Abstract
Limited information exists on 24-hr movement and habitat selection patterns of stream dwelling smallmouth bass, Micropterus dolomieu. We monitored the 24-hr movement patterns of smallmouth bass in an Ozark river during three seasons: summer, autumn, and winter. During each season, fish were located every two hours throughout a 24-hr period; habitat data and water depth were collected at each fish location. Four random points representing available locations around each fish location were generated in ArcGIS. Habitat and depth data were collected at each of these points, and discrete choice models were fit to the data to predict habitat and depth selection by smallmouth bass. No significant differences in movement across seasons or time of day were evident, although the greatest observed displacement within a 2-hr tracking period occurred during the winter, with one bass moving over 630 m. Across all three seasons, water depth and habitat type were strong predictors of bass locations. Throughout our study, water depths used by smallmouth bass ranged from 0.6 to 3.7 m. Although depth of water used by fish did not differ by time of day, fish used the deeper waters of Big Spring during the winter and intermediate depths during the summer and autumn. Smallmouth bass utilized several habitat types; however, bass selected boulders more frequently in all seasons than any other available habitat type. Our work provides additional insight into smallmouth bass behavior that will help guide future management.
Introduction
Despite a rich history of research on smallmouth bass (Micropterus dolomieu), there has been limited work on their 24-hr movement and many specific questions remain regarding movement patterns and habitat use by smallmouth bass in rivers and streams (Lyons & Kanehl Citation2002). Previous studies suggest smallmouth bass populations display geographic variability in seasonal and daily movement patterns. For example, smallmouth bass daily movement varied seasonally in the Jacks Fork River, Missouri with most activity occurring during crepuscular periods (Todd & Rabeni Citation1989), whereas smallmouth bass movement did not seem to be influenced by seasons in a Michigan river system (Beam Citation1990). Gerber and Haynes (Citation1988) found smallmouth bass in tributaries of Lake Ontario to be most active throughout the day with little to no activity during nighttime periods. In general, warmer water temperatures appear to trigger increased activity whereas colder waters reduce smallmouth bass activity, as seen in an Ontario lake (Suski & Ridgway Citation2009a). A more thorough understanding of 24-hr movement trends and how they vary across seasons and latitudes would be beneficial to the future development of localized monitoring protocols for stream-dwelling smallmouth bass.
Smallmouth bass habitat and water depth selection tendencies vary depending on the aquatic systems monitored (Angermeier & Karr Citation1984; Rankin Citation1986; Lyons Citation1991). Smallmouth bass did not select for any single habitat type in an Illinois stream (Larimore et al. Citation1952) or Tennessee reservoir (Hubert & Lackey Citation1980), whereas studies in Ozark streams found that smallmouth bass generally selected boulders, woody debris, or undercut banks (Probst et al. Citation1984; McClendon & Rabeni Citation1987; Todd & Rabeni Citation1989; Fore et al. Citation2007). When examining depths of water used by smallmouth bass, Todd and Rabeni (Citation1989) found that intermediate depths generally greater than 0.6 m were selected by smallmouth bass while shallower depths were avoided. Fore et al. (Citation2007) also found intermediate depths (∼1 m) were preferred by smallmouth bass in the summer. Munther (Citation1970) and Coble (Citation1975) noted increased water depths being used by smallmouth bass as water temperatures decreased. Due to the complexity of smallmouth bass habitat and water depth selection patterns in streams, our ability to define locally important habitat metrics for management purposes is limited.
Although smallmouth bass are thought by many to be sedentary species (Funk Citation1957; Fajen Citation1962; Coble Citation1975; Todd & Rabeni Citation1989), recent work documented substantial movement by individuals in the Current River and one of its tributaries, the Jacks Fork River located in the Ozark Highlands ecoregion of Missouri (Westhoff et al. Citation2014 ). Considering the mobility of Ozark populations relative to other populations of smallmouth bass, we sought to document the 24-hr movement patterns of Ozark smallmouth bass. The primary objectives of this study were to (1) monitor smallmouth bass 24-hr movement patterns in the Current River across three seasons: summer, autumn, and winter, and (2) determine which habitats and depths were selected by these smallmouth bass, and whether selection varied throughout the day or seasonally. By documenting smallmouth bass movement tendencies and habitat selection patterns in an Ozark river exhibiting groundwater and surface water interactions, we were able to develop habitat selection models across three seasons for smallmouth bass existing in this unique system.
Methods
Study site
The Current River, located in southern Missouri and northern Arkansas within the Ozark Highlands eco-region, spans nine Missouri counties and is within a karst landscape comprised primarily of hardwood woodlands and glades mixed with pine. The river is sixth order at the study site and has an average channel gradient of 0.74 m/km. Discharge at the upper end of the study site varied from 33.6 m3/s (±0.59 SE) in the summer to 25.7 m3/s (±1.13 SE) during autumn and 23.7 m3/s (±0.02 SE) during winter (USGS Citation2012). We monitored fish movements within a 9.2 km stretch of the Current River that included the confluence of Big Spring branch and the Current River (Figure 1). Big Spring contributes approximately 12.5 m3/s of flow to the Current River, with near constant water temperatures ranging from 13 °C to 15 °C (Imes et al. Citation2007), strongly influencing the thermal regime within this stretch of the river. The outflow from Big Spring travels 600 m down the spring branch (46 m mean width) before emptying into the Current River. Big Spring contributes an estimated 31% of the Current River discharge (Mugel et al. Citation2009). The Big Spring and Current River confluence width measured about 90 m with an average river width of 65 m throughout the study site.
