Fossils indicate marine dispersal in osteoglossid fishes, a classic example of continental vicariance

Abstract

The separation of closely related terrestrial or freshwater species by vast marine barriers represents a biogeographical riddle. Such cases can provide evidence for vicariance, a process whereby ancient geological events like continental rifting divided ancestral geographical ranges. With an evolutionary history extending tens of millions of years, freshwater ecology, and distribution encompassing widely separated southern landmasses, osteoglossid bonytongue fishes are a textbook case of vicariance attributed to Mesozoic fragmentation of the Gondwanan supercontinent. Largely overlooked fossils complicate the clean narrative invoked for extant species by recording occurrences on additional continents and in marine settings. Here, we present a new total-evidence phylogenetic hypothesis for bonytongue fishes combined with quantitative models of range evolution and show that the last common ancestor of extant osteoglossids was likely marine, and that the group colonized freshwater settings at least four times when both extant and extinct lineages are considered. The correspondence between extant osteoglossid relationships and patterns of continental fragmentation therefore represents a striking example of biogeographical pseudocongruence. Contrary to arguments against vicariance hypotheses that rely only on temporal or phylogenetic evidence, these results provide direct palaeontological support for enhanced dispersal ability early in the history of a group with widely separated distributions in the modern day.

Full text

Fossils indicate marine dispersal in
osteoglossid fishes, a classic example of
continental vicariance
Alessio Capobianco1,2,3,4 and Matt Friedman3,4
1GeoBio-Center LMU, and 2Department of Earth and Environmental Sciences, Palaeontology & Geobiology,
Ludwig-Maximilians-Universität München, Munich, Germany
3Department of Earth and Environmental Sciences, and 4Museum of Paleontology, University of Michigan, Ann
Arbor, MI, USA
AC,0000-0002-6096-3875; MF,0000-0002-0114-7384
The separation of closely related terrestrial or freshwater species by vast
marine barriers represents a biogeographical riddle. Such cases can provide
evidence for vicariance, a process whereby ancient geological events
like continental rifting divided ancestral geographical ranges. With an
evolutionary history extending tens of millions of years, freshwater ecology,
and distribution encompassing widely separated southern landmasses,
osteoglossid bonytongue fishes are a textbook case of vicariance attributed
to Mesozoic fragmentation of the Gondwanan supercontinent. Largely
overlooked fossils complicate the clean narrative invoked for extant
species by recording occurrences on additional continents and in marine
settings. Here, we present a new total-evidence phylogenetic hypothesis for
bonytongue fishes combined with quantitative models of range evolution
and show that the last common ancestor of extant osteoglossids was likely
marine, and that the group colonized freshwater settings at least four times
when both extant and extinct lineages are considered. The correspondence
between extant osteoglossid relationships and patterns of continental
fragmentation therefore represents a striking example of biogeographical
pseudocongruence. Contrary to arguments against vicariance hypotheses
that rely only on temporal or phylogenetic evidence, these results provide
direct palaeontological support for enhanced dispersal ability early in the
history of a group with widely separated distributions in the modern day.
1. Introduction
Why closely related terrestrial and freshwater organisms can be found in
landmasses separated by vast stretches of sea is an outstanding question that
traces back to the very beginnings of evolutionary biology as a discipline [1,2].
Proposed models to explain these disjunct geographical distributions fall into
two broad categories: vicariance, whereby ancient geological events such as
continental breakup created marine barriers and divided ancestral geograph-
ical ranges, and long-distance dispersal, whereby organisms dispersed over
those barriers more recently. While vicariance became the dominant frame-
work to interpret inter-continental distributions after the wide acceptance
of plate tectonics [3], the last 20 years have seen a resurgence of long-dis-
tance dispersal as a plausible and even widespread biogeographical proc-
ess [4,5]. However, a long-distance dispersal framework has been criticized
in the past for relying on ad hoc explanations and negative evidence,
and for not proposing testable hypotheses [6–8]. Even though most of
these critiques have been countered thanks to methodological and statisti-
cal advances [5,9], the mechanisms by which terrestrial and freshwater taxa
managed to cross oceanic barriers remain unclear, with positive evidence for
© 2024 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution
License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original
author and source are credited.
Research
Cite this article: Capobianco A, Friedman M.
2024 Fossils indicate marine dispersal in
osteoglossid fishes, a classic example of
continental vicariance. Proc. R. Soc. B 291:
20241293.
https://doi.org/10.1098/rspb.2024.1293
Received: 5 February 2024
Accepted: 2 July 2024
Subject Category:
Palaeobiology
Subject Areas:
palaeontology, taxonomy and systematics,
evolution
Keywords:
biogeography, dispersal, bonytongue fishes,
vicariance, FBD, total-evidence
Author for correspondence:
Matt Friedman
e-mail: mfriedm@umich.edu
Electronic supplementary material is available
online at https://doi.org/10.6084/
m9.figshare.c.7389801.

transoceanic dispersals proving particularly elusive. Further complications emerge when considering the fossil record, as extinct
species can often be found in geographical areas outside the distribution of their living relatives. Some notable cases include
marsupials [10], lungfishes [11] and gars [12], all of which show more complex past geographical distributions. Because of such
patterns, the importance of fossils for biogeographical studies has been appreciated for more than a century [2]. Nevertheless,
inclusion of fossil data in model-based biogeographical analyses of extant taxa remains limited to just a few remarkable
examples in the literature [12–21].
Freshwater fishes in particular provide a model system in historical biogeography owing to how evolving geomorpho-
logical and tectonic features can present either hard barriers or favourable corridors to their dispersal (e.g. [22–24]).
