Hidden biodiversity in Neotropical streams: DNA barcoding uncovers high endemicity of freshwater macroinvertebrates at small spatial scales

Abstract

Aquatic macroinvertebrates play a crucial role in freshwater ecosystems, but their diversity remains poorly known, particularly in the tropics. This “taxonomic void” limits our understanding of biodiversity patterns and processes in freshwater ecosystems, and the scale at which they operate. We used DNA barcoding to estimate lineage diversity (and the diversity of unique haplotypes) in 224 specimens of freshwater macroinvertebrates at a small spatial scale within the Panama Canal Watershed (PCW). In addition, we compiled available barcoding data to assess macroinvertebrate diversity at a broader spatial scale spanning the Isthmus of Panama. Consistently across two species delimitation algorithms (i.e., ABGD and GMYC), we found high lineage diversity within the PCW, with ~ 100–106 molecular operational taxonomic units (MOTUs) across 168 unique haplotypes. We also found a high lineage diversity along the Isthmus of Panama, but this diversity peaked within the PCW. However, our rarefaction/extrapolation approach showed that this diversity remains under-sampled. As expected, these results indicate that the diversity of Neotropical freshwater macroinvertebrates is higher than previously thought, with the possibility of high endemicity even at narrow spatial scales. Consistent with previous work on aquatic insects and other freshwater taxa in this region, geographic isolation is likely a main factor shaping these patterns of diversity. However, other factors such as habitat variability and perhaps local adaptation might be reshaping these patterns of diversity at a local scale. Although further research is needed to better understand the processes driving diversification in freshwater macroinvertebrates, we suggest that Neotropical streams hold a high proportion of hidden biodiversity. Understanding this diversity is crucial in the face of increasing human disturbance.

Full text

RESEARCH ARTICLE
Hidden biodiversity in Neotropical streams:
DNA barcoding uncovers high endemicity of
freshwater macroinvertebrates at small
spatial scales
Luis F. De Leo
´nID
1,2,3
*, Aydee
´CornejoID
4
, Ronnie G. Gavila
´nID
5,6
, Celestino AguilarID
2,3
1Department of Biology, University of Massachusetts Boston, Boston, MA, United States of America,
2Centro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Cientı
´ficas y Servicios
de Alta Tecnologı
´a (INDICASAT AIP), Panama
´, Repu
´blica de Panama
´,3Smithsonian Tropical Research
Institute, Balboa, Panama
´,4Instituto Conmemorativo Gorgas de Estudios de la Salud, Panama
´, Repu
´blica
de Panama
´,5Centro Nacional de Salud Pu
´blica, Instituto Nacional de Salud, Lima, Peru
´,6Escuela
Profesional de Medicina Humana, Universidad Privada San Juan Bautista, Lima, Peru
´
*luis.deleonreyna@umb.edu
Abstract
Aquatic macroinvertebrates play a crucial role in freshwater ecosystems, but their diversity
remains poorly known, particularly in the tropics. This “taxonomic void” limits our under-
standing of biodiversity patterns and processes in freshwater ecosystems, and the scale at
which they operate. We used DNA barcoding to estimate lineage diversity (and the diversity
of unique haplotypes) in 224 specimens of freshwater macroinvertebrates at a small spatial
scale within the Panama Canal Watershed (PCW). In addition, we compiled available bar-
coding data to assess macroinvertebrate diversity at a broader spatial scale spanning the
Isthmus of Panama. Consistently across two species delimitation algorithms (i.e., ABGD
and GMYC), we found high lineage diversity within the PCW, with ~ 100–106 molecular
operational taxonomic units (MOTUs) across 168 unique haplotypes. We also found a high
lineage diversity along the Isthmus of Panama, but this diversity peaked within the PCW.
