates, m, in two directions between CA and CWE, between CWE and NEE, and between CA and NEE in the unite of per generation per individual are shown in (c–e). Divergence times, t, for the three pairwise comparisons in the unite of year are shown in (f).
be some migration from NEE to CWE (2 Â 10À6 per generation per individual; 95% CI = $0 to 1.6 Â 10À5 [we could not reject the possibility of zero gene flow]; Fig. 5d). The divergence times between CA and CWE (78,300 years ago; 95% CI = 52,200–117,000 years ago), between CWE and NEE (78,800 years ago; 95% CI = 52,000– 117,200 years ago), and between CA and NEE (76,200 years ago; 95% CI = 42,200–141,700 years ago) were similar and recent (Fig. 5f), suggesting contemporaneous origins of the three groups (see Hung et al. 2012). The IMa results for the two-group model revealed that the current population size of ME (8,645,000; 95% CI = 5,396,000–18,196,000) was significantly larger than the ancestral population (147,000; 95% CI = 88,000–282,000), but that of CA (144,000; 95% CI = 70,000–394,000) was not. The IMa results showed no migration between the two groups. The estimated divergence time (66,400 years ago; 95% CI = 45,500–96,600 years ago) was similar to that of the three-group model. Comparison of the simulated and empirical data supported the three-group models over the two-group model (Fig. 6). The empirical UST value was within the 95% distribution range of UST values of the three-group models regardless of the level of gene flow
(Fig. 6a and b) but out of the 95% range of UST values for the two-group (Fig. 6c). Therefore, we could reject the two-group but not either of the three-group models. The similarity between the distributions of UST values for the two three-group models, one with and one without gene flow, suggested that the level of gene flow from NEE to CWE was negligible.
3.2. Current and LGM distributions predicted by SDM The AUC of the MAXENT distribution model was 0.88, indicating good quality in the predictions (AUC > 0.7 = informative; Baldwin, 2009; Swets, 1988). The SDM under current climatic conditions predicted the breeding range of common rosefinches including newly colonized areas in Scandinavia (Fig. 7a). Although the model predicts occurrence in France, Portugal and Spain the species has not yet become established in these areas, but there are sporadic records (Cramp and Perrins, 1994). Therefore, the predicted current distribution of common rosefinches in Europe was somewhat wider than the observed distribution but consistent with the trend
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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Fig. 6. Histograms of UST values for 5000 simulated sequence datasets. (a) Results from simulations of the three-group model without gene flow. (b) Results from simulation of the three-group model with a low level of gene flow from NEE to CWE. (c) Results from simulations of the two-group model. The dashed lines represent the 2.5 and 97.5 percentiles in the distribution. The black triangles represent the UST value of our empirical data.
of recent expansion towards the western and northwestern Palearctic (Cramp and Perrins, 1994; Payevsky, 2008). The predicted distribution at the LGM suggested that common rosefinches mainly occurred in four areas (i.e., refugia): (1) Kamchatka and Magadan, (2) southern Siberia, Mongolia, China and Japan, (3) Caucasus and (4) southern Europe (Fig. 7b). The first three predicted refugia sustainably or partially overlapped with the present distributions of the three haplotype groups. Comparing the extent of the present and LGM distributions suggested that the Caucasian population (CA) and Kamchatka and Magadan populations (corresponding to NEE) had not undergone expansion whereas the other populations (corresponding to CWE) expanded westwards since the LGM (Fig. 7).
niche conservatism in the eight pairwise background tests, which took into account the environment available to each group (Fig. 8).
4. Discussion Our re-analyses of the mtDNA data, and analyses of the mtDNA data plus the sex-linked sequences, support the existence of three groups of populations in the common rosefinch, namely the Caucasus, northeastern Eurasia, and central-western Eurasia. These three groups are not reciprocally monophyletic for either mtDNA or the Z-linked gene tree, suggesting that the rosefinches are at an early stage of diversification. Our estimates of gene flow were essentially zero, indicating that the groups are evolving independently. Hence we infer that speciation has commenced. In addition, the SDM implies that these three groups might have occupied distinct LGM refugia. Further supporting our hypothesis of the distinctness of these groups, we note that the three groups, CA, NEE and CWE, correspond to named subspecies, C. e. kubanensis, C. e. grebnitskii and C. e. erythrinus, respectively (Cramp and Perrins, 1994; Fig. 1). The subspecies C. e. kubanenesis is larger and more rosy-red colored
3.3. Niche divergence The pairwise niche identity tests (not shown) suggested that the niches of different groups of rosefinches were significantly different based on the niche similarity index, Schoener’s D (P < 0.001). However, we found no instances of either niche divergence or
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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Fig. 7. Predicted distributions of the common rosefinch (Carpodacus erythrinus) for (a) present and (b) LGM. Darker colors reflect areas with higher probabilities of occurrence.
than the nominate subspecies C. e. erythrinus, and C. e. grebnitskii has more red or carmine on its upperparts than C. e. erythrinus (Clement et al., 1993; Cramp and Perrins, 1994). A fourth subspecies, C. e. ferghanensis, represented only by our Almaty sample was not genetically distinct, and fell within C. e. erythrinus. Although we do not propose elevating these taxa to species, any analysis of recent trends in biodiversity should recognize their historical existence.
4.1. Recent history of common rosefinches revealed by phylogeography and SDM The application of SDMs to evolutionary studies is promising (Carnaval et al., 2009; Kozak et al., 2008) although their performance has been under debate (e.g., Araújo et al., 2009; Beale et al., 2008). Our SDM under current climatic condition predicted the occurrence of common rosefinches in western Europe even though our model did not incorporate breeding sites from this region. The fact that the species has recently become common in Scandinavia and has bred locally in other European areas (Cramp and Perrins, 1994; Payevsky, 2008), and that the considerable part of the predicted range conforms to the known distribution, suggests that our SDM is relatively robust. However, our SDM underestimated the distribution of this species in northeastern Eurasia and overestimated that in China and Japan when compared with the known distribution. The inconsistency may reflect limitations
of SDMs and/or the fact that our knowledge about the distribution of this species in these regions is incomplete. In general, it is difficult to determine the specific geographic locations of LGM refugia, irrespective of whether one uses a SDM or makes inferences from the extant phylogeographic pattern. We consider our SDM and genetic results to be reciprocally illuminating. Our SDM (Fig. 7) is a snapshot at the maximum of the last glacial period, which began ca. 100,000 years before (Lisiecki and Raymo, 2007), and hence it is unclear how many refugia existed during this period. Our genetic results suggested three recently (e.g., ca. 75,000 ybp) isolated groups (Figs. 4 and 6), which we think helps guide interpretation of the SDM. Assuming that the three groups originated prior to the LGM, we suggest that two refugia existed in the eastern Palearctic at the LGM, even though our SDM shows a relatively narrow gap (i.e., the coast near the northwestern tip of the Sea of Okhotsk) between them (Fig. 7b). However, many extant phylogroups are parapatrically distributed or separated by narrow gaps (e.g., Hung et al., 2012; Zink et al., 2008). The lack of sorting of mtDNA haplotypes from the Palearctic (excluding CA; Fig. 3a) coupled with the inference of negligible gene flow between NEE and CWE, is consistent with our estimate of divergence time (ca. 75,000 ybp). Haploid, non-recombining mtDNA gene trees require isolation lasting approximately Ne generations to reach reciprocal monophyly (Hudson and Coyne 2002). Given the large estimates of Ne for the two main Palearctic groups (7,032,000 and 616,000), considerable time would have to elapse before the mtDNA gene tree would become reciprocally
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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Fig. 8. Background tests for niche divergence. Arrows indicate observed niche similarity index (Schoener’s D) between two groups and are compared with a null distribution for the niche similarity indices between one group and random points from the range of the other group and vice versa. (a) Gray histogram indicates a null distribution of NEE versus the background of CWEE, and black indicates the opposite comparison. (b) Gray indicates a null distribution of CA versus the background of NEE, and black indicates the opposite comparison. (c) Gray indicates a null distribution of CA versus the background of CWEW, and black indicates the opposite comparison. (d) Gray indicates a null distribution of CWEW versus the background of CWEE, and black indicates the opposite comparison. Niche similarity values smaller than a null distribution indicate niche divergence, larger values indicate niche conservatism, and values within a null distribution indicate neither niche divergence nor niche conservatism.
