Transactions of the American Fisheries Society 136:1285–1297, 2007 [Article] Ó Copyright by the American Fisheries Society 2007 DOI: 10.1577/T06-223.1

Tracking Nursery Habitat Use in the Estuary, , by Young American Shad Using Stable Isotopes

1 J. C. HOFFMAN,* D. A. BRONK, AND J. E. OLNEY Virginia Institute of Marine Science, Post Office Box 1346, Gloucester Point, Virginia 23062, USA

Abstract.—We developed and applied a stable isotope turnover model to estimate how long age-0 American shad Alosa sapidissima reside within tidal freshwater and brackish-water habitats in the York River estuary, Virginia. The residence time was estimated by modeling the changing stable isotope ratio (either the carbon [d13C] or sulfur [d34S] stable isotope ratio) of an age-0 American shad as it migrates seaward from its present habitat to a new habitat and determining the minimum time required to acquire the isotopic signature of its new habitat. A sensitivity analysis of our turnover model indicates that the results are robust at relatively fast turnover rates, such as those experienced by young fish, but that at slow turnover rates the model can yield biologically meaningful differences with relatively small changes in variables. The average 6 SE isotopic ratios for the dorsal muscle tissue of age-0 fish increased along the estuary, from 31.8 6 0.3% for d13C and 5.2 6 0.7% for d34S at the farthest upriver region to 21.8 6 1.2% for d13C and 10.3 6 1.7% for d34S in the lower estuary, and were significantly different among regions. To account for these distinct signatures along the estuary, the turnover model predicts that age-0 fish remain in discrete regions (;10 river kilometers) of the tidal freshwater portion of the river for at least 15–45 d and in the lower estuary for at least 32–66 d. Juveniles, therefore, are spatially segregated, and probably migrate slowly downstream during the summer and early fall, accumulating in the lower freshwater and oligohaline portions of the estuary before their oceanic migration.

American shad Alosa sapidissima, the largest North as the carbon (C) stable isotope ratio, tend to closely American anadromous clupeid, migrate from their resemble their prey (DeNiro and Epstein 1978; Fry and freshwater nursery habitat to the ocean in their first Sherr 1984). Stable isotopes, therefore, offer the year of life. Investigators propose both temperature- potential to track habitat changes when either (1) based migration, consistent with fall migration (e.g., movement is related to ontogenetic niche (diet) shifts Leggett and Whitney 1972; Williams and Bruger 1972; or (2) the habitats of interest possess distinct O’Leary and Kynard 1986; Hoffman et al., in press) biogeochemical properties, such as a switch from fresh and size-based migration, migration occurring as early to marine waters, and the rate of movement between as June (Marcy 1976; Limburg 1996). A detailed habitats is faster than the rate of change of the isotope analysis of the age-structure of Hudson River age-0 ratio in the animal’s tissue (Hobson 1999). Thus, the American shad suggests that age-0 fish move about animal arrives at the new habitat with an isotopic 120 km downriver in about 2 weeks (Limburg 1996), composition indicative of its previous habitat. After implying rapid movement through their freshwater settling into the new habitat, the animal’s tissues will habitat. Given the coast-wide concerns regarding acquire the isotope ratio specific to that habitat. American shad population declines (ASMFC 1999), The ability to quantify the timing of these move- which are, in part, due to habitat degradation (e.g., ments (or diet shifts) is dependent on the turnover rate Limburg et al. 2003), further measures of age-0 in the tissue being analyzed (Tieszen et al. 1983; American shad habitat use, including the spatial scale, Hobson and Clark 1992). The turnover rate, in turn, duration, and rate of seaward migration, are needed. depends on growth and metabolism. Growth turnover Stable isotopes have been applied to document occurs as new tissue is added, diluting the pool of older movement patterns in a variety of animals (Hobson tissue derived from the previous diet. Metabolic 1999). Certain stable isotope ratios of consumers, such turnover occurs as older tissue is broken down and new tissue synthesized. In both slowly and rapidly growing fish, growth dominates stable isotope turnover * Corresponding author: [email protected] (Fry and Arnold 1982; Hesslein et al. 1993; Herzka and 1 Present address: U.S. Environmental Protection Agency, National Health and Ecological Effects Research Laboratory, Holt 2000; MacAvoy et al. 2001; Sakano et al. 2005) Mid-Continent Ecology Division, 6201 Congdon Boulevard, and metabolism can accelerate the turnover rate beyond Duluth, Minnesota 55804, USA. that exerted by growth alone (Frazer et al. 1997; Received October 5, 2006; accepted May 3, 2007 Vander Zanden et al. 1998; Herzka et al. 2001; Published online August 2, 2007 Trueman et al. 2005).

1285 1286 HOFFMAN ET AL.

Two different models are commonly used to model turnover. Fry and Arnold (1982) proposed the following power model:

c Rf ¼ Rf þðRi Rf Þ 3ðWi=WtÞ ; ð1Þ 13 where Rt is the stable isotope ratio (e.g., d C) of the animal or tissue at time t, Rf is the stable isotope ratio at equilibrium, Ri is the initial stable isotope ratio, Wi and Wt represent the initial weight and weight at time t, respectively, and c is the turnover coefficient. The model simplifies to dilution-only turnover (i.e., growth only) when c ¼1 and can be used to date ecologically significant events associated with changes in isotopic ratios (Fry and Arnold 1982), such as age at settlement of fish larvae (Herzka et al. 2001). Hesslein et al. (1993) used an exponential model with terms for a specific growth rate (k ¼ loge[Wt/Wi]/t) and a metabolic rate (m), as follows:

ðkþmÞt Rt ¼ Rf þðRi Rf Þ 3 e ; ð2Þ where i indicates the ratio at t ¼ 0 and f the equilibrium ratio. The advantages of this model are that time, t,is an explicit term and that m can be estimated using a curve-fitting procedure if k is known. If Rf and Ri are both known (e.g., the isotopic signatures of two FIGURE 1.—A comparison between (a) Hesslein et al.’s habitats with distinct isotopic distributions), then the (1993) turnover model and (b) the model proposed in this equation can be solved directly for the equilibrium time study. For both models, results are shown over 100 d for a population in freshwater at t ¼ 0 with a d13C ¼28.0% ( R ;a (teq) theoretically required for the isotopic signature of i the population in the first habitat to resemble that in the typical riverine value) that moves into a marine habitat with an equilibrium value of 20.0% (Rf). The combined growth and second (Rf) upon moving into the second habitat. However, the time required for R to exactly equal R is metabolic rates are 0.05/d. In panel (a), the isotopic turnover t f ‘‘half-life’’ is 14 d; in panel (b), the time required to reach infinite because the model has an asymptote at R f equilibrium (t ) is 56 d. In the proposed model, SD ¼ 1 for R (Figure 1a). eq i and Rf, and n ¼ 25 fish. The figure shows the mean value of To resolve this problem, the turnover ‘‘half-life’’ d13C at time t (R ; solid line) and the SDs around the mean (i.e., the time required to reach one-half the difference t (dashed lines). The probability distribution function of Rf is between the initial [Ri] and final [Rf] isotopic ratios; shown to the right. The Kolmogorov–Smirnov (K–S) test was Figure 1a) is often estimated. It would be better, run at each daily time step (P-value: gray line). however, to have a biologically meaningful estimate of the teq than a convenient reference point along the transition. To achieve this, we propose a statistical turnover rate model. To evaluate the model, a method (Figure 1b). If Rf and Ri are variables with some mean and standard deviation, then we can define sensitivity analysis was done by calculating the effect on the estimate of the time to equilibrium, t ,by teq as the time at which the distribution of Rt is not eq changing the model variables (i.e., R , R , and k þ m) significantly different from that of Rf at some i f and population variables (i.e., the number of fish probability level (e.g., a ¼ 0.05). Now teq is not infinite. It represents both the minimum residence time sampled [n] and the standard deviations of Ri and Rf). 13 required to reach approximate equilibrium and the We surveyed the d C of age-0 American shad during period during which we can estimate how long ago the their summer residence in the upper York River organism (or population) arrived in its new habitat estuary, Virginia, and subsequent migration to Ches- (after which the organism will have an isotopic apeake Bay to determine whether habitat-specific signature similar to that of its new habitat). signatures were present. We then measured the d13C Our objective was to estimate habitat-specific and sulfur stable isotope ratios (d34S) of age-0 residence times (teq) by applying a stable isotope American shad at selected locations and times to apply NURSERY HABITAT USE BY AMERICAN SHAD 1287

FIGURE 2.—The Mattaponi River, Virginia. The inset shows its location with respect to Chesapeake Bay (CB). River kilometer (rkm) 0 is the mouth of the York River. During the study period the upstream limit of salt intrusion was generally at about rkm 76.

