CONCORDANCE AMONG FISH AND MACROINVERTEBRATE
ASSEMBLAGES IN INDIANA STREAMS
A THESIS SUBMITTED TO THE GRADUATE SCHOOL IN PARTIAL
FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE
MASTER OF SCIENCE
BY
JULIA BACKUS
ADVISOR: DR. MARK PYRON
BALL STATE UNIVERSITY
MUNCIE, INDIANA
MAY 2014
CONCORDANCE AMONG FISH AND MACROINVERTEBRATE ASSEMBLAGES IN
INDIANA STREAMS
A THESIS SUBMITTED TO THE GRADUATE SCHOOL IN PARTIAL FULFILLMENT OF
THE REQUIREMENTS FOR THE DEGREE
MASTER OF SCIENCE
BY
JULIA BACKUS
ADVISOR: DR. MARK PYRON
Committee Approval:
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Committee Chairperson
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Date
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Committee Member
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Date
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Committee Member
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Date
Departmental Approval:
______________________________________
Departmental Chairperson
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Date
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Dean of the Graduate School
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Date
BALL STATE UNIVERSITY
MUNCIE, INDIANA
MAY 2014
TABLE OF CONTENTS
TABLE OF CONTENTS……………………………………………………..…….iii
LIST OF FIGURES………………………………………………………………...iv
LIST OF TABLES…………………………………………………………….….....v
ACKNOWLEGEMENTS……………………………………………………….…..1
ABSTRACT………………………………………………………………................2
INTRODUCTION…………………………………………………………………..3
METHODS……………………………………………………………………….....4
RESULTS…………………………………………………………………………...9
DISCUSSION……………………………………………………………………...10
REFERENCES……………………………………………………………………..14
FIGURES AND TABLES………………………………………………………….20
APPENDIXES……………………………………………………………………...29
LIST OF FIGURES
Figure
Page
1. Map of 16 sites where fish and macroinvertebrates were sampled
in summer 2013 in the Eastern Cornbelt Plain ecoregion of
Indiana.
26
2. Two axes from CCA analysis of macroinvertebrate relative
abundances at 16 Indiana sites in the Eastern Cornbelt Plain
ecoregion in summer 2013. Triangles represent macroinvertebrate
taxa. Environmental variables are represented as vectors.
Macroinvertebrate abbreviations are in Table 2.
27
3. Two axes from CCA analysis of fish relative abundances at 16
Indiana sites in the Eastern Cornbelt Plain ecoregion in summer
2013. Triangles represent fish taxa. Environmental variables are
represented as vectors. Abbreviations for fish names are in Table
3.
28
LIST OF TABLES
Table
Page
1. Physicochemical parameters measured at 16 sites in the Eastern
Cornbelt Plain ecoregion of Indiana in summer 2013.
20
2. Macroinvertebrate family and order names and abbreviations for
Figure 2. Macroinvertebrates were collected from 16 sites in the
Eastern Cornbelt Plain ecoregion of Indiana in summer 2013.
21
3. Fish species loadings on the first three axes of a CA of fish
species. Abbreviations from Figure 3 are in parentheses. Fish
were collected from 16 sites in the Eastern Cornbelt Plain
ecoregion of Indiana in summer 2013.
23
4. Significant environmental predictor variables of
macroinvertebrate and fish assemblages at 16 Indiana sites in
summer 2013 based on percentage contribution to variance
explained in two canonical correspondence analyses (CCA).
25
1
ACKNOWLEGEMENTS
I acknowledge the funding source for this study, the Ball State Graduate Student Research
Program. Thanks to Anna Settineri and Nick Haunert for their field assistance, and Scott Zello
and Ashley Nakata for lab assistance. Thank you to Luke Etchison for his help with mapping my
sites, and to Jesse Becker for his advice and insight on this project. Thanks to Jason Doll for his
field assistance, valuable insight in presenting my results, and help with analyses. Thanks to Dr.
Randy Bernot and Dr. Gary Dodson for their time spent serving as valuable committee members.
I thank my advisor, Dr. Mark Pyron, for providing this opportunity to develop my research skills
and giving his advice and guidance. I finally thank my family and friends for their support
throughout my education.
2
ABSTRACT
THESIS:
Concordance among fish and macroinvertebrate assemblages in Indiana streams
STUDENT:
Julia K. Backus
DEGREE:
Master of Science
COLLEGE:
Science and Humanities
DATE:
May 2014
PAGES:
47
Our objective was to quantify if macroinvertebrate assemblages in Indiana streams were
better predicted from co-occurring fish assemblages or environmental variables. We used
Canonical Correspondence Analysis (CCA) with forward-selection of variables to identify
significant environmental predictor variables for macroinvertebrate and fish assemblages. A
partial Mantel test was used to determine if fish assemblage composition and macroinvertebrate
assemblage composition significantly co-vary while controlling for environmental effects. The
CCAs resulted in two significant predictors of macroinvertebrate distribution and relative
abundance, and four significant predictors of fish distribution and relative abundance. Similarity
matrices of fish and macroinvertebrates were significantly correlated in the Mantel (r = 0.22, p =
0.019) and partial Mantel tests (r = 0.23, p = 0.013). Our results suggest that macroinvertebrates
respond to local and regional environmental variation, and less to local presence of fishes.
3
Introduction
A fundamental objective of ecology is to understand the patterns and processes that
govern the distribution and abundance of organisms. Assemblages, or groups of species in like
taxonomic divisions, are regulated at multiple spatial scales by a hierarchy of physiochemical
environmental characteristics and interactions with other organisms (Li et al. 2001, Brosse,
Arbuckle, and Townsend 2003, Heino, Louhi, and Muotka 2004). This resulting distribution of
organisms across patch and landscape scales provides a base for studies and management of
biodiversity and ecosystem integrity (Warfe et al. 2013).
The use of multiple taxa of stream organisms, rather than a single taxon, in ecological
studies is relatively recent, but appears necessary to interpret independent influences of the
environment on each group, and interactions among groups (Bowman et al. 2008, Warfe et al.
