NOAA Technical Memorandum GLERL-160

SAGINAW BAY Multiple Stressors Summary Report

Craig Stow1 and Tomas Hook2, Editors

Project Team: 

Dmitry Beletsky

Raisa Beletsky

Ashley Burtner

James H. Bredin

Joann Cavaletto

Yoonkyung Cha

Carlo De Marchi

Joseph V. DePinto

Julianne Dyble 

Dave Fanslow

Steve Francoeur

Duane Gossiaux

Nathan Hawley

Chansheng He

Thomas H. Johengen

Donna R. Kashian

UNITED STATES

DEPARTMENT OF COMMERCE

Penny Pritzker

Secretary

NATIONAL OCEANIC AND

ATMOSPHERIC ADMINISTRATION

Kathy Sullivan

Acting, Under Secretary for Oceans & Atmosphere

NOAA Administrator

NAT OI NAL OCEANIC AND ATMOSPHERIC ADMINISTRAT OI N

U.S.DEPARTMENT OF COMMERCE

Michael D. Kaplowitz

William Keiper

Peter J. Lavrentyev

Frank Lupi 

David F. Millie

Nancy Morehead

Thomas F. Nalepa

Tammy J. Newcomb

Danna Palladino

Scott D. Peacor

Steven A. Pothoven

Todd Redder

Michelle Selzer

Henry A. Vanderploeg 

Ed Verhamme

Kim Winslow

1

NOAA, Great Lakes Environmental Research Laboratory, Ann Arbor, MI 48108

2

Purdue University, W. Lafayette, IN 47907

September 2013
2

NOTICE

Mention of a commercial company or product does not constitute an endorsement by the NOAA. 

Use of information from this publication concerning proprietary products or the tests of such 

products for publicity or advertising purposes is not authorized. This is GLERL Contribution No. 

1684.

This publication is available as a PDF file and can be downloaded from GLERL’s web site: 

www.glerl.noaa.gov. Hard copies can be requested from GLERL Information Services, 

4840 S. State Rd., Ann Arbor, MI 48108.

pubs.glerl@noaa.gov.

NOAA’s Mission – To understand and predict changes in Earth’s environment and conserve and 

manage coastal and marine resources to meet our nation’s economic, social, and environmental 

needs 

NOAA’s Mission Goals:

•	 Protect, restore and manage the use of coastal and ocean resources through an ecosystem

approach to management

•	 Understand climate variability and change to enhance society’s ability to plan and respond

•	 Serve society’s needs for weather and water information

•	 Support the Nation’s commerce with information for safe, efficient, and environmentally

sound transportation

•	 Provide critical support for NOAA’s Mission
3

TABLE OF CONTENTS

1.0 INTRODUCTION ....................................................................................................................................... 7

1.1 Purpose of Report

2.0 MANAGEMENT ISSUE FINDINGS AND IMPLICATIONS.................................................................... 7

2.1 Water Quality/HABs/Beach Issues (Muck)

2.2 Project Findings

2.2.1 Phosphorus Inputs

2.2.2 Physical Processes

2.2.3 Water Quality/Harmful Algal Blooms (HABs)

2.2.4 Muck and Beach Fouling

2.2.5 Field Study – Beach Survey

2.2.6 Fecal Indicator Bacteria

2.2.7 Field Study - Saginaw Bay Survey

2.3 Knowledge/Data Gaps – Research Needs

2.4 Management Implications

2.5 Section 2 References

3.0 INVASIVE SPECIES AND FOODWEB DYNAMICS............................................................................. 29

3.1 Brief History of Saginaw Bay Invertebrate and Vertebrate Assemblages

3.2 Project Findings

3.2.1 Data sources

3.2.2 Key findings

3.3 Research Needs and Management Implications (these sections are separated in other chapters)

3.4 Section 3 References 

4.0 FISH AND FISHERY MANAGEMENT IN SAGINAW BAY.................................................................. 39

4.1 Brief History of Saginaw Bay Walleye and Perch Fishery

4.2 Project Findings

4.3 Knowledge/Data Gaps – Research Needs

4.4 Management Implications

4.5 Section 4 References

LIST OF FIGURES

Figure 2.1. Saginaw Bay station location map.

Figure 2.2. Estimates of the Saginaw River total phosphorus load. Blue dots represent the mean of the Bayesian predictive 

distribution, bars represent ± 2 standard deviations. Red dots and lines indicate estimates for 2010 and 2011 using 

Saginaw River flow data without total phosphorus concentration data. Horizontal orange line denotes 440 tonnes target 

established in the GLWQA.

Figure 2.3. Depiction of the Saginaw River long-term flow pattern produced with a technique known as “season trend 

decomposition using loess” (Cleveland 1993). The data are broken into three components: a smoothed long-term trend 

(top left), an oscillating seasonal pattern (top middle), and residual (top right). Smoothed long-term monthly patterns 

(bottom) indicate departures (blue line) from the long-term mean (horizontal black line).

Figure 2.4a. Location of thermistor strings in Saginaw Bay.

Figure 2.4b. Temperature profiles from each location. Temperatures in degrees C, horizontal axis in julian days.
4

Figure 2.5. (a) Surface and bottom temperatures recorded by RECON buoy deployed in 2011 near site 10, and (b) 

corresponding bottom oxygen concentrations.

Figure 2.6. Average Saginaw Bay circulation pattern in 1994.

Figure 2.7. Data from numerous extant sources depicting Saginaw Bay total phosphorus (top) and chlorophyll a 

concentrations vs time. Sample average (dots) ± 1 standard deviation (vertical bars).

Figure 2.8. Box and whisker plots depicting sample distributions of GLERL collected total phosphorus in various time 

periods and locations in Saginaw Bay. Boxes indicate middle 50% of observations, dots indicate sample averages, 

horizontal lines indicate sample medians, notches depict 95% confidence intervals about the medians, whiskers indicate 

extreme values, box width is proportional to sample size. Sample sizes and sample averages for each group are shown 

above plot. Horizontal dashed line indicates 15 ug/L concentration objective.

Figure 2.9. Box and whisker plots of GLERL collected data depicting sample distributions of chlorophyll a in various 

time periods and locations in Saginaw Bay. Boxes indicate middle 50% of observations, dots indicate sample averages, 

horizontal lines indicate sample medians, notches depict 95% confidence intervals about the medians, whiskers indicate 

extreme values, box width is proportional to sample size. Sample sizes and sample averages for each group are shown 

above plot. Horizontal dashed line indicates 3.6 ug/L concentration objective.

Figure 2.10. Box and whisker plot depicting sample distributions of GLERL collected secchi depth measurments in 

various time periods and locations in Saginaw Bay. Boxes indicate middle 50% of observations, dots indicate sample 

averages, horizontal lines indicate sample medians, notches depict 95% confidence intervals about the medians, whiskers 

indicate extreme values, box width is proportional to sample size. Sample sizes and sample averages for each group are 

shown above plot. Horizontal dashed line indicates 3.9 meter objective.

Figure 2.11. Chlorophyll a vs total phosphorus in surface water samples and corresponding simple linear regression lines. 

red = river plume, blue=non-plume, green=outer bay, circle = 1991-1996, dot = 2008-2010, dashed line = 1991-1996, 

solid line = 2008-2010.

Figure 2.12. Changes in phosphorus concentration in intact sediment cores from sites 5, 14 and 10 under differing oxygen 

levels.

Figure 2.13. 2010 data depicting phytoplankton species by density (top) and biovolume (bottom) in surface samples from 

sites 2, 5, 10, 14, and 20.

Figure 2.14. 2010 data depicting cynobacteria species in surface samples from sites 2, 5, 10, 14, and 20.

Figure 2.15. Microcystin concentrations from 2009-2010. Horizontal dashed line depicts World Health Organization 

drinking water standard. All samples were of raw water, not polished drinking water.

Figure 2.16. Average dreissenid mussel densities vs time. Inset shows mussel colonization on an instrumentation tripod 

that was deployed from April-September in 2009. Red ellipse highlights the 11-year monitoring gap.

Figure 2.17. Depiction of the location on Saginaw Bay that experiences frequent, severe shoreline fouling events, and the 

region of benthic algal growth identified by our bay-wide observations. Sampling sites were established in this zone of 

high deposition. Public Access Beach at the end of Cottage Grove Road (Linwood, MI) on 5/16/2010 (above) Bay City 

Recreation Area (Bay City, MI) on 5/16/2010 (below).

Figure 2.18. Comparison of beach detritus between a location north of the Bay City Recreation Area (Linwood, MI) 

versus the wash-up at the Bay City Recreation Area (Bay City, MI) on the same day. Detritus at northern sites were less 

decomposed and more identifiable than material at the BCRA sites.

Figure 2.19. Mean Log10 concentrations (± Standard Error) of E. coli, Enterococci, and C. perfringens concentrations in 

wet decaying algae (muck), dry algal (muck) deposits, nearshore water, and beach sand. The means represent six samples 

collected between June and August 2010 on a biweekly basis. 
5

Figure 2.20. Effect of 96 hrs sunlight exposure on the persistence (survival) of several fecal indicator organisms (FIBs; 

E. coli, Enterococci, and C. perfringens) within freshly deposited wet muck collected from Tobico Beach at the Bay City 

State Recreation Area. Upon moving a mat of muck to an area of direct sunlight and away from possible contamination 

from wave action, the muck was spread to a thickness of 15 cm, and 5g was collected daily from the start of the 

experiment August 27-31, 2010 and analyzed for FIB following methods by Whitman et al. 2003. 

Figure 2.21. Underwater photos of benthic green filamentous algal growth at transect 9 (near Pinconning, MI), 4.0 m 

depth on 6/14/2010.

Figure 2.22. Photo of algal growth near Rosebud Agricultural Drain, Linwood Michigan on 6/7/2010. 

Figure 2.23. Tissue phosphorus (mg P/g dwt) of benthic filamentous algae in the inner bay of Saginaw Bay, Lake Huron 

in 2009 compared to published values of phosphorus-limiting tissue concentrations (n = 21). 1.6 mg P/g dwt is the level 

below which phosphorus is limiting. Based on this threshold, 100% are P-limited. P-starvation 0.6 mg P/g dwt is the 

critical growth requirement. 26% of the samples are below this threshold, indicating P deficiency. The data is averaged 

across sample site. Error bars indicate standard error and are based on multiple measurements at a single sample site.

Figure 2.24. The difference between midday benthic light (μmol/m2-sec) and the light saturation index (EK, μmol/m2-

sec), also known as relative EK, or EKR. Data below 0 indicates subsaturating light conditions. The data is averaged 

across sample site. Error bars indicate standard error and are based on multiple measurements at a single sample site.

Figure 3.1. Timeline of notable changes to the Saginaw Bay foodweb.

Figure 3.2. Median richness in 10 trawls as determined by Monte Carlo simulations from the fall Saginaw Bay trawl 

survey (1970-2008) for (a) total (rho=+0.57, p<0.05) and signal (relatively rare; see Ludsin et al. 2001) species richness 

(p>0.05), and (b) tolerant (rho=-0.32, p<0.05), intolerant (rho=+0.32, p<0.05), and moderately tolerant (rho=+0.77, 

p<0.001) species richness.

Figure 3.3. Results of a preliminary non-metric multidimensional scaling analyses to visualize changes in the relative 

abundances of the Saginaw Bay fish assemblage, based on Michigan Department of Natural Resources trawling data from 

1970 to 2008.

Figure 3.4. Gut contents of round gobies, summarized by size, season collected, and year. Chironomid larvae (red) make 

up large proportions of the gut contents regardless of size, season, or year. Dreissenids (green) make up increasingly 

larger proportions of items consumed as fish length increases or the season progresses. Even the smallest gobies rely on 

dreissenids to some degree. Zooplankton (turquoise) are dominated by ostracods. Other benthos (purple) are dominated by 

mayfly larvae, chironomid pupae, and amphipods.

Figure 3.5. Mean length of dreissenids found in different-sized round gobies. Larger gobies consume larger dreissenids 

regardless of time of year, while few gobies tend to consume dreissenids that are larger than 10 mm. 

Figure 4.1 Spawning stock biomass of yellow perch in Saginaw Bay, 1970-2011.

Figure 4.2. (a) Production of age-0, and (b) recruitment of age-1 yellow perch in Saginaw Bay, including observed CPUE 

(Obs: mean catch per minute of fall assessment trawling by the Michigan DNR), predicted (based on Ricker stockrecruitment model with spawning stock biomass as the sole predictor), and best model (based on Ricker stock-recruitment 

model with spawning stock biomass as predictor and assuming non-stationarity).

Figure 4.3. CPUE (number 1000 m-3) of larval walleye caught in bongo tows by week for 2009 and 2010. In 2009 and 

2010, larvae first appeared near the mouth of the Saginaw River before distributing throughout the Bay. Spring 2010 was 

warmer than 2009, and in turn, walleye larvae emerged. During both years, young larvae less than 2 days old were caught 

far from the Saginaw River.

Figure 4.4 . Diets of larval walleye in Saginaw Bay, 2009 and 2010. Larvae began exogenous feeding at approximately 9 

mm and fed on a diversity of taxa through the larval stage.
6

Figure 4.5. Diets of young of year (YOY) walleye in Saginaw Bay 2009 and 2010. (a) YOY walleye diet composition for 

all taxa by counts. Predatory zooplankton, primarily non-native Bythotrephes, and fishes became important as walleye 

transitioned from herbaceous zooplankton. Walleye shifted to piscivory in early fall, as fish dominated diets by September 

in terms of biomass. (b) Composition of fishes in YOY diets by counts. Young walleye relied on various fish prey, 

including non-native gobies. 

Figure 4.6. Diets of age-1 and older walleye in Saginaw Bay 2009 and 2010.

Figure 4.7. CPUE (number m-3) of larval yellow perch caught in bongo tows during sampling weeks in 2009 and 2010.

Figure 4.8. Diets of larval yellow perch in Saginaw Bay by sampling week in 2009 and 2010.

Figure 4.9. Lengths of larval and juvenile yellow perch collected in bongo nets and trawls (circles) in Saginaw Bay during 

2009 and 2010. Lengths of yellow perch found in walleye stomachs are depicted with “+”, and asterisks indicate weeks 

when lengths of yellow perch ion walleye stomachs were significantly lower than trawl-caught yellow perch (2 sample 

t-test).

Figure 4.10 Diets of young-of-year yellow perch by sampling location in Saginaw Bay, 2009 and 2010.

