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\begin{document}

\title{DNA barcodes provide insights into the diversity and biogeography of the
non-biting midge Polypedilum (Diptera, Chironomidae) in South America.}



\author[1]{Fabio Laurindo Silva}%
\author[2]{Luiz Pinho}%
\author[3]{Elisabeth Stur}%
\author[1]{Silvio Nihei}%
\author[3]{Torbjorn Ekrem}%
\affil[1]{Universidade de São Paulo Instituto de Biociências}%
\affil[2]{Universidade Federal de Santa Catarina - Campus Florianópolis}%
\affil[3]{Norwegian University of Science and Technology}%


\vspace{-1em}



  
  \date{May 15, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Aim The Neotropics, particularly South America, holds unparalleled high
levels of species richness, when compared to other major biomes. Some
neotropical areas are hotspots of a fragmentary known diversity of
insects and are under manifest danger of biodiversity loss and climate
change. Therefore, prompt estimates methods of its diversity are
urgently required to complement slower traditional taxonomic approaches.
Despite a variety of algorithms for delimiting species through
single-locus DNA barcodes having been developed and applied for rapid
estimates of species diversity in a wide array of taxa; however,
tree-based and distance-based methods may lead to different group
assignments, either overestimating or underestimating the number of
putative species. Here, we investigate the performance of different
DNA-based species delimitation approaches for a rapid biodiversity
estimate of the diversity of Polypedilum (Chironomidae, Diptera) in
South America. Location Worldwide Methods We analyze a mtDNA dataset
comprising 1,492 specimens from 598 locations worldwide. Molecular
operational taxonomic units (MOTUs) ranged from 267 to 520, based on the
Barcode Index Number (BIN), Bayesian Poisson tree processes (bPTP),
multi-rate Poisson tree processes (mPTP), single-rate Poisson tree
processes (sPTP), and generalized mixed Yule coalescent (sGMYC)
approaches. Results Our results highlight Polypedilum as a species-rich
genus, yet incompletely documented, and found the sGMYC method to be the
most adequate to estimate putative species in our dataset. Furthermore,
based on these data, we describe the distribution of diversity and some
biogeographical patterns of Polypedilum. Main Conclusions Findings imply
the genus exhibited high levels of endemism and richness of species in
the Neotropics, which confirmed our hypothesis that there are
substantial differences in community structure between the Polypedilum
fauna in South America and the neighboring regions.%
\end{abstract}%



\sloppy


\textbf{DNA barcodes provide insights into the diversity and
biogeography of the non-biting midge \emph{Polypedilum} (Diptera,
Chironomidae) in South America}

Fabio Laurindo da Silva*

Department of Natural History, NTNU University Museum, Norwegian
University of Science and Technology, Trondheim, Norway

Luiz Carlos Pinho

Laboratory of Systematics of Diptera, Department of Ecology and Zoology,
Federal University of Santa Catarina, Florian\selectlanguage{ngerman}ópolis, Brazil.

Elisabeth Stur

Department of Natural History, NTNU University Museum, Norwegian
University of Science and Technology, Trondheim, Norway

Silvio Shigueo Nihei

Laboratory of Systematic and Biogeography of Insecta, Department of
Zoology, Institute of Biosciences, University of São Paulo, São Paulo,
Brazil.

Torbjørn Ekrem

Department of Natural History, NTNU University Museum, Norwegian
University of Science and Technology, Trondheim, Norway

*Corresponding author. E-mail:\emph{fabiolaurindo@usp.br}

\textbf{Acknowledgements}

We are grateful to several colleagues and associates who contributed
specimens, both South American and critical northern hemisphere taxa,
towards this study:

\begin{itemize}
\tightlist
\item
  Brian Farrell, Harvard University, United Stated
\item
  Anthony Eugene Kiszewski, Bentley University, United Stated
\item
  Neusa Hamada, National Institute of Amazonian Research, Brazil
\item
  Ana Maria Oliveira Pes, National Institute of Amazonian Research,
  Brazil
\item
  Galileu Petronilo da Silva Dantas, National Institute of Amazonian
  Research, Brazil
\item
  Susana Trivinho-Strixino, Federal University of São Carlos, Brazil
\item
  Gilberto Gonçalves Rodrigues, Federal University of Pernambuco, Brazil
\end{itemize}

We thank all Argentinian, Brazilian, Chilean and Dominican Republic
state and territory governments, and their relevant environment
officers, park rangers and private owners who approved collecting
permits and enabled access that allowed us to collect in protected
areas. Our deepest gratitude goes out to Everton Santos Dias and Rogério
Campos de Oliveira for their help and support during various fieldwork
trips. We are also very grateful to Amanda Carvalho de Andrade and
Paloma Helena Fernandes Shimabukuro for useful comments and valuable
suggestions during the initial phase of this study. Special thanks go to
Mark Miller and the CIPRES Science Gateway. The data reported in this
paper were partly obtained thanks to the generosity of George Putnam,
through a Putnam expedition Grant from the Museum of Comparative Zoology
at Harvard University. F. L. da Silva was supported by fellowships of
the São Paulo Research Foundation (FAPESP - 2016/07039--8,
2018/01507--5, 2021/08464--2, 2019/25567--0), which allowed the
preparation of the present manuscript.

\textbf{Conflict of Interest}

The authors declare no conflict of interest.