monophyletic. Therefore, there has been insufficient time for the mtDNA gene tree to evolve to reciprocal monophyly. Given that the average Ne of Z-linked genes is three times greater than mtDNA, we expected that the ADSMTS6 gene tree would show less geographic structure than the mtDNA gene tree, which we observed. Combining coalescence and SDM analyses allowed additional insight into rosefinch population history. Our coalescence analyses revealed that CWE and NEE experienced population expansion, whereas CA did not (Fig. 5). Our SDM analyses suggested a similar history except that NEE had similar distributions between the present and LGM predictions. However, the degree of expansion for CWE was at least 10 times greater than that for NEE according to the coalescence analyses (Fig. 5), and from the SDM it would appear logical given the large area into which CWE expanded, and the relatively stable distribution of NEE. The predicted LGM occurrence of rosefinches in areas south of where they presently occur in southern Europe is relevant to past hypotheses about the distribution of genetic variation following glacial retreat. Hewitt (2004) suggested that genetic variability decreases in the direction of colonization from a refugium owing to sampling effects, termed ‘‘leading edge expansion.’’ However, if the refugium no longer has suitable habitat, as is the case for common rosefinches in southern Europe, this prediction is not testable. In this case, one might look to the southern extent of the current range as being the closest to refugial populations, and hence currently harboring the greatest genetic variability, but we lacked data for a strong test of this hypothesis. Thus, a SDM can modify predictions about post-glacial patterns of genetic variation. The SDM is consistent with a history of isolation for rosefinches in the Caucasus (Fig. 7). Compared to CWE and NEE, CA has a relatively smaller effective population size and has not experienced population expansion. These attributes can explain why
approximately 70% of haplotypes in CA form a clade in the mtDNA tree (Pavlova et al. 2005) and haplotype network (Fig. 3), whereas haplotypes in the other two groups do not. That is, lineage sorting is a function of Ne, and therefore one expects faster sorting in the CA group. We predict that if the isolation and current population size continues, the Caucasian population will be the first group to become a new species. This example illustrates that relatively small and isolated populations on islands, continental habitat islands, or mountaintops are potent grounds for lineage diversification. 4.2. Niche evolution between the recently diverged common rosefinch groups As the three rosefinch groups are in the early stages of speciation, our study can help to show whether ecological divergence drives speciation or accrues after speciation. We found no evidence for niche divergence, a result consistent with that for other groups of birds that are considerably more differentiated (Peterson et al., 1999; McCormack et al., 2010). The significant tests for niche identity coupled with the insignificant background tests reinforce the importance of considering environment availability when testing niche divergence (McCormack et al., 2010). In other words, the results imply that rosefinches in different areas do not have the same niche space available to them. The lack of support for niche divergence or conservatism may indicate that rosefinches can survive in varied habitats, as suggested by the significant niche identity tests. This may explain the recent population expansion of rosefinches shown by genetic data and current expansion to new ranges in Europe. On the other hand, given the general lack of niche divergence, one might expect that the groups would invade each other’s ranges. That is, during
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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the ensuing 21,000 years since the LGM, and a dispersal distance typical for passerine birds of P1 km per generation (Barrowclough 1980), there would have been ample time for range expansion and homogenization of the three groups. However, our estimates of gene flow suggest this is not occurring. Hence it is possible that the forms exclude each other behaviorally (Waters, 2011) or we have not captured the most important niche dimensions. Acknowledgments We thank S. Rohwer for his roles in gathering specimens and A. Pavlova for doing the original analyses, and S. Birk for loans. K. Kozak and D. Shepard helped in conducting ecological niche modeling. T. Rodrigues assisted with map making. B. McKay, H. Vazquez and two anonymous reviewers helped to improve the manuscript. We are grateful to the University of Minnesota Supercomputing Institute for assistance with the computations. Support came from NSF (DEB 9707496, and DEB 0212832), FCT (PTDC/BIABEC/103435/2008) and the Dayton-Wilkie fund of the Bell Museum. Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.ympev.2012.09. 012. References
Araújo, M.B., Thuiller, W., Yoccoz, N., 2009. Reopening the climate envelope reveals macroscale associations with climate in European birds. Proc. Natl. Acad. Sci. USA 106, E45–E46. Arbogast, B.S., Drovetski, S.V., Curry, R.L., Boag, P.T., Seutin, G., Grant, P.R., Grant, B.R., Anderson, D.J., 2006. The origin and diversification of Galapagos mockingbirds. Evolution 60, 370–382. Avise, J.C., 2000. Phylogeography: The History and Formation of Species. Harvard University Press, Cambridge. Backström, N., Brandström, M., Gustafsson, L., Qvarnström, A., Cheng, H., Ellegren, H., 2006. Genetic mapping in a natural population of collared flycatchers (Ficedula albicollis): conserved synteny but gene order rearrangements on the avian z chromosome. Genetics 17, 377–386. Baldwin, R.A., 2009. Use of maximum entropy modeling in wildlife research. Entropy 11, 854–866. Barrowclough, G.F., 1980. Genetic and phenotypic differentiation in a wood warbler (genus Dendroica) hybrid zone. Auk 97, 655–668. Beale, C.M., Lennon, J.J., Gimona, A., 2008. Opening the climate envelope reveals no macroscale associations with climate in European birds. Proc. Natl. Acad. Sci. USA 105, 14908–14912. Brown, J.L., Knowles, L.L., 2012. Spatially explicit models of dynamic histories: examination of the genetic consequences of Pleistocene glaciation and recent climate change on the American pika. Mol. Ecol. 21, 3757–3775. Carnaval, A.C., Hickerson, M.J., Haddad, C.F.B., Rodrigues, M.T., Moritz, C., 2009. Stability predicts genetic diversity in the Brazilian Atlantic forest hotspot. Science 323, 785–789. Clement, P., Harris, A., Davis, J., 1993. Finches and Sparrows: An Identification Guide. Princeton University Press, Princeton. Cramp, S., Perrins, C.M., 1994. Handbook of the Birds of Europe, the Middle East and North Africa, vol. 5. Oxford University Press, Oxford. Dolman, G., Moritz, C., 2006. A multilocus perspective on refugial isolation and divergence in rainforest skinks (Carlia). Evolution 60, 573–582. Dupanloup, I., Schneider, S., Excoffier, L., 2002. A simulated annealing approach to define the genetic structure of populations. Mol. Ecol. 11, 2571–2581. Ellegren, H., 2007. Molecular evolutionary genomics of birds. Cytogenet. Genome Res. 117, 120–130. Emerson, B.C., 2006. Alarm Bells for the molecular clock? No support for Ho et al’.s model of time-dependent molecular rate estimates. Syst. Biol. 56, 337–345. Excoffier, L., Smouse, P., Quattro, J., 1992. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131, 479–491. Godsoe, W., 2010. Regional variation exaggerates ecological divergence in niche models. Syst. Biol. 59, 298–306. Herman, J.S., Searle, J.B., 2011. Post-glacial partitioning of mitochondrial genetic variation in the field vole. Proc. Roy. Soc. B 278, 3601–3607. Hewitt, G.M., 2000. The genetic legacy of the quaternary. Nature 405, 907–913. Hewitt, G.M., 2004. Genetic consequences of climatic oscillations in the quaternary. Philos. Trans. Roy. Soc. B 359, 183–195.