Figure 4.11. Total length (mm) and total body energy (J) of age-0 yellow perch collected in the fall (filled circles) and age1 yellow perch the following spring (open circles). Yellow perch lost ~20% of body energy over winter (based on lengthspecific comparisons).

LIST OF TABLES

Table 3.1 Mean density (no m-2) of Dreissena in Saginaw Bay (from T. Nalepa).

Table 4.1. From Ivan et al. (2011): Age-specific correlations of walleye and yellow perch surveyed through the Michigan 

DNR’s annual trawling surveys in Saginaw Bay. (a) Yellow perch display strong compensatory density-dependent effects

on growth, while such effects are weaker for walleye. (b-c) Year-class strength (b) in terms of mean length; (c) in terms of 

abundance) of walleye are set by fall of age-0, while year-class of perch appear to be set by fall of age-1.
7

SAGINAW BAY Multiple Stressors Summary Report

1. INTRODUCTION

1.1 Purpose of report

This report synthesizes results obtained during a five-year study (2008-2012) on Saginaw Bay, a large embayment on the 

southwest side of Lake Huron. The report is a summary of findings relevant for management decision making regarding 

issues related to the fishery and water quality of Saginaw Bay. Because the report is intended as an overview, detailed 

descriptions of the approaches and methods used are omitted, but can be found in papers published in the peer-reviewed 

literature, including a special issue in the Journal of Great Lakes Research, scheduled for publication in late 2013.

The project was sponsored by the National Oceanic and Atmospheric Administration Center for Sponsored Coastal Ocean 

Research (NOAA CSCOR), administered through the NOAA Great Lakes Environmental Research Laboratory (GLERL) 

and builds on previous research in Saginaw Bay conducted by NOAA GLERL from 1991 to 1996. The organizing project 

concept was an “Adaptive Integrated Framework” (AIF) in which models and data are used interactively to inform one 

another and guide the research approach. While the project was headquartered at NOAA GLERL, the research team 

included partners from Michigan State University, the University of Michigan, Purdue University, Wayne State University, 

Western Michigan University, Eastern Michigan University, Case Western Reserve, the University of Akron, Duke 

University, LimnoTech, Inc., and the Michigan Departments of Natural Resources and Environmental Quality.

From the early conceptual stages of the project, our intent was to focus on research to inform pending management 

decisions. To help achieve this goal, project team members had numerous meetings with personnel from the MI DNR 

and DEQ, before the project proposal was written, to discuss the major uncertainties regarding fisheries and water quality 

management issues in Saginaw Bay. Additionally, representatives from both agencies were included as co-investigators 

on the proposal. Once the proposal was funded, we held additional meetings and a workshop to further refine our research 

agenda. Throughout the project, we tried to maintain an open communication with the participating management agencies.

After considerable consultation, our research agenda centered on issues related to phosphorus inputs and eutrophication 

symptoms including harmful algal blooms, benthic algal production and beach fouling (aka “muck”), invasive species and 

their influence on foodweb dynamics, and concerns regarding walleye and yellow perch production. Previous research 

had established a set of monitoring locations in the bay, our new project incorporated a subset of these stations and also 

included nearshore transects where divers conducted various monitoring activities (Figure 2.1). The results included 

herein highlight findings from our ambient monitoring as well as insights gained from related quantitative modeling 

efforts.

2. MANAGEMENT ISSUE FINDINGS AND IMPLICATIONS

2.1 Water Quality / HABs / beach issues (“muck”)

Saginaw Bay has a long history of eutrophication-related symptoms including drinking water taste and odor problems 

associated with high cyanobacteria levels (Bierman et al. 1980) and decaying organic matter deposits along the beaches. 

Excessive algal production around the Great Lakes catalyzed an extended debate from the 1960s into the 1970s about the 

primary cause of eutrophication, which was largely resolved by the mid-1970s with the recognition that phosphorus was 

the primary limiting nutrient in most freshwater ecosystems (Schindler and Vallentyne 2008), and that excess phosphorus 

loading was the cause of eutrophication symptoms in Saginaw Bay and other areas of the Great Lakes.

The earliest known phosphorus data from Saginaw Bay, collected in 1956, indicated total phosphorus concentrations as 

high as 70 ug/L, with average inner bay concentrations ranging from 37 to 45 ug/L, and average outer bay concentrations 

ranging from 13 to 24 ug/L (Beeton et al. 1967). A 1974 report indicated that data were insufficient to evaluate historical 
8

phosphorus trends, but concentrations were sufficiently 

high to support excessive algal growth, and Microcystis and 

Aphanizomenon were described as “common” (Freedman 

1974). 

Few detailed historical observations exist about the 

composition of shoreline detritus in Saginaw Bay. A 1961 

Michigan Department of Natural Resources (MDNR) 

memorandum described the wash-up as a “grey-black 

substance” composed of zooplankton (primarily ostracods 

and cladocerans), aquatic plant material, Fragillaria pieces, 

and Cladophora (Fetterolf 1961). Similar observations were 

made in an MDNR memorandum in 1978 (Kenaga 1978). 

However, more recent observations suggest that beach 

“muck” is composed primarily of decomposing metaphytonic chlorophytes (benthic autotrophs), including Zygnematales, 

Oedogonium, diatoms, Cladophora, and vascular hydrophytes (macrophytes) (Pillsbury et al. 2002). 

To mitigate the problems associated with high phosphorus levels, the 1978 amendments to the Great Lakes Water Quality 

Agreement (GLWQA) included a 440 tonnes/year total phosphorus target load for Saginaw Bay, which was based on 

conclusions from four mathematical models (International Joint Commission 1978). A 1979 phosphorus conference to 

establish a phosphorus management strategy for the Great Lakes included a recommendation that the “spring area-wide 

mean total phosphorus concentrations in Saginaw Bay should not exceed 15 ug/L”. The report also included proposed 

objectives to correspond with a 15 ug/L total phosphorus concentration including a 3.6 ug/L chlorophyll a concentration, 

a 3.9 m secchi depth, and the goal of a mesotrophic state (Thomas et al. 1980). Assessments following the establishment 

of target phosphorus loads (Bierman et al. 1984, DePinto et al. 1986) indicated general improvements in water quality; 

concurrently, management emphasis shifted from eutrophication to concerns with toxic contaminants. As a result, active 

monitoring for phosphorus and other eutrophication indicators lapsed for a number of years. 

Under the 1987 Protocol amending the GLWQA, the Saginaw River/Bay was designated as 1 of 43 Areas of Concern 

(AOC) due to impairment of 12 of the 14 possible Beneficial Use Impairments (BUIs) including:

•	 Restrictions on fish and wildlife consumption 

•	 Eutrophication or undesirable algae 

•	 Tainting of fish and wildlife flavor 

•	 Restrictions on drinking water consumption, or taste and odor 

•	 Degradation of fish and wildlife populations 

•	 Beach closings 

•	 Degradation of aesthetics 

•	 Bird or animal deformities or reproduction problems 

•	 Degradation of benthos 

•	 Degradation of phytoplankton and zooplankton populations 

Figure 2.1 - Saginaw Bay 

station location map.
9

•	 Restriction on dredging activities 

•	 Loss of fish and wildlife habitat 

Since 1988, seven Remedial Action Plans (RAPs) have been developed for the Saginaw River/Bay AOC, detailing a list 

of activities to address the sources contributing to these BUIs and the progress that has been made to restore the AOC. 

Two of the 12 BUIs were removed in 2008, including the fish and wildlife tainting, and drinking water taste and odor 

impairments (MI Department of Environmental Quality 2012). The removal of the taste and odor BUI was based on 

meeting treatment and water quality standards at the point of distribution into the water system. However, taste and odor 

problems associated with cyanobacteria growth still occur periodically, thus the two Bay City drinking water intakes are 

listed as not supporting the public water supply designated use under the Clean Water Act. 

Invasive dreissenid mussels were discovered in Saginaw Bay in 1991. Zebra (Dreissena polymorpha) and quagga 

(Dreissena rostriformis bugensis) mussels are believed to alter phosphorus cycling and promote the growth of 

cyanobacteria (Vanderploeg et al. 2001, Bierman et al 2005) as well as nuisance benthic algae including Cladophora. The 

“nearshore shunt hypothesis” posits that dreissenid mussels intercept influent phosphorus near tributary mouths limiting 

offshore phosphorus transport and increasing phosphorus availability in benthic nearshore regions (Hecky et al. 2004). 

In many areas around the Great Lakes, there has been a resurgence of beach fouling resulting from the deposition of 

decaying Cladophora, a problem that had diminished following implementation of phosphorus reduction strategies in the 

late 1970s. Beach “muck” continues to be an active concern in some areas around Saginaw Bay.

Annex 4 of the Great Lakes Water Quality Protocol of 2012 (the protocol amending the 1978 GLWQA) establishes an 

interim total phosphorus concentration target of 5 ug/L for the open waters of Lake Huron, and carries forward the 440 

tonnes/year total phosphorus load for Saginaw Bay as an interim target. The protocol also requires development of target 

phosphorus concentrations for nearshore waters of the Great Lakes and calls for load reduction targets for watersheds that 

have a “significant localized impact” on nearshore waters of the Great Lakes with consideration for “the bioavailability 

of various forms of phosphorus, related productivity, seasonality, fisheries productivity requirements, climate change, 

invasive species, and other factors, such as downstream impacts, as necessary” (Great Lakes Water Quality Protocol 

2012).

2.2 Project Findings

2.2.1 Phosphorus Inputs

Phosphorus load estimation is limited by the availability of both flow (volume/time) and phosphorus concentration (mass/

volume) measurements in the tributaries entering Saginaw Bay. An important consequence of this sparse data record is 

that annual total phosphorus load estimates are highly uncertain. To calculate annual loads and quantify their uncertainty, 

we developed a Bayesian hierarchical model for the Saginaw River (Cha et al. 2010). The Saginaw River is the largest 

tributary entering Saginaw Bay, has the best data record, and has been previously estimated to contribute ~78% of the 

total phosphorus load into the Bay (Canale and Squire 1976). Our results are consistent with previous reports (Bierman et 

al. 1984, DePinto et al. 1986) that documented TP load decreases following the GLWQA; however by the early 1990s the 

declines ceased, with considerable yearly variability since then. Even when only the Saginaw River is considered, the 440 

tonnes/year target TP load has rarely been met (Figure 2.2). If annual estimates for the Saginaw River are increased by 

25% to approximate the total load from all tributaries, then only in 2003 is there a > 50% probability that the target load 

was met. 

Initial load decreases resulted from declining total phosphorus concentrations in the Saginaw River; current yearly 

variability results primarily from annual river flow fluctuations. Saginaw River flow fluctuates yearly but shows no 

consistent long-term trend (Figure 2.3). The lowest annual TP loads occurred in the late 1990s- early 2000s, a period when 

the river was experiencing slightly lower flows. Although annual flow exhibits no obvious trend, there is some indication 

that seasonal changes may be occurring. In particular, early spring flow (March-April) has declined since the 1990s, 

whereas flow in May has generally increased. 
10

Inputs from the tributaries outside of the Saginaw River basin are not well-monitored for either flow or phosphorus 

concentration. Limited sampling (n=28) in 2009 in the Kawkawlin, Rifle, Pine, and Aus Gres Rivers indicated total 

phosphorus concentrations ranging from 19 to 221 ug/L with a sample average of 70.6 ug/L, and soluble reactive 

phosphorus concentrations ranging from 0.72 to 89.5 ug/L with a sample average of 21.6 ug/L. The highest concentrations 

occurred in the Kawkawlin River.

The wetlands around the Shiawassee National Wildlife Refuge just southwest of Saginaw partially mitigate the loads 

originating in the Flint River, Shiawassee River, Tittabawasse River, and other smaller tributaries, with an average 

reduction of approximately 13%. This estimate was derived by calculating the difference of the average 1997-2010 loads 

at the outlets of Tittabawasse, Shiawassee, Flint, and Cass Rivers with the Saginaw River load just upstream of Saginaw. 

These loads were estimated using regression models developed using available total phosphorus values from 1998 to 2008 

and observed flows from 1997 to 2010.

Figure 2.2 - Estimates of the 

Saginaw River total phosphorus 

load. Blue dots represent the 

mean of the Bayesian predictive 

distribution, bars represent ± 2 

standard deviations. Red dots and 

lines indicate estimates for 2010 

and 2011 using Saginaw River 

flow data without total phosphorus 

concentration data. Horizontal 

orange line denotes 440 tonnes 

target established in the GLWQA.

Figure 2.3 – Depiction of the 

Saginaw River long-term 

flow pattern produced with a 

technique known as “season 

trend decomposition using loess” 

(Cleveland 1993). The data are 

broken into three components: 

a smoothed long-term trend (top 

left), an oscillating seasonal 

pattern (top middle), and residual 

(top right). Smoothed long-term 

monthly patterns (bottom) indicate 

departures (blue line) from the 

long-term mean (horizontal black 

line). 
11

Based on a tally of discharge monitoring reports from National Pollutant Discharge Elimination System (NPDES) 

permitted facilities, urban and industrial point sources totaled approximately 178 and 163 metric tons of phosphorus in 

2004 and 2005, respectively, two average years, 194 and 177 metric tons in 2006 and 2009, respectively, two wet years, 

and 115 metric tons P in 2010, a dry year. In each of these years, the proportion originating in the Saginaw River basin 

was approximately 80-90% of the total reported discharge. The contribution of retention treatment basins (RTBs) in each 

of these years was approximately 14-19 metric tons phosphorus. Based on the ratio between reported discharges and 

summer low flow river load, we estimate that approximately 50% of the total point-source phosphorus load is exported to 

the bay. Thus, the contribution of NPDES permitted point sources to the total load to the bay ranges from approximately 

9% in wet years to approximately 16% in dry years. Contributions of RTBs range from approximately 1.5 to 4.5% of the 

total phosphorus load. 

2.2.2 Physical Processes

Inner Saginaw Bay has generally been regarded as well-mixed and vertically isothermal. However, thermistor strings 

deployed in 2009 at two sites (Figure 2.4a) revealed sporadic short-term summer stratification (Figure 2.4b). In 2010, 

2011, and 2012, GLERL deployed a Realtime Coastal Observation Network (RECON) buoy, in the deep area (~11 m) of 

inner-Saginaw Bay, equipped with sensors that measure surface and bottom characteristics including temperature, pH, 

dissolved oxygen, and current profiles. These measurements are logged and simultaneously transmitted in near real-time 

for web-based access (http://www.glerl.noaa.gov/res/recon/station-sbb.html). Periodic, albeit generally weak, stratification 

has also been documented at this location (Figure 2.5a), possibly resulting as cold water pulses from the outer bay enter 

the inner bay. Additionally, periods of rapid oxygen depletion occur regularly near the bottom (Figure 2.5b), with oxygen 

concentrations occasionally dropping below 2 mg/L. Because there is only one oxygen sensor, located approximately 

20-50 cm from the bottom, neither the vertical or horizontal extent of these dynamics are currently known. We anticipate 

deploying a RECON buoy at this site for several years into the future to better document these dynamics.

