Fish Assemblage Response to Altered Dendritic Connectivity in the Red River Basin, Central Louisiana.
Freshwater lotic systems comprise some of the most diverse and productive habitats in the world (Taylor et al., 2007; Bogan, 2008; Carrizo et al., 2013), but are also among the most threatened by anthropogenic disturbance (Millennium Ecosystem Assessment, 2005; Dudgeon et al., 2006; Jelks et al., 2008; Baillie, 2010; Carrizo et al., 2013). Repeatedly recognized as hotspots for aquatic diversity, streams in the southeastern United States are of particular concern regarding anthropogenic alteration (Williams et al., 1993; Abell et al., 2000; Smith et al., 2002; Taylor et al., 2007; Jelks et al., 2008). Stream systems in Louisiana have a long history of heavy exploitation and alteration (Felley, 1992; Lydeard and Mayden, 1995; Warren et al., 2000), but consequences of these disturbances on the ecology of resident fish assemblages remain poorly understood. As effective management and conservation decisions rely on understanding factors responsible for species' distribution and abundance patterns, filling this data gap is a priority for state regulatory agencies (Holcomb et al., 2015), especially for management of threatened or endangered species.
Fish assemblage distribution, composition, and structure have been correlated with physicochemical gradients at both local and watershed scales (Wang et al., 2003; Diana et al., 2006; Helms et al., 2009: Albanese et al., 2014). In particular, forest (Anderson et al., 2012), impervious/urban (Meador et al, 2005; Roy et al., 2005; Wenger et al., 2008), and agricultural (Harding et al, 1998; Walser and Bart, 1999; Vondracek et al., 2005; Infante and Allan, 2010) land covers have been shown to strongly influence fish assemblage composition in adjacent streams (Weijters et al., 2009). However, the predictive power of these variables regarding fish distribution and abundance is still widely debated and may be influenced by additional factors, such as the level of disturbance (Diana et al., 2006; Wang et al., 2006) and dominance of a specific land-cover type (Heitke et al, 2006).
Shifts in riverine fish assemblage composition and abundance within mainstem impoundments have been well documented, often resulting in replacement of lotic specialists and native species with lentic, introduced, and generalist species, particularly piscivorous sportfishes (Schlosser et al., 2000; Gido et al., 2002; Freeman and Marcinek, 2006; Freedman et al., 2014). Dams block upstream movement, isolating migratory fishes from historic breeding areas and reducing gene flow between formerly connected populations (Neraas and Spruell, 2001; Limburg and Waldman, 2009). Impoundment can also result in upstream declines in native stream-specialist fishes (Franssen and Tobler, 2013), and a range of downstream effects, including alteration of the sediment regime, flow volume and seasonality, and channel platform (Kondolf, 1997; Vorosmarty et al., 2003; Petts and Gurnell, 2005; Graf, 2006; Poff et al., 2007), degradation offish spawning habitat (Peoples et al., 2014), and reductions in riparian plant recruitment (Kondolf, 1997; Poff et al., 2007).
Increasingly, dendritic connectivity has been recognized as another important factor shaping fish distribution and abundance (Pringle et al., 2000; Swan and Brown, 2011). The effects of impoundment on tributary stream systems have been less thoroughly described (Pringle, 1997), but modified stream connectivity results in truncated streams that flow into lentic habitat rather than the previously unimpounded river. This can create a degree of isolation of tributary streams that can influence resident fish assemblage structure due to restricted movements among adjacent tributaries (Fraser et al., 1995; Schlosser et al., 2000). Reservoir-induced fragmentation of stream networks reduces gene flow between populations of some stream fishes, with potential negative impacts on persistence (Franssen, 2012; Fluker et al., 2014). Influx of new individuals to repopulate a stream after a disturbance can also be limited by stream disconnection. Importantly, reductions in gene flow and recolonization potential can both serve to drive documented changes in native lotic fish assemblages in impounded reaches (Winston et al., 1991; Reyes-Gavilan et al., 1996; Falke and Gido, 2006; Guenther and Spacie, 2006; Matthews and Marsh-Matthews, 2007). Only species that can occupy or traverse lentic habitat conditions can easily repopulate these streams. As a consequence numerous reservoir tributary streams have been reported to exhibit greater diversity and abundance of lentic and generalist species compared to similar stream tributaries in unmodified watersheds (Herbert and Gelwick, 2003; Falke and Gido, 2006; Guenther and Spacie, 2006).
