The systematics and biogeography of the Bearded Greenbuls (Aves: Criniger) reveals the impact of Plio-Pleistocene forest fragmentation on Afro-tropical avian diversity

The systematics and biogeography of the Bearded Greenbuls (Aves: Criniger) reveals the impact of... Abstract The biogeographical history of Afro-tropical lowland forests during the Plio-Pleistocene is characterized by pervasive fragmentation-coalescence cycling due to global climatic oscillations. Vicariance scenarios driven by forest fragmentation have long been hypothesized as major mechanisms for the creation and maintenance of Afro-tropical avian diversity. However, the timing and centre of diversification events remains unclear. We undertook the first molecular phylogenetic and biogeographic investigation of the avian genus Criniger, a group of understory birds endemic to the lowland forests of West and Central Africa. Utilizing DNA from 43 specimens and a combination of molecular and biogeographic methods, we constructed time-calibrated phylogenies and ancestral area estimations. We estimated a widespread origin for the genus, with a basal divergence dating to the late Miocene. All other speciation events were dated to the Pliocene. However, we recovered substantial geographic structuring of genetic diversity, dating to the Pleistocene, within both Western and Central Africa for three species. The biogeographic patterns observed in the genus Criniger are likely the result of allopatric diversification driven by forest fragmentation during the Plio-Pleistocene. The results of this study indicate that Afro-tropical forests harbour substantially higher levels of cryptic diversity and greater genetic complexity than previously hypothesized. Afro-tropics, Aves, Criniger, cryptic speciation, endemism, phylogeography, Pleistocene, Pliocene, refugia, systematics INTRODUCTION The Paleo-environmental history of the Guineo-Congolian lowland forests of Africa is characterized by retraction and expansion cycles relating to climatic oscillations of global humidity (see Plana, 2004 for a review). Between the late Miocene (~7 Mya) and early Pliocene (~3.5 Mya), Afro-tropical forests were in an expanded state, covering substantially more land area than at present (Maley, 1996). In response to a decrease in global humidity in the early Pliocene (~3.4 Mya), Guineo-Congolian lowland forests began a major retraction phase (deMenocal, 1995; Maley, 1996). Since the initiation of this period of retraction, Guineo-Congolian forests have been subject to several perturbations in global humidity relating to glacial cycling, characterized by step-like shifts in the amplitude of overall aridity with peaks at 2.8 (±0.2), 1.7 (±0.1) and 1.0 (±0.2) Mya (deMenocal, 2004). The consequences of this cyclical aridification on the Guineo-Congolian forests during the Plio-Pleistocene were episodes of severe fragmentation in which forests were isolated in refugial pockets. And indeed, palynological and distributional patterns of forest-dwelling taxa support the existence of multiple pockets of historical refugia throughout the Guineo-Congolian forests (palynological: Colyn, Gautier-Hion & Verhaven, 1991; Maley, 1996, 2001; Anhuf et al., 2006; distributional: Diamond & Hamilton, 1980; Crowe & Crowe, 1982; Mayr & O’Hara, 1986; Prigogine, 1988; Hamilton & Taylor, 1991; Happold, 1996; Levinsky et al., 2013). However, the size, location and number of Plio-Pleistocene refugia remain controversial, making further biogeographic investigations of Afro-tropical forest taxa crucial to resolving this picture. Early investigations of avian distributions across African lowland forests relied on the Pleistocene Forest Refuge Hypothesis (PFRH; Haffer, 1969) as the causal agent of observed patterns (Diamond & Hamilton, 1980; Crowe & Crowe, 1982; Mayr & O’Hara, 1986). Developed initially to explain distributional patterns in South America, the hypothesis outlines a scenario of allopatric diversification specific to the Pleistocene [A recent adjustment of the Plio-Pleistocene boundary has been formally accepted, with the new beginning of the Pleistocene Epoch set at 2.58 Mya, as opposed to the historical boundary of c. 1.8 Mya. However, due to the fact that hypotheses and concepts introduced above as being relevant to the discussion of Plio-Pleistocene diversification relate to the 1.8 Mya boundary, we have chosen to use that date as the transition here, for consistency of context.] (defined at that time as 1.8 Mya–11.8 Kya), in which lowland forest taxa became isolated in refugia during forest fragmentation periods, which in turn promoted allopatric speciation or in some cases, subspecific phenotypic variation. Research assessing this hypothesis in Africa favoured the investigation of (1) taxa with restricted ranges (i.e. not widespread species) and (2) taxa which display plumage variation across their range. In both instances, patterns were assumed to have derived from isolation in refugia. On the other hand, widespread species which lacked obvious phenotypic variation were viewed as ‘uninformative’ with regards to the PFRH. Indeed, 107 taxa are specifically listed as ‘uninformative’ in this regard by Mayr & O’Hara (1986). An alternative refugial hypothesis, made possible with the early proliferation of molecular divergence estimates, is the Montane Speciation Hypothesis (MSH) (Fjeldså, 1994; Fjeldså & Lovett, 1997; Roy, 1997; Roy, Sponer & Fjeldså, 2001; Fjeldså et al., 2007; Fjeldså & Bowie, 2008). These investigations revealed that many lineages of montane avifauna were relatively young (latest Miocene or younger) compared with lowland forest lineages which were dated as ‘ancient’ (~12–20 Mya). The MSH shifted the centre of diversification events away from the lowland forests and into montane regions where topographic habitat complexity and microclimatic stability during forest fragmentation were assumed to promote speciation. In subsequent forest expansion periods, species which diverged in the Afro-montane regions dispersed into nearby lowland forests where further diversification was minimal. The MSH views the Guineo-Congolian lowland forests as ‘evolutionary museums’, where species accumulated over time and persisted, with little change, since the Miocene. An early consequence of the MSH and the ‘evolutionary museum’ concept were less interest in the lowland forests role as a diversification centre which can, in part, account for the relative dearth of investigations focused on endemic lowland avifauna. However, over the past decade, investigations have begun to present a pattern that counters the ‘evolutionary museum’ concept and provides support for a more diverse picture of lowland forest diversity (Illadopsis: Nguembock et al., 2009; Sheppardia: Voelker, Outlaw & Bowie, 2010; Stiphrornis: Voelker et al., 2016b; Sylvietta: Huntley & Voelker, 2017). For instance, the widespread, phenotypically monotypic Green Hylia (Hylia prasina) displays deep genetic divergences linked to highly discreet geographic structure across Afro-tropical forest blocks (Marks, 2010). A recent investigation of the avian genus Bleda, a lowland forest endemic, found substantial geographic structuring and genetic divergences dating to the Plio-Pleistocene in three of the five species of that genus (B. syndactylus, B. eximius, B. canicapillus; Huntley & Voelker, 2016). Additionally, varying levels of cryptic diversification have also been demonstrated in several mammalian taxa (Sylvisorex: Quérouil et al., 2003; Lemniscomys: Nicolas et al., 2008; Praomys: Bryja et al., 2010; Nicolas et al., 2011; Crocidura: Jacquet et al., 2015; Grammomys: Bryja et al., 2016; Manis tricuspis: Gaubert et al., 2016). Alternatively, and in conjunction with traditional refugial scenarios, two additional sources of genetic diversification have been demonstrated across Guineo-Congolian forest blocks. First, early biogeographers pointed out the disjunction between West African and Central African species distributions (Diamond & Hamilton, 1980; Crowe & Crowe, 1982; Mayr & O’Hara, 1986). It has long been hypothesized that the Dahomey Gap (Fig. 1A), a broad savannah corridor breaking the lowland forests into two blocks (Salzmann & Hoelzmann, 2005), has been a major barrier to gene flow in the region. Recent investigations have recovered geographic structuring supporting an east-west vicariance scenario for several avian species (Campethera: Fuchs & Bowie, 2015; Dicrurus: Fuchs, Fjeldså & Bowie, 2017). Secondly, the Riverine Barrier Hypothesis (RBH) proposes that large river systems may act as barriers to gene flow for populations across rivers (Wallace, 1852). Evidence for the RBH in Africa was demonstrated by a comparative study which recovered genetic divergence patterns in four out of ten avian species distributed across the Congo River (Voelker et al., 2013). More broadly, investigations of several vertebrate taxa with ranges straddling other substantial river systems (e.g. the Niger, Sanaga and Ogooué rivers) have found evidence for varying levels of diversification supporting the RBH (rodents: Kennis et al., 2011; Nicolas et al., 2012; Bohoussou et al., 2015; Jacquet et al., 2015; bats: Hassanin et al., 2014; birds: Fuchs & Bowie, 2015; Huntley & Voelker, 2016; Fuchs et al., 2017). Figure 1. View largeDownload slide A, approximate current Guineo-Congolian lowland forest cover and locations of forest refugia during the Last Glacial Maximum, as suggested by Maley (1996), as well as dashed delineations of traditional lowland forest blocks. Range maps for currently recognized species within Criniger along with sampling points: B, C. calurus; C, C. olivaceus; D, C. barbatus; E, C. choloronotus; F, C. ndussumensis. Forest block abbreviations: UGF, Upper Guinean forest block; LGF, Lower Guinean forest block. Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Figure 1. View largeDownload slide A, approximate current Guineo-Congolian lowland forest cover and locations of forest refugia during the Last Glacial Maximum, as suggested by Maley (1996), as well as dashed delineations of traditional lowland forest blocks. Range maps for currently recognized species within Criniger along with sampling points: B, C. calurus; C, C. olivaceus; D, C. barbatus; E, C. choloronotus; F, C. ndussumensis. Forest block abbreviations: UGF, Upper Guinean forest block; LGF, Lower Guinean forest block. Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Collectively, these recent studies cast doubt on the veracity of the ‘evolutionary museum’ concept as a sweeping explanation for patterns of diversity in Guineo-Congolian lowland forests, and instead point to lowland forests as regions harbouring complex genetic patterns. Therefore, it is important that further investigations of African forest taxa be undertaken to determine the scope and potential role of historic mechanisms within lowland forests in creating genetic diversity. The Bearded Greenbuls (genus: Criniger), provide an excellent model for further investigations of lowland forest patterns. This genus formerly consisted of ten Afro-Asian species, but recent investigations of the family Pycnonotidae found evidence for moving the Asian species into a separate genus (Alophoixus), thus making Criniger an entirely African group (Pasquet et al., 2001; Moyle & Marks, 2006). Criniger currently consists of five understory bird species all endemic to Afro-tropical lowland forests. The Red-tailed Greenbul (C. calurus) is a widespread species inhabiting all regions of the Guineo-Congolian lowland forests (Fig. 1B). Criniger calurus encompasses three subspecies: C. c. verrauxi (Senegal to south-west Nigeria), C. c. calurus [south-west Nigeria to western Democratic Republic of Congo (DRC)] and C. c. emini (western DRC to eastern Uganda). Two members of Criniger are West African endemics, the Yellow-bearded Greenbul (C. olivaceus) inhabiting the Upper Guinean forests (Fig. 1C), and the Western Bearded Greenbul (C. barbatus) which can be found in both the Upper and a relatively small portion of the Lower Guinean forests (Fig. 1D). The Eastern Bearded Greenbul (C. chloronotus) displays a disjunction within its range, with two main populations separately inhabiting areas east and west of Ivory Coast (Fig. 1E). However, it is possible that this disjunct pattern is artificial, given the general scarcity of avian records from the Ivory Coast. The final species, the White-bearded Greenbul (C. ndussumensis), inhabits both the Lower Guinean and Congo forests, while staying mostly north of the Congo River within the latter (Fig. 1F). To date, no investigation of the molecular phylogenetics of the genus Criniger has been published. While morphological and ecological evidence has traditionally recognized at least four species, with C. barbatus and C. chloronotus as sister species (Sibley & Monroe, 1990; Keith, 1992; Dowsett & Forbes-Watson, 1993), several hypotheses regarding the taxonomic status and relationship of C. ndussumensis to other Criniger species have been offered. Criniger ndussumensis has been considered to be conspecific with C. olivaceus (Dowsett & Forbes-Watson, 1993; Dowsett-Lemaire & Dowsett, 2001), a subspecies of C. olivaceus (Dowsett-Lemaire & Dowsett, 1991), or completely invalid as a taxon (Brosset & Erard, 1986). A molecular phylogenetic investigation by Beresford (2002) utilizing the mitochondrial cytochrome-b gene and a fragment of the nuclear beta-fibrinogen gene recovered evidence confirming (1) the sister relationship between C. barbatus and C. chloronotus and (2) that C. ndussumensis deserves full species status. However, despite the adoption of the result of Beresford’s molecular investigation by most current classifications, the study was never published. Therefore, we feel it vital to re-visit earlier hypotheses within the genus Criniger with a larger molecular data set than utilized by Beresford. Here we undertake the first investigation of the systematics and biogeography of the genus Criniger. As understory-dwelling birds with low vagility, Criniger species are potentially more susceptible to forest fragmentation events and as such are well positioned to retain the stamp of past refugial-driven diversification events (Lees & Peres, 2009; Kahindo, Bates & Bowie, 2017). Furthermore, one genus member, C. calurus, is a widespread morphologically monotypic species specifically included in Mayr & O’Hara’s (1986) list of 107 ‘uninformative’ taxa. Our study goals are three-fold. First, we examine the molecular phylogenetics of the genus Criniger. Second, we explore the biogeographic patterns displayed within Criniger in relation to broad patterns and diversification timing within lowland forests. Third, we investigate the phylogeography of each species for patterns of genetic diversification across Guineo-Congolian lowland forest blocks, with the results from C. calurus being a direct test of Mayr & O’Hara’s (1986) assertion that widespread species lacking geographically structured, phenotypic variation are ‘uninformative’ for investigations of historic Afro-tropical forest diversification. METHODS Taxon sampling and molecular data We gathered 43 tissue samples of Criniger from museum collections (C. calurus = 24, C. ndussumensis = 7, C. chloronotus = 4, C. olivaceus = 4, C. barbatus = 4; Supporting Information, Table S1). In addition, four taxa were chosen from within Pycnonotidae, to which Criniger belongs, as outgroups (Eurillas latirostris, Phyllastrephus albigularis, Bleda syndactylus and Baeopogon indicator). These species were all found to be closely related to Criniger in a recent phylogeny of the Pycnonotidae (Johansson et al., 2007). We extracted whole genomic DNA from fresh tissue using proteinase K digestion according to the manufacturer’s instructions (DNeasy Blood and Tissue Kit, Qiagen, Valencia, CA). We used polymerase chain reaction (PCR) to amplify two mitochondrial (mtDNA) loci: nicotinamide adenine dinucleotide dehydrogenase subunit-2 (ND2) and cytochrome oxidase b (cyt b) and two nuclear loci: transforming growth factor β2 intron-5 (TGF β2), Myoglobin intron-2 (MB2). We used standard published primers and protocols for each gene (see Supporting Information, Table S2). Bidirectional single-pass Sanger sequencing, using the same primer sets as utilized for PCR (Supporting Information, Table S2), were performed using ABI Big Dye Terminator v3.1 at the Beckman-Coulter Genomics facility (Danvers, MA). Both mitochondrial loci were aligned by eye and translation was verified using Sequencer 4.9 (Gene Codes Corporation, Ann Arbor, MI). Nuclear loci were aligned using MUSCLE in the Geneious 8.1 platform (Biomatters Ltd; http://www.geneious.com, Kearse et al., 2012). Phylogenetic analysis and divergence dating Phylogenies were derived from two concatenated data sets: (1) a mitochondrial-only data set with all individuals (n = 43) and (2) a subset of individuals (n = 24) for which we sequenced four loci. We used PartitionFinder (Lanfear et al., 2014) to determine best fit models of evolution and the most appropriate partitioning schemes for both data sets. Maximum likelihood (ML) analyses were performed using RAxML 8.0 (Stamatakis, 2014) using the GTR + G model option and support was assessed using the rapid bootstrap algorithm with 1000 replicates. Bayesian inference was performed using MrBayes 3.2.5 (Huelsenbeck & Ronquist, 2001) using two runs of four Markov chain Monte Carlo (MCMC) chains of 10 million generations, sampled every 2000 generations. Tracer v1.6 (Rambaut et al., 2014) was used to visualize post-run statistics and determine if stationarity was reached, and for estimating an appropriate burn-in. Species tree analysis and divergence dating estimates for a further reduced four-gene data set (n = 24) were run in BEAST v2.3 (Drummond et al., 2012), using the standard BEAST template for divergence estimates and the *BEAST template for