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Determinate Versus Indeterminate Fecundity inAmerican Shad, an Anadromous ClupeidA. Reid Hylea, Richard S. McBrideb & John E. Olneyc
a Florida Fish and Wildlife Conservation Commission, Fish and Wildlife Research Institute,2595 McGraw Avenue, Melbourne, Florida 32934, USAb National Marine Fisheries Service, Northeast Fisheries Science Center, 166 Water Street,Woods Hole, Massachusetts 02543, USAc Virginia Institute of Marine Science, College of William and Mary, Route 1208 Greate Road,Gloucester Point, Virginia 23062, USAPublished online: 15 Apr 2014.
To cite this article: A. Reid Hyle, Richard S. McBride & John E. Olney (2014) Determinate Versus Indeterminate Fecundityin American Shad, an Anadromous Clupeid, Transactions of the American Fisheries Society, 143:3, 618-633, DOI:10.1080/00028487.2013.862178
To link to this article: http://dx.doi.org/10.1080/00028487.2013.862178
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Transactions of the American Fisheries Society 143:618–633, 2014C© American Fisheries Society 2014ISSN: 0002-8487 print / 1548-8659 onlineDOI: 10.1080/00028487.2013.862178
ARTICLE
Determinate Versus Indeterminate Fecundity in AmericanShad, an Anadromous Clupeid
A. Reid Hyle*Florida Fish and Wildlife Conservation Commission, Fish and Wildlife Research Institute,2595 McGraw Avenue, Melbourne, Florida 32934, USA
Richard S. McBrideNational Marine Fisheries Service, Northeast Fisheries Science Center, 166 Water Street, Woods Hole,Massachusetts 02543, USA
John E. Olney1
Virginia Institute of Marine Science, College of William and Mary, Route 1208 Greate Road,Gloucester Point, Virginia 23062, USA
AbstractHistorical fecundity estimates of American Shad Alosa sapidissima used a determinate method that estimated
annual fecundity as the standing stock of oocytes at a single point of time prior to spawning. Such fecundity estimateshave been (1) reported for populations from the Canadian Maritimes to Florida, (2) applied to hypothesis tests of lifehistory evolution, and (3) used in demographic models to advise management policy. However, American Shad haveasynchronous development of yolked oocyte clutches, which suggests that new oocytes could arise after spawningcommences, biasing the results of a determinate fecundity method downward. If so, annual fecundity should bea product of batch size and the number of batches—an indeterminate fecundity method. We investigated oocyterecruitment, atresia, and spawning intervals using gonad histology of females from the Mattaponi River, Virginia.Batch size (i.e., the number of hydrated oocytes prior to a spawning event) was estimated using a gravimetric method.Spawning duration was obtained from an independent acoustic tagging study. A size hiatus between primary andsecondary oocytes was only evident in some individuals during spawning, so we conclude that an indeterminatefecundity method is necessary for this population of American Shad. Atresia was evident during spawning but waslow at the end of the 2002 spawning season. Females spawned every 2.2–2.9 d, releasing 11–17 batches per season.Batch fecundity (range: 12,700–81,400) was 23% higher for repeat versus virgin spawners. A bootstrapped estimate ofpotential annual fecundity for a virgin female—as calculated with an indeterminate fecundity method—was 478,000–544,000 eggs (95% confidence interval), about double the previous (determinate) estimates from this river system(260,000 and 288,000). Until more comparisons are done with other populations, we urge caution in using the manypublished determinate fecundity estimates of American Shad and other Alosa species.
The American Shad Alosa sapidissima is an anadromousclupeid native to the western North Atlantic Ocean. Ameri-can Shad spawn in both tidal and nontidal freshwater portionsof rivers stretching from St. John’s River, Florida, to Atlantic
*Corresponding author: [email protected] June 3, 2013; accepted October 25, 2013Published online April 15, 2014
Canada (Bigelow and Schroeder 1953). Though American Shadfrom all populations mix in the ocean, they return to natalwaters, and this homing behavior leads to reproductive isola-tion and river-specific phenotypic traits (Melvin et al. 1986;
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AMERICA SHAD FECUNDITY ESTIMATION 619
Waters et al. 2000). Spawning history demonstrates gradientvariation (i.e., semelparous in southern and iteroparous in north-ern populations), whereas potential annual fecundity estimatesshow countergradient variation (i.e., southern populations havehigher annual fecundity). These reciprocating traits are thoughtof as adaptive. Variable environmental conditions and shortgrowing seasons in northern nursery areas lead to recruitmentfailure frequently enough to select for adults that spread repro-ductive effort out over several years. Southern fish migrate thefarthest in the open ocean, too far to make more than one trip,but experience longer and more environmentally stable spawn-ing and nursery conditions. Thus southern fish invest greaterreproductive effort — by producing more eggs – in their singlespawning season to compensate for reduced iteroparity (Leggettand Carscadden 1978; Roff 2002). The higher allocation of en-ergy to reproduction by southern females involves transferringexhaustive levels of somatic and visceral reserves to gonadsduring their spawning migration, which in turn contributes toreduced survival of these populations (Glebe and Leggett 1981).
Many American Shad populations are overfished and someare under a harvest moratorium (Olney and Hoenig 2001; Latouret al. 2012). Egg production models can influence mortality tar-gets in managed species in general (Morgan et al. 2009; Fitzhughet al. 2012). Recently, fecundity data has been used as input indemographic models to assess management options relative toAmerican Shad rebuilding plans to evaluate (1) the known delaysof fish passage during upstream migration on realized fecundityand survival (Castro-Santos and Letcher 2010), (2) effects oftransporting spawning fish past dams (Harris and Hightower2012), and (3) rates of rebuilding stocks via hatchery supple-mentation (Bailey and Zydlewski 2013). The consequences ofestimating fecundity accurately relates to a broad range of basicand applied scientific investigations.
To date, life history studies of American Shad have used adeterminate fecundity method, which counts the total numberof yolked oocytes present prior to the onset of spawning (e.g.,Nichols and Massman 1963; Leggett and Carscadden 1978).This method assumes that the fecundity is set—i.e., no newvitellogenesis or atresia of yolked oocytes occurs after spawningbegins (Hunter et al. 1992; Murua et al. 2003). If no new vitello-genesis occurs once spawning commences, there will typicallybe a gap in size between previtellogenic (primary) and yolked(secondary [vitellogenic]) oocytes. The presence of this size gapprior to spawning is referred to as a group synchronous patternand is the basis of the determinate fecundity method, whichrepresents the maximum value of that year’s egg production.The enumeration process of yolked oocytes is relatively easy.In some cases, fish exhibit no hiatus between primary and sec-ondary oocytes, but investigators deduce determinate fecunditywhen they discern that new vitellogenesis stops or is negligibleafter spawning commences (Witthames and Greer Walker 1995;Alonso-Fernandez et al. 2008).