The Red River basin contains the greatest number of reservoirs in Louisiana, with 77 impoundments constructed from the 1950s to 1975 that altered the connectivity of small wadeable tributaries within the watershed. Consequently, the basin is an excellent system for exploring the relative importance of in-stream, watershed, and connectivity factors in structuring fish assemblages in connected and tnincated tributary systems. We designed this study to assess the role of dendritic connectivity in structuring fish assemblage composition in Red River tributary streams in central Louisiana. Based on previous studies in other river systems, we hypothesized that relative to river tributaries, reservoir tributaries would exhibit lower richness and abundance of stream-specialist fishes and a greater richness and abundance of generalist/reservoir species.
Between May and August of both 2014 and 2015, 21 wadeable first and second order streams within the central portion of the Red River basin were sampled (Fig. 1; Table 1). Of these streams 10 were considered 'river' tributaries, i.e., they fed into free flowing dendritic systems, or in one case, was 20 km upstream from a reservoir and exhibited habitat characteristics similar to other river tributaries. The 11 remaining 'lake' tributaries flowed directly into impoundments, representing streams in a truncated watershed (all sites < 5 km from reservoir). Streams were chosen based on access points, com parable size, and similar surrounding land use.
For each stream sampling event in each year, a 130 to 150 m sampling reach was established beginning at the tree line running parallel to the road upstream of the bridge crossing access point, usually 25-30m. Upstream and downstream block nets were set to isolate the reach for quantitative two-pass removal electrofishing with backpack DC electrofishing units (Halltech HT-2000) accompanied by a single dip-netter. Time of each pass was recorded to allow calculation of catch per unit effort (CPUE). Prior to electrofishing, open water habitats within each reach were seined (3 m seine with 6.35 mm bar mesh, two to three hauls) for cyprinids and fundulids that were less vulnerable to electrofishing. All sampled fish were removed from the stream and kept in an aerated bucket until the end of the electrofishing pass to prevent further stress. Each fish was then identified to species and returned to the water, with the exception of voucher specimens or unidentifiable individuals. These individuals were placed in an ice bath until moribund and then transferred to 10% formalin to be returned to the lab for identification to the lowest practical taxon and preservation. All fish handling followed approved Louisiana State University Institutional Animal Care and Use Committee (IACUC) A2011-16 protocol.
On each sampling date, temperature (C), specific conductance (mS/cm), dissolved oxygen (DO; mg/L), and turbidity (NTU) were recorded at each site with a YSI 650 multiprobe water quality monitor. We then recorded wetted width, stream bank stability (Platts et al., 1983), riparian cover, % canopy cover (forest densitometer, mid-transect), and pebble counts (pebbles intersecting transect) along 10 transects spaced 15 m apart through the sample reach. Depth (m; graduated wading rod), flow velocity (m/s; Sontek Flowtracker ADV Doppler flow meter), and abundance of woody debris (visual estimate of coverage within aim circle) were also recorded at 25%, 50%, and 75% of stream width (Kaufmann, 1999). Percent land cover of open water (lotic and lentic habitats), developed infrastructure (high, medium, low, bare), forest (mixed, evergreen, deciduous), shrub, herbaceous, agriculture (crop, pasture), and wetlands (woody, herbaceous) was determined with the 2001 United States Geological Survey National Land Cover Dataset for Louisiana and verified with onsite observations. Upstream watershed catchment area for each stream site was calculated with a digital elevation model and the National Hydrography Dataset (NHD; Homer et al, 2007) within GIS (ArcMap 10.2)
All fishes were categorized as either habitat generalists or specialists based on Ross (2001) and Hendrickson and Cohen (2015). Due to differences in gear selectivity, data from seining and electrofishing collections were analyzed separately. Relative abundance was calculated for each taxon, and relative abundance and richness were calculated for specialist or generalist groups. We used partial canonical correspondence analysis, detrended correspondence analysis (DCA), and nonmetric multi-dimensional scaling to examine associations between fish species, habitat variables, and site types. Axis length and STRESS2 were examined to decide which method was most appropriate for interpretation following selection criteria of ter Braak and Verdonschot (1995) and Hirst and Jackson (2007). These analyses led to further investigation of relationships between fish species distributions and environmental variables with a step-forward selection canonical correspondence analysis (CCA). Habitat variables included in the final model were then used as partial variables in an additional CCA that evaluated fish assemblages as explained by the two site types. All ordinations were performed in Program R (vers. 3.3.3, package vegan, R Core Team, 2017; Oksanen et al., 2017).
We also used separate generalized linear mixed models to examine the relationship between site type and several different response variables: overall species richness, species richness of habitat generalist and specialists, and relative abundance of specialists (Table 2). Habitat variables retained by the earlier step-forward constrained ordination were initially included, but they did not improve model fit based on general [chi.sup.2]/degrees of freedom and proximity of the y-intercept to 0. Therefore, conclusions are based on a simple model structure with site type as the only explanatory variable. Generalized linear models were implemented with log link functions and Poisson distributions for richness analyses and logit link functions and binomial distributions for relative abundance analysis.
