Distribution of Ephemeroptera, Plecoptera, and Trichoptera assemblages in relation to environmental variables in headwater streams of Mongolia

Abstract

Effects of stream environmental variables on the distribution and abundance of Ephemeroptera, Plecoptera and Trichoptera (EPT) assemblages in the headwaters of rivers and streams of Mongolia were investigated in this broad scale survey aimed to provide a baseline for future research and management of the country’s aquatic ecosystems. The survey was carried out in the first-, second- and third-order streams of 80 rivers selected from the three main watersheds of Mongolia, namely the Arctic Ocean Basin (AOB), Pacific Ocean Basin (POB) and Central Asian Internal Basin (CAIB). We sampled larvae of EPT by kick and D-nets from the headwater sites during summers of 2007–2009. Chemical and hydrological variables of the sites were measured, and habitat of those sites was assessed. We recorded 89 taxa belonging to 34 families of EPT orders during the survey. The family Baetidae (Ephemeroptera) was the dominant taxon among all sites. Taxon richness was higher in the POB and AOB than CAIB, while total EPT abundance was higher in the CAIB. Significant differences in the community variables, such as taxon richness, Shannon’s diversity index and evenness of EPT assemblages were observed among the basins. Results of canonical correspondence analysis suggested that altitude, dissolved oxygen, order and width of streams were the most important factors explaining the variability in EPT larval distribution in the headwater streams in Mongolia.

Full text

THEMATIC ISSUE
Distribution of Ephemeroptera, Plecoptera, and Trichoptera
assemblages in relation to environmental variables in headwater
streams of Mongolia
Dashdondog Narangarvuu •Jargalsaikhan Oyunbileg •
Ping-Shih Yang •Bazartseren Boldgiv
Received: 15 June 2013 / Accepted: 16 November 2013
ÓSpringer-Verlag Berlin Heidelberg 2014
Abstract Effects of stream environmental variables on
the distribution and abundance of Ephemeroptera, Ple-
coptera and Trichoptera (EPT) assemblages in the head-
waters of rivers and streams of Mongolia were investigated
in this broad scale survey aimed to provide a baseline for
future research and management of the country’s aquatic
ecosystems. The survey was carried out in the first-, sec-
ond- and third-order streams of 80 rivers selected from the
three main watersheds of Mongolia, namely the Arctic
Ocean Basin (AOB), Pacific Ocean Basin (POB) and
Central Asian Internal Basin (CAIB). We sampled larvae
of EPT by kick and D-nets from the headwater sites during
summers of 2007–2009. Chemical and hydrological vari-
ables of the sites were measured, and habitat of those sites
was assessed. We recorded 89 taxa belonging to 34 fami-
lies of EPT orders during the survey. The family Baetidae
(Ephemeroptera) was the dominant taxon among all sites.
Taxon richness was higher in the POB and AOB than
CAIB, while total EPT abundance was higher in the CAIB.
Significant differences in the community variables, such as
taxon richness, Shannon’s diversity index and evenness of
EPT assemblages were observed among the basins. Results
of canonical correspondence analysis suggested that alti-
tude, dissolved oxygen, order and width of streams were
the most important factors explaining the variability in EPT
larval distribution in the headwater streams in Mongolia.
Keywords Ephemeroptera Plecoptera 
Trichoptera Mongolia Arctic Ocean Basin 
Pacific Ocean Basin Central Asian Internal Basin 
Aquatic ecosystem health
Introduction
Aquatic macroinvertebrate assemblages can be affected by
various local and regional environmental factors, such as
chemical and physical characteristics of stream water,
hydrology, and geographical location, as well as climatic
factors (Malmqvist 2002; Heino et al. 2003; Vannote et al.
1980; Zamora-Mun
˜oz et al. 1993; Bispo et al. 2006; Heino
2012; Sandin and Johnson 2004). Spatial and temporal
variability of these factors largely determine the macroin-
vertebrate communities in stream ecosystems (Baptista
et al. 2001). Among the macroinvertebrates, orders
Ephemeroptera, Plecoptera and Trichoptera (EPT) are
highly diverse insect assemblages in the headwater cobble
streams (Bispo et al. 2006) with important roles in trophic
transfer (Merritt et al. 2008). They are sensitive to distur-
bances and their diversity is often considered as an indi-
cator of good quality of the ecosystems (Rosenberg and
Resh 1993).
Human activities such as climate change, livestock
herding, agriculture, deforestation, unregulated urban and
industrial development and irresponsible mining have
negatively affected the environment of Mongolia. In recent
D. Narangarvuu P.-S. Yang
Department of Entomology, College of Bio-Resource
and Agriculture, National Taiwan University,
Taipei 106, Taiwan, ROC
D. Narangarvuu (&)B. Boldgiv (&)
Department of Ecology, School of Biology and Biotechnology,
National University of Mongolia, Ulaanbaatar 210646, Mongolia
e-mail: garvuu@gmail.com
B. Boldgiv
e-mail: boldgiv@num.edu.mn
J. Oyunbileg
Ecology Education Center, National University of Mongolia,
Ulaanbaatar 210646, Mongolia
123
Environ Earth Sci
DOI 10.1007/s12665-013-2968-9