Evidence that the determinate fecundity method is not appro-priate for American Shad has been reported. No discernible ooc-
tye size hiatus is evident between primary and secondary oocytesin four different populations: Edisto River, South Carolina; YorkRiver, Virginia; Susquehanna River, Maryland; and the Con-necticut River, Massachusetts (Mylonas and Zohar 1995; Olneyet al. 2001). Such evidence for asynchronous oocyte size distri-butions with respect to vitellogenesis generally invalidates usinga determinate fecundity method (outlined above; see also Gordoet al. 2008; Schismenou et al. 2012). If true, determinate methodestimates of potential annual fecundity will be too low becausenew yolked oocytes recruit after spawning has commenced (denovo vitellogensis).
Estimating fecundity accurately also requires quantifyinglevels of atresia of yolked oocytes during and at the end ofspawning. Some, but not all, studies report atresia of yolkedoocytes in American Shad at the end of the spawning run (Ol-ney et al. 2001, but see Lehman [1953] for relatively low rates ofpostspawning atresia). When this occurs, realized annual fecun-dity will be lower than potential annual fecundity. Not reportedfor American Shad, but a general concern, is when atresia ofyolked oocytes occurs during the spawning period. If so, deter-minate method estimates of potential annual fecundity will betoo high. When rates of new recruitment or new atresia of yolkedoocytes occurs during spawning, simply counting the standingstock of oocytes prior to spawning will not produce an accurateestimate of potential annual fecundity (Murua et al. 2003).
In addition, American Shad have asynchronous runs ofspawning individuals during the upstream migration (Olneyet al. 2006), so there is no particular point during the spawningrun to standardize the measurement of individual annual fe-cundity, unless ovary development is complete when AmericanShad are intercepted en route to the spawning ground. Thesecombined traits demand an indeterminate fecundity estimationmethod. Such a method calculates annual fecundity as a functionof the number of eggs released in each spawning event (batchfecundity) and the number of batches released during the spawn-ing season. The number of batches is dictated by the duration ofspawning and the number of days between each spawning event(spawning interval).
Herein, we demonstrate new evidence that confirms asyn-chronous oocyte development with respect to vitellogenesis andthe appropriateness of using an indeterminate fecundity methodfor American Shad in the Mattaponi River, a tributary of Vir-ginia’s York River. We also calculate potential annual fecun-dity using an indeterminate method. New data values regard-ing spawning interval, batch fecundity, and spawning historywere integrated with published data regarding spawning dura-tion estimated from a contemporary acoustic tagging study inthe York River and its tributaries (Olney et al. 2006). Our resultsfor this mid-latitudinal river population of American Shad arehigher than previous estimates using the determinate fecunditymethod: twice as high as previous estimates for this popula-tion, and even higher than any previous estimate for the speciesthroughout its range. We do not conclude that this new methodand its results invalidate the existence of life history tradeoffs
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between populations of American Shad. Still, these results indi-cate that reevaluating fecundity estimation methods and fecun-dity estimates across the species range would enhance under-standing of evolutionary ecology, as well as management andrestoration of American Shad.
METHODSField collections.—Female American Shad were obtained
on the spawning grounds of the Mattaponi River, between 86and 96 km upstream of the mouth of the York River, Virginia,in the spring of 2002 and 2003. The spawning grounds weredelineated from egg collections in Bilkovic et al. (2002). Adultspecimens were obtained from a Native American drift gill-net fishery (exempt from the fishing moratorium in Virginia)in 2002 and 2003 and from separate, fishery-independent 72-hcollections in 2002.
Samples were taken from the drift gill-net fishery once ortwice weekly as long as fishers were actively fishing. Fishersused floating gill nets of 127–133 mm stretched mesh betweenriver kilometers 85 and 90. They were instructed to set asideup to the first 20 females captured without regard for size orcondition. In 2002, diurnal collection times were selected atrandom within the following periods (eastern standard time):morning (daybreak to 1000 hours), midday (1000–1600 hours),and evening (1600 hours to sunset). Based on the prelimi-nary results from 2002, collections in 2003 were restricted to amorning period, before noon, when the opportunity to collecthydrated females was maximized. Fish were placed on ice, re-turned to the laboratory, and processed fresh. Specimens in 2002were processed for histology and batch fecundity. Specimens in2003 were examined macroscopically for the presence or ab-sence of hydrated oocytes but processed further only for batchfecundity.
Sequential collections in 2002 of mature females over twodiscrete 72-h periods, each consisting of three 24-h diel periods,were used to evaluate spawning periodicity in detail (Hunterand Macewicz 1985) and compare microscopic versus macro-scopic results to estimate spawning interval. A 100-m (124 mmstretched mesh) drift gill net was fished over 4–6-h intervalsfrom April 4–7 (16 sets) and April 17–20 (11 sets). Each setwas allowed to fish for no more than 1 h to maintain temporalseparation between sets. The first (up to) 20 females were re-moved from each set. All fish were processed fresh in the field,and an ovary sample was taken for histology. Random subsam-ples of ovaries with hydrated oocytes were placed on ice to beprocessed for batch fecundity.
Fish, scale, and whole oocyte processing.—Fork length (FL;mm), ovary-free body weight (OFBW, 0.1 g), and gonad weight(GW, 0.1 g) were measured for all specimens. A gonadoso-matic index (GSI) was calculated as GSI = GW/OFBW ×100. All females were observed to be mature. Characterizationof macroscopic gonad stage followed Olney et al. (2001), whichis consistent with other maturity schemes used in the northeast-
ern United States (Burnett et al. 1989; McBride et al. 2013).Ovarian tissue collected for histology was immediately fixedin 10% neutral buffered formalin. Scales were collected fromindividuals selected for batch fecundity counts.
Although fish ages were estimated by counting scale annuli,recent reports demonstrate that scale ages are less precise andbiased low compared with otolith ages (Duffy et al. 2011, 2012;Upton et al. 2012). Since otolith ages were not available, wefocus our use of scale interpretation on the effects of spawninghistory (i.e., parity: virgin and repeat spawners). Spawninghistory was determined using scales removed from the dorsalsection of the fish, posterior to the dorsal fin. Spawning historywas evident from the presence (repeat spawner) or absence (vir-gin) of spawning marks on the periphery of the scale (per Cating1953).
Batch fecundity (BF) was estimated using whole oocytesand the gravimetric method of Lowerre-Barbieri and Barbieri(1993). Although Olney et al. (2001) showed no systemic differ-ences in batch fecundity among locations within the gonad, three4–5 g subsamples of tissue were still taken from the anterior,middle, and posterior locations of ripe ovaries to ensure goodrepresentation of oocyte density. Oocytes were washed, sepa-rated from the tissue in a sieve, placed in 2% neutral bufferedformalin, and allowed to harden before enumeration. Preservedeggs larger than 1.6 mm were considered hydrated (Mylonaset al. 1995); these were manually counted, and oocyte density(OD) was calculated as mature oocytes per gram of subsample.An average BF was estimated as BF = (�OD)−3 × GW (perOlney et al. 2001).
Gonad histology and spawning interval.—Fixed gonad tissuewas processed following Olney et al. (2001). Briefly, dehydrated(ETOH) tissue was embedded in paraffin blocks, sectioned to6 µm in thickness, and stained with Harris’ hematoxylin andeosin counter-stain. These histological preparations were usedto confirm asynchronous oocyte development and to calculatethe spawning interval.
