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2014 NORTHEASTERN NATURALIST 21(3):419–430
Fish Assemblages of Floodplain Lakes in the Ohio River
Basin
Mark Pyron1,*, Luke Etchison1, and Julia Backus1
Abstract - We sampled fish assemblages in 41 floodplain lakes in the Ohio River Basin in
the summer of 2012. We collected 2427 individual fishes in 70 species. Mean abundance of
individuals at sites was 66, and mean species richness per site was 8.1. We used two multivariate
procedures to predict fish-assemblage variation from habitat and environmental
variables: an indirect gradient approach (reciprocal averaging [RA]) and a direct gradient
approach (canonical correspondence analysis [CCA]). When we applied a forward selection
process in the CCA, the habitat and environmental variables that contributed significantly
to explaining variation in fishes were mean elevation, latitude, maximum depth, conductivity,
longitude, dissolved oxygen, cobble and sand substrates, and lake-surface area. RA
provided different results that suggested the presence of additional environmental gradients
we did not quantify. Our results show that floodplain lakes in the Ohio River basin contain
high species richness and are important habitats to conserve because they have the potential
to act as source pools for river fish populations.
Introduction
Lowland rivers are dynamic ecosystems consisting of main channels and broad
floodplains that contain aquatic off-channel habitats including sloughs, oxbow
lakes, and wetlands that are collectively described as floodplain lakes. These floodplain
features extend river ecosystems into terrestrial environments and provide
important habitats for many aquatic organisms including fishes. Fishes may require
floodplain-lake habitat as adults, or as spawning and nursery sites (Scheimer 2000,
Winemiller et al. 2000). Lateral connections between a river and its floodplain
provide a means for fishes and other aquatic organisms to move between the two,
and they help to maintain habitats by facilitating sediment movement (Amoros and
Bornette 2002, Junk et al. 1989). Maintenance of these lateral connections is contingent
on hydrology and processes of sediment erosion and deposition (Sullivan
and Watzin 2009).
Floodplain lakes are biodiversity hotspots that can provide source populations
of fish and other organisms to streams (Copp 1989, Sullivan and Watzin 2009).
Winemiller et al. (2000) suggested that these habitats serve as source populations
for recruitment of certain fishes. Their example was for periodic-strategist fishes
that may have good recruitment during years with favorable spring discharge followed
by flooding, allowing young-of-the-year fishes connections to the main river
channel. Environmental variables strongly influence fish assemblages in floodplain
lakes (Lubinski et al. 2008, Miyazono et al. 2010). The degree of connectivity,
1Aquatic Biology and Fisheries Center, Department of Biology, Ball State University, Muncie,
IN 47306. *Corresponding author - mpyron@bsu.edu.
Manuscript Editor: David B. Halliwell
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and lake size and volume variables tend to be correlated, and they explain most
fish assemblage variation (Miranda 2005, Miyazono et al. 2010). Connectivity also
tends to influence local habitat variables such as turbidity and dissolved oxygen as
isolated lakes fill with sediments (Miranda 2005). Fish-occurrence patterns and assemblage
structure are well described for many locations in the Mississippi River
basin (Dembkowski and Miranda 2012, Miranda 2005, Miranda and Lucas 2004,
Miyazono et al. 2010) and elsewhere in North America (Sullivan and Watzin 2009,
Winemiller et al. 2000). Our goal was to quantify fish biodiversity and describe
relationships between environmental variables and fish assemblages in floodplain
lakes of the Ohio River Basin.
Field-Site Description
Floodplain rivers in the Ohio River watershed are impaired from a multitude of
anthropogenic influences including urban point-source pollution, dam operations,
agriculture, channelization, and dredging (Pyron and Neumann 2008, White et al.
2005). These impairments have created hydrologically altered ecosystems with
losses of riparian vegetation, excessive streambank erosion, increased turbidity,
altered temperature regimes, and loss of natural connectivity to floodplain lakes.
