Cryptic biodiversity in streams: a comparison of macroinvertebrate communities based on morphological and DNA barcode identifications Author(s)

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Cryptic biodiversity in streams: a comparison of macroinvertebrate communities based on
morphological and DNA barcode identifications
Author(s): John K. Jackson, Juliann M. Battle, Bryan P. White, Erik M. Pilgrim, Eric D.
Stein, Peter E. Miller and Bernard W. Sweeney
Source:
Freshwater Science,
(-Not available-), p. 000
Published by: The University of Chicago Press on behalf of Society for Freshwater Science
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Cryptic biodiversity in streams: a comparison
of macroinvertebrate communities based on
morphological and DNA barcode identifications
John K. Jackson
1,5
, Juliann M. Battle
1,6
, Bryan P. White
2,7
, Erik M. Pilgrim
3,8
, Eric D. Stein
2,9
,
Peter E. Miller
4,10
, and Bernard W. Sweeney
1,11
1
Stroud Water Research Center, Avondale, Pennsylvania 19311 USA
2
Southern California Coastal Water Research Project, Costa Mesa, California 92626 USA
3
US Environmental Protection Agency, National Exposure Research Laboratory, Cincinnati, Ohio 45268 USA
4
Canadian Centre for DNA Barcoding, Biodiversity Institute of Ontario, University of Guelph, Guelph, Canada N1G 2W1
Abstract: Species-level identifications are difficult or impossible for many larval aquatic macroinvertebrates. We
described the taxonomic composition of macroinvertebrate communities from 5 coastal streams in 3 neighbor-
ing catchments in southern California. We compared taxonomic identifications based on deoxyribonucleic acid
(DNA) barcoding (cytochrome coxidase subunit I [COI]) with morphological identifications of the same spec-
imens. We examined 5870 individuals, and barcodes with sequence lengths >350 base pairs (bp) for 91% of
those specimens. We used the naturally occurring gaps in divergence frequencies for each order (usually 2%
level of genetic divergence) to delimit putative species for all taxonomic groups except Simulium (3%) and
Baetis (1%). We identified 200 species across these 5 streams. We identified 104 more species via barcodes than
via morphology (200 vs 96, a 108% increase). Richness increases were greatest for Chironomidae (60 more
species), Ephemeroptera (10 species), Acari (10 species), and Trichoptera (6 species). Forty-five percent of the
genera/species identified morphologically represented >2 species. Many (86) species identified with barcodes
were represented by only 1 or 2 specimens and were found at only 1 stream. Thus, species rarity (either spa-
tially or numerically) appears to be a common characteristic of these streams. Barcoding increased total rich-
ness at each site by 12 to 40 taxa over morphology alone, and increased the difference between reference and
impact sites in terms of lost taxa. These results suggest that macroinvertebrate biodiversity in streams has been
underestimated substantially in the past, as has the biodiversity lost in response to environmental stress. The po-
tential of DNA barcoding will not be fully realized until we can assign traits, such as habitat preference, eco-
logical function, and pollution tolerance, at the species level.
Key words: DNA barcoding, cytochrome coxidase, COI gene, mitochondrial DNA, freshwater, macroinver-
tebrates, water-quality monitoring, community structure, species richness, taxonomy
Species are the basic unit of ecology and ecosystems.
Species are the building blocks of ecological structure
and function, the currency used to attach value and as-
sess change in conservation biology, and the basis of en-
vironmental advocacy and regulation. However, ecolo-
gists have rarely, if ever, had complete knowledge of the
species composition of any given habitat or set of habi-
tats. For example, the few relatively thorough inventories
of stream macroinvertebrates suggest that at least several
hundred to >1000 macroinvertebrate species can exist
in a section of stream or river (e.g., Morse et al. 1980, 1983,
Zwick 1998, Humpesch and Fesl 2005, J. C. Morse [Clem-
son University], personal communication). Unfortunately,
most stream invertebrates can be identified only on the
basis of morphological characters apparent in adult males
or (in some cases) relatively mature juveniles, neither of
which is often collected. Thus, many small, juvenile, or dam-
aged individuals commonly collected in stream macro-
invertebrate samples are identifiable only to the level of ge-
nus or higher. In addition, many genera in a given stream are
represented by ≥2 morphologically cryptic species, which
can greatly complicate data interpretation (e.g., Zurwerra
et al. 1987, Funk et al. 1988, 2008, Jackson and Resh 1992,
1998, Duan et al. 2000, Hogg et al. 2005, Williams et al. 2006,
E-mail addresses:
5
jkjackson@stroudcenter.org;
6
jbattle@stroudcenter.org;
7
bryan2@sccwrp.org;
8
pilgrim.erik@epamail.epa.gov;
9
erics@sccwrp.org;
10
pemiller@uoguelph.ca;
11
sweeney@stroudcenter.org
DOI: 10.1086/675225. Received 30 April 2013; Accepted 23 November 2013; Published online 13 January 2014.
Freshwater Science. 2014. 33(1):000–000. © 2014 by The Society for Freshwater Science. 000
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Pauls et al. 2010, Kim et al. 2012, Anderson et al. 2013).
Thus, although the scientific literature and environmental
regulations often refer to aquatic macroinvertebrate species,
in practice, we are generally unsure what macroinvertebrate
species are actually present in a stream or river.
The difficulty of attaching a species name to each
stream macroinvertebrate collected is evident in the pub-
lished literature and in the protocols designed for stream
monitoring. For example, even in studies that take macro-
invertebrate identifications to the lowest taxonomic level
possible, authors generally leave ≥50% of the individuals
examined at the genus or higher level (e.g., Waite et al.
2004, Arscott et al. 2006, Sweeney et al. 2011). Moreover,
to save time and reduce inconsistencies among personnel,
dates, and sites, most state sampling protocols in the USA
require only genus or family identifications or a combina-
tion of taxonomic efforts (e.g., some mayflies to species,
caddisflies and stoneflies to genus, and chironomid
midges to family or “genus”based on gross morphology;
Carter and Resh 2001, Richards and Rogers 2006). Even
where indicator species are monitored and communicated
to the public, the “species”is actually a genus or a com-
plex of closely related species (e.g., Hexagenia in the
Mississippi River or Great Lakes; Fremling 1991, Webb
et al. 2012). When investigators have been able to differen-
tiate between closely related, congeneric species, they have
observed some differences in both pollution tolerance and
functional traits (Lenat 1993, Schmidt-Kloiber et al. 2006).
Our intent is not to disparage the current system for mon-
itoring streams and rivers but, rather, to point out that to
date we have been unable take full advantage of the speci-
mens collected during environmental assessments. These
bioassessments also are missed opportunities to add to our
species-specific knowledge base because new ecological and
regulatory information has gone unrecognized. The numer-
ous analyses and discussions over the last 4 decades that
examined the information lost or gained depending on the
taxonomic resolution in stream macroinvertebrate data
(e.g., Resh and Unzicker 1975, Bowman and Bailey 1997,
Lenat and Resh 2001, Arscott et al. 2006, Jones 2008,
Greffard et al. 2011, Monk et al. 2012) is evidence that the
value of species identifications has long been of interest.
This issue remains unresolved to some degree today be-
cause of our inability to identify most individuals to species.
Genetic methods developed over the last several de-
cades have helped and can help further with species iden-
tifications and the clarification of species boundaries for
aquatic macroinvertebrates. One such molecular taxonomic
method is referred to as deoxyribonucleic acid (DNA) bar-
coding and uses a 658-base pair (bp) region (the Folmer
region) of the mitochondrial cytochrome coxidase subunit
I (COI) gene. Genetic distinctness based on DNA barcodes
has helped identify or confirmed morphologically distinct
species and has provided insights into boundaries among
morphologically indistinct species (e.g., Hebert et al. 2004a,
b, Monaghan et al. 2005, Ward et al. 2005, Hajibabaei et al.