2013). Fish and benthic invertebrate assemblages are commonly surveyed and used as indicators
for ecosystem integrity (Kilgour and Barton 1999, Brown, May, and Wulff 2012), and as
predictors for co-occurring assemblages, including each other (Heino 2010). This surrogate
taxon approach can be faster and less expensive than comprehensive surveys of all assemblages
in an ecosystem if the indicator taxa exhibit a high degree of concordance (r > 0.7) with cooccurring taxa (Heino 2010, Dolph et al. 2011). Concordance of two assemblages can reveal
patterns in how each assemblage responds to characteristics of its environment and interactions
among assemblages (Santoul et al. 2004).
Concordance analysis, or cross-taxon congruence, is used to measure the similarity of
assemblage composition or richness among sites between two or more taxonomic groups
(Pazskowksi and Tonn 2000, Paavola et al 2006, Larsen et al. 2012). Concordance has been
evaluated by observing the similarity of assemblages across a set of sites by measuring taxon
4
richness or diversity, or assemblage composition (Heino 2010). Several mechanisms are thought
to produce concordance: similar but independent responses of taxa to the same environmental
conditions, biotic interactions such as trophic cascades (Paavola et al. 2003, Gioria et al. 2011,
Larsen et al. 2012), co-occurring taxa because of the shared biogeographical and evolutionary
history of a regional pool of taxa (Gioria et al. 2011, Larsen et al. 2012), and concurrent loss of
taxa along stress gradients (Larsen et al. 2012).
Previous studies have detected statistically significant concordance in freshwater lotic
ecosystems (Paavola et al. 2006, Infante et al. 2009, Virtanen et al. 2009, Heino 2010), though
detection of concordance is complicated by the differing metrics used (e.g. taxon richness versus
assemblage composition) and the spatial scale of the collections. Patterns of assemblage
composition often exhibit stronger concordance than patterns of species richness, which can
result in differential detection of concordance (Gioria et al. 2011). Concordance also tends to be
stronger at larger scales, for example multiple watersheds, rather than within a single river
system (Paavola et al. 2006, Grenouillet et al. 2008, Gioria et al. 2011), though the mechanisms
for concordance may be difficult to identify at larger scales (Larsen et al. 2012).
We studied assemblage concordance of, and environmental influences on fish and
macroinvertebrate assemblages in Indiana streams. Our objective was to quantify if
macroinvertebrate assemblages in Indiana streams were better predicted from co-occurring fish
assemblages or environmental variables. We expected that macroinvertebrate and fish
assemblages would respond to different environmental variables. We also expected that
environmental variables would have a stronger effect on macroinvertebrate assemblage
composition than the effect from the local fish assemblage.
Methods
5
Site Identification and Selection
Stream sites with drainage areas less than 2,600 km² were selected from an Indiana
Department of Environmental Management site list for the Indiana Eastern Corn Belt Plain
Ecoregion (Figure 1). Sixteen sites in this ecoregion were randomly selected using Hawth’s
analysis tools in ArcGIS from the site list from the Indiana Department of Environmental
Management as primary sampling sites and an additional 50 secondary sites were selected as
alternates. Drainage areas were obtained with Hawth’s analysis tools in ArcGIS. Primary sites
that were too shallow or inaccessible were omitted, and secondary sites were used as
replacements. Secondary site selection was not based on proximity to each primary site. We
required one additional secondary site to fit our site selection criteria. Reach length for sites was
15 times the wetted width of the stream with a maximum length of 200 m (Barbour et al. 1999).
We used a range finder (Wildgame Innovations D600X Laser Rangefinder) to quantify stream
width, and then sample reach length. GPS coordinates were recorded at each end of sample
reaches.
Sites were sampled from June through August of 2013. Sampling for fish and
invertebrates took place on the same day, and fish were collected before invertebrates at each
site.
Environmental Variables
We measured 18 physical and chemical stream variables at each site to quantify
habitat variation (Table 1). Stream width and sampling reach length were measured with a
laser range finder. Average depth was at seven equidistant points along transects placed
across the width of the stream, and transects were at 10 m distances. Substrate type was
estimated from a qualitative assessment for percentage of sampling area as fine substrate,
6
gravel, cobble, and boulder. Habitat type was estimated from a qualitative assessment for
percentage of sampling area as pool, riffle, run, and glide. Chemical characteristics were
measured with a Hydrolab DS5 probe with the Hach Trimble Recon field computer and
included conductivity (mS), water temperature (°C), turbidity (NTU), dissolved oxygen
(mg/L), and pH.
The methodology of the Qualitative Habitat Evaluation Index (QHEI) of Rankin
(1989) was used to estimate habitat qualities of substrate, in-stream cover, channel
morphology, bank erosion and riparian status, pool and current quality, riffle and run
quality, and gradient at each site.
Macroinvertebrate Collection and Identification
A multihabitat sampling method from USEPA was used to define benthic
macroinvertebrate collections (Barbour et al. 1999). All major habitats (cobble, snags, vegetated
banks, macrophytes, and sand) were sampled in proportion to their overall representation within
the sample reach. Sampling began at the downstream end of the reach and proceeded upstream,
and approximately 3.1 m² of habitat was sampled in each sample reach (Barbour et al. 1999).
The substrate of the sampled habitat was disturbed, either by jabbing or kicking and a D-frame
dipnet with 500 μm mesh was used to collect macroinvertebrates 0.5 m downstream of the
disturbed habitat. A kick consisted of standing 0.5 m upstream of the net and forcefully moving
or scraping the substrate once. In areas with limited flow or areas where kicking was constrained,
jabbing was used, which involved forcefully thrusting the net into 0.5 m of the habitat being
sampled (Barbour et al. 1999). We collected a total of 20 dipnet kicks or jabs from each
sampling reach, that were proportionally divided based on the percent representation of habitat
types (e.g., if riffles represented 50% of the habitat of the reach, 10 kicks were from riffle areas)
7
(Barbour et al. 1999). The number of dipnet kicks and jabs in each habitat type was recorded.
