Southern Flounder Life History Diversity and Contributions to Fisheries from Differing Estuarine Salinity Zones
Abstract
Otolith chemistry is a useful natural tracer for discerning habitat-use of estuarine fishes. For Southern Flounder Paralichthys lethostigma, recent otolith chemistry studies have revealed a diversity of residency patterns across salinity gradients. However, the contribution of recruits with specific residency patterns to fisheries is poorly understood. The objectives of this study were to (1) use otolith chemistry from fishery-independent and fishery-dependent collections in Mobile Bay, Alabama, to classify lifetime residency patterns (i.e., freshwater, transient, estuarine) in Southern Flounder collected across a large estuarine salinity gradient (0–30 psu); (2) to test if Southern Flounder exhibited resident or migratory behavior by determining if lifetime residency patterns in fishery-independent samples matched expected salinity patterns in the region of collection after accounting for annual variation in river discharge; and (3) to examine which residency patterns contributed to the commercial and recreational Southern Flounder fisheries in nearby coastal waters. Age-0 residency patterns in fishery-independent samples were strongly correlated with region of collection and annual river discharge, suggesting that the majority of Southern Flounder had resided in the same region in which they spent their age-0 growth phase. Southern Flounder with a combination of freshwater and estuarine salinity signals and classified as “transient” did not appear to have conducted large-scale movements across salinity gradients, but instead resided in regions of the estuary experiencing seasonal fluctuations in salinity. The majority (57%) of commercially and recreationally harvested Southern Flounder were transients, while a minority (39%) were estuarine residents and lifetime freshwater residents (4%) were rarely harvested. Results from this study suggest that Southern Flounder settle in and remain in the certain habitats during the estuarine residency phase. Given the lack of movement across habitats, future efforts to understand how habitat-specific conditions (e.g., abiotic, biotic, fishing exploitation) affect vital rates seems warranted for a species currently experiencing population declines.
Estuaries are essential to the ontogenetic development of many recreationally and commercially important fishes. As an interface between freshwater and marine ecosystems, estuaries are highly productive and extremely complex ecosystems that provide nursery habitat to numerous fish species (Beck et al. 2001; Able 2005). Understanding the benefits these habitats provide and the physical and bioenergetic movements of nutrients and organisms across estuarine habitats is essential to developing appropriate management and conservation actions (Nathan et al. 2008). A better understanding of how fish utilize and benefit from a diverse suite of estuarine habitats is therefore essential to protect critical estuarine habitats and the fisheries that rely on them.
Euryhaline fishes that inhabit estuaries may use a wide diversity of salinities and habitat types. This can result from partial migration, in which a population has distinct groups of resident and migratory individuals that use different salinities as a result of migratory or resident behaviors (Secor 1999; Elsdon and Gillanders 2006; Chapman et al. 2012). Conversely, a wide diversity of salinity and habitat-use variation can also exist when populations have no identifiable contingent structure but contain individuals that exhibit facultative use of various salinities throughout life (Cucherousset et al. 2005; Rohtla and Vetemaa 2016; Nelson et al. 2021). Regardless of the exact underlying mechanism, differing habitat use can have important implications for growth, mortality, fitness, and vulnerability to fishery exploitation (Secor 1999; Hodge et al. 2014; Gillanders et al. 2015). As a result, the contribution of individuals from specific salinity zones or habitat types to the overall stock or population may change across time in response to changing environmental conditions or spatial differences in harvest pressure (Secor 1999; Kraus and Secor 2004). For species that support commercial and recreational fisheries, understanding how fisheries exploit or fail to exploit specific salinity zones or habitat types is important for maintaining life history diversity, with implications for sustainable fisheries management (Parsons et al. 2011; Siskey et al. 2020).
Otolith chemistry has been a useful tool for quantifying fish residency and migratory patterns across salinity gradients, as differences in elemental concentrations are typically discernible between freshwaters and marine waters. Such differences can be detected and interpreted across transects or depth profiles (Macdonald et al. 2008) in the otolith to reconstruct lifetime movement patterns across estuarine salinity gradients (Campana et al. 2000; Elsdon et al. 2008). Despite this usefulness, limitations exist and should be accounted for in any study seeking to use otolith elemental concentrations to recreate lifetime residency and migratory patterns. One limitation of otolith chemistry in differentiating residency versus migratory behavior is that it can be difficult to determine if a fish is moving across a salinity gradient or if a fish is remaining sedentary while the salinity of the surrounding waters is changing. For example, seasonal fluctuations in freshwater discharge may shift the locality of estuary salinity classifications (i.e., oligohaline [0.5–5 psu], mesohaline [5–18 psu], polyhaline [18–30 psu]) several miles within a single year. Any study seeking to understand fish movement and habitat use patterns across salinity gradients should consider spatiotemporal variations in salinity and resulting water chemistry due to interannual differences in freshwater discharge (Teichert et al. 2017). Another limitation is that elemental incorporation into otoliths may differ across salinity gradients (Nelson and Powers 2020). Partition coefficients, which describe the proportional incorporation of water elemental concentrations into otoliths, should be shown to be consistent across salinity gradients for any element used as a marker of salinity (Macdonald and Crook 2010).
Being a euryhaline, estuarine-dependent species, Southern Flounder Paralichthys lethostigma rely on estuaries for growth and ontogenetic development. The putative life history for Southern Flounder includes offshore spawning by adults during late fall and winter followed by larval ingress into estuaries where they undergo sinistral, craniofacial metamorphosis, and settle (Jager 1999; Schreiber 2006; Glass et al. 2008). After settlement, juvenile Southern Flounder have increased tolerance for low-salinity habitats (Glass et al. 2008). Use of freshwater or oligohaline habitats during early life has been documented by a long history of field studies (Powell and Schwartz 1977; Burke et al. 1991; Glass et al. 2008; Smith and Scharf 2010; Furey and Rooker 2013), leading to the expectation that postsettlement juveniles actively select freshwater and low-salinity habitats before emigrating back to higher salinity estuarine habitats where they mature. However, recent studies using otolith chemistry has revealed diverse patterns in lifetime salinity exposure and suggests that Southern Flounder may settle across a wide range of salinities during early life and remain in distinct habitats during later juvenile and adult stages (Lowe et al. 2011; Farmer et al. 2013; Nims and Walther 2014). These studies suggest that three primary salinity exposure patterns were observed: (1) marine-estuarine residency at salinities >5 psu, (2) oligohaline-freshwater residence at salinity <5 psu, or (3) some combination of (1) and (2) above. For the third group, previous studies were unable to determine if these fish were migrating across salinity gradients or if they resided in locations with high temporal variability in salinity.
Another limitation of these studies was that they only collected Southern Flounder from a limited range of habitats in estuaries. Lowe et al. (2011) and Farmer et al. (2013) collected Southern Flounder in oligohaline-freshwater habitats in Alabama, while Nims and Walther (2014) primarily collected Southern Flounder during the offshore spawning migration (November–February) at passes connecting estuaries to the Gulf of Mexico. Importantly, no published studies have quantified lifetime salinity experience in individuals collected across large estuarine salinity gradients to test the hypothesis that Southern Flounder settle and remain in distinct regions of the estuary prior to offshore spawning migrations. Additionally, no published studies have quantified lifetime salinity experience in Southern Flounder captured in commercial or recreational fisheries to understand how fishery exploitation is distributed across salinity gradients for this euryhaline species.
