Patterns of age-0 yellow perch growth, diets, and mortality in Saginaw Bay, Lake Huron

Journal of Great Lakes Research xxx (2014) xxx–xxx

JGLR-00673; No. of pages: 10; 4C:

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Patterns of age-0 yellow perch growth, diets, and mortality inSaginaw Bay, Lake Huron

Charles R. Roswell a,1, Steven A. Pothoven b, Tomas O. Höök a,c,⁎a Purdue University, Department of Forestry and Natural Resources, 195 Marsteller St., West Lafayette, IN 47907, United Statesb National Oceanic and Atmospheric Administration, Great Lakes Environmental Research Laboratory, 1431 Beach St., Muskegon, MI 49441, United Statesc Illinois–Indiana Sea Grant, Purdue University, 195 Marsteller St., West Lafayette, IN 47907, United States

⁎ Corresponding author at: Purdue University, DeparResources, 195 Marsteller St., West Lafayette, IN 47907, U6799.

E-mail address: [email protected] (T.O. Höök).1 Current Address: Illinois Natural History Survey, Lake

17th St., Zion, IL 60099.

0380-1330/$ – see front matter © 2014 Published by Elsehttp://dx.doi.org/10.1016/j.jglr.2014.01.008

Please cite this article as: Roswell, C.R., et al., PRes (2014), http://dx.doi.org/10.1016/j.jglr.2

a b s t r a c t
a r t i c l e i n f o
Article history:Received 28 February 2013Accepted 6 December 2013Available online xxxx

Communicated by Scott Peacor

Keywords:Saginaw BayAge-0Yellow perchGrowthDietsSize-selective mortality

Identifying mechanisms influencing early-life survival may elucidate recruitment variability of fish populations.Yellow perch (Perca flavescens), are economically and ecologically important in Saginaw Bay, Lake Huron, buthave recently experienced low recruitment despite strong production of age-0 fish. Recent year classes havebeen characterized by slow first-year growth, as indexed by fall size of age-0 yellow perch; however, seasonalgrowth patterns and accompanying diet and survivorship patterns have not been documented for age-0 yellowperch in Saginaw Bay. To this end, we collected age-0 yellow perch weekly (larvae) and monthly (juveniles)throughout the first year of life during 2009 and 2010 to track changes in growth and diet composition. Wealso evaluatedpredation and over-winter energy-loss as potentialmechanismsof size-selectivemortality. Yellowperch growth, energy accumulation and size-specific condition decreased during late summer and fall. Duringlarval and juvenile stages, predominant components of yellowperch diets transitioned from copepods toDaphniaand other zooplankton; however, we observed onlyweak ontogenetic shifts toward benthic prey. Smaller yellowperch a) were preferentially preyed upon by walleye (the bay's main piscivore) and b) displayed lower mass-specific energy content, potentially increasing overwinter starvation risk, suggesting that slow growth increasesmortality risk. Our results are consistent with the hypothesis that recruitment dynamics are influenced by aninterplay of size-selective mortality and diet-induced reductions in growth.

© 2014 Published by Elsevier B.V. on behalf of International Association for Great Lakes Research.

Introduction

Mortality during larval and juvenile stages often limits recruitmentsuccess and subsequent abundances of fish populations (Cushing,1990; Hjort, 1914; Houde, 2008). Thus, recognizingmechanisms under-lying early-life survival can facilitate understanding of fish populationdynamics and improve management of fish stocks and communities(Houde, 2008). However, processes impacting early-life aremultifacetedand may vary across populations and ecosystems (Houde, 1994, 2008).For example, survival among many freshwater fish larvae tends to behigher than in many marine populations, suggesting that juvenile-stage dynamics are relatively more important in inland ecosystems(Houde, 1994). Moreover, variability in growth rates can influencerecruitment success by affecting predation and starvation risks for bothlarvae (Miller et al., 1988) and juvenile fish (e.g., Garvey et al., 1998).In fact, several studies have established links among high early-lifegrowth rates, increased survival, and enhanced recruitment for fishes

tment of Forestry and Naturalnited States. Tel.: +1 765 496

Michigan Biological Station, 400

vier B.V. on behalf of International As

atterns of age-0 yellowperch014.01.008

that occupy various well-studied temperate-zone freshwater ecosys-tems (e.g., Fullerton et al., 2000; Höök et al., 2007; Post and Evans,1989b; Santucci and Wahl, 2003).

Yellowperch (Percaflavescens) are important coolwaterfish through-out much of North America. In the Laurentian Great Lakes, yellow perchsupport both commercial and recreational fisheries in numerous loca-tions (Craig, 2000; Fielder and Thomas, 2006). Moreover, yellow perchare important components of coolwater Great Lakes foodwebs, servingas both predators and key prey for exploited piscivorous fishes(e.g. Hartman and Margraf, 1993). Recruitment of yellow perch to adultpopulations is often characterized by high inter-annual variation, andthis high temporal variability can complicate the management of bothyellow perch fisheries and other species that interact with yellow perch(Fielder and Thomas, 2006; Isermann and Willis, 2008).

