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Mixed-origins of channel catfish in a large-river tributary
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Full length article
Mixed-origins of channel catfish in a large-river tributary ⁎
Jonathan J. Spurgeona, , Mark A. Pegga, Norman M. Haldenb a b
School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE, USA Department of Geological Sciences, University of Manitoba, Winnipeg, MB, Canada,
A R T I C L E I N F O
A B S T R A C T
Handled by George A. Rose
An understanding of factors responsible for population structure including the origins of individuals from among habitats is fundamental to conservation and management of large-river fishes. The prevalence of population mixing of channel catfish Ictalurus punctatus was evaluated within a large-river tributary environment using information from recent environmental history and natal origin derived from otolith microchemistry. Trace elements in water and otoliths were assessed using univariate and multivariate statistical approaches. Water and otolith trace elements differed among river segments facilitating classification of channel catfish to the river segment of capture. Accuracy of the classification tree model for juvenile channel catfish ranged from 44% to 88%. Recent environmental and natal origin microchemistry signatures suggested the channel catfish population within a large-river tributary comprises individuals from multiple locations. Population demographics of channel catfish is likely influenced by mixing of individuals from across the riverine-network. Consideration of the importance of connectivity between main-stem and tributary systems may, therefore, benefit conservation and management of channel catfish and other large-river fishes displaying similar life-history strategies.
Keywords: Otolith microchemistry Connectivity Population mixing River network
1. Introduction The diversity of movement patterns displayed both within and among populations of freshwater fishes has important consequences including maintenance of animal distribution across ecological networks (Chapman et al., 2012; Smith and Kwak, 2014; Moore, 2015). Riverine fishes may use complementary habitat types to carry out lifehistory events (e.g., reproduction and recruitment), find refuge from biotic and abiotic stressors, and take advantage of seasonally available food resources (Lucas and Baras, 2001; Neely et al., 2009; Brönmark et al., 2014). Furthermore, extensive migrations involving freshwater fishes are increasingly evident (Duponchelle et al., 2016; Jager et al., 2016), where migration is defined as movement between distinguishable habitats on a predictable basis (Brönmark et al., 2014). However, not all species and not all individuals within a population undertake prolonged movements and instead may carry out the majority of lifestages within a localized area (Koehn and Nicol, 2016). In some cases, populations may consist of both migrants and non-migrants (Chapman et al., 2012; Brodersen et al., 2014). The great scope for movement of riverine species may facilitate different levels of mixing of individuals among locations and subsequent ecological and evolutionary processes (Moore, 2015; Hawkins et al., 2016). For instance, movement patterns and natal homing of some anadromous species promotes metapopulation structure as well as genetically distinguishable populations
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(Schtickzelle and Quinn, 2007). As such, developing an understanding regarding how populations are distributed across riverine networks and potential mechanisms responsible for maintaining such distribution is dependent in part on quantifying the exchange of individuals among habitat types at ecologically meaningful scales (Porreca et al., 2016). The movement capabilities of fishes in conjunction with the linear connectedness of habitats in riverine environments may increase the likelihood of individuals originating from multiple habitats to mix. An understanding of where within river-networks fishes originate is increasingly needed for conservation and management given the past and proposed alteration of large-river systems throughout the world (Nilsson et al., 2005; Ziv et al., 2012). For instance, fragmentation has impeded historical migration routes across river networks, and isolated freshwater fish populations from habitats conducive for reproduction and recruitment (Duponchelle et al., 2016; Jager et al., 2016). Additionally, large-river fishes are subject to intense harvest through both recreational and commercial fishing (Ziv et al., 2012). As a result, many fish populations in large-river systems have experienced dramatic declines (Allan et al., 2005). Mitigation strategies attempt to reconnect migration corridors and expand species’ distributions (Schaffler et al., 2015; Jager et al., 2016). Harvest regulations are also used to protect certain components of a population (e.g., adults; Gwinn et al., 2015), and maintain refuge areas throughout a riverine network (Abell et al., 2007). Information regarding fish origin may aid in linking
Corresponding author at: School of Natural Resources University of Nebraska-Lincoln Hardin Hall 314 3310 Holdredge Street Lincoln, NE 68583-0973, USA. E-mail address: [email protected] (J.J. Spurgeon).
http://dx.doi.org/10.1016/j.fishres.2017.09.001 Received 6 June 2017; Received in revised form 1 September 2017; Accepted 4 September 2017 0165-7836/ © 2017 Elsevier B.V. All rights reserved.
Please cite this article as: Spurgeon, J.J., Fisheries Research (2017), http://dx.doi.org/10.1016/j.fishres.2017.09.001
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Fig. 1. Location of water samples collected (solid circles), juvenile channel catfish otoliths (open squares), and angled fish (open diamond) in the Platte River, Loup River, Elkhorn River, and the Missouri River. The central Platte River is west of the Loup and Platte river confluence and lower Platte River is east of the Loup and Platte River confluence and extends to the Missouri River.
chemistry exist (Woods et al., 2010; Benjamin et al., 2014; Humston et al., 2016). The exchange of individuals from tributaries to main-stem environments has varied across systems and species (Humston et al., 2010; Laughlin et al., 2016). As such, a greater understanding regarding levels of mixing among river systems and across species is needed as differing connectivity patterns may influence population response to conservation and management strategies in contrasting ways. The goal of this study was to assess prevalence of population mixing of channel catfish Ictalurus punctatus within a large-river tributary environment using information from recent environmental history. The objectives to accomplish this goal were to 1) establish differences in both water chemistry and the microchemistry signatures of juvenile channel catfish otoliths among river segments in both main-stem and tributary environments, and 2) predict the recent river segment inhabited by channel catfish within a large-river tributary. A greater understanding regarding the relative proportions of individuals originating from mainstem or tributary environments may refine concepts regarding population structure across a river network enabling more effective conservation and management of large-river fish populations (Cooke et al., 2016).
conservation and management strategies (e.g., habitat rehabilitation or harvest limits) to fish population response. As such, strategies to restore connectivity and reduce harvest pressure may benefit from a greater understanding regarding origins of individuals within a population (Schaffler et al., 2015; Porreca et al., 2016). Tributaries are an integral component in riverine networks providing complementary habitats to large main-stem rivers that may enhance biodiversity and regulate population dynamics (Benda et al., 2004; Campbell Grant et al., 2007; Pracheil et al., 2009). Tributary systems with mean annual discharge > 166 m3 s−1 are thought to possess suitable habitat characteristics for sustaining large-river fish communities (Pracheil et al., 2013). However, the degree to which these relatively large tributary systems support independent populations of large-river fishes, or the dependence of populations on connectedness between main-stem and tributary environments is not well understood. Information regarding population connectivity between tributary and main-stem environments can identify appropriate scales and locations for conservation and management efforts including habitat remediation, non-native control, and harvest regulations by shedding light on population structure across river networks (Whitledge et al., 2007; Cooke et al., 2016; Duponchelle et al., 2016). Traditional methods for assessing movement patterns and connectivity of large-river fish populations (e.g., telemetry) can be limited for assessing ecological questions regarding origins or migration patterns throughout an individual fish’s lifetime (Campana and Thorrold, 2001; Pracheil et al., 2014). However, the relation between ambient water and fish hard-part (i.e., otoliths) chemical composition enables assessment of movement patterns within and among river systems (Muhlfeld et al., 2012; Loewen et al., 2015) as well as origin of individuals in mixed-origin fisheries (Whitledge et al., 2007; Pangle et al., 2010; Veinott et al., 2012). Microchemical techniques have also provided new insight into alternative life-history strategies through assessment of movement patterns among and within species (Chase et al., 2015; Clarke et al., 2015; Smith and Kwak, 2016). Microchemical and isotopic signatures can facilitate assessment of population connectivity between tributary and main-stem habitats when differences in water
2. Methods 2.1. Study river-network The Missouri River is a highly altered large-river system characterized by armored banks (i.e., pylons, rip-rap, and boulders) and channelizing structures that create a swift and self-dredging channel to maintain navigation (Pegg et al., 2003). The hydrologic character of the Middle Missouri River (river kilometer [rkm] 1305–787) consists of elevated low-flow periods and limited seasonal variability in flows compared to pre-modification conditions (Pegg et al., 2003). The Platte River is a tributary of the Missouri River and is considered less impaired in comparison to the Middle Missouri River (Hamel et al., 2016). The Platte River is characterized by a relatively unrestricted wide channel intertwining with shifting sandbar complexes. The flow regime of the 2
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Platte River is, however, subject to hydropeaking flows as well as periods of no-flow (Spurgeon et al., 2016). Limited information exists regarding the origin of large-river fishes in the Platte River. Therefore, understanding the prevalence of mixing of individuals in the Platte River from differing environments will provide information regarding sources of fishes in the Platte River as well as roles the Platte River may have in maintaining population structure of riverine fishes within the greater river network.
Table 1 Size summary (mm Total Length [TL]) of channel catfish used in microchemical analysis to determine origins. * indicates channel catfish taken from anglers in the middle Platte River.