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08 April 2015Figure 1. Lower Current River depicting the 9.2 km study area which includes the confluence of Big Spring in Carter and Ripley counties of southeastern Missouri.
Figure 1. Lower Current River depicting the 9.2 km study area which includes the confluence of Big Spring in Carter and Ripley counties of southeastern Missouri.
Fish tagging
In January 2011, 30 smallmouth bass (TL range = 305–457 mm) were collected at the confluence of Big Spring and the Current River using pulsed DC electrofishing as part of a separate study examining seasonal movement and use of springs by smallmouth bass in the Current River. For that study, individuals were surgically implanted with trailing whip antenna radio tags (Nanotags NTC 6-2 beeper tags, 164–168 MHz, 4.5 gram weight, battery life of 375 days, LOTEK Wireless Inc. Ontario, Canada) following standard procedures for freshwater fishes (Hart & Summerfelt Citation1975; Liedtke & Rub Citation2012). Tag size was limited to no more than 2% of the mass of the smallest smallmouth bass in the study (Winter Citation1983; Bridger & Booth Citation2003). Of the 30 smallmouth bass captured and tagged for that study, 7 individuals located adjacent to the spring confluence were monitored in our evaluation of 24-hr movement and habitat selection. Prior tracking experience suggested that a maximum of 7 individuals could be safely tracked by boat within each 2-hr period, limiting our sample size.
Fish tracking
Smallmouth bass locations were documented using a GPS unit throughout a single 24-hr period during the summer (16 August) and autumn (11 October) of 2011, and winter (17 January) of 2012. During the winter tracking session, our smallmouth bass numbers were reduced to four fish due to mortality. To increase our sample size for habitat modeling during the winter season, we added one smallmouth bass from the 30 initially tagged fish bringing our number of tracked fish up to five. This individual was selected for inclusion because it was located near the remaining cohort of fish.
During each 24-hr tracking event, smallmouth bass locations were determined via triangulation every 2-hr using a SRX600 telemetry receiver (LOTEK Wireless, Inc., Ontario, Canada) equipped with a three-element Yagi antenna (Eiler Citation2012). Water depth (m) and physical habitat type were documented at each fish location. Possible physical habitat types included open water, boulders, logs/woody debris (hereafter logs), aquatic vegetation, overhanging vegetation, and all combinations of these habitat types. We recorded time of day and classified each time period as either day (sunrise until sunset) or night (sunset until sunrise).
After smallmouth bass locations were determined, we used ArcGIS 9.3 (ESRI, Redlands, CA) to create a convex polygon centered on each fish location to delineate the area of available habitat. Size of the polygon was set as twice the maximum distance moved by any individual bass during each season allowing inclusion of all habitats available to that individual at that time (Cooper & Millspaugh Citation1999). Four random points were selected within each polygon to represent available locations. At each of those points, habitat type and water depth data were collected.
Analysis and modeling
Using location data collected during each 2-hr tracking event, we calculated the observed displacement of smallmouth bass as the distance between the individual's location in two subsequent tracking events. A repeated measures analysis of variance with season as the repeated factor was employed (SAS Institute Inc., SAS 9.2, 2008) to examine differences in both observed displacement and depth used by smallmouth bass in day and night time periods. Only individuals tracked across all three seasons (four fish) were included in the analysis. If sphericity was not met based on Mauchly's test, a Huynh–Feldt correction was used for calculating degrees of freedom and determining p-value. Post hoc contrast statements were employed to compare time of day (day vs. night) within each season. An alpha of 0.05 was used to determine significance.
We developed nine a priori literature-based models representing hypotheses on variables influencing smallmouth bass habitat selection within each season (). We then determined water depths and habitat types present at fish locations (used) as well as randomly selected (available) locations (). Since smallmouth bass were not observed using aquatic vegetation or overhanging vegetation habitat types alone and had limited use (3% of total observations) of those same habitat types combined with other more widely used habitat types (e.g., aquatic vegetation/log combination), all habitat type data were retained but grouped into four primary categories for analysis (i.e., open water, boulder, log, and boulder/log). Dummy variable coding for the habitat variables required one class of habitat be removed from each model so it may be used as a reference; in our study, open water was used due to its prevalence across all seasons.
Table 1. List of a priori candidate models and the hypotheses they represent used for model selection (summer, autumn, and winter) in discrete choice analysis of habitat selection for smallmouth bass (Micropterus dolomieu). See Table 2 for abbreviations and definitions of model variables.
Table 2. Variables used during our assessment of habitat selection by smallmouth bass during 24-hr tracking. Abbreviations for the parameters (β*) and a description of each variable are given. Values of 0 or 1 indicate absence or presence, respectively, of a habitat type at each location. Boulder size follows Lane (Citation1947) classification of substrates.
We fit discrete choice resource selection models using habitat and depth data from smallmouth bass. Parameters were set using iterative maximum likelihood methods (Cooper & Millspaugh Citation1999). Like logistic regression, used and available locations are compared in discrete choice modeling; however, data from used and available locations are paired to account for temporal and spatial changes in resource availability. This unique pairing of used and available locations allowed us to better estimate resource availability and use in a dynamic stream system. As we developed our discrete choice resource selection models, each sample consisted of a ‘choice set’, or data that included the location of each smallmouth bass and four locations considered accessible to the individual (Cooper & Millspaugh Citation2001).