However, our rarefaction/extrapolation approach showed that this diversity remains under-
sampled. As expected, these results indicate that the diversity of Neotropical freshwater
macroinvertebrates is higher than previously thought, with the possibility of high endemicity
even at narrow spatial scales. Consistent with previous work on aquatic insects and other
freshwater taxa in this region, geographic isolation is likely a main factor shaping these pat-
terns of diversity. However, other factors such as habitat variability and perhaps local adap-
tation might be reshaping these patterns of diversity at a local scale. Although further
research is needed to better understand the processes driving diversification in freshwater
macroinvertebrates, we suggest that Neotropical streams hold a high proportion of hidden
biodiversity. Understanding this diversity is crucial in the face of increasing human
disturbance.
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OPEN ACCESS
Citation: De Leo
´n LF, Cornejo A, Gavila
´n RG,
Aguilar C (2020) Hidden biodiversity in Neotropical
streams: DNA barcoding uncovers high endemicity
of freshwater macroinvertebrates at small spatial
scales. PLoS ONE 15(8): e0231683. https://doi.
org/10.1371/journal.pone.0231683
Editor: Michael A. Chadwick, King’s College
London, UNITED KINGDOM
Received: March 28, 2020
Accepted: July 8, 2020
Published: August 7, 2020
Copyright: ©2020 De Leo
´n et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: COI sequences
associated with this study are available in GenBank
(https://www.ncbi.nlm.nih.gov) under accession
numbers KX039451 - KX039650 and KU980966 -
KU981004. Data are also available on the Barcode
of Life Data System (BOLD systems, under project
code INVPA: http://www.boldsystems.org/).
Taxonomic and molecular diversity data have been
provided in Supporting information (S1 Table).
Funding: Financial support was provided by a grant
from the Consortium for the Barcode of Life to L. F.

Introduction
Aquatic macroinvertebrates are a fundamental component of freshwater environments. They
mediate important processes such as food web dynamics, energy flow, and nutrient cycling,
and therefore play a central role in sustaining the biodiversity and functioning of freshwater
ecosystems [1–3]. However, the diversity of Neotropical freshwater macroinvertebrates
remains poorly described, and even less is known about the processes that drive their diversity,
and the scale at which they operate [4]. For instance, despite considerable efforts by local tax-
onomists (e.g., [5–8], most of the published literature use genus and family as a standard taxo-
nomic unit for Neotropical macroinvertebrates (e.g., [9–14]. This is partially due to the
complexity of these communities, which are often composed of multiple life-stages existing at
the interface between the terrestrial and aquatic environment [15,16]. Another limitation is
the low efficiency of traditional morphological methods, which are generally time-consuming,
and highly variable in the quality of identification across taxa and experts.
This “taxonomic void” has important consequences for our general understanding of biodi-
versity patterns and processes, both in Neotropical environments and globally. For example,
species diversity is generally expected to increase at lower latitudes [17,18], but no consensus
has been reached for macroinvertebrates, given the current lack of taxonomic knowledge [19–
22]. Within the Neotropics, our current understanding of the drivers of species diversity in
benthic macroinvertebrates is also limited [23–25].
Similar to other freshwater taxa (e.g., [26,27], spatial isolation is likely a major factor driving
diversification in macroinvertebrates, but few studies have tested this expectation [25,28,29].
In particular, Mu
´rria et al. [25] found a high frequency of unique haplotypes associated with
the geographical distance across watersheds in Panama. While confirmatory, these findings
are not surprising, given the large geographic distance among the watersheds included in Mu
´r-
ria et al. [25]. However, patterns of haplotype (or lineage) diversity at smaller scales (e.g.,
among streams within watersheds), where dispersal and gene flow might be less restricted,
have received less attention. We use DNA-barcoding to assess patterns of lineage diversity
(and the diversity of unique haplotypes) in freshwater macroinvertebrates in four streams
within the Panama Canal Watershed (PCW). In addition, we compiled available barcoding
data [25] to contrast macroinvertebrate diversity at a broader spatial scale, among eight
streams along the Isthmus of Panama.