2.2. Microchemistry data collection Water samples were collected using a syringe filtration technique according to Shiller (2003) from seven sample locations among four river systems including the Platte River (3 sites), Loup River (1 site), Elkhorn River (1 site), and Missouri River (2 sites; Fig. 1). Sample locations within river systems were grouped according to river segments that included the central Platte River (west of Loup and Platte river confluence; n = 9 water samples), middle Platte River (Loup River confluence to Elkhorn River confluence; n = 9 water samples), lower Platte River (Elkhorn River confluence to the Missouri River; n = 7 water samples), Loup River (near Genoa, NE; n = 9 water samples), Elkhorn River (near Waterloo, NE; n = 7 water samples), upper Missouri River (above Platte River confluence; n = 9 water samples), and the lower Missouri River (below Platte River confluence; n = 7 water samples). Water samples were collected in 2014 and 2015 from each location during base flow periods (i.e., late summer to early fall). Water sample kits were provided by the University of Southern Mississippi’s Trace Analysis Lab. Details on preparing sample kits can be found in Shiller (2003), and included soaking all sample bottles and syringes in hot 1.2 M HCl baths for at minimum 8 h and rinsing with ultrapure distilled deionized water. Kits remained sealed until samples were obtained. Sample bottles and syringes were rinsed a minimum of three times with river water before extracting a water sample with a 250-ml high density polyethylene bottle. A subsample was extracted using a polyethylene 50-mL syringe (without a rubber seal). Approximately 10 mL of water was filtered as waste using a 0.45-μm syringe filter. The remainder of the subsample was filtered until a 15-mL polyethylene bottle was filled. Water samples were collected from all locations within 1–2 days and kept in refrigeration until shipment to the University of Southern Mississippi’s Trace Analysis Lab. Water samples were analyzed for elemental concentrations of Sr, Ba, Mg, Mn, and Ca using high resolution Inductively Coupled Plasma Mass Spectrometry (ICPMS; Thermo-Finnigan Element 2). Channel catfish Ictalurus punctatus lapilli otoliths (Long and Stewart, 2010) were collected from sample locations in the central Platte River, middle Platte River, lower Platte River, the Elkhorn River, and the upper Missouri River in late spring and summer 2015 (Fig. 1). Baited hoopnets were used to collect juvenile channel catfish (< 300 mm TL, Holland and Peters, 1992). Juvenile channel catfish were used to establish otolith signatures from the different river segments to reduce the risk of extensive movements by older individuals. Channel catfish otoliths were also collected from anglers within a 5 rkm reach of the lower Platte River near Fremont, NE (Latitude: 41.424231; Longitude: −96.539654). Angled channel catfish were targeted for approximately a five day period in late May 2015 using set-lines baited with live fathead minnows Pimephales promelas. Channel catfish anglers target larger individuals and provided an opportunity to assess potential migratory patterns and natal homing of sexually mature adults (Table 1). Otoliths were embedded on paraffin film strips using Buhler Epothin epoxy with sulcus up and the otolith rostrum pointing toward the film edge. Once dry, the otolith nucleus was located and marked dorsoventrally under a dissecting microscope. Otoliths were sectioned along the transverse plane immediately anterior (i.e., toward the rostrum) and posterior of the nucleus mark (approximately 2-mm) using a Buhler Isomet low-speed saw. Otolith sections were placed onto double sided tape in plastic rings with the posterior cut face down. Plastic rings were
River Segment
N
Mean TL
SE
Range
Elkhorn Missouri Central Platte Middle Platte Lower Platte Middle Platte*
5 7 8 14 9 30
155 196 222 185 178 630
6 25 20 20 13 15
141–170 129–283 100–276 89–292 107–235 436–744
back-filled with Buhler Epothin epoxy and air-dried for 48 h. Otolith surfaces were cleaned and polished in a sequential process involving hand polishing with both 30- and 9-μm lapping film and with a 1- and 0.05- μm disk with a 0.1-μm aluminum oxide paste. Otoliths were ultrasonically cleaned between each polish step. Microchemical analysis of channel catfish otoliths was performed by ablating the surface of the otolith with a New Wave Research UP-213 laser and measuring elemental concentrations with a ThermoFinnigan Element-2 ICPMS. Ablation occurred across the diameter of the otolith surface passing through the primordium. A warm-up period of 150 s was used between successive samples, and gas blanks were analyzed within the last fifty seconds of each warm-up. The beam size used was 30-μm with a scanning speed of 2-μm/s and a fluence of 3.5-4J/cm2. A NIST610 glass standard was ran at the start of laser analysis and approximately every 1.5 h following; an average standard value was taken to correct for instrument drift. Elements assessed included Sr, Ba, Mg, Mn, and Ca. The otolith edge and primordial (i.e., near primordium) regions of each otolith were assessed to obtain an estimate of recent environmental signatures and natal environmental signatures for each channel catfish. 2.3. Statistical analysis Water and fish hard-part structures grouped by river segment and were assessed using univariate and multivariate methods. Visual inspection of the data and test of normality (i.e., Shapiro-Wilks test) indicated deviation from normality for both water and otolith data. Thus, log10-transformation of elemental concentrations was done and normality was achieved for otolith data expect for Ba. Normality was not achieved for water data; however, graphical inspection (i.e., normal distribution quantile–quantile plots) of both water and otolith Ba data suggested only minor deviation from normality and thus we proceeded with parametric tests (Ramsay et al., 2011). A single-factor analysis of variance (ANOVA) followed by Tukey’s HSD test for multiple comparisons was used to assess differences in individual water and otolith mean elemental concentrations among river segments (Zeigler and Whitledge, 2011). A multivariate analysis of variance (MANOVA) was used to assess differences in both water and otolith elemental concentrations among river segments. Individual contrasts were performed using MANOVA between each river segment (e.g., central Platte River vs. lower Platte River). A Bonferroni correction was used to adjust significance levels and reduce type I error rate when performing multiple comparisons. An alpha value of 0.002 and 0.005 was used in MANOVA pairwise comparison tests for differences in water microchemistry and channel catfish otolith microchemistry among river segments. A classification tree modelling approach was used to separate juvenile channel catfish based on river segment of capture (Mercier et al., 2011). Otolith edge data (mean of outer 10 s of laser ablation; approximately 30 μm) from juvenile channel catfish was used to characterize the recent river segment inhabited by individuals (Zeigler and Whitledge, 2011; Schoen et al., 2016). The outer edge data represented approximately the last year of life for our sampled channel catfish. Classification trees were built using recursive partitioning in the rpart 3
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River (P = 0.9024); the lower Platte River and the middle Platte River (P = 0.7245); the lower Missouri River and the middle Platte River (P = 0.1843). Comparisons among segments indicated Mg differed among all segments except between the central Platte River and the Elkhorn River (P = 0.4767) as well as the upper Missouri River (P = 0.9781) and lower Missouri River (P = 0.9953); the Elkhorn River and the upper Missouri River (P = 0.0789) and lower Missouri River (P = 0.1638); the upper and lower Missouri River (P = 0.9999). Evidence suggests Mn may be under significant physiological control and thus may be limited in assessing origin of freshwater fishes (Turner and Limburg, 2015). Additionally, the Elkhorn River was the only river segment were Mn differed between a few river segments (i.e., Loup River; middle Platte River; lower Platte River). We, therefore, did not use Mn to assess differences in otolith microchemistry among river segments due to the low variability among sites and the susceptibility to physiological control. The middle and lower Platte River as well as their tributaries (i.e., the Loup River and the Elkhorn River) displayed elevated Ba signatures compared to the central Platte River and the upper and lower Missouri River (Fig. 2). In contrast, the middle and lower Platte River displayed lower Sr signatures compared to the central Platte River and the upper and lower Missouri River (Fig. 2). Water microchemistry signatures differed among river segments using the combination of Sr, Ba, and Mg (MANOVA, Wilks = 0.001, NumDF = 18, DenDF = 130.59, P < 0.0001). Multivariate comparisons among river segments were all significant (Table 2).
package (Therneau et al., 2015) in Program R (R Core Team, 2015). Classification tree methods repeatedly split the data into increasingly homogenous groups (e.g., river segments) using combinations of explanatory variables (e.g., otolith chemical signatures; Breiman et al., 1984). A splitting criterion based on the Gini impurity index (De’ath and Fabricius, 2000) was used, and the smallest tree within 1 standard error of the tree with the lowest classification error as determined using 10-fold cross-validation was selected (Brieman et al., 1984). Variable importance was assessed using a goodness-of-split criterion based on the classification accuracy when the variable was used as either a primary or surrogate splitting variable (scaled to sum to 100; Therneau et al., 2015). The classification tree model was applied to predict recent environmental signatures and natal origins of angled channel catfish. The area of each otolith corresponding to the first year of growth was isolated to obtain an estimate of natal microchemistry signatures.