years, a number of rivers have dried up, and water flow of
streams has decreased due to the human activities. Con-
tinuous increase of livestock numbers affected the aquatic
ecosystems by increasing eutrophication in Mongolian
streams and rivers (Maasri and Gelhaus 2011). Moreover,
increased concentrations of heavy metals and suspended
sediments in waterways are contaminating streams, rivers,
and groundwater tables (Hartwig et al. 2012; Hofmann
et al. 2013). Some negative effects of human activities
resulted in an aquatic biodiversity decline (The Asia
Foundation 2008). Especially, for the most recent years,
mining has increased dramatically without any proper
environmental protection actions due to lack of enforce-
ment of environmental standards and laws. Another factor
that is potentially affecting Mongolian river ecosystem is
climate change occurring rapidly compared with other
parts of the world. The average annual temperature for the
whole country has increased by 2.1 °C during the last
70 years (Dagvadorj et al. 2009). Trends in annual pre-
cipitation are not significant, but the daily event size dis-
tribution has changed (Batima et al. 2005). There is an
urgent need to investigate and assess the recent condition
and quality of the rivers in Mongolia to provide a baseline
for future research, management and conservation of river
ecosystems.
We studied EPT assemblages of headwaters of streams
in Mongolia’s three main river basins, namely the Arctic
Ocean (AOB), Pacific Ocean (POB), and Central Asian
Internal (CAIB). Our research was the first broad scale
survey carried out throughout Mongolia including head-
waters (first- to third-order streams). The purpose of the
research was to define the distribution patterns of EPT
assemblages in headwater streams and to assess which
environment variables are important in determining EPT
assemblages. Our results will be useful in indicating the
state of aquatic ecosystem health in Mongolian headwater
streams.
Brief review on macroinvertebrate communities
in Mongolia
In Mongolia, many taxonomic studies have been conducted
since the 1940s mostly on rivers in western and central
parts of the country by Russian, Hungarian, German,
American and Mongolian researchers concentrating on
distributional records or new species descriptions (Dulmaa
and Nansalmaa 1970; Dashdorj et al. 1969; Purevdorj
2009; Enkhtaivan and Solda
´n2008; Morse et al. 2006).
From late 1990s, the approach of using aquatic insects for
biomonitoring was initiated in Mongolia. Also, several
studies on the effects of livestock grazing and mining on
river ecosystems were carried out. The Ho
¨vsgo
¨l GEF
project funded by World Bank studied the effects of
livestock grazing on macroinvertebrate communities in the
eastern tributary streams of Lake Ho
¨vsgo
¨l between 2002
and 2006. In the Hentiy mountain watershed, effects of
surface gold mining on benthic communities were assessed
(Avlyush 2011). The ‘‘Integrated Water Resources Man-
agement for Central Asia: Model Region Mongolia
(MoMo)’’ project considered the effect of anthropogenic
activities on aquatic communities of Haraa River that is a
part of Selenge River watershed between 2007 and 2012
(Daniel et al. 2010; Kalbus et al. 2012). Taxonomic and
bioassessment surveys of aquatic insects in river ecosys-
tems of the central and western Mongolia were carried out
by the Mongolian Aquatic Insect Survey (MAIS) from
2003 to 2012 (Gelhaus et al. 2008; Gelhaus 2010; Hayford
and Gelhaus 2010). They determined the consequences of
the hydrological connectivity between subdrainages of
Arctic Ocean and Central Asian Internal Basins of Mon-
golia and the effects of grazing on the macroinvertebrate
communities (Hayford and Gelhaus 2010; Maasri and
Gelhaus 2012). However, there are very few attempts to
study distribution patterns of macroinvertebrate assem-
blages and their relations to the environment factors in less
impacted streams at a broad scale in Mongolia because of
the difficulty to reach remote areas.
Materials and methods
Study area
Surface waters of Mongolia are classified into three main
basins, AOB, POB, and CAIB. Arctic Ocean Basin and
POB drain into the Arctic Ocean and Pacific Ocean,
respectively, while CAIB drains into the Central Asia. We
sampled a total of 80 first- to third-order stream sites dis-
tributed in the AOB, POB, and CAIB (Fig. 1). Forty
streams (I order =17, II order =19, and III order =4) of
AOB, 32 streams (I order =15, II order =16, and III
order =1) of CAIB and eight streams (I order =3, II
order =3, and III order =2) of POB were selected for the
survey. Altitude ranged from 662 to 2,456 m for the survey
sites.
Macroinvertebrate sampling
We collected samples during three consecutive summers,
2007–2009 using dip and kick sampling nets with 500 lm
net mesh size in accordance with the Rapid Bioassessment
Protocol of the US EPA (Barbour et al. 1999). Samples
were taken from the same locations of the stream sites
every year. At each site, one kick net sample was taken
from a 1 m
2
water surface area in riffles with cobble sub-
strates and at least 200 specimens were collected from the
Environ Earth Sci
123

net screen. Three dip net collections were randomly made
from the pool, run and the bank area of each site. Speci-
mens of EPT larvae were sorted from sediments in the field
and preserved in 96 % ethanol. Samples were sorted and
EPT larvae were identified to the genus level using iden-
tification keys by Morse et al. (1994), Tsalolikhin (1997,
2001), Zaika (2000a,b), Lepneva (1970,1971), Dashdorj
et al. (1969), and Merritt et al. (2008).
Environmental variables
Environmental variables were measured in the field using
portable instruments. We measured water temperature
(°C), pH, electric conductivity (EC, lS/cm), specific elec-
tric conductivity, suspended solids (SS, mg/L) using a
probe YSI Model 63 Multimeter and dissolved oxygen
(DO, mg/L) with sensION6 portable DO Meter. Ammonia
(NH
4?
, mg/L), nitrate (NO
3-
, mg/L), nitrite (NO
2-
, mg/L),
sulfate (SO
42-
, mg/L) and phosphate (PO
43-
, mg/L) were
measured with DR2800 Spectrophotometer by Hach
according to standard analytical methods of US EPA
(AWWA 1998). Hardness, alkalinity, and acidity test kits
were also used. Stream width (m) was measured using a
tape meter and the current velocity (m/s) and water depth
(m) were measured in the several equal transects with a
Price-type current meter (Model 1205), Current meter
digitizer (Model 9000), and Top setting rod (Model 12056).
Habitat assessment (HA) data were collected at each site
with visual observation based on the US EPA protocol
(Barbour et al. 1999). HA protocol includes a total of ten
habitat parameters (epifaunal substrate/available cover,
embeddedness, velocity/depth regime, sediment deposi-
tion, channel flow status, channel alteration, frequency of
riffles, bank stability, vegetative protection, and riparian
buffer width) with 200 scores. Altitude (m), latitude, and
longitude were marked using a Garmin GPS system.
Stream order was determined based on the river network
map, 1:50,000 resolution.
Data analysis
Community variables, including taxon richness, evenness
(Pielou’s evenness J’), and Shannon-Wiener (H’) were
estimated to study the patterns of EPT assemblages among
the three basins and stream orders. The indices were cal-
culated using Primer 6 software (Clarke and Gorley 2006).
One-way analysis of variance (ANOVA) with Tukey’s
range test was used to test for the differences of environ-
mental and community variables among the basins and
stream orders. One-way ANOVA was done using JMP
Version 10 (SAS 2012). Non parametric two-way ANOVA
was used to determine the effects of basin and stream order
on the taxon richness and relative abundance. Square-root
transformation was used to meet the assumption of nor-
mality because the data are counts (Sokal and Rohlf 2012).
Non parametric two-way ANOVA (with P\0.05 for
significance) was run using SPSS 16.0 (SPSS 2007). A
canonical correspondence analysis (CCA) was used to
describe the variation in the ETP assemblages among the
sites and to identify relationships between their distribution
and environmental variables. CCA was used because pre-
liminary detrended correspondence analysis (DCA) indi-
cated the gradient length of the first DCA axis was 3.2 SD
units, suggesting that both linear and unimodal methods
(because gradient length falls between 3 and 4 standard
units) would fit the data of this study (Leps and Smilauer
Fig. 1 Map of the river
network of Mongolia with the
locations of the EPT sampling
sites included in this study.
AOB-Arctic Ocean Basin, POB-
Pacific Ocean Basin, CAIB-
Central Asian Internal Basin.
The sampling sites abbreviated
as numerals are listed in
Appendix 2
Environ Earth Sci
123