Inclusion of fossils in freshwater fish biogeography is limited by the geographical and temporal patchiness of freshwater
deposits with the potential for exceptional preservation of relatively small, delicate vertebrates. Osteoglossomorphs or
bonytongue fishes (Osteoglossomorpha) are a celebrated example of a freshwater fish clade with an unusually good
fossil record, encompassing every continent except Antarctica and extending to the Late Jurassic–Early Cretaceous (ca
160−100 Ma) [25,26]. Owing to the wide distribution and exclusively freshwater ecology of extant osteoglossomorphs, they
have been often viewed as a textbook example of vicariance, at the level either of the entire clade or of some of their
subclades, including Osteoglossidae [7,27–29]. Osteoglossidae is today represented by four genera living in South America,
Africa, Southeast Asia and Australia. These fishes, commonly called arapaimas and arowanas, include some of the
largest freshwater fishes in the world and are popular staples of public aquariums for their charismatic and ‘prehistoric’
appearance. Remarkably, fossils of osteoglossids are found not only outside their current geographical range but also
outside their present environmental tolerance, with several extinct species known from marine deposits dating to the early
Cenozoic (66−40 Ma) (figure 1) [25,26,31,32]. Thus, marine long-distance dispersal represents a possible explanation for
the modern disjunct distribution of osteoglossid bonytongues [25,26,31,32,34–38], but this hypothesis has never been tested
within a phylogenetic framework under a biogeographical model.
Here, we estimate ancestral geographical ranges and ancestral habitats for bonytongue fishes under a new total-evidence
phylogenetic hypothesis including all extant genera and 32 extinct species of bonytongues. We aim to answer three key
questions about the evolutionary history of bonytongue fishes: (i) what are the phylogenetic relationships of extinct marine
bonytongues; (ii) what are the major patterns of historical biogeography within the clade, and are they consistent with
a vicariance or long-distance dispersal framework; and (iii) are extant freshwater osteoglossids (arapaimas and arowanas)
descended from marine ancestors? By doing so, we provide an unprecedented example of how fossil data can dramatically
revise biogeographical scenarios that would be strongly supported by the examination of extant species only.
2. Methods
(a) Morphological dataset
The morphological matrix used for the total-evidence phylogenetic analysis of this study is a modification of the morphological
dataset of Capobianco et al. [32], with the novel addition of 2 extant and 14 extinct species. The list of newly added taxa,
complete with the list of specimens and literature used to determine the scoring of morphological characters, is available
in the electronic supplementary material. To make the morphological matrix compatible with the molecular dataset for a
total-evidence analysis, the taxonomic resolution of extant operational taxonomic units (OTUs) was changed from genus level
to species level. In the cases where an extant genus was represented by multiple species in the molecular dataset, we assigned
the morphological character scoring for that genus to the species that was examined by the original scorer of those characters
(e.g. [39]) and/or to the species that we could examine through osteological specimens or micro-computed tomography (µCT)
data. Thus, we changed OTUs from the matrix in [32] as follows: Campylomormyrus → C. tamandua; Chitala → C. chitala; Hiodon
→ H. alosoides and H. tergisus; Osteoglossum → O. bicirrhosum; Papyrocranus → P. afer; Petrocephalus → P. simus; Scleropages → S.
formosus, S. leichardti and S. jardinii. Notably, the morphological characters of this matrix are mostly invariant for congeneric
extant species (with the exception of Scleropages; see electronic supplementary material), because they were defined to capture
morphological variation across Osteoglossomorpha with the purpose of resolving relationships between major bonytongue
clades [32,39,40]. The morphological matrix, which ultimately comprised 96 characters for 53 OTUs (33 extinct and 20 extant),
was assembled and edited in Mesquite v. 3.61 [41].
(b) Molecular dataset
The molecular data matrix was assembled by integrating part of the genomic dataset of [38] with semi-automated extraction
of DNA sequences from Genbank (via the NCBI platform) and BOLD (Barcode Of Life Data system), using functions from
the R package regPhylo [42]. A total of 12 DNA markers were selected: 2 protein-coding mitochondrial markers (coI, cytb),
2 non-protein-coding mitochondrial markers (12S rRNA, 16S rRNA) and 8 protein-coding nuclear markers (rag1, rag2, glyt,
ficd, megf8, pdzd8, suox, vcpip1). Details of the assembly of the molecular dataset are available in the electronic supplementary
material. As the phylogeny and biogeography of the hyperdiverse Mormyridae (elephantfishes) are not the main focus of this
study, we subsampled mormyrids to maximize phylogenetic coverage of the clade while reducing computational burden. The
final molecular dataset comprised 14 084 nucleotides for 63 OTUs—including all extant osteoglossomorph genera and 23.4% of
all extant osteoglossomorph species—with 87% matrix completeness at the marker level.
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(c) Total-evidence phylogenetic analysis
We combined the morphological and molecular matrices to generate a total-evidence dataset including 96 OTUs (33 extinct and
63 extant). A partitioning scheme for the molecular portion of the dataset was determined using PartitionFinder 2 [43], with
greedy search algorithm and allowing partitions based on codon position in the 10 protein-coding markers. As a result, the best
partitioning scheme included eight molecular partitions (electronic supplementary material). The morphological portion of the
dataset was treated as a separate additional partition.
An unrooted, non-time-calibrated tree was first estimated in the software MrBayes [44] to provide a starting tree for
the time-calibrated phylogenetic analysis (electronic supplementary material, figure S1). Amia calva was constrained as the
outgroup to all other OTUs, while the other three outgroups (Elops saurus, Dorosoma cepedianum and †Ellimmichthyiformes)
were constrained to be outside of total-group Osteoglossomorpha, which included the remaining 93 OTUs. A GTR + Γ + I
substitution model was applied to each molecular partition, while an Mkv substitution model was applied to the morphological
partition. The Metropolis-coupled Markov chain Monte Carlo (MCMCMC) was set up as 2 runs with 4 chains each, running
for 50 million generations and sampling every 10 000. Parameter summaries and the ‘Allcompat’ summary consensus tree were
calculated using a 50% burn-in fraction.