the model and estimate teq for various regions along the randomly chosen from each. During 2002, river estuary. kilometer (rkm) 76 was generally about the upstream limit of salt incursion, depending on discharge and tide Methods stage. Surveys began at the uppermost end of the Field sampling.—Age-0 American shad were sam- nursery zone, at rkm 109 (the Mattaponi River mouth is pled in the Mattaponi River, part of the freshwater at rkm 52 and the York River mouth at rkm 0) and nursery grounds in the York River estuary, and the proceeded down-river. Additionally, age-0 American brackish York River during their migration to Ches- shad were captured in the York River (rkm 0–52) from apeake Bay. The York River is located in the southern November 2002 to March 2003 by the Virginia Chesapeake Bay and is formed by the confluence of the Institute of Marine Science Juvenile Finfish and Blue Mattaponi and rivers, both of which are Crab Trawl Survey (9.1-m semiballoon otter trawl, almost entirely fresh (Figure 2). American shad hatch 6.34-mm-mesh cod end). The survey sampled the York from March through July in the freshwater portions of River estuary monthly using a mixed random and the Mattaponi and Pamunkey rivers (Bilkovic et al. fixed-station design (metadata are available at www. 2002; Hoffman and Olney 2005). fisheries.vims.edu/trawlseine/methods.htm). In both We studied the Mattaponi River because age-0 surveys fish were stored on ice in the field and frozen American shad are more abundant there than in the upon arrival at the laboratory. (Wilhite et al. 2003). During 2002, Stable isotope analysis.—We surveyed d13C ratios age-0 American shad were sampled in the tidal in age-0 American shad throughout the year to assess freshwater portion of the Mattaponi River every week temporal variability and determine whether habitat- from May through July with a bow-mounted push net specific ratios were present. We analyzed fish from (1.5-m 3 1.5-m opening, 5.2-m-long net, 1.27-cm- every other sample (i.e., bi-weekly) because we stretch-mesh cod end). Twelve stations were sampled anticipated that this period was about half the time on each survey. The freshwater habitat was sectioned necessary for age-0 shad to reach isotopic equilibrium into three strata of equal size, and four stations were based on previously published growth rates (Hoffman 1288 HOFFMAN ET AL. and Olney 2005). For d13C analysis, age-0 fish were were measured (61 mm TL), weighed (60.01 g), and sorted into size-classes (,40, 40–59.9, 60–79.9, and rinsed thoroughly with de-ionized (DI) water. For fish .80 mm total length [TL]) and regions (rkm 104–109, selected for d13C and d34S analysis (i.e., for the model 95–100, and 74–87) by sampling date. The regions application), dorsal muscle tissue was removed, rinsed were chosen based on river geomorphology and with 10% HCl (American shad have intermuscular salinity. Fish from each size-class exceeding 40 mm bones that are difficult to remove), rinsed with DI TL, region, and date were subsampled for stable water, homogenized, divided for separate analyses, and isotope analysis by randomly selecting 10 fish of each dried at 458C for 24 h. The d13C samples (;1mg size-class. If fewer than 10 age-0 fish were available, tissue) were analyzed with an ANCA GSL elemental then all the fish were sampled. Only age-0 American analyzer and Europa Hydra 20–20 isotope ratio mass shad exceeding 40 mm TL were used for two reasons: spectrometer (IRMS; University of California–Davis first, it is the size at which age-0 shad fully recruit to Stable Isotope Facility). The standard deviation (SD) the push-net gear (Hoffman and Olney 2005), and between replicate d13C standards was 0.04% and that second, this is the earliest size at which migration from between randomly assigned replicate tissue samples the nursery zone has been documented (Limburg was 0.10%. The d34S samples (;6 mg tissue) were 1996). All American shad captured in the York River analyzed with a Carlo Erba NC2100 elemental analyzer 13 were sampled for d C. and Finnegan DELTA-plus Advantage IRMS (Colo- For the modeling application, we compared turnover rado Plateau Stable Isotope Laboratory, Northern 13 34 model results using either d Cord S. These isotopes Arizona University). The SD between replicate labo- were chosen because trophic discrimination (i.e., the ratory d34S standards was 0.20%. For fish selected for difference in isotopic composition between a consumer d13C analysis only (i.e., for isotopic equilibrium and its diet) is small for both C and S (Peterson and Fry evaluation), the d13C samples were analyzed as 1987; Hesslein et al. 1991) and both C and S have been previously described, with similar error. used as a marine tracer (e.g., Hesslein et al. 1991; Stable isotope ratios are reported in dX notation, MacAvoy et al. 2001). The same American shad were 3 34 13 where dX ¼ ([Ratiosample/Ratiostandard] 1) 3 10 , and sampled for both d S and d C to directly compare the X is the stable isotope of carbon (C) or sulfur (S), Ratio two stable isotopes. We analyzed a subsample of fish is the ratio of light to heavy isotopes, and the standards captured owing to the expense of analyzing both are Pee Dee belemnite and Canyon Diablo trilobite for isotopes. We analyzed age-0 shad collected in the C and S, respectively. Samples were not corrected for Mattaponi River on 30 June 2002 and in the York lipid content (lipids are d13C depleted relative to River 13 January 2003. These dates were chosen carbohydrates and proteins [DeNiro and Epstein 1977]) because age-0 fish had acquired regionally distinct, because atomic C:N was low and similar among constant stable isotope ratios by midsummer based on muscle samples from the three Mattaponi River regions the season-long d13C data (described previously). We (average, 3.5; one-way ANOVA between regions: df ¼ randomly selected 10 fish from regions along the 2, F ¼ 0.61, P ¼ 0.5), indicative of low lipid content estuary, as in the season-long d13C survey regions (Sweeting et al. 2006). (Mattaponi River: rkm 104, rkm 96 and 102, rkm 85 Turnover model development.—We modified Hes- and 89, and rkm 74 and 78; York River: rkm 13). slein et al.’s (1993) turnover rate model so that it could Adjacent stations were combined to obtain 10 fish, be applied to a population by assuming that each R though only 7 were available from rkm 74 and 78. To term represents the mean of a distribution. Thus reduce potentially confounding effects from size- related diet shifts, we sampled larger juveniles and ðkþmÞt R¯ t ¼ R¯ f þðR¯ i R¯ f Þ 3 e : ð3Þ fish of a similar size within a region. Fish 40–59.9 mm TL were sampled from rkm 104, rkm 96 and 102, and The model describes the mean isotopic ratio of a ¯ rkm 85 and 89. Fish 60–79.9 mm TL were sampled population at time t (i.e., Rt) as it approaches isotopic ¯ from rkm 74 and 78 and fish 80–99.9 mm TL from rkm equilibrium with the new habitat (or diet), where Rt is 13. Neither d13C nor d34S were significantly different the mean of the population at equilibrium with the ¯ between pooled stations (t-test, a ¼ 0.05). Differences original habitat and Rf is the population’s mean once at among regions were tested using one-way analysis of equilibrium with its new habitat. Of course, Rt, Rf , and variance (ANOVA) and a Tukey’s post hoc compar- Ri each have an associated underlying distribution. An ison. appropriate statistical test, therefore, can be applied to

American shad were frozen until analysis because the distributions of Rt and Rf to determine the time, teq, freezing has negligible effects on isotopic ratios at which the mean isotopic signature of the recently (Bosley and Wainright 1999). After being thawed, fish arrived population is not significantly different from NURSERY HABITAT USE BY AMERICAN SHAD 1289

13 the mean isotopic signature of the new habitat (i.e., H0: region to the trend in age-0 d C with respect to their Rt ¼ Rf at a ¼ 0.05; Matlab 7.0.1; see Appendix for change in weight (i.e., growth). Finally, we compared code). each region’s mean d13C with typical prey d13C ratios To verify that the distribution-based turnover model to determine whether the population means were projected the mean isotopic ratio in the same manner as isotopically representative of each region. the original model, we simulated the seaward migration Model application to field data.—We used the of 25 age-0 American shad with a typical growth rate (k distribution-based turnover model to predict the

