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\begin{document}

\title{Excluding spatial sampling bias does not eliminate over-splitting in
DNA-based species delimitation analyses}



\author[1]{Daniel Lukic}%
\author[2]{Jonas Eberle}%
\author[1]{Jana Thormann}%
\author[3]{Carolus Holzschuh}%
\author[1]{Dirk Ahrens}%
\affil[1]{Zoological Research Museum Alexander Koenig}%
\affil[2]{University of Salzburg}%
\affil[3]{Affiliation not available}%


\vspace{-1em}



  
  \date{May 17, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
DNA-barcoding and DNA-based species delimitation are major tools in DNA
taxonomy. Sampling has been a central debate in this context, because
the geographical composition of samples affect the accuracy and
performance of DNA-barcoding. Performance of complex DNA-based species
delimitation is to be tested under simpler conditions in absence of
geographic sampling bias. Here, we present an empirical data set sampled
from a single locality in a Southeast-Asian biodiversity hotspot (Laos:
Phou Pan mountain). We investigate the performance of various species
delimitation approaches on a megadiverse assemblage of herbivore chafer
beetles (Coleoptera: Scarabaeidae) to infer whether species delimitation
suffers in the same way from exaggerate infraspecific variation despite
the lack of geographic genetic variation that led to inconsistencies
between entities from DNA-based and morphology-based species inference
in previous studies. For this purpose, a 658 bp fragment of the
mitochondrial cytochrome c oxidase subunit 1 (cox1) was analysed for a
total of 186 individuals of 56 morphospecies. Tree based and distance
based species delimitation methods were used. All approaches showed a
rather limited match ratio (max. 77\%) with morphospecies. PTP and TCS
prevailingly over-splitted morphospecies, while 3\% clustering and ABGD
also lumped several species into one entity. ABGD revealed the highest
congruence between molecular operational taxonomic units (MOTUs) and
morphospecies. Disagreements between morphospecies and MOTUs were
discussed in the context of historically acquired geographic genetic
differentiation, incomplete lineage sorting, and hybridization. The
study once again highlights how important morphology still is in order
to correctly interpret the results of molecular species delimitation.%
\end{abstract}%



\sloppy


\textbf{Excluding spatial sampling bias does not eliminate
over-splitting in DNA-based species delimitation analyses}

Daniel Lukic\textsuperscript{1}, Jonas Eberle\textsuperscript{2}, Jana
Thormann\textsuperscript{1}, Carolus Holzschuh\textsuperscript{3}, Dirk
Ahrens\textsuperscript{1, 4}

\emph{\textsuperscript{1} Zoologisches Forschungsmuseum Alexander
Koenig, Zentrum fur Taxonomie und Evolutionsforschung, Adenauerallee
160, 53113 Bonn, Germany}\selectlanguage{english}

\selectlanguage{ngerman}\emph{\textsuperscript{2} Paris-Lodron-Universität, Zoologische
Evolutionsbiologie, Hellbrunner Straße 34, 5020 Salzburg, Austria}

\emph{\textsuperscript{3} Spitzeckweg 11, 9500 Villach, Austria}

\emph{\textsuperscript{4} corresponding author:
d.ahrens@leibniz-zfmk.de; ahrens.dirk\_col@gmx.de}

\textbf{Abstract}

DNA-barcoding and DNA-based species delimitation are major tools in DNA
taxonomy. Sampling has been a central debate in this context, because
the geographical composition of samples affect the accuracy and
performance of DNA-barcoding. Performance of complex DNA-based species
delimitation is to be tested under simpler conditions in absence of
geographic sampling bias. Here, we present an empirical data set sampled
from a single locality in a Southeast-Asian biodiversity hotspot (Laos:
Phou Pan mountain). We investigate the performance of various species
delimitation approaches on a megadiverse assemblage of herbivore chafer
beetles (Coleoptera: Scarabaeidae) to infer whether species delimitation
suffers in the same way from exaggerate infraspecific variation despite
the lack of geographic genetic variation that led to inconsistencies
between entities from DNA-based and morphology-based species inference
in previous studies. For this purpose, a 658 bp fragment of the
mitochondrial cytochrome c oxidase subunit 1 (\emph{cox1} ) was analysed
for a total of 186 individuals of 56 morphospecies. Tree based and
distance based species delimitation methods were used. All approaches
showed a rather limited match ratio (max. 77\%) with morphospecies. PTP
and TCS prevailingly over-splitted morphospecies, while 3\% clustering
and ABGD also lumped several species into one entity. ABGD revealed the
highest congruence between molecular operational taxonomic units (MOTUs)
and morphospecies. Disagreements between morphospecies and MOTUs were
discussed in the context of historically acquired geographic genetic
differentiation, incomplete lineage sorting, and hybridization. The
study once again highlights how important morphology still is in order
to correctly interpret the results of molecular species delimitation.