species tree analysis, respectively. We note here that no fossil calibration is available for Criniger; therefore, a relaxed, lognormal clock was utilized with lineage substitution rates (per lineage/million years) for three of the four genes gathered from Lerner et al. (2011) (ND2 = 0.029, cyt b = 0.014, TGF β2 = 0.0017) and set a substitution rate of 0.002 for MB2 as previously employed by Voelker et al. (2016a). Standard deviations (SDs) for both mitochondrial genes and TGF β2 (cyt b = 0.001; ND2 = 0.0025; TGF β2 = 0.0020) followed Lerner et al. (2011) while we used an SD of 0.002 for MB2. Both BEAST analyses (standard BEAST and *BEAST) utilized a normal Yule process speciation prior and linear population function with constant root in two MCMC runs of 50000000 generations (sampled every 2500 generations), with a 25% burn-in. Both runs were combined using LogCombiner v2.3 (Drummond et al., 2012) and subsequently evaluated in Tracer v1.6 to measure the posterior effective sample size (ESS), as well as the 95% confidence interval for divergence dating. The combined tree topology was analysed in TreeAnnotator v2.3 (Drummond et al., 2012). Haplotype networks To further assess phylogeographic patterns within the genus Criniger, we created median-joining haplotype networks based on the ND2 data set using Network v4.6.1.3 (Fluxus-Engineering) for C. calurus, C. chloronotus and C. barbatus individuals, as these species showed discrete intraspecific structure in preliminary phylogenetic analyses. The resulting network was tested for unnecessary median vectors using the most probable (MP) post-processing option. Genetic distances, in the form of average uncorrected p-distances for the ND2 data among clades recovered from the mtDNA Bayesian analysis, were calculated using Mega6 (Tamura et al., 2013). Historical biogeography Ancestral range estimation was performed using the BioGeoBEARS package in the R statistical program (Matzke, 2013a, b). We made use of BioGeoBEARS ability to run two basic models of ancestral area reconstruction, the DEC and DEC + J models. The DEC (dispersal-extinction cladogenesis) model utilizes two parameters: the dispersal rate (range expansion) and the extinction rate (range contraction), while fixing the cladogenesis model. The second model DEC + J uses the same parameters as the DEC model while adding a third free parameter (J) corresponding to long-distance dispersal. This free parameter allows one daughter lineage to move to a non-adjacent area outside of the ancestral range. We were then able to compare the two models (DEC vs. DEC + J) using a likelihood ratio test (LRT). We coded each lineage as being present or absent in the three widely recognized lowland forest blocks: the Upper Guinean, Lower Guinean and Congo forests (Fig. 1), and utilized an adjacency matrix to inform BioGeoBEARS of the geographical separation between the Upper Guinean and Congo forests. RESULTS Molecular data and phylogenetic analyses The mitochondrial data set (ND2 and cyt b) contained 42 individuals and 2054 total amplified base pairs (bp; ND2 = 1029 bp and cyt b = 1025 bp), while the four-gene data set contained 24 individuals and 3452 bp (mtDNA, MB2 = 738 bp, TGF β2 = 660 bp) (see Supporting Information, Table S1 for all voucher and GenBank accession numbers). We recovered the first strongly supported, multilocus ML and Bayesian trees for the genus Criniger. ML and Bayesian analyses of the mitochondrial-only data set (Fig. 2) and four-gene data set (Supporting Information, Fig. S1) produced phylograms with congruent topologies. ML and Bayesian phylograms produced independently for each nuclear locus as well as for a combined nuclear data set differed slightly in topology. The Bayesian MB2 phylogeny recovered well-supported [posterior probability (PP) ≥ 0.97] sister relationships similar to the mtDNA and four-gene data set; however, the basal divergence results in a polytomy (Supporting Information, Fig. S2). The RAxML analysis produced a congruent topology for the MB2 locus, albeit with moderately lower support at the break between C. calurus and C. ndussumensis + C. olivaceus (bootstrap value = 85) (Supporting Information, Fig. S2). Additionally, the Bayesian TGF β2 phylogeny recovered a well-supported pattern in which C. ndussumensis + C. olivaceus is sister to the remaining species (Supporting Information, Fig. S3). However, while the ML analysis for TGF β2 produced identical relationships, support was generally lower. The phylogeny constructed by both the Bayesian and ML analyses is topographically congruent with the MB2 tree; however, support at the basal node of C. calurus displayed lower support (PP = 0.80; bootstrap value = 70) (Supporting Information, Fig. S4). In both the mtDNA-only and four-gene combined phylogeny (Fig. 2 and Supporting Information, Fig. S1), five lineages were recovered with strong support (>0.97 PP), reflecting the five currently recognized species of Criniger. We recover a phylogenetic pattern where an initial divergence separates the five clades into two major groups. The first consists of C. calurus, C. olivaceus and C. ndussumensis, with the latter two species being sister taxa. The second major group consists of the two remaining species, C. chloronotus and C. barbatus (Fig. 2 and Supporting Information, Fig. S1). Figure 2. View largeDownload slide Maximum likelihood and Bayesian molecular phylogenies of the genus Criniger utilizing only the mitochondrial data set (cyt b and ND2). Values above the nodes represent posterior probabilities (* = posterior probability of 1.0) and those below represent bootstrap support values (* = 100). Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Figure 2. View largeDownload slide Maximum likelihood and Bayesian molecular phylogenies of the genus Criniger utilizing only the mitochondrial data set (cyt b and ND2). Values above the nodes represent posterior probabilities (* = posterior probability of 1.0) and those below represent bootstrap support values (* = 100). Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Both phylogenies (mtDNA-only and four-gene) reflect the same patterns of intraspecific diversification in Criniger (Fig. 2 and Supporting Information, Fig. S1). The phylogeny produced by the more densely sampled mitochondrial-only data set shows two patterns of intraspecific diversification amongst the five recovered species: (1) limited structure with shallow divergence estimates and (2) substantial structure with deep divergences. Pertaining to the first pattern, we find little to no structure in either C. ndussumensis or C. olivaceus, as both have shallow divergences (Fig. 2). We did recover two subclades for C. ndussumensis, one from Gabon and the other containing individuals from the DRC, Central African Republic (CAR) and Equatorial Guinea; however, these subclades differ by just 0.2% uncorrected p-distance (Table 1) and as such have no support (Fig. 2). Criniger olivaceus displays limited structure between a Liberian group and two individuals from Ghana, separated by an uncorrected p-distance of only 0.4% (Table 1), with no support (Fig. 2). Table 1. Uncorrected pairwise distances for ND2 among and within five Criniger species   1  2  3  4  5  6  7  8  9  10  11  1. calurus (Ghana)                        2. calurus (SLL)  0.001                      3. calurus (EGG)  0.048  0.047                    4. calurus (DRC1 + CAR)  0.066  0.065  0.058                  5. calurus (DRC2)  0.069  0.068  0.062  0.042                6. chloronotus (DRC)  0.136  0.137  0.131  0.137  0.138              7. chloronotus (EGG)  0.142  0.141  0.138  0.142  0.141  0.052            8. barbatus (Ghana)  0.139  0.140  0.128  0.141  0.144  0.092  0.103          9. barbatus (SLL)  0.134  0.135  0.129  0.138  0.142  0.082  0.097  0.055        10. ndussumensis (Gabon)  0.124  0.123  0.117  0.125  0.121  0.138  0.144  0.143  0.149      11. ndussumensis (DRC + EG + CAR)  0.124  0.123  0.118  0.126  0.122  0.139  0.145  0.143  0.150  0.002      1  2  3  4  5  6  7  8  9  10  11  1. calurus (Ghana)                        2. calurus (SLL)  0.001                      3. calurus (EGG)  0.048  0.047                    4. calurus (DRC1 + CAR)  0.066  0.065  0.058                  5. calurus (DRC2)  0.069  0.068  0.062  0.042                6. chloronotus (DRC)  0.136  0.137  0.131  0.137  0.138              7. chloronotus (EGG)  0.142  0.141  0.138  0.142  0.141  0.052            8. barbatus (Ghana)  0.139  0.140  0.128  0.141  0.144  0.092  0.103          9. barbatus (SLL)  0.134  0.135  0.129  0.138  0.142  0.082  0.097  0.055        10. ndussumensis (Gabon)  0.124  0.123  0.117  0.125  0.121  0.138  0.144  0.143  0.149      11. ndussumensis (DRC + EG + CAR)  0.124  0.123  0.118  0.126  0.122  0.139  0.145  0.143  0.150  0.002    Country abbreviations: SLL, Sierra Leone/Liberia; EGG, Equatorial Guinea + Gabon; DRC, Democratic Republic of the Congo; CAR, Central African Republic; EG, Equatorial Guinea. View Large Table 1. Uncorrected pairwise distances for ND2 among and within five Criniger species   1  2  3  4  5  6  7  8  9  10  11  1. calurus (Ghana)                        2. calurus (SLL)  0.001                      3. calurus (EGG)  0.048  0.047                    4. calurus (DRC1 + CAR)  0.066  0.065  0.058                  5. calurus (DRC2)  0.069  0.068  0.062  0.042                6. chloronotus (DRC)  0.136  0.137  0.131  0.137  0.138              7. chloronotus (EGG)  0.142  0.141  0.138  0.142  0.141  0.052            8. barbatus (Ghana)  0.139  0.140  0.128  0.141  0.144  0.092  0.103          9. barbatus (SLL)  0.134  0.135  0.129  0.138  0.142  0.082  0.097  0.055        10. ndussumensis (Gabon)  0.124  0.123  0.117  0.125  0.121  0.138  0.144  0.143  0.149      11. ndussumensis (DRC + EG + CAR)  0.124  0.123  0.118  0.126  0.122  0.139  0.145  0.143  0.150  0.002      1  2  3  4  5  6  7  8  9  10  11  1. calurus (Ghana)                        2. calurus (SLL)  0.001                      3. calurus (EGG)  0.048  0.047                    4. calurus (DRC1 + CAR)  0.066  0.065  0.058                  5. calurus (DRC2)  0.069  0.068  0.062  0.042                6. chloronotus (DRC)  0.136  0.137  0.131  0.137  0.138              7. chloronotus (EGG)  0.142  0.141  0.138  0.142  0.141  0.052            8. barbatus (Ghana)  0.139  0.140  0.128  0.141  0.144  0.092  0.103          9. barbatus (SLL)  0.134  0.135  0.129  0.138  0.142  0.082  0.097  0.055        10. ndussumensis (Gabon)  0.124  0.123  0.117  0.125  0.121  0.138  0.144  0.143  0.149      11. ndussumensis (DRC + EG + CAR)  0.124  0.123  0.118  0.126  0.122  0.139  0.145  0.143  0.150  0.002    Country abbreviations: SLL, Sierra Leone/Liberia; EGG, Equatorial Guinea + Gabon; DRC, Democratic Republic of the Congo; CAR, Central African Republic; EG, Equatorial Guinea. View Large Pertaining to the second pattern, the remaining three species in the mitochondrial-only phylogeny, C. calurus, C. chloronotus and C. barbatus, display substantial structuring with deep divergences. The widespread C. calurus is divided into four highly supported subclades corresponding to three discrete geographical regions and the three recognized subspecies (Fig. 2). We recover two subclades representing Congolian forest taxa (DRC1 and DRC2; C. c. emini) as sister to two subclades comprising Lower Guinean forest taxa (Equatorial Guinea + Gabon; C. c. calurus) or Upper Guinean forest taxa (Sierra Leone + Liberia + Ghana; C. c. verrauxi; Fig. 2). These four subclades have substantial average uncorrected p-distances between them (5.8–6.8%; Table 1). The DRC1 subclade is composed of six individuals collected south of the Congo River, three collected north of the river and one individual from the CAR, while the DRC2 subclade is composed of five individuals from the northern banks of the Congo River and only one individual from south of the river (Fig. 2). Despite the general overlap in distribution, these two DRC subclades are separated by an average uncorrected p-distance of 4.2% (Table 1). The Lower Guinean forest subclade (Equatorial Guinea + Gabon) is separated by an uncorrected p-distance of 4.7% from its Upper Guinean sister subclade (Table 1). Subclades within C. chloronotus and C. barbatus show similar strongly supported and discrete geographic structuring with substantial genetic divergence (Fig. 2). A genetic break similar to C. calurus is recovered in C. chloronotus, separating Lower Guinean individuals from those in the DRC, including a similar uncorrected p-distance of 5.2% (Fig. 1 and Table 1). Criniger barbatus, an Upper Guinean forest endemic, shows a strongly supported divergence between a subclade of individuals from Ghana and a subclade from Sierra Leone/Liberia, with an average uncorrected p-distance of 5.5% between them (Table 1). Divergence estimates The species tree analysis (*BEAST) with molecular divergence analysis recovered a strongly supported (≥0.99) topology congruent (Fig. 3) with both mtDNA-only and four-gene Bayesian analyses. The molecular clock analysis recovered a late Miocene (~6.2 Mya) basal divergence within Criniger. We recover Pliocene ages for the divergence of C. calurus from C. ndussumensis + C. olivaceus (~5.1 Mya) and between C. barbatus and C. chloronotus (~3.2 Mya; Fig. 3). The initial diversification of C. calurus lineages and the divergence of C. ndussumensis and C. olivaceus from a common ancestor are dated to the latest Pliocene (~1.9 Mya). All remaining intraspecific diversification events recovered within the genus are estimated to have occurred within the Pleistocene (Fig. 3). Figure 3. View largeDownload slide Species tree from *BEAST with molecular clock estimates of lineage divergence dates for the genus Criniger, based on evolutionary rates from Lerner et al. (2011) (cyt b, ND2, TGF β2) and Voelker et al. (2016a) (MB2). Nodal values are posterior probabilities (* = 1.0) and nodal bars represent the 95% highest posterior density intervals. BioGeoBEARS ancestral range estimations are represented at each node and current recognized range is bracketed for each species. Area abbreviations: UG, Upper Guinean; LG, Lower Guinean; C, Congo. Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Figure 3. View largeDownload slide Species tree from *BEAST with molecular clock estimates of lineage divergence dates for the genus Criniger, based on evolutionary rates from Lerner et al. (2011) (cyt b, ND2, TGF β2) and Voelker et al. (2016a) (MB2). Nodal values are posterior probabilities (* = 1.0) and nodal bars represent the 95% highest posterior density intervals. BioGeoBEARS ancestral range estimations are represented at each node and current recognized range is bracketed for each species. Area abbreviations: UG, Upper Guinean; LG, Lower Guinean; C, Congo. Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Haplotype network The ND2 haploytpe networks derived for C. barbatus, C. calurus and C. chloronotus all display geographically discrete haplogroups separated by substantial numbers of mutations (Fig. 4). The ND2 network for C. barbatus (restricted to Upper Guinean forests) estimates two haplogroups: one consisting of individuals from Sierra Leone/Liberia, and another from Ghana, with 56 mutations separating them (Fig. 4B). The network for C. calurus (Fig. 4C) produced four distinct haplogroups corresponding to the subclades recovered in the Bayesian analysis: an Upper Guinean (Sierra Leone/Liberia + Ghana), a Lower Guinean (Equatorial Guinea + Gabon) and two Congo haplogroups, one representing a CAR haplotype plus five DRC individuals and one consisting of nine DRC individuals, with a substantial number of mutations (N = 44) separating these two DRC groups. Overall, the western most haplogroup (Upper Guinean) is separated by 117 mutational steps from the DRC2 haplogroup (Fig. 4). Lastly, we recover two haplogroups for C. chloronotus (Fig. 4D). These are separated by 53 mutational steps, with one haplogroup representing Lower Guinean individuals (Equatorial Guinea + Gabon) and the other representing individuals from south of the Congo River in the DRC. Figure 4. View largeDownload slide A, sample locations pertaining to median-joining networks of Criniger (B), C. barbatus (C) and C. chloronotus (D) using the ND2 data set. Hash marks between haplotypes represent mutational steps and lack thereof represent one mutation. Unfilled circles represent missing haplotypes. Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Figure 4. View largeDownload slide A, sample locations pertaining to median-joining networks of Criniger (B), C. barbatus (C) and C. chloronotus (D) using the ND2 data set. Hash marks between haplotypes represent mutational steps and lack thereof represent one mutation. Unfilled circles represent missing haplotypes. Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Ancestral area estimates The DEC model was not determined to be significantly better than the DEC + J model using a LRT [Χ2 = 3.84; P-value (0.05) = 0.052]. Overall, the ancestral area estimation suggests a widespread origin (all three forest blocks) for the basal divergence of C. chloronotus + C. barbatus from the remaining species (Fig. 3). The analysis further estimates a scenario in which the ancestors of the C. chloronotus + C. barbatus clade, the C. olivaceus + C. ndussumensis clade, and C. calurus were distributed across all three forest blocks (UG + LG + C). Subsequently, our results indicate a diversification pattern in which widespread (UG + LG + C) ancestors diverged across the Dahomey Gap (Fig. 1), resulting in C. barbatus and C. olivaceus occupying the forests west of the gap (UG) and C. chloronotus and C. ndussumensis inhabiting the forests east of the gap (LG + C). For C. calurus, the analysis estimates the divergence of a widespread ancestor into a clade occupying the Upper Guinea + Lower Guinean forest blocks and one occupying the Congo forest (Fig. 3). DISCUSSION Systematics In agreement with Beresford (2002), we recover all five currently recognized species of Criniger as strongly supported monophyletic lineages. Consistent with current taxonomic classifications based on Beresford’s study, we recover a strongly supported sister-species relationship between C. barbatus and C. chloronotus in both the mtDNA-only and four-gene phylogenies (Fig. 2 and Supporting Information, Fig. S1). Both analyses recover a well-supported clade of C. ndussumensis as sister to C. olivaceus, with a substantial uncorrected p-distance between the two of ~5.5% (Table 1). Overall then, our phylogenetic results support the taxonomic relationships currently recognized based on previous research efforts. However, due to our more extensive sampling regime and increased amount of molecular data compared to that of Beresford, we recover greater numbers of strongly supported geographically differentiated subclades in three Criniger species. Patterns and timing of speciation The DEC model was not found to be a significantly better fit than the DEC + J, but by a narrow margin [Χ2 = 3.84; P-value (0.05) = 0.052]. Due to the sedentary nature of all Criniger species, we determined jump dispersal to be highly unlikely and utilized the results of the DEC model. The BioGeoBEARS analysis estimates a widespread origin (i.e. all three forest blocks) (~6.22 Mya) for the genus Criniger and the timing of this initial divergence is tied to early Pliocene forest retraction during the arid phase of long-term climatic oscillations (Fig. 3). We then observe that the ancestors of C. calurus + C. ndussumensis + C. olivaceus are also estimated as widespread, having reached that range during the high humidity phase of forest expansion from the early to late Pliocene. However, the subsequent divergence event splitting C. calurus from C. ndussumensis + C. olivaceus (~5.1 Mya) is difficult to explain given the state of forest expansion at this time. We suggest more intense geographic sampling of Criniger would be necessary to explain the causative factors of this early Pliocene-aged speciation event. Beyond these first two divergences, the speciation patterns and timing recovered within the genus can be explained through a combination of isolation in lowland forest refugia and the breakup of the Guineo-Congolian forests into western and eastern blocks, separated by the Dahomey Gap. Indeed, several investigations have recovered similar evidence for east-west genetic diversification of avian and mammalian populations distributed across the Dahomey Gap (birds: Beresford & Cracraft, 1999; Schmidt et al., 2008; Marks, 2010; Fuchs & Bowie, 2015; Huntley & Voelker, 2016; mammals: Gonder et al., 2011; Nesi et al., 2013; reptiles: Leaché et al., 2014). The patterns and timing of speciation we recovered in Criniger also support the involvement of the Dahomey Gap, in conjunction with more regional refugial scenarios, as a driver of two speciation events. For example, our ancestral area estimation (Fig. 3) reconstructs a widespread (UG + LG + C) distribution for the ancestors of C. barbatus + C. chlorontus and C. olivaceus + C. ndussumensis, with estimated divergence times of ~3.2 and ~1.9 Mya, respectively, both within the forest contraction phase of the Pliocene. These divergence dates are just prior to known aridity peaks at 2.8 and 1.7 Mya, suggesting that forest retraction can be implicated as the driver of diversification between these lineages. Specifically, our ancestral area estimations suggest speciation of these lineages as a result of isolation in forest refuges west of the Dahomey Gap (C. barbatus and C. olivaceus) and east of the Dahomey Gap (C. chloronotus and C. ndussumensis; Fig. 1). Subsequently, the distribution of C. chloronotus (east of the Dahomey Gap: Fig. 1) suggests the gap remained a geographic barrier for this species during recent forest expansion phases. However, the current distribution of C. barbatus in both Upper and Lower Guinean forests (i.e., across the gap; Fig. 1) indicates the Dahomey Gap was not a barrier to eastward expansion for that species. Further evidence for the effects of Pleistocene-aged forest fragmentation and the Dahomey Gap as a potential barrier is demonstrated in C. calurus, where we recover a divergence between Upper Guinean and Lower Guinean haplogroups dated to ~1.1 Mya (Figs 2, 3, 4C). This date aligns with the most recent Pleistocene aridity spike defined by deMenocal (2004) at 1.0 Mya, in which forests were severely fragmented. We suggest allopatric diversification driven by a climate-induced east-west refugial scenario, subsequently reinforced by the Dahomey Gap, as the causal agent for this pattern of divergence. Intraspecific genetic patterns in West Africa Two refugial areas have long been proposed to exist within the Upper Guinean forest block: one straddling the border between Sierra Leone and Liberia, and one within Ghana (Prigogine, 1988; Maley, 1996; Anhuf et al., 2006; Fig. 1). We find varying levels of evidence for these refugial areas within all three species of Criniger inhabiting the Upper Guinean forests. Criniger barbatus displays a deep divergence (uncorrected p-distance ~5.5%; Table 1; Fig. 4B) between individuals in Sierra Leone/Liberia and those in Ghana. This divergence is estimated to have occurred ~1.6 Mya (Fig. 3), a date closely corresponding to one of the Pleistocene spikes in aridity and forest fragmentation (at 1.7 Mya; deMenocal, 2004). The two other species inhabiting the Upper Guinean forests, C. calurus and C. olivaceus, also display geographic structuring between Sierra Leone/Liberia and Ghana dating to the Pleistocene (Figs 2, 4), albeit at substantially shallower levels (uncorrected p-distance of 0.1 and 0.2%, respectively; Table 1) than recovered in C. barbatus. Given the lack of any substantial geological barrier to gene flow between these historic refugial centres (i.e. major rivers or mountain formations), it seems likely the patterns observed in these three species are a result of climate-induced forest fragmentation during the Holocene (Salzmann & Hoelzmann, 2005). Notably, the recovery of geographic structuring of genetic diversity between Sierra Leone/Liberia and Ghana is not surprising given that studies of several mammalian (Lemnoscomys striatus: Nicolas et al., 2008; Crocidura olivieri: Jacquet et al., 2015) and avian species (H. prasina: Marks, 2010; three species of Bleda: Huntley & Voelker, 2016) found similar patterns. The contrast in depth of observed intraspecific genetic divergences (i.e., shallow vs. deep) recovered in the West African lineages of Criniger (C. barbatus, C. calurus, C. olivaceus) may be explained in two ways. First, the amount of time these populations remained in isolation, thereby varying the effective population size and amount of accumulated genetic mutations, was different between species. Second, isolation levels during forest fragmentation events may have varied due to differing life history strategies. Criniger barbatus is not observed in new growth forests and is rarely documented foraging more than 5 m off the ground, making it a true understory specialist (Fishpool & Tobias, 2005). This characteristic behaviour is also shared by the three previously mentioned species of Bleda in which deep genetic divergences were documented between Sierra Leone/Liberia and Ghana (Huntley & Voelker, 2016). Understory taxa may display higher levels of genetic structure than more dispersive species (i.e. canopy species), a scenario related to significantly lower dispersal levels of understory birds across open spaces (Lees & Peres, 2009; Kahindo et al., 2017). In contrast, C. calurus and C. olivaceus have been observed regularly from 5 to 25 m off the ground, and can be found in regenerating forest (Fishpool & Tobias, 2005). We suggest this flexibility in habitat preference and usage may have contributed to their response to fragmentation scenarios, with both C. calurus and C. olivaceus being able to disperse between refugial centres using gallery forest, edge habitat and suboptimal habitats. This flexibility has been cited as a possible explanation of similar shallow geographic structuring in similarly distributed avian species (Nectarinia olivacea: Bowie et al., 2004; Platysteira peltata/ P. cyanea: Njabo, Bowie & Sorenson, 2008; Sylvietta virens: Huntley & Voelker, 2017). Intraspecific genetic patterns in Central Africa Within both C. calurus and C. chloronotus, we recover deep genetic breaks (Fig. 4; Table 1) between populations in Equatorial Guinea/Gabon (EGG) and the DRC (Figs 2, 4) with divergences estimated to have occurred near the Pliocene-Pleistocene boundary (C. calurus: ~1.9 Mya) or within the Pleistocene (C. chloronotus: ~1.3 Mya; Fig. 3). Several investigations have shown evidence for Plio-Pleistocene refuges within Equatorial Guinea, Gabon and the DRC (Maley, 1996; Anhuf et al., 2006). The deep divergences recovered in these two species between EGG and the DRC would suggest isolation in refugial forest fragments during the Plio-Pleistocene, a result supported by similar patterns observed in other avian taxa (H. prasina: Marks, 2010; Bleda: Huntley & Voelker, 2016). Additionally, the lower Congo River exists as a potential barrier between populations in EGG and those in the DRC. We suggest the lower Congo River could have played a role in shaping genetic structure in the region, either as a barrier during fragmentation events or as a barrier reinforcing patterns post-fragmentation, as species ranges expanded from refugia. However, the extent of the lower Congo River’s influence on the patterns observed within C. calurus and C. chloronotus is difficult to discern given the limited sampling available in the area for these species. We are unaware of studies assessing the lower Congo River as a putative barrier separating EGG and DRC populations. In contrast to the deep genetic structure recovered in C. calurus and C. chloronotus, minimal genetic structure is recovered for C. ndussumensis (Fig. 2) and we estimate an origin of ~1.95 Mya for this species (Fig. 3). This result suggests that C. ndussumensis experienced similar fragmentation events as the previously mentioned species displaying high genetic differentiation levels across central African forests. For instance, a similar pattern of minimal genetic geographic structuring within the Congo forests was recovered in both Bleda notatus and B. ugandae (Huntley & Voelker, 2016). We suggest the lack of deep patterns within C. ndussumensis may be the result of historic isolation within only one Congo forest refuge during fragmentation, a scenario which would negate the effects of allopatric divergence observed in other species. However, given the dearth of information regarding this species’ specific habitat usage, we lack the data necessary to draw more than suggestions regarding how the life history strategies of C. ndussumensis may affect the patterns we recovered. Additionally, we acknowledge that the shallow patterns recovered for C. ndussumensis in the present study may also be a consequence of poor sampling across its range. The upper Congo River as a genetic barrier Several recent studies have recovered evidence for the upper Congo River as an historic barrier to gene flow over at least the past two million years. Voelker et al. (2013) found evidence for genetic differentiation across the Congo River in four out of ten avian species sampled with distributions both north and south of the upper Congo River. A subsequent study focusing on B. syndactylus, one of the species included in Voelker et al. (2013), reinforced the evidence for genetic differentiation north and south of the upper Congo River through more extensive sampling (Huntley & Voelker, 2016). In contrast, Voelker et al. (2013) found no evidence for genetic diversity structure north and south of the river in C. calurus, a result which this study upholds with greater sampling (Figs 2, 4C). However, we do recover two geographically overlapping clades of C. calurus within the DRC which are substantially divergent from one another (Fig. 4C; Table 1). Prigogine (1988) and Maley (1996) both suggested the existence of one large Pleistocene forest refuge in the central DRC (along and south of the Congo River) and another in the north-eastern DRC (north of the Congo River; Fig. 1A). We propose the pattern recovered in the individuals of C. calurus from the DRC is due to isolation in these two refuges for a long enough period of time to allow substantial genetic differentiation between the two populations. Subsequently, as forests expanded in the more humid interglacial period, these populations expanded to occupy their present ranges across the upper Congo River. Further analyses of these two deeply divergent populations using other data, such as morphology and song, may well support the recognition of them as species. Such analyses should obviously assess the other deeply divergent C. calurus lineages, as well as similar deeply divergent lineages in other Criniger species. CONCLUSION The patterns recovered in this investigation add to the growing number of studies indicating African lowland forests harbour far more cryptic diversity than previously thought. These results offer an argument against the hypothesis that the Guineo-Congolian lowland forests are ‘evolutionary museums’, where little in situ genetic diversification occurs (Fjeldså, 1994; Roy, 1997; Fjeldså & Lovett, 1997; Roy et al., 2001; Fjeldså et al., 2007; Fjeldså & Bowie, 2008). Additionally, and in contrast to the assertions by Mayr & O’Hara (1986), the deeply divergent, intraspecific variation recovered in Criniger highlights the possible utility of widespread species, which lack plumage variation, in understanding the role of historic refugial scenarios in driving avian diversity in lowland forests. In fact, of the 107 widespread taxa deemed ‘uninformative’ in Mayr & O’Hara’s (1986) study, ten have been investigated, including the current study, and all were found to display geographic structuring, albeit at varying levels (Bleda eximius, B. syndactylus: Huntley & Voelker, 2016; Campethera nivosa: Fuchs et al., 2015; H. prasina: Marks, 2010; Illadopsis rufipennis: Nguembock et al., 2009; N. olivacea: Bowie et al., 2004; Platysteira cyanea: Njabo et al., 2008; Sylvietta denti: Huntley & Voelker, 2017; Stiphrornis erythrothorax: Beresford & Cracraft, 1999, Schmidt et al., 2008; Voelker et al., 2016b). The results from these ten ‘uninformative’ taxa in conjunction with investigations of several taxa with restricted ranges indicate the substantial complexity of biogeographic patterns within Guineo-Congolian lowland forests. The current study, as well as those previously cited, highlights that no sole hypothesis can operate as a singular explanation of the substantial complexity of genetic patterns recovered throughout the African lowland forests within vertebrate species. For instance, the timing and extent of intraspecific diversification events recovered in the understory-dwelling Criniger lend plausibility to the PFRH (Haffer, 1969) and RBH (Wallace, 1852) as possible mechanisms working in tandem to create genetic diversity. However, these results would seem to eschew the ‘evolutionary museums’ concept. In contrast, recent studies of several more vagile species of ubiquitous Afro-tropical forest birds have recovered minimal genetic geographic structuring across widespread species (Bowie et al., 2004; Fuchs & Bowie, 2015; Fuchs et al., 2017), an outcome that lends support to the ‘evolutionary museum’ hypothesis. The disparity in patterns between understory specialists (poor dispersers) and canopy users/generalists (better dispersers) reveals the importance of considering varying life history strategies on species response to historic fragmentation scenarios. Overall, the evidence recovered in Criniger for varying levels of diversification across the Dahomey Gap, the Congo River and recurring climate-induced historic forest fragmentation over the last ~7 Mya indicates that African Guineo-Congolian lowland forests are dynamic zones, fully capable of creating complex and often substantial levels of genetic diversity. SUPPORTING INFORMATION Additional Supporting Information may be found in the online version of this article at the publisher’s website: Figure S1. Bayesian and maximum likelihood phylogeny of the genus Criniger using all four loci (two mtDNA and two nuclear). Values above the nodes represent Bayesian posterior probabilities (* = 1.0) and those below the nodes represent maximum likelihood bootstrap values (* = 100). Geographical abbreviations are as follows: DRC; Democratic Republic of the Congo; EG, Equatorial Guinea. Figure S2. Phylogeny of the Myoglobin (MB2) gene derived from both Bayesian and maximum likelihood methods. Values above the nodes are Bayesian posterior probabilities and those below are maximum likelihood bootstrap supports. Figure S3. Phylogeny of the TGF β2 gene derived from both Bayesian and maximum likelihood methods. Values above the nodes are Bayesian posterior probabilities and those below are maximum likelihood bootstrap supports. Figure S4. Combined phylogeny of the TGF β2 and Myoglobin (MB2) genes derived from both Bayesian and maximum likelihood methods. Values above the nodes are Bayesian posterior probabilities and those below are maximum likelihood bootstrap supports. Table S1. Species and specimens used, with institution and voucher information for each specimen. GenBank reference numbers are listed for each gene sequenced. Table S2. Primers Used. ACKNOWLEDGEMENTS We would like to thank the curators and collection managers of the following institutions for providing genetic material: Field Museum of Natural History, American Museum of Natural History, Smithsonian National Museum of Natural History, Kansas University Museum of Natural History, the Academy of Natural Sciences of Drexel University, Carmagnola Natural History Museum (Turin, Italy) and the Yale Peabody Museum of Natural History. M.P. was funded by the University of Torino Research Grants 2015 and 2016. For technical advice throughout the project we thank Adrian Castellanos and Jessica Light. This is publication number 1553 of the Biodiversity, Research and Teaching Collections. REFERENCES Anhuf D , Ledru MP , Behling H , Da Cruz FW , Cordeiro RC , Van der Hammen T , Karmann I , Marengo JA , De Oliveira PE , Pessenda L , Siffedine A , Albuquerque AL , Da Silva Dias PL . 