Early lives of yellow perch are dynamic: initially pelagic planktivoresas larvae, perch transition at various sizes (e.g., 30 mmWu and Culver,1992) to a demersal lifestyle for the remainder of the juvenile stage.Coincident with changes in habitat utilization, some yellow perchpopulations also exhibit strong ontogenetic diet transitions. From larvalto juvenile stages, yellow perch generally transition from consumingsmall-bodied (e.g., copepod nauplii) to larger-bodied zooplankton(e.g., copepod adults and Cladocera; Graeb et al., 2004). Subsequently,older juvenilesmay transition fromzooplankton to larger-bodied, benthic

sociation for Great Lakes Research.

growth, diets, andmortality in Saginaw Bay, LakeHuron, J Great Lakes

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2 C.R. Roswell et al. / Journal of Great Lakes Research xxx (2014) xxx–xxx

macroinvertebrates; however, such transitions may be dependent onhabitat conditions and prey availability (Mills and Forney, 1981; Postand McQueen, 1994). For example, Daphnia are often preferred preyitems of young yellowperchwhen they are available, butwhenDaphniaare absent, young perchmay transition to energy-rich benthic prey suchas Chironomidae larvae (Wu and Culver, 1992). While a transition fromzooplankton prey to benthic prey is apparent for several age-0 yellowperch populations (e.g., Roseman et al., 1995; Whiteside et al., 1985;WuandCulver, 1992),manypopulations of yellowperch, and congenericEurasian perch (Perca fluviatilis) primarily consume zooplanktonthroughout the juvenile stage (e.g., Fisher and Willis, 1997; Persson,1986).

Changes in diets and resulting growth rates of age-0 yellow perchmay impact subsequent recruitment success, as low growth rates maylead to poor survival (Fitzgerald et al., 2006; Irwin et al., 2009; Millsand Forney, 1981). Due to relatively high mass-specific metabolic ratesand low potential energy stores, smaller juvenile fish may experiencerelatively elevated overwinter mortality (Sogard, 1997). While wintermay not be as important a bottle-neck for yellow perch as for someother species (Johnson and Evans, 1991), small yellow perch havebeen shown to be more susceptible to overwinter mortality, both inthe lab and in Lake St. George, Ontario (Post and Evans, 1989b). Addi-tionally, slower growth extends the time during which young perchare most vulnerable to piscivorous predators (Post and Evans, 1989a;Post and Prankevicius, 1987). As yellowperch increase in size anddevel-op larger, stronger spines, they may become less attractive food forgape-limited predators. Moreover, yellow perch swimming speedsincrease with size (Nelson, 1989), thereby improving their ability toactively escape potential predators.

Saginaw Bay, a large, shallow embayment of Lake Huron, has histor-ically supported a large yellow perch population, with associated recre-ational and commercial fisheries (Fielder and Thomas, 2006; Haas,1995). Due to their numerical abundance, yellow perch are importantcomponents of the Saginaw Bay foodweb. They are considerableconsumers of zooplankton, benthic invertebrates, and fish, and havebeen prevalent in diets of piscivorous fishes (Fielder and Thomas,2006). Saginaw Bay has undergone extensive changes as a result ofvarious anthropogenic activities (Fielder and Thomas, 2006; Fielderet al., 2000; Haas, 1995; Johengen et al., 2000). Overfishing and declinesin habitat quality led to a collapse ofmany Saginaw Bay fisheries by 1950(Fielder et al., 2000; Hile and Buettner, 1959; Schneider and Leach, 1977).Presently, Saginaw Bay remains an altered ecosystem, as a multitude ofexotic species have been introduced and proliferated, and some popula-tions of native species have not recovered (Fielder and Thomas, 2006;Haas, 1995; Nalepa et al., 1996). Although yellow perch fisheries recov-ered in SaginawBay by1970, abundances of yellowperchhave continuedto fluctuate, with high numbers noted in the 1970s and 1980s, and lowernumbers during the1990s (Fielder et al., 2000;Haas, 1995).More recently(2000–2008), abundance of adult yellow perch remained relatively lowin Saginaw Bay (Fielder and Thomas, 2006; Ivan et al., 2011).

From 2003–2008, catch-per-unit-effort (CPUE) of age-0 yellowperch was generally high in annual fall trawling surveys conducted bythe Michigan Department of Natural Resources (MDNR) in SaginawBay (Fielder and Thomas, 2006; Ivan et al., 2011). However, these abun-dant age-0 cohorts coincided with reduced mean autumn size of age-0yellow perch (Fielder and Thomas, 2006; Ivan et al., 2011), consistentwith compensatory density-dependent reductions in growth, possiblyas a result of food resource limitation. Moreover, high densities of age-0 yellow perch in the fall did not translate to an increase in recruitmentto adult or sub-adult components of the Saginaw Bay yellow perch pop-ulation (Fielder and Thomas, 2006; Ivan et al., 2011). High production ofyoung percids (walleye Sander vitreus and yellowperch) in SaginawBayhas been linkedwith a drastic decline in alewife (Alosa pseudoharengus)abundances which have remained very low throughout Lake Huronsince 2003 (Fielder et al., 2007). Previously, large numbers of alewivesin Saginaw Bay likely influenced survival rates of young yellow perch

Please cite this article as: Roswell, C.R., et al., Patterns of age-0 yellowperchRes (2014), http://dx.doi.org/10.1016/j.jglr.2014.01.008

through competition and predation on larval stages (Brandt et al.,1987; Shroyer and McComish, 2000). The decline of alewife may haveresulted in increased survival of yellow perch during pelagic larvalstages and increased intraspecific competition during the juvenilestage. Moreover, since alewives can influence zooplankton communitycomposition and abundance (Brooks and Dodson, 1965), the absenceof alewives could contribute to a novel prey community for youngyellow perch. Finally, the Saginaw Bay walleye population increased inabundance since the collapse of the LakeHuron alewife population, likelyresulting in increased predation pressure on young yellowperch (Fielderand Thomas, 2006). Increased larval survival, slower growth rates, andenhanced predation pressure may interactively influence yellow perchrecruitment in Saginaw Bay.