¼ 0.05/d; Hoffman and Olney 2005) and no metabolic minimum residence time (teq) required for an age-0 turnover (i.e., k þ m ¼ 0.05/d). We simulated their American shad to isotopically equilibrate to the habitat muscle tissue to turn over from a d13C representative of immediately downstream. We modeled the progression ¯ feeding and growth within a freshwater river habitat (Rt of a fish’s isotopic ratio by projecting the range of ¯ ¼28%,SD¼ 1.0) to that within a marine habitat (Rf values it would have through time after moving to the ¼20%,SD¼ 1.0; Limburg 1998). The modified next region immediately downstream (e.g., those model yields the same projection and predicts that the captured at rkm 104 were simulated to move to rkm fish arrive at equilibrium in about 56 d (Figure 1b), 96–102) and then statistically determined whether that compared with an isotopic half-life of 14 d (Figure 1a). range was significantly different from the range of fish We performed a sensitivity analysis on the model. already in that habitat. For this we used a Monte-Carlo 13 The teq, defined as the first day when a Kolmogorov– approach. Each fish began with its measured d Cor 34 Smirnov (K–S) test yielded a P-value greater than 0.05 d S ratio (Ri). The model was run 100 times for each (i.e., there was no longer a significant difference of about 10 fish sampled in a region by randomly between the distributions), was obtained under four selecting 100 Rf values drawn from a normal isotopic gradients (DR ¼ Rf Ri ¼ 5, 2, 1, and 0.5), five distribution having the region-specific mean and SD (k þ m) values (0.2, 0.1, 0.05, 0.01, and 0.001), two estimated from the d13C and d34S data from the next ¯ ¯ ¯ standard deviations (1.0 and 0.5), and two sample sizes region downstream (i.e., Rf,96–102, Rf,85–89, Rf,74–78, and ¯ (n ¼ 10 and 100). In all trials both Ri and Rf were Rf,13). The fish was then projected through time toward assumed to have the same SD and n. Turnover was each of those 100 Rf values. The Ri and Rf values and simulated using a normal distribution to represent Ri their associated distributions were determined from ¯ 13 and Rf (Rt ¼30% d C, which was chosen independent, spatially disparate fish samples. arbitrarily). The K–S test was applied to Rt and Rf at For each fish, an estimate of teq was obtained. At each daily time step. each 5-d time step, a K–S test was used to determine

Identification of habitat-specific ratios.—We used whether Rt ¼ Rf at a ¼ 0.05 (i.e., whether the present the season-long survey of age-0 d13C ratios (1) to isotopic ratio of fish migrating from the upstream quantify the stable isotope gradient across the estuary habitat was no longer significantly different from those and thereby verify that habitat-specific ratios were in the downstream habitat), where Rt is the frequency present and (2) to ensure that habitat-specific ratios distribution of the 100 d13Cord34S values at time t and were constant in time. Our concern was that our model Rf is the frequency distribution of the 100 randomly ¯ application would be problematic if the Rf and SD selected Rf values (estimated from each region). As (which are estimated from field data taken on a single before, teq was defined as the first day when P . 0.05. day) did not represent the long-term signature of each We summarized the results by averaging the teq values habitat. This could occur if the fish were not in for each region (i.e., if 10 fish were simulated, we equilibrium with the habitat (e.g., if they had not been averaged the 10 teq values). resident for sufficient time). To quantify the isotopic We made two assumptions about growth when gradient across the estuary, we estimated population applying the turnover model: first, that growth is mean d13C ratios and SDs for each region within the constant (k ¼ 0.05/d) and second, that growth could Mattaponi River (rkm 105–109, 95–100, and 74–87) account entirely for isotopic turnover (i.e., m ¼ 0). The and the low-salinity (0–15%) portion of the York first assumption is consistent with a growth variability River (rkm 19–52). Because age-0 fish were randomly study of juvenile American shad from the adjacent subsampled by length-class, we estimated the popula- Pamunkey River (Hoffman and Olney 2005). We tion’s mean (analogous to Rf) and SD within a region tested the second assumption by fitting Fry and 13 by weighting d C using the region-specific length– Arnold’s (1982) model (equation 1; Wi ¼ 0.1 g [the frequency distribution in the catch. We assessed wet weight at metamorphosis]) to the d13C ratios of whether the d13C ratio was constant in each habitat fish captured in the upriver habitat (rkm 104–109) (implying that isotopic equilibrium was reached) by during a period in which a marked d13C depletion comparing the population’s mean d13C within each (approximately 6%) occurred. We used only those 1290 HOFFMAN ET AL.

IGURE F 3.—Time required to reach stable isotope equilibrium (teq) for various isotopic gradients (DR ¼ Rf Ri) and combined growth and metabolic rates (k þ m) when changing the power of the Kolmogorov–Smirnov test by altering the number of fish in the sample (n) and the standard deviations of Rf and Ri.

2 age-0 fish with Wt/Wi 25 (fish captured from 27 May K–S test (i.e., 0.5 SD and n ). At the slowest turnover to 15 July, or from metamorphosis at ;25 mm to ;65 rate (k þ m ¼ 0.001) and DR ¼ 5, teq increases from mm TL). The model was fit using nonlinear regression about 1,861 d (n ¼ 10, SD ¼ 1.0) to 2,370 d (n ¼ 10, SD (S-Plus 2000). ¼ 0.5) to 2,882 d (n ¼ 100, SD ¼ 1.0) and to 3,550 d (n ¼ 100, SD ¼ 0.5). At the fastest turnover rate (k þ m ¼ Results 0.2) and DR ¼ 5, the teq estimated with the lowest Model Sensitivity statistical power (n ¼ 10, SD ¼ 1) is about 10 d,

Absolute differences in teq between isotopic gradi- whereas it increases to about 15 d by increasing the ents (DR) are much greater at slow turnover rates than sample size (n ¼ 100, SD ¼ 1) or decreasing the SD (n at rapid rates (Figure 3). For example, at a rapid rate (k ¼ 10, SD ¼ 0.5). It increases to 18 d by increasing the

