Tropical Lowland Forests

Received: 24 May 2018 | Revised: 13 November 2018 | Accepted: 19 November 2018 DOI: 10.1111/jbi.13505

RESEARCH PAPER

Underestimated and cryptic diversification patterns across Afro‐tropical lowland forests

Jerry W. Huntley1,2 | Katrina D. Keith1 | Adrian A. Castellanos1 | Lukas J. Musher2,3 | Gary Voelker1

1Department of Wildlife and Fisheries Sciences, Texas A&M University, College Abstract Station, Texas Aim: Vertebrate diversity in the Guineo‐Congolian forests (GCF) of Africa is high, 2Department of Ornithology, American yet mechanisms responsible for generating that diversity remain remarkably under- Museum of Natural History, New York, New York studied. These forests have alternatively been viewed as centres of diversification 3The Richard Gilder Graduate School, (“cradles”) or more recently, as the opposite (“museums”). Here, we use a compara- American Museum of Natural History, New York, New York tive dataset of avian and mammalian species to examine genetic diversification patterns across these forests and use these results to explain observed patterns in light Correspondence ‐ ‐ Jerry W. Huntley, Department of of Plio Pleistocene climatic change and life history. Ornithology, American Museum of Natural Location: Africa. History, New York, NY. Email: [email protected] Methods: We analysed patterns of diversification across the GCF using a dataset composed of 629 and 1,048 mitochondrial sequences from 60 avian and 36 mam- Editor: Judith Masters malian species, respectively. Uncorrected pairwise genetic distances were compared at three distinct geographical levels: west versus east of the Dahomey Gap, among the three major forest blocks, and among seven historical refugial areas. The timing of diversification was assessed for passerines, Rodentia, and Chiroptera. Results: We found substantial signatures of diversification in all three levels of our geographical comparisons. We recovered substantial disparity in the amount and depth of structure of diversification patterns between low dispersers (understorey birds and rodents) and more capable dispersers (other bird species and bats). Addi- tionally, our chronogram recovered recent speciation and intraspecific diversification across songbird and mammalian lineages. Main conclusions: The discrete, and often deep, structuring of genetic diversification for both birds and mammals across the GCF revealed strong correlations between historic landscape fragmentation and dispersal ability. Our results revealed a striking amount of unrecognized genetic diversity, which may be suggestive of cryptic species. Given the rate at which these forests are being negatively impacted by human inter- vention, our general lack of knowledge concerning vertebrate diversity across these forests may very well impact our ability to identify evolutionary processes underlying diversity and enact meaningful conservation efforts in the future.

KEYWORDS Africa, Aves, conservation, cryptic species, diversification, Guineo-Congolian, historical biogeography, landscape fragmentation, Mammalia

