# Exploring community assembly among Javanese and Balinese freshwater shrimps (Atyidae, Palaemonidae) through DNA barcodes

Rena Hernawati, Ujang Nurhaman, Frédéric Busson, Bambang Suryobroto, Robert Hanner, Philippe Keith, Daisy Wowor, Nicolas Hubert

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## To cite this version:

Rena Hernawati, Ujang Nurhaman, Frédéric Busson, Bambang Suryobroto, Robert Hanner, et al. Exploring community assembly among Javanese and Balinese freshwater shrimps (Atyidae, Palaemonidae) through DNA barcodes. Hydrobiologia, 2020, 847(2), pp.647-663. 10.1007/s10750-019-04127-7. http://dx.doi.org/10.1007/s10750-019-04127-7

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1 Exploring community assembly among Javanese and Balinese freshwater shrimps

2 (Atyidae, Palaemonidae) through DNA barcodes

3

4 Rena Hernawati¹, Ujang Nurhaman¹, Frédéric Busson³, Bambang Suryobroto², Robert

5 Hanner⁴, Philippe Keith³, Daisy Wowor¹, Nicolas Hubert⁵

6

7 ¹Division of Zoology, Research Center for Biology, Indonesian Institute of Sciences (LIPI),

8 Jalan Raya Jakarta Bogor Km 46, Cibinong 16911, Indonesia.

9 ²Bogor Agricultural University, Faculty of Mathematics and Natural Science, Animal

10 Bioscience. Jl. Raya Darmaga, Bogor 16680, Indonesia.

11 ³Muséum National d'Histoire Naturelle, UMR 7208 (MNHN-CNRS-UPMC-IRD-UCBN), CP

12 026, 43, rue Cuvier, F-75231 Paris Cedex 05, France.

13 ⁴Department of Integrative Biology, University of Guelph, 50 Stone Rd E, Guelph, ON

14 N1G2W1, Canada

15 ⁵UMR 226 ISEM, Université de Montpellier, CNRS, IRD, EPHE, Montpellier, France.

16

17 *Correspondence*: Nicolas Hubert, Institut de Recherche pour le Développement, UMR 226

18 ISEM (UM2-CNRS-IRD), Place Eugène Bataillon, CC 065, F-34095 Montpellier cedex 05,

19 France.

20 E-mail: nicolas.hubert@ird.fr

21

22

23 ABSTRACT

24 Species proliferate through evolutionary mechanisms but co-exist through ecological

25 dynamics. As such, it might be expected that mechanisms of speciation and species

26 maintenance jointly influence the settlement of ecological communities, a process called

27 community assembly. Disentangling the relative contribution of evolutionary and

28 ecological dynamics might be a difficult task, particularly so for the tropical biotas due to

29 their extreme diversity and large knowledge gaps. Here, we explore genetic diversity

30 and distribution of 23 freshwater shrimp species of the genera *Caridina* and

31 *Macrobrachium* in Sundaland to examine patterns of species co-occurrence based on

32 1583 observations across 19 sites in Java and Bali islands. DNA-based species

33 delimitation methods applied to 204 Cytochrome oxidase I sequences detected 30

34 Operational Taxonomic Units (OTUs) and a few cases of deep intra-specific divergence.
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Species co-occurrence and phylogenetic community structure show no departure from
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expectations under a random distribution of species in landscapes, and support a lottery
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model of community assembly. Species age estimates expand beyond the geological
38
settlement of Sundaland, suggesting that species proliferation and community assembly
39
are driven by mechanisms acting at distinct spatial and temporal scales.

40

41 **Keywords** *Caridina*, *Macrobrachium*, Species delimitation, Dispersal, Phylogenetic
42 Community Structure, Lottery model.

43

44 INTRODUCTION

45
Species proliferate through evolutionary dynamics and further persist in landscapes
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through a variety of ecological dynamics (Ricklefs 1987; Ricklefs and Schluter 1993;
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McPeek 2008). The mechanisms of species aggregation in ecological communities, often
48
referred to as community assembly, result from the integration of eco-evolutionary
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dynamics of species proliferation and persistence through time (Kraft et al. 2007;
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Emerson and Gillespie 2008; Kembel 2009; Hubert et al. 2015a). By acknowledging the
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overlap of speciation and ecological dynamics through space and time, recent studies of
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community assembly have increasingly incorporated species phylogenetic relationships
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to address the nature of community assembly mechanisms (Emerson and Gillespie
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2008; Cavender-Bares et al. 2009; Vamosi et al. 2009). Phylogenetic community
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structure analyses have been successfully applied to the study of community assembly
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for terrestrial biotas, particularly for plants (Cavender-Bares et al. 2006; Webb et al.
57
2006; Kraft et al. 2008). In turn, community assembly of freshwater biotas has attracted
58
much less attention in the literature; however, historical contingencies, niche diversity
59
and temporal heterogeneity have been identified as potential drivers (Vamosi and
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Vamosi 2006; Vamosi et al. 2009; Hoverman et al. 2011; Brown and Milner 2012; Hauffe
61
et al. 2016).

62
Most of the previous studies on community assembly of freshwater biotas have
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been focused on temperate biomes; meanwhile' dynamics in tropical biotas have been
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largely overlooked. This is due, in part, to the fact that studying community assembly
65
dynamics is particularly challenging in tropical biotas where taxonomic knowledge gaps
66
and historical contingencies may have confounding effects on the nature of the
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ecological dynamics in ecological communities (Hebert et al. 2004; Smith et al. 2007,
68
2008). This situation is well exemplified by the freshwater biotas of Southeast Asia
(SEA) that are extremely rich (De Grave et al. 2008; Hubert et al. 2015b), and result from a complex geological and volcanic history that prompted the settlement of some of the world's largest insular biodiversity hotspots (Myers et al. 2000; Hoffman et al. 2010). This is particularly true in Sundaland, which includes the islands of Java, Sumatra, Borneo and Bali, and has been repeatedly connected to the continent during the sea levels low-stand associated with glacial times (Voris 2000; Woodruff 2010). In such a mosaic of contiguous continental and insular aquatic systems, riverine habitats have been colonized by a large diversity of strictly freshwater organisms, through temporary connections to the continent, and freshwater organisms having a marine stage in their life cycle (Kottelat et al. 1993; De Grave et al. 2008; Keith et al. 2015). This diversity of life history traits and dispersal abilities is well exemplified by the shrimps genera *Caridina* (Atyidae) and *Macrobrachium* (Palaemonidae). South East Asia (SEA) hosts more than 50 percent of the diversity of *Caridina* and *Macrobrachium*, and both genera include species displaying a variety of reproductive strategies, scattered along a *r/K* continuum (MacArthur and Wilson 1967; Pianka 1970) and broadly classified into Abbreviated Larval Development (ALD) or Elongated Larval Development (ELD) strategies (Cai 2003; De Grave et al. 2008; Wowor et al. 2009).