Assessing the patterns and drivers of macroinvertebrate diversity at different scales is par-
ticularly relevant, given the increasing rate of environmental degradation in Neotropical
regions [30–33]. This includes alterations such as introduction of alien species [34,35], the
development of megaprojects [36], habitat degradation, water pollution, and climate change
[30,33,37,38]. As a consequence, a large portion of this biodiversity risks being lost before
discovery.
Material and methods
Study sites and sample processing
Samples were collected from four streams within the PCW (Frijolito, Frijoles, Trinidad, and
Indio) between April and May of 2013 (Fig 1). Frijolito (09º08’57.9’’ N, 79º43’53.2’’ W) and
Frijoles (09º09’08.2’’ N, 79º44’05.3’’ W) are typical Neotropical streams separated by approxi-
mately 300 m and located inside Soberanı
´a National Park. These streams are surrounded by
dense secondary forest and present low levels of disturbance. Rı
´o Trinidad (8º58’28.50’’ N,
79º57’23.9’’ W) is located approximately 30 km West Rı
´o Frijoles in an agricultural landscape
dominated by pasture, but it has abundant riparian vegetation. Rı
´o Indio (09º12’04.1’’ N,
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De Leo
´n. Additional funding was provided by
Secretarı
´a Nacional de Ciencia, Tecnologı
´a e
Innovacio
´n (SENACYT; Grants No. ITE12-002 and
FID16-116 to L. F. De Leo
´n), Sistema Nacional de
Investigacio
´n (SNI; to C. Aguilar), and the
University of Massachusetts Boston (to Luis F. De
Leo
´n). The funders had no role in study design,
data collection and analysis, decision to publish, or
preparation of the manuscript.
Competing interests: The authors have declared
that no competing interests exist.

079º24’20.4’’ W), located 35 Km east of Frijoles, is intermediately disturbed and is surrounded
by secondary forest with dense riparian vegetation. At each site, we haphazardly collected
aquatic macroinvertebrates using standard kick-netting from the two dominant habitats types
(riffles and pools). The sampling effort was approximately two hours at each site. All samples
were sorted in the field and immediately preserved in 95% ethanol. Sampling permit was
obtained from the Autoridad Nacional del Ambiente de Panama
´(Permit No. SC/A-44-12).
In the laboratory, specimens were morphologically identified to the lowest possible taxo-
nomic level (i.e., family or genus) using taxonomic keys for Neotropical macroinvertebrates
[6,8,9,39]. However, given the low accuracy of morphological identification, and the fact that
less than 50% of the individuals were successfully identified to species level using our barcod-
ing data (see results), we focused our analyses and discussion on lineage rather than morpho-
logical diversity. Representative specimens have been deposited in the invertebrate collection
at Coleccio
´n Zoolo
´gica Dr. Eustorgio Me
´ndez (CoZEM) at Instituto Conmemorativo Gorgas
de Estudio de la Salud in Panama City (Voucher numbers: B001 –TR020).
DNA sequencing
Tissue samples were obtained from the hind leg or part of the body of each specimen, and total
DNA was extracted by using the DNeasy Blood & Tissue kit (Qiagen, CA, USA), according to
Fig 1. Sampling sites of macroinvertebrates in the Panama Canal Watershed. Names on the inset map indicate the sites previously sampled by Mu
´rria et al. [25].
https://doi.org/10.1371/journal.pone.0231683.g001
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the manufacturer’s instructions. A standard sequencing protocol [40] was used to amplify the
full-length 658 base pair (bp) of the COI barcode region using the following primers sets:
LCO1490/HCO2198 [41] and LepF1/LepR1 [42]. All PCR products were verified on a 1% aga-
rose gel, and purified with EXO-SAP-IT (USB Corp., Cleveland, Ohio, U.S.A.). The protocol
included adding 1 μl of 1 U/μl Shrimp Alkaline Phosphatase (SAP), 0.5 μl of 20 U/μl Exonucle-
ase I (EXO), and 5 μl of amplified product, and then incubating as indicated in the manufac-
turer’s protocol [43]. This product was sequencing using an Applied Biosystems Genetic
Analyzer (ABI 3130xl, Applied Biosystems, Carlsbad, California). Sequences were aligned in
Geneious V7.03 [44], using the MAFFT 7.313 [45] tool and the L-INS-i algorithm. Sequence
alignments were also inspected by eye in Geneious to confirm overall sequence quality. We
did not find gaps or stop codons in any of the sequences. Project sequences, together with the
information on collected specimens, are available on the Barcode of Life Data System (BOLD
systems, under project code INVPA: http://www.boldsystems.org/). Project sequences are also
available in GenBank (accession numbers: KX039451-KX039650, KU980966-KU981004).
