Condition and diet of yellow perch in Saginaw Bay, Lake Huron (1970–2011)

JGLR-00701; No. of pages: 9; 4C: Journal of Great Lakes Research xxx (2014) xxx–xxx

Contents lists available at ScienceDirect

Journal of Great Lakes Research journal homepage: www.elsevier.com/locate/jglr

Condition and diet of yellow perch in Saginaw Bay, Lake Huron (1970–2011) Jay M. Staton a,⁎, Charles R. Roswell a,1, David G. Fielder b, Michael V. Thomas c, Steven A. Pothoven d, Tomas O. Höök a a

Purdue University, Department of Forestry and Natural Resources, 195 Marsteller Street, West Lafayette, IN 47907, USA Michigan Department of Natural Resources, Alpena Fisheries Research Station, 160 E. Fletcher, Alpena, MI 49707, USA Michigan Department of Natural Resources, Lake St. Clair Fisheries Research Station, 33135 South River Road, Harrison Township, MI 48045, USA d NOAA/GLERL Lake Michigan Field Station, 1431 Beach Street, Muskegon, MI 49441, USA b c

a r t i c l e

i n f o

Article history: Received 14 March 2013 Accepted 15 February 2014 Available online xxxx Communicated by Ed Rutherford Index words: Yellow perch Relative weight Foodweb

a b s t r a c t In Saginaw Bay, Lake Huron, yellow perch (Perca flavescens) constitute an ecologically important component of the ecosystem and support both recreational and commercial fisheries. Over the past 40 years, Saginaw Bay has experienced multiple ecosystem-level changes (e.g., non-indigenous species introductions, reduced nutrient loading and variable temperatures). In turn, abundances and growth rates of yellow perch and their predators and prey have fluctuated. Recent changes to Saginaw Bay and Lake Huron foodwebs have potential to influence prey composition and subsequently, growth and condition for yellow perch; but a complete description of yellow perch diet composition across seasons has not been undertaken in recent years. We calculated mean relative weight (Wr), an index of condition, of age-1 and older yellow perch in Saginaw Bay annually for 1970–2011. We found high interannual variation in condition and documented low mean Wr during 1978–1991. We developed regression models to explain this variation using phosphorus load, temperature, forage fish density, and yellow perch density as potential explanatory factors. Patterns of Wr were associated with changes in yellow perch densities, although interannual variation was not significantly associated with any of the available explanatory variables. Diet analysis of yellow perch collected in 2009 and 2010 demonstrated that age-1 and older yellow perch consumed a fundamentally different diet from a previous study (1986–1988), exhibiting a greater reliance on non-indigenous prey (e.g. Bythotrephes longimanus). © 2014 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved.

Introduction Fish populations are often characterized both by their overall abundance and the distribution of traits of individuals constituting the population. Size, age, sex distributions, condition, and growth rates of individuals can have strong influence on a population's cumulative reproductive capacity, resistance to disease, and resilience to exploitation while also strongly mediating interspecific ecological interactions (i.e., predator–prey and competitive interactions). Individual condition (length-adjusted mass) is strongly related to individual energy acquisition and growth rates (e.g., Jacobs et al., 2012). Condition is indicative of individual lipid content (Shul'man, 1974) and is related to foraging success (e.g., Garvey et al., 2004), maturation schedules (Justus and Fox, 1994), fecundity (Blanchard et al., 2003; Ferreri and Taylor, 1996; Henderson et al., 2000), ⁎ Corresponding author. Tel.: +1 317 523 2776. E-mail addresses: [email protected] (J.M. Staton), [email protected] (C.R. Roswell), fi[email protected] (D.G. Fielder), [email protected] (M.V. Thomas), [email protected] (S.A. Pothoven), [email protected] (T.O. Höök). 1 Current address: Illinois Natural History Survey, Lake Michigan Biological Station, 400 17th Street, Zion, IL 60099, USA.

offspring quality (Collingsworth and Marschall, 2011) and mortality risk (Lambert and Dutil, 1997; Post and Evans, 1989). A population with greater mean condition has a higher probability of producing strong year classes at low spawning stock biomass and may have the capacity to sustain a higher exploitation rate (Rätz and Lloret, 2003). Moreover, fish with relatively low condition factor may be at greater risk of starvation and experience higher over winter mortality (Eckmann, 2004; Garvey et al., 2004). Compared to length-atage, individual condition is not biased by systematic errors in age estimation and is fairly responsive to both short- and long-term variation in growth conditions (e.g., Jacobs et al., 2012) including changes in prey availability and type of prey consumed (e.g., Hondorp et al., 2005). Thereby, mean condition can serve both as a useful descriptor of population status and an indicator of environmental conditions. In the Great Lakes, yellow perch (Perca flavescens) support valuable commercial and recreational fisheries, and play important ecological roles as prey for piscivores and predators of forage fishes and invertebrates. Abundances and mean individual traits of several Great Lakes yellow perch stocks have fluctuated over time (Diana and Salz, 1990; Marsden and Robillard, 2004; Tyson and Knight, 2001). Due to important ecological interactions of yellow perch, such temporal variation likely is reflective of broader environmental variation

http://dx.doi.org/10.1016/j.jglr.2014.02.021 0380-1330/© 2014 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved.

Please cite this article as: Staton, J.M., et al., Condition and diet of yellow perch in Saginaw Bay, Lake Huron (1970–2011), J Great Lakes Res (2014), http://dx.doi.org/10.1016/j.jglr.2014.02.021

2

J.M. Staton et al. / Journal of Great Lakes Research xxx (2014) xxx–xxx

Phosphorus Loading (Tonnes)

Temperature CPUE Age 1+ (Degree Days) (Fish/10min Trawl)

affecting individual ecosystems as well as cascades to affect other foodweb components through predator–prey and competitive interactions. Such temporal variation potentially complicates multispecies management of fisheries if not understood. Since 1970, Saginaw Bay, Lake Huron has experienced a series of alterations to potential external and internal system drivers (Fig. 1) which may have influenced yellow perch condition. The implementation of the Great Lakes Water Quality Agreement and the Clean Water Act in the early 1970s contributed to significant reductions in nutrient loading (Bierman et al., 1984; Cha et al., 2011; Dobiesz et al., 2005) and likely led to decreased primary production in the bay (Dobiesz et al., 2005; Nalepa et al., 2002). Over this period, discharges of industrial contaminants into Saginaw Bay and its tributaries declined although high concentrations of several contaminants still persist in many regions of the system (Dobiesz et al., 2005). Lower primary production and reduced contaminant loads could translate into reduced prey availability for yellow perch (via bottom up effects), but they could also favor yellow

100 80 60 40 20 0

a

b 800 600 400 2000

c

1500 1000 500

Forage Fish Index

0

d

4000 3000 2000 1000

1970

1980

1990

2000

Walleye stocking ceased

Crash of alewife

Round gobies invaded Quagga mussels invaded

Zebra mussels invaded

White perch invaded Bythotrephes invaded

Walleye stocking began

Clean Water Act Established

Saginaw Bay Events

0

e

2010

Fig. 1. Temporal environmental patterns in Saginaw Bay, Lake Huron (1970–2011). a) Mean annual catch per unit effort (CPUE) of age-1+ yellow perch captured in annual trawling surveys conducted by the Michigan Department of Natural Resources (MDNR). CPUE trended negatively with year (Spearman's rho = −0.79). b) Mean annual growing degree days calculated using data obtained from the National Weather Service at the Bay City station. Cumulative degree days trended positively with year (Spearman's rho = + 0.17). c) Mean annual phosphorus loading from the Saginaw River (1970–2009; from Cha et al., 2010). Phosphorus loading trended negatively with year (Spearman's rho = −0.46). d) Mean annual soft-rayed forage fish index from MDNR annual trawling. Sum of mean catch-per-10 minute trawl of alewife, gizzard shad, rainbow smelt, round goby, spottail shiner, and trout perch (Fielder and Thomas, 2006). e) Major events and invasive species introductions into Saginaw Bay.