2006. Paleo-environmental change in Amazonian and African rainforest during the LGM. Palaeogeography, Palaeoclimatology, Palaeoecology  239: 510– 527. Google Scholar CrossRef Search ADS   Beresford P . 2002. Molecular systematics and biogeography of certain Guineo-Congolian passerines  . Unpublished D. Phil. Thesis, The City University of New York. Beresford P , Cracraft J . 1999. Speciation in African forest robins (Stiphrornis): species limits, phylogenetic relationships, and molecular biogeography. American Museum Novitates  3270: 1– 20. Bohoussou KH , Cornette R , Akpatou B , Colyn M , Kerbis Peterhans J , Kennis J , Šumbera R , Verheyen E , N’Goran E , Katuala P , Nicolas V . 2015. The phylogeography of the rodent genus Malacomys suggests multiple Afrotropical Pleistocene lowland forest refugia. Journal of Biogeography  42: 2049– 2061. Google Scholar CrossRef Search ADS   Bowie RC , Fjeldså J , Hackett SJ , Crowe TM . 2004. Molecular evolution in space and through time: mtDNA phylogeography of the Olive Sunbird (Nectarinia olivacea/obscura) throughout continental Africa. Molecular Phylogenetics and Evolution  33: 56– 74. Google Scholar CrossRef Search ADS PubMed  Brosset A , Erard C . 1986. Les oiseaux des ŕegions forestières du nord-est du Gabon. Société nationale de protection de la nature  1: 1– 289. Bryja J , Granjon L , Dobigny G , Patzenhauerová H , Konečný A , Duplantier JM , Gauthier P , Colyn M , Durnez L , Lalis A , Nicolas V . 2010. Plio-Pleistocene history of West African Sudanian savanna and the phylogeography of the Praomys daltoni complex (Rodentia): the environment/geography/genetic interplay. Molecular Ecology  19: 4783– 4799. Google Scholar CrossRef Search ADS PubMed  Bryja J , Šumbera R. , Kerbis Peterhans JC , Aghová T , Bryjová A , Ondřej M , Nicolas V , Denys C , Verheyen E . 2016. Evolutionary history of the thicket rats (genus Grammomys) mirrors the evolution of African forests since late Miocene. Journal of Biogeography  44: 182–194. Colyn M , Gautier-Hion A , Verhaven W . 1991. A re-appraisal of paleoenvironmental history of central Africa: evidence for a major fluvial refuge in the Zaire Basin. Journal of Biogeography  18: 403– 407. Google Scholar CrossRef Search ADS   Crowe TM , Crowe AA . 1982. Patterns of distribution, diversity and endemism in Afro-tropical birds. Journal of Zoology Proceedings of the Zoological Society of London  198: 417– 442. Google Scholar CrossRef Search ADS   deMenocal PB . 1995. Plio-Pleistocene African climate. Science  270: 53– 59. Google Scholar CrossRef Search ADS PubMed  deMenocal PB . 2004. African climate change and faunal evolution during the Pliocene-Pleistocene. Earth Planetary Science Letters  220: 3– 24. Google Scholar CrossRef Search ADS   Diamond AW , Hamilton AC . 1980. The distribution of forest passerine birds and Quaternary climatic changes in Tropical Africa. Journal of Zoology Proceedings of the Zoological Society of London  191: 379– 402. Google Scholar CrossRef Search ADS   Dowsett RJ , Forbes-Watson AD . 1993. Checklist of birds of the Afrotropical and Malagasy regions, Vol. 1: species limits and distribution  . Liège, Belgium: Tauraco Press. Dowsett-Lemaire F , Dowsett RJ . 1991. The avifauna of the Kouilou basin Congo. Tauraco Research Report  4: 182– 239. Dowsett-Lemaire F , Dowsett RJ . 2001. African forest birds: Patterns of endemism and species richness. In Weber W , White LJT , Vedder A , Naughton-Treves L , eds. African rain forest ecology and conservation: an interdisciplinary perspective  . New Haven, CT: Yale University Press, 233– 262. Drummond AJ , Suchard MA , Xie D , Rambaut A . 2012. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Molecular Biology and Evolution  29: 1969– 1973. Google Scholar CrossRef Search ADS PubMed  Fishpool LDC , Tobias JA . 2005. Family Pycnonotidae (Bulbuls). In del Hoyo J , Elliot A , Christie DA , eds. Handbook of the birds of the world, Vol. 10. Cuckoo-shrikes to thrushes  . Barcelona: Lync Edicions, 220–222. Fjeldså J . 1994. Geographical patterns of relict and young species of birds in Africa and South America and implications for conservation priorities. Biodiversity and Conservation  3: 107– 226. Google Scholar CrossRef Search ADS   Fjeldså J , Bowie RCK . 2008. New perspectives on the origin and diversification of Africa’s forest avifauna. African Journal of Ecology  46: 235– 247. Google Scholar CrossRef Search ADS   Fjeldså J , Johansson US , Lokugalappatti SLG , Bowie RCK . 2007. Diversification of African greenbuls in space and time: linking ecological and historical processes. Journal of Ornithology  148: 359– 367. Google Scholar CrossRef Search ADS   Fjeldså J , Lovett JC . 1997. Geographical patterns of old and young species in African forest biota: the significance of specific montane areas as evolutionary centres. Biodiversity and Conservation  6: 325– 346. Google Scholar CrossRef Search ADS   Fuchs J , Bowie RC . 2015. Concordant genetic structure in two species of woodpecker distributed across the primary West African biogeographic barriers. Molecular Phylogenetics and Evolution  88: 64– 74. Google Scholar CrossRef Search ADS PubMed  Fuchs J , Fjeldså J , Bowie RCK . 2017. Diversification across major biogeographical breaks in the African Shining/Square-tailed Drongos complex (Passeriformes: Dicruridae). Zoologica Scripta  46: 27– 41. Google Scholar CrossRef Search ADS   Gaubert P , Njiokou F , Ngua G , Afiademanyo K , Dufour Gonedelé Bi S , Tougard C , Olayemi A , Danquah E , Djagoun CAMS , Kalema P , Nebesse Mololo C , Stanley W , Luo S-J , Antunes A . 2016. Phylogeography of the heavily poached African common pangolin (Philodota, Manis tricuspis) reveals six cryptic lineages as traceable signatures of Pleistocene diversification. Molecular Ecology  25: 5975–5993. Gonder MK , Locatelli S , Ghobrial L , Mitchell MW , Kujawski JT , Lankester FJ , Stewart C-B , Tishkoff SA . 2011. Evidence from Cameroon reveals differences in the genetic structure and histories of chimpanzee populations. Proceedings of the National Academy of Sciences of the United States of America  108: 4766– 4771. Google Scholar CrossRef Search ADS PubMed  Haffer J . 1969. Speciation in Amazonian forest birds. Science  165: 131– 137. Google Scholar CrossRef Search ADS PubMed  Hamilton AC , Taylor D . 1991. History of climate and forests in Tropical Africa during the last 8 million years. Climatic Change  19: 65– 78. Google Scholar CrossRef Search ADS   Happold DCD . 1996. Mammals of the Guinea-Congo rain forest. Proceedings of the Royal Society of Edinburgh  104B: 243– 284. Hassanin A , Khouider S , Gembu GC , Goodman SM , Kadjo B , Nesi N , Pourrut X , Nakouné E , Bonillo C . 2014. The comparative phylogeography of fruit bats of the tribe Scotonycterini (Chiroptera, Pteropodidae) reveals cryptic species diversity related to African Pleistocene forest refugia. Comptes Rendus Biologies  338: 197– 211. Google Scholar CrossRef Search ADS   Huelsenbeck JP , Ronquist F . 2001. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics  17: 754– 755. Google Scholar CrossRef Search ADS PubMed  Huntley JW , Voelker G . 2016. Cryptic diversity in Afro-tropical lowland forests: the systematics and biogeography of the avian genus Bleda . Molecular Phylogenetics and Evolution  99: 297– 308. Google Scholar CrossRef Search ADS PubMed  Huntley JW , Voelker G . 2017. A tale of the nearly tail-less: the effects of Plio-Pleistocene climate change on the diversification of the African avian genus Sylvietta . Zoologica Scripta  46: 523–535. Jacquet F , Denys C , Couloux A , Colyn M , Nicolas V . 2015. Phylogeography and evolutionary history of the Crocidura olivieri complex (Mammalia, Soricomorpha): from a forest-dwelling origin to a wide expansion throughout Africa. BMC Evolutionary Biology  15: 1– 15. Google Scholar CrossRef Search ADS PubMed  Johansson US , Fjeldså J , Lokugalappatti SLG , Bowie RCK . 2007. A nuclear DNA phylogeny and proposed taxonomic revision of African greenbuls (Aves, Passeriformes, Pycnonotidae). Zoologica Scripta  36: 417– 427. Google Scholar CrossRef Search ADS   Kahindo CM , Bates JM , Bowie RCK . 2017. Population genetic structure of Grauer’s Swamp Warbler Bradypterus graueri, an Albertine Rift endemic. Ibis  159: 415– 429. Google Scholar CrossRef Search ADS   Kearse M , Moir R , Wilson A , Stones-Havas S , Cheung M , Sturrock S , Buxton S , Cooper A , Markowitz S , Duran C , Thierer T , Ashton B , Meintjes P , Drummond A . 2012. Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics  28: 1647– 1649. Google Scholar CrossRef Search ADS PubMed  Keith S . 1992. Family Pycnonotidae (Bulbuls). In Keith S , Urban EK , Fry CH , eds. The birds of Africa, Vol. IV  . London: Academic Press, 1– 459. Kennis J , Nicolas V , Hulselmans J , Katuala PGB , Wendelen W , Verheyen E , Dudu AM , Leirs H . 2011. The impact of the Congo River and its tributaries on the rodent genus Praomys: speciation origin or range expansion limit? Zoological Journal of the Linnean Society  163: 983– 1002. Google Scholar CrossRef Search ADS   Lanfear R , Calcott B , Kainer D , Mayer C , Stamatakis A . 2014. Selecting optimal partitioning schemes for phylogenomic datasets. BMC Evolutionary Biology  14: 82. Google Scholar CrossRef Search ADS PubMed  Leaché AD , Fujita MK , Minin VN , Bouckaert RR . 2014. Species delimitation using genome-wide SNP data. Systematic Biology  63: 534– 542. Google Scholar CrossRef Search ADS PubMed  Lees AC , Peres CA . 2009. Gap-crossing movements predict species occupancy in Amazonian forest fragments. Oikos  118: 280– 290. Google Scholar CrossRef Search ADS   Lerner HR , Meyer M , James HF , Hofreiter M , Fleischer RC . 2011. Multilocus resolution of phylogeny and timescale in the extant adaptive radiation of Hawaiian honeycreepers. Current Biology  21: 1838– 1844. Google Scholar CrossRef Search ADS PubMed  Levinsky I , Araujo MB , Nogues-Bravo D , Haywood AM , Valdes PJ , Rahbek C . 2013. Climate envelope models suggest spatio-temporal co-occurrence of refugia of African birds and mammals. Global Ecology and Biogeography  22: 351– 363. Google Scholar CrossRef Search ADS   Maley J . 1996. The African rain forest - main characteristics of changes in vegetation and climate from the Upper Cretaceous to the Quaternary. Proceedings of the Royal Society of Edinburgh  104B: 31– 73. Maley J . 2001. The impact of arid phases on the African rain forest through geological history. In Weber W , White LJT , Vedder A , Naughton-Treves L , eds. African rain forest ecology and conservation. an interdisciplinary perspective  . New Haven, CT: Yale University Press, 69– 85. Marks BD . 2010. Are lowland rainforests really evolutionary museums? Phylogeography of the green hylia (Hylia prasina) in the Afrotropics. Molecular Phylogenetics and Evolution  55: 178– 184. Google Scholar CrossRef Search ADS PubMed  Matzke NJ . 2013a. Probabilistic historical biogeography: new models for founder-event speciation, imperfect detection, and fossils allow improved accuracy and model-testing  . Unpublished D. Phil. Thesis, University of California, Berkeley. Matzke NJ , 2013b. BioGeoBEARS: BioGeography with Bayesian (and likelihood) evolutionary analysis in R scripts  . Berkeley, CA: CRAN: The Comprehensive R Archive Network. Mayr E , O’Hara RJ . 1986. The biogeographic evidence supporting the Pleistocene forest refuge hypothesis. Evolution  40: 55– 67. Google Scholar CrossRef Search ADS PubMed  Moyle RG , Marks BD . 2006. Phylogenetic relationships of the bulbuls (Aves: Pycnonotidae) based on mitochondrial and nuclear DNA sequence data. Molecular Phylogenetics and Evolution  40: 687– 695. Google Scholar CrossRef Search ADS PubMed  Nesi N , Kadjo B , Pourrut X , Leroy E , Pongombo Shongo C , Cruaud C , Hassanin A . 2013. Molecular systematics and phylogeography of the tribe Myonycterini (Mammalia, Pteropodidae) inferred from mitochondrial and nuclear markers. Molecular Phylogenetics and Evolution  66: 126– 137. Google Scholar CrossRef Search ADS PubMed  Nguembock B , Cibois A , Bowie RCK , Cruaud C , Pasquet E . 2009. Phylogeny and biogeography of the genus Illadopsis (Passeriformes: Timaliidae) reveal the complexity of diversification of some African taxa. Journal of Avian Biology  40: 113– 1125. Google Scholar CrossRef Search ADS   Nicolas V , Mboumba JF , Verheyen E , Denys C , Lecompte E , Olayemi A , Missoup AD , Katuala P , Colyn M . 2008. Phylogeographic structure and regional history of Lemniscomys striatus (Rodentia: Muridae) in tropical Africa. Journal of Biogeography  35: 2074– 2089. Google Scholar CrossRef Search ADS   Nicolas V , Missoup AD , Colyn M , Cruaud C , Denys C . 2012. West-Central African Pleistocene lowland forest evolution revealed by the phylogeography of Misonne’s Soft-Furred Mouse. African Zoology  47: 100– 112. Nicolas V , Missoup AD , Denys C , Kerbis Peterhans J , Katuala P , Couloux A , Colyn M . 2011. The roles of rivers and Pleistocene refugia in shaping genetic diversity in Praomys misonnei in tropical Africa. Journal of Biogeography  38: 191– 207. Google Scholar CrossRef Search ADS   Njabo KY , Bowie RC , Sorenson MD . 2008. Phylogeny, biogeography and taxonomy of the African wattle-eyes (Aves: Passeriformes: Platysteiridae). Molecular Phylogenetics and Evolution  48: 136– 149. Google Scholar CrossRef Search ADS PubMed  Pasquet E , Han LX , Khobkhet O , Cibois A . 2001. Towards a molecular systematics of the genus Criniger, and a preliminary phylogeny of the bulbuls (Aves, Passeriformes, Pycnonotidae). Zoosystema  23: 857– 863. Plana V . 2004. Mechanisms and tempo of evolution in the African Guineo-Congolian rainforest. Proceedings of the National Academy of Sciences  359: 1585– 1594. Prigogine A . 1988. Speciation pattern of birds in the Central African Forest Refugia and their relationship with other refugia. Proceedings of the International Ornithological Congress  19: 2537– 2546. Quérouil S , Verheyen E , Dillen M , Colyn M . 2003. Patterns of diversification in two African forest shrews: Sylvisorex johnstoni and Sylvisorex ollula (Soricidae, Insectivora) in relation to paleo-environmental changes. Molecular Phylogenetics and Evolution  28: 24– 37. Google Scholar CrossRef Search ADS PubMed  Rambaut A , Suchard MA. , Xie D , Drummond AJ . 2014. Tracer v1.6  . Available at: http://beast.bio.ed.ac.uk/Tracer Roy MS . 1997. Recent diversification in African greenbuls (Pycnonotidae: Andropadus) supports a montane speciation model. Proceedings of the Royal Society B: Biological Sciences  264: 1337– 1344. Google Scholar CrossRef Search ADS   Roy MS , Sponer R , Fjeldså J . 2001. Molecular systematics and evolutionary history of kalats (genus Sheppardia): a pre-Pleistocene radiation in a group of African forest birds. Molecular Phylogenetics and Evolution  18: 74– 83. Google Scholar CrossRef Search ADS PubMed  Salzmann U , Hoelzmann P . 2005. The Dahomey Gap: an abrupt climatically induced rain forest fragmentation in West Africa during the late Holocene. Holocene  15: 190– 199. Google Scholar CrossRef Search ADS   Schmidt BK , Foster JT , Angehr GR. , Durrant KL , Fleischer RC , 2008. A new species of African forest robin from Gabon (Passeriformes: Muscicapidae: Stiphrornis). Zootaxa  1850: 27– 42. Sibley CG , Monroe BL Jr . 1990. Distribution and taxonomy of birds of the world  . New Haven, CT: Yale University Press. Stamatakis A . 2014. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics  30: 1312– 1313. Google Scholar CrossRef Search ADS PubMed  Tamura K , Stecher G , Peterson D , Filipski A , Kumar S . 2013. MEGA6: molecular evolutionary genetics analysis version 6.0. Molecular Biology and Evolution  30: 2725– 2729. Google Scholar CrossRef Search ADS PubMed  Voelker G , Huntley JW , Peñalba JV , Bowie RCK . 2016a. Resolving taxonomic uncertainty and historical biogeographic patterns in Muscicapa flycatchers and their allies. Molecular Phylogenetics and Evolution  94: 618– 625. Google Scholar CrossRef Search ADS   Voelker G , Marks BD , Kahindo C , A’genonga U , Bapeamoni F , Duffie LE , Huntley JW , Mulotwa E , Rosenbaum SA , Light JE . 2013. River barriers and cryptic biodiversity in an evolutionary museum. Ecology and Evolution  3: 536– 545. Google Scholar CrossRef Search ADS PubMed  Voelker G , Outlaw RK , Bowie RCK . 2010. Pliocene forest dynamics as a primary driver of African bird speciation. Global Ecology and Biogeography  19: 111– 121. Google Scholar CrossRef Search ADS   Voelker G , Tobler M , Prestridge HL , Duijm E , Groenenberg D , Hutchinson MR , Martin AD , Nieman A , Roselaar CS , Huntley JW . 2016b. Three new species of Stiphrornis (Aves: Muscicapidae) from the Afro-tropics, with a molecular phylogenetic assessment of the genus. Systematics and Biodiversity  15: 87– 104. Google Scholar CrossRef Search ADS   Wallace AR . 1852. On the monkeys of the Amazon. Proceedings of the Zoological Society of London  20: 107– 110. © 2017 The Linnean Society of London, Zoological Journal of the Linnean Society http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Zoological Journal of the Linnean Society Oxford University Press

The systematics and biogeography of the Bearded Greenbuls (Aves: Criniger) reveals the impact of Plio-Pleistocene forest fragmentation on Afro-tropical avian diversity

Loading next page...