As described by Cooper and Millspaugh (Citation1999), the utility provided by the resource i to the individual j can be expressed as
where B′ is a vector of length m of estimable parameters determining an individual attribute's contribution to overall utility and Xij is a vector of length m of the attributes (continuous or categorical) of resource i as experienced by the individual j (e.g., boulder, log, boulder/log, open water, water depth). To determine the comparative utility, we then calculated the probability of an individual choosing a resource (choice probability function) as
where A is one of the total i resources available and j is the individual suggesting the resource providing the maximum utility/satisfaction to the individual will be chosen. The probability of selecting resource A is equal to the probability of the utility or satisfaction derived from resource A is greater than the satisfaction the individual will receive from the other available resources (Cooper & Millspaugh Citation1999). Using Akaike's Information Criterion (AIC), we adjusted for the small sample size using the AICC criteria (Burnham & Anderson Citation2002; Hu Citation2007). We identified the most parsimonious models for each season from among all the candidate models by selecting the models with ∆AICC values of less than 2 (Hu Citation2007). We selected the model with the fewest parameters in instances where more than one model was supported.
Model validation
The most supported discrete choice model within each seasonal data-set was identified using the AICC framework, but the process did not assess model accuracy. To address this issue, we used k-fold cross validation to estimate the accuracy of each of the top-ranked models for each season (Boyce et al. Citation2002; Westhoff & Rabeni Citation2013). We randomly selected 80% of our original input data-sets as the ‘training’ data and used the remaining 20% as the ‘test set’. This was done five times which created five replicate sets for each season. We then used the training data from each of the five sets to create new model parameters (βm) using the discrete choice analysis procedure explained above, but only for the top-ranked model as determined from the ΔAICC value comparison. Test data from the five replicate sets were applied to the new model parameters and used to create a probability of use value for each used and available record from each choice set. The used record probability of presence values were then either compared to the value from one randomly selected available location from its choice set (liberal method) or to all four available values (conservative method). In the liberal method, if the used value was greater than the randomly selected available value, the record was considered to be correctly classified. For the conservative method, the value of the used location had to be greater than all four available values in order for the record to be considered correctly classified. The percentage of each correctly classified record from each season was calculated and reported as the measure of model accuracy.
Results
During the summer and autumn we tracked seven smallmouth bass, generating a total of 77 and 84 used fish locations, respectively. Fish locations were not recorded from 0400 to 0600 during the summer tracking session due to severe weather. During the winter, five individuals were tracked resulting in the measurement of 59 used fish locations because one fish was not located during a single 2-hr tracking period.
There was substantial individual variation in smallmouth bass movement; observed displacement ranged from 1.7 to 251.6 m (mean = 36.3 m) during the summer, from 0.5 to 513.5 m (mean = 60.9 m) during autumn, and from 3.0 to 635.8 m (mean = 48.6 m) during the winter (Figure 2). Across all seasons, 2-hr mean observed displacement by smallmouth bass was 49.3 m. The observed displacement of bass during 2-hr observation periods did not vary across seasons (F = 1.73; corrected p = 0.20; corrected df = 1.2, 35.4). Furthermore, observed displacement of smallmouth bass tracked across all three seasons did not vary between day (mean ± 1 SE, 52.3 ± 10.8 m) and night (38.0 ± 14.6 m) periods (F = 0.58; p = 0.45; df = 1, 30). There was also no significant interaction between season and time of day that influenced bass movement patterns (F = 0.25; corrected p = 0.66; corrected df = 1.2, 35.4).
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08 April 2015Figure 2. Box plots of observed displacement (distance between an individual's location in two subsequent tracking events) through time for smallmouth bass tracked in the Current River, Missouri during 24-hr periods in summer, autumn, and winter. Values on the x-axis represent the time period when the movement took place (e.g., the data at 1000 represent observed displacement between 0800 and 1000). Shaded areas represent the period from sunset to sunrise. * = no data was collected during this time period.
Figure 2. Box plots of observed displacement (distance between an individual's location in two subsequent tracking events) through time for smallmouth bass tracked in the Current River, Missouri during 24-hr periods in summer, autumn, and winter. Values on the x-axis represent the time period when the movement took place (e.g., the data at 1000 represent observed displacement between 0800 and 1000). Shaded areas represent the period from sunset to sunrise. * = no data was collected during this time period.
Depth of water used by smallmouth bass varied by time of day (F = 8.10; p = 0.0075; df = 1, 33) and by season (F = 8.85; corrected p = 0.0006; corrected df = 1.8, 60.4) with no interaction between time of day and season (F = 1.66; corrected p = 0.2014; corrected df = 1.8, 60.4; Figure 3). Although depths selected by smallmouth bass during the summer (F = 0.03; p = 0.86) and autumn (F = 2.57; p = 0.12) did not differ between day and night, the depths of water used by smallmouth bass during winter varied based on time of day (F = 15.75; p = 0.0004). During the winter, smallmouth bass used deeper water during the day (mean ± 1 SE = 2.6 ± 0.11 m) than at night (1.9 ± 0.12 m). Across all seasons, smallmouth bass were never observed in water shallower than 0.6 m and in general selected with higher frequency intermediate depths (1 to 3 m; 77% of all observations).
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08 April 2015Figure 3. Box plots of seasonal depth values through time for smallmouth bass tracked in the Current River, Missouri during 24-hr periods in summer, winter, and autumn. Data show depth of water where smallmouth bass was located during that tracking session. Values on the x-axis represent the time period when the movement took place and shaded areas represent the period from sunset to sunrise. * = no data was collected during this time period.