þ m ¼ 0.2) and low power (n ¼ 10, SD ¼ 1.0), teq ranges sample size and decreasing the SD (n ¼ 100, SD ¼ 0.5). from 3 to 10 d for DR values of 0.5–5, respectively. For With respect to the sample size chosen for the Monte- the same conditions at a slow rate (k þ m ¼ 0.001), teq Carlo analysis (n ¼ 100), the simulation implies that ranges from 740 to 1,861 d for DR values of 0.5–5, our results are robust on the time scale relevant to respectively. For a given turnover rate (i.e., k þ m), teq juvenile fish biology (weeks) given the fast growth rate approximately doubles by increasing the power of the characteristic of juvenile American shad. NURSERY HABITAT USE BY AMERICAN SHAD 1291

TABLE 1.—Characteristics of juvenile American shad greater than 40 mm total length (TL) captured in the Mattaponi (MP) and York rivers (YK), including the number sampled for stable isotope analysis (n), the mean TL and weight of all juveniles captured (1,240 in the Mattaponi River, 14 in the York River), and the region-specific, catch-weighted mean d13C. Standard deviations (SDs) are in parentheses. The d13C values of the common prey Eurytemora affinis (a calanoid copepod) and Bosmina freyi (a cladoceran) measured on 30 June 2002 at river kilometers 113, 98, and 81 are shown within the closest region (SDs are given where replicates were taken; Hoffman 2006).

d13C

River Region (rkm) n TL (mm) Weight (g) American shad E. affinis B. freyi

MP 104–109 28 48.5 (7.3) 1.41 (0.75) 31.3 (0.3) 32.6 (0.1) 33.8 MP 95–100 54 52.2 (7.9) 1.78 (0.89) 30.4 (0.5) 31.4 32.3 MP 74–87 29 54.7 (8.6) 2.06 (0.97) 28.2 (1.4) 30.1 (0.3) 28.2 YK 19–52 14 102.2 (16.2) 8.05 (4.43) 22.7 (1.7)

Habitat-Specific Ratios population mean d13C ratios (Table 1) were similar to ¯ 13 The population means estimated from the season- the Rf d C values used in the model application (Table long d13C survey were depleted at rkm 104–109 and 2). From the upper estuary to the lower estuary, we 13 increasingly enriched toward the lower estuary, observed a gradient of approximately þ10% for d C 34 13 implying that habitat-specific signatures are present and þ15.5% for d S. The d C signature is signifi- (Table 1). The d13C of age-0 American shad was cantly different between regions (ANOVA: df ¼ 4, F ¼ constant with respect to weight after 17 June (Figure 130.8, P , 0.001), all regions being distinct except 34 4). The similarity of the d13C of fish 60–79.9 mm TL rkm 104 and rkm 96–102. Similarly, the d S signature captured 30 June and 15 July to the weighted average is different between regions (ANOVA: df ¼ 4, F ¼ d13C, as well as to each other, implies that fish in each 385.9, P , 0.001), though Tukey’s test indicates that region had obtained a reasonably stable and constant the Mattaponi River is separated into only two distinct d13C value (61%). Temporal variation did occur. On regions. The age-0 American shad captured in the 27 May, the d13C of age-0 shad was similar among lower Mattaponi River are slightly larger and heavier regions (approximately 28%; Figure 4). Thereafter, than those captured upriver, which is consistent with the d13C became increasingly depleted at rkm 105–109 our assumption of downstream movement in the and rkm 95–100, stabilizing at approximately 30 to population. Those age-0 fish captured in January in 31%, whereas no trend was visible at rkm 74–87. In the York River are larger still. The two stable isotopes the brackish estuary (rkm 19–52) the d13Cwas trace proximity to marine habitat similarly (Figure 5). 13 depleted in November, indicative of a recent emigra- To account for the observed d C distribution, age-0 tion of these age-0 fish from freshwater, and was American shad would have to reside in each region of increasingly similar to an estuarine d13C signature the Mattaponi River for at least 15–41 d and in the (24% to 20%; Michener and Schell 1994) as winter lower York River for 48–60 d; the corresponding progressed. residence times for d34S are 16–45 d and 32–66 d

Available data confirm that these equilibrium values (Table 3). The variability by region in teq is a function are representative of each region. In summer, particu- of both the isotopic gradients between regions and the late organic matter d13C is enriched along the estuary SD of the downstream region. Owing to their similarity axis from approximately 29% to 30% at rkm 113 to in tracing marine influence, d13C and d34S data result

22% at rkm 7 in the York River (Hoffman and Bronk in similar estimates of teq. The estimates of the average 2006). Further, presuming zooplankton were the teq are within 7 d of each other; no consistent difference ¯ ¯ common diet items (Table 1), American shad would is observed. Generally the difference between Rt and Rf have a d13C from approximately 31.5% to 32.5% at was small (,0.5%), indicating a close convergence of rkm 104, 30.4% to 31.3% at rkm 96 and 102, and the two populations at the teq. Notably, even where 29.1% to 27.2% near rkm 78, given a trophic only small isotopic differences exist between habitats discrimination of approximately þ1% (Post 2002). (e.g., rkm 104 and rkm 96–102), the model yields teq This is similar to the measured gradient. estimates from weeks to over a month because these distributions have a small SD. Model Application Application of the Fry and Arnold (1982) model to The d13C and d34S of age-0 American shad vary the d13C data from rkm 104 to rkm 109 indicated that among the regions and are increasingly enriched in fish turnover was growth dominated, supporting this captured further downriver (Table 2). Further, the assumption (Figure 6). The turnover coefficient (c)is 1292 HOFFMAN ET AL.

0.7 (SE ¼ 0.4), which is not significantly different from 1.0 (i.e., dilution only). A model with the same

Ri and Rf estimates and c ¼1 yields a similar, though slightly worse, fit (r2 ¼ 0.39 versus 0.54).