Data analysis
To confirm morphological identification for our sequenced specimens, we performed BLAST
searches for publicly available sequences in GenBank. We created a final dataset comprising
unique haplotypes from our study and including three COI sequences retrieved from Genbank
that were used as an outgroup. The retrieved sequences were Thermobia domestica (GenBank
NC006080), Atelura formicaria (GenBank NC01119), and Tricholepidion gertschi (GenBank
NC005437).
We estimated phylogenetic relationships among taxa using maximum likelihood (ML)
searches in IQ-TREE v 1.6 [46] and Bayesian inference (BI) in BEAST v 2.4.6 [47] as implemented
on the CIPRES Science Gateway [48]. The best-fit model of nucleotide substitution for the dataset,
selected using jModelTest 2.0 [49] based on the Bayesian Information Criterion, was GTR+I+G.
To determine node support for the IQ-TREE we used 10000 ultrafast bootstraps [50] and 1000
Shimodaira-Hasegawa-like approximate likelihood ratio test replicates [51]. BI analysis was exe-
cuted with an uncorrelated lognormal relaxed clock and coalescent prior, with the default settings
of BEAUti for the remaining parameters. We performed two runs of 2.0×10
7
generations, and
sampled trees every 5000 generations. Trace logs and species trees for the two runs were combined
using LogCombiner v 2.4.8 [52]. We used Tracer v. 1.6 [53] to ensure that effective sample size
(ESS) values for all parameters were above 200 and to determine the burn-in. Finally, output trees
were summarized as maximum clade credibility (MCC) trees using mean node heights after dis-
carding 25% of generations as burn-in using TreeAnnotator v1.8.4 [54].
We then assessed the diversity of “molecular species” by estimating molecular operational
units (MOTUs; [55] using the software MEGA 7.0 [56] and the BOLD analyses tools [57].
Sequence divergence was estimated using the Kimura-2-Parameter (K2P) model with 1000
bootstrap estimates in MEGA7. This a standard model that has been extensively used in bar-
coding studies [58,59]. The Barcode Index Number (BIN) system [57] was used as delimitation
criterion for the assignment of MOTUs across the full dataset. This method uses a 2.2% in
sequence divergence cut-off, but updates this value according to the distribution of divergence
among sequences in the dataset. Recent studies suggest that using a single divergence cut-off
may not be appropriate for every organism (reviewed in [60], such as in the case of diverse
non-tropical chironomids [60,61]. But, given that our sample of this taxon was small, we
assumed a single cut-off value for the entire dataset. However, future work should evaluate the
optimal level of genetic divergence to delimit biological species in Neotropical
macroinvertebrates.
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In addition, given recent concerns with the use of the K2P model for species delimitation
(e.g., [62], we applied two additional single-locus analyses to confirm lineage diversity: the
Bayesian General Mixed Yule Coalescent model (GMYC; [63] and the Automatic Barcode
Gap Discovery (ABGD; [64]. The GMYC approach uses branch lengths to determine the tran-
sition from intraspecific to interspecific relationships [63]. The ABGD algorithm allows to sort
DNA sequences into “hypothetical species” based on the gaps in the distribution of intra- and
inter-specific genetic divergence in a given sample [64]. Although the two approaches differ in
their properties (i.e., tree branch length vs. distribution gaps), we used them to confirm the
patterns of species delimitation.