Numerical modeling conducted for ice-free seasons in 1991-1996 and 2008-2010 advanced our knowledge of circulation 

and water exchange with the main lake, revising existing views on hydrodynamics of Saginaw Bay. In particular, we 

found that some existing current maps (Bratzel et al. 1977) inaccurately depict circulation in the outer bay. Model results 

Figure 2.4b – Temperature profiles from each location. 

Temperatures in degrees C, horizontal axis in Julian days.

Figure 2.4a – Location of thermistors in 

Saginaw Bay.

43o

44o

45o

46o 46o

44o

43o

45o

84o 83o 82o 81o 80o

84o 83o 82o 81o 80o

0 20 40 60

0 20 40 60 80 100

Miles

Kilometers

N

Alpena

Harbor

Beach

Bay City

LAKE HURON

1 2

3

5

6

4
12

for 1991-96 and 2008-10 show a persistent anticyclonic gyre, rather than a cyclonic gyre, near the mouth of the outer bay, 

limiting water and constituent exchange with Lake Huron (Figure 2.6). Real-time, high-resolution circulation patterns can 

be viewed at http://www.glerl.noaa.gov/res/glcfs/currents/, and nowcasts depicting Saginaw River plume dynamics are 

available at http://www.glerl.noaa.gov/res/glcfs/sb/.

Previous studies (Dolan 1975) showed that water exchange driven by lake circulation resulted in an estimated riverine 

flushing time of the inner bay of approximately 3.7 months. New model results, based on a 2-dimensional particle 

transport model, which was run from spring to late summer for 9 years, revealed considerably longer flushing times, 

ranging from ~7 months in the mid-late summer and exceeding 10 months in the spring. 

2.2.3 Water Quality/Harmful Algal Blooms (HABs)

To evaluate temporal total phosphorus and chlorophyll a concentration patterns in the inner bay, we acquired extant data 

from numerous sources (Cha et al. 2011). A broad view considering the data from all of these sources, indicates that both 

total phosphorus and chlorophyll a declined in the late 1970s to the early 1980s (Figure 2.7), approximately in concert 

with decreasing total phosphorus loads (Figure 2.2). However, since approximately the mid-1980s, concentrations of both 

have been fairly stable.

Figure 2.5. - (a) Surface and 

bottom temperatures recorded 

by RECON buoy deployed 

in 2011 near site 10, and (b) 

corresponding bottom oxygen 

concentrations.

(a)

(b)
13

Figure 2.6 – Average Saginaw Bay circulation pattern in 1994.

Figure 2.7 – Data from numerous extant sources depicting Saginaw Bay 

total phosphorus (top) and chlorophyll a concentrations vs time. Sample 

average (dots) ± 1 standard deviation (vertical bars).
14

Figure 2.8 - Box and whisker plots 

depicting sample distributions of 

GLERL-collected total phosphorus 

in various time periods and locations 

in Saginaw Bay. Boxes indicate 

middle 50% of observations, dots 

indicate sample averages, horizontal 

lines indicate sample medians, 

notches depict 95% confidence 

intervals about the medians, whiskers 

indicate extreme values, box width is 

proportional to sample size. Sample 

sizes and sample averages for 

each group are shown above plot. 

Horizontal dashed line indicates 15 

ug/L concentration objective.

A more-focused examination considering only the data collected by NOAA GLERL from 1991 to 1996 and 2008 to 2010 

offers a different perspective. High-resolution hydrodynamic models of the bay indicate that, generally, the Saginaw 

River plume flows counter-clockwise and most strongly influences water quality on the southeast side of the inner bay. 

Generally, both total phosphorus and chlorophyll a concentration are higher in the plume-influenced samples than the nonplume samples. When the ambient monitoring stations are separated into three groups: inner-bay stations within the river 

plume, inner-bay stations outside of the river plume, and outer-bay stations, temporal patterns become more discernible 

(Figure 2.8). In the inner bay, within the Saginaw River plume, there is little difference between the distributions of TP 

concentrations from 1991 to 1996 and 2008 to 2010, and the sample averages are similar. However, within the inner bay, 

outside of the river plume, TP concentration distributions are higher in 1991-1996 than 2008-2010, and sample averages 

reflect this difference. Similarly, outer-bay concentration distributions were also higher in 1991-1996 than 2008-2010. 

Thus, outside of the Saginaw River plume, TP concentrations demonstrate a slight decrease in the more recent data. Data 

distributions from the nearshore diver transects exhibit a pattern similar to the 2008-2010 ambient stations with slightly 

higher concentrations in the plume than the non-plume stations. Overall, outer-bay concentrations are considerably lower 

than inner-bay concentrations, while transect concentrations are consistent with current TP levels at the inner bay ambient 

stations. Recent (2008-2010) exceedance rates of the 15 ug/L TP target were 47% within the river plume and 32% in the 

non-plume samples, while no outer-bay samples exceeded the limit. Transect sample exceedance rates in and out of the 

river plume were 28% and 11%, respectively.

Figure 2.9 - Box and whisker plots of 

GLERL-collected data depicting sample 

distributions of chlorophyll a in various 

time periods and locations in Saginaw 

Bay. Boxes indicate middle 50% of 

observations, dots indicate sample 

averages, horizontal lines indicate 

sample medians, notches depict 95% 

confidence intervals about the medians, 

whiskers indicate extreme values, box 

width is proportional to sample size. 

Sample sizes and sample averages 

for each group are shown above plot. 

Horizontal dashed line indicates 3.6 

ug/L concentration objective.
15

Chlorophyll a concentration patterns (Figure 2.9) are not as pronounced as those exhibited by TP, although outer bay 

concentrations are still notably lower than inner bay concentrations, as they are for phosphorus. Within the river plume, 

the overall distribution of CHLA is similar in 1991-1996 and 2008-2010, although the sample average is slightly higher in 

the later period. Within the inner bay, outside of the river plume, the overall concentration distributions are also similar as 

are the sample averages. High extremes are less apparent in the outer bay in 2008-2010 than 1991-1996, while the sample 

averages are similar. Exceedance probabilities of the 3.6 ug/L objective in 2008-2010 were 64%, 52%, and 14% in the 

plume, non-plume, and outer bay samples, respectively.

Secchi depth sample distributions (Figure 2.10) within the inner bay do not differ markedly, although the 2008-2010 

non-plume readings exhibit slightly higher averages than the plume readings in both the ambient and nearshore transect 

stations. Nearshore transect measurements somewhat under-represent the actual water clarity, as these measurements 

were generally in shallow water; approximately 30% hit bottom, and the reading was set to the water depth. Outer bay 

measurements exhibit much greater secchi distributions than the inner bay, and the 2008-2010 samples indicate greater 

depths than the 1991-1996 samples. Only 10% of the inner bay measurements from 2008 to 2010 met the 3.9 m objective, 

whereas the objective was met in 78% of the outer bay readings.

There is a well-defined relationship between chlorophyll a and total phosphorus concentration (Figure 2.11), implying 

phosphorus continues to limit phytoplankton production. The relationship, on a log-scale, is similar among inner- and 

outer-bay stations and between the 1991-1996 and 2008-2010 time periods. A rigorous quantification of this relationship 

may be useful guidance for developing enforceable, numerical phosphorus “Substance Objectives” (USEPA 2010, 

GLWQP 2012).

Process-based model simulations confirm that phosphorus is limiting primary production in Saginaw Bay. It is also clear 

that reduction in phosphorus inputs from the watershed will reduce algal growth. However, at this time, the model has 

not been explored via diagnostic scenarios to be able to recommend optimal spatial and temporal strategies (i.e., focus on 

Saginaw River or minor tributaries directly feeding into nearshore zones of the bay) for this load reduction. Further, the 

model has not been exercised to develop a quantitative load-response relationship for these endpoints. 

Model-based simulations indicate that wind-driven resuspension in the shallower areas of the inner bay contributes 

significantly to water column total phosphorus concentration on an event basis. Simulation of total phosphorus in the bay 

would not match observations very well if sediment resuspension is not included in the simulation. However, it is not clear 

that sediment resuspension of particulate phosphorus contributes significantly to algal growth. 

Figure 2.10 - Box and whisker plot 

depicting sample distributions of 

GLERL-collected secchi depth 

measurments in various time 

periods and locations in Saginaw 

Bay. Boxes indicate middle 50% of 

observations, dots indicate sample 

averages, horizontal lines indicate 

sample medians, notches depict 

95% confidence intervals about the 

medians, whiskers indicate extreme 

values, box width is proportional 

to sample size. Sample sizes and 

sample averages for each group are 

shown above plot. Horizontal dashed 

line indicates 3.9 meter objective.
16

Incubated sediment cores from site 10, in the deep area of the inner bay, exhibit high phosphorus flux to the water column 

under low oxygen conditions (Figure 2.12). This is in the same area where low bottom-water oxygen conditions have been 

recorded (Figure 2.5b), indicating the potential for periodic sediment phosphorus release. However, because low oxygen 

conditions have not been documented to persist, and ambient bottom-water phosphorus concentrations from site 10 are 

generally similar to surface concentrations, it seems unlikely that sediment phosphorus release is a consistent driver of 

phytoplankton production.

Phytoplankton biovolume measures show a mix of diatoms and cyanobacteria. On a cell-density basis, cyanobacteria are 

dominant at most times of the year (Figure 2.13a), whereas on a biovolume basis, Bacillaryophyta (diatoms) generally 

dominate (Figure 2.13b). While there are no enforceable numerical criteria for cyanobacteria, these levels are not 

particularly high by comparison to other lakes. For example, a target cyanobacteria concentration of 2 uL/L (20 x 108 μm3

L-1) has been considered in Lake Mendota, WI, (Stow et al. 1997); the levels reported here are generally below that target.

Figure 2.11 – Chlorophyll a vs 

total phosphorus in surface water 

samples and corresponding simple 

linear regression lines. Red = 

river plume, blue=non-plume, 

green=outer bay, circle = 1991-

1996, dot = 2008-2010, dashed line 

= 1991-1996, solid line = 2008-

2010.

Figure 2.12 – Changes in 

phosphorus concentration in 

intact sediment cores from sites 

5, 14, and 10 under differing 

oxygen levels.
17

Cyanobacteria composition is mixed; species of Merisomopedia and Microcystis generally dominate in the summer 

(Figure 2.14). Summer Microcystis blooms continue to occur, driven by a combination of warm water column 

temperatures and elevated levels of available phosphorus. Ambient microcystin concentrations were variable; 

approximately 19% of the 145 measurements exceeded the 1 ug/L World Health Organization drinking water 

concentration, mostly in the late summer (Figure 2.15). All samples analyzed for microcystin were untreated lake water 

and do not reflect concentrations in polished drinking water.

Diver-conducted dreissenid mussel surveys at hard-substrate sites indicate that mussel densities are lower than levels 

recorded in the 1990s (Figure 2.16). An 11-year monitoring gap makes it difficult to know if current levels represent 

a long-term decline or if densities experience large fluctuations over time-scales of 5-10 years. In the 1990s, zebra 

mussels (D. polymorpha) were the only dreissenids collected. In 2008-2010, samples consisted of approximately 20% 

zebra and 80% quagga mussels (D. rostriformis bugensis). Though densities at these sites were lower than in the 1990s, 

mussels were observed to be widely distributed, and quickly colonized equipment that was deployed for extended periods 

(Figure 2.16). Simple mass-balance model results indicate that, since the mussels first invaded, the proportion of influent 

phosphorus retained in the bay has remained relatively high (Cha et al. 2011), supporting the idea that mussel filtration is 

still influential even at lower densities. Additionally, the complement of phytoplankton species observed (Figure 2.13) is 

consistent with a community that would be promoted by the ability of mussels to selectively reject unpalatable algal forms 

Figure 2.13 – 2010 data depicting 

phytoplankton species by density (top) 

and biovolume (bottom) in surface 

samples from sites 2, 5, 10, 14, and 

20.

(a)

(b)
18

(Vanderploeg et al. 2001). Thus, it is likely that these invasive mussels still strongly influence ambient water quality and 

may be responsible for the total phosphorus declines observed outside of the Saginaw River plume (Figure 2.8).

2.2.4 Muck and Beach Fouling 

BCRA Park Ranger Logs 

Reduced phosphorus levels following the 1978 GLWQA are believed to have significantly reduced beach fouling in the 

1980s-1990s along most Great Lakes shorelines, prior to the proliferation of dreissenid mussels (Bootsma et al. 2004, 

Higgins et al. 2008a, Auer et al. 2010). However, park ranger logs from the Bay City Recreation Area (BCRA), located 

northwest (NW) of the mouth of Saginaw River, reveal that muck was a regular problem in Saginaw Bay throughout the 

1980s and early 90s. A few example entries include: 

Figure 2.14 - 2010 data 

depicting cynobacteria 

species in surface samples 

from sites 2, 5, 10, 14, and 

20.

Figure 2.15 – Microcystin 

concentrations 

from 2009 to 2010. 

Horizontal dashed line 

depicts World Health 

Organization drinking 

water standard. All 

samples were of raw 

water, not polished 

drinking water.
19

June 18, 1978 - Considerable time was spent removing muck from the swimming area. Our muck problem is very bad 

again this year. 

June 10, 1979 - Our muck problem is very severe at the present time. The muck is about a foot deep and extends along the 

entire beach and approximately 25 feet from the shoreline out into the bay. 

June 22, 1980 - Offshore winds and rains moved our muck from the beach area and we have the best swimming conditions 

we have had for several seasons. 

June 20, 1982 - The prevailing NW winds have piled up the muck on our beach to the extent our bombardier tractor can’t 

push it. With settled water conditions we may again make some progress in clearing our swimming area. 

Aug 5, 1984 - Muck on the beach is very thick. 

May 21, 1989 - We have a very low water level in the bay and a very big concentration of muck. 

Extensive entries throughout this period describe “thick, stinky muck”, and winds are sometimes mentioned as the cause 

of accumulation on the beach. Overall, these descriptions indicate that the phosphorus reductions attained in Saginaw Bay 

did not cause a decrease in beach muck comparable to what other Great Lakes beaches experienced after the 1978 target 

phosphorus loads became effective.