Discussion Turnover Rate Mode Our formulation of the turnover model has the advantage that it accommodates isotopic variability, both in the initial and final isotopic values, when estimating the time to equilibrium. Like other turnover models, it has some arbitrariness in determining when close is considered close enough. Here it is determined by statistical power and a; in other versions it is determined by the half-life (or three-quarter life, etc.).

In our example (Figure 1), the half-life was 14 d, the teq was 56 d (equivalent to the fifteen-sixteenths life), and ¯ at 56 d Rt was 20.9%. Note that teq is related to the isotopic gradient whereas the half-life is not (t1/2 ¼ loge[2]/[k þ m]). Ultimately, what determines close enough is dependent on the research question being asked, and we therefore recommend that investigators ¯ who use this model report the Rt corresponding to teq (e.g., Table 3). In our simulation the migratory population statistically reached equilibrium when it ¯ was within 0.6% or less of the corresponding Rf, which is similar to the smallest isotopic gradient observed between regions (0.4%) and thus well suited to our data. The sensitivity analysis indicates that investigators should be cautious when using a small sample size or when the natural variability in stable isotope ratios is high. As a result of the model’s statistical properties, increasing the power of the K–S test, either by reducing the SD or increasing the sample size, can result in biologically meaningful differences in the time to equilibrium, particularly at slow turnover rates. When only a few samples are available (e.g., 3–5), as is common in stable isotope studies, using an individual- based Monte-Carlo approach (e.g., our model applica- tion to American shad) will provide a range of possible

teq values that would be more biologically meaningful than an average or an isotopic half-life.

13 Studies that use isotopic turnover probably will be FIGURE 4.—The mean d C value of age-0 American shad versus average wet weight for fish 40–59 mm (filled symbols), difficult, if not impractical, for organisms with slow 60–79 mm (open symbols), and 80 mm or more TL (gray growth and metabolism (k þ m 0.001/d) because the symbols) in (a–d) various river segments. In panels (a–c), age- time to isotopic equilibrium can be on the order of 0 fish were sampled on 27 May (circles), 17 June (squares), 30 1,000 d (.2 years), even for small isotopic gradients June (diamonds), and 15 July (triangles). In panel (d), age-0 (i.e., DR ¼ 0.5%). Further, at slow turnover rates, small fish were sampled on 7 November (circles), 10 January changes in the estimate of R or R will lead to large (squares), and 4 March (diamonds). The error bars represent f i SDs. Note the difference in the scale of the y-axis in the last differences in teq. In contrast, this type of study should panel. The weighted mean d13C is indicated by the dashed line be feasible for organisms with fast growth, metabolism, and its value is given. or both, particularly for combined rates of greater than 0.05/d, because these organisms arrive at equilibrium NURSERY HABITAT USE BY AMERICAN SHAD 1293

13 34 13 TABLE 2.—Mean total length (TL), weight, d C, and d S and sample size (n) of juvenile American shad sampled for d C and d34S from the Mattaponi (MP; 30 June 2002) and York rivers (YK; 13 January 2003). Standard deviations are in parentheses. 13 34 ¯ 13 34 The mean d C and d S values are the same as the mean ratios at equilibrium (Rf; e.g., the mean d C and d S of rkm 96, 102 is ¯ equal to Rf,96–102). Within columns, means with the same letter are not different (Tukey’s post-hoc test). River Location (rkm) TL (mm) Weight (g) d13C d34S n

MP 104 49.3 (5.2) 1.1 (0.4) 31.8 (0.3) z 5.2 (0.7) z 10 MP 96, 102 51.3 (5.1) 1.3 (0.3) 31.4 (0.3) z,y 4.2 (1.4) z 10 MP 85, 89 57.1 (2.4) 1.6 (0.2) 30.2 (1.0) y 0.1 (2.3) y 10 MP 74, 78 68.0 (4.1) 2.5 (0.3) 27.8 (2.3) x 2.9 (4.7) y 7 YK 15 93.1 (4.1) 5.1 (0.8) 21.8 (1.2) w 10.3 (1.7) x 10 within 100 d and are less sensitive (in absolute terms) Model Application to Juvenile American Shad to changes in the isotopic gradient. Additional Our assumption that the population could be problems using muscle tissue may occur where a modeled using growth-dominated turnover is supported seasonal bias is present (Perga and Gerdeaux 2005) or by field data. It was possible to estimate the turnover trophic discrimination is not constant owing to variable coefficient (c) of a subset of age-0 American shad food quality or nutritional demands or a change in because there was a shift in the d13C during the early growth rate (Tieszen et al. 1983; Hobson and Clark juvenile stage, probably due to an increased contribu- 1992; Adams and Sterner 2000; Trueman et al. 2005), tion from phytoplankton to the food web during May– resulting in isotope shifts that are inconsistent in July. In the Mattaponi River, the phytoplankton magnitude with diet or habitat shifts. If isotopic values produced in situ are isotopically light (d13C , are measured from the organism and its ecosystem, 30%) compared with allochthonous, terrestrially then these problems may be assessed. None of these derived matter (26 to 28%; Hoffman and Bronk problems seem to have occurred with respect to 2006). For this analysis to be applicable, we must American shad; the isotopic gradient (d13C) observed assume that there was no emigration from or along the estuary was similar to the isotopic gradient in immigration into the region (rkm 104–109). This zooplankton prey, implying similar trophic discrimina- appears to be reasonable because common prey for tion. age-0 American shad (i.e., zooplankton and macroin- vertebrates; Crecco and Blake 1983; Grabe 1996) had a

13 34 13 FIGURE 5.—The d C and d S values of age-0 American FIGURE 6.—The d C turnover of age-0 American shad shad sampled from the Mattaponi River on 30 June 2002 and captured at rkm 104–109, including the best fitting equation from Fry and Arnold’s (1982) turnover model (equation 1 in the York River on 13 January 2003 (rkm 52 is the mouth of the text; solid line) and the model assuming growth turnover the Mattaponi River). Salinity was 17.4% (rkm 15) and only (c ¼1.0; dashed line). The values for the variables Ri, 20.0% (rkm 9) at the river bottom on 13 January 2003. Rf, and c were estimated by means of nonlinear regression. 1294 HOFFMAN ET AL.