perch foraging through increased water clarity and expansion of certain eutrophic sensitive prey species. Since the 1980s, Saginaw Bay has experienced numerous invasions, including multiple invertebrates (e.g., Bythotrephes longimanus, hereafter, Bythotrephes, zebra mussels Dreissena polymorpha, quagga mussels Dreissena bugensis, and fishes, e.g., white perch Morone americana and round goby Neogobius melanostomus; Boileau, 1985; Fielder and Thomas, 2006; Nalepa et al., 1995; Pothoeven and Nalepa, 2006). The cumulative influence of these invaders on yellow perch condition may be quite complex. Some invasive species may now serve as important prey for yellow perch while others may directly compete with yellow perch (or the prey of yellow perch) for resources. Dreissena mussels may have altered physical conditions in Saginaw Bay, with Dreissena-induced increase in water clarity potentially aiding visual foraging success of yellow perch while Dreissena shells potentially impede benthic foraging (Mayer et al., 2000). Moreover, Dreissena shells and excretions may provide structure and nutrients favoring expansion of certain high energy benthic macroinvertebrates such as Gammarus (Amphipod) which yellow perch have been known to consume (Hayward and Margraf, 1987; Nalepa et al., 2003). Finally, similar to other regions in the Laurentian Great Lakes, Saginaw Bay has been characterized by a general warming trend over the past 40 years (Fielder and Thomas, 2006; Jensen et al., 2007). While warmer temperatures may lead to an extended growing season and thereby favor increased net growth and condition due to the non-linear influences of water temperatures on fish metabolism, exceedingly warm summer temperatures could lead to substantial energetic losses. In short, while a plethora of potential system drivers have varied substantially over the past 40 years in Saginaw Bay, their individual and cumulative impacts on yellow perch condition are not straightforward to anticipate. While various historical surveys have sporadically documented changes in potential system drivers in Saginaw Bay, in general there has been a lack of continuous monitoring of environmental variables. However, the long-term assessment of the Saginaw Bay fish community by the Michigan Department of Natural Resources (MDNR) is a notable exception, having been conducted annually from 1970 to the present. This monitoring program has documented a variety of changes to the Saginaw Bay fish community and individual populations, including populations of key forage fishes and two of the most exploited species, walleye (Sander vitreum) and yellow perch (Fielder and Thomas, 2006). Historically, yellow perch in Saginaw Bay have been characterized by high variation in abundance and individual growth rates. Yellow perch were particularly abundant during the 1970s and 1980s; but recruitment subsequently declined and densities of adults have remained relatively low since the 1990s (Fielder and Thomas, 2006; Ivan et al., 2011). While the 1980s were characterized by relatively slow growth, growth rates of adult yellow perch were relatively high during the 1970s and after 1990 (Fielder and Thomas, 2006). Schaeffer et al. (2000) examined diets of Saginaw Bay yellow perch during 1986– 1988, a period of slow growth, and found yellow perch (ages 1–4) obtained the majority of their energy from Chironomidae and fish prey. More recently, the collapse of the Lake Huron alewife (Alosa pseudoharengus) population in 2003 precipitated a set of ecosystem changes, including increases in production of age-0 yellow perch (Fielder and Thomas, 2006). However, age-1 and older (hereafter: age-1+) yellow perch abundance remained low, and potential changes in individual traits (e.g., condition) of adult yellow perch driven by changes in diets and various factors associated with these ecosystem changes have remained unexplored. The objectives of our study were to a) describe trends in condition of yellow perch in Saginaw Bay and b) explore factors that may contribute to these patterns. To this end, we used long term data sets to track condition of yellow perch and related patterns to environmental metrics in Saginaw Bay from 1970 to 2011 at multiple temporal scales. We also compared recent diets of age-1 + yellow perch to other published

Please cite this article as: Staton, J.M., et al., Condition and diet of yellow perch in Saginaw Bay, Lake Huron (1970–2011), J Great Lakes Res (2014), http://dx.doi.org/10.1016/j.jglr.2014.02.021

J.M. Staton et al. / Journal of Great Lakes Research xxx (2014) xxx–xxx

studies to explore the potential role of diet composition in contributing to changes in growth and condition. Methods Yellow perch condition (1970–2011) We tracked annual condition of yellow perch caught in bottom trawls (10 min tows at a speed of approximately 1 m/s) employed by MDNR during September–October (1970–2011). Trawling in inner Saginaw Bay has targeted 4 fixed index grids (North, South, West, and East) and multiple randomly-selected locations. For further details on trawling surveys, see (Fielder and Thomas, 2006). Yellow perch collected during trawling were measured (length to 1 mm; mass to 1 or 10 g) either on board or in the laboratory (after they were initially frozen in liquid nitrogen and stored at −20 °C). To track temporal trends in mean condition, we quantified relative weight (Wr) of individual yellow perch using a standard weight equation (developed for yellow perch greater than 99 mm; Willis et al., 1991): log10 Ws ¼ −5:386 þ 3:230 log10 L

ð1Þ

where Ws is the standard weight (g) of a yellow perch at a given length and L is total length (mm). We chose Wr to allow for straightforward comparisons among fish over a wide range of lengths, as other metrics (e.g., Fulton's K) do not allow such comparisons under allometric growth (Murphy et al., 1991). After calculating standard weight, we calculated Wr for an individual fish by dividing observed weight by standard weight. Total length of age-1 yellow perch collected in fall surveys conducted by the MDNR are generally ≥ 100 mm (Ivan et al., 2011) and individual measurements of mass of age-0 yellow perch were inconsistently collected; thus, we limited our analyses of Wr to fish at least 100 mm in total length. We evaluated trends in mean Wr for two separate size classes of age-1+ yellow perch; small, i.e., 100–150 mm, and large, i.e., N150 mm. For each size class, we calculated annual Wr by separately grouping yellow perch collected in trawls. Furthermore, we analyzed condition by grouping each data set into four time periods using major “events” in Saginaw Bay to define time periods (Fig. 1). We quantified Wr for each period by averaging the mean annual Wr for each year included in that period. We eliminated any year from our annual analysis that did not include at least 10 fish used to calculate the mean Wr to avoid bias due to low sample size. The first time period (1971–1977) encompasses the passing of the Clean Water Act and Great Lakes Water Quality Agreement (1972) and subsequent implementation to reduce nutrient loading. Due to walleye's potential impact on yellow perch recruitment and consequent growth rates (Hartman and Margraf, 1993; Rudstam et al., 1996), the next period (1978–1991) starts with the beginning of walleye stocking in Saginaw Bay and includes the introduction of the non-indigenous white perch (1982) and Bythotrephes (1984). The third time period (1992–1999) begins with the colonization of zebra mussels (Fielder and Thomas, 2006) as this was thought to have a large impact on water clarity (Budd et al., 2001; Fahnenstiel et al., 1995), submerged vegetation (Zhu et al., 2006), and benthic algae in Saginaw Bay (Lowe and Pillsbury, 1995; Pillsbury et al., 2002). The final time period (2000–2011) begins when round goby comprised a substantial composition of the catch in MDNR trawl surveys and also includes the crash of alewives in the bay (2003) along with the cessation of walleye stocking (2006). Again, to compare mean Wr across time periods, we included years with a minimum of 10 individual length and mass observations. Thus, while the second (1978–1991) and fourth (2000–2011) time periods cover more years than the other two periods, during each time period we used similar numbers of years to calculate the mean Wr of both small and large yellow perch (1971–77, N = 7; 1978–91, N = 8; 1992–99, N = 7; 2000–11, N = 8). We used one-