Habitat types representing less than 5% of the habitat in the reach were not sampled. All jabs and
kicks were combined into a single sample for each sample reach. Samples were labeled and
preserved in 95% ethanol.
A subsample of macroinvertebrates for sorting was removed in the laboratory as follows.
Each sample was first washed through a 500 μm sieve and then poured into a 38 x 31.7 cm tray
with a 6.3 x 6.3 cm numbered grid and fresh 95% ethanol. The sample contents were evenly
distributed in the tray, and five numbered grid squares were selected for sub-samples using a
random number generator. All macroinvertebrates from these grid squares were picked from the
sample and counted. If the total number of macroinvertebrates from the first five squares was
under 200 individuals (Barbour et al. 1999), additional grid squares were randomly selected and
counted until the total of all macroinvertebrates equaled or exceeded 200 individuals, or all grid
squares had been selected. The macroinvertebrates in each subsample were identified to the
lowest practical taxon, generally genus (Peckarsky et al. 1990, Barbour et al. 1999, Merritt,
Cummins, and Berg 2008, Thorp and Covich 2010). The count of invertebrates represented their
relative abundance in the habitat, rather than a density measurement.
Fish Collection and Identification
Sampling reach length was 15 times the wetted width of the stream with a maximum
length of 200 m (Barbour et al. 1999). Sampling reaches were closed off at the upstream and
downstream ends with block nets. Fishes were then collected by electrofishing the blocked-off
study reach. One pass with a tote-barge DC electrofishing unit was conducted in an upstream
pattern. At the end of the pass, fishes were identified and counted. After all fishes were identified
and counted for the pass, the fishes were released in the stream outside of the sampling reach
8
blocked by the nets. Fishes that required visual examination under a dissecting microscope to be
identified were kept as vouchers, as well as one voucher specimen for each species present.
Voucher specimens were preserved in 10% formalin on site and later identified at Ball State
University (Smith 1979, Pflieger 1997, Simon 2011). The count of fish represented their relative
abundance in the habitat, rather than a density measurement.
Data Analysis
Multivariate analyses were used to summarize patterns among sites for macroinvertebrate
family and fish species composition. Insect and fish taxa with total relative abundances for all
sites that comprised less than 1% of the total relative abundance of all individuals for all sites
were considered rare and were not included in the analyses (Gauch 1982). Non-insect
invertebrate taxa occurring at more than one site were recorded as presence/absence and included
in multivariate analyses. Relative abundances of insect families and fish species were
transformed by log (x+1). Environmental variables that were measured as percentages (substrate
type, habitat type) were transformed with an arc-sine transformation.
A Correspondence Analysis (CA) in CANOCO 5 software (ter Braak and Smilauer 2012)
was used to summarize patterns in log (x+1) transformed fish relative abundances across sites.
Axes that explained more than 11% of the variation were included in subsequent analyses. The
first three resulting CA axes were used as environmental predictors, along with the
environmental variables measured at each site, of macroinvertebrates in a direct gradient analysis
known as Canonical Correspondence Analysis. A separate Canonical Correspondence Analysis
was performed with fish and the site environmental variables. Canonical Correspondence
Analysis (CCA), a multivariate technique that is constrained by environmental variables, was
used as a separate predictor of taxon relative abundances for both macroinvertebrates and fishes
9
in CANOCO 5 software (ter Braak and Smilauer 2012). We used the forward selection of
environmental variables to identify significant predictor variables of macroinvertebrate
assemblages and fish assemblages at alpha = 0.05. We assessed concordance between fish and
macroinvertebrate assemblages with a Mantel test and a partial Mantel test (to control for
environmental effects) using Bray-Curtis dissimilarity matrices in R version 2.15.3 (R Core
Team 2013).
Results
A total of 3,344 invertebrates comprising 58 families, and 6,072 fishes comprising 62 species
were collected (Appendixes 1-3). After deleting rare taxa, we used 25 macroinvertebrate families
and 21 fish species in multivariate analyses. The first three CA axes of fish relative abundances
explained 55% of total variation. The first CA axis was positively related to greenside darter,
johnny darter, logperch, mottled sculpin, orangethroat darter, rock bass, and striped shiner and
negatively related to golden redhorse, longear sunfish, mimic shiner, sand shiner, silverjaw
minnow, and spotfin shiner. Variation on the second CA axis was explained positively by
greenside darter, logperch, mimic shiner, northern hogsucker, rainbow darter, rock, and spotfin
shiner while creek chub, green sunfish, silverjaw minnow, and white sucker loaded negatively.
Variation on the third CA axis was explained positively by creek chub, bluegill, green sunfish,
mimic shiner, mottled sculpin, and rock bass, and negatively by golden redhorse, logperch, and
silverjaw minnow (Table 3).
The first two CCA axes of the relationship between macroinvertebrates and environmental
variables resulted in two significant predictors of macroinvertebrate distribution and relative
abundance (P < 0.0001) which explained 26% of the variance (Table 4). Cover was negatively
correlated with the first CCA axis (Figure 2). Leptohyphid mayflies, talitrid amphipods, and
10
ilyocryptid cladocerans occurred in locations with greater in-stream cover. The second CCA axis
was positively correlated with turbidity and hydrachnid mites, which occurred more frequently
where turbidity was greatest (Figure 2). Correspondence analysis axes of fish relative
abundances were included in this CCA, but were not significant predictors of macroinvertebrate
distribution and relative abundance.
The second CCA resulted in a significant result (P <0.0001) with four significant predictors
of fish distribution and relative abundance, and explained 47.5% of the variance (Table 4). Fine
sediments were negatively correlated with the first CCA axis. Pools were positively correlated
with the first CCA axis, and Logperch occurred in greater relative abundances in locations with
more pools. The second CCA axis was positively correlated with both bedrock and water
temperature. Mimic Shiner occurred in greater relative abundances in sites with a higher
percentage of bedrock (Figure 3).