1 | INTRODUCTION especially noticeable when compared to highly sampled and studied regions such as the Neotropics, where an abundance of avian‐ Biologists have long been fascinated by the complex diversity har- focused genetic studies have shown intricate patterns of diversifica- boured in tropical forests. In assessing the patterns and drivers of tion, at both temporal and spatial scales (e.g., Ribas et al., 2018; this diversity, many studies have attempted to explain complexity by Schultz et al., 2017; Smith et al., 2014). Importantly, the abundance categorizing tropical forests as being either evolutionary “cradles” or of Neotropical studies has facilitated additional studies seeking to “museums” (e.g., Jablonski, Roy, & Valentine, 2006; McKenna & Far- assess diversification patterns in a broad comparative framework. rell, 2006; Moreau & Bell, 2013; Wiens & Donoghue, 2004). These While molecular studies of GCF birds have been increasing (e.g., opposing hypotheses describe tropical forests as being either impor- Fuchs, Fjeldså, & Bowie, 2017; Huntley & Voelker, 2016, 2017; tant centres of diversification (evolutionary “cradles”) or static Huntley, Harvey, Pavia, Boano, & Voelker, 2017; Voelker et al. 2017) regions which promote very little diversity in situ (evolutionary broader comparative studies are only now becoming possible. “museums”). Another limitation, also presumably connected to the lack of In Africa, these hypotheses have primarily been limited to avian genetic material, has been a narrow research focus regarding the diversity within the Guineo‐Congolian forests (GCF) and have often mechanisms responsible for creating and maintaining diversification been treated as mutually exclusive. The evolutionary “cradle” model within the GCF. The larger part of the avian biogeographical litera- has been invoked to explain patterns of endemicity and disjunct ture from Africa centres on repeated climatically induced landscape ranges under the Pleistocene Forest Refuge Hypothesis paradigm fragmentation as the primary driver for speciation and lineage diver- (PFRH) (Diamond & Hamilton, 1980; Haffer, 1969; Mayr & O'Hara, sification. The structure and measure of genetic diversity within spe- 1986; Prigogine, 1988; for endemicity in mammals see Grubb, 1990). cies and groups focus on pervasive, cyclical climate variation driving The PFRH focuses on widespread, climate‐driven landscape fragmen- lowland forest fragmentation/coalescence events which, in turn, have tation, specifically during the Pleistocene (~1.8 Ma–11,700 ka, when proven to be a driving force in the creation and maintenance of developed), as a driver for avian distributional patterns. But impor- many diversity patterns (e.g., Huntley & Voelker, 2016; Huntley et tantly, not all avian species were considered equal: in defining which al., 2017). While historic fragmentation has undoubtedly played a species would be of use in analysing patterns under the PRFH, Mayr vital role, other factors may be necessary to explain mosaic patterns and O'Hara (1986) specifically argued that biogeographical patterns of diversity, including lineage persistence and functional traits (e.g., could only be discerned by analysing taxa which display distinct plu- dispersal capabilities). These characteristics have been shown to play mage variation across the forest. As a function of this argument, an important role in influencing the response of Neotropical taxa to they published a list of 107 avian forest species lacking such varia- historical events (e.g., Smith et al., 2014), but such characteristics tion, and explicitly deemed them to be of little utility for biogeo- have rarely been assessed for their potential impact in shaping GCF graphical investigations. bird distributions (but see Kruger, Sorenson, & Davies, 2009 and As an alternative to the evolutionary “cradle” framework, the Voelker et al., 2013). Montane Speciation Hypothesis (MSH) was developed to explain, Further hindering a broader conceptual framework for under- primarily, avian distributional patterns (or lack thereof) under an evo- standing how diversity across the GCF is distributed and structured lutionary “museum” concept (Fjeldså, Bayes, Bruford, & Roy, 2005; in space and time, is that the relevant literature overwhelmingly Fjeldså & Bowie, 2008; Fjeldså, Johansson, Lokugalappatti, & Bowie, focuses on avian taxa. Indeed the “museum” versus “cradle” debate 2007; Fjeldså & Lovett, 1997; Roy, 1997; Roy, Sponer, & Fjeldså, for the GCF has been focused on avian species. However, a growing 2001; but see Voelker, Outlaw, & Bowie, 2010). Based on speciation number of recent studies focused on GCF forest mammals have times derived from molecular analyses, these studies demonstrated found evidence for patterns concordant with those recovered in that lowland forest species were “ancient” (~22.0–5.0 Ma) and mon- birds (e.g., Bryja et al., 2016; Gaubert et al., 2016), revealing the tane birds “young” (≤5.0 Ma). A collective conclusion was that little necessity of a broader focus on the faunal makeup of this region. in situ genetic diversity or structure has arisen in lowland forests Because GCF bird and mammal studies have been increasing, a com- and that any genetic diversity that does exist is derived from mon- bined comparison of genetic variation along with consideration of tane forests nearby. roughly similar behavioural traits such as capable dispersers (i.e., Molecular techniques utilized to develop the MSH were not canopy birds and bats) or more sedentary species (i.e., understorey available during the development of the PFRH, which was limited to birds and rodents/shrews) may broaden our understanding of shared patterns of phenotypic variation, and it is clear that molecular tools biogeographical patterns and the impact of processes driving diversi- would enhance our ability to compare and contrast patterns regard- fication. ing these competing hypotheses. One limitation in this regard is that Comparing phylogeographical patterns from 60 avian species and acquisition of genetic material from many regions of the GCF has 36 mammalian species codistributed (to varying extents) across the historically been difficult. As such there is a rather small body of GCF, we seek to assess four evolutionary or conservation‐based recent literature addressing these hypotheses, and others that might goals. First, we examine the extent and timing of intraspecific diver- explain biogeographical patterns. This lack of material and data is sification patterns and their drivers across the GCF region. Second, HUNTLEY ET AL. | 383 we seek to assess the influence of dispersal ability on species’ We utilized p‐distances taken from Appendix Tables S3–S6 to response to potential diversification mechanisms. Third, we examine create box plots for each dispersal type with individual comparisons whether a dataset of codistributed birds and mammals will support across both the forest block and refugial level. To further assess the “evolutionary cradle” (i.e., geographical structuring of genetic these p‐distances across dispersal type (i.e., low dispersers vs. disper- variation and Plio‐Pleistocene divergence times) or “evolutionary salists), we ran linear mixed models at each geographical scale sepa- museum” (minimal structure and divergence estimates > 5 Ma) rately for birds and mammals. We set dispersal ability as a fixed hypotheses. And finally, we frame recovered patterns (or lack effect and species as a random effect using the ‘nlme’ package (Pin- thereof) within an assessment of how our data may be valuable to heiro, Bates, DebRoy, & Sarkar, 2017) in R version 3.4.3 (R Develop- conservation prioritization. ment Core Team 2017).