2.2.5 Field Study – Beach Survey 

Each summer from 2009 to 2012 we conducted an observational study of 7-10 sites along the southwestern Saginaw 

Bay shoreline, between the Saginaw River and Linwood, MI, where the volume, frequency, and composition of detrital 

Figure 2.16 – Average dreissenid mussel densities vs time. Inset shows mussel colonization on an 

instrumentation tripod that was deployed from April-September in 2009. Red ellipse highlights the 11 

year monitoring gap.
20

wash-up was monitored. Sites were chosen based on a preliminary study assessing areas of moderate to severe shoreline 

deposition (Figure 2.17). Results suggest that muck composition differs across the summer season and between years; 

Cladophora, Mougeotia, Oedogonium, Spirogyra, Zygnema, Chara, macrophytes, and wood chips have all been 

observed in varying proportions. For example, in 2009, instances of Spirogyra, Cladophora, and macrophyte deposition 

were observed all at different times in the summer months. In 2011, an early, severe deposition of macrophytes and a 

small amount of filamentous green algae was observed, measuring over 60 cm in depth in some areas along the BCRA. 

Mougeotia, Ulothrix, and diatoms were observed in early 2012. This varied composition suggests a more complex 

underlying process than most other Great Lakes areas where shoreline fouling is usually attributed to deposits of 

Cladophora. 

The state of decay of the beach detritus, and thus our ability to identify the main constituents, differed over the study 

period. Along areas of severe deposition, primarily near the BCRA, fresh muck deposition (i.e. identifiable composition) 

occurred early in the season and only occasionally thereafter. More often, deposition events contained material so badly 

decomposed that the composition was indeterminate. However, as we moved north along the shoreline, the detritus was 

less decomposed and more consistently identifiable. Figure 2.18 compares photos taken at a public access on the end of 

Cottage Grove Road (Linwood, MI; one of our northern sites) versus a photo taken at the Bay City Recreation Center 

(Bay City, MI; one of our southern sites) on the same day. We also typically saw a late season (late July, early August) 

deposition of macrophytes that was consistent across nearly all sites, though this late season deposition was often much 

smaller in volume than early season (April, May) deposition events. 

We also observed a pattern in muck movement and evidence as to the source of the muck precursors. First, muck appears 

to collect most heavily in inlets and coves along the shoreline, which are areas protected from heavy wind and wave scour. 

Additionally, the general direction of muck movement is north to south with the most severe areas of deposition located in 

Figure 2.17 – Depiction of the 

location on Saginaw Bay that 

experiences frequent, severe 

shoreline fouling events and the 

region of benthic algal growth 

identified by our bay-wide 

observations. Sampling sites 

were established in this zone of 

high deposition.
21

the BCRA. Fine-scale circulation models confirm that currents run in a north to south pattern parallel to the shoreline and 

indicate that currents regularly converge just north of the river mouth, usually during periods of northerly winds (http://

www.glerl.noaa.gov/res/glcfs/currents/). The location of the convergence is in the same area as the areas with heaviest 

muck deposition. Also, the circulation models suggest that the source of the detritus comes from the southwest portion of 

the inner bay, which is supported by our field work, explained below.

2.2.6 Fecal Indicator Bacteria

Wet muck samples collected near the water’s edge displayed high fecal indicator bacteria (FIB) levels, and nearshore

water in the vicinity of muck deposits had higher FIB counts than water from control sites (Figure 2.19). Levels in dry 

muck samples collected further up on the beach, and levels in beach sand were lower than levels in the wet muck. Wet 

muck samples experimentally exposed to sunlight for several days showed declining FIB levels with time (Figure 2.20). 

These results suggest that wet muck harbors FIB and may be a bacteria source to nearby areas.

2.2.7 Field Study – Saginaw Bay Survey 

In 2009 and 2010, we conducted a survey to determine the location, composition, and limits to growth of the benthic 

filamentous algal community of Saginaw Bay. An oblong region, approximately 20 km long and 3.5 km wide (70 

km2), was identified in the southwest region of the inner bay, which extended from 5 km west of the Saginaw River 

to the northern reach of Pinconning, MI, ranging from 2.0 to <5.0 m depth (Figure 2.17). This region was chosen for 

accessibility and because simulation models suggested that conditions for Cladophora and similar benthic filamentous 

green algal species production in the inner bay seem to be optimal in the shallow (~2 m depth) areas of the west and 

southeast portions of the inner bay. The greatest benthic growth was observed in the middle of this region and declined 

to nearly no growth at the edges, both parallel and perpendicular to the shoreline (for an example of high coverage, 

see Figure 2.21). In July 2009, sloughed Cladophora was observed at multiple locations, in some areas causing 100% 

coverage of the benthos. During this same time, beach observations indicated that a deposition event included substantial 

amounts of degraded Cladophora. We did not see sloughed Cladophora elsewhere in the bay or near agricultural drains, 

thereby supporting the idea that the decaying Cladophora on the beach originated in our sampling area. Additionally, a 

fine-scale circulation model indicated that currents moving over this area of heavy algal growth converge north of the 

Saginaw River, where muck deposition is most severe. Therefore, our results support the source of muck precursors to be 

located in the southwest region of the bay. 

Figure 2.18 – Comparison of beach detritus between a location 

north of the Bay City Recreation Area (Linwood, MI) versus the 

wash-up at the Bay City Recreation Area (Bay City, MI) on the 

same day. Detritus at northern sites were less decomposed and 

more identifiable than material at the BCRA sites.

Public Access Beach at the end 

of Cottage Grove Road (Linwood, 

MI) on 5/16/2010.

Bay City Recreation Area (Bay City, MI) on 5/16/2010.
22

Figure 2.19 - Mean Log10

concentrations (± Standard Error) 

of E. coli, Enterococci, and C. 

perfringens concentrations in wet 

decaying algae (muck), dry algal 

(muck) deposits, nearshore water, 

and beach sand. The means 

represent six samples collected 

between June and August 2010 on a 

biweekly basis. 

Figure 2.20 – Effect of 96 hrs 

sunlight exposure on the persistence 

(survival) of several Fecal 

Indicator Organisms (FIBs; E. coli, 

Enterococci, and C. perfringens) 

within freshly deposited wet muck 

collected from Tobico Beach, at the 

Bay City State Recreation Area. 

Upon moving a mat of muck to an 

area of direct sunlight and away 

from possible contamination from 

wave action, the muck was spread 

to a thickness of 15 cm, and 5 g was 

collected daily from the start of the 

experiment August 27-31, 2010 and 

analyzed for FIB following methods 

by Whitman et al. 2003. 

Figure 2.21 – Underwater photos of benthic green filamentous algal growth at transect 9 (near Pinconning, MI), 4.0 m 

depth on 6/14/2010.
23

Benthic algal growth was also observed in the localized nearshore areas near agricultural drains and other potential 

phosphorus sources (Figure 2.22), but we have reason to believe these zones do not provide a majority of the detritus we 

see in shoreline fouling events. In 2012, muck and nearshore water samples were collected south of an agricultural drain 

experiencing a large Cladophora sloughing event. However, the samples did not show any Cladophora, suggesting that 

the detritus source was not the agricultural drain. 

We assessed algae collected from the southwest quadrant of the bay to understand which natural levels of light and 

phosphorus elicited both the healthiest and least healthy algae in unaltered habitats. Benthic light and tissue phosphorus 

measurements were made on algal samples collected from a variety of light and phosphorus conditions. Measurements 

were compared to published light and phosphorus levels documented to cause light and phosphorus stress. At all sites, 

internal phosphorus measurements were below 1.6 mg P/g dwt, the threshold at which reductions in tissue phosphorus 

have been reported to reduce algal growth rates (Wong and Clark 1976, Auer and Canale 1982, Higgins et al. 2008; Figure 

2.23). The relative light saturation coefficient, a measure of how different the actual light environment is from the required 

light environment, was below 0 at 14 of 18 sites, indicating that a majority of the samples were light stressed (Figure 

2.24). Therefore, our results indicate that the algal muck precursors in the southwest quadrant of the bay are both light and 

phosphorus stressed.

2.3 Knowledge/Data Gaps – Research Needs 

The uncertainty of the annual load estimate in a given year is inversely proportional to the number of TP concentration 

measurements collected. For most recent years, there are approximately 10-12 concentration measurements available. 

Managers should evaluate whether the precision available from this level of monitoring is adequate for decision-making. 

A monitoring schedule consistent with the level of precision appropriate for decision-making should be developed. The 

load estimation method developed in this study is useful for estimates at the annual scale. If finer-temporal scales are of 

interest additional methods should be explored and should be supported with data at an appropriate temporal scale. 

Our calculations indicate that point sources currently contribute a relatively low proportion of the total annual phosphorus 

load to the bay. However, the distribution of non-point sources within the watershed is not well-characterized.

Dreissenid mussel densities are now much lower than they were in the 1990s, and the community is currently dominated 

Figure 2.22 – Photo of 

algal growth near Rosebud 

Agricultural Drain, Linwood 

Michigan on 6/7/2010. 
24

Figure 2.24 – The difference between midday benthic light (μmol/m2-sec) and the light saturation 

index (EK, μmol/m2-sec), also known as relative EK, or EKR. Data below 0 indicates subsaturating light 

conditions. The data is averaged across sample site. Error bars indicate standard error and are based on 

multiple measurements at a single sample site.

Figure 2.23 – Tissue phosphorus (mg P/g dwt) of benthic filamentous algae in the inner bay of Saginaw 

Bay, Lake Huron in 2009 compared to published values of phosphorus-limiting tissue concentrations (n 

= 21). 1.6 mg P/g dwt is the level below which phosphorus is limiting. Based on this threshold, 100% 

are P-limited. P-starvation 0.6 mg P/g dwt is the critical growth requirement. 26% of the samples are 

below this threshold, indicating P deficiency. The data is averaged across sample site. Error bars 

indicate standard error and are based on multiple measurements at a single sample site.
25

by quagga rather than zebra mussels. However, it is unclear if mussel densities are trending lower or if they just vary over 

periods of years. The relative role of the mussels in promoting benthic algal production, if further phosphorus reductions 

occur, is unclear.

Although we have an approximate understanding of the makeup of both beach detritus and the benthic algal community, 

we do not have estimates of the proportion of detrital material produced that actually washes onto the beaches. If this 

proportion is small, significant reductions may be needed to noticeably affect beach deposition. 

We still have low predictive power as to the timing and severity of major shoreline fouling events. High-resolution, near 

real-time hydrodynamic models are under active development. Coupling these models with future beach surveys may 

provide a useful predictive tool to managers and residents of pending deposition events. 

The origin of the fecal bacteria observed in association with the beach muck is unknown as is its health risk and 

association with pathogenic organisms. 

Although observed microcystin levels were relatively low, Microcystis was observed regularly in the warmer months, and 

the relationship between Microcystis abundance and microcystin production remains unclear. The development of simple 

empirical models to predict microcystin may be useful to provide an early warning to beach and drinking water managers.

2.4 Management Implications 

The 440 tonnes/year target total phosphorus load originally developed for the 1978 GLWQA has almost never been met, 

and ambient total phosphorus and chlorophyll a concentrations and secchi depth objectives are regularly exceeded in 

the inner bay. While there is some evidence for episodic sediment phosphorus reintroduction to the water column, the 

observation that the highest phosphorus and phytoplankton levels consistently occur in the Saginaw River plume make 

it unlikely that periodic sediment phosphorus release is an important promoter of algal growth. Water-column primary 

production appears to be phosphorus-limited as does benthic algal growth, thus it is likely that further phosphorus 

reductions will result in reduced algal production. Point-source total phosphorus discharges constitute a relatively low 

proportion of the current total phosphorus load; a focus on reducing non-point phosphorus inputs will be necessary to 

promote further improvements in eutrophication symptoms. 

However, the effect of further phosphorus reductions on beach fouling is unclear. Because muck was a consistent 

occurrence in the 1980s, before dreissenid mussels appeared, it cannot be considered a resurgent problem resulting 

from the mussel invasion, as it is in other areas around the Great Lakes. Unlike many other Great Lakes beaches, where 

Cladophora is the primary constituent of beach muck, the composition varies near the Bay City Recreation Area. 

Although benthic algal production, including Cladophora, is extensive in the Bay, the observed beach detritus often 

contains other filamentous algae as well as significant amounts of decaying macrophytes. Phosphorus reductions are 

unlikely to limit the production of macrophytes, which obtain phosphorus from deposited sediments. Currents in the bay 

are also important. Our results indicate a significant source of muck precursors in the southwest region of the bay; it is 

likely that decaying vegetation circulates in large gyres in the inner bay, and is pushed ashore at under appropriate wind 

conditions. 

Published reports in the 1980s, following efforts to reduce phosphorus loading, indicated water quality improvements 

associated with declining phosphorus inputs. Shortly thereafter, management priorities shifted, and active phosphorus 

surveillance languished for an extended period. During that time, phosphorus loads stabilized above the 440 tonnes/

year target, and dreissenid mussels became established, altering phosphorus cycling and the composition of the algal 

community. The lapse in active monitoring has made it difficult to fully understand the changes that have occurred over 

this period. Although invasive mussel densities are currently much lower than they were in the 1990s, they are still 

widespread, and their future population trajectory is unknown. Additionally, the composition of the mussel community 

has shifted from exclusively zebra mussels to approximately 75% quagga mussels; their role in nutrient cycling and 
26

algal productivity may continue to evolve as conditions in the bay change. To reduce future uncertainties, an active 

Adaptive Management Strategy, including regular monitoring and routinely updated modeling, should be developed and 

implemented. The Adaptive Management concept was in its nascent stage at the time of the 1978 Great Lakes Water 

Quality Agreement but is the basis of Annex 10 of the 2012 Protocol Amending the Agreement. 

2.5 Section 2 References

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Research Division Publication No. 15. (pp. 1–8). Ann Arbor: University of Michigan.

Beeton, A.M, S.H. Smith, and F.H. Hooper. 1967. Physical Limnology of Saginaw Bay, Lake Huron. Great Lakes Fishery 

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Lake Huron, to reductions in phosphorus loadings. Environmental Science & Technology 18:23-31.

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proliferation of blue-green algae in Saginaw Bay, Lake Huron. Journal of Great Lakes Research 31:32-55.