\textbf{Key words}

\emph{Cox1} , barcoding, species delimitation, geographic sampling bias,
Laos.

\section*{Introduction}

{\label{introduction}}

Since DNA barcoding was formally proposed on a large scale ,
\emph{cox1}sequences have been rapidly accumulated from all around the
world (Porter \& Hajibabaei, 2018). Early studies mostly had a narrow
systematic focus and targeted local or regional species assemblages.
With emerging global comprehensiveness from the global iBOL project
(International Barcode of Life), researchers became aware of the
problems that arise with the use of \emph{cox1} (i.e., mitochondrial
DNA) as taxonomic marker (Funk \& Omland 2003; Ballard \& Whitlock,
2004; Dasmahapatra \& Mallet, 2006; Dupuis et al., 2012; Nicholls et
al., 2012; Smith et al., 2012; Dowton et al., 2014; Ross, 2014; Eberle
et al., 2019), but also the effects of geographic scale on accuracy and
performance of barcoding (Lohse, 2009; Bergsten et al., 2012; Gaytán et
al., 2020). Therefore, geographic sampling has been a central debate
(Lim et al., 2012; Reid \& Carstens, 2012; Talavera et al., 2013; Ahrens
et al., 2016), in particular with respect to DNA barcoding, one of the
major tools of DNA taxonomy.

In order to infer in more detail the nature of the genetic markers used
for taxonomy, and also to investigate further the empirical behaviour of
species delimitation approaches currently in use, it would be desirable
to test commonly used methods on a dataset without geographic bias that
still provides a sufficient number of closely related taxa. Here, we
focus on \emph{cox1} , since it continues and will continue to be a
widely used marker for taxonomy in barcoding and metabarcoding studies.

So far, most comprehensive barcoding efforts have been made in
''northern'' and widely temperate countries (e.g., Pentinsaari et al.,
2014, 2019; Gwiazdowski et al., 2015, Hendrich et al., 2015; Rougerie et
al., 2015, Hebert et al., 2016, Rulik et al., 2017; Bouchard et al.,
2017, Steinke et al., 2017; see also: ;
https://www.bolgermany.de/wp/startseite/news-publikationen/publikationen/page/2/).
The number of studies in tropical or subtropical areas is comparatively
low or limited to a narrow focal group (e.g., Elias et al., 2007; Janzen
et al., 2009; Janzen \& Hallwachs, 2011; Astrin et al., 2012; Ahrens et
al., 2016; Cancian de Araujo et al., 2019), and only few authors
assembled data on the global level (e.g., Zhou et al. 2016).

Interestingly, in regional (i.e., national) level libraries, molecular
operational taxonomic units (MOTUs, i.e., BINs; Ratnasingham \& Hebert,
2013) showed perfect matches to known morphospecies in nearly 90\% of
the studied species (e.g., Pentinsaari et al., 2014; Hendrich et al.,
2015). Occasionally, mismatch to described species occurred due to
splitting into clusters of different geographic origin (e.g., Morinière
et al., 2017) or sharing of identical or closely related haplotypes
among different morphospecies (e.g., Hawlitschek et al., 2017). However,
matches generally decreased when geographic sampling of species was
wider, e.g., on a continental scale (Bergsten et al., 2012; Schmid-Egger
et al., 2018, Mutanen et al., 2016), with 12-30\% of the species
resulting paraphyletic. Identification success may decrease with
increasing spatial scale of sampling; up to a drop of 50\% at
continental scales (Bergsten et al., 2012). Sampling on a continental
scale thus considerably increases the complexity of barcoding studies.
Most of the ''northern'' latitude studies, however, are supposed to
contain species with only low infraspecific haplotype diversity (due to
extinctions and recolonization events during and after the Pleistocene;
e.g., Hewitt, 1996, 1999; Schmitt, 2007; Ahrens et al., 2013), and often
assemblages only contain a small number of closely related species.
Thus, these data do not represent suitable test cases of species
delimitation performance when the component of actual geographic genetic
variation is excluded. On the other hand, several studies on tropical
groups or locations also include specimens from one or more other sites
(e.g., Elias et al., 2007; Thormann et al., 2016; Janzen et al., 2009;
Janzen \& Hallwachs, 2011) or large amount of mismatch of MOTUs with
morphospecies was seen as evidence for cryptic diversity (e.g., Janzen
et al., 2009; Janzen \& Hallwachs, 2011).