\textbf{Author contributions}

F.L.S. conceived the study, performed the analyses, drafted and reviewed
the manuscript; L.C.P contributed in data collation, taxonomical
identification and reviewed the manuscript; E.S and T.E. conceived the
study, drafted and reviewed the manuscript; S.S.N reviewed the
manuscript

\textbf{Aim}

The Neotropics, particularly South America, holds unparalleled high
levels of species richness, when compared to other major biomes. Some
neotropical areas are hotspots of a fragmentary known diversity of
insects and are under manifest danger of biodiversity loss and climate
change. Therefore, prompt estimates methods of its diversity are
urgently required to complement slower traditional taxonomic approaches.
Despite a variety of algorithms for delimiting species through
single-locus DNA barcodes having been developed and applied for rapid
estimates of species diversity in a wide array of taxa; however,
tree-based and distance-based methods may lead to different group
assignments, either overestimating or underestimating the number of
putative species. Here, we investigate the performance of different
DNA-based species delimitation approaches for a rapid biodiversity
estimate of the diversity of \emph{Polypedilum} (Chironomidae, Diptera)
in South America.

\textbf{Location}

Worldwide

\textbf{Methods}

We analyze a mtDNA dataset comprising 1,492 specimens from 598 locations
worldwide. Molecular operational taxonomic units (MOTUs) ranged from 267
to 520, based on the Barcode Index Number (BIN), Bayesian Poisson tree
processes (bPTP), multi-rate Poisson tree processes (mPTP), single-rate
Poisson tree processes (sPTP), and generalized mixed Yule coalescent
(sGMYC) approaches.

\textbf{Results}

Our results highlight \emph{Polypedilum} as a species-rich genus, yet
incompletely documented, and found the sGMYC method to be the most
adequate to estimate putative species in our dataset. Furthermore, based
on these data, we describe the distribution of diversity and some
biogeographical patterns of \emph{Polypedilum} .

\textbf{Main Conclusions}

Findings imply the genus exhibited high levels of endemism and richness
of species in the Neotropics, which confirmed our hypothesis that there
are substantial differences in community structure between
the\emph{Polypedilum} fauna in South America and the neighboring
regions.

\textbf{Keywords} : DNA barcode, GMYC, PTP, Chironomidae, Biogeography

\textbf{1 Introduction}

In the past decades, natural environments have been disturbed and
destroyed worldwide at alarming rates, which results in a large loss of
species (Barnosky et al., 2011; Stork, 2018). In hyperdiverse
ecosystems, such as those in the Neotropical region, several species
could go extinct before even being identified (Bradshaw et al., 2011;
Laurance, 1999). This indicates that biodiversity evaluation needs to be
accelerated by combining the strengths of molecular biology, sequencing
technology, and bioinformatics to recognize previously known and
described species (Gostel \& Kress, 2022), and to allow new findings. In
this context, DNA-based approaches have become increasingly useful and
promising tools for estimating diversity and guaranteeing rapid and
accurate identification of species. Since the proposal of the DNA
barcoding technique, using a short standard genetic marker for
species-level identification and cryptic species detection (Hebert et
al., 2003; Hebert et al., 2004), the procedure has been becoming
progressively popular among conservationists and taxonomists (Farooq et
al., 2020; Pearlet al., 2022), and paved the way for biological
monitoring using metabarcoding (e.g., Steinke et al., 2022).

Aquatic insects play a crucial role for the equilibrium of aquatic
ecosystems because of their complex life cycle, which distinguishes them
from exclusively aquatic or terrestrial life forms, and generates a
differentiated potential for understanding biogeographical and
ecological research. It is therefore paramount to invest in knowledge of
the diversity of these organisms, as they are extremely rich both in
functionality and species numbers. Non-biting midges (Diptera:
Chironomidae) are true flies, and frequently dominate aquatic insect
communities in both abundance and species richness. It is a cosmopolitan
group, occurring in an enormous variety of aquatic ecosystems, in all
biogeographical regions of the world, including Antarctica. Presumably,
the great species and habitat diversity in this family is a product of
its antiquity, relatively low vagility and evolutionary plasticity
(Ferrington, 2008), which makes the family not only a valuable source of
indicator species for lentic and lotic aquatic ecosystems, but also one
of the most interesting groups for phylogenetic and biogeographical
analyses (Silva \& Ekrem, 2016).

The advantage of dealing with hyperdiverse taxa is that they surely
exhibit several repeated patterns, which may provide evidence of
underlying processes (Coscaron et al., 2009). Therefore, a genus such
as\emph{Polypedilum} , widespread and rich in species, may be suitable
for biogeographical and ecological research, as the diversity of these
insects is strongly linked with the conservation of aquatic
habitats.\emph{Polypedilum} is one of the largest chironomid genera
containing about 440 described species (Sæther et al., 2010). Larvae
of\emph{Polypedilum} occur in nearly all types of still and flowing
waters. Knowledge of their community compositions is essential due to
their potential as bioindicators, since natural or man-made shifts have
impact on them, and consequently in ecosystem processes. However, whilst
most studies rather focus on taxonomic or phylogenetic issues (e.g.,
Bidawid \& Fittkau, 1995; Bidawid-Kafka, 1996; Sæther \& Sundal, 1999;
Vårdal et al., 2002; Sæther \& Oyewo, 2008; Oyewo \& Sæther, 2008;
Shimabakuro, et al., 2019; Pinho \& Silva, 2020), so far there have been
only few detailed studies on the species richness and species turnover
of the hyperdiverse Chironomidae (Lin et al., 2015; Song et al., 2018).