3

way ANOVAs to evaluate differences in mean Wr among time periods. We used mean annual Wr as elementary units for these comparisons and applied the inverse of standard error of each year's Wr estimate as a weighting factor to account for varying sample sizes and variance across years. We then applied Tukey's Post-hoc test to define which time periods were significantly different from others (α = 0.05; tests conducted using SPSS 19, SPSS Inc., IBM, Chicago, IL, USA). To evaluate potential drivers of differences in annual Wr of trawlcaught fish, we performed a multiple variable regression analysis to assess annual patterns of condition, 1970–2011 (SAS 9.3, SAS Institute, Inc., Cary, NC, USA). We obtained a set of potential explanatory variables (i.e., annual measures) including: phosphorus loading, relative abundance of age-1+ yellow perch, forage fish density, and cumulative degree days (Fig. 1). We used estimates of phosphorus loading from the Saginaw River, as it is the source of most the organic matter entering Saginaw Bay (Nalepa et al., 2002). Phosphorus estimates were quantified in tonnes per year, from Cha et al. (2010). We obtained catch per unit effort (CPUE, an index of relative abundance) of age-1 + yellow perch from MDNR trawl data and natural log-transformed these data to approximate a normal distribution. We used the soft-rayed forage fish index from Fielder and Thomas (2006) to evaluate possible contributions of forage fish density to changes in Wr. This index was calculated from the sum of the mean catch-per-10 minute trawl of the most common soft-rayed forage fishes in inner Saginaw Bay, including alewife, gizzard shad (Dorosoma cepedianum), rainbow smelt (Osmerus mordax), round goby, spottail shiner (Notropis hudsonius), and trout perch (Percopsis omiscomaycus). While direct measures of water temperature are available for Saginaw Bay for most of the study period (measured at Bay City water intake), we chose to use average air temperatures during the yellow perch growing season to represent water temperature. Water temperature measures at fixed locations can be influenced by annual differences in wind or internal physical processes of the lake that can change the ability of specific locations to index systemwide temperature. Additionally, a shift in the water intake location during the 1980s further complicated the use of fixed measures of water temperature. Considering a time period when the water intake location was stationary, annual indices of measured Saginaw Bay water temperatures are strongly correlated with annual indices of air temperatures measured near Bay City (mean summer temperatures correlation, r = 0.80; Ivan et al. in review). Thus, we obtained mean temperatures from the National Weather Service website at the Bay City, Michigan station from June 1 to August 31, 1973–2011. We chose this seasonal time period because most energy during this time is allocated to growth in yellow perch (Henderson et al., 2000). We developed a linear regression relating mean temperatures in Alpena, Michigan and Bay City from 1973 to 1979 to predict missing temperatures in Bay City from 1970 to 1972. We summed all temperatures above 13.5 °C (minimum temperature at which yellow perch and Eurasian perch Perca fluvitalis growth occurs, Le Cren, 1958; O'Gorman and Burnett, 2001; Power and Van Den Heuvel, 1999) for June 1–August 31 to obtain the cumulative degree days (CDD) for that year. Using these explanatory variables (phosphorus loading, soft-rayed forage fish index, CPUE, and CDD), we developed a model to explain variation in Wr of yellow perch caught in fall trawls using forward stepwise regression. The forward stepwise model selection algorithm started with only an intercept (initially the mean Wr), and sequentially added variables based on partial F-tests (criterion for entry: p b 0.15) and evaluated if there are variables that could be removed after each addition (criterion for removal: p N 0.15). Yellow perch diet patterns (2009–2010) To consider diet changes as potential drivers of temporal patterns in yellow perch growth and condition, we evaluated diets of age-1+ yellow perch collected during 2009 and 2010. For more details on these collections and diet analyses, see Blouzdis et al. (2013) and Roswell et al. (2013) who analyzed diets of other fishes collected

Please cite this article as: Staton, J.M., et al., Condition and diet of yellow perch in Saginaw Bay, Lake Huron (1970–2011), J Great Lakes Res (2014), http://dx.doi.org/10.1016/j.jglr.2014.02.021

4

J.M. Staton et al. / Journal of Great Lakes Research xxx (2014) xxx–xxx

Small Fish (100-150mm) Relative Weight

1.2 1.05 0.9 0.75 0.6

Large Fish (>150 mm) RelativeWeight

1.2

Yellow perch condition (1970–2011)

0.75

1980

1990

2000

2010

Fig. 3. Mean annual (1970–2011) relative weight (Wr) of small (100–150 mm) and large (N150 mm) yellow perch captured in Saginaw Bay, Lake Huron with trawls by the Michigan Department of Natural Resources. Years with b10 yellow perch were excluded from analysis.

of small (100–150 mm) yellow perch (i.e., F-statistics were not significant at the α = 0.05 level for linear relationships with any potential explanatory variable). Model selection indicated annual mean Wr of large (N150 mm) yellow perch caught in trawls was significantly, negatively associated with relative abundance (natural log of CPUE; slope = −0.020, F1, 28 = 8.64, p = 0.007, R2 = 0.24). No other variables were selected for entry into the large yellow perch regression model.

1.2

Small Fish (100-150 mm) Mean Relative Weight

Results

0.9

0.6 1970

Fig. 2. Location of Saginaw Bay, Lake Huron and sites where yellow perch were collected for diet analysis (2009 and 2010).

contemporaneously. In brief, we collected fish monthly from April to November using a 7.6 m semi-balloon bottom trawl with a 13 mm stretch mesh cod-end (towed for 10 min at 1.29 m·s−1 at four stations; Fig. 2). On board, we sorted by species into separate bags on ice; and, once on shore, we stored fish at − 20 °C for subsequent analyses. In the laboratory, we selected up to 10 age-1+ fish from each size group (≤150 mm and N150 mm) from each site and month. Age-1+ yellow perch were clearly distinguished from age-0 yellow perch using month-specific length–frequency data (C. Roswell, unpublished data). We measured length (to mm) and wet mass (to 0.01 g) and removed stomach contents from individual yellow perch. We identified (to the lowest possible taxonomic level), enumerated, and measured stomach contents under a dissecting microscope outfitted with a digital camera (Micrometrics) and image analysis software (Image J). We used measurements of individual diet items to estimate diet composition by biomass using published length–mass relationships (Benke et al., 1999; Dumont et al., 1975; Makarewicz and Jones, 1990). We dried diets and whole fish (without stomach contents) at 70 °C for 2–4 days, and quantified dry mass of diets and fish.

1.05

1.1

a

1

a,b b

b

0.9

Large Fish (>150 mm) Mean Relative Weight

0.8 We observed high inter-annual variation of mean annual Wr for small (100–150 mm) and large (N 150 mm) yellow perch caught in MDNR trawls (Fig. 3). Mean condition of trawl-caught yellow perch varied significantly across time periods for both small (100– 150 mm; F3, 26 = 5.998, p = 0.003) and large (N150 mm; F3, 26 = 11.721, p b 0.0005) fish (Fig. 4). Specifically, mean Wr of small yellow perch during years 1971–1977 was significantly greater than those from 1978 to 1991 (Tukey's post-hoc test, p = 0.002) and 2000 to 2011 (p = 0.023); and mean Wr of large yellow perch was significantly lower from 1978 to 1991 than the time period preceding it (1971–1977, p = 0.006) and the two following time periods (1992–1999, 2000–2011; p b 0.0005). Forward stepwise selection of multiple linear regression models suggested differential associations between environmental factors and Wr for small and large yellow perch (Table 1). None of our available explanatory variables were selected for entry into a model explaining Wr

1.2 1.1 1

a a

0.9

a

b

0.8 1971-1977

1978-1991

1992-1999

2000-2011

Fig. 4. Mean relative weight, Wr (grouped by ecological time periods), of small (100–150 mm; top panel) and large (N150 mm; bottom panel) yellow perch captured in Saginaw Bay, Lake Huron with trawls by the Michigan Department of Natural Resources. Error bars denote standard error and different letters over bars denote significant differences among time periods.