ABLE T 3.—Comparison of equilibrium times (teq [d]) for age-0 American shad simulated to migrate downstream in turnover 13 34 ¯ model simulations using either d Cord S, the corresponding mean stable isotope ratios at teq (Rt), and the differences from ¯ their equilibrium values (Rf) at various river locations (rkm; see text); n ¼ the number of fish simulated. Stable isotope ratio and n Variable 104 to 96–102 96–102 to 85–89 85–89 to 74–78 74–78 to 15

13 d C teq (range) 32 (19–41) 31 (15–38) 28 (19–37) 53 (48–60) ¯ ¯ Rt, Rf Rt 31.5, 0.1 30.5, 0.3 28.3, 0.5 22.1, 0.3 34 d S teq (range) 26 (16–33) 38 (24–45) 26 (17–33) 46 (32–66) ¯ ¯ Rt, Rf Rt 4.4, 0.2 0.5, 0.6 2.4, 0.5 9.9, 0.4 n 10 10 10 7

13 d C value similar to the estimated Rf (31.8%; Table declined to 0.02/d and metabolic turnover was 1), implying that age-0 fish were at isotopic equilib- relatively low (Figure 3). Some growth turnover, rium in this region. The average d13C (SD) estimated however, must have occurred between the summer from sampling at rkm 109 (27 May, 30 June, and 21 and winter sampling because the average weight of July) was 32.2% (0.8) for Eurytemora affinis (a age-0 fish increased by a factor of four over the period calanoid copepod), 32.6% (1.2) for Bosmina freyi (a corresponding to the migration from the river (Table 1). cladoceran), and 32.4% (1.7) for Chironomus spp. In general, the role of metabolism is difficult to (Diptera larvae; Hoffman 2006). Moreover, movement assess in wild populations owing to the variation in from an upstream region was unlikely because this individual growth, metabolism, and diet. As growth region is the farthest upriver within the nursery zone. slows the contribution of maintenance metabolism to While immigration from a downstream habitat could isotopic turnover increases, which is the premise confound the analysis, the effect would be slight behind turnover studies of adult animals. Although because there is a small isotopic gradient (;1%) the average 6 SD weights of the age-0 American shad between fish at rkm 104–109 and those at rkm 96–100. captured in the upper York River estuary during To simulate migration using the turnover model, November (7.1 6 2.6 g) and January (8.6 6 5.1 g) 13 13 each region was assigned an Rf value using the d Cor were similar, albeit highly variable, the d C of age-0 d34S distribution of fish captured within that region. fish was more enriched in January (mean 6 SE, 22.7 The advantage of using the empirical probability 6 0.4%) than in November (24.9 6 0.5%), implying distribution with the turnover model is that we do not that some metabolic turnover occurred during the need to make assumptions regarding the behavior of winter months. Metabolic processes remain relatively any individual fish. Rather, we can postulate that a fish unexplored with respect to isotopic discrimination. could equilibrate at any of the isotopic values observed Different tissues are subject to different turnover rates downstream and thereby obtain a biologically realistic (Tieszen et al. 1983); however, assessing the relative range of teq values. Migration, however, could bias the contribution by growth and metabolism to isotopic region’s mean d13Cord34S, resulting in a lighter turnover, especially in field studies, remains extremely estimate than is representative of the region due to the difficult. As others have argued (Gannes et al. 1997; presence of recent arrivals. The problem is not unique Hobson 1999), more experimental work is needed. The to this study but applies to any in which a local variable contribution of metabolism could be indirectly mea- is measured from a potentially mobile population. In sured in a field experiment in which direct estimates of this study, the available data (particulate organic growth, and possibly even the change in an individ- matter, zooplankton) provide independent support for ual’s isotopic composition, are obtained, perhaps by our equilibrium values (Table 1). combining conventional tagging and stable isotope The growth rate used in the model application, 0.05/ studies (if that is possible) or by means of cage d, is applicable to age-0 American shad of 40–80 mm experiments (e.g., Herzka et al. 2001). TL but may be an overestimate for larger age-0 fish because growth during year 1 is asymptotic, slowing at American Shad Habitat Use around 80–100 mm TL (Crecco et al. 1983; Limburg American shad are the focus of conservation efforts 1996). The average size of estuarine age-0 shad used in along the Atlantic coast of North America owing to a this study was about 100 mm TL; therefore, teq may be widespread population decline caused by pollution, underestimated in the simulation of migration from the dam construction, and overfishing (ASMFC 1999). Mattaponi River to the York River. It could be Young American shad are habitat generalists and use underestimated by as much as 40 d if the growth rate all available habitats within a river (Ross et al. 1997). NURSERY HABITAT USE BY AMERICAN SHAD 1295