2006, Smith et al. 2006, Burns et al. 2008, Zhou et al. 2010,
2011, Renaud et al. 2012, Webb et al. 2012). Species we have
defined based on barcodes are described as putative. How-
ever, for stream macroinvertebrates, limited data suggests
that agreement is good among species designated by DNA
barcoding and those based on morphological, ecological, or
behavioral data (Zhou et al. 2010, 2011, Sweeney et al. 2011,
Renaud et al. 2012, Webb et al. 2012, Anderson et al. 2013).
The purpose of our study was to examine how our percep-
tion of macroinvertebrate community structure changes
when it is based on species-level taxonomy (using barcodes)
vs genus/species- or higher-level taxonomy associated with
state-of-the-art traditional morphology. We examined 2 ques-
tions: 1) How much does macroinvertebrate taxon richness
and rarity at a site and across a region change when spec-
imens are identified by DNA barcoding vs morphology
alone, and 2) How do barcode identifications affect the as-
sessment of “lost taxa”in response to environmental stress?
METHODS
Sampling sites
We compared macroinvertebrate assemblages collected
from 5 streams in the Los Angeles region (Ventura and
Los Angeles Counties, California; Stein et al. 2013). Two
sites (West Fork [WF], lat 34.2410°N, long 117.8690°W,
and East Fork [EF], lat 34.2300°N, long 117.7800°W) of
the San Gabriel River drain mountainous watersheds (469
and 536 m asl, respectively) covered primarily by ever-
green forests and shrub/scrub. Two of the sites (Big
Tujunga Wash, lat 34.2740°N, long 118.3150°W; Arroyo
Seco, lat 34.2050°N, long 118.1660°W) are tributaries of
the Los Angeles River. Both of these watersheds are transi-
tional (395 and 344 m asl, respectively) between the moun-
tains and lowlands, with predominantly shrub/scrub land
cover and some urban development. Conejo Creek (lat
34.2010°N, long 119.0010°W) is a tributary of Calleguas
Creek in Ventura County. This lowland watershed (32 m asl)
is highly modified with extensive agricultural and urban de-
velopment. Thus, the 5 study streams represent a range of
environmental conditions, with WF and EF San Gabriel drain-
ing relatively natural watersheds, Big Tujunga Wash and
Arroyo Seco with some urban development near the sam-
pling sites, and Conejo with more-extensive agricultural
and urban development (Stein et al. 2013). A 6
th
stream (Ar-
royo Simi in the Calleguas Creek watershed) also was sam-
pled and included in the analyses by Stein et al. (2013),
but this site was not included in our paper because the
macroinvertebrate samples were improperly preserved for
molecular analysis and barcode success was low (11%).
We sampled 2 reaches at each site: one 150-m-long
reach upstream of where stream banks had been physically
000 | Cryptic biodiversity in streams J. K. Jackson et al.
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stabilized by armoring (i.e., primarily bank stabilization
with hard substrates, such as concrete walls, boulders, or
gabions) and 1 within the 100- to 200-m reach where ar-
moring had occurred on 1 or both stream banks. This ar-
moring severely changes in-stream habitat by constraining
the lateral movement of the reach and affects pool scour
and meander development (Stein et al. 2013). Our focus
was on the macroinvertebrate faunas that characterized
each of these streams, so we combined the specimens col-
lected at the 2 reaches into a single sample from each
stream. Analyses of the effects of stream-bank armoring
on the macroinvertebrate community were presented by
Stein et al. (2013, 2014).
Field collections
We collected macroinvertebrates in June and July 2010
using the multihabitat method described in Ode (2007).
Each reach was divided into 11 equidistant transects, and
a 30- to 60-s kick sample with a 500-μm mesh D-frame
net was collected at an objectively chosen location along
each transect (i.e., 25, 50, or 75% of the way across the
stream), for a total of 0.9 m
2
of streambed sampled per
reach. The 11 subsamples were composited into 1 con-
tainer and specimens were preserved immediately in 95%
ethanol. Samples were drained and replenished with 95%
ethanol within 24 to 48 h of collection to preserve tissue
for DNA analysis.
Identifications, barcoding and data interpretation
We sorted ∼1200 macroinvertebrates from each site
(600/reach) and identified them morphologically follow-
ing the taxonomic standards of the Southwestern Associ-
ation of Freshwater Invertebrate Taxonomists (i.e., mainly
to genus, including chironomids; level 2 in Richards and
Rogers 2006). Some noninsect groups (e.g., oligochaetes,
ostracods) were left at higher taxonomic levels, such as
class or order (Table 1). Morphological identifications were
provided by personnel at the California Department of Fish
and Game Aquatic Bioassessment Laboratory at California
State University Chico.
We sent tissue from each specimen (typically legs
where possible or an anterior body part [e.g., chironomids,
worms]) to the Canadian Centre for DNA Barcoding
(CCDB) at the University of Guelph. Genomic mitochon-
drial DNA was extracted and the 658-bp barcoding re-
gion of the COI gene was amplified and sequenced using
highly automated protocols established at the CCDB by
Ivanova et al. (2006; http://www.ccdb.ca/resources.php).
Sequences and detailed information about all specimens
including photographs are stored on GenBank and Bar-
code of Life Data systems (BOLD) web sites (Ratnasingham
and Hebert 2007; http://www.barcodinglife.com/, projects
CFWIA to CFWII). For specimens that failed to barcode,
another tissue sample was sent to EMP (US Environmental
Protection Agency, National Exposure Research Labora-
tory, Cincinnati, Ohio) for a 2
nd
attemptatobtainingabar-
code.
Of the 5870 individuals submitted for barcoding, COI
sequences ≥350 bp from 5349 specimens (91% of total)
were exported from BOLD and brought into MEGA 5.05
(Tamura et al. 2007) and aligned using ClustalW with de-
fault parameters. We used pairwise comparisons to as-
sess frequency of % genetic divergence for major macro-
invertebrate groups (i.e., by orders), and neighbor-joining
(NJ) trees with pairwise deletion and Kimura-2-parameter
distance to identify the genetically distinct Molecular Op-
erational Taxonomic Units (MOTUs) or barcode species
present (Fig. S1A–I). Bootstrap values on NJ trees were
based on 500 replications.
Table 1. Richness measured for 5 California (CA) streams and White Clay Creek (Pennsylvania [PA]) based on morphology (M) and
barcode (B) identifications for Ephemeroptera, Plecoptera, Trichoptera, Chironomidae, oligochaete worms, and other macroinver-
tebrates (e.g., other Diptera, Coleoptera, Acari, Corixidae, Odonata, Mollusca, Prostoma, Ostracoda). WF = West Fork, EF = East Fork.
Stream
Total
Ephemer-
optera
Plecop-
tera
Trichop-
tera
Chirono-
midae
Oligo-
chaeta Others
M B MBMBMBMBMBMB
WF San Gabriel 61 95 8 12 0 0 10 12 19 37 1 1 23 33
EF San Gabriel 51 91 7 15 1 1 8 10 16 35 1 4 18 26
Big Tujunga Wash 26 38 2 4 0 0 1 2 19 25 0 0 4 7
Arroyo Seco 21 45 3 6 1 1 0 0 12 29 1 1 4 8
Conejo 30 46 4 5 0 0 1 1 12 25 1 1 12 14
5 CA streams 96 200 13 23 2 2 12 18 31 91 1 6 37 60
White Clay
a
88 180 10 19 3 9 14 17 42 93 1 8 18 34
a
Data modified from Sweeney et al. 2011.
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We used the gap in divergence frequencies beginning at
∼2% for each of the macroinvertebrate groups (Figs 1A–G,
2) to distinguish the difference in genetic structure within
a species (<2% divergence) vs between species (>2% diver-
gence) (cf. Hebert et al. 2003a, b, Meyer and Paulay 2005,
Rivera and Currie 2009, Sweeney et al. 2011, and others).