2 | MATERIALS AND METHODS 2.3 | Timing of diversification

We used BEAST 2.3.1 (Drummond, Suchard, Xie, & Rambaut, 2012) to 2.1 | Molecular data estimate molecular divergence times across avian and mammalian From GenBank (www.ncbi.nlm.nih.gov/genbank), we downloaded species for the larger ND2 and CYTB datasets only. For birds, we 629 mitochondrial (mtDNA) sequences representing four genes from used empirical substitution rates and standard deviations derived in 60 avian species and 1,048 Cytochrome oxidase b (CYTB) sequences Lerner, Meyer, James, Hofreiter, and Fleischer (2011) for songbirds. from 36 mammalian species, whose primary habitat preferences are This resulted in an ND2 alignment of 38 species (130 sequences), defined as lowland tropical forest (del Hoyo, Elliott, Sargatal, & and a CYTB alignment of 14 species (43 sequences). We employed a Christie, 1992-2013; Kingdon et al., 2013) (see Appendix Tables S1 GTR+G evolutionary model and an uncorrelated log‐normal relaxed and S2 for sampling detail). To minimize stochastic bias, we excluded clock with a normal Yule process speciation prior. We ran two sequences <500 base pairs in length. By taxon (bird or mammal), for MCMC runs of 100,000,000 generations with sampling every 1,000 each of the mtDNA loci separate alignment matrices were created in steps.

SEQUENCHER 4.9 (Gene Codes Corporation, Ann Arbor, MI) and we For mammals, we also applied a GTR+G substitution model on used MUSCLE 3.8 (Edgar, 2004) to estimate proper alignment in the the CYTB alignment and applied a birth‐death tree prior. We then two largest matrices (ND2 and CYTB of birds). Alignments of all loci utilized secondary calibrations of uniform priors based on 95% HPD were validated by checking for internal stop codons and confirming from previous studies (Tarver et al., 2016; Teeling et al., 2005) in lieu protein translation. of a well‐understood empirical clock rate, and ran separate analyses for bats (Chiropterans) and rodents (Rodentia). We applied priors for the crown of Chiroptera (55.71–60.28 Ma; Tarver et al., 2016) and 2.2 | Genetic distances and geographical partitions the split between Rhinolophidae and Hipposideridae (37–43 Ma; Using del Hoyo et al. (1992‐2013) and Sinclair and Ryan (2010), Teeling et al., 2005). For chiropterans, we also restricted mean sub- avian species were divided into two categories: low dispersers (un- stitution rates across the tree with a uniform prior between 0.01 derstorey species) or those that are predominately dispersive and 0.05 substitutions per lineage Ma (Mao, Zhang, Zhang, & Ros- (canopy dwellers or habitat generalists). For both birds and mammals, siter, 2010; Nesi et al., 2013). For Rodentia, we placed priors for the we estimated uncorrected pairwise (p‐distances) differences between crown (60.07–63.78 Ma), the split between porcupines and Muridae lineages within each species (for each locus represented) using MEGA7 (56.91–60.28 Ma), crown Muridae (10.46–13.98 Ma; Tarver et al., (Tamura, Stecher, Peterson, Filipski, & Kumar, 2013). Distance mea- 2016), crown Malacomys (2.5–5.1 Ma; Bohoussou et al., 2015), and sures were estimated across three GCF geographical partitions. For also put a prior with normal distribution of mean = 12.0 and sigma = the broadest comparison we divided sequences into two groups: 1.0 on crown Murinae as used in previous studies (Nicolas et al., those representing individuals from west of the Dahomey Gap (DG) 2008). versus those from east of the gap. The DG is an arid corridor located All resulting logfiles were examined in TRACER 1.6 (Rambaut, in Benin and Togo which breaks the GCF into western and eastern Suchard, Xie, & Drummond, 2014) to ensure that effective sample forest expanses (Salzmann & Hoelzmann, 2005) (Figure 1a). Next, we sizes for all parameters were >200, and to evaluate the 95% con- divided sequences into groups corresponding to the three floristic fidence intervals for divergence dating. TREEANNOTATOR 2.3 (Drum- blocks traditionally delineated within the GCF: Upper Guinean Forest mond et al., 2012) was used to summarize the posterior (UGF), Lower Guinean Forest (LGF), and Congo Forest (CF) (Fig- distribution of trees for maximum clade credibility. To ensure ure 1a). Finally, we grouped sequences according to known refugial clock calibrations were reasonable, we compared the divergence regions: Sierra Leone/Liberia (SLL) and Ghana (both UGF); Nigeria/ times on the best tree to previously published divergence esti- Cameroon (Nig/Cam) (LGF); and Equatorial Guinea (EG), Gabon, mates for several of the lineages included here (p Table S1). Equatorial Guinea/Gabon (EG/G), the Central African Republic (CAR), Times of divergence for nodes within each genus were then and the Democratic Republic of the Congo/Uganda (DRC/U) (all CF) placed into half million‐year bins and a histogram of divergence (Figure 1a,b). times was created. 384 | HUNTLEY ET AL.