3. Results 3.1. Water microchemistry Univariate tests among river segments indicated Sr (ANOVA, NumDF = 6, DenDF = 48, F = 68.64,P < 0.0001), Ba (ANOVA, NumDF = 6, DenDF = 48, F = 80.81, P < 0.0001), Mg (ANOVA, NumDF = 6, DenDF = 48, F = 162.7, P < 0.0001), and Mn (ANOVA, NumDF = 6, DenDF = 48, F = 4.94, P < 0.001) were significantly different among river segments (Fig. 2). Comparisons among segments using Tukey’s HSD indicated Sr differed between all segments except between the central Platte River and the upper Missouri River (P = 0.1968); the Elkhorn River and the lower Platte River (P = 0.9971) and middle Platte River (P = 0.5992); the lower and middle Platte River (P = 0.9191); the lower and upper Missouri River (P = 0.8482). Comparisons among segments indicated Ba differed between all segments except between the central Platte River and the upper Missouri River (P = 0.7378); the lower Platte River and the Loup
3.2. Juvenile channel catfish otolith microchemistry Sampled juvenile channel catfish had mean length of 189 mm TL (SE = 9). Univariate tests of otolith microchemistry signatures indicated Ba (ANOVA, NumDF = 4, DenDF = 38, F = 12.66, P < 0.0001), Sr (ANOVA, NumDF = 4, DenDF = 38, F = 5.187, P = 0.0019), and Mg (ANOVA, NumDF = 4, DenDF = 38, F = 4.818, P = 0.0031) varied by river segment. Comparisons among segments Fig. 2. Comparison of water microchemistry signatures from the central Platte River (CP), Loup River (LOUP), middle Platte River (MP), Elkhorn River (ELK), lower Platte River (LP), upper Missouri River (UMR), and lower Missouri River (LMR). Samples were collected from each site in both 2014 and 2015. The horizontal solid line within boxes is the median value, boxes represent the interquartile range, and whiskers are the 95% confidence intervals. Points represent data beyond the 95% confidence interval. Measurements are in parts per million (ppm).
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Table 2 Multivariate analysis of variance comparisons of water microchemistry signatures among river segments. River segments include the central Platte River (CP), the lower Platte River (LP), the upper Missouri River (UMR), the lower Missouri River (LMR), the lower Loup River (LOUP), and the lower Elkhorn River (ELK). A Bonferroni correction was used to adjust significance level to 0.002. An * indicates a significant difference between river segments. Comparison
Wilk’s λ
NumDF
DenDF
MP vs. CP MP vs. UMR MP vs. ELK MP vs. LOUP MP vs. LMR MP vs. LP LP vs. CP LP vs. UMR LP vs. ELK LP vs. LOUP LP vs. LMR CP vs. ELK CP vs. UMR CP vs. LMR CP vs. LOUP UMR vs. ELK UMR vs. LOUP UMR vs. LMR LMR vs. LOUP LMR vs. ELK LOUP vs. ELK
0.0233 0.0175 0.0174 0.0511 0.0208 0.1387 0.0087 0.0251 0.1066 0.0165 0.0327 0.0050 0.0702 0.0086 0.0059 0.0257 0.0069 0.0794 0.0078 0.0232 0.0118
3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
12 14 12 14 12 12 10 12 10 12 10 10 12 10 12 12 14 12 12 10 12
Table 3 Classification matrix for channel catfish < 300 mm TL used to build the classification tree model. River segments include the central Platte River (CP), the middle Platte River (MP), the Elkhorn River (ELK), the lower Platte River (LP), and the upper Missouri River (UMR). Sampled Predicted CP MP ELK LP UMR Accuracy:
P-value < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.001* < 0.0001* < 0.0001* < 0.001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001*
CP 7 0 1 0 0 88%
MP 3 11 0 0 0 79%
ELK 0 1 4 0 0 80%
LP 1 4 0 4 0 44%
UMR 2 0 0 0 5 71%
otolith microchemistry signatures sampled from the upper Missouri River differed from those sampled in the Elkhorn River (MANOVA, Wilks = 0.11937, NumDF = 3, DenDF = 8, P = 0.0004). Accuracy of the classification tree model for juvenile channel catfish ranged from 44% to 88% (Table 3). The classification tree model had the greatest classification accuracy for juvenile channel catfish sampled in the central Platte River, the Elkhorn River, and the middle Platte River (Table 3). The greatest difficulty in classifying individuals back to their location of capture was for the lower Platte River where the model largely split individuals between the lower Platte River and the middle Platte River (Table 3). The first split within the classification tree separated channel catfish into two groups consisting of individuals from the middle and lower Platte River as well as the Elkhorn River from those located in the central Platte River and the upper Missouri River (Fig. 3). Further refinement of classification between the middle and lower Platte River and the Elkhorn River was achieved by differences in Ba and Mg levels between these segments. Further refinement of classification between the central Platte River and the upper Missouri river was achieved by differences in Sr levels between these two segments. The most influential variable differentiating channel catfish otolith signatures by river segment was Ba (importance score = 43), followed by, in decreasing order of importance, Sr (importance score = 34), and Mg (importance score = 23).
using Tukey’s HSD indicated Sr differed between the Elkhorn River and the central Platte River (P < 0.001) as well as the middle Platte River (P = 0.0477). Comparisons among river segments indicated Ba differed among all river segments except between the upper Missouri River and central Platte River (P = 0.9818); the Elkhorn River and the middle Platte River (P = 0.1810) and the lower Platte River (P = 0.5885); the lower Platte River and the middle Platte River (P = 0.1810). Comparisons among river segments indicated Mg differed between the Elkhorn River and the central Platte River (P = 0.0220), the middle Platte River (P = 0.0021), the lower Platte River (P = 0.0095), and the upper Missouri River (P = 0.0036). Otolith microchemistry signatures differed among river segments using the combination of Sr, Ba, and Mg signatures (MANOVA, Wilks = 0.20317, NumDF = 12, DenDF = 95.53, P < 0.0001). Juvenile channel catfish sampled in the middle Platte River had different otolith microchemistry signatures compared to those individuals sampled in the Missouri River (MANOVA, Wilks = 0.32465, NumDF = 3, DenDF = 17, P = 0.0002).However, juvenile channel catfish sampled in the middle Platte River did not have different otolith microchemistry signatures compared to those individuals sampled in the lower Platte River (MANOVA, Wilks = 0.76482, NumDF = 3, DenDF = 19, P = 0.1562), the central Platte River (MANOVA, Wilks = 0.63492, NumDF = 3, DenDF = 18, P = 0.0386), or the Elkhorn River (MANOVA, Wilks = 0.46863, NumDF = 3, DenDF = 15, P = 0.0084). Juvenile channel catfish sampled in the lower Platte River had different otolith microchemistry signatures compared to those individuals sampled in the upper Missouri River (MANOVA, Wilks = 0.32503, NumDF = 3, DenDF = 12, P = 0.0029) and central Platte River (MANOVA, Wilks = 0.22927, NumDF = 3, DenDF = 13, P = 0.0001). In contrast, juvenile channel catfish microchemistry signatures in the lower Platte River did not differ from those individuals sampled in the Elkhorn River (MANOVA, Wilks = 0.38063, NumDF = 3, DenDF = 10, P = 0.01786). Juvenile channel catfish otolith microchemistry signatures sampled from the central Platte River differed from those sampled in the Elkhorn River (MANOVA, Wilks = 0.068742, NumDF = 3, DenDF = 9, P < 0.0001), but not from those individuals sampled in the upper Missouri River (MANOVA, Wilks = 0.48665, NumDF = 3, DenDF = 11, P = 0.04116). Juvenile channel catfish
3.3. Angled channel catfish otolith microchemistry Angled channel catfish had a mean length of 630 mm TL (SE = 15), and displayed unique microchemistry signatures across their life-
Fig. 3. Classification rule used to separate channel catfish among river segments. The classification tree was built using rpart() in Program R; tree pruned at size = 5 with an cp of 0.098. The smallest tree that was within 1 standard error of the minimum error was selected. River segments include central Platte River (CP), middle Platte River (MP), Elkhorn River (ELK), lower Platte River (LP), and upper Missouri River (UMR). No channel catfish from the Loup River or lower Missouri River were sampled below our cutoff threshold of 300 mm TL for inclusion in the classification model.
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Fig. 4. Example cross-sections for Ba signatures across the otolith for two angled channel catfish exhibiting different origins and residency patterns. Channel catfish 18070 (long dash line) was predicted to have both a recent environmental signature and natal origin signature from the middle Platte River. Channel catfish 18070 appears to have remained in the middle Platte River throughout its life. In contrast, channel catfish 19632 (short dash) was predicted to have a natal origin signature from the middle Platte River, but a recent environmental signature from the upper Missouri River. Channel catfish 19632 appears to have migrated out of the middle Platte River to the upper Missouri River before returning to the Middle Platte River where the individual was caught. The horizontal solid line indicates the cutoff value for Ba values in the classification tree model separating the middle and lower Platte River and Elkhorn River from the rest of the river network. Both cross sections represent ablation across the entire otolith from edge (distance = 0) to edge (maximum distance) crossing through the primordium indicated by arrow at top of figure.