To address these knowledge gaps, we collected Southern Flounder across an estuarine salinity gradient ranging from 0 to 30 psu in Mobile Bay, Alabama, and used otolith chemistry to quantify lifetime residency patterns. We also determined the contribution of specific residency patterns to commercial and recreational fisheries. Specifically, we aimed to (1) use otolith chemistry from fishery-independent and fishery-dependent collections from 2004–2007 and 2018–2019 to classify lifetime residency patterns (i.e., freshwater, transient, estuarine) in Southern Flounder collected from sites across a large estuarine salinity gradient (0–30 psu); (2) determine if lifetime residency patterns in fishery-independent samples matched expected patterns of salinity in a given collection region after accounting for annual variation in river discharge, thereby testing if fish exhibited resident or migratory behavior; and (3) examine which residency patterns contributed to the commercial and recreational Southern Flounder fisheries in nearby coastal waters. Ultimately, the results from this study aimed to inform management and conservation actions for Southern Flounder, which are currently experiencing population declines across its range (Lee et al. 2018; Erickson et al. 2021).
METHODS
Sample collections
Fishery-independent collections
During 2004–2007, Southern Flounder were collected by Auburn University from six sites in northern Mobile Bay and the Mobile–Tensaw River delta (Delta; Figure 1). Sampling was conducted monthly using pulsed DC boat electrofishing (Smith-Root, Inc., Vancouver, Washington). Complete descriptions of sampling efforts during 2004–2007 can be found in Lowe et al. (2011) and Glover et al. (2013). While previous studies (Lowe et al. 2011; Farmer et al. 2013) reported Southern Flounder otolith chemistry results from these collections, we processed archived otolith samples that had not previously been analyzed for otolith chemistry. The results reported here for 2004–2007 represent new data not previously reported in the literature.
During 2018–2019, Southern Flounder were collected by Clemson University from 10 sites located along a 60-km seasonal salinity gradient of salt marshes, bays, tidal creeks, and freshwater rivers across the Delta and Mobile Bay (Figure 1). Sites in lower Mobile Bay (Lower Bay) were located on the landward side of barrier islands and within tributaries of Mobile Bay in meso- to polyhaline habitats (Figure 1). Sites in the upper Mobile Bay region (Upper Bay) were located in upper Mobile Bay and in the lower Delta. Sites in the Delta were located in upstream, presumably year-round freshwater habitats in the Mobile–Tensaw River delta (Figure 1). Sites were sampled 1–2 times monthly during May–July of 2018 and during March and May–July of 2019.
Three sampling methods were used to collect Southern Flounder during the 2018–2019 sampling period. These included beam trawls, gill nets, and electrofishing. A 1-m-wide beam trawl with 2 mm mesh was used at all sampling locations. Beam trawl transects (eight at sites in Lower Bay and three at sites in Upper Bay and the Delta) were hauled by boat in 2-min trawls during each site visit. Gill nets measuring 30 m by 2.4 m with 127 mm stretch mesh were set for four soaking hours (two 2-h sets) at Lower Bay sites. Nets were set parallel to the shore with a hook towards shore at the downstream end. At Upper Bay and Delta sites, pulsed DC boat electrofishing (Midwest Lake Electrofishing Systems Infinity Box) was used along shorelines. Six 15-min boom mounted electrofishing transects were conducted during each site visit. All Southern Flounder collected were euthanized with a lethal dose (1 g/L) of buffered MS-222 (tricaine methanesulfonate), placed on ice, and returned to the laboratory for processing in accordance with guidelines outlined in Institutional Animal Care and Use Community protocol #AUP2018-001 by Clemson University.
Additional flounder were collected by Alabama Marine Resources Division (MRD) during their Fisheries Monitoring and Assessment Program (FAMP). This survey program used a 4.88-m otter trawl with 4.76 mm mesh pulled for 10 min at 2–2.5 knots. Surveys occur monthly at 24 locations across all of Alabama's coastal waters in Upper Bay and Lower Bay sites (Figure 1). Trawl samples were placed on ice and returned to MRD's Dauphin Island laboratory for processing.
Fishery-dependent collections
Southern Flounder were collected from the commercial and recreational fisheries during both the 2004–2007 and 2018–2019 sampling periods. Alabama MRD (2004–2007) collected from recreational anglers using protocols from the National Oceanic and Atmospheric Administration's Fisheries Marine Recreational Information Program (MRIP) and from commercial fish houses. Alabama MRD used the Access Point Angler Intercept Survey (APAIS) to randomly select public access locations across Mobile Bay and Alabama's coast to creel recreational anglers fishing from shore and vessel. Clemson University (2018–2019) collections included weekly collections from commercial fish houses during summer 2019, opportunistic collections from boat access points (2018–2019), and two large annual fishing tournaments held during 2019 in Dauphin Island, Alabama, and Orange Beach, Alabama.
Water quality, water chemistry, and annual discharge
To understand the relationships between freshwater river discharge, salinity, and water elemental concentrations, we collected abiotic data at a variety of spatial and temporal scales. Mean daily river discharge values were collected from the most downstream U.S. Geological Survey (USGS) gauge stations on the Alabama (gauge 02428400, 31°36′54′′N, 87°33′02′′W) and Tombigbee (gauge 02469761, 31°45′30′′N, 88°07′45′′W) rivers. The locations of these gauge stations are just upstream from their confluence to form the Mobile River. Together, flows from these two rivers contribute the majority of the freshwater inflow into the Mobile River system and largely drive temporal and spatial salinity dynamics in the Delta (DeVries et al. 2015) and Mobile Bay (Dzwonkowski et al. 2011). Daily time-series salinity data helped us understand how salinity across the three regions within Mobile Bay changed in response to seasonal and annual patterns in river discharge. In the Delta, salinity was monitored by Auburn University at Gravine Island during 2005–2006. Additionally, daily time-series salinity data were collected from three Dauphin Island Sea Lab stations (Meaher State Park, Middle Bay, and Dauphin Island; https://arcos.disl.org/). The Meaher Park station monitored upper Mobile Bay salinity, while the Middle Bay and Dauphin Island loggers monitored lower Mobile Bay salinity (Figure 1).
Water chemistry samples for quantifying elemental concentrations in ambient water were collected during July 2018 and March, May, and July 2019. Water chemistry samples were collected at 1-m depth using a Van Dorn water sampler, filtered through a 47-mm-diameter, 0.45-μm cellulose nitrate membrane filters (Thermo Scientific and Nalgene Water Quality Membrane, both Waltham, Massachusetts) using a vacuum filtration system in the field, fixed with 95% nitric acid (HNO3) at 2%, stored in 200-mL acid-washed bottles on ice, and refrigerated at 4°C upon return to the lab. In conjunction with water chemistry samples, water salinity was measured using a YSI ProPlus (Yellow Springs, Ohio) handheld unit. These samples allowed us to quantify relationships between salinity and water chemistry. Water chemistry was compared to otolith edge elemental concentrations from fish collected on the same day and site as water chemistry samples to quantify partition coefficients describing uptake of elements from water into the otolith (see Water to otolith partition coefficient section below for details).