Please cite this article as: Staton, J.M., et al., Condition and diet of yellow perch in Saginaw Bay, Lake Huron (1970–2011), J Great Lakes Res (2014), http://dx.doi.org/10.1016/j.jglr.2014.02.021

J.M. Staton et al. / Journal of Great Lakes Research xxx (2014) xxx–xxx

5

Table 1 Best (determined by forward stepwise model selection) linear regression models to explain variation in Wr for two size classes of yellow perch collected in Saginaw Bay, 1970–2011. Note that for the 100–150 mm length class none of the available explanatory variables were selected; thus, the intercept represents the mean Wr for all years. Length class

n

Parameters

Value

p

R2

Adjusted R2

100–150 mm N150 mm

30 30

Intercept Intercept CPUE (ln transformed)

0.944 0.940 −0.020

– b0.001 0.007

0 0.236

0 0.208

Yellow perch diet patterns

Discussion

We examined diets of 287 age-1+ yellow perch from collections in 2009 and 2010. The most commonly occurring prey categories were Chironomidae, Bythotrephes, zooplankton, and other invertebrates (Table 2). Consumption of Chironomidae and zooplankton prey was more common for relatively small fish while piscivory was more common for larger fish. Hexagenia (mayfly nymphs), a large benthic insect which is sensitive to poor water quality and occurs at low densities in Saginaw Bay (Siersma et al., 2014), was found only in two fish (80– 99 mm total length) from site SB-10. Diets of small yellow perch exhibited substantial seasonal variation (Fig. 5). Chironomidae dominated diet biomass in spring (April–June) and declined in importance during summer (July–August) and fall (September–November) of both years. Moreover, diets of small yellow perch were more diverse in the summer and fall as Insecta, Bythotrephes, other zooplankton, and other fish comprised portions of diet biomass similar to or greater than Chironomidae. Contribution of Bythotrephes to diet biomass peaked during fall 2009 and during summer 2010. Fish, including round goby, emerald shiner, and walleye comprised nearly half of diet biomass during fall 2010, while fish were of limited importance during 2009. Due to low sample size, we grouped diets of large yellow perch across the two years (Fig. 5). Chironomidae constituted an important prey in spring diets of large yellow perch, but declined in importance in summer and fall. Similar to small yellow perch, contributions of Bythotrephes to diets of large yellow perch were high during summer and fall, and in summer Bythotrephes contributed 53% of large yellow perch diet biomass. As compared to small yellow perch, piscivory was more important for larger yellow perch diets both in terms of overall diet biomass (Fig. 5) and frequency of occurrence (Table 2). In total, across the three seasons, fish constituted 40% of large yellow perch diet biomass. The relative contribution of fish prey increased through the seasons and was greatest in the fall.

Over the past four decades, mean annual condition of age-1+ yellow perch has varied tremendously in Saginaw Bay, Lake Huron. Compensatory density-dependent processes and changes in the Saginaw Bay foodweb may have contributed to these changes in condition. We demonstrated a weak negative association between large yellow perch relative abundance and mean condition which is consistent with a density-dependent effect. Small yellow perch Wr was not wellexplained by any of our long-term data, suggesting other factors have influenced their condition. Direct evidence for foodweb changes leading to shifts in mean condition is lacking. However, the timing of changes in condition is generally consistent with arrival of invasive species and subsequent foodweb modifications. Moreover, our diet analyses revealed that age-1+ yellow perch relied on a different diet composition during 2009–2010 than during 1986–1988 (a period of relatively low condition; Schaeffer et al., 2000). Condition, indexed by Wr, may serve as a useful indicator of the response of individual fish to recent environmental influences. Whereas size (especially length) at age is reflective of energy acquisition during the entirety of a fish's lifetime, condition may be responsive to both long and short term changes in environmental conditions (Jacobs et al., 2012; Wuenschel et al., 2006). We observed both periodical and annual differences in condition, and given that energy content of young yellow perch varies seasonally (see Pothoven et al., 2014-in this issue; Roswell et al., 2014-in this issue), we expect that yellow perch mean condition in Saginaw Bay also varies intra-annually. Moreover, long-term differences in yellow perch condition are consistent with past analyses. Specifically, for both small (100–150 mm) and large (N150 mm) yellow perch, we observed low condition during the second time period (1978–1991). Similarly, Fielder and Thomas (2006) reported poor yellow perch condition during the 1980s, and Ivan et al. (2011) documented very low length-at-age of age-0–2 yellow perch during the 1978–1991 time period.

Table 2 Percent frequency of occurrence of diet categories arranged by length bins of yellow perch collected in Saginaw Bay during 2009–2010. The category “Other zooplankton” includes Bosminidae, Diaphanosoma, Harpacticoida, and Leptadoridae, “Other invertebrates” includes Isopoda, Molusca, Mysidae, and Ostrocoda, and the category, “Other fish” includes emerald shiner, walleye, and unidentified fish. Length bin (mm) 60–79

80–99

100–119

120–139

140–159

160–179

180–199

200–219

220–249

250+

Number of diets

24

62

62

48

25

23

13

13

8

9

Daphnia spp. Calanoid Chydorid Cyclopoid Bythotrephes Other zooplankton Chironomidae Amphipod Tricoptera Ephemeroptera Hexagenia spp. Other insecta Other invertebrates Round goby Other fish

25 21 50 50 17 38 88 13 0 0 0 4 21 0 0

35 3 23 29 32 21 85 10 3 13 3 0 18 0 0

31 5 8 10 61 10 73 29 2 11 0 0 13 0 3

25 13 15 6 71 15 69 46 8 2 0 0 31 2 4

24 0 12 4 40 12 64 28 4 0 0 0 32 12 8

9 0 13 9 22 0 74 39 13 0 0 13 39 4 17

23 0 0 0 54 0 46 31 0 0 0 0 23 15 0

46 0 8 0 77 0 23 8 0 0 0 8 8 15 23

38 0 0 0 100 0 38 13 0 13 0 0 13 0 25

11 0 0 0 44 0 11 0 0 0 0 0 0 22 56

Please cite this article as: Staton, J.M., et al., Condition and diet of yellow perch in Saginaw Bay, Lake Huron (1970–2011), J Great Lakes Res (2014), http://dx.doi.org/10.1016/j.jglr.2014.02.021

6

J.M. Staton et al. / Journal of Great Lakes Research xxx (2014) xxx–xxx

2009 (small, ≤ 150) % contribution of prey types to total dry weight

100%

43

74

1980s (small, ≤ 150)

2010 (small, ≤ 150) 20

a

b

32

34

3108

18

4600

3363

c

75% 50% 25% 0% Spring

Summer

Fall

Round Goby Bythotrephes Zooplankton Insecta Chironomidae

% contribution of prey types to total dry weight

100% Other Fish

1980s (large, > 150 mm)

2009-2010 (large, > 150 mm)

Other Invertebrates

38

38

9

d

877

617

505

Sping

Summer

Fall

e

75% 50% 25% 0% Spring

Summer

Fall

Fig. 5. Seasonal percent dry biomass of different prey categories in yellow perch diets during spring (April–June), summer (July–August), and fall (September–November). a) Diets of small (≤150 mm) yellow perch from 2009; b) diets of small (≤150 mm) yellow perch from 2010; c) diets of small (≤150 mm) yellow perch from 1986 to 1988, derived from Schaeffer et al. (2000); d) diets of large (N150 mm) yellow perch from 2009 to 2010 (years combined due to low sample size); e) diets of large (N150 mm) yellow perch from 1986–1988. “Other fish” includes emerald shiner, walleye, and unidentified fish, and “other invertebrates” includes Amphipoda, Isopoda, Mollusca, Mysidae, and Ostrocoda. Numbers of fish sampled indicated by number over each bar.