In the present study, we sampled *Caridina* and *Macrobrachium* species in the Islands of Java and Bali to examine diversity patterns and community assembly in a mosaic of watersheds that have been varyingly connected to the continent during glacial times and, as such, potentially hosting a variety of reproductive strategies. The community composition of *Caridina* and *Macrobrachium* assemblages was examined across 19 sites in Java and Bali through DNA barcoding (i.e. use of the mitochondrial Cytochrome oxidase I gene for species identification [Hebert et al. 2003]) with the following objectives: (1) explore diversity and species co-occurrence patterns to detect potential departures from random species aggregation that may result from biotic interactions such as competitive interactions (Hutchinson 1959; MacArthur and Levins 1967) or life history trade-offs (MacArthur and Wilson 1967), (2) explore phylogenetic community structure in order to detect a potential departure of the distribution of cladogenetic events from expected at random that may result from the overlap of speciation dynamics and species aggregation in ecological communities (Gillespie 2004; Emerson and Gillespie 2008), (3) explore the potential consequences of reproductive strategies on the accumulation of genetic divergence among populations. Considering the lack of prior studies on evolutionary community ecology of *Macrobrachium* and
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*Caridina* assemblages in this area, this study, based on newly generated DNA barcodes and occurrence data, aims at identifying trends in diversity patterns to be further explored at wider spatial scale in SEA freshwater ecosystems.

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# MATERIALS AND METHODS

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## Sampling and collection management

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Specimens from the genera *Caridina* and *Macrobrachium* were sampled using tray net (mesh size 0.2mm) and electroshocking at 19 sites in Java and Bali during a field expedition conducted by the authors in April, 2014 (Fig. 1A). A total of 1583 specimens was collected and preserved in a 95% ethanol solution (Table S1). Sampling information, including geographic coordinates, was recorded for each of the sites visited. Tissues were taken from abdominal muscle samples for further genetic analyses. Both tissues and voucher specimens were deposited in the Museum Zoologicum Bogoriense (MZB), Research Centre for Biology (RCB), Indonesian Institute of Sciences (LIPI). Specimens were identified to the species level according to the identification keys (Cai 2003; Wowor 2004), and their valid names updated according to De Grave and Fransen (De Grave and Fransen 2011). Once species were delimitated and identified using morphological characters, a total of 285 specimens was selected for DNA barcoding. For each species, several specimens were selected for each site in order to cover the intraspecific genetic diversity at the study sites and further validate or reject the initial set of identification hypotheses based on morphological characters. The comprehensiveness of the sampling was further examined through accumulation curve analysis as implemented in the Barcode of Life Data System (Ratnasingham and Hebert 2007).

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## Sequencing and international repositories

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Genomic DNA was extracted using a Qiagen DNeasy 96 tissue extraction kit following the manufacturer's specifications. A 654-bp segment from the 5' region of the cytochrome oxidase I gene (COI) was amplified using primers cocktails C_FishF1t1/C_FishR1t1 including M13 tails (Ivanova et al. 2007). PCR amplifications were done on a Veriti 96-well Fast (ABI-AppliedBiosystems) thermocycler with a final volume of 10.0µl containing 5.0µl Buffer 2X, 3.3µl ultrapure water, 1.0µl each primer (10µM), 0.2µl enzyme Phire® Hot Start II DNA polymerase (5U) and 0.5µl of DNA template (~50 ng). Amplifications were conducted as follows: initial denaturation at

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98°C for 5 min followed by 30 cycles denaturation at 98°C for 5s, annealing at 56°C for 137
20s and extension at 72°C for 30s, followed by a final extension step at 72°C for 5 min. 138
The PCR products were purified with ExoSap-IT® (USB Corporation, Cleveland, OH, 139
USA) and sequenced in both directions. Sequencing reactions were performed using the 140
"BigDye® Terminator v3.1 Cycle Sequencing Ready Reaction" and sequencing was 141
performed on an ABI 3130 DNA Analyzer (Applied Biosystems). The sequences and 142
collateral information have been deposited in BOLD (Ratnasingham and Hebert 2007) in 143
the project BICA "Barcoding Indonesian Crustaceans" (Table S2) and DNA sequences 144
were submitted to GenBank (Accession numbers MN526034 to MN526237). 145

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147 DNA-based species delimitation and genetic diversity

148
The DNA barcode reference library was first analyzed to check for a potential
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mismatch between species delimitation hypotheses based on morphological characters
150
and DNA barcodes. DNA sequences divergence was calculated using the Kimura 2-
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parameter (K2P) model (Kimura 1980) and further used to construct a mid-point rooted
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Neighbor-Joining (NJ) tree to provide a graphic representation of the species divergence
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as implemented in the Sequence Analysis module of BOLD (Ratnasingham and Hebert
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2007). Sequence divergence was considered below and above species boundaries by
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calculating the maximum intraspecific distance and the minimum interspecific distance.
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The distribution of both distances was examined through bins of 1% to visualize a
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potential overlap between intraspecific and interspecific genetic distances. The presence
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of a barcoding gap, that is the absence of overlap between the distributions of the
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maximum intraspecific and the minimum interspecific distance (Meyer and Paulay
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2005), was further checked by plotting both distances for each species. For each species,
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Haplotype diversity (h) and nucleotide diversity (π) were calculated using the R package
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pegas 0.1 (Paradis 2010). 163