While long-term fall trawling surveys have documented populationtrends of Saginaw Bay yellow perch (e.g. Fielder and Thomas, 2006),these annual snapshots do not allow for a complete examination ofpotential mechanisms contributing to relatively slow growth of youngyellow perch, and further, have not quantified the link between slowgrowth and poor survival. We sought to examine early-life dynamicsof yellow perch at a higher temporal resolution throughout the firstyear of life by tracking yellow perch cohorts from the larval stagethrough survival to the following spring during 2009 and 2010. Wedocumented growth rates, condition, and diets of young yellow perch,and examined potential relationships between yellow perch size andrisk of starvation and predation mortality. Although we cannot directlyevaluate causes of recent low recruitment without similar data fromhigh-recruitment periods, these analyses can help describe processesthat influence survival during critical early life stages. Consistent withthe hypothesis that the absence of alewives leads to high survival oflarval yellow perch and increased potential for density-dependent reduc-tions in growth,wepredicted conditions for growthwouldbepoor duringthe juvenile stage (i.e. low prey abundance would reduce consumption,causing declines in condition). We expected prey items consumed byperch in other ecosystems, such as Daphnia and Chironomidae larvae,to be important prey items. Finally, given the importance of growth tosurvival, we predicted smaller yellow perch to be more vulnerable topredation and overwinter mortality.

Methods

Sampling design

During 2009–2010, we collected yellow perch and quantified theirphysical and biological environments at multiple sites in Saginaw Bay,a large (2770 km2), shallow (mean depth 8.9m), eutrophic embaymentof Lake Huron (Nalepa et al., 1996; Fig. 1). Specifically, we sampledlarval fish weekly at 8 fixed sites during April–June 2009 and 2010,and we collected juvenile yellow perch monthly at 4 sites during May–October 2009 and April–September 2010. We selected sites to providebroad spatial coverage and to overlap with locations of historical collec-tions (e.g., Nalepa et al., 1996) and concurrent sampling conducted byother researchers as part of a larger study examining the Saginaw Bayecosystem. Moreover, we limited sampling to these sites because theselocations could be reasonably sampled within a week after accountingfor travel time and weather. We used a handheld thermometer tomeasure surface temperature (within 0.5 m of surface) at each site, andduring monthly sampling, we also sampled benthic macroinvertebratesand zooplankton to index available prey for age-0 yellow perch.

To capture zooplanktonprey,we conducted vertical towswith a 0.3mdiameter, 1.5m long, 64 μmmesh zooplanktonnet.We anesthetized zoo-plankton with bicarbonate and preserved samples in 10% sugar-bufferedformaldehyde. In the laboratory, we sub-sampled zooplankton with aHensen-Stempel pipette, and identified and counted a minimum of 600individual organisms per sample. We sampled benthic macroinverte-brates with a standard Ponar dredge (0.052 m2 with a 500 μm mesh),and to concentrate contents, wewashed samples through a sieve bucket



Fig. 1. Location of Saginaw Bay, Lake Huron and sampling locations for this study.

3C.R. Roswell et al. / Journal of Great Lakes Research xxx (2014) xxx–xxx

with a 500 μm screen. We placed concentrated samples into jars andadded 10% formaldehyde with rose Bengal to preserve the sample andstain organisms pink. In the laboratory, we examined preserved benthicsamples in a tray under magnification (1.5×), and we removed, identi-fied, and enumerated all animals in a sample. We did not enumerateindividual Oligochaeta because these animals broke apart into smallpieces in our samples; and because this prey type was generally notconsumed by yellow perch, we felt justified in excluding these counts.

Table 1Linear regressions developed to relate age-0 Saginaw Bay yellow perch total length tostandard length, and energy density to proportion dry mass.

n Independent(range)

Dependent(range)

Slope Intercept R2

483 Standard length(34–87 mm)

Total length(41–102 mm)

1.17 1.30 0.98

148 Proportion dry mass(0.17–0.29)

Energy density(3274–5872 J/g wet)

23,231 −658.7 0.87

Larval yellow perch

We sampled larval fishwith a bongo sampler, which consisted of two0.5 m diameter, 1.5 m long ichthyoplankton nets (333 μm and 700 μmmesh), mounted on a single frame (approximately weekly sampling:2009 April 17 to July 8; 2010 April 12 to July 1). We estimated filteredvolume by use of flow meters (General Oceanics) attached at themouth of each net. We towed the sampler at approximately 1.3 m∙s−1

for 5 min just below the surface behind a research vessel. We used sur-face samples because Saginaw Bay is shallow and well mixed, and wefound no consistent differences in catches or size distributions of larvalyellow perch between surface and oblique tows of our bongo sampler(C. Roswell, unpublished data). In the laboratory, we picked samplesunder magnification and gently placed all larvae into vials containing95% ethanol. We used a dissecting microscope and characteristics listedin Auer (1982) to identify larvae to lowest possible taxonomic level(usually species or genus). We used the dissecting microscope with amounted Micrometrics camera and Image J open-source image analysissoftware to measure total lengths of each larval yellow perch (to0.1 mm). We evaluated diets of larvae by examining contents of theentire digestive tract under a dissecting microscope. We removed con-tents of each digestive tract, identified prey types to general taxonomicgroups, and counted diet items. To estimate diet composition by


biomass, we used published values for dry mass from Hawkins andEvans (1979).

Juvenile yellow perch

We sampled age-0 juvenile yellow perchmonthly at 4 offshore sites(2009, May 5 to October 5; 2010 April 14 to September 22). We alsocollected age-1 (i.e., survivors of 1 winter) yellow perch during May2010 and April and May 2011. We collected juvenile fish using a 7.6 msemi-balloon trawl with a 13 mm mesh cod liner. We towed the trawlat approximately 1.3 m∙s−1 for 10 min, and each month we conducted1–5 trawls per site. On board, we sorted fish by species, placed fish inbags with water, and immediately put bags on ice in coolers. Uponreturning to shore, we stored bags at −20 °C. In the laboratory, wethawed and enumerated yellow perch and measured total lengths andmasses of up to 30 yellow perch from each trawl sample. We separatedage-0 and age-1 yellowperchusing total length, based on clear divisionsin length frequency data (C. Roswell, unpublished data). We alsomeasured standard lengths of a subsample of young yellow perch toestablish a relationship between standard and total lengths to estimatetotal lengths of partially-digested fish in predator diets and fish withdamaged caudal fins (Table 1).