MOTUs or barcode species were delimited using 2% di-
vergent distance for all taxa groups except Baetis (1%) and
Simulium (3%) (Figs 1A–G, 2). The break between intra-
and interspecificdivergencefortheblackflySimulium be-
gan at ∼3% (Fig. 1E), which split Simulium into 6 species
(Fig. S1F). Baetis was complicated in that 3 species were
delimited morphologically (Baetis tricaudatus,Baetis
adonis, and Baetis sp.), but barcodes in the NJ tree dis-
tinguished 6 clusters, 4 of which are similar genetically
(B. adonis 1vsB. tricaudatus 1, B. adonis 2vsB. tricau-
datus 3; Figs 2, S1A). The above approach was applied to
most specimens collected, and most barcode species were
defined based on individuals with full (658 bp) sequences.
Additional examination of delimitation challenges and ana-
lytical options for Simulium,Baetis, and Eukiefferiella can
be found in White et al. (2014).
If a short sequence (<350 bp) had <2% divergence
match to a long sequence (>350 bp), then it was given the
designated MOTU name associated with that >350 bp se-
quence. To make the barcode data comparable to the mor-
phology data (i.e., include all individuals identified mor-
phologically), specimens that did not have a barcode (i.e.,
no sequence or a short sequence <350 bp that did not
match a >350 bp sequence) were assigned the morphology-
based designation. These individuals were counted as a
new OTU if they had not been barcoded and it was the
only time it occurred in the sample, but if it had been
sampled as a barcoded taxon then it did not add to richness
measures. This approach to assigning names to individuals
that did not have a barcode was conservative and may
have underestimated barcode richness, but it affected rela-
tively few individuals (392 of 5870 [6.7%] across 5 sites, in-
cluding 278 [70.9%] at Conejo) and allowed us to include
all individuals collected in the analyses.
RESULTS
Biodiversity revealed by barcoding: taxonomic
resolution and cryptic species
We identified a total of 200 species across the 5 streams
(Table 1), 191 based on barcodes and 9 based on morphol-
ogy because no or inadequate barcodes were obtained. To-
tal richness for individual streams was far less than the
regional total, and ranged from 91 and 95 species at EF and
WF San Gabriel, respectively, to 38 species at Big Tujunga
Wash, 45 species at Arroyo Seco, and 46 species at Conejo.
Most (167) of these species were insects. Among the 191
species delimited based on barcodes, most were defined
with complete (652–658 bp) COI sequences and >1 indi-
Figure 1. Number of pairwise comparisons vs % genetic dis-
tance for Ephemeroptera (A), Plecoptera (B), Trichoptera (C),
Coleoptera (D), Diptera without chironomids (E), Chirono-
midae (F), and Arachnida (G) collected from 5 California
streams in June 2010. Solid and dashed vertical lines indicate
divergence used to separate molecular operational taxonomic
units (MOTUs): 2% for all groups except Baetis (1%) and
Simulium (3%).
000 | Cryptic biodiversity in streams J. K. Jackson et al.
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viduals. Of the 55 species represented by only 1 specimen,
only 8 had sequence lengths <652 bp (407–634 bp). Differ-
ent species in the same genus were relatively distinct ge-
netically, with a mean divergence of 13.3% (range = 2.0–
29.7%). Thus, interspecific differences were, on average,
5×greater than the 2% threshold used to delimit most
species. Valid species names could be assigned to only 34
(18%) of the 191 barcoded species (Fig. S1). Eleven names
were based on our morphological identifications, whereas
23 names came from the barcode library in BOLD or
GenBank. The remaining barcode MOTUs did not closely
match (i.e., >2% difference) any species with sequences in
the barcode library in BOLD or were a match to a BOLD
specimen identified only to genus or higher.
The objective of the morphological identifications ini-
tially used in our study was not to identify individuals to
the lowest taxonomic level possible, but rather, to a pre-
determined, standard level that balanced availability of
keys, effort, and information gained (i.e., Richards and
Rogers 2006). The standard level in most cases was genus,
but species-level identifications were standard for some
genera (especially Baetis, but also Diphetor,Calineuria,
Ordobrevia,Eubrianax,andPsephenus, which are all mono-
typic in California). Of the 96 morphological taxa iden-
tified among these 5 streams, 18 (19%) were species and
69 (72%) were genera, and only 9 (9%) were family or
higher. Of the 5870 specimens examined morphologically,
22% were identified to species, 74% to genus, and only
4% identified to family or higher. Barcodes revealed that
many of the genera and species identified morphologically
might actually represent >1 species. For example, of the
18 species or species groups initially identified based on
morphology alone, 6 (Ephemerella maculata,Drunella co-
loradensis,Baetis adonis,Diphetor hageni,Microtendipes
pedellus grp., Microtendipes rydalensis grp.) represented
2 species based on barcodes, whereas Baetis tricaudatus
represented 3 species. In addition, among the 69 genera
with no species identified morphologically, 16 represented
2 species based on barcodes, and another 16 had 3 to
10 species. If all specimens were identified only to genus
or higher (as in many stream-monitoring programs), 19 of
84 genera would have been represented by 2 species, and
an additional 19 genera would have been represented by 3
to 10 species (based on barcodes). Many of the genera
with multiple species were chironomids (19 of 38), but
other groups, such as caddisflies (6 genera with multiple
species), mayflies (5 genera), mites (4 genera), and nonchi-
ronomid Diptera (3 genera) were represented. Polypedi-
lum (10 species), Eukiefferiella (9 species), Cricotopus,and
Tanytarsus (8 species each) were especially speciose.
Barcodes also allowed identification of 100 specimens
(1.7% of total) that were too small to be identified mor-
phologically beyond family and allowed us to group these
specimens with conspecifics (e.g., Ephemerellidae to Ser-
ratella micheneri, Heptageniidae to Ecdyonurus criddlei,
Hydropsychidae to Hydropsyche 1 or 2, Libellulidae to Pal-
tothemis lineatipes, Empididae to Neoplasta, Stratiomyi-
dae to Caloparyphus/Euparyphus 1, 2, or 3). Barcodes also
detected individuals that initially had been misidentified
based on morphology so they could be re-examined and
properly grouped with conspecifics. For example, the ini-
tial identifications of 228 midges (15% of the chironomids)
and 49 Baetis adonis,Baetis tricaudatus,orBaetis CA 1
(4.7% of the Baetis) were changed to reflect the correct
genus/species. Based on morphological misidentifications,
several chironomid genera (Tanytarsus vs Micropsectra,
Figure 2. Number of pairwise comparisons vs % genetic distance for pairs of genetically similar Baetis molecular operational
taxonomic units (MOTUs) (Baetis adonis 2vsBaetis tricaudatus 3 and B. adonis 1vsB. tricaudatus 1); numbers after a name
indicates our MOTU designations (see neighbor-joining [NJ] trees in Fig. S1A–I). All individuals were collected from 5 California
streams in June 2010. Baetis adonis 2 had only 4 individuals so intraspecific variation (maximum = 0.002%) is not shown.
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Eukiefferiella vs Cardiocladius,Eukiefferiella vs Ortho-
cladius,Orthocladius vs Cricotopus) appeared to be espe-
cially challenging for the taxonomists. However, in our
study, chironomid identifications to genus were based pri-
marily on gross body morphology rather than detailed
head-capsule characteristics that are essential elements in
chironomid keys.
Biodiversity and rare species detected by barcoding
Many species (86 of 200, 43%) were represented by only
1 (29%) or 2 (14%) of the 5870 specimens examined and,
therefore, generally were found at only 1 stream. Similarly,
45 to 63% of the species at a site were represented by only
1 or 2 of the ∼1200 specimens examined at each site. Over
half (121) of the species were found at only 1 of the 5 sites.
Thus, many of the macroinvertebrate taxa in these streams
were relatively rare in samples within and among sites.