2003). The forward selection procedure and the Monte
Carlo permutation test (499 permutations, P\0.05) were
performed to select significant variables. Before running
CCA, to downweight the dominant taxa, to avoid over-
stating their influence on the ordination, the EPT abun-
dance and environmental data were transformed as square-
root and log (x?1), respectively. The taxa constituting
more than 0.1 % of the total abundance were selected and
40 taxa were used in the analysis. Both DCA and CCA
were run using CANOCO for Windows vers. 4.5 (Smilauer
and ter Braak 2002).
Results
Environmental variables
The all sampled sites represented a broad range of water
temperature (7.7–20.45 °C), EC (29.55–345.55 lS/cm), SS
(0–550 mg/L), acidity (19–152 mg/L), alkalinity
(24–222.7 mg/L), hardness (24–212 mg/L), and sulfate
(0–56 mg/L). Stream water had highly variable DO
(4.96–18.3 mg/L), and high pH (6.63–9.41), whereas low
concentration of nutrients. Stream channel widths ranged
from 2.98 to 79.05 m. Current velocity varied from 0.9 to
1.16 m/s. The resulting HA scoring (ranged from 57 to
184) showed that stream habitat conditions were assessed
as marginal to optimal categories.
The means of the environmental variables of the stream
sites by the three main basins are shown in Table 1.
According to ANOVA, altitude (F=16.3, P\0.0001),
velocity (F=4.73, P=0.01), DO (F=35.94,
P\0.0001), SS (F=3.02, P=0.05), acidity (F=4.46,
P=0.01), sulfate (F=3.79, P=0.02), ammonia
(F=12.11, P\0.0001), nitrate (F=3.96, P=0.02),
and nitrite (F=7.74, P=0.0009) differed significantly
among the three basins.
Moreover, stream width (F=5.21, P=0.007), dis-
charge (F=4.23, P=0.01), and altitude (F=3.04,
P=0.05) showed significant differences between the I–III
stream orders. However, DO was not statistically different
among the stream orders (F=2.59, P=0.08).
In general, the means of the twelve variables including
the altitude, velocity, pH, EC, SS, acidity, alkalinity, sul-
fate, ammonia, nitrate, nitrite, and phosphate were higher
in CAIB headwater streams. DO, temperature, and hard-
ness were higher in POB headwaters, while the stream
width, depth and discharge were higher in AOB streams.
Table 1 Mean values ±SE of the environmental variables of the three basins
AOB (n=39) POB (n=8) CAIB (n=32) F-ratio Pvalue
Habitat variables
Altitude (m) 1,512.33 ±64.26b 1,056.13 ±39.12c 1,854.81 ±69.89a 16.3 \0.0001
HA scores 119.83 ±4.92a 130.35 ±6.38a 117.68 ±5.01a 0.61 NS
Stream width (m) 20.53 ±2.47a 19.06 ±7.11a 17.36 ±2.81a 0.35 NS
Water depth (m) 0.63 ±0.21a 0.12 ±0.01a 0.54 ±0.07a 0.57 NS
Velocity (m/s) 0.503 ±0.03a 0.18 ±0.04b 0.54 ±0.05a 4.73 0.011
Discharge (m
3
/s) 4.58 ±1.2a 0.32 ±0.14a 2.39 ±0.46a 2.03 NS
Water chemistry variables
pH 8.34 ±0.08a 8.05 ±0.11a 8.47 ±0.09a 2.19 NS
Temperature (°C) 13.45 ±0.5a 14.6 ±0.85a 14.03 ±0.48a 0.65 NS
DO (mg/L) 7.62 ±0.2b 12.19 ±1.5a 6.81 ±0.12b 35.94 \0.0001
EC (lS/cm) 100.9 ±11.49a 103.41 ±24.29a 108.1 ±10.41a 0.1 NS
SS (mg/L) 16.45 ±6.7a 3.48 ±1.71a 54.67 ±18.43a 3.02 0.05
Acidity (mg/L) 54.03 ±5.08b 73.48 ±9.7ab 78.01 ±6.69a 4.46 0.01
Alkalinity (mg/L) 89.37 ±8.41a 92.18 ±19.71a 92.72 ±8.15a 0.04 NS
Hardness (mg/L) 88.46 ±6.81a 100.88 ±22.58a 88.31 ±7a 0.29 NS
Sulfate (SO
42-
, mg/L) 8.38 ±1.13b 6.87 ±1.34b 15.57 ±2.96a 3.79 0.02
Ammonia (NH
4?
, mg/L) 0.05 ±0.003b 0.06 ±0.01b 0.102 ±0.01a 12.11 \0.0001
Nitrate (NO
3-
, mg/L) 0.92 ±0.05b 0.94 ±0.16ab 1.53 ±0.25a 3.96 0.02
Nitrite (NO
2-
, mg/L) 0.003 ±0.0003b 0.007 ±0.002ab 0.009 ±0.001a 7.74 0.0009
Phosphate (PO
43-
, mg/L) 0.36 ±0.1a 0.34 ±0.07a 0.62 ±0.14a 1.33 NS
Mean values with different letters indicate significant difference in one-way ANOVA among the basins
Values indicated by the same letters do not significantly differ at P\0.05 by the Tukey’s test
Environ Earth Sci
123

