Fish Assemblages of Floodplain Lakes in the Ohio River Basin - BioOne

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Northeastern Naturalist NORTHEASTERN NATURALIST M.Pyron, L. Etchison, and J. Backus

Vol. 21, No. 3 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, Aquatic Biology and Fisheries Center, Department of Biology, Ball State University, Muncie, IN 47306. *Corresponding author - [email protected]. 1

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, 420

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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 different 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. 421

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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. Common name

# of Code Scientific name Abundance sites

Bluegill Brook Silverside Gizzard Shad Western Mosquitofish Bluntnose Minnow Central Stoneroller Lepomis hybrid LargemouthBass Creek Chub Warmouth Southern Redbelly Dace Longear Sunfish Spotfin Shiner Green Sunfish White Sucker Eastern Blacknose Dace Sand sShiner Steelcolor Shiner White Crappie Black Bullhead Common Carp Northern Hog Sucker Rock Bass Blackspotted Topminnow Blackstripe Topminnow Pumpkinseed Mottled Sculpin Shortnose Gar Yellow Bullhead Spotted Sucker Black Crappie Goldfish Golden Shiner Redfin Shiner Smallmouth Bass Channel Catfish Silverjaw Minnow Striped Shiner Bowfin Bullhead Minnow Greenside Darter Mississippi silvery Minnow Redfin Pickerel Smallmouth Buffalo Black Buffalo Grass Carp Johnny Darter Mud Darter

BLGI BRSI GISH MOSQ BLMI CEST LESP LABA CRCH WAMO SRBD LESF SPSH GRSF WHSU BLDA SASH STSH WHCR BLBU COCA NOHS RB BLTM BSTM PUSF MOSC SNGA YEBH SPSU BLCR GOFI GOSH RFSH SMBA CHCA SJMI STRS BOFI BHMI GRDA MSMI RDPI SMBU BLBU

Lepomis macrochirus Rafinesque 689 29 Labidesthes sicculus (Cope) 210 7 Dorosoma cepedianum (Lesueur) 194 10 Gambusia affinis (Baird & Girard) 171 14 Pimephales notatus (Rafinesque) 125 11 Campostoma anomalum (Rafinesque) 91 5 Lepomis spp. 65 7 Micropterus salmoides (Lacepéde) 65 15 Semotilus atromaculatus (Mitchill) 63 8 Lepomis gulosus (Cuvier) 52 12 Phoxinus erythrogaster (Rafinesque) 50 2 Lepomis megalotis (Rafinesque) 49 10 Cyprinella spiloptera (Cope) 49 7 Lepomis cyanellus Rafinesque 48 14 Catostomus commersonii (Lacepéde) 48 4 Rhinichthys atratulus (Hermann) 45 3 Notropis stramineus (Cope) 33 3 Cyprinella whipplei Girard 29 5 Pomoxis annularis Rafinesque 27 9 Ameiurus melas (Rafinesque) 25 3 Cyprinus carpio L. 22 5 Hypentelium nigricans (Lesueur) 22 3 Ambloplites rupestris(Rafinesque) 21 4 Fundulus olivaceus (Storer) 19 3 Fundulus notatus (Rafinesque) 17 5 Lepomis gibbosus (L.) 17 5 Cottus bairdii Girard 14 3 Lepisosteus platostomus Rafinesque 13 4 Ameiurus natalis (Lesueur) 12 6 Minytrema melanops (Rafinesque) 11 6 Pomoxis nigromaculatus (Lesueur) 9 5 Carassius auratus (L.) 9 5 Notemigonus crysoleucas (Mitchill) 7 3 Lythrurus umbratilis (Girard) 7 4 Micropterus dolomieu Lacepéde 7 5 Ictalurus punctatus (Rafinesque) 6 3 Notropis buccata (Cope) 6 4 Luxilus chrysocephalus Rafinesque 6 4 Amia calva Linnaeus 5 4 Pimephales vigilax (Baird & Girard) 4 2 Etheostoma blennioides Rafinesque 4 4 Hybognathus nuchalis Agassiz 4 2 Esox americanus Gmelin 4 3 Ictiobus bubalus (Rafinesque) 4 4 Ictiobus niger (Rafinesque) 3 2 Ctenopharyngodon idella (Valenciennes) 3 3 Etheostoma nigrum Rafinesque 3 2 Etheostoma asprigene (Forbes) 3 2 422


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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. Common name

# of Code Scientific name Abundance sites

Orangespotted Sunfish Redear Sunfish Silver Carp Bigeye Chub Blackside Darter Freshwater Drum Logperch Mimic Shiner Pirate Perch Silver Shiner Bigeye Shiner Bigmouth Buffalo Brindled Madtom Brown Bullhead Flier Longnose Gar Quillback Rainbow Darter River Carpsucker Shortnead Redhorse Slough Darter Tadpole Madtom

Lepomis humilis (Girard) 3 4 Lepomis microlophus (Günther) 3 3 Hypophthalmichthys molatrix (Valenciennes) 3 4 Hybopsis amblops (Rafinesque) 2 2 Percina maculate (Girard) 2 2 Aplodinotus grunniens Rafinesque 2 3 Percina caprodes (Rafinesque) 2 2 Notropis volucellus (Cope) 2 2 Aphredoderus sayanus (Gilliams) 2 3 Notropis photogenis (Cope) 2 2 Notropis boops Gilbert 1 2 Ictiobus cyprinellus (Valenciennes) 1 2 Noturus miurus Jordan 1 2 Ameiurus nebulosus (Lesueur) 1 2 Centrarchus macropterus (Lacepéde) 1 2 Lepisosteus osseus (L.) 1 2 Carpiodes cyprinus (Lesueur) 1 2 Etheostoma caeruleum Storer 1 2 Carpiodes carpio (Rafinesque) 1 2 Moxostoma macrolepidotum (Lesueur) 1 2 Etheostoma gracile (Girard) 1 2 Noturus gyrinus (Mitchill) 1 2 423

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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 Mean elevation (m) Distance to river (km) Surface area (m2) Sand substrate Dissolved oxygen (mg/L) Total variation

Percent variation

P

11.3 0.034 10.2 0.038 10.3 0.002 7.0 0.010 5.9 0.044 44.7 424

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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. 425

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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 426

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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