Many of the differences among streams presumably reflect
the environmental stressors associated with urban or agri-
cultural development at Big Tujunga Wash, Arroyo Seco,
and Conejo that eliminated some pollution-sensitive spe-
cies and created new opportunities for some pollution-
tolerant species. However, even 2 neighboring streams (WF
and EF San Gabriel) with limited anthropogenic influences
supported faunas that differed in the species present. For
example, 47 of the 95 (49%) barcode species at WF San
Gabriel were not collected at EF San Gabriel (i.e., unique
taxa), and 44 of 91 (48%) barcode species at EF San Gabriel
were not collected at WF San Gabriel (Fig. 3). In addition,
47 of the 95 (49%) barcode species at WF San Gabriel and
43 of 91 (46%) barcode species at EF San Gabriel were
represented by only 1 or 2 of the ∼1200 specimens exam-
ined (∼0.1–0.2% of the specimens at each site; Fig. 3).
Thus, whether rarity is defined spatially (at only 1 site) or
numerically (only 1–2 specimens per site), almost ½ of the
macroinvertebrate taxa at the 2 San Gabriel sites would be
considered rare.
High frequency of rare species increases the number
of individuals requiring examination when describing a
local or regional fauna. Species accumulation curves for
individual sites approached horizontal asymptotes for Big
Tujunga Wash, Arroyo Seco, and Conejo (Fig. 4), results
suggesting that the sampling effort (∼1200 individuals)
had produced a reasonably accurate representation of the
spring/summer macroinvertebrate faunas for these sites.
Examining additional specimens would not add much to
the total number of species found at these sites, even for
chironomid midges (Fig. 5). The accumulation curves for
WF and EF San Gabriel also began to level out toward
horizontal asymptotes, but increasing the number of in-
dividuals examined from 1000 to 1200 at either stream
added 3 to 4 additional species (primarily chironomid
midges; Figs 4, 5). The accumulation curve for 5 streams
combined was similar to the curves for WF and EF San
Gabriel (i.e., increasing the number of individuals exam-
ined from 5500 to 5700 added 3 to 4 additional species;
Fig. 4). This result indicates that we have a reasonably
good representation of the regional fauna in the spring/
summer, although some species in this region probably
were not collected in our study.
Figure 3. Molecular operational taxonomic units (MOTUs)
for the West Fork (WF) and East Fork (EF) of the San Gabriel
River sorted into 4 groups based on presence and abundance:
unique low density (at only 1 site and ≤2 individuals), unique
abundant (at only 1 site and ≥3 individuals), common low den-
sity (at both sites but ≤2 individuals at specified site), and com-
mon abundant (at both sites and ≥3 individuals at specified site).
Figure 4. Species accumulation curves for all barcode mo-
lecular operational taxonomic units (MOTUs) in 5 California
(CA) streams collectively and individually and 1 Pennsylvania
stream (White Clay Creek). Values were based on resampling
1000 times. WF = West Fork, EF = East Fork.
000 | Cryptic biodiversity in streams J. K. Jackson et al.
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Implications of cryptic biodiversity
revealed by barcodes
If we assume that morphological data yielded a con-
servative estimate of species richness in our study (i.e.,
assume a genus was represented by only 1 species unless
otherwise indicated), barcodes identified 104 more spe-
cies than were identified with morphology alone across
the 5 streams (96 taxa vs 200 species), a 108% increase
(Table 1). Richness increases were greatest for Chirono-
midae (60 additional species, 194% increase), followed by
Ephemeroptera (10 species, 77% increase), Acari (10 spe-
cies, 200% increase), and Trichoptera (6 species, 50% in-
crease). The increase in total richness per stream ranged
from 34 species at WF San Gabriel and 40 at EF San
Gabriel to 12 species at Big Tujunga Wash, 24 species at
Arroyo Seco, and 16 species at Conejo (Table 1). The in-
crease was greater for the WF and EF San Gabriel sites,
which are in watersheds with much less intensive land
use than the other 3 watersheds. If we use the WF San
Gabriel as a reference site, then barcoding increased the
species loss from environmental stress by 22 species (63%)
at Big Tujunga Wash, 10 species (25%) at Arroyo Seco,
and 18 species (58%) at Conejo (Table 1). Thus, relying on
morphology alone underestimated the loss of biodiversity
in response to environmental stress in these streams by 25
to 63%.
Barcode identifications also found more subtle differ-
ences among sites that reflected species replacements
within a genus rather than just lost species. This effect
was observed between reference sites, between potentially
impaired sites, and between reference and potentially im-
paired sites. For example, the dominant species of Si-
mulium and Orthocladius at EF San Gabriel were not
dominant at WF San Gabriel (Fig. 6B, C). The dominant
species of Orthocladius at Arroyo Seco was not domi-
nant at Big Tujunga Wash (the 2 similarly situated de-
graded sites) (Fig. 6C). In addition to the species losses at
Big Tujunga Wash and Arroyo Seco relative to WF and
EF San Gabriel (Table 1), the dominant species changed
for several genera (e.g., Baetis and Simulium [Fig. 6A, B],
Eukiefferiella,Rheotanytarsus). None of these differences
among sites would have been apparent had the compari-
sons relied on morphology to produce only genus-level
identifications. As a result, the similarity (Jaccard index)
between sites decreased when genus data were converted
to species (i.e., barcodes) (Table 2). For example, the sim-
ilarity between WF and EF San Gabriel decreased from
58 to 35.
DISCUSSION
Species identifications based on barcodes
Barcodes from the benthic macroinvertebrates collected
from the 5 streams identified >100 more taxa than were
identified based on morphology alone and resulted in pu-
tative species-level designations for 93% of the individuals
examined. This percentage is a significant increase in the
number of individuals identified to species relative to the
results of most studies of benthic macroinvertebrates. Car-
ter and Resh (2001) found that larval Ephemeroptera, Ple-
coptera, and Trichoptera were left at the genus or higher
level in 54 to 56% of state monitoring programs, and chi-
ronomid midges were left at the genus or higher level in
70% of the programs. In 3 studies, investigators attempted
Figure 5. Species accumulation curves for barcode molecular operational taxonomic units (MOTUs) of 3 common groups in 3 creeks:
White Clay Creek, WF San Gabriel River, and Big Tujunga Wash. In Big Tujunga Wash >800 Trichoptera were examined but the asymp-
tote was reached and the line cropped after a resampling of 150 individuals. MOTU values were based on resampling 1000 times.
Volume 33 March 2014 | 000
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to identify as many specimens as possible to species based
on morphology. Waite et al. (2004) took 25% of the speci-
mens from 490 streams to species, Arscott et al. (2006)
took 36% of the specimens from 60 streams to species,
and Sweeney et al. (2011) took 46% of the specimens from
1 stream to species.
Genetic divergence among species in a genus averaged
13% across all macroinvertebrate groups examined. Thus,
most of the species we identified had genetic divergences
that far exceeds our 2% cut offfor delimiting species and
were well differentiated from their nearest neighbors. Ge-
netic differences between nearest neighbors approached
or marginally exceeded our 2% cut offfor delimiting spe-
cies in only 8 species pairs or groups among the 191
MOTUs. The genetic differentiation we observed among
species was similar in magnitude to results of more fo-
cused taxonomic studies that found good agreement be-
tween morphological and barcode species and numerous
morphologically cryptic species that were genetically dis-
tinct (e.g., Monaghan et al. 2005, Stahls and Savolainen
2008, Pauls et al. 2010, Zhou et al. 2010, 2011, Lucentini
et al. 2011, Mynott et al. 2011, Harvey et al. 2012, Kim et al.
2012, Larson et al. 2012, Renaud et al. 2012, Webb et al.
2012). We recognize the importance of discussions of spe-
cies delimitation and species concepts (e.g., Agapow et al.
2004, Sites and Marshall 2004, DeSalle et al. 2005, Pons
et al. 2006) and concerns about taxonomic inflation (e.g.,
Isaac et al. 2004, Zachos et al. 2013), but we think that the
vast majority of the species identified in our study are dis-
tinct species and that when barcode libraries are more
complete, many will match up well with morphologically
defined species known to occur in this region. For exam-
ple, 306 mayfly species, 379 stonefly species, 746 caddisfly
species, and 516 chironomid species, most of which are
not in the barcode library of BOLD and GenBank, are
currently listed on the California inventory maintained by
the Southwest Association of Freshwater Invertebrate Tax-
onomists (http://www.safit.org/ste.html).
