Supplementary Material: Multiple evolutionary origins of Australian soil
burrowing cockroaches driven by climate change in the Neogene
Nathan Loa,1, *, K. Jun Tonga,1, Harley Roseb, Simon Y. W. Hoa, Tiziana Beninatic,
David Lowea, Tadao Matsumotod, and Kiyoto Maekawae*
Supplementary Materials and Methods
PCR
Partial regions of mitochondrial 12S rDNA (~430 bp) and nuclear 18S rDNA (~500
bp) (hereafter termed 12S and 18S, respectively), as well as the full mitochondrial
cytochrome oxidase subunit II gene (COII; 685 bp) and nuclear ITS1, were amplified
and sequenced in the samples shown in Table S1. Sequencing was performed by
Macrogen (Seoul, South Korea) and sequence data were submitted to GenBank.
ITS1 was amplified using the primers ITS1 and 5.8S (Innis 1990), which amplify a
~480 bp fragment. Thermal cycling conditions for the amplification of ITS1 (White et
al. 1990) were: 96 °C for 10 min, followed by 35 cycles of 95 °C for 1 min
(denaturation), 50 °C for 1 min (primer annealing), and 72 °C for 1 min (extension),
before a final stage of 72 °C for 10 min (extension).
Phylogenetic inference
Diploptera punctata, Nauphoeta cinerea, Epilampra sp., Phoetalia pallida, Zetobora
sp., Schultesia lampyridiformis, Trichoblatta pygmaea, Pycnoscelus surinamensis,
and Blaberus giganteus, and the ectobiid Nictybora sp., were used as outgroups.
PartitionFinder v1.1.1 (Lanfear et al. 2012) was used to select the best-fitting model
of nucleotide substitution for each gene, using the Bayesian Information Criterion
(BIC). The BIC has been shown to perform well under a variety of simulation
scenario (Luo et al. 2010). The GTR+I+G model was selected for codon positions 1
and 3 of COII, as well as for 12S and 18S. The HKY+I+G model was selected for
codon position 2 of COII and the HKY+G model was selected for ITS1. For RAxML
analyses, the tree with the best-known likelihood was found using 100 replicate
searches, with node support estimated via bootstrapping with 1000 pseudo-replicates.
The incongruence length-difference test (also known as a partitionhomogeneity test) was carried out using the program PAUP v.4b.10 (Swofford 2000)
to test for phylogenetic congruence between mitochondrial (COII and 12S) and
nuclear markers (ITS1 and 18S). This test determines whether different markers
support the same phylogenetic tree. If two markers have congruent phylogenetic
signals, they can be analysed in combination to produce an improved and more
informative estimate of the tree. We were unable to reject the hypothesis of
phylogenetic congruence (p=0.078; 1000 replicates), so it was appropriate to analyse
the mitochondrial and nuclear markers in combination.
Divergence dating analyses in BEAST were performed using an uncorrelated
lognormal relaxed-clock model (Drummond et al. 2006) using the software BEAST
1.7.0 (Drummond & Rambaut 2007), with separate clock models for nuclear and
mitochondrial markers to account for differing patterns of among-lineage rate
heterogeneity (Duchêne & Ho 2014). A Yule speciation process was used for the tree
prior and posterior distributions of parameters, including the tree, were estimated
using MCMC sampling. We performed two replicate MCMC runs, with the tree and
parameter values sampled every 1000 steps over a total of 50 million generations. In
the absence of fossils assigned to either subfamily, we calibrated the clock using four
fossils from representatives of other extant subfamilies in Blaberidae (the family to
which Panesthiinae and Geoscapheinae belong). We used exponential priors to reflect
uncertainty in these calibrations (Ho and Phillips 2009), with age constraints on the
following clades: Diploptera + Nauphoeta (mean = 13.0, offset = 52 Ma); Epilampra
+Panesthiinae/Geoscapheinae (mean 15 and offset 44.5 Ma; based on a Epilamprinae
fossil (Pongracz 1935)); Phoetalia + Zetobora + Schultesia (mean 17.5 and offset
35.6 Ma; based on a Zetoborinae fossil (Scudder 1890)); and Pycnoscelus +
Diploptera + Nauphoeta (mean 13 and offset 52 Ma; based on a Pycnoscelinae fossil
(Cockerell 1920)). The soft maximum bounds reflect a probability of 97.5% that the
clade is not older than 93.5 Ma, based on the oldest known fossil from Ectobiidae
(Vrsansky 2008)), a cockroach family that is paraphyletic with respect to Blaberidae
(Djernaes et al 2015). The ectobiid taxon Nyctibora was included as an outgroup and
monophyly was enforced for Blaberidae, following previous evidence (Inward et al
2007).