Hey, J., 2010. Isolation with migration models for more than two populations. Mol. Biol. Evol. 27, 905–920. Hey, J., Nielsen, R., 2007. Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics. Proc. Natl. Acad. Sci. USA 104, 2785–2790. Hijmans, R.J., Guarino, L., Bussink, C., Mathur, P., Cruz, M., Barrentes, I., Rojas, E., 2004. DIVA-GIS. Vsn. 7.1.7. A geographic information system for the analysis of species distribution data. <http://www.diva-gis.org>. Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G., Jarvis, A., 2005. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978. Ho, S.Y.W., Phillips, M.J., Cooper, A., Drummond, A., 2005. Time dependency of molecular rate estimates and systematic overestimation of recent divergence times. Mol. Biol. Evol. 22, 1561–1568. Hudson, R.R., Coyne, J.A., 2002. Mathematical consequences of the genealogical species concept. Evolution 56, 1557–1565. Hung, C.-M., Drovetski, S.V., Zink, R.M., 2012. Multilocus coalescence analyses support a mtDNA-based phylogeographic history for a widespread Palearctic passerine bird, Sitta europaea. Evolution 66, 2850–2864. Knowles, L.L., Alvarado-Serrano, D.F., 2010. Exploring the population genetic consequences of the colonization process with spatio-temporally explicit models: insights from coupled ecological, demographic and genetic models in montane grasshoppers. Mol. Ecol. 19, 3727–3745. Kozak, K.H., Graham, C.H., Wiens, J.J., 2008. Integrating GIS-based environmental data into evolutionary biology. Trends Ecol. Evol. 23, 141–148. Laval, G., Excoffier, L., 2004. SIMCOAL 2.0: a program to simulate genomic diversity over large recombining regions in a subdivided population with a complex history. Bioinformatics 20, 2485–2487. Librado, P., Rozas, J., 2009. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25, 1451–1452. Lisiecki, L.E., Raymo, M.E., 2007. Plio-Pleistocene climate evolution: trends and transitions in glacial cycle dynamics. Quat. Sci. Rev. 26, 56–69. Lovette, I.J., 2004. Mitochondrial dating and mixed support for the ‘‘2% rule’’ in birds. Auk 121, 1–6. McCormack, J.E., Zellmer, A.L., Knowles, L.L., 2010. Does niche divergence accompany allopatric divergence in Aphelocoma jays as predicted under ecological speciation?: insights from tests with niche models. Evolution 64, 1231–1244. Pavlova, A., Zink, R.M., Rohwer, S., 2005. Evolutionary history, population genetics, and gene flow in the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. 36, 669–681. Payevsky, V.A., 2008. Breeding and demographic parameters and range expansion of the common rosefinch (Carpodacus erythrinus). Ring 30, 63–69. Peterson, A.T., Sobersón, J., Sánchez-Cordero, V., 1999. Conservatism of ecological niches in evolutionary time. Science 285, 1265–1267. Phillips, S.J., Anderson, R.P., Schapire, R.E., 2006. Maximum entropy modeling of species geographic distributions. Ecol. Model. 19, 231–259. Polzin, T., Daneschmand, S.V., 2003. On Steiner trees and minimum spanning trees in hypergraphs. Oper. Res. Lett. 31, 12–20. Schluter, D., 2009. Evidence for ecological speciation and its alternative. Science 323, 737–741. Schneider, S., Roessli, D., Excoffier, L., 2000. Arlequin: A Software for Population Genetics Data Analysis. Version 2. Genetics and Biometry Lab, Dept of Anthropology, Univ of Geneva, Switzerland. <http://anthro.unige.ch/software/ arlequin/>. Sousa-Santos, C., Robalo, J.I., Collarrs-Pereira, M.-J., Almada, V.C., 2005. Heterozygous indels as useful tools in the reconstruction of DNA sequences and in the assessment of ploidy level and genomic constitution of hybrid organisms. DNA Sequence 16, 462–467. Stephens, M., Scheet, P., 2005. Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation. Am. J. Hum. Genet. 76, 449– 462. Stephens, M., Smith, N., Donnelly, P., 2001. A new statistical method for haplotype reconstruction from population data. Am. J. Hum. Genet. 68, 978–989. Stjernberg, T., 1979. Breeding biology and population dynamics of the scarlet rosefinch Carpodacus erythrinus. Acta Zool. Fennica 157, 1–88. Swets, J.A., 1988. Measuring the accuracy of diagnostic systems. Science 240, 1285– 1293. Tamura, K., Dudley, J., Nei, M., Kumar, S., 2007. MEGA4: molecular Evolutionary genetics analysis (MEGA) software version 4.0. Mol. Biol. Evol. 24, 1596–1599. Warren, D.L., Glor, R.E., Turelli, M., 2008. Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution 62, 2868– 2883. Warren, D.L., Glor, R.E., Turelli, M., 2010. ENMTools: a toolbox for comparative studies of environmental niche models. Ecography 33, 607–611. Waters, J.M., 2011. Competitive exclusion: phylogeography’s ‘elephant in the room’? Mol. Ecol. 20, 4388–4394. Weir, J.T., Schluter, D., 2008. Calibrating the avian molecular clock. Mol. Ecol. 17, 2321–2328. Zink, R.M., Pavlova, A., Drovetski, S., Rohwer, S., 2008. Mitochondrial phylogeographics of five widespread Eurasian bird species. J. Ornithol. 149, 399–413.
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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Molecular Phylogenetics and Evolution
journal homepage: www.elsevier.com/locate/ympev
Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus)
Chih-Ming Hung a,b,c,⇑, Sergei V. Drovetski d, Robert M. Zink a,b
a
Bell Museum, University of Minnesota, St. Paul, MN 55108, USA Department of Ecology, Evolution and Behavior, University of Minnesota, St. Paul, MN 55108, USA c Department of Life Science, National Taiwan Normal University, Taipei 116, Taiwan d Tromsø University Museum, NO-9037 Tromsø, Norway
b
a r t i c l e
i n f o
a b s t r a c t
A previously published phylogeographic analysis of mtDNA sequences from the widespread Palearctic common rosefinch (Carpodacus erythrinus) suggested the existence of three recently diverged groups, corresponding to the Caucasus, central-western Eurasia, and northeastern Eurasia. We re-evaluated the mtDNA data using coalescence methods and added sequence data from a sex-linked gene. The mtDNA gene tree and SAMOVA supported the distinctiveness of the Caucasian group but not the other two groups. However, UPGMA clustering of mtDNA UST-values among populations recovered the three groups. The sex-linked gene tree recovered no phylogeographic signal, which was attributed to recent divergence and insufficient time for sorting of alleles. Overall, coalescence methods indicated a lack of gene flow among the three groups, and population expansion in the central-western and northeastern Eurasia groups. These three groups corresponded to named subspecies, further supporting their validity. A species distribution model revealed potential refugia at the Last Glacial Maximum. These three groups, which we hypothesized are in the early stages of speciation, provided an opportunity for testing tenets of ecological speciation. We showed that the early stages of speciation were not accompanied by ecological niche divergence, consistent with other avian studies. Ó 2012 Elsevier Inc. All rights reserved.