We examined stomach contents of 20 age-0 yellow perch from eachcombination of site and month. To ensure adequate description of vari-ation, we proportionally selected a minimum of 3 fish for diet analysisfrom each trawl sample when multiple trawls were conducted on asite and date. We removed the stomach of each fish, emptied the dietcontents into a Petri dish, and replaced the empty stomach in the fishfor measurement of wet mass. We counted and identified diet itemsto general taxonomic groups under a dissecting microscope. We sub-sampled zooplankton in diets containing more than 100 zooplanktonby adding a known volume of water and removing 1 mL of the sample.We included only items with heads attached, or the heads themselves,in counts of each prey type. We then photographed up to 20 items ofeach prey type for measurement with Image J software. We placeddiet contents and fish in separate pre-weighed drying tins and placedthem in a drying oven at 70 °C for 2–4 days (Lantry and O'Gorman,2007). After drying, we measured dry mass of diet contents and fish.To estimate diet composition by biomass, we 1) used publishedlength-mass regressions from various sources (Roswell, 2011) to esti-mate the dry mass of each prey item and 2) then multiplied measureddrymass of entire diet content by the estimated proportion of total bio-mass comprised by each prey type.

We measured energy content of age-0 and age-1 yellow perch as atemporal index of condition. We used bomb calorimetry (Parr 1261isoperibol calorimeter) to determine energy density of approximately15–20 fish randomly selected from each month of capture to obtainestimates for a range of sizes and seasons. We homogenized whole driedfish with diet contents removed and determined energy content of a sub-sample of dried material (0.1–1.1 g). We developed a linear relationshipbetween proportion dry mass and energy density (e.g., Hartman andBrandt, 1995) to estimate energy densities of all juvenile yellow perchfor which dry and wet mass were recorded (Table 1).

Predators

We retained yearling-and-older (YAO) walleye and yellow perch(determined via length-frequencies) collected in bottom trawls toevaluate potential patterns of predation on age-0 yellow perch. Weevaluated sizes, densities, and diets of YAO walleye and yellow perchin the same manner as described above for age-0 yellow perch. Toaccount for partial digestion of juvenile perch (e.g., missing caudalfin), we estimated total lengths from standard lengths of digestedperch using the relationship between total and standard length wedeveloped from age-0 yellow perch caught in trawls (Table 1).

Data analysis

We conducted a set of analyses 1) to evaluate temporal differencesin growth and amount of food consumed by yellow perch, and 2) toexamine the plausibility of size-dependentmortality through predationand over-winter mortality.

To compare growth rates of juvenile age-0 yellow perch over time,we calculated monthly instantaneous, growth in mass (G). For eachpair of consecutive months, we estimated the slope of a line for differ-ences in natural log total mass over the number of days separatingtrawling. We also calculated and compared estimates of instantaneousgrowth in energy (E) to identify trends of energy accumulation becausefish may allocate energy differently across seasons. We calculated E byestimating the slope of a line for differences in natural log total bodyenergy over the number of days separating trawling. We evaluatedwhether instantaneous growth differed significantly over time by eval-uating differences in slopes with t-tests: for each comparison of twotime periods, we included a binary variable (0 or 1 for different timeperiods) and an interaction variable (the binary variable multiplied bythe day of collection for each fish) as predictors in a linear regressionmodel for mass or energy in both periods. A t-test indicating an interac-tion slope coefficient significantly different from 0 indicated a


significant difference in instantaneous growth rates between periods(i.e., different slopes of the relationship between log-mass or log-energy and day of year).

To further assess seasonal differences in mass acquisition, whilecontrolling for individual size, we indexed seasonal condition of yellowperch. Specifically,we used analysis of covariance (ANCOVA) to evaluatetrends of mass-at-length, i.e. monthly comparisons of the natural log ofperch wet mass in grams (LNMass), using the natural log of total lengthinmm(LNTL) as a covariate (Pope andKruse, 2007). To evaluate seasonaltrends in diet mass while accounting for fish size, we regressed thenatural log of diet dry mass (LNDM) in grams on the natural log of totallength (in mm) of yellow perch (LNTL). We then examined residuals ofthe linear regression model by month.

We evaluated whether predation mortality was size-selective bycomparing mean total lengths of age-0 yellow perch captured in trawlsand age-0 yellow perch found in predator diets caught during the samemonthly sampling using a two-sample t-test. We compared mean totallengths of age-0 yellow perch caught immediately prior to winter(October 2009 and September 2010) and following winter (April andMay 2010 and 2011) using a two-sample t-test to evaluate whetherchanges were consistent with an increase in mean length that wouldbe expected under size-selective overwinter mortality. Additionally,we used ANCOVA to evaluate changes in the natural log of total bodyenergy overwinter.We used the natural log of total length as a covariateto account for length-related differences in total body energy with size(see Höök and Pothoven, 2009; Hurst and Conover, 2003). All statisticalanalyses were evaluated at the α = 0.05 significance level.

Results

Environmental characteristics

During 2009–2010, environmental conditions in inner Saginaw Bayvaried intra- and inter-annually. Temperatures followed similar trendsduring both years, peaking in mid-summer. However, spring and sum-mer temperatures were generally warmer during 2010 (Fig. 2a,b).

Densities of potential yellow perch prey also varied over time(Fig. 3). In 2009, mean total zooplankton density was initially lowerthan 20,000 zooplankters m−3 in May, steadily increased throughAugust, with a sharp peak of around 160,000 zooplankters m−3 in earlySeptember, and a slight decline by October. While temporal patterns oftotal zooplanktonwere roughly similar during 2010, initial mean densitywas slightly higher, 30,000 zooplanktersm−3, and peak total densitywas~130,000 zooplankters m−3 in August.