To examine the sensitivity of the date estimates to our choices of models and
priors, we performed additional analyses using a strict clock model, a birth-death tree
prior, and an increase in the soft maximum bound for each fossil to 150 Ma. We
evaluated support for the clock models and tree priors using Bayes factors, with
marginal likelihoods calculated using the harmonic-mean estimator in Tracer
(Rambaut et al 2014; Suchard et al 2001).
The monophyly of the subfamily Geoscapheinae was tested by comparing
unconstrained trees with an artificially constrained tree topology in which the
monophyly of Geoscapheinae was enforced. We performed these comparisons using
both Bayesian and likelihood approaches.
To evaluate the sensitivity of our results to the choice of models and priors, we
performed additional analyses using a strict clock and the birth-death tree prior. We
compared support for these using Bayes factors, with marginal likelihoods calculated
using the harmonic-mean estimator (Suchard et al. 2001).
Topology tests and diversification rates
Under the Bayesian framework in BEAST (see Materials and Methods (b) in main
text), the marginal likelihoods of the two trees were compared to determine the Bayes
factor (Suchard et al. 2001). The likelihood-based topology test involved a number of
steps. First, PAUP was used to calculate log-likelihood values for both the
constrained and unconstrained trees. Differences between the values of the competing
hypotheses were then examined in CONSEL (Shimodaira & Hasegawa 2001), which
employs the Kishino-Hasegawa test, the Shimodaira-Hasegawa test, the weighted
Shimodaira-Hasegawa and the approximately-unbiased test (Shimodaira 2002).
We used the BiSSE method (Maddison et al 2007) to compare the speciation
rates in lineages leading to wood- and soil-burrowing taxa. This method implements a
six-parameter model in which each parameter can be estimated or constrained. Of the
six parameters, the two representing the speciation rates for the two burrowing habits
were estimated using likelihood; the corresponding extinction rates were set to 0,
whilst the two rates of character changes were assumed to be equal to one another.
Supplementary Results and Discussion
Changing the soft maximum bound for calibrations from 93.5 Ma to 150 Ma led to an
approximate doubling of the mean estimates of divergence times shown in figure 2
(see figure S6). For example, the inferred ages for clade B and clade C of 44.1 Ma
(95% CI 32.8–54.6 Ma) and 25.4 Ma (95% CI 17.3–33-3 Ma), respectively (figure
S6), are less compatible with the colonization of Australia by these lineages following
the collision of the Asian and Australian tectonic plates ~20 Ma. The estimated dates
are also incongruent with expected divergence times based on the Tokara Tectonic
Strait and the formation of the Lord Howe Island group (see main text).
Clade A exclusively comprises wood feeders from both Asia and Australia.
The Australian taxa within this clade form a monophyletic group, labelled as clade C.
Clade B contains exclusively Australian taxa, including both wood feeders and soil
burrowers (posterior probability 1.0; 100% ML bootstrap support). The wood-feeding
taxa within this clade do not form a monophyletic group. Instead, some wood feeders
are more closely related to soil burrowers than to other wood feeders, and vice versa.