Several alternate methods have been proposed for delimitating molecular
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lineages that all have in common to detect departure from mutation-drift equilibrium in
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branching events (Pons et al. 2006; Puillandre et al. 2012; Ratnasingham and Hebert
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2013; Kekkonen and Hebert 2014). Each of these methods is prone to pitfalls and
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combining different approaches is increasingly used to circumvent potential pitfalls
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arising from, for instance, uneven sampling among species (Kekkonen and Hebert 2014;
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Kekkonen et al. 2015; Blair and Bryson 2017). We used four sequence-based methods of
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species delimitation to establish a final delimitation scheme based on a 50 percent
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consensus among methods. For the sake of clarity, species identified based on
morphological characters are referred to as morphological species, while species
delimited by DNA sequences are referred to as Operational Taxonomic Units (OTU),
defined as diagnosable molecular lineages (Avise 1989; Moritz 1994; Vogler and DeSalle
1994). OTUs were delimitated using the following algorithms: (1) Refined Single
Linkage (RESL) as implemented in BOLD and used to produce Barcode Index Numbers
(BIN) (Ratnasingham and Hebert 2013a), (2) Automatic Barcode Gap Discovery (ABGD)
(Puillandre et al. 2012b) using the initial DNA sequence alignment, (3) Poisson Tree
Process (PTP) in its multiple rates version (mPTP) as implemented in the stand-alone
software mptp_0.2.3 (Zhang et al. 2013; Kapli et al. 2017), and (4) General Mixed Yule-
Coalescent (GMYC) in its multiple rate version (mGMYC) as implemented in the R
package Splits 1.0-19 (Fujisawa and Barraclough 2013).

The mPTP algorithm uses a phylogenetic tree as an input file, thus, a Maximum
Likelihood (ML) tree was first reconstructed using RAxML (Stamatakis 2014) based on a
GTR+I substitution model. An ultrametric and fully resolved tree was also reconstructed
using the Bayesian approach implemented in BEAST 2.4.8 (Bouckaert et al. 2014) to be
further used for OTUs delineation using the mGMYC algorithm. The best-fit substitution
model for the Bayesian analysis was selected using JMODELTEST 2.1.7 (Darriba et al.
2012). Two markov chains of 10 million each were run independently using a Yule pure
birth model tree prior with the monophyly of each genera enforced. Previous
substitution rate estimates for shrimps mitochondrial genes ranged from 1.1%/Myr to
1.4%/Myr (Knowlton et al. 1992; Knowlton and Weigt 1998). These estimates are close
to the 1.2%/Myr substitution rate that have been previously observed at COI for
vertebrates (Bermingham et al. 1997). BEAST reconstructions were done using a
relaxed clock exponential model with a canonical 1.2%/Myr substitution rate. Trees
were sampled every 5,000 states after an initial pre-burning period of 1 million, and
both runs were combined using LogCombiner 2.4.8 (Bouckaert et al. 2014) after a burn
in period of 10% of the sampled trees. The maximum credibility tree was constructed
using TreeAnnotator 2.4.7 (Bouckaert et al. 2014). Duplicated sequences were removed
prior to the Bayesian analysis using RAxML.

Once OTUs were delineated, the potential impact of cryptic diversity,
introgressive hybridization or overlapping morphological characters was estimated by
examining the distribution of genetic distances for the morphology-based and DNA-
based delimitation schemes. We further quantified the match among methods and their
relative power using the *match ratio* and the Relative Taxonomic Index of Congruence index (*R*<sub>tax</sub>) following Blair and Bryson (Blair and Bryson 2017). The match ratio is a measure of concordance among methods and is defined as twice the number of matches divided by the sum of the number of delimitated OTUs and the number of morphological species (Arhens et al. 2016). The *R*<sub>tax</sub> index quantifies the relative power of a method to infer all estimated speciation events and is defined as the number of speciation events identified by a method divided by the total number of speciation events identified by the different methods (Miralles and Vences 2013).

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## Species co-occurrence and phylogenetic relatedness within communities

Morphological species and OTU occurrences were recorded across the 19 sampling sites (Fig. 1A; Tables S1 & S2). A hierarchical cluster of sites was established based on dissimilarities in species occurrence using the R package Vegan (Oksanen et al. 2007). The significance of the correlation between dissimilarity and geographic distance among sites was tested with a Mantel test (Mantel 1967). The matrix of geographic distance was derived from the geographic coordinates using the R package Geosphere (Hijmans et al. 2016). Patterns of species aggregation were further explored using the probabilistic model of Veech (Veech 2013) as implemented in the R package Cooccur (Griffith et al. 2016). This approach provides the expected probabilities of species co-occurrence under a null model of random association that can be used to identify departures related to repulsion or association dynamics among species.

The signature of non-random dynamics of species co-occurence on species phylogenetic relatedness within communities was examined by calculating the Mean Phylogenetic Distance (i.e. MPD, the average phylogenetic distance among species within sites) and the Mean Nearest Taxon Distance (i.e. MNTD, the average phylogenetic distance among the most closely related species within sites) as implemented in the R package Picante (Kembel et al. 2010). The departure of phylogenetic distances from those expected under random patterns of species co-occurence was calculated based on 1000 random samplings of species from the regional pool. A hierarchical cluster based on the matrix of average phylogenetic distance among sites was further established using the R Stats ver. 3.1.2 package (R_Core_Team 2014). The correlation between average phylogenetic distance and geographic distance among sites was tested through a Mantel test (Mantel 1967).

238
239 **RESULTS**

240 **DNA barcoding, genetic divergence and species delimitation**

241 A total of 1583 specimens was collected across the 19 sampling sites visited.
242 Identifications based on the taxonomic keys established by Cai (Cai 2003) and Wowor
243 (Wowor 2004) resulted in the delimitation of 23 morphological species out of which a
244 single ALD species was observed, *Macrobrachium pilimanus* (De Man, 1879) in Java (Fig.
245 1A, sites 1, 2, 3 and 5). The species accumulation curve indicates that a ceiling has been
246 reached for morphological species, hence suggesting that a comprehensive sample of the
247 species diversity has been obtained (Fig. 1B). A set of 204 sequences was successfully
248 obtained. All the sequences were above 500 bp of length and no codon stops were
249 detected, suggesting that the sequences collected represent functional coding regions.
250 Large levels of genetic divergence are observed within morphological species as the
251 mean genetic distance peaks at 4.77% between conspecifics and reaches 27.68% when
252 considering the maximum distance (Table 1, Figs. 2A & 2D). These values overlap those
253 observed among morphological species within genera as the mean genetic distance
254 reaches 24.8% among congeneric morphological species. The inspection of the NJ tree
255 confirmed this general trend and indicates that the high genetic distances within
256 morphological species are due to deep divergences in 5 taxa (Fig. S1). Haplotype sharing
257 is also observed as 0 minimum genetic distances are detected among congeneric
258 morphological species (Table 1). The NJ tree highlights three mismatches between
259 individual assignments based on morphology and sequences clustering, including
260 *Caridina typus* H. Milne-Edwards, 1837 with an individual nested within *C. brachydactyla*
261 De Man, 1908, *C. appendiculata* Jalihal & Shenoy, 1998 with an individual nested within
262 *C. brachydactyla*, and *C. papuana* Nobili, 1905 with an individual nested within *C.
263 serratirostris* De Man, 1892 (Fig. S1).