The biota of South America always has attracted the attention of
naturalists because of the interesting distributional patterns exhibited
by its flora and fauna (Hooker, 1844-47; Darwin, 1859; Wallace, 1876).
For more than a century, biogeographers have proposed theories to
explain the origin and relationships of the biodiversity found in South
America and other southern temperate regions such as Australia, New
Zealand and South Africa (Silva \& Farrell, 2017). Moreover, the region
is a preferred target for investigating the function of these components
in the dynamic of diversification, both by harboring the majority of the
Earth's species and extending across temperate and tropical belts. The
high number of species in South America, on a regional as well as on a
continental scale, makes the region an important reference mark for
estimation of biodiversity loss. However, for the Neotropical non-biting
midge fauna, the knowledge of the actual species diversity is
fragmentary and formal identifications often are unachievable (Spies \&
Reiss, 1996).

Usually, automated species delimitation approaches are considered
particularly useful in organisms with uncertain species boundaries, due
to fragmentary taxonomic knowledge or signals in phylogenetic inferences
being obscured by lineage sorting or introgression (O'Meara, 2010 and
references therein). In this sense, several methods for species
delimitation have been developed and applied, for instance, the
Automatic Barcode Gap Discovery -- ABGD (Puillandre et al., 2012), the
Barcode Index Number -- BIN (Ratnasingham \& Hebert, 2013), the
Generalized Mixed Yule Coalescent -- GMYC (Pons et al., 2006), the
Poisson Tree Processes -- PTP (Zhang et al., 2013). Despite these
approaches being suitable to delimit species, they can occasionally lead
to uncertainty in genetic diversity estimates due to either
oversplitting or overlumping of the taxa. Therefore, the integration of
different algorithms is needed for accurate species delimitation. In
this study, we first compare the performance of different methods of
species estimation and evaluate how much these different approaches
affect estimates of putative species richness in South America. We then
test the hypothesis that there will be substantial differences in
community structure between the \emph{Polypedilum} fauna in South
America, considered more diverse, and neighboring regions, particularly
the Nearctic.

\textbf{2 Material and methods}

\textbf{2.1 Taxon sampling and data collection}

Specimens were collected between 2014 and 2017 from 34 localities, in a
diverse array of habitats including small streams and ponds to lakes,
rivers and bays in Argentina, Brazil, Chile and Dominican Republic. The
main emphasis was on adult sampling, collected with a sweep net near
aquatic systems. A 20 cm diameter D-frame kick net (mesh size 250 \selectlanguage{greek}μ\selectlanguage{english}m)
was also used to collect immature stages at some localities. All sampled
adults were preserved in 75\%-85\% ethanol and larvae in 96-100\%
ethanol and stored at 4\selectlanguage{ngerman}°C in the dark prior to the extraction. Specimens
were identified using the classification proposed by Townes (1945),
Bidawid \& Fittkau (1995), Bidawid-Kafka (1996), Shimabakuro et al.
(2019), Pinho \& Silva (2020), and eventual examination of type
material. Voucher specimens are deposited in the Museum of Comparative
Zoology (MCZ) at Harvard University and in the National Institute of
Amazonian Research (INPA).

In addition to data generated for this publication, we also searched for
public COI barcodes in the Barcode of Life Data Systems
(BOLD,\emph{www.boldsystems.org}) belonging to the genus
\emph{Polypedilum} that were longer than 300 base pairs and without stop
codons. Searches were performed on 25 January 2022 in BOLD. In total,
9,540 COI barcodes were included in our dataset, of which 149 barcodes
of 54 identified species were not previously used in any molecular
analysis. A reduced data set, containing 1,492 sequences, was generated
based on the manual deletion of the highly similar sequences based on an
UPGMA tree. Duplicate sequences occurring at different sampling
localities were retained in our dataset. The detailed specimen records
and sequence information, including trace files, are available in BOLD
through the dataset `DS-RPPPOL - Reduced personal and publicly available
records of \emph{Polypedilum} (Diptera: Chironomidae)'' with DOI:
https://doi.org/XXXX.

\textbf{2.1 DNA extraction, PCR amplification, sequencing and alignment}

The targeted taxa were sorted and dissected under a stereo microscope.
Thorax and one pair of legs were used for genomic DNA extraction. All
extraction procedures followed the Qiagen DNeasy Blood and Tissue kit
protocol provided by the manufacturer. DNA was extracted from the thorax
and head in a buffered solution with the enzyme proteinase-K at 56 °C
overnight, and otherwise followed the manufacturer's protocol, except
using a final elution volume of 100 \selectlanguage{greek}μ\selectlanguage{english}l. After digestion, the
exoskeletons were removed carefully using a fine-tipped forceps and
washed with 96\% ethanol before mounting in Euparal on the same
microscope slide as its corresponding head, antennae, wings, legs and
abdomen following the procedure outlined by S\selectlanguage{ngerman}æther (1969).

