SELECTION OF ZOOPLANKTON PREY BY LARVAL YELLOW PERCH ACROSS
MULTIPLE LAKE SYSTEMS
By
Darrin Eugene McCullough

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Fisheries and Wildlife – Master of Science
2017

ABSTRACT
SELECTION OF ZOOPLANKTON PREY BY LARVAL YELLOW PERCH ACROSS
MULTIPLE LAKE SYSTEMS
By
Darrin Eugene McCullough
Yellow perch Perca flavescens are widely distributed across North America where they
inhabit a variety of aquatic ecosystems, playing an ecologically and economically significant role
as both predator and prey. Like many fishes, successful recruitment of yellow perch depends on
the availability of suitable densities and sizes of zooplankton prey at critical early life history
periods. Thus, evaluation of prey selection may lend insight into processes driving year class
strength. In order to assess prey selectivity, we collected larval yellow perch and zooplankton
samples across a variety of inland lakes in Michigan’s Lower Peninsula. The size structure of
zooplankton taxa (e.g. Bosmina spp., cyclopoid copepods) was quite consistent across multiple
system types, but zooplankton densities varied widely both within and between lakes. Selection
for prey type and size varied in relation to fish size, but remained relatively consistent between
eutrophic, mesotrophic and oligotrophic lakes. In my study lakes, I concluded that rotifers were
not an important first food of larval yellow perch and analysis of prey selection patterns is
confounded by a summative interaction of morphological limitations of the predators with
behavioral preference for specific prey types within prey size classes. Additionally, I
demonstrated that large numbers of samples were necessary to improve the level of confidence in
measuring prey availability (e.g. density, species composition).

Copyright by
DARRIN EUGENE MCCULLOUGH
2017

ACKNOWLEDGEMENTS

My gratitude goes to the Michigan Department of Natural Resources and the Robert C.
Ball and Betty A. Ball Michigan State University Fisheries and Wildlife Graduate Fellowship
who provided funding for this research project.
I would like to thank Dr. Daniel Hayes, Dr. Michael Jones, Dr. Mary Tate Bremigan, and
Dr. Ed Roseman for their contribution to this project. Their expertise of ‘all things fisheries’ and
provision of constructive feedback and mentorship has been foundational to the success of this
study. Thank you Dan, Mike, Mary, and Ed for your support and contribution to my research.
I would also like to express gratitude to Jason Smith, Elle Gulloty, Corrine Higley, Mitch
Nisbet, Kelley Smith, Andrew Powlaski, Zach Fyke, Ben Bejcek, Katie Kierczynski, Brandon
Bergen, and Xinzhing Han (A.K.A. Hammer) for their assistance in the field and laboratory.
Their many hours spent collecting samples in the bow of the boat along with identifying
ichthyoplankton and zooplankton on the microscope yielded volumes of useful data for this
project. I could not have completed the process of organism identification and enumeration
without all of your help.
Lastly, I thank my wife Jennifer, son Mark, and canine amigo Tag-A-Long for all the
sacrifice they have made to support my pursuit of an education. Without your unyielding love
and support, I would have abandoned this adventure long ago.

iv

TABLE OF CONTENTS

LIST OF TABLES ......................................................................................................................... vi
LIST OF FIGURES ..................................................................................................................... viii
INTRODUCTION ...........................................................................................................................1
METHODS ................................................................................................................................6
Study Area .............................................................................................................................6
Ichthyoplankton Collection .................................................................................................10
Zooplankton Collection .......................................................................................................14
Diet Analysis .......................................................................................................................16
Sample Size Analysis ..........................................................................................................17
Selectivity Data Analysis ....................................................................................................19
Establishing Patterns of Selection .......................................................................................20
RESULTS ................................................................................................................................21
Zooplankton communities ...................................................................................................21
Zooplankton sample size analysis .......................................................................................24
Summary of larval traits and diet ........................................................................................28
Overall taxon-specific selection ..........................................................................................33
Individual taxon-specific selection ......................................................................................34
Summary of taxon-specific selection ..................................................................................44
Overall prey size-specific selection .....................................................................................45
Individual prey size-specific selection ...............................................................................50
Summary of prey size-specific selection ............................................................................61
DISCUSSION ..........................................................................................................................63
Zooplankton ........................................................................................................................63
Selection ..............................................................................................................................66
CONCLUSION ........................................................................................................................70
APPENDIX ………………………………………………………………………………….72
BIBLIOGRAPHY ……………………………………………………………………………………………………………………….98

v

LIST OF TABLES

Table 1. Characteristics of study lakes. Lake trophic status was inferred from Secchi disk
readings where oligotrophic is >5 m, mesotrophic 2-5 m, and eutrophic <2 m (Secchi depth
ranges taken from 2007 Michigan Inland Lakes Assessment Report, MDEQ 2010). Lake area
and maximum depths were taken from USGS spatial database (http://miwebmapper.er.usgs.gov).
N (Days) represents the number of sampling events across all years of the study………………10
Table 2. Estimate of required zooplankton sample size necessary to attain various relative
precision of the mean estimates for total zooplankton densities among tow groups……………25
Table 3. Estimate of required zooplankton sample size necessary to attain various relative
precision of the mean estimates for copepod nauplii densities among tow groups…….........…..26
Table 4. Estimate of required zooplankton sample size necessary to attain various relative
precision of the mean estimates for cyclopoid copepod densities among tow groups ………….27
Table 5. Estimate of required zooplankton sample size necessary to attain various relative
precision of the mean estimates for Bosmina spp. total densities among tow groups………...…27
Table 6. Summary of total larvae processed, total with empty guts, and proportion of total empty
guts by lake trophic state. Size ranges provided in mm………………………………………….29
Table A1. Mean number of zooplankton per liter with Standard Error (SE) of the mean, and
number of samples collected and analyzed (N) for each lake-day sampling event….…………..73
Table A2. Proportions of available zooplankton prey (Pi) by taxa for eutrophic systems with the
mean, minimum (Min), and maximum (Max) proportion…………………………………..…...76
Table A3. Proportions of available zooplankton prey (Pi) by taxa for mesotrophic systems with
the mean, minimum (Min), and maximum (Max) proportion……………………………...……77
Table A4. Proportions of available zooplankton prey (Pi) by taxa for oligotrophic systems with
the mean, minimum (Min), and maximum (Max) proportion…………………………………...78
Table A5. Proportions of available zooplankton prey (Pi) by size for eutrophic systems with the
mean, minimum (Min), and maximum (Max) proportion……………………………………….79
Table A6. Proportions of available zooplankton prey (Pi) by size for mesotrophic systems with
mean, minimum (Min), and maximum (Max) proportion……………………………..………...80
Table A7. Proportions of available zooplankton prey (Pi) by size for oligotrophic systems with
mean, minimum (Min), and maximum (Max) proportion……………………………………….81

vi

Table A8. Number of fish processed (N) per lake-day sampling event with number of empty
larval stomachs, mean total length (TL), standard error (SE) of total length, minimum size of
larvae (Min), and maximum length of larvae (Max)………………………………………..…...82
Table A9. Mean number of major zooplankton taxa groups per larval gut by date with Standard
Error (SE) of the mean, and number of samples collected and analyzed (N) for each lake-day
sampling event…………………………………………………………………………………...86
Table A10. Average proportion of zooplankton prey (Pi) taxa per larval gut by lake-day combo
for eutrophic systems with the mean, minimum (Min), and maximum (Max) proportion……....89
Table A11. Average proportion of zooplankton prey (Pi) taxa per larval gut by lake-day combo
for mesotrophic systems with the mean, minimum (Min), and maximum (Max) proportion…...90
Table A12. Average proportion of zooplankton prey (Pi) taxa per larval gut by lake-day combo
for oligotrophic systems with the mean, minimum (Min), and maximum (Max) proportion…...91
Table A13. Mean number of major zooplankton size groups per larval gut by date with Standard
Error (SE) of the mean, and number of samples collected and analyzed (N) for each lake-day
sampling event………………………………………………………………………………...…92
Table A14. Average proportion of zooplankton prey (Pi) size group per larval gut by lake-day
combo for eutrophic systems with the mean, minimum (Min), and maximum (Max)
proportion………………………………………………………………………………………...95
Table A15. Average proportion of zooplankton prey (Pi) size group per larval gut by lake-day
combo for mesotrophic systems with the mean, minimum (Min), and maximum (Max)
proportion……………………………………………………………………………………...…96
Table A16. Average proportion of zooplankton prey (Pi) size group per larval gut by lake-day
combo for oligotrophic systems with the mean, minimum (Min), and maximum (Max)
proportion………………………………………………………………………………...………97

vii

LIST OF FIGURES

Figure 1. Size distribution and trophic status of study lakes. Black shade depicts eutrophic lakes,
gray shade depicts mesotrophic lakes, and white box depicts oligotrophic lakes...………………8
Figure 2. Location, relative size, and trophic status of study lakes. Diamonds represent small
lakes (<4 km^2), circles represent medium lakes (4 to 25 km^2), and triangles represent large
lakes (25 to 82 km^2). Solid symbols represent eutrophic systems, shaded symbols represent
mesotrophic systems, and open symbols represent oligotrophic systems. ......................................9
Figure 3. Representative 2014 sampling event from Park Lake. Open circles represent location of
vertical zooplankton tows. Solid lines represent location and relative distance of horizontal
ichthyoplankton trawls. The combination of one zooplankton tow and one ichthyoplankton trawl
is considered a ‘Tow Group’..........................................................................................................12
Figure 4. Representative 2015 sampling event from Park Lake. Open circles represent location of
vertical zooplankton tows. Solid lines represent location and relative distance of horizontal
ichthyoplankton trawls. The set of three zooplankton tows and one ichthyoplankton trawl broken
in half is considered a ‘Tow Group’. .............................................................................................13
Figure 5. Total proportions of environmental prey by taxa across all oligotrophic lakes,
mesotrophic lakes, and eutrophic lakes..................................................................................…...22
Figure 6. The total proportions of environmental prey by size for oligotrophic lakes, mesotrophic
lakes, and eutrophic lakes. ……………………………………………………………………....23
Figure 7. Proportions of environmental zooplankton prey size by taxon. Environmental
zooplankton prey grouped into 0.05 mm bins and plotted as total proportion for all lakes…......24
Figure 8. Total number and size distribution of larval and early juvenile yellow perch processed
across all lakes and years. Dark shade depicts larvae with empty stomachs. Light shade depicts
larvae with diet items present in gut…………………………………………………………..…29
Figure 9. The total proportions of zooplankton prey taxa groups within larval guts by lake-day
combo for oligotrophic lakes, mesotrophic lakes, and eutrophic lakes……………………….....31
Figure 10. The total proportions of zooplankton prey size groups within larval guts by lake-day
combo for oligotrophic lakes, mesotrophic lakes, and eutrophic lakes………………………….32
Figure 11. Chesson’s Rescaled Index of selection of zooplankton prey by larval and early
juvenile yellow perch for major taxonomic group. Filled circles represent a single selectivity
value by combining all fish diets in a given lake-day combination. Shaded triangles represent
overall mean selectivity. Zero represents neutral selection, 1.00 represents complete positive
selection, and -1.00 represents complete negative selection…………….……………………….34

viii

Figure 12. Chesson’s Rescaled Index of selection for copepod nauplii by larval and early
juvenile yellow perch. Circles represent individual selectivity from eutrophic lakes. Plus symbols
represent individual selectivity from mesotrophic lakes. Triangles represent individual selectivity
from oligotrophic lakes. Solid line depicts LOESS function fit to all data with gray band
representing 95% confidence interval of the mean………………….…………..………..……..35
Figure 13. LOESS functions with 95% Confidence Intervals relating taxon-specific selectivity
for copepod nauplii as a function of larval and early juvenile yellow perch length as influenced
by system specific trophic status. Solid lines represent eutrophic systems, dashed lines represent
mesotrophic systems, and dotted lines represent oligotrophic systems…………………..……...36
Figure 14. Chesson’s Rescaled Index of selection for cyclopoid copepods by larval and early
juvenile yellow perch. Circles represent individual selectivity from eutrophic lakes. Plus symbols
represent individual selectivity from mesotrophic lakes. Triangles represent individual selectivity
from oligotrophic lakes. Solid line depicts LOESS function fit to all data with gray band
representing 95% confidence interval of the mean. ………………………………………...…...37
Figure 15. LOESS functions with 95% Confidence Intervals relating taxon-specific selectivity
for cyclopoid copepods as a function of larval and early juvenile yellow perch length as
influenced by system specific trophic status. Solid lines represent eutrophic systems, dashed lines
represent mesotrophic systems, and dotted lines represent oligotrophic systems. …………...…38
Figure 16. Chesson’s Rescaled Index of selection for calanoid copepods by larval and early
juvenile yellow perch. Circles represent individual selectivity from eutrophic lakes. Plus symbols
represent individual selectivity from mesotrophic lakes. Triangles represent individual selectivity
from oligotrophic lakes. Solid line depicts LOESS function fit to all data with gray band
representing 95% confidence interval of the mean………………………………………………39
Figure 17. LOESS functions with 95% Confidence Intervals relating taxon-specific selectivity
for calanoid copepods as a function of larval and early juvenile yellow perch length as influenced
by system specific trophic status. Solid lines represent eutrophic systems, dashed lines represent
mesotrophic systems, and dotted lines represent oligotrophic systems……………….…………40
Figure 18. Chesson’s Rescaled Index of selection for Bosmina spp. by larval and early juvenile
yellow perch. Circles represent individual selectivity from eutrophic lakes. Plus symbols
represent individual selectivity from mesotrophic lakes. Triangles represent individual selectivity
from oligotrophic lakes. Solid line depicts LOESS function fit to all data with gray band
representing 95% confidence interval of the mean………………………………………………41
Figure 19. LOESS functions with 95% Confidence Intervals relating taxon-specific selectivity
for Bosmina spp. as a function of larval and early juvenile yellow perch length as influenced by
system specific trophic status. Solid lines represent eutrophic systems, dashed lines represent
mesotrophic systems, and dotted lines represent oligotrophic systems………………………….42
Figure 20. Chesson’s Rescaled Index of selection for Daphnia spp. by larval and early juvenile
yellow perch. Circles represent individual selectivity from eutrophic lakes. Plus symbols