Prior to our study, floodplain-lake fish assemblages in the Ohio River basin had not
been examined. We identified 115 floodplain-like sites in the Ohio River basin in
Google Earth and sampled fishes at 41 of the sites that were accessible and not dry
during our visit in summer 2012 (Fig. 1). The drought of 2012 was the most severe
since 1895 (Hoerling et al. 2013) and caused the majority of sites we visited to be
too dry to sample.
Methods
Our sites varied widely in water depth and habitat complexity (thick macrophytes,
trees, and rootwads), which made it impossible for us to use the same
sampling approach for all of them. We sampled fishes with a backpack electrofisher
(ETS Electrofishing Model ABP-3, Middletown, WI) for 30 min (35 sites), a boat
electrofisher (Midwest Lake Electrofishing Systems Infinity, Polo, MO) for 30 min
(1 site), or at least 3 hauls with a 10-m x 2-m x 10-mm-mesh seine (5 sites). We
used 7mm-mesh dipnets for electrofishing collections and released fishes after we
identified them. At each site, we recorded latitude and longitude with a GPS unit and
quantified habitat and environmental variables as follows: water temperature (°C),
pH, dissolved oxygen (mg/L), and conductivity (μmhos) with a Hydrolab portable
meter; maximum water depth; dominant substrate type (boulder, cobble, gravel,
sand, silt, hardpan); and presence of woody debris. The following variables were
obtained using GIS ArcMap 10 software and a Bing maps base-layer: surface-water
area (m2), elevation of water body, elevation difference to closest river (m), and
distance to closest river (m).
To avoid effects of rare species on multivariate analyses (Gauch 1982), we
included only species with abundances higher than 0.1% of total fishes collected,
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and abundances were log (x + 1) transformed. We analyzed fish and habitat data
using two ordination approaches—an indirect gradient analysis based on an underlying
unimodal model of species distributions, and a direct gradient analysis
that constrained the results using the environmental variables (Palmer 1993).
Our purpose in using two analyses was to identify associations between the fish
assemblages and environmental variables. We used an indirect gradient method—
reciprocal averaging (RA) in Canoco 5 (Ter Braak and Smilauer 2012)—to examine
the distribution of species among sites and subsequent correlations with environmental
variables. We employed a constrained multivariate analysis—canonical
correspondence analysis (CCA) in Canoco 5 (Ter Braak and Smilauer 2012)—with
a stepwise-regression approach to predict species-abundance patterns among sites
based on environmental variables. We included the forward selection option (P ≤
0.05) to select habitat variables that were significant contributors to variation in fish
abundance, with 499 permutations to test significance (Miyazono et al. 2010). Both
multivariate analyses were repeated without the single boat-electrofishing site, to
test whether the site provided biased or dif ferent responses.
Results
Floodplain lakes are unevenly distributed across the Ohio River watershed.
Because the gradient of rivers decreased in the western portion of the watershed,
there was a greater number of sites in the Wabash River watershed (Fig. 1) than in
Figure 1. Collection sites in the Ohio River basin.
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Table 1. Ranked abundance and number of sites where fishes were captured. Code is abbreviation used
for species inluded in Figures 2 and 3.