EPT communities
We identified 89 genera belonging to 34 families of EPT
orders from 75,885 individuals collected during the survey
(Table 4of Appendix 1). Trichoptera were the most
diverse with 36 genera belonging to 14 families, followed
by the Ephemeroptera (12 families and 29 genera) and
Plecoptera (eight families and 24 genera). However,
Ephemeroptera were the most abundant and constituted
73.61 % of the total abundance. Trichoptera made up
16.33 % of the total abundance. The percentage of
Ephemeroptera was the highest in CAIB, while percentages
of Plecoptera and Trichoptera were higher in AOB, and
POB, respectively. At the level of genera, the genus Baetis
(Baetidae) was the most abundant accounting for 29.22 %
of the total abundance among the three basins. Ephemerella
(Ephemerellidae) and Brachycentrus (Brachycentridae)
occurred frequently. But Ephemerella was especially
abundant in AOB headwaters, whereas Brachycentrus was
found in almost all stream sites of CAIB.
Significant differences were observed in the taxon
richness (P=0.0003), evenness (P=0.0004), and Shan-
non index (P\0.0001) among the basins (Table 2).
However, there were no significant differences in the total
abundance and relative abundances of each order
Ephemeroptera, Plecoptera, and Trichoptera among the
three basins.
One-way ANOVA showed that significant differences in
the taxon richness (F=4.73, P=0.01), and Shannon
indices (F=4.38, P=0.01) were also observed among
the first to third stream orders.
Table 3shows the results of two-factor ANOVA of the
effects of the basin and stream order on the taxon richness
and abundance. There was no effect of the basin on the
taxon richness (P=0.17). However, stream order signifi-
cantly affected the taxon richness (P=0.04). The stream
order did not significantly affect the abundance, while it
was affected significantly by the basin (P=0.02) and two-
factor interaction (P=0.03). The significant two-factor
interaction indicates that the effect of basin depends on the
level of stream order. However, the abundance of CAIB
was increased in the third stream order, while the abun-
dance of the two other basins decreased in the third-order
streams. The taxon richness was increased with increasing
stream order (Fig. 2).
The means of the taxon richness, relative abundance of
Trichoptera, evenness, and Shannon index were greater for
POB streams than AOB and CAIB streams. Specifically,
the taxon richness, evenness, and Shannon index were
higher in the streams Balj, Barh, and Shuus (Table 5of
Appendix 2). However, the total abundance and relative
abundance of Ephemeroptera were higher in CAIB
streams, while the abundance of Plecoptera was higher in
AOB headwaters. Total abundance was highest at Borshoo,
Bulgan, and Uyench, which belong to CAIB. In case of
stream orders, the taxon richness, evenness, and Shannon
index were higher in the third stream order, while the total
abundance was higher in the first stream order.
Relationship between EPT assemblages
and environmental variables
CCA analysis was performed on the relative abundances of
EPT assemblages and environmental variables. Forty taxa
Table 2 Mean values ±SE of macroinvertebrate community parameters among the three basins
AOB (n=40) POB (n=8) CAIB (n=32) F-ratio Pvalue
Richness 17.79 ±0.76a 20.12 ±3.28a 13.12 ±0.84b 9.13 0.0003
Abundance 925.69 ±98.87a 846.63 ±176.48a 1,073.09 ±149.79a 0.54 NS
Evenness 0.66 ±0.01a 0.73 ±0.02a 0.55 ±0.03b 8.68 0.0004
Shannon 0.82 ±0.02a 0.92 ±0.06a 0.62 ±0.04b 14.34 \0.0001
Ephemeroptera 279.37 ±37.38a 201.85 ±33.13a 297.03 ±41.85a 0.58 NS
Plecoptera 41.87 ±5.52a 37.42 ±10.35a 33.83 ±5.45a 0.54 NS
Trichoptera 48.16 ±7.4a 83.38 ±19.67a 72.34 ±20.84a 0.99 NS
Mean values with different letters indicate significant differences in one-way ANOVA among the basins
Values indicated by the same letters do not significantly differ at P\0.05 by the Tukey’s honestly significant difference test
Table 3 Non-parametric two-way ANOVA for the effects of basin,
stream and their interaction on the taxon richness and abundance
Source of variance df Taxon richness Abundance
Fratio Pvalue Fratio Pvalue
Basin 2 1.8 NS 3.97 *
Stream order 2 2.77 * 0.77 NS
Basin 9stream order 4 0.12 NS 2.84 *
NS not significant
*Pvalue lower than 0.05
** Pvalue lower than 0.005
*** Pvalue lower than 0.0001
Environ Earth Sci
123

from three basins were selected in the CCA. Four envi-
ronmental variables out of nineteen, including altitude,
stream order, stream width and DO were detected as sig-
nificant factors explaining the EPT distribution in the
headwater streams (Fig. 3). The CCA revealed that 30.6 %
of the variation in the data could be explained by the
environmental variables (cumulative percentage variance
of species data, first four CCA axes). The first and second
canonical axes explained 4.2 % (eigenvalue of 0.11) and
7.2 % (eigenvalue of 0.07) of the variance in the species
data, respectively. The Monte Carlo significance test for
the first and all canonical axes showed significant values at
P=0.002, respectively. The species and environment
correlations of the first and second axes were 0.72 and 0.67,
respectively.
The most important gradient was composed of DO and
altitude, which were closely correlated with the first CCA
axis. The first axis was positively correlated to DO (0.62),
and negatively correlated with altitude (-0.62). Several
taxa showed variable responses along this axis, such as
Hydroptila sp., Leptophlebia sp., Paraleptophlebia sp.,
Cloeon sp., Caenis sp., Agnetina sp., and Eporon sp., all
presented high scores on the first axis, and tended to be
associated with higher DO streams, which were mostly
located in the POB. Moreover, taxa, especially rheophilous
taxa Rhyacophilidae (Rhyacophila sp.) and Heptageniidae
(Heptagenia sp., Rhithrogenia sp.), Brachycentrus sp.,
Acentrella sp., Nemoura sp., and Arcynopteryx sp., were
related to the altitude. The most sites located in the CAIB
were found at the bottom left of the biplot with strong
association with the altitude. The second axis was posi-
tively correlated to stream order and width. Fewer taxa,
such as Hydropsyche sp., Ameletus sp., Procloeon sp., and
Glossosoma sp., responded to stream order and width.
Discussion
In general, we found significant differences in EPT
assemblages between the three basins (AOB, CAIB, and
POB). Baetidae and Heptageniidae (Ephemeroptera) and
Brachycentridae (Trichoptera) dominated in the EPT
Fig. 2 Effects of the basins and
stream orders on the ataxon
richness and babundance of
EPT
Fig. 3 CCA biplot for athe
EPT assemblages and
significant environmental
variables and bCCA biplot for
environmental variables and
sampling sites. Names
corresponding to the
abbreviations of the taxa are
listed in Appendix 1, and the
sampling sites abbreviated as
numerals are listed in
Appendix 2
Environ Earth Sci
123