Oocytes viewed in histology sections were staged as primarygrowth, partially yolked, yolked, migratory nucleus stage, hy-drated, or atretic (Table 1; Figure 1). All types of oocytes werecounted on all histological slides to examine oocyte recruitment.Counts were made from five nonoverlapping fields of view ofthe slide at 40 × magnification on a standard compound mi-croscope. All oocytes for which 50% or more of the oocytewas visible in the field of view were counted before selectinga new field of view. A one-way ANOVA was used to com-pare the average fraction of oocytes that were partially yolkedby date.
Oocyte diameters were measured from 10 slides selected torepresent the entire date range of collections. One or two slideswere picked from each collection event, the criteria for selectionbeing completeness and quality of the cross section for imagingand measuring. Oocytes were measured with calibrated imag-ing software connected to a microscope via a digital camera.Only oocytes with a visible nucleus were measured to obtain
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TABLE 1. Stages of oocyte development and postovulatory follicle (POF) degradation as observed in American Shad from the Mattaponi River, Virginia. Thecortical alveolar and early vitellogenic stages were combined into a partially yolked (PY) stage. Oocyte maturation was split into three stages: early nuclearmigration (NM), intermediate NM, and late NM (see also Figure 1). Postovulatory follicles were divided into three age categories based on the observation thatspawning occurs near dusk (see Figures 1, 4).
Oocyte development1. Primary growth (PG): These are small (<200 µm) with a large central nucleus (germinal vesicle) and dark basophilic
ooplasm. The germinal epithelium is not yet pronounced and consists of a single layer of simple squamous epithelia. Thechorion is not yet developed. No cortical alveoli (yolk vesicles) are visible. Multiple nucleoli are visible within the nucleus.
2. Partially yolked (PY): This early stage of secondary oocytes more than doubles in size (200–800 µm). They exhibitbasophilic ooplasm and clear cortical alveoli may be present in the ooplasm. As they mature, eosinophilic yolk vesiclesappear among the cortical alveoli and proliferate throughout but do not fill the ooplasm. The chorion is evident, and thegerminal epithelium is now distinguishable as two separate layers: a cuboidal granulosa layer and squamous theca layer.
3. Yolked (Y): The nucleus is still centrally located. The entire volume of the ooplasm is filled with eosinophilic yolk globules.Cortical alveoli line the periphery of the oocyte near the chorion (diameter: 800–1,000 µm).
4. Early NM: Nuclear migration marks the onset of final maturation. Here, the nucleus is displaced slightly off center in sections(Figure 1A). The oocyte otherwise looks like a stage 3, yolked oocyte (diameter: 1,000–1,200 µm).
5. Intermediate NM: The nucleus is displaced further toward the periphery of the cell (Figure 1B). Yolk coalescence has begunand yolk globules are larger and paler than early NM (diameter: 1,000–1,200 µm).
6. Late NM: The nucleus has reached the periphery of the germ cell (Figure 1C). The yolk has mostly coalesced into large palestaining globules and oocyte diameter has increased (diameter: 1,200–1,400 µm).
7. Hydrated (H): The nucleus is no longer evident. Yolk has coalesced into large pale pink staining globules (Figure 1D). Sizemay be reduced or shape may be highly irregular compared with late NM because of the extraction of lipids and water thatoccurs during the dehydration process of histological preparation.
8. Alpha Atresia (α): The nucleus is ragged or absent. The chorion is irregular or absent because it is dissolving in atreticoocytes. Granulosa cells are enlarged with enlarged vacuoles and appear to invade the yolk. Yolk globules are indistinct andpale staining generally appearing as a homogenous eosinophilic mass.
Postovulatory folliclesNew POFs (P0): spawning <12 h prior. POFs observed in running ripe females (Figure 1E), have a large, convoluted central
lumen. At higher magnification, the granulosa cells have a distinct cuboidal shape with well-defined borders and prominentbasophilic nuclei.
One-day POFs (P1): spawning 12–24 h prior. One-day POFs are smaller (half to one-quarter the size) than new POFs. Thecentral lumen is also smaller and less convoluted. The granulosa layer is still recognizable, but its cells begin to hypertrophy,are less distinguished by a columnar to cuboidal shape, and stain with less intensity. POFs were classified as 1-day up to thepoint where the lumen was barely evident. At higher temperatures (>20◦C) observed in late April, the lumen was fullycollapsed by 24-h postspawn (Figure 1F–G).
Two-day POFs (P2): spawning within 24–48 h prior. Size was one to three times that of primary growth oocytes and included anindistinct clump of granulosa. Staining affinity was much weaker than in fresh POFs. The nuclei of the granulosa cells may beobserved, but most cells were difficult to distinguish from one another. (Figure 1H).
representative sizes. The purpose of these measurements wasto assess whether a gap in size was present between primarygrowth oocytes and oocytes progressing through vitellogene-sis, so shrinkage of oocytes by dehydration in ETOH was notregarded as a problem.
Spawning interval (SI) was estimated as the reciprocal of thefraction of females spawning per day. Spawners were classifiedin relation to days to the next, or days since the most recent,spawning event (Uriarte et al. 2012). Day – 1 spawners werelikely to have spawned the day following capture, as evidentfrom oocytes undergoing nucleus migration. Day – 0 spawnerswere likely to or did spawn on the day of capture, as evident byhydrating or hydrated oocytes or by <12-h old postovulatory
follicles (POFs). Day + 1 and day + 2 spawners were femalesthat had spawned 1 or 2 d previously, based on their POFs(Table 1). The classification of oocytes in final maturation, be-ginning with nuclear migration (Table 1; Figure 1), followedWallace and Selman (1981), and calculation of diel spawningfollowed McBride et al. (2002, 2003). The appearance of POFdegradation during our 72-h periods of sampling (Table 1) andcriteria to age POFs was based on Hunter and Macewicz (1985),Fitzhugh and Hettler (1995), and Ganias et al. (2007). Collec-tion of running ripe fish provided known spawning time (hour0) to establish a POF baseline. A spawning interval distribu-tion by day was assembled from these multiple histology-basedestimates.
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FIGURE 1. Gonad histology depicting the progression of oocyte final maturation, ovulation, and postovulatory follicle (POF) degradation in American Shad:(A) early nuclear migration and recent POFs (P1), (B) intermediate nuclear migration, (C) late nuclear migration, (D) hydration, (E) new POF, (F) 12-h-old POF,(G) 24-h-old POF, (H) 36–48-h-old POF, and (I) P0 present simultaneously with P2. [Color figure available online.]
Spawning interval was also calculated from macroscopic ob-servation of ovaries collected in 2002 and 2003. When usingthis method, SI could only be evaluated macroscopically bythe presence or absence of hydrated eggs, observed as large,translucent spheres scattered throughout the ovary. Based onthe initial inspection of the raw data, samples were split intotwo groups: before noon and after noon. For all specimens col-lected in 2002 a chi-square analysis was used to compare theability to identify, macroscopically and by histology, whether afemale would spawn on the day of capture (when both methodswere used). For each group, morning and afternoon, a 2 × 2table was created: row labels = a fish that would or did spawn
on the day of capture, column labels = day-0 spawner versusnot-day-0 spawner as. The macroscopic count of each categorywas expected to equal the histology count.