After the unrooted analysis, we ran a Bayesian time-calibrated phylogenetic analysis in MrBayes under a skyline fossilized
birth–death (SFBD) model [45]. The analysis was run on the PalMuc high-performance computing (HPC) cluster at LMU
Munich. As in the unrooted analysis, a GTR + Γ + I substitution model was applied to each molecular partition, and an Mkv
substitution model was applied to the morphological partition, with all characters unordered. A relaxed clock model with
independent gamma rates (IGR) was applied separately to the mitochondrial, nuclear and morphological portions of the
dataset, to allow for rate variation across branches. The SFBD tree model was set up to allow fossil sampling rate to vary
between four time intervals: pre-Cretaceous (up to 145 Ma), Cretaceous (145−66 Ma), Palaeocene–Eocene (66−33.9 Ma) and
Oligocene–Recent (33.9−0 Ma). We did not allow extinct taxa to be recovered as sampled ancestors, as incorrectly recovered
sampled ancestors (false positives) might heavily bias downstream ancestral state reconstructions like the biogeographical
analyses performed in this study, owing to their zero-length branches. More detailed information about the settings of our
time-calibrated analysis, including choice of clock rate and tree age priors, and internal node constraints, can be found in the
electronic supplementary material. Tip ages of extinct taxa were assigned a prior uniform distribution ranging from minimum
to maximum possible age of the fossil deposit where that taxon has been found. A list of all fossil tip ages with references can be
found in the electronic supplementary material. The MCMCMC was set up as 2 runs with 4 chains each, running for 450 million
generations and sampling every 1000, with 10% burn-in fraction. Convergence of parameters between the two runs was checked
in Tracer [46] by comparing their posterior estimates and by calculating their effective sample sizes, which were >200 for all
parameters. Posterior tree files were resampled as one tree every 10 000 generations before calculating the ‘Allcompat’ summary
Cretaceous Palaeogene Late Cenozoic
Figure 1. Geographical distribution of extinct and extant osteoglossid bonytongues. Fossil occurrences are divided by preservation state (circles: fragmentary and
disarticulated fossils; squares: articulated fossils) and palaeoenvironment (orange fill: freshwater deposits; light blue fill: marine deposits). Fossil occurrences with
thicker borders indicate where the extinct osteoglossids included in the phylogenetic and biogeographical analyses have been found. The red area in the late Cenozoic
map displays the current geographical distribution of extant osteoglossids. Palaeogeographic maps at 0, 50 and 85 Ma were generated in the R package mapast
under the MULLER2016 model [30]. Fossil osteoglossid occurrences from [26,31,32]. Geographical distribution of extant osteoglossids from [33].
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consensus tree (a majority rule tree showing all compatible taxon bipartitions). The phylogenetic position of extinct taxa with
respect to extant ones across the posterior distribution of trees was evaluated using the function ‘create.rogue.plot’ from the R
script RoguePlots [47].
(d) Biogeographical analysis
The biogeographical analysis was set up and run in the R package BioGeoBEARS [48]. Continental land masses were divided
into seven areas encompassing the whole distribution of extant and extinct Osteoglossomorpha and corresponding to major
biogeographical regions for extant freshwater fishes [22]: Nearctic, Neotropical, Ethiopian, Palaearctic, Sinean, Indo-Malayan
(or Oriental) and Australian. For simplicity, we refer to these regions, respectively, as North America, South America, Africa,
Europe, continental Asia, Indo-Malaya and Australia in the main text and figures. Additionally, we considered the marine realm
as an additional geographical area (bringing the total to eight areas), and extinct taxa found in marine deposits were scored as
occurring exclusively in the marine area.
We also tested an alternative scoring scheme where extinct taxa found in marine deposits were scored as belonging to the
continental biogeographical regions where their fossils have been found (electronic supplementary material). This alternative
scoring scheme, while providing more granular information about the geographical distribution of marine bonytongues, has
the disadvantage of confounding marine and freshwater biogeographical regions (e.g. a marine taxon found in North America
could come from the eastern Pacific or the western Atlantic, two very distinct regions with different biogeographical affinities).
Thus, we will primarily refer to results obtained under the first scoring scheme.
The maximum number of areas that could be occupied by a single lineage at any one point was fixed to 3, to reduce the
number of allowed geographical states and reduce computational time. We further restricted the state space of the analysis
by removing all geographical states corresponding to the marine realm plus two continental regions, but we kept states
corresponding to the marine realm plus one continental region to potentially allow for a euryhaline (freshwater + marine)
condition.
We applied the standard biogeographical models implemented in BioGeoBEARS on the ‘AllCompat’ summary consensus
tree obtained by the total-evidence phylogenetic analysis. These models include DEC (Dispersal–Extinction–Cladogenesis [49]),
DIVALIKE (a likelihood interpretation of the parsimony DIVA, DIspersal Vicariance Analysis model [50]) and BAYAREALIKE
(a simplified likelihood interpretation of the Bayesian model implemented in the software ‘BayArea’ [51]). Additionally, we ran
variants of these three models that include a jump dispersal parameter, j, which allows for founder-event jump dispersal during
cladogenesis (see [52] for a critique of the DEC + model, and [53] for a partial response to that critique). Standard tools for
statistical model comparison [54]—including likelihood ratio test for pairs of nested models and Akaike information criterion
for small sample sizes (AICc)—were used to evaluate model support.