assemblages of all three basins. They were also reported to
be the most common taxa in neighboring geographical
areas (Jiang et al. 2013; Suren 1994). There were no
obvious anthropogenic impacts occurred in the headwater
streams included in this study as there was no dam, chan-
nelization, and waste water drainage effects.
The distribution of EPT assemblages in the headwater
streams of the three basins was primarily associated with
stream order, altitude, DO, and stream width in this large
scale survey. Many studies have shown that precipitation,
stream order, substrate type, and altitude were the most
important factors in determining the distribution and
abundance of the macroinvertebrates (Bispo et al. 2006;
Heino et al. 2005; Hawkins et al. 1982). In our study,
stream order was the major factor influencing the total
taxon richness of EPT assemblages. The taxon richness
increased with the increasing stream order among the
three basins, which is consistent with the River Contin-
uum Concept (RCC). According to the RCC, biological
communities change with stream size and peak in med-
ium size (3–5th order) streams (Vannote et al. 1980).
However, EPT abundance decreased except in the third-
order streams of CAIB. The taxon richness was higher in
streams of POB which had diverse riparian habitats than
streams in AOB and CAIB. Some taxa, which are sensi-
tive to perturbation, live in the high oxygen water, such as
Agnetina,Limnephilus, and Hydroptila, which were more
abundant in POB. A previous study noticed that highly
diverse habitats also contain a higher biodiversity (Maasri
and Gelhaus 2012).
Altitude has been reported as another important factor in
structuring the lotic communities (Bispo et al. 2006;
Townsend et al. 2003). The altitude played a main role in
the distribution of EPT assemblages in our study, as sug-
gested by the results of CCA. Most of the stream sites of
CAIB were associated with higher altitudes. Arcynopteryx,
Brachycentrus,Rhyacophila, and Rhithrogena, which are
considered as characteristic taxa of high altitudes and fast-
flowing streams, were abundant in CAIB. Brachycentrus
occurred at high altitudes with fast current streams in
Taiwan (Dudgeon 1999) and Tibetan-Plateau (Jiang et al.
2013).
DO was significantly different between the three basins,
and was much higher in streams of POB. However, our
findings that DO did not affect the EPT assemblages sig-
nificantly among the stream orders were consistent with
studies in other headwater streams (Jiang et al. 2013;
Jacobsen et al. 2003). According to the CCA, the sites of
POB had a higher taxon richness associated with a higher
DO. Streams located in POB seem to have a better water
quality with related higher taxon richness and DO. EPT are
gill-breathing insects that may be easily affected by con-
ditions that change the DO (Goodnight 1973). Thus, higher
EPT taxon richness in a stream indicates a better water
quality.
However, the physicochemical variables were inade-
quate to explain the majority of the variance. Other influ-
ences such as biotic interactions, flood, and drought as well
as regional factors may have a profound effect on the
distribution of the EPT. Conservation efforts in Mongolian
stream ecosystems are constrained by a variety of factors
including lack of ecological information. Therefore,
including the assessment of EPT assemblages in future
studies is crucial to assess the ecological quality or streams.
Conclusion
This study has identified the distributions and abundances
of EPT assemblages of the least-disturbed headwater
streams of Mongolia. Results showed that there were sig-
nificant differences in the taxon richness among the basins.
Taxon richness is increasing with increasing stream order.
CCA results indicated that some environment variables
such as altitude, DO, stream order and stream width
affected the distribution and abundance of EPT assem-
blages significantly. From a bioassessment perspective, our
data may represent a reference condition for Mongolian
headwater streams, because all data were collected from
near-pristine streams.
Acknowledgments We would like to express our sincere thanks to
Mr. William Infante, Ms. Rebecca Darling, Mrs. Shelagh Rosenthal
and other staff of the Asia Foundation of Mongolia, who supported
this study both professionally and logistically. Dashdondog
Narangarvuu would like to thank Puntsag Tamir, Dashzeveg Batkhuu,
and Shar Usukhbayar for their contributions and providing water
chemistry, hydrology, and habitat assessment data, to Nyamsuren
Odchimeg, Nyamjav Indra, Batsaikhan Oyunbat, and Ganbat Un-
dralbat for helping in the sampling and sorting of macroinvertebrates,
to Ariuntsetseg Lkhagva for her valuable advice on data analysis, and
to Badam Barkhas for her help with the Geographic Information
Systems analysis. We also would like to thank the anonymous
reviewers for their very helpful comments. This research was made
possible by funding provided by the Royal Netherlands Embassy to
the Asia Foundation’s Securing Our Future Project and its ‘‘Mongo-
lian Watershed Monitoring Network’’ program implemented in
2007–2009.
Appendix 1
See Table 4.
Environ Earth Sci
123

Table 4 Relative abundance of EPT among the three basins (in percent)
Order Family Genus Abbr. AOB (n=40) CAIB (n=32) POB (n=8)
Ephemeroptera
Ameletidae Ameletus* Amele 1.050 0.041 2.140
Baetidae Acentrella* Acent 1.677 3.921 0.192
Baetis* Baeti 25.274 37.283 9.548
Baetopus* Baeto 0.533 1.663 3.778
Centroptilium 0.006 0.000 0.000
Cloeon* Cloeo 0.519 0.210 0.310
Procloeon* Procl 0.387 0.697 0.826
Caenidae Caenis* Caeni 0.450 0.875 9.460
Brachycercus* Brach 0.351 0.058 0.000
Ephemeridae Ephemera 0.028 0.047 0.000
Ephemerellidae Drunella* Drune 1.469 0.102 2.937
Ephemerella* Ephem 14.924 8.657 8.663
Serratella* Serra 6.370 1.263 3.793
Heptageniidae Cinygma* Ciny 2.613 0.245 0.266
Cinygmula* Cinyg 3.911 2.317 0.089
Ecdyonurus 0.000 0.012 1.299
Epeorus* Epeor 1.992 2.854 0.930
Heptagenia* Hepta 2.342 2.915 2.184
Rhithrogena* Rhith 6.776 9.223 3.940
Leptophlebiidae Leptophlebia* Lepto 0.235 0.000 0.782
Paraleptophlebia* Paralep 0.097 0.000 1.830
Isonychiidae Isonychia 0.039 0.000 0.000
Metrotophodidae Metrotopus* Metro 0.425 0.000 0.133
Metroplecton 0.072 0.000 0.030
Oligoneuridae Oligoneurella 0.014 0.000 0.000
Polymitarcyidae Ephoron* Ephor 0.141 0.642 6.287
Siphlonuridae Parameletus* Param 1.748 0.073 0.059
Siphlonurus* Siphl 2.155 0.569 3.084
Siphlurella 0.030 0.000 0.000
Plecoptera
Capniidae Capnia 0.044 0.000 0.044
Chloroperlidae Alloperla 0.064 0.134 0.177
Haploperla* Haplo 0.680 0.149 0.015
Suwallia* Suwal 0.633 0.677 0.192
Triznaka 0.025 0.020 0.635
Leuctridae Leuctra 0.003 0.000 0.620
Nemouridae Amphinemura 0.254 0.003 0.000
Nemoura* Nemou 0.878 0.035 0.000
Perlidae Agnetina* Agnet 0.699 0.659 7.896
Claasenia 0.003 0.000 0.000
Kamimuria 0.014 0.000 0.000
Paragnetina 0.041 0.000 0.221
Togoperla 0.000 0.000 0.251
Perlodidae Arcynopteryx* Arcyn 2.364 4.003 0.428
Duira* Diura 1.058 1.710 0.103
Isoperla* Isope 3.624 0.925 0.974
Environ Earth Sci
123