Article history: Received 3 December 2011 Revised 8 September 2012 Accepted 14 September 2012 Available online xxxx Keywords: Coalescence Simulation Species distribution model Niche divergence Phylogeography
1. Introduction Quaternary climatic fluctuations repeatedly shifted the distributions of species, presumably resulting in multiple cycles of retraction into refugia during glacial advance and subsequent expansion during interglacial periods (Hewitt, 2000, 2004). These fluctuations in range could have had at least three consequences: (1) initiation of divergence among populations, (2) continued maintenance of already distinct populations, or (3) merging of once-differentiated populations. Phylogeographic studies can provide a description of the current geographic deployment of genetic variation and yield inferences about which of these potential histories was experienced by a particular species (Avise, 2000). For example, the discovery of three phylogroups in an extant species implies the existence of at least three glacial refugia at the Last Glacial Maximum (LGM; 21,000 years ago), assuming that the groups evolved prior to the last glacial period. A species distribution model (SDM), often referred to as an ecological niche model (Peterson et al., 1999), can be used to determine the sizes and locations of
⇑ Corresponding author at: Department of Life Science, National Taiwan Normal University, Taipei 116, Taiwan. Fax: +1 612 624 6777. E-mail address: [email protected] (C.-M. Hung).
1055-7903/$ - see front matter Ó 2012 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ympev.2012.09.012
LGM refugia and then relate them to the current population structure (Carnaval et al., 2009; Knowles and Alvarado-Serrano, 2010). One could also discover whether these intraspecific groups have diverged ecologically, providing a test of the tenets of ecological speciation (Schluter, 2009; McCormack et al., 2010). Peterson et al. (1999) suggested that ecological divergence only occurred after speciation; however, there are relatively few tests of niche divergence early in the speciation process. The common rosefinch (Carpodacus erythrinus) inhabits various types of woodlands and grasslands, spanning much of the Palearctic. During the past century, its range has expanded westward into Scandinavia, France, Spain and England (Cramp and Perrins, 1994; Payevsky, 2008), although persistent breeding is limited to Scandinavia. Pavlova et al. (2005) surveyed mtDNA variation and postulated the existence of three taxa corresponding to the Caucasus (CA), northeastern Eurasia (NEE), and central-western Eurasia (CWE, Fig. 1). However, the geographic limits of the groups were unclear and maximum likelihood estimates of migration suggested a low level of gene flow among groups. In this study, we reexamined the conclusion of Pavlova et al. (2005) by (1) using robust coalescence methods and adding a Z-linked gene, (2) using a SDM to reconstruct the current and LGM distributions of the common rosefinch, to search for sites of potential refugia, and to
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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C.-M. Hung et al. / Molecular Phylogenetics and Evolution xxx (2012) xxx–xxx
C. e. grebnitskii MAG DOR TÖV
KUR
MEZ YEK MED MOS KRD
C. e. erythrinus GOR TYV
KRY IRK KHA
ANA KAM
ALM C. e. ferghanensis
SAK
C. e. kubanensis
Fig. 1. Breeding range of the common rosefinch (Carpodacus erythrinus) with four subspecies indicated and location of sample sites (re-drawn from Fig. 1 in Pavlova et al. (2005). Gray area indicates breeding range. Large solid circles indicate sample sizes of 10 or more individuals. Dotted lines partition the population into three groups as indicated by the pairwise mtDNA UST analysis (Pavlova et al., 2005) and the UPGMA tree based on a matrix of mtDNA UST values (Fig. 4 in this study). ALM is Almaty, ANA is Anadyr’, DOR is Dornod, GOR is Gorno-Altay, IRK is Irkutsk, KAM is Kamchatka, KHA is Khabarovsk, KRD is Krasnodar, KRY is Krasnoyarsk, KUR is Kursk, MAG is Magadan, MED is Medvedevo, MEZ Mezen’, MOS is Moscow, SAK is Sakhalin, TÖV is Töv, TYV is Tyva, and YEK is Yekaterinburg.
assess the relative sizes of populations at each time, and (3) testing for ecological divergence between these groups to determine if niche differentiation has accompanied the early stages of lineage divergence (Warren et al., 2008). 2. Methods and materials 2.1. Genetic analyses We used the ND2 sequence data for 186 common rosefinches from Pavlova et al.’s (2005) study (Fig. 1 and Table S1, NCBI accession numbers AY703261-AY703446). In addition, one Z-linked intron, ADAMTS6 (Backström et al., 2006), was sequenced for 28 individuals from 15 localities (Table S1; 12, 7, and 9 individuals from the three mtDNA-defined groups, CWE, NEE and CA, respectively). Phases of sequences containing indels were sorted manually by subtracting chromatogram peaks upstream of the indel in the reverse primer sequences from the double peaks downstream of the indel in the forward primer sequences. This procedure was repeated in the alternative direction and allowed the two alleles of a heterozygous individual to be determined (Sousa-Santos et al., 2005; Dolman and Moritz, 2006). Alleles present in individuals with multiple heterozygous sites but no indel(s) were resolved using PHASE 2.1.1 (Stephens et al., 2001; Stephens and Scheet, 2005). 2.2. Detection of population division NETWORK 4.5.1.6 (fluxus-engineering.com) was used to generate minimum spanning networks (Polzin and Daneschmand, 2003) for mtDNA and ADAMTS6 data to detect geographic partitioning of haplotypes and alleles. Pairwise UST-values of mtDNA (but not ADAMTS6 due to small sample sizes) among populations were estimated using DnaSP 5 (Librado and Rozas, 2009). To determine the overall geographic pattern of population structure, we pooled individuals from each locality and then clustered the matrix of pairwise UST values using the unweighted pair-group method using arithmetic averages (UPGMA) implemented in MEGA 4 (Tamura et al., 2007). We combined the populations with sample sizes smaller than five with samples in the nearest and sufficiently large population to avoid bias in UST estimates. If the combination was not geographically reasonable, the samples were excluded from analyses. For example, the Sakhalin population was not combined with the Kamchatka or Magadan population because they are separated by a wide area of sea or a long geographic distance.