Distance matrices of fish and macroinvertebrates were significantly correlated in both
the Mantel test (r= 0.22, p= 0.019) and the partial Mantel test (r=0.23, p= 0.013).
Discussion
Fish and macroinvertebrate assemblages are used in rapid bioassessment studies to
evaluate the ecological integrity of freshwater ecosystems. These studies assume that the
assemblages respond similarly to environment gradients (Kilgour and Barton 1999, Infante et al.
2009) and in the case of the surrogate taxa approach, that the assemblages have a high degree of
concordance (Heino 2010). Our objective was to quantify if macroinvertebrate assemblages in
Indiana streams were better predicted from co-occurring fish assemblages or environmental
variables. We found that benthic invertebrate assemblages and fish assemblages responded to
different sets of environmental variables, and that patterns in fish assemblages were not
11
significant predictors of invertebrate relative abundances. The fish and invertebrate assemblages
were significantly concordant, but an r value of 0.23, and a failure of fish assemblage patterns to
be significant predictors of macroinvertebrates in the CCA made environmental variables, rather
than fish assemblage composition, better predictors of invertebrate assemblage composition. This
contributes to an increasing volume of literature with evidence for a low degree of concordance
among fish and invertebrate assemblages in freshwater ecosystems (Heino 2010). Different
responses of fish and macroinvertebrate assemblages to environmental variables and significant
but low correlation between the two assemblages indicates that the surrogate taxa approach to
bioassessment probably is not useful in the Eastern Cornbelt Plains ecoregion (Heino 2010,
Dolph et al. 2011).
Our two canonical correspondence analyses indicated that fish and invertebrates do not
respond similarly to environment gradients we quantified. Fish responded to bedrock, fine
sediments, pools, and water temperature, while invertebrates responded to in-stream cover and
turbidity. Jackson and Harvey (1993) and Larsen et al. (2012) both found that fish and
invertebrate assemblages responded to different abiotic drivers. Jackson and Harvey (1993)
found that fish assemblages among 40 lakes in Ontario were associated with lake morphological
characteristics but not water chemistry, whereas invertebrate assemblages were not associated
with lake morphology, but were correlated with water chemistry. Larsen et al. (2012) found that
invertebrates in 31 reaches of 13 Mediterranean streams responded to water organic content,
channel morphology, and substrate morphology, while fishes were associated with water
temperature and local land use. Such dissimilar sensitivities of fish and invertebrate assemblages
to alternative environmental variables of the same habitats suggest that environmental
management plans need to include surveys of diverse assemblages to thoroughly assess
12
ecological integrity (Larsen et al. 2012).
Based on a literature review by Heino (2010), the level of concordance that was found in
our study would not be adequate to use one assemblage to predict the other. The surrogate taxa
approach, which is used to predict community metrics of assemblages using the same metrics
from an indicator assemblage relies on strong (r > 0.7) positive concordance between the
assemblages for the technique to be useful to environmental managers (Heino 2010). We found
that although concordance between fish and macroinvertebrate assemblages was highly
significant, it was not a strong relationship (r = 0.23). Stronger concordance tends to be found at
larger spatial scales (Heino et al. 2005, Heino 2010, Gioria et al. 2011). Our study was across a
fairly large ecoregion and across multiple watersheds, and despite this large scale the degree of
concordance between the two assemblages was low. The large biogeographical or regional scales
at which concordance tends to be strongest are not the scales for management decisions using
biodiversity and ecological integrity (Heino et al. 2005). Since the surrogate taxa approach relies
on strong concordance among assemblages, the tendency for weaker relationships at local scales
makes this approach of little use in local management decisions.
Paszkowksi and Tonn (2000) and Kilgour and Barton (1999) studied fish and bird
assemblages and fish and invertebrate assemblages, and the two assemblages studied in each
case were strongly influenced by the same environmental factors. The assemblages in each study
were also concordant. Paszkowksi and Tonn (2000) claimed that concordance of fishes and birds
was likely an outcome of indirect, parallel assemblage responses to the environment. In contrast,
Jackson and Harvey (1993) attributed the concordance between fishes and invertebrates in their
study to contributions from biotic interactions both within and between the assemblages. We
found that fish and invertebrate assemblages were significantly concordant in a Mantel test as
13
well as a partial Mantel test with control for environmental variables. The results of the partial
Mantel test indicate that the low degree of concordance between fish and invertebrate
assemblages is not the result of similar assemblage responses to environmental gradients. The
Mantel and partial Mantel tests do not rule out that biotic interactions within and between the
assemblages could have produced concordance, as suggested by Jackson and Harvey (1993).
However, our ordination of the fish assemblages using correspondence analysis did not
significantly explain variation of the macroinvertebrate assemblages when included in a CCA,
and we did not directly assess biotic interactions of fish and invertebrate assemblages. Future
work using co-correspondence analysis would directly quantify the importance of biotic
interactions to assemblage concordance (ter Braak and Scaffers 2004).
Assemblage composition and richness are the sum of many variables at multiple spatial
scales (Vinson and Hawkins 1998, Brosse et al. 2003). Both niche theory and neutral theory
effectively explain regulation of species assemblages (Saetersdal and Gjerde 2011), though
previous studies typically document support for niche theory dynamics or neutral theory
dynamics, not both. Niche theory hypothesizes that species distributions are based on the
availability of favorable environmental conditions for a particular species, or a niche. Each
species is thought to have a unique niche. Neutral theory hypothesizes that biodiversity of
organisms is not dependent on niches, as organisms of the same trophic level are assumed to be
equivalent in terms of their suitability for the habitat, but rather dependent on dispersal,
immigration, and death (Volkov et al. 2003, Saetersdal and Gjerde 2011). In an example of niche
theory, Townsend et al. (2003) found that stream fish assemblages were most strongly influenced
by environmental variables at the bedform scale. However, Lammert and Allen (1999) suggested
that the mobility of fishes between connected streams could reduce their sensitivity to local
14
habitat patchiness. Macroinvertebrate assemblage composition seems best explained based on
niche theory dynamics (Heino and Mykra 2008, Robinson et al. 2014). In direct studies of
mechanisms dictating macroinvertebrate assemblage composition, both Robinson et al. (2014)
and Heino and Mykra (2008) found that spatial distribution of macroinvertebrate assemblages
were significantly related to spatial patterns in environmental characteristics. Regardless of the
dominant mechanism that structures assemblages, Saetersdal and Gjerde (2011) argue against the
claim that assemblage concordance provides support for the use of surrogate taxa methods of
bioassessment. Neither niche theory nor neutral theory supports the use of the surrogate taxa
approach because both theories maintain that species are independent, and their locations are
independent of other species (Saetersdal and Gjerde 2011).