To perform GMYC tree-based analyses, we used the ultrametric trees previously generated
with BEAST. GMYC was performed using the single threshold parameter at the GMYC web-
server (https://species.h-its.org/gmyc/). ABGD was carried out using the online version of
ABGD software [64]; https://bioinfo.mnhn.fr/abi/public/abgd/abgdweb.html). Default settings
were used, however, distance matrices based on K2P distance calculated in MEGA7 were used
as input. All analyses were run using a relative barcoding gap width (X value) set to 1.0. Only
the recursive results were used because they allowed for different gap thresholds among taxa.
To compare patterns of spatial variation in genetic diversity (MOTUs), we quantified the
number of shared species among sampling sites. We also estimated Fisher’s alpha index of
diversity and Whittaker’s measure of β- beta diversity. Given that these analyses might be
affected by variation in sampling size, we also used rarefaction and extrapolation methods
[65,66] as implemented in the R package iNEXT [67]. This method allows for comparisons
between sites while controlling for differences in abundance and sampling effort. For these anal-
yses, we fit curves for the first three Hill numbers: species richness (q = 0), the exponential of
Shannon entropy (“Shannon diversity”, q = 1), and the inverse Simpson concentration (“Simp-
son diversity”, q = 2), using individual-based abundance data. Given the limitation in sample
size, we did attempt to make statistical inferences regarding differences in diversity among sites.
Finally, to assess lineage diversity and the diversity of unique haplotypes across watersheds
spanning the Isthmus of Panama, we collected haplotype information (426 haplotypes: Gen-
Bank accession numbers KR134410-KR134835) from a previous study in this region [25].
After adding these sequences to our dataset, we generated multiple sequence alignments with
MAFFT 7.313 [45] using the L-INS-i algorithm in Geneious V7.03. Then, we trimmed the
sequences to the same fragment size and compared the previously reported haplotypes with
the ones encountered in our dataset. To exclude redundancies prior to phylogenetic analyses,
we applied DAMBE v. 6.4.11 [68] to identify and remove duplicate haplotypes from our data-
set. In total, we found a total of 15 duplicate haplotypes between the two datasets. The com-
bined dataset contained 12 sites (8 from Mu
´rria et al. [25], and 4 from the present study). One
site (Frijolito) was sampled during both studies, but we analyzed them separately to preserve
independence between the two studies. We then applied the same rarefaction/extrapolation
approach described above to generate rarefaction curves as a function of the number of indi-
viduals sampled. Although the collection method was similar (i.e., both studies used kick-nets
during a given amount of time), the two studies may not be directly comparable due to differ-
ences in sampling effort and the overall study objective. Therefore, we did not attempt to make
statistical inferences about the relative abundance of macroinvertebrates among sites or
between studies. Instead, we only focused on compiling the total number of unique haplotypes
or molecular species that are currently known within each site in this region. In addition, our
ultimate goal was to explore the overall molecular endemicity of aquatic macroinvertebrates,
rather than providing precise estimates of species diversity in this region. Thus, substantially
more research that includes more data, sites, and replication is needed to confirm if current
patterns hold across the entire region.
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Results
We collected approximately 300 specimens across the four sites; however, our analysis focused
on the 224 individuals that were successfully barcoded (Table 1 and S1 Table). We were able to
identify nearly 70% of individuals to genus level using the morphological approach, but spe-
cies-level identification was only possible for 56 individuals (25%). Some of the most numer-
ous taxa across sites included Leptophlebiidae (11.2% of individuals), Libellulidae (11.2%),
Naucoridae (6.7%), Notonectidae (6.3%), Chironomidae (5.4%), Gerridae (4.9%), Hydropsy-
chidae (4.0%), Perlidae (3.6%), and Baetidae (3.6%).
The 224 COI sequences revealed a total of 168 haplotypes (S1 Table). After comparing these
haplotypes with molecular data from Mu
´rria et al [25], we found 153 (~91%) unique haplo-
types from the Panama Canal Watershed. In Frijolito, the site sampled by the two studies, we
found a total of 46 haplotypes, 45 of which were unique to our study.