# of
Common name Code Scientific name Abundance sites
Bluegill BLGI Lepomis macrochirus Rafinesque 689 29
Brook Silverside BRSI Labidesthes sicculus (Cope) 210 7
Gizzard Shad GISH Dorosoma cepedianum (Lesueur) 194 10
Western Mosquitofish MOSQ Gambusia affinis (Baird & Girard) 171 14
Bluntnose Minnow BLMI Pimephales notatus (Rafinesque) 125 11
Central Stoneroller CEST Campostoma anomalum (Rafinesque) 91 5
Lepomis hybrid LESP Lepomis spp. 65 7
LargemouthBass LABA Micropterus salmoides (Lacepéde) 65 15
Creek Chub CRCH Semotilus atromaculatus (Mitchill) 63 8
Warmouth WAMO Lepomis gulosus (Cuvier) 52 12
Southern Redbelly Dace SRBD Phoxinus erythrogaster (Rafinesque) 50 2
Longear Sunfish LESF Lepomis megalotis (Rafinesque) 49 10
Spotfin Shiner SPSH Cyprinella spiloptera (Cope) 49 7
Green Sunfish GRSF Lepomis cyanellus Rafinesque 48 14
White Sucker WHSU Catostomus commersonii (Lacepéde) 48 4
Eastern Blacknose Dace BLDA Rhinichthys atratulus (Hermann) 45 3
Sand sShiner SASH Notropis stramineus (Cope) 33 3
Steelcolor Shiner STSH Cyprinella whipplei Girard 29 5
White Crappie WHCR Pomoxis annularis Rafinesque 27 9
Black Bullhead BLBU Ameiurus melas (Rafinesque) 25 3
Common Carp COCA Cyprinus carpio L. 22 5
Northern Hog Sucker NOHS Hypentelium nigricans (Lesueur) 22 3
Rock Bass RB Ambloplites rupestris(Rafinesque) 21 4
Blackspotted Topminnow BLTM Fundulus olivaceus (Storer) 19 3
Blackstripe Topminnow BSTM Fundulus notatus (Rafinesque) 17 5
Pumpkinseed PUSF Lepomis gibbosus (L.) 17 5
Mottled Sculpin MOSC Cottus bairdii Girard 14 3
Shortnose Gar SNGA Lepisosteus platostomus Rafinesque 13 4
Yellow Bullhead YEBH Ameiurus natalis (Lesueur) 12 6
Spotted Sucker SPSU Minytrema melanops (Rafinesque) 11 6
Black Crappie BLCR Pomoxis nigromaculatus (Lesueur) 9 5
Goldfish GOFI Carassius auratus (L.) 9 5
Golden Shiner GOSH Notemigonus crysoleucas (Mitchill) 7 3
Redfin Shiner RFSH Lythrurus umbratilis (Girard) 7 4
Smallmouth Bass SMBA Micropterus dolomieu Lacepéde 7 5
Channel Catfish CHCA Ictalurus punctatus (Rafinesque) 6 3
Silverjaw Minnow SJMI Notropis buccata (Cope) 6 4
Striped Shiner STRS Luxilus chrysocephalus Rafinesque 6 4
Bowfin BOFI Amia calva Linnaeus 5 4
Bullhead Minnow BHMI Pimephales vigilax (Baird & Girard) 4 2
Greenside Darter GRDA Etheostoma blennioides Rafinesque 4 4
Mississippi silvery Minnow MSMI Hybognathus nuchalis Agassiz 4 2
Redfin Pickerel RDPI Esox americanus Gmelin 4 3
Smallmouth Buffalo SMBU Ictiobus bubalus (Rafinesque) 4 4
Black Buffalo BLBU Ictiobus niger (Rafinesque) 3 2
Grass Carp Ctenopharyngodon idella (Valenciennes) 3 3
Johnny Darter Etheostoma nigrum Rafinesque 3 2
Mud Darter Etheostoma asprigene (Forbes) 3 2
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the subwatersheds east of it. We collected 2427 individual fishes in 69 species and
1 hybrid at 34 sites (Table 1; 7 sites contained no fishes). Mean abundance of individuals
at sites was 66 (range = 0–1506), and mean species richness per site was 8.1
(range = 2–21). Mean Shannon-Weiner diversity for sites was 1.2 (range = 0–2.3),
mean Jaccard evenness index was 0.64 (range = 0–1), and mean Simpson dominance
score was 0.43 (range = 0.13–1). Mean water temperature was 21 °C (range
5–35 °C), mean dissolved oxygen was 5.7 mg/L (range = 0.5–12 mg/L), mean pH
was 7.5 (range = 5.5–8), and mean conductivity was 508 μmhos (range = 35–1090
μmhos). Mean surface area was 12,000 m2 (SD = 19,000), mean maximum depth
was 0.27 m (SD = 0.1), mean elevation difference from the site to nearest river was
9 m (SD = 10), and mean distance from the nearest river was 289 m (SD = 491).