The best statistical analysis to evaluate concordance is not certain (Gioria et al. 2011).
The Mantel test is a commonly used method to measure concordance of assemblages, but
Procrustes analysis and the recently developed co-correspondence analysis are also used (Gioria
et al. 2011, ter Braak and Schaffers 2004). However, Heino (2010) found that concordance
studies of freshwater assemblage composition detected significant concordance that was fairly
consistently below r = 0.5 (in correlations) or above m2 = 0.5 (for Mantel tests and Procrustes
analysis), indicating that assemblages did not tend to show similar patterns in composition across
sites.
In summary, our results suggest that macroinvertebrates respond significantly to local and
regional environmental variation, and less to the local presence of fishes. Fish and invertebrates
responded to different environmental variables, and invertebrates did not respond to patterns in
fish abundances. There was weak but significant concordance between fish and invertebrate
assemblages, consistent with many other freshwater systems (Heino 2010). This weak
15
connection indicates that the surrogate taxa approach has little use at the Eastern Cornbelt Plain
ecoregion of Indiana. Stream biodiversity is best predicted using multiple variables at several
scales that are modeled simultaneously (Brosse et al. 2003). Stream surveys of multiple taxa and
environmental variables are likely appropriate assessment methods for ecosystem integrity.
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20
Table 1. Physicochemical parameters measured at sixteen sites in the Eastern Cornbelt Plain
ecoregion of Indiana in summer 2013.
Parameter
Conductivity
Turbidity
Water temperature
pH
Dissolved Oxygen
Stream width
Reach length
Average depth
Habitat type
pool
riffle
run
glide
Substrate type
fines
gravel
cobble
boulder
bedrock
QHEI indices
Substrate
In-stream Cover
Channel Morphology
Erosion and Riparian
Pool/Current
Riffle/Run Quality
Gradient
Total QHEI
Units
mS
NTU
°C
mg/L
m
m
m
Mean value
620.2
44.5
21.9
8.07
7.31
12
139
0.36
%
%
%
%
20
19
42
21
%
%
%
%
%
62
17
12
4
4
Maximum 20
Maximum 20
Maximum 20
Maximum 10
Maximum 12
Maximum 8
Maximum 10
Maximum 100
13.3
14.9
9.7
4.2
8.7
2.9
6.9
60.6
21
Table 2. Macroinvertebrate family and order names and abbreviations for Figure 2.
Macroinvertebrates were collected from 16 sites in the Eastern Cornbelt Plain ecoregion of
Indiana in summer 2013.
Family Name
Abbreviation
Ancylidae
Ancylida
Asellidae
Asellida
Baetidae
Baetidae
Caenidae
Caenidae
Cambaridae
Cambarid
Chironomidae
Chironom
Coenagrionidae
Coenagri
Copepoda unknown
CopeUnkn
Corbiculidae
Corbicul
Diptera Pupae
DiptPupa
Elmidae
Elmidae
Heptageniidae
Heptagen
Hyalellidae
Hyalelld
Hydrachnidae
Hydrachn
Hydrachnidia Unknown
HydrUnkn
Hydrobiidae
Hydrobii
Hydrophilidae
Hydrophl
Hydropsychidae
Hydropsc
Ilyocryptidae
Ilyocryp
Leptohyphidae
Leptohyp
22
Oligochaeta unknown
OligUnkn
Physidae
Physidae
Pleuroceridae
Pleurocr
Sphaeridae
Sphaerid
Talitridae
Talitrid
23
Table 3. Fish species loadings on the first three axes of a CA of fish species. Abbreviations from
Figure 3 are in parentheses. Fish were collected from 16 sites in the Eastern Cornbelt Plain
ecoregion of Indiana in summer 2013.
CA axis 1 CA axis 2
Bluegill (Bluegill)
0.1525
-0.7977
Bluntnose Minnow (BlunMinn)
0.1206
-0.1771
Central Stoneroller (CentSton)
-0.0190
-0.2604
Creek Chub (CreeChub)
0.0312
0.0972
Golden Redhorse (GoldRedh)
-0.3063
0.1459
Green Sunfish (GreeSunf)
-0.1565
-0.4202
Greenside Darter (GreeDart)
0.4247
0.3506
Johnny Darter (JohnDart)
0.3172
-0.2604
Logperch (Logperch)
0.4830
1.0789
Longear Sunfish (LongSunf)
-0.5413
-0.0282
Mimic Shiner (MimcShin)
-1.3909
1.3218
Mottled Sculpin (MottScul)
1.4546
0.0372
Northern Hogsucker (NortHogs) 0.0850
0.5358
Orangethroat Darter (OranDart)
0.4299
0.1281
Rainbow Darter (RainDart)
0.1619
0.3320
Rock Bass (RockBass)
0.4041
0.4128
Sand Shiner (SandShin)
-0.4888
-0.0968
Silverjaw Minnow (SilvMinn)
-0.5251
-0.6719
Spotfin Shiner (SpotShin)
-0.4404
0.3579
24
Striped Shiner (StrpShin)
0.3979
-0.2981
White Sucker (WhitSuck)
0.2825
-0.6080
Variation Explained (%)
22.01
18.94
25
Table 4. Significant environmental predictor variables of macroinvertebrate and fish assemblages
at 16 Indiana sites in summer 2013 based on percentage contribution to variance explained in
two canonical correspondence analyses (CCA).