A 658 bp fragment of the COI region was PCR-amplified in 25 \selectlanguage{greek}µ\selectlanguage{english}L reactions
and containing 2 \selectlanguage{greek}µ\selectlanguage{english}L DNA template (concentration not measured), 2.5 \selectlanguage{greek}µ\selectlanguage{english}L 5X
buffer, 2 \selectlanguage{greek}µ\selectlanguage{english}L MgCl\textsubscript{2} in 25 \selectlanguage{greek}µ\selectlanguage{english}M concentration, 0.2 \selectlanguage{greek}µ\selectlanguage{english}L of
dNTPs in 10 mM concentration, 1 \selectlanguage{greek}µ\selectlanguage{english}L of each of the universal standard
barcode primers (Folmer et al\emph{.,} 1994) LCO1490
(50-GGTCAACAAATCATAAAGATATTGG-30) and HCO2198
(50-TAAACTTCAGGGTGACCAAAAAATCA-30), in 10 \selectlanguage{greek}µ\selectlanguage{english}M concentration, 0.2 \selectlanguage{greek}µ\selectlanguage{english}L of
HotStarTaq (Qiagen, Germany) and 16.1 \selectlanguage{greek}µ\selectlanguage{english}L of ddH2O. PCR amplification was
performed in a thermocycler with an initial denaturation step of 95 \selectlanguage{ngerman}ºC
for 15 minutes, then followed by five cycles of 94 ºC for 30 seconds, 45
ºC for 30 seconds, 72 ºC for 1 minute, followed by 35 cycles of 94 ºC
for 30 seconds, 51 ºC for 30 seconds, 72 ºC for 1 minute, and one cycle
at 72 ºC for 5 minutes, then held at 4 ºC.

PCR products were checked visually by electrophoresis on a 1.5\% agarose
gel and purified using shrimp alkaline phosphatase and exonuclease I
(USB Corp., USA). For bidirectional sequencing, we used the ABI PRISM
BigDye Terminator version 3.1 Cycle Sequencing Kit (Life Technologies,
USA), and cycle sequencing reactions were performed on ABI PRISM 3130xl
or 3730xl automated sequencers (Life Technologies, USA) at Harvard
University, or shipped to EurofinsGenomics (Ebersberg, Germany). Raw
sequences were assembled and edited using Geneious 2021.2.2 (Kearse et
al\emph{.} , 2012), checked for stop codons and aligned as translated
amino acids using the MUSCLE algorithm (Edgar, 2004) on amino acids as
implemented in MEGA11 (Tamura et al\emph{.} , 2021). The nucleotide
compositions were calculated in MEGA11, while the pairwise genetic
distances for each individual sequence were determined in BOLD, both
using the K2P model (Kimura, 1980).

\textbf{2.3 Phylogenetic analysis}

Two phylogenetic trees were generated: a non-ultrametric phylogram using
Maximum Likelihood (ML) (Felsenstein, 1981) and an ultrametric
chronogram using Bayesian inference (BI) (Drummond et al., 2002). The ML
tree was generated using Iq-Tree (Trifinopoulos et al., 2016). Node
support was assessed with 1000 ultrafast bootstrap replicates (Hoang et
al., 2018), using the GTR+G+I model, with the data partitioned according
to codon position, as recommended by PartitionFinder version 2.1.
(Lanfear et al., 2017).

The BI tree was generated using BEAST version 2.6.7 (Bouckaert et al.,
2019), using default settings for all parameters. XML files were made
with the BEAUti version 2.6.7 interface with the following settings:
GTR+G+I substitution model, empirical base frequencies, 4 gamma
categories and all codon positions partitioned with unlinked base
frequencies and substitution rates. Since there is no agreement
concerning the most appropriate clock and tree priors for reconstructing
gene trees for species delimitation (Monaghan et al., 2009; Ratnasingham
\& Hebert 2013; Talavera et al., 2013; Tang et al., 2014), preliminary
analyses to compare the use of two different clock (strict and relaxed
lognormal) and two different tree priors (coalescent constant population
and Yule) were undertaken (Rodrigues et al., 2020). The results of these
exploratory analyses (data not shown) indicated the strict clock and
Yule priors as the most suitable for our data set, thus these priors
were used for the Bayesian inference analyses.

To account for mixing within chains and convergence among chains with
reversible jump MCMC (Elworth et al., 2018), a total of 10 chains were
run from different seeds for 100 million generations each. Log files
from each run were combined in LogCombiner version 2.6.7 (Drummond et
al., 2012) after removal of the first 10\% of samples from each run as
burn-in. Convergence of each run and the combined data were checked for
proper mixing using effective sample size (ESS) \textgreater{} 200 in
Tracer version 1.7.1 (Rambaut et al., 2018). Tree files from each run
were resampled to retain only 10\% of the total trees and combined using
LogCombiner after removal of the first 10\% of retained trees from each
run as burn-in. A maximum clade credibility (MCC) tree was then produced
using TreeAnnotator version 2.6.6 (Drummond et al., 2012) and FigTree
version 1.4.4 (Rambaut, 2010) was used to visualize and edit the trees.

All phylogenetic analyses were conducted on the CIPRES Science Gateway
High Performance Computing platform (Miller et al., 2011).

\textbf{2.4 Putative species estimation}

The two single-locus DNA barcoding methods consisted of two
fundamentally different approaches. First, we implemented three
distance-based approaches: (1) the Automatic Barcode Gap Discovery --
ABGD (Puillandre et al., 2012) performed using the online version of the
software (\emph{https://bioinfo.mnhn.fr/abi/public/abgd/abgdweb.html});
(2) the Assemble Species by Automatic Partitioning -- ASAP (Puillandre
et al., 2021), an updated implementation of the ABGD hierarchical
clustering algorithm, performed with the ASAP web version
(\emph{https://bioinfo.mnhn.fr/ abi/public/asap/}). Both methods used
the MUSCLE aligned matrix as the input file and adopted the Kimura
model, following the default settings for all parameters. (3) The
Barcode Index Number (BIN), a method implemented in BOLD, in which newly
submitted and already available sequences clustered in unique BINs using
a refined single linkage analysis in which records with high sequence
similarity and connectivity are clustered and separated from those with
lower similarity and sparse connectivity (Ratnasingham \& Hebert, 2013).