We also applied spatial analysis of molecular variance implemented in SAMOVA 1.0 (Dupanloup et al., 2002) to the mtDNA data to explore population division. Based on an F-statistic, SAMOVA uses a simulated annealing procedure to determine groups of populations that are geographically and genetically homogeneous and maximally differentiated from each other (i.e., the configuration has the largest UCT). We tested population partitions (K) ranging from 2 to 8 with 100 to 300 initial conditions each based on 105 annealing permutations. Given that populations with small sample sizes might be erroneously identified as isolated groups in SAMOVA (Dupanloup, pers. comm.), we combined the localities with small sample sizes according to the same rules we used for calculating the pairwise UST-values. 2.3. Estimates of demographic parameters A coalescence-based program, IMa (Hey and Nielsen, 2007), was used to estimate the effective population sizes of two current populations and their common ancestral populations (h1, h2, and ha; h = 4 Nel), migration rates (m1 and m2; m = m/l), and divergence times (t = t l) between groups of populations determined from the procedures outlined above. The UPGMA phenogram based on pairwise UST values and SAMOVA suggested two possible group structures, a three-group model and a two-group model (see Section 3.1). The three-group model included CA, CWE, and NEE. The two-group model consisted of a combined CWE and NEE (termed ME) and CA. We estimated the demographic parameters associated with the various groupings in the two alternative models. We did not use IMa2 (Hey, 2010) because we cannot specify a tree topology for the three groups. A minimum of two independent analyses of >2 Â 107 steps after a burn-in of 106 steps were performed for each pairwise comparison. Plots of trend lines and the effective sample size values (ESS > 250) were examined to assess convergence in parameter estimates. The IMa estimates were based on all available mtDNA and ADAMTS6 sequence data combined. To convert the scaled demographic parameters to absolute values, we calculated the geometric mean of the substitution rates of ND2 and ADAMTS6 by multiplying the sequence lengths by 4 Â 10À8 substitutions/site/ year for ND2 (Arbogast et al., 2006) and 1.62 Â 10À9 substitutions/ site/year for ADAMTS6 (Ellegren, 2007; given the mean divergence of Z-linked introns between chicken and turkey is 1.2 times higher than that of autosomal introns, which have an average rate of 1.35 Â 10À9 substitutions/site/year) and assumed a generation time of 2 years (Stjernberg, 1979). The substitution rate used in this study was higher than widely used rates for avian mtDNA (Lovette,
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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2004; Weir and Schluter, 2008) but more appropriate for recent divergences (Ho et al., 2005; Arbogast et al., 2006; Herman and Searle, 2011; but see Emerson 2006). 2.4. Group delimitation using hypothesis testing We tested alternative population models using a coalescent simulation program, SIMCOAL 2.1.2 (Laval and Excoffier, 2004) to simulate ND2 sequences. The simulations were performed using the demographic parameters estimated from IMa based on mtDNA and ADAMTS6, i.e., current effective population sizes (the effective population size of mtDNA, Nef, was assumed to be half of the Ne of populations), migration rates, divergence times, exponential growth rates (calculated from the current and ancestral population sizes), a substitution rate of 4 Â 10À8 substitutions/site/year, and the generation time of two years. One two-group model and two three-group models were simulated (Fig. 2). In the latter case, two models were considered due to the uncertainty in gene flow from NEE to CWE based on the IMa analyses (see Section 3.1). One three-group model postulated no gene flow (Fig. 2a) and the other assumed a low level of gene flow (2 Â 10À6 per generation per individual; see Section 3.1) from NEE to CWE (Fig. 2b). Given that the dispersal distance of rosefinches is unlikely to span the entire geographic range, the widely distributed ME (in the two-group model; Fig. 2c) was not assumed to be panmictic. We simulated ME by connecting two subgroups with a substantial level of migration, 100 individuals per generation at present but decreasing exponentially backwards in time as the population size decreased (Fig. 2c). This level of migration is large enough to prevent population differentiation (Hudson and Coyne, 2002). The ratio of Ne for the two subgroups in ME was 12:1 (Fig. 2c) similar to that for CWE and NEE. We simulated 5000 datasets of 186 ND2 sequences (1041 bp) for each hypothesized model. The simulated datasets were analyzed using Arlequin 3.1 (Schneider et al., 2000) to calculate UST values (Excoffier et al., 1992) and the distribution and the upper and lower bounds of 95% ranges of these values were recorded. The UST values for simulated data were compared with the empirical UST to evaluate which model was most consistent with the observed data. 2.5. Species distribution modeling Online databases ORNIS and GBFI together with our own museum data resulted in 196 breeding localities (see Fig. S1), which we input into MAXENT v 3.2.2. (Phillips et al., 2006) to infer a SDM. Because the species has only colonized western Europe during the past few decades (Cramp and Perrins, 1994), we excluded
breeding records from Scandinavia, France, Spain and England. We obtained climatic data (19 layers) for present and LGM conditions from the Worldclim bioclimatic database (Hijmans et al., 2005). We ran MAXENT five times (using 30% of values for training) and examined the jackknifed contributions of each bioclimatic layer, picking seven layers (bioclim layers 1, 5, 9, 10, 11, 15 and 18) that contributed 5% or more to the total variation for the final analysis (Brown and Knowles, 2012). For the final model, we constructed a SDM from the average of 10 MAXENT runs using all locality points, which we displayed using DIVA-GIS ver. 7.1.7.2 (Hijmans et al., 2004). 2.6. Niche divergence tests We used the program ENMTools v.1.3 (Warren et al., 2010) to perform niche identity tests and background tests for whether taxa that were defined according to the genetic data (i.e., the CA, CWE and NEE groups) exhibit niche divergence or conservatism (or neither). The niche identity test assesses whether the similarity between ecological niches of two taxa is significantly different from a null distribution generated from random draws of pooled empirical occurrence points. The identity test often suggests that two taxa have significantly different niches (Godsoe, 2010; Warren et al., 2008). However, this inference is only true when the two groups tolerate the exact same set of environmental conditions and have the same suite of environmental conditions available to them (Warren et al., 2010). Because this is unlikely for allopatric populations that are distributed across environmental gradients, the background test determines whether two taxa are more or less similar than expected based on the differences in the environmental background where they occur. The background test determines whether an empirical niche similarity index between two taxa is significantly smaller (niche divergence) or greater (niche conservatism) than a null distribution of the niche similarity indices between one taxon and random points from the environment within the other taxon’s range; two null distributions result because the comparisons are done in both directions (Warren et al., 2010). For the background tests, we divided the large central area of rosefinch distribution into eastern (CWEE) and western (CWEW) groups to account further for the large geographic distance involved. 3. Results 3.1. Population structure The mtDNA network revealed that 9 of the 13 haplotypes from the Caucasus (CA) formed a clade, which was separated by a few steps from the remaining haplotypes (Fig. 3a). The haplotypes in
(a)
t= 39,200
Na = 63,000
(b)
t= 39,200
Na = 63,000
(c)
t =33,200
Na = 72,000
m= 2 × 10 -6
NCA = 83,000 NCWE = 3,516,000 NNEE = 308,000 NCA = 83,000 NCWE = 3,516,000 NNEE = 308,000 NCA = 72,000 NME = 3,990,000 + 333,000
Fig. 2. Outline of two three-group models (a and b) and one two-group model (c) developed to test hypothesized demographic histories for the common rosefinch. Na, NCA, NCWE, NNEE and NME indicate effective population sizes of ancestral, CA, CWE, NEE and ME groups, respectively. t indicates time of divergence in units of generations from present. Arrows indicate gene flow. The immigration rate (m) in the (b) model is shown in the figure. The dashed lines indicate that the groups are connected to each other with substantial levels of gene flow.
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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Fig. 3. Network of (a) mtDNA and (b) a Z-linked intron (ADAMTS6) haplotypes of the common rosefinch by the minimum spaning criterion. Colors on the network indicate the locations at which each haplotype was detected. Black circles indicate central-western Eurasian (CWE) haplotypes, white circles indicate northeastern Eurasian (NEE) ones, and gray circles indicate Caucasian (CA) ones. Open triangles indicate unsampled or extinct haplotypes. Sizes of circles are proportional to haplotype frequencies. Short lines indicate one mutation step.
northeastern Eurasia (NEE) were not separated from those in central-western Eurasia (CWE). Thus, the mtDNA network revealed limited geographic structure. The allele network for ADAMTS6 showed no geographic structure (Fig. 3b). The UPGMA phenogram based on the matrix of mtDNA pairwise UST values (see Table S2 for the UST values) clustered rosefinch populations into three distinct groups corresponding to CA, NEE, and CWE groups (Fig. 4). The SAMOVA supported a two-group structure, CA and all remaining populations (i.e., CWE plus NEE). The UCT value was highest when K = 2 (UCT = 0.349) and decreased as K increased. IMa analyses based on mtDNA, and mtDNA plus ADAMTS6, suggested recent isolation with little or no gene flow followed by population expansion (except for CA), for both the three-group and two-group models. In addition, the IMa analyses revealed that the values of demographic parameters for the two datasets differed in magnitude, with the combined data (i.e., mtDNA plus ADAMTS6) suggesting longer divergence times, greater effective population sizes and lower migration rates (Table S3). We used results based on the combined dataset in our simulations. For the three-group model, IMa revealed that the current population sizes of CWE (7,032,000; 95% credibility interval [CI] = 4,130,000 to 17,303,000) and NEE (616,000; 95% CI = 334,000–1,839,000) are significantly larger than that of the ancestral population (136,000; 95% CI = 58,000–240,000), whereas the current population size of CA
Fig. 4. UPGMA phenogram showing relationships among rosefinch population samples. The tree is reconstructed based on the matrix of UST values. The three clades correspond to the central-western Eurasian (CWE), northeastern Eurasian (NEE), and Caucasian (CA) groups. Populations with sample sizes smaller than five were combined with samples in the nearest and sufficiently large population. Therefore, DOR + TÖV is the combination of Dornod and Töv’s samples, IRK + KRY is that of Irkutsk and Krasnoyarsk, MED + MEZ is that of Medvedevo and Mezen, and MOS + KUR is that of Moscow and Kursk.