Here we present a data set that was sampled from one local assemblage in
a Southeast-Asian biodiversity hotspot (Laos: Phou Pan mountain). We
investigate the performance of various species delimitation approaches
on a megadiverse assemblage of herbivore chafer beetles (Coleoptera:
Scarabaeidae: Sericini). Our objective is to infer whether species
delimitation suffers from exaggerate infraspecific variation in the same
way that led to inconsistencies between entities from DNA-based and
morphology-based species inference in previous studies, despite the lack
of geographic genetic variation. We are interested in the degree of deep
coalescence in this local species assemblage and in how species
delimitation approaches handle these data. Excluding geographic genetic
variation we would expect less problems due to deep coalescences and
thus higher rates of taxonomic congruence between morphospecies and
MOTUs. Furthermore we employ clustering algorithms similar to those used
in metabarcoding approaches, to explore the reliability of this critical
step in current metabarcoding analyses pipelines (e.g., Coissac et al.,
2012; Deiner et al., 2017; Macher et al., 2018; Ruppert et al., 2019).

\section*{Material and methods}

{\label{material-and-methods}}

\section*{}

{\label{section}}

\subsection*{Study group, sampling and
identification}

{\label{study-group-sampling-and-identification}}

The study group is the megadiverse tribe Sericini that contains
worldwide nearly 4000 described species in about 200 genera . They are
one of the oldest lineages of phytophagous Scarabaeidae and diversified
with the rise of the angiosperms 108 Ma . Sericini are nearly worldwide
distributed, except in Australia, most oceanic islands, archipelagos,
and circumpolar regions . The polyphagous herbivore adults are fully
winged while larvae feed on roots and underground stems of living plants
. Some species are considered as crop pests . Their highly similar
external morphology makes the species difficult to distinguish, but
highly complex male genitalia are well-differentiated between species
and show only little intraspecific variation .

Sampling was conducted during four weeks in April, 2014 by Carolus
Holzschuh and local collectors in the Phou Pan mountain area (Laos, Hua
Phan province) (Fig. 1) (ca. 20°12'N, 104°01'E), at an elevation between
1300 to 2000 meters. Specimens were collected using light traps, by
hand, or netting during daytime. The Phou Pan mountain is situated in
the Indo-Burmese biodiversity hotspot area (Myers et al., 2000) which is
characterized by extremely high endemism. The habitat with its dense
rainforests offers a large variety of plant species for herbivore
insects to feed on. For this study we used only males (1086 specimens),
since they were assignable to distinct morphospecies, while females are
often not distinguishable among closely related syntopically occurring
species. Samples were pinned after DNA extraction, dry mounted,
labelled, and preserved at the ZFMK (Zoologisches Forschungsmuseum
Alexander König, Bonn, Germany) (see Supplement Table 1).

Specimens were sorted to morphospecies by the complex shape of their
copulation organ, i.e., aedeagus, which has been proven to be the best
suited trait system to robustly infer the species entities for this
group . For this purpose, male genitalia of all specimens were
dissected. Habitus and genitalia of each species were photographed with
a stereomicroscope (ZEISS Stereo Discovery.V20) connected to a ZEISS
Axiocam. Presumably undescribed species that were not yet referable to
an available species name, were numbered consecutively (sp1, sp2, etc.).

\subsection*{DNA sequencing}

{\label{dna-sequencing}}

We sequenced the \emph{cox1} gene (5\selectlanguage{english}'-end) of multiple specimens (3-5)
per morphospecies (in total 190). Lab work followed the standard
protocols of the German Barcode of Life project . DNA was extracted from
mesothoracic leg and attached muscles using the Qiagen DNeasy Blood and
Tissue Kit (Hilden, Germany) or the Qiagen BioSprint96 magnetic bead
extractor (Hilden, Germany).