Figure 3. Box plots of seasonal depth values through time for smallmouth bass tracked in the Current River, Missouri during 24-hr periods in summer, winter, and autumn. Data show depth of water where smallmouth bass was located during that tracking session. Values on the x-axis represent the time period when the movement took place and shaded areas represent the period from sunset to sunrise. * = no data was collected during this time period.
Candidate model 8 (water depth, boulder, log, and boulder/log habitat types) and candidate model 9 (global) received the most support in all three seasons (). Candidate model 8 received the greatest support in summer and autumn, and candidate model 9 received the most support in winter (). Because of the model selection uncertainty in the winter, we only considered parameter estimates from the model with the fewest parameters (Model 8) and did not further address Model 9. This also allowed us to more clearly compare model results across seasons. Odds ratios indicated that smallmouth bass positively selected deeper water in all seasons (). For every one-meter increase in depth, smallmouth bass were 3-times (summer and autumn) or 4.5-times (winter) more likely to select deeper water. For example, during the summer, smallmouth bass were 3-times more likely to select 2 m deep water over 1 m deep water and 6-times more likely to select 3 m deep water over 1 m deep water. Smallmouth bass use of habitat changed across seasons; habitat types were used most during the winter. Smallmouth bass were 36-times more likely to select boulders over open water during winter, 25-times more likely in the autumn, and 11-times more likely in the summer (). Compared to open water, smallmouth bass were 11-times more likely to select log habitat in winter, 8-times as likely to select logs in the autumn, and 4-times as likely to during the summer. Boulder/log combinations were selected by smallmouth bass more often than logs without boulders. Smallmouth bass selected boulder/log habitat 24-times more often than open water in the winter, 10-times as often in the autumn, and 5-times more often in the summer.
Table 3. Top candidate models selection results for smallmouth bass habitat selection across three seasons. Only the two most supported models are displayed for each season and all other models not displayed had a model weight (w) of <0.01. Selected models for each season (bold) had ΔAICC values of <2 and the fewest number of parameters. Model number from is shown in parentheses.
Table 4. Model parameter estimates for variables (β) including standard errors (SE ±) and odds ratios (ex) for smallmouth bass (Micropterus dolomieu) tracked over a 24-hr period in the Current River. Values were derived from the set of top-ranked models (summer, autumn, and winter) for the discrete choice modeling.
Model accuracy varied both among seasons and between the conservative and liberal k-fold cross-validation methods. The conservative approach contained what we consider the lowest accuracy percentages and ranged from 52% in the summer, 55% in the autumn, and 80% in winter. Across all seasons, model accuracy was estimated at 57%. Using the liberal approach, the percentages increased to 77% in the summer, 71% in autumn, and 88% in winter. Model accuracy was estimated at 82% across all seasons using this approach. The true accuracy of our models at predicting habitat use by smallmouth bass should occur between the values derived from the two methods (57%–82%).
Discussion
Smallmouth bass in our study moved both day and night (Figure 2), although previous work has shown reduced movement at night in some systems (Munther Citation1970; Helfman Citation1981; Gerber & Haynes Citation1988; Todd & Rabeni Citation1989). Previous work (Reynolds & Casterlin Citation1976; Todd & Rabeni Citation1989; Cole & Moring Citation1997; Lott Citation2000; Suski & Ridgway Citation2009b) has also documented increased movement during dawn and dusk periods but we did not observe such a pattern. On average, 24-hr smallmouth bass movements were not overtly large, yet some individuals moved over 500 m between 2-hr tracking events, expanding on past studies that observed limited movements by smallmouth bass (Munther Citation1970; Langhurst & Schoenike Citation1990); however, these studies tracked only intermittently and not continuously over an entire 24-hr period. Our observed displacement estimates were likely conservative, since we only measured fish locations at distinct times and our sample sizes were low. Furthermore, we only tracked individuals during the summer, autumn, and winter seasons although smallmouth bass in Ozark rivers tend to increase their movements during the spring (Todd & Rabeni Citation1989; Westhoff et al. Citation2014). Considering previous work on smallmouth bass movement patterns, it appears that movement may be system- or site-specific making it difficult to generalize movement patterns across systems as a whole.
Smallmouth bass movements were potentially influenced by environmental variables. Observed displacement between 2-hr tracking events during the summer averaged 36.3 m;this could have been due to an increase in day length since smallmouth bass are known to exhibit strong ‘cover-seeking’ behavior to avoid light sources (Coble Citation1975; Miller Citation1975; Edwards et al. Citation1983). During autumn, we observed the highest average displacement of 60.9 m. These displacement rates could be related to seasonal migration. In a concurrent study examining timing of fish movement and utilization of springs, 42% of individuals returned to an overwintering area near Big Spring (a large thermal refuge) in autumn. Winter observed displacement averaged 48.6 m, suggesting that fish had completed their seasonal migration to the thermal refuge by the time we monitored their movements in January. Smallmouth bass have been shown to seek out thermal refuges such as springs (Langhurst & Schoenike Citation1990; Peterson & Rabeni Citation1996) and seeps (Webster Citation1954) when available during the winter. Overall, our results conflict with Todd and Rabeni's (Citation1989) work on the Jacks Fork River that suggested smallmouth bass total movements were greatest in the summer and lowest during winter. The wider and deeper stream conditions available in our study site, the percent contribution of the spring to the river that stabilized water temperatures, or other environmental factors may have influenced movement patterns.