Laboratory Processing
Upon returning to the laboratory in Clemson, South Carolina, Southern Flounder were measured for total length (mm) and weight (g). Sagittae were removed, cleaned of tissue in research-grade ultrapure water, and air-dried under a hood. Due to differences in chemical composition, mass, and aging accuracy between left and right otoliths within flatfish species, right otoliths were selected for further processing (Sipe and Chittenden 2001; Loher et al. 2008; Kajajian et al. 2014; Gao et al. 2015). Left otoliths were processed for otolith chemistry but later corrected to resemble right otoliths if the right was unusable (detailed below in Left to right otolith comparison). Otoliths were embedded in individual wells and sectioned with a Buehler IsoMet low-speed saw, making two cuts perpendicular to the sulcal groove, one on each side of the otolith's core. Sectioned otoliths were polished using a Buehler circular polishing station with 600 and 1,000 grit paper until the core and annuli were exposed. Otoliths were fixed to a glass slide with Crystalbond 509, imaged with a digital imaging analysis system, and aged by two readers before being processed for otolith chemistry. The image analysis system comprised a Canon Rebel T3i connected to a Meiji EMZ-TR dissecting microscope. Digital inmates were viewed with iSolution Lite (Image & Microscope Technology [IMT] Inc.) software. When two readers disagreed on otolith age, a third reader aged the otolith in question. If the third reader agreed with one of the previous two readers, a final age was assigned. If the third reader disagreed with both previous readers, the otolith in question was omitted from analysis. All Southern Flounder otoliths had at least two readers who agreed upon the final age, allowing us to assign final ages to 100% of collected otoliths.
Otolith and water chemistry samples were processed at the Dauphin Island Sea Lab in Dauphin Island, Alabama, instrumentation lab using an Agilent (Palo Alto, California) 7,700× quadrupole inductively coupled plasma mass spectrometer (ICPMS) coupled to a 213-nm Nd:YAG NWR laser. In both water and otoliths, we quantified concentrations of magnesium (24Mg), calcium (43Ca), manganese (55Mn), zinc (65Zn), strontium (88Sr), and barium (137Ba) (Supplement [available separately online]). Mounted otoliths were rinsed with ultrapure deionized water, dried in a clean hood, and cleaned with a low power, preablation cleaning (40 μm spot, 100 μm/s, 20% laser power, 5 Hz) to remove any remaining contaminants on the otolith surface (Gover et al. 2014). Chemistry analysis transects (25 μm spot, 5 μm/s, 30% laser power, 10 Hz) were run in a straight line from the core to the distal edge along the sulcal groove to obtain lifetime otolith elemental signatures. Prior to statistical analyses, elemental concentrations of water and otoliths were converted to molar ratios with 43Ca (Supplement). To obtain age-specific signatures, elemental transect output (s) was converted to μm (laser speed [5 μm/s] × s) and transect distance was measured to each annulus and the otolith edge. Otolith signatures were scaled to years (that is, fractional ages) by assuming the last reading along the otolith's edge was laid on the date of harvest, that each annulus was laid down on April 1 (Corey et al. 2017), and the core was a hatch date of January 1 (Fitzhugh et al. 1996; Glass et al. 2008). We assigned fractional ages by dividing the distance of an otolith growth region (for example, the distance from the last annuli to the otolith edge in mm) by the number of days that elapsed during that growth period (the number of days between the date of last annuli formation and the date of capture). This produced an otolith growth rate for each growth region in mm/d. We then used this growth rate to convert distance into time (d) and assign factional ages based on the day of the year on which each elemental measurement was made across the laser ablation path.
Statistical Analysis
Water to otolith partition coefficient
(Morse and Bender 1990), partition coefficients (DSr:Ca) for each flounder were calculated by using the Sr:Ca (mmol : mol) from the last 30 d of otolith growth and water chemistry (Sr:Cawater) from samples collected on the same day from March to July of 2019 (N = 43). To determine the last 30 d of otolith growth, we calculated the distance of otolith growth for the last 30 d prior to capture (which ranged from 25 to 92 μm, depending on fish age) and averaged the Sr:Ca values during that time frame. Individual flounder DSr:Ca were grouped by water salinity classification (i.e., freshwater [<1 psu], mesohaline [5–18 psu], and polyhaline [>18 psu]), and a one-way analysis of variance (ANOVA) was used to test if partition coefficients from Southern Flounder otoliths differed across water salinity classification groups. The grand mean partition coefficient used to determine residency status was calculated by averaging the mean partition coefficient from each salinity classification. All analyses were completed in R version 3.6.1 (R Development Core Team, Vienna).
Left to right otolith comparison
To determine if differences existed among left and right mean otolith Sr:Ca values, we analyzed both the left and right otoliths from a subset of Southern Flounder (n = 20). Using these samples, we conducted three paired t-tests, comparing left and right otoliths Sr:Ca for (1) age 0, (2) age 1, and (3) all ages combined. For each t-test, we confirmed that residuals were normally distributed using the Shapiro–Wilk test, meeting the assumptions for the parametric test. If a significant difference was detected across both ages and the combined group (all flounder included in a single t-test), we calculated the mean difference between left and right otoliths and applied a correction factor to all left otoliths in our final analysis. This approach allowed us to increase our overall sample size by including additional historical samples from 2004 to 2007 for which only left otoliths were available. To investigate potential biological mechanisms underlying any differences in otolith chemistry, we also tested if the total dry weight of left versus right otoliths differed using a paired t-test.
Residency classification
Our goal in analyzing otolith elemental data was to classify each Southern Flounder as a freshwater resident (salinity ≤1 psu), estuarine (salinity >1 psu) resident, or transient during each year of life. To accomplish this, we quantified the relationship between otolith Sr:Ca ratios (using only values from right otoliths) and water salinity. We fit nonlinear models of water Sr:Ca (mmol : mol) to ambient salinity values at the time of collection for all water samples collected during 2018 and 2019. From this relationship, we quantified the expected water Sr:Ca value for 1 psu salinity (i.e., the threshold value for residency classification). Variance was estimated using bootstrapped 95% confidence intervals (CIs) generated using 1,000 iterations in the R package “nlsBoot” (Baty et al. 2015). The predicted water Sr:Ca value for 1 psu was then multiplied by the partition coefficient to develop the expected mean otolith Sr:Ca value at 1 psu salinity. To quantify the uncertainty in the otolith Sr:Ca threshold value at 1 psu salinity, we multiplied the 95% upper and lower confidence intervals of the predicted water Sr:Ca value by the partition coefficient.