The first and second RA axes explained 19.6 and 9.0% of variation, respectively
(Fig. 2), and gradient lengths of these axes were 4.3 and 2.9, respectively. The first
RA axis was negatively correlated with latitude (r = - 0.40, P = 0.017) and positively
correlated with surface area (r = 0.44, P = 0.007). Lepomis gulosus (Warmouth) and
Ameiurus melas (Black Bullhead) were abundant at southern lakes with large surface
areas (Fig. 2). Phoxinus erythrogaster (Southern Redbelly Dace) and Rhinichthys
atratulus (Eastern Blacknose Dace) were abundant at northern lakes with small
surface areas. The second RA axis was negatively correlated with conductivity ( r =
-0.33, P = 0.048). Sites with lower conductivity had higher abundance of Labidesthes
sicculus (Brook Silverside) and Pomoxis annularis (White Crappie) (Fig. 2). Sites
with higher conductivity had increased abundance of Black Bullhead.
Table 1, continued.
# of
Common name Code Scientific name Abundance sites
Orangespotted Sunfish Lepomis humilis (Girard) 3 4
Redear Sunfish Lepomis microlophus (Günther) 3 3
Silver Carp Hypophthalmichthys molatrix (Valenciennes) 3 4
Bigeye Chub Hybopsis amblops (Rafinesque) 2 2
Blackside Darter Percina maculate (Girard) 2 2
Freshwater Drum Aplodinotus grunniens Rafinesque 2 3
Logperch Percina caprodes (Rafinesque) 2 2
Mimic Shiner Notropis volucellus (Cope) 2 2
Pirate Perch Aphredoderus sayanus (Gilliams) 2 3
Silver Shiner Notropis photogenis (Cope) 2 2
Bigeye Shiner Notropis boops Gilbert 1 2
Bigmouth Buffalo Ictiobus cyprinellus (Valenciennes) 1 2
Brindled Madtom Noturus miurus Jordan 1 2
Brown Bullhead Ameiurus nebulosus (Lesueur) 1 2
Flier Centrarchus macropterus (Lacepéde) 1 2
Longnose Gar Lepisosteus osseus (L.) 1 2
Quillback Carpiodes cyprinus (Lesueur) 1 2
Rainbow Darter Etheostoma caeruleum Storer 1 2
River Carpsucker Carpiodes carpio (Rafinesque) 1 2
Shortnead Redhorse Moxostoma macrolepidotum (Lesueur) 1 2
Slough Darter Etheostoma gracile (Girard) 1 2
Tadpole Madtom Noturus gyrinus (Mitchill) 1 2
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The first 2 axes of the CCA explained 17% and 11% of variation, respectively
(Fig. 3). Habitat and environmental variables—mean elevation, distance to
river, surface area, sand substrate, and dissolved oxygen—accounted for 44.7%
of fish variation in a forward selection process (Table 2). Sites with lower elevation
difference, further distance from the adjacent river, smaller surface area,
and low dissolved oxygen had higher abundances of Carassius auratus (Goldfish)
and Gambusa affinis (Western Mosquitofish) than other sites (Fig. 3). Sites
nearer the adjacent river with greater surface area, higher dissolved oxygen, and
lower frequency of sand substrates had higher abundances of Dorsoma cepedianum
(Gizzard Shad) and Pomoxis nigromaculatus (Black Crappie) than sites
farther from the river with different conditions. Sites with lower surface area,
higher elevation difference, and sand substrates tended to have high species
richness (Fig. 3).
Figure 2. Biplot for first and second axes of a reciprocal averaging analysis. Closed circles
represent fish species and open circles are sites. Significant environmental correlations are
listed along axes. See Table 1 for species codes.
Table 2. Significant environmental variables from a forward selection procedure in canonical correspondence
analysis (CCA).
Variable Percent variation P
Mean elevation (m) 11.3 0.034
Distance to river (km) 10.2 0.038
Surface area (m2) 10.3 0.002
Sand substrate 7.0 0.010
Dissolved oxygen (mg/L) 5.9 0.044
Total variation 44.7
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Discussion
Floodplain river ecosystems are maintained by predictable seasonal flood
pulses that add and distribute nutrients and sediments (Sparks 1995). Scheimer
(2000) defined the ecological integrity of a large river and its floodplain habitats
Figure 3. First two axes of a canonical correspondence analysis (CCA) ordination. The top
plot contains species, and vectors represent significant habitat/environmental predictors of
fish abundances. The bottom plot represents sites, and circles are scaled to species richness
at sites. See Table 1 for species codes.