Two of the five remaining fish in our 24-hr study did not return to Big Spring during the winter. Previous studies from different regions found smallmouth bass movements were influenced by temperature fluctuations (Webster Citation1954; Todd & Rabeni Citation1989; Beam Citation1990; Siegwarth Citation1996; Tschantz et al. Citation2002). Winter air temperatures of 2011–2012 were considered mild with a statewide average temperature 5 °C to 7 °C above normal (Missouri Climate Center Citation2012). Warmer atmospheric conditions likely influenced water temperatures in the river and reduced the need for fish to move into overwintering sites, such as springs. Todd and Rabeni (Citation1989) and Westhoff et al. Citation2014 noted that not all Ozark smallmouth bass migrated to spring refugia during the winter, with several observed in the mainstem river throughout the year. Unfortunately, due to low sample sizes, we were not able to compare movement patterns of smallmouth bass that returned to the spring confluence with those that remained in the river during the winter months. Additional work may show that smallmouth bass utilizing thermal refuges tend to move more than those that remain in the colder waters of the river during winter months.
In general, depths utilized during the winter were deeper than those used during summer or autumn (Figure 3). This could be a result of the depths present near the spring confluence where most of the smallmouth bass overwintered. In this area, water depths were greater than in other adjacent sections of the river. However, smallmouth bass have been found to avoid shallow regions (Rankin Citation1986) and this remained true in our study as individuals were never found in depths shallower than 0.6 m. Earlier work on smallmouth bass concurred with our findings that, in general, smallmouth bass preferred intermediate depths (range used = 0.6 to 4.0 m compared to range available = 0 to 4.3 m depth) within the rivers they inhabit (Paragamian Citation1981; McClendon & Rabeni Citation1987; Todd & Rabeni Citation1989).
Habitats selected by smallmouth bass in our study area of the Current River did not differ among seasons. Both water depth and habitat types were important predictors of smallmouth bass habitat use. While it may be argued that smallmouth bass have no habitat preference (Edwards et al. Citation1983), individuals we monitored overwhelmingly selected for boulders across seasons (). From summer to winter, the odds of boulders being selected increased. Similar findings were documented by Todd and Rabeni (Citation1989) in the Jacks Fork River, a major tributary to the Current River. Whereas boulders were the primary habitat type selected in our study, woody debris and undercut banks appear to have value as well (Edwards et al. Citation1983; Todd & Rabeni Citation1989). Although undercut banks were extremely rare in our study area, we did monitor woody debris (logs) and it was also used by smallmouth bass. Use of woody debris and other habitat types increased at a lesser rate across seasons. Habitat selection by smallmouth bass appears to be driven primarily by prey and cover needs (Edwards et al. Citation1983; Rankin Citation1986; Bevelhimer Citation1996), although these behaviors are likely also influenced by large-scale habitat variables (Fajen Citation1962; Whitledge et al. Citation2006; Brewer et al. Citation2007; Dauwalter et al. Citation2007).
Discrete choice models have their origins in the social sciences (Ben-Akiva & Lerman Citation1985), but have more recently been used to examine habitat selection in fisheries and wildlife studies such as ours. Their initial applications were in terrestrial settings (Cooper & Millspaugh Citation2001), but several researchers have adopted the methods for questions related to aquatic systems. For example, discrete choice models have been used to examine habitat choice in hellbender salamanders (Cryptobranchus alleganiensis bishop; Bodinof et al. Citation2012), white crappie (Pomoxis annularis;Bajer et al. Citation2007), shovelnose sturgeon (Scaphirhynchus platorynchus; Bonnot et al. Citation2011), and freshwater crayfish (Westhoff & Rabeni Citation2013). Our model accuracy was estimated at 57%–82%, which is comparable to other discrete choice studies that reported model accuracy rates of 65%–77% (Bajer et al. Citation2007), 74%–91% (Bodinof et al. Citation2012), and 71%–84% (Westhoff & Rabeni Citation2013). The number of available choices in a choice set influences the outcome of the model validation procedure, which is why we took both a conservative and liberal approach. These prior studies and our work demonstrate a need to further develop validation procedures for discrete choice models.
Our work provides additional insight into smallmouth bass behavior that could be beneficial to management personnel. Based on our movement data, sampling for smallmouth bass to assess population densities and size structure may be most efficient during the summer when they move less, use shallower depths, and are less often in boulder cover. In the autumn, however, smallmouth bass movement increased potentially making sampling more difficult, especially if some type of mark and recapture sampling was utilized. In the winter, smallmouth bass were found at greater depths, suggesting that sampling those individuals may be more difficult. Lyons and Kanehl (Citation2002) determined that sampling in autumn and winter was difficult because of fish migrations and harsh weather conditions. As a result, winter months are often not considered when sampling many aquatic systems.
Our study reiterates the importance of boulder and woody debris to smallmouth bass. The presence of boulders in aquatic systems has been shown to have a positive correlation with standing fish stocks (Paragamian Citation1981; McClendon & Rabeni Citation1987). Programs to improve or increase boulder and woody debris habitat in streams could have a positive effect on smallmouth bass populations. Properly maintained riparian corridors improve steam conditions for smallmouth bass by shading the stream and providing woody debris (Schlosser Citation1991; Whitledge et al. Citation2006). Stream habitat improvements have also been shown to benefit other species (Roni et al. Citation2008). In our study, we only examined selection by adult smallmouth bass, but these practices will likely also improve habitat for juvenile bass. Many ecological factors contribute to smallmouth bass movement and habitat selection patterns within streams, resulting in regional and even stream-specific differences among smallmouth bass populations.