To summarize the time series of otolith Sr:Ca values, we used a regime shift detection algorithm to detect significant shifts in otolith Sr:Ca values along the laser ablation transects (Rodionov 2004). The regime shift algorithm uses a sequential F-test given the variance, a selected cutoff length, and the selected level of significance to test for shifts in the moving average and determine where significant shifts in Sr:Ca occur across the otolith transect. Changes or “shifts” in the moving average occur when more than one point is found to significantly differ from the current moving average. Following the methods from Turner and Limburg (2015) and Seeley and Walther (2018), algorithm parameters were set at a significance level of P < 0.05, cutoff length of 10 cells (~27 μm), and a Huber's weight parameter of 1 for omitting outliers from the regime shift algorithm. The algorithm used these parameters to identify regime shifts, or discontinuity, in Sr:Ca values along otolith transects and created a smoothed average between shifts. Cell cutoffs of 5, 15, and 20 were tested and compared to determine the best-fitting minimum cutoff length. A 10 cell cutoff had improved fit to raw Sr:Ca values over a 5 cell cutoff, while any cutoff over 10 resulted in no change in smoothed averages.
Smoothed moving averages of time series otolith Sr:Ca values were classified as above or below the 1 psu salinity threshold at each time step (i.e., fractional ages). A Sr:Ca value equal to or below the 1 psu threshold value was classified as a “freshwater resident” for a given time step, while an Sr:Ca value above the threshold value was classified as an “estuarine resident.” The proportion of total values above or below this threshold value were then summarized in each year of life (i.e., between each annulus; subsequently referred to as “age-specific residency classification”) and across the entire lifetime for each individual (subsequently referred to as “lifetime residency classification”). If >90% of the values across each age or lifetime fell into one classification (i.e., freshwater or estuarine), residency patterns were assigned to that classification. If neither classification consisted of 90% of the transect, then a “transient resident” classification was assigned to indicate a fish that either moved between freshwater and estuarine habitats or a fish that resided in an area that experienced seasonal changes in salinity. The classification threshold was restricted to 90%, as this value was the most conservative threshold that best fit our data.
Fisher's exact tests used 3 × 2 contingency tables to test the null hypothesis that lifetime residency classifications (rows) were independent of a region of collection for fishery-independent samples and method of collection (i.e., recreational versus commercial) for fishery-dependent samples (columns). If lifetime residency classifications differed by region, we interpreted this as support for the hypothesis that distinct contingents of Southern Flounder existed within Mobile Bay. If lifetime residency classifications differed between recreational and commercial fisheries, we interpreted this as support for the hypothesis that these two fisheries had different patterns of exploitation across contingents. Finally, we combined fishery-dependent sources (flounder sampled from commercial and recreational fisheries) and compared lifetime residency proportions to those observed in fishery-independent samples from known locations of collection (i.e., fishery-dependent versus fishery-independent Delta, fishery-dependent versus fishery-independent Upper Bay, fishery-dependent versus fishery-independent Lower Bay). This series of tests aimed to determine if Southern Flounder sampled from the recreational and commercial fisheries were similar to fishery-independent samples from known regions of Mobile Bay, thus testing if recreational and commercial fisheries targeted specific regions within Mobile Bay. A separate contingency table was used to test for differences between the seven analyses listed above.
Finally, we examined age distributions of Southern Flounder belonging to each lifetime residency classification by region. If the putative life history for Southern Flounder is correct, we would expect that freshwater residents would be the youngest of all three residency groups, as this group would be dominated by younger fish seeking freshwater. We would expect that transients would be intermediate in age and that the oldest flounder would be estuarine residents, as these fish would be expected to have migrated back to the lower estuary to prepare for out-migration to marine habitats for offshore spawning. We also compared age at capture for fishery-independent samples among regions of collection and lifetime residency classification using Kruskal–Wallis tests. We conducted a separate Wilcoxon two-sample test to determine if age at capture differed between fishery-independent and fishery-dependent samples.
Evaluating the effect of river discharge on residency classifications
One of the limitations in using otolith chemistry to infer movement patterns is that it can be difficult to determine if annual changes in otolith chemistry result from fish actively moving across a gradient of water chemistry (e.g., freshwater to oligohaline habitats) or water chemistry changing in a given habitat in which fish remain stationary. We used multinomial logistic regression (R package “nnet”; Venables and Ripley 2002) to test if differences in the proportion of age-0 residency classifications for fishery-independent samples was related to age at capture, region of collection, and an index of annual freshwater river discharge, which is a key driver of salinity and associated water chemistry in Mobile Bay. In multinomial logistic regression, residency classifications determined from the age-0 region of the otolith (that is, the core to the first annuli) were the response variable and age at capture, the region of collection (i.e., Delta, Upper Bay, and Lower Bay), and cumulative river discharge (m3/s) during the age-0 growth phase were predictor variables. To align our index of river discharge with the age-0 growth phase for Southern Flounder, mean daily river discharge was summed from January 1 (assumed hatch date) through April 1 (assumed annuli formation date) of the following year. Ultimately, we aimed to use this analysis to test the hypothesis that Southern Flounder settle in a given region of the estuary early in the age-0 growth phase and largely remain in their region of settlement during their first 1–3 years of life until moving offshore to spawn as mature adults. If true, we expected that the region of collection would be a significant predictor of lifetime residency patterns and that adult (age-1 to age-3) Southern Flounder collected in the Delta and Upper Bay would have annual proportions of age-0 residency classifications that would follow a predictable response to annual changes in river discharge. We included age at capture to test the putative life history hypothesis that freshwater residents would be younger and estuarine residents would be older. We used stepwise multinomial logistic regression (R package “MASS”; Venables and Ripley 2002) model selection to determine the most parsimonious model by minimizing the Akaike information criteria (AIC) score. We also compared residency classifications from the age-0 growth phase of otoliths collected from fishery-dependent samples to predicted region-specific age-0 residency classifications from multinomial logistic regression using fishery-independent samples. In doing so, we aimed to better understand where Southern Flounder recruited to the commercial and recreational fisheries spent their age-0 growth phase.
RESULTS
Water to Otolith Partition Coefficient
Temporal trends in annual salinity patterns were relatively consistent across years for Mobile Bay and the Delta. Annual salinity patterns across all sites were lowest in the spring, increased throughout the summer, and then decreased during the fall (Figure 2). Salinities in Lower Bay (Middle Bay and Dauphin Island loggers; Figure 1) ranged from 2 to 30 psu, salinity in Upper Bay (Meaher State Park logger; Figure 1) ranged from 0 to 14 psu, and salinity in the Delta (Gravine Island; Figure 1) ranged from 0 to 1 psu. Upper Bay salinity values were above the 1 psu salinity threshold during summer and fall but remained below 1 psu during winter and spring for most years of this study (Figure 2). On average, 62% of Upper Bay annual salinity values were below 1 psu, indicating that this area was the transition zone between freshwater and estuarine otolith signatures. Salinity values in the Delta at the Gravine Island logger remained below 1 psu except one 15-d period in the fall of 2005 when Hurricane Katrina altered the long-term salinity regime, resulting in a salinity of 1.24 psu in the Delta. Salinity in Lower Bay never reached below 1 psu during the 11 years of observation included in this study. Given that controlled laboratory experiments have found a lag time of ~21 d (depending on the species: Secor et al. 1995; Milton and Chenery 2001; Elsdon and Gillanders 2005; Lowe et al. 2009) for otolith chemistry to reach equilibrium with water chemistry, these relatively stable annual salinity regimes in each region should allow us to classify Southern Flounder that either remained in a given region or moved across regions during their lifetimes.