Questions concerning species delimitation, species
concepts, and taxonomic inflation may become an issue
for stream macroinvertebrates in the future as barcode
libraries expand to include more species, and species are
better represented by specimens from sites across a
wider geographic range (Bergsten et al. 2012, Webb et al.
2012, Anderson et al. 2013). However, the biggest im-
pediment to accurate identification of benthic macro-
invertebrates is that diagnostic morphological characters
for species frequently are unknown or nonexistent for the
life stages most commonly collected from streams or riv-
ers (i.e., immature larvae of species identified by adult
male characters). We think that COI barcodes and other
genetic data are additional characters that may facilitate
morphological identifications by helping to associate lar-
vae with named adults and to differentiate between intra-
and interspecific variation in morphology. We do not view
barcodes as a replacement for morphological characters,
but as a tool to help resolve species by confirming and
directing morphological effort and by pushing taxonomic
resolution beyond the limits of morphology for many
specimens (e.g., larval chironomid midges, mayflies, stone-
flies, caddisflies). We also recognize that COI barcodes
may not be able to resolve all species relationships (e.g.,
Figure 6. Differences among the 5 California streams for
Baetis (A), Simulium (B), and Orthocladius (C) containing mul-
tiple species. Conejo Creek had no Simulium or Orthocladius.
000 | Cryptic biodiversity in streams J. K. Jackson et al.
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Shaw 2002, Whitworth et al. 2007, Alexander et al. 2009,
Chen et al. 2012), and that other DNA methods may occa-
sionally give different results or give rise to questions about
delimiting/distinguishing closely related species. That said,
our study provides additional evidence that barcodes have
the potential to increase greatly the frequency and accu-
racy of species identifications from commonly collected
benthic macroinvertebrate samples.
Biodiversity and rare species detected by barcoding
Barcodes have been used primarily to discriminate or
describe relationships among closely related species or a
number of species within a genus or family (Hebert et al.
2004a, Smith et al. 2006, Burns et al. 2008, Pauls et al. 2010,
Anderson et al. 2013, but see also Hebert et al. 2004b, Ward
et al. 2005, Hajibabaei et al. 2006, Dincăet al. 2011, Webb
et al. 2012). It is unusual for a single barcode study to ex-
amine numerous individuals across a wide range of unre-
lated species within a small region as we have done here. In
the most similar effort, investigators examined 1579 benthic
macroinvertebrates from 2 sites in a small stream (White
Clay Creek [WCC]) in southeastern Pennsylvania (PA) at
about the same altitude but >3500 km east of the streams in
our study (Sweeney et al. 2011). A comparison of the results
of these 2 studies provides interesting insights into the
structure of stream macroinvertebrate communities and the
frequency of morphologically cryptic species. First, in both
studies, many species that could not be or were not resolved
based on morphological characters present in the specimens
collected were identified based on barcodes (104 more spe-
cies [108% increase] for California (CA); 86 more species
[78% increase] for PA). Many species identified with
barcodes were rare spatially (at only 1 site) or numerically
(represented by 1 or 2 specimens). Rare taxa (species or
genera) repeatedly have been a subject of interest in the
study of stream macroinvertebrate communities (e.g., Cao
and Williams 1999, Lenat and Resh 2001, Nijboer and
Verdonschot 2004, Arscott et al. 2006, Van Sickle et al.
2007, Heino and Soininen 2010, Poos and Jackson 2012,
Heino 2013, and references therein). Little agreement
exists among investigators regarding the value/contribu-
tion of rare taxa. Some authors have concluded they are
redundant, whereas others have found them informative,
especially if the goal is to detect subtle changes or if they
are diagnostic of different stream conditions. Many of
these authors analyzed data sets in which most the speci-
mens were not identified to species, and therefore, the full
impact of species identifications has not yet been exam-
ined.
Second, the total number of species was greater at the
PA site than at any individual CA site and was comparable
to the total number of species in the 5 CA streams com-
bined (Table 1). Species accumulation curves for each site
showed the potential differences in the number of speci-
mens needed to describe the fauna at a site or for a region
(e.g., WCC > CA, WF San Gabriel > Arroyo Seco) (Figs 4,
5). Differences between CA and PA are evidence that these
macroinvertebrate communities are structured differently,
with more species at WCC relative to any of the CA sites
at similar sampling efforts. Thus, sampling efforts recom-
mended to characterize a local fauna (e.g., Vinson and Haw-
kins 1996, Cao et al. 2007, Cao and Hawkins 2011) may
vary depending on whether sampling focuses on more or
less speciose habitats, regions, or taxonomic groups (e.g.,
Chironomidae vs Ephemeroptera, Plecoptera, Trichoptera).
Implications of cryptic biodiversity
revealed by barcoding
Our results and those of Sweeney et al. (2011) clearly
show that reliance on morphology has limited our per-
ception of macroinvertebrate biodiversity in streams and
rivers and of the loss of biodiversity in response to envi-
ronmental stressors. Using barcodes in the identification
process would greatly increase the number of species col-
lected at a site, especially reference sites and, therefore,
would produce a more accurate estimate of the biodiver-
sity lost at an impaired site. Increased frequency of spe-
cies identifications will be an important step toward gen-
Table 2. Similarity between sites as measured with the Jaccard index. WF = West Fork, EF = East Fork.
Stream Taxonomic level Conejo EF San Gabriel Arroyo Seco WF San Gabriel
Big Tujunga Wash Genus 26 23 38 25
Species 13 9 34 14
Conejo Genus . 14 20 16
Species . 3 10 5
EF San Gabriel Genus . . 28 58
Species . . 18 35
Arroyo Seco Genus . . . 19
Species . . . 13
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erating the data and insights needed to put discussions
regarding protection and management of streams based
on data involving aquatic macroinvertebrates on the same
level with ongoing, similar conversations involving plants,
fish, amphibians, reptiles, birds, and mammals (all of which
are species based). At present, we cannot discuss in a robust
fashion macroinvertebrate species’presence or absence,
rarity or abundance, stability or variability for streams and
rivers anywhere in the world. We cannot truly understand
abiotic or biotic interactions if we do not know the species
involved. Last, connections to and impacts of our scientific
communications are limited and possibly inaccurate if the
names we use are incorrect or too general.
Species-level identifications will become more informa-
tive as we replace our current understanding of stream
macroinvertebrates (largely genus- or family-based) with
knowledge of the basic biology for individual species. We
need to know if species have narrow or broad environmen-
tal requirements in natural settings and how this translates
into sensitivity to or tolerance of anthropogenic changes in
water or habitat quality (Heino 2013). Use of species-based
biology will be a major change in functional traits-based
approaches to understanding macroinvertebrate commu-
nity structure and applications to biomonitoring that refer
to species traits but actually use genus- or family-level char-
acteristics (e.g., Poff1997, Poffet al. 2006, Heino et al.
2007, Statzner and Bêche 2010, Heino 2013) that (often
unknowingly) homogenize species-level differences (e.g.,
Janzen et al. 2012). Species-specific insights may not be
needed to identify highly impaired stream sites because
the level of impairment often involves loss of entire genera
or families. However, species-level data would improve
our ability to identify, with confidence, subtle changes in
macroinvertebrate communities and, hence, water quality
in streams and rivers. This ability would be invaluable for
detecting and assessing impacts to streams and rivers in a
more timely fashion (before serious degradation occurs)
and would provide more rapid measurement of the rate
and degree of stream and river recovery in response to
improved watershed management or proactive stream and
river restoration.