264 The number of delimitated OTUs ranged from 30 with ABGD to 33 with mGMYC
265 (Fig. 3, Table 2), with 18 morphological species displaying fully convergent delimitation
266 scheme across all methods, 2 morphological species with one method yielding
267 conflicting results (*Caridina gracilipes* De Man, 1892 and *C. peninsularis* Kemp, 1918)
268 and 3 morphological species with conflicting scheme among methods (*C. gracilirostris*
269 De Man, 1892, *Macrobrachium esculentum* (Thallwitz, 1891) and *M. pilimanus*). The
270 consensus delimitation scheme identified 30 OTUs within the 23 morphological species
271 recognized here, with 19 morphological species displaying 1 OTU, 2 morphological
272 species displaying 2 OTUs (*C. brachydactyla*, *C. gracilipes*), 1 morphological species
displaying 3 OTUs (C. papuana) and 1 morphological species displaying 4 OTUs (M. pilimanus). The match ratio was similar among methods ranging from 0.63 for RESL to 0.679 in mGMYC with the highest value observed for the consensus delimitation scheme and the highest resolution power observed for mGMYC with a Rtax of 0.943 (Table 2).
Similarly to that of species, OTUs accumulation curves indicate that a ceiling has been reached (Fig. 1B).

The distributions of the maximum intra-specific and minimum inter-specific genetic distances confirmed the relative influence of cryptic molecular lineages and haplotype sharing in shaping genetic divergence patterns (Fig. 2). A first examination of the genetic distances based on morphological species confirms that the distributions of maximum intra-specific and minimum inter-specific distances largely overlap (Fig. 2A).
This trend was much less pronounced, however, if plotting both distances on an individual basis (Fig. 2D). Accounting for cryptic diversity by considering OTUs reduces the overlap between the distributions of the maximum intraspecific and minimum interspecific distances (Figs. 2B, 2E). Accounting for both cryptic diversity and the 3 cases of haplotype sharing further reduced the overlap (Fig. 2C), however, a barcoding gap is observed only if maximum intraspecific and minimum interspecific distances are plotted individually (Fig. 2F). Genetic diversity largely varies among morphological species with haplotype diversity ranging from 0 (C. brevicarpalis De Man, 1892, M. australe (Guérin & Méneville, 1838), M. bariense (De Man, 1892) and M. gracilirostre (Miers, 1875)) to 1 (C. celebensis De Man, 1892, C. gracilirostris, C. weberi De Man, 1892 and M. pilimanus) and nucleotide diversity ranging from 0 (C. brevicarpalis, M. australe (Guérin-Méneville, 1838), M. bariense and M. gracilirostre) to 0.081 (M. pilimanus) (Table 2).

## Species richness and co-occurrence

The species richness varies among sites, ranging from 1 morphological species for 6 of the visited sites to 8 morphological species for one site (Fig. 4A). Species commonness also largely varies with 9 morphological species distributed in a single site and one morphological species distributed in 8 sites (Fig. 4C). The distribution of OTUs richness per sites is similar to that of morphological species (Fig. 4B), however, OTUs distribution is skewed toward rare OTUs present at a single site (Fig. 4D). The hierarchical cluster recovered using sites dissimilarity based on OTUs occurrence clearly separates sites 1, 2, 4 and 5 (Fig. 5A) that correspond to the sites hosting *M. pilimanus* OTUs with an ALD
strategy (Fig. 3). Clustering patterns among sites hosting OTUs with ELD strategies show no clear trends, however, a significant correlation between sites dissimilarity and geographic distance was detected (Mantel test; *p*-value = 0.003). The analysis of species co-occurrence using the probabilistic model of Veech (2013) revealed that, out of the 435 pairs of OTUs analyzed, only 6 were significantly associated (Fig. 5B). This co-occurrence analysis was further performed on the two larval development categories (ELD, ALD) and resulted in a significant departure of the observed co-occurrence from expected at random (observed probability = 0, expected probability = 0.166, *p*-value < 0.001). The OTUs show no clear relationship with their distribution between islands and across the 19 sites (Fig. 3). Examining the distribution of species phylogenetic relatedness within sites returned non-significant departures from expected by chance of the Mean Phylogenetic Distance (MPD) and Mean Nearest Taxon Distance (MNTD) (Table 3). The hierarchical cluster constructed using the average phylogenetic distances among sites, and derived from the Bayesian tree, clearly separates sites 1, 2, 4 and 5 that host *M. pilimanus* with an ALD strategy (Fig. 5C). The correlation between the average phylogenetic and geographic distances among sites was significant (Mantel test, *p*-value = 0.009).

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# DISCUSSION

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## Species co-occurrence and phylogenetic community structure are consistent with a lottery model of recruitment and community assembly

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The lack of significant departure of the species phylogenetic relatedness within communities is consistent with a lottery model of recruitment as previously described for communities where stochastic dispersal is sustained by early stages of the life cycle such as in coral reef fishes (Sale 1977; Sale and Dybdal 1978; Sale and Williams 1982; Hubert et al. 2011) or tropical trees (Webb 2000; Hubbell 2001). This pattern was expected considering that 95% of the visited sites host communities composed exclusively of ELD species dispersing through their early life stages. In fact, ELD species invest their reproductive effort into producing many offspring at the cost of low survival rates, usually resulting in stochastic fluctuations of recruitment success and population size through time (Gotelli 1991; Hanski 1991). In such biological models, dispersal occurs at random and species turnover is a function of geographic distance among connected sites (Hubbell 2001; Alonso et al. 2006; Chisholm and Lichstein 2009). The detection of a significant correlation between sites dissimilarity or average phylogenetic
distance among sites and geographic distance seems to confirm that dispersal is limited to a random diffusion into neighboring watersheds. This pattern is surprising, however, considering that most ELD species sampled here have been reported outside of the study area, expanding into the neighboring Wallacea and Sahul provinces. The detection of high levels of cryptic diversity at the scale of the present study, however, questions the taxonomic status of the ELD species with large distribution ranges as recently highlighted (de Mazancourt et al. 2019). This pattern of isolation by distance may have several origins depending on the relative contribution of historical contingency during community assembly and colonization that usually produces stable patterns through time, and the stochasticity of a lottery model eventually leading to a dynamic equilibrium between dispersal and extinction (Emerson and Gillespie 2008; Vamosi et al. 2009; Hubert et al. 2011). Considering the species age inferred here, the persistence of small-size populations through millions of years is unlikely, particularly so in changing landscapes such as those of Java and Bali islands that have experienced major rearrangements during their history through volcanic activities and associated geological changes (Lohman et al. 2011). The present pattern seems consistent with a dynamic equilibrium between dispersal and extinction and the isolation by distance pattern is likely to result from limited random diffusion of larvae into neighboring watersheds.