Composition of the zooplankton community also varied withinand among years. Crustacean zooplankton, especially non-daphnidcladocerans (e.g., Bosmina), increased dramatically during the fall of2009, substantially contributing to peak total abundance. During 2010,cladocerans were less abundant, and dreissenid mussel veligers and“other zooplankton” (e. g., rotifers) were important components ofpeak abundance. While large-bodied cladocerans, such as Daphnia,were not numerically dominant during any part of the year, this taxonwas continuously present in the environment, with minimum densityestimates of 562 m−3 in 2009 (May) and 652 m−3 in 2010 (August).

Composition of benthic macroinvertebrate samples changed littlewithin years (Fig. 3). Amphipoda, Chironomidae larvae, and dreissenidmussels (primarily Dreissena bugensis, hereafter Dreissena sp.) weredominant components of macroinvertebrate communities at our samplesites. Densities of Chironomidae larvaewere slightly higher during 2010,contributing to higher total densities of macroinvertebrates in 2010 than2009.

Abundance and growth

Wecollected a total of 817 larval yellowperch in surface tows. Larvalyellow perch emergence began at similar times during both years. We



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)Fig. 2. Top panels: temperature (closed diamonds, with ranges) and mean mass-specific dry diet biomass (open boxes, with standard error) plotted against time for 2009 (panel a) and2010 (panel b). Unique letters indicate a statistically significant difference inmass-specific diet drymass, (Tukey post-hoc tests (α= 0.05) followingANOVA).Middle panels: total lengthsof larval (frombongo sampler) and juvenile (frombottom trawl) yellowperch (open circles)with interpolatedmean lengths (line) and total lengths of yellowperch found inwalleye diets(open rectangles) in Saginaw Bay during 2009 (panel c) and 2010 (panel d). Asterisks indicate significantly smaller mean total lengths of yellow perch found in walleye diets than meantotal lengths in the trawl catches (t-tests). The dashed line indicates the mean total length of yellow perch in the Michigan Department of Natural Resources annual fall (September–October) trawl survey, 1970–2004 (81.2 mm, Fielder and Thomas, 2006). Bottom panels: mean (with standard error) instantaneous growth in mass (G, closed circles) and energy(E, open circles), plotted on the midpoints of time periods used to calculate each rate in 2009 (panel e) and 2010 (panel f). Unique letters indicate a statistically significant difference(within-years only) in G (letters a, b, c) and E (symbols α, β, γ; t-tests).


first collected larvae on April 30 during 2009 and on April 28 during2010. The larval period for yellow perch appeared to last longer during2009 because larvae were captured through June 17 during 2009 butonly through May 26 in 2010.

We collected a total of 12,638 age-0 yellow perch in bottom trawlsduring 2009 (n = 6577) and 2010 (n = 6061), and we collected 29and 1097 surviving age-1 yellow perch during April–May 2010 andMay2011, respectively.Whilemean sizes of young yellowperch changedseasonally, a wide range of sizes comprised each cohort throughout theyear (Fig. 2c,d). By late summer and fall, mean sizes of age-0 yellowperch were smaller in 2009 (reaching 75.6 mm mean total length inOctober) than 2010 (by September 2010 age-0 yellow perch averaged80.7 mm). While mean total length of annual cohorts of age-0 yellowperch increased relatively rapidly from July to August, growth appearedto slow after August during both years. Relative growth and instanta-neous growth in mass (G) and energy (E) also slowed by fall duringboth years (Fig. 2e, f), before water temperatures cooled. Specifically,


G and E decreased significantly with each consecutive month (fromJuly–October 2009; July–September 2010; t = −8.47 to −4.47, df =144 to 165, p b 0.01), indicating a consistent slowing of growth andaccumulation of energy.

Relationships between LNMass and LNTLwere consistently allometric(i.e., slope N3), and after adjusting for this length effect yellow perchmass-at-length was lowest during September of both years (Fig. 4). For2009, LNMass was significantly related to LNTL (F1, 315 = 2776.97,p b 0.001) and month (F3, 315 = 14.02, p b 0.001). Adjusted to meanlength (55.99 mm), LNMass was higher in July than other months (t318range: 3.03–5.22, p range: b0.001–0.002) and lower in September thanother months (t318 range:−5.23–−4.10, p b 0.001 for all comparisons),while August and October were characterized by similar (t318 = − .52,p = 0.60) and intermediate values for LNMass (Fig. 4).

For 2010, the interaction between LNTL and month was significant(F2, 214 = 9.88, p b 0.001) due to a higher slope in the relationshipbetween LNMass and LNTL during July. By excluding July, we were able



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to compare length-adjustedmeans of LNMass for August andSeptember,2010. For these two months, there were significant effects of LNTL(F1, 142 = 2134.92, p b 0.001) and month (F1, 142 = 12.55, p b 0.001)on natural log of mass. Adjusted to mean length (71.37 mm), LNMasswas lower during September thanduringAugust (t143= 3.54, pb 0.001).