Compensatory density-dependent effects on condition of fish is a common phenomenon (e.g., Ellis et al., 2002; Pothoven et al., 2001; Sass et al., 2004) and has been documented in other populations of yellow perch in the Laurentian Great Lakes (e.g., Headley and Lauer, 2008). Therefore, negative associations between yellow perch abundance and condition of large fish are not surprising. Poor survival by young yellow perch in recent years (Ivan et al., 2011) may have released older yellow perch from compensatory density-dependent controls leading to relatively high mean condition for large, adult yellow perch during the 1990s and 2000s. However, decreases in Wr from 1978 to 1991 despite similar relative abundances of large yellow perch during the preceding time period (1971–1977), along with low explanatory power of our model for large yellow perch (R2 ~ 0.2), suggest processes in addition to density-dependence influenced condition of yellow perch in Saginaw Bay. Thayer et al. (2007) modeled yellow perch population patterns in Saginaw Bay and suggested that an unidentified phenomenon around 1990 had strong influence on the population, the timing of which roughly corresponds with colonization by zebra mussels in Saginaw Bay. Similarly, we found that mean condition of large yellow perch appeared to rebound after zebra mussels invaded Saginaw Bay. The presence of dreissenid mussels has been shown to reduce benthic foraging efficiency of yellow perch (Mayer et al., 2001). However, the proliferation of dreissenid mussels has been associated with changes in a variety of ecosystem characteristics, such as water clarity (Fahnenstiel et al., 1995) and invertebrate community composition (Nalepa et al., 2003), suggesting their establishment may affect yellow perch through multiple mechanisms. Field studies conducted in Oneida Lake, NY showed a positive effect of light penetration on frequency of occurrence of amphipods in yellow perch diets. Moreover, because yellow perch foraging shows a diel pattern, the majority of feeding takes place under low light conditions (Jansen and Mackay, 1992; Mayer et al., 2001). To that end, increased water clarity as a consequence of Dreissena proliferation can potentially have positive effects on yellow perch benthic foraging at times of low light such as dawn or dusk (Mayer et al., 2001).

Interestingly, after the introduction of zebra mussels in 1992, condition of small and large yellow perch has followed somewhat different trajectories in Saginaw Bay. While condition of large yellow perch rebounded after the second time period (1978–1991), mean Wr of small yellow perch was not significantly different among the two following time periods. Ivan et al. (2011) demonstrated that recent high abundances of age-0 yellow perch have not translated to subsequent high abundances of adult yellow perch. Through compensatory density-dependent effects, high abundances of age-0 yellow perch may compromise growth and subsequent size at age-1 (Ivan et al., 2011), either via lag effects (e.g., condition of a fish at age-1 is influenced by condition of that fish at age-0), or by competition with age-0 fish for prey resources. However, composition of age-1 + yellow perch diets differs substantially from diets of age-0 yellow perch (Roswell et al., 2013, 2014-in this issue) as age-0 consume more zooplankton than older age yellow perch. Moreover, none of our available explanatory variables, including CPUE, explained sufficient variation in Wr of small yellow perch (100–150 mm, approximating age-1) to be included in our best model, suggesting Wr of smaller, younger fish during the last 4 decades may have been more sensitive to some unidentified density-independent factors. Our regression models were limited by the scarcity of long-term datasets describing environmental variables in Saginaw Bay. Aside from fish sampling conducted by the MDNR, few environmental variables (e.g., primary production, invertebrate composition and abundance) have been consistently or directly measured on an annual basis in Saginaw Bay. Furthermore, our metrics of CDD and phosphorus loading are imperfect measures of climate and productivity changes, respectively. Yellow perch likely selected habitat with preferred temperatures, and condition may have been influenced on a timescale differing from our 3 month period used to calculate CDD. We used phosphorus loading estimates for the Saginaw River, the major tributary to Saginaw Bay; but these estimates do not directly indicate primary production in Saginaw Bay. Indeed, some evidence suggests some past production in Saginaw Bay was not simply limited by phosphorus (Bierman and

Please cite this article as: Staton, J.M., et al., Condition and diet of yellow perch in Saginaw Bay, Lake Huron (1970–2011), J Great Lakes Res (2014), http://dx.doi.org/10.1016/j.jglr.2014.02.021

J.M. Staton et al. / Journal of Great Lakes Research xxx (2014) xxx–xxx

Dolan, 1981). Moreover, bay-wide annual production may respond to cumulative nutrient loading over multiple years. From 1970 to 2011, major foodweb changes occurred in the Saginaw Bay ecosystem, and these may have contributed to temporal changes in yellow perch condition. The fish community transitioned from being characterized by eutrophic tolerant species during the 1970s, to a community containing a mix of eutrophic tolerant and sensitive species by the 1990s (Dobiesz et al., 2005; L. Ivan, CILER, personal communication, 2013). In addition, a number of invasive invertebrates (e.g., Bythotrephes and dreissenid mussels) and fish (e.g., white perch and round goby) became established in Saginaw Bay (Fig. 1). In addition, in 2003 and 2004 the Lake Huron alewife population collapsed, virtually eliminating this voracious planktivore from Saginaw Bay. Though we did not model the influence of interspecific competition on yellow perch condition, diets of nonindigenous species (including round gobies and white perch) likely overlap with yellow perch diets, potentially limiting prey availability for yellow perch (Barton et al., 2005; Johnson et al., 2005; Lederer et al., 2008; Parrish and Margraf, 1994; Truemper et al., 2006; C. Foley IN-IL Sea Grant, personal communication, 2013). The proliferation of dreissenid mussels and Bythotrephes and decline of alewife were accompanied by dramatic changes in Saginaw Bay's zooplankton assemblage from the 1990s to late 2000s (Pothoven et al., 2013). Moreover, as evidenced in other Great Lakes systems (Barton et al., 2005; Kuhns and Berg, 1999) establishments of dreissenid mussels and benthivorous gobies have likely affected assemblages of benthic invertebrates in Saginaw Bay. Nalepa et al. (2003) investigated the benthic macroinvertebrate community in Saginaw Bay pre- and post-Dreissena invasion and found no significant changes in Chironomidae biomass in the inner bay after Dreissenids were established. Gammarus (Amphipoda), a frequently occurring and high energy prey item in yellow perch diets, increased five-fold in density over the majority of the inner bay. With increased densities of Gammarus and unchanged Chironomidae biomass, combined with increased light penetration throughout Saginaw Bay, yellow perch likely experienced increased energetic benefits from foraging on benthos during the post-Dreissena invasion period. In addition to changes in benthic invertebrate abundances, densities of forage fish increased as Dreissena invaded and became established in Saginaw Bay (Fig. 1). However, this overall forage fish increase in the mid-1990s was followed by a subsequent decrease in the early-2000s, when the Lake Huron alewife population crashed. It is possible that increased densities of forage fish in the mid-1990s, coupled with enhanced foraging on benthic invertebrates contributed to increased yellow perch condition. On the other hand, the subsequent decrease in forage fish densities did not lead to a drop in yellow perch condition and the forage fish index did not have much explanatory power in our regression analyses to explain annual yellow perch condition. This lack of a consistent relationship between forage fish density and yellow perch condition suggest that the compensatory density-dependent relationship observed for large fish cannot be explained by simple resource competition for forage fish prey although it does not rule out interference competition or exploitative competition for other resources. Perhaps, the primary factors that influenced yellow perch condition in Saginaw Bay from 1970 to 2011 were non-stationary. While time series data for prey abundance and composition in Saginaw Bay are incomplete, we were able to compare current diets of yellow perch to historical diet patterns. Schaeffer et al. (2000) examined the diets of yellow perch throughout the growing season during 1986–1988. These years coincided with a time period when mean condition of yellow perch was relatively low. To facilitate these comparisons, we converted Schaeffer et al.'s (2000) measures of relative diet wet mass into relative dry mass using dry:wet ratios from Hanson et al. (1997). Chironomidae were important components of yellow perch diets during both 2009–2010 and 1986–1988. Moreover, during both time periods strong seasonal declines in Chironomidae importance (i.e., b 50% diet biomass) were observed. Such seasonal