Elemental concentrations of dissolved Ca and Sr from 55 water samples collected during 2018–2019 showed positive, linear relationships with salinity (R2 > 0.99, P < 0.001). Water Sr:Ca ratios (asy = 7.62, k = 0.99, s0 = −0.31) and otolith ratios (asy = 2.42, k = 0.72, s0 = −0.42) showed positive, asymptotic relationships with salinity (Figure 3). Partition coefficients were averaged by salinity categories (i.e., freshwater, mesohaline, polyhaline). Mean partition coefficients (DSr:Ca) remained relatively constant, with a standard deviation of 0.024 mmol : mol across all salinity categories (Table 1). Ninety-five percent confidence intervals for partition coefficients overlapped for each salinity category, indicating that partition coefficients did not differ in response to changing salinity. The grand mean partition coefficient was DSr:Ca = 0.31 across all salinity categories. Otolith and water elemental concentrations of barium and magnesium were also analyzed, but these elements were not significant predictors of water chemistry (Chrisp 2020). Specifically, the partition coefficient of Ba:Ca was not consistent across the salinity range and was 200% more variable compared to Sr:Ca. Ba:Ca partition coefficients also increased with increasing salinity, indicating higher uptake of Ba at higher salinities.
Salinity (psu) | n | Water Sr:Ca | Otolith Sr:Ca | DSr |
---|---|---|---|---|
Freshwater (<1) | 29 | 2.824 (0.084) | 0.824 (0.029) | 0.295 (0.010) |
Mesohaline (5–17) | 13 | 7.557 (0.051) | 2.418 (0.079) | 0.319 (0.009) |
Polyhaline (24–25) | 2 | 7.799 (0.104) | 2.462 (0.249) | 0.316 (0.036) |
The predicted water Sr:Ca values for 1 psu was 5.53 mmol : mol (95% CI = 5.25–5.89; Figure 3). When multiplied by the grand mean partition coefficient for Sr:Ca, the freshwater threshold for 1 psu salinity in Southern Flounder otoliths was 1.71 mmol : mol Sr:Ca (95% CI = 1.62–1.82). Uncertainty surrounding the 1.71 mmol : mol Sr:Ca threshold was not incorporated into further analyses, as the bootstrapped 95% CI was narrow relative to other studies that formally included the uncertainty of Sr:Ca thresholds into their analyses (Seeley and Walther 2018).
Left to right otolith comparison
Prior to fitting the regime shift algorithm to lifetime Sr:Ca data, a correction factor of −0.104 Sr:Ca (developed from analysis of paired otoliths) was applied to all 50 left otoliths to correct their lifetime Sr:Ca values to be on the same scale as right otoliths (Table 2). This correction factor accounted for the small, but significant, difference between left and right Sr:Ca concentrations. Paired t-tests found that the mean Sr:Ca was significantly higher in left otoliths than in right otoliths and that this difference was present across individual ages of flounder (age 0 and age 1) and all ages combined (Table 2). We used the mean difference from the analysis of paired otoliths from all age-0 and age-1 Southern Flounder combined (0.104 Sr:Ca) as our correction factor. Otolith dry weights also differed between paired left and right otoliths, with right otoliths being ~0.001 mg larger than left otoliths (Table 2).
Age 0 | Age 1 | All ages combined | |||||||
---|---|---|---|---|---|---|---|---|---|
S-W | P | Diff (mean ± SE) | S-W | P | Diff (mean ± SE) | S-W | P | Diff (mean ± SE) | |
Mass (mg) | 0.395 | 0.005 | −0.001 ± <0.001 | ||||||
Sr:Ca | 0.662 | 0.006 | −0.102 ± 0.033 | <0.001 | 0.001* | −0.121 ± 0.041 | 0.545 | 0.004 | −0.104 ± 0.032 |
Residency Classification
After applying corrections to raw Sr:Ca from left otoliths, otolith chemistry data from 346 Southern Flounder (198 fishery dependent, 148 fishery independent) were fitted to the regime shift algorithm and the smoothed, mean values were used to examine proportional occurrence of residency classifications (i.e., freshwater, transient, estuarine; Figure 4). Across all 346 Southern Flounder (combined for both fishery-independent and fishery-dependent samples) that were classified into one of three lifetime residency classifications, the transient classification was the most common (n = 154, 45%), followed by estuarine residency (n = 104, 30%) then freshwater residency (n = 88, 25%). Transient flounder exhibited a wide diversity of patterns in their use of freshwater habitats (salinity <1 psu), which ranged from 10% to 90% of their lifetime. Of the individuals classified as lifetime transients, 24% used freshwater habitats for 10–30% of their lifetime, 36% used freshwater habitats during 30–50% of their lifetime, 20% used freshwater habitats for 50–70% of their lifetime, and 20% used freshwater habitats for 70–90% of their lifetime, suggesting there was no predominant pattern of lifetime exposure to freshwater (i.e., salinity <1 psu) in fish classified as transients (Figure 5). Age-specific patterns in lifetime residency showed a wide diversity of freshwater and estuarine salinity exposure, with a general trend of increasing salinity exposure (i.e., transient and estuarine resident classifications) with age (Figure 5). However, the small sample sizes of older Southern Flounder (age 2+) limited insight into older ages.
Fishery-independent residency classifications
The proportion of lifetime Southern Flounder residency classifications in fishery-independent samples differed significantly by region of collection. Southern Flounder collected from fishery-independent sampling in the Delta were predominately freshwater lifetime residents (74%) or transient (26%), with none classified as estuarine residents (Figure 6). Similarly, Southern Flounder collected in fishery-independent samples in Upper Bay were predominantly freshwater lifetime residents (62%) or transient (33%), with only a few (5%) classified as estuarine residents. Southern Flounder collected in fishery-independent samples in Lower Bay were majority estuarine residents (78%), with fewer transients (22%), and none were freshwater residents (Figure 6). Proportions of lifetime salinity classifications from fishery-independent samples differed significantly among regions (Fisher's exact test: Delta versus Upper Bay [P < 0.001]; Delta versus Lower Bay [P < 0.001]; Upper Bay versus Lower Bay [P < 0.001]). Importantly, age at capture did not differ significantly among regions (Kruskal–Wallis 2 = 1.83, P = 0.4) or among lifetime residency classifications (2 = 0.89, P = 0.6) for fishery-independent samples. This suggests that age differences are not responsible for the observed variation in residency patterns across regions (Figure 6).
Beyond examining age at capture among regions, we also examined age-specific residency patterns for each year of life for fishery-independent samples in each region. In this analysis, a flounder captured at age 2 would contribute age-specific residency patterns for age 0 and age 1 to the analysis, as these years of life had complete growth phases. Age-specific results largely mirrored the results for lifetime residency patterns (Figure 7). A majority of Southern Flounder from fishery-independent collections in the Delta and Upper Bay resided in freshwater habitats during the age-0 and age-1 growth phases (Figure 7). Similarly, a majority of Southern Flounder from Lower Bay were classified as estuarine residents during all age-specific growth phases (age 0 to age 2). There was some evidence that the proportion of freshwater residents in the Delta declined during older ages (age 2+), but low sample sizes of these individuals in our collections limited inferences that could be drawn from older ages (Figure 7).