Models and analysis.—The Akaike information criterion(AIC) was used to evaluate the effect of abiotic and biotic vari-ables on batch fecundity. Model selection used the AICcmodavgpackage of the software R (version 3.0.0, R Core Team, 2012).The reported value (AICc) is a second-order estimate that ac-counts for sample size.
It was not part of the original field sampling design, butthe Olney et al. (2006) estimate of residence time for Amer-ican Shad on the spawning grounds prompted us to develop
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AMERICA SHAD FECUNDITY ESTIMATION 623
an egg production model to estimate potential annual fecundity(PAF) using an indeterminate fecundity method. Such a modelrequired data regarding spawning interval (SI), batch fecundity(BF), and residence time (RT) on the spawning ground. Thesevariables could be influenced by fish age, size, or spawning ex-perience (Fitzhugh et al. 2012), which we considered duringmodel development. The effect of sampling dates, parity (virginand repeat spawners), and size (quartile ranks of FL) on spawn-ing interval were tested with ANOVA; no significant effectswere found. Batch fecundity overlapped widely between virginand repeat spawning, but repeat spawners produced significantlylarger batches, so this was taken into account in developmentof the egg production model. Olney et al. (2006) did not reportany effect of age, size, or parity on residence time.
We simulated indeterminate egg production using the soft-ware R. The data for SI was pooled across dates in 2002 usingestimates from gonad histology. The data for BF were restricted(to be conservatively low) to values from virgin females. First, toavoid unrealistically low values (e.g., negative values), a gammaprobability density function (pdf) was fit by eye to approximatethe SI and BF data, then a Kolmogorov–Smirnov test (KS) wasuse to examine deviations and select final parameters of shapeand scale of the SI and BF pdfs. A normal pdf was simulatedfrom the published estimates of RT (mean = 29.9, SD = 2.3)for fish spawning in the Mattaponi River (Olney et al. 2006).Each pdf was used to create 1,000 random draws, and the result-ing vectors were used to calculate: PAF = RT/SI × BF. Thisvector of 1,000 PAF values was re-sampled 1,000 times by boot-strapping, resulting in a PAF mean and 95% confidence interval(Davison and Hinkley 1997). Evidence of atresia at the end ofthe spawning run was low in 2002, so the effects of atresia andany resulting residual yolked oocytes were not included in thissimulation because we could not estimate a nontrivial value.
RESULTS
Sample Sizes and Field ConditionsHistological sections were analyzed from 383 female Amer-
ican Shad in 2002. Sixty-four females were purchased from thedrift gill-net fishery between March 28 and April 25 to supple-ment the 72-h collections of 149 females taken between April 4and April 7 and 170 females taken between April 17 and April20. One hundred females were purchased from the drift gill-netfishery in 2003 between April 14 and May 5 for macroscopicevaluation of ovaries and batch fecundity, which was estimatedfor 26 females in 2002 and 46 females in 2003.
Sample collection was affected by environmental conditions.The 72-h collections in 2002 were planned in early April andearly May to occur early and late during the spawning run, andthe fishery-dependent samples were designed to occur through-out the spawning run from beginning to end. However, in 2002water temperature ranged from 13◦C to 16◦C between March 28and April 12, rose rapidly to 24◦C by April 17, and remained at23–25◦C until April 25, forcing the second fishery-independent
sample to occur earlier than planned. These elevated temper-atures appeared to have caused an early end to the 2002 run.In 2003, water temperatures followed a more typical patternand ranged from 14◦C to 21◦C during the sampling period ofApril 14–May 5. Sampling ended in 2003 when fishing ceasedbecause American Shad catches declined and bycatch becameexcessive.
Oocyte DevelopmentNo females were observed in a prespawning condition. Go-
nad histology showed either an advanced clutch of oocytes infinal maturation or POFs. Only nine specimens were consid-ered spent (i.e., no advanced yolked oocytes and POFs <24 hold). The GSI was as high as 45% among individuals. Althoughhigher median GSIs were measured early in each season andlower GSIs were measured late in each season, overall, GSI re-mained high on the spawning grounds in both years (Figure 2),presumably a result of de novo vitellogenesis. Primary growth,partially yolked, and yolked oocytes were present together in>80% of ovary sections, and mature oocytes and POFs in vari-ous stages of degradation were common. Alpha atretic oocyteswere uncommon, comprising 1% or less of oocyte types ob-served in 87% ovaries examined. Still, atresia prevalence andintensity were high enough to indicate a down regulation of thenumber of yolked oocytes early in the spring, >1% of oocytesbeing atretic in 15% to 30% of specimens collected up to April7. Atresia declined as the season progressed (Table 2).
Between 0% and 7% of specimens did not contain anypartially yolked oocytes prior to April 7, 2002, after whichthis increased slightly (11% to 21%; Table 2). However, the
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FIGURE 2. Individual values for female American Shad gonadosomatic index(upper panel) and batch fecundity (lower panel) during the spawning runs of2002 (filled circles) and 2003 (open circles) in the Mattaponi River. Linesconnect the median values in 2002 (solid line) and 2003 (dashed).
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TABLE 2. The seasonal patterns of alpha (α) atresia and partially yolked (PY)oocytes in ovaries of American Shad collected from the Mattaponi River in 2002.Atresia prevalence is the percentage of individuals with α atretic oocytes, andintensity is the percentage of individuals with >1% of α atretic oocytes; N isthe number of ovary cross sections analyzed from that date.
PY oocytes (%)
Atresia (%) Mean PY Fish withpercent per no PY
Date Prevalence Intensity ovary (SD) oocytes N
Mar 28 50 15 10 (7) 5 19Apr 3 45 30 9 (6) 5 20Apr 4 57 14 12 (8) 7 14Apr 5 45 18 11 (7) 5 65Apr 6 42 18 13 (6) 0 48Apr 7 40 25 9 (6) 11 28Apr 12 25 5 10 (8) 20 20Apr 17 25 5 8 (6) 15 20Apr 18 43 0 10 (6) 16 61Apr 19 28 2 9 (9) 13 60Apr 20 21 0 8 (7) 21 29
average percent of each ovary comprising partially yolkedoocytes did not differ by date (ANOVA: F10, 372 = 1.53, P =0.13). Of the 10 slides from which oocyte size distribution wasmeasured, 5 showed a continuous size distribution of oocytesfrom primary growth through the most advanced stage and 5had a gap in size between primary growth oocytes and moreadvanced stages (Table 3; Figure 3). Continuous distributionswere observed from specimens collected on March 28 and April5, 7, 12, and 17. Discontinuous oocyte size distributions wereobserved from specimens collected on March 28 and April 3, 12,19, and 25. All 10 had evidence of imminent or recent spawningin the form of oocytes in final maturation or POFs. The GSIdid not differ between the two groups (Student’s t = 0.3, df =8, P = 0.8), but specimens with a continuous size distributionof oocytes contained a significantly larger fraction of partiallyyolked oocytes (Student’s t = 6.9, df = 8, P < 0.001). Eachof the five specimens with continuous oocyte size distributionshad >10% partially yolked oocytes, whereas specimens witha gap in size between primary growth and secondary oocyteshad ≤10% partially yolked oocytes. Out of the 383 slides forwhich oocytes were classified and enumerated, 171 had >10%of oocytes partially yolked. We infer that a similar proportion,45%, of fish would have a continuous size distribution of oocytesif measurements were made for all specimens collected.