Variable
% variation
P
Macroinvertebrate CCA
Cover
14.0
0.002
Turbidity
12.1
0.002
Variance Explained
26.1
Fish CCA
Fines
15.8
0.002
Bedrock
13.3
0.004
Water Temperature
9.8
0.042
Pools
8.6
0.036
Variance Explained
47.5
26
Figure 1. Map of 16 sites where fish and macroinvertebrates were sampled in summer 2013 in
the Eastern Cornbelt Plain ecoregion of Indiana.
1.0
27
Turbidity
Hydrachn
OligUnkn
Cambarid
Ancylida
CopeUnkn
Physidae
Corbicul Chironom Caenidae
Coenagri
Pleurocr
Sphaerid
DiptPupa
Hydrophl
Heptagen
Elmidae
Hydropsc
Hydrobii
Leptohyp HydrUnkn
Baetidae
-0.6
Asellida
Talitrid
Cover
Hyalelld
Ilyocryp
-1.0
0.8
Figure 2. Two axes from CCA analysis of macroinvertebrate relative abundances at 16 Indiana
sites in the Eastern Cornbelt Plain ecoregion in summer 2013. Triangles represent
macroinvertebrate taxa. Environmental variables are represented as vectors. Macroinvertebrate
abbreviations are in Table 2.
1.0
28
Bedrock
MimcShin
-0.4
Water Temperature
LongSunf
RainDart
GoldRedh
SilvMinn
NortHogs
SpotShin
BlunMinn
OranDart
GreeSunf
GreeDart
Bluegill
SandShin
CentSton RockBass
WhitSuck
JohnDart
Logperch
CreeChub StrpShin
Fines
MottScul
-1.0
Pool
0.8
Figure 3. Two axes from CCA analysis of fish relative abundances at 16 Indiana sites in the
Eastern Cornbelt Plain ecoregion in summer 2013. Triangles represent fish taxa. Environmental
variables are represented as vectors. Abbreviations for fish names are in Table 3.
29
Appendix 1.
Insect Family Abundances
Order:
Family:
Diptera
Chironomidae
Ephemeroptera
Caenidae
Trichoptera
Hydropsychidae
Coleoptera
Elmidae
Ephemeroptera
Baetidae
Odonata
Coenagrionidae
Diptera
Pupae
Ephemeroptera
Heptageniidae
Site
Blue River
Killbuck
White River
Nolan Creek
Little Blue River
Pipe Creek
Prong Creek
Lake Ditch
Whitewater River
Cedar Creek
8 mile Creek
6 mile Creek
Wildcat Creek
Little Pine Creek
Mill Creek
Sand Creek
Total
97
171
102
143
19
83
148
94
83
146
219
183
64
62
256
71
1941
0
0
1
5
24
2
25
56
2
2
61
58
0
5
6
3
250
41
4
8
9
15
0
0
0
21
4
0
0
106
13
7
7
235
1
20
24
5
0
4
6
0
17
29
8
4
23
42
1
7
191
2
19
3
16
12
0
0
6
11
0
0
0
10
38
0
5
122
0
0
0
0
0
0
5
25
1
0
34
4
1
0
0
28
98
4
4
0
8
6
3
21
0
1
0
2
3
0
0
3
16
0
2
65
5
1
3
10
6
3
5
18
2
7
6
3
77
30
Insect Family Abundances
Order:
Family:
Coleoptera
Hydrophilidae
Ephemeroptera
Leptohyphidae
Diptera
Simuliidae
Diptera
Tipulidae
Trichoptera
Hydroptilidae
Coleoptera
Haliplidae
Hemiptera
Corixidae
Diptera
Ceratopogonidae
Trichoptera
Leptoceridae
Site
Blue River
Killbuck
White River
Nolan Creek
Little Blue River
Pipe Creek
Prong Creek
Lake Ditch
Whitewater River
Cedar Creek
8 mile Creek
6 mile Creek
Wildcat Creek
Little Pine Creek
Mill Creek
Sand Creek
Total
0
0
0
0
0
0
1
7
0
0
4
1
0
1
1
43
58
0
0
1
12
1
0
0
0
13
2
0
0
16
6
0
1
52
2
2
0
1
0
0
0
0
1
0
0
0
2
14
0
0
22
4
0
0
0
3
0
1
0
2
1
1
0
0
0
1
0
13
1
1
0
0
0
0
0
1
0
0
1
1
3
0
3
1
12
0
0
0
1
0
0
0
1
0
0
0
0
0
0
2
6
10
0
3
0
0
5
0
0
0
0
0
0
0
0
0
1
0
9
0
0
0
0
0
1
1
3
2
0
0
0
0
0
1
0
8
1
0
0
3
3
0
0
0
0
0
0
0
0
0
0
0
7
31
Insect Family Abundances
Order:
Family:
Diptera
Culicidae
Diptera
Tabanidae
Hemiptera
Gerridae
Coleoptera
Psephenidae
Odonata
Aeshnidae
Hemiptera
Belostomatidae
Trichoptera
Polycentropodidae
Diptera
Psychodidae
Hemiptera
Notonectidae
Site
Blue River
Killbuck
White River
Nolan Creek
Little Blue River
Pipe Creek
Prong Creek
Lake Ditch
Whitewater River
Cedar Creek
8 mile Creek
6 mile Creek
Wildcat Creek
Little Pine Creek
Mill Creek
Sand Creek
Total
0
0
0
0
0
0
0
0
0
0
1
5
0
0
0
0
6
0
0
0
0
5
0
0
0
0
0
0
0
0
1
0
0
6
0
1
0
0
0
0
0
0
1
0
0
1
0
0
0
3
6
0
0
5
1
0
0
0
0
0
0
0
0
0
0
0
0
6
0
0
2
0
0
0
0
0
0
0
0
0
0
3
0
1
6
0
0
0
0
5
0
0
0
0
0
0
0
0
0
0
0
5
0
0
0
0
0
0
0
0
0
1
0
0
0
2
0
0
3
0
0
0
0
0
3
0
0
0
0
0
0
0
0
0
0
3
0
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
3
32
Insect Family Abundances
Order:
Family:
Coleoptera