Further analyses were performed for 14 species that were only found in one connectivity type, had much greater abundance in a specific connectivity type, or showed some resolution in the ordination analyses, and occurred in at least 12 sites. Fish abundance relationships with site type were modeled with generalized linear mixed models based on the log link function, with month and year included as random variables, and either a negative binomial or Poisson distribution for the response variables. We used Zippin (1958) estimates of abundance (fish/1000 s electrofishing) for each species from the two-pass removal data, as it is more difficult for models to detect differences between smaller proportion-based values inherent in relative abundance data (herein, relative abundance was estimated by species specific Zippin estimate/total sample Zippin estimate; Zuur et al., 2009; Agresti, 2015). All generalized linear mixed model analyses were performed with SAS (vers. 9.4, SAS Institute, Inc., Cary, NC).
Stream sites were all located in relatively small shallow first or second order streams at base flow conditions [mean width 3.5 [+ or -] 0.2 m (se), mean depth 29 [+ or -] 2 cm] with very low flow velocities (mean 0.057 [+ or -] 0.009 m/s) and high canopy cover (mean coverage 90 [+ or -] 1%). Streams contained a variety of substrate types but most were dominated by sand and silt/clay (mean sand coverage 40 [+ or -] 4% se, mean silt/clay coverage 23 [+ or -] 4% se) with abundant woody debris (mean coverage 15 [+ or -] 2% se). Other habitat variables were similar between reservoir tributaries and river tributaries, although the latter were typically less turbid (Table 3). Watershed area was variable across streams (range 0.58-92.6 [km.sup.2]), but all watersheds were rural, primarily forested, with less than 2% developed area, less than 2% row crop agriculture, and with the exception of two sites, less than 2% pasture.
Electrofishing and seining yielded 42 species of fish (Table 4; individuals not identified to species are not included), ranging from 1-24 species and 25 to 356 individuals at a given site. Electrofishing yielded greater abundance and richness of fishes, but pelagic fishes such as Ribbon Shiner (Lythrurus fumeus) were much more abundant in the seine hauls. Overall richness was dominated by the Centrarchidae (12 species), Cyprinidae (9), and Percidae (5). There were 33 species common to both stream types, with Flier (Centrarchus macropterus), Chestnut Lamprey (Ichthyomyzon castaneus), and Blackspot Shiner (Notropis atrocaudalis) found only in river tributaries, and Harlequin Darter (Etheostoma histrio), Golden Topminnow (Fundulus chrysotus), Brook Silverside (Labidesthes sicculus), Spotted Gar (Lepisosteus oculatus), Spotted Sucker (Minytrema melanops), and White Crappie (Pomoxis annularis) captured only in reservoir tributaries. We classified 25 species as habitat generalists and 17 species as habitat specialists (Table 4), with most fishes characterized as benthic or water column invertivores.
We identified 16 species that appeared to exhibit distributional relationships with site type (Table 5). Of these 14 species yielded meaningful models (Western Mosquitofish and Redear sSunfish did not meet model convergence criteria). Creek Chubsucker (Erimyzon oblongus), Grass Pickerel (Esox americanus), Redspot Darter (Etheostoma artesiae), Bluntnose Darter (E. chlorosoma), Slough Darter (E. graale), Green Sunfish (Lepomis cyanellus), and Redfin Shiner (Lythrurus umbratilis) all exhibited significantly greater abundance (all P < 0.02) in river tributaries than reservoir tributaries.
Although DCA of electrofishing and seining data provided little resolution of fish abundance patterns, forward stepwise CCA identified several habitat variables that significantly influenced fish assemblage composition. For the electrofishing data, sampling year, root wads, depth, flow, and tributary type were identified as important structuring variables, whereas only dissolved oxygen influenced the abundances of fishes collected by seine (Table 6). Subsequent partial CCAs also detected a statistically significant assemblage difference between river and reservoir tributary streams in the electrofishing data ([chi square] = 0.10, F = 1.83, P < 0.01; Fig. 2), although no differences were detected in the seine data.
Analyses of the electrofishing data failed to detect any statistically significant differences in total species richness, generalist richness, and specialist richness between stream types. However, total richness ([F.sub.1,31] = 17.71, P < 0.01), generalist richness ([F.sub.1,37] = 12.44, P < 0.01), and specialist richness ([F.sub.1,31] = 12.44, P < 0.01) of seined fishes were all higher in river tributaries (total 7.85 [+ or -] 0.79 se, generalist 3.90 [+ or -] 0.62 se, specialist 3.85 [+ or -] 0.42 se) than in reservoir tributaries (total 4.64 [+ or -] 0.48 se, generalist 1.77 [+ or -] 0.25 se, specialist 2.73 [+ or -] 0.37 se).