central Platte River and the upper Missouri River. As such, otolith microchemistry may be particularly useful for assessing mixing of individuals from the lower and middle Platte River with individuals from the central Platte River and Missouri River. Consistent differences in water chemistry among river segments through time is needed to assess origins of individuals from differing year classes (Pracheil et al., 2014). The differences in water microchemistry between river segments were consistent across a two-year period suggesting temporal stability during this study. Additionally, Sr and Ba levels measured in this study were consistent with long-term (i.e., 1983–2015) water samples collected in the lower Platte River (unpublished data from Louisville, NE collected by USGS National Water-Quality Assessment Program). A greater spatial coverage of microchemistry signatures may, however, be needed to assess the uniqueness of the middle and lower Platte River signatures across greater spatial scales of the river network to assess potential contributions of individuals from the Platte River to the Missouri River. Complex population structure may exist among main-stem and tributary habitats within large-river networks (Duponchelle et al., 2016). For instance, Humston et al. (2010) suggested substantial mixing between tributary and main-stem river environments for smallmouth bass Micropterus dolomieu may drive population dynamics between the two systems. The occurrence of channel catfish angled in the middle Platte River that recently resided in the upper Missouri River suggests a portion (e.g., approximately 30% of angled individuals in this study) of channel catfish are from mixed-origins and are using both systems. Channel catfish are considered a mobile species (Pugh and Schramm, 1999; Wendel and Kelsch, 1999) and have displayed movement patterns between main-stem river systems and tributaries (Dames et al., 1989; Newcomb, 1989) as well as between lake environments and tributaries (Butler and Wahl, 2011; Siddons et al., 2017). Pellett et al. (1998) suggested movement patterns based on mark-recapture data between the Mississippi River and the Wisconsin River may be linked to reproduction. The timing of sample collection in this study is aligned
history reflective of movement between river systems (Fig. 4). Angled channel catfish were predicted to have recently inhabited the middle Platte River (n = 15, 50%), the upper Missouri River (n = 9, 30%), the central Platte River (n = 3, 10%), the Elkhorn River (n = 2, 6%) and the lower Platte River (n = 1, 3%). Natal microchemical signatures suggested 66% (20/30) of the angled channel catfish originated from the middle Platte River. The remaining individuals were predicted to have natal signatures from the lower Platte River (n = 9) and the upper Missouri River (n = 1).
4. Discussion Microchemical approaches may be a beneficial tool for use in predicting origins and prevalence of mixing of channel catfish among river segments in the Platte and Missouri river systems. Differences existed in both water and channel catfish otolith chemical signatures among river segments and suggests Ba, Sr, and Mg together may serve as chemical markers to differentiate individuals based on movement among river segments. Previous works have also effectively used similar chemical markers to assess origins and movements of several freshwater fish species (Wells et al., 2003; Clarke et al., 2015). The river segments among which movement may be assessed, however, could be limited by similarities in water chemistry. For instance, elemental signatures of Sr and Ba in water did not vary between the middle and lower Platte River. The greater error in classification of juvenile channel catfish between the middle and lower Platte River was likely due to similarities in water chemistry or a prevalence of movement between these two river segments by juveniles. Water chemistry signatures in the middle and lower Platte River and their tributaries (i.e., Loup and Elkhorn rivers) did, however, exhibit greater Ba and less Sr when compared to the central Platte River and the Missouri River. The classification model was able to differentiate individual channel catfish sampled from the lower and middle Platte River from those individuals sampled in the 6
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maintaining population distribution in North American river-networks (Pellett et al., 1998; Laughlin et al., 2016). Microchemistry techniques can facilitate linking movement patterns of large-river fishes and the spatial and temporal scales of management needed (Humston et al., 2010; Porreca et al., 2016). As such, management and conservation strategies of large-river fishes may benefit from consideration of population connectivity across spatial scales and the different roles that some habitats (e.g., tributaries) hold in maintaining population structure across the river-network.
with both the pre-spawning and spawning period of channel catfish (May to June; Pellett et al., 1998; Hubert, 1999), and both ripe males and females were observed (JJ Spurgeon, personal observation; 81% of individuals had visible and developed gametes). Therefore, the premise that mixture of channel catfish from different river segments in the middle Platte River is a consequence of spawning movement is plausible and corroborates previous tag-based approaches assessing channel catfish movement (Newcomb, 1989; Pellett et al., 1998). Channel catfish caught by anglers from the middle Platte River predominately possessed natal origin signatures from both the middle and lower Platte River with only one individual possessing natal signatures from the Missouri River. Spawning and recruitment of channel catfish in large tributary environments may contribute recruits to larger main-stem systems (Laughlin et al., 2016). As such, movement of adults into tributary systems for reproduction as well as the potential for tributary recruits to move into main-stem environments may blur distinct population boundaries and necessitate examining population processes across greater spatial scales (Pugh and Schramm, 1999; Laughlin et al., 2016; Siddons et al., 2017). For instance, movement from natal habitats has been shown to support population structure of freshwater fishes in both riverine and lentic environments (Norman and Whitledge, 2015; Brodnik et al., 2016). Harvest regulations may have unintended consequences if not applied at appropriate spatial or temporal scales (e.g., protection not afforded to reproductive individuals; Siddons et al., 2017). However, the mixed-origin composition of channel catfish is rarely given consideration when examining alternative harvest strategies and the sustainability of populations to both recreational and commercial harvest (Beultmann and Phelps, 2015; Eder et al., 2016). Our results suggest management recommendations for channel catfish may need to consider the potential mixed-origins of individuals within a river segment. For instance, channel catfish recently inhabiting the Missouri River are harvested by anglers in the Platte River. Therefore, management actions taken solely within the Missouri River (e.g., size limits), may not afford protection to larger individuals moving into the Platte River. Movement from natal habitats may also contribute individuals throughout a river network (Humpson et al., 2010; Duponchelle et al., 2016). Of the nine angled channel catfish with recent environmental signatures from the upper Missouri River, all except one individual was classified as having natal origins from the middle or lower Platte River. As such, channel catfish from the Platte River may be contributing individuals to the Missouri River. Additionally, channel catfish may be exhibiting a degree of homing behavior. Homing has been quantified for some catfish species (Duponchelle et al., 2016), and has been suggested for channel catfish (Pellet et al., 1998). Further investigation regarding recruitment sources among tributary and mainstem habitats and the propensity of movement among such habitats using otolith microchemistry may shed light on the interdependence of channel catfish population dynamics among different habitat types in riverine-networks (Schlosser and Angermeier, 1995). However, physiological and environmental changes may influence the allocation of trace elements within fish otoliths (Sturrock et al., 2015; Turner and Limburg, 2015). As such, information regarding changes in otolith trace element composition of channel catfish resulting from changes in lifestage (e.g., sexual maturity) or environmental stressors (e.g., drought) may be needed. Though the presence of multiple calcium carbonate phases (vaterite and aragonite) within otoliths may influence microchemical signatures (Melancon et al., 2005), the differences in partitioning of trace elements such as Sr into vaterite and aragonite are understood. Additionally, trace elemental signatures of channel catfish from across different otolith sections have been used to assign origin and assess environmental history (Laughlin et al., 2016). Management and conservation of large-river catfishes and largeriver fishes in general may depend on assessing the large-scale spatial complexity of population structure (Hogan, 2011; Cooke et al., 2016). For channel catfish, spatially explicit recruitment dynamics along with wide-ranging movement patterns may be important mechanisms in