 
/lp/ou_press/the-systematics-and-biogeography-of-the-bearded-greenbuls-aves-ggatfDdDwR
Publisher
The Linnean Society of London
Copyright
© 2017 The Linnean Society of London, Zoological Journal of the Linnean Society
ISSN
0024-4082
eISSN
1096-3642
D.O.I.
10.1093/zoolinnean/zlx086
Publisher site
See Article on Publisher Site

Abstract

Abstract The biogeographical history of Afro-tropical lowland forests during the Plio-Pleistocene is characterized by pervasive fragmentation-coalescence cycling due to global climatic oscillations. Vicariance scenarios driven by forest fragmentation have long been hypothesized as major mechanisms for the creation and maintenance of Afro-tropical avian diversity. However, the timing and centre of diversification events remains unclear. We undertook the first molecular phylogenetic and biogeographic investigation of the avian genus Criniger, a group of understory birds endemic to the lowland forests of West and Central Africa. Utilizing DNA from 43 specimens and a combination of molecular and biogeographic methods, we constructed time-calibrated phylogenies and ancestral area estimations. We estimated a widespread origin for the genus, with a basal divergence dating to the late Miocene. All other speciation events were dated to the Pliocene. However, we recovered substantial geographic structuring of genetic diversity, dating to the Pleistocene, within both Western and Central Africa for three species. The biogeographic patterns observed in the genus Criniger are likely the result of allopatric diversification driven by forest fragmentation during the Plio-Pleistocene. The results of this study indicate that Afro-tropical forests harbour substantially higher levels of cryptic diversity and greater genetic complexity than previously hypothesized. Afro-tropics, Aves, Criniger, cryptic speciation, endemism, phylogeography, Pleistocene, Pliocene, refugia, systematics INTRODUCTION The Paleo-environmental history of the Guineo-Congolian lowland forests of Africa is characterized by retraction and expansion cycles relating to climatic oscillations of global humidity (see Plana, 2004 for a review). Between the late Miocene (~7 Mya) and early Pliocene (~3.5 Mya), Afro-tropical forests were in an expanded state, covering substantially more land area than at present (Maley, 1996). In response to a decrease in global humidity in the early Pliocene (~3.4 Mya), Guineo-Congolian lowland forests began a major retraction phase (deMenocal, 1995; Maley, 1996). Since the initiation of this period of retraction, Guineo-Congolian forests have been subject to several perturbations in global humidity relating to glacial cycling, characterized by step-like shifts in the amplitude of overall aridity with peaks at 2.8 (±0.2), 1.7 (±0.1) and 1.0 (±0.2) Mya (deMenocal, 2004). The consequences of this cyclical aridification on the Guineo-Congolian forests during the Plio-Pleistocene were episodes of severe fragmentation in which forests were isolated in refugial pockets. And indeed, palynological and distributional patterns of forest-dwelling taxa support the existence of multiple pockets of historical refugia throughout the Guineo-Congolian forests (palynological: Colyn, Gautier-Hion & Verhaven, 1991; Maley, 1996, 2001; Anhuf et al., 2006; distributional: Diamond & Hamilton, 1980; Crowe & Crowe, 1982; Mayr & O’Hara, 1986; Prigogine, 1988; Hamilton & Taylor, 1991; Happold, 1996; Levinsky et al., 2013). However, the size, location and number of Plio-Pleistocene refugia remain controversial, making further biogeographic investigations of Afro-tropical forest taxa crucial to resolving this picture. Early investigations of avian distributions across African lowland forests relied on the Pleistocene Forest Refuge Hypothesis (PFRH; Haffer, 1969) as the causal agent of observed patterns (Diamond & Hamilton, 1980; Crowe & Crowe, 1982; Mayr & O’Hara, 1986). Developed initially to explain distributional patterns in South America, the hypothesis outlines a scenario of allopatric diversification specific to the Pleistocene [A recent adjustment of the Plio-Pleistocene boundary has been formally accepted, with the new beginning of the Pleistocene Epoch set at 2.58 Mya, as opposed to the historical boundary of c. 1.8 Mya. However, due to the fact that hypotheses and concepts introduced above as being relevant to the discussion of Plio-Pleistocene diversification relate to the 1.8 Mya boundary, we have chosen to use that date as the transition here, for consistency of context.] (defined at that time as 1.8 Mya–11.8 Kya), in which lowland forest taxa became isolated in refugia during forest fragmentation periods, which in turn promoted allopatric speciation or in some cases, subspecific phenotypic variation. Research assessing this hypothesis in Africa favoured the investigation of (1) taxa with restricted ranges (i.e. not widespread species) and (2) taxa which display plumage variation across their range. In both instances, patterns were assumed to have derived from isolation in refugia. On the other hand, widespread species which lacked obvious phenotypic variation were viewed as ‘uninformative’ with regards to the PFRH. Indeed, 107 taxa are specifically listed as ‘uninformative’ in this regard by Mayr & O’Hara (1986). An alternative refugial hypothesis, made possible with the early proliferation of molecular divergence estimates, is the Montane Speciation Hypothesis (MSH) (Fjeldså, 1994; Fjeldså & Lovett, 1997; Roy, 1997; Roy, Sponer & Fjeldså, 2001; Fjeldså et al., 2007; Fjeldså & Bowie, 2008). These investigations revealed that many lineages of montane avifauna were relatively young (latest Miocene or younger) compared with lowland forest lineages which were dated as ‘ancient’ (~12–20 Mya). The MSH shifted the centre of diversification events away from the lowland forests and into montane regions where topographic habitat complexity and microclimatic stability during forest fragmentation were assumed to promote speciation. In subsequent forest expansion periods, species which diverged in the Afro-montane regions dispersed into nearby lowland forests where further diversification was minimal. The MSH views the Guineo-Congolian lowland forests as ‘evolutionary museums’, where species accumulated over time and persisted, with little change, since the Miocene. An early consequence of the MSH and the ‘evolutionary museum’ concept were less interest in the lowland forests role as a diversification centre which can, in part, account for the relative dearth of investigations focused on endemic lowland avifauna. However, over the past decade, investigations have begun to present a pattern that counters the ‘evolutionary museum’ concept and provides support for a more diverse picture of lowland forest diversity (Illadopsis: Nguembock et al., 2009; Sheppardia: Voelker, Outlaw & Bowie, 2010; Stiphrornis: Voelker et al., 2016b; Sylvietta: Huntley & Voelker, 2017). For instance, the widespread, phenotypically monotypic Green Hylia (Hylia prasina) displays deep genetic divergences linked to highly discreet geographic structure across Afro-tropical forest blocks (Marks, 2010). A recent investigation of the avian genus Bleda, a lowland forest endemic, found substantial geographic structuring and genetic divergences dating to the Plio-Pleistocene in three of the five species of that genus (B. syndactylus, B. eximius, B. canicapillus; Huntley & Voelker, 2016). Additionally, varying levels of cryptic diversification have also been demonstrated in several mammalian taxa (Sylvisorex: Quérouil et al., 2003; Lemniscomys: Nicolas et al., 2008; Praomys: Bryja et al., 2010; Nicolas et al., 2011; Crocidura: Jacquet et al., 2015; Grammomys: Bryja et al., 2016; Manis tricuspis: Gaubert et al., 2016). Alternatively, and in conjunction with traditional refugial scenarios, two additional sources of genetic diversification have been demonstrated across Guineo-Congolian forest blocks. First, early biogeographers pointed out the disjunction between West African and Central African species distributions (Diamond & Hamilton, 1980; Crowe & Crowe, 1982; Mayr & O’Hara, 1986). It has long been hypothesized that the Dahomey Gap (Fig. 1A), a broad savannah corridor breaking the lowland forests into two blocks (Salzmann & Hoelzmann, 2005), has been a major barrier to gene flow in the region. Recent investigations have recovered geographic structuring supporting an east-west vicariance scenario for several avian species (Campethera: Fuchs & Bowie, 2015; Dicrurus: Fuchs, Fjeldså & Bowie, 2017). Secondly, the Riverine Barrier Hypothesis (RBH) proposes that large river systems may act as barriers to gene flow for populations across rivers (Wallace, 1852). Evidence for the RBH in Africa was demonstrated by a comparative study which recovered genetic divergence patterns in four out of ten avian species distributed across the Congo River (Voelker et al., 2013). More broadly, investigations of several vertebrate taxa with ranges straddling other substantial river systems (e.g. the Niger, Sanaga and Ogooué rivers) have found evidence for varying levels of diversification supporting the RBH (rodents: Kennis et al., 2011; Nicolas et al., 2012; Bohoussou et al., 2015; Jacquet et al., 2015; bats: Hassanin et al., 2014; birds: Fuchs & Bowie, 2015; Huntley & Voelker, 2016; Fuchs et al., 2017). Figure 1. View largeDownload slide A, approximate current Guineo-Congolian lowland forest cover and locations of forest refugia during the Last Glacial Maximum, as suggested by Maley (1996), as well as dashed delineations of traditional lowland forest blocks. Range maps for currently recognized species within Criniger along with sampling points: B, C. calurus; C, C. olivaceus; D, C. barbatus; E, C. choloronotus; F, C. ndussumensis. Forest block abbreviations: UGF, Upper Guinean forest block; LGF, Lower Guinean forest block. Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Figure 1. View largeDownload slide A, approximate current Guineo-Congolian lowland forest cover and locations of forest refugia during the Last Glacial Maximum, as suggested by Maley (1996), as well as dashed delineations of traditional lowland forest blocks. Range maps for currently recognized species within Criniger along with sampling points: B, C. calurus; C, C. olivaceus; D, C. barbatus; E, C. choloronotus; F, C. ndussumensis. Forest block abbreviations: UGF, Upper Guinean forest block; LGF, Lower Guinean forest block. Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Collectively, these recent studies cast doubt on the veracity of the ‘evolutionary museum’ concept as a sweeping explanation for patterns of diversity in Guineo-Congolian lowland forests, and instead point to lowland forests as regions harbouring complex genetic patterns. Therefore, it is important that further investigations of African forest taxa be undertaken to determine the scope and potential role of historic mechanisms within lowland forests in creating genetic diversity. The Bearded Greenbuls (genus: Criniger), provide an excellent model for further investigations of lowland forest patterns. This genus formerly consisted of ten Afro-Asian species, but recent investigations of the family Pycnonotidae found evidence for moving the Asian species into a separate genus (Alophoixus), thus making Criniger an entirely African group (Pasquet et al., 2001; Moyle & Marks, 2006). Criniger currently consists of five understory bird species all endemic to Afro-tropical lowland forests. The Red-tailed Greenbul (C. calurus) is a widespread species inhabiting all regions of the Guineo-Congolian lowland forests (Fig. 1B). Criniger calurus encompasses three subspecies: C. c. verrauxi (Senegal to south-west Nigeria), C. c. calurus [south-west Nigeria to western Democratic Republic of Congo (DRC)] and C. c. emini (western DRC to eastern Uganda). Two members of Criniger are West African endemics, the Yellow-bearded Greenbul (C. olivaceus) inhabiting the Upper Guinean forests (Fig. 1C), and the Western Bearded Greenbul (C. barbatus) which can be found in both the Upper and a relatively small portion of the Lower Guinean forests (Fig. 1D). The Eastern Bearded Greenbul (C. chloronotus) displays a disjunction within its range, with two main populations separately inhabiting areas east and west of Ivory Coast (Fig. 1E). However, it is possible that this disjunct pattern is artificial, given the general scarcity of avian records from the Ivory Coast. The final species, the White-bearded Greenbul (C. ndussumensis), inhabits both the Lower Guinean and Congo forests, while staying mostly north of the Congo River within the latter (Fig. 1F). To date, no investigation of the molecular phylogenetics of the genus Criniger has been published. While morphological and ecological evidence has traditionally recognized at least four species, with C. barbatus and C. chloronotus as sister species (Sibley & Monroe, 1990; Keith, 1992; Dowsett & Forbes-Watson, 1993), several hypotheses regarding the taxonomic status and relationship of C. ndussumensis to other Criniger species have been offered. Criniger ndussumensis has been considered to be conspecific with C. olivaceus (Dowsett & Forbes-Watson, 1993; Dowsett-Lemaire & Dowsett, 2001), a subspecies of C. olivaceus (Dowsett-Lemaire & Dowsett, 1991), or completely invalid as a taxon (Brosset & Erard, 1986). A molecular phylogenetic investigation by Beresford (2002) utilizing the mitochondrial cytochrome-b gene and a fragment of the nuclear beta-fibrinogen gene recovered evidence confirming (1) the sister relationship between C. barbatus and C. chloronotus and (2) that C. ndussumensis deserves full species status. However, despite the adoption of the result of Beresford’s molecular investigation by most current classifications, the study was never published. Therefore, we feel it vital to re-visit earlier hypotheses within the genus Criniger with a larger molecular data set than utilized by Beresford. Here we undertake the first investigation of the systematics and biogeography of the genus Criniger. As understory-dwelling birds with low vagility, Criniger species are potentially more susceptible to forest fragmentation events and as such are well positioned to retain the stamp of past refugial-driven diversification events (Lees & Peres, 2009; Kahindo, Bates & Bowie, 2017). Furthermore, one genus member, C. calurus, is a widespread morphologically monotypic species specifically included in Mayr & O’Hara’s (1986) list of 107 ‘uninformative’ taxa. Our study goals are three-fold. First, we examine the molecular phylogenetics of the genus Criniger. Second, we explore the biogeographic patterns displayed within Criniger in relation to broad patterns and diversification timing within lowland forests. Third, we investigate the phylogeography of each species for patterns of genetic diversification across Guineo-Congolian lowland forest blocks, with the results from C. calurus being a direct test of Mayr & O’Hara’s (1986) assertion that widespread species lacking geographically structured, phenotypic variation are ‘uninformative’ for investigations of historic Afro-tropical forest diversification. METHODS Taxon sampling and molecular data We gathered 43 tissue samples of Criniger from museum collections (C. calurus = 24, C. ndussumensis = 7, C. chloronotus = 4, C. olivaceus = 4, C. barbatus = 4; Supporting Information, Table S1). In addition, four taxa were chosen from within Pycnonotidae, to which Criniger belongs, as outgroups (Eurillas latirostris, Phyllastrephus albigularis, Bleda syndactylus and Baeopogon indicator). These species were all found to be closely related to Criniger in a recent phylogeny of the Pycnonotidae (Johansson et al., 2007). We extracted whole genomic DNA from fresh tissue using proteinase K digestion according to the manufacturer’s instructions (DNeasy Blood and Tissue Kit, Qiagen, Valencia, CA). We used polymerase chain reaction (PCR) to amplify two mitochondrial (mtDNA) loci: nicotinamide adenine dinucleotide dehydrogenase subunit-2 (ND2) and cytochrome oxidase b (cyt b) and two nuclear loci: transforming growth factor β2 intron-5 (TGF β2), Myoglobin intron-2 (MB2). We used standard published primers and protocols for each gene (see Supporting Information, Table S2). Bidirectional single-pass Sanger sequencing, using the same primer sets as utilized for PCR (Supporting Information, Table S2), were performed using ABI Big Dye Terminator v3.1 at the Beckman-Coulter Genomics facility (Danvers, MA). Both mitochondrial loci were aligned by eye and translation was verified using Sequencer 4.9 (Gene Codes Corporation, Ann Arbor, MI). Nuclear loci were aligned using MUSCLE in the Geneious 8.1 platform (Biomatters Ltd; http://www.geneious.com, Kearse et al., 2012). Phylogenetic analysis and divergence dating Phylogenies were derived from two concatenated data sets: (1) a mitochondrial-only data set with all individuals (n = 43) and (2) a subset of individuals (n = 24) for which we sequenced four loci. We used PartitionFinder (Lanfear et al., 2014) to determine best fit models of evolution and the most appropriate partitioning schemes for both data sets. Maximum likelihood (ML) analyses were performed using RAxML 8.0 (Stamatakis, 2014) using the GTR + G model option and support was assessed using the rapid bootstrap algorithm with 1000 replicates. Bayesian inference was performed using MrBayes 3.2.5 (Huelsenbeck & Ronquist, 2001) using two runs of four Markov chain Monte Carlo (MCMC) chains of 10 million generations, sampled every 2000 generations. Tracer v1.6 (Rambaut et al., 2014) was used to visualize post-run statistics and determine if stationarity was reached, and for estimating an appropriate burn-in. Species tree analysis and divergence dating estimates for a further reduced four-gene data set (n = 24) were run in BEAST v2.3 (Drummond et al., 2012), using