In this study we examined the role of altered dendritic connectivity on fish assemblage dynamics in headwater tributaries of the Red River Basin, Louisiana. We hypothesized stream type would be an important structuring variable for fish species abundance patterns and habitat generalists would be more abundant and diverse than habitat specialists in reservoir tributaries, similar to other disturbed systems (Herbert and Gelwick, 2003; Falke and Gido, 2006; Guenther and Spacie, 2006). Supporting our first hypothesis, we did observe three species that were exclusive to river tributaries and six exclusive to reservoir tributaries, greater abundance of seven species in river tributaries, and greater richness of pelagic (seining data) cyprinid and cyprinodontid generalists and specialists in river tributaries. Further support may be found in a review of historical fish collections from the time period prior to reservoir construction that indicated that for species with available data, several species, including Flier and Chestnut Lamprey, were reported from streams within impounded watersheds prior to impoundment (www.FishNet2.net). Several habitat variables such as canopy cover, flow, and depth were significantly associated with fish assemblage composition at the study sites, and have been found to be important predictors of fish distribution and abundance in other streams within the region (Lienesch et al., 2000; Herbert and Gelwick, 2003). However, all of the sample sites were characteristic of coastal plain warmwater systems (Cross et al., 1986; Felley, 1992; Ross, 2001), and habitat characteristics did not differ consistently enough between river and reservoir tributaries to result in obvious type-specific fish assemblages. This similarity in in-stream habitat suggested the presence of the reservoir itself was the key difference influencing the relative abundance of fishes between stream types.
Evidence supporting our second hypothesis was more equivocal, in that: (1) no significant differences were found in the richness of electrofished specialists and generalists between the two stream types, (2) two of three exclusively river tributary species were specialists, (3) four of six exclusively reservoir tributary species were generalists, and (4) four of the seven species that were significantly more abundant in river tributaries were specialists. Williams et al. (2005) investigated relationships between fish assemblage structure and habitat variables such as depth, flow velocity, substrate composition, and disturbance (military training) in the Red, Sabine, and Calcasieu Rivers. The amount of fish assemblage variation attributable to habitat was similar to this study (25%), but was not statistically significant. The authors attributed these results to similarity in habitat among all of the coastal plain streams they studied, as well as a lack of strong habitat associations for many fish species (Williams et al., 2005). Interestingly, more than half of the fish species present within streams of the Red River basin are shared between many other southern drainages (Felley, 1992; Kaller et al., 2013), suggesting assemblages within this basin are dominated by cosmopolitan generalist species that are able to successfully exploit a wide range of habitat conditions.
Other studies of impoundment effects on headwater stream fishes in noncoastal plain regions of the southcentral U.S. have consistently reported declines in abundances of stream specialists and increases abundances of generalists (Winston et al., 1991; Herbert and Gelwick, 2003; Falke and Gido, 2006; Guenther and Spacie, 2006; Matthews and MarshMatthews, 2007). In these studies, taxa such as Largemouth Bass (Micropterus salmoides), Gizzard Shad (Dorosoma cepedianum), and Western Mosquitofish (Gambusia affinis) were generalist reservoir native and non-native fishes that distinguished fish assemblages in reservoir tributaries and unimpounded streams. Our study streams contained these species, as well as other species found in the more inland systems that were considered habitat generalists. As sampling methodology and number of sample sites were comparable between all studies, our results suggest a reduction of fish species replacement in truncated 1st and 2nd order coastal plain streams relative to larger 3rd order upland systems (Winston et al., 1991; Falke and Gido, 2006; Guenther and Spacie, 2006). Suggested mechanisms behind species assemblage shifts include isolation of truncated streams caused by the reservoir, or the proximity of novel fish species living in the reservoir (Fraser et al., 1995; Schlosser et al., 2000; Gido et al., 2002; Freeman and Marcinek, 2006). Our data provided limited evidence of the second hypothesis, with only Spotted Gar and White Crappie suggestive of upstream expansion of reservoir fishes.