In this study, the distinct d13C and d34S between and Virginia Sea Grant College Program. Additional regions within the nursery zone, combined with the support was provided by the Wallop–Breaux program turnover model results, indicate that the fish remain in of the U.S. Fish and Wildlife Service through the small-scale habitats (5–10 rkm) for a month or longer. Marine Recreational Fishing Advisory Board of the This suggests that habitat restoration efforts on the Virginia Marine Resources Commission (grants F-116- spatial scale of 5–10 rkm (i.e., a river reach) would be R-5 and F-116-R-6). This is contribution 2824 of the well matched to the scale of habitat use by American Virginia Institute of Marine Science, College of shad in the York River estuary. William and Mary. In contrast, Hudson River juvenile American shad actively migrate downstream and enter brackish water References as early as June (Limburg 1996). Most of the age-0 Adams, T. S., and R. W. Sterner. 2000. The effect of dietary American shad captured in the upper York River nitrogen content on trophic level 15N enrichment. estuary had an isotopic composition similar to the Limnology and Oceanography 45:601–607. expected d13C of an estuary (d13C ¼20 to 25%; ASMFC (Atlantic States Marine Fisheries Commission). Figures 4, 5), indicating that they were at or 1999. Amendment 1 to the interstate fishery management plan for shad and river herring. ASMFC, Fishery approaching isotopic equilibrium with the new habitat. 13 34 Management Report 35, Washington, D.C. With either d Cord S data, the turnover model Bilkovic, D. M., J. E. Olney, and C. H. Hershner. 2002. indicates that American shad captured in the upper Spawning of American shad (Alosa sapidissima) and York River estuary in early January 2003 would have striped bass (Morone saxatilis) in the Mattaponi and had to enter this brackish habitat no later than early Pamunkey rivers, Virginia. U.S. National Marine Fish- December or late November 2002. This result is eries Service Fishery Bulletin 100:632–640. consistent with analyses of trawl data from the York Bosley, K., and S. Wainright. 1999. Effects of preservatives and acidification on the stable isotope ratios (15N:14N, River system that suggest that age-0 American shad 13C:12C) of two species of marine animals. Canadian remain within freshwater habitats until November Journal of Fisheries and Aquatic Sciences 56:2181–2185. before migrating out during the winter months (Hoff- Crecco, V. A., and N. M. Blake. 1983. Feeding ecology of man and Olney 2005; Hoffman et al., in press). It is coexisting larvae of American shad and blueback herring likely, therefore, that juveniles slowly exit the upper in the Connecticut River. Transactions of the American and middle reaches of the tidal freshwater portion over Fisheries Society 112:498–507. the summer and early fall, accumulating in the lower Crecco, V. A., T. F. Savoy, and L. Gunn. 1983. Daily freshwater and oligohaline portions of the estuary mortality rates of larval and juvenile American shad (Alosa sapidissima) in the Connecticut River, with before their oceanic migration. In contrast to the changes in year-class strength. Canadian Journal of Hudson River, the York River is a warm, short, coastal- Fisheries and Aquatic Sciences 40:1719–1728. plain tributary; further research may reveal patterns in DeNiro, M. J., and S. Epstein. 1977. Mechanism of carbon fish movement and habitat use among Atlantic coast isotope fractionation associated with lipid synthesis. tributaries in relation to their physical characteristics. Science 197:261–263. These findings are relevant to the population dynamics DeNiro, M. J., and S. Epstein. 1978. Influence of diet on the of American shad. A residence time of weeks to distribution of carbon isotopes in animals. Geochimica et Cosmochimica Acta 45:341–351. months is sufficient for habitat differences to influence Frazer, T. K., R. M. Ross, L. B. Quetin, and J. P. Montoya. population demographics because larval and juvenile 1997. Turnover of carbon and nitrogen during growth of American shad have high mortality and growth rates larval krill, Euphausia superba Dana: a stable isotope (Crecco et al. 1983; Houde 1997). approach. Journal of Experimental Marine Biology and Ecology 212:259–275. Acknowledgments Fry, B., and C. Arnold. 1982. Rapid 13C/12C turnover during growth of brown shrimp (Penaeus aztecus). Oecologia We thank D. Evans for input on model development; 54:200–204. Brian Watkins, Jim Goins, Patricia Crewe, Reid Hyle, Fry, B., and E. B. Sherr. 1984. d13C measurements as and Ashleigh Rhea for field assistance; and Karin indicators of carbon flow in marine and freshwater Limburg, Anett Trebitz, and two anonymous reviewers ecosystems. Contributions in Marine Science 27:13–47. for helpful comments on the manuscript. This material Gannes, L. Z., D. M. O’Brien, and C. Martinez del Rio. 1997. is based on work supported under a National Science Stable isotopes in animal ecology: assumptions, caveats, Foundation Graduate Research Fellowship to J.C.H. and a call for more laboratory experiments. Ecology 78:1271–1276. This work is a result of research sponsored in part by Grabe, S. A. 1996. Feeding chronology and habits of Alosa National Oceanic and Atmospheric Administration spp. (Clupeidae) juveniles from the lower Hudson River Office of Sea Grant under grant NA03OAR4170084 estuary, New York. Environmental Biology of Fishes to the Virginia Graduate Marine Science Consortium 47:321–326. 1296 HOFFMAN ET AL.

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Appendix: Model Code for MATLAB 7.0.1 This appendix presents a stable isotope turnover rate F ¼ muþSD*randn(1,n); model to estimate the time span required for two I ¼ mu2þsd2*randn(1,n); populations (initial and final) with different stable s ¼ 0:1:t; isotope means and standard deviations to become j ¼ 0;u ¼ zeros(length(s),n); statistically similar. The variable D returns the matrix v ¼ zeros(length(s),1); of stable isotope ratios given the mean ratio of the final for b ¼ 0:1:t population (mu) and its standard deviation (SD), the E ¼ Fþ(I-F)*exp(-r*b); mean ratio of the initial population (mu2) and its [H,P] ¼ kstest2(F,E); standard deviation (sd2), the combined growth and j ¼ j þ 1; metabolic rates of the initial population (r), the number u(j,:) ¼ E; of individuals in the population (n), and the time length v(j) ¼ P; of the run in days (t). The variable result is the output at end; each day of the Kolmogorov–Smirnov (K–S) good- D ¼ [s’ u]; ness-of-fit test comparing the population at time t with result ¼ [s’ v]; the final population. plot(s’,v’) function [D,result] ¼ turn- xlabel(’Time (d)’) over(mu,SD,mu2,sd2,r,n,t) ylabel(‘K-S P-value’)