ix

represent individual selectivity from mesotrophic lakes. Triangles represent individual selectivity
from oligotrophic lakes. Solid line depicts LOESS function fit to all data with gray band
representing 95% confidence interval of the mean………………………………………......…..43
Figure 21. LOESS functions with 95% Confidence Intervals relating taxon-specific selectivity
for Daphnia spp. as a function of larval and early juvenile yellow perch length as influenced by
system specific trophic status. Solid lines represent eutrophic systems, dashed lines represent
mesotrophic systems, and dotted lines represent oligotrophic systems………………………….44
Figure 22. Summary of LOESS functions relating taxon-specific selectivity as a function of
larval and early juvenile yellow perch length……………………………………………………45
Figure 23. Length of prey found in larval and early juvenile yellow perch guts as a function of
fish length. Open circles represent individual diet items. Solid line represents LOESS function fit
with gray band representing 95% confidence interval of the mean……………………………...46
Figure 24. Length of prey found in larval and early juvenile yellow perch guts as a function of
fish gape. Open circles represent individual diet items. Solid blue line represents 1:1 ratio of fish
gape to prey length. Solid black line represents LOESS function fit with gray band representing
95% confidence interval of the mean. Gape size estimated using the following literature based
regression. Gape=0.159(Total length)-0.597. (Schael et al. 1991)………………………………47
Figure 25. Ratio of prey length to gape as a function of fish length. Open circles represent the
ratio for individual diet items. Solid line represents LOESS function fit with gray band
representing 95% confidence interval of the mean………………………………………………48
Figure 26. Chesson’s Rescaled Index of selection of zooplankton prey by larval and early
juvenile yellow perch as a function of prey size category. Filled circles represent a single
selectivity value by combining all fish diets in a given lake-day combination. Shaded triangles
represent overall mean selectivity. Zero represents neutral selection, 1.00 represents complete
positive selection, and -1.00 represents complete negative selection……………………………49
Figure 27. Chesson’s Rescaled Index of selection for zooplankton less than 0.2 mm by larval and
early juvenile yellow perch. Circles represent individual selectivity from eutrophic lakes. Plus
symbols represent individual selectivity from mesotrophic lakes. Triangles represent individual
selectivity from oligotrophic lakes. Solid line depicts LOESS function fit to all data with gray
band representing 95% confidence interval of the mean………………………………………...50
Figure 28. LOESS functions with 95% Confidence Intervals relating size-specific selectivity for
zooplankton less than 0.2 mm as a function of larval and early juvenile yellow perch length as
influenced by system specific trophic status. Solid lines represent eutrophic systems, dashed lines
represent mesotrophic systems, and dotted lines represent oligotrophic systems……………….51
Figure 29. Chesson’s Rescaled Index of selection for zooplankton 0.2 mm to less than 0.4 mm by
larval and early juvenile yellow perch. Circles represent individual selectivity from eutrophic
lakes. Plus symbols represent individual selectivity from mesotrophic lakes. Triangles represent

x

individual selectivity from oligotrophic lakes. Solid line depicts LOESS function fit to all data
with gray band representing 95% confidence interval of the mean……………………………...52
Figure 30. LOESS functions with 95% Confidence Intervals relating size-specific selectivity for
zooplankton 0.2 mm to less than 0.4 mm as a function of larval and early juvenile yellow perch
length as influenced by system specific trophic status. Solid lines represent eutrophic systems,
dashed lines represent mesotrophic systems, and dotted lines represent oligotrophic systems….53
Figure 31. Chesson’s Rescaled Index of selection for zooplankton 0.4 mm to less than 0.6 mm by
larval and early juvenile yellow perch. Circles represent individual selectivity from eutrophic
lakes. Plus symbols represent individual selectivity from mesotrophic lakes. Triangles represent
individual selectivity from oligotrophic lakes. Solid line depicts LOESS function fit to all data
with gray band representing 95% confidence interval of the mean……………………………...54
Figure 32. LOESS functions with 95% Confidence Intervals relating size-specific selectivity for
zooplankton 0.4 mm to less than 0.6 mm as a function of larval and early juvenile yellow perch
length as influenced by system specific trophic status. Solid lines represent eutrophic systems,
dashed lines represent mesotrophic systems, and dotted lines represent oligotrophic systems…55
Figure 33. Chesson’s Rescaled Index of selection for zooplankton 0.6 mm to less than 0.8 mm by
larval and early juvenile yellow perch. Circles represent individual selectivity from eutrophic
lakes. Plus symbols represent individual selectivity from mesotrophic lakes. Triangles represent
individual selectivity from oligotrophic lakes. Solid line depicts LOESS function fit to all data
with gray band representing 95% confidence interval of the mean……………………………...56
Figure 34. LOESS functions with 95% Confidence Intervals relating size-specific selectivity for
zooplankton 0.6 mm to less than 0.8 mm as a function of larval and early juvenile yellow perch
length as influenced by system specific trophic status. Solid lines represent eutrophic systems,
dashed lines represent mesotrophic systems, and dotted lines represent oligotrophic systems….57
Figure 35. Chesson’s Rescaled Index of selection for zooplankton 0.8 mm to less than 1.0 mm by
larval and early juvenile yellow perch. Circles represent individual selectivity from eutrophic
lakes. Plus symbols represent individual selectivity from mesotrophic lakes. Triangles represent
individual selectivity from oligotrophic lakes. Solid line depicts LOESS function fit to all data
with gray band representing 95% confidence interval of the mean……………………………...58
Figure 36. LOESS functions with 95% Confidence Intervals relating size-specific selectivity for
zooplankton 0.8 mm to less than 1.0 mm as a function of larval and early juvenile yellow perch
length as influenced by system specific trophic status. Solid lines represent eutrophic systems,
dashed lines represent mesotrophic systems, and dotted lines represent oligotrophic systems….59
Figure 37. Chesson’s Rescaled Index of selection for zooplankton greater than 1.0 mm by larval
and early juvenile yellow perch. Circles represent individual selectivity from eutrophic lakes.
Plus symbols represent individual selectivity from mesotrophic lakes. Triangles represent
individual selectivity from oligotrophic lakes. Solid line depicts LOESS function fit to all data
with gray band representing 95% confidence interval of the mean……………………………...60

xi

Figure 38. LOESS functions with 95% Confidence Intervals relating size-specific selectivity for
zooplankton greater than 1 mm as a function of larval and early juvenile yellow perch length as
influenced by system specific trophic status. Solid lines represent eutrophic systems, dashed lines
represent mesotrophic systems, and dotted lines represent oligotrophic systems…………….....61
Figure 39. Summary of LOESS functions relating prey size-specific selectivity as a function of
larval and early juvenile yellow perch length……………………………………………………62

xii

INTRODUCTION

Yellow perch Perca flavescens are widely distributed across North America and inhabit a
variety of lacustrine aquatic systems, ranging in size from 0.1 to 56,000 km2 (Jenkins and
Burkhead 1994), as well as riverine systems (McDonald et al. 2013) throughout their range. The
yellow perch is an economically important species in both Canadian and U.S. waters of the
Laurentian Great Lakes (Fielder and Thomas 2006; Michigan Department of Natural Resources
2013), providing significant income to commercial fisheries in both countries (Craig 2008).
Additionally, recreational anglers target yellow perch throughout the Great Lakes as well as
within inland waterbodies, contributing to local economies of nearby communities (Craig 2008).
The presence of healthy yellow perch populations are also used as an indicator of the overall
health of an ecosystem (Poe 1983), due to their ecologically important role as both predator and
prey species in aquatic food webs throughout their range (Fielder and Thomas 2006; Roswell et
al. 2014). Because of their socioeconomic (Craig 2008) and ecological (Roswell et al. 2014)
significance, tremendous effort has focused on increasing our understanding of the mechanisms
affecting the success of Great Lakes (Bremigan et al. 2003; Fulford et al. 2006a, 2006b; Farmer
et al. 2015) and inland yellow perch populations (Hayes and Taylor 1990; Schael et al. 1991).
Although much is known of yellow perch population dynamics, the processes influencing
recruitment success across different lake system types remains a key source of uncertainty.
Specifically, studies of the dynamics of yellow perch recruitment report similar broad trends in
life history across various lake system types. However, few evaluate and synthesize similarities
or differences found in the ecology of early life stages among a range of lake system types.

1

The early life history ecology of fishes plays an important role in fisheries recruitment
(Houde and Hoyt 1987; Houde 1989; Cushing 1990). Variability in the survival of larval fishes is
well-known to be a critical process driving year class strength (Sharp 1987). Larval survival of
not only yellow perch, but all fishes, is the result of dynamic interactions of biological and
environmental factors, such as larval predation (Fulford et al. 2006a), temperature fluctuations
(Clady 1976; Farmer et al. 2015), turbidity, and algal blooms (Manning et al. 2014).
Furthermore, ecologists have observed that brief critical periods in the early life history of many
fishes play especially important roles in recruitment success. For instance, the recruitment of
yellow perch has been shown to depend on the availability of suitable densities and sizes of
zooplankton prey during critical early life history periods (Dettmers et al. 2003). These critical
periods include the transition from endogenous nutrition, dependent on yolk sac viability and
larvae size, to development of the ability to sustain growth and life through exogenous feeding.
Additionally, adequate food sources are needed for rapid growth and development of the motor
skills that are necessary to seek, find, and capture prey, while at the same time evading predation.
Thus, zooplankton prey community characteristics can have far reaching consequences to
successful recruitment of yellow perch. For example, the invasion of Bythotrephes longimanus
(Barbiero and Tuchman 2004; Barbiero et al. 2009; Bunnell et al. 2011) to the Great Lakes
Basin, concurrent with changes in phytoplankton biomass resulting from invasive dreissenid
mussels (Nalepa et al. 2007; Barbiero et al. 2009) has effectively altered available food resources
throughout the Great Lakes region, including inland waterbodies, for all larval fishes during
these critical periods (Barbiero and Tuchman 2004; Vanderploeg et al. 2015; Kerfoot et al.
2016). These changes in zooplankton community structures, coupled with competition and
predation from exotics, such as rainbow smelt Osmerus mordax, alewife Alosa pseudoharengus

2

(Fulford et al. 2006a), and changing climatic conditions (Farmer et al. 2015), likely have resulted
in changes to the survival, growth, and recruitment of young yellow perch throughout inland lake
systems as well as areas within the Great Lakes (Fielder and Thomas 2006; Farmer et al. 2015).
One key component of the predator-prey relationship between larval yellow perch and
zooplankton is the process of prey selection. Prey selection is not only behavioral and occurs
when predators actively choose their prey, but for larval fishes, is also heavily dependent on
limitations imposed by their structural morphology and size. Larval fish size and morphology are
important components in predator-prey interactions and responsible for a larvae’s ability to
detect, encounter, capture, and consume prey. These components of feeding are apparent in all
organisms, including fish, mammals, and birds, when looking at predatory behavior in selection
of food items (Holling 1959a, 1959b, 1965). Specifically, characteristics such as visual acuity,
swimming ability, and swim speed limit a larval fish’s ability to detect and encounter prey as
well as avoid predation. Many larval fishes, such as yellow perch, bluegill Lepomis macrochirus,
and black crappie Pomoxis nigromaculatus are also gape-limited (Schael et al. 1991; Bremigan
and Stein 1994; Bremigan et al. 2003) in their ability to consume prey. Prey size also interacts
with a larvae’s visual acuity and its ability to search for and locate suitable sizes of microscopic
and transparent zooplankton prey. As such, the size and visibility of available prey types
regulates a larvae’s choice of prey types. Therefore, larval yellow perch prey choice may not
simply be determined by which prey are most abundant, but also by their ability to detect and
capture the prey.
Selective predation is defined as when the relative frequency of items found in a
predator’s gut is different than the relative frequency of available prey found in the environment
(Ivlev 1961; Chesson 1978). Furthermore, selective predation may occur for a variety of reasons,

3

as discussed above, but if specific prey types are relatively more energy rich than other prey
types due to larger size or higher lipid content, then the cost: benefit of capture will be lower and
selective behavior may be apparent where larval fish actively choose for specific taxa within
certain sizes of different prey types. Many approaches exist for determining a relative index of
selective predation, all of which look to describe the relationship between a predator’s diet and
the availability of prey in the environment. Early approaches include Ivlev's Electivity Index
(1961), Manly et al.'s Analysis of Selective Predation (1972), and Strauss's Linear Index of Food
Selection (1979). These methods for the analysis of prey selectivity aimed to identify significant
sources of error in the interpretation of food selection data and provided the foundation for
indices of selective predation. One of the most widely used methods among early life history
researchers to represent selection is Chesson’s Index of Selective Predation (Chesson 1978,
1983). This method is popular among researchers due to its ability to incorporate in the analysis
any number of prey types found in the environment, i.e. 2 through n prey types, as well as
compare selection indices among environments with different numbers of prey types.
Prior insight into yellow perch prey selection has mainly been derived from laboratory
studies (Letcher et al. 1996; Dettmers et al. 2003), studies of individual lake types (Schael et al.
1991) or portions of the Great Lakes, such as Green Bay (Bremigan et al. 2003), Saginaw Bay
(Roswell et al. 2013, 2014), and Southern Lake Michigan (Fulford et al. 2006b). In Wisconsin’s
Lake Mendota, researchers were able to explain variability in average prey size as limited by
predator gape size and noted the importance of copepod zooplankton to larval yellow perch,
black crappie and freshwater drum Aplodinotus grunniens (Schael et al. 1991). In Southern Lake
Michigan, researchers have documented consistent patterns of prey selection through a
combination of laboratory experiments, empirical models, and field samples (Fulford et al.