Second, we applied four tree-based approaches, which models speciation
along the branches of an inferred phylogenetic: (1) the Single Poisson
Tree Processes -- sPTP (Zhang et al., 2013), implemented using the PTP
online version (\emph{http://species.h-its.org/ptp}); (2) the Bayesian
Poisson tree process -- bPTP (Zhang et al., 2013), also conducted on the
PTP web-server. Both analyses were conducted with 500,000 MCMC
generations and other parameters as default. (3) the Multi-rate Poisson
Tree Processes -- mPTP (Kapli et al., 2017), performed with the mPTP
web-server (\emph{https://mcmc-mptp.h-its.org/mcmc/}), using the
multi-rate Poisson tree process model and following default settings.
All PTP analyses (sPTP, mPTP and bPTP) used the ML trees calculated with
Iq-Tree. (4) the Generalized Mixed Yule Coalescent -- GMYC (Pons et al.,
2006), performed by submitting the single ultrametric MCC tree resulting
from BI obtained from BEAST to the online version of the GMYC software
(\emph{https://species.h-its.org/gmyc/}), following default
single-threshold (sGMYC). We also tested the multiple-threshold model
(mGMYC); however, it did not perform well, overestimating putative
species (data not shown). Similar species estimates with the mGMYC
algorithm were also observed in previous studies (Fujisawa \&
Barraclough, 2013; Schwarzfeld \& Sperling, 2015).

\textbf{2.5 Biogeographical analysis}

The biogeographical relationships between samples were implemented with
the software PRIMER 7 (Plymouth Routines In Multivariate Ecological
Research). In the Neotropical region, we pre-assigned a set of smaller
hierarchical geographical areas (zones), following Morrone et al.
(2022), to enable hypothesis testing using non-metric multidimensional
scaling (nMDS). The faunal similarity between zones and between larger
regions was quantitatively measured using Sørensen similarity index of
presence/absence data, and the significance of the geographical
groupings was assessed using the ANOSIM test (see Appendices S1 \& S2).
Species accumulation curves were implemented by the vegan package
(Oksanen et al., 2017) in the software R (R Development Core Team, 2021)
using 100 randomizations. Accumulation curves are randomized plots of
the presence or absence of each species (here delimited by the sGMYC
algorithm) against the number of observations.

\textbf{3 Results}

\textbf{3.1 Species delimitation}

The complete data set consisted of 1,492 barcodes, ranging from 312 to
658 bp in length. In total, there were 319 variable sites (48.5\%), of
which 299 (93.7\%) were parsimony informative. Most parsimony
informative sites occurred in the third codon-position (Table 1). The
sequences were heavily AT-biased, specifically in the third position,
which exhibited a combined average AT-composition of 89.3\% (Table 1).
Average intraspecific and interspecific K2P-distances for all
analyzed\emph{Polypedilum} species were 1.3\% and 15.2\%, respectively.
The barcode gap is an important concept in barcoding studies (Puillandre
et al., 2012). It works well when the amount of intraspecific divergence
is much smaller than the amount of interspecific variation between
species. When this condition is met, a `barcoding gap' exists (Meyer \&
Paulay, 2005). In general, our data showed clearly larger interspecific
than intraspecific divergences, but we still could not observe the
expected `barcoding gap' in the pairwise K2P distances. On the contrary,
a barcode overlap between the intraspecific and the interspecific
distances was found, which may be attributable to the presence of
cryptic species diversity and a few misidentifications. The lack of a
gap is usually associated with recently diverged species with little
genetic diversification, frequently coupled with incomplete lineage
sorting and introgression (Wiemers \& Fiedler, 2007; Dupuis et al.,
2012).

Overall, most of the tested methods recovered similar groupings of
molecular operational taxonomic units (MOTUs) (Figures 1-4), with the
mPTP method being the most conservative, lumping the sequences into
fewer MOTUs, and the bPTP algorithm the most relaxed, lumping the
sequences into several MOTUs (Table 2). Two out of the three
distance-based methods, ABGD and ASAP, yield unreliable delimitations
with wide confidence intervals, with several clusters not reflecting
relationships as understood based on the geographical sampling
localities and others diverging into numerous lineages despite
diminished divergence between them. ABGD and ASAP results were not
included in the Figures 1-4. The BIN analysis returned a total of 415
MOTUs of which 174 were singleton BINs, 222 concordant BINs, and 19
discordant BINs. In total, 615 sequences of 143 morphospecies were
assigned to 179 BINs, including 72 singleton BINs, 519 concordant BINs,
and 24 discordant BINs. The unidentified 877 specimens, without binomial
names, were assigned to 236 BIN-species, including 102 singleton BINs,
118 concordant BINs, and 16 discordant BINs.