Instead, our evidence suggests observed differences in fish assemblage composition among stream types were related to stream truncation. Although it is unclear what mechanisms are driving reduced abundance of the three darters, Green Sunfish, and Redfin Shiner in reservoir tributaries, it is possible these species are keying in on fine-scale differences in substrate composition, flow velocity, pool morphology, woody debris characteristics, etc., that were not measured in our habitat assessment. Alternatively, they may be rarer in reservoir tributaries because of reduced colonization from stream fragmentation or increased interactions with reservoir piscivores or generalist competitors that are moving into tributaries from the reservoir (Hebert and Gelwick, 2003; Matthews and Marsh-Matthews, 2007). Creek Chubsuckers were over three times more abundant in our untruncated study streams, a pattern that was reflected in populations in the San Jacinto River in Texas (Guenther and Spacie, 2006). Interestingly, increased abundance of Creek Chubsuckers in a northwestern Mississippi stream in autumn (Shields et al, 1994) may have reflected upstream movements to the study site, and it may be that elimination of downstream connectivity inhibits colonization and movements of this small catostomid. Similarly, Grass Pickerel have been previously found in greater abundance and size in unfragmented tributaries (Herbert and Gelwick, 2003; Guenther and Spacie, 2006), which may also reflect the proclivity of this species to move between larger downstream rivers and off-channel headwater habitats. Impacts of reduced connectivity on Grass Pickerel populations could be of particular conservation concern in Louisiana, as this esocid has been identified as a glochidial host for the endangered Louisiana Pearlshell Mussel (Margaritfera hemlbiv, US Fish and Wildlife Service, 2017), which is found only is streams within two parishes in the Red River basin (Holcomb et al, 2015).
Current fish distributions within the Gulf of Mexico coastal plain have been determined by the combined legacies of geologic change (Robinson, 1986; Felley, 1992; Isphording and Fitzpatrick, 1992; Adams et al, 2004; Brown and Matthews, 2006), climatic events (Perret et al., 2010, van Vrancken and O'Connell, 2010), and anthropogenic disturbance (Harding et al., 1998; Lopez, 2009; Piller and Geheber, 2015). These factors have collectively acted as ecological filters of local fish assemblage composition given the regional taxonomic pool (Schlosser, 1987; Resh et al., 1988; Winemiller and Rose, 1992; Poff et al., 1997; Kaller et al., 2013; McManamay and Frimpong, 2015). Fish assemblages subject to colonization/ recolonization barriers have been shown to be resilient to upland and riparian fire (Glitzenstein et al., 1995; Dunham et al., 2007), seasonal and multi-year dry conditions with low water quality and depressed dissolved oxygen (Felley, 1992; Justus et al., 2012), and changing in-stream habitat conditions (Geheber and Piller, 2012). In addition headwater steams generally experience frequent disturbance, potentially exacerbating selective pressures (Horwitz, 1978; Schlosser, 1987; Poff and Allan, 1995; Griffiths, 2010). In the coastal plain, low-order streams are home to a large number of cosmopolitan, environmentally tolerant fishes, with overall assemblage composition dominated by widely distributed habitat generalists that can occupy streams, swamps, ponds, and reservoirs (Felley, 1992; Ross, 2001; Warren et al., 2002). In this study less than half of the species captured qualified as stream habitat specialists, and for many, their habitat requirements were not reportedly stringent (Ross, 2001). We believe it likely fishes inhabiting Red River headwater streams have faced selection processes that have favored habitat generalists tolerant of periodic poor water quality. Evidence of these legacies is clear in coastal plain fishes' rapid recolonization abilities (Sheldon and Meffe, 1995) and their resiliency to land cover changes and timber harvest (Williams et al., 2002; Williams et al., 2007; Fitzgerald, 2012; but see Daniel et al., 2014). As a consequence altered dendritic connectivity may not be an insuperable disturbance for fishes inhabiting Red River basin coastal plain headwater streams, a hypothesis that may apply to many coastal river systems in the southeastern U.S. In particular the weak link between fish assemblage composition and altered connectivity in these streams may be more related to the nature of the disturbance than the fish assemblages facing it, i.e., for many fishes adapted to low flow, high temperature, low dissolved oxygen streams, construction of a reservoir does not qualify as a significant disturbance.
However, abundances patterns of seven Red River basin fishes did appear to be related to stream fragmentation and reduced connectivity, with all seven species displaying reduced abundance in streams truncated by reservoirs. Although the mechanisms driving this pattern for the three darters, green sunfish, and redfin shiner are unclear, it is possible these species are keying in on fine-scale differences in microhabitat characteristics between stream types such as substrate composition, flow velocity, pool morphology, or woody debris characteristics that were not measured in our habitat assessment. Alternatively, they may be rarer in reservoir tributaries because of reduced colonization from stream fragmentation or increased interactions with reservoir piscivores or generalist competitors that are moving into tributaries from the reservoir (Hebert and Gelwick, 2003; Matthews and MarshMatthews, 2007). Creek Chubsuckers were over three times more abundant in our untruncated study streams, a pattern that was reflected in populations in the San Jacinto River in Texas (Guenther and Spacie, 2006). Similarly, grass pickerel have been previously found in greater abundance and size in unfragmented tributaries (Herbert and Gelwick, 2003; Guenther and Spacie, 2006), which may also reflect the proclivity of this species to move between larger downstream rivers and off-channel headwater habitats. Impacts of reduced connectivity on grass pickerel populations could be of particular conservation concern in Louisiana, as this esocid has been identified as a glochidial host for the endangered Louisiana pearlshell mussel.