In sum, it is possible that almost half of females were un-dergoing de novo vitellogenesis while actively spawning. Thisevidence of fundamental oocyte asynchrony, together with theevidence that down-regulation of the number of yolked oocytesoccurs throughout the spawning season, demonstrates that an-nual egg production is indeterminate.
TABLE 3. Characteristics of ovaries in 10 females in which oocyte size dis-tribution was checked for a gap between primary growth oocytes and oocytesin vitellogenesis. Most advanced oocyte stage includes yolked (Y), early nu-clear migration (ENM), intermediate nuclear migration (NM), and hydrated (H)oocytes. Postovulatory follicles were observed as none, new (P0), 1-d old (P1),or 2-d old (P2). The gonad-somatic index (GSI) is the ratio of ovary weight tothe body weight less the ovary.
Gap in Most PYoocyte advanced Postovulatory oocytes
Date sizes oocyte stage follicles GSI (%)
Mar 28 Yes NM None 20 5Mar 28 No Y P0 17 28Apr 3 Yes H P1 32 10Apr 5 No ENM P0 14 17Apr 7 No NM P2 17 26Apr 12 Yes H P1 27 0Apr 12 No ENM P1 23 25Apr 17 No ENM P0 15 33Apr 19 Yes NM P2 9 0Apr 25 Yes NM P1 6 3
Spawning IntervalDiel periodicity of oocyte maturation, POF degradation, and
spawning were evident in the shad we examined. Mature oocytesearly in nucleus migration (NM) were most prevalent in earlyand late morning samples (Figure 4A). Mature oocytes inter-mediate in the NM/MN peaked in prevalence in mid to lateafternoon. Mature oocytes late in NM began to appear in thelate evening and were prevalent in morning samples. Hydratedoocytes appeared between early and late morning samples. NewPOFs appeared during the afternoon and were absent in themorning. A proposed timeline of oocyte maturation and ovula-tion, based on the April 17–20 data, is presented in Figure 4B.In the April 4–7 collections, a similar pattern was apparent butwith more overlap between stages when the temperatures werecooler.
These stage-specific patterns over the diel cycle were ex-plained if spawning activity peaks at dusk following oocytematuration that began up to 36 h before spawning. Therefore,the presence of oocytes in early and intermediate NM stagesindicated that spawning would have occurred the day followingcapture. Mean spawning fraction, estimated using incidencesof these mature oocyte stages and POFs, ranged between 35%and 46% of females spawning on any given day in 2002, whichyields an estimated spawning interval of 2.17–2.86 d (Table 4).The sum of the percent frequency of fish that would spawn theday following capture (i.e., day – 1) and the day of capture(day 0) was between 0.83 and 1.0 (Table 4). Histological evi-dence that spawning events occurred within 48 h was directlyobserved in about two-thirds of the females. For example, 70%of the females with intermediate NM-stage oocytes also con-tained 1-day-old POFs. Similarly, 66% of specimens containing
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TABLE 4. Spawning fraction (SF) means by sample day and spawning interval (SI; the inverse of SF), as determined by microscopic evaluation of AmericanShad ovaries from the Mattaponi River. Proportional estimates of SF are made using multiple histology markers, as denoted in Table 3. There was no significantdifference in spawning frequency by date (ANOVA: F5, 18 = 0.11, P = 0.98; N = females sampled for histology per date).
Proportions by day relative to spawing (day 0)Means
Dates Day – 1: Day 0: Day + 1: Day + 2:in 2002 N ENM + INM LNM + H + P0 P1 P2 SF SI
Mar 28 19 0.53 0.37 0.47 0.21 0.36 2.78Apr 3 18 0.5 0.33 0.55 0.27 0.41 2.44Apr 4–7 156 0.44 0.39 0.32 0.34 0.35 2.86Apr 12 20 0.70 0.25 0.60 0.35 0.46 2.17Apr 17–20 170 0.44 0.48 0.35 0.40 0.41 2.44Apr 25 4 1.00 0.00 0.25 0.50 0.44 2.27
late NM oocytes, hydrated oocytes, or new POFs contained2-day-old POFs. Batches were often 2 d apart but were not ob-served to be more frequent than a batch every 2 d. Specifically,no ovary simultaneously contained early or intermediate NM-stage and hydrated oocytes or hydrated oocytes and 1-d POFs.Among 21 specimens for which both scales and histology wereavailable, spawning interval was exactly 2.2 d for both virgin (N= 11) and repeat (N = 10) spawners. Spawning interval also didnot differ between size groups (ANOVA: F3, 12 = 0.22, P = 0.87)
More spawning females (day 0) were detected by histologythan by macroscopic appraisal of ovaries (Table 5). The macro-scopic and histologic methods did not differ in ability to detectday-0 spawners in morning samples (χ2 = 0.07, df = 1, P =0.8), but there was a significant difference between methods inafternoon samples (χ2 = 17.9, df = 1, P < 0.001). Macroscopicappraisal of ovaries collected in the afternoon and evening un-derestimated the number of day-0 spawners because detectingindividuals that had already ovulated and spawned earlier thatday was not possible with the naked eye, whereas histologywould detect new POFs in the afternoon. Such analyses con-firmed that the macroscopic method could account for spawn-ing interval, but only during morning hours, when an advancedclutch of oocytes was unambiguously present and daily spawn-ing activity had not yet commenced. In 2003, when no gonadhistology was prepared, macroscopic examination of gonadsoccurred before noon (Table 5).
FecundityBatch fecundity ranged nearly sevenfold among individuals
(Figures 2, 5). It generally increased with OFBW, FL, and agebut was not significantly correlated (α = 0.05). Repeat spawn-ers had a mean BF that was 23% higher than virgin spawners(Student’s t = −2.39; df = 61; P = 0.02); the mean for virginspawners was 33,200 (SD = 10,300, range = 12,700–57,000, N= 29) and for repeat spawners was 40,800 (SD = 14,000, range= 14,500–81,400, N = 34). Multiple predictors of BF wereexamined with an AIC approach, and the most likely models
accounted for whether a female was a virgin or repeat spawner(Model 6; Table 6) or included spawning history with one othervariable (Models 7 and 8; Table 6). Whether using a frequen-tist or an information-theoretic approach, spawning history wasidentified as the most likely source of variation in batch fecun-dity.
Bootstrapped estimates of the indeterminate PAF were dou-ble that of previously published determinate-based fecundityestimates. A gamma distribution was fit to the data for both SI(Table 4; Figure 6A; gamma probability density function (pdf)
TABLE 5. Spawning fraction (SF) inferred from macroscopic (m) and his-tological (h) assessment of ovaries from female American Shad collectedfrom the Mattaponi River. Approximate sampling times were morning (0500–1200 hours), afternoon (1200–1700 hours), and evening (1700–2200 hours); SF= number of females sampled (Nf) that date divided by those judged via m or hassessment to be spawning on the day of capture. Histology was only availablefor specimens collected in 2002.