| Model ID | Hypothesis | Model structure |
|---|---|---|
| 1 | Positive influence of boulders | β1(HB)+ei |
| 2 | Positive influence of logs | β1(HL)+ei |
| 3 | Positive influence of boulders and logs | β1(HBL)+ei |
| 4 | Positive influence of depth | β1(Dm)+ei |
| 5 | Positive influence of boulder habitat as depth increases (interaction) | β1(HB)*β2(Dm)+β3(HB*Dm)+ei |
| 6 | Positive influence of log habitat as depth increases (interaction) | β1(HL)*β2(Dm)+β3(HL*Dm)+ei |
| 7 | Positive influence of boulder and log habitat as depth increases (interaction) | β1(HBL)*β2(Dm)+β3(HBL*Dm)+ei |
| 8 | Positive influence of habitat and depth | β1(HB)+β2(HL)+ β3(HBL)+β4(Dm)+ei |
| 9 | Positive influence of habitat as water depth increases (interaction) | Global model |
| Β | Description | Range |
|---|---|---|
| HO | Open water consisting of sand, gravel, and cobble | 0 or 1 |
| HB | Boulder with diameter > 256 mm | 0 or 1 |
| HL | Woody debris consisting of logs and root wads | 0 or 1 |
| HBL | Boulder/log combination | 0 or 1 |
| Dm | Water depth (m) | 0–5 (m) |
| E | Random effect for individual |
| Models | Model (number) | n | K | AICC | ∆AICC | w |
|---|---|---|---|---|---|---|
| Summer | Depth and habitat type (8) | 77 | 5 | 187.75 | 0.00 | 0.96 |
| Global (9) | 77 | 8 | 194.12 | 6.38 | 0.04 | |
| Autumn | Depth and habitat type (8) | 84 | 5 | 176.14 | 0.00 | 0.97 |
| Global (9) | 84 | 8 | 182.98 | 6.84 | 0.03 | |
| Winter | Global (9) | 59 | 8 | 68.71 | 0.00 | 0.55 |
| Depth and habitat type (8) | 59 | 5 | 69.14 | 0.43 | 0.45 |
| Models | β | Estimate | SE± | ex |
|---|---|---|---|---|
| Summer | H0* | – | – | – |
| Dm | 1.13 | 0.21 | 3.09 | |
| HB | 2.36 | 0.57 | 10.62 | |
| HL | 1.32 | 0.41 | 3.76 | |
| HBL | 1.57 | 1.01 | 4.79 | |
| Autumn | H0* | – | – | – |
| Dm | 1.01 | 0.27 | 2.73 | |
| HB | 3.22 | 0.62 | 25.04 | |
| HL | 2.07 | 0.32 | 7.94 | |
| HBL | 2.3 | 4.76 | 9.97 | |
| Winter | H0* | – | – | – |
| Dm | 1.50 | 0.34 | 4.5 | |
| HB | 3.58 | 0.84 | 35.80 | |
| HL | 2.37 | 0.92 | 10.68 | |
| HBL | 3.17 | 1.03 | 23.75 |
Acknowledgements
The authors thank Missouri Department of Conservation staff (J. Ackerson, D. Baldridge, L. Ball, J. Capps, D. Mayers, A. Pratt, M. Scott, C. Steen, A. Turner, and B. Vandiver) for field support throughout this study.
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
Funding for this work was provided by Fisheries and Resource Science Divisions of the Missouri Department of Conservation, the Heartland Inventory and Monitoring Network of the National Park Service (HTLN), and a Missouri State University graduate research grant awarded to SAED by the HTLN.
References
- Angermeier FL, Karr JR. 1984. Relationships between woody debris and fish habitat in a small warm water stream. Trans Am Fish Soc. 113(6):716–726. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Bajer PG, Millspaugh JJ, Hayward RS. 2007. Application of discrete choice models to predict white crappie temperature selection in two Missouri impoundments. Trans Am Fish Soc. 136:889–901. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Beam JD. 1990. Daily and seasonal movement, as related to habitat use of smallmouth bass in the Huron River, Michigan [Master's thesis]. Ann Arbor (MI): University of Michigan. [Google Scholar]
- Ben-Akiva M, Lerman SR. 1985. Discrete choice analysis: theory and application to travel demand. Cambridge (MA): MIT Press. [Google Scholar]
- Bevelhimer MS. 1996. Relative importance of temperature, food, and physical structure to habitat choice by smallmouth bass in laboratory experiments. Trans Am Fish Soc. 125(2):274–283. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Bodinof, CM, Briggler JT, Junge RE, Beringer J, Wanner MD, Schuette CD, Ettling J, Millspaugh JJ. 2012. Habitat attributes associated with short-term settlement of Ozark hellbender (Cryptobranchus alleganiensis bishopi) salamanders following translocation to the wild. Freshwater Biol. 57:178–192. [Crossref], [Web of Science ®], [Google Scholar]
- Bonnot TW, Wildhaber ML, Millspaugh JJ, DeLonay AJ, Jacobson RB, Bryan JL. 2011. Discrete choice modeling of shovelnose sturgeon habitat selection in the lower Missouri River. J Appl Ichthyology. 27:291–300. [Crossref], [Web of Science ®], [Google Scholar]
- Boyce MS, Vernier PR, Nielson SE, Schmiegelow FKA. 2002. Evaluating resource selection functions. Ecological Modelling. 157(2–3):281–300. [Crossref], [Web of Science ®], [Google Scholar]
- Brewer SK, Rabeni CF, Sowa SP, Annis G. 2007. Natural landscape and stream segment attributes influencing the distribution and relative abundance of riverine smallmouth bass in Missouri. North Am J Fish Manage. 27(1):326–341. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Bridger CJ, Booth RK. 2003. The effects of biotelemetry transmitter presence and attachment procedures on fish physiology and behavior. Rev Fish Sci. 11(1):13–34. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Burnham KP, Anderson DR. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd ed. New York (NY): Springer Science. [Crossref], [Google Scholar]