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TL = 55.99 mmSlope = 3.41

2009

Fig. 4. Natural log of fish mass (LNMass), with standard error, for each month, estimated usthe relationship between LNMass and LNTL was estimated separately for each year. Points reptransformed value – total length inmm – is shown). For 2010, wewere unable to include fish cbetween LNTL and month (i.e., the slope of the LNMass–LNTL relationship was significantly hi


Diets

As expected,we observed an ontogenetic transition from larval yellowperch consuming small zooplankton prey to juvenile yellow perch con-suming larger prey. However, we did not observe a strong ontogenetic

1.1

1.3

1.5

187 222 266

Day of year

TL = 71.37 mmSlope = 3.32

2010

ing ANCOVA with the natural log of fish total length (LNTL) as a covariate. The slope ofresent mass-at-length for each month using the mean value of LNTL for each year (back-aught in July (Day 187) using ANCOVA to comparemonths, due to a significant interactiongher than for August and September). Note differences in y-axis values for each year.




diet shift from zooplankton to benthic prey after the larval stage, andage-0 yellow perch primarily consumed zooplankton during summerand fall of both years. Patterns of larval yellowperch dietswere fairly sim-ilar in 2009 and 2010. Yellow perch larvae consumed mostly cyclopoidand calanoid copepodites, and copepod nauplii. Calanoid copepodswere more important in the diets of larval yellow perch during 2009than during 2010, while copepod nauplii comprised a larger portion ofdiets during 2010 (Fig. 5).

Larger-bodied zooplankton, such asDaphnia and calanoid copepods,were important components of juvenile age-0 yellowperch diets duringall months. Chironomidae larvae were the most important benthicinvertebrate found in age-0 perch diets, but rarely comprised a substan-tial portion of perch diet biomass (Fig. 5).

While the type of prey items consumed by age-0 yellow perch didnot vary greatly across months, there was a significant decrease inmean mass-specific stomach content mass from July–August duringboth years and August–September in 2009 (Fig. 2a,b). Diet massappeared to decline during late summer and early fall in both yearsrelative to expected values based on fish lengths (Fig. 6). The naturallog of diet drymass (LNDM) increasedwith the natural log of total length(LNTL), but linear regressions using data from all months each yearsuggested that this occurred at a faster rate in 2009 (slope = 2.10,intercept =−12.93, r2 = 0.56) than in 2010 (slope = 1.19, intercept =9.26, r2 = 0.34). In 2009, LNDM tended to be lower than that predictedby the annual linear regression model on day 188 of the year (mean ofresidual values: −0.01) and day 244 (mean of residuals: −0.03), andhigher during day of year 216 (mean of residuals: 0.12) and day 278(mean of residuals: 0.03). For fish collected during 2010, the meanof residuals for the linear regression model was negative for day ofyear 266 (−0.08), following a positive mean of residuals for day ofyear 222 (0.06). The mean of residuals for day of year 187 in 2010was near zero.

Potential sources of size-dependent mortality

To evaluate changes in total body energy and potential overwintermortality, we quantified energy content of young yellow perch. Thetotal energy content of yellow perch scaled similarly with length during

Other ZooplanktonCopepod Nauplii

CalanoidaChironomidae Larvae

Pro

port

ion

of D

iet

Day of Year

2009105

Larvae87 81 81 62

Juveniles

0.0

0.5

1.0

133-168 188 216 244 278

n = n =

Fig. 5. Proportional biomass composition of age-0 yellow perch diets in Saginaw Bay during 20diets examined).


the summer and fall months in 2009 and 2010. Thus, given larger meansizes in 2010, age-0 yellow perch reached a higher mean total bodyenergy during 2010 (24, 933 J) than in 2009 (17, 610 J; t125 = −5.47,p b 0.01). Nonetheless, both annual cohorts lost a large amount of energyoverwinter; i.e., therewas a significant decrease in length-adjusted totalenergy between October 2009 and spring 2010 (mean length-adjusteddecrease, 16.3%; F1, 77= 34.73, p b 0.01) as well as between September2010 and spring 2011 (mean length-specific decrease, 19.3%; F1, 82 =52.26, p b 0.01; Fig. 7). The relationships between total energy contentand length of yellow perch were allometric (i.e., the slope of the logtotal energy–log length relationship was 3.41 for the 2009 cohort, 3.55for the 2010 cohort), suggesting smaller fish had disproportionatelylower energy content prior to winter. Moreover, there was a significantincrease inmean total length of age-0 yellow perch followingwinter forthe 2009 and 2010 cohorts (2009: t154=−2.12, p= 0.04; 2010: t421=−5.84, p b 0.01).

We assessed stomach contents of 159 YAO walleyes and 162 YAOyellow perch (N100 mm TL) for the presence of age-0 yellow perch inpredator diets. We could not fully quantify temporal patterns of preda-tion on juvenile perch due to low catches of walleyes in many of themonthly trawl sampling events, but smaller bodied yellow perchappeared to be more vulnerable to predation than larger perch of thesame cohort throughout much of the first year of life. While walleyesconsumed a wide size range of yellow perch, age-0 yellow perchfound in walleye diets tended to be smaller than yellow perch collectedfrom bottom trawls. These differences were significant during July(t288 = 8.049, p b 0.01), August (t287 = 5.1159, p b 0.01), and October(t116= 2.415, p= 0.017) of 2009, and July (t313= 3.857, p b 0.01) andSeptember (t156= 2.900, p= 0.004) of 2010 (Fig. 2c, d).We foundonlyone, heavily digested, unidentifiable percid in YAO yellow perch diets.

Discussion

Age-0 Saginaw Bay yellow perchwere abundant but relatively slow-growing after the collapse of the Lake Huron alewife population (Ivanet al., 2011). These small sizes of young yellow perch may contributeto increased mortality as smaller yellow perch are more susceptible topredation by walleye and may experience size-selective overwinter

Other

DaphniaCyclopoida

Day of Year

201056

Larvae76 77 62

Juveniles

125-146 187 222 266

09 (left) and 2010 (right). Numbers above each column indicate sample size (numbers of



3.4 3.8 4.2 4.6

Series1

Series2

Series3

-8

-6

-4

-23.4 3.8 4.2 4.6

Series1

Series2

Series3

Series4

Nat

ural

Log

Die

t Mas

s

Natural Log Total Length Natural Log Total Length

20102009

Day of Year

188

216

244

278

Day of Year

187

222

266

Fig. 6. The relationship between the natural log of diet dry mass and the natural log of total length. The solid line represents a linear regression using all data from each year, whileobservations from each monthly sampling event are plotted as separate symbols.


mortality. Although our study cannot unequivocally address the causesof slow growth, we documented that mass-at-length (an index ofcondition, which correlates with growth on intermediate time scales;e.g., Bentley and Schindler, 2013) decreased in late summer and earlyfall, i.e., before substantial declines in temperature. Unlike many othersystems, age-0 yellowperch in SaginawBay did not appear to undertakea strong ontogenetic diet transition from zooplankton to benthic prey,and this feeding pattern may partially contribute to reduced conditionand growth in the late summer and early fall.