To test how phylogenetic uncertainty impacts the results of the biogeographical analysis, we applied the best-fitting
biogeographic model to 200 phylogenies sampled from the Bayesian posterior distribution. The results from these 200 anal-
yses were summarized by recording marginal ancestral area reconstructions for eight clades: total-group Osteoglossomorpha
(root node), crown Osteoglossomorpha (Hiodon alosoides + Osteoglossum bicirrhosum node), crown Osteoglossiformes (Pantodon
buccholzi + Osteoglossum bicirrhosum node), crown Osteoglossidae (Osteoglossum bicirrhosum + Arapaima gigas node), crown
Osteoglossinae (Osteoglossum bicirrhosum + Scleropages formosus node), crown Arapaiminae (Arapaima gigas + Heterotis niloticus
node), crown Notopteroidei (Notopterus notopterus + Mormyrus ovis node) and crown Notopteridae (Notopterus notopterus +
Papyrocranus afer node). For these clades, we calculated average marginal probabilities for each possible state, corresponding to
empirical Bayesian posterior probabilities.
To explore how the inclusion of fossil data impacts biogeographical inference, we ran the standard BioGeoBEARS models
listed above on the Bayesian consensus tree pruned of all extinct taxa. We compared marginal ancestral states found in this
extant-only analysis with marginal ancestral states recovered from the previous integration of 200 phylogenies with extinct taxa
from the posterior distribution.
To examine dispersal directionality between the eight biogeographical regions, we performed biogeographical stochastic
mapping (BSM) [55] as implemented in BioGeoBEARS. We simulated 100 BSMs under the best-fitting parameters with the DEC
+ j model for each of the 200 phylogenies previously sampled from the Bayesian posterior distribution. The average number of
dispersal events from and to each biogeographical region, comprehensive of both anagenetic and cladogenetic (jump) dispersal,
were tabulated for each of the 200 posterior phylogenies and then averaged across phylogenetic uncertainty by calculating their
mean.
(e) Ancestral habitat estimation
As a complementary approach to reconstruct transitions between freshwater regions and the marine realm, we applied
ancestral state estimation (ASE) on a binary ecological character (freshwater versus marine) in the R package corHMM [56].
Extinct taxa were assigned to the freshwater or marine state depending on the palaeoenvironmental reconstruction of the
fossil deposits they have been found in (electronic supplementary material). We estimated marginal ancestral states under an
all-rates-different (ARD) model on the Bayesian consensus tree, with root state probabilities based on the estimated transition
rates (root.p=“yang” flag in the corHMM function). To estimate the number of transition events from freshwater to marine
environments and vice versa, we used the makeSimmap function to generate 10 000 stochastic character mappings on the
Bayesian consensus tree using the maximum likelihood transition rate matrix previously calculated under the ARD model.
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In order to account for phylogenetic uncertainty when estimating freshwater–marine transitions, stochastic character
mapping was also performed on a random sample of 1000 phylogenies from the Bayesian posterior distribution in the R
package phytools [57]. Ten stochastic character mappings were generated for each sampled phylogeny under the ARD model
with estimated root state probabilities. The simulated numbers of transition events from freshwater to marine environments and
vice versa were summarized by plotting histograms and by calculating mean and relevant quantiles.
3. Results
(a) Phylogenetic relationships
Most major phylogenetic relationships recovered in the Bayesian total-evidence time-calibrated phylogenetic analysis (figure
2) are compatible with previous morphological and molecular studies (e.g. [38–40,58–61]; see [25] for a review of osteoglosso-
morph systematics). These include mooneyes (Hiodontidae) as living sister group to all other extant bonytongues (Osteoglossi-
formes); elephantfishes (Mormyridae) and the aba (Gymnarchidae) as closely related to Old World knifefishes (Notopteridae);
and arapaimas and relatives (Arapaiminae) being closely related to arowanas (Osteoglossinae) and forming the clade Osteoglos-
sidae. The African butterflyfish Pantodon was recovered as living sister group to all other extant Osteoglossiformes, a position
that is not supported by morphological characters alone [32,39,40] but which is often found in molecular phylogenetic analyses
(e.g., [38,61]). Intergeneric relationships within the species-rich Mormyridae match those recovered by Peterson et al. [38].
The posterior probabilities of several nodes forming the ‘backbone’ of the osteoglossomorph
tree are extremely low owing to the uncertain position of several extinct taxa (figure 2). However, even when posterior
probabilities of nodes including extinct taxa are very low, those taxa might consistently resolve in few distinct positions
compared with extant taxa [47]. Hence, exploring the position of extinct taxa with respect to extant ones across the posterior
distribution of phylogenies can be more informative than just examining node supports on a consensus tree (electronic
supplementary material, figure S2). Relationships of non-osteoglossid extinct taxa broadly match previous hypotheses, and
are discussed in further detail in the electronic supplementary material.
All marine taxa included in the analysis (†Brychaetus, †Furichthys, †Heterosteoglossum, †Macroprosopon, †Magnigena, †Thrissop‐
terus, †Xosteoglossid and the undescribed Habib Rahi taxon) are recovered as either crown or stem members of Osteoglossi-
dae. Some of them are often grouped together with extinct freshwater taxa from various continents (†Phareodus, †Phareoides,
†Taverneichthys and †Cretophareodus), making up the clade †Phareodontinae (sensu [32]). The position of †Phareodontinae within
Osteoglossidae is not well resolved, although a stem osteoglossid position is more favoured than other placements. The marine
taxa †Heterosteoglossum and †Thrissopterus are most often recovered as stem members of Arapaiminae. †Sinoglossus from the
late Eocene–Oligocene (ca 38–23 Ma) of China is either reconstructed as sister to the African Heterotis or as sister to the South
American Arapaima. The Eocene Chinese species of Scleropages (†S. sinensis and †S. sanshuiensis) resolve almost always as stem
Osteoglossinae, suggesting they might represent members of an extinct genus distinct from Scleropages.