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361 **No evidence that species diversification and current co-existence are driven by**
362 **the same mechanisms**

363 The settlement of Sundaland in its modern configuration happened during the
364 last 10 Myr and was initiated with the isolation of Borneo from the SEA continent
365 through tectonic plate drift (Lohman et al. 2011). The final establishment of Sundaland,
366 particularly the southern part including Java and the lesser Sunda island (e.g. Bali), is
367 much more recent and happened during the last 5 Myr. Recent phylogeographic studies
368 on primary freshwater organisms in South Sundaland suggest that the settlement of the
369 populations of Java and Bali started at 3myr and most populations were fragmented
370 during the last glacial cycle (Hutama et al. 2017; Hubert et al. 2019). In addition, several
371 cases of *in situ* diversification were previously reported for primary freshwater fishes in
372 Java (Hutama et al. 2017; Hubert et al. 2019). The present study shows a markedly
373 distinct pattern that is likely to be due to the peculiar dispersal strategies of *Caridina*
374 and *Macrobrachium* that disperse through the diffusion of their early life stages in the
375 marine environment. In fact, the present study shows no evidence of interactions
376 between the mechanisms of species diversification and species co-existence. The ages of
377 most of the morphological species referred to here expand beyond the estimated age of
378 settlement of Sundaland and Lesser Sunda Islands, which started around 10 Myr
379 (Lohman et al. 2011). Except for the 2 OTUs within *C. peninsularis* and *C. gracilipes*, the
380 species pair including *M. bariense* and *M. esculentum* and 3 OTUs in *M. pilimanus*, most
381 species are older than 10 Myr and actually predate the settlement of Sundaland Islands.
382 Furthermore, previous cases of *in situ* diversification among freshwater species
383 described in Java are consistent with a marked influence of landscape fragmentation
384 through the rise of volcanic arches, resulting in allopatric distribution between sister-
385 species (Hutama et al. 2017; Hubert et al. 2019). The dominance of geographic
386 speciation through allopatric divergence was also reported for other freshwater species
387 at wider spatial scales in Sundaland (De Bruyn et al. 2005, 2013). Such mechanisms of
388 species proliferation might be expected to impact species co-occurrence patterns and
389 phylogenetic community structure, resulting in phylogenetic over-dispersal (Hubert et
390 al. 2011) and negative species associations. The present pattern of lottery assembly and
391 species age inferred here suggest that mechanisms of species proliferation and
392 community assembly do not overlap in space and time for the *Caridina* and
393 *Macrobrachium* communities in Java and Bali.
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Potential evolutionary consequences of life history traits on the accumulation of
genetic divergence and species occurrence

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397 The present study evidences several cases of deep genetic divergence within
398 morphological species, a trend that has been previously described for several shrimp
399 families including Atyidae (Baker et al. 2004; Page and Hughes 2007; von Rintelen et al.
400 2007; von Rintelen et al. 2010) and Palaemonidae (De Bruyn et al. 2005; Liu et al. 2007;
401 Wowor et al. 2009; Castelin et al. 2017). Several cases of morphologically similar, yet
402 genetically divergent, lineages are identified, particularly in *Macrobrachium pillimanus*,
403 the only species of the present study characterized by an ALD strategy. Larvae of species
404 with ALD strategy are bottom-dwellers with only a few zoeal stages that show little
405 tolerance to salinity fluctuations and as such, have limited dispersal abilities (Wowor et
406 al. 2009). This larval development may be expected to increase population
407 differentiation by limiting gene flow among populations and to induce faster rates of
408 genetic drift (Kimura 1983; Tajima 1983). The detection of highly divergent OTUs in *M*.

400

401

402

403

404

405

406

407

408
409 *pillimanus*, all restricted to a single watershed, and the high haplotype and nucleotide diversities seem to confirm that the species is accumulating genetic diversity at a faster rate than other species with ELD strategies.
410
411

The co-occurrence and distribution patterns of *M. pillimanus* also depart from those observed for ELD species that are usually restricted to a single site and largely co-exist with other ELD species. *Macrobrachium pillimanus* is one of the few species observed at multiple sites and is the only species that was not sampled together with other *Caridina* and *Macrobrachium* species. This pattern suggests that ALD and ELD strategies do not co-occur within sites despite their contiguous distributions within the same watersheds. In fact, species with ALD strategy exhibit faster growth rates during their early life stages as a consequence of both higher energetic stocks due to the large size of the eggs and less energy invested into zoeal metamorphoses (Cai 2003; Wowor et al. 2004). From an ecological perspective, their limited dispersal abilities due to their abbreviated larval stages might be balanced by higher competitive skills, a trade-off that may translate into a competition/colonization trade off (Calcagno et al. 2006; Logue et al. 2011).

425

426 Potential limits and perspectives

Several limitations of our study, which may have confounding effects on the interpretation of present results, should be acknowledged. Species age estimates are particularly old considering the age of the geological context of Sundaland and the globally limited range distribution observed here for both *Caridina* and *Macrobrachium* species. It is likely that our species age estimates are inflated due to the limited spatial scope of the study and the lack of actual sister species, however, this potential bias involves speciation events that happened at a wider spatial scale than examined here (de Mazancourt et al. 2019). Along the same line, deep divergence and old age of cladogenetic events have been previously reported for the families Atyiidae and Palaemonidae, a trend that is consistent with the present phylogenetic inferences (Page and Hughes 2007; von Rintelen et al. 2007; de Mazancourt et al. 2019). Expanding the spatial scope might be expected to add more closely related species and lead to more accurate species age estimates. It is unlikely, however, that the results on phylogenetic community structure will be affected at the scale under scrutiny as the metrics were used to detect potential departure from random species aggregation through randomization procedures, and our inferences were not based on the absolute values of
these metrics. As such, our results are more prone to bias due to diversity gaps during
sampling than to phylogenetic inferences *per se*. The accumulation curves for both
species and OTUs show, however, that a ceiling was reached, and significant bias due to
a substantial amount of unsampled species is unlikely. Along the same line, it should be
acknowledged that Sundaland ecosystems have been significantly disrupted during the
last decades (Schipper et al. 2008; Hoffman et al. 2010). In Java for instance, numerous
dams have been constructed for the cultivation of rice in terraces. These dams are
usually built for irrigation purposes and consist of structures a few meters high with a
moderate slope and a constant flow of freshwater throughout the year. Many of these
dams have been visited during the present survey, and ELD species have been collected
upstream of many of those structures. In addition, species with ELD strategies are able
to climb large waterfalls (Keith et al. 2010, 2013; de Mazancourt et al. 2017) and as such,
anthropogenic perturbations *per se* are unlikely to account for the present patterns of
species co-occurrence.