Table 4 continued
Order Family Genus Abbr. AOB (n=40) CAIB (n=32) POB (n=8)
Kogotus 0.119 0.020 0.015
Levanidova 0.439 0.000 0.000
Megarcys 0.249 0.000 0.015
Pictetiella 0.000 0.055 0.000
Skwala 0.006 0.000 0.000
Sweltsa 0.069 0.000 0.015
Pteronarcyidae Pteronarcys 0.064 0.000 0.000
Taeniopterygidae Taeniopteryx 0.008 0.000 0.000
Trichoptera
Apataniidae Apatania 0.171 0.003 0.000
Brachycentridae Brachycentrus* Brachy 3.262 10.297 7.556
Micrasema* 0.624 0.003 0.517
Hydropsychidae Arctopsyche 0.006 0.000 0.000
Ceratopsyche 0.094 0.000 0.000
Cheumatopsyche 0.000 0.128 0.074
Hydropsyche* Hydro 4.201 6.086 0.517
Potamiya 0.191 0.038 0.000
Hydroptilidae Hydroptila* Hydrop 0.000 0.000 2.524
Stactobia 0.000 0.003 0.000
Goeridae Goera* Goera 0.240 0.035 0.118
Glossosomatidae Agapetus 0.003 0.000 0.000
Anagapetus 0.017 0.000 0.000
Glossosoma* Gloss 0.406 0.152 0.207
Leptoceridae Ceraclea 0.058 0.000 0.236
Leptocerus 0.000 0.012 0.059
Oecetis 0.000 0.000 0.133
Setodes 0.000 0.000 0.044
Triaenodes 0.044 0.000 0.015
Lepidostomatidae Lepidostoma 0.000 0.044 0.000
Goerodes 0.008 0.000 0.000
Limnephilidae Anabolia* Anabo 0.497 0.125 1.992
Asynarchus* Asyna 0.182 0.020 1.063
Dicosmoecus 0.055 0.061 0.133
Ecclisomiya 0.041 0.000 0.000
Limnephilus* Limne 0.771 0.263 6.523
Philarctus 0.008 0.000 0.000
Pseudostenophylax 0.003 0.018 0.000
Molanidae Molanna 0.006 0.000 0.000
Rhyacophilidae Rhyacophila* Rhyac 1.939 0.522 2.066
Phryganeidae Agrypnia* Agryp 0.075 0.000 1.800
Psychomyiidae Lype 0.008 0.000 0.000
Psychomyia 0.113 0.058 0.089
Polycentropoididae Neureclipsis 0.003 0.000 0.000
Nyctiophylax 0.003 0.000 0.000
Polycentropus 0.008 0.073 0.177
Taxon indicated with * was included in the CCA analysis
Environ Earth Sci
123

Appendix 2
See Table 5.
Table 5 List of the streams, basins, stream orders, and community parameters
# Sample Basin Stream order Number of taxa NEvenness Shannon
1 Alagtsar AOB I 25 1,929 0.56 0.79
2 Amgalant POB I 18 513 0.70 0.88
3 Angirt CAIB I 13 1,366 0.62 0.69
4 Baga Oigor CAIB I 9 276 0.67 0.64
5 Bahtag AOB II 21 1,413 0.71 0.94
6 Balj POB II 29 1,233 0.82 1.20
7 Barh POB III 36 926 0.73 1.13
8 Baruunturuun CAIB I 14 546 0.76 0.87
9 Bodonch CAIB II 12 2,158 0.50 0.54
10 Bogd CAIB II 10 342 0.81 0.81
11 Boroo AOB II 9 353 0.60 0.58
12 Borshoo CAIB I 23 3,916 0.45 0.61
13 Borsog AOB I 20 1,242 0.35 0.46
14 Bugant AOB I 26 690 0.69 0.98
15 Bulgan CAIB III 20 3,150 0.56 0.73
16 Burgaltai AOB I 18 925 0.80 1.00
17 Buyant CAIB II 13 867 0.64 0.71
18 Chigestei CAIB II 9 608 0.32 0.31
19 Chuluut AOB III 21 357 0.78 1.03
20 Dalbay AOB I 9 742 0.65 0.62
21 Dund tsenher CAIB I 9 279 0.65 0.62
22 Eg-HNT POB II 23 1,743 0.75 1.02
23 Eg-HVG AOB I 14 2,102 0.58 0.67
24 Eren AOB II 20 1,233 0.80 1.04
25 Eved AOB II 16 226 0.84 1.02
26 Gichgene AOB II 22 1,491 0.50 0.67
27 Guna AOB II 16 1,465 0.63 0.76
28 Halh POB III 13 408 0.66 0.74
29 Halhan AOB II 27 2,088 0.59 0.85
30 Hanui AOB II 25 759 0.67 0.93
31 Harchuluut CAIB II 17 1,100 0.76 0.94
32 Harganat CAIB I 9 1,614 0.15 0.14
33 Har-Us CAIB I 10 604 0.75 0.75
34 Hoit Tamir AOB II 13 684 0.57 0.64
35 Hoit Terh AOB I 16 964 0.66 0.80
36 Hoit Tsenher CAIB II 6 499 0.44 0.35
37 Hojuul AOB II 13 365 0.74 0.82
38 Homol POB I 22 1,140 0.70 0.94
39 Hongio CAIB II 10 1,389 0.33 0.33
40 Huder AOB II 20 482 0.72 0.93
41 Hug AOB III 21 692 0.62 0.82
42 Ider AOB II 15 676 0.70 0.82
43 Ih Oigor CAIB I 7 675 0.32 0.27
44 Jarai AOB I 18 660 0.71 0.89
Environ Earth Sci
123