Date Time Nf Nm Nh SFm SFh
2002Apr 4–7 Morning 40 14 16 0.35 0.4Apr 17–20 Morning 81 38 38 0.47 0.47Apr 4–7 Afternoon 38 10 18 0.26 0.47Apr 17–20 Afternoon 25 11 11 0.44 0.44Mar 28 Evening 19 1 7 0.05 0.37Apr 3 Evening 18 3 6 0.17 0.33Apr 4–7 Evening 45 17 30 0.38 0.67Apr 12 Evening 20 5 9 0.25 0.45Apr 17–20 Evening 60 24 35 0.4 0.58
2003Apr 14 Morning 20 4 0.2Apr 21 Morning 15 7 0.47Apr 24 Morning 17 6 0.35Apr 28 Morning 9 6 0.67May 2 Morning 19 11 0.58May 5 Morning 20 14 0.7
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FIGURE 3. Demonstration of asynchronous versus group synchronous oocytedevelopment early in the spawning season, by plotting oocyte size frequenciesfrom two American Shad in 2002 that were actively spawning in the MattaponiRiver. (A) This female, collected on April 5 when water temperature was 16◦C,had most advanced oocytes that were in the intermediate migratory nucleusstage, 1-day-old POFs, a gonadosomatic index (GSI) of 14.3, and had spawnedthe day prior to capture and probably spawned the day following capture. Theplot shows a continuum of oocyte sizes from perinucleolar through advancedyolked, which is typical of asynchronous oocyte development. (B) This female,collected on April 17 in the evening when water temperature was 24◦C, hadmost advanced oocytes that were fully yolked, fresh POFs, a GSI of 20, andresidual hydrated oocytes in the lumen that did not show up in histology, furthersuggesting this fish had just spawned. In contrast to fish (A), there is a distinctsize gap between perinucleolar and more advanced oocytes, suggesting that denovo vitellogenesis had ceased for fish (B) during this spawning run. Abbrevi-ations: PN = perinucleolar, PY = partially yolked, Y = fully yolked, NM =intermediate nuclear migration.
shape = 2.9, scale = 1; KS: D = 0.172, P = 0.48), and virginfemale BF (Figures 5, 6B; gamma pdf shape = 5.75, scale= 1.75; KS: D = 0.168, P = 0.35).Residence time (RT) wassimulated via a normal distribution (Figure 6C) using the datafrom Olney et al. (2006). The bootstrapped mean PAF estimate(PAF = RT/SI × BF) was 511,000 eggs (95% CI = 478,000–544,000; Figure 6D). This estimate of virgin female fecundity inthe Mattoponi River during 2002–2003 was significantly higherthan Leggett’s (1969) estimate for virgin females of 260,000(one-sample t-test: t = 540, df = 999, P < 0.0001). The newestimate should be conservative since older repeat spawnersare likely to have higher fecundity, but it was also significantlyhigher (Student’s t = 51, df = 1,016, P < 0.0001) than Nichols
FIGURE 4. (A) Observed via gonad histology (see Table 3 for abbrevia-tions), and (B) predicted diel reproductive periodicity of American Shad in theMattaponi River. Panel (B) depicts a schematic timeline of oocyte maturationand ovulation, where the horizontal bars represent a period when each oocytetype is expected in ovaries when multiple females are collected and examined.Following the bars diagonally from early NM to new POFs approximates thetime required for the final maturation and spawning of a cohort of eggs. Theshaded areas labeled “spawning” depict the time when ovulation occurs, with“hydration” being replaced by “new POFs.”
and Massman’s (1963) estimate of 288,000 (SD = 83,300, 95%CI = 169,000–436,000, N = 18) for both virgin and repeatspawners, ages 4–7. Our new, indeterminate estimates werealso higher than previous estimates of PAF for American Shad inFlorida’s St. Johns River, which had been the highest estimate inthe literature (Figure 6D; Davis 1957; Leggett and Carscadden1978).
DISCUSSION
An Indeterminate PatternThe evidence of asynchronous oocytedevelopment with re-
spect to vitellogenesis (Olney et al. 2001; data herein), suggeststhat using the determinate method is unreliable for this popula-tion. De novo vitellogenesis appears to stop before the end ofthe season in many, perhaps all females, but the indeterminatefecundity method is more appropriate for this population be-cause of the substantial evidence of new oocytes produced afterspawning begins.
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FIGURE 5. American Shad batch fecundity compared between virgin and repeat spawners (upper left panel) and between years (lower left panel). Size-adjustedbatch fecundity compared between virgin and repeat spawners (upper right panel; filled symbols = virgin spawners and open = repeat spawners) and betweenyears (lower right panel; filled symbols = 2002 and open = 2003.
The dynamics of oocyte growth and recruitment have beendirectly measured only for a few Alosa species, but in all cases,some degree of asynchronous oocyte development with respectto vitellogenesis is evident (Mylonas et al. 1995; Olney et al.2001; Pina et al. 2003; data herein), as well as batch spawn-ing (Jessop 1993; Pina et al. 2003; Harris and McBride 2007;McBride et al. 2010; data herein). Olney et al. (2001) and Mu-rauskas and Rulifson (2011) refer to groups of oocytes in syn-chrony, but they are both referring to maturation of an individualbatch, and not vitellogenesis. Jessop (1993) assumed that the re-lated river herrings (Blueback Herring A. aestivalis and AlewifeA. pseudoharengus) were group synchronous as in oceanic her-ring but this has not been substantiated. Atlantic Herring Clupea
harengus have group-synchronous oocyte development with re-spect to vitellogenesis and they spawn all their eggs in a singleevent (i.e., total spawning; Murua and Saborido-Rey, 2003), butmany clupeids do not (McBride et al. in press), so Jessop’sassociation is doubtful.
In a historical context, it is interesting that the determinatemethod was initially applied to American Shad to correct in-terpretations from hatchery reports that females only produce10,000s of eggs each year (Lehman 1953). Such low estimateswere based on strip spawning efforts, which would producebatch fecundity estimates. Lehman’s application of a determi-nate method changed, by an order of magnitude, our perceptionof egg production by American Shad, and it lead to observations
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TABLE 6. Model comparisons of eight different data aggregates testing theeffect of various environmental proxies (year, day of year [DOY]) and biologicalvariables (length, weight, and spawning history) on batch fecundity of AmericanShad: (1) all variables, (2) environment only, (3) biological only, (4) ovary-freebody weight (OFBW) only, (5) fork length (FL) only, (6) spawning history only(virgin versus repeat spawners [Repeat]); the last two models (7, 8) considerenvironmental proxies added to the strongest biological variable. Model sets areevaluated using the second-order Akaike’s information criterion (AICc) value;�AICc values <2 are considered indistinguishable. Abbreviations: K = numberof estimated parameters for each model, Wt = evidence ratio in favor of anygiven model being the most parsimonious, LL = log-likelihood, and the sign ∼symbolizes a relationship between the dependent and independent variables.