Our study in the southeastern U.S. coastal plain expands results of earlier research in inland streams regarding effects of impoundment on tributary stream fish assemblages. Although several fishes exhibited greater abundance in river tributaries relative to reservoir tributaries, overall assemblage-level effects of stream truncation were small. Multi-region analyses of disturbances, such as pesticide use, land conversion to agriculture, and urbanization have indicated that fish assemblage responses are mediated by local rates of physicochemical change, land use history, and species' inherent vulnerability and resilience (Jordan et al, 1997; Poff et al., 2006; Sprague and Nowell, 2008). Disturbances that elicit significant responses in one system may induce milder, more nuanced impacts in other habitats. Because of their adaptation to physicochemically dynamic stream systems, southeastern coastal plain fishes in particular may be less vulnerable to anthropogenic disturbance than fishes in other ecoregions (Williams et al., 2002, Morgan and Cushman, 2005; Utz et al., 2010), and reduced dendritic connectivity may not result in substantial changes in assemblage composition in truncated streams. However, it should be noted that impoundment effects on abundances of individual species could have important consequences for the resident stream community. In the Red River basin, Grass Pickerel were substantially more abundant in unfragmented streams, which could have significant consequences for its glochidial parasite, the Louisiana Pearlshell Mussel, in streams truncated by future reservoir development.
Acknowledgments.--We thank Corrine Bird, Joseph Danigole, Kamela Gallardo, A. Raynie Harlan, Brad Hester, Tyler Loeb, Kaitlyn Matherne, Samantha Lott. Jesse Sabo, Kayla Smith, Jacqueline Salter, Renee Saucier, Tiffany Pasco, and Bradley Wood for assistance in sampling. We thank D. /Mien Rutherford for a review of an earlier version of ibis manuscript. This research was supported in pari by the State Wildlife Grant program administered by the Louisiana Department of Wildlife and Fisheries and U.S. Fish and Wildlife Service. This work was partially supported by the Nalional Institute of Food and Agriculture, U.S. Department of Agriculture, under the Mclntire-Stennis Cooperative Forestry Program as project number LAB-94335. This manuscript was approved for publication by the Director of the Louisiana Agricultural Experiment Station as manuscript 2018-241-33314.
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Submitted 11 June 2018
Accepted 21 September 2018
CATHERINE N. REUTER, MICHAEL D. KALLER (1), COLLEEN E. WALSH and WILLIAM E. KELSO
School of Renewable Natural Resources, Louisiana State University Agricultural Center, 227 RNR Building, Baton Rouge 70803
(1) Corresponding author: e-mail: email@example.com
Caption: Fig. 1.--Location of the 21 river tributary (black dots) and reservoir tributary (gray dots) streams in the Red River basin sampled in 2014 and 2015
Caption: Fig. 2.--Partial canonical correspondence analysis of electrofishing fish collections. Open dots represent species and filled dots represent sampling sites. The horizontal arrow represents the direction and magnitude of the river tributary variable. The following species located near the origin (<|0.5|) are not shown: Elassoma zonatum, Erimyzon oblongus, Etheostoma artesia, E. chtorosoma, E. gracile, E. proeliare, Fundulus olivaceus, Lepomis cyanellus, L. gulosus, L. macrochirus, L. megalotis, Lepomis spp., Lythrurus fumeus, L. umbratilis, Micropterus salmoides, Nolurus phaeus, and Semotilus atromaculatus