the standard BEAST template for divergence estimates and the *BEAST template for species tree analysis, respectively. We note here that no fossil calibration is available for Criniger; therefore, a relaxed, lognormal clock was utilized with lineage substitution rates (per lineage/million years) for three of the four genes gathered from Lerner et al. (2011) (ND2 = 0.029, cyt b = 0.014, TGF β2 = 0.0017) and set a substitution rate of 0.002 for MB2 as previously employed by Voelker et al. (2016a). Standard deviations (SDs) for both mitochondrial genes and TGF β2 (cyt b = 0.001; ND2 = 0.0025; TGF β2 = 0.0020) followed Lerner et al. (2011) while we used an SD of 0.002 for MB2. Both BEAST analyses (standard BEAST and *BEAST) utilized a normal Yule process speciation prior and linear population function with constant root in two MCMC runs of 50000000 generations (sampled every 2500 generations), with a 25% burn-in. Both runs were combined using LogCombiner v2.3 (Drummond et al., 2012) and subsequently evaluated in Tracer v1.6 to measure the posterior effective sample size (ESS), as well as the 95% confidence interval for divergence dating. The combined tree topology was analysed in TreeAnnotator v2.3 (Drummond et al., 2012). Haplotype networks To further assess phylogeographic patterns within the genus Criniger, we created median-joining haplotype networks based on the ND2 data set using Network v4.6.1.3 (Fluxus-Engineering) for C. calurus, C. chloronotus and C. barbatus individuals, as these species showed discrete intraspecific structure in preliminary phylogenetic analyses. The resulting network was tested for unnecessary median vectors using the most probable (MP) post-processing option. Genetic distances, in the form of average uncorrected p-distances for the ND2 data among clades recovered from the mtDNA Bayesian analysis, were calculated using Mega6 (Tamura et al., 2013). Historical biogeography Ancestral range estimation was performed using the BioGeoBEARS package in the R statistical program (Matzke, 2013a, b). We made use of BioGeoBEARS ability to run two basic models of ancestral area reconstruction, the DEC and DEC + J models. The DEC (dispersal-extinction cladogenesis) model utilizes two parameters: the dispersal rate (range expansion) and the extinction rate (range contraction), while fixing the cladogenesis model. The second model DEC + J uses the same parameters as the DEC model while adding a third free parameter (J) corresponding to long-distance dispersal. This free parameter allows one daughter lineage to move to a non-adjacent area outside of the ancestral range. We were then able to compare the two models (DEC vs. DEC + J) using a likelihood ratio test (LRT). We coded each lineage as being present or absent in the three widely recognized lowland forest blocks: the Upper Guinean, Lower Guinean and Congo forests (Fig. 1), and utilized an adjacency matrix to inform BioGeoBEARS of the geographical separation between the Upper Guinean and Congo forests. RESULTS Molecular data and phylogenetic analyses The mitochondrial data set (ND2 and cyt b) contained 42 individuals and 2054 total amplified base pairs (bp; ND2 = 1029 bp and cyt b = 1025 bp), while the four-gene data set contained 24 individuals and 3452 bp (mtDNA, MB2 = 738 bp, TGF β2 = 660 bp) (see Supporting Information, Table S1 for all voucher and GenBank accession numbers). We recovered the first strongly supported, multilocus ML and Bayesian trees for the genus Criniger. ML and Bayesian analyses of the mitochondrial-only data set (Fig. 2) and four-gene data set (Supporting Information, Fig. S1) produced phylograms with congruent topologies. ML and Bayesian phylograms produced independently for each nuclear locus as well as for a combined nuclear data set differed slightly in topology. The Bayesian MB2 phylogeny recovered well-supported [posterior probability (PP) ≥ 0.97] sister relationships similar to the mtDNA and four-gene data set; however, the basal divergence results in a polytomy (Supporting Information, Fig. S2). The RAxML analysis produced a congruent topology for the MB2 locus, albeit with moderately lower support at the break between C. calurus and C. ndussumensis + C. olivaceus (bootstrap value = 85) (Supporting Information, Fig. S2). Additionally, the Bayesian TGF β2 phylogeny recovered a well-supported pattern in which C. ndussumensis + C. olivaceus is sister to the remaining species (Supporting Information, Fig. S3). However, while the ML analysis for TGF β2 produced identical relationships, support was generally lower. The phylogeny constructed by both the Bayesian and ML analyses is topographically congruent with the MB2 tree; however, support at the basal node of C. calurus displayed lower support (PP = 0.80; bootstrap value = 70) (Supporting Information, Fig. S4). In both the mtDNA-only and four-gene combined phylogeny (Fig. 2 and Supporting Information, Fig. S1), five lineages were recovered with strong support (>0.97 PP), reflecting the five currently recognized species of Criniger. We recover a phylogenetic pattern where an initial divergence separates the five clades into two major groups. The first consists of C. calurus, C. olivaceus and C. ndussumensis, with the latter two species being sister taxa. The second major group consists of the two remaining species, C. chloronotus and C. barbatus (Fig. 2 and Supporting Information, Fig. S1). Figure 2. View largeDownload slide Maximum likelihood and Bayesian molecular phylogenies of the genus Criniger utilizing only the mitochondrial data set (cyt b and ND2). Values above the nodes represent posterior probabilities (* = posterior probability of 1.0) and those below represent bootstrap support values (* = 100). Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Figure 2. View largeDownload slide Maximum likelihood and Bayesian molecular phylogenies of the genus Criniger utilizing only the mitochondrial data set (cyt b and ND2). Values above the nodes represent posterior probabilities (* = posterior probability of 1.0) and those below represent bootstrap support values (* = 100). Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Both phylogenies (mtDNA-only and four-gene) reflect the same patterns of intraspecific diversification in Criniger (Fig. 2 and Supporting Information, Fig. S1). The phylogeny produced by the more densely sampled mitochondrial-only data set shows two patterns of intraspecific diversification amongst the five recovered species: (1) limited structure with shallow divergence estimates and (2) substantial structure with deep divergences. Pertaining to the first pattern, we find little to no structure in either C. ndussumensis or C. olivaceus, as both have shallow divergences (Fig. 2). We did recover two subclades for C. ndussumensis, one from Gabon and the other containing individuals from the DRC, Central African Republic (CAR) and Equatorial Guinea; however, these subclades differ by just 0.2% uncorrected p-distance (Table 1) and as such have no support (Fig. 2). Criniger olivaceus displays limited structure between a Liberian group and two individuals from Ghana, separated by an uncorrected p-distance of only 0.4% (Table 1), with no support (Fig. 2). Table 1. Uncorrected pairwise distances for ND2 among and within five Criniger species   1  2  3  4  5  6  7  8  9  10  11  1. calurus (Ghana)                        2. calurus (SLL)  0.001                      3. calurus (EGG)  0.048  0.047                    4. calurus (DRC1 + CAR)  0.066  0.065  0.058                  5. calurus (DRC2)  0.069  0.068  0.062  0.042                6. chloronotus (DRC)  0.136  0.137  0.131  0.137  0.138              7. chloronotus (EGG)  0.142  0.141  0.138  0.142  0.141  0.052            8. barbatus (Ghana)  0.139  0.140  0.128  0.141  0.144  0.092  0.103          9. barbatus (SLL)  0.134  0.135  0.129  0.138  0.142  0.082  0.097  0.055        10. ndussumensis (Gabon)  0.124  0.123  0.117  0.125  0.121  0.138  0.144  0.143  0.149      11. ndussumensis (DRC + EG + CAR)  0.124  0.123  0.118  0.126  0.122  0.139  0.145  0.143  0.150  0.002      1  2  3  4  5  6  7  8  9  10  11  1. calurus (Ghana)                        2. calurus (SLL)  0.001                      3. calurus (EGG)  0.048  0.047                    4. calurus (DRC1 + CAR)  0.066  0.065  0.058                  5. calurus (DRC2)  0.069  0.068  0.062  0.042                6. chloronotus (DRC)  0.136  0.137  0.131  0.137  0.138              7. chloronotus (EGG)  0.142  0.141  0.138  0.142  0.141  0.052            8. barbatus (Ghana)  0.139  0.140  0.128  0.141  0.144  0.092  0.103          9. barbatus (SLL)  0.134  0.135  0.129  0.138  0.142  0.082  0.097  0.055        10. ndussumensis (Gabon)  0.124  0.123  0.117  0.125  0.121  0.138  0.144  0.143  0.149      11. ndussumensis (DRC + EG + CAR)  0.124  0.123  0.118  0.126  0.122  0.139  0.145  0.143  0.150  0.002    Country abbreviations: SLL, Sierra Leone/Liberia; EGG, Equatorial Guinea + Gabon; DRC, Democratic Republic of the Congo; CAR, Central African Republic; EG, Equatorial Guinea. View Large Table 1. Uncorrected pairwise distances for ND2 among and within five Criniger species   1  2  3  4  5  6  7  8  9  10  11  1. calurus (Ghana)                        2. calurus (SLL)  0.001                      3. calurus (EGG)  0.048  0.047                    4. calurus (DRC1 + CAR)  0.066  0.065  0.058                  5. calurus (DRC2)  0.069  0.068  0.062  0.042                6. chloronotus (DRC)  0.136  0.137  0.131  0.137  0.138              7. chloronotus (EGG)  0.142  0.141  0.138  0.142  0.141  0.052            8. barbatus (Ghana)  0.139  0.140  0.128  0.141  0.144  0.092  0.103          9. barbatus (SLL)  0.134  0.135  0.129  0.138  0.142  0.082  0.097  0.055        10. ndussumensis (Gabon)  0.124  0.123  0.117  0.125  0.121  0.138  0.144  0.143  0.149      11. ndussumensis (DRC + EG + CAR)  0.124  0.123  0.118  0.126  0.122  0.139  0.145  0.143  0.150  0.002      1  2  3  4  5  6  7  8  9  10  11  1. calurus (Ghana)                        2. calurus (SLL)  0.001                      3. calurus (EGG)  0.048  0.047                    4. calurus (DRC1 + CAR)  0.066  0.065  0.058                  5. calurus (DRC2)  0.069  0.068  0.062  0.042                6. chloronotus (DRC)  0.136  0.137  0.131  0.137  0.138              7. chloronotus (EGG)  0.142  0.141  0.138  0.142  0.141  0.052            8. barbatus (Ghana)  0.139  0.140  0.128  0.141  0.144  0.092  0.103          9. barbatus (SLL)  0.134  0.135  0.129  0.138  0.142  0.082  0.097  0.055        10. ndussumensis (Gabon)  0.124  0.123  0.117  0.125  0.121  0.138  0.144  0.143  0.149      11. ndussumensis (DRC + EG + CAR)  0.124  0.123  0.118  0.126  0.122  0.139  0.145  0.143  0.150  0.002    Country abbreviations: SLL, Sierra Leone/Liberia; EGG, Equatorial Guinea + Gabon; DRC, Democratic Republic of the Congo; CAR, Central African Republic; EG, Equatorial Guinea. View Large Pertaining to the second pattern, the remaining three species in the mitochondrial-only phylogeny, C. calurus, C. chloronotus and C. barbatus, display substantial structuring with deep divergences. The widespread C. calurus is divided into four highly supported subclades corresponding to three discrete geographical regions and the three recognized subspecies (Fig. 2). We recover two subclades representing Congolian forest taxa (DRC1 and DRC2; C. c. emini) as sister to two subclades comprising Lower Guinean forest taxa (Equatorial Guinea + Gabon; C. c. calurus) or Upper Guinean forest taxa (Sierra Leone + Liberia + Ghana; C. c. verrauxi; Fig. 2). These four subclades have substantial average uncorrected p-distances between them (5.8–6.8%; Table 1). The DRC1 subclade is composed of six individuals collected south of the Congo River, three collected north of the river and one individual from the CAR, while the DRC2 subclade is composed of five individuals from the northern banks of the Congo River and only one individual from south of the river (Fig. 2). Despite the general overlap in distribution, these two DRC subclades are separated by an average uncorrected p-distance of 4.2% (Table 1). The Lower Guinean forest subclade (Equatorial Guinea + Gabon) is separated by an uncorrected p-distance of 4.7% from its Upper Guinean sister subclade (Table 1). Subclades within C. chloronotus and C. barbatus show similar strongly supported and discrete geographic structuring with substantial genetic divergence (Fig. 2). A genetic break similar to C. calurus is recovered in C. chloronotus, separating Lower Guinean individuals from those in the DRC, including a similar uncorrected p-distance of 5.2% (Fig. 1 and Table 1). Criniger barbatus, an Upper Guinean forest endemic, shows a strongly supported divergence between a subclade of individuals from Ghana and a subclade from Sierra Leone/Liberia, with an average uncorrected p-distance of 5.5% between them (Table 1). Divergence estimates The species tree analysis (*BEAST) with molecular divergence analysis recovered a strongly supported (≥0.99) topology congruent (Fig. 3) with both mtDNA-only and four-gene Bayesian analyses. The molecular clock analysis recovered a late Miocene (~6.2 Mya) basal divergence within Criniger. We recover Pliocene ages for the divergence of C. calurus from C. ndussumensis + C. olivaceus (~5.1 Mya) and between C. barbatus and C. chloronotus (~3.2 Mya; Fig. 3). The initial diversification of C. calurus lineages and the divergence of C. ndussumensis and C. olivaceus from a common ancestor are dated to the latest Pliocene (~1.9 Mya). All remaining intraspecific diversification events recovered within the genus are estimated to have occurred within the Pleistocene (Fig. 3). Figure 3. View largeDownload slide Species tree from *BEAST with molecular clock estimates of lineage divergence dates for the genus Criniger, based on evolutionary rates from Lerner et al. (2011) (cyt b, ND2, TGF β2) and Voelker et al. (2016a) (MB2). Nodal values are posterior probabilities (* = 1.0) and nodal bars represent the 95% highest posterior density intervals. BioGeoBEARS ancestral range estimations are represented at each node and current recognized range is bracketed for each species. Area abbreviations: UG, Upper Guinean; LG, Lower Guinean; C, Congo. Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Figure 3. View largeDownload slide Species tree from *BEAST with molecular clock estimates of lineage divergence dates for the genus Criniger, based on evolutionary rates from Lerner et al. (2011) (cyt b, ND2, TGF β2) and Voelker et al. (2016a) (MB2). Nodal values are posterior probabilities (* = 1.0) and nodal bars represent the 95% highest posterior density intervals. BioGeoBEARS ancestral range estimations are represented at each node and current recognized range is bracketed for each species. Area abbreviations: UG, Upper Guinean; LG, Lower Guinean; C, Congo. Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Haplotype network The ND2 haploytpe networks derived for C. barbatus, C. calurus and C. chloronotus all display geographically discrete haplogroups separated by substantial numbers of mutations (Fig. 4). The ND2 network for C. barbatus (restricted to Upper Guinean forests) estimates two haplogroups: one consisting of individuals from Sierra Leone/Liberia, and another from Ghana, with 56 mutations separating them (Fig. 4B). The network for C. calurus (Fig. 4C) produced four distinct haplogroups corresponding to the subclades recovered in the Bayesian analysis: an Upper Guinean (Sierra Leone/Liberia + Ghana), a Lower Guinean (Equatorial Guinea + Gabon) and two Congo haplogroups, one representing a CAR haplotype plus five DRC individuals and one consisting of nine DRC individuals, with a substantial number of mutations (N = 44) separating these two DRC groups. Overall, the western most haplogroup (Upper Guinean) is separated by 117 mutational steps from the DRC2 haplogroup (Fig. 4). Lastly, we recover two haplogroups for C. chloronotus (Fig. 4D). These are separated by 53 mutational steps, with one haplogroup representing Lower Guinean individuals (Equatorial Guinea + Gabon) and the other representing individuals from south of the Congo River in the DRC. Figure 4. View largeDownload slide A, sample locations pertaining to median-joining networks of Criniger (B), C. barbatus (C) and C. chloronotus (D) using the ND2 data set. Hash marks between haplotypes represent mutational steps and lack thereof represent one mutation. Unfilled circles represent missing haplotypes. Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Figure 4. View largeDownload slide A, sample locations pertaining to median-joining networks of Criniger (B), C. barbatus (C) and C. chloronotus (D) using the ND2 data set. Hash marks between haplotypes represent mutational steps and lack thereof represent one mutation. Unfilled circles represent missing haplotypes. Country abbreviations: DRC, Democratic Republic of the Congo; CAR, Central African Republic. Ancestral area estimates The DEC model was not determined to be significantly better than the DEC + J model using a LRT [Χ2 = 3.84; P-value (0.05) = 0.052]. Overall, the ancestral area estimation suggests a widespread origin (all three forest blocks) for the basal divergence of C. chloronotus + C. barbatus from the remaining species (Fig. 3). The analysis further estimates a scenario in which the ancestors of the C. chloronotus + C. barbatus clade, the C. olivaceus + C. ndussumensis clade, and C. calurus were distributed across all three forest blocks (UG + LG + C). Subsequently, our results indicate a diversification pattern in which widespread (UG + LG + C) ancestors diverged across the Dahomey Gap (Fig. 1), resulting in C. barbatus and C. olivaceus occupying the forests west of the gap (UG) and C. chloronotus and C. ndussumensis inhabiting the forests east of the gap (LG + C). For C. calurus, the analysis estimates the divergence of a widespread ancestor into a clade occupying the Upper Guinea + Lower Guinean forest blocks and one occupying the Congo forest (Fig. 3). DISCUSSION Systematics In agreement with Beresford (2002), we recover all five currently recognized species of Criniger as strongly supported monophyletic lineages. Consistent with current taxonomic classifications based on Beresford’s study, we recover a strongly supported sister-species relationship between C. barbatus and C. chloronotus in both the mtDNA-only and four-gene phylogenies (Fig. 2 and Supporting Information, Fig. S1). Both analyses recover a well-supported clade of C. ndussumensis as sister to C. olivaceus, with a substantial uncorrected p-distance between the two of ~5.5% (Table 1). Overall then, our phylogenetic results support the taxonomic relationships currently recognized based on previous research efforts. However, due to our more extensive sampling regime and increased amount of molecular data compared to that of Beresford, we recover greater numbers of strongly supported geographically differentiated subclades in three Criniger species. Patterns and timing of speciation The DEC model was not found to be a significantly better fit than the DEC + J, but by a narrow margin [Χ2 = 3.84; P-value (0.05) = 0.052]. Due to the sedentary nature of all Criniger species, we determined jump dispersal to be highly unlikely and utilized the results of the DEC model. The BioGeoBEARS analysis estimates a widespread origin (i.e. all three forest blocks) (~6.22 Mya) for the genus Criniger and the timing of this initial divergence is tied to early Pliocene forest retraction during the arid phase of long-term climatic oscillations (Fig. 3). We then observe that the ancestors of C. calurus + C. ndussumensis + C. olivaceus are also estimated as widespread, having reached that range during the high humidity phase of forest expansion from the early to late Pliocene. However, the subsequent divergence event splitting C. calurus from C. ndussumensis + C. olivaceus (~5.1 Mya) is difficult to explain given the state of forest expansion at this time. We suggest more intense geographic sampling of Criniger would be necessary to explain the causative factors of this early Pliocene-aged speciation event. Beyond these first two divergences, the speciation patterns and timing recovered within the genus can be explained through a combination of isolation in lowland forest refugia and the breakup of the Guineo-Congolian forests into western and eastern blocks, separated by the Dahomey Gap. Indeed, several investigations have recovered similar evidence for east-west genetic diversification of avian and mammalian populations distributed across the Dahomey Gap (birds: Beresford & Cracraft, 1999; Schmidt et al., 2008; Marks, 2010; Fuchs & Bowie, 2015; Huntley & Voelker, 2016; mammals: Gonder et al., 2011; Nesi et al., 2013; reptiles: Leaché et al., 2014). The patterns and timing of speciation we recovered in Criniger also support the involvement of the Dahomey Gap, in conjunction with more regional refugial scenarios, as a driver of two speciation events. For example, our ancestral area estimation (Fig. 3) reconstructs a widespread (UG + LG + C) distribution for the ancestors of C. barbatus + C. chlorontus and C. olivaceus + C. ndussumensis, with estimated divergence times of ~3.2 and ~1.9 Mya, respectively, both within the forest contraction phase of the Pliocene. These divergence dates are just prior to known aridity peaks at 2.8 and 1.7 Mya, suggesting that forest retraction can be implicated as the driver of diversification between these lineages. Specifically, our ancestral area estimations suggest speciation of these lineages as a result of isolation in forest refuges west of the Dahomey Gap (C. barbatus and C. olivaceus) and east of the Dahomey Gap (C. chloronotus and C. ndussumensis; Fig. 1). Subsequently, the distribution of C. chloronotus (east of the Dahomey Gap: Fig. 1) suggests the gap remained a geographic barrier for this species during recent forest expansion phases. However, the current distribution of C. barbatus in both Upper and Lower Guinean forests (i.e., across the gap; Fig. 1) indicates the Dahomey Gap was not a barrier to eastward expansion for that species. Further evidence for the effects of Pleistocene-aged forest fragmentation and the Dahomey Gap as a potential barrier is demonstrated in C. calurus, where we recover a divergence between Upper Guinean and Lower Guinean haplogroups dated to ~1.1 Mya (Figs 2, 3, 4C). This date aligns with the most recent Pleistocene aridity spike defined by deMenocal (2004) at 1.0 Mya, in which forests were severely fragmented. We suggest allopatric diversification driven by a climate-induced east-west refugial scenario, subsequently reinforced by the Dahomey Gap, as the causal agent for this pattern of divergence. Intraspecific genetic patterns in West Africa Two refugial areas have long been proposed to exist within the Upper Guinean forest block: one straddling the border between Sierra Leone and Liberia, and one within Ghana (Prigogine, 1988; Maley, 1996; Anhuf et al., 2006; Fig. 1). We find varying levels of evidence for these refugial areas within all three species of Criniger inhabiting the Upper Guinean forests. Criniger barbatus displays a deep divergence (uncorrected p-distance ~5.5%; Table 1; Fig. 4B) between individuals in Sierra Leone/Liberia and those in Ghana. This divergence is estimated to have occurred ~1.6 Mya (Fig. 3), a date closely corresponding to one of the Pleistocene spikes in aridity and forest fragmentation (at 1.7 Mya; deMenocal, 2004). The two other species inhabiting the Upper Guinean forests, C. calurus and C. olivaceus, also display geographic structuring between Sierra Leone/Liberia and Ghana dating to the Pleistocene (Figs 2, 4), albeit at substantially shallower levels (uncorrected p-distance of 0.1 and 0.2%, respectively; Table 1) than recovered in C. barbatus. Given the lack of any substantial geological barrier to gene flow between these historic refugial centres (i.e. major rivers or mountain formations), it seems likely the patterns observed in these three species are a result of climate-induced forest fragmentation during the Holocene (Salzmann & Hoelzmann, 2005). Notably, the recovery of geographic structuring of genetic diversity between Sierra Leone/Liberia and Ghana is not surprising given that studies of several mammalian (Lemnoscomys striatus: Nicolas et al., 2008; Crocidura olivieri: Jacquet et al., 2015) and avian species (H. prasina: Marks, 2010; three species of Bleda: Huntley & Voelker, 2016) found similar patterns. The contrast in depth of observed intraspecific genetic divergences (i.e., shallow vs. deep) recovered in the West African lineages of Criniger (C. barbatus, C. calurus, C. olivaceus) may be explained in two ways. First, the amount of time these populations remained in isolation, thereby varying the effective population size and amount of accumulated genetic mutations, was different between species. Second, isolation levels during forest fragmentation events may have varied due to differing life history strategies. Criniger barbatus is not observed in new growth forests and is rarely documented foraging more than 5 m off the ground, making it a true understory specialist (Fishpool & Tobias, 2005). This characteristic behaviour is also shared by the three previously mentioned species of Bleda in which deep genetic divergences were documented between Sierra Leone/Liberia and Ghana (Huntley & Voelker, 2016). Understory taxa may display higher levels of genetic structure than more dispersive species (i.e. canopy species), a scenario related to significantly lower dispersal levels of understory birds across open spaces (Lees & Peres, 2009; Kahindo et al., 2017). In contrast, C. calurus and C. olivaceus have been observed regularly from 5 to 25 m off the ground, and can be found in regenerating forest (Fishpool & Tobias, 2005). We suggest this flexibility in habitat preference and usage may have contributed to their response to fragmentation scenarios, with both C. calurus and C. olivaceus being able to disperse between refugial centres using gallery forest, edge habitat and suboptimal habitats. This flexibility has been cited as a possible explanation of similar shallow geographic structuring in similarly distributed avian species (Nectarinia olivacea: Bowie et al., 2004; Platysteira peltata/ P. cyanea: Njabo, Bowie & Sorenson, 2008; Sylvietta virens: Huntley & Voelker, 2017). Intraspecific genetic patterns in Central Africa Within both C. calurus and C. chloronotus, we recover deep genetic breaks (Fig. 4; Table 1) between populations in Equatorial Guinea/Gabon (EGG) and the DRC (Figs 2, 4) with divergences estimated to have occurred near the Pliocene-Pleistocene boundary (C. calurus: ~1.9 Mya) or within the Pleistocene (C. chloronotus: ~1.3 Mya; Fig. 3). Several investigations have shown evidence for Plio-Pleistocene refuges within Equatorial Guinea, Gabon and the DRC (Maley, 1996; Anhuf et al., 2006). The deep divergences recovered in these two species between EGG and the DRC would suggest isolation in refugial forest fragments during the Plio-Pleistocene, a result supported by similar patterns observed in other avian taxa (H. prasina: Marks, 2010; Bleda: Huntley & Voelker, 2016). Additionally, the lower Congo River exists as a potential barrier between populations in EGG and those in the DRC. We suggest the lower Congo River could have played a role in shaping genetic structure in the region, either as a barrier during fragmentation events or as a barrier reinforcing patterns post-fragmentation, as species ranges expanded from refugia. However, the extent of the lower Congo River’s influence on the patterns observed within C. calurus and C. chloronotus is difficult to discern given the limited sampling available in the area for these species. We are unaware of studies assessing the lower Congo River as a putative barrier separating EGG and DRC populations. In contrast to the deep genetic structure recovered in C. calurus and C. chloronotus, minimal genetic structure is recovered for C. ndussumensis (Fig. 2) and we estimate an origin of ~1.95 Mya for this species (Fig. 3). This result suggests that C. ndussumensis experienced similar fragmentation events as the previously mentioned species displaying high genetic differentiation levels across central African forests. For instance, a similar pattern of minimal genetic geographic structuring within the Congo forests was recovered in both Bleda notatus and B. ugandae (Huntley & Voelker, 2016). We suggest the lack of deep patterns within C. ndussumensis may be the result of historic isolation within only one Congo forest refuge during fragmentation, a scenario which would negate the effects of allopatric divergence observed in other species. However, given the dearth of information regarding this species’ specific habitat usage, we lack the data necessary to draw more than suggestions regarding how the life history strategies of C. ndussumensis may affect the patterns we recovered. Additionally, we acknowledge that the shallow patterns recovered for C. ndussumensis in the present study may also be a consequence of poor sampling across its range. The upper Congo River as a genetic barrier Several recent studies have recovered evidence for the upper Congo River as an historic barrier to gene flow over at least the past two million years. Voelker et al. (2013) found evidence for genetic differentiation across the Congo River in four out of ten avian species sampled with distributions both north and south of the upper Congo River. A subsequent study focusing on B. syndactylus, one of the species included in Voelker et al. (2013), reinforced the evidence for genetic differentiation north and south of the upper Congo River through more extensive sampling (Huntley & Voelker, 2016). In contrast, Voelker et al. (2013) found no evidence for genetic diversity structure north and south of the river in C. calurus, a result which this study upholds with greater sampling (Figs 2, 4C). However, we do recover two geographically overlapping clades of C. calurus within the DRC which are substantially divergent from one another (Fig. 4C; Table 1). Prigogine (1988) and Maley (1996) both suggested the existence of one large Pleistocene forest refuge in the central DRC (along and south of the Congo River) and another in the north-eastern DRC (north of the Congo River; Fig. 1A). We propose the pattern recovered in the individuals of C. calurus from the DRC is due to isolation in these two refuges for a long enough period of time to allow substantial genetic differentiation between the two populations. Subsequently, as forests expanded in the more humid interglacial period, these populations expanded to occupy their present ranges across the upper Congo River. Further analyses of these two deeply divergent populations using other data, such as morphology and song, may well support the recognition of them as species. Such analyses should obviously assess the other deeply divergent C. calurus lineages, as well as similar deeply divergent lineages in other Criniger species. CONCLUSION The patterns recovered in this investigation add to the growing number of studies indicating African lowland forests harbour far more cryptic diversity than previously thought. These results offer an argument against the hypothesis that the Guineo-Congolian lowland forests are ‘evolutionary museums’, where little in situ genetic diversification occurs (Fjeldså, 1994; Roy, 1997; Fjeldså & Lovett, 1997; Roy et al., 2001; Fjeldså et al., 2007; Fjeldså & Bowie, 2008). Additionally, and in contrast to the assertions by Mayr & O’Hara (1986), the deeply divergent, intraspecific variation recovered in Criniger highlights the possible utility of widespread species, which lack plumage variation, in understanding the role of historic refugial scenarios in driving avian diversity in lowland forests. In fact, of the 107 widespread taxa deemed ‘uninformative’ in Mayr & O’Hara’s (1986) study, ten have been investigated, including the current study, and all were found to display geographic structuring, albeit at varying levels (Bleda eximius, B. syndactylus: Huntley & Voelker, 2016; Campethera nivosa: Fuchs et al., 2015; H. prasina: Marks, 2010; Illadopsis rufipennis: Nguembock et al., 2009; N. olivacea: Bowie et al., 2004; Platysteira cyanea: Njabo et al., 2008; Sylvietta denti: Huntley & Voelker, 2017; Stiphrornis erythrothorax: Beresford & Cracraft, 1999, Schmidt et al., 2008; Voelker et al., 2016b). The results from these ten ‘uninformative’ taxa in conjunction with investigations of several taxa with restricted ranges indicate the substantial complexity of biogeographic patterns within Guineo-Congolian lowland forests. The current study, as well as those previously cited, highlights that no sole hypothesis can operate as a singular explanation of the substantial complexity of genetic patterns recovered throughout the African lowland forests within vertebrate species. For instance, the timing and extent of intraspecific diversification events recovered in the understory-dwelling Criniger lend plausibility to the PFRH (Haffer, 1969) and RBH (Wallace, 1852) as possible mechanisms working in tandem to create genetic diversity. However, these results would seem to eschew the ‘evolutionary museums’ concept. In contrast, recent studies of several more vagile species of ubiquitous Afro-tropical forest birds have recovered minimal genetic geographic structuring across widespread species (Bowie et al., 2004; Fuchs & Bowie, 2015; Fuchs et al., 2017), an outcome that lends support to the ‘evolutionary museum’ hypothesis. The disparity in patterns between understory specialists (poor dispersers) and canopy users/generalists (better dispersers) reveals the importance of considering varying life history strategies on species response to historic fragmentation scenarios. Overall, the evidence recovered in Criniger for varying levels of diversification across the Dahomey Gap, the Congo River and recurring climate-induced historic forest fragmentation over the last ~7 Mya indicates that African Guineo-Congolian lowland forests are dynamic zones, fully capable of creating complex and often substantial levels of genetic diversity. SUPPORTING INFORMATION Additional Supporting Information may be found in the online version of this article at the publisher’s website: Figure S1. Bayesian and maximum likelihood phylogeny of the genus Criniger using all four loci (two mtDNA and two nuclear). Values above the nodes represent Bayesian posterior probabilities (* = 1.0) and those below the nodes represent maximum likelihood bootstrap values (* = 100). Geographical abbreviations are as follows: DRC; Democratic Republic of the Congo; EG, Equatorial Guinea. Figure S2. Phylogeny of the Myoglobin (MB2) gene derived from both Bayesian and maximum likelihood methods. Values above the nodes are Bayesian posterior probabilities and those below are maximum likelihood bootstrap supports. Figure S3. Phylogeny of the TGF β2 gene derived from both Bayesian and maximum likelihood methods. Values above the nodes are Bayesian posterior probabilities and those below are maximum likelihood bootstrap supports. Figure S4. Combined phylogeny of the TGF β2 and Myoglobin (MB2) genes derived from both Bayesian and maximum likelihood methods. Values above the nodes are Bayesian posterior probabilities and those below are maximum likelihood bootstrap supports. Table S1. Species and specimens used, with institution and voucher information for each specimen. GenBank reference numbers are listed for each gene sequenced. Table S2. Primers Used. ACKNOWLEDGEMENTS We would like to thank the curators and collection managers of the following institutions for providing genetic material: Field Museum of Natural History, American Museum of Natural History, Smithsonian National Museum of Natural History, Kansas University Museum of Natural History, the Academy of Natural Sciences of Drexel University, Carmagnola Natural History Museum (Turin, Italy) and the Yale Peabody Museum of Natural History. M.P. was funded by the University of Torino Research Grants 2015 and 2016. For technical advice throughout the project we thank Adrian Castellanos and Jessica Light. This is publication number 1553 of the Biodiversity, Research and Teaching Collections. REFERENCES Anhuf D , Ledru MP , Behling H , Da Cruz FW , Cordeiro RC , Van der Hammen T , Karmann I , Marengo JA , De Oliveira PE , Pessenda L , Siffedine A , Albuquerque AL , Da Silva Dias PL . 