We observed slowing rates of growth and energy accumulation dur-ing mid–late summer and early fall. First-year growth of age-0 yellowperch was slow relative to historical growth rates observed in SaginawBay (Fielder and Thomas, 2006; Ivan et al., 2011). Seasonal decreasesin growth due to reduced temperatures and declines in mass-specificmetabolic and consumption rates are expected as fish grow. Thus, wecannot directly compare growth and consumption rates across fish ofdifferent sizes, and our results should be viewed as quantitative docu-mentation of how and when growth patterns change as age-0 perchgrow through the first year of life. However, we document significantdeclines in growth and relative diet mass prior to cooling temperatures.Moreover, seasonal declines in mass-at-length suggest that seasonaldeclines in growth may not simply reflect allometric effects. Instead,reduced consumption, growth, and mass-at-length may have beenexacerbated by environmental conditions or foraging patterns duringlate summer and early fall. Similar patterns of first year growth havebeen observed in other populations of yellow perch, though the degreeof reduction in growth varies among years and across systems (FisherandWillis, 1997;Mills and Forney, 1981;Wu andCulver, 1992). Despite

8.8

9.4

10

10.6

11.2

4 4.2 4.4 4.6 4.

Natural Log Total Length (mm)

2009

Nat

ural

Log

Tot

al E

nerg

y (J

)

Fig. 7.Natural log ofmeasured total body energy of young yellowperch in SaginawBay plotted acircles indicate yellow perch caught in October of 2009 or September 2010; open circles indica


similar temporal patterns of growth reduction among years, juvenileyellow perch reached larger mean size by fall in 2010 than in 2009.Warmer conditions during 2010 may have contributed to earlier meanlarval emergence and increased growth rates. Consistent with ourresults, collections during MDNR annual October surveys also indicatedage-0 yellow perch reached a substantially larger pre-winter size in2010 than in 2009 (M. Thomas, MDNR, personal communication).

Slow age-0 yellow perch growth relative to historical rates might beexpected in Saginaw Bay due to compensatory density-dependenteffects following increased larval survival and high juvenile densities.However, recent (post-2003) fall mean lengths were among the lowestrecorded for age-0 yellow perch in Saginaw Bay (Fielder and Thomas,2006; Ivan et al., 2011). Previously, cohorts of age-0 yellow perchreaching larger mean fall sizes regularly coincided with high densitiesof age-0 perch in Saginaw Bay. Thus, recent conditions in Saginaw Baymay not present a favorable environment for growth relative to histor-ical conditions, and reduced growth of juvenile perchmay be related tooverall prey availability and not simply reflect compensatory processes.Dietmass appeared to decline during late summer and early fall relativeto trends in the relationship between dietmass andfish length.Weusedthe natural log of diet dry mass as an indirect index of the rate of con-sumption. Water temperatures and prey composition were generallyfairly consistent during July–September, but it is important to pointout that diet mass may be influenced by these and several other factorsdriving both consumption and gut evacuation rates (e.g., Schaeffer et al.,1999). Nonetheless, the trends we observed were consistent with a latesummer or early fall decline in availability of prey resources suggestedby trends in weight at length.

8 4 4.2 4.4 4.6 4.8

Natural Log Total Length (mm)

2010

gainst natural log of total length for 2009 (left panel) and 2010 (right panel) cohorts. Filledte yellow perch caught during April and May 2010 or 2011.




While linking diet composition directly to growth is difficult, it isimportant to point out that, due to varying energy densities (J/g) acrossprey types, the composition of diets can influence growth beyond simplythemass of prey consumed (e.g. Keast andEadie, 1985).Whenmodelingenergetics of Saginaw Bay yellow perch, Schaeffer et al. (1999) usedvalues of 3138 J/g and 2510 J/g for Chironomidae larvae and generalzooplankton, respectively. Thus, based on energy densities, equivalentconsumption of Chironomidae larvae should lead to faster growth thanconsumption of zooplankton. Diet items consumed by Saginaw Bayyellow perch larvae were similar to items consumed in other locations(Dettmers et al., 2003; Post and McQueen, 1988), and were similar tothose prey items preferred in laboratory studies (Fulford et al., 2006;Graeb et al., 2004). However, we found no evidence that juvenile yellowperch exhibit a distinct diet shift from zooplankton to benthic taxaduring the first year of life in Saginaw Bay, unlike other Great Lakes eco-systems such as Lake Erie (Wu and Culver, 1992) and Lake Michigan(Pothoven et al., 2000). Our results also differ from findings by Parkeret al. (2009) demonstrating high importance of macroinvertebrates inyoung perch diets in nearshore Saginaw Bay wetlands (rather than theopen waters we sampled). Fielder and Thomas (2006) reported thatzooplanktivory was becoming less common in yellow perch in recentyears, but their data were dominated by yearling and older fish.