(b) Evolutionary timescale
Our Bayesian time-calibrated phylogenetic analysis provides the most comprehensive assessment of the evolutionary timescale
of bonytongue fishes to date. Osteoglossomorph origin is estimated to occur between the Late Triassic and the Early Jurassic
(95% highest posterior density (HPD) = 235.3–175.3 Ma). This is older than previous fossil-based estimates [26], but slightly
younger than estimates based only on molecular data [38,59,62]. Crown Osteoglossiformes appear to have originated in the
Jurassic (95% HPD = 196.8–145.4 Ma), while the divergence between the two largest bonytongue clades (Osteoglossidae on
one side, Mormyroidei and Notopteridae on the other) occurred between the Middle Jurassic and the very beginning of
the Early Cretaceous (95% HPD = 173.1–131.4 Ma). Old World knifefishes (Notopteridae) diverged from elephantfishes and
relatives (Mormyroidei) in the Early Cretaceous (95% HPD = 137.5–107.3 Ma). The divergence between extant African and Asian
knifefishes likely happened in the Late Cretaceous (95% HPD = 104.3–60.6 Ma), significantly postdating the fragmentation of
East and West Gondwana [37]. The hyper-diverse elephantfishes started diversifying between the Palaeocene and the early
middle Eocene (95% HPD = 64.7–40.9 Ma), with most divergences between extant genera occurring in the Oligocene and
Miocene.
The origin of osteoglossid bonytongues is estimated to occur between the Early Cretaceous and the early Late Cretaceous
(95% HPD = 137.7–89.7 Ma). The divergence between Arapaiminae and Osteoglossinae (crown Osteoglossidae) likely happened
in the Late Cretaceous before the Maastrichtian (95% HPD = 108.9–72.5 Ma). The split between the South American Arapaima
and the African Heterotis likely occurred between the Maastrichtian and the middle Eocene (95% HPD = 70.4–37.5 Ma), while
the split between the Southeast Asian Scleropages formosus and the South American Osteoglossum is estimated to occur in the
Palaeocene–Eocene interval (95% HPD = 64.5–31.3 Ma). These divergences between osteoglossid genera inhabiting disjunct
continents postdate the fragmentation of Gondwanan landmasses, except for the separation between South America, Antarctica
and Australia, which likely occurred during the Palaeocene–Eocene interval [63].
(c) Historical biogeography and freshwater–marine transitions
In a biogeographical analysis excluding fossils, we find a pattern broadly consistent with a continental vicariance scenario that
matches previous hypotheses for the biogeographical history of bonytongues [7,27–29]. Major biogeographical findings include
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a West Gondwanan plus North American ancestral distribution for crown osteoglossomorphs, and a West Gondwanan ancestral
distribution for crown osteoglossids (figure 3a; electronic supplementary material, figures S3 and S4). Both are associated with
major vicariant splits: the split between Laurasia and Gondwana leads to the North American Hiodon on one side and to the
Gondwanan Osteoglossiformes on the other, while the split between Africa and South America leads to Heterotis on one side
and to South American osteoglossids on the other.
Fossils radically revise this picture of osteoglossomorph biogeography. Our two approaches to considering marine associ-
ations in extinct osteoglossomorphs yield consistent and complementary inferences about the group’s biogeographical and
ecological history. When marine settings are treated as a biogeographical region, we find a marine ancestral distribution for
crown osteoglossids under the DEC + j model (figure 2). This striking result is robust to phylogenetic uncertainty (figure 3a).
The ancestral distributions of both crown Osteoglossinae and crown Arapaiminae are not reconstructed as marine and are
instead uncertain between the freshwater geographical areas in which their members are found (Indo-Malaya, Australia and
South America for crown Osteoglossinae; Africa, continental Asia and South America for crown Arapaiminae). However, this
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Figure 2. Time-calibrated phylogeny of Osteoglossomorpha. The phylogeny plotted here is the ‘AllCompat’ summary consensus tree from the Bayesian total-evidence
analysis. Tips are coloured according to geographical distribution. Taxa found in marine settings are highlighted in bold. Coloured triangles at internal nodes represent
the most likely ancestral geographical area under the DEC+j model when it is at least 3.2 times more likely than the second most likely geographical area, indicating
substantial strength of evidence under a Bayes factor framework. Coloured triangles at internal nodes for which all descendant tips and the immediately ancestral node
inhabit the same area were masked to avoid figure cluttering. Circles at internal nodes indicate node support as Bayesian posterior probabilities of clades when equal
to or larger than 0.50. White bars represent 95% highest posterior densities (HPDs) of node ages. Boxes encompass terminals belonging to total group (crown group +
stem group) of named clades.
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might represent a conservative result owing to the likely under-parameterized nature of the biogeographical models used here
(see §4). Other key biogeographical findings include a Laurasian (Asia + North America) origin for crown osteoglossomorphs,
followed by a dispersal from Laurasian landmasses to Africa leading to the origin of Osteoglossiformes. The specific source of
this dispersal (North America or Asia) is sensitive to topological differences in the posterior distribution of phylogenies.