Our final COI dataset consisted of 171 terminals, including the 168 new barcode sequences,
and 3 outgroup sequences retrieved from GenBank. The final aligned and pruned dataset con-
tained 620 aligned positions, including gaps, with 371 variable sites, of which 359 were parsi-
mony-informative (~96% of variable positions). As expected, we observed a hierarchical
increase in the mean K2P genetic divergence with increasing taxonomic levels from within a
species 0.38% (SE = 0.002), to within family 9.92% (SE = 0.01), to within order 19.75%
(SE = 0.01). However, we were not able to identify our specimens to species level from our
BLAST search, given that only around 50% of our sequences matched existing data in the pub-
lic databases, and most of these matches corresponded to genus and family level only. Both
ML and BI inference trees for all specimens showed well-defined clades at the level of order
and family, with some differences in the topology, but overall support was higher for the BI
tree, which we used to represent the number of molecular species (S1 Fig and S2 Fig).
Our species delimitation analyses yielded variable, but relatively high numbers of species.
Specifically, GMYC detected 106 MOTUs (95% confidence intervals: 104–109), whereas
ABGD found a total of 100 MOTUs (S1 Fig). These ABGD results were confirmed indepen-
dently of the chosen model (Jukes-Cantor and Kimura) and were unaffected by changes of
prior limits for intraspecific variation and threshold.
When looking at spatial patterns of diversity, we observed some overlap in the number of
shared MOTUs as well as a considerable number of unique haplotypes in each river: Frijoles
(65), Frijolito (43), Trinidad (31) and Indio (22) (Fig 2). This pattern was also supported by
the Fisher’s alpha diversity index, which showed variation in molecular species among sites:
Frijoles 53.40, Frijolito 22.80, Trinidad 17.01, and Indio 67.63. Whittaker’s index of βdiversity
also showed high species turn-over across sites (0.87). Similarly, our rarefaction/extrapolation
analyses showed variation in species richness across sites: Frijoles (52), Frijolito (27), Trinidad
(22) and Indio (22). However, the most striking pattern was a lack of saturation in the
Table 1. Macroinvertebrate lineage diversity in the Panama Canal Watershed.
Site Ind. Hap. GMYC ABGD
Trinidad (TRI) 45 33 22 21
Frijolito (FTO) 65 46 27 26
Frijoles (FES) 88 72 52 50
Indio (IND) 26 24 22 21
All 224 168 106 100
The data show the number of successfully barcoded individuals (Ind.), cox1 haplotypes (Hap.), and molecular species
(based on GMYC and ABGD) collected at four sites.
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accumulation curves for most of the sites (Fig 3), and this pattern was consistent across the
first three Hill numbers (S3 Fig). Similar results were found when looking at diversity Hill
across the Isthmus of Panama using the compiled barcoding dataset (Fig 3). In particular, we
observed substantial diversity of both MOTUs and unique haplotypes across sites, but the
accumulation curves did not reach saturation for most of the sites (Fig 3). In addition, both
molecular species and haplotype diversity tended to increase at sites within the PCW, in con-
trast to sites located in the eastern and western portion of the country (Fig 3). Data on assign-
ment and diversity of MOTUs across study sites are available in the supplementary material
(S1 Table).
Discussion
Using DNA-barcoding, we examined the diversity of freshwater macroinvertebrates at a small
spatial scale, among four streams within the Panama Canal watershed (PCW). We also com-
piled existing barcoding data [25] to contrast macroinvertebrate diversity at a broader spatial
scale, across eight streams along the Isthmus of Panama. Overall, we found high lineage diver-
sity across sites within the PCW (Table 1;S1 Fig), and a large portion of these lineages appear
to be unique to each site (Fig 2). In addition, our rarefaction/extrapolation approach showed
that this diversity is still under-sampled across sites both within the PCW and along the Isth-
mus of Panama (Fig 3).