The main limit of the present study is the scarcity of ALD species and replicates of
sites including them. Three of the four OTUs detected in *M. pillimanus* correspond to a
single sequence (i.e. singleton), that exhibits high genetic divergence ranging from 1.3 to
5.5% (BOLD:ACS9506, BOLD:ACS9365, BOLD:ACS9366). Highly divergent singletons are
varyingly delineated as independent lineages by the available algorithms of species
delimitation (Fujisawa and Barraclough 2013; Kekkonen and Hebert 2014; Kekkonen et
al. 2015), and the conflicting delimitation schemes recovered by the four methods
confirm the difficulties in accurately delimitating OTUs represented by a singleton. As
such, the validity of the OTUs consisting in singletons call for a specific assessment
based on more comprehensive sampling schemes. Along the same line, the generality of
a potential competition/colonization trade-off between ALD and ELD species calls for a
broader assessment at larger spatial scales with ALD species replicates.

CONCLUSION

The present study highlights the complexity of the interactions between spatial and
temporal scales and their consequences on species co-occurrence and diversity patterns
in Java and Bali communities of *Macrobrachium* and *Caridina*. The lack of ALD replicates
in the present study limits the exploration of the eco-evolutionary consequences of
reproductive strategies on species co-occurrence; however, the spatial segregation of *M.
pilimanus* from other ELD species within the same watersheds suggests that the
477 coexistence of species with varying reproductive strategies might be driven by a
478 competition/colonization trade off. For ELD species, however, a pattern of random co-
479 occurrence is observed that matches a lottery model of recruitment as expected for r
480 strategists. From a molecular evolutionary perspective, the higher genetic distances and
481 nucleotidic diversity in *M. pilimanus* suggest that ALD species accumulates genetic
482 diversity at a faster rate, potentially as a consequence of their lower dispersal abilities,
483 hence higher fragmentation of the populations, and potentially smaller population sizes.
484 In the absence of information about local scale community ecology dynamics among
485 freshwater shrimps of insular SEA, this study provides crucial clues about community
486 dynamics that point to several aspects that will deserve more attention in the near-
487 future, such as the geographic scale of speciation and its potential influence on
488 community assembly.
489

489

490 Acknowledgements

491 The authors wish to thank Dr. Siti Nuramaliati Prijono, Dr. Bambang Sunarko, Dr.
492 Witjaksono, Mohammad Irham Msc., Dr. Marlina Adriyani, Ruliyana Susanti, Dr.
493 Rosichon Ubaidillah, Dr. Hari Sutrisno and Muhamad Syamsul Arifin Zein Msc. at
494 Research Centre for Biology (RCB-LIPI); Jean-Paul Toutain, Robert Arfi, Valérie Verdier
495 and Jean-François Agnès from the ‘Institut de Recherche pour le Développement’; Joel
496 Le Bail and Nicolas Gascoin at the French embassy in Jakarta for their continuous
497 support. We are thankful to late Renny Kurnia Hadiaty and Sopian Sauri at RCB-LIPI,
498 Sumanta at IRD Jakarta for their help during the field sampling in East Java and Bali. Part
499 of the present study was funded by the Institut de Recherche pour le Développement
500 (UMR226 ISE-M and IRD through incentive funds), the MNHN (UMR BOREA), the RCB-
501 LIPI, the French Ichthyological Society (SFI), the Foundation de France and the French
502 embassy in Jakarta. The Indonesian Ministry of Research and Technology approved this
503 study and field sampling was conducted according to the research permits
504 097/SIP/FRP/SM/IV/2014 for Philippe Keith, 60/EXT/SIP/FRP/SM/XI/2014 for
505 Frédéric Busson and 41/EXT/SIP/FRP/SM/VIII/2014 for Nicolas Hubert. Sequence
506 analysis was aided by funding from the government of Canada through Genome Canada
507 and the Ontario Genomics Institute in support of the International Barcode of Life
508 project. We thank Paul Hébert and Evgeny Zakharov as well as BOLD and CCDB staffs at
509 the University of Guelph for their valuable support. We are also very grateful to our
510 editor, Diego Fontaneto, as well as the two anonymous reviewers for their insightful
511 feedbacks on the earlier version of the manuscript. This publication has ISEM number
512 2019-189 SUD.

513

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761 Wowor, D., V. Muthu, R. Meier, M. Balke, Y. Cai, and P. K. L. Ng. 2009. Evolution of life history traits in Asian freshwater prawns of the genus Macrobrachium (Crustacea: Decapoda: Palaemonidae) based on multilocus molecular phylogenetic analysis. Mol. Phylogenet. Evol. 52:340–350.

765 Zhang, J., P. Kapli, P. Pavlidis, and A. Stamatakis. 2013. A general species delimitation method with applications to phylogenetic placements. Bioinformatics 29:2869–2876.
<figure><img src="image_3.png" /></figure>

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**Fig. 1** Sampling scheme. A, location of the 19 collection sites visited during the present study. B, accumulation curves for species (green) and OTUs (blue).

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<figure><img src="image_4.png" /></figure>

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**Fig. 2** Summary distributions of K2P genetic distances including the maximum intraspecific and minimum interspecific distances. A, B and C, distribution of maximum intraspecific and minimum interspecific distances. D, E and F, plotting of maximum intraspecific and minimum interspecific. A and D, based on morphological species. B and E, based on Operational Taxonomic Units (OTUs). C and F, based on OTUs and excluding the three cases of conflicting assignment between morphology and DNA barcodes clustering.