7

reductions in Chironomidae consumption were especially evident for large (N150 mm) yellow perch that shifted seasonally to consume more fish prey (Fig. 5). Moreover, due in part to introductions of non-indigenous species, yellow perch appeared to consume a more diverse diet during 2009–2010, as zooplankton, Bythotrephes, round gobies, and other invertebrates were consistently important components of diet biomass. In fact, large components of 2009 and 2010 yellow perch diets were absent in 1980s diets: invasive round gobies and Bythotrephes were not established or abundant in Saginaw Bay during 1986–1988, and Amphipoda (a large part of the “other invertebrates” category) were not reported as diet components by Schaeffer et al. (2000). Additionally, Fielder and Thomas (2006) presented the frequency of occurrence of different prey items in yellow perch diets between 1986 and 2002. Although not directly comparable to diet biomass measures presented in this study, these data show that by 2002 round goby appeared in slightly over one-third of piscivorous yellow perch diets, further demonstrating the increased role of this invasive species in yellow perch diets. While we cannot directly link these changes in diet composition with changes in condition, the degree of change in diet composition suggests that changes in foodweb structure have had a large impact on yellow perch in Saginaw Bay. Currently-important prey taxa, such as Bythotrephes and round goby, may be particularly beneficial for net energetic gain (including search and capture costs) and the establishment of some invasive species in Saginaw Bay may have had a positive effect on yellow perch condition. Yellow perch may benefit from consuming abundant round gobies, and consumption of round gobies has been shown to increase condition of other Great Lakes fish populations (e.g., Johnson et al., 2005; Steinhart et al., 2004). Bythotrephes have become abundant and make up a large proportion of yellow perch diets in other areas of the Laurentian Great Lakes (e.g., Baker et al., 1992). Moreover, yellow perch (especially large, N150 mm) prey heavily on Bythotrephes in the summer when they begin to emerge (Straile and Hälbich, 2000) suggesting opportunistic feeding on this invasive zooplankter by age-1 + yellow perch. An energy-rich native insect, Hexagenia spp. constitutes important prey for yellow perch elsewhere in the Great Lakes, and was important for yellow perch growth in Saginaw Bay prior to the mid-1960s (Schaeffer et al., 2000). Hexagenia spp. abundance may be recovering in Saginaw Bay (Siersma et al., 2014), but remained rare in yellow perch diets we examined. Temporal variation in condition among Great Lakes fish populations appears to be widespread (e.g., Dobiesz et al., 2005; Madenjian et al., 2003). Foodweb changes have occurred throughout the Great Lakes (Dettmers et al., 2012), and may have influenced condition variation of other fish populations. However, as evidenced by our study, consistent environmental data necessary to relate such foodweb changes to long-term trends in fish population characteristics are often rare. Understanding factors leading to fluctuations in condition of Saginaw Bay yellow perch and other Great Lakes fish populations may require increased monitoring of both biotic and abiotic ecosystem trends.

Acknowledgements We thank Lori Ivan for her help organizing data into a workable format and Alicia Roswell for her help with diet analysis and data entry. We are grateful for all who helped in the field, especially, Beth Coggins, Jared Militello, Jack Workman, and the rest of the NOAA boat crews. The MDNR data stemmed from projects funded by Sport Fish Restoration funds (230466). The entire Höök lab should be acknowledged for their invaluable support throughout the sampling and lab work process. This research was sponsored by a grant from the National Oceanic and Atmospheric Administration Center for Sponsored Coastal Ocean Research. This is NOAA-GLERL contribution number 1701.

Please cite this article as: Staton, J.M., et al., Condition and diet of yellow perch in Saginaw Bay, Lake Huron (1970–2011), J Great Lakes Res (2014), http://dx.doi.org/10.1016/j.jglr.2014.02.021