Bootsma, H.A., E.T. Jensen, E.B. Young, and J.A. Berges. 2004. Introduction. In Cladophora Research and Management 

in the Great Lakes (Workshop Proceedings). GLWI Special Report No. 2005-01. (pp. 1–4). University of WisconsinMilwaukee: Great Lakes Water Institute.

Bratzel, M.P., M.E. Thompson, and R.J. Bowden. 1977. The waters of Lake Huron and Lake Superior,Vol. II (Part A). 

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Bridgeman, T.B., G.L. Fahnenstiel, G.A. Lang, and T.F. Nalepa. 1995. Zooplankton grazing during the zebra mussel 

(Dreissena polymorpha) colonization of Saginaw Bay, Lake Huron. Journal of Great Lakes Research 21: 567-573.

Canale, R.P. and J. Squire. 1976. A model for total phosphorus in Saginaw Bay. Journal of Great Lakes Research 2:364-

373.

Cecala, R.K., C.M. Mayer, K.L. Schultz, and E.L. Mills. 2008. Increased benthic algal primary production in response 

to the invasive zebra mussel (Dreissena polymorpha) in a productive ecosystem, Oneida Lake, New York. Journal of 

Integrative Plant Biology, 50: 1452-1466.

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River, MI using a Bayesian hierarchical/multilevel model. Water Research 44: 3270-3282.
27

Cha, Y., C.A. Stow, T.F. Nalepa, and K.H. Reckhow. 2011. Do invasive mussels restrict offshore phosphorus transport in 

Lake Huron? Environmental Science & Technology 45: 7226-7231.

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Discharge Control Is Evaluated. Environmental Science & Technology 20: 752-759.

Dolan, D.M. 1975. Saginaw Bay residence times. Internal working paper, US EPA, Large Lakes research Station, Grosse 

Ile, Michigan.

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colonization on water quality parameters in Saginaw Bay, Lake Huron. Journal of Great Lakes Research 21: 435-448. 

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Concern.

Pillsbury, R.W., R.L. Lowe, Y.D. Pan, and J.L. Greenwood. 2002. Changes in the benthic algal community and nutrient 

limitation in Saginaw Bay, Lake Huron. Journal of the North American Benthological Society 21.2: 238–252.

Schindler, D.W., and J.R. Vallentyne. 2008. The Algal Bowl. The University of Alberta Press.

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biovolume from spring total phosphorus in Lake Mendota, Wisconsin. Canadian Journal of Fisheries and Aquatic 

Sciences 54: 464-473.
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Controls. Chapter 4 in: Phosphorus Management Strategies for Lakes. R.C. Loehr, C.S. Martin, and W. Rast, eds. Ann 

Arbor Science, Ann Arbor, MI.

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Huron) and Lake Erie. Canadian Journal of Fisheries and Aquatic Sciences 58: 1208-1221

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Fish. Res. Board Can. 33: 85–92.
29

3. INVASIVE SPECIES AND FOODWEB DYNAMICS 

3.1 Brief history of Saginaw Bay invertebrate and vertebrate assemblages

The Saginaw Bay ecosystem has been impacted by a suite of anthropogenic stressors, including chemical contamination, 

over-fishing, nutrient enrichment, sedimentation habitat destructions, and invasions of non-indigenous species 

(Vollenweider et al. 1974, Verbrugge et al. 1995, Fielder 2002). Until the 1970s, the bay was considered highly degraded 

due to high nutrient loads, various chemical pollutants, and land-use related sedimentation (Schneider 1977). Saginaw 

Bay historically supported productive cool water fisheries for species such as yellow perch, walleye, and lake herring, 

because it is generally warmer and more eutrophic than the main basin of Lake Huron. However, overfishing and 

habitat degradation led to declines and extirpation of many native fish populations by the 1940s (Hile and Buettner 

1959, Schneider and Leach 1977, Fielder et al. 2000). Degradation in overall water quality and fisheries led to the 

listing of Saginaw Bay as an Area of Concern (AOC) by the International Joint Commission in 1978 (International Joint 

Commission 1978). 

Since the 1970s, the impacts of several environmental stressors on Saginaw Bay may have seemingly lessened, and 

environmental conditions may have improved. Nutrient abatement programs have led to a reduction in phosphorous 

loadings (Cha et al. 2010). Direct discharges of chemical contaminants have decreased, although many legacy impacts 

of contaminants still persist (Jude et al. 2010, Wan et al. 2010). Stocking of walleye, beginning in 1980, led to the 

reestablishment of this fish population (Fielder et al. 2007). However, since the 1970s, Saginaw Bay has experienced 

numerous invasions, including spiny water fleas (Bythotrephes), white perch (Morone americana), round goby 

(Neogobius melanostomus), and zebra/quagga mussels (Dreissena polymorpha and D. bugensis). In addition, alewife, an 

invasive fish species that was a dominant component of the ecosystem since the 1950’s, crashed in 2003 (Schaeffer et al.

2004, Schaeffer et al. 2005, Roseman et al. 2006) and has since not fully recovered. For a timeline of some noteworthy 

events in Saginaw Bay see Figure 3.1.

Altered environmental conditions, species invasions, and shifts in dominant foodweb components have undoubtedly 

altered Saginaw Bay’s foodweb. However, due in part to limited, long-term monitoring of physical conditions, nutrient

loading (but see Cha et al. 2010), chemical concentrations and lower trophic levels, a complete understanding of foodweb 

responses is lacking. In contrast to many environmental variables, the Michigan Department of Natural Resources (MIDNR) has maintained a long-term fish trawling program in Saginaw Bay from 1970 to present. This dataset facilitates 

evaluation of long-term changes to the Saginaw Bay fish community and inferences regarding potential environmental 

variables driving changes in this fish community.

We aim to describe current patterns and long-term changes in the Saginaw Bay foodweb through field surveys and 

analyses of historic data. While many previous biotic studies of Saginaw Bay have focused on yellow perch and walleye 

(i.e., key species targeted by recreational and commercial fisheries; see section 4), production of walleye and yellow perch 

is dependent on conditions of the entire foodweb. We collected zooplankton, benthic invertebrates, and fish to examine 

spatial and seasonal assemblage patterns and trophic connections. In addition, we used the long-term MI DNR trawling 

survey to evaluate changes at the fish assemblage level and we compared lower trophic level (zooplankton and benthic 

invertebrates) to patterns documented during the 1990s.

3.2 Project Findings

3.2.1 Data sources

Field Surveys: From April 2009 through June 2011, we conducted extensive field collections in Saginaw Bay. These 

surveys targeted a number of different research questions and aspects of the Saginaw Bay ecosystem (described elsewhere 

in this report). We collected zooplankton using vertical tows of 64 μm zooplankton nets. We collected predatory 

zooplankton (Leptodora and Bythotrephes) and ichthyoplankton primarily using surface and oblique tows of a bongo 

sampler (335 and 700 μm) mesh. We sampled benthic macroinvertebrates with a standard Ponar dredge (0.052 m2 with 
30

Figure 3.1 - Timeline of notable changes to the Saginaw Bay foodweb.

Figure 3.2 - Median 

richness in 10 trawls 

as determined 

by Monte Carlo 

simulations from the 

fall Saginaw Bay 

trawl survey (1970-

2008) for A) total 

(rho=+0.57, p<0.05) 

and signal (relatively 

rare; see Ludsin et 

al. 2001) species 

richness (p>0.05) and 

B) tolerant (rho=-0.32, 

p<0.05), intolerant 

(rho=+0.32, p<0.05), 

and moderately 

tolerant (rho=+0.77, 

p<0.001) species 

richness.
31

500 μm mesh). Finally, we collected fish with a 7.6 m semi-balloon bottom trawl with a 13 mm stretched-mesh codend, which was towed for 10 min at approximately 1.29 ms-1. Organisms were preserved on board and then identified, 

enumerated, and examined (length/mass measurement, diet analyses) in the laboratory.

Historical analyses: We also evaluated biotic patterns in Saginaw Bay by analyzing historic patterns of fish collected 

through a long-term MI DNR trawling program (1970-present). Compared to fish community assessments, long-term 

surveys of invertebrates in Saginaw Bay are lacking. Thus, we compared invertebrate patterns observed during 2009-2011 

with patterns documented during the 1990s by NOAA GLERL (for description see: Nalepa et al. 1996, Johengen et al. 

2000). These data from the 1990s represent a time period when zebra mussels proliferated in Saginaw Bay, alewives were 

still abundant, and round goby were not established.

3.2.2 Key Findings

Zooplankton: Our findings related to zooplankton community patterns are described in a recent paper by Pothoven et 

al. (2013). In brief, we found a substantial shift in the zooplankton community from the 1990s to 2009-2010. Calanoid 

copepods increased in proportional abundance, as did some large-bodied taxa, such as Daphnia galeata. Relatively 

small Bosminidae were the most abundant taxa during both time periods, but their proportional abundance was greater 

during the 1990s than 2009-2010. These shifts in zooplankton size structure coincided with the collapse of alewife 

in 2003. Alewives are voracious size-selective planktivores, capable of restructuring zooplankton size assemblages 

(e.g., Brooks 1968). Other shifts in the zooplankton assemblage (e.g., increased abundance of calanoid copepods) are 

suggestive of a shift towards oligotrophication. Similar patterns are evident for Lake Huron, where decreased nutrient 

loading and dreissenid filtering may contribute to a more oligotophic-indicative zooplankton assemblage (Barbiero et al. 

2011). However, Saginaw Bay has remained relative productive since 1990, and hence the shift to a more oligotrophic 

assemblage is somewhat perplexing.

In addition to shifts in composition, Saginaw Bay’s zooplankton community seems to have shifted phenologically.

During the 1990s, zooplankton abundance was greatest in late spring and early summer (June), whereas during 2009-

2010, zooplankton abundance was greatest during fall (September-October). This shift in abundance and the decreased 

abundance in late spring and early summer may have important implications for survival and subsequent recruitment of 

young fish, which may rely on zooplankton as prey during larval and early juvenile stages. However, the mechanisms 

underlying this temporal shift are unclear. Bottom up processes (e.g., reduced phytoplankton densities in spring/early 

summer) and shifts in planktivore composition may be contributing factors. Planktivory by young alewives may be 

greatest in late summer and early fall (Hewett and Stewart 1990). In contrast, consumption by young yellow perch may be 

greater in early summer than early fall (e.g., Hayward et al. 1991). Thus, a shift from abundant alewife to abundant age-0 

yellow perch may have led to temporal shifts in zooplankton abundance.

Finally, not only herbaceous zooplankton, but also predatory zooplankton patterns shifted in Saginaw Bay from the 1990’s

to 2009-2010 (Pothoven et al. 2013). Two taxa of predatory zooplankton (Leptodora and Bythotrephes) were present in 

the system during both of these time periods. While densities of Bythotrephes increased significantly between the two 

time periods, Leptodora did not. Nonetheless, Leptodora densities decreased qualitatively: While Leptodora peaked in 

abundance during June in both 1991-1996 and 2009-2010, a subsequent peak in late summer was only evident in the 

1990s. In contrast, Bythotrephes densities were consistently higher during the 2009-2010 period (0.9 m-3 vs 7.6 m-3), with 

a small peak in abundance in the early summer and a much greater peak in the fall (Pothoven et al. 2013).

Benthic invertebrates: We collected benthic invertebrates on a monthly basis from several locations in Saginaw Bay 

and documented much greater spatial than temporal variation in benthic invertebrate assemblages (Foley et al. in review). 

Dominant taxa included quagga mussels (which have now almost entirely replaced zebra mussels in Saginaw Bay) and 

Chironomidae. For the most part, Saginaw Bay continues to be dominated by benthic invertebrate species tolerant of 

eutrophic and poor water quality conditions. However, we have found some more pollution sensitive taxa (e.g., Hexagenia

and Trichoptera; Foley et al. in review, D. Kashian unpublished data) suggesting that the benthic community may be 

marginally responding to decreased nutrient loading and improved water quality.
32

The most noteworthy difference between benthic invertebrates collected during the 1990s and 2009-2010 was a 

significant decline in dreissenid mussel densities (Table 3.1). The mechanisms responsible for this decline are enigmatic. 

It is plausible that the densities observed during the 1990s followed a near exponential population growth that would 

inevitably lead to a compensatory reduction in sustainable density. Moreover, the shift from zebra to quagga mussels, 

slight decreases in nutrient loading, and potential predation by round gobies (see below) may all have contributed to this 

decline.

Table 3.1 - Mean density (no m-2) of Dreissena in Saginaw Bay (from T. Nalepa).

Year Inner Bay (5 sites) Outer Bay (1 site)

1991 9,305 3,408

1992 31,334 4,695

1993 3,803 5,813

1994 5,633 9,925

1995 2,562 3,824

1996 5,261 6,981

Mean (91-96) 4,314 6,636

2008 538 596

2009 421 411

2010 1,808

Fish community: Analyses of long-term sampling of the Saginaw Bay fish assemblage by the Michigan DNR (1970-

2011) suggest that the community has shifted dramatically over the past four decades. We considered temporal changes 

in the fish assemblage using: 1) analyses of changes in richness metrics, 2) dynamic factor analyses (DFA) to fit longterm trend models of the most abundant fish species, and 3) non-metric multidimensional scaling (nMDS) to visualize 

differences in assemblage structure among different years. The median richness of fishes collected through Michigan 

DNR trawling increased marginally from the 1970s to present. In particular, richness of species classified as tolerant 

of eutrophic conditions decreased, whereas richness of species classified as marginally tolerant of eutrophic conditions 

increased. DFA and nMDS analyses which account for species-specific trends in relative abundance also suggest that the 

fish assemblage has shifted dramatically (for details see Ivan et al. in revision).

These shifts in the Saginaw Bay fish assemblage have occurred coincident with decreased nutrient loading and overall 

productivity in Saginaw Bay (Cha et al. 2010). In addition, the observed shifts in assemblage composition and structure 

(e.g., reductions in eutrophic tolerant species) are indicative that the fish assemblage has responded to improved water and 

habitat quality related to diminished eutrophy. We compared the ability of annual nutrient loading to explain assemblage 

patterns, versus the explanatory ability of other environmental variables (temperature, water levels, water flow). In 

so doing, we found that annual phosphorous loading was most strongly associated with shifts in assemblage patterns. 

However, the paucity of long-term environmental data made it difficult to rigorously evaluate a complete set of potential 

environmental variables, potentially structuring the Saginaw Bay fish community (for details see Ivan et al. in revision).