(167,000; 95% CI = 80,000–438,000) was not significantly larger than that of the ancestral population (Fig. 5a and b). There was little if any migration between any pair of groups (Fig. 5c–e). There could
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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Fig. 5. The marginal posterior probabilty distribution of the IMa parameters under the three-group model. The three groups are Caucasus (CA), central-western Eurasia (CWE) and northeastern Eurasia (NEE). The IMa analyses were based on mtNDA and a Z-linked gene (ADMATS6) combined. Effective population sizes, h, for CA, CWE, NEE and their ancestral populations are shown in (a and b). Migration rates, m, in two directions between CA and CWE, between CWE and NEE, and between CA and NEE in the unite of per generation per individual are shown in (c–e). Divergence times, t, for the three pairwise comparisons in the unite of year are shown in (f).
be some migration from NEE to CWE (2 Â 10À6 per generation per individual; 95% CI = $0 to 1.6 Â 10À5 [we could not reject the possibility of zero gene flow]; Fig. 5d). The divergence times between CA and CWE (78,300 years ago; 95% CI = 52,200–117,000 years ago), between CWE and NEE (78,800 years ago; 95% CI = 52,000– 117,200 years ago), and between CA and NEE (76,200 years ago; 95% CI = 42,200–141,700 years ago) were similar and recent (Fig. 5f), suggesting contemporaneous origins of the three groups (see Hung et al. 2012). The IMa results for the two-group model revealed that the current population size of ME (8,645,000; 95% CI = 5,396,000–18,196,000) was significantly larger than the ancestral population (147,000; 95% CI = 88,000–282,000), but that of CA (144,000; 95% CI = 70,000–394,000) was not. The IMa results showed no migration between the two groups. The estimated divergence time (66,400 years ago; 95% CI = 45,500–96,600 years ago) was similar to that of the three-group model. Comparison of the simulated and empirical data supported the three-group models over the two-group model (Fig. 6). The empirical UST value was within the 95% distribution range of UST values of the three-group models regardless of the level of gene flow
(Fig. 6a and b) but out of the 95% range of UST values for the two-group (Fig. 6c). Therefore, we could reject the two-group but not either of the three-group models. The similarity between the distributions of UST values for the two three-group models, one with and one without gene flow, suggested that the level of gene flow from NEE to CWE was negligible.
3.2. Current and LGM distributions predicted by SDM The AUC of the MAXENT distribution model was 0.88, indicating good quality in the predictions (AUC > 0.7 = informative; Baldwin, 2009; Swets, 1988). The SDM under current climatic conditions predicted the breeding range of common rosefinches including newly colonized areas in Scandinavia (Fig. 7a). Although the model predicts occurrence in France, Portugal and Spain the species has not yet become established in these areas, but there are sporadic records (Cramp and Perrins, 1994). Therefore, the predicted current distribution of common rosefinches in Europe was somewhat wider than the observed distribution but consistent with the trend
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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Fig. 6. Histograms of UST values for 5000 simulated sequence datasets. (a) Results from simulations of the three-group model without gene flow. (b) Results from simulation of the three-group model with a low level of gene flow from NEE to CWE. (c) Results from simulations of the two-group model. The dashed lines represent the 2.5 and 97.5 percentiles in the distribution. The black triangles represent the UST value of our empirical data.
of recent expansion towards the western and northwestern Palearctic (Cramp and Perrins, 1994; Payevsky, 2008). The predicted distribution at the LGM suggested that common rosefinches mainly occurred in four areas (i.e., refugia): (1) Kamchatka and Magadan, (2) southern Siberia, Mongolia, China and Japan, (3) Caucasus and (4) southern Europe (Fig. 7b). The first three predicted refugia sustainably or partially overlapped with the present distributions of the three haplotype groups. Comparing the extent of the present and LGM distributions suggested that the Caucasian population (CA) and Kamchatka and Magadan populations (corresponding to NEE) had not undergone expansion whereas the other populations (corresponding to CWE) expanded westwards since the LGM (Fig. 7).
niche conservatism in the eight pairwise background tests, which took into account the environment available to each group (Fig. 8).
4. Discussion Our re-analyses of the mtDNA data, and analyses of the mtDNA data plus the sex-linked sequences, support the existence of three groups of populations in the common rosefinch, namely the Caucasus, northeastern Eurasia, and central-western Eurasia. These three groups are not reciprocally monophyletic for either mtDNA or the Z-linked gene tree, suggesting that the rosefinches are at an early stage of diversification. Our estimates of gene flow were essentially zero, indicating that the groups are evolving independently. Hence we infer that speciation has commenced. In addition, the SDM implies that these three groups might have occupied distinct LGM refugia. Further supporting our hypothesis of the distinctness of these groups, we note that the three groups, CA, NEE and CWE, correspond to named subspecies, C. e. kubanensis, C. e. grebnitskii and C. e. erythrinus, respectively (Cramp and Perrins, 1994; Fig. 1). The subspecies C. e. kubanenesis is larger and more rosy-red colored
3.3. Niche divergence The pairwise niche identity tests (not shown) suggested that the niches of different groups of rosefinches were significantly different based on the niche similarity index, Schoener’s D (P < 0.001). However, we found no instances of either niche divergence or
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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Fig. 7. Predicted distributions of the common rosefinch (Carpodacus erythrinus) for (a) present and (b) LGM. Darker colors reflect areas with higher probabilities of occurrence.
than the nominate subspecies C. e. erythrinus, and C. e. grebnitskii has more red or carmine on its upperparts than C. e. erythrinus (Clement et al., 1993; Cramp and Perrins, 1994). A fourth subspecies, C. e. ferghanensis, represented only by our Almaty sample was not genetically distinct, and fell within C. e. erythrinus. Although we do not propose elevating these taxa to species, any analysis of recent trends in biodiversity should recognize their historical existence.