Acknowledgements We thank the Nebraska Game and Parks Commission for project funding through the National Sport Fish Restoration Fund (F-75-R) and the University of Nebraska-Lincoln, Institute of Agriculture and Natural Resources. We thank members of the Fremont Airboat Club for aiding in channel catfish sample collection. We thank P. Yang and Z. Song for their technical support along with the University of Manitoba LA-ICPMS facility. References Abell, R., Allan, J.D., Lehner, B., 2007. Unlocking the potential of protected areas for freshwaters. Biol. Conserv. 134, 48–63. Allan, J.D., Abell, R., Hogan, Z., Revenga, C., Taylor, B.W., Welcomme, R.L., Winemiller, K., 2005. Overfishing of inland waters. Bioscience 55, 1041–1051. Benda, L., Poff, N.L., Miller, D., Dunne, T., Reeves, G., Pess, G., Pollock, M., 2004. The network dynamics hypothesis: how channel networks structure riverine habitats. Bioscience 54, 413–427. Benjamin, J.R., Wetzel, L.A., Martens, K.D., Larsen, K., Connolly, P.J., 2014. Spatiotemporal variability in movement age, and growth of mountain whitefish (Prosopium williamsoni) in a river network based upon PIT tagging and otolith chemistry. Can. J. Fish. Aquat.Sci. 71, 131–140. Brönmark, C., Hulthen, K., Nillson, P.A., Skov, C., Hansson, L.A., Brodersen, J., Chapman, B.B., 2014. There and back again: mirgration in freshwater fishes. Can. J. Zool. 92, 467–479. Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J., 1984. Classification and Regression Trees. Chapman and Hall, New York. Brodersen, J., Chapman, B.B., Nilsson, P.A., Skov, C., Hansson, L.A., Brönmark, C., 2014. Fixed and flexible: coexistence of obligate and facultative migratory strategies in a freshwater fish. PLoS One 9, e90294. http://dx.doi.org/10.1371/journal.pone. 0090294. Brodnik, R.M., Fraker, M.E., Anderson, E.J., Carreon-Martinez, L., DeVanna, K.M., Heath, D.D., Reichert, J.M., Roseman, E.F., Ludsin, S.A., 2016. Larval dispersal underlies demographically important intersystem connectivity in a Great Lakes yellow perch (Perca flavescens) population. Can. J. Fish. Aquat.Sci. 73, 416–426. Butler, S.E., Wahl, D.H., 2011. Distribution movements, and habitat use of channel catfish in a river with multiple low-head dams. River Res. Appl. 27, 1182–1191. Campana, S.E., Thorrold, S.R., 2001. Otoliths, increments, and elements: keys to a comprehensive understanding of fish populations? Can. J. Fish. Aquat.Sci. 58, 30–38. Campbell Grant, E.H., Lowe, W.H., Fagan, W.F., 2007. Living in the branches: population dynamics and ecological processes in dendritic networks. Ecol. Lett. 10, 165–175. Chapman, B.B., Hulthen, K., Brodersen, J., Nilsson, P.A., Skov, C., Hansson, L.A., Brönmark, C., 2012. Partial migration: causes and consequences. J. Fish Biol. 81, 456–478. Chase, N.M., Caldwell, C.A., Carleton, S.A., Gould, W.R., Hobbs, J.A., 2015. Movement patterns and dispersal potential of Pecos bluntnose shiner (Notropis simus pecosensis) revealed using otolith microchemistry. Can. J. Fish. Aquat.Sci. 72, 1575–1583. Clarke, A.D., Telmer, K.H., Shrimpton, J.M., 2015. Movement patterns of fish revealed by otolith microchemistry: a comparision of putative migratory and resident species. Environ. Biol. Fishes 98, 1583–1597. Cooke, S.J., Martins, E.G., Struthers, D.P., Gutowsky, L.F.G., Power, M., Doka, S.E., Dettmers, J.M., Crook, D.A., Lucas, M.C., Holbrook, C.M., Kruger, C.C., 2016. A moving target— incorporating knowledge of the spatial ecology of fish into assessment and management of freshwater fish populations. Environ. Monit. Assess. 188, 1–18. Dames, H.R., Coon, T.G., Robinson, J.W., 1989. Movements of channel and flathead catfish between the Missouri River and a tributary: perche Creek. Trans. Am. Fish. Soc. 118, 670–679. De’ath, G., Fabricius, K.E., 2000. Classification and regression trees: a powerful yet simple technique for ecological data analysis. Ecology 81, 3178–3192. Duponchelle, F., Pouilly, M., Pécheyran, C., Hauser, M., Renno, J.F., Panfili, J., Darnaude, A.M., García-Vasquez, A., Carvajal-Vallejos, F., García-Dávila, C., Doria, C., Bérail, S., Donard, A., Sondag, F., Santos, R.V., Nuñez, J., Point, D., Labonne, M., Baras, E., 2016. Trans- Amazonian natal homing in giant catfish. J. Appl. Ecol. 53, 1511–1520. Eder, B.L., Pegg, M.A., Mestl, G.E., 2016. Modelling effects of length limit regulations on riverine populations of channel catfish. North Am. J. Fish. Manage. 36, 140–146. Gwinn, D.C., Allen, M.S., Johnston, F.D., Brown, P., Todd, C.R., Arlinghaus, R., 2015. Rethinking length-based fisheries regulations: the value of protecting old and large
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Full length article
Mixed-origins of channel catfish in a large-river tributary ⁎
Jonathan J. Spurgeona, , Mark A. Pegga, Norman M. Haldenb a b
School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE, USA Department of Geological Sciences, University of Manitoba, Winnipeg, MB, Canada,
A R T I C L E I N F O
A B S T R A C T
Handled by George A. Rose
An understanding of factors responsible for population structure including the origins of individuals from among habitats is fundamental to conservation and management of large-river fishes. The prevalence of population mixing of channel catfish Ictalurus punctatus was evaluated within a large-river tributary environment using information from recent environmental history and natal origin derived from otolith microchemistry. Trace elements in water and otoliths were assessed using univariate and multivariate statistical approaches. Water and otolith trace elements differed among river segments facilitating classification of channel catfish to the river segment of capture. Accuracy of the classification tree model for juvenile channel catfish ranged from 44% to 88%. Recent environmental and natal origin microchemistry signatures suggested the channel catfish population within a large-river tributary comprises individuals from multiple locations. Population demographics of channel catfish is likely influenced by mixing of individuals from across the riverine-network. Consideration of the importance of connectivity between main-stem and tributary systems may, therefore, benefit conservation and management of channel catfish and other large-river fishes displaying similar life-history strategies.
Keywords: Otolith microchemistry Connectivity Population mixing River network
1. Introduction The diversity of movement patterns displayed both within and among populations of freshwater fishes has important consequences including maintenance of animal distribution across ecological networks (Chapman et al., 2012; Smith and Kwak, 2014; Moore, 2015). Riverine fishes may use complementary habitat types to carry out lifehistory events (e.g., reproduction and recruitment), find refuge from biotic and abiotic stressors, and take advantage of seasonally available food resources (Lucas and Baras, 2001; Neely et al., 2009; Brönmark et al., 2014). Furthermore, extensive migrations involving freshwater fishes are increasingly evident (Duponchelle et al., 2016; Jager et al., 2016), where migration is defined as movement between distinguishable habitats on a predictable basis (Brönmark et al., 2014). However, not all species and not all individuals within a population undertake prolonged movements and instead may carry out the majority of lifestages within a localized area (Koehn and Nicol, 2016). In some cases, populations may consist of both migrants and non-migrants (Chapman et al., 2012; Brodersen et al., 2014). The great scope for movement of riverine species may facilitate different levels of mixing of individuals among locations and subsequent ecological and evolutionary processes (Moore, 2015; Hawkins et al., 2016). For instance, movement patterns and natal homing of some anadromous species promotes metapopulation structure as well as genetically distinguishable populations
⁎
(Schtickzelle and Quinn, 2007). As such, developing an understanding regarding how populations are distributed across riverine networks and potential mechanisms responsible for maintaining such distribution is dependent in part on quantifying the exchange of individuals among habitat types at ecologically meaningful scales (Porreca et al., 2016). The movement capabilities of fishes in conjunction with the linear connectedness of habitats in riverine environments may increase the likelihood of individuals originating from multiple habitats to mix. An understanding of where within river-networks fishes originate is increasingly needed for conservation and management given the past and proposed alteration of large-river systems throughout the world (Nilsson et al., 2005; Ziv et al., 2012). For instance, fragmentation has impeded historical migration routes across river networks, and isolated freshwater fish populations from habitats conducive for reproduction and recruitment (Duponchelle et al., 2016; Jager et al., 2016). Additionally, large-river fishes are subject to intense harvest through both recreational and commercial fishing (Ziv et al., 2012). As a result, many fish populations in large-river systems have experienced dramatic declines (Allan et al., 2005). Mitigation strategies attempt to reconnect migration corridors and expand species’ distributions (Schaffler et al., 2015; Jager et al., 2016). Harvest regulations are also used to protect certain components of a population (e.g., adults; Gwinn et al., 2015), and maintain refuge areas throughout a riverine network (Abell et al., 2007). Information regarding fish origin may aid in linking
Corresponding author at: School of Natural Resources University of Nebraska-Lincoln Hardin Hall 314 3310 Holdredge Street Lincoln, NE 68583-0973, USA. E-mail address: [email protected] (J.J. Spurgeon).
http://dx.doi.org/10.1016/j.fishres.2017.09.001 Received 6 June 2017; Received in revised form 1 September 2017; Accepted 4 September 2017 0165-7836/ © 2017 Elsevier B.V. All rights reserved.
Please cite this article as: Spurgeon, J.J., Fisheries Research (2017), http://dx.doi.org/10.1016/j.fishres.2017.09.001
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Fig. 1. Location of water samples collected (solid circles), juvenile channel catfish otoliths (open squares), and angled fish (open diamond) in the Platte River, Loup River, Elkhorn River, and the Missouri River. The central Platte River is west of the Loup and Platte river confluence and lower Platte River is east of the Loup and Platte River confluence and extends to the Missouri River.
chemistry exist (Woods et al., 2010; Benjamin et al., 2014; Humston et al., 2016). The exchange of individuals from tributaries to main-stem environments has varied across systems and species (Humston et al., 2010; Laughlin et al., 2016). As such, a greater understanding regarding levels of mixing among river systems and across species is needed as differing connectivity patterns may influence population response to conservation and management strategies in contrasting ways. The goal of this study was to assess prevalence of population mixing of channel catfish Ictalurus punctatus within a large-river tributary environment using information from recent environmental history. The objectives to accomplish this goal were to 1) establish differences in both water chemistry and the microchemistry signatures of juvenile channel catfish otoliths among river segments in both main-stem and tributary environments, and 2) predict the recent river segment inhabited by channel catfish within a large-river tributary. A greater understanding regarding the relative proportions of individuals originating from mainstem or tributary environments may refine concepts regarding population structure across a river network enabling more effective conservation and management of large-river fish populations (Cooke et al., 2016).