Fishery-dependent residency classifications
Southern Flounder lifetime salinity classifications between fishery-dependent samples from commercial and recreational fisheries did not differ (Fisher's exact test: P = 0.1). Subsequently, we combined all fishery-dependent samples (recreational or commercially harvested fish) into a single group for further analyses. Lifetime freshwater residencies occurred in only 4% of fishery-dependent samples, while 57% had a transient lifetime residency and 39% were classified as estuarine residents (Figure 6). Lifetime salinity classifications for fishery-dependent samples were significantly different from those observed in all fishery-independent regions of collection (Fisher's exact test: all P < 0.001). Age at capture was also greater for fishery-dependent samples (1.4 ± 0.7 years; mean ± SD) compared to fishery-independent salinity classifications (0.9 ± 0.5 years; Wilcoxon two-sample test: P < 0.001). However, comparing age-specific residency patterns among fishery-dependent and -independent samples suggests that differences in lifetime residency patterns are not simply due to the presence of older fish in fishery-dependent samples (Figure 7).
Age-specific residency classifications from fishery-dependent Southern Flounder showed that transient classifications were most common during the age-0 growth phase. This differed from age-specific residency patterns for fishery-independent samples in the Delta and Upper Bay, where freshwater residency was most common during the age-0 growth phase. It also differed from the Lower Bay, where the estuarine residency pattern was most common during the age-0 growth phase. However, the proportion of transient classifications declined at older ages (ages 1–3) in fishery-dependent samples, while the proportion of estuarine residency classifications increased (Figure 7). This pattern of increasing estuarine residency at ages 1+ was similar to the trend in the Lower Bay for age 1+ fishery-independent samples, suggesting Southern Flounder harvested in commercial and recreational fisheries may primarily reside in the Lower Bay after their age-0 growth phase.
Evaluating the effect of river discharge on residency classifications
Region-specific residency classifications during the age-0 growth phase changed in predictable ways in response to changes in freshwater river discharge, suggesting that flounder in fishery-independent collections were captured in the same regions that they resided in during the 16-month (January through April of the following year) age-0 growth phase. Multinomial logistic regression with AIC stepwise model selection found that the best model contained both region (P < 0.001) and annual freshwater river discharge (P < 0.001), and both were significant predictors of the proportions of residency classifications during the age-0 growth phase (Nagelkerke pseudo R2 = 0.67) (Figure 8). Age at capture was not significant (P = 0.57) and was omitted from the final model during stepwise model selection. Our data met all assumptions for multinomial logistic regression, including linearity, independence, and absence of multicollinearity.
In the Delta and Upper Bay, the proportion of freshwater residents during the age-0 growth phase increased in years with high river discharge and declined in years with low river discharge. Predicted shifts in age-0 residency classifications in response to changes in freshwater river discharge were large. When river discharge was low (1,000 m3/s) 19% and 35% of Southern Flounder in the Delta and Upper Bay, respectively, were predicted to be age-0 freshwater residents. When river discharge was high (2,500 m3/s), 93% and 97% of flounder in the Delta and Upper Bay, respectively, were predicted to be freshwater residents (Figure 8). Similarly, the proportion of transients during the age-0 growth phase in the Delta and Upper Bay increased in years with low river discharge and decreased in years of high river discharge (Figure 8). In Lower Bay, the proportion of Southern Flounder classified as estuarine residents during the age-0 growth phase was highest (96%) when river discharge was low and decreased (down to 73%) with increasing freshwater river discharge. Similarly, the proportion of flounder classified as transients. In Lower Bay was highest (27%) when freshwater river discharge was high and declined (down to 4%) in years with low freshwater river discharge (Figure 8). Taken together, these results from multinomial logistic regression suggest that adult Southern Flounder (ages 1–3) collected across our three regions in the Delta and Mobile Bay likely settled in and spent their age-0 growth phase in the same region in which they were collected, suggesting little movement occurs between regions in Mobile Bay during the estuarine residency phase. Finally, the proportion of residency classifications during the age-0 growth phase for fishery-dependent samples was unrelated to annual variability in river discharge. The one exception to this pattern in the fishery-dependent data was the 2005 cohort (Figure 8). The proportion of freshwater, estuarine, and transient classifications during the age-0 growth phase of the 2005 cohort largely matched those predicted for Lower Bay as a function of annual river discharge.
DISCUSSION
Southern Flounder are marine migrants, requiring offshore habitats to spawn but inshore estuarine habitats for juvenile growth and development (Burke et al. 1991; Glass et al. 2008). Similar to previous otolith chemistry studies across the northern Gulf of Mexico (Lowe et al. 2011; Farmer et al. 2013; Nims and Walther 2014), we found that Southern Flounder in a large, river-dominated estuary had a diversity of residency patterns during their first 4 years of life. Differences in residency patterns did not appear to be driven by divergent postsettlement migratory behaviors but rather by Southern Flounder settling and remaining in specific regions of the estuary, each with distinctive annual salinity regimes. Southern Flounder collected in fishery-independent samples from a given region typically had age-0 otolith signatures that matched the expected patterns of salinity exposure in the region of collection based on long-term salinity monitoring and annual discharge patterns. Additionally, we found that the probability of a Southern Flounder being classified as a transient during the age-0 phase was significantly related to mean annual river discharge and region of collection. These results suggested that changing salinity conditions around sedentary fish are likely responsible for age-0 transient classifications. As expected under this hypothesis, years of high freshwater river discharge led to higher probabilities of freshwater classifications and lower probabilities of transient classifications in the Delta and Upper Bay. In Lower Bay, years of high freshwater river discharge led to lower probabilities of estuarine classifications and higher probabilities of transient classifications. Therefore, we believe fish classified as transient are not actively moving across salinity gradients during their first year of life but, instead, are settling and residing in regions where freshwater conditions are transient, with the arrival and departure of freshwater conditions largely dictated by river discharge.
Contrary to the putative life history (Powell and Schwartz 1977; Rogers et al. 1984), we did not see strong evidence in age-specific analysis of fishery-independent samples that all Southern Flounder sought out freshwater to oligohaline habitats during the age-0 phase then slowly moved back towards higher salinity waters during older ages. Instead, many larger and older (age-1+) Southern Flounder collected in the Delta and Upper Bay appeared to remain in freshwater habitats for extended durations and many Southern Flounder in Lower Bay never appeared to experience freshwater conditions for extended durations. These results suggest that freshwater habitat use may be facultative for this species, as Nims and Walther (2014) also suggested for Southern Flounder in Texas estuaries. It should be noted that our fishery-independent samples contained few age-2+ individuals. This could be due to older, age-2+ fish reaching sexual maturity and moving offshore to spawn. A recent study in the north-central Gulf of Mexico estimated that age at 50% maturity was 0.97 years for female Southern Flounder (Corey et al. 2017). If some older age-2+ Southern Flounder from the Delta and Upper Bay remain in the estuary, the putative life history suggests that these older fish would seek out higher salinity habitats in the lower estuary. However, our fishery-independent samples did not collect older, age-2+ individuals in the lower estuary with transient signals (i.e., freshwater early in life followed by estuarine later in life). Likewise, there was little evidence of up-estuary movement after settlement in Lower Bay. Taken together, otolith chemistry results from our fishery-independent collections suggest most Southern Flounder remain in the region of settlement during their estuarine residency phase.