DNA-based species delimitation applying bPTP, mPTP, sPTP, and sGMYC
resulted in divergent number of clusters. The single-threshold general
mixed Yule-coalescent calculations (sGMYC) recovered 370 MOTUs, while
the sPTP model produced a more conservative number of MOTUs (411)
compared to the bPTP method, which yielded 520 MOTUs (Table 2). The
results from analyses using the multi-rate PTP (mPTP) model were also
comparable to those of the other models, but revealed larger clusters,
occasionally joining lineages belonging to different species in a single
MOTU (Figure 1). Divergences in the number of clusters generated by the
different species delimitation algorithms are caused by erroneously
inferred splitting or lumping events (i.e., specimens of one
morphospecies were divided or joined into two or more different MOTUs).
However, regardless of the method applied, the total number of species
delimited in \emph{Polypedilum} in this study is at least twice as high
(267--520) as the number of included morphospecies (143, see above).

\textbf{3.2 Biogeography}

The following biogeographical analyses were based on the MOTUs (370)
delimited by the sGMYC approach (see discussion below). In our dataset,
the number of species per sampling location varied from a single species
to over 15 species across the different sampling sites at the studied
biogeographical realms. Just a few of all sampled locations (3.8\%) had
5 or more species present, while 203 (54.9\%) of the 370 species
included were only recorded at a single location. Since collecting
methods, sampling sites, protocols and reporting varied in our dataset,
comparisons of overall biodiversity between locations is challenging.
Numbers of \emph{Polypedilum} species and sampled locations varied
between regions (Table 1). Our results indicate that 90.2 \% of species
were recorded only in a single major biogeographical region, while only
36 species spanned two or more of these regions.

The relative diversity and dominance of \emph{Polypedilum} species as a
proportion of the total number of species per region shows a clear
divergence between the geographical regions studied (Figure 5).
Insufficiently sampled areas (Afrotropical, Australasian and Panamanian)
with low numbers of recorded species present low levels of diversity and
are dominated by few species. On the other hand, biogeographical regions
exhaustively sampled exhibit high numbers of recorded species with the
highest degree of species richness (Nearctic, Palearctic, Oriental and
Sino-Japanese). Regarding the Neotropics, the region presented moderate
levels of \emph{Polypedilum} species diversity, particularly when
compared to the neighboring Nearctic region (Figure 5); however, it is
noteworthy that although only 6.2\% of the sampling sites are located in
the Neotropical region (mostly in South America), 19.1\% of the total
number of species occurred in this region. Moreover, based on our
results, the Neotropical \emph{Polypedilum} fauna can be considered
endemic, since only one unidentified species was also recorded in the
Nearctic region.

None of the species accumulation (rarefaction) curves for the
biogeographical realms (Figure 6) exhibit asymptote for any area,
although the Nearctic sequences may be approaching one. The
Afrotropical, Australasian and Panamanian regions presented the lowest
levels of diversity. The highest levels of diversity were seen in the
Nearctic, Palearctic and Sino-Japanese regions, with the Neotropical and
Oriental regions curves being noticeably lower, with levels of diversity
which seems to be comparable. Biogeographical realm patterns across the
entire assembly (Figure 7a) showed distinct groupings for Afrotropical
and Australasian, while the ANOSIM (see Appendix S1) and nMDS results
show some overlap between Nearctic and Palearctic regions. The
Neotropical \emph{Polypedilum} fauna despite the closeness to the
Nearctic region presents distinct clustering. The different Neotropical
zones compose distinct well supported groups (Figure 7b), with some
degree of overlap between Southeastern Amazonia and Boreal Brazilian
domination zones. In particular, the Palearctic region appears to
display affinities for both the Nearctic and Oriental region (Figure
7b).

\textbf{4 Discussion}

\textbf{4.1 Species delimitation}

One of the objectives of this study was to explore the utility of a
large-scale single-locus DNA barcode analysis of the
genus\emph{Polypedilum} to investigate its molecular diversity and
compare the adequacy of molecular species delimitation approaches. Our
results suggest that tree-based algorithms are more suitable than
distanced-based because they are able to integrate evolutionary theory,
not requiring arbitrary thresholds (Schwarzfeld \& Sperling, 2015). In
our study, ABGD and ASAP produced unreasonable delimitations, not
consistently proposing species hypotheses. These approaches are known to
over-lump, performing poorly on more speciose datasets such as ours,
whereas the success rate increases remarkably for small populations
(Dellicour \& Flot, 2015; 2018). In contrast to ABGD and ASAP's
over-lumping, the Barcode Index Number (BINs) method, assigned by BOLD,
is known to oversplit species numbers due to the low intracluster
distance (2.2\%) at the initial clustering step of RESL algorithm
(Ratnasingham \& Hebert, 2013). Similar results were found by Song et
al. (2018), when applying the BIN system also to
delimit\emph{Polypedilum} species, mostly from East Asia.

Among the drawbacks of distance-based methods is the lack of a universal
threshold that fits all taxa (Yang \& Rannala, 2017). Several DNA
barcoding studies try to determine a fixed threshold value, Hebert et
al. (2004) suggested the interspecific divergences at least 10 times as
large as the intraspecific divergence the so-called ``10 × rule,''.
However, it seems that different best-fit thresholds apply to different
taxonomic groups (Havermans, et al., 2011). For example, a threshold of
2-3\% was indicated for some for Ephemeroptera, Plecoptera and
Trichoptera (Zhou et al., 2010), and 3-5\% for some dipteran species
groups (Lin et al., 2015; Nzelu et al., 2015), while a threshold 5-8\%
for species in \emph{Polypedilum} was suggested by Song et al. (2018).
Another downside of distance-based approaches is that they do not
consider evolutionary relationships into their algorithms (Kapli et al.,
2017). Tree-based methods are not influenced by such thresholds, since
they use phylogenetic inference for a more precise barcode assignment
(Song et al., 2018).