4

2006b) citing the importance of rotifers as well as other small zooplankton prey to the first
feeding period of larval yellow perch. In Lake Michigan’s Green Bay, researchers compared
prey selection through gut analysis of larval yellow perch to patterns of prey selection found in
Southern Lake Michigan and found copepod nauplii and cyclopoid copepods to be important for
larvae during first feeding periods (Bremigan et al. 2003). Additionally, they found gapelimitation to be an important predictor of selection for specific prey types. In Lake Huron’s
Saginaw Bay, a recent exploration of the importance of prey selection and availability
throughout the first year of life (Roswell et al. 2013, 2014) described the relationship between
the density and size of zooplankton prey with growth, survival, and successful recruitment of
yellow perch. Although these studies have explored relationships between larval success and
prey availability through both lab and field methods, there is currently a knowledge gap
regarding how general patterns of prey selection might vary across multiple system types, such
as Michigan’s inland waters.
Patterns observed to date have been specific to each researcher’s particular waterbody.
While there appears to be an expectation among researchers that generally similar patterns of
prey selectivity would occur across different system types, research completed to date does not
include a robust comparison of prey selection among different lake trophic categories. With the
wide range of lake trophic state among Michigan’s inland lakes – from oligotrophic to
eutrophic– it would be valuable to know whether prey selection patterns vary across this range.
Zooplankton community structure and density have been observed to vary across trophic
conditions (Patalas 1972), leading to differences in available prey fields. Moreover, water clarity
varies with trophic state, possibly leading to differences in prey selection through systematic
difference in detectability of prey (Vanderploeg et al. 2015).

5

The overall goal of this study was to evaluate patterns of prey selection by larval yellow
perch across multiple system types in inland lakes of Michigan’s Lower Peninsula. I hypothesize
that general overall patterns of prey selection for larval yellow perch exist and can be expected
regardless of system size or trophic state. Additionally, I hypothesize that selective predation by
larval yellow perch is primarily driven by larval fish morphology, i.e., gape limitation. While
some variation in selective predation may occur among different system types, I expect to see a
common pattern across different lake system types. However, if patterns of selective predation
depend partly on system type, then quantification of prey selection indices across multiple
system types will reveal system-specific patterns of prey selection that will be useful for future
assessments of yellow perch recruitment dynamics. Also, if larvae actively choose certain taxa
over other taxa of similar size, then quantification of this behavior across multiple systems will
increase our understanding of factors likely influencing early life history yellow perch survival.
My objectives were to determine if 1) patterns of selection for zooplankton prey differed among
different lake system types, and 2) patterns of selection for zooplankton prey in inland lakes
differed in comparison to established patterns of selection from laboratory and field studies
focused on Great Lakes proper waterbodies and Wisconsin’s Lake Mendota, and 3) patterns of
prey selection were driven primarily by morphological characteristics of larvae.

METHODS

Study Area
To meet the primary goal of this study, I included a broad range of inland lake systems
ranging from small, < 200 acres, to some of the largest inland lakes in Michigan, i.e. ~20,000

6

acres, as well as ranging in productivity from eutrophic to oligotrophic states (Figures 1 and 2).
Discussions with regional stakeholders (i.e. bait shop owners, anglers, and fisheries biologists)
led me to non-randomly choose these lakes, based on size, trophic state, geographic location, and
well known populations of naturally reproducing yellow perch. The intent was to include a broad
range of systems to provide a representative sample of Michigan inland lakes containing yellow
perch populations and provide opportunity for high contrast in predator diet and prey availability
data, thereby increasing our understanding of general patterns in larval yellow perch prey
selection. Table 1 provides an overview of lake characteristics including surface area, maximum
depth, and location by county. Some of the study lakes were included in a previous study of the
‘Inland Waterway’ where larval fish and zooplankton had been previously collected and
processed. The Inland Waterway is a series of large inland lakes running across the northern
lower peninsula of Michigan that provide a connecting channel between Lakes Michigan and
Huron and it is comprised of Crooked, Pickerel, Burt, and Mullet Lakes. Several other large
systems were selected in the northern Lower Peninsula after consultation with the regional
MDNR biologist to help expand the scope of my comparison. These samples provided new
information on yellow perch population dynamics for these lakes, which previously had been
limited to knowledge of the presence of yellow perch. These systems included Black, Grand,
Long, and Hubbard Lakes. Southern study lakes were much smaller in size and depth and
included Park Lake, Lake Lansing, Lake Ovid, and Lobdell Lake. To further expand my
comparison across variable system types, I included Higgins Lake during the 2015 field season
because of its well-known and valued yellow perch fishery. Also, I included Houghton Lake
during the 2015 field to incorporate a large eutrophic system because my other eutrophic lakes
were rather small in size.

7

Figure 1. Size distribution and trophic status of study lakes. Black shade depicts eutrophic lakes,
gray shade depicts mesotrophic lakes, and white box depicts oligotrophic lakes.

8

Figure 2. Location, relative size, and trophic status of study lakes. Diamonds represent small
lakes (<4 km^2), circles represent medium lakes (4 to 25 km^2), and triangles represent large
lakes (25 to 82 km^2). Solid symbols represent eutrophic systems, shaded symbols represent
mesotrophic systems, and open symbols represent oligotrophic systems.

9

Table 1. Characteristics of study lakes. Lake trophic status was inferred from Secchi disk
readings where oligotrophic is >5 m, mesotrophic 2-5 m, and eutrophic <2 m (Secchi depth
ranges taken from 2007 Michigan Inland Lakes Assessment Report, MDEQ 2010). Lake area
and maximum depths were taken from USGS spatial database (http://miwebmapper.er.usgs.gov).
N (Days) represents the number of sampling events across all years of the study.

Area
(km^2)

Acres

Max depth
(m)

County

Park Lake

0.8

185

9

3.1

Mesotrophic

6.1

Clinton

Lake Ovid

1.7

420

5

1.2

Eutrophic

9.1

Clinton

Lake Lansing

2.0

494

7

4.2

Mesotrophic

10.7

Ingham

Lobdell Lake

2.2

544

1

1.9

Eutrophic

23.8

Genesee

Pickerel Lake
Crooked Lake

4.4

1087

11

6.2

Oligotrophic

22.9

Emmet

9.5

2348

12

3.6

Mesotrophic

15.2

Emmet

Long Lake

22.7

5609

2

2.3

Mesotrophic

7.6

Alpena/Presque Isle

Grand lake

22.9

5659

3

3.1

Mesotrophic

6.1

Presque Isle

Hubbard lake

36.0

8896

2

5.1

Oligotrophic

26.0

Alcona

Higgins Lake

40.0

9884

1

7.2

Oligotrophic

41.2

Roscommon

Black Lake

41.0

10131

5

2.7

Mesotrophic

15.2

Cheboygan

Mullet lake

67.6

16704

8

5.3

Oligotrophic

44.0

Cheboygan

Burt Lake

69.3

17124

12

5.6

Oligotrophic

22.3

Cheboygan

Houghton Lake

81.1

20045

3

1.8

Eutrophic

6.4

Roscommon

Waterbody

N
Mean
Trophic Status
(Days) Secchi (m)

Ichthyoplankton Collection
Larval fish collections occurred from late April through June during the 2011-13 field
seasons as part of the Inland Waterway Study. Additionally, collection efforts occurred for the
2014-15 field seasons from late April through June, beginning with southern study lakes and
progressing north as water temperatures rose. The following methods were consistent across all
sampling years unless otherwise noted. Initial sampling began approximately two weeks after
study lakes were ice free and continued until fewer than 5 yellow perch were collected via
ichthyoplankton trawling per sampling event. At each lake sampling event, I conducted a
minimum of 3 replicate larval trawling events, but up to 15 when additional sampling was

10

required to locate and capture larval fish. Typically, yellow perch are susceptible to surface
collection from the yolk-sac stage until approximately 20 mm. Larger than 20 mm yellow perch
larvae become able to escape surface collection efforts. For this reason, I targeted larval fish
from ~5 mm, (i.e. yolk sac fry), to 20 mm for collection. At each lake, collection sites in
nearshore areas were chosen based on previously published methods as spawning yellow perch
are known to associate with sub-surface vegetation (Post and McQueen 1988; Sullivan and
Stepien 2014; Massicotte et al. 2015). Ichthyoplankton trawling occurred from approximately
1400 until 2300 hours, when larval yellow perch actively feed (Post and McQueen 1988; Leclerc
et al. 2011). Larvae were collected from the top 0.5 m of the water column using a standard side
mounted 500 Âľm ichthyoplankton trawl net with 50 cm mouth opening. A flow meter was
suspended in the center of the mouth opening to estimate volume of water sampled. For the field
seasons 2011-14, a standard side mounted ichthyoplankton net was towed in a straight line,
parallel to the shoreline in 1-3 meter deep water with occasional collections occurring in deeper
waters, ~4-10 meters, for 5 minutes per tow at approximately 1-1.5 m/sec (Figure 3). In 2015,
tow duration was reduced to 2.5 minutes per tow at approximately 1-1.5 m/sec (Figure 4). I
reduced trawling time in 2015 to allow time for additional zooplankton collection events (See
Zooplankton Collection) for each larval trawl. Regardless of year and upon completion of the
tow, the net was retrieved from the water and rinsed from the outside with lake water. The codend was removed, rinsed from the outside with lake water and contents transferred to an 8 inch
by 13 inch picking tray. Large pieces of vegetation were picked from the sample, rinsed with
lake water and checked for entrained larvae. The remaining contents, including larval fish, were
euthanized with a 10 % solution of 95% ethanol, i.e. 10 mL ethanol/ 90mL of lake water. After
euthanization of the larval fish, contents of the picking tray were drained, transferred to 1 L

11

Figure 3. Representative 2014 sampling event from Park Lake. Open circles represent location of
vertical zooplankton tows. Solid lines represent location and relative distance of horizontal
ichthyoplankton trawls. The combination of one zooplankton tow and one ichthyoplankton trawl
is considered a ‘Tow Group’.

12

Figure 4. Representative 2015 sampling event from Park Lake. Open circles represent location of
vertical zooplankton tows. Solid lines represent location and relative distance of horizontal
ichthyoplankton trawls. The set of three zooplankton tows and one ichthyoplankton trawl broken
in half is considered a ‘Tow Group’.

polyethylene bottles filled with 95% ethanol, and labeled with tow ID number, lake, and date.
After collection efforts ceased, typically the following morning, larvae were picked from the
sample, enumerated, placed into 25 mL glass vials, and preserved in 95% ethanol for
identification in the laboratory. Upon completion of field work, all larval fish were processed in
the laboratory using a compound stereomicroscope. All larvae were removed from vials,
enumerated, and identified to species (Auer et al. 1982). Auer et al. (1982) define larvae as the

13

phase of development from complete absorption of the yolk to development of the full
complement of adult fin rays and absorption of the finfold. Juveniles are defined as the phase of
development from complete fin ray development and finfold absorption to sexual maturity (Auer
et al. 1982). Thus, samples collected during this study include the larval stage and early juvenile
stage of development. However, I refer to all fish included in this study as larval yellow perch.

Zooplankton Collection
Field collections of micro-crustacean zooplankton occurred immediately adjacent to
ichthyoplankton collection sites. During the 2011-14 field seasons, a matching zooplankton
collection was gathered at the beginning of each ichthyoplankton trawl from a neutral position
(i.e. drifting with prevailing wind/current to allow for a vertical tow) or while anchored by using
a 12 cm diameter Wisconsin Plankton Net with 80Âľm mesh. Figure 3 illustrates this scheme for
all study lakes, but is specific to Park Lake in 2014. The combination of one zooplankton tow
and one ichthyoplankton trawl is considered a ‘Tow Group’. In 2015, zooplankton collections
efforts were increased and occurred at the beginning, mid-point, and end of each ichthyoplankton
trawl. Figure 4 illustrates combined larval fish and zooplankton collections for all lakes during
the 2015 field season, but is specific to Park Lake for 2015. The set of three zooplankton tows
and one ichthyoplankton trawl which was broken in half to collect a zooplankton sample is
considered a ‘Tow Group’. For all years, 2011-15, water depth was recorded and the
zooplankton net was lowered until it made slight contact with the substrate, then slowly (~30.5
cm/ sec) brought to the surface. After retrieval, the outside of the net was rinsed with lake water
to wash planktonic crustaceans into the cod-end. At this point, the cod-end was rinsed with 95%
ethanol, which effectively euthanized the samples collected. Samples were then transferred to a

14

125mL polyethylene bottle labeled with Tow ID, lake, and date, and then preserved in 95%
ethanol for identification and enumeration in the laboratory.
Concurrent with ichthyoplankton identification, zooplankton were processed using the
following lab protocols across all years, 2011-15, of this study. Because the emphasis of this
research was the relationship between larval diet and prey density, species composition, and size
composition, zooplankton sample processing focused on samples associated with positive
catches of ichthyoplankton. Zooplankton samples were identified (Pennak 1953; Balcer et al.
1984) and placed into major groups for selectivity analysis, including small cladocerans (e.g.
Bosmina, Eubosmina, Chydorus), large cladocerans (e.g. Daphnia spp.), calanoid copepods,
cyclopoid copepods, copepod nauplii, ostracods, Leptodoridae, and harpacticoid copepods. Rare
species were noted in order to be considered during larval diet analysis. Rotifers were also noted
as general presence or absence within each zooplankton tow to be considered during larval
analysis. Initial dissection of a random sample of the smallest larvae under a high power
stereomicroscope yielded no evidence of rotifers in the guts of larval yellow perch. Therefore, it
was decided to exclude rotifers from quantification as available prey. Each sample was drained
of ethanol, rinsed with water, and diluted to 100mL for enumeration. Depending on observed
density, counting methods varied. If density appeared by eye to be extremely low, common to
early season northern lakes, the entire sample was counted. If the samples were moderately
dense, they were split with a Folsom Plankton Splitter to 50%, 25% or 12.5%. Extremely dense
samples were subsampled using a 2 mL Hensen-Stempel pipette. A minimum of 100 organisms
were counted in samples that were split or subsampled and total density calculated by scaling the
proportional contribution of each major group to the entire volume of water sampled during the
respective zooplankton tow. Samples were placed into a Ward’s Zooplankton Counting Wheel

15

and examined at 50X on a compound dissecting stereomicroscope. The first 10 micro-organisms
of each major group for each zooplankton tow were measured to the nearest 0.01 mm following
standard measurement protocol (U.S. Environmental Protection Agency (USEPA) 2003) by
using an ocular micrometer calibrated prior to each session. Total density for binned size groups,
i.e. <0.2 mm, 0.2 to <0.4 mm, 0.4 to <0.6 mm, etc., was calculated by the proportional
contribution of each size group to the total density of the entire sample.