Scirtidae
Ephemeroptera
Isonychiidae
Trichoptera
Philopotamidae
Coleoptera
Dytiscidae
Megaloptera
Sialidae
Odonata
Calopterygidae
Ephemeroptera
Ephemeridae
Ephemeroptera
Polymitarcyidae
Site
Blue River
Killbuck
White River
Nolan Creek
Little Blue River
Pipe Creek
Prong Creek
Lake Ditch
Whitewater River
Cedar Creek
8 mile Creek
6 mile Creek
Wildcat Creek
Little Pine Creek
Mill Creek
Sand Creek
Total
0
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
3
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
2
0
0
0
1
0
0
0
0
0
0
0
0
0
1
0
0
2
0
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
2
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
2
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
33
Insect Family Abundances
Order:
Family:
Trichoptera
Limnephilidae
Trichoptera
Phryganeidae
Trichoptera
Psychomyiidae
Diptera
Scizomyzidae
Diptera
Stratiomyidae
Hemiptera
Pleidae
Hemiptera
Vellidae
Coleoptera
Dryopidae
Site
Blue River
Killbuck
White River
Nolan Creek
Little Blue River
Pipe Creek
Prong Creek
Lake Ditch
Whitewater River
Cedar Creek
8 mile Creek
6 mile Creek
Wildcat Creek
Little Pine Creek
Mill Creek
Sand Creek
Total
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
1
34
Appendix 2.
Non-Insect Invertebrate Families
Order:
Amphipoda
Hyalellidae
Family:
Site
Blue River
Killbuck
White River
Nolan Creek
Little Blue River
Pipe Creek
Prong Creek
Lake Ditch
Whitewater River
Cedar Creek
8 mile Creek
6 mile Creek
Wildcat Creek
Little Pine Creek
Mill Creek
Sand Creek
Amphipoda
Talitridae
Bivalvia
Corbiculidae
Bivalvia
Sphaeridae
Present
Present
Present
Present
Present
Present
Cladocera
Ilyocryptidae
Copepoda
Decapoda
Cambaridae
Entomobryomorpha
Isotomidae
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
35
Non-Insect Invertebrate Families
Order:
Gastropoda
Ancylidae
Family:
Site
Blue River
Killbuck
White River
Present
Nolan Creek
Little Blue River
Pipe Creek
Prong Creek
Lake Ditch
Present
Whitewater River
Cedar Creek
8 mile Creek
6 mile Creek
Wildcat Creek
Present
Little Pine Creek
Mill Creek
Sand Creek
Gastropoda
Hydrobiidae
Gastropoda
Physidae
Gastropoda
Planorbidae
Gastropoda
Pleuroceridae
Hirudinea
Erpobdellidae
Hirudinea
Glossiphoniidae
Hydrachnidia
Hydrachnidae
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
36
Non-Insect Invertebrate Families
Order:
Hydrachnidia
Limnesiidae
Family:
Site
Blue River
Killbuck
White River
Nolan Creek
Little Blue River
Pipe Creek
Prong Creek
Lake Ditch
Whitewater River
Cedar Creek
8 mile Creek
Present
6 mile Creek
Wildcat Creek
Little Pine Creek
Mill Creek
Sand Creek
Hydrachnidia
Unknown
Isopoda
Asellidae
Oligochaeta
Present
Present
Present
Present
Present
Present
Present
Present
Present
Present
37
Appendix 3.
Fish Species Abundances
Longear
Species
Sunfish
Site
Blue River
Killbuck
White River
Nolan Creek
Little Blue River
Pipe Creek
Prong Creek
Lake Ditch
Whitewater River
Cedar Creek
8 mile Creek
6 mile Creek
Wildcat Creek
Little Pine Creek
Mill Creek
Sand Creek
Total
0
0
20
0
68
2
109
16
8
0
363
168
98
28
60
293
1233
Bluntnose
Minnow
Central
Stoneroller
Green
Sunfish
Creek
Chub
Spotfin
Shiner
Bluegill
Northern
Hogsucker
Sand
Shiner
19
7
64
112
33
8
120
24
4
1
107
41
3
3
226
27
799
10
1
28
98
3
1
7
0
93
0
29
0
4
20
161
0
455
2
9
2
2
0
19
12
35
2
52
142
89
19
2
24
0
411
29
3
13
14
0
55
20
0
1
2
51
1
0
14
112
0
315
0
0
2
7
6
0
38
10
145
3
0
9
12
24
17
14
287
19
0
11
14
2
8
29
16
4
86
5
15
6
0
0
1
216
22
1
2
35
4
0
7
0
57
9
0
1
24
3
3
39
207
0
0
0
43
0
0
16
10
15
2
26
0
1
51
39
0
203
38
Fish Species Abundances
Silverjaw
Species
Minnow
Site
Greenside
Darter
Golden
Redhorse
White Sucker
Rock Bass
Mimic Shiner
Rainbow
Darter
Striped
Shiner
Orangethroat Darter
Blue River
Killbuck
White River
Nolan Creek
Little Blue River
Pipe Creek
Prong Creek
Lake Ditch
Whitewater River
Cedar Creek
8 mile Creek
6 mile Creek
Wildcat Creek