References
Avlyush S (2011) Effects of surface gold mining on macroinverte-
brate communities: a case study in river systems in the North–
East of Mongolia. Lambert Academic Publishing, Germany
AWWA (1998) Standard methods for the examination of water and
waste-water, 20th edn. American Public Health Association,
Washington DC
Baptista DF, Dorville LFM, Buss DF, Nessiamian JL (2001) Spatial
and temporal organization of aquatic insects assemblages in the
longitudinal gradient of a tropical river. Rev Bras Biol
61:295–304. doi:10.1590/S0034-71082001000200012
Barbour MT, Gerritsen J, Snyder BD, Stribling JB (1999) Rapid
bioassessment protocols for use in streams and wadeable
rivers: periphyton, benthic macroinvertebrates and fish. 2nd
edn. EPA/841-B-99-002. U.S. EPA Office of Water, Wash-
ington DC
Batima P, Natsagdorj L, Gombluudev P, Erdenetsetseg B (2005)
Observed climate change in Mongolia. AIACC, p 25
Bispo PC, Oliveira LG, Bini LM, Sousa KG (2006) Ephemeroptera,
Plecoptera and Trichoptera assemblages from riffles in mountain
streams of Central Brazil: environmental factors influencing the
distribution and abundance of immatures. Braz J Biol
66:611–622. doi:10.1590/S1519-69842006000400005
Table 5 continued
# Sample Basin Stream order Number of taxa NEvenness Shannon
45 Mogoit CAIB I 7 414 0.57 0.48
46 Nomrog POB I 11 354 0.67 0.69
47 Noyon AOB I 10 414 0.74 0.74
48 Sagsai CAIB II 16 677 0.69 0.83
49 Sevsuul AOB I 15 515 0.63 0.74
50 Shagnuul AOB I 15 2,169 0.48 0.56
51 Sharga AOB I 16 1,688 0.66 0.80
52 Shargaljuut CAIB I 12 1,714 0.48 0.52
53 Shar-Us CAIB I 10 267 0.61 0.61
54 Sharyn gol AOB II 13 293 0.70 0.78
55 Shiver CAIB I 15 645 0.29 0.34
56 Shuus POB II 9 456 0.84 0.80
57 Sogoo CAIB II 15 862 0.70 0.82
58 Suman AOB I 19 577 0.67 0.86
59 Tavt AOB III 18 323 0.79 0.99
60 Tengis AOB III 26 803 0.76 1.07
61 Terelj AOB II 20 391 0.76 0.99
62 Tes AOB I 15 251 0.78 0.91
63 Torhilog CAIB I 25 1,347 0.78 1.09
64 Tsagaan CAIB II 9 579 0.37 0.35
65 Tsagaan gol AOB I 11 253 0.74 0.77
66 Tsagaanturuun CAIB II 16 525 0.80 0.96
67 Tsenher AOB I 23 1,377 0.61 0.83
68 Tui CAIB II 13 1,626 0.64 0.71
69 Turag AOB I 19 1,655 0.54 0.69
70 Turgen CAIB II 19 869 0.59 0.75
71 Uyench CAIB II 16 2,259 0.53 0.63
72 Uilgan AOB II 14 1,875 0.62 0.71
73 Ulziit CAIB II 12 741 0.60 0.65
74 Umnu CAIB II 22 1,138 0.55 0.73
75 Urd Terh AOB II 18 628 0.68 0.85
76 Zag CAIB I 12 183 0.66 0.71
77 Zart AOB II 15 363 0.79 0.93
78 Zelter AOB II 23 381 0.74 1.01
79 Zuil CAIB I 10 1,104 0.32 0.32
80 Zuunmod AOB I 14 859 0.65 0.75
Environ Earth Sci
123