Diet Analysis
Typical of field collection of larval fishes, certain samples contained large numbers of
larvae, while others contain only a few larvae. To avoid over-representing high density samples
we subsampled by randomly selecting 5 larvae from each larval trawl. If the tow contained less
than 5 yellow perch larvae, I dissected all fish in the sample. For field seasons 2011-13, I
included at least one larval trawling event per day for a minimum of 5 larvae dissected per lake
date combination. Additionally, I included a minimum of 3 individual days of samples per lake.
For the 2014-15 field seasons, I included a minimum of 3 larval trawling events, but up to 15,
per lake-date combination. In subsequent statistical analysis, the unit of replication is the ‘Tow
Group’ as defined previously.
Larval length was measured to the nearest 0.01 mm at 10X using a compound
stereomicroscope equipped with an ocular micrometer calibrated prior to each measurement. The
stomach was removed from the anterior opening of the esophagus to the vent and contents
removed. All contents of the stomach were identified to major group as defined above for
zooplankton (Pennak 1953, Balcer et al. 1984), enumerated, and measured following above

16

microscopic techniques and standard measurement protocol (U.S. Environmental Protection
Agency (USEPA) 2003).

Sample Size Analysis
Often, many studies rely on a single zooplankton tow per lake/date combination to
describe the prey field available to larval fish (McDonnell et al. 2014; McCullough et al. 2015).
Given the known patchiness and highly variable distribution of zooplankton within waterbodies,
I used my replicate tow data to conduct an analysis to determine the implications for relative
precision of estimates of mean zooplankton density where multiple tows per lake/date are
collected. I based my analysis on zooplankton density data from the 2015 season, where three
zooplankton tows per ichthyoplankton tow were consistently collected. I calculated the
coefficient of variation (CV) across all 2015 sampling events using tow groups as described in
Figure 4 above by taking the variance (s2) averaged across all tow groups, and calculating the
grand standard error (SE) by using the following series of equations (Krebs 1989):
∑𝑛1 𝐷𝑒𝑛𝑠𝑖𝑡𝑦/𝑡𝑜𝑤
#
𝑀𝑒𝑎𝑛 𝑑𝑒𝑛𝑠𝑖𝑡𝑦 ( ) 𝑓𝑜𝑟 𝑒𝑎𝑐ℎ 𝑡𝑜𝑤 𝑔𝑟𝑜𝑢𝑝 =
𝐿
𝑛
Where L=Liter and n=tow group size (=3).
∑𝑁
1 (𝑀𝑒𝑎𝑛)
𝐺𝑟𝑎𝑛𝑑 𝑀𝑒𝑎𝑛 (𝜇) =
𝑁
Where N=Total # of tow groups in 2015.

𝐺𝑟𝑎𝑛𝑑 𝑉𝑎𝑟𝑖𝑎𝑛𝑐𝑒 (𝑠𝐺2 ) =

2
∑𝑁
1 𝑠𝑡𝑜𝑤
𝑁

2
Where 𝑠𝑡𝑜𝑤
=Variance in total density within each tow group.

17

𝑠𝐺2
√
𝐺𝑟𝑎𝑛𝑑 𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝐸𝑟𝑟𝑜𝑟 (𝑆𝐸) =
𝑛
Where 𝑠𝐺2 = 𝐺𝑟𝑎𝑛𝑑 𝑉𝑎𝑟𝑖𝑎𝑛𝑐𝑒 and 𝑛 = 3.

𝐺𝑟𝑎𝑛𝑑 𝐶𝑉 =

𝑆𝐸
𝜇

Where 𝑆𝐸 = 𝐺𝑟𝑎𝑛𝑑 𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝐸𝑟𝑟𝑜𝑟 𝑎𝑛𝑑 𝜇 = 𝐺𝑟𝑎𝑛𝑑 𝑀𝑒𝑎𝑛.
Utilizing the Grand CV from 2015 zooplankton collection efforts, I then calculated the estimated
sample size necessary to detect differences in total density among tow groups whether within the
same lake or among tow groups from different lakes by the following equation (Krebs 1989).

𝑛=(

100 ∗ 𝐶𝑉 ∗ 𝑡∝ 2
)
𝑟

Where 𝑛= estimated sample size, 𝐶𝑉= 𝐺𝑟𝑎𝑛𝑑 𝐶𝑉, 𝑡∝ =Student’s 𝑡 with n-1 degrees of freedom
for 1-∝ level of confidence, and 𝑟=Desired relative error (Defined as + 20% relative precision of
the mean).
Because I was attempting to estimate a required sample size (𝑛) for a specified level of precision,
I would either have to solve iteratively for 𝑛 or estimate 𝑡∝ . Krebs 1989 offers that it is almost
never worth the effort since 𝑡 values for 95% confidence limits are almost always around 2. As
such, I used the approximation of the Student’s 𝑡 value of 𝑡∝ =2 and estimated 𝑛 for relative
precision = + 10%, + 20%, + 30%, and + 40%.

18

Selectivity Data Analysis
Chesson’s Index of Selective Predation (Chesson 1978, 1983) was used to compare
yellow perch diet items with prey proportions in the environment to determine prey selectivity.
This method is useful because it allows for multiple prey species with varying densities and only
changes if an organisms behavior alters in response to those changes (Chesson 1978, 1983). This
measure of preference is derived from a stochastic model involving the probability of encounter
and the probability of capture upon encounter (Chesson 1978). Chesson’s (α) is defined as:

𝑟𝑖
( )
𝑝𝑖
𝛼𝑖 =
𝑟
∑1𝑛 ( 𝑖 )
𝑝𝑖
Where 𝛼𝑖 = selectivity coefficient of prey type i, 𝑟𝑖 = proportion of prey type i in the diet,
𝑝𝑖 =proportion of prey type i in the environment, and n = number of available prey types in the
environment. Positive selection is indicated when 𝛼𝑖 > (1/n), neutral selection when 𝛼𝑖 = (1/n),
and negative selection when 𝛼𝑖 < (1/n). Although 𝛼𝑖 is useful when comparing selection within
one experiment where n is uniform, it is not easy to compare the strength of non-random
selection when comparing sites with varying numbers of available prey taxa. To address this,
Chesson’s Rescaled Index of Selection (Chesson 1983) was calculated and yields a measure of
preference ranging from -1 to 1, with -1indicative of complete avoidance, 0 representing neutral
selection and 1 displaying complete selection for prey type i. Chesson’s Rescaled Index of
′
Selection (𝛼𝑖 ) is defined as:

19

𝑛 𝛼𝑖 −1
′
𝛼𝑖 = (𝑛−2)𝛼𝑖 +1

, 𝑖 = 1, . … , 𝑛

Where 𝛼𝑖′ =rescaled selectivity coefficient of prey type i.

Establishing Patterns of Selection
To examine overall patterns of selection across multiple system types and throughout the
larval and early juvenile phase of yellow perch life history, I plotted Chesson’s Rescaled Index
of Selectivity (𝛼𝑖′ ) for each major prey taxa group against larval fish total length for all
individual larvae across all lakes. Additionally, I plotted Chesson’s Rescaled Index of Selectivity
(𝛼𝑖′ ) for each prey size group against larval fish total length for all individual larvae across all
lakes. Next, in order to assess differences in patterns of selection among different lake trophic
states, I plotted Chesson’s Rescaled Index of Selectivity (𝛼𝑖′ ) as before, but stratified by lake
trophic state. I overlaid these plots of major prey taxa and prey size by trophic state as a method
to visually evaluate differences in patterns of selection among trophic states. I examined
selection patterns for taxa, selection patterns for size, and plots of the size distribution of each
zooplankton taxa to infer if selection for specific taxa and selection for specific prey size are
totally confounded or if prey selection results from the additive effects of both of these
parameters. Lastly, I applied a Locally Weighted Scatterplot Smoothing (LOESS) function to
each 𝛼𝑖′ plot and calculated a 95% confidence interval of the smoothing function (Cleveland
1979; Cleveland and Devlin 1988) for each trophic state. Overlaying these plots and looking for
overlap of 95 % confidence intervals between trophic lake types for all predator-prey selectivity
functions allowed me to assess whether selectivity patterns differed substantially among lake
trophic types.

20

RESULTS

Zooplankton communities
Zooplankton density and community structure varied substantially among tows within a
lake-day sampling event, across dates within a lake, and among lakes (Appendix Table A1).
Bosmina spp. ranged from 0 to 700 organisms per liter, calanoid copepods ranged from 0 to 87
per liter, cyclopoid copepods ranged from 0 to 248 per liter, Daphnia spp. ranged from 0 to 106
per liter, and nauplii ranged from 0 to 725 per liter. Additionally, proportions of zooplankton
prey taxa (Pi) varied substantially across dates within a lake and among lakes within the three
trophic states (Appendix Table A2, A3, A4). The total proportions of the main taxa encountered,
calculated as a single proportion by combining all lakes within a trophic state, were quite
consistent across lake trophic categories (Figure 5). However, Bosmina spp. tended to be more
prevalent in eutrophic lakes while Daphnia spp. and calanoid copepods were less prevalent in
eutrophic systems. Among all lake types, Bosmina spp. and copepod nauplii dominated the
zooplankton community; the total proportions of Bosmina spp. ranged between 30% and 42%,
and nauplii between 29% and 41%. Cyclopoid copepods were the next most common taxon,
ranging between 15 and 19%. Calanoid copepods and Daphnia spp. were generally low in
proportional contribution, making up from 4% to 9% and 1% to 8%, respectively. Other
zooplankton (i.e. Leptodoridae, harpacticoid copepods, ostracods, and Bythotrephes) were also
generally low in proportional contribution, making up between 2% and 5% of the overall
zooplankton community.

21

Figure 5. Total proportions of environmental prey by taxa across all oligotrophic lakes,
mesotrophic lakes, and eutrophic lakes.

The proportions of zooplankton prey size classes (Pi) also varied substantially across
dates within a lake and among lakes within the three trophic states (Appendix Table A5, A6,
A7). However, total proportions of size classes encountered within each lake trophic state,
calculated as a single proportion by combining all lakes within a trophic state, were also quite
consistent across lake trophic categories (Figure 6). Across all system types, small zooplankton
sizes (i.e. less than 0.4 mm) tended to make up a majority, greater than 50%, of available prey.
The pattern continued with prey sizes of 0.4 mm to 0.6 mm making up the next largest
proportion across all trophic states, ~ 22%, of zooplankton sampled. In all system types, larger

22

prey between 0.6 mm and 0.8 mm, made up the next largest proportion, ~12%, of available prey.
Lastly, the smallest proportions of available prey were comprised of individuals greater than 0.8
mm. Although small differences occurred between trophic system types, a strikingly similar
pattern of prey size structure was evident across lake trophic states.

Figure 6. The total proportions of environmental prey by size across all oligotrophic lakes,
mesotrophic lakes, and eutrophic lakes.

The size composition of individual zooplankton taxa showed variable degrees of overlap
(Figure 7). Results indicate an overlap between copepod nauplii and Bosmina spp. for
zooplankton prey less than 0.4 mm with some overlap of cyclopoid copepods also occurring

23

below 0.4 mm. Additionally, cyclopoid copepods, calanoid copepods, and Daphnia spp.
displayed an overlap in size groups above 0.4 mm.

Figure 7. Proportions of environmental zooplankton prey size by taxon. Environmental
zooplankton prey grouped into 0.05 mm bins and plotted as total proportion for all lakes.

Zooplankton sample size analysis
Analysis of total zooplankton density data from 2015 tow groups, as described in Figure
4, yielded a grand coefficient of variation of 53% with a grand mean of 151organisms per liter,
and grand mean variance of 19350. Average densities of tow groups, across all lakes, ranged
between 1 organism per liter and 1,040 organisms per liter. This demonstrates the highly variable
nature of zooplankton prey availability within my study lakes. Sample size analysis indicated a
sample size requirement of ~28 replicate zooplankton tows per tow group in order to develop a +

24

20% relative precision of the mean estimate (Table 2) for total density among tow groups across
all lakes in this study. Given I collected a minimum of 3 tow groups per lake-day combo during
the 2015 field season, (i.e. minimum of 9 replicate zooplankton tows per lake-day combo), I can
expect a roughly + 35% relative precision of the mean estimate for total zooplankton density
among different tow groups, whether within a lake or among tow groups from different lakes.

Table 2. Estimate of required zooplankton sample size necessary to attain various relative
precision of the mean estimates for total zooplankton densities among tow groups.

Relative Precision of the Mean Sample Size
n+ 10% Relative Precison of Mean Estimate
112
n+ 20% Relative Precison of Mean Estimate
28
n+ 30% Relative Precison of Mean Estimate
12
n+ 40% Relative Precison of Mean Estimate
7

Copepod nauplii, cyclopoid copepods, and Bosmina spp. together typically made up the majority
of the zooplankton prey community throughout all lakes (Figure 5). Sample size analysis of total
density for the copepod nauplii prey group suggests 54 replicate zooplankton tows per tow group
would be required in order to develop a + 20% relative precision of the mean estimate (Table 3)
for total density of copepod nauplii among different tow groups, whether within a lake or among
tow groups from different lakes. Analysis of total copepod nauplii density data from 2015 tow
groups yielded a grand coefficient of variation of 74% with a grand mean of 74 organisms per
liter, and grand mean variance of 4,150. Average copepod nauplii densities of tow groups, across
all lakes, ranged between 1 organism per liter and 428 organisms per liter. This analysis suggests
that with my sampling effort, I could expect a roughly + 50% relative precision of the mean

25

estimate for total copepod nauplii density among different tow groups, whether within a lake or
among tow groups from different lakes.

Table 3. Estimate of required zooplankton sample size necessary to attain various relative
precision of the mean estimates for copepod nauplii densities among tow groups.