783
<figure><img src="image_5.png" /><figcaption>**Fig. 3** Bayesian chronogram constructed using 654 bp of the mitochondrial Cytochrome oxidase I gene including 95% Highest Posterior Density intervals for median node ages, Barcode Index Numbers (BINs), species delimitation schemes based on RESL (BIN), ABGD, mPTP, mGMYC and the consensus scheme (Final), species and OTUs distribution across the 19 sites. Larval development categories refer to the Abbreviated Larval Development (ALD) in brown and Elongated Larval Development (ELD) in green. Elevation categories correspond to the maximum elevation observed per OTUs and separated into classes of 100m ranging from 0-100m in yellow, 201-300m in red and above 301m in brown. Distribution of each OTU is given across the 19 sites sampled with presence represented by black square and absence represented by white square. Sites in yellow correspond to Java Island, sites in green to Bali Island. Reconstruction based on the 140 unique sequences selected using RAxML. ¹, including specimen BICA146-14 of *C. appendiculata* and specimen BICA114-14 of *C. typus*. ², including specimen BICA051-14 of *C. papuana*.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Fig. 4** Distribution of species and OTUs richness per site, A and B respectively, and distribution of species and OTUs across the 19 sites, C and D respectively.</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>**Fig. 5** Analysis of beta-diversity among sites and co-occurrence patterns including the hierarchical cluster based on dissimilarity matrix among sites (A), Veech (2013) matrix of co-occurrence (B) and average phylogenetic distance among sites (C). Only OTUs involved in pairwise comparisons with co-occurrence patterns departing from expected at random at included (C).</figcaption></figure>
Table 1 Summary statistics of the K2P genetic distances among sequences within species and among species within genus including minimum, mean and maximum distances.

<table><thead><tr><th></th><th>n</th><th>Taxa</th><th>Comparisons</th><th>Min Dist(%)</th><th>Mean Dist(%)</th><th>Max Dist(%)</th><th>SE Dist(%)</th></tr></thead><tbody><tr><td>Within Species</td><td>201</td><td>20</td><td>1585</td><td>0</td><td>4.87</td><td>28.02</td><td>0.01</td></tr><tr><td>Within Genus</td><td>204</td><td>2</td><td>11421</td><td>0</td><td>24.76</td><td>32.54</td><td>0</td></tr></tbody></table>

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<table><caption>**Table 2** Summary statistics of *Caridina* and *Macrobrachium* species genetic diversity and species delimitation schemes. *n*, number of individual sequences analyzed. Max. K2P distance, maximum K2P genetic distance (percent). Min. Nearest Neighbor K2P distance (percent), minimum K2P genetic distance to the nearest phylogenetic neighbor (percent) in the present data set. *h*, haplotype diversity. *π*, nucleotide diversity. match ratio, twice the number of match divided by the sum of the number of delimitated OTU and the number of morphological species. Rtax, number of speciation events identified by a method divided by the total number of speciation events identified by the different methods.</caption><thead><tr><th rowspan="2">Taxon</th><th rowspan="2">n</th><th rowspan="2">Max. K2P distance</th><th rowspan="2">Min. Nearest Neighbor K2P distance</th><th colspan="2">h</th><th colspan="2">ABG</th><th colspan="2">mPT</th><th colspan="2">mGMY</th><th rowspan="2">Consensus</th></tr><tr><th>h</th><th>π</th><th>D</th><th>P</th><th>C</th></tr></thead><tbody><tr><td>Caridina appendiculata</td><td>17</td><td>23.74</td><td>0</td><td>0.85</td><td>0.02</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Caridina brachidactyla</td><td>24</td><td>22.01</td><td>0</td><td>0.35</td><td>0.05</td><td>2</td><td>2</td><td>2</td><td>2</td><td>2</td><td>2</td></tr><tr><td>Caridina brevicarpalis</td><td>5</td><td>0</td><td>21.03</td><td>0</td><td>0.00</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Caridina celebensis</td><td>2</td><td>0.37</td><td>20.58</td><td>0.81</td><td>0.06</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Caridina endehensis</td><td>7</td><td>28.02</td><td>0</td><td>0.88</td><td>0.01</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Caridina gracilipes</td><td>9</td><td>3.64</td><td>17.56</td><td>0.01</td><td>0.01</td><td>2</td><td>2</td><td>2</td><td>1</td><td>2</td><td>2</td></tr><tr><td>Caridina gracilirostris</td><td>5</td><td>2.34</td><td>22.65</td><td>0.86</td><td>0.11</td><td>2</td><td>1</td><td>1</td><td>3</td><td>1</td><td>1</td></tr><tr><td>Caridina papuana</td><td>26</td><td>25.04</td><td>0</td><td>0.00</td><td>0.00</td><td>3</td><td>3</td><td>3</td><td>3</td><td>3</td><td>3</td></tr><tr><td>Caridina peninsularis</td><td>4</td><td>0.68</td><td>7.15</td><td>0.69</td><td>0.00</td><td>1</td><td>2</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Caridina serratirostris</td><td>16</td><td>1.22</td><td>0</td><td>0.33</td><td>0.00</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Caridina sp</td><td>6</td><td>0.15</td><td>17.53</td><td>0.85</td><td>0.01</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Caridina typus</td><td>30</td><td>27.68</td><td>0</td><td>0.00</td><td>0.00</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Caridina weberi</td><td>3</td><td>0.46</td><td>21.72</td><td>0.00</td><td>0.00</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Macrobrachium australe</td><td>8</td><td>0</td><td>20.48</td><td>0</td><td>0.00</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Macrobrachium bariense</td><td>2</td><td>0</td><td>2.51</td><td>0.53</td><td>0.00</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Macrobrachium esculentum</td><td>10</td><td>0.62</td><td>2.51</td><td>0.00</td><td>0.00</td><td>1</td><td>2</td><td>2</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Macrobrachium gracilirostre</td><td>2</td><td>0</td><td>16.88</td><td>0.89</td><td>0.00</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Macrobrachium horstii</td><td>14</td><td>0.65</td><td>16.88</td><td>0.90</td><td>0.00</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Macrobrachium lar</td><td>5</td><td>0.77</td><td>18.31</td><td>0.00</td><td>0.00</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Macrobrachium latidactylus</td><td>1</td><td>-</td><td>17.96</td><td>-</td><td>-</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Macrobrachium lepidactyloides</td><td>1</td><td>-</td><td>19.38</td><td>-</td><td>0.08</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Macrobrachium pilimanus</td><td>6</td><td>12.97</td><td>17.39</td><td>0.00</td><td>0.00</td><td>4</td><td>2</td><td>5</td><td>6</td><td>4</td><td>4</td></tr><tr><td>Macrobrachium scabriculum</td><td>1</td><td>20</td><td>15.58</td><td>-</td><td>-</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Total</td><td>4</td><td>-</td><td>-</td><td>-</td><td>-</td><td>31</td><td>30</td><td>32</td><td>33</td><td>30</td><td>30</td></tr><tr><td>match ratio</td><td>-</td><td>-</td><td>-</td><td>-</td><td>0.63</td><td>2</td><td>5</td><td>0.679</td><td>0.717</td><td>-</td><td>-</td></tr><tr><td>Rtax</td><td>-</td><td>-</td><td>-</td><td>-</td><td>0.88</td><td>0.85</td><td>0.91</td><td>0.943</td><td>0.857</td><td>-</td><td>-</td></tr></tbody></table>
**Table 3** Summary statistics of the phylogenetic community structure analysis including the number of taxa included in the computations (N taxa), the observed Mean Phylogenetic Distance (MPDobs), the average Mean Random Phylogenetic Distance estimated based on random assortment of species (MPDrandmean) and its standard deviation (MPDrandsd), the standardized deviation of MPD from expected at random (MPDobs.z) and its significance level (MPD.OBS.P), the Mean Nearest Taxon Distance (MNTD) observed (MNTDobs), average of expected values based on random assortment of species (MNTDrand.mean) and its standard deviation (MNTDrand.sd), the standardized deviation of MNTD from expected at random (MNTDobs.z) and its significance (MNTDobs.p). A total of 1000 random rearrangements of species per site were conducted to estimate the significance of the departures observed.