When marine and freshwater settings are treated as a binary ecological character evolving under an ARD Markov model, we
also find strong support for an ancestral marine ecology in crown osteoglossids (figure 4). Rates of transition between marine
and freshwater environments are strongly asymmetric, with the marine-to-freshwater transition rate estimated to be more than
one order of magnitude larger than the freshwater-to-marine rate (freshwater-to-marine rate = 7.47 × 10−4 Myr−1 per lineage;
marine-to-freshwater rate = 1.96 × 10−2 Myr−1 per lineage). This asymmetry is reflected in the number of transitions calcula-
ted across 1000 stochastic character mappings simulated under maximum-likelihood parameter estimates on the Bayesian
consensus tree (figure 4c). Bonytongue fishes invaded marine environments on average 1.9 times (mode = 1, corresponding to
the marine invasion associated with the origin of the osteoglossid lineage), but they re-entered freshwater environments on
average 6.3 times (mode = 5). Comparable results are found when considering phylogenetic uncertainty by simulating stochastic
character mappings across a sample of the Bayesian posterior distribution of trees (electronic supplementary material, figure
S5).
4. Discussion
(a) Biogeographical history of Osteoglossomorpha
A comprehensive picture of the biogeographical history of Osteoglossomorpha can be reconstructed by integrating the
divergence-time estimates and ancestral eco-geographical reconstructions obtained in this study with Earth’s geo-palaeontologi-
cal history. The ancestral osteoglossomorph likely lived in freshwater environments in the Laurasian supercontinent between
the Late Triassic and Early Jurassic. Several early-diverging lineages of osteoglossomorphs are found in bothAsian and North
American fossil deposits, hinting at multiple dispersals between these continents during the Mesozoic. Faunal exchanges
between Asia and North America in the Jurassic and Cretaceous are strongly supported for multiple groups of continental
organisms, including dinosaurs, mammals, and several other freshwater fish taxa [26,64]. Crown Osteoglossiformes are here
inferred to have an African origin in the Jurassic. Strikingly, while no articulated bonytongue fossil has ever been found in
African Jurassic deposits, fragments of scales (squamules) similar to those of modern osteoglossiforms have been recovered
Crown Osteoglossidae (arapaimas + arowanas) ancestral area
Continental
Asia
South America
+ Africa
South
America
North America
South America
Africa
Continental Asia
Indo-Malaya
Oceania
Marine realm
432 1 0
0.7
1.5
0.7
0.3
0.3
0.6
To/from
North America
1 2 34
Africa
Marine
To/from Oceania
To/from
continental Asia
To/from
Indo-Malaya
0.5
0.4
0.4
0.5
0.4
0.4 To/from Oceania
0.6
0.3
0.3
1.2
0.5
1.0
0.4
0.4
0.5
0.9
0.6
0.3
1.6
0.9
W  W 
I
( )
E
( )
(a)
(c)
(b)
Figure 3. Historical biogeography of bonytongue fishes integrated over phylogenetic uncertainty. Marginal probabilities and numbers of dispersal events shown in this
figure have been integrated over a random sample of 200 phylogenies from the Bayesian posterior distribution. (a) Marginal probabilities of ancestral biogeographical
area under the DEC + j model for crown Osteoglossidae when fossils are included in (left) or excluded from the analysis (right). (b) Average number of dispersal
events into (immigration) and from (emigration) biogeographical areas, calculated under biogeographical stochastic mapping (BSM) and integrated over phylogenetic
uncertainty. (c) Directionality of dispersal between biogeographical areas, calculated under BSM. Arrow thickness is proportional to the average number of dispersal
events, indicated by the number next to the arrow. Arrows from one area to another are not shown when the average number of dispersal events is lower than 0.3.
7
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from the Middle Jurassic Anoual Formation of Morocco [65], matching our age estimate for the origin of Osteoglossiformes and
providing a potential earliest occurrence of this group in the African continent. Moreover, a dispersal from North America to
Africa—potentially via Europe—in the Jurassic would be consistent with the similarities among Late Jurassic terrestrial faunas
of these continents [64,66]. Given the long evolutionary history of osteoglossiforms in Africa, it is perhaps surprising that fossils
of these fishes are almost absent from South American Mesozoic deposits, as South America and Africa were joined into a single
continental landmass until the beginning of the Late Cretaceous, around 100 Ma [67]. The only exception is represented by
†Laeliichthys, a close South American relative of notopterid knifefishes, a clade that today inhabits only Africa and Southeast
Asia. Crown notopterids are reconstructed as ancestrally African like other osteoglossiforms, and they probably dispersed from
Africa to the Indian subcontinent in the Late Cretaceous across a narrow Mozambique Channel [25,26].
The last common ancestor of all osteoglossids (extant and extinct) included in this analysis is inferred to have been marine,
probably descending from an African freshwater lineage of osteoglossiforms (with some uncertainty between African and
North American origin under the alternative biogeographical scoring scheme; see electronic supplementary material). All
three major clades within Osteoglossidae (†Phareodontinae, Arapaiminae and Osteoglossinae) have likely originated from
marine ancestors, and reinvaded freshwater habitats multiple times independently in different continents—including North
America, Asia, Australia and South America. Though starkly in contrast with traditional views of bonytongue biogeography
(e.g. [7]), these results strongly support recent hypotheses of marine dispersal as the biogeographical process responsible for the
disjunct distribution of extant osteoglossid bonytongues [31,37,38]. The four-to-five independent transitions towards freshwater
environments from the marine realm reconstructed from BSMs (figure 3b,c) are very likely to be an underestimate. This is
due to the somewhat simplistic nature of the DEC + j model used for the biogeographical analysis, which assumes that the
per-lineage dispersal rates between regions are all equal, symmetric, and constant through time, and does not penalize direct
dispersal between very distant freshwater regions. For example, the two closely related Eocene freshwater genera †Phareodus
and †Phareoides are, respectively, from the western United States and from Australia, and our analysis reconstructs their
ancestral geographical area to be either North America or Oceania, implying a direct long-distance dispersal from one to the
other without passing through a marine stage. Given that these genera are nested within a marine clade (figure 2), it is not
unreasonable to hypothesize that they might instead represent two independent freshwater invasions from marine ancestors,
not captured by the DEC + j model. A similar reasoning might be applied to the reconstructed ancestral areas of crown
Osteoglossinae and crown Arapaiminae (see §3). Thus, we predict that biogeographical models downweighting direct dispersal
between distant freshwater regions would recover an even more pre-eminent role of marine dispersal and marine-to-freshwater
transitions in the biogeographical history of bonytongue fishes.