Clarke K, Gorley R (2006) PRIMER (v6): user manual/tutorial.
PRIMER-E, Plymouth
Dagvadorj D, Natsagdorj L, Dorjpurev J, Namkhainyam B (2009)
Mongolia assessment report on climate change. Ministry of
Nature, Environment and Tourism, Ulaanbaatar
Daniel AK, Ibisch RB, Avylush S, Enkhbayar G, Nergui S, Borchardt
D (2010) Impacts of open placer gold mining on aquatic
communities in rivers of the Khentii mountains, North–East
Mongolia. Mong J Biol Sci 8(1):41–50
Dashdorj A, Tsendsuren A, Dulmaa A, Danzan G (1969) Identifica-
tion key to aquatic animals of Mongolia (in Mongolian). Ulsiin
khevleliin khereg erkhlekh khoroo, Ulaanbaatar
Dudgeon D (1999) Tropical Asian streams: zoobenthos, ecology and
conservation. Hong Kong University Press, Hong Kong
Dulmaa A, Nansalmaa B (1970) Gobi desert lakes, plankton and
bottom animals (in Mongolian). Biol Inst Res Info No 5:65–74
Enkhtaivan S, Solda
´n T (2008) Mayflies (Ephemeroptera) of the Lake
Hovsgol region, Mongolia. In: Hauer FR, Stanford JA, Newell
RL (eds) International advances in the ecology, zoogeography
and systematics of Mayflies and Stoneflies, vol 2008. University
of California Press, Berkeley and Los Angeles, pp 103–115
Gelhaus J (2010) The census of aquatic biodiversity in Mongolia:
results from the Mongolian Aquatic Insect Survey 2002–2010.
In: First international conference ‘‘Survey of Mongolian aquatic
ecosystems in a changing climate: results, new approaches and
future outlook’’, Ulaanbaatar, Mongolia, p 37
Gelhaus J, Hayford B, Morse J, Nelson R, Suvdtsetseg C,
Oyunchuluun Y, Sanaa E (2008) The Mongolian Aquatic Insect
Survey (MAIS): progress and future projects, In: Boldgiv B (ed)
Proceedings of the international conference, fundamental and
applied issues of ecology and evolutionary biology, National
University of Mongolia, Ulaanbaatar, pp 53–60
Goodnight CJ (1973) The use of aquatic macroinvertebrates as
indicators of stream pollution. Trans Am Microsc Soc 92(1):
1–13
Hartwig M, Theuring P, Rode M, Borchardt D (2012) Suspended
sediments in the Kharaa River catchment (Mongolia) and its
impact on hyporheic zone functions. Environ Earth Sci
65(5):1535–1546. doi:10.1007/s12665-011-1198-2
Hawkins CP, Murphy ML, Anderson NH (1982) Effects of canopy,
substrate composition, and gradient on the structure of macro-
invertebrate communities in cascade range streams of Oregon.
Ecology 63(6):1840–1856
Hayford B, Gelhaus J (2010) The relationship between grazing,
erosion and adult aquatic insects in streams in Mongolia. Mong J
Biol Sci 8(1):27–39
Heino J (2012) The importance of metacommunity ecology for
environmental assessment research in the freshwater realm. Biol
Rev Camb Philos Soc 88(1):166–178. doi:10.1111/j.1469-185X.
2012.00244.x
Heino J, Muotka T, Paavola R (2003) Determinants of macroinver-
tebrate diversity in headwater streams: regional and local
influences. J Anim Ecol 72(3):425–434. doi:10.1046/j.1365-
2656.2003.00711.x
Heino J, Parviainen J, Paavola R, Jehle M, Louhi P, Muotka T (2005)
Characterizing macroinvertebrate assemblage structure in rela-
tion to stream size and tributary position. Hydrobiologia
539(1):121–130. doi:10.1007/s10750-004-3914-3
Hofmann JM, Watson V, Scharaw B (2013) Groundwater quality
under stress: contaminants in the Kharaa river basin (Mongolia).
Environ Earth Sci
Jacobsen D, Rostgaard S, Va
´sconez J (2003) Are macroinvertebrates
in high altitude streams affected by oxygen deficiency? Freshw
Biol 48(11):2025–2032. doi:10.1046/j.1365-2427.2003.01140.x
Jiang X, Xie Z, Chen Y (2013) Longitudinal patterns of macroinver-
tebrate communities in relation to environmental factors in a
Tibetan-Plateau river system. Quatern Int 304:107–114. doi:10.
1016/j.quaint.2013.02.034
Kalbus E, Kalbacher T, Kolditz O, Kru
¨ger E, Seegert J, Ro
¨stel G,
Teutsch G, Borchardt D, Krebs P (2012) Integrated water
resources management under different hydrological, climatic and
socio-economic conditions. Environ Earth Sci 65(5):1363–1366.
doi:10.1007/s12665-011-1330-3
Lepneva SG (1970) Fauna of the U.S.S.R. Trichoptera (Larvae and
Pupae of Annulipalpia), vol 2. vol 1. Akademiya Nauk, SSSR
Lepneva SG (1971) Fauna of the U.S.S.R.Trichoptera (Larvae and
Pupae of Integripalpia), vol 2. vol 2. Akademiya Nauk, SSSR
Leps J, Smilauer P (2003) Multivariate analysis of ecological data
using CANOCO. Cambridge University Press, Cambridge
Maasri A, Gelhaus J (2011) The new era of the livestock production
in Mongolia: consequences on streams of the Great Lakes
Depression. Sci Total Environ 409(22):4841–4846. doi:10.1016/
j.scitotenv.2011.08.005
Maasri A, Gelhaus J (2012) Stream invertebrate communities of
Mongolia: current structure and expected changes due to climate
change. Aquatic Biosystems8(1):18. doi:10.1186/2046-9063-8-18
MalmqvistB (2002) Aquatic invertebrates in riverinelandscapes. Freshw
Biol 47(4):679–694. doi:10.1046/j.1365-2427.2002.00895.x
Merritt RW, Cummins KW, Berg MB (2008) An Introduction to the
aquatic insects of North America, 4th edn. Kendall/Hunt
Publishing Company, Dubuque
Morse JC, Lianfang Y, Lixin T (1994) Aquatic insects of China useful
for monitoring water quality. Hohai University Press, Nanjing
Morse JC, Rozhkova NA, Prather AL, Vshivkova TS, Harris SC
(2006) Trichoptera of Mongolia, with emphasis on the Hovsgol
drainage fauna. In: Gelhaus J, Sitnikova T, Boldgiv B, Goulden
C (eds) The geology, biodiversity and ecology of Lake Hovsgol.
Backhuys Publ, Mongolia, pp 305–332
Purevdorj S (2009) Updated species list of stoneflies (Plecoptera) of
Mongolia. Aquatic Insects 31:707–720. doi:10.1080/016504
20903146364
Rosenberg DM, Resh VH (1993) Freshwater biomonitoring and
benthic macroinvertebrates. Chapman and Hall, New York
Sandin L, Johnson RK (2004) Local, landscape and regional factors
structuring benthic macroinvertebrate assemblages in Swedish
streams. Landscape Ecol 19(5):501–514. doi:10.1023/B%
3ALAND.0000036116.44231.1c
SAS (2012) JMP
Ò
Version 10. SAS Institute Inc, Cary
Smilauer P, ter Braak C (2002) CANOCO reference manual on
CanoDraw for Windows User’s guide: Software for Canonical
Community Ordination (version 4.5). Micro-computer Power,
Ithaca
Sokal R, Rohlf F (2012) Biometry, 4th edn. WH Freeman and
company, New York
SPSS (2007) SPSS for Windows, Version 16.0. SPSS Inc, Chicago
Suren AM (1994) Macroinvertebrate communities of streams in
western Nepal: effects of altitude and land use. Freshw Biol
32(2):323–336. doi:10.1111/j.1365-2427.1994.tb01129.x
The Asia Foundation (2008) Science and Conservation. http://www.
mongolianriverresources.mn/index.php?option=com_content&
task=view&id=126&Itemid=142
Townsend CR, Dole
´dec S, Norris R, Peacock K, Arbuckle C (2003)
The influence of scale and geography on relationships between
stream community composition and landscape variables:
description and prediction. Freshw Biol 48(5):768–785. doi:10.
1046/j.1365-2427.2003.01043.x
Tsalolikhin S (1997) Key to freshwater invertebrates of Russia and
adjacent lands. Zoological Institute of the Russian Academy of
Sciences, Saint Petersburg
Tsalolikhin S (2001) Key to freshwater invertebrates of Russia and
adjacent lands. Zoological Institute of the Russian Academy of
sciences, Saint Petersburg
Environ Earth Sci
123

Vannote RL, Minshall GW, Cummins KW, Sedell JR, Cushing CE
(1980) The River Continuum Concept. Can J Fish Aquat Sci
37:130–137
Zaika VV (2000a) An atlas guide to the aquatic invertebrates of Tuva
and West Mongolia, part 1: Mayflies-Insecta, Ectognatha,
Ephemeroptera. Tuvanian Institute for the Exploration of Natural
Resources SB RAS, Kyzyl
Zaika VV (2000b) An atlas guide to the aquatic invertebrates of Tuva
and West Mongolia, part 2: Stonefly Insecta, Ectognatha,
Plecoptera. Tuvanian Institute for the Exploration of Natural
Resources SB RAS, Kyzyl
Zamora-Mun
˜oz C, Sanchez-Ortega A, Alba-Tercedor J (1993)
Physico-chemical factors that determine the distribution of
mayflies and stoneflies in a high-mountain stream in Southern
Europe (Sierra Nevada, Southern Spain). Aquatic Insects
15(1):11–20. doi:10.1080/01650429309361495
Environ Earth Sci
123