The PCR reaction was carried out in total reaction mixes of 20 \selectlanguage{greek}μ\selectlanguage{english}l,
including 2 \selectlanguage{greek}μ\selectlanguage{english}l of undiluted DNA template, 0.8 \selectlanguage{greek}μ\selectlanguage{english}l of each primer (10
pmol/\selectlanguage{greek}μ\selectlanguage{english}l), and standard amounts of the reagents provided with the
``Multiplex PCR'' kit from Qiagen (Hilden, Germany) using primers
LCO1490-JJ {[}5'-CHACWAAYCATAAAGATATYGG-3'{]} and HCO2198-JJ
{[}5'-AWACTTCVGGRTGVCC AAARAATCA-3'{]} . Thermal cycling was performed
on Applied Biosystems 2720 thermal cyclers (Life Technologies, Carlsbad,
CA, USA), using a PCR program with two cycle sets, combining a
``touchdown'' and a ``step-up'' routine as follows: hot start Taq
activation: 15 min at 95 \selectlanguage{ngerman}°C; first cycle set (15 repeats): 35 s
denaturation at 94°C, 90 s annealing at 55°C (\selectlanguage{english}-1degC per cycle) and 90 s
elongation at 72degC; second cycle set (25 repeats): 35 s denaturation at
94degC, 90 s annealing at 40degC, and 90 s elongation at 72degC; final
elongation 10 min at 72 degC. Unpurified PCR products were subsequently
sent for bidirectional Sanger sequencing to BGI Tech Solutions
(Hongkong, China).

Raw DNA sequences were assembled (forward and reverse sequence) and
edited in Geneious R7 (version 7.1.3, Biomatters Ltd.) to correct
base-calling errors and to assign ambiguities (when forward and reverse
sequence were not congruent for certain nucleotides). Sequences were
aligned with Muscle (Edgar, 2004) as implemented into Geneious using the
default settings. Primers were trimmed subsequently. All data are
deposited in BOLD (project: SCOIB) and GenBank (accession numbers
MW128167-MW128351) respectively (see Supplement Table 1).

\subsection*{}

{\label{section-1}}

\subsection*{Phylogenetic analysis and species
delimitation}

{\label{phylogenetic-analysis-and-species-delimitation}}

Putative morphospecies were compared with results obtained from the
DNA-based species delimitation methods. We applied Poisson tree process
(PTP) , statistical parsimony network analysis (TCS) , Automatic Barcode
Gap Discovery (ABGD) , distance based clustering, and Barcode of Life
database (BOLD) - Barcode Index Numbers (BINs). These methods were
applied on all sequenced beetles to result in clusters that are
considered molecular taxonomic units (MOTUs) , i.e., DNA-based
species-assignments by the respective method.

A phylogenetic tree was calculated with maximum likelihood from the
final multiple alignment of all DNA sequences using the IQ-TREE web
server (IQ-TREE version 1.6.12; http://iqtree.cibiv.univie.ac.at/) ; the
best substitution model (GTR+F+I+G4) was chosen with ModelFinder
(Kalyaanamoorthy et al., 2017) according to Bayesian Information
criterion (BIC). Branch support was calculated by generating 1000
samples for ultrafast bootstrapping (Hoang et al., 2018). The resulting
tree was midpoint rooted in FigTree v1.4.3 (available from
http://tree.bio.ed.ac.uk/software/figtree/). This tree was the basis for
the PTP analysis. Additionally, split networks were generated using
SplitsTree4 v. 4.16.1 to visualize incompatible and ambiguous signals in
the \emph{cox1} dataset. In these networks the parallel edges, rather
than the single branches, illustrate splits concluded from the data.

We used both versions of the Poisson tree process model (PTP) on the PTP
web server (https://species.h-its.org/; accessed on August 5th 2020):
bPTP, which adds Bayesian support (pp) values to branches that delimit
species in the input tree, and the refined multi-rate mPTP. PTP uses the
shift in the number of substitutions at internal nodes to identify
branching rate transition points which indicate speciation events. We
used default settings for the bPTP analysis (100000 MCMC generations,
thinning: 100, burn-in: 0.1, seed 123).