- Coble DW. 1975. Smallmouth bass. In: Clepper H, editor. Black bass biology and management. Washington (DC): Sport Fishing Institute; p. 21–22. [Google Scholar]
- Cole MB, Moring JR. 1997. Relation of adult size to movements and distribution of smallmouth bass in a central Maine lake. Trans Am Fish Soc. 126(5):815–821. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Cooper BA, Millspaugh JJ. 1999. The application of discrete choice models to wildlife resource selection studies. Ecology 80:566–575. [Crossref], [Web of Science ®], [Google Scholar]
- Cooper BA, Millspaugh JJ. 2001. Accounting for variation in resource availability and animal behavior in resource selection studies. Radio Tracking and Animal Populations. San Diego (CA): Academic Press; p. 243–273. [Google Scholar]
- Dauwalter DC, Splinter DK, Fisher WL, Marston RA. 2007. Geomorphology and stream habitat relationships with smallmouth bass (Micropterus dolomieu) abundance at multiple spatial scales in eastern Oklahoma. Can J Fish Aquatic Sci. 64:1116–1129. [Crossref], [Web of Science ®], [Google Scholar]
- Edwards EA, Gebhart G, Maughan OE, Terrell JW, Raleigh RF. 1983. Habitat suitability information: smallmouth bass (FWS/OBS-82/10.36). Washington (DC): U.S. Department of the Interior, Fish and Wildlife Service. [Google Scholar]
- Eiler JH. 2012. Tracking aquatic animals with radio telemetry. In: Adams NS, Beeman JW, Eiler JH, editors. Telemetry techniques: a user guide for fisheries research. Bethesda (MD): American Fisheries Society; p. 163–204. [Google Scholar]
- Fajen OF. 1962. The influence of stream stability on homing behavior of two smallmouth bass populations. Trans Am Fish Soc. 91(4):346–349. [Taylor & Francis Online], [Google Scholar]
- Fore JD, Dauwalter DC, Fisher WL. 2007. Microhabitat use by smallmouth bass in an Ozark stream. J Freshwater Ecol. 22(2):189–199. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Funk JL. 1957. Movement of stream fishes in Missouri. Trans Am Fish Soc. 85(1):39–57. [Taylor & Francis Online], [Google Scholar]
- Gerber GP, Haynes JM. 1988. Movements and behavior of smallmouth bass, Micropterus dolomieui, and rock bass, Ambloplites rupestris, in southcentral Lake Ontario and two tributaries. J Freshwater Ecol. 4(4):425–440. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Hart LG, Summerfelt RC. 1975. Surgical procedures for implanting ultrasonic transmitters into flathead catfish (Pylodictus olivaris). Trans Am Fish Soc. 104(1):56–59. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Helfman GS. 1981. Twilight activities and temporal structure in a freshwater fish community. Can J Fish Aquatic Sci. 38:1405–1420. [Crossref], [Web of Science ®], [Google Scholar]
- Hu, S. 2007. Akaike information criterion. Raleigh (NC): Center for Research in Scientific Computation. North Carolina State University. Available from: http://www4.ncsu.edu. [Google Scholar]
- Hubert WA, Lackey RT. 1980. Habitat of adult smallmouth in a Tennessee River Reservoir. Trans Am Fish Soc. 109(4):364–370. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Imes JL, Plummer LN, Kleeschulte MJ, Schumacher JG. 2007. Recharge area, base-flow and quick-flow discharge rates and ages, and general water quality of Big Spring in Carter County, Missouri, 2000-04 (SIR 2007-5049). Reston (VA): U.S. Geological Survey. Available from: http://pubs.usgs.gov. [Google Scholar]
- Lane EW. 1947. Report of the subcommittee on sediment terminology. Trans Am Geophysical Union. 28(6):936–938. [Crossref], [Google Scholar]
- Langhurst RV, Schoenike DL. 1990. Seasonal migration of smallmouth bass in the Embarrass and Wolf rivers, Wisconsin. North Am J Fish Manage. 10(2):224–227. [Taylor & Francis Online], [Google Scholar]
- Larimore RW, Pickering QH, Durham L. 1952. An inventory of the fishes of Jordon Creek, Vermilion County, Illinois (Biological Notes No. 29). Urbana (IL): Natural History Survey Division. [Google Scholar]
- Liedtke TL, Rub AMW. 2012. Techniques for telemetry transmitter attachment and evaluation of transmitter effects on fish performance. In: Adams NS, Beeman JW, Eiler JH, editors. Telemetry techniques: a user guide for fisheries research. Bethesda (MD): American Fisheries Society; p. 45–87. [Google Scholar]
- Lott JP. 2000. Smallmouth bass movement, habitat use and electrofishing susceptibility in lower Lake Oahe, South Dakota (Annual Report No. 00-15). Pierre (SD): South Dakota Game, Fish and Parks. [Google Scholar]
- Lyons J. 1991. Predicting smallmouth bass presence/absence and abundance in Wisconsin streams using physical habitat characteristics. In: Jackson DC, editor. The first international smallmouth bass symposium. Bethesda (MD): American Fisheries Society. p. 96–103 [Google Scholar]
- Lyons J., Kanehl P. 2002. Seasonal movements of smallmouth bass in streams. In: Philipp DP, Ridgway MS, editors. Black bass: ecology, conservation, and management. Bethesda (MD): American Fisheries Society. p. 149–160. [Google Scholar]