2006. Paleo-environmental change in Amazonian and African rainforest during the LGM. Palaeogeography, Palaeoclimatology, Palaeoecology  239: 510– 527. Google Scholar CrossRef Search ADS   Beresford P . 2002. Molecular systematics and biogeography of certain Guineo-Congolian passerines  . Unpublished D. Phil. Thesis, The City University of New York. Beresford P , Cracraft J . 1999. Speciation in African forest robins (Stiphrornis): species limits, phylogenetic relationships, and molecular biogeography. American Museum Novitates  3270: 1– 20. Bohoussou KH , Cornette R , Akpatou B , Colyn M , Kerbis Peterhans J , Kennis J , Šumbera R , Verheyen E , N’Goran E , Katuala P , Nicolas V . 2015. The phylogeography of the rodent genus Malacomys suggests multiple Afrotropical Pleistocene lowland forest refugia. Journal of Biogeography  42: 2049– 2061. Google Scholar CrossRef Search ADS   Bowie RC , Fjeldså J , Hackett SJ , Crowe TM . 2004. Molecular evolution in space and through time: mtDNA phylogeography of the Olive Sunbird (Nectarinia olivacea/obscura) throughout continental Africa. Molecular Phylogenetics and Evolution  33: 56– 74. Google Scholar CrossRef Search ADS PubMed  Brosset A , Erard C . 1986. Les oiseaux des ŕegions forestières du nord-est du Gabon. Société nationale de protection de la nature  1: 1– 289. Bryja J , Granjon L , Dobigny G , Patzenhauerová H , Konečný A , Duplantier JM , Gauthier P , Colyn M , Durnez L , Lalis A , Nicolas V . 2010. Plio-Pleistocene history of West African Sudanian savanna and the phylogeography of the Praomys daltoni complex (Rodentia): the environment/geography/genetic interplay. Molecular Ecology  19: 4783– 4799. Google Scholar CrossRef Search ADS PubMed  Bryja J , Šumbera R. , Kerbis Peterhans JC , Aghová T , Bryjová A , Ondřej M , Nicolas V , Denys C , Verheyen E . 2016. Evolutionary history of the thicket rats (genus Grammomys) mirrors the evolution of African forests since late Miocene. Journal of Biogeography  44: 182–194. Colyn M , Gautier-Hion A , Verhaven W . 1991. A re-appraisal of paleoenvironmental history of central Africa: evidence for a major fluvial refuge in the Zaire Basin. Journal of Biogeography  18: 403– 407. Google Scholar CrossRef Search ADS   Crowe TM , Crowe AA . 1982. Patterns of distribution, diversity and endemism in Afro-tropical birds. Journal of Zoology Proceedings of the Zoological Society of London  198: 417– 442. Google Scholar CrossRef Search ADS   deMenocal PB . 1995. Plio-Pleistocene African climate. Science  270: 53– 59. Google Scholar CrossRef Search ADS PubMed  deMenocal PB . 2004. African climate change and faunal evolution during the Pliocene-Pleistocene. Earth Planetary Science Letters  220: 3– 24. Google Scholar CrossRef Search ADS   Diamond AW , Hamilton AC . 1980. The distribution of forest passerine birds and Quaternary climatic changes in Tropical Africa. Journal of Zoology Proceedings of the Zoological Society of London  191: 379– 402. Google Scholar CrossRef Search ADS   Dowsett RJ , Forbes-Watson AD . 1993. Checklist of birds of the Afrotropical and Malagasy regions, Vol. 1: species limits and distribution  . Liège, Belgium: Tauraco Press. Dowsett-Lemaire F , Dowsett RJ . 1991. The avifauna of the Kouilou basin Congo. Tauraco Research Report  4: 182– 239. Dowsett-Lemaire F , Dowsett RJ . 2001. African forest birds: Patterns of endemism and species richness. In Weber W , White LJT , Vedder A , Naughton-Treves L , eds. African rain forest ecology and conservation: an interdisciplinary perspective  . New Haven, CT: Yale University Press, 233– 262. Drummond AJ , Suchard MA , Xie D , Rambaut A . 2012. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Molecular Biology and Evolution  29: 1969– 1973. Google Scholar CrossRef Search ADS PubMed  Fishpool LDC , Tobias JA . 2005. Family Pycnonotidae (Bulbuls). In del Hoyo J , Elliot A , Christie DA , eds. Handbook of the birds of the world, Vol. 10. Cuckoo-shrikes to thrushes  . Barcelona: Lync Edicions, 220–222. Fjeldså J . 1994. Geographical patterns of relict and young species of birds in Africa and South America and implications for conservation priorities. Biodiversity and Conservation  3: 107– 226. Google Scholar CrossRef Search ADS   Fjeldså J , Bowie RCK . 2008. New perspectives on the origin and diversification of Africa’s forest avifauna. African Journal of Ecology  46: 235– 247. Google Scholar CrossRef Search ADS   Fjeldså J , Johansson US , Lokugalappatti SLG , Bowie RCK . 2007. Diversification of African greenbuls in space and time: linking ecological and historical processes. Journal of Ornithology  148: 359– 367. Google Scholar CrossRef Search ADS   Fjeldså J , Lovett JC . 1997. Geographical patterns of old and young species in African forest biota: the significance of specific montane areas as evolutionary centres. Biodiversity and Conservation  6: 325– 346. Google Scholar CrossRef Search ADS   Fuchs J , Bowie RC . 2015. Concordant genetic structure in two species of woodpecker distributed across the primary West African biogeographic barriers. Molecular Phylogenetics and Evolution  88: 64– 74. Google Scholar CrossRef Search ADS PubMed  Fuchs J , Fjeldså J , Bowie RCK . 2017. Diversification across major biogeographical breaks in the African Shining/Square-tailed Drongos complex (Passeriformes: Dicruridae). Zoologica Scripta  46: 27– 41. Google Scholar CrossRef Search ADS   Gaubert P , Njiokou F , Ngua G , Afiademanyo K , Dufour Gonedelé Bi S , Tougard C , Olayemi A , Danquah E , Djagoun CAMS , Kalema P , Nebesse Mololo C , Stanley W , Luo S-J , Antunes A . 2016. Phylogeography of the heavily poached African common pangolin (Philodota, Manis tricuspis) reveals six cryptic lineages as traceable signatures of Pleistocene diversification. Molecular Ecology  25: 5975–5993. Gonder MK , Locatelli S , Ghobrial L , Mitchell MW , Kujawski JT , Lankester FJ , Stewart C-B , Tishkoff SA . 2011. Evidence from Cameroon reveals differences in the genetic structure and histories of chimpanzee populations. Proceedings of the National Academy of Sciences of the United States of America  108: 4766– 4771. Google Scholar CrossRef Search ADS PubMed  Haffer J . 1969. Speciation in Amazonian forest birds. Science  165: 131– 137. Google Scholar CrossRef Search ADS PubMed  Hamilton AC , Taylor D . 1991. History of climate and forests in Tropical Africa during the last 8 million years. Climatic Change  19: 65– 78. Google Scholar CrossRef Search ADS   Happold DCD . 1996. Mammals of the Guinea-Congo rain forest. Proceedings of the Royal Society of Edinburgh  104B: 243– 284. Hassanin A , Khouider S , Gembu GC , Goodman SM , Kadjo B , Nesi N , Pourrut X , Nakouné E , Bonillo C . 2014. The comparative phylogeography of fruit bats of the tribe Scotonycterini (Chiroptera, Pteropodidae) reveals cryptic species diversity related to African Pleistocene forest refugia. Comptes Rendus Biologies  338: 197– 211. Google Scholar CrossRef Search ADS   Huelsenbeck JP , Ronquist F . 2001. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics  17: 754– 755. Google Scholar CrossRef Search ADS PubMed  Huntley JW , Voelker G . 2016. Cryptic diversity in Afro-tropical lowland forests: the systematics and biogeography of the avian genus Bleda . Molecular Phylogenetics and Evolution  99: 297– 308. Google Scholar CrossRef Search ADS PubMed  Huntley JW , Voelker G . 2017. A tale of the nearly tail-less: the effects of Plio-Pleistocene climate change on the diversification of the African avian genus Sylvietta . Zoologica Scripta  46: 523–535. Jacquet F , Denys C , Couloux A , Colyn M , Nicolas V . 2015. Phylogeography and evolutionary history of the Crocidura olivieri complex (Mammalia, Soricomorpha): from a forest-dwelling origin to a wide expansion throughout Africa. BMC Evolutionary Biology  15: 1– 15. Google Scholar CrossRef Search ADS PubMed  Johansson US , Fjeldså J , Lokugalappatti SLG , Bowie RCK . 2007. A nuclear DNA phylogeny and proposed taxonomic revision of African greenbuls (Aves, Passeriformes, Pycnonotidae). Zoologica Scripta  36: 417– 427. Google Scholar CrossRef Search ADS   Kahindo CM , Bates JM , Bowie RCK . 2017. Population genetic structure of Grauer’s Swamp Warbler Bradypterus graueri, an Albertine Rift endemic. Ibis  159: 415– 429. Google Scholar CrossRef Search ADS   Kearse M , Moir R , Wilson A , Stones-Havas S , Cheung M , Sturrock S , Buxton S , Cooper A , Markowitz S , Duran C , Thierer T , Ashton B , Meintjes P , Drummond A . 2012. Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics  28: 1647– 1649. Google Scholar CrossRef Search ADS PubMed  Keith S . 1992. Family Pycnonotidae (Bulbuls). In Keith S , Urban EK , Fry CH , eds. The birds of Africa, Vol. IV  . London: Academic Press, 1– 459. Kennis J , Nicolas V , Hulselmans J , Katuala PGB , Wendelen W , Verheyen E , Dudu AM , Leirs H . 2011. The impact of the Congo River and its tributaries on the rodent genus Praomys: speciation origin or range expansion limit? Zoological Journal of the Linnean Society  163: 983– 1002. Google Scholar CrossRef Search ADS   Lanfear R , Calcott B , Kainer D , Mayer C , Stamatakis A . 2014. Selecting optimal partitioning schemes for phylogenomic datasets. BMC Evolutionary Biology  14: 82. Google Scholar CrossRef Search ADS PubMed  Leaché AD , Fujita MK , Minin VN , Bouckaert RR . 2014. Species delimitation using genome-wide SNP data. Systematic Biology  63: 534– 542. Google Scholar CrossRef Search ADS PubMed  Lees AC , Peres CA . 2009. Gap-crossing movements predict species occupancy in Amazonian forest fragments. Oikos  118: 280– 290. Google Scholar CrossRef Search ADS   Lerner HR , Meyer M , James HF , Hofreiter M , Fleischer RC . 2011. Multilocus resolution of phylogeny and timescale in the extant adaptive radiation of Hawaiian honeycreepers. Current Biology  21: 1838– 1844. Google Scholar CrossRef Search ADS PubMed  Levinsky I , Araujo MB , Nogues-Bravo D , Haywood AM , Valdes PJ , Rahbek C . 2013. Climate envelope models suggest spatio-temporal co-occurrence of refugia of African birds and mammals. Global Ecology and Biogeography  22: 351– 363. Google Scholar CrossRef Search ADS   Maley J . 1996. The African rain forest - main characteristics of changes in vegetation and climate from the Upper Cretaceous to the Quaternary. Proceedings of the Royal Society of Edinburgh  104B: 31– 73. Maley J . 2001. The impact of arid phases on the African rain forest through geological history. In Weber W , White LJT , Vedder A , Naughton-Treves L , eds. African rain forest ecology and conservation. an interdisciplinary perspective  . New Haven, CT: Yale University Press, 69– 85. Marks BD . 2010. Are lowland rainforests really evolutionary museums? Phylogeography of the green hylia (Hylia prasina) in the Afrotropics. Molecular Phylogenetics and Evolution  55: 178– 184. Google Scholar CrossRef Search ADS PubMed  Matzke NJ . 2013a. Probabilistic historical biogeography: new models for founder-event speciation, imperfect detection, and fossils allow improved accuracy and model-testing  . Unpublished D. Phil. Thesis, University of California, Berkeley. Matzke NJ , 2013b. BioGeoBEARS: BioGeography with Bayesian (and likelihood) evolutionary analysis in R scripts  . Berkeley, CA: CRAN: The Comprehensive R Archive Network. Mayr E , O’Hara RJ . 1986. The biogeographic evidence supporting the Pleistocene forest refuge hypothesis. Evolution  40: 55– 67. Google Scholar CrossRef Search ADS PubMed  Moyle RG , Marks BD . 2006. Phylogenetic relationships of the bulbuls (Aves: Pycnonotidae) based on mitochondrial and nuclear DNA sequence data. Molecular Phylogenetics and Evolution  40: 687– 695. Google Scholar CrossRef Search ADS PubMed  Nesi N , Kadjo B , Pourrut X , Leroy E , Pongombo Shongo C , Cruaud C , Hassanin A . 2013. Molecular systematics and phylogeography of the tribe Myonycterini (Mammalia, Pteropodidae) inferred from mitochondrial and nuclear markers. Molecular Phylogenetics and Evolution  66: 126– 137. Google Scholar CrossRef Search ADS PubMed  Nguembock B , Cibois A , Bowie RCK , Cruaud C , Pasquet E . 2009. Phylogeny and biogeography of the genus Illadopsis (Passeriformes: Timaliidae) reveal the complexity of diversification of some African taxa. Journal of Avian Biology  40: 113– 1125. Google Scholar CrossRef Search ADS   Nicolas V , Mboumba JF , Verheyen E , Denys C , Lecompte E , Olayemi A , Missoup AD , Katuala P , Colyn M . 2008. Phylogeographic structure and regional history of Lemniscomys striatus (Rodentia: Muridae) in tropical Africa. Journal of Biogeography  35: 2074– 2089. Google Scholar CrossRef Search ADS   Nicolas V , Missoup AD , Colyn M , Cruaud C , Denys C . 2012. West-Central African Pleistocene lowland forest evolution revealed by the phylogeography of Misonne’s Soft-Furred Mouse. African Zoology  47: 100– 112. Nicolas V , Missoup AD , Denys C , Kerbis Peterhans J , Katuala P , Couloux A , Colyn M . 2011. The roles of rivers and Pleistocene refugia in shaping genetic diversity in Praomys misonnei in tropical Africa. Journal of Biogeography  38: 191– 207. Google Scholar CrossRef Search ADS   Njabo KY , Bowie RC , Sorenson MD . 2008. Phylogeny, biogeography and taxonomy of the African wattle-eyes (Aves: Passeriformes: Platysteiridae). Molecular Phylogenetics and Evolution  48: 136– 149. Google Scholar CrossRef Search ADS PubMed  Pasquet E , Han LX , Khobkhet O , Cibois A . 2001. Towards a molecular systematics of the genus Criniger, and a preliminary phylogeny of the bulbuls (Aves, Passeriformes, Pycnonotidae). Zoosystema  23: 857– 863. Plana V . 2004. Mechanisms and tempo of evolution in the African Guineo-Congolian rainforest. Proceedings of the National Academy of Sciences  359: 1585– 1594. Prigogine A . 1988. Speciation pattern of birds in the Central African Forest Refugia and their relationship with other refugia. Proceedings of the International Ornithological Congress  19: 2537– 2546. Quérouil S , Verheyen E , Dillen M , Colyn M . 2003. Patterns of diversification in two African forest shrews: Sylvisorex johnstoni and Sylvisorex ollula (Soricidae, Insectivora) in relation to paleo-environmental changes. Molecular Phylogenetics and Evolution  28: 24– 37. Google Scholar CrossRef Search ADS PubMed  Rambaut A , Suchard MA. , Xie D , Drummond AJ . 2014. Tracer v1.6  . Available at: http://beast.bio.ed.ac.uk/Tracer Roy MS . 1997. Recent diversification in African greenbuls (Pycnonotidae: Andropadus) supports a montane speciation model. Proceedings of the Royal Society B: Biological Sciences  264: 1337– 1344. Google Scholar CrossRef Search ADS   Roy MS , Sponer R , Fjeldså J . 2001. Molecular systematics and evolutionary history of kalats (genus Sheppardia): a pre-Pleistocene radiation in a group of African forest birds. Molecular Phylogenetics and Evolution  18: 74– 83. Google Scholar CrossRef Search ADS PubMed  Salzmann U , Hoelzmann P . 2005. The Dahomey Gap: an abrupt climatically induced rain forest fragmentation in West Africa during the late Holocene. Holocene  15: 190– 199. Google Scholar CrossRef Search ADS   Schmidt BK , Foster JT , Angehr GR. , Durrant KL , Fleischer RC , 2008. A new species of African forest robin from Gabon (Passeriformes: Muscicapidae: Stiphrornis). Zootaxa  1850: 27– 42. Sibley CG , Monroe BL Jr . 1990. Distribution and taxonomy of birds of the world  . New Haven, CT: Yale University Press. Stamatakis A . 2014. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics  30: 1312– 1313. Google Scholar CrossRef Search ADS PubMed  Tamura K , Stecher G , Peterson D , Filipski A , Kumar S . 2013. MEGA6: molecular evolutionary genetics analysis version 6.0. Molecular Biology and Evolution  30: 2725– 2729. Google Scholar CrossRef Search ADS PubMed  Voelker G , Huntley JW , Peñalba JV , Bowie RCK . 2016a. Resolving taxonomic uncertainty and historical biogeographic patterns in Muscicapa flycatchers and their allies. Molecular Phylogenetics and Evolution  94: 618– 625. Google Scholar CrossRef Search ADS   Voelker G , Marks BD , Kahindo C , A’genonga U , Bapeamoni F , Duffie LE , Huntley JW , Mulotwa E , Rosenbaum SA , Light JE . 2013. River barriers and cryptic biodiversity in an evolutionary museum. Ecology and Evolution  3: 536– 545. Google Scholar CrossRef Search ADS PubMed  Voelker G , Outlaw RK , Bowie RCK . 2010. Pliocene forest dynamics as a primary driver of African bird speciation. Global Ecology and Biogeography  19: 111– 121. Google Scholar CrossRef Search ADS   Voelker G , Tobler M , Prestridge HL , Duijm E , Groenenberg D , Hutchinson MR , Martin AD , Nieman A , Roselaar CS , Huntley JW . 2016b. Three new species of Stiphrornis (Aves: Muscicapidae) from the Afro-tropics, with a molecular phylogenetic assessment of the genus. Systematics and Biodiversity  15: 87– 104. Google Scholar CrossRef Search ADS   Wallace AR . 1852. On the monkeys of the Amazon. Proceedings of the Zoological Society of London  20: 107– 110. © 2017 The Linnean Society of London, Zoological Journal of the Linnean Society

Journal

Zoological Journal of the Linnean SocietyOxford University Press

Published: Dec 12, 2017

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off