4.1. Recent history of common rosefinches revealed by phylogeography and SDM The application of SDMs to evolutionary studies is promising (Carnaval et al., 2009; Kozak et al., 2008) although their performance has been under debate (e.g., Araújo et al., 2009; Beale et al., 2008). Our SDM under current climatic condition predicted the occurrence of common rosefinches in western Europe even though our model did not incorporate breeding sites from this region. The fact that the species has recently become common in Scandinavia and has bred locally in other European areas (Cramp and Perrins, 1994; Payevsky, 2008), and that the considerable part of the predicted range conforms to the known distribution, suggests that our SDM is relatively robust. However, our SDM underestimated the distribution of this species in northeastern Eurasia and overestimated that in China and Japan when compared with the known distribution. The inconsistency may reflect limitations
of SDMs and/or the fact that our knowledge about the distribution of this species in these regions is incomplete. In general, it is difficult to determine the specific geographic locations of LGM refugia, irrespective of whether one uses a SDM or makes inferences from the extant phylogeographic pattern. We consider our SDM and genetic results to be reciprocally illuminating. Our SDM (Fig. 7) is a snapshot at the maximum of the last glacial period, which began ca. 100,000 years before (Lisiecki and Raymo, 2007), and hence it is unclear how many refugia existed during this period. Our genetic results suggested three recently (e.g., ca. 75,000 ybp) isolated groups (Figs. 4 and 6), which we think helps guide interpretation of the SDM. Assuming that the three groups originated prior to the LGM, we suggest that two refugia existed in the eastern Palearctic at the LGM, even though our SDM shows a relatively narrow gap (i.e., the coast near the northwestern tip of the Sea of Okhotsk) between them (Fig. 7b). However, many extant phylogroups are parapatrically distributed or separated by narrow gaps (e.g., Hung et al., 2012; Zink et al., 2008). The lack of sorting of mtDNA haplotypes from the Palearctic (excluding CA; Fig. 3a) coupled with the inference of negligible gene flow between NEE and CWE, is consistent with our estimate of divergence time (ca. 75,000 ybp). Haploid, non-recombining mtDNA gene trees require isolation lasting approximately Ne generations to reach reciprocal monophyly (Hudson and Coyne 2002). Given the large estimates of Ne for the two main Palearctic groups (7,032,000 and 616,000), considerable time would have to elapse before the mtDNA gene tree would become reciprocally
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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Fig. 8. Background tests for niche divergence. Arrows indicate observed niche similarity index (Schoener’s D) between two groups and are compared with a null distribution for the niche similarity indices between one group and random points from the range of the other group and vice versa. (a) Gray histogram indicates a null distribution of NEE versus the background of CWEE, and black indicates the opposite comparison. (b) Gray indicates a null distribution of CA versus the background of NEE, and black indicates the opposite comparison. (c) Gray indicates a null distribution of CA versus the background of CWEW, and black indicates the opposite comparison. (d) Gray indicates a null distribution of CWEW versus the background of CWEE, and black indicates the opposite comparison. Niche similarity values smaller than a null distribution indicate niche divergence, larger values indicate niche conservatism, and values within a null distribution indicate neither niche divergence nor niche conservatism.
monophyletic. Therefore, there has been insufficient time for the mtDNA gene tree to evolve to reciprocal monophyly. Given that the average Ne of Z-linked genes is three times greater than mtDNA, we expected that the ADSMTS6 gene tree would show less geographic structure than the mtDNA gene tree, which we observed. Combining coalescence and SDM analyses allowed additional insight into rosefinch population history. Our coalescence analyses revealed that CWE and NEE experienced population expansion, whereas CA did not (Fig. 5). Our SDM analyses suggested a similar history except that NEE had similar distributions between the present and LGM predictions. However, the degree of expansion for CWE was at least 10 times greater than that for NEE according to the coalescence analyses (Fig. 5), and from the SDM it would appear logical given the large area into which CWE expanded, and the relatively stable distribution of NEE. The predicted LGM occurrence of rosefinches in areas south of where they presently occur in southern Europe is relevant to past hypotheses about the distribution of genetic variation following glacial retreat. Hewitt (2004) suggested that genetic variability decreases in the direction of colonization from a refugium owing to sampling effects, termed ‘‘leading edge expansion.’’ However, if the refugium no longer has suitable habitat, as is the case for common rosefinches in southern Europe, this prediction is not testable. In this case, one might look to the southern extent of the current range as being the closest to refugial populations, and hence currently harboring the greatest genetic variability, but we lacked data for a strong test of this hypothesis. Thus, a SDM can modify predictions about post-glacial patterns of genetic variation. The SDM is consistent with a history of isolation for rosefinches in the Caucasus (Fig. 7). Compared to CWE and NEE, CA has a relatively smaller effective population size and has not experienced population expansion. These attributes can explain why
approximately 70% of haplotypes in CA form a clade in the mtDNA tree (Pavlova et al. 2005) and haplotype network (Fig. 3), whereas haplotypes in the other two groups do not. That is, lineage sorting is a function of Ne, and therefore one expects faster sorting in the CA group. We predict that if the isolation and current population size continues, the Caucasian population will be the first group to become a new species. This example illustrates that relatively small and isolated populations on islands, continental habitat islands, or mountaintops are potent grounds for lineage diversification. 4.2. Niche evolution between the recently diverged common rosefinch groups As the three rosefinch groups are in the early stages of speciation, our study can help to show whether ecological divergence drives speciation or accrues after speciation. We found no evidence for niche divergence, a result consistent with that for other groups of birds that are considerably more differentiated (Peterson et al., 1999; McCormack et al., 2010). The significant tests for niche identity coupled with the insignificant background tests reinforce the importance of considering environment availability when testing niche divergence (McCormack et al., 2010). In other words, the results imply that rosefinches in different areas do not have the same niche space available to them. The lack of support for niche divergence or conservatism may indicate that rosefinches can survive in varied habitats, as suggested by the significant niche identity tests. This may explain the recent population expansion of rosefinches shown by genetic data and current expansion to new ranges in Europe. On the other hand, given the general lack of niche divergence, one might expect that the groups would invade each other’s ranges. That is, during
Please cite this article in press as: Hung, C.-M., et al. Recent allopatric divergence and niche evolution in a widespread Palearctic bird, the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. (2012), http://dx.doi.org/10.1016/j.ympev.2012.09.012
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the ensuing 21,000 years since the LGM, and a dispersal distance typical for passerine birds of P1 km per generation (Barrowclough 1980), there would have been ample time for range expansion and homogenization of the three groups. However, our estimates of gene flow suggest this is not occurring. Hence it is possible that the forms exclude each other behaviorally (Waters, 2011) or we have not captured the most important niche dimensions. Acknowledgments We thank S. Rohwer for his roles in gathering specimens and A. Pavlova for doing the original analyses, and S. Birk for loans. K. Kozak and D. Shepard helped in conducting ecological niche modeling. T. Rodrigues assisted with map making. B. McKay, H. Vazquez and two anonymous reviewers helped to improve the manuscript. We are grateful to the University of Minnesota Supercomputing Institute for assistance with the computations. Support came from NSF (DEB 9707496, and DEB 0212832), FCT (PTDC/BIABEC/103435/2008) and the Dayton-Wilkie fund of the Bell Museum. Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.ympev.2012.09. 012. References
Araújo, M.B., Thuiller, W., Yoccoz, N., 2009. Reopening the climate envelope reveals macroscale associations with climate in European birds. Proc. Natl. Acad. Sci. USA 106, E45–E46. Arbogast, B.S., Drovetski, S.V., Curry, R.L., Boag, P.T., Seutin, G., Grant, P.R., Grant, B.R., Anderson, D.J., 2006. The origin and diversification of Galapagos mockingbirds. Evolution 60, 370–382. Avise, J.C., 2000. Phylogeography: The History and Formation of Species. Harvard University Press, Cambridge. Backström, N., Brandström, M., Gustafsson, L., Qvarnström, A., Cheng, H., Ellegren, H., 2006. Genetic mapping in a natural population of collared flycatchers (Ficedula albicollis): conserved synteny but gene order rearrangements on the avian z chromosome. Genetics 17, 377–386. Baldwin, R.A., 2009. Use of maximum entropy modeling in wildlife research. Entropy 11, 854–866. Barrowclough, G.F., 1980. Genetic and phenotypic differentiation in a wood warbler (genus Dendroica) hybrid zone. Auk 97, 655–668. Beale, C.M., Lennon, J.J., Gimona, A., 2008. Opening the climate envelope reveals no macroscale associations with climate in European birds. Proc. Natl. Acad. Sci. USA 105, 14908–14912. Brown, J.L., Knowles, L.L., 2012. Spatially explicit models of dynamic histories: examination of the genetic consequences of Pleistocene glaciation and recent climate change on the American pika. Mol. Ecol. 21, 3757–3775. Carnaval, A.C., Hickerson, M.J., Haddad, C.F.B., Rodrigues, M.T., Moritz, C., 2009. Stability predicts genetic diversity in the Brazilian Atlantic forest hotspot. Science 323, 785–789. Clement, P., Harris, A., Davis, J., 1993. Finches and Sparrows: An Identification Guide. Princeton University Press, Princeton. Cramp, S., Perrins, C.M., 1994. Handbook of the Birds of Europe, the Middle East and North Africa, vol. 5. Oxford University Press, Oxford. Dolman, G., Moritz, C., 2006. A multilocus perspective on refugial isolation and divergence in rainforest skinks (Carlia). Evolution 60, 573–582. Dupanloup, I., Schneider, S., Excoffier, L., 2002. A simulated annealing approach to define the genetic structure of populations. Mol. Ecol. 11, 2571–2581. Ellegren, H., 2007. Molecular evolutionary genomics of birds. Cytogenet. Genome Res. 117, 120–130. Emerson, B.C., 2006. Alarm Bells for the molecular clock? No support for Ho et al’.s model of time-dependent molecular rate estimates. Syst. Biol. 56, 337–345. Excoffier, L., Smouse, P., Quattro, J., 1992. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131, 479–491. Godsoe, W., 2010. Regional variation exaggerates ecological divergence in niche models. Syst. Biol. 59, 298–306. Herman, J.S., Searle, J.B., 2011. Post-glacial partitioning of mitochondrial genetic variation in the field vole. Proc. Roy. Soc. B 278, 3601–3607. Hewitt, G.M., 2000. The genetic legacy of the quaternary. Nature 405, 907–913. Hewitt, G.M., 2004. Genetic consequences of climatic oscillations in the quaternary. Philos. Trans. Roy. Soc. B 359, 183–195.