Osteoglossidae
(a)
(b)(c)
0.4
0.3
0.2
0.1
0
1510 15
ML transition rates SCM transitions count
Osteoglossidae
# transitions
200 180 160 140 120 100 80 60 40 20 0 Ma
Freshwater
Frequency
Marine
1.96 ×10-2 Myr-1 lin-1
7.47 ×10-4 Myr-1 lin-1
Figure 4. Ancestral habitat estimation for bonytongue fishes. (a) Marginal ancestral states under an all-rates-different (ARD) model on the Bayesian consensus tree
of Osteoglossomorpha. Orange fill indicates freshwater environment, while light blue fill indicates marine environment. Tip identities are the same as in figure 2,
with light grey box encompassing terminals belonging to total-group Osteoglossidae. (b) Maximum-likelihood (ML) estimates of transition rates between freshwater
and marine environments, expressed per million years per lineage (Myr−1 lin−1). (c) Distribution of the inferred number of environmental transitions under stochastic
character mapping (SCM) on the Bayesian consensus tree of Osteoglossomorpha. Freshwater-to-marine transitions are in dark blue and marine-to-freshwater
transitions are in rosy brown.
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(b) Marine origin and dispersal in bonytongue fishes
Speculation on marine dispersal in osteoglossid bonytongues began with recognition of the Eocene †Brychaetus as an osteoglos-
sid [34]. Several more taxa have been subsequently described from marine deposits, all restricted to the early Palaeogene
[35,36,68]. However, the lack of a phylogenetic framework and the uncertain systematics of these marine forms hindered any
formal test of the marine dispersal hypothesis. Until now, the strongest arguments in favour of marine dispersal in osteoglossids
came from estimated divergence times younger than the continental fragmentation of Gondwana [37,38,69], and from the
observation that closely related Palaeogene taxa—sometimes even classified in the same genus—have been found in freshwater
deposits as distant as Wyoming is from Australia [31]. Here we provide direct fossil evidence for marine dispersal in the lineage
leading to extant osteoglossid bonytongues—arowanas and arapaimas. We find that, rather than forming a single clade or
being randomly interspersed across bonytongue phylogeny, marine bonytongues form a ‘cloud’ at the base of Osteoglossidae
from which all three major osteoglossid subclades (Arapaiminae, Osteoglossinae and †Phareodontinae) emerged. Ancestral
state reconstructions strongly support a single freshwater-to-marine transition on the osteoglossid stem, followed by at least
four—but likely more—independent marine-to-freshwater reversals. This result is remarkable for several reasons. First, to
the authors’ knowledge, this is the first time that a group (crown Osteoglossidae) whose extant members and closer extant
relatives are all exclusively freshwater is reconstructed as ancestrally marine. Second, major environmental transitions such as
the freshwater-to-marine one are rare—albeit not unlikely—in teleost fish groups [70,71]. Third and finally, this reconstruction
implies that several distinct lineages of osteoglossids were wiped out from marine environments around or soon after the
middle Eocene, and that these fishes never reinvaded the sea afterwards. More palaeontological data would be needed to test
whether competition with other predatory fishes such as several acanthomorph lineages that diversified around the same time
[72], or severe climate change towards colder temperatures in the middle Eocene–Oligocene interval [73], played some role in
the demise of marine bonytongues.
Because occurrences of bonytongue fossils in marine deposits are mostly restricted to the early Palaeogene (figure 1),
it has been previously suggested that the evolution of marine bonytongues might have happened in the wake of the Creta-
ceous–Palaeogene (K–Pg) mass extinction that wiped out several large predators [74] and triggered the diversification of new
clades, including most modern lineages of marine piscivorous fishes [29,75]. However, our total-evidence analysis recovers
a much older origin of marine bonytongues, with the ancestral osteoglossid—reconstructed as marine—originating deep in
the Cretaceous, at least 90 million years ago (figure 2). Several factors—not mutually exclusive—might explain this 25 Myr
discrepancy between the oldest known marine bonytongue fossils and the youngest inferred age for the ancestral osteoglossid.
It is possible that bonytongues invaded marine environments early in the Cretaceous but remained geographically and/or
ecologically restricted for several million years, until the K–Pg mass extinction. If that was the case, then their absence from the
Cretaceous marine fossil record could be more easily explained by regional (rather than global) patterns of the marine fossil
record. Our results suggest that the bonytongue lineage leading to osteoglossids and to the freshwater-to-marine transition was
likely African (although this is more uncertain under our alternative biogeographical scoring scheme; see electronic supplemen-
tary material), and the marine fossil fish record of the Late Cretaceous of Africa is extremely limited—virtually non-existent
in Sub-Saharan Africa [76]. Another possible explanation for the age discrepancy pertains to the tree model employed for our
total-evidence phylogenetic analysis, which assumes constant diversification rates through time and among lineages. If the
environmental transition at the base of Osteoglossidae triggered an increase in the diversification rate of the group compared
with other bonytongues, then a constant diversification model would likely overestimate the origin age of osteoglossids.