FIGURE 1 (a) Approximate current cover of the Guineo‐Congolian lowland forests (green shaded areas) and delineation of all three floristically defined blocks of the forest (dashed). (b) Hypothesized configuration of Quaternary lowland tropical forest refugia according to Mayr & O'Hara, 1986 (grey), Prigogine, 1988 (dashed), and Maley, 1996 (green). (c) General sampling areas for avian taxa. (d) General sampling areas for mammalian taxa [Colour figure can be viewed at wileyonlinelibrary.com]

(range: 0.0%–5.7%) (Figure 2a and Table 1). For six low dispersal 3 | RESULTS mammalian species, we calculated an average p‐distance of 5.8% (range: 2.2%–10.2%) for the UGF versus LGF comparison, with one 3.1 | Divergence estimates relevant bat species (high disperser) having a p‐distance of 2.2% (Fig- Overall, significant differences in genetic distances were seen for ure 2a and Table 1). For the LGF versus CF comparison we recov- birds and mammals across dispersal type. These trends showed dif- ered average p‐distances of 5.9% (range: 0.7%–18.5%) for 20 low ferent patterns of significance according to geographic scale and dispersal mammals and 1.0% (range: 0.5%–1.9%) for three high dis- taxon (Appendix Table S7). For our broadest Afro‐tropical forest persal species (Figure 2a and Table 1). comparison (west vs. east of the DG; Figure 1a), we were able to Our narrowest partitioning involved seven refugial area compar- include data from 15 predominately understorey (low dispersers), isons (Table 2; see Appendix Tables S5 and S6 for greater detail). and 22 predominately dispersive avian species (Table 1; see Tables Our analyses allowed comparisons across 23 understorey avian spe- S3 and S4 in Appendix for more detail). Across understorey species, cies and 21 dispersive avian species; depending on the species, one we recovered an average mtDNA p‐distance of 6.9% (range 1.3%– to seven comparisons were possible (Table 2). We recovered sub- 14.6%) (Table 1). For dispersive lineages, we recovered a lower aver- stantial differences in four comparisons (between 2.6%–5.2%; see age of 4.2% (range: 0.1%–11.4%). For mammals, we recovered an Figure 2b). However, the remaining three comparisons showed mini- average p‐distance of 7.7% (range: 2.4%–15.6%) for the six low dis- mal differences (between 0.6%–2.0%) between compared refugial persal species and much lower average distance of 2.5% (range: regions. Averages for both bird groups with species distributed in 2.1%–4.5%) for three dispersalist species. The three forest block par- Equatorial Guinea and Gabon, the two geographically closest refugia, tition (Figure 1a) included 24 avian comparisons between the UGF were low, (understorey: 1.9%; dispersive: 0.6%). However, two and LGF blocks, and 32 comparisons between the LGF and CF understorey species (Bleda syndactylus and Stiphrornis eyrthrothorax) (Table 1). We recovered values similar to the DG comparison for the showed a substantial difference at 3.4% and 6.8%, respectively. Simi- UGF versus LGF, with 12 understorey species averaging 6.4% (range: larly, the comparison between Equatorial Guinea/Gabon and CAR 1.0%–12.9%) and 12 dispersive species averaging 3.8% (range: 0.3%– produced low average distance (understorey: 2.6%; dispersive: 0.6%; 11.4%; Figure 2a). Values for the LGF versus CF comparisons were Figure 2b), yet three understorey species displayed a p‐distance in much lower: 18 understorey bird species averaged 4.3% (range: this comparison of 6.5% or higher (see Table 2). The refugial com- 0.1%–14.3%) while the 14 dispersive species averaged just 1.4% parison within the CF (DRC/U and CAR) only recovered an average HUNTLEY ET AL. | 385