Little Pine Creek
Mill Creek
Sand Creek
1
0
0
2
0
1
45
22
0
0
4
0
0
0
87
4
10
6
18
17
31
1
4
0
22
25
0
1
4
0
4
20
0
1
0
54
7
0
20
9
15
0
1
4
1
3
2
44
13
5
16
40
0
13
7
9
0
3
11
15
0
0
8
0
1
9
25
34
29
2
0
0
3
7
0
1
10
9
0
0
0
0
0
0
0
0
0
1
0
0
0
0
113
2
0
0
12
0
8
38
0
1
2
0
22
0
0
0
6
0
12
12
1
0
16
66
8
0
1
0
0
0
20
0
0
0
1
0
0
10
43
12
2
5
2
0
18
0
0
0
1
0
11
2
Total
166
163
161
140
130
116
113
113
106
39
Fish Species Abundances
Johnny
Species
Darter
Site
Mottled
Sculpin
Logperch
Smallmouth
Bass
Steelcolor
Shiner
Yellow
Bullhead
Largemouth
Bass
Common
Carp
Redfin
Shiner
Blue River
Killbuck
White River
Nolan Creek
Little Blue River
Pipe Creek
Prong Creek
Lake Ditch
Whitewater River
Cedar Creek
8 mile Creek
6 mile Creek
Wildcat Creek
Little Pine Creek
Mill Creek
Sand Creek
2
3
32
6
2
2
8
0
0
3
6
0
2
0
29
0
55
18
1
7
2
0
0
0
0
2
0
0
0
0
0
0
0
0
1
0
3
0
0
0
69
9
0
0
0
0
0
0
0
0
0
8
1
0
0
0
3
0
0
11
11
5
4
10
0
0
1
0
1
0
1
3
13
0
0
1
4
18
3
4
0
0
1
0
1
2
0
0
0
1
16
8
0
3
12
0
4
0
0
3
0
2
7
4
7
1
3
0
1
0
0
2
1
0
0
1
0
0
0
24
5
1
0
0
1
0
0
0
0
4
11
1
0
0
0
0
0
0
1
1
1
7
4
0
Total
95
85
82
53
49
44
34
33
30
40
Fish Species Abundances
Emerald
Species
Shiner
Site
Blue River
Killbuck
White River
Nolan Creek
Little Blue River
Pipe Creek
Prong Creek
Lake Ditch
Whitewater River
Cedar Creek
8 mile Creek
6 mile Creek
Wildcat Creek
Little Pine Creek
Mill Creek
Sand Creek
Total
0
0
0
1
12
0
0
0
2
4
0
0
0
0
0
0
19
Blackstripe
Topminnow
Pumpkinseed
Sunfish
Banded
Darter
Channel
Catfish
Blacknose
Dace
Black
Redhorse
Fantail
Darter
River
Chub
0
0
0
7
0
4
0
1
0
2
3
1
0
0
0
0
18
0
0
0
0
0
0
0
0
0
0
0
18
0
0
0
0
18
0
0
0
1
0
0
0
0
14
0
0
0
0
0
1
0
16
0
0
0
0
0
0
0
0
11
0
1
4
0
0
0
0
16
11
0
0
0
0
0
0
0
0
0
0
0
0
0
4
0
15
0
0
0
0
0
0
0
0
13
0
0
0
0
1
0
0
14
0
0
2
0
1
0
0
0
0
7
0
0
0
0
0
1
11
0
0
0
0
0
0
0
0
0
0
0
0
5
0
0
5
10
41
Fish Species Abundances
Blackside
Species
Darter
Site
Blue River
Killbuck
White River
Nolan Creek
Little Blue River
Pipe Creek
Prong Creek
Lake Ditch
Whitewater River
Cedar Creek
8 mile Creek
6 mile Creek
Wildcat Creek
Little Pine Creek
Mill Creek
Sand Creek
Total
0
3
4
0
0
1
1
0
0
0
0
0
0
0
0
0
9
Hybrid
Sunfish
Shorthead
Redhorse
Suckermouth
Minnow
Bigeye
Chub
Mississippi Silvery
Minnow
Brindled
Madtom
Gizzard
Shad
Redear
Sunfish
2
0
0
1
0
0
0
0
0
5
0
0
0
0
0
0
8
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
5
8
0
0
0
0
0
0
0
0
7
0
0
0
1
0
0
0
8
0
0
0
0
0
0
0
0
0
0
0
0
6
0
0
0
6
0
0
0
0
0
0
0
0
0
0
0
0
0
6
0
0
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
4
5
0
0
0
0
0
0
0
0
5
0
0
0
0
0
0
0
5
1
0
0
0
0
0
0
0
0
4
0
0
0
0
0
0
5
42
Fish Species Abundances
Silver
Species
Shiner
Site
Blue River
Killbuck
White River
Nolan Creek
Little Blue River
Pipe Creek
Prong Creek
Lake Ditch
Whitewater River
Cedar Creek
8 mile Creek
6 mile Creek
Wildcat Creek
Little Pine Creek
Mill Creek
Sand Creek
Total
0
0
0
4
0
0
0
0
0
0
0
0
0
0
0
1
5
Grass
Pickerel
Tadpole
Madtom
Fathead
Minnow
Lamprey
ammocoetes
Quillback
Carpsucker
Brook
Silverside
Silver
Redhorse
Western Mosquitofish
0
3
1
0
0
0
0
0
0
0
0
0
0
0
0
0
4
0
0
0
0
0
3
0
0
0
0
0
0
1
0
0
0
4
0
0
0
0
0
3
0
0
0
0
0
0
0
0
0
0
3
2
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
3
0
0
0
0
0
0
1
0
1
0
0
0
1
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
2
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
0
2
0
0
0
0
0
0
0
1
0
0
0
0
0
1
0
0
2
43
Fish Species Abundances
Bigeye
Species
Shiner
Site
Blue River
Killbuck
White River
Nolan Creek
Little Blue River
Pipe Creek
Prong Creek
Lake Ditch
Whitewater River
Cedar Creek
8 mile Creek
6 mile Creek
Wildcat Creek
Little Pine Creek
Mill Creek
Sand Creek
Total
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1
Black
Crappie
Hornyhead
Chub
River Redhorse
Slenderhead
Darter
Spotted
Sucker
Stonecat
Madtom
Walleye
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1