Statistical network analysis as performed with TCS v. 1.21 separates the
sequence data into clusters of closely related haplotypes connected by
changes that are non-homoplastic with a 95\% probability (Templeton et
al., 1992); if applied to mtDNA the extent of the networks has been
found to be largely congruent with morphospecies

Automatic Barcode Gap Discovery (ABGD) was conducted using the ABGD
webserver (https://bioinfo.mnhn.fr/abi/public/abgd/abgdweb.html;
accessed on August 17th 2020) with default parameters (i.e., using
Jukes-Cantor model (JC69) distances, a relative gap width of 1 and 50
steps, Pmin=0.001, Pmax=0.1, Nb bins for distance distribution= 20).
ABGD partitions individuals for a range of prior intraspecific
distances, instead of using one predefined distance threshold . A robust
result across a range of prior intraspecific distances was chosen as the
best partition scheme. This outcome was also closest to the number of
morphospecies and simultaneously matched the presumptive barcode gap in
the histogram of distances.

Distance based clustering was done with the tclust-function in the
R-package spider (v. 1.5.0; Brown et al., 2012). A threshold of 3\% was
applied to the pairwise distance matrix of all specimens that was
corrected with the Kimura model (K80). The logic of this approach
underlies most metabarcoding protocols (Macher et al., 2018; Piper et
al., 2019; Liu et al., 2020), relying on the presence of a barcoding gap
(Elbrecht et al., 2017), which was chosen as a gap at 3~\% pairwise
distance by the majority of studies (however, see Beentjes et al., 2019
for an 2 \% example). Finally, we compared outcome from species
delimitations to Barcode Index Number (BIN) assignments (Ratnasingham \&
Hebert, 2013) in the BOLD data base (Project - SCOIB: Sericini COI
Barcoding).

To check the performance and accuracy of the DNA-based delimitation
methods compared to the a priori morphospecies hypotheses based on the
genital morphology, the match ratio was calculated: Match ratio =
2*N\textsubscript{match}/(N\textsubscript{MOTU}+N\textsubscript{morph})\textsubscript{.}N\textsubscript{match}
is the number of species with exact matches, when the morphospecies and
DNA-based species delimitation results to include the same specimens.
N\textsubscript{MOTU} is the number of classified groups by the
different delimitation methods and finally N\textsubscript{morph} is the
number of morphospecies. All resulting MOTUs were mapped onto the
phylogenetic tree beside terminal's labels (Fig. 2).

\section*{Results}

{\label{results}}

\subsection*{}

{\label{section-2}}

\subsection*{Morphospecies and sequencing
success}

{\label{morphospecies-and-sequencing-success}}

Fifty-six morphospecies could be determined from the Phu Phan mountain
area. Twenty-seven of the morphospecies (48\%) were supposedly
undescribed species or could not yet be assigned to an existing species
(the fauna of mainland Asia has been fully revised in terms of type
specimen revision (Ahrens, unpublished data), however, several species
from Indonesia are known to widely occur in the Oriental region. Some
species might thus still be assigned to already described species, when
taxonomic revisions are finished for all parts of Asia).

186 specimens were sequenced successfully. The length of the
aligned\emph{cox1} sequences was 658 base pairs (bp). For
\emph{Maladera} sp 16 and \emph{Neoserica phuphanensis} more than five
individuals per morphospecies have been sequenced, since a few specimens
were initially mistakenly assigned to other morphospecies. Of the 56
morphospecies 14 were singletons, i.e., only represented by one specimen
per species.

Due to shared haplotypes in different morphospecies, lowest inter- and
infrasepcific distances were both zero (Table 2), while maximum
infraspecific distances were around 7\%. The infraspecific mean distance
was 1.5\%, and the median even lower (0.8\%). Nine morphospecies (i.e.,
16\% of the taxa) had infraspecific distances larger than 3\%.

\subsection*{Species delimitation}

{\label{species-delimitation}}

All morphospecies included in the analysis resulted monophyletic with
three exceptions (Fig. 2): 1) \emph{Microserica} sp 11
and\emph{Microserica} sp 13 are nested within the clade
of\emph{Microserica varians} ; 2) one of the five specimens
of\emph{Neoserica} sp 29 was within the clade of \emph{Neoserica
martinui} ; and 3) \emph{Maladera} sp 27 is placed within the clade of
the morphologically very similar \emph{Maladera} sp 9.