8

J.M. Staton et al. / Journal of Great Lakes Research xxx (2014) xxx–xxx

References Baker, E.A., Tolentino, S.A., McComish, T.S., 1992. Evidence for yellow perch predation on Bythotrephes cederstroemi in southern Lake Michigan. J. Great Lakes Res. 18 (1), 190–193. Barton, D.R., Johnson, R.A., Campbell, L., Petruniak, J., Patterson, M., 2005. Effects of round gobies (Neogobius melanostomus) on dreissenid mussels and other invertebrates in eastern Lake Erie, 2002–2004. J. Great Lakes Res. 31, 252–261. Benke, A.C., Huryn, A.D., Smock, L.A., Wallace, J.B., 1999. Length–mass relationships for freshwater macroinvertebrates in North America with particular reference to the southeastern United States. J. N. Am. Benthol. Soc. 18 (3), 308–343. Bierman, V.J., Dolan, D.M., 1981. Modeling of phytoplankton-nutrient dynamics in Saginaw Bay, Lake Huron. Int. Assoc. Great Lakes Res. 7 (4), 409–439. Bierman, V.J., Dolan, D.M., Kasprzyk, R., 1984. Retrospective analysis of the response of Saginaw Bay, Lake Huron, to reductions in phosphorus loadings. Environ. Sci. Technol. 18, 23–31. Blanchard, J.L., Frank, K.T., Simon, J.E., 2003. Effects on condition on fecundity and total egg production of eastern Scotian Shelf haddock (Melanogrammus aeglefinus). Can. J. Fish. Aquat. Sci. 60 (3), 321–332. Blouzdis, C.E., Ivan, L.N., Pothoven, S.A., Roswell, C.R., Foley, C.J., Höök, T.O., 2013. A trophic bottleneck?: The ecological role of trout–perch Percopsis omiscomaycus in Saginaw Bay, Lake Huron. J. Appl. Ichtlyol. 29, 416–424. Boileau, M.G., 1985. The expansion of white perch, Morone Americana, in the lower Great Lakes. Fisheries 10 (1), 6–10. Budd, J.W., Drummer, T.D., Nalepa, T.F., Fahnenstiel, G.L., 2001. Remote sensing of biotic effects: zebra mussels (Dreissena polymorpha) influence on water clarity in Saginaw Bay, Lake Huron. Limnol. Oceanogr. 46 (2), 213–223. Cha, Y., Stow, C.A., Reckhow, K.H., DeMarchi, C., Johengen, T.H., 2010. Phosphorus load estimation in Saginaw River, MI using a Bayesian hierarchical/multilevel model. Water Res. 44, 3270–3282. Cha, Y., Stow, C.A., Nalepa, T.F., Reckhow, K.H., 2011. Do invasive mussels restrict offshore phosphorus transport in Lake Huron. Environ. Sci. Technol. 45 (17), 7226–7231. Collingsworth, P.D., Marschall, E.A., 2011. Spatial and temporal patterns in maternal energetic traits of yellow perch (Perca flavescesns) in Lake Erie. Freshw. Biol. 56, 2500–2513. Dettmers, J.M., Goddard, C.I., Smith, K.D., 2012. Management of alewife using Pacific salmon in the Great Lakes: whether to manage for economics or the ecosystem? Fisheries 37 (11), 495–501. Diana, J.S., Salz, R., 1990. Energy storage, growth, and maturation of yellow perch from different locations in Saginaw Bay, Michigan. Trans. Am. Fish. Soc. 119 (6), 976–984. Dobiesz, N.E., McLeish, D.A., Eshenroder, R.L., Bence, J.R., Mohr, L.C., Ebener, M.P., Nalepa, T.F., Woldt, A.P., Johnson, J.E., Argyle, R.L., Makarewicz, J.C., 2005. Ecology of the Lake Huron fish community, 1970–1999. Can. J. Fish. Aquat. Sci. 62, 1432–1451. Dumont, H.J., Van de Velde, I., Dumont, S., 1975. The dry weight estimate of biomass in a selection of Cladocera, Copepoda, and Rotifera from the plankton, periphyton and benthos of continental waters. Oecologia 19, 75–97. Eckmann, R., 2004. Overwinter changes in mass and lipid content of Perca fluviatilis and Gymnocephalus cernuus. J. Fish Biol. 65, 1498–1511. Ellis, T., North, B., Scott, A.P., Bromage, N.R., Porter, M., Gadd, D., 2002. The relationships between stocking density and welfare in farmed rainbow trout. J. Fish Biol. 61, 493–531. Fahnenstiel, G.L., Lang, G.A., Nalepa, T.F., Johengen, T.H., 1995. Effects of zebra mussel (Dreissena polymorpha) colonization on water quality parameters in Saginaw Bay, Lake Huron. Int. Assoc. Great Lakes Res. 21 (4), 435–448. Ferreri, C.P., Taylor, W.W., 1996. Compensation in individual growth rates and its influence on lake trout population dynamics in the Michigan waters of Lake Superior. J. Fish Biol. 49, 763–777. Fielder, D.G., Thomas, M.V., 2006. Fish population dynamics of Saginaw Bay, Lake Huron 1998–2004. Michigan Department of Natural Resources, Fisheries Research Report 2083, Ann Arbor (http://129.33.82.145/documents/dnr/2083rr_185820_7.pdf). Garvey, J.E., Ostrand, K.G., Wahl, D.H., 2004. Energetics, predation, and ration affect sizedependent growth and mortality of fish during winter. Ecology 85 (10), 2860–2871. Hanson, P.C., Johnson, T.B., Schindler, D.E., Kitchell, J.F., 1997. Fish Bioenergetics 3.0 for Windows Contents. University of Wisconsin-Madison Center for Limnology and University of Wisconsin Sea Grant Institute (http://aqua.wisc.edu/publications/ ProductDetails.aspx?productID=360). Hartman, K.J., Margraf, F.J., 1993. Evidence of predatory control of yellow perch (Perca flavescens) recruitment in Lake Erie, U.S.A. J. Fish Biol. 43, 109–119. Hayward, R.S., Margraf, F.J., 1987. Eutrophication effects on prey size and food available to yellow perch in Lake Erie. Trans. Am. Fish. Soc. 116, 210–223. Headley, H.E., Lauer, T.E., 2008. Density-dependent growth of yellow perch in southern Lake Michigan, 1984–2004. N. Am. J. Fish Manag. 28 (1), 57–69. Henderson, B.A., Trivedi, T., Collins, N., 2000. Annual cycle of energy allocation to growth and reproduction of yellow perch. J. Fish Biol. 57, 122–133. Hondorp, D.W., Pothoven, S.A., Brandt, S.B., 2005. Influence of Diporeia density on diet composition, relative abundance, and energy density of plantivorous fishes in southeast Lake Michigan. Trans. Am. Fish. Soc. 134, 588–601. Ivan, L.N., Höök, T.O., Thomas, M.V., Fielder, D.G., 2011. Long-term and interannual dynamics of walleye and yellow perch in Saginaw Bay, Lake Huron. Trans. Am. Fish. Soc. 140, 1078–1092. Jacobs, G.R., Breck, J.E., Höök, T.O., 2012. Growth-mediated seasonal energy allocation patterns of young-of-year largemouth bass (Micropterus salmoides). J. Freshw. Ecol. 27, 63–76. Jansen, W.A., Mackay, W.C., 1992. Foraging in yellow perch, Perca flavescens: biological and physical factors affecting diel periodicity in feeding, consumption, and movement. Environ. Biol. Fish 34, 287–303.