Fish species of note: Our surveys during 2009-2011 were primarily designed to describe yellow perch and walleye 

performance and interactions in Saginaw Bay (see other section of this report). However, we collected various other 

species during these surveys and below we point to some observations related to round goby, trout-perch and lake 

whitefish.

-Round goby: As described above, round goby invaded Saginaw Bay in the late 1990s and subsequently proliferated 

throughout the bay. They now represent an important diet item for piscivorous yellow perch and walleye (see walleye-
33

Figure 3.3 - Results of a preliminary 

non-metric multidimensional scaling 

analysis to visualize changes in the 

relative abundances of the Saginaw Bay 

fish assemblage, based on Michigan 

Department of Natural Resources 

trawling data from 1970 to 2008.

perch section). In addition, they may play important roles as predator on benthic invertebrates and a competitor with 

benthivorous fishes. In many areas of the Great Lakes, round goby have been identified as contributing to altered spatial 

distributions, decreased abundance, and local extirpations of species such as johnny darter, logperch, and slimy sculpin. In 

fact, since the round goby invasion in Saginaw Bay, some small-bodied benthivorous species have become less common 

in annual trawl surveys (Fielder and Thomas 2006). 

We found that round goby preferentially consumed Chironomidae larvae in Saginaw Bay (Figure 3.4). Since these prey 

are also targeted by several ecologically and economically important native species (e.g., young walleye, yellow perch, 

lake whitefish, trout-perch, etc), round goby have the potential to compete for prey resources (if these resources are 

limited).

As described above, abundance of dreissend mussels in Saginaw Bay declined from the mid 1990s to the late 2000s. 

As a potential predator on dreissenid mussels, round goby may have contributed to this decline. We found that relative 

consumption of dreissenids by round gobies increased with size (Figure 3.4) and tended to be highest in the fall. In 

addition, the size of dreissenids consumed increased with round goby size (Figure 3.5). Foley et al. (in prep) compared the 

size of dreissenids in the environment with the size of dreissenids in the guts of gobies and suggested that size-selective 

predation by gobies could partially explain dreissenid size distributions in the environment. However, preliminary 

bioenergetics analyses (based on maximum consumption rates and observed goby densities) suggest that the potential for 

goby consumption to limit dreissenid abundance is low.

-Trout-perch: Trout-perch are a native but largely understudied species in the Great Lakes. Due to their relative high 

abundance (third most abundant species collected in our bottom trawls), trout-perch likely play an important role in the 

Saginaw Bay foodweb. Our findings related to trout-perch interactions are described in a recent paper by Blouzdis et al. 

(2013). In brief, we found that trout-perch primarily consume Chironomidae larvae, and often display strong positive 

selection for Chironomidae and Amphipoda (a less abundant benthic prey). In contrast, dreissenid mussels, the most 

abundant benthic invertebrates in Saginaw Bay, were entirely absent from trout perch diets.

Despite their high abundance, trout-perch were very rare in the diets of potential piscivorous yellow perch and walleye; 

trout-perch constituted 5 out of 1370 piscine diet items (0.4%), while they constituted 15% of fish collected in bottom 

trawls (Blouzdis et al. 2013).
34

Figure 3.4 - Gut contents of round gobies, summarized by size, season collected, and year. Chironomid larvae 

(red) make up large proportions of the gut contents regardless of size, season or year. Dreissenids (green) 

make up increasingly larger proportions of items consumed as fish length increases or the season progresses. 

Even the smallest gobies rely on dreissenids to some degree. Zooplankton (turquoise) are dominated by 

ostracods. Other benthos (purple) are dominated by mayfly larvae, chironomid pupae and amphipods.

Figure 3.5 - Mean 

length of dreissenids 

found in differentsized round 

gobies. Larger 

gobies consume 

larger dreissenids 

regardless of time of 

year, while few gobies 

tend to consume 

dreissenids that are 

larger than 10 mm. 
35

-Lake whitefish: Lake whitefish support important commercial fisheries in outer Saginaw Bay and in the main basin of 

Lake Huron. Lake whitefish spawn in inner Saginaw Bay and given the high productivity of inner Saginaw Bay, this 

habitat may allow for rapid growth of young whitefish and represent an important source of lake whitefish production 

for other regions of Lake Huron. We collected larval lake whitefish during April-June in both 2009 and 2010, and 

subsequently collected young-of-year lake whitefish in bottom trawls from June-November (for details see Pothoven et al. 

in review). Age-0 lake whitefish shifted from initially feeding on cyclopoid copepods to subsequently target cladocerans 

and then benthic prey (Chironomidae, Chydoridae and Sphaeridae). While we did not directly measure growth rates of 

young lake whitefish, the high abundance (relative to main basin of Lake Huron) of their preferred prey suggests that the 

potential for growth of young whitefish in Saginaw Bay is high (Pothoven et al. 2013). Also, it is worth noting that we did 

not find any young lake whitefish in diets of potential piscovorous fish.

3.3 Research Needs and Management Implications

Eutrophication and biotic responses: Saginaw Bay’s biota appears to have partially responded to long-term reductions

in nutrient loading and improved water quality. A variety of patterns point to such responses including: 1) a more 

oligotrophic zooplankton assemblage, 2) reemergence of some sensitive benthic invertebrates, and 3) a shift in the fish 

assemblage from species highly tolerant of eutrophic conditions to species moderately tolerant of eutrophic conditions. 

Nonetheless, many tolerant invertebrate and fish species remain highly abundant in Saginaw Bay and more sensitive 

species remain a minor component of overall communities. Thus, while our findings point to positive biotic responses, 

continued efforts to reduce nutrient loading/sedimentation and improve water quality are likely necessary for Saginaw 

Bay’s biotic composition to continue to shift towards more sensitive species.

Invasive species: Several of the taxa that seem to have responded to ecosystem level changes in Saginaw Bay are not 

actively managed, and hence the taxa-specific management implications of some of our findings are not straightforward. 

For example, while it is clear that several invasive species play important roles in the Saginaw Bay’s foodweb (e.g.,

quagga mussels, Bythotrephes, round gobies) it is not obvious how to control these species.

While invasive species are generally considered negatively, some invaders are contributing to production of desirable 

native fish species in Saginaw Bay. Bythotrephes are consumed by age-0 walleye and are strongly selected as preferred 

prey by age-1 and older yellow perch in Saginaw Bay. Similarly, round goby are consumed by piscivrous walleye (from 

age-0 through the end of life) and age-1 and older yellow perch.

Coregonids: To our knowledge, there have been limited previous studies of lake whitefish in Saginaw Bay. We found 

evidence that inner Saginaw Bay supports relatively fast growth of young whitefish, and we found no evidence that 

young lake whitefish are targeted by piscivorous walleye or yellow perch. We speculate that due to high availability of 

invertebrate prey (both zooplankton and benthic invertebrates), inner Saginaw Bay may constitute a high quality nursery 

source for adult lake whitefish, which in turn support fisheries in outer Saginaw Bay and main basin of Lake Huron. 

The strong performance of young lake whitefish in Saginaw Bay may suggest that physiologically similar species may 

also thrive in Saginaw Bay. The potential for reestablishment of abundant stocks of native cisco (lake herring) in Lake 

Huron has received strong support. In the absence of alewife, this planktivore may now be able to fill an important 

ecological role in both Saginaw Bay and main basin of Lake Huron. 

While growth conditions appear to be suitable for young coregonids, spawning habitat may constitute a potential 

bottleneck for increased lake whitefish and cisco production in Saginaw Bay. Past studies suggest that many potentially 

suitable spawning sites in Saginaw Bay have been lost through sedimentation. It is an open question where lake whitefish 

are currently spawning in inner Saginaw Bay. We suggest that future surveys could evaluate (a) whether coregonid 

spawning habitat is truly limited, and (b) the potential for creation of additional spawning habitat in Saginaw Bay. 
36

Temporal shifts of invertebrates: We documented some temporal shifts (both within and across years) in invertebrate 

densities which are not straightforward to explain, but may have important implications. First, we found that zooplankton 

peak densities occur much later in the year now, than they did historically. This may have important implications for 

young fish that rely on abundant zooplankton as prey during early, critical life stages. Although we speculate that both 

bottom-up and top-down changes may have contributed to this shift (see above), we are unable to robustly evaluate the 

mechanistic underpinnings. Given the potential importance of this change in zooplankton density cycles, we suggest that 

future studies should more fully explore the mechanisms. 

Second, we also documented a decline in dressenid abundance from the 1990s to late 2000s. This trend is opposite 

to patterns observed in many systems, where dreissenids have continued to increase over time. While some patterns 

(i.e., dreissenid size structures) suggest that goby predation may influence dreissenid populations, our preliminary 

bioenergetics estimates of goby consumption suggest that such predatory control is unlikely. Future efforts to understand 

the mechanisms of dreissenid declines would be useful and may help inform management efforts in several other systems, 

where control of dreissenids would be highly desirable.

Long-term monitoring: Finally, we believe that our studies in Saginaw Bay demonstrate the value of long-term 

monitoring. Many aspects of the Saginaw Bay ecosystem (e.g., water quality, invertebrate assemblages) have not been 

routinely monitored over a long time period, making it difficult to document historic trends and consider potential 

mechanisms underlying changes. In contrast, the Michigan Department of Natural Resources long-term (1970-present) 

trawling program in Saginaw Bay represents an invaluable resource for exploring historic biotic responses. In many 

aquatic systems, data availability is the converse of Saginaw Bay (i.e., long-term data on environmental conditions, but 

limited data on upper trophic levels like fishes). The Michigan DNR should be applauded for maintaining this program 

and we hope that it will continue indefinitely.

3.4 Section 3 References

Barbiero R.P., B.M. Lesht, and G.J. Warren. 2011. Evidence for bottom-up control of recent shifts in the pelagic food web 

of Lake Huron. Journal of Great Lakes Research 37:78–85.

Brooks, J.L. 1968. The effects of prey size selection by lake planktivores. System Zoology 17:273–291

Blouzdis, C.E., L.N. Ivan, S.A. Pothoven, C.R. Roswell, C.J. Foley, and T.O. Höök. 2013. A trophic bottleneck?: The 

ecological role of trout-perch Percopsis omiscomaycus in Saginaw Bay, Lake Huron. Journal of Applied Ichthyology 29: 

416–424.

Cha, Y., C.A. Stow, K.W. Reckhow, C. DeMarchi, and T.H. Johengen. 2010. Phosphorus load estimation in the Saginaw 

River, MI using a Bayesian hierarchical/multilevel model. Water Research 44: 3270-3282.

Fielder, D.G., J.E. Johnson, J.R. Weber, M.V. Thomas, and R.C. Haas. 2000. Fish population survey of Saginaw Bay, 

Lake Huron, 1989-1997. Michigan Department of Natural Resources, Fisheries Research Report No. 2083. Ann Arbor, 

MI.

Fielder, D.G. 2002. Sources of walleye recruitment in Saginaw Bay, Lake Huron. North American Journal of Fisheries 

Management 22: 1032-1040.

Fielder, D.G. and M.V. Thomas. 2006. Fish population dynamics of Saginaw Bay, Lake Huron, 1998-2004. Michigan 

Department of Natural Resources, Fisheries Research Report No. 2083. Ann Arbor, MI.

Fielder, D.G., J.S. Schaeffer and M.V. Thomas. 2007. Environmental and ecological conditions surrounding the 

production of large year classes of walleye (Sander vitreus) in Saginaw Bay, Lake Huron. Journal of Great Lakes 

Research 33(Supplement 1): 118-132.
37

Foley, C.J., S.A. Pothoven, C.R. Roswell, and T.O. Höök. in prep. Spatial and temporal patterns of benthic 

macroinvertebrates in Saginaw Bay, Lake Huron, 2009-2010.

Foley, C.J., S.A. Pothoven, C.R. Roswell, and T.O. Höök. in prep. Prey selection of gobies in Saginaw Bay, Lake Huron. 

Hayward R.S., F.J. Margraf, D.L. Parrish, and B. Vondracek B. 1991. Low-cost estimation of yellow perch daily ration. 

Transactions of the American Fisheries Society 120:589–604.

Hewett, S.W. and D.J. Stewart. 1989. Zooplanktivory by alewives in Lake Michigan: ontogenetic, seasonal, and historical 

patterns. Transactions of the American Fisheries Society 118: 581-596.

Hile, R. and Buettner, H. J. 1959. Fluctuations in the commercial fisheries of Saginaw Bay, 1885-1959. Fish and Wildlife 

Service Research Report 51, U.S. Department of the Interior.

International Joint Commission. 1978. Great Lakes Water Quality Agreement of 1978, with annexes and terms of 

reference between the United States and Canada, Signed at Ottawa, November 22, 1978, Windsor, Ontario, Canada.

Ivan, L.N., D.G. Fielder, M.V. Thomas, and T.O. Höök. in prep. Fish community dynamics in the face of multiple 

anthropogenic stressors: Saginaw Bay, Lake Huron, 1970-2008.

Johengen T.H., T.F. Nalepa, G.A. Lang, D.F. Fanslow, H.A. Vanderploeg, M.A. Agy. 2000. Physical and chemical 

variables of Saginaw Bay, Lake Huron in 1994-1996. NOAA Technical Memorandum, GLERL-115. Ann Arbor, MI. 

NOAA-GLERL.

Jude, D.J., R. Rediske, J. O’Keefe, S. Hensler, and J.P. Giesy. 2010. PCB concentrations in walleyes and their prey from

the Saginaw River, Lake Huron: A comparison between 1990 and 2007. Journal of Great Lakes Research 36: 267-276.

Nalepa, T.F., G.L. Fahnenstiel, M.J. McCormick, T.H. Johengen, G.A. Lang, J.F. Cavaletto, and G. Goudy. 1996. Physical 

and chemical variables of Saginaw Bay, Lake Huron in 1991-1993. NOAA Technical Memorandum, ERL GLERL-115. 

Ann Arbor, MI. NOAA-GLERL.

Pothoven, S.A., T.O. Höök, T.F. Nalepa, M. Thomas, and J.D. Bressie. 2013. Changes in zooplankton community 

structure associated with the disappearance of invasive alewife in Saginaw Bay, Lake Huron. Aquatic Ecology 47:1–12.

Pothoven, S.A., T.O. Höök, and C.R. Roswell. In press. Feeding ecology of age–0 lake whitefish in Saginaw Bay, Lake 

Huron. Journal of Great Lakes Research.

Roseman, E.F., J.S. Schaeffer, J.R.P. French III, T.P. O’Brien, and C.S. Faul. 2006. Status and trends in the Lake Huron

deepwater aquatic community, 2005. Report to the Great Lakes Fishery Commission. Upper Lakes meetings, Ypsilanti, 

MI, March 2006.