TABLE 1 Mitochondrial uncorrected pairwise distances between difference between 3.7% and 8.2%) (Figure 2b and Table 2). The forests east and west of the Dahomey gap and between forest exception to this pattern is the comparison between Nigeria/Camer- blocks oon and CAR, which displayed an average difference of 2.6%. How- Upper ever, one rodent species (low disperser) (Hylomyscus parvus) showed Guinean a p‐distance of 8.6% between these two areas. West Gap versus Lower Guinean versus Lower versus Group East Gap Guinean Congo Forest 3.2 | Timing of diversifications Aves The BEAST analyses for both passerines and mammals recovered Low dispersers strongly supported topologies and divergence times congruent with N species 15 12 18 estimates previously established for several genera (see Appendix Fig- Average 6.9% 6.4% 4.3% ures S1–S4). We recovered low posterior probabilities (PP ˂99) at Range 1.3%–14.6% 1.9%–12.9% 0.1%–14.3% several nodes representing older (>5.0 Ma) intergeneric lineages in High dispersers which numerous species are known to be missing, and in mammals N species 22 12 14 for some very young nodes (<0.1 Ma). For passerines, divergence Average 4.2% 3.8% 1.4% dates were taken from a combined 150 intrageneric nodes across Range 0.1%–11.4% 0.3%–11.4% 0.0%–5.7% the ND2 and CYTB topologies, and of these 142 were ≤5.0 Ma Mammalia (Figure 3), while within mammals, 92 of 98 intrageneric nodes were Low dispersers ≤5.0 Ma. Divergences across time slices are low from 5.0–1.0 Ma, N species 6 6 20 after which divergences increase to 19 avian and 19 mammalian Average 7.7% 5.8% 5.9% nodes between 1 and 0.5 Ma and greatly increase again to 59 avian Range 2.4%–15.6% 2.2%–10.2% 0.7%–19.4% and 31 mammalian nodes from 500 ka to present (Figure 3). High dispersers N species 3 1 4 4 | DISCUSSION Average 2.5% 2.2% 1.0% Range 2.1%–4.5% – 0.5%–1.9% 4.1 | Structural patterns and tempo

Since the 1970s, biogeographers have hypothesized the existence of p‐distance between eight understorey and six dispersive species, Plio‐Pleistocene lowland forest refugia during periods of high global 3.7% and 3.1%, respectively. However, for dispersive species this aridity (Figure 1b) and discussed their potential importance for shap- average is inflated by one species (Muscicapa cassini: 11.4%) and ing diversity in Africa (Diamond & Hamilton, 1980; Mayr & O'Hara, when it is removed the average falls to 1.4% (Table 2). Additionally, 1986; Prigogine, 1988). While, Mayr and O'Hara (1986) implicated four refugial comparisons in the mammal dataset recovered a sub- Pleistocene refugia as the primary avian speciation driver within stantially higher average p‐distance for low dispersers (an average African lowland forests, they specifically limited their analysis to

FIGURE 2 Box plots displaying the intraspecific p‐distances found in each group by dispersal type with individual comparisons overlaid as jittered points for comparison across (a) forest blocks and (b) refugial areas [Colour figure can be viewed at wileyonlinelibrary.com] 386 | HUNTLEY ET AL.

TABLE 2 Mitochondrial uncorrected pairwise distances between regions within the Guineo‐Congolian forest blocks

SLL versus Nig/Cam Nig/Cam EG/G EG/G EG versus DRC/U Group Ghana versus CAR versus EG/G versus CAR versus DRC/U Gabon versus CAR Aves Low dispersers N species 11 13 6 10 9 6 8 Average 4.2% 4.8% 6.3% 2.6% 6.0% 1.9% 3.7% Range 0.1%–9.3% 0.1%–13.0% 2.1%–12.2% 0.2%–7.2% 1.5%–14.7% 0.0%–6.8% 1.5%–10.4% High dispersers N species 3 5 8 4 3 4 6 Average 0.1% 0.2% 1.1% 0.6% 2.7% 0.6% 3.1% Range 0.1%–4.2% 0.0%–0.3% 0.1%–3.6%% 0.3%–0.7% 0.8%–6.5% 0.4%–1.3% 0.4%–11.4% Mammalia Low dispersers N species 2 11 13 11 6 – 5 Average 5.6% 2.6% 3.7% 3.7% 5.5% – 8.2% Range 2.1%–9.0% 0.1%–8.6% 0.7%–9.9% 0.4%–19.4% 2.5%–9.2% – 2.9%–19.3% High dispersers N species – 12 33 – 3 Average – 0.8% 0.8% 1.0% 1.1% – 1.1% Range –– 0.6%–0.9% 0.4%–1.8% 0.7%–1.6% – 0.9%–1.5%