<table><thead><tr><th>Site</th><th>ntax</th><th>mpd.o</th><th>mpdrand.m</th><th>mpdrand.sd</th><th>mpdob</th><th>mpdobs.p</th><th>mntd.o</th><th>mntdrand.m</th><th>mntdrand.sd</th><th>mntdob</th><th>mntdobs.p</th><th>run</th></tr><tr><th>s</th><th>a</th><th>bs</th><th>ean</th><th>ean</th><th>s.z</th><th>p</th><th>bs</th><th>ean</th><th>sd</th><th>s.z</th><th>p</th><th>s</th></tr></thead><tbody><tr><td>1</td><td>1</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>100</td></tr><tr><td>2</td><td>1</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>100</td></tr><tr><td>3</td><td>1</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>100</td></tr><tr><td>4</td><td>7</td><td>114.63</td><td>118.88</td><td>6.35</td><td>-0.67</td><td>0.19</td><td>57.13</td><td>76.33</td><td>13.24</td><td>-1.45</td><td>0.09</td><td>100</td></tr><tr><td>5</td><td>1</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>100</td></tr><tr><td>6</td><td>5</td><td>125.30</td><td>119.00</td><td>10.08</td><td>0.62</td><td>0.72</td><td>86.68</td><td>86.92</td><td>16.69</td><td>-0.01</td><td>0.42</td><td>100</td></tr><tr><td>7</td><td>3</td><td>121.80</td><td>118.54</td><td>18.60</td><td>0.18</td><td>0.44</td><td>114.82</td><td>103.82</td><td>22.79</td><td>0.48</td><td>0.66</td><td>100</td></tr><tr><td>8</td><td>1</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>100</td></tr><tr><td>9</td><td>4</td><td>119.40</td><td>119.78</td><td>11.83</td><td>-0.03</td><td>0.40</td><td>85.94</td><td>94.23</td><td>19.44</td><td>-0.43</td><td>0.27</td><td>100</td></tr><tr><td>10</td><td>8</td><td>125.30</td><td>118.90</td><td>5.94</td><td>1.08</td><td>0.93</td><td>85.83</td><td>71.75</td><td>12.45</td><td>1.13</td><td>0.87</td><td>100</td></tr><tr><td>11</td><td>3</td><td>121.80</td><td>119.12</td><td>18.07</td><td>0.15</td><td>0.44</td><td>114.82</td><td>104.12</td><td>24.04</td><td>0.44</td><td>0.63</td><td>100</td></tr><tr><td>12</td><td>2</td><td>107.84</td><td>119.88</td><td>29.48</td><td>-0.41</td><td>0.27</td><td>107.84</td><td>119.21</td><td>30.64</td><td>-0.37</td><td>0.27</td><td>100</td></tr><tr><td>13</td><td>2</td><td>107.84</td><td>118.44</td><td>30.36</td><td>-0.35</td><td>0.29</td><td>107.84</td><td>118.53</td><td>31.06</td><td>-0.34</td><td>0.28</td><td>100</td></tr><tr><td>14</td><td>6</td><td>115.17</td><td>119.17</td><td>8.05</td><td>-0.50</td><td>0.23</td><td>61.62</td><td>80.46</td><td>15.09</td><td>-1.25</td><td>0.12</td><td>100</td></tr><tr><td>15</td><td>3</td><td>99.69</td><td>118.32</td><td>19.17</td><td>-0.97</td><td>0.14</td><td>87.24</td><td>104.18</td><td>23.64</td><td>-0.72</td><td>0.19</td><td>100</td></tr><tr><td>16</td><td>5</td><td>106.55</td><td>118.63</td><td>10.52</td><td>-1.15</td><td>0.14</td><td>88.87</td><td>85.53</td><td>17.33</td><td>0.19</td><td>0.53</td><td>100</td></tr><tr><td>17</td><td>1</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>100</td></tr><tr><td>18</td><td>4</td><td>120.50</td><td>119.40</td><td>11.89</td><td>0.09</td><td>0.45</td><td>80.46</td><td>94.36</td><td>19.61</td><td>-0.71</td><td>0.23</td><td>100</td></tr><tr><td>19</td><td>5</td><td>124.94</td><td>119.09</td><td>9.89</td><td>0.59</td><td>0.69</td><td>96.97</td><td>86.82</td><td>16.90</td><td>0.60</td><td>0.70</td><td>100</td></tr></tbody></table>

836

837
838 **Fig. S1** Neighbour Joining phenogram based on the 204 individual COI sequences.

839
840 **Table S1** Occurrence data for the 23 species included in the present study and based on
841 1583 observations across 19 sites.

842
843 **Table S2** Details of BOLD records for the 204 specimens with a COI sequence.

844
845 **Table S3** Details of the species delimitation schemes.

846
847 **Table S4** Occurrence data for the 30 OTUs detected in the present study across the 19
848 sites.