Hey, J., 2010. Isolation with migration models for more than two populations. Mol. Biol. Evol. 27, 905–920. Hey, J., Nielsen, R., 2007. Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics. Proc. Natl. Acad. Sci. USA 104, 2785–2790. Hijmans, R.J., Guarino, L., Bussink, C., Mathur, P., Cruz, M., Barrentes, I., Rojas, E., 2004. DIVA-GIS. Vsn. 7.1.7. A geographic information system for the analysis of species distribution data. <http://www.diva-gis.org>. Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G., Jarvis, A., 2005. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978. Ho, S.Y.W., Phillips, M.J., Cooper, A., Drummond, A., 2005. Time dependency of molecular rate estimates and systematic overestimation of recent divergence times. Mol. Biol. Evol. 22, 1561–1568. Hudson, R.R., Coyne, J.A., 2002. Mathematical consequences of the genealogical species concept. Evolution 56, 1557–1565. Hung, C.-M., Drovetski, S.V., Zink, R.M., 2012. Multilocus coalescence analyses support a mtDNA-based phylogeographic history for a widespread Palearctic passerine bird, Sitta europaea. Evolution 66, 2850–2864. Knowles, L.L., Alvarado-Serrano, D.F., 2010. Exploring the population genetic consequences of the colonization process with spatio-temporally explicit models: insights from coupled ecological, demographic and genetic models in montane grasshoppers. Mol. Ecol. 19, 3727–3745. Kozak, K.H., Graham, C.H., Wiens, J.J., 2008. Integrating GIS-based environmental data into evolutionary biology. Trends Ecol. Evol. 23, 141–148. Laval, G., Excoffier, L., 2004. SIMCOAL 2.0: a program to simulate genomic diversity over large recombining regions in a subdivided population with a complex history. Bioinformatics 20, 2485–2487. Librado, P., Rozas, J., 2009. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25, 1451–1452. Lisiecki, L.E., Raymo, M.E., 2007. Plio-Pleistocene climate evolution: trends and transitions in glacial cycle dynamics. Quat. Sci. Rev. 26, 56–69. Lovette, I.J., 2004. Mitochondrial dating and mixed support for the ‘‘2% rule’’ in birds. Auk 121, 1–6. McCormack, J.E., Zellmer, A.L., Knowles, L.L., 2010. Does niche divergence accompany allopatric divergence in Aphelocoma jays as predicted under ecological speciation?: insights from tests with niche models. Evolution 64, 1231–1244. Pavlova, A., Zink, R.M., Rohwer, S., 2005. Evolutionary history, population genetics, and gene flow in the common rosefinch (Carpodacus erythrinus). Mol. Phylogenet. Evol. 36, 669–681. Payevsky, V.A., 2008. Breeding and demographic parameters and range expansion of the common rosefinch (Carpodacus erythrinus). Ring 30, 63–69. Peterson, A.T., Sobersón, J., Sánchez-Cordero, V., 1999. Conservatism of ecological niches in evolutionary time. Science 285, 1265–1267. Phillips, S.J., Anderson, R.P., Schapire, R.E., 2006. Maximum entropy modeling of species geographic distributions. Ecol. Model. 19, 231–259. Polzin, T., Daneschmand, S.V., 2003. On Steiner trees and minimum spanning trees in hypergraphs. Oper. Res. Lett. 31, 12–20. Schluter, D., 2009. Evidence for ecological speciation and its alternative. Science 323, 737–741. Schneider, S., Roessli, D., Excoffier, L., 2000. Arlequin: A Software for Population Genetics Data Analysis. Version 2. Genetics and Biometry Lab, Dept of Anthropology, Univ of Geneva, Switzerland. <http://anthro.unige.ch/software/ arlequin/>. Sousa-Santos, C., Robalo, J.I., Collarrs-Pereira, M.-J., Almada, V.C., 2005. Heterozygous indels as useful tools in the reconstruction of DNA sequences and in the assessment of ploidy level and genomic constitution of hybrid organisms. DNA Sequence 16, 462–467. Stephens, M., Scheet, P., 2005. Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation. Am. J. Hum. Genet. 76, 449– 462. Stephens, M., Smith, N., Donnelly, P., 2001. A new statistical method for haplotype reconstruction from population data. Am. J. Hum. Genet. 68, 978–989. Stjernberg, T., 1979. Breeding biology and population dynamics of the scarlet rosefinch Carpodacus erythrinus. Acta Zool. Fennica 157, 1–88. Swets, J.A., 1988. Measuring the accuracy of diagnostic systems. Science 240, 1285– 1293. Tamura, K., Dudley, J., Nei, M., Kumar, S., 2007. MEGA4: molecular Evolutionary genetics analysis (MEGA) software version 4.0. Mol. Biol. Evol. 24, 1596–1599. Warren, D.L., Glor, R.E., Turelli, M., 2008. Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution 62, 2868– 2883. Warren, D.L., Glor, R.E., Turelli, M., 2010. ENMTools: a toolbox for comparative studies of environmental niche models. Ecography 33, 607–611. Waters, J.M., 2011. Competitive exclusion: phylogeography’s ‘elephant in the room’? Mol. Ecol. 20, 4388–4394. Weir, J.T., Schluter, D., 2008. Calibrating the avian molecular clock. Mol. Ecol. 17, 2321–2328. Zink, R.M., Pavlova, A., Drovetski, S., Rohwer, S., 2008. Mitochondrial phylogeographics of five widespread Eurasian bird species. J. Ornithol. 149, 399–413.
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