Jensen, O.P., Benson, B.J., Magnuson, J.J., Card, V.M., Futter, M.N., Soranno, P.A., Stewart, K. M., 2007. Spatial analysis of ice phenology trends across Laurentian Great Lakes region during recent warming period. Limnol. Oceanogr. 52 (5), 2013–2026. Johnson, T.B., Bunnell, D.B., Knight, C.T., 2005. A potential new energy pathway in central Lake Erie: the round goby connection. J. Great Lakes Res. 31 (Suppl. 2), 238–251. Justus, J.A., Fox, M.G., 1994. The cost of early maturation on growth, body condition and somatic lipid content in a lake pumphseed (Lepomis gibbosus) population. Ecol. Freshw. Fish 3, 9–17. Kuhns, L.A., Berg, M.B., 1999. Benthic invertebrate community response to round goby (Neogobius melanostomus) and zebra mussel (Dreissena polymorpha) invasion in southern Lake Michigan. J. Great Lakes Res. 25 (4), 910–917. Lambert, Y., Dutil, J.D., 1997. Condition and energy reserves of Atlantic cod (Gadus morhua) during the collapse of the northern Gulf of St. Lawrence stock. Can. J. Fish. Aquat. Sci. 54 (10), 2388–2400. Le Cren, E.D., 1958. Observations on the growth of perch (Perca fluviatilis L.) over twentytwo years with special reference to the effects of temperature and changes in population density. J. Anim. Ecol. 27 (2), 287–334. Lederer, A.M., Janssen, J., Reed, T., Wolf, A., 2008. Impacts of the introduced round goby (Apollonia melanostoma) on dreissenids (Dreissena polymorpha and Dreissena bugensis) and on macroinvertebrate community between 2003 and 2006 in the littoral zone of Green Bay, Lake Michigan. J. Great Lakes Res. 34, 690–697. Lowe, R.L., Pillsbury, R.W., 1995. Shifts in benthic algal community structure and function following the appearance of zebra mussels (Dreissena polymorpha) in Saginaw Bay, Lake Huron. J. Great Lakes Res. 21 (4), 558–566. Madenjian, C.P., Holuszko, J.D., Desorcie, T.J., 2003. Growth and condition of alewives in Lake Michigan, 1984–2001. Trans. Am. Fish. Soc. 132, 1104–1116. Makarewicz, J.C., Jones, H.D., 1990. Occurrence of Bythotrephes cederstroemi in Lake Ontario offshore waters. J. Great Lakes Res. 16 (1), 143–147. Marsden, J.E., Robillard, S.R., 2004. Decline of yellow perch in southwestern Lake Michigan, 1987–1997. N. Am. J. Fish Manag. 24 (3), 952–966. Mayer, C.M., VanDeValk, A.J., Forney, J.L., Rudstam, L.G., Mills, E.L., 2000. Response of yellow perch (Perca flavescens) in Oneida Lake, New York, to establishment of zebra mussels (Dreissena polymorpha). Can. J. Fish. Aquat. Sci. 57, 742–754. Mayer, C.M., Rudstam, L.G., Mills, E.L., Cardiff, S.G., Bloom, C.A., 2001. Zebra mussels (Dreissena polymorpha), habitat alteration, and yellow perch (Perca flavescens) foraging: system-wide effects and behavioural mechanisms. Can. J. Fish. Aquat. Sci. 58, 2459–2467. Murphy, B.R., Willis, D.W., Springer, T.A., 1991. The relative weight index in fisheries management: status and needs. Fisheries 16 (2), 30–38. Nalepa, T.F., Wojcik, J.A., Fanslow, D.L., Lang, G.A., 1995. Initial colonization of zebra mussels (Dreissena polymorpha) in Saginaw Bay, Lake Huron: population, recruitment, density, and size structure. J. Great Lakes Res. 21 (4), 417–434. Nalepa, T.F., Fanslow, D.L., Lansing, M.B., Lang, G.A., Ford, M., Gostenik, G., Hartson, D., 2002. Abundance, biomass, and species composition of benthic macroinvertebrate populations in Saginaw Bay, Lake Huron, 1987–96. NOAA Technical Memorandum GLERL-122. Nalepa, T.F., Fanslow, D.L., Lansing, M.B., Lang, G.A., 2003. Trends in benthic macroinvertebrate community of Saginaw Bay, Lake Huron, 1987 to 1996: responses to phosphorus abatement and the zebra mussel, Dreissena polymorpha. Int. Assoc. Great Lakes Res. 29 (1), 14–33. O'Gorman, R., Burnett, J.A.D., 2001. Fish community dynamics in northeastern Lake Ontario with emphasis on the growth and reproductive success of yellow perch (Perca flavescens) and white perch (Morone Americana), 1978 to 1997. J. Great Lakes Res. 27 (3), 367–383. Parrish, D.L., Margraf, J.F., 1994. Spatial and temporal patterns of food use by white perch and yellow perch in Lake Erie. J. Freshw. Ecol. 9 (1), 29–35. Pillsbury, R.W., Lowe, R.L., Pan, Y.D., Greenwood, J.L., 2002. Changes in benthic algal community and nutrient limitations in Saginaw Bay, Lake Huron, during the invasion of zebra mussels (Dreissena polymorpha). J. N. Am. Benthol. Soc. 21 (2), 238–252. Post, J.R., Evans, D.O., 1989. Size-dependent overwinter mortality of young-of-the-year yellow perch (Perca Flavescens): laboratory, in situ enclosure, and field experiments. Can. J. Fish. Aquat. Sci. 48 (4), 672–680. Pothoeven, S.A., Nalepa, T.F., 2006. Feeding ecology of lake whitefish in Lake Huron. J. Great Lakes Res. 32, 489–501. Pothoven, S.A., Nalepa, T.F., Schneeberger, P.J., Brandt, S.B., 2001. Changes in diet and body condition of lake whitefish in southern Lake Michigan associated with changes in benthos. N. Am. J. Fish Manag. 21 (4), 876–883. Pothoven, S.A., Höök, T.O., Nalepa, T.F., Thomas, M.V., Dyble, J., 2013. Changes in zooplankton community structure associated with the disappearance of invasive alewife in Saginaw Bay, Lake Huron. Aquat. Ecol. 47, 1–12. Pothoven, S.A., Höök, T.O., Roswell, C.R., 2014. Feeding ecology of age-0 lake whitefish in Saginaw Bay, Lake Huron. J. Great Lakes Res. http://dx.doi.org/10.1016/j.jglr.2013. 09.016 (in this issue). Power, M., Van Den Heuvel, M.R., 1999. Age-0 yellow perch growth and its relationship to temperature. Trans. Am. Fish. Soc. 128, 687–700. Rätz, H.J., Lloret, J., 2003. Variation in fish condition between Atlantic cod (Gadus morhua) stocks, the effect on their productivity and management implications. Fish. Res. 60, 369–380. Roswell, C.R., Pothoven, S.A., Höök, T.O., 2013. Spatio-temporal, ontogenetic and interindividual variation of age-0 diets in a population of yellow perch. Ecol. Freshw. Fish 22, 479–493. Roswell, C.R., Pothoven, S.A., Höök, T.O., 2014. Patterns of age-0 yellow perch growth, diets, and mortality in Saginaw Bay, Lake Huron. J. Great Lakes Res. http://dx.doi. org/10.1016/j.jglr.2014.01.008 (in this issue).

Please cite this article as: Staton, J.M., et al., Condition and diet of yellow perch in Saginaw Bay, Lake Huron (1970–2011), J Great Lakes Res (2014), http://dx.doi.org/10.1016/j.jglr.2014.02.021

J.M. Staton et al. / Journal of Great Lakes Research xxx (2014) xxx–xxx Rudstam, L.G., Green, D.M., Forney, J.L., Stang, D.L., Evans, J.T., 1996. Evidence of interactions between walleye and yellow perch in New York State lakes. Ann. Zool. Fenn. 33, 443–449. Sass, G.G., Hewett, S.W., Beard Jr., T.D., Fayram, A.H., 2004. The role of density dependence in growth patterns of ceded territory walleye populations of northern Wisconsin: effects of changing management regimes. N. Am. J. Fish Manag. 24, 1262–1278. Schaeffer, J.S., Diana, J.S., Haas, R.C., 2000. Effects of long-term changes in benthic community on yellow perch in Saginaw Bay, Lake Huron. J. Great Lakes Res. 26 (3), 340–351. Shul'man, G.E., 1974. Life Cycles of Fish. Wiley, New York. Siersma, H.M.H., Foley, C.J., Nowicki, C.J., Qian, S.S., Kashian, D.R., 2014. Status of and trends in the distribution and abundance of Hexagenia spp. in Saginaw Bay, Lake Huron, 1954–2012: moving towards recovery? Steinhart, G.B., Stein, R.A., Marschall, E.A., 2004. High growth rate of young-of-the-year smallmouth bass in Lake Erie: a result of the round goby invasion? Int. Assoc. Great Lakes Res. 30 (3), 381–389. Straile, D., Hälbich, A., 2000. Life history and multiple antipredator defenses of an invertebrate pelagic predator, Bythotrephes longimanus. Ecology 81 (1), 150–163.

9

Thayer, S.A., Taylor, W.W., Hayes, D.B., Haas, R.C., 2007. Weight of evidence for underlying dynamics of yellow perch in Saginaw Bay, Lake Huron. Ecol. Model. 206, 31–40. Truemper, H.A., Lauer, T.E., McComish, T.S., Edgell, R.A., 2006. Response of yellow perch diet to a changing forage base in southern Lake Michigan, 1984–2002. Int. Assoc. Great Lakes Res. 32, 806–816. Tyson, J.T., Knight, R.L., 2001. Response of yellow perch to changes in the benthic invertebrate community of western Lake Erie. Trans. Am. Fish. Soc. 130 (5), 766–782. Willis, D.W., Guy, C.S., Murphy, B.R., 1991. Development and evaluation of a standard weight (Ws) equation for yellow perch. N. Am. J. Fish Manag. 11, 374–380. Wuenschel, M.J., Jugovich, A.R., Hare, J.A., 2006. Estimating the energy density of fish: the importance of ontogeny. Trans. Am. Fish. Soc. 135, 379–385. Zhu, B., Fitzgerald, D.G., Mayer, C.M., Rudstam, L.G., Mills, E.L., 2006. Alteration of ecosystem function by zebra mussels in Oneida Lake: impacts on submerged macrophytes. Ecosystems 9, 1017–1028.

Please cite this article as: Staton, J.M., et al., Condition and diet of yellow perch in Saginaw Bay, Lake Huron (1970–2011), J Great Lakes Res (2014), http://dx.doi.org/10.1016/j.jglr.2014.02.021