Schaeffer, J.S., J.R.P. French IIII, A.A. Shakoor, C.S. Faul, and K. Powell. 2004. Status and trends in the Lake Huron 

deepwater aquatic community, 2003. Report to the Great Lakes Fishery Commission. Upper Lakes meetings, Ypsilanti, 

MI, March 2004.

Schaeffer, J.S., E.F. Roseman, S.C. Riley, C.S. Faul, T.P. O’Brien, and A. Fouilleroux. 2005. Status and trends in the

Lake Huron deepwater aquatic community, 2004. Report to the Great Lakes Fishery Commission. Upper Lakes meetings, 

Ypsilanti, MI, March 2005.
38

Schneider, J.C., and J.H. Leach. 1977. Walleye (Stizostedion vitreum vitreum) fluctuations in the Great Lakes and possible 

causes, 1800-1975. Journal of the Fisheries Research Board of Canada 34:1878-1889.

Vebrugge D.A., J.P. Giesy, M.A. Mora, L.L. Williams, R. Rossman, R.A.Moll, and M. Tuchman. 1995. Concentrations of 

dissolved and particulate polychlorinated-biphenyls in water from the Saginaw River, Michigan. Journal of Great Lakes 

Research 21:219-233.

Vollenweider R.A., M. Munawar, and P. Stadelman. 1974. Comparative review of phytoplankton and primary production 

in the Laurentian Great Lakes. Journal of Fisheries Research Board of Canada 31:739-762.

Wan Y., P.D. Jones, R.R. Holem, J.S. Khim, H. Chang, D.P. Kay, S.A. Roark, J.L. Newsted, W.P. Patterson, and J.P. Giesy. 

2010. Bioaccumulation of polychlorinated dibenzo-p-dioxins, dibenzofurans, and dioxin-like polycholinated biphenyls in 

fishes from the Tittabawassee and Saginaw Rivers, Michigan, USA. Science of the Total Environment 408: 2394-2401.
39

4. FISH AND FISHERY MANAGEMENT IN SAGINAW BAY

4.1 Brief History of Saginaw Bay Walleye and Perch Fishery

Yellow perch and walleye presently and historically represent the most important fisheries in Saginaw Bay (Fielder and 

Thomas 2006). Successful production of harvestable walleye and yellow perch requires survival from hatching to a size 

suitable for harvest. As is the case for most fish species, walleye and yellow perch are highly fecund and produce large 

numbers of young most of which die during early life. Large initial cohort sizes imply that the greatest capacity for 

altering fish population production relates to changes in vital rates (survival and growth) during early life. These early life 

determinants of walleye and perch recruitment have evidently varied dramatically over time in Saginaw Bay. 

Prior to the middle of the 20th Century, the Saginaw Bay walleye stock consistently supported the second largest 

commercial fishery in the Great Lakes (i.e., during this time there was consistent successful natural reproduction; 

Schneider and Leach 1977, Mrozinski et al. 1991). However, due to a variety of factors (including over-exploitation, 

invasive species, and intensive eutrophication) the stock collapsed. Even though the Michigan Department of Natural 

Resources (MDNR) was able to reestablish (and subsequently maintain) an adult walleye population (Keller et al. 1987), 

until recently, this population has been almost entirely dependent upon stocking (i.e., limited evidence of successful 

natural reproduction; Mrozinski et al. 1991, Fielder 2002).

The Saginaw Bay yellow perch population, on the other hand, has persisted despite dramatic changes to the ecosystem 

and without intensive stocking efforts, and in fact, continues to support both commercial and sport fisheries. However, 

growth rates of this population have varied dramatically over time: during the 1980’s, growth rates of Saginaw Bay yellow

perch were anomalously low (likely owing to insufficient benthic invertebrate prey resources; Schaeffer et al. 2000), but 

following a severe decline in population abundance from 1989 to 1991, growth rates increased markedly (Fielder et al. 

2000).

Interestingly, during the past few years, MDNR early fall survey trawling has documented large numbers of age-0 

walleye and yellow perch in Saginaw Bay (Fielder and Thomas 2006). However, the young fish that constitute these 

abundant cohorts have experienced poor growth rates and obtained relatively small body sizes by the fall (Fielder and 

Thomas 2006). In turn, these small individuals may have limited energy reserves and high mass-specific metabolic rates 

potentially leading to high starvation mortality during winter (a period of resource scarcity) and prolonged susceptibility 

to gape limited predators. In fact, recent MDNR collections of age-1 walleye and yellow perch indicate that survival rates 

from age-0 to age-1 are low for walleye and extremely low for yellow perch.

These differential survival rates of young percids suggest that the bottlenecks limiting recruitment of walleye and yellow 

perch in Saginaw Bay have changed over time. Prior to 2003, fall age-0 walleye abundance was low (Fielder et al. 2007), 

indicating poor survival during larval and early juvenile planktivorous ontogenetic stages. During this time, invasive 

alewives dominated the Lake Huron fish community (Dobiesz et al. 2005) and were seasonally abundant in Saginaw 

Bay (i.e., adults were abundant during spawning migrations in late spring and early summer, while age-0 alewives 

utilized Saginaw Bay as a nursery habitat during summer and early fall). Alewives are voracious planktivores capable 

of restructuring zooplankton communities (Brooks and Dodson 1965, Wells 1970, O’Gorman et al. 1991, Scavia et al.

1986, Evans 1992) and thereby competing with young planktivorous walleye and perch. In addition, there is a plethora 

of evidence from a variety of systems that alewives are potentially important predators on percid early life stages (e.g., 

Brandt et al. 1987, Mason and Brandt 1996). It is thus not surprising that coincident with the recent collapse of the Lake 

Huron alewife population (Fielder et al. 2007), early life survival rates of walleye and perch increased dramatically 

(Fielder and Thomas 2006), such that growth conditions during the late summer and fall (when young walleye and perch 

rely primarily upon piscivory and invertivory, respectively) may now more strongly affect recruitment success (Fielder 

and Thomas 2006).
40

While it is apparent that recruitment bottlenecks for walleye and yellow perch in Saginaw Bay have changed over 

time, it is not clear how the suite of stressors affecting the Saginaw Bay ecosystem (nutrient loading, river discharge, 

invasive species, and climate change) have (in the past) and will (in the future) interactively impact annual production 

and recruitment of these two species. An empirical (regression) analyses evaluating the effects of various biological and 

physical potential determinants of walleye recruitment (based on MDNR fall trawling surveys) suggests that from the 

period including 1993-2005, adult alewife abundance in Lake Huron was the single best predictor of walleye recruitment 

(fall abundance of wild and hatchery age-0 walleye; Fielder et al. 2006). This and other empirical analyses are useful 

for identifying potentially important determinants of recruitment success and for generating hypotheses regarding 

recruitment mechanisms, but such analyses are less useful for rigorously evaluating such hypotheses. Further, given that 

(1) ecosystems are characterized by strong non-linear relationships (which are difficult to account for through empirical 

analyses), (2) a multitude of temporally correlated natural and anthropogenic forcing factors can influence temporal trends 

in population biomass and growth, and (3) the Saginaw Bay ecosystem may have undergone a regime shift leading to 

potential non-stationarity in causal relationships; empirical relationships may have limited predictive power beyond the 

time-period represented by their underlying data sets. This is especially true if future values of predictive variables extend 

beyond the range of values upon which the relationship was established.

We therefore explore mechanisms of walleye and perch recruitment in Saginaw Bay by evaluating their early-life 

dynamics (growth, survival, and food-web interaction) from hatching through survival to the following spring. During 

this time, these fish are expected to change from consuming primarily zooplankton to consuming primarily benthic 

invertebrates and fish. Thus, depending upon how nutrients move through the ecosystem (to zooplankton vs. benthos), 

different life stages (larvae, late-stage juveniles) may be growth limited (population bottlenecks) during this period. In 

turn, growth rates will have clear implications for survival (due to size-dependent predation pressure and size-dependent 

over-winter mortality), and survival rates will also vary independent of growth, as abiotic conditions can dramatically 

mediate predation pressure. 

4.2 Project Findings

Historical analyses: To appreciate dynamics structuring early-life performance of yellow perch and walleye in Saginaw 

Bay, we initially analyzed historical data (1970-2008) collected as part of the Michigan Department of Natural Resources’

long-term trawling program in Saginaw Bay. These analyses are largely described by Ivan et al. (2011).

Walleye have been stocked in Saginaw Bay since 1980, and hence, our historical analyses of walleye covered the period 

1980-2008. During this time period, we found weak evidence of density-dependent controls on walleye growth. That 

is, while the mean lengths of young (ages 0-2) walleye cohorts in the fall were negatively associated with the relative 

abundances of these cohorts, these relationships were weak and insignificant. In addition, our analyses suggest that 

walleye year-class strength (both in terms of abundance and mean size) are set by fall of age 0. Relative abundances of 

age-0 walleye were strongly, positively related to the relative abundances of age-1 and age-2 walleye 1 and 2 years in 

the future, respectively. Similarly, mean lengths of age-0 walleye were strongly, positively related to the mean lengths of 

age-1 and age-2 walleye 1 and 2 years in the future, respectively. In short, these analyses suggest that factors influencing 

growth and survival of walleye before fall of their first year of life are strong determinants of year-class strength (Table 

4.1).

Our analyses suggest that for the period 1970-2008, growth of young yellow perch cohorts in Saginaw Bay are negatively 

related to density of a particular cohort (particularly strong correlations for ages 0 and 2), suggesting that growth is 

influenced by compensatory density-dependence. Moreover, these analyses suggest that yellow perch year-class strength 

(both in terms of abundance and mean size) are set by fall of age 1. That is, for the period 1970-2008 the relative 

abundance and mean length of age-1 yellow perch were strongly, positively related to the relative abundance and mean 

length (respectively) of age-2 yellow perch the following year. In contrast, while relative abundance and mean length of 

age-0 yellow perch were positively related to the relative abundance and mean length (respectively) of age-1 yellow perch 

the follow year, relative abundance and mean length of age-0 yellow perch were unrelated to relative abundance and mean 

length of age-2 yellow perch 2 years later. In short, these analyses suggest that factors influencing growth and survival 
41

of yellow perch before fall of their first year of life are insufficient to explain subsequent year-class strength; however, 

processes occurring before fall of their second year of life do seem to define year-class strength (Table 4.1).

Table 4.1 - From Ivan et al. (2011): Age-specific correlations of walleye and yellow perch surveyed through the Michigan 

DNR’s annual trawling surveys in Saginaw Bay. (a) Yellow perch display strong compensatory density-dependent effects 

on growth, while such effects are weaker for walleye. (b-c) Year-class strength (b) in terms of mean length; (c) in terms of 

abundance) of walleye are set by fall of age-0, while year-class of perch appear to be set by fall of age-1.

Walleye (1980-2008) Yellow perch (1970-2008)

a) Correlations between annual age-specific mean CPUE and mean length.

age-0 -0.44 -0.53*

age-1 -0.28 -0.18

age-2 -0.10 -0.65*

b) Correlations between annual age-specific mean lengths [age (x) in year (t) vs. age (x+1) in year (t+1)].

age-1 age-2 age-1 age-2

age-0 +0.64* +0.70* +0.66* +0.04

age-1 +0.62* +0.78*

c) Correlations between annual age-specific CPUE [age (x) in year (t) vs. age (x+1) in year (t+1)].

age-1 age-2 age-1 age-2

age-0 +0.64* +0.79* +0.35* +0.18

age-1 +0.72* +0.78*

Analyses of these long-term time series may provide insights to factors structuring past recruitment of walleye and 

yellow perch in Saginaw Bay. Fielder et al. (2007) evaluated the effects of various potential biological and physical 

determinants of walleye recruitment (based on MDNR fall trawling surveys) and suggested that from 1993 to 2005, adult 

alewife abundance in Lake Huron was the single best predictor of walleye recruitment (fall abundance of age-0 walleye). 

We conducted similar analyses evaluating yellow perch recruitment during the period 1970-2008. Since yellow perch 

recruitment seems to be set by fall of age-1, we used relative abundance of age-1 yellow perch in fall trawling surveys as 

a measure of recruitment. In addition, we developed models to explain variation in age-0 yellow perch production. Longterm (i.e., 1970-present) annual environmental data are lacking for Saginaw Bay, and we were thus limited in the number 

of explanatory variables we could consider. We used annual measures of temperature and model-derived estimates of 

P loading and flow rates in the Saginaw River as potential environmental explanatory variables, and we used spawning 

stock biomass (SSB) of female yellow perch as a measure of spawning stock size (Figure 4.1). In addition, we considered 

non-stationarity in recruitment models by evaluating potential models with different parameters for separate blocks of 

years. Ultimately, models including such non-stationarity were far more successful at describing variation in yellow 

perch production and recruitment than models assuming fixed model parameters and models incorporating the influence 

of environmental variables. Specifically, since 1995, yellow perch production and recruitment appear to be influenced 

by differential processes than earlier time periods (Figure 4.2). In addition, during these later years, the spawning stock 

biomass of yellow perch in Saginaw Bay has been consistently low. On the one hand, this may be of concern given that 

low SSB has been accompanied with poor recruitment of age-1 yellow perch. On the other hand, the recent time period 

has been characterized by relatively high abundances of age-0 yellow perch, suggesting that low SSB is not a key limiting 

factor in production of young yellow perch.

Field Surveys: From April 2009 through June 2011, we conducted extensive field collections in Saginaw Bay. These 

surveys targeted a number of different research questions and aspects of the Saginaw Bay ecosystem (described elsewhere 

in this report). In terms of walleye and yellow perch, field surveys were designed to track two annual cohorts (2009 and 

2010) from just after hatching through survival to the following spring. We aimed to describe the prey base underlying 
42

Figure 4.2 - (A) Production of age-0, and (B) 

recruitment of age-1 yellow perch in Saginaw 

Bay, including observed CPUE (Obs: 

mean catch per minute of fall assessment 

trawling by the Michigan DNR), predicted 

(based on Ricker stock-recruitment model 

with spawning stock biomass as the sole 

predictor), and best model (based on Ricker 

stock-recruitment model with spawning stock 

biomass as predictor and assuming nonstationarity).

Figure 4.1 - Spawning stock 

biomass of yellow perch in 

Saginaw Bay, 1970-2011.
43

walleye and yellow perch production in the altered Saginaw Bay ecosystem and identify potential impediments to early 

life survival for young percids.