These findings confirm that the diversity of freshwater macroinvertebrates in Neotropical
environments is largely under-studied [33,69,70], and could be much higher than previously
thought. In particular, these findings highlight the fact that there is limited published research
using genetic methods to study macroinvertebrate diversity in this region. This was reflected
by one of our sites (Frijolito), which despite being sampled by a previous barcoding study [25],
still showed a substantial number of novel haplotypes. In addition, the fact that only a small
number of our specimens matched available sequences in public databases further highlights
the potential for biodiversity discovery in Neotropical freshwater environments. This seems
particularly relevant for taxa such as Hydropsychidae, Gerridae, Chironomidae, Leptophlebii-
dae, Libellulidae and Notonectidae, which showed high lineage/haplotype diversity across sites
Fig 2. Distribution of molecular diversity in freshwater macroinvertebrates among streamswithin Panama Canal Watershed. Venn diagrams show the number of
shared and unique haplotypes (A) and MOTUs (B) across four streams: Trinidad (pink), Frijolito (blue), Indio (yellow), and Frijoles (green).
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(S1 Fig;S1 Table). Some of these taxa also showed high haplotype diversity in a previous
molecular study across Panama [25], and are thought to hold a high number of undescribed
species in the Central American Isthmus [6,69]. Unfortunately, our analysis is limited by rela-
tively small sample size, particularly at one of our sites (Rı
´o Indio), where we were only able to
Fig 3. Molecular diversity in freshwater macroinvertebrates along the Isthmus of Panama. Panels show Simpson’s diversity index for both haplotype (A) and
MOTUs (B), as well as rarefaction and extrapolation curves for both haplotypes (C) and MOTUs (D) diversity at each site. Sites are Alema
´n (ALE), Chorro (CHO),
Blanco (BLA), Guabal (GUA), Capira (CAP), Frijolito (FRI), Cerro Azul (CAZ), and Chucantı
´(CHR) from Mu
´rria et al. 2015; and Trinidad (TRI), Frijolito (FTO),
Frijoles (FES) and Indio (IND) from present study (indicated with asterisks). Regions are indicated as East, West and the Panama Canal Watershed (PCW).
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sequence 26 specimens. In addition, the fact that our rarefaction/extrapolation analysis showed
a lack of saturation for most of the sites indicates that substantially more research is needed in
this region. Overall, however, our results are in line with recent work showing high haplotype
endemicity among isolated watersheds across the Isthmus of Panama [25]. In fact, despite low
sample size, we found at least 153 (~91%) novel haplotypes within the PCW. Thus, we expand
on this previous work by highlighting the possibility that endemicity of Neotropical macroin-
vertebrates can be substantial even within a single watershed.
Typically, diversification in freshwater organisms is marked by a strong geographic signa-
ture, where genetic divergence is facilitated by spatial isolation among populations [26,27].
However, the contribution of geographic isolation to the diversification of Neotropical fresh-
water macroinvertebrates has received little attention to date [25]. In addition, the fact that
most macroinvertebrates are semiaquatic, and are likely to disperse during the adult stages
[15,16] could limit genetic isolation among nearby stream communities. Yet, the possibility of
high endemicity even within a single watershed suggests that spatial isolation, habitat variabil-
ity, and perhaps, local adaptation are important drivers of macroinvertebrate diversity.
Another interesting finding was that macroinvertebrate diversity appeared to increase at sites
located in Central Panama, specifically within the PCW (e.g., Frijoles, Frijolito, Trinidad).
However, additional research is needed to confirm this pattern and to explore the underlying
drivers. We encourage the application of more efficient tools such as DNA metabarcoding to
facilitate this endeavor.
Our finding of high endemicity at a small geographic scale is also relevant in the face of
increasing anthropogenic disturbances [31,32,71–73]. Specifically, it suggests that small-scale
local disturbances could have drastic consequences for the maintenance of a unique freshwater
biodiversity–but this diversity is still unknown. We therefore predict that the current rate of
species loss in freshwater ecosystems might be surpassing the rate of species discovery in Neo-
tropical environments. Overall, however, further work is clearly needed to disentangle the con-
tribution of other factors such as genetic drift, local adaptation, and environmental
disturbance to persistence and diversification of Neotropical freshwater macroinvertebrates.