Three morphospecies shared identical haplotypes (\emph{Maladera} sp 3a,
sp 3b; sp 4; Figs 2, 3). Branch support values (ultrafast bootstrapping)
of morphospecies clades are high with values of 0.8 to 1. DNA-based
species delimitation applying PTP, TCS, and ABGD resulted in different
clusters. Thirty-one morphospecies showed congruent results for all
DNA-based delimitation (Fig. 2). For 46 morphospecies the results of at
least one method matched with the morphospecies assignment. All methods
showed splitting and also lumping of morphospecies.

bPTP and mPTP subdivided the specimens into 70 and 65 MOTUs (Table 1),
with 37 (bPTP) and 38 (mPTP) matches between the morphospecies and
MOTUs. Deviations are caused by erroneously inferred splitting events
(i.e., individuals of one morphospecies were separated into two or more
different MOTUs). Match ratios of both PTP variants were relatively low:
0.59 and 0.63, for bPTP and mPTP, respectively. TCS resulted in 69 MOTUs
and had same number of matches (37) as bPTP. The match ratio (0.60) was
higher than bPTP, but lower than mPTP.

ABGD yielded 51 MOTUs and showed the highest match ratio of all
delimitation methods (0.77). It was the species delimitation method that
showed most lumping of different morphospecies (Fig. 2). Examples for
lumping are: one MOTU for \emph{Maladera exima} plus \emph{M.parexima} ;
\emph{Maladera} sp 9 plus \emph{Ma.} sp 27;\emph{Neoserica} sp 37,
\emph{N. martinui} plus \emph{N.} sp 29; as well as \emph{Microserica
varians} , \emph{Mi.} sp 11 plus \emph{Mi.} sp 13.

Distance based clustering at the 3\% level yielded similar results to
the previous methods. It found 62 MOTUs and matched with 40
morphospecies; the match ratio (0.68) was the second highest, after
ABGD. Barcode Index Number (BIN) assignments revealed 65 MOTUs and
matched as well with 40 morphospecies, however, its match ratio was
lower (0.66) than that of 3\% clustering.

In 21\% of the morphospecies (n= 12) we found relatively deep
coalescence (i.e., distinct infraspecific phylogenetic structure)
(e.g.,\emph{Ma.} sp 4, sp 6, sp 16, \emph{Ma. fuscipes} , \emph{Ma.
futschauana} , \emph{Ma. obscurata} , \emph{Ma. peregoi} , \emph{N.} sp
26,\emph{Mi. panzona} , \emph{Mi. varians} , \emph{G. marginalis} ,
\emph{G. carolusi} ). In all others, infraspecific branches were rather
shallow. Taxa sampled with more than three specimens and that were
represented by a single haplotype did not occur. For all those cases
with deep coalescence, at least one of the DNA-based species
delimitations split the morphospecies, which in turn decreased the match
ratio.

\section*{Discussion}

{\label{discussion}}

In the present paper we investigated the DNA taxonomy of a megadiverse
assemblage of chafer beetles (Sericini) with particular focus on the
performance of commonly used species delimitation methods. The setup of
examining barcodes of a single locality was chosen to investigate
molecular species delimitation performance using data without geographic
bias. While we know that match ratios strongly vary in tropical taxa
(e.g., from 0.14 to 1.00; Ahrens et al., 2016), we theoretically
expected that match ratios would go against one due to the exclusion of
geography-induced variance. Instead, for different standard species
delimitation methods, we could also not report match ratios higher than
0.77. Interestingly, the 3\% threshold clustering that is commonly used
in metabarcoding approaches did not perform worse than more
sophisticated approaches (like PTP, or TCS), however, an accuracy of
only less than 80\% is not really what one could call a reliable
taxonomy assessment.

DNA-based species delimitation approaches may oversplit morphological
entities (Ahrens et al., 2016), while at the same time the opposite may
be also the case (Dalstein et al., 2019), even in the same taxon (as
demonstrated here for the tribe Sericini). This particularly proved to
be true in presence of incomplete lineage sorting and hybridisation and
if geographic bias is not excluded (match ratio \textless{} 0.5;
Dalstein et al., 2019). Extreme over-splitting has been reported for
both mtDNA and nDNA, when sex-biased dispersal occurs (Eberle et al.,
2019) and were the general dispersal is in consequence also very
limited.