Lifetime and age-specific patterns of otolith Sr:Ca in fishery-dependent samples (collected from the commercial and recreational fisheries) differed from observed Sr:Ca patterns in our three fishery-independent sampling regions. Overall, a majority of fishery-dependent lifetime residency patterns were transient, which was higher than the proportions of transients from any of our three fishery-independent collections regions. Also, there were very few lifetime freshwater residents observed in fishery-dependent samples. Age-specific residency patterns suggest that the majority of Southern Flounder in our survey of the commercial and recreational fisheries resided in habitats with variable salinities during the age-0 growth phase. In Mobile Bay, these conditions would be most common in the upper and middle portions of the bay, where proximity to the mouths of large rivers creates freshwater conditions during periods of high discharge in the spring followed by periods of elevated salinities (>1 psu) in response to lower river discharge during late summer and fall. However, age-specific patterns during older ages (age 1+) for fishery-dependent samples suggest that most flounder resided in the Lower Bay region or similar habitats with elevated salinities prior to harvest. These age-specific patterns for fishery-dependent samples, which suggest decreasing freshwater exposure at older ages, differ from age-specific patterns observed in fishery-independent samples. It should be noted that fishery-dependent flounder were, on average, older than fishery-independent flounder, which may contribute to differences in age-specific residency patterns. The lack of older individuals in fishery-independent samples may explain the higher proportion of freshwater residences, as these individuals have not migrated to high-salinity waters, which would change their lifetime classification to transient.
With the goal of better understanding where harvested Southern Flounder resided during their first year of life, we compared the annual age-0 residency proportions from fishery-dependent samples to those from fishery-independent samples, which have known collection locations. We found that annual age-0 residency proportions in fishery-dependent samples were unrelated to annual variability in river discharge and that the proportions of age-0 residency classifications for fishery-dependent samples included very few freshwater residents. With the exception of 2005 (which matched well with predicted proportions for the Lower Bay), fishery-dependent age-0 residency proportions also did not match predicted annual proportions from the Upper Bay or Lower Bay regions after accounting for the effect of river discharge. This suggests that Southern Flounder harvested in fisheries appear to be an aggregate of fish that spent their first year of life in different regions, possibly including areas that were not well sampled by fishery-independent collections in our study. Additionally, as the collection location is unknown for fishery-dependent samples, it is possible that some flounder in these collections were harvested in adjacent estuaries to Mobile Bay, which would likely have a higher annual salinity regime due to lower freshwater inflow in nearby estuaries.
The lack of freshwater residents in fishery-dependent samples suggests that Southern Flounder residing in freshwater regions may experience lower fishery exploitation compared to those residing in higher-salinity areas. If true, this has important implications for management of the species, as the portion of the stock that settles and remains in freshwater may be functionally protected from harvest. Previous studies that examined fishery exploitation patterns across differing migratory contingents or spatially distinct population segments have suggested that unexploited contingents or population segments may provide overall stability or resilience to the population (Fogarty 1998; Kerr et al. 2010; Gahagan et al. 2015). Previous studies have suggested and explored the extent to which offshore movement of adult Southern Flounder may allow for a portion of the stock to remain cryptic to the fishery (Midway et al. 2018). We suggest that additional effort be devoted to understanding the spatial distribution of harvest pressure across estuarine salinity gradients for Southern Flounder. Analysis of spatially specific creel survey data across estuarine salinity gradients could potentially provide information to fill this knowledge gap.
To our knowledge, this is the first study to use otolith chemistry from Southern Flounder collected from both fishery-independent and fishery-dependent across a diversity of inshore habitats (i.e., freshwater to oligohaline) within an estuary. Our findings highlight the importance of collecting individuals with fishery-independent sampling from known locations across the entire salinity gradient when evaluating lifetime residency patterns to ensure that all potential migratory contingents or population segments are represented in the data. Additionally, collecting fish across a large temporal frame allows for interpretation of fish movements over different environmental conditions (e.g., different annual discharge regimes). Finally, fishery-dependent samples from unknown locations were important for understanding the contribution of different residency classifications to the commercial and recreational fisheries.
Our findings align with previous studies that suggest both freshwater and estuarine habitats play an important role in providing suitable habitat for growth and development of Southern Flounder within Gulf of Mexico estuaries (Lowe et al. 2011; Farmer et al. 2013; Nims and Walther 2014). Specifically, Farmer et al. (2013), who examined otolith chemistry from fishery-independent Southern Flounder samples collected in freshwater and oligohaline habitats (<5 psu) in the Delta and Upper Bay, found lifetime residency classifications (95% flounder assayed: 16% freshwater, 37% transient, 42% estuarine residencies) proportionally similar to the fishery-independent lifetime residency patterns observed in this study (25% freshwater, 45% transient, 30% estuarine residencies). Southern Flounder collected in Texas estuarine habitats (>5 psu) showed much lower utilization of freshwater habitats (Nims and Walther 2014). Analysis of Nims and Walther (2014) otolith chemistry data from Texas using the methods from this study (i.e., proportional oligohaline residencies of 0–10% = estuarine, 10–90% = transient, and 90–100% = freshwater residencies) revealed lifetime residency classifications of 4% oligohaline (<5 psu), 36% transient, and 60% estuarine residencies (data acquired using GraphGrabber V2.0). Nims and Walther (2014) used a 5 psu oligohaline threshold rather than a 1 psu freshwater threshold, indicating that freshwater residency proportions were potentially even lower than the 4% that resided in oligohaline habitats. Higher utilization of estuarine compared to freshwater (<1 psu) habitats has also been observed by other Southern Flounder studies in Texas (Glass et al. 2008; Nañez-James et al. 2009). Follow-up studies that investigated the ecological consequences of freshwater residence appear needed for this species. Specifically, recent work suggests that freshwater habitats are suboptimal for osmoregulation and growth of juvenile Southern Flounder (Howson and Targett 2020). However, if freshwater habitats have lower predation risk than estuarine habitats, lower mortality may be an acceptable trade-off for slower growth (sensu Werner et al. 1983). Additionally, freshwater regions of Mobile Bay may reduce the risk of sex reversal (Luckenbach et al. 2003), as these regions typically warm slower during spring compared to downstream, shallower regions of the estuary. Previous work in North Carolina documented that warmer springtime temperatures were correlated with higher proportions of male Southern Flounder in North Carolina estuaries (Honeycutt et al. 2019). Future work investigating sex reversal in Southern Flounder may also examine how the spatial gradient of temperatures across salinity gradients within estuaries affect rates of sex reversal.