(c) Impact of fossil data on biogeographical inference
Bonytongue fishes represent a striking case study of how the inclusion of fossil data can dramatically alter biogeographical
inference for extant organisms. Such an outcome might happen for two main reasons: (i) extinct taxa might be found in
geographical areas outside the modern biogeographical range of the clade of interest; (ii) extinct taxa might display eco-mor-
phological characteristics that are outside the spectrum of adaptations found in extant representatives of the same clade. In the
case of bonytongue fishes, both reasons apply: extinct bonytongues have been found in Europe and continental Asia, where
they are completely absent today; and bonytongue fossils have been found in marine deposits, demonstrating a much broader
ecological tolerance in the past than today. The fossil record has arguably caught osteoglossid bonytongues in the act, provid-
ing a snapshot of their marine-adapted evolutionary history which would have otherwise remained concealed. Face-value
interpretation of biogeographical patterns derived exclusively from modern distributions can lead to a partial—if not outright
wrong—inference by ignoring a key data source like the fossil record, as showcased by the results of our biogeographical
analysis when excluding extinct taxa (figure 3a; electronic supplementary material, figures S3 and S4).
Despite the obvious relevance of fossil data, some limitations remain to their inclusion in phylogeny-based biogeographical
studies. First, fragmentary fossils are often not included in tip-dating phylogenetic analyses because they cannot be scored for
the vast majority of characters in a morphological matrix. However, fragmentary specimens still provide useful biogeographical
information if they can be at least assigned to a broad taxonomic level (such as family or order). For example, they can record
the first or only occurrence of a clade in a certain geographical area. This information is lost when including only more complete
fossils that are diagnostic at species level into biogeographical analyses. Second, current phylogeny-based biogeographical
models such as DEC do not take into account spatial and temporal biases of the fossil record [77]. The effect of these biases on
biogeographical analyses that include extinct taxa as tips has been explored only in limited cases [78,79] and never for DEC-like
models, but it is likely that they have an impact on reconstructed ancestral areas. As biogeographical studies including fossils
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as sampled tips will become more common in the future, further exploration of fossil record biases in biogeographical inference
will be paramount.
Occurrence-based approaches to biogeographical inference can accommodate both fragmentary fossils and spatio-temporal
biases of the fossil record [80,81], but they lack phylogenetic information. Time-stratified, spatially explicit models of fossil
preservation potential could be developed in a Bayesian phylogenetic framework, similarly to how the geographical structure
of biomes over time and its interaction with lineage dispersal has been recently modelled [82]. At the same time, fossil
occurrence data can be jointly modelled with a phylogenetic tree through the occurrence birth–death process [83], and relevant
biogeographical parameters such as dispersal rates might be estimated under this framework. While a comprehensive model-
ling of spatio-temporal fossilization dynamics for phylogeny-based biogeographical inference will pose several technical and
computational challenges, it represents a promising research avenue to properly use an invaluable data source that cannot be
substituted by neontological data, as demonstrated by the case of bonytongue fishes.
Ethics. This work did not require ethical approval from a human subject or animal welfare committee.
Data accessibility. Morphological and molecular character matrices, MrBayes scripts, MCMCMC log and tree files, tree files of the consensus tree
and the 200 sampled trees from the posterior, BioGeoBEARS and other R package scripts and BioGeoBEARS output files are available in the
Dryad repository [84].
Supplementary material is available online [85].
Declaration of AI use. We have not used AI-assisted technologies in creating this article.
Authors’ contributions. A.C.: conceptualization, data curation, formal analysis, funding acquisition, investigation, methodology, visualization, writing
—original draft, writing—review and editing; M.F.: conceptualization, funding acquisition, investigation, methodology, project administration,
resources, supervision, writing—original draft, writing—review and editing.
Both authors gave final approval for publication and agreed to be held accountable for the work performed herein.
Conflict of interest declaration. We declare we have no competing interests.
Funding. This work was supported by funding from the Department of Earth and Environmental Sciences of the University of Michigan (Scott
Turner Student Research Grant Award 2017, to A.C.), by the Rackham Graduate School of the University of Michigan (Rackham Predoctoral
Fellowship Award 2020-2021, to A.C.), by the Society of Systematic Biologists (2017 SSB Graduate Student Research Award, to A.C.), and by the
Palaeontological Association (Palaeontological Association Career Development Grant PA-CD202102, to A.C.). This work was also supported
by the European Union (ERC, MacDrive, GA 101043187). Views and opinions expressed are however those of the authors only and do not
necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the
granting authority can be held responsible for them. This material is based upon work supported by the National Science Foundation (Award
DEB-2017822, to M.F.).
Acknowledgements. We thank Sebastian Höhna and Rachel Warnock for helpful discussions on this work. For specimen access, we thank Douglas
Nelson and Randy Singer at the University of Michigan Museum of Zoology, William F. Simpson at the Field Museum of Natural History,
Chicago, Bo Schultz and René L. Sylvestersen at the Fur Museum, Bent E. K. Lindow at the Natural History Museum of Denmark, Emma
Bernard at the Natural History Museum, London, Matt Riley at the Sedgwick Museum of Earth Sciences, Cambridge, Mariagabriella Fornasiero
at the Istituto Geologico dell’Università di Padova, the late Anna Vaccari and Roberta Salmaso at the Museo Civico di Storia Naturale, Verona,
Gaël Clement at the Muséum National d’Histoire Naturelle, Paris and Florias Mees at the Musée Royal de l’Afrique Centrale. We thank René
Neumaier for developing and maintaining the High-Performance Computing (HPC) Infrastructure of the Chair of Paleontology and Geobiology
at LMU Munich. Two reviewers and the associate editor provided constructive feedback on an earlier version of this contribution. We finally
would like to thank the Friedman Lab students and postdocs for helpful discussion and comments on this manuscript.
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