conservation and management strategies (e.g., habitat rehabilitation or harvest limits) to fish population response. As such, strategies to restore connectivity and reduce harvest pressure may benefit from a greater understanding regarding origins of individuals within a population (Schaffler et al., 2015; Porreca et al., 2016). Tributaries are an integral component in riverine networks providing complementary habitats to large main-stem rivers that may enhance biodiversity and regulate population dynamics (Benda et al., 2004; Campbell Grant et al., 2007; Pracheil et al., 2009). Tributary systems with mean annual discharge > 166 m3 s−1 are thought to possess suitable habitat characteristics for sustaining large-river fish communities (Pracheil et al., 2013). However, the degree to which these relatively large tributary systems support independent populations of large-river fishes, or the dependence of populations on connectedness between main-stem and tributary environments is not well understood. Information regarding population connectivity between tributary and main-stem environments can identify appropriate scales and locations for conservation and management efforts including habitat remediation, non-native control, and harvest regulations by shedding light on population structure across river networks (Whitledge et al., 2007; Cooke et al., 2016; Duponchelle et al., 2016). Traditional methods for assessing movement patterns and connectivity of large-river fish populations (e.g., telemetry) can be limited for assessing ecological questions regarding origins or migration patterns throughout an individual fish’s lifetime (Campana and Thorrold, 2001; Pracheil et al., 2014). However, the relation between ambient water and fish hard-part (i.e., otoliths) chemical composition enables assessment of movement patterns within and among river systems (Muhlfeld et al., 2012; Loewen et al., 2015) as well as origin of individuals in mixed-origin fisheries (Whitledge et al., 2007; Pangle et al., 2010; Veinott et al., 2012). Microchemical techniques have also provided new insight into alternative life-history strategies through assessment of movement patterns among and within species (Chase et al., 2015; Clarke et al., 2015; Smith and Kwak, 2016). Microchemical and isotopic signatures can facilitate assessment of population connectivity between tributary and main-stem habitats when differences in water
2. Methods 2.1. Study river-network The Missouri River is a highly altered large-river system characterized by armored banks (i.e., pylons, rip-rap, and boulders) and channelizing structures that create a swift and self-dredging channel to maintain navigation (Pegg et al., 2003). The hydrologic character of the Middle Missouri River (river kilometer [rkm] 1305–787) consists of elevated low-flow periods and limited seasonal variability in flows compared to pre-modification conditions (Pegg et al., 2003). The Platte River is a tributary of the Missouri River and is considered less impaired in comparison to the Middle Missouri River (Hamel et al., 2016). The Platte River is characterized by a relatively unrestricted wide channel intertwining with shifting sandbar complexes. The flow regime of the 2
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Platte River is, however, subject to hydropeaking flows as well as periods of no-flow (Spurgeon et al., 2016). Limited information exists regarding the origin of large-river fishes in the Platte River. Therefore, understanding the prevalence of mixing of individuals in the Platte River from differing environments will provide information regarding sources of fishes in the Platte River as well as roles the Platte River may have in maintaining population structure of riverine fishes within the greater river network.
Table 1 Size summary (mm Total Length [TL]) of channel catfish used in microchemical analysis to determine origins. * indicates channel catfish taken from anglers in the middle Platte River.
2.2. Microchemistry data collection Water samples were collected using a syringe filtration technique according to Shiller (2003) from seven sample locations among four river systems including the Platte River (3 sites), Loup River (1 site), Elkhorn River (1 site), and Missouri River (2 sites; Fig. 1). Sample locations within river systems were grouped according to river segments that included the central Platte River (west of Loup and Platte river confluence; n = 9 water samples), middle Platte River (Loup River confluence to Elkhorn River confluence; n = 9 water samples), lower Platte River (Elkhorn River confluence to the Missouri River; n = 7 water samples), Loup River (near Genoa, NE; n = 9 water samples), Elkhorn River (near Waterloo, NE; n = 7 water samples), upper Missouri River (above Platte River confluence; n = 9 water samples), and the lower Missouri River (below Platte River confluence; n = 7 water samples). Water samples were collected in 2014 and 2015 from each location during base flow periods (i.e., late summer to early fall). Water sample kits were provided by the University of Southern Mississippi’s Trace Analysis Lab. Details on preparing sample kits can be found in Shiller (2003), and included soaking all sample bottles and syringes in hot 1.2 M HCl baths for at minimum 8 h and rinsing with ultrapure distilled deionized water. Kits remained sealed until samples were obtained. Sample bottles and syringes were rinsed a minimum of three times with river water before extracting a water sample with a 250-ml high density polyethylene bottle. A subsample was extracted using a polyethylene 50-mL syringe (without a rubber seal). Approximately 10 mL of water was filtered as waste using a 0.45-μm syringe filter. The remainder of the subsample was filtered until a 15-mL polyethylene bottle was filled. Water samples were collected from all locations within 1–2 days and kept in refrigeration until shipment to the University of Southern Mississippi’s Trace Analysis Lab. Water samples were analyzed for elemental concentrations of Sr, Ba, Mg, Mn, and Ca using high resolution Inductively Coupled Plasma Mass Spectrometry (ICPMS; Thermo-Finnigan Element 2). Channel catfish Ictalurus punctatus lapilli otoliths (Long and Stewart, 2010) were collected from sample locations in the central Platte River, middle Platte River, lower Platte River, the Elkhorn River, and the upper Missouri River in late spring and summer 2015 (Fig. 1). Baited hoopnets were used to collect juvenile channel catfish (< 300 mm TL, Holland and Peters, 1992). Juvenile channel catfish were used to establish otolith signatures from the different river segments to reduce the risk of extensive movements by older individuals. Channel catfish otoliths were also collected from anglers within a 5 rkm reach of the lower Platte River near Fremont, NE (Latitude: 41.424231; Longitude: −96.539654). Angled channel catfish were targeted for approximately a five day period in late May 2015 using set-lines baited with live fathead minnows Pimephales promelas. Channel catfish anglers target larger individuals and provided an opportunity to assess potential migratory patterns and natal homing of sexually mature adults (Table 1). Otoliths were embedded on paraffin film strips using Buhler Epothin epoxy with sulcus up and the otolith rostrum pointing toward the film edge. Once dry, the otolith nucleus was located and marked dorsoventrally under a dissecting microscope. Otoliths were sectioned along the transverse plane immediately anterior (i.e., toward the rostrum) and posterior of the nucleus mark (approximately 2-mm) using a Buhler Isomet low-speed saw. Otolith sections were placed onto double sided tape in plastic rings with the posterior cut face down. Plastic rings were
River Segment
N
Mean TL
SE
Range
Elkhorn Missouri Central Platte Middle Platte Lower Platte Middle Platte*
5 7 8 14 9 30
155 196 222 185 178 630
6 25 20 20 13 15
141–170 129–283 100–276 89–292 107–235 436–744
back-filled with Buhler Epothin epoxy and air-dried for 48 h. Otolith surfaces were cleaned and polished in a sequential process involving hand polishing with both 30- and 9-μm lapping film and with a 1- and 0.05- μm disk with a 0.1-μm aluminum oxide paste. Otoliths were ultrasonically cleaned between each polish step. Microchemical analysis of channel catfish otoliths was performed by ablating the surface of the otolith with a New Wave Research UP-213 laser and measuring elemental concentrations with a ThermoFinnigan Element-2 ICPMS. Ablation occurred across the diameter of the otolith surface passing through the primordium. A warm-up period of 150 s was used between successive samples, and gas blanks were analyzed within the last fifty seconds of each warm-up. The beam size used was 30-μm with a scanning speed of 2-μm/s and a fluence of 3.5-4J/cm2. A NIST610 glass standard was ran at the start of laser analysis and approximately every 1.5 h following; an average standard value was taken to correct for instrument drift. Elements assessed included Sr, Ba, Mg, Mn, and Ca. The otolith edge and primordial (i.e., near primordium) regions of each otolith were assessed to obtain an estimate of recent environmental signatures and natal environmental signatures for each channel catfish. 2.3. Statistical analysis Water and fish hard-part structures grouped by river segment and were assessed using univariate and multivariate methods. Visual inspection of the data and test of normality (i.e., Shapiro-Wilks test) indicated deviation from normality for both water and otolith data. Thus, log10-transformation of elemental concentrations was done and normality was achieved for otolith data expect for Ba. Normality was not achieved for water data; however, graphical inspection (i.e., normal distribution quantile–quantile plots) of both water and otolith Ba data suggested only minor deviation from normality and thus we proceeded with parametric tests (Ramsay et al., 2011). A single-factor analysis of variance (ANOVA) followed by Tukey’s HSD test for multiple comparisons was used to assess differences in individual water and otolith mean elemental concentrations among river segments (Zeigler and Whitledge, 2011). A multivariate analysis of variance (MANOVA) was used to assess differences in both water and otolith elemental concentrations among river segments. Individual contrasts were performed using MANOVA between each river segment (e.g., central Platte River vs. lower Platte River). A Bonferroni correction was used to adjust significance levels and reduce type I error rate when performing multiple comparisons. An alpha value of 0.002 and 0.005 was used in MANOVA pairwise comparison tests for differences in water microchemistry and channel catfish otolith microchemistry among river segments. A classification tree modelling approach was used to separate juvenile channel catfish based on river segment of capture (Mercier et al., 2011). Otolith edge data (mean of outer 10 s of laser ablation; approximately 30 μm) from juvenile channel catfish was used to characterize the recent river segment inhabited by individuals (Zeigler and Whitledge, 2011; Schoen et al., 2016). The outer edge data represented approximately the last year of life for our sampled channel catfish. Classification trees were built using recursive partitioning in the rpart 3
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River (P = 0.9024); the lower Platte River and the middle Platte River (P = 0.7245); the lower Missouri River and the middle Platte River (P = 0.1843). Comparisons among segments indicated Mg differed among all segments except between the central Platte River and the Elkhorn River (P = 0.4767) as well as the upper Missouri River (P = 0.9781) and lower Missouri River (P = 0.9953); the Elkhorn River and the upper Missouri River (P = 0.0789) and lower Missouri River (P = 0.1638); the upper and lower Missouri River (P = 0.9999). Evidence suggests Mn may be under significant physiological control and thus may be limited in assessing origin of freshwater fishes (Turner and Limburg, 2015). Additionally, the Elkhorn River was the only river segment were Mn differed between a few river segments (i.e., Loup River; middle Platte River; lower Platte River). We, therefore, did not use Mn to assess differences in otolith microchemistry among river segments due to the low variability among sites and the susceptibility to physiological control. The middle and lower Platte River as well as their tributaries (i.e., the Loup River and the Elkhorn River) displayed elevated Ba signatures compared to the central Platte River and the upper and lower Missouri River (Fig. 2). In contrast, the middle and lower Platte River displayed lower Sr signatures compared to the central Platte River and the upper and lower Missouri River (Fig. 2). Water microchemistry signatures differed among river segments using the combination of Sr, Ba, and Mg (MANOVA, Wilks = 0.001, NumDF = 18, DenDF = 130.59, P < 0.0001). Multivariate comparisons among river segments were all significant (Table 2).