Note. SLL: Sierra Leone/Liberia; Nig/Cam: Nigeria/Cameroon; CAR: Central African Republic; EG/G: Equatorial Guinea/Gabon; EG: Equatorial Guinea; DRC/U: Democratic Republic of the Congo/Uganda.

species with geographically diagnosable phenotypic differentiation of genetic divergence clearly suggest the possibility of cryptic spe- and suggested that species lacking plumage variation were biogeo- cies (e.g., Huntley et al., 2017; Voelker et al. 2017). graphically uninformative. Our assessment of genetic divergence It is clear from our analyses that the scale at which forest areas levels for lowland forest species, some of which lack phenotypic are delimited is important. Indeed, the spatial diversity patterns we variation, contradict Mayr and O'Hara's assertions, and highlights the recovered by utilizing refugial areas (seven) rather than major forest importance of genotypic information for understanding diversity blocks (three) for bird and mammal distributions indicate that Plio‐ within phenotypically uniform species. By extension, sufficient levels Pleistocene forest fragmentation within major blocks played a significant role in the creation of phylogeographical structure in many species. For instance, we observed >3.0% sequence divergence between eight (of 13) populations of avian and mammalian taxa distributed across Sierra Leone/Liberia and Ghana in the UGF (Table 2). These two regions are continuously connected by lowland forests in Cote d'Ivoire, lack major barriers to gene flow (i.e., rivers or moun- tains) between them, and each is hypothesized to have been a Pleis- tocene refugium (Figure 1b). Indeed, several other sampling locations we include are former refugial centres, and diversification patterns between these centres and other areas supports their role as refugia between which lineages are currently or have diversified in the past (Figure 1b–d). Much of the standing genetic structure in many species is overlooked when only assessing diversity among the three major forest blocks. In addition, the tempo of diversification we recover for avian and mammalian species also supports the importance of Plio‐Pleistocene FIGURE 3 Histogram of intrageneric molecular divergence climate‐based landscape alterations on the creation of avian genetic estimates younger than 5 Ma from sequences in both the ND2 and CYTB alignments (passerine‐only). Each bar represents the number diversity. Of the 150 intrageneric lineage divergences recovered, of divergences occurring in that 0.5‐million‐year bin [Colour figure 113 occurred within the last 3 Ma (Figure 3), a time period during can be viewed at wileyonlinelibrary.com] which Afro‐tropical forests underwent major fragmentation events HUNTLEY ET AL. | 387 related to successive spikes in global aridity (Maley, 1996; deMeno- of bird and mammal taxa support this contention, where species do cal, 1995, 2004). Furthermore, 78 of these divergences are dated not share haplotypes across the gap (Beresford & Cracraft, 1999; from the late Pleistocene to present (1.0–0.0 Ma) (Figure 3), and this Fuchs & Bowie, 2015; Fuchs et al., 2017; Hassanin et al., 2014; is not surprising as the last 800 ka, was subject to increased fluctua- Marks, 2010; Nesi et al., 2013; Schmidt, Foster, Angehr, Durrant, & tions of global aridity associated with glacial cycling, which led to Fleischer, 2008; Voelker et al. 2017). severe bouts of forest fragmentation (see Plana, 2004 for review). However, the extent to which the DG has served as a biogeo- While we have focused on major blocks or refugia, it is possible graphical isolating mechanism for the large regional faunal assem- that divergences may be associated with more than one biogeo- blage has not been comparatively examined via molecular methods, graphical isolating mechanism. Indeed, some regions harbour major as we do here. We found strong evidence for a genetic break in 37 rivers such as the Sanaga (Cameroon), Ogooué (Gabon), and Congo, avian species whose range is fragmented by the DG, including 24 all of which have been recently implicated as barriers for bird and which inhabit the forests directly adjacent to the gap (UGF and mammal taxa. For instance, the Congo River was recently found to LGF) (Table 1). While the number of understorey birds showing evi- be a barrier for four of 10 avian species examined; all four were dence of the DG as a barrier may be expected, it is also evident understorey lineages (Voelker et al., 2013). For mammals, the Sanaga that the DG has impacted 12 of the 22 dispersive species as well or Ogooué Rivers are possible genetic barriers for several taxa (e.g., (≥3.0%; Table 1). Similar patterns are recovered in mammals, where Anthony et al., 2007; Nicolas, Missoup, Colyn, Cruaud, & Denys, six dispersal‐limited species have a higher average