Applied to our dataset, sGMYC and PTP tended to over-perform when
compared to delineations made with distance-based methods and the
morphological species concept. The Poisson Tree Process (PTP) relies on
the distribution of branch lengths in the gene tree in order to identify
species status (Zhang et al., 2013). The tree and branch lengths are
inferred from a sequence alignment using maximum likelihood and then
treated as lacking errors (Ranala \& Yang, 2020). In our study, there
was a large difference between recovered MOTUs among the PTP methods.
There was a 109 MOTU difference between results based on the bPTP and
sPTP methods. mPTP was the most conservative and commonly underestimated
species by lumping singleton species, represented in our tree by
isolated branches, into MOTUs. Along with our results, other studies
have found that the mPTP algorithm leads to a lower number of recovered
species when compared with other approaches (e.g., da Silva et al. 2018,
Parslow et al. 2021).

The sGMYC analysis based on a single gene revealed the presence of 370
MOTUs (likelihood ratio: 600.4823, confidence interval: 349-383,
threshold time: -0.01053644). This species-delimitation algorithm relies
on the priors and parameters used to construct the ultrametric tree
(Ceccarelli et al., 2012), and tends to overestimate species diversity
compared to other methods (Paz \& Crawford, 2012; Miralles \& Vences,
2013; Talavera et al., 2013; Kekkonen \& Hebert, 2014). In our study,
the sGMYC method seems to be the most accurate since it recovered
substantially fewer putative species than the bPTP and sPTP analyses
despite its hypothesized oversplitting. Moreover, the sGMYC approach has
been suggested to suit datasets with large numbers of singleton taxa
(Talavera et al., 2013), which is what we observe for\emph{Polypedilum}
. Based on the aforementioned considerations, we chose the putative
species delimited by the sGMYC method as the basis for the
biogeographical analyses.

\textbf{4.2 Biogeography}

The level of taxonomic diversity present in an environment can be
quantified by either enumerating numbers of species (e.g. Simpson's
diversity) or estimating evolutionary divergences among species in which
genetic divergences have been calculated (Webb, 2000). Moreover, besides
the number of individuals sampled, the size of the local species pool,
the evenness of species abundances in the community, size and
environmental heterogeneity of the area, and the status of taxonomic
understanding of the taxa investigated are parameters essential to the
accuracy of estimates of taxonomic diversity (Antonelli et al., 2018).
Although most measures of alpha and beta diversity rely on species
numbers, DNA sequence data may provide an evolutionary framework to
diversity estimates (Hebert et al., 2016). In this sense, genetic
measures may also be used to evaluate species boundaries when compared
with species richness in the same communities. Additionally, DNA
barcodes can be used for species delimitation, assisting in documenting
new species, and identifying targeted habitats for conservation (Faith,
1992; 2008). In geographic regions especially known for their unique
lineages of organisms, biological diversity determined with DNA barcode
sequence data can be essential for comparing diversity and establishing
protected areas across the landscape (Shapcott et al., 2015, Hobner,
2021).

Numerical species delimitation methods require species to be
sufficiently sampled (Dopheide et al., 2019) across geographical ranges
to improve their ability to correctly delimit species (Parslow et al.,
2021). In practice, this is a challenging task when it comes
to\emph{Polypedilum} due to its known worldwide diversity of\selectlanguage{english} ca. 440
described species and the expected number of undescribed species.
Although recent taxonomic studies of regional fauna have been conducted
(Song et al., 2016; 2018), particularly in East Asia, there are several
regions that need modern taxonomic treatments, for example, Australia,
Africa and South America. Therefore, it is difficult to determine the
degree of sampling completeness of \emph{Polypedilum} caused by the
potentially large number of undescribed species. In the current study,
many of the biogeographical differences in recorded species numbers can
be ascribed to different sampling efforts and methods between regions.
Usually, knowledge of species distributions and diversity patterns are
strongly concentrated toward areas which are more easily accessible by
roads, rivers, and research stations (Antonelli et al., 2018). This fact
is evident in our investigation, as though we included all publicly
available COI sequences for \emph{Polypedilum} in BOLD, there was a bias
towards Nearctic (33.2\%) and Sino-Japanese (23.2\%) taxa, with a
reduced representation of Afrotropical (1.6\%), Australasian (1.6\%) and
Panamanian (1.3\%) species, regions known for receive less investment
for research in Chironomidae.

Much of what we need to comprehend about biodiversity can be undertaken
as a matrix of the presence or abundance of multiple species across time
and space (Hobner, 2021). That said, plotting species accumulation
curves permit researchers to measure and compare diversity across
populations or to assess the benefits of further sampling (Deng et al.,
2015). In our study, the rarefaction curve analysis suggests that even
when randomization sampling methods are considered there are regional
differences in species richness. Noticeably, the most species-rich
regions were the Nearctic and Sino-Japanese regions. This came as a
little surprise, since we expected the Palearctic region also to be
among the most specious biogeographical areas, due to the high number
of\emph{Polypedilum} sequences available in BOLD and the numerous
studies performed on the family Chironomidae in this area. Although we
used species accumulation curves to indicate the pattern of sequence
accumulation within the current study, they are not expected to
represent the accurate diversity of each region, as they are not based
on actual random sampling (Schwarzfeld \& Sperling 2015).