LogModel K �AICc Wt likelihood
1. BF ∼ DOY +Year + FL +OFBW + Repeat
7 5.61 0.02 −680.49
2. BF ∼ DOY +Year
4 6.10 0.01 −684.41
3. BF ∼ FL +OFBW + Repeat
5 3.76 0.04 −682.06
4. BF ∼ OFBW 3 2.33 0.09 −683.675. BF ∼ FL 3 2.35 0.09 −683.686. BF ∼ Repeata 3 0.00 0.29 −682.507. BF ∼ DOY +
Repeat4 0.15 0.27 −681.44
8. BF ∼ Year +Repeat
4 0.92 0.18 −681.82
aThe lowest AICc value.
of a latitudinal gradient in the standing crop of yolked oocytes(Leggett and Carscadden 1978). Leggett and Carscaddens’conclusion that there is equal lifetime fecundity across popu-lations, which is both expected by life history theory and anadaptive mechanisms to support natal homing, codified an ac-ceptance of the determinate fecundity method. The indetermi-nate fecundity method is simply an extension of the determinatefecundity method, without the assumption that standing stockequals productivity, and this investigation is simply an extensionof these earlier efforts to evaluate and appropriately adjust meth-ods to estimate American Shad fecundity. Similar reassessmentsare occurring for other species as well (e.g., Gordo et al. 2008).
The Indeterminate MethodEvidence of de novo vitellogenesis means that the determi-
nate method will underestimate annual fecundity. An indeter-minate fecundity method should be a more accurate methodbecause it accounts for the yolked oocytes that recruit af-ter spawning commences. Its disadvantage relative to the de-terminate method is that there are many more parameters toestimate—namely the spawning period, the spawning interval,batch fecundity, and atresia—to calculate annual fecundity (Mu-rua et al. 2003). These data are rarely measured for AmericanShad populations (Olney and McBride 2003). In comparison,the determinate method only requires an estimate of the standing
stock of fully recruited yolked oocytes and verification of the as-sumption that standing stock equals annual productivity (Kuritaet al. 2003; Kurita and Kjesbu 2009). As this is the first applica-tion of the indeterminate method to American Shad, we explorethe additional costs and sources of error of this approach.
Residence time measured using acoustic tagging technologyis a reasonable proxy for spawning duration in the York Riverstock. The migration route is short and most spawning is pre-sumed to occur within 48–64 rkm of the listening station placedat the entrance to the spawning grounds by Olney et al. (2006,see also Bilkovic et al. 2002). Gonad histology did not revealany evidence of females on the spawning ground that were notactively spawning. The few spent fish collected contained re-cent (<24-h-old) POFs. Moreover, specimens containing recentPOFs have been documented in the York River estuary well be-low the spawning grounds, which suggests rapid exit followingthe cessation of spawning (Olney et al. 2001).
The sensitivity of spawning duration to environmental con-ditions is unknown. We noted that the 2002 spawning seasonwas truncated by anomalously warm weather during the middleof April. It is possible that the 2002 spawning period occurredearlier or was shorter than in 2003. Telemetry data were onlyavailable from a single year. Data on interannual variability inspawning duration would help inform future estimates of PAFgenerated using an indeterminate method.
Gonad histology is more costly than macroscopic interpre-tation of spawning markers, but it is more informative in termsof estimating spawning interval. In addition to the direct costsof laboratory processing, studies in other systems need to con-sider additional calibrations of the POF method if spawningoccurs at markedly different temperatures because the degra-dation of POFs varies with temperature (Fitzhugh and Hettler1995; Witthames et al. 2010); however, spawning by AmericanShad generally occurs at the same temperature among popula-tions (Leggett and Whitney 1972), so that these calibration costsare not be needed in all future studies. In monitoring situations,the macroscopic method is reliable if collections are planned at atime when individuals ready to spawn that day are unambiguous,which occurred in the morning hours for the York River popu-lation of American Shad. The more cost-effective macroscopicmethod can be justified for any river in which diel spawning canbe demonstrated.
Batch-spawning has long been recognized in American Shad(Lehman 1953), and it may be ignored in terms of calculatingPAF if conditions for using a determinate fecundity method canbe verified. However, improved estimates of batch fecunditiesamong spawners or during the spawning run have been identi-fied as useful in demographic models for assessing managementoptions (Castro-Santos and Letcher 2010; Harris and Hightower2012). In some fishes, relative batch fecundity declines towardthe end of the spawning season or in relation to reduced food(Macchi et al. 2003; Ganias et al. 2004; McBride et al. in press).Our estimates of batch fecundity were similar to previous esti-mates for the York River system (11,300–79,000 eggs, N = 15;Olney and McBride, 2003), and we report that American Shad
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FIGURE 6. Measures of reproductive potential for female American Shad: (A) spawning interval (SI), (B) batch fecundity (BF), (C) residence time (RT) as aproxy for spawning period, and (D) potential annual fecundity (PAF). Data are plotted from this study in panels (A) and (B) as open bars together with simulateddistributions (solid curves). In panel (C) RT is simulated as a normal distribution using data from Olney et al.’s (2006) 2003 tagging study in the same river. Virginspawner PAF estimates, as measured by the determinate method and reported by Leggett (1969), are plotted in panel (D) as vertical lines for the St. John Riverin Canada (148,000; dotted line), the York River in Virginia (260,000; dashed line), and the St. John’s River in Florida (412,000; solid line), along with 1,000bootstrapped mean estimates of PAF (gray bars) from the simulations of PAF = RT/SI × BF.
maintained consistent egg output over the course of sampling inthis study. However, our study may not have captured the fullspawning season. As observed in 2002, water temperatures rosesuddenly, and the spawning season appeared to be truncatedin time. Spawning and sampling in 2003 was extended fromApril 14 to May 5, which was similar to when Bilkovic et al.(2002) reported collecting American Shad eggs in 1998 (April16 to May 13) and 1999 (April 11 to May 7). It is possible thatthe different interannual temperature patterns simply offset the
spawning periods in each year rather than shortened or length-ened one or the other. Still, future investigations should addressthe possibility that some difference in batch fecundity exists atextreme ends of the spawning season because this could nothave been detected in our study.
Accounting for atresia is necessary, whether using indeter-minate or determinate fecundity models. We noted a patternof downregulation of vitellogeneic oocytes by atresia duringthe spawning season—which, again, supports the use of an
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indeterminate method—but little evidence of postspawning atre-sia. The determinate method, as developed for American Shad,counts oocytes based on size criteria but does not specify how torecognize or discount atretic germ cells (Lehman 1953; Davis1957; Nichols and Massman 1963). The prevalence of atresiacan also increase at the end of spawning in many fishes (Hunterand Macewicz 1985; Barbieri et al. 1994). Lehman (1953) re-ports low levels of unovulated secondary oocytes among spentfish in the Hudson River during the 1951 spawning run, but Ol-ney et al. (2001) reported extensive post spawning atresia, so thistrait may vary between years. Olney et al. (2001) observed 68%of post-spawn American Shad in the York River Estuary havingleft the spawning grounds still containing a substantial amountof vitellogenic oocytes as well as identifiable POFs. Ovariesin those fish were large enough that field scientists could mis-take them as prespawn without the histological confirmation ofthe presence of POFs. The frequency among individuals, theamount per individual, and causal factors leading to atresia ofunspawned oocytes at the end of the spawning period warrantcontinued investigation.