Relative Precision of the Mean
n+ 10% Relative Precison of Mean Estimate
n+ 20% Relative Precison of Mean Estimate
n+ 30% Relative Precison of Mean Estimate
n+ 40% Relative Precison of Mean Estimate

Sample Size
216
54
24
14

Sample size analysis of total density for the cyclopoid copepod prey group suggests 36 replicate
zooplankton tows per tow group would be required in order to develop a + 20% relative
precision of the mean estimate (Table 4) for total density of cyclopoid copepods among different
tow groups. Analysis of total cyclopoid copepod density data from 2015 tow groups yielded a
grand coefficient of variation of 60% with a grand mean of 26 organisms per liter, and grand
mean variance of 731. Average cyclopoid copepod densities of tow groups, across all lakes,
ranged between 1 organism per liter and 193 organisms per liter. This analysis suggests that with
my sampling effort, I could expect a roughly + 40% relative precision of the mean estimate for
total cyclopoid copepod density among different tow groups, whether within a lake or among
tow groups from different lakes.

26

Table 4. Estimate of required zooplankton sample size necessary to attain various relative
precision of the mean estimates for cyclopoid copepod densities among tow groups.

Relative Precision of the Mean
n+ 10% Relative Precison of Mean Estimate
n+ 20% Relative Precison of Mean Estimate
n+ 30% Relative Precison of Mean Estimate
n+ 40% Relative Precison of Mean Estimate

Sample Size
143
36
16
9

Sample size analysis of total density for the Bosmina spp. prey group suggests 36 replicate
zooplankton tows per tow group would be required in order to develop a + 20% relative
precision of the mean estimate (Table 5) for total density of Bosmina spp. among tow groups.
Analysis of total Bosmina spp. density data from 2015 tow groups yielded a grand coefficient of
variation of 60% with a grand mean of 62 organisms per liter, and grand mean variance of 4,273.
Average Bosmina spp. densities of tow groups, across all lakes, ranged between 1 organism per
liter and 408 organisms per liter. This analysis suggests that with my sampling effort, I could
expect a roughly + 40% relative precision of the mean estimate for total Bosmina spp. density
among tow groups, whether within a lake or among tow groups from different lakes.

Table 5. Estimate of required zooplankton sample size necessary to attain various relative
precision of the mean estimates for Bosmina spp. total densities among tow groups.

Relative Precision of the Mean
n+ 10% Relative Precison of Mean Estimate
n+ 20% Relative Precison of Mean Estimate
n+ 30% Relative Precison of Mean Estimate
n+ 40% Relative Precison of Mean Estimate

27

Sample Size
145
36
16
9

In summary, this analysis was designed in an attempt to determine an approximation of the
number of zooplankton tows it would take per tow group to get a reasonably good estimate of
zooplankton density within a lake, or by extension, a reasonably good estimate of zooplankton
density among tow groups, whether from the same lake or among tow groups from different
lakes. Based on the results of this analysis, it is reasonable to assume that, in general, large
sample sizes per tow group would be required to develop a precise estimate of the mean density
of zooplankton within a lake. Thus, by extension, prohibitively huge sample sizes would be
required, whether from tow groups within the same lake or among lake types, in order to develop
a precise estimate of the mean density of zooplankton among lakes, regardless of type.

Summary of larval traits and diet
In general and across all lakes, sampling events early in the season tended to yield
smaller sizes of larvae (i.e. <8 mm), while as the season progressed, larger sizes (i.e. > 8 mm)
became more predominant. The sizes of fish collected were highly variable within lake-day
sampling events and among lakes (Table A8).
The gut contents of a total of 1003 yellow perch larvae were examined. These fish
ranged in length from 4 mm to 21 mm, with over half between 5 and 8 mm (Figure 8).
Abundance of fish in the catch declined steadily between 9 mm and 16 mm, and dropped off
rapidly thereafter. Fish less than 7 mm had a substantial proportion of empty guts, up to 38%, but
larvae between 7 and 12 mm displayed a much lower proportion of empty guts, ranging between
2 and 9 % across lake trophic types (Table 6). Nearly all larvae greater than 12 mm contained at
least one prey item with proportion of empty guts at less than 1 % across all lake trophic types.

28

Table 6. Summary of total larvae processed, total with empty guts, and proportion of total empty
guts by lake trophic state. Size ranges provided in mm.
Total Processed
Eutrophic
Mesotrophic
Oligotrophic

Small (<7.01)
32
216
52

Medium (7.01 to < 12)
87
354
112

Large (>12)
26
56
67

Small (<7.01)
8
83
16

Medium (7.01 to < 12)
2
7
10

Large (>12)
0
0
1

Small (<7.01)
0.25
0.38
0.31

Medium (7.01 to < 12)
0.02
0.02
0.09

Large (>12)
0.00
0.00
0.01

Total Empty
Eutrophic
Mesotrophic
Oligotrophic
Proportion Empty
Eutrophic
Mesotrophic
Oligotrophic

Figure 8. Total number and size distribution of larval and early juvenile yellow perch processed
across all lakes and years. Dark shade depicts larvae with empty stomachs. Light shade depicts
larvae with diet items present in gut.

29

The average contribution of major zooplankton taxa groups to larval diets varied
substantially within lake-day sampling events, across dates within a lake, and across lake trophic
types (Table A9). The average number of Bosmina spp. in larval diets from lake-day
combinations across all lakes ranged between 0 and 64 organisms per larvae. The average
number of calanoid copepods in larval diets from lake-day combinations across all lakes ranged
between 0 and 63 organisms. The average number of cyclopoid copepods in larval diets from
lake-day combinations across all lakes ranged between 0 and 69 organisms. The average number
of Daphnia spp. in larval diets from lake-day combinations across all lakes ranged between 0 and
7 organisms. The average number of copepod nauplii in larval diets from lake-day combinations
across all lakes ranged between 0 and 132 organisms (Table A9). Additionally, proportions of
zooplankton prey taxa (Pi) in larval diets varied substantially across dates within a lake and
among lakes within the three trophic states (Appendix Table A10, A11, A12). The total
proportions within each lake trophic state of the main taxa consumed, calculated as a single
proportion by combining all larval guts for lakes within a trophic state, were quite consistent
when comparing oligotrophic to eutrophic systems (Figure 9). However, the total proportional
contribution of cyclopoid copepods in mesotrophic systems was lower, and the proportion of
copepod nauplii was higher compared to larval diets in oligotrophic and eutrophic systems.

30

Figure 9. The total proportions of zooplankton prey taxa groups within larval guts by lake-day
combo for oligotrophic lakes, mesotrophic lakes, and eutrophic lakes.

The average contribution of major zooplankton size groups to larval diets varied
substantially within lake-day sampling events, across dates within a lake, and across lake trophic
types (Table A13). The average < 0.2 mm zooplankton in larval diets from lake-day
combinations across all lakes ranged between 0 and 52 organisms. The average 0.2 to < 0.4 mm
zooplankton in larval diets from lake-day combinations across all lakes ranged between 0 and 81
organisms. The average 0.4 to < 0.6 mm zooplankton in larval diets from lake-day combinations
across all lakes ranged between 0 and 56 organisms. The average 0.6 to < 0.8 mm zooplankton in
larval diets from lake-day combinations across all lakes ranged between 0 and 48 organisms. The
average 0.8 to < 1.0 mm zooplankton in larval diets from lake-day combinations across all lakes

31

ranged between 0 and 10 organisms. The average > 1.0 mm zooplankton in larval diets from
lake-day combinations across all lakes ranged between 0 and 5 organisms (Table A13).
Additionally, proportions of zooplankton prey sizes (Pi) in larval diets varied substantially across
dates within a lake and among lakes within the three trophic states (Appendix Table A14, A15,
A16). The total proportions within each lake trophic state of the main size groups consumed,
calculated as a single proportion by combining all larval guts for lakes within a trophic state,
were quite consistent across trophic states for prey larger than 0.8 mm (Figure 9). However,
total proportional contribution of smaller zooplankton prey, i.e. <0.2 to < 0.8 mm, display unique
differences among trophic system status. For example, the total proportion of zooplankton < 0.2
mm in larval guts within oligotrophic systems accounts for less than 5% of their diet. However,
< 0.2 mm zooplankton account for ~28% of larval diets in mesotrophic systems (Figure 10). In
general, smaller zooplankton tended to account for larger proportions of overall larval diets in
mesotrophic systems.

32

Figure 10. The total proportions of zooplankton prey size groups within larval guts by lake-day
combo for oligotrophic lakes, mesotrophic lakes, and eutrophic lakes.
Overall taxon-specific selectivity
Selection of zooplankton prey by larval and early juvenile yellow perch predators varied
considerably across all sampling events when calculating a single selectivity value for all fish in
a given lake-day combination (Figure 11). For all major functional taxonomic groups, prey
selectivity ranged from complete negative selection to complete positive selection. The average
of Chesson’s Rescaled Index of Selectivity for Bosmina spp. was -0.60. Average selection for
calanoid copepods was -0.48. Average selection for cyclopoid copepods was 0.26. Out of all
functional groups, cyclopoid copepods were the only taxon to display an average positive
selection across all sampling events. Average selection for Daphnia spp. was -0.73. Average
selection for copepod nauplii was -0.05. For all functional groups, copepod nauplii were the only
taxon to have a nearly neutral average selection. Average selection for other taxa (i.e. Leptidora,
harpacticoid copepods, ostracods, and Bythotrephes) was -0.71.

33

Figure 11. Chesson’s Rescaled Index of selection of zooplankton prey by larval and early
juvenile yellow perch for major taxonomic group. Filled circles represent a single selectivity
value by combining all fish diets in a given lake-day combination. Shaded triangles represent
overall mean selectivity. Zero represents neutral selection, 1.00 represents complete positive
selection, and -1.00 represents complete negative selection.

Individual taxon-specific selection
Although selectivity varied widely across lake-date sampling, taxon-specific selectivity
showed a clear progression across sizes of yellow perch. Copepod nauplii were strongly selected
for by the smallest larvae (i.e. <7mm). As larvae grew in size, their selection for copepod nauplii
declined and became neutral at ~ 9mm. Continuing this pattern, larger larvae began to negatively

34

select for nauplii after 9mm and approached complete avoidance (i.e. -1.00) when growing past
16 mm (Figure 12).

Figure 12. Chesson’s Rescaled Index of selection for copepod nauplii by larval and early
juvenile yellow perch. Circles represent individual selectivity from eutrophic lakes. Plus symbols
represent individual selectivity from mesotrophic lakes. Triangles represent individual selectivity
from oligotrophic lakes. Solid line depicts LOESS function fit to all data with gray band
representing 95% confidence interval of the mean.

Additionally, patterns for selectivity of copepod nauplii remained relatively consistent among
lake trophic types (Figure 13). However, selection for copepod nauplii was less positive for 7
mm to 10mm larvae in oligotrophic systems as compared to eutrophic and mesotrophic systems.

35

Figure 13. LOESS functions with 95% Confidence Intervals relating taxon-specific selectivity
for copepod nauplii as a function of larval and early juvenile yellow perch length as influenced
by system specific trophic status. Solid lines represent eutrophic systems, dashed lines represent
mesotrophic systems, and dotted lines represent oligotrophic systems.

Selection by individual larvae for cyclopoid copepods also displayed a general pattern when
applying a LOESS Function to individual data points across all sampling events. The smallest
larvae (i.e. < 5mm) displayed complete avoidance for cyclopoid copepods. As larvae grew,
selectivity increased and became neutral at ~ 7mm. The pattern for selection continued to
increase to a peak of ~0.50 when larvae reached 9 to 11mm. At this point, selection began to
decline back to neutral as the larvae grew into larger sizes (i.e. >11mm). Eventually selection for
cyclopoids became negative again for the largest larvae (i.e. > 19mm). However, small sample

36

sizes of the largest larvae resulted in higher levels of uncertainty when applying the LOESS
Function (Figure 14).

Figure 14. Chesson’s Rescaled Index of selection for cyclopoid copepods by larval and early
juvenile yellow perch. Circles represent individual selectivity from eutrophic lakes. Plus symbols
represent individual selectivity from mesotrophic lakes. Triangles represent individual selectivity
from oligotrophic lakes. Solid line depicts LOESS function fit to all data with gray band
representing 95% confidence interval of the mean.

Patterns for selectivity of cyclopoid copepods remained relatively consistent among lake trophic
types (Figure 15), with the exception that selection for cyclopoid copepods was slightly more
positive for 7 mm to 10mm larvae in oligotrophic systems as compared to eutrophic and
mesotrophic systems.

37

Figure 15. LOESS functions with 95% Confidence Intervals relating taxon-specific selectivity
for cyclopoid copepods as a function of larval and early juvenile yellow perch length as
influenced by system specific trophic status. Solid lines represent eutrophic systems, dashed lines
represent mesotrophic systems, and dotted lines represent oligotrophic systems.
Nearly all individual fish displayed complete avoidance for calanoid copepods at sizes of less
than 7mm. After larvae grew past 7mm, selection for calanoid copepods began to increase until
reaching neutral at ~15mm. The largest larvae began to positively select for calanoid copepods
after 15mm. (Figure 16).

38

Figure 16. Chesson’s Rescaled Index of selection for calanoid copepods by larval and early
juvenile yellow perch. Circles represent individual selectivity from eutrophic lakes. Plus symbols
represent individual selectivity from mesotrophic lakes. Triangles represent individual selectivity
from oligotrophic lakes. Solid line depicts LOESS function fit to all data with gray band
representing 95% confidence interval of the mean.
Patterns for selectivity of calanoid copepods remained relatively consistent among lake trophic
types (Figure 17) for larvae up to 13 mm, although selection for calanoid copepods was more
positive for larvae greater than 13mm in eutrophic systems as compared to oligotrophic and
mesotrophic systems.

39

Figure 17. LOESS functions with 95% Confidence Intervals relating taxon-specific selectivity
for calanoid copepods as a function of larval and early juvenile yellow perch length as influenced
by system specific trophic status. Solid lines represent eutrophic systems, dashed lines represent
mesotrophic systems, and dotted lines represent oligotrophic systems

Similar to calanoid copepods, selection for Bosmina spp. showed an increasing trend with fish
length (Figure 18). Larvae <7mm displayed complete avoidance, but as larvae grew past 7mm,
selectivity of Bosmina spp. steadily increased until reaching neutral at ~19mm. After 19mm,
selectivity became positive. However, small sample sizes of the largest fish (i.e. >19mm) add
uncertainty to this aspect of yellow perch early life history.