Taken together, our results confirm the expectation that the diversity of Neotropical macro-
invertebrates remains under-studied. They also indicate that uncovering this hidden diversity
is crucial to our understanding of the local and regional processes that shape biodiversity in
Neotropical freshwater environments.
Supporting information
S1 Fig. Molecular diversity in freshwater macroinvertebrates from Central Panama. The
Bayesian inference tree shows species delimitation analyses based on generalized mixed Yule
coalescent (GMYC) and the automatic barcode gap discovery (ABGD). Black and grey blocks
represent putative molecular species, with taxa sharing the same block corresponding to simi-
lar species. The numbers next to the nodes represent Bayesian posterior probability values.
(PDF)
S2 Fig. Rarefaction and extrapolation curves for molecular diversity (MOTUs) at each site.
Number at the top represent fit curves for the first three Hill numbers: species richness (q = 0),
the exponential of Shannon entropy (“Shannon diversity”, q = 1), and the inverse Simpson
concentration (“Simpson diversity”, q = 2), using individual-based abundance data. Sites are:
Alema
´n (ALE), Chorro (CHO), Blanco (BLA), Guabal (GUA), Capira (CAP), Frijolito (FRI),
Cerro Azul (CAZ), and Chucantı
´(CHR) from Mu
´rria et al. 2015; and Trinidad (TRI), Frijolito
(FTO), Frijoles (FES) and Indio (IND) (from the present study).
(PDF)
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Hidden biodiversity in Neotropical streams
PLOS ONE | https://doi.org/10.1371/journal.pone.0231683 August 7, 2020 9 / 13

S3 Fig. Phylogenetic tree determined by the Maximum Likelihood (ML). Data represent
cox1 sequences obtained from 224 freshwater macroinvertebrates collected within the Panama
Canal Watershed. The numbers on the branches show nodal support.
(PNG)
S1 Table. Molecular and taxonomic diversity of freshwater macroinvertebrates within the
Panama Canal Watershed. For each specimen, we show a taxonomic group (i.e., order, fam-
ily, and genus), molecular species identity (MOTUs: based on ABGD and GMYC), Haplotype
identity, Genbank accession number, and sampling site. Sites are Trinidad (TRI), Frijolito
(FTO), Frijoles (FES) and Indio (IND).
(XLSX)
Acknowledgments
We dedicate this study to our friend Ruth G. Reina. Her passion for tropical freshwater biology
served as an inspiration to this work. Logistical support was provided by the Smithsonian
Tropical Research Institute. Field assistance was provided by Celestino Martı
´nez, Nohelys
Alvarado, Carlos Nieto, and De
´bora Delgado. Diana Sharpe provided valuable comments on
an earlier version of the manuscript. We thank editor Dr. Michael A. Chadwick and four
anonymous reviewers for providing feedback on our manuscript.
Author Contributions
Conceptualization: Luis F. De Leo
´n.
Data curation: Luis F. De Leo
´n, Aydee
´Cornejo, Ronnie G. Gavila
´n, Celestino Aguilar.
Formal analysis: Luis F. De Leo
´n, Ronnie G. Gavila
´n, Celestino Aguilar.
Funding acquisition: Luis F. De Leo
´n.
Investigation: Luis F. De Leo
´n, Aydee
´Cornejo, Ronnie G. Gavila
´n, Celestino Aguilar.
Methodology: Luis F. De Leo
´n, Aydee
´Cornejo, Ronnie G. Gavila
´n.
Resources: Aydee
´Cornejo, Ronnie G. Gavila
´n.
Supervision: Luis F. De Leo
´n, Aydee
´Cornejo.
Writing – original draft: Luis F. De Leo
´n.
Writing – review & editing: Luis F. De Leo
´n, Celestino Aguilar.
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