- McClendon DD, Rabeni CF. 1987. Physical and biological variables useful for predicting populations characteristics of smallmouth bass and rock bass in an Ozark stream. North Am J Fish Manage. 7(1):46–56. [Taylor & Francis Online], [Google Scholar]
- Miller RJ. 1975. Comparative behavior of centrarchid basses. In: Stroud RA, Clepper H, editors. Black bass biology and management. Washington (DC): Sport Fishing Institute. p. 85–94 [Google Scholar]
- Missouri Climate Center. 2012. January 2012 Weather and Its Impacts on Missouri [Internet]. Columbia (MO): College of Agriculture, Food and Natural Resources, University of Missouri; [accessed 2012 July 10]. Available from: http://climate.missouri.edu/news/arc/jan2012.php. [Google Scholar]
- Mugel DN, Richards JM, Schumacher JG. 2009. Geohydrologic investigations and landscape characteristics of areas contributing water to springs, the Current River, and Jacks Fork, Ozark National Scenic Riverways, Missouri (SIR 2009-5138). Reston (VA). U.S. Geological Survey. Available from: http://pubs.usgs.gov. [Google Scholar]
- Munther GL. 1970. Movement and distribution of smallmouth bass in the Middle Snake River. Trans Am Fish Soc. 99:44–53. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Paragamian VL. 1981. Some habitat characteristics that affect abundance and winter survival of smallmouth bass in the Maquoketa River, Iowa. In: Krumholz LA, editor. The warmwater streams symposium. Bethesda (MD): American Fisheries Society. p. 45–53. [Google Scholar]
- Peterson JT, Rabeni CF. 1996. Natural thermal refugia for temperate warm water stream fishes. North Am J Fish Manage. 16(4):738–746. [Taylor & Francis Online], [Google Scholar]
- Probst WE, Rabeni CF, Covington WG, Marteney RE. 1984. Resource use by stream-dwelling rock bass and smallmouth bass. Trans Am Fish Soc. 113(3):283–294. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Rankin ET. 1986. Habitat selection by smallmouth bass in response to physical characteristics in a natural stream. Trans Am Fish Soc. 115(2):322–334. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Reynolds WW, Casterlin ME. 1976. Activity rhythms and light intensity preferences of Micropterus salmoides and M. dolomieui. Trans Am Fish Soc. 105(3):400–403. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Roni P, Hanson K, Beechie T. 2008. Global review of the physical and biological effectiveness of stream habitat rehabilitation techniques. North Am J Fish Manag. 28(3):856–890. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Schlosser IJ. 1991. Stream fish ecology: a landscape perspective. Bioscience. 41(10):704–712. [Crossref], [Web of Science ®], [Google Scholar]
- Siegwarth G. 1996. Evaluation of the use and importance of available interior river habitat by gamefish species. Anuual Performance Report, Stream Fisheries Investigation, Project F-115-R-9, Study 2, Job 2. Des Moines (Iowa): Iowa Department of Natural Resources. [Google Scholar]
- Suski CD, Ridgway MS. 2009a. Winter biology of centrarchid fishes. In: Cooke SJ, Philipp DP, editors. Centrarchid Fishes: Diversity, Biology, and Conservation. Oxford (UK): Wiley-Blackwell; p. 264–292. [Crossref], [Google Scholar]
- Suski CD, Ridgway MS. 2009b. Seasonal pattern of depth selection in smallmouth bass. J Zool. 279(2):119–128. [Crossref], [Web of Science ®], [Google Scholar]
- Todd BL, Rabeni CF. 1989. Movement and habitat use by stream dwelling smallmouth bass. Trans Am Fish Soc. 118(3):229–242. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Tschantz DR, Crockett EL, Niewiarowski PH, Londraville RL. 2002. Cold acclimation strategy is highly variable among the sunfishes (Centrarchidae). Physiol Biochem Zool. 75(6):544–556. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- [USGS] United States Geological Survey. 2012. National Water Information System data available on the World Wide Web (USGS Water Data for the Nation); [accessed 2012 July 10]. Available from: http://waterdata.usgs.gov/mo/nwis/uv?site_no=07067000 [Google Scholar]
- Webster DA. 1954. Smallmouth bass (Micropterus dolomieui) in Cayuga Lake. Part I. Life history and environment (Memoir 327). Ithaca (NY): Cornell University Agricultural Experiment Station. [Google Scholar]
- Westhoff JT, Paukert C, Ettinger-Dietzel S, Dodd H, Siepker M. 2014. Behavioral thermoregulation and bioenergetics of riverine smallmouth bass associated with ambient cold-period thermal refuge. Ecol Freshwater Fish. doi: 10.1111/eff.12192 [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Westhoff JT, Rabeni CF. 2013. Resource selection and space use of a native and invasive crayfish: evidence for competitive exclusion? Freshwater Sci. 32(4):1383–1397. [Crossref], [Web of Science ®], [Google Scholar]
- Whitledge GW, Rabeni CF, Annis G, Sowa SP. 2006. Riparian shading and groundwater enhance growth potential for smallmouth bass in Ozark streams. Ecol Appl. 16(4):1461–1473. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Winter JD. 1983. Underwater biotelemetry. In: Nielson LA, Johnson DL, editors. Fisheries techniques. Bethesda (MD): American Fisheries Society. p. 371–395. [Google Scholar]