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according to hydrological connectivity, flux of nutrients and organic matter, and
habitat connectivity for fishes. Connectivity of a river with off-channel habitats
varies with water level (Lyon et al. 2010), and is likely the strongest explanation
of fish occurrence in off-channel habitats. Miyazono et al. (2010) found that fish
species with periodic life-history strategies (e.g., Lepisosetus spp. [gar] , Ictiobus
spp. [buffalo fish]; see Winemiller and Rose 1992) tended to occur in floodplain
lakes with higher connectivity-index scores than other species. These authors also
reported that fishes with opportunistic strategies (minnows, topminnows, and
poeciliids) tended to occur in floodplain lakes with lower connectivity; their connectivity
index increased with increasing distance of lakes to rivers, outlets, and
other nearby lakes (Miyazono et al. 2010). We found that 2 connectivity variables
were significant predictors of assemblage structure: mean elevation difference
and distance to the nearest river, but they were at opposite ends of the CCA ordination.
In our study, the floodplain lakes that were isolated by a higher elevation
difference contained higher abundances of Hypentelium nigricans (Northern Hog
Sucker), Cottus bairdii (Mottled Sculpin), and several minnows, a pattern that fits
the opportunistic life-history strategy of Winemiller and Rose (1992). However,
floodplain lakes that were isolated by distance contained invasive Goldfish and
Western Mosquitofish.
Isolation of floodplain lakes has a strong influence on fish-assemblage attributes.
Shoup and Wahl (2009) suggested that lakes with sufficient depth to avoid dessication
that were farther from a main river channel were more stable because they were
less affected by flood events than shallower water bodies located closer to main
channels. Schomaker and Wolter (2011) suggested an alternative interpretation of
the influence of isolation on fish occurrences using a generalist-specialist categorization:
generalist species of fishes tend to occupy water bodies in river floodplains
near a river channel, and specialist species tend to occupy water bodies farther away
from rivers. We found a generalist group of cyprinids (Notropis stramineus [Sand
Shiner], Eastern Blacknose Dace, Semotilus atromaculatus [Creek Chub]; Fig. 2)
and Catostomus commersonii [White Sucker] at sites with high connectivity (low
elevation difference from river to a floodplain lake). However, we did not find a
specialist group of fishes in floodplain lakes at the opposite end of this connectivity
gradient. In addition, we did not find a strong pattern of species richness with the
maximum depth gradient. Our findings were likely influenced by conditions during
the drought year in which we made our collections when isolated sites with the potential
to contain specialist species were dry. Sampling floodplain lakes for multiple
years would likely result in different patterns (Shoup and Wahl 2009).
Fish species richness is higher in assemblages that occur in floodplain lakes
where water depth and surface area are higher and where habitat diversity may be
greater (Dembkowski and Miranda 2012). Dembkowski and Miranda (2012) predicted
that shallow lakes that are likely to experience desiccation during drought
will have depauperate fish assemblages that are limited to species with the ability
to colonize rapidly. Deeper floodplain lakes with more stable water levels are predicted
to contain higher species richness and sensitive species (Dembkowski and
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Miranda 2012). We found a strong surface-area gradient for the second CCA axis,
but sites with the highest species richness tended to have a smaller surface area.
The species that we collected in floodplain lakes with smaller surface areas included
rapid colonizers (Western Mosquitofish and cyprinids).