Water and otolith Sr:Ca values were used to develop a freshwater threshold (≤1 psu) for Southern Flounder in Alabama's coastal waters. The water Sr:Ca freshwater threshold of 5.53 ± 0.16 (mean ± standard deviation) in Mobile Bay was similar to the water Sr:Ca oligohaline (<5 psu) threshold of 5.23 ± 1.23 from Texas (Seeley and Walther 2018). The otolith freshwater (≤1 psu) threshold value calculated in this study (1.71 mmol : mol Sr:Ca) was empirically quantified to be 1 psu rather than assumed to approximate 2 psu, as was the case with previous studies using otolith chemistry to study Southern Flounder residency patterns in Mobile Bay (Lowe et al. 2011; Farmer et al. 2013). Otolith Sr:Ca was able to effectively delineate water salinities above and below the 1 psu threshold; however, Sr:Ca quickly saturated within the otolith at salinities above 1 psu. This general trend of otolith Sr:Ca quickly saturating within the otolith as salinities increase has been previously documented (Walther and Limburg 2012; Nelson et al. 2018), although the results are system- and species-specific. The results of our residency analysis could be skewed towards classifying individuals living in consistently low-salinity, oligohaline habitats (1–5 psu) as estuarine residents.
We also investigated using Ba:Ca as an indicator of salinity exposure, as some previous work with Southern Flounder in Texas estuaries have found Ba:Ca a useful marker of low salinity experience (Nims and Walther 2014). Previous work in Mobile Bay has indicated that Ba:Ca does not mix conservatively with salinity and exhibits greater concentrations under low flow conditions, leading to fluctuating water Ba:Ca with changing discharge and seasonality (Nelson and Powers 2020). Furthermore the Ba:Ca partition coefficient was more variable and increased with increasing salinity, which indicates higher uptake of Ba at higher salinities. This has the potential to lead to artificially elevated otolith Ba:Ca levels at higher salinities by causing estuarine habitats with elevated salinities and lower ambient Ba:Ca levels to leave similar Ba:Ca otolith signatures as freshwater habitats, which have lower ambient Ba:Ca levels. Instability of Ba partition coefficients across salinity gradients has also been documented for several other species (Nelson and Powers 2020). Given this, Ba:Ca ratios in the otolith may not be informative of salinity changes if freshwater endmembers are too high.
Several assumptions were necessary when classifying otolith chemistry data into residency patterns (Elsdon et al. 2008; Walther 2019). First, water Sr:Ca, collected at the same time as fish collection, was assumed to be representative of the last 30 d, which corresponded to the outer portion of the otolith transect from which elemental concentrations were related to water chemistry. Salinity observations collected every 2–3 weeks during summer site visits during 2018–2019 suggested this was generally true, but some variability did occur, as expected. Second, we analyzed the outer edge (~30 d of otolith increments) for Sr:Ca. We assumed Southern Flounder collected at a given location had remained in that location for at least 30 d prior to collection. Conventional tagging of Southern Flounder in the mid-Atlantic showed limited movement (<1 km) during summer estuarine residency (Craig et al. 2015), but acoustic telemetry suggests high-frequency, small-scale movements among habitat types occurs frequently in juvenile Southern Flounder (Furey et al. 2013). Additionally, once a change in salinity occurs due to either changing ambient salinity or movements among nearby habitat types, otolith elemental concentrations can take 21 d to reach equilibrium (Lowe et al. 2009). The result of all of this is that otolith chemistry is not an exact deterministic product of salinity exposure but, rather, an interpretation of a fish's complex life history (Walther 2019). Accordingly, our 1 psu freshwater threshold was an approximation, as the true salinity experience of sampled individuals during the last 30 d of life was estimated from a single water chemistry sample at the time of collection.
Several flatfish species exhibit variation in otolith mass and elemental composition between left and right otoliths (Sipe and Chittenden 2001; Loher et al. 2008; Kajajian et al. 2014; Gao et al. 2015). To increase sample size, left otoliths were corrected to resemble right otoliths. Left Southern Flounder otoliths in this study exhibited significantly lower mass and Sr:Ca values than right otoliths. Consistent with Pacific Halibut Hippoglossus stenolepis (Loher et al. 2008) and Summer Flounder Paralichthys dentatus (Kajajian et al. 2014), the blind-side otolith of Southern Flounder exhibited a larger mass. Sr:Ca values did not exhibit a consistent change across species. The overall impact of correcting the left otoliths had little effect on the outcome of the study, with only 2 out of 50 individuals experiencing a change in their lifetime residency classification. Both of these individuals changed from transient to estuarine classifications. One potential physiological cause of mass differences in paired sagittal otoliths in sinistral Southern Flounder, which lay on their right side, is that right otoliths are larger due to the gravitational pull of elements towards the right otolith, which is below the left otolith in orientation. Another potential explanation for larger right otoliths is that nutrient flow to otoliths may be altered during the larval craniofacial metamorphism. Increased mass deposition in the lower otolith may be a consistent trait with flatfish species, as this has been documented in sinistral summer flounder (Kajajian et al. 2014) and dextral Pacific Halibut (Loher et al. 2008).
Several factors in addition to salinity may influence flounder residency patterns that are not quantifiable with otolith chemistry. Other factors, including food web dynamics, abiotic conditions, predation pressure, and other variables, ultimately determine true habitat quality, potentially driving fish residency and movements (Burke 1995; Zucchetta et al. 2010; Furey and Rooker 2013). Future evaluation of prey availability, diets, and growth rates across estuarine salinity gradients may provide further insights into the relative importance of freshwater versus estuarine habitats for Southern Flounder growth and survival.
The results of this study have several management implications for Southern Flounder, which are currently experiencing a population decline across their entire range (Lee et al. 2018; Erickson et al. 2021). Following the nursery-role hypothesis from Beck et al. (2001) and Dahlgren et al. (2006), it appears that nursery habitats for Southern Flounder encompass a diversity of salinity concentrations and that habitats from across the estuarine salinity gradient play an important role in contributing Southern Flounder recruits to the adult (age-1+) commercial and recreational fisheries. Since lifetime transient individuals form a large proportion of the fishery-dependent samples, protecting both freshwater and high-salinity habitats ensure connectivity between all potential habitats exploited by flounder during ontogenetic growth and development. Protection of diverse habitats within estuaries would also preserve the life history diversity, potentially increasing resiliency against future environmental and harvest pressures.
ACKNOWLEDGEMNTS
Thanks to Kevin Anson, John Mareska, and Craig Newton from the Alabama Department of Conservation and Natural Resources, Marine Resources Division for supplying Southern Flounder otoliths from fishery-independent and fishery-dependent collections. Special thanks to Dr. Matt Catalano for assistance with project development and management. Thanks to Dr. Sean Powers, Crystal Hightower, and the Dauphin Island Sea Lab for assisting with sample collection from the Alabama Deep Sea Fishing Rodeo. Thanks to Meghan Angelina for assisting with data collection and processing. Thanks to Mason Collins, Jacob Moreland, and Hannah Mulligan for assistance with field collections. This research was funded by the Alabama Department of Conservation and Natural Resources through Federal Aid in Sport Fish Restoration Project F18AF00231 to M. Catalano and T. M. Farmer. Additional support was provided by the Clemson University Creative Inquiry and Undergraduate Research Program. There is no conflict of interest declared in this article.