Our PAF estimates account for the potential effect of size,age, and spawning history. Females used to estimate fecunditywere similar in size with those used in earlier studies (e.g.,378–483 mm FL; see Table 8 in Nichols and Massman 1963).Age-based and size-based variations in fecundity have been re-ported for many species (e.g., Lambert 1987; Marteinsdottir andThorarinsson, 1998; Olin et al. 2012), including previous inves-tigations of American Shad (e.g., Lehman 1953; Nichols andMassmann 1963; Leggett and Carscadden 1978). Although wedid not observe the specific effects in 2002–2003, we did ob-serve that spawning history was important (i.e., repeat spawnershad higher batch fecundity than virgin spawners), so we usedonly virgin spawner batch fecundity as a conservative estimateof indeterminate PAF. As to why we did not observe a signifi-cant correlation between fecundity and size or age, it may be thatlarger and older fish are able to produce higher standing cropsof yolked oocytes upon arriving to the spawning grounds (mea-sured as determinate PAF, a method that we did not pursue), orthat high fishing mortality rates have truncated the size and ageof the recent population so these effects are no longer evident.The number of batches per season, and thus PAF, can increasewith age or size by either decreased spawning interval, increasedspawning duration, or by a combination of the two (Fitzhughet al. 2012). We did not find that spawning interval was affectedby either spawning history (repeat versus virgin) or size. Indeter-minate fecundity is a process that could boost fecundity beyondthe physical limitations of body cavity for all females, whichreduces but may not eliminate the effect of size on PAF. Data onspawning duration versus age or size are not currently availableand would be needed to better describe these relationships.
Implications of Indeterminate FecundityConsidering that American Shad are not known to feed regu-
larly on the spawning grounds (Walters and Olney 2003; Harris
and McBride 2009), asynchronous oocyte development and theneed for an indeterminate fecundity method were not necessarilyexpected. In the absence of continued feeding while spawning,production of yolked oocytes after spawning commences re-quires energy from stored somatic reserves. Drawing on suchreserves prior to spawning is characteristic of a capital breedingpattern, which is typically associated with determinate fecun-dity (McBride et al. in press). However, we postulate that themany American Shad populations may differ or perhaps be quiteflexible with regard to acquisition and allocation of energy to re-production. Intermittent feeding during the spawning run is doc-umented (Harris and McBride 2009), and from south to north,different populations allocate progressively less energy to re-production. This energy is allocated earlier in the spawning mi-gration in the north, among the iteroparous populations. Specif-ically, American Shad continued to transfer energy to gonadsonce in the York River, Virginia, and St. Johns River, Florida,whereas American Shad in the Connecticut River entered theriver having completed gonad development at sea (Glebe andLeggett 1981). Glebe and Leggett (1981) regarded this processas responsible for latitudinal differences in postspawning sur-vival of the adults. This effect may also increase the numberof spawning events through de novo vitellogenesis, particularlyin the southern populations. Batch size has not been found toincrease with latitude (Olney and McBride 2003) and may besimply constrained by the physical limit of the coelomic cavity,but spawning season length decreases from south to north, as thewindow of favorable temperatures becomes shorter (Leggett andWhitney 1972). Southern fish may spawn for a longer durationand release many more batches than northern fish, thus puttingas much somatic energy into egg production as is physiologi-cally possible, up to death. If the indeterminate fecundity type ismore prevalent in southern populations, then this could increasethe latitudinal gradient of PAF even more than already reported(Leggett and Carscadden 1978; Limburg et al. 2003). In turn, thenumber of repeat spawning events is thought to equilibrate life-time fecundity between the iteroparous northern and the semel-parous southern populations (Leggett and Carscadden 1978), buta reevaluation of this latitudinal gradient is now warranted. Notonly are these life history traits quite likely dynamic (Leggettet al. 2004; Castro-Santos and Letcher, 2010), but as presentedherein, the fecundity estimates may be biased low for at leastsome of the populations measured by the determinate method.
We predict three possible outcomes if investigation of fe-cundity type and estimates of American Shad annual fecunditycontinue. First, a single adjustment may occur across all popula-tions, as in all determinate estimates of PAF turn out to be abouthalf that of indeterminate estimates. This is unlikely, becausethese populations range across three biogeographic regions thatappear to force several phenotypic traits to vary with latitude.Second, fecundity adjustments may be regional. This is quitepossible, and may be particularly interesting if some populationsexhibit a determinate fecundity type and some an indeterminatetype, as noted between other species and expected within some
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species along large environmental clines (Qasim 1956; Ganias2013). American Shad and other Alosa species are well suitedto address this topic because of their extensive latitudinal rangealong both coasts of the eastern and western North AtlanticOcean. If so, we expect that northern populations to exhibita determinate type, where researchers in this region may thenexplore application of more modern, rapid methods of fecun-dity estimation (Friedland et al. 2005). Third, it is possible thatprevious PAF estimates are more or less accurate but egg pro-duction varies considerably by some time-varying condition. Ifso, then previous estimates for the York River system may havebeen lower in the past as a result of some density-dependentor environmental effect. One can find evidence of interannualvariations in population-specific estimates of PAF, and twofoldvariations in annual fecundity are not undocumented in otherspecies (Rideout and Morgan, 2007; McBride et al. in press), sothis possibility also deserves further attention.
In sum, American Shad have asynchronous oocyte devel-opment with respect to vitellogenesis and group synchronousoocyte development with respect to oocyte maturation (equalsbatch fecundity), so an indeterminate method is appropriate toestimate annual fecundity. This is certainly true for the York–Mattaponi River population and is probably true for other pop-ulations of American Shad and other Alosa species. The inde-terminate method has more parameters to measure, so it is morecostly and errors can compound in the PAF estimate. The appli-cation of the indeterminate method does, however, demonstratethat previous investigations have overlooked important sourcesof variation in annual and lifetime egg production and have un-derestimated fecundity in American Shad. Application of theindeterminate method will not be easy to implement in a routinemanner, but it is likely to expand our awareness of variation inreproductive potential and recruitment dynamics among thesefishes. An immediate message arising from this work is thatmangers should consider the effect of higher fecundity of repeatspawners in rebuilding of this population, which is presentlysubject to a fishing moratorium.
ACKNOWLEDGMENTSWe thank both students and staff at the Virginia Institute of
Marine Science for assistance in field sampling and laboratoryprocessing. Special mention for field assistance to B. Watkins,J. Goins, S. Denny, J. Romine, W. Dowd, B. Daniels, D. Grusha,and R. A. Hyle for assistance with field collections. J. and V.Crawford of Walkerton generously offered their private dock asa staging area for the 72-h sampling efforts. C. and T. Custalowsupplied specimens as well as valuable technical guidance onhow, where, and when to fish drift gill nets for spawning Amer-ican Shad. S. Denny provided crucial knowledge of preparationof fish ovaries for paraffin histology. A. Collins, K. Friedland,J. E. Harris and two anonymous reviewers provided helpful cri-tiques of earlier iterations of this manuscript. Input on measuringand understanding fecundity was received from the Northwest
Atlantic Fisheries Organization’s Working Group on Reproduc-tive Potential, particularly under the auspices of the COST Ac-tion FA0601, “Fish Reproduction and Fisheries.” We appreciateeveryone’s assistance in this study.
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