package (Therneau et al., 2015) in Program R (R Core Team, 2015). Classification tree methods repeatedly split the data into increasingly homogenous groups (e.g., river segments) using combinations of explanatory variables (e.g., otolith chemical signatures; Breiman et al., 1984). A splitting criterion based on the Gini impurity index (De’ath and Fabricius, 2000) was used, and the smallest tree within 1 standard error of the tree with the lowest classification error as determined using 10-fold cross-validation was selected (Brieman et al., 1984). Variable importance was assessed using a goodness-of-split criterion based on the classification accuracy when the variable was used as either a primary or surrogate splitting variable (scaled to sum to 100; Therneau et al., 2015). The classification tree model was applied to predict recent environmental signatures and natal origins of angled channel catfish. The area of each otolith corresponding to the first year of growth was isolated to obtain an estimate of natal microchemistry signatures.
3. Results 3.1. Water microchemistry Univariate tests among river segments indicated Sr (ANOVA, NumDF = 6, DenDF = 48, F = 68.64,P < 0.0001), Ba (ANOVA, NumDF = 6, DenDF = 48, F = 80.81, P < 0.0001), Mg (ANOVA, NumDF = 6, DenDF = 48, F = 162.7, P < 0.0001), and Mn (ANOVA, NumDF = 6, DenDF = 48, F = 4.94, P < 0.001) were significantly different among river segments (Fig. 2). Comparisons among segments using Tukey’s HSD indicated Sr differed between all segments except between the central Platte River and the upper Missouri River (P = 0.1968); the Elkhorn River and the lower Platte River (P = 0.9971) and middle Platte River (P = 0.5992); the lower and middle Platte River (P = 0.9191); the lower and upper Missouri River (P = 0.8482). Comparisons among segments indicated Ba differed between all segments except between the central Platte River and the upper Missouri River (P = 0.7378); the lower Platte River and the Loup
3.2. Juvenile channel catfish otolith microchemistry Sampled juvenile channel catfish had mean length of 189 mm TL (SE = 9). Univariate tests of otolith microchemistry signatures indicated Ba (ANOVA, NumDF = 4, DenDF = 38, F = 12.66, P < 0.0001), Sr (ANOVA, NumDF = 4, DenDF = 38, F = 5.187, P = 0.0019), and Mg (ANOVA, NumDF = 4, DenDF = 38, F = 4.818, P = 0.0031) varied by river segment. Comparisons among segments Fig. 2. Comparison of water microchemistry signatures from the central Platte River (CP), Loup River (LOUP), middle Platte River (MP), Elkhorn River (ELK), lower Platte River (LP), upper Missouri River (UMR), and lower Missouri River (LMR). Samples were collected from each site in both 2014 and 2015. The horizontal solid line within boxes is the median value, boxes represent the interquartile range, and whiskers are the 95% confidence intervals. Points represent data beyond the 95% confidence interval. Measurements are in parts per million (ppm).
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Table 2 Multivariate analysis of variance comparisons of water microchemistry signatures among river segments. River segments include the central Platte River (CP), the lower Platte River (LP), the upper Missouri River (UMR), the lower Missouri River (LMR), the lower Loup River (LOUP), and the lower Elkhorn River (ELK). A Bonferroni correction was used to adjust significance level to 0.002. An * indicates a significant difference between river segments. Comparison
Wilk’s λ
NumDF
DenDF
MP vs. CP MP vs. UMR MP vs. ELK MP vs. LOUP MP vs. LMR MP vs. LP LP vs. CP LP vs. UMR LP vs. ELK LP vs. LOUP LP vs. LMR CP vs. ELK CP vs. UMR CP vs. LMR CP vs. LOUP UMR vs. ELK UMR vs. LOUP UMR vs. LMR LMR vs. LOUP LMR vs. ELK LOUP vs. ELK
0.0233 0.0175 0.0174 0.0511 0.0208 0.1387 0.0087 0.0251 0.1066 0.0165 0.0327 0.0050 0.0702 0.0086 0.0059 0.0257 0.0069 0.0794 0.0078 0.0232 0.0118
3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
12 14 12 14 12 12 10 12 10 12 10 10 12 10 12 12 14 12 12 10 12
Table 3 Classification matrix for channel catfish < 300 mm TL used to build the classification tree model. River segments include the central Platte River (CP), the middle Platte River (MP), the Elkhorn River (ELK), the lower Platte River (LP), and the upper Missouri River (UMR). Sampled Predicted CP MP ELK LP UMR Accuracy:
P-value < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.001* < 0.0001* < 0.0001* < 0.001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001* < 0.0001*
CP 7 0 1 0 0 88%
MP 3 11 0 0 0 79%
ELK 0 1 4 0 0 80%
LP 1 4 0 4 0 44%
UMR 2 0 0 0 5 71%
otolith microchemistry signatures sampled from the upper Missouri River differed from those sampled in the Elkhorn River (MANOVA, Wilks = 0.11937, NumDF = 3, DenDF = 8, P = 0.0004). Accuracy of the classification tree model for juvenile channel catfish ranged from 44% to 88% (Table 3). The classification tree model had the greatest classification accuracy for juvenile channel catfish sampled in the central Platte River, the Elkhorn River, and the middle Platte River (Table 3). The greatest difficulty in classifying individuals back to their location of capture was for the lower Platte River where the model largely split individuals between the lower Platte River and the middle Platte River (Table 3). The first split within the classification tree separated channel catfish into two groups consisting of individuals from the middle and lower Platte River as well as the Elkhorn River from those located in the central Platte River and the upper Missouri River (Fig. 3). Further refinement of classification between the middle and lower Platte River and the Elkhorn River was achieved by differences in Ba and Mg levels between these segments. Further refinement of classification between the central Platte River and the upper Missouri river was achieved by differences in Sr levels between these two segments. The most influential variable differentiating channel catfish otolith signatures by river segment was Ba (importance score = 43), followed by, in decreasing order of importance, Sr (importance score = 34), and Mg (importance score = 23).
using Tukey’s HSD indicated Sr differed between the Elkhorn River and the central Platte River (P < 0.001) as well as the middle Platte River (P = 0.0477). Comparisons among river segments indicated Ba differed among all river segments except between the upper Missouri River and central Platte River (P = 0.9818); the Elkhorn River and the middle Platte River (P = 0.1810) and the lower Platte River (P = 0.5885); the lower Platte River and the middle Platte River (P = 0.1810). Comparisons among river segments indicated Mg differed between the Elkhorn River and the central Platte River (P = 0.0220), the middle Platte River (P = 0.0021), the lower Platte River (P = 0.0095), and the upper Missouri River (P = 0.0036). Otolith microchemistry signatures differed among river segments using the combination of Sr, Ba, and Mg signatures (MANOVA, Wilks = 0.20317, NumDF = 12, DenDF = 95.53, P < 0.0001). Juvenile channel catfish sampled in the middle Platte River had different otolith microchemistry signatures compared to those individuals sampled in the Missouri River (MANOVA, Wilks = 0.32465, NumDF = 3, DenDF = 17, P = 0.0002).However, juvenile channel catfish sampled in the middle Platte River did not have different otolith microchemistry signatures compared to those individuals sampled in the lower Platte River (MANOVA, Wilks = 0.76482, NumDF = 3, DenDF = 19, P = 0.1562), the central Platte River (MANOVA, Wilks = 0.63492, NumDF = 3, DenDF = 18, P = 0.0386), or the Elkhorn River (MANOVA, Wilks = 0.46863, NumDF = 3, DenDF = 15, P = 0.0084). Juvenile channel catfish sampled in the lower Platte River had different otolith microchemistry signatures compared to those individuals sampled in the upper Missouri River (MANOVA, Wilks = 0.32503, NumDF = 3, DenDF = 12, P = 0.0029) and central Platte River (MANOVA, Wilks = 0.22927, NumDF = 3, DenDF = 13, P = 0.0001). In contrast, juvenile channel catfish microchemistry signatures in the lower Platte River did not differ from those individuals sampled in the Elkhorn River (MANOVA, Wilks = 0.38063, NumDF = 3, DenDF = 10, P = 0.01786). Juvenile channel catfish otolith microchemistry signatures sampled from the central Platte River differed from those sampled in the Elkhorn River (MANOVA, Wilks = 0.068742, NumDF = 3, DenDF = 9, P < 0.0001), but not from those individuals sampled in the upper Missouri River (MANOVA, Wilks = 0.48665, NumDF = 3, DenDF = 11, P = 0.04116). Juvenile channel catfish
3.3. Angled channel catfish otolith microchemistry Angled channel catfish had a mean length of 630 mm TL (SE = 15), and displayed unique microchemistry signatures across their life-
Fig. 3. Classification rule used to separate channel catfish among river segments. The classification tree was built using rpart() in Program R; tree pruned at size = 5 with an cp of 0.098. The smallest tree that was within 1 standard error of the minimum error was selected. River segments include central Platte River (CP), middle Platte River (MP), Elkhorn River (ELK), lower Platte River (LP), and upper Missouri River (UMR). No channel catfish from the Loup River or lower Missouri River were sampled below our cutoff threshold of 300 mm TL for inclusion in the classification model.