divergence esti- 2012; Nicolas et al., 2011) which, like understorey birds, may show mate than the more dispersal capable Chiroptera (Figure 2a and similar avoidance of nonforested habitats. Additionally, recent stud- Table 1). Past studies have found evidence for lineages endemic to ies of reptiles and amphibians have yielded complex results regarding relictual forests within the DG (e.g., Gaubert et al., 2016; Huntley & riverine barriers as diversification drivers in the GCF (e.g., Bell et al., Voelker, 2016; Voelker et al., 2017). However, despite increasing 2017; Jongsma et al., 2018; Leaché & Fujita, 2010). Yet overall, evidence of endemism within the gap, it appears that the DG may focused assessments of Afro‐tropical rivers as drivers of diversity are have played a substantial role in the creation and maintenance of lacking, despite the evidence that rivers may be adding to complex genetic diversification between the UGF and LFG across birds, intraregional patterns of diversification. mammals, and even amphibians (Jongsma et al., 2018), regardless of dispersal ability. 4.2 | Influence of life history on patterns 4.4 | Are Afro‐tropical lowland forests evolutionary Previous studies of the diversification patterns of bird and mammal “cradles” or “museums”? lineages in the GCF have largely focused on single species, or a small number of related taxa. As such, there has been little scope for com- Our results suggest that the Guineo‐Congolian lowland tropical for- parative assessments of life‐history variations, such as dispersal abil- ests of Africa are simultaneously acting as an “evolutionary cradle” ity. Our results, based on co‐occurring avian and mammalian taxa and an “evolutionary museum” for both avian and mammalian spe- with different dispersal abilities, revealed an extraordinary complex- cies. In support of an “evolutionary cradle” the large number of sub- ity of genetic diversification patterns across the GCF. We find that stantial divergences between multiple regions of the GCF suggests dispersal ability greatly affects both bird and mammal species’ that significant vertebrate diversity has been created in situ over the response to historical vicariance scenarios. In birds, intraforest block past 3–5 Ma. This strongly implies that lowland forests have served partitions show that understorey species display overall deeper as diversification centres, particularly for understorey taxa, likely due levels of genetic lineage divergences than more dispersive species, to repeated and widespread landscape alterations in the Plio‐Pleisto- with several dispersive taxa displaying relatively low levels of diversi- cene. fication across broad areas (Figure 2 and Table 2). Mammals con- In support of an “evolutionary museum” our results show that verge on a similar pattern with rodents and shrews (low dispersal) despite repeated habitat fragmentation, some species show little displaying deeper divergences than more dispersive bats (Figure 2 genetic diversification across their range. Since the majority of these and Table 2). These patterns are consistent with evidence that species are dispersive taxa, it appears likely that higher levels of understorey species are generally less likely to cross open areas (i.e., vagility allow them to “escape” the effects of fragmented landscapes, rivers or open habitat) and are therefore more susceptible to forest thereby maintaining high levels of gene flow through time. The con- fragmentation events than are dispersive species (Kahindo, Bates, & clusion that the GCF are both diversification centres and museums, Bowie, 2017; Lees & Peres, 2009; Voelker et al., 2013). dependent upon species behaviour, is consistent with studies from other tropical regions (Jablonski et al., 2006; McKenna & Farrell, 2006; Moreau & Bell, 2013). 4.3 | Dahomey Gap It is clear that the amount of both avian and mammalian diversity The arid DG has been considered historically important in driving across the GCF has been drastically under‐estimated. While we do biodiversity patterns (Booth, 1958; Endler, 1982; Mayr & O'Hara, not specifically seek to address subspecies validity in the taxa 1986) (Figure 1a). Genetic diversification patterns of a small number addressed here, our data also suggest that we may lack a proper 388 | HUNTLEY ET AL. understanding of the true species limits for many taxa. As such, we Given the substantial divergences found in our analyses, coupled may be operating under a paradigm of misinformed taxonomic classi- with a lack of rigorous phylogenetic focus on the vast majority of fications due to a system established solely using phenotypic varia- lowland forest birds, many of which are widespread and lack dis- tion. For example, the sole genus of Afro‐tropical birds (Stiphrornis) crete plumage variation, it