In particular, we documented high consumption of Daphnia by age-0yellow perch in Saginaw Bay. Similarly, Roswell et al. (2013) reportedthatwhile age-0 yellowperchdiets vary spatially in SaginawBay,Daphniawere positively selected as prey items at these open water locations onmost sampling occasions. Although patterns of age-0 perch diet compo-sition may vary substantially among systems, Daphnia are commonlypreferred prey items (Mills et al., 1984; Roseman et al., 1995; Wu andCulver, 1994). Prout et al. (1990) found that young yellow perch inOneida Lake consumed primarily Daphnia (53-100%; median N80%)in 1980, when Daphnia comprised N10% of total environmental zoo-plankton abundance for much of the summer and fall, but consumedprimarily benthic prey items in 1987, when Daphnia were generallyabsent.

In contrast to other systems were Daphnia may become essentiallyabsent in late summer and fall (e.g., Lake Erie, Wu and Culver, 1994;Oneida Lake, Mills and Forney, 1983), Daphnia were never completelyabsent in Saginaw Bay during 2009 and 2010. Moreover, Pothovenet al. (2013) reportDaphnia galeata abundance appears to have increasedin Saginaw Bay following recent declines in alewife abundance.

In contrast to expectations for juvenile perch consumingmost otherzooplankters, evidence from other systems suggests that consumptionof Daphnia should promote fast growth (Mills and Forney, 1981; Millset al., 1989; Post andMcQueen, 1994). However, we observed decreasesin mass-at-length in late summer and fall despite high consumptionof Daphnia. Again, young yellow perch may switch to benthic prey,especially Chironomidae larvae, during late summer, especially whenDaphnia are absent (Roseman et al., 1995; Wu and Culver, 1992). Thecontinued consumption of Daphnia may have contributed to the lackof a strong ontogenetic foraging transition, as benthic prey remainedrelatively unimportant in age-0 yellow perch diets in Saginaw Bay. Itis plausible, albeit not definitive, that such a diet transition wouldhave facilitated faster growth.

Benthic invertebrate densities were more stable through time thanzooplankton. While Chironomidae larvae were more abundant in2010 than in 2009, the importance of Chironomidae larvae in diets ofyoung yellow perch remained low across both years. However, it isnoteworthy that recent benthic invertebrate communities in SaginawBay differ from historical conditions (Nalepa et al., 1996; Schaefferet al., 2000). Hexagenia mayflies were very rare in our sampling, andthere is evidence that their absence may contribute to the slow growthrates by yellow perch in Saginaw Bay (Schaeffer et al., 2000). Further-more, Dreissena sp. mussels invaded Saginaw Bay in the early 1990sand may make benthic prey more difficult to capture for yellow perch(Mayer et al., 2001).


Size-dependent mortality

The slow growth of juveniles appears to increase mortality riskthrough predation, and (potentially to a lesser extent) loss of energycontent (i.e., starvation) during winter may have led to greater over-winter mortality for smaller yellow perch. Consecutive years of highrecruitment by walleye led to increased predation pressure in SaginawBay (Fielder and Thomas, 2006), and age-0 yellow perch appear tobe selected more frequently than some other potential prey fish(e.g., trout-perch; Blouzdis et al., 2013). We found mean sizes of yellowperch in walleye diets to often be significantly smaller than the meansize of age-0 yellow perch available to walleyes. Selectivity by walleyesfor smaller-bodied yellowperch prey appears to be a common phenom-enon (Campbell, 1998). In addition to the limitations of gape-size,piscivores may be more likely to consume small-bodied prey due toincreased capture success (e.g., Lundvall et al., 1999) and reducedhandling time (e.g., Nilsson and Brönmark, 2000).

Slow growth of yellow perch may also exacerbate overwintermortality. Survival over winter is positively size-selective among otheryellow perch populations, due to processes of starvation (Post andEvans, 1989b) andpredation (Fitzgerald et al., 2006). The increased like-lihood of overwinter mortality for small-bodied perch may be closelylinked to energy reserves, which increase with fish size (Huss et al.,2008) and mass-specific metabolic rate, which decreases with fishsize. High energy reserves may not only minimize the risk of starvationover winter, but may alsominimize risky foraging that increases preda-tion risk duringwinter (Garvey et al., 2004). Mean length-adjusted totalenergy content of young yellow perch captured after their first winter inSaginawBaywas significantly lower than during fall.Wedid not directlymeasure energy reserves (i.e., the amount of energy fish could usewith-out starvation), but disproportionately lower energy content in smallfish, coupled with higher mass-specific metabolic rates in small fish,suggest that smaller fish would be more susceptible to overwinter star-vation. In addition, mean sizes of yellow perch caught in spring weresignificantly larger than those in pre-winter trawls. Althoughwe cannotrule out growth as contributing to increases in mean size from fall tospring, our observations are consistent with the hypothesis of size-selective overwinter mortality.

To conclude, unlike other populations of yellow perch in theLaurentian Great Lakes, yellow perch in Saginaw Bay did not switch tobenthic prey during the first year of life, but instead consumed primarilyzooplankton. Due to size-selective processes of predation and overwin-ter survival, juvenile growth and resulting mean size have importantimplications for survival of Saginaw Bay age-0 yellow perch. Our resultssuggest that recruitment dynamics are influenced by the interplay ofsize-selective mortality and potential diet-induced reductions ingrowth.

Acknowledgments

We thank the following individuals for assistance with field collec-tions and laboratory analyses: J. Cavaletto, B. Coggins, C. Foley, S. Lyttle,J. Militello, A. Roswell, and A. Spikes, J. Workman, andmany undergradu-ate laboratory assistants. Comments from two anonymous reviewershelped improve this manuscript. This study was funded by the NationalOceanic and Atmospheric Administration's (NOAA) Center for SponsoredCoastal Ocean Research. This is NOAA-GLERL contribution 1697.

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Patterns of age-0 yellow perch growth, diets, and mortality in Saginaw Bay, Lake Huron