For instance, clade D contains a group of soil burrowers, including M. rhinoceros, and
a number of divergent lineages of the wood feeder Panesthia sloanei from northern
Queensland. Clade E contains two clades, F and G, which contain wood-feeding (P.
australis and P. obtusa) and soil-burrowing taxa (G. dilatatus and G. robustus),
respectively, though support for a sister relationship between these two clades was not
strong. Clades H, I, and J each contain strongly supported clades with both woodfeeding and soil-burrowing taxa. For example, in clade I the wood feeder P. tryoni
tryoni is the sister lineage to a group of soil burrowers and wood feeders, and the
wood feeder Panesthia tryoni tegminifera forms a sister group to the soil burrower
Parapanesthia gigantea.
There was a general trend for the taxa in clades containing both wood feeders
and soil burrowers to be present in similar geographical regions. For example,
representatives of clade D, which contains the wood-burrowing species P. sloanei as
well as M. rhinoceros and other soil burrowers, are found in northern and central
Queensland (figure S1). Members of clade H, containing the wood burrower P. tryoni
tryoni and various soil burrowing species, are found in central and south east
Queensland. Members of clade I, containing both P. tryoni tryoni and P. tryoni
tegminifera are found further south around the south-eastern border of Queensland
and northern New South Wales.
The trees estimated using Bayesian and likelihood methods are not concordant
with the current morphology-based generic designations. None of the four genera of
Geoscapheinae (Geoscapheus, Neogeoscapheus, Macropanesthia, and
Parapanesthia) was found to be monophyletic. No support was found for the
monophyly of the wood-feeding genus Panesthia. However, in cases where more than
one individual of a species were examined, morphological species were usually
monophyletic. Some exceptions to this include M. rhinoceros (e.g., the specimens
from Alpha, Queensland, appear to be divergent), P. sloanei, M. lithgowae, Para.
gigantea, P. tryoni, P. cribrata, and P. angustipennis. The absence of monophyly for
each of these species was found in both Bayesian and likelihood analyses.
When we varied the clock model and tree prior, as well as relaxing the soft
maximum age constraint, we inferred tree topologies that were almost identical to that
shown in figure 2. Bayes factors indicated that the uncorrelated lognormal clock
provided a better fit to the data than a strict clock (ln Bayes factor = 248), and that the
Yule tree prior was favoured over the birth-death prior (ln Bayes factor = 3.58). Our
analysis using the birth-death tree prior produced slightly younger (~15%) mean
estimates of divergence times (figure S5) than those shown in figure 2. When we
changed the soft maximum bound for calibrations from 93.5 Ma to 150 Ma, the mean
date estimates (figure S6) were approximately double those shown in figure 2.
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Supplementary Figure Legends
Figure S1. The distribution of Australian Panesthiinae and Geoscapheinae. Clade
names shown on each map (C, D, F, G, H, I, J) correspond to those shown in figure 2
of the main text. Black pins denote wood feeding taxa whilst orange pins represent
soil burrowing taxa. Each pin is labelled with a numerical code that corresponds to
location data found in Table S1.
Figure S2. Bayesian tree estimated from the mitochondrial-nuclear dataset (142
ingroup taxa), equivalent to figure 2 but showing 10 outgroup taxa as well as
individual posterior probabilities.
Figure S3. Maximum-likelihood tree based on analyses in RAxML v1.0.9 of 142
ingroup taxa plus 10 outgroup taxa. Support values from 100 bootstrap replicates are
shown adjacent to nodes. Support values from key nodes are shown in figure 2 of the
main text.
Figure S4. Bayesian tree estimated from the mitochondrial-nuclear dataset (142
ingroup taxa), equivalent to figure 2 but showing locations of taxa matching data
presented in Table S1.
Figure S5. Bayesian tree estimated from the mitochondrial-nuclear dataset (142
ingroup taxa) using a birth-death tree prior instead of a Yule tree prior.
Figure S6. Bayesian tree estimated from the mitochondrial-nuclear dataset (142
ingroup taxa plus 10 outgroup taxa) using a relaxed soft-maximum constraint of 150
Ma for each of the fossils described in the text.