seems exceptionally likely that numerous that has seen multiple, rigorous investigations (i.e., genetics, mor- cryptic species or lineages have yet to be described. Our study also phology, behaviour) was originally described as one widespread spe- indicates that nondispersive taxa sampled at a fine geographic scale cies lacking substantial plumage variation and included in Mayr and may be the best indicator for identifying areas of conservation O'Hara's (1986) list of biogeographically uninformative taxa. Subse- concern. quently, the genus has been shown to contain no fewer than eight Overall, many conservation organizations have proposed schemes species (Beresford & Cracraft, 1999; Schmidt et al., 2008; Voelker centred on scrutinizing irreplaceability (endemism), species richness, et al. 2017). In addition, recent studies of the genera Bleda (Huntley and vulnerability when prioritizing regions of concern around the & Voelker, 2016) and Criniger (Huntley et al., 2017) revealed higher globe (Aukema et al., 2017; Brooks et al., 2006; Olsen et al., 2001). than expected levels of diversification across the GCF than expected, Our results, based on many species, suggest that we may have a especially given their inclusion on Mayr and O'Hara's (1986) list. rather poor understanding of (a) which areas of the Afrotropical for- Despite the focus of our study on avian and mammalian taxa, ests are vital for creating and maintaining biodiversity, (b) species cryptic diversity is not restricted to these groups. Evidence is emerg- limits and richness, and (c) the full extent of diversification patterns ing that reptiles (Bell et al., 2017; Greenbaum, Portillo, Jackson, & across the GCF. Given the lack of attention to, and vague under- Kusamba, 2015; Jongsma et al., 2018) and invertebrates (Light, Ness- standing of, the structural patterns and species limits of vertebrate ner, Gustafsson, Wise, & Voelker, 2016; Takano et al., 2017) may diversity within the GCF, it seems likely that conservation decision‐ contain substantial cryptic diversity. Although we acknowledge the making may be lacking the information necessary for prioritizing known limitations to using pairwise distance averages from mito- areas of the forest harbouring unique lineages and promoting evolu- chondrial genes and that we lack the sampling power to make tionary processes. sweeping conclusions about any one species, the patterns we recovered underscore the urgent need for more extensive future sampling ACKNOWLEDGEMENTS efforts and further exploration of species limits and patterns of diversification across all terrestrial vertebrate groups in Afro‐tropical We thank all of the museums, curators, collection staff, and scien- forests. tists for efforts in the field and laboratory that made sequences in this study available. We thank members of the Voelker Lab at Texas A&M University and Cracraft Lab at the American Museum of Natu- 4.5 | Conservation ral History for conversations related to the study. We thank Kelsey Determining broad speciation patterns and documenting biodiversity Garner for providing valuable feedback on the manuscript. This study across the Afro‐tropical forests have impacts beyond an evolutionary was funded, in part, by the Willie Mae Harris Graduate Fellowship framework. Our understanding of the various drivers leading to provided to J.W.H. at Texas A&M University. This is publication deforestation or habitat degradation is incomplete (Mosnier et al., number 1584 of the Biodiversity Research and Teaching Collections 2014) but recent studies have shown that deforestation in the (BRTC) at Texas A&M University. Afro‐tropics has been increasing, likely due to rising human populations (Aukema, Pricope, & Husak, 2017; Ernst, Verheggen, Mayaux, ORCID Hansen, & Defourny, 2012). Specifically, the UGF, traditionally considered a major biodiversity hotspot (Brooks et al., 2002), is an Jerry W. 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SUPPORTING INFORMATION BIOSKETCH Additional supporting information may be found online in the Jerry W. Huntley is interested in the systematics and biogeogra- Supporting Information section at the end of the article. phy of organisms within the Afro‐tropics. This study represents the final portion of his dissertation work at Texas A&M Univer- ‐ sity on patterns of diversity in avian species across the Guineo How to cite this article: Huntley JW, Keith KD, Castellanos Congolian Forests. AA, Musher LJ, Voelker G. Underestimated and cryptic diversification patterns across Afro‐tropical lowland forests. Author contributions: J.W.H. and G.V. conceived the ideas; J Biogeogr. 2019;46:381–391. https://doi.org/10.1111/ J.W.H., K.D.K., A.A.C., and L.J.M. collected and analysed the jbi.13505 data; J.W.H. led the writing with assistance from G.V.