40

Figure 18. Chesson’s Rescaled Index of selection for Bosmina spp. by larval and early juvenile
yellow perch. Circles represent individual selectivity from eutrophic lakes. Plus symbols
represent individual selectivity from mesotrophic lakes. Triangles represent individual selectivity
from oligotrophic lakes. Solid line depicts LOESS function fit to all data with gray band
representing 95% confidence interval of the mean.
Patterns for selectivity for Bosmina spp. remained relatively consistent among lake trophic types
(Figure 19) for larvae up to 13 mm, except that selection for Bosmina spp. was less positive for
larvae greater than 13mm in eutrophic systems as compared to oligotrophic and mesotrophic
systems.

41

Figure 19. LOESS functions with 95% Confidence Intervals relating taxon-specific selectivity
for Bosmina spp. as a function of larval and early juvenile yellow perch length as influenced by
system specific trophic status. Solid lines represent eutrophic systems, dashed lines represent
mesotrophic systems, and dotted lines represent oligotrophic systems.

Selection for Daphnia spp. also displayed a positive relationship with increasing length. Small
larvae (i.e. <8mm) displayed complete avoidance while as fish grew, selection increased.
However, selection for Daphnia never became positive over the range of sizes of fish sampled
(Figure 20).

42

Figure 20. Chesson’s Rescaled Index of selection for Daphnia spp. by larval and early juvenile
yellow perch. Circles represent individual selectivity from eutrophic lakes. Plus symbols
represent individual selectivity from mesotrophic lakes. Triangles represent individual selectivity
from oligotrophic lakes. Solid line depicts LOESS function fit to all data with gray band
representing 95% confidence interval of the mean.
Patterns for selectivity for Daphnia spp. remained strongly consistent among lake trophic types
(Figure 21) for all sizes of larvae.

43

Figure 21. LOESS functions with 95% Confidence Intervals relating taxon-specific selectivity
for Daphnia spp. as a function of larval and early juvenile yellow perch length as influenced by
system specific trophic status. Solid lines represent eutrophic systems, dashed lines represent
mesotrophic systems, and dotted lines represent oligotrophic systems.

Summary of taxon-specific selection
Although some differences were observed among lake trophic types, especially for
copepod nauplii and cyclopoid copepods, overall taxon-specific selectivity showed a broadly
similar ontogeny of selectivity across all lake trophic types. Copepod nauplii were preferred as a
first food source of larval yellow perch less than 7 mm. As selection for nauplii declined, fish
began to select more positively for cyclopoid species. As fish grew to ~11mm, this preference
for cyclopoid copepods began to decline. Following closely this decline in selection for

44

cyclopoids, larvae continued to increase their preference for calanoid copepods, Bosmina spp.,
and Daphnia spp. (Figure 22) although Daphnia spp. were never positively selected, just avoided
less.

Figure 22. Summary of LOESS functions relating taxon-specific selectivity as a function of
larval and early juvenile yellow perch length.

Overall prey size-specific selection
In general, larval yellow perch consumed relatively small zooplankton with few prey
>1.0 mm being consumed. As fish grew in size, the average size of prey consumed increased as
well. The average prey size consumed by the smallest fish was generally less than 0.2 mm. As
fish grew into the 9 to 14 mm range, the average size of zooplankton prey increased to between

45

0.4 and 0.6 mm. This pattern continued as fish grew above 14 mm where the average size of prey
was 0.6 mm (Figure 23).

Figure 23. Length of prey found in larval and early juvenile yellow perch guts as a function of
fish length. Open circles represent individual diet items. Solid line represents LOESS function fit
with gray band representing 95% confidence interval of the mean.
A positive relationship between gape size and prey length was observed, although there was
considerable variation around this relationship (Figure 24). At very small sizes, larval perch are
able to consume prey approaching their gape size, but as gape size increases the ratio of prey size
to gape size rapidly drops to less than 0.5 (Figure 25).

46

Figure 24. Length of prey found in larval and early juvenile yellow perch guts as a function of
fish gape. Open circles represent individual diet items. Solid blue line represents 1:1 ratio of fish
gape to prey length. Solid black line represents LOESS function fit with gray band representing
95% confidence interval of the mean. Gape size estimated using the following literature based
regression. Gape=0.159(Total length)-0.597. (Schael et al. 1991)

47

Figure 25. Ratio of prey length to gape as a function of fish length. Open circles represent the
ratio for individual diet items. Solid line represents LOESS function fit with gray band
representing 95% confidence interval of the mean.

Zooplankton were placed into 0.2 mm bins to determine selectivity for specific size ranges of
zooplankton prey. Selection for size classes of zooplankton, irrespective of their taxonomic
identity, varied considerably for all fish across all lakes, days, and years. For all size classes of
zooplankton, Chesson’s Rescaled Index of Selection ranged from complete avoidance (i.e. -1.00)
to completely positive selection (i.e. 1.00). Selection for small prey declined with increasing
larvae size (Figure 26). Specifically, average selection for zooplankton from 0 to < 0.2 mm was -

48

0.17. Average selection for zooplankton from 0.2 to < 0.4 mm was 0.03. Out of all size classes,
the 0.2 to < 0.4 range was the only size class to have an average selection greater than 0. Average
selection for zooplankton from 0.4 to < 0.6 mm was -0.28. The pattern continued as average
selection for the 0.6 to <0.8 mm size was -0.62. Average selection for the 0.8 to <1.00 size class
of zooplankton was -0.75. Lastly, average selectivity for zooplankton greater than 1.00 mm was
nearly completely negative at -0.97.

Figure 26. Chesson’s Rescaled Index of selection of zooplankton prey by larval and early
juvenile yellow perch as a function of prey size category. Filled circles represent a single
selectivity value by combining all fish diets in a given lake-day combination. Shaded triangles
represent overall mean selectivity. Zero represents neutral selection, 1.00 represents complete
positive selection, and -1.00 represents complete negative selection.

49

Individual prey size-specific selectivity
Selection for size classes of zooplankton showed a clear progression with increasing fish
size. The smallest larval yellow perch (i.e. < 5mm) strongly selected for the smallest zooplankton
(i.e. <0.2 mm). As larvae grew, their selection of <0.2 mm zooplankton declined to neutral at
~8mm. The pattern continued as larvae increased in size past 8mm, with their selection of < 0.2
mm zooplankton steadily declined to complete avoidance at ~20 mm (Figure 27).

Figure 27. Chesson’s Rescaled Index of selection for zooplankton less than 0.2 mm by larval and
early juvenile yellow perch. Circles represent individual selectivity from eutrophic lakes. Plus
symbols represent individual selectivity from mesotrophic lakes. Triangles represent individual
selectivity from oligotrophic lakes. Solid line depicts LOESS function fit to all data with gray
band representing 95% confidence interval of the mean.

50

General patterns of selectivity for < 0.2 mm zooplankton remained relatively consistent among
lake trophic types (Figure 28) for larvae up to 13 mm, except that selection for < 0.2 mm
zooplankton was more positive for larvae between 8 and 10 mm in mesotrophic systems as
compared to eutrophic and oligotrophic systems.

Figure 28. LOESS functions with 95% Confidence Intervals relating size-specific selectivity for
zooplankton less than 0.2 mm as a function of larval and early juvenile yellow perch length as
influenced by system specific trophic status. Solid lines represent eutrophic systems, dashed lines
represent mesotrophic systems, and dotted lines represent oligotrophic systems.

Zooplankton in the 0.2 to <0.4 mm size class were negatively selected for by the smallest larval
fish (i.e. < 5mm). As larvae grew to ~6 mm, selection increased to neutral and continued to

51

increase positively until larvae grew to ~8mm. At this point, selection for 0.2 to < 0.4 mm
zooplankton began to decline steadily back to neutral at ~ 10 mm fish length. The pattern of
selection continued to steadily decrease as larvae grew to 21 mm. Larvae never completely
avoided zooplankton in the 0.2 to < 0.4 mm size class (Figure 29).

Figure 29. Chesson’s Rescaled Index of selection for zooplankton 0.2 mm to less than 0.4 mm by
larval and early juvenile yellow perch. Circles represent individual selectivity from eutrophic
lakes. Plus symbols represent individual selectivity from mesotrophic lakes. Triangles represent
individual selectivity from oligotrophic lakes. Solid line depicts LOESS function fit to all data
with gray band representing 95% confidence interval of the mean.

General patterns of selectivity for 0.2 to < 0.4 mm zooplankton remained relatively consistent
among lake trophic types (Figure 30), except that selection for 0.2 to < 0.4 mm zooplankton was

52

negative for larvae between 7 and 9 mm in oligotrophic systems as compared to mesotrophic and
oligotrophic systems where selection for this size range was positive.

Figure 30. LOESS functions with 95% Confidence Intervals relating size-specific selectivity for
zooplankton 0.2 mm to less than 0.4 mm as a function of larval and early juvenile yellow perch
length as influenced by system specific trophic status. Solid lines represent eutrophic systems,
dashed lines represent mesotrophic systems, and dotted lines represent oligotrophic systems.
Zooplankton in the 0.4 to < 0.6 mm size class were completely avoided by the smallest larvae
(i.e. < 5mm). As larvae increased in size, selection for this zooplankton size class climbed to
neutral at ~9 mm fish length. Briefly, selection became positive for larvae in the 9 to 13 mm

53

range, at which point, selection became steady at neutral and remained neutral as fish grew to 21
mm (Figure 31).

Figure 31. Chesson’s Rescaled Index of selection for zooplankton 0.4 mm to less than 0.6 mm by
larval and early juvenile yellow perch. Circles represent individual selectivity from eutrophic
lakes. Plus symbols represent individual selectivity from mesotrophic lakes. Triangles represent
individual selectivity from oligotrophic lakes. Solid line depicts LOESS function fit to all data
with gray band representing 95% confidence interval of the mean.

General patterns of selectivity for 0.4 to < 0.6 mm zooplankton remained relatively consistent
among lake trophic types (Figure 32), other than a slight tendency for more positive selection for
larvae between 7 and 9 mm in oligotrophic systems as compared to mesotrophic and eutrophic
systems.

54

Figure 32. LOESS functions with 95% Confidence Intervals relating size-specific selectivity for
zooplankton 0.4 mm to less than 0.6 mm as a function of larval and early juvenile yellow perch
length as influenced by system specific trophic status. Solid lines represent eutrophic systems,
dashed lines represent mesotrophic systems, and dotted lines represent oligotrophic systems.

Larvae never positively selected for 0.6 to <0.8 mm zooplankton. Small larvae < 6mm
completely avoided zooplankton in this size class. At ~8 mm fish length, selectively began to
become less negative and increase quickly until approaching neutral at ~12 mm. The pattern of
selection for this size class remained steady and ranged from 0 to -0.1 for larvae greater than 12
mm (Figure 33).

55

Figure 33. Chesson’s Rescaled Index of selection for zooplankton 0.6 mm to less than 0.8 mm by
larval and early juvenile yellow perch. Circles represent individual selectivity from eutrophic
lakes. Plus symbols represent individual selectivity from mesotrophic lakes. Triangles represent
individual selectivity from oligotrophic lakes. Solid line depicts LOESS function fit to all data
with gray band representing 95% confidence interval of the mean.

General patterns of selectivity for 0.6 to < 0.8 mm zooplankton remained relatively consistent
among lake trophic types (Figure 34), except for neutral selection for larvae between 7 and 11
mm in oligotrophic systems as compared to negative selection for mesotrophic and eutrophic
systems.

56

Figure 34. LOESS functions with 95% Confidence Intervals relating size-specific selectivity for
zooplankton 0.6 mm to less than 0.8 mm as a function of larval and early juvenile yellow perch
length as influenced by system specific trophic status. Solid lines represent eutrophic systems,
dashed lines represent mesotrophic systems, and dotted lines represent oligotrophic systems.

A strong positive relationship was evident between fish length and selection for 0.8 to < 1.0 mm
zooplankton. Small larvae < 8mm completely avoided this size class of prey. As fish grew past 8
mm selection began to steadily increase and reach neutral at ~16 mm fish length. After 16mm,
selection for 0.8 to < 1.0 mm zooplankton continued to increase steadily through 21 mm fish
(Figure 35).

57

Figure 35. Chesson’s Rescaled Index of selection for zooplankton 0.8 mm to less than 1.0 mm by
larval and early juvenile yellow perch. Circles represent individual selectivity from eutrophic
lakes. Plus symbols represent individual selectivity from mesotrophic lakes. Triangles represent
individual selectivity from oligotrophic lakes. Solid line depicts LOESS function fit to all data
with gray band representing 95% confidence interval of the mean.

General patterns of selectivity for 0.8 to < 1.0 mm zooplankton remained consistent among lake
trophic types (Figure 36) for larvae less than 14 mm, but diverged as larvae grew past 14 mm.

58

Figure 36. LOESS functions with 95% Confidence Intervals relating size-specific selectivity for
zooplankton 0.8 mm to less than 1.0 mm as a function of larval and early juvenile yellow perch
length as influenced by system specific trophic status. Solid lines represent eutrophic systems,
dashed lines represent mesotrophic systems, and dotted lines represent oligotrophic systems.

Zooplankton greater than 1.0 mm were never positively selected for by this range of larval fish
size. Larvae < 9 mm completely avoided greater than 1.0 mm zooplankton. As larvae grew from
9 mm to 21 mm, their selection for large zooplankton increased steadily to -0.45 (Figure 37).

59

Figure 37. Chesson’s Rescaled Index of selection for zooplankton greater than 1.0 mm by larval
and early juvenile yellow perch. Circles represent individual selectivity from eutrophic lakes.
Plus symbols represent individual selectivity from mesotrophic lakes. Triangles represent
individual selectivity from oligotrophic lakes. Solid line depicts LOESS function fit to all data
with gray band representing 95% confidence interval of the mean.

General patterns of selectivity for > 1.0 mm zooplankton remained consistent among lake trophic
types (Figure 38) for larvae of all sizes.

60

Figure 38. LOESS functions with 95% Confidence Intervals relating size-specific selectivity for
zooplankton greater than 1 mm as a function of larval and early juvenile yellow perch length as
influenced by system specific trophic status. Solid lines represent eutrophic systems, dashed lines
represent mesotrophic systems, and dotted lines represent oligotrophic systems.