Table 1.--Locations of river and reservoir tributary sample sites in latitude and longitude (WGS 1984) River tributary Reservoir tributary 31.39 -92.79 31.39 -92.79 31.57 -93.27 31.40 -92.78 31.55 -93.26 31.96 -92.92 31.44 -92.78 31.63 -92.63 31.78 -92.70 31.97 -93.00 31.85 -93.42 31.83 -92.86 31.64 -93.17 31.65 -92.75 31.89 -93.46 31.96 -92.84 31.74 -93.38 31.74 -93.17 31.88 -93.44 31.74 -93.17 31.56 -92.62 Table 2.--Model structures for species assemblage analyses, which were run separately for electrofishing and seine datasets Response variable Fixed Response variable distribution variable Total species richness Poisson site type Habitat generalist richness Poisson site type Habitat specialist richness Poisson site type Stream specialist relative abundance binomial site type Random Link Response variable variables function Total species richness month, year log Habitat generalist richness month, year log Habitat specialist richness month, year log Stream specialist relative abundance month, year logit Table 3.--Mean ([+ or -]se) physicochemical characteristics at stream sampling sites, averaged between years Reservoir tributary Dissolved oxygen (DO; mg/L) 6.17 [+ or -] 0.56 (1.70-9.88) Temperature (C) 22. 24 [+ or -] 0.041 (19.22-25.32) Turbidity (NTU) 36.1 [+ or -] 3.3 (13.3-68.0) Boulders (% coverage) 0.26 [+ or -] 0.22 (0-4.76) Fine gravel (% coverage) 1.31 [+ or -] 0.61 (0-10.74) Leaf litter (% coverage) 9.24 [+ or -] 1.71 (0-25.00) Root (% coverage) 0.81 [+ or -] 0.54 (0-10.61) Woody debris (% coverage) 8.44 [+ or -] 1.06 (0.40-18.93) River tributary Dissolved oxygen (DO; mg/L) 5.32 [+ or -] 0.68 (0.30-8.84) Temperature (C) 22.94 [+ or -] 0.90 (18.79-26.08) Turbidity (NTU) 23.2 [+ or -] 3.0 (6.0-68.6) Boulders (% coverage) 0.14 [+ or -] 0.14 (0-2.86) Fine gravel (% coverage) 10.05 [+ or -] 4.18 (0-76.19) Leaf litter (% coverage) 4.72 [+ or -]1.21 (0-16.19) Root (% coverage) 2.15 [+ or -] 1.48 (0-32.07) Woody debris (% coverage) 7.02 [+ or -] 1.22 (0.62-20.36) Table 4.--Frequency of occurrence (FO), total numbers captured by seining and electrofishing (Sum), and habitat affinities especialist (S) or generalist (G)] of fishes collected in reservoir and river tributaries in the Red River Basin in 2014 and 2015 River River Common name Scientific name FO sum Reservoir tributaries only Harlequin Darter Etheostoma histrio Golden Topminnow Fundulus chrysotus Brook Silverside Labidesthes sicculus Spotted Gar Lepisosteus oculatus Spotted Sucker Minytrema melanops While Crappie Pomoxis annularis River tributaries only Flier Centrarchus macropterus 5 51 Chestnut Lamprey Ichthyomyzon castaneus 1 4 Blackspot Shiner Notropis atrocaudalis 1 2 Both reservoir and river tributaries Black Bullhead Amriurus metas 5 26 Yellow Bullhead Ameiurus nalalis 5 24 Pirate Perch Aphredoderus sayanus 10 343 Banded Pygmy Sunfish Elassoma zonatum 3 19 Creek Chubsucker F.rimyzon oblongas 6 100 Lake Chubsucker Erimyzon su celta 1 1 Grass Pickerel Esox americanus 7 110 Redspot Darter Etheostoma artesiae 6 37 Bluntnose Darter Etheostoma cldorosoma 7 66 Slough Darter Etheostoma gracile 9 188 Cypress Darter Etheostoma proeliare 3 13 Blackstripe Topminnow Fundulus notatus 3 7 Blackspotted Topminnow Fundulus olivaceus 9 268 Western Mosquitofish Gambusia ajfinis 9 673 Green Sunfish Lepomis cyanellus 8 29 Figure 4 cont. Warmouth Lepomis gulosus 6 28 Orangespotted Sunfish Lepomis humilis 2 2 Bluegill Lepomis macrochirus 6 109 Dollar Sunfish Lepomis marginatus 4 36 Longear Sunfish Lepomis megalotis 7 58 Redear Sunfish Lepomis microtophus 5 11 Redspotted Sunfish Lepomis miniatus 6 52 Bantam Sunfish Lepomis symmetricus 4 5 Striped Shiner Luxilus chrysocephalus 4 79 Ribbon Shiner Lythrurus fumeus 5 84 Redfin Shiner Lythrurus umbratilis 7 391 