Over-splitting in our data is caused by the relatively deep coalescence
in 21\% of the species, which widely corresponds with the missing match
to the morphospecies, which is also reflected by the lack of a classical
barcoding gap (Fig. 4). The impact is high with only 31 out of the 56
morphospecies matching perfectly the boundaries of inferred MOTUs (Fig.
2). The nature of maternal inheritance of mtDNA and its very low
recombination rate is probably the major reason for these patterns of
deep coalescence. Historically acquired genetic differentiation, for
example in previously isolated populations, is maintained in secondarily
mixing populations. The more often such isolated populations occur in
time and space, for example due to climatic fluctuation during the
Pleistocene in geographically highly structured areas such as Southeast
Asia, the more often we encounter such ''paleogeographically induced''
infraspecific variation which leads to the same result as current
geographic variation. This effect consequently impedes species
delimitation methods in the same way, particularly in a single marker
system (e.g., \emph{cox1} ).

Similarly, in our data we could also report cases of incomplete lineage
sorting and/or hybridisation. In three cases, morphospecies were not
monophyletic (\emph{Microserica} sp 11/ \emph{Microserica} sp 13
vs.\emph{Microserica varians} ; \emph{Neoserica} sp 29 vs.
\emph{Neoserica martinui} ; \emph{Maladera} sp 27 vs. \emph{Maladera} sp
9.), while another three morphospecies shared identical haplotypes
(\emph{Maladera}sp 3a, sp 3b; sp 4). In all cases, we may exclude cross
contamination based on the position of the single samples on the
DNA-extraction microtiter-plates. These cases do occur in only rather
closely related species, which might show similar life traits (e.g.,
daytime activity in\emph{Microserica} ), chemical communication, or
mating behaviour (which is however, unknown for all species). In those
instances, lumping of morphospecies in DNA based species delimitation
seems to be more likely; however, also over-splitting was observed (e.g.
\emph{Microserica} ). Despite strong divergence in male genital
morphology, hybridization between closely related species of Sericini
have been reported (e.g., . The rather divergent structure of the
aedeagus of the different species might function with females by
mechanical isolation (lock-and-key hypothesis) that prevents mating
between different species . However, although there have been some
recent work on the morphology of female genitalia, our knowledge on
copulation functionality and mechanics is still not sufficient to tell
if morphological structures of males and female genitalia actually
function as a barrier, if only through tactile recognition by cryptic
female choice .

Again, the present study demonstrates the necessity of an integrative
taxonomy in the sense of Yeates et al. (2011) (see also . We showed that
the use of different clustering- and tree-based delimitation methods
(Carstens et al., 2013) with the same single maker reproduces the same
erroneous signal in slightly different variations. It is thus critical
to corroborate results with data from other sources (e.g., genital or
larval morphology, feeding traits, behaviour, etc.; e.g. Janzen et al.,
2009) to allow for independent testing of species boundaries.

Sericini chafers proved to be a valuable model system, because of robust
morphospecies assignments that were facilitated by the highly dissimilar
and morphologically complex male genitalia that perfectly serve as a
species diagnostic trait .

Overall, the initial hypothesis of impeccable DNA-based species
boundaries in syntopically co-occurring species assemblages clearly had
to be rejected. This was rather unexpected, especially since there was
no additional evidence from other sources that these over-splittings
could relate to cryptic diversity (Janzen et al., 2009, 2017; Janzen \&
Hallwachs, 2011).

Given the highly simplified parameters of DNA based species delimitation
in this one-site species assemblage, it becomes clear how complex
species delimitation with DNA-based methods is. Performance with mean
error rates of more than 30\% are under the expectations for proper use
for applied sciences and conservation management. Even more
sophisticated methods did not perform better than over-simplified
threshold clustering methods as used for example in metabarcoding. Once
more, we highlight the necessity of morphology for the verification
of\emph{de novo} species delimitation results and the constant need of
integrative taxonomic approaches.

\section*{Acknowledgements}

{\label{acknowledgements}}

\section*{}

{\label{section-3}}

We are grateful to Benedict Wipfler for his technical assistance.
Furthermore, we are thankful to Silvia Fabrizi, Sasanka Ranasinghe,
Julian Enss, Ralph Tollrian, Thomas Eltz and Hans-Joachim Krammer for
helpful advice and discussions. This research was support by
institutional funding of the ZFMK.