Walleye: During both 2009 and 2011, we initially collected young walleye near the mouth of the Saginaw River (Figure 

4.3). This is a relatively warm area of inner Saginaw Bay, and a past study indicated that the Tittabawasee River (a 

tributary to the Saginaw) was the major contributor of walleye recruits to Saginaw Bay (Fielder 2002). Hence, initial 

detection of young walleye in this area was not surprising. However, in subsequent weeks, we also collected young, 

recently hatched larvae (2 days or less post-hatch based on otolith increment counts) in other areas of Saginaw Bay. Some 

initial simulations using hydrodynamics and particle transport models suggest that it is highly unlikely that young walleye 

collected in these other areas would have originated from the Saginaw River, suggesting that other habitats are also 

potentially important contributors of walleye recruits.

Young walleye grew rapidly from larvae to juveniles. Larval walleye fed on a diversity of zooplankton prey, with 

cladocerans and dreissenid veligers serving as important prey (Figure 4.4). Juvenile walleye transitioned from feeding 

primarily on zooplankton, to larger invertebrates (predatory zooplankton, Bythotrephes and Leptodora; and benthic 

invertebrates, Chironomidae), and then fish (rainbow smelt, shiners and round goby; Figure 4.5). A dearth of previous data 

makes it difficult to compare young walleye diets to historical Saginaw Bat diet patterns. However, observed diet patterns 

of both larval and later-stage age-0 walleye were roughly consistent with diets observed in other systems. Of note, we 

found that relatively-recent invasive species (Bythotrephes and round goby) were important diet components for young 

walleye. Moreover, we found that yellow perch constituted a relatively unimportant diet component for age-0 walleye. 

As adults (age-1 and older), walleye fed almost exclusively on fish (primarily round goby, yellow perch, shiners, and 

rainbow smelt; Figure 4.6). In contrast to age-0 walleye, young yellow perch were a more important prey for age-1+ 

walleye, particularly during the summer when young perch represented 60% (by number) of fish prey in walleye diets. 

During other seasons, yellow perch were less common in walleye diets and in both spring and fall, round goby was the 

most common prey in age-1+ walleye diets (41% and 60%, respectively). The importance of round goby as walleye 

prey is noteworthy as this relatively-recent invader has become a key forage species, seemingly supporting the walleye 

population in a manner similar to alewife before their crash.

Yellow perch: During both 2009 and 2010, we initially collected larval yellow perch in far inner Saginaw Bay (a relatively 

warm area near the mouth of the Saginaw River). Subsequently, we collected recently hatched larval yellow perch (2 

Figure 4.3 - CPUE (number 

1000 m-3) of larval walleye 

caught in bongo tows by 

week for 2009 and 2010. In 

2009 and 2010, larvae first 

appeared near the mouth 

of the Saginaw River before 

distributing throughout 

the Bay. Spring 2010 was 

warmer than 2009, and in 

turn, walleye larvae emerged. 

During both years, young 

larvae less than two days 

old were caught far from the 

Saginaw River.
44

Figure 4.4 - Diets 

of larval walleye in 

Saginaw Bay, 2009 and 

2010. Larvae began 

exogenous feeding at 

approximately 9 mm and 

fed on a diversity of taxa 

through the larval stage.

Figure 4.5 - Diets of young of year (YOY) walleye in Saginaw Bay 2009 and 2010.

a. YOY walleye diet composition for all taxa by counts. Predatory zooplankton, primarily non-native Bythotrephes, and 

fishes became important as walleye transitioned from herbaceous zooplankton. Walleye shifted to piscivory in early fall 

as fish dominated diets by September in terms of biomass.

b. Composition of fishes in YOY diets by counts. Young walleye relied on various fish prey, including non-native gobies. 
45

Figure 4.6 - Diets 

of age-1 and 

older walleye in 

Saginaw Bay 2009 

and 2010.

days or less post-hatch based on otolith increment counts) from throughout inner Saginaw Bay. The emergence of yellow 

perch was rather prolonged during both years (Figure 4.7). Larval yellow perch ate a fairly diverse diet of small-bodied 

zooplankton, with cyclopoid copepods, calanoid copepods, and nauplii all serving as important prey (Figure 4.8). Most 

larval yellow perch diets we examined had some prey in their digestive tract (in contrast to some systems where empty 

larval digestive tracts are relatively common). In turn, larval yellow perch grew at a relatively fast rate (~0.3 mm d-1 from 

hatch to 20 days post-hatch; Figure 4.9).

Later-stage age-0 yellow perch (collected via trawling from July-November) expanded their diet to include more diverse 

prey, including larger bodied zooplankton and benthic invertebrates. Based on diet biomass, Daphnia represented the most 

common zooplankton prey, followed by calanoid copepods and Bythotrephes, while Chironomidae larvae represented the 

most common benthic prey, followed by Chydoridae. Surprisingly, we did not find evidence of strong ontogenetic niche 

shifts from zooplankton to larger-bodied benthic prey (as has been documented in other sytsems). Instead, zooplankton 

constituted the main prey for age-0 yellow perch from July-November during both study years. We did, however, find 

evidence of strong spatial differences, with site SB-10 primarily supporting benthic-feeding age-0 yellow perch and site 

SB-5 supporting primarily zooplanktivores (Figure 4.10).

Similar to larval yellow perch, older age-0 yellow perch maintained fairly rapid growth during early summer (JulyAugust). Their growth then slowed in late summer and fall (Figure 4.9). This seasonal decline was evident for both growth 

in biomass and growth in total body energy. Moreover, the decline in growth appeared to occur before seasonal drops 

in water temperatures in inner Saginaw Bay. On the one hand, this suggests that declining growth may reflect feeding 

habits of young yellow perch; perhaps continued consumption of small-bodied zooplankton prey leads to seasonally slow 

growth. On the other hand, slower growth later in life may simply reflect the allometry of consumption and metabolism, 

whereby the potential for growth may decline precipitously as young yellow perch increase in size.

While it is not entirely clear why growth of young yellow perch slowed down in late summer and early fall, it is clear 

that smaller yellow perch are more susceptible to mortality, and hence slow growth could contribute to poor survival. We 

found that the mean lengths of young yellow perch in the environment (collected via trawling) were consistently lower 

than the mean lengths of young yellow perch found in the stomachs of piscivorous walleye; suggesting that the smallest 
46

indivdiuals were most likely to be consumed by predators (Figure 4.9). In addition, when comparing length distributions 

and total body energies of young yellow perch just prior to winter (October-November) versus after winter (age-1 yellow 

perch in April-early June), we documented an increase in mean size of yellow perch and a 20% drop in length-specific 

total body energy (Figure 4.11). Thus, young yellow perch lose a great deal of energy over winter, which could contribute 

to size-dependent mortality. That is, smaller yellow perch may be more likely to die over winter due to lower energy stores 

and higher mass-specific metabolism, leading to starvation and/or necessitating risky feeding behavior.

4.3 Knowledge/Data Gaps – Research Needs

Collapse of alewife in Lake Huron appears to have released young walleye in Saginaw Bay from predatory and 

competitive control. In turn, young walleye now appear to survive well during early life and are entirely supported by 

Figure 4.7 - CPUE (number m-3) of larval yellow perch caught in bongo tows during sampling weeks in 2009 and 2010.
47

Figure 4.9 - Lengths of larval 

and juvenile yellow perch 

collected in bongo nets and 

trawls (circles) in Saginaw 

Bay during 2009 and 2010. 

Lengths of yellow perch 

found in walleye stomachs 

are depicted with “+”, and 

asterisks indicate weeks 

when lengths of yellow 

perch ion walleye stomachs 

were significantly lower than 

trawl-caught yellow perch (2 

sample t-test).

Figure 4.8 - Diets of larval yellow perch in Saginaw Bay by 

sampling week in 2009 and 2010.
48

natural reproduction. Nonetheless, under this new regime, there must be limits to walleye production in Saginaw Bay. 

For example, spawning habitat may now limit walleye production. In the 1990’s, most natural production of walleye

in Saginaw Bay appeared to come from the Tittabawasee River (a tributary to the Saginaw River; Fielder 2002). Our 

collections (and studies by other researchers) suggest that walleye larvae are now emerging in other areas, likely including 

other Saginaw Bay river systems. Historically, walleye likely also spawned on reefs in Saginaw Bay; however, it is an 

open question if reefs are important contributors of larval walleye in the new regime. We suggest that future studies should 

evaluate the contributions of walleye from different habitats in Saginaw Bay.

Walleye transition through diverse diets as larvae, juvenile, and adults. As larvae and later stage age-0, walleye rely on 

invertebrates including herbaceous zooplankton, predatory zooplankton (invasive Bythotrephes) and, to a lesser extent, 

benthic invertebrates. However, by the end of their first year of life, walleye have transitioned to an entire piscine diet. 

While alewives were an important fish prey for walleye in the past, walleye now utilize a diversity of prey (shiners, smelt, 

round goby, yellow perch), with key diet contributors changing seasonally. Yellow perch were largely absent in diets of 

age-0 walleye, but they were important diets components for age-1 and older walleye. As a whole, however, soft-rayed 

fishes including shiners and most importantly, round goby, now constitute the walleye forage base. Nonetheless, we 

suggest that this forage base may be undergoing transition. Alewife relatively recently collapsed, round goby are fairly 

recent invaders, high age-0 yellow perch production may not continue indefinitely, and additional forage fish (e.g., lake 

herring) may be stocked into Saginaw Bay in the future. Moreover, continued species invasions and environmental (e.g., 

Figure 4.10 - Diets of young-of-year yellow perch by sampling location in Saginaw Bay, 2009 and 2010.
49

Figure 4.11 - Total length (mm) and 

total body energy (J) of age-0 yellow 

perch collected in the fall (filled 

circles) and age-1 yellow perch 

the following spring (open circles). 

Yellow perch lost ~20% of body 

energy over winter (based on lengthspecific comparisons).

changes in nutrient loading and sedimentation) and physical (e.g., climate change) changes to the Saginaw Bay ecosystem 

may favor certain types of small-bodied fish species. Potential resulting shifts in the forage base may lead to changes 

in the type of prey supporting walleye production. In turn, this may have implications for maintenance of the current 

large Saginaw Bay walleye population and sustainability of small-bodied fish species. Such effects may be difficult to 

anticipate, and we suggest: (1) a need to continue monitoring of the forage base supporting walleye production in Saginaw 

Bay throughout the year, and (2) development and application of models to evaluate plausible responses of walleye and 

forage fish populations to potential future ecosystem changes.

Many potential factors limiting yellow perch recruitment in Saginaw Bay remain unknown. As described above, since 

1995, yellow perch production (age-0 abundance) and recruitment (to age-1) in Saginaw Bay appear to be structured 

differentially than during earlier time periods. In addition, during recent years, spawning stock biomass of yellow perch 

has remained at the lowest levels during the period of record (since 1970). While, this low spawning stock may be a factor 
50

contributing to poor recruitment of yellow perch, high abundances of age-0 yellow perch in recent years suggest that 

spawning stock size may not be the sole limiting factor. Instead, high predation on age-0 yellow perch by the burgeoning 

walleye population, coupled with slow growth by later stage age-0 yellow perch (leading to increased susceptibility to 

predation and overwinter mortality), may also be important factors contributing to poor recruitment. Perhaps, greater 

overall production of age-0 yellow perch is now necessary to swamp the predation pressure exerted by the walleye 

population and lead to high numbers of age-1 yellow perch recruits. Future studies should evaluate these balances between 

walleye predation pressure, young yellow perch growth, density-dependence, and recruitment. Again, we suggest that 

linked population models should provide a unique mechanism to effectively consider the interactions of these different 

processes. 

4.4 Management Implications

Walleye spawning habitat may now be a limiting factor for production. Moreover, even if there is sufficient spawning 

habitat, population sustainability may benefit by partitioning spawning among multiple, diverse habitats. That is, walleye 

recruitment success displays high inter-annual variation, and heterogeneity in spawning may temper such variation by 

increasing the breadth of environmental conditions experienced by spatially-distinct young walleye during a particular 

year. In Saginaw Bay, walleye spawning may be diversified by increasing the availability of spawning habitats in rivers 

and/or reefs. Many Saginaw Rivers are dammed, limiting passage of walleye to potentially suitable upstream spawning 

habitats. While removal of dams could alleviate such blockages, dam removal may also lead to various deleterious effects 

(e.g., downstream sediment release, increased contaminant flux, and upstream movement of invasive species [round 

goby, sea lamprey]). Moreover, walleye in Saginaw Bay are already thought to primarily spawn in rivers, and additional 

river spawning habitat may not provide environmental conditions fundamentally different from existing spawning 

environments (and hence, may not temper inter-annual recruitment variation). Instead, we suggest that Saginaw Bay 

reef restoration represents a particularly worthwhile approach for expanding walleye spawning habitat. Reef spawning 

habitat could provide a substantially different spawning environment from river habitats (different thermal conditions 

leading to temporally offset spawning and emergence; dissimilar incubation conditions; and no long-distance, downstream 

transport). Thus, we suggest that Saginaw Bay management agencies should explore the potential for reef restoration.

Historically, Saginaw Bay likely supported both large walleye and yellow perch populations. However, high predation 

pressure by walleye may now be a factor contributing to low yellow perch recruitment; potentially coupled with a slow 

growth of later-stage age-0 yellow perch and a low perch spawning stock biomass. Potential management actions to 

overcome these bottlenecks could include increased harvest of walleye (thereby decreasing predation pressure on yellow 

perch), decreased harvest of yellow perch (thereby increasing spawning stock biomass of yellow perch), or establishment 

of another forage fish population to divert predation pressure from yellow perch. The ultimate effects of any of these 

actions are unfortunately unknown. Increased harvest rates of walleye have the potential to deleteriously impact the 

walleye population (especially if recruitment success decreases in the future), and decreased harvest of yellow perch will 

have social and economic impacts on the commercial and recreational fishers that exploit this population. Introduction 

of a new, native forage fish (e.g., lake herring) could decrease predation pressure on yellow perch, but to a large extent, 

round goby are already serving as a predation buffer on yellow perch. Moreover, it is unclear if walleye would select a 

novel forage fish as prey in favor of yellow perch (e.g., young lake whitefish are present in Saginaw Bay, but were absent 

from walleye diets). In short, the most suitable management actions are unknown, and we suggest that Saginaw Bay 

fisheries managers should take an adaptive approach to build the yellow perch population: establish a management action 

and then monitor responses of populations of interest.
51

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