Summary of prey size-specific selection
A summary of size-specific selectivity showed a distinct ontogeny of selectivity for
individual larvae across all lakes, days, and years (Figure 39). The smallest larvae (i.e. < 5mm)
positively selected for zooplankton <0.2 mm. As larvae grew, they began to select more
positively for the next size class of zooplankton (i.e. 0.2 to <0.4 mm). At ~8mm fish length, this
increase in selection began to decline as larvae began selecting more for the next size class (i.e.
0.4 to < 0.6 mm). This ontogeny continued through the remaining size classes of zooplankton.

61

As fish grew to ~ 12 mm, their selection for 0.6 to < 0.8 mm zooplankton approached and
remained near neutral. Larvae greater than 12 mm began selecting more for 0.8 to <1.0 mm
zooplankton until reaching ~16mm. At this point, selection for this size class of zooplankton
continued to increase positively until fish reach 21 mm. Selection for zooplankton >1.0 mm
never became positive. In fact, larvae < 9mm completely avoided these larger prey.

Figure 39. Summary of LOESS functions relating prey size-specific selectivity as a function of
larval and early juvenile yellow perch length.

62

DISCUSSION

The overall goal of this study was to evaluate patterns of prey selection by larval yellow
perch across a broad range of system types in inland lakes of Michigan’s Lower Peninsula. The
purpose behind this evaluation was to increase knowledge of yellow perch feeding during the
transition from endogenous nutrition to exogenous feeding, specifically in terms of consistency
among lakes. My goal was to reveal relationships during this critical period among prey
availability, prey community structure, lake characteristics, and larval fish morphology. While
the early life history of yellow perch has been the focus of a tremendous amount of effort in both
field and laboratory experiments, these efforts tended to examine this period of yellow perch
early life history within a laboratory setting or field study specific to individual lake systems.
Such experiments advance our knowledge of yellow perch feeding ecology within the specific
waterbody type, but then tend to be generalized across different lake system types without direct
evidence. Predictive models developed from these expectations contain a level of uncertainty
about the uniformity or differences in system specific processes. My research added an in-depth
evaluation of prey selectivity across waterbodies with differing levels of productivity, thereby
providing a more direct empirical basis for making such generalizations.

Zooplankton
One important aspect to consider in the feeding ecology of larval fishes is the availability
of suitable densities and sizes of zooplankton prey at the critical transition period between
endogenous and exogenous food sources (Dettmers et al. 2003). Several studies have stressed the
importance of rotifers to the survival and growth of larval yellow perch during this critical period

63

(Siefert 1972; Post and McQueen 1988; Fulford et al. 2006b). However, others have found that
the availability of rotifers in the environment is not necessarily an important component of larval
yellow perch feeding ecology (Bremigan et al. 2003). Specifically, yellow perch larvae
displayed negative selection for rotifer species in Lake Michigan’s Green Bay (Bremigan et al.
2003). My study supports this conclusion. Across all of my study lakes, including eutrophic,
mesotrophic, and oligotrophic waterbodies, rotifers were rarely found in the diet of yellow perch
larvae. In fact, out of 1003 stomachs examined, only 21, from larvae ranging in size from 4.6
mm to 10.9 mm, were found with rotifers in their guts, and these were distributed relatively
evenly across lake trophic type. During the course of zooplankton processing, rotifers were
consistently evident in environmental prey samples, but mostly absent from diets of larval yellow
perch. I conclude that while rotifers may be an occasional food item in naturally occurring larval
yellow perch diets, they were not critically important to the successful feeding, growth, and
survival of larval yellow perch in my study lakes. Consequently, individual based models which
utilize laboratory findings citing the importance of the availability of rotifer species (Fulford et
al. 2006b) to larval feeding ecology may not be representative of naturally occurring larval
predator-prey interactions in all waterbodies.
I categorized my lakes on an a priori grouping of trophic classes, based on the
commonly-used criterion of water clarity as indicated by Secchi disk depth. Although substantial
variation was evident in zooplankton densities across lakes, dates, and even within lakes (Table
A1), I found that the average proportions of the different zooplankton prey types were similar
across these trophic categories. The same was true for the mean proportion of zooplankton
present across size categories. This result is somewhat unexpected, given previous research
showing differences in the zooplankton community across trophic classes (Patalas 1972). I

64

speculate that the similarity in proportions of zooplankton taxa and size composition may be a
more conservative property of the zooplankton community across trophic states than overall
density, however answering this question would require a different study design.
The substantial observed variation in densities of prey taxa and size classes among lakeday sampling events suggests that future investigators should carefully evaluate their sample size
needs for quantification of available prey densities that are representative of an individual
sampling event (i.e., lake/date combination or locale within a lake). My analysis indicates that
relatively large sample sizes are necessary to achieve a high level of precision for mean density.
However, a trade off exists between the goal of determining the availability and composition of
prey resources with a high level of precision and the costs to collect and process the large
numbers of samples required. Moreover, the ability to detect differences among systems
depends not only on the variation within a lake on a specified date, but the variation across dates
within a lake and across lakes. I suggest that it would be beneficial if a method could be
developed to collect larvae and prey that better integrates spatial variation in zooplankton
density. Currently, we typically rely on two different techniques in natural systems; one for
predators where we collect a horizontal sample across a large spatial area, and another for prey
where we collect a representative vertical sample in a very specific locale and use that
information to extrapolate prey community structure to the whole system. I speculate that
developing a method to collect fish larvae along with their prey resource would benefit our
determination of predatory processes and increase our understanding of critical early life
processes in naturally occurring systems. In many studies of larval fish diet and selection, a
single zooplankton tow is used to characterize the available prey (McDonnell et al. 2014;
McCullough et al. 2015); in my view one zooplankton sample is simply not enough to develop a

65

robust understanding of prey community density and structure. A potential method may be to
capture every organism within a small area of a naturally occurring system by mechanical
isolation, and then quantifying the entire sample. For example, this technique is often used to
quadrant off benthic habitats, but could also be useful for capturing larval predators and
zooplankton prey. This would potentially yield a direct measurement, (i.e. absolute encounter
rates), of prey density, predator density, and environmental conditions, such as water clarity,
which are known to influence larval feeding processes.

Selection
Yellow perch display an ontogenetic diet shift as fish grow in size during the larval and
juvenile phase (Whiteside et al. 1985; Graeb et al. 2006). Yellow perch begin feeding on small
zooplankton and as their body size increases, they switch to larger zooplankton (Mills et al.
1989; Graeb et al. 2004a). At approximately the 20 to 40 mm total length range, juvenile fish
transition to a diet primarily composed of benthic invertebrates (Wu and Culver 1992). Lastly, as
the fish reach approximately 80 mm, they begin to transition to a diet of prey fish (Graeb et al.
2006). Many studies focus on and stress the importance of these transitions to recruitment
success by examining larger juvenile fish , (> 20 mm) , while few have considered the
importance of the finer-scale ontogeny of prey selection by larval fish in the early stages of
exogenous feeding (Graeb et al. 2004a). Recent observations of prey selection by age 0 yellow
perch in Lake Huron’s Saginaw Bay demonstrate the absence of an ontogenetic shift from
zooplankton to benthic invertebrates in this zooplankton rich system (Roswell et al. 2013),
suggesting that this ontogeny is plastic and the shift from zooplankton to benthic invertebrates
may depend on relative abundance and foraging profitability of these groups (Hayes and Taylor

66

1990; Hayes et al. 1992). Therefore, the finer-scale ontogeny displayed in my study through
different zooplankton taxa and sizes may indeed present an important component for modeling
survival and recruitment of yellow perch to existing fisheries.
A number of other studies have demonstrated that copepod nauplii are likely a very
important first food source for newly hatched yellow perch larvae (Schael et al. 1991; Bremigan
et al. 2003; Graeb et al. 2004b; Roswell et al. 2013, 2014). My study supports this theory. Across
the different types of waterbodies that I sampled, only copepod nauplii were positively selected
for by larvae in the 5 to 8 mm range. This is consistent with the findings of Bremigan et al.
(2003) in Green Bay, Graeb et al. (2004) in Saginaw Bay, and Schael et al. (1991) in Lake
Mendota, suggesting that this selection for copepod nauplii as a first food occurs across a variety
of system types and may be of general importance to larval yellow perch. Interactions between
copepod nauplii density and larval yellow perch early feeding success should be used in the
formation of predictive models of the early life history of this species. This behavior is likely
easily explained by the vulnerability and size of copepod nauplii as the consumption of prey by
small larvae is limited by their gape size. My analysis of selection by size of prey supports this
conclusion as only zooplankters <0.2 mm were found to be positively selected for across
multiple system types by the smallest larvae. Copepod nauplii are the principal prey item in this
size range, so my data do not allow assessment of whether selection for copepod nauplii by small
larval yellow perch is driven by anything other than gape limitation. However, certain species of
copepod nauplii such as calanoid copepod nauplii can be larger in size and begin to overlap with
Bosmina spp. and cyclopoid copepod sizes (Figure 7). This provides some indication that
selection on the basis of something other than prey size alone is occurring; as larvae increase in
size, they begin to actively choose larger copepod nauplii over similarly-sized Bosmina spp. and

67

small cyclopoids. Patterns of selection for larvae are likely primarily regulated by gape limitation
and evasive capabilities of the zooplankton prey, but are also affected by behavioral preference
for certain prey types.
Positive selection for copepod nauplii is slightly lower in oligotrophic systems as
compared to eutrophic and mesotrophic systems (Figure 13). Larval yellow perch are visual
predators. Water clarity may play a critical role in selection during early feeding because
increased visual acuity in clearer waters likely allows for less reliance on the slow moving small
nauplii by increasing detection and capture distance for larger, more energy rich prey. Manning
et al. (2014) describe turbidity and phytoplankton abundance as a driving force controlling
consumption rates, growth, and starvation of larval yellow perch. They concluded feeding rates
decreased significantly with higher levels of phytoplankton. Although my study quantified prey
preference while their study quantified larval feeding rates, both demonstrate that water clarity
plays a role in the predation process, which has implications for year class development for
larval yellow perch.
Next in the ontogeny of prey selection by larval yellow perch is their preference for
cyclopoid copepods. As in previous studies, I found that yellow perch larvae made a distinctive
transition from copepod nauplii to cyclopoid copepods at roughly 8 mm total length and
continued to transition to larger cyclopoids as the larvae grow in size (Schael et al. 1991;
Bremigan et al. 2003). It has been postulated that net gains in energetic benefits due to larger
prey size and less handling time explains this behavior (Graeb et al. 2004a). I found that my
analysis of selection of prey size agrees with my findings of taxa selection as cyclopoid
copepods vary considerably in size, but smaller, 0.2 to <0.4 mm, zooplankters were positively
selected for by larvae in the 7 to 10 mm range. Then, selection began to shift to larger prey sizes,

68

0.4 to <0.6mm, as fish grew into the 9 to 13 mm range, followed by positive selection for larger
and larger prey sizes as larvae grow past 13 mm in size. As they grow, larval fish increase their
gape size, swimming ability, and visual acuity, which allows for the efficient capture and
handling of larger and larger prey. However, prey selection is again likely to be a summation of
both morphological limitations, (i.e. gape size), and preference for more energetically cost
effective prey. Figure 7 demonstrates a small overlap in size for large nauplii, Bosmina spp., and
small cyclopoids. Therefore, results of my study show that prey selection is a product of both
morphological limitations and feeding behavior as larvae grow in size, as demonstrated by
comparison of selection curves for cyclopoids and Bosmina spp. In other words, Bosmina spp.
and small cyclopoids overlap in size, but selection curves for larvae in the 7 mm to 10 mm range
demonstrate larvae consistently choose cyclopoid copepods over Bosmina spp. as a food source.
Lastly, while variation exists in prey selection among trophic states for Bosmina spp. and smaller
sizes of cyclopoids, i.e. 0.2 to <0.4mm, a general pattern is evidenced by selection curves for this
size range of prey. Specifically, mid-size larvae displayed a higher preference for mid-sized
zooplankton in oligotrophic lakes and compared to eutrophic and mesotrophic systems.
I found that selection for calanoid copepods, Bosmina spp., and Daphnia spp. only began
to become positive as larvae begin to develop into juvenile fish. These findings are consistent
with other studies (Bremigan et al. 2003; Graeb et al. 2004a) and make sense as these
zooplankters are either more difficult to capture and handle because of evasive ability or they
have protective defenses such as spines and hard carapaces. Also, they tend to be larger
zooplankters, which make capture and consumption by smaller larvae nearly impossible. There is
overlap in prey sizes > 0.4 mm among taxa, specifically, larger cyclopoid copepods, calanoid
copepods, and Daphnia spp. (Figure 7). My results demonstrate that selection for cyclopoids, on

69

average and among the different lake types, remains positive for larvae, even as they grow into
larger sizes. Only when they grow beyond 11 mm does selection for calanoid copepods and
Daphnia spp. prey begin to become more positive. This supports the theory of gape-limitation in
larval yellow perch, but also displays evidence of behavioral selection for certain prey types over
others of similar size.