Although our collections resulted in high overall species richness (70), the distribution
of species among lakes varied widely. Only 1 species occurred in more
than half of lakes— Lepomis macrochirus (Bluegill)—and only 7 additional species
occurred in one third of lakes. The majority of species occurred in less than 10 lakes, so
each was relatively rare in our collections. We found 4 non-native species, and only
Cyprinus carpio (Common Carp) occurred in higher abundance (22) than the other
exotics (maximum of 9). However, we observed multiple dry floodplain lakes that
appeared to contain hundreds of dead Hypophthalmichthys molatrix (Silver Carp)
or H. nobilis (Richardson) (Bighead Carp); flooded backwater areas are likely highquality
nursery habitats for larvae of these two species (Garve y 2008).
Floodplain habitats in the Ohio River Basin contain high fish-species richness,
with the potential to act as source pools to repopulate rivers following disturbances.
Several studies have provided evidence that floodplain lakes contribute to fish assemblages
in adjacent streams (Copp 1989, Lyon et al. 2010, Sullivan and Watzin
2009). Sullivan and Watzin (2009) interpreted the widespread presence of habitat
opportunists in floodplain habitats as evidence that these habitats are important
refuges under conditions stressful to fish, including high flows, drought, and
temperature extremes. Zeug and Winemiller (2008) found that fish recruitment in
floodplain lakes occurred primarily during low-flow periods, resulting in important
contributions to river-channel populations when flows increased. Floodplain lakes
with seasonal connections to rivers are spawning and nursery habitats for fishes
and contribute to main river populations (Sabo et al. 1991, Shoup and Wahl 2009,
Turner et al. 1994).
Our use of multiple gears and collection techniques likely biased our results.
Boat electrofishing is biased towards larger-bodied species, and seine collection
is biased towards smaller-bodied species. In smaller water bodies with low habitat
complexity where we effectively sampled all habitats, we were confident that our
collections were representative of the species present. In water bodies with complex
habitats and deeper water, our collections were likely not representative because
we could not effectively sample all habitats. We suggest that deleting rare species
prior to ordinations partially addressed these issues; given the habitat complexity
in floodplain lakes, we might also have eliminated some problematic sites from our
analyses or, for species that we consider to have been undersampled, we might have
interpreted the results differently. Our indirect and direct ordination approaches to
analyze these fish-assemblage data had different results. Although the results of
direct gradient ordination (CCA) showed significant patterns explained by sampled
environmental variables, indirect gradient ordination (RA) resulted in different patterns
for sites and species. Outcomes of both analyses suggested that surface area
was a significant predictor (or correlate) of fish-occurrence. The indirect gradient
analysis did not show significant gradients for elevation difference, sand substrate,
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2014 Vol. 21, No. 3
or maximum depth. This finding implies the presence of other unknown environmental
gradients we did not quantify.
Historically, these floodplain habitats have been degraded by levee and dam
construction, bank stabilization, and agricultural activities (including draining).
These modifications block natural flooding, eliminate floodplain connections, and
prevent the flood-pulse hydrologic regime that many organisms require (Sparks
1995). The natural hydrologic regime controls sediment accumulation and water
depth in floodplain lakes (Miranda 2011). Anthropogenic disturbances cause increased
sediment accumulation and subsequent loss of depth in floodplain lakes.
Agricultural activities in the watershed likely contribute the most sediments and
have the greatest impact on water depth (Dembkowski and Miranda 2012, Wren et
al. 2008). Miranda (2011) posited that decreased depth in floodplain lakes results in
the presence of fewer available habitats and decreased biodiversity. Management of
floodplain lakes requires increased awareness of the diverse habitats they support
and maintenance of natural flow regimes and connectivity (Sparks 1995). A natural
flow regime can only be restored in these floodplain ecosystems if anthropogenic
flow and connectivity modifications (i.e., dams and levees) are removed or mitigated
(Bayley 1991, Gergel et al. 2002). River-ecosystem improvement by flow
restoration can be accomplished through modification of dam operations (Bednarek
and Hart 2005) including flow experiments (Konrad et al. 2011), removal or repositioning
of levees (Opperman et al. 2009), and removal of modifications that alter
natural-flow regimes (Poff et al. 1997).
Acknowledgments
Funding for collections was from the Ohio River Basin Fish Habitat Partnership, Bloomington,
MN. We are grateful to R. Durtsche and D. Etchison for lodging durin g sampling.
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