Largemouth Bass Micropterus salmoides 4 10 Blacktail Redhorse Moxostoma poecilurum 1 1 Golden Shiner Notemigonus nysoleu cas 4 57 Brown Madtom Noturus phaeus 1 4 Pugnose Minnow Opsopoeodus emiliae 1 2 Bullhead Minnow Pimephales vigilax 1 9 Creek Chub Semotilus atromaculatus 6 132 Reservoir Reservoir Habitat Common name FO sum affinity Reservoir tributaries only Harlequin Darter 1 4 S Golden Topminnow 1 2 G Brook Silverside 2 2 G Spotted Gar 1 50 G Spotted Sucker 1 1 S While Crappie 1 7 G River tributaries only Flier G Chestnut Lamprey S Blackspot Shiner S Both reservoir and river tributaries Black Bullhead 3 8 G Yellow Bullhead 8 65 G Pirate Perch 11 277 G Banded Pygmy Sunfish 5 19 G Creek Chubsucker 10 52 S Lake Chubsucker 1 1 G Grass Pickerel 8 75 G Redspot Darter 9 50 S Bluntnose Darter 5 39 S Slough Darter 8 77 G Cypress Darter 3 16 G Blackstripe Topminnow 5 172 S Blackspotted Topminnow 10 165 s Western Mosquitofish 10 295 G Green Sunfish 8 25 G Figure 4 cont. Warmouth 7 34 G Orangespotted Sunfish 4 117 G Bluegill 7 20 G Dollar Sunfish 6 89 G Longear Sunfish 6 10 G Redear Sunfish 8 69 G Redspotted Sunfish 6 8 G Bantam Sunfish 4 49 G Striped Shiner 4 81 S Ribbon Shiner 6 342 S Redfin Shiner 8 69 S Largemouth Bass 3 5 G Blacktail Redhorse 1 2 S Golden Shiner 1 10 G Brown Madtom 4 82 S Pugnose Minnow 1 1 S Bullhead Minnow 1 1 S Creek Chub 4 30 S Table 5.--Mean Zippin abundance estimates (se) for fishes collected by electrofishing from at least 12 streams (inestimable for species with low frequency of occurrence) estimated from the observed data in the Red River Basin in 2014 and 2015. Generalized linear mixed models tested for differences in species abundance between tributary and nontributary streams. Models for Western Mosquitofish and Redear Sunfish did not meet model convergence criteria River Reservoir Species tributary tributary [F.sub.1.21] Yellow Bullhead 11 (0.3) 34 (0.8) 2.35 Pirate Perch 358 (8.8) 151 (1.8) 1.07 Creek Chubsucker 68.4 (2.8) 21.7 (0.4) 5.97 Grass Pickerel 50.3 (1.4) 23.0 (0.4) 21.72 Redspot Darter 28.8 (1.0) 37 (0.7) 6.19 Bluntnose Darter 28.0 (1.0) 10 (0.2) 17.20 Slough Darter 112.5 (2.6) 29.0 (1.0) 34.04 Blackspotted Topminnow 104.9 (4.6) 139.6 (2.2) 0.01 Green Sunfish 71.8 (1.8) 36.0 (0.7) 25.81 Warmouth 15.0 (0.4) 25.0 (0.4) 2.04 Bluegill 81.5 (2.2) 67 (1.2) 0.19 Longear Sunfish 43.7 (1.1) 28.0 (0.5) 2.22 Redspotled Sunfish 25.0 (0.7) 31.0 (0.6) 0.15 Redfin Shiner 29.5 (1.0) 12.0 (0.3) 8.57 Species P-value Direction Yellow Bullhead 0.14 Pirate Perch 0.31 Creek Chubsucker 0.02 More in river Grass Pickerel <0.01 More in river Redspot Darter 0.02 More in river Bluntnose Darter <0.01 More in river Slough Darter <0.01 More in river Blackspotted Topminnow 0.92 Green Sunfish <0.01 More in river Warmouth 0.17 Bluegill 0.66 Longear Sunfish 0.15 Redspotled Sunfish 0.7 Redfin Shiner <0.01 More in river Table 6.--Habitat variables identified by stepwise Canonical Correspondence Analysis as significantly influencing fish assemblage structure in reservoir and river tributary streams in the Red River Basin sampled in 2014 and 2015. Electrofishing and seining data were analyzed separately Electrofishing [chi square] F P (>F) Seining Root wads 0.21 3.86 <0.01 Dissolved oxygen Depth 0.14 2.63 <0.01 Year 0.11 1.94 <0.01 Flow 0.10 1.75 0.02 Tributary type 0.10 1.83 0.01 Electrofishing [chi square] F P (>F) Root wads 0.22 2.10 <0.01 Depth Year Flow Tributary type
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|Author:||Reuter, Catherine N.; Kaller, Michael D.; Walsh, Colleen E.; Kelso, William E.|
|Publication:||The American Midland Naturalist|
|Date:||Jan 1, 2019|
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