The Palearctic fauna overlaps partially with that of the Nearctic,
especially in the north. This is similar to what is found in other
studies (Ekrem et al., 2018; Marusik \& Koponen, 2005) where distinct
communities in the two regions share several species. This can be the
result of numerous faunal interchanges that took place across the Bering
land bridge (135~000 -- 70~000 YBP). However, these migrations were
mostly limited to large, cold-tolerant species (Rodriguez et al., 2006),
and it is mainly these species which are found throughout the Holarctic
realm today. Chironomids have also been observed as aerial plankton
(Hardy \& Milne, 1938; Gressitt et al., 1960; Cotoras \& Zumbad, 2020)
and one cannot rule out long distance dispersal as an explanation for
trans-Atlantic distribution patterns in \emph{Polypedilum} (Ekrem et
al., 2018). Species overlap was also recorded between Palearctic and
Oriental fauna, despite the Himalayas forming an altitudinal barrier
between these realms, a pattern also previously recorded for butterflies
(Larsen, 1984). Inasmuch as the majority of species (54.9\%) were only
recorded at a single location and only 3.8\% of species were recorded at
five or more locations, it is no surprise that a small number of wider
distributed species are driving the regional and larger scale
biogeographical patterns. The high number of species recorded only once
is a typical result for understudied taxa (Velasco-Castrillon et al.,
2014; Zhang et al., 2018).

The Neotropical region as one of the lesser studied regions with 71
species recorded from 37 localities, exhibited a higher species richness
than that of the Palearctic and Oriental realms. Moreover, despite the
Neotropical fauna being closely linked with that of the adjacent
Nearctic fauna, from which it has received some, especial boreal
components (e.g. \emph{Polypedilum beckae} and \emph{Paralauterborniella
nigrohalteralis} , Silva et al., 2015), the results in the current study
corroborate our hypothesis that there are significant differences in
community structure between the \emph{Polypedilum} fauna in South
America, and the neighboring regions. Only a single unidentified species
spanned from the Neotropics to the Nearctic region, recorded in
Argentina and Mexico, which confirms our expectations of high levels of
endemism and richness of \emph{Polypedilum} species in the Neotropical
region. The outstanding biodiversity there, when compared to other major
biotic realms (Lundberg et al., 2000; Antonelli \& Sanmartin, 2011) can
be attributed to a complex process in which palaeo-geographical and
palaeoclimatic forces have been constantly interacting and new species
have originated continuously in that area since the late Eocene/early
Oligocene (Rull, 2008). As such, the Neotropics is paramount for
research on the origin of biological diversity. Finally, some
neotropical areas are under manifest danger of biodiversity loss
(Antonelli, 2021). Our study shows that DNA-based species delimitation
approaches can be used in rapid biodiversity estimates of poorly known
taxonomic groups so these can be utilized as basis for biodiversity
conservation strategies, and to unravel biogeographical patterns at both
local and global scales.

\textbf{4.3 Conclusion: implications of DNA barcoding to accelerate
biogeography research}

As different analytical methods have different theoretical foundations,
it is advisable to test a wide variety of approaches of species
delimitation, and to favor patterns that are congruent across the
results. Moreover, the contrast of different methods helps to comprehend
their propensity to either split or lump clusters. We evaluated some
approaches for species delimitation in the genus
\emph{Polypedilum}through single-locus DNA barcodes and found the sGMYC
as the method more adequate to estimate putative species on our dataset.
Our results highlight \emph{Polypedilum} as species-rich genus, yet
incompletely documented, which implies in the need of increased taxon
sampling, across geographical ranges, and the use of additional
molecular data for greater resolution when using molecular species
delimitation approaches for the group. Quantitative species delimitation
methods are sensitive to sampling effort. Since communities typically
contain several species that are locally rare, observed species richness
provides just an underestimate of the diversity actually present, except
if the community is thoroughly sampled. Therefore, a reference COI
sequence library derived from expert-identified reference material is
fundamental to assign organisms into species by matching the sequence of
an unknown sample to the reference library. Our hypothesis that there
would be substantial differences in community structure between
the\emph{Polypedilum} fauna in South America and other neighboring
regions, particularly the Nearctic region, was confirmed. The
Neotropical region exhibited high levels of endemism and richness for
\emph{Polypedilum}species. Despite major advances in our understanding
of Neotropical biodiversity in recent years, several questions remain to
be answered: When did the Neotropics reach globally outstanding levels
of species richness? Why do nearly all groups of organisms have more
species in the Neotropics? What drives latitudinal patterns of
diversity? When did the species observed today split from their most
recent common ancestors? Further biological and geological data,
associated with the integration of different DNA-based methods for
estimating species richness, will advance the field of natural history
and increase our ability to make knowledge-based decisions in
conservation issues. The integration of biodiversity genomics in
biogeography science therefore represents a major scientific priority.

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\textbf{Data Accessibility Statement}

The detailed specimen records and sequence information, including trace
files, are freely available in BOLD through the dataset `DS-RPPPOL,
Reduced personal and publicly available records of
\emph{Polypedilum}(Diptera: Chironomidae)' with DOI:
https://doi.org/XXXX. Significant ANOSIM results per realm and region
are given in Appendices S1 and S2.

\textbf{Hosted file}

\verb`Table 1.docx`  available at \url{https://authorea.com/users/584361/articles/623607-dna-barcodes-provide-insights-into-the-diversity-and-biogeography-of-the-non-biting-midge-polypedilum-diptera-chironomidae-in-south-america}

\textbf{Hosted file}

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