CONCLUSION

Other studies have found that variation in both selection and ontogeny of prey choice can
be quite high within single waterbodies as well as across waters of different types (Roswell et al.
2013). My study supports this by demonstrating that selection of zooplankton prey varies
considerably within and across waterbody types. However, it also provides evidence that general
patterns of prey selection can be expected across a wide range of lakes. My results support what
has generally been documented for larval yellow perch and other gape limited larval fish. My
work contributes to this body of knowledge by expanding data coverage across a wide range of
lakes, ranging from less than 200 acres to greater than 20,000 acres, and from oligotrophic to
eutrophic. My a priori hypothesis is supported in that general, common patterns of selectivity by
larval yellow perch do exist and can be expected in inland and waters of Michigan. I also suggest
that selection for prey taxa and size by larval yellow perch is not only regulated by
morphological characteristics of predator and prey, but also by behavioral choices for certain
types of prey. I found that larvae consume prey well below a 1:1 gape to prey length ratio
(Figure 25). If selective predation by larval yellow perch was solely regulated by morphological
characteristics, then it follows that they would be consistently be consuming prey at or near the

70

1:1 gape to prey size ratio (i.e., the largest prey, regardless of taxon, that they are able to
consume).
My research is limited by small sample sizes of larvae greater than 15 mm. This most
likely reflects the capability of larger larvae to avoid my sampling gear because of increased
motility and their tendency to switch to benthic prey. While I feel confident in my description of
prey selection by larvae from first feed to about 15 mm, I also recommend that future researchers
plan for and attempt to include more larvae greater than 15 mm. Switching from larval surface
trawls to littoral seining techniques would assist with capturing larger larvae, but it is also likely
that larger larval fish would begin feeding on benthic invertebrates, thus confounding analysis of
selectivity indices for zooplankton prey. An interesting trend is seen in the larger larvae, where it
appears that selection is increasing for larger prey, including calanoid copepods and Daphnia
species, but with limited sample sizes in that fish size range, I feel that any inference I could
make would be an extrapolation beyond the confines of my dataset. Also, my sample sizes for
environmental prey limit my ability to detect modest differences in prey communities across
different system types.
In closing, this study will be useful to researchers looking to develop models that include
patterns of prey selection by larval yellow perch. Despite considerable variation both within and
among lake trophic types, my findings indicate a general pattern that spans lake characteristics.
This is an important result because project leaders can use this information when developing
sampling schemes for future studies, utilizing my data to determine sample size requirements.

71

APPENDIX

72

Table A1. Mean number of zooplankton per liter with Standard Error (SE) of the mean, and
number of samples collected and analyzed (N) for each lake-day sampling event.
Lake

Date

N

Bosmina

Calanoid

Cyclopoid

Daphnia

Nauplii

Other

Mean SE Mean SE Mean SE Mean SE Mean SE Mean SE
Black

8
9

0.2
0.1

0.1
0.0

2.5
1.8

1.3
0.4

1.5
1.6

0.7
0.3

0.1
0.2

0.0
0.1

2.2
1.4

0.0
1.0

0.0
0.3

28-May-15 9
4-Jun-15 6
5-Jun-15 12

1.5
1.2
1.5

0.2
0.5
0.5

5.8
0.1
0.2

0.9
0.1
0.0

5.2
1.6
1.6

1.5
1.2
0.3

0.2
0.2
0.1

0.1 10.6 2.9
0.1 111.2 45.5
0.0 18.6 3.5

0.1
0.0
0.1

0.0
0.0
0.0

21-May-11 1
4-Jun-11 1
10-Jun-11 1

0.1
31.3
1.6

.
.
.

0.2
0.2
1.7

.
.
.

0.3
0.3
0.8

.
.
.

0.0
0.4
1.8

.
.
.

0.0
0.0
2.4

.
.
.

8-May-12
18-May-12
31-May-12
6-Jun-12

1
1
1
2

2.2
0.5
2.9
3.1

.
.
.
2.1

0.7
0.3
18.1
5.4

.
.
.
0.8

1.8
0.4
4.1
2.1

.
.
.
0.3

.
.
.
0.3

0.0
0.0
2.1
1.8

.
.
.
0.3

8-May-13 1
22-May-13 1
31-May-13 1

4.2
2.9
3.3

.
.
.

1.2
1.2
0.4

.
.
.

5.4
3.9
2.4

.
.
.

1.0
0.6
0.7

.
.
.

15.9
19.0
4.8

.
.
.

7.0
1.2
1.3

.
.
.

28-May-15 9
6-Jun-15 6

1.0
1.5

0.4
0.9

0.3
0.6

0.1
0.2

0.3
0.7

0.1
0.5

0.1
0.2

0.0
0.1

0.9
9.5

0.2
2.6

0.0
0.4

0.0
0.1

Crooked 5-May-11 1
16-May-11 1
6-Jun-11 1

4.2
1.4
1.8

.
.
.

0.7
0.1
0.4

.
.
.

8.4
4.3
3.6

.
.
.

0.0
0.1
0.1

.
.
.

7.9
11.2
2.3

.
.
.

0.0
1.8
0.0

.
.
.

16.3
0.0
4.9
0.4

.
.
.
.

1.7
0.0
1.5
1.9

.
.
.
.

43.5
0.0
8.1
7.2

.
.
.
.

0.0
0.0
0.0
0.1

.
.
.
.

17.4
0.1
3.8
2.5

.
.
.
.

0.0
0.1
22.5
8.3

.
.
.
.

Burt

4-Jun-14
18-Jun-14

13-Apr-12
14-May-12
22-May-12
30-May-12

1
1
1
1

73

.
.
.

6.7
7.2

11.6
0.8
7.1

0.4
.
2.5
0.0
.
1.0
1.2
.
10.1
11.9 10.1 10.5

Table A1 cont.
Lake

Date

N

Bosmina

Calanoid

Cyclopoid

Daphnia

Nauplii

Other

Mean SE Mean SE Mean SE Mean SE Mean SE Mean SE
Crooked 7-May-13
14-May-13
21-May-13
28-May-13

1
1
1
1

2.8
11.0
1.6
11.8

.
.
.
.

1.6
2.5
0.7
3.4

.
.
.
.

3.3
19.3
2.9
4.4

.
.
.
.

0.0
0.2
0.2
0.6

.
.
.
.

16.8
7.7
5.6
3.8

.
.
.
.

0.7
12.8
0.2
0.1

.
.
.
.

27-May-15 6

1.5

0.3

0.9

0.4

2.0

0.5

0.0

0.0

10.5

2.0

0.0

0.0

Grand 23-May-14 8
5-Jun-14 5

0.3
9.4

0.1
3.2

0.9
0.6

0.2
0.1

10.4
2.1

4.6
0.2

0.5
0.6

0.3
0.3

9.2
26.1

1.8
2.6

0.3
12.3

0.1
0.7

11-Jun-15

9

11.2

2.1

0.6

0.2

1.8

0.3

0.1

0.0

2.6

0.4

0.0

0.0

9-Jun-15

12

1.2

0.6

0.3

0.2

1.1

0.3

0.1

0.1

2.2

1.1

0.0

0.0

Houghton20-May-15 12 6.7 1.1
21-May-15 12 24.6 3.7
27-May-15 9 72.9 22.4

0.7
0.7
3.5

0.1
0.1
0.8

6.2
6.1
14.3

1.1
1.6
2.1

0.7
0.3
1.4

0.1
0.1
0.6

9.6
9.0
14.0

2.0
1.5
4.5

0.3
0.0
0.0

0.0
0.0
0.0

Hubbard 6-Jun-14 5
19-Jun-14 13

0.4
0.0

0.4
0.7

0.2
0.1

0.1
0.2

0.1
0.1

0.7
0.3

0.3
0.1

6.4
1.8

1.8
0.4

0.1
0.1

0.0
0.0

Lansing 30-Apr-14
6-May-14
16-May-14
27-May-14

10.3 4.3 6.8 2.6 12.4
24.5 10.4 12.3 3.8 20.8
67.0 18.7 38.2 17.4 31.3
65.8 19.5 8.0 1.3 13.8

4.4
9.2
6.7
1.9

2.5
1.1
5.3
3.5

1.3
0.6
1.9
0.8

24.3 8.9
76.6 34.9
83.0 14.2
48.3 10.6

0.0
0.0
6.1
5.4

0.0
0.0
2.9
1.6

39.4
16.4
5.7

Higgins

4
5
4
8

0.2
0.0

7-May-15 9 62.3 8.8 23.6
13-May-15 11 42.9 7.4 11.1
19-May-15 9 67.4 14.8 16.3
Lobdell 11-May-14 3

3.2
2.0
2.3

25.6
9.5
15.9

3.1
1.4
3.1

1.7
3.0
6.2

0.5
0.3
1.7

7.0
2.1
0.8

0.9
0.0
0.3

0.2
0.0
0.1

24.8 10.8

2.6

1.7

68.8 15.0

1.3

0.2 148.6 30.5

9.1

4.0

Long 24-May-14 5
5-Jun-14 6

0.7
1.0

0.1
0.3

1.1
2.5

0.3
1.0

2.3
1.2

0.5
0.5

0.1
0.1

0.0
0.1

5.7
2.8

1.4
0.3

0.0
2.8

0.0
0.9

28-May-15 9

1.2

0.4

1.2

0.2

1.2

0.3

0.0

0.0

4.7

0.8

0.2

0.0

74

Table A1 cont.
Lake

Date

N

Bosmina

Calanoid

Cyclopoid

Daphnia

Nauplii

Other

Mean SE Mean SE Mean SE Mean SE Mean SE Mean SE
Mullett

Ovid

Park

2-Jun-11
12-Jun-11

1
1

29.3
18.8

.
.

0.3
0.0

.
.

3.4
4.4

.
.

0.0
0.2

.
.

8.8
17.6

.
.

1.0
2.6

.
.

19-May-12 1
31-May-12 1
5-Jun-12 2

31.5
2.7
6.3

.
.
1.1

0.2
0.3
0.7

.
.
0.0

2.2
2.2
5.4

.
.
2.9

0.0
0.1
0.2

.
.
0.2

2.4
4.0
8.3

.
.
6.8

0.1
5.6
5.3

.
.
3.2

15-May-13 1
24-May-13 2

0.2
1.6

.
1.2

0.2
0.5

.
0.3

0.7
3.6

.
1.5

0.0
0.1

.
0.1

0.9
5.5

.
2.3

0.2
0.4

.
0.0

6-May-14 5 72.4 21.6 13.5
17-May-14 6 188.4 43.7 5.5

5.8
2.0

27.1 4.2
85.2 20.7

4.2
6.1

1.4
3.1

49.5 13.9 7.4 6.2
96.8 12.3 22.0 10.8

30-Apr-15 12 258.5 51.7 22.8
12-May-15 6 141.3 34.3 12.0
14-May-15 15 216.5 35.9 27.4

6.6 114.1 21.3 3.7
3.5 83.8 21.0 13.1
4.5 102.0 14.7 4.7

1.1 133.0 22.9
4.7 100.3 28.7
1.2 262.6 46.4

0.0
0.8
0.0

0.0
0.1
0.0

25-Apr-14
5-May-14
8-May-14
12-May-14
28-May-14

2 39.2 10.2
5 15.2 11.3
5 78.6 28.3
5 113.1 58.9
6 105.8 14.2

0.0
0.8
0.3
0.4
1.2

0.0
0.5
0.2
0.3
0.5

93.9 4.0 1.8
66.6 26.9 0.7
70.3 11.1 2.8
58.9 12.2 0.9
83.2 9.1 15.5

1.8
0.4
1.3
0.4
3.7

401.4
125.2
125.8
120.1
177.8

1.1
62.9
42.4
26.9
20.8

0.0
0.0
1.6
4.5
6.5

0.0
0.0
0.9
1.1
1.2

28-Apr-15
13-May-15
19-May-15
1-Jun-15

9 43.4 21.0 2.9
9 116.4 18.0 7.9
6 179.4 44.0 13.5
6 82.4 12.2 20.2

1.1
1.3
3.7
7.0

53.5 22.2 1.7 0.6
42.3 3.8 18.0 4.1
31.0 8.2 19.5 5.1
22.9 4.4 49.1 12.2

131.9
93.7
20.4
24.0

46.4
13.5
4.1
4.8

0.0
0.0
0.7
0.0

0.0
0.0
0.1
0.0

Pickerel 7-May-11 1
17-May-11 1
3-Jun-11 1

1.5
1.8
1.6

.
.
.

0.6
0.2
0.4

.
.
.

5.6
9.4
3.3

.
.
.

0.0
0.0
0.0

.
.
.

7.9
14.4
7.0

.
.
.

0.1
0.4
0.1

.
.
.

9-May-12 1
21-May-12 1
3-Jun-12 1

0.7
9.6
2.0

.
.
.

0.7
0.9
4.8

.
.
.

4.9
6.4
1.7

.
.
.

0.0
0.0
0.0

.
.
.

1.9
3.0
2.3

.
.
.

0.0
0.6
0.7

.
.
.

75

Table A1 cont.
Lake

Date

N

Bosmina

Calanoid

Cyclopoid

Daphnia

Nauplii

Other

Mean SE Mean SE Mean SE Mean SE Mean SE Mean SE
Pickerel 6-May-13
13-May-13
20-May-13
27-May-13

1
1
1
1

0.4
1.6
1.9
1.6

.
.
.
.

0.0
0.3
0.5
0.1

.
.
.
.

1.1
8.9
15.8
4.9

.
.
.
.

0.1
0.0
0.0
0.0

.
.
.
.

3.5
6.4
17.4
10.2

.
.
.
.

0.4
0.0
0.2
0.1

.
.
.
.

27-May-15 6

3.9

1.2

0.2

0.1

1.6

0.6

0.0

0.0

4.4

1.8

0.0

0.0

Table A2. Proportions of available zooplankton prey (Pi) by taxa for eutrophic systems with the
mean, minimum (Min), and maximum (Max) proportion.
Lake
Date
Houghton 20-May-15
21-May-15
27-May-15

Bosmina
0.285
0.614
0.686

Calanoid
0.029
0.018
0.031

Cyclopoid
0.253
0.137
0.131

Daphnia
0.030
0.007
0.015

Nauplii
0.403
0.220
0.133

Other
0.001
0.004
0.004

Lobdell

11-May-14

0.099

0.009

0.268

0.005

0.580

0.038

Ovid

6-May-14
17-May-14
30-Apr-15
12-May-15
14-May-15

0.382
0.452
0.488
0.395
0.370

0.080
0.014
0.039
0.037
0.045

0.159
0.198
0.214
0.236
0.171

0.023
0.016
0.007
0.035
0.008

0.310
0.257
0.252
0.295
0.407

0.045
0.062
0.000
0.001
0.000

Mean proportion

0.421

0.039

0.192

0.013

0.319

0.016

Min

0.099

0.009

0.131

0.005

0.133

0.000

Max

0.686

0.080

0.268

0.035

0.580

0.062

76

Table A3. Proportions of available zooplankton prey (Pi) by taxa for mesotrophic systems with
the mean, minimum (Min), and maximum (Max) proportion.
Lake
Black

Date
Bosmina
4-Jun-14
0.013
18-Jun-14
0.006
28-May-15
0.061
4-Jun-15
0.