ACKNOWLEDGEMENTS
We thank Kristin Smith, JeffBrown, and Greg Lyon of
Southern California Coastal Water Research Project for assis-
tance with macroinvertebrate collections, with added assistance
from California State University Stanislaus students Veronica
Menendez, Tamera Rogers, and Brittany Bjelde. Morphological
identifications were provided by Daniel Pickard and the staffat
the Department of Fish and Game Aquatic Bioassessment Lab-
oratory at California State University Chico. Stephanie Liguori
of the Stroud Water Research Center was responsible for pre-
paring DNA samples for processing. Sequencing of the DNA
barcodes was done by the Canadian Centre for DNA Barcoding
with funds from the Life Technologies Corporation, and at the
US Environmental Protection Agency in Cincinnati, Ohio. Mel-
anie Arnold of the Stroud Water Research Center helped with
statistical programming and analyses. We thank Associate Editor
Michael T. Monaghan and 2 anonymous referees for comments
that improved an earlier version of this manuscript. Support for
work at the Stroud Water Research Center was provided by
Southern California Coastal Water Research Project, the Penns-
wood Endowment Fund, and the Stroud Water Research Center
Endowment Funds. This is Stroud Contribution 2013008.
LITERATURE CITED
Agapow, P. M., O. R. P. Bininda-Emonds, K. A. Crandall, J. L.
Gittleman, G. M. Mace, J. C. Marshall, and A. Purvis. 2004.
The impact of species concept on biodiversity studies. Quar-
terly Review of Biology 79:161–179.
Alexander, L. C., M. Delion, D. J. Hawthorne, W. O. Lamp, and
D. H. Funk. 2009. Mitochondrial lineages and DNA bar-
coding of closely related species in the mayfly genus Ephem-
erella (Ephemeroptera:Ephemerellidae). Journal of the North
American Benthological Society 28:584–595.
Anderson, A. M., E. Stur, and T. Ekrem. 2013. Molecular and
morphological methods reveal cryptic diversity and three
new species of Nearctic Micropsectra (Diptera:Chironomi-
dae). Freshwater Science 32:892–921.
Arscott, D. B., J. K. Jackson, and E. B. Kratzer. 2006. Role of rar-
ity and taxonomic resolution in a regional and spatial analysis
of stream macroinvertebrates. Journal of the North American
Benthological Society 25:977–997.
Bergsten, J., D. T. Bilton, T. Fujisawa, M. Elliott, M. T. Mona-
ghan, M. Balke, J. Hermann, G. N. Foster, A. N. Nilsson, T. G.
Barraclough, and A. P. Vogler. 2012. The effect of geographi-
cal scale of sampling on DNA barcoding. Systematic Biology
61:851–869.
Bowman, M. F., and R. C. Bailey. 1997. Does taxonomic resolu-
tion affect the multivariate description of the structure of
freshwater benthic macroinvertebrate communities? Cana-
dian Journal of Fisheries and Aquatic Sciences 54:1802–1807.
Burns, J. M., D. H. Janzen, M. Hajibabaei, W. Hallwachs, and
P. D. N. Hebert. 2008. DNA barcodes and cryptic species of
skipper butterflies in the genus Perichares in Area de Conser-
vación Guanacaste, Costa Rica. Proceedings of the National
Academy of Sciences of the United States of America 105:
6350–6355.
Cao, Y., and C. P. Hawkins. 2011. The comparability of bio-
assessments: a review of conceptual and methodological is-
sues. Journal of the North American Benthological Society
30:680–701.
Cao, Y., C. P. Hawkins, D. P. Larsen, and J. Van Sickle. 2007. Ef-
fects of sample standardization on mean species detectabilities
and estimates of relative differences in species richness among
assemblages. American Naturalist 170:381–395.
Cao, Y., and D. D. Williams. 1999. Rare species are important
in bioassessment (reply to the comment by Marchant). Lim-
nology and Oceanography 44:1841–1842.
Carter, J. L., and V. H. Resh. 2001. After site selection and be-
fore data analysis: sampling, sorting, and laboratory proce-
dures used in stream benthic macroinvertebrate monitoring
programs by USA state agencies. Journal of the North Amer-
ican Benthological Society 20:658–682.
000 | Cryptic biodiversity in streams J. K. Jackson et al.
This content downloaded from 12.28.106.2 on Tue, 14 Jan 2014 09:10:12 AM
All use subject to JSTOR Terms and Conditions

Chen, R., L. Y. Jiang, and G. X. Qiao. 2012. The effectiveness of
three regions in mitochondrial genome for aphid DNA bar-
coding: a case in Lachininae. PLoS ONE 7:e46190.
DeSalle, R., M. G. Egan, and M. Siddall. 2005. The unholy
trinity: taxonomy, species delimitation and DNA barcoding.
Philosophical Transactions of the Royal Society of London
Series B: Biological Sciences 360:1905–1916.
Dincă, V., E. V. Zakharov, P. D. N. Hebert, and R. Vila. 2011.
Complete DNA barcode reference library for a country’s but-
terfly fauna reveals high performance for temperate Europe.
Proceedings of the Royal Society of London Series B: Bio-
logical Sciences 278:347–355.
Duan, Y., S. I. Guttman, J. T. Oris, and A. J. Bailer. 2000. Ge-
netic structure and relationships among populations of
Hyalella azteca and H. montezuma (Crustacea:Amphipoda).
Journal of the North American Benthological Society 19:
308–320.
Fremling, C. R. 1991. Hexagenia mayflies (Ephemeroptera:
Ephemeridae): biological monitors of water quality in the
upper Mississippi River. Pages 118–128 in L. G. Sanders
(editor). Techniques for Evaluating Aquatic Habitats in
Rivers, Streams, and Reservoirs; Proceedings of a Workshop.
Miscellaneous Paper W-91-2. Waterways Experiment Sta-
tion, US Army Corps of Engineers, Vicksburg, Mississippi.
Funk, D. H., B. W. Sweeney, and J. K. Jackson. 2008. A taxonomic
reassessment of the Drunella lata (Morgan) species complex
(Ephemeroptera:Ephemerellidae) in northeastern North Amer-
ica. Journal of the North American Benthological Society 27:
647–663.
Funk, D. H., B. W. Sweeney, and R. L. Vannote. 1988. Electro-
phoretic study of eastern North American Eurylophella
(Ephemeroptera: Ephemerellidae) with the discovery of mor-
phologically cryptic species. Annals of the Entomological So-
ciety of America 81:174–186.
Greffard, M. H., É. Saulnier-Talbot, and I. Gregory-Eaves. 2011.
A comparative analysis of fine versus coarse taxonomic res-
olution in benthic chironomid community analyses. Ecologi-
cal Indicators 11:1541–1551.
Hajibabaei, M., D. H. Janzen, J. M. Burns, W. Hallwachs, and
P. D. N. Hebert. 2006. DNA barcodes distinguish species of
tropical Lepidoptera. Proceedings of the National Academy
of Sciences of the United States of America 103:968–971.
Harvey, L. E., C. J. Geraci, J. L. Robinson, J. C. Morse, K. M.
Kjer, and X. Zhou. 2012. Diversity of mitochondrial and
larval morphology characters in the genus Diplectrona (Tri-
choptera: Hydropsychidae) in the eastern United States. Ter-
restrial Arthropod Reviews 5:191–211.
Hebert, P. D. N., A. Cywinska, S. L. Ball, and J. R. deWaard.
2003a. Biological identifications through DNA barcodes. Pro-
ceedings of the Royal Society of London Series B: Biological
Sciences 270:313–321.
Hebert, P. D. N., E. H. Penton, J. M. Burns, D. H. Janzen, and
W. Hallwachs. 2004a. Ten species in one: DNA barcoding
reveals cryptic species in the Neotropical skipper butterfly
Astraptes fulgerator. Proceedings of the National Academy of
Sciences of the United States of America 101:14812–14817.
Hebert, P. D. N., S. Ratnasingham, and J. R. deWaard. 2003b.
Barcoding animal life: cytochrome coxidase subunit 1 di-
vergences among closely related species. Proceedings of the
Royal Society of London Series B: Biological Sciences 270
(Supplement 1):S596–S599.
Hebert, P. D. N., M. Y. Stoeckle, T. S. Zemlak, and C. M. Francis.
2004b. Identification of birds through DNA barcodes. PLoS
Biology 2:e312.