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Fig. 4. Example cross-sections for Ba signatures across the otolith for two angled channel catfish exhibiting different origins and residency patterns. Channel catfish 18070 (long dash line) was predicted to have both a recent environmental signature and natal origin signature from the middle Platte River. Channel catfish 18070 appears to have remained in the middle Platte River throughout its life. In contrast, channel catfish 19632 (short dash) was predicted to have a natal origin signature from the middle Platte River, but a recent environmental signature from the upper Missouri River. Channel catfish 19632 appears to have migrated out of the middle Platte River to the upper Missouri River before returning to the Middle Platte River where the individual was caught. The horizontal solid line indicates the cutoff value for Ba values in the classification tree model separating the middle and lower Platte River and Elkhorn River from the rest of the river network. Both cross sections represent ablation across the entire otolith from edge (distance = 0) to edge (maximum distance) crossing through the primordium indicated by arrow at top of figure.
central Platte River and the upper Missouri River. As such, otolith microchemistry may be particularly useful for assessing mixing of individuals from the lower and middle Platte River with individuals from the central Platte River and Missouri River. Consistent differences in water chemistry among river segments through time is needed to assess origins of individuals from differing year classes (Pracheil et al., 2014). The differences in water microchemistry between river segments were consistent across a two-year period suggesting temporal stability during this study. Additionally, Sr and Ba levels measured in this study were consistent with long-term (i.e., 1983–2015) water samples collected in the lower Platte River (unpublished data from Louisville, NE collected by USGS National Water-Quality Assessment Program). A greater spatial coverage of microchemistry signatures may, however, be needed to assess the uniqueness of the middle and lower Platte River signatures across greater spatial scales of the river network to assess potential contributions of individuals from the Platte River to the Missouri River. Complex population structure may exist among main-stem and tributary habitats within large-river networks (Duponchelle et al., 2016). For instance, Humston et al. (2010) suggested substantial mixing between tributary and main-stem river environments for smallmouth bass Micropterus dolomieu may drive population dynamics between the two systems. The occurrence of channel catfish angled in the middle Platte River that recently resided in the upper Missouri River suggests a portion (e.g., approximately 30% of angled individuals in this study) of channel catfish are from mixed-origins and are using both systems. Channel catfish are considered a mobile species (Pugh and Schramm, 1999; Wendel and Kelsch, 1999) and have displayed movement patterns between main-stem river systems and tributaries (Dames et al., 1989; Newcomb, 1989) as well as between lake environments and tributaries (Butler and Wahl, 2011; Siddons et al., 2017). Pellett et al. (1998) suggested movement patterns based on mark-recapture data between the Mississippi River and the Wisconsin River may be linked to reproduction. The timing of sample collection in this study is aligned
history reflective of movement between river systems (Fig. 4). Angled channel catfish were predicted to have recently inhabited the middle Platte River (n = 15, 50%), the upper Missouri River (n = 9, 30%), the central Platte River (n = 3, 10%), the Elkhorn River (n = 2, 6%) and the lower Platte River (n = 1, 3%). Natal microchemical signatures suggested 66% (20/30) of the angled channel catfish originated from the middle Platte River. The remaining individuals were predicted to have natal signatures from the lower Platte River (n = 9) and the upper Missouri River (n = 1).
4. Discussion Microchemical approaches may be a beneficial tool for use in predicting origins and prevalence of mixing of channel catfish among river segments in the Platte and Missouri river systems. Differences existed in both water and channel catfish otolith chemical signatures among river segments and suggests Ba, Sr, and Mg together may serve as chemical markers to differentiate individuals based on movement among river segments. Previous works have also effectively used similar chemical markers to assess origins and movements of several freshwater fish species (Wells et al., 2003; Clarke et al., 2015). The river segments among which movement may be assessed, however, could be limited by similarities in water chemistry. For instance, elemental signatures of Sr and Ba in water did not vary between the middle and lower Platte River. The greater error in classification of juvenile channel catfish between the middle and lower Platte River was likely due to similarities in water chemistry or a prevalence of movement between these two river segments by juveniles. Water chemistry signatures in the middle and lower Platte River and their tributaries (i.e., Loup and Elkhorn rivers) did, however, exhibit greater Ba and less Sr when compared to the central Platte River and the Missouri River. The classification model was able to differentiate individual channel catfish sampled from the lower and middle Platte River from those individuals sampled in the 6
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maintaining population distribution in North American river-networks (Pellett et al., 1998; Laughlin et al., 2016). Microchemistry techniques can facilitate linking movement patterns of large-river fishes and the spatial and temporal scales of management needed (Humston et al., 2010; Porreca et al., 2016). As such, management and conservation strategies of large-river fishes may benefit from consideration of population connectivity across spatial scales and the different roles that some habitats (e.g., tributaries) hold in maintaining population structure across the river-network.
with both the pre-spawning and spawning period of channel catfish (May to June; Pellett et al., 1998; Hubert, 1999), and both ripe males and females were observed (JJ Spurgeon, personal observation; 81% of individuals had visible and developed gametes). Therefore, the premise that mixture of channel catfish from different river segments in the middle Platte River is a consequence of spawning movement is plausible and corroborates previous tag-based approaches assessing channel catfish movement (Newcomb, 1989; Pellett et al., 1998). Channel catfish caught by anglers from the middle Platte River predominately possessed natal origin signatures from both the middle and lower Platte River with only one individual possessing natal signatures from the Missouri River. Spawning and recruitment of channel catfish in large tributary environments may contribute recruits to larger main-stem systems (Laughlin et al., 2016). As such, movement of adults into tributary systems for reproduction as well as the potential for tributary recruits to move into main-stem environments may blur distinct population boundaries and necessitate examining population processes across greater spatial scales (Pugh and Schramm, 1999; Laughlin et al., 2016; Siddons et al., 2017). For instance, movement from natal habitats has been shown to support population structure of freshwater fishes in both riverine and lentic environments (Norman and Whitledge, 2015; Brodnik et al., 2016). Harvest regulations may have unintended consequences if not applied at appropriate spatial or temporal scales (e.g., protection not afforded to reproductive individuals; Siddons et al., 2017). However, the mixed-origin composition of channel catfish is rarely given consideration when examining alternative harvest strategies and the sustainability of populations to both recreational and commercial harvest (Beultmann and Phelps, 2015; Eder et al., 2016). Our results suggest management recommendations for channel catfish may need to consider the potential mixed-origins of individuals within a river segment. For instance, channel catfish recently inhabiting the Missouri River are harvested by anglers in the Platte River. Therefore, management actions taken solely within the Missouri River (e.g., size limits), may not afford protection to larger individuals moving into the Platte River. Movement from natal habitats may also contribute individuals throughout a river network (Humpson et al., 2010; Duponchelle et al., 2016). Of the nine angled channel catfish with recent environmental signatures from the upper Missouri River, all except one individual was classified as having natal origins from the middle or lower Platte River. As such, channel catfish from the Platte River may be contributing individuals to the Missouri River. Additionally, channel catfish may be exhibiting a degree of homing behavior. Homing has been quantified for some catfish species (Duponchelle et al., 2016), and has been suggested for channel catfish (Pellet et al., 1998). Further investigation regarding recruitment sources among tributary and mainstem habitats and the propensity of movement among such habitats using otolith microchemistry may shed light on the interdependence of channel catfish population dynamics among different habitat types in riverine-networks (Schlosser and Angermeier, 1995). However, physiological and environmental changes may influence the allocation of trace elements within fish otoliths (Sturrock et al., 2015; Turner and Limburg, 2015). As such, information regarding changes in otolith trace element composition of channel catfish resulting from changes in lifestage (e.g., sexual maturity) or environmental stressors (e.g., drought) may be needed. Though the presence of multiple calcium carbonate phases (vaterite and aragonite) within otoliths may influence microchemical signatures (Melancon et al., 2005), the differences in partitioning of trace elements such as Sr into vaterite and aragonite are understood. Additionally, trace elemental signatures of channel catfish from across different otolith sections have been used to assign origin and assess environmental history (Laughlin et al., 2016). Management and conservation of large-river catfishes and largeriver fishes in general may depend on assessing the large-scale spatial complexity of population structure (Hogan, 2011; Cooke et al., 2016). For channel catfish, spatially explicit recruitment dynamics along with wide-ranging movement patterns may be important mechanisms in
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