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\textbf{Data Accessibility:}

- DNA sequences: Genbank accessions (MW128167-MW128351);

- DNA sequences (incl. abi files, locality data): BARCODE OF LIFE DATA
SYSTEM (https://doi.org/10.5883/DS-DS-SCOIBL.\%0d\%0d\%20)

\textbf{Table 1.} Match ratio (after of DNA-based species delimitation
methods on Sericini chafer data based on number of MOTUs and number of
matches between MOTUs and morphospecies (N\textsubscript{morph}=56).\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
& \textbf{bPTP} & \textbf{mPTP} & \textbf{TCS} & \textbf{ABGD} &
\textbf{3\%Clust} & \textbf{BINs}\tabularnewline
\midrule
\endhead
\textbf{N\textsubscript{matches}} & 37 & 38 & 37 & 41 & 40 &
40\tabularnewline
\textbf{N\textsubscript{MOTU}} & 70 & 65 & 68 & 51 & 62 &
65\tabularnewline
\textbf{Match ratio} & 0.59 & 0.63 & 0.60 & 0.77 & 0.68 &
0.66\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 2.} Infra-and interspecific genetic distances of
the\emph{cox1} dataset based on morphospecies assignments, as well as
number of cases beyond an arbitral 3\% threshold distance being often
used for MOTU clustering in Metabarcoding studies.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
& \textbf{interspecific} & \textbf{interspecific} &
\textbf{infraspecific} & \textbf{infraspecific}\tabularnewline
\midrule
\endhead
& \textbf{k2p} & \textbf{ml} & \textbf{k2p} & \textbf{ml}\tabularnewline
\textbf{min} & 0 & 0 & 0 & 0\tabularnewline
\textbf{max} & 0.24 & 0.24 & 0.074 & 0.073\tabularnewline
\textbf{mean} & 0.17 & 0.18 & 0.015 & 0.015\tabularnewline
\textbf{median} & 0.17 & 0.18 & 0.0083 & 0.0083\tabularnewline
\textbf{N\textsubscript{dist\textgreater{}3\%}} & - & - & 9 &
9\tabularnewline
\textbf{N\textsubscript{dist\textless{}3\%}} & 9 & 9 & - &
-\tabularnewline
\bottomrule
\end{longtable}

\textbf{Fig. 1.} Collecting area in Laos (20\selectlanguage{ngerman}°12'N, 104°01'E) (marked
with a black dot).

\textbf{Fig. 2.} Rooted maximum likelihood tree with information about
morphospecies assignments, results of species delimitations (bPTP, mPTP,
TCS, ABGD, BOLD, and BINs) and photographs of the aedeagi (lateral
view). Green boxes indicate agreement between molecular species
delimitation method and morphospecies assignment, while red boxes
indicate disagreement. Ultra fast bootstrap supports \textgreater{}0.5
is shown above nodes. Genus name abbreviations: Chr.
-\emph{Chrysoserica} , G. - \emph{Gastroserica} , Ma. - \emph{Maladera}
, Mi. - \emph{Microserica} , N. - \emph{Neoserica} , L.
-\emph{Lasioserica} , S. - \emph{Serica} .

\textbf{Fig. 3.} Split network of all examined specimens. Singletons are
highlighted in blue squares, others in orange colours. Morphospecies
nested within others are highlighted with red squares or circles around
them.

\textbf{Fig. 4.} Frequency of intra-\selectlanguage{english}V and interspecific distances of the
Sericini data from Mt. Phu Pan (Laos).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Lukic-etal-Fig1-PhuPan-map2/Lukic-etal-Fig1-PhuPan-map2}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Lukic-etal-Fig2-Laos-Sericini-COI-Daniel-Stammbaum-mit-Balken-final-3/Lukic-etal-Fig2-Laos-Sericini-COI-Daniel-Stammbaum-mit-Balken-final-3}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Lukic-etal-Fig3-Laos-Sericini-COI-Daniel-Splitstree-final/Lukic-etal-Fig3-Laos-Sericini-COI-Daniel-Splitstree-final}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Lukic-etal-Fig4-Maximum-Likelihood-Histogram-Laos-COI/Lukic-etal-Fig4-Maximum-Likelihood-Histogram-Laos-COI}

\end{center}
\end{figure}

\selectlanguage{english}
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