Heino, J. 2013. The importance of metacommunity ecology for
environmental assessment research in the freshwater realm.
Biological Reviews 88:166–178.
Heino, J., H. Mykrä, J. Kotanen, and T. Muotka. 2007. Ecologi-
cal filters and variability in stream macroinvertebrate com-
munities: do taxonomic and functional structure follow the
same path? Ecography 30:217–230.
Heino, J., and J. Soininen. 2010. Are common species sufficient
in describing turnover in aquatic metacommunities along
environmental and spatial gradients? Limnology and Ocean-
ography 55:2397–2402.
Hogg, I. D., M. I. Stevens, K. E. Schnabel, and M. A. Chapman.
2005. Deeply divergent lineages of the widespread New Zea-
land amphipod Paracalliope fluviatilis revealed using allo-
zyme and mitochondrial DNA analyses. Freshwater Biology
51:236–248.
Humpesch, U., and C. Fesl. 2005. Biodiversity of macrozoo-
benthos in a large river, the Austrian Danube, including quan-
titative studies in a free-flowing stretch below Vienna: a short
review. Freshwater Forum 24:3–23.
Isaac, N. J., J. Mallet, and G. M. Mace. 2004. Taxonomic infla-
tion: its influence on macroecology and conservation. Trends
in Ecology and Evolution 19:464–469.
Ivanova, N. V., J. R. deWaard, and P. D. N. Hebert. 2006. An
inexpensive, automation-friendly protocol for recovering
high-quality DNA. Molecular Ecology Notes 6:998–1002.
Jackson, J. K., and V. H. Resh. 1992. Variation in genetic struc-
ture among populations of the caddisflyHelicopsyche borealis
from three streams in northern California, U.S.A. Freshwater
Biology 27:29–42.
Jackson, J. K., and V. H. Resh. 1998. Morphologically cryptic
species confounding ecological studies of the caddisfly genus
Gumaga (Sericostomatidae) in northern California. Aquatic In-
sects 20:69–84.
Janzen, D. H., W. Hallwachs, D. J. Harvey, K. Darrow, R.
Rougerie, M. Hajibabaei, M. A. Smith, C. Bertrand, I. C.
Gamboa, B. Espinoza, J. B. Sullivan, T. Decaens, D. Herbin,
L. F. Chavarria, R. Franco, H. Cambronero, S. Rios, F.
Quesada, G. Pereira, J. Vargas, A. Guadamuz, R. Espinoza, J.
Hernandez, L. Rios, E. Cantillano, R. Moraga, C. Moraga, P.
Rios, M. Rios, R. Calero, D. Martinez, D. Briceño, M. Car-
mona, E. Apu, K. Aragon, C. Umaña, J. Perez, A. Cordoba,
P. Umaña, G. Sihezar, O. Espinoza, C. Cano, E. Araya, D.
Garcia, H. Ramirez, M. Pereira, J. Cortez, M. Pereira, W.
Medina, and P. D. N. Hebert. 2012. What happens to the
traditional taxonomy when a well-known tropical saturniid
moth fauna is DNA barcoded? Invertebrate Systematics 26:
478–505.
Jones, F. C. J. F. 2008. Taxonomic sufficiency: the influence of
taxonomic resolution on freshwater bioassessments using
benthic macroinvertebrates. Environmental Reviews 16:45–69.
Kim, S., K. H. Song, H. I. Ree, and W. Kim. 2012. A DNA barcode
library for Korean Chironomidae (Insecta: Diptera) and in-
dexes for defining barcode gap. Molecules and Cells 1:9–17.
Volume 33 March 2014 | 000
This content downloaded from 12.28.106.2 on Tue, 14 Jan 2014 09:10:12 AM
All use subject to JSTOR Terms and Conditions

Larson, E. R., C. L. Abbott, N. Usio, N. Azuma, K. A. Wood,
L. M. Herborg, and J. D. Olden. 2012. The signal crayfish is
not a single species: cryptic diversity and invasions in the
Pacific Northwest range of Pacifastacus leniusculus. Fresh-
water Biology 57:1823–1838.
Lenat, D. R. 1993. A biotic index for the southeastern United
States: derivation and list of tolerance values, with criteria
for assigning water-quality ratings. Journal of the North
American Benthological Society 12:279–290.
Lenat, D. R., and V. H. Resh. 2001. Taxonomy and stream ecology:
the benefits of genus- and species-level identifications. Journal
of the North American Benthological Society 20:287–298.
Lucentini, L., M. Rebora, M. E. Puletti, L. Gigliarelli, D.
Fontaneto, E. Gaino, and F. Panara. 2011. Geographical and
seasonal evidence of cryptic diversity in the Baetis rhodani
complex (Ephemeroptera, Baetidae) revealed by means of
DNA taxonomy. Hydrobiologia 673:215–228.
Meyer, C. P., and G. Paulay. 2005. DNA barcoding: error rates
based on comprehensive sampling. PLoS Biology 3:e422.
Monaghan, M. T., M. Balke, T. R. Gregory, and A. P. Vogler.
2005. DNA-based species delineation in tropical beetles us-
ing mitochondrial and nuclear markers. Philosophical Trans-
actions of the Royal Society of London Series B: Biological
Sciences 360:1925–1933.
Monk, W. A., P. J. Wood, D. M. Hannah, C. A. Extence, R. P.
Chadd, and M. J. Dunbar. 2012. How does macroinverte-
brate taxonomic resolution influence ecohydrological rela-
tionships in riverine ecosystems. Ecohydrology 5:36–45.
Morse, J. C., J. W. Chapin, D. D. Herlong, and R. S. Harvey.
1980. Aquatic insects of Upper Three Runs Creek, Savannah
River Plant, South Carolina. Part I: orders other than Diptera.
Journal of the Georgia Entomological Society 15:73–101.
Morse, J. C., J. W. Chapin, D. D. Herlong, and R. S. Harvey.
1983. Aquatic insects of Upper Three Runs Creek, Savannah
River Plant, South Carolina. Part II: Diptera. Journal of the
Georgia Entomological Society 18:303–316.
Mynott, J. H., J. M. Webb, and P. J. Suter. 2011. Adult and
larval associations of the alpine stonefly genus Riekoperla
McLellan (Plecoptera: Gripopterygidae) using mitochondrial
DNA. Invertebrate Systematics 25:11–21.
Nijboer, R. C., and P. F. Verdonschot. 2004. Rare and common
macroinvertebrates: definition of distribution classes and
their boundaries. Archiv für Hydrobiologie 161:45–64.
Ode, P. R. 2007. Standard operating procedures for collecting
macroinvertebrate samples and associated physical and chemi-
cal data for ambient bioassessments in California. Bioassess-
ment SOP 001. California State Water Resources Control Board
Surface Water Ambient Monitoring Program (SWAMP), Sac-
ramento, California. (Available from: http://www.waterboards
.ca.gov/water_issues/programs/swamp/docs/phab_sopr6.pdf)
Pauls, S. U., R. J. Blahnik, X. Zhou, C. T. Wardwell, and R. W.
Holzenthal. 2010. DNA barcode data confirm new species
and reveal cryptic diversity in Chilean Smicridea (Smicridea)
(Trichoptera:Hydropsychidae). Journal of the North Ameri-
can Benthological Society 29:1058–1074.
Poff, N. L. 1997. Landscape filters and species traits: towards
mechanistic understanding and prediction in stream ecology.
Journal of the North American Benthological Society 16:
391–409.
Poff, N. L., J. D. Olden, N. K. M. Vieira, D. S. Finn, M. P.
Simmons, and B. C. Kondratieff. 2006. Functional trait niches
of North American lotic insects: traits-based ecological ap-
plications in light of phylogenetic relationships. Journal of the
North American Benthological Society 25:730–755.
Pons, J., T. G. Barraclough, J. Gomez-Zurita, A. Cardoso, D. P.
Duran, S. Hazell, S. Kamoun, W. D. Sumlin, and A. P.
Vogler. 2006. Sequence-based species delimitation for the
DNA taxonomy of undescribed insects. Systematic Biology
55:595–609.
Poos, M. S., and D. A. Jackson. 2012. Addressing the removal
of rare species in multivariate bioassessments: the impact of
methodological choices. Ecological Indicators 18:82–90.
Ratnasingham, S., and P. D. N. Hebert. 2007. BOLD: the Bar-
code of Life Data System (http://www.barcodinglife.org). Mo-
lecular Ecology Notes 7:355–364.
Renaud, A. K., J. Savage, and S. J. Adamowicz. 2012. DNA
barcoding of northern Nearctic Muscidae (Diptera) reveals
high correspondence between morphological and molecular
species limits. BMC Ecology 12:24.
Resh, V. H., and J. D. Unzicker. 1975. Water quality monitoring
and aquatic organisms: the importance of species identifica-
tion. Journal of the Water Pollution Control Federation 47:
9–19.
Richards, A. B., and D. C. Rogers. 2006. List of the freshwater
macroinvertebrate taxa from California and adjacent states
including standard taxonomic effort levels. Southwest Asso-
ciation of Freshwater Invertebrate Taxonomists, Chico, Cali-
fornia. (Available from: www.safit.org)
Rivera, J., and D. C. Currie. 2009. Identification of Nearctic
black flies using DNA barcodes (Diptera: Simuliidae). Mo-
lecular Ecology Resources 9:224–236.
Schmidt-Kloiber, A., W. Graf, A. Lorenz, and O. Moog. 2006. The
AQEM/STAR taxa list −a pan-European macro-invertebrate
ecological database and taxa inventory. Hydrobiologia 566:
325–342.
Shaw, K. L. 2002. Conflict between nuclear and mitochondrial
DNA phylogenies of a recent species radiation: what mtDNA
reveals and conceals about modes of speciation in Hawaiian
crickets. Proceedings of the National Academy of Sciences of
the United States of America 99:16122–16127.
Sites, J. W., and J. C. Marshall. 2004. Operational criteria for
delimiting species. Annual Review of Ecology, Evolution,
and Systematics 35:199–227.
Smith, M. A., N. E. Woodley, D. H. Janzen, W. Hallwachs, and
P. D. N. Hebert. 2006. DNA barcodes reveal cryptic host-
specificity within the presumed polyphagous members of a
genus of parasitoid flies (Diptera: Tachinidae). Proceedings
of the National Academy of Sciences of the United States of
America 103:3657–3662.
Stahls, G., and E. Savolainen. 2008. mtDNA COI barcodes re-
veal cryptic diversity in the Baetis vernus group (Ephem-
eroptera, Baetidae). Molecular Phylogenetics and Evolution
46:82–87.
Statzner, B., and L. A. Bêche. 2010. Can biological invertebrate
traits resolve effects of multiple stressors on running water
ecosystems? Freshwater Biology 55:80–119.
Stein, E. D., M. R. Cover, A. E. Fetscher, C. O’Reilly, R. Guardado,
and C. W. Solek. 2013. Reach-scale geomorphic and bio-
000 | Cryptic biodiversity in streams J. K. Jackson et al.
This content downloaded from 12.28.106.2 on Tue, 14 Jan 2014 09:10:12 AM
All use subject to JSTOR Terms and Conditions

logical effects of localized stream bank armoring. Journal of
the American Water Resources Association 49:780–792.
Stein, E. D., B. P. White, R. D. Mazor, J. K. Jackson, J. M. Battle,
P. E. Miller, E. M. Pilgrim, and B. W. Sweeney. 2014. Does
DNA barcoding improve performance of traditional stream
bioassessment metrics? Freshwater Science 33:XXX–XXX.
Sweeney, B. W., J. M. Battle, J. K. Jackson, and T. Dapkey.
2011. Can DNA barcodes of stream macroinvertebrates im-
prove descriptions of community structure and water qual-
ity? Journal of the North American Benthological Society
30:195–216.
Tamura, K., J. Dudley, M. Nei, and S. Kumar. 2007. MEGA4:
molecular evolutionary genetic analysis (MEGA) software.
Version 4.0. Molecular Biology and Evolution 24:1596–1599.
Van Sickle, J., D. P. Larsen, and C. P. Hawkins. 2007. Exclusion
of rare taxa affects performance of the O/E index in bio-
assessments. Journal of the North American Benthological So-
ciety 26:319–331.
Vinson, M. R., and C. P. Hawkins. 1996. Effects of sampling area
and subsampling procedure on comparisons of taxa richness
among streams. Journal of the North American Benthological
Society 15:392–399.
Waite, I. R., A. T. Herlihy, D. P. Larsen, N. S. Urquhart, and
D. J. Klemm. 2004. The effects of macroinvertebrate taxo-
nomic resolution in large landscape bioassessments: an ex-
ample from the Mid-Atlantic Highlands, USA. Freshwater
Biology 49:474–489.
Ward, R. D., T. S. Zemlak, B. H. Innes, P. R. Last, and P. D. N.
Hebert. 2005. DNA barcoding Australia’sfish species. Philo-
sophical Transactions of the Royal Society of London Series B:
Biological Sciences 360:1847–1857.
Webb, J. M., L. M. Jacobus, D. H. Funk, X. Zhou, B. Kondratieff,
C. J. Geraci, R. E. DeWalt, D. J. Baird, B. Richard, I. Phillips,
and P. D. Hebert. 2012. A DNA barcode library for North
American Ephemeroptera: progress and prospects. PLoS ONE
7:e38063.
White, B. P., E. M. Pilgrim, L. M. Boykin, E. D. Stein, and R. D.
Mazor. 2014. Comparing four species delimitation methods
applied to a DNA barcode data set of insect larvae for use
in routine bioassessment. Freshwater Science 33:XXX–XXX.
Whitworth, T. L., R. D. Dawson, H. Magalon, and E. Baudry.
2007. DNA barcoding cannot reliably identify species of the
blowfly genus Protocalliphora (Diptera: Calliphoridae). Pro-
ceedings of the Royal Society of London Series B: Biological
Sciences 274:1731–1739.
Williams, H. C., S. J. Ormerod, and M. W. Bruford. 2006. Mo-
lecular systematics and phylogeography of the cryptic spe-
cies complex Baetis rhodani (Ephemeroptera, Baetidae). Mo-
lecular Phylogenetics and Evolution 40:370–382.
Zachos, F. E., M. Apollonio, E. V. Bärmann, M. Festa-Bianchet, U.
Göhlich, J. C. Habel, E. Haring, L. Kruckenhauser, S. Lovari,
A. D. McDevitt, C. Pertoldi, G. E. Rössner, M. R. Sánchez-
Villagra, M. Scandura, and F. Suchentrunk. 2013. Species infla-
tion and taxonomic artefacts—a critical comment on recent
trends in mammalian classification. Mammalian Biology 78:1–6.
Zhou, X., L. M. Jacobus, R. E. DeWalt, S. J. Adamowicz, and
P. D. N. Hebert. 2010. Ephemeroptera, Plecoptera, and Tri-
choptera fauna of Churchill (Manitoba, Canada): insights
into biodiversity patterns from DNA barcoding. Journal of
the North American Benthological Society 29:814–837.
Zhou, X., J. L. Robinson, C. J. Geraci, C. R. Parker, O. S. Flint,
D. A. Etnier, D. Ruiter, R. E. DeWalt, L. M. Jacobus, and
P. D. N. Hebert. 2011. Accelerated construction of a regional
DNA-barcode reference library: caddisflies (Trichoptera) in
the Great Smoky Mountains National Park. Journal of the
North American Benthological Society 30:131–162.
Zurwerra, A., M. Metzler, and I. Tomka. 1987. Biochemical sys-
tematics and evolution of the European Heptageniidae (Ephem-
eroptera). Archiv für Hydrobiologie 109:481–510.
Zwick, P. 1998. Australian net-winged midges of the tribe
Apistomyiini (Diptera: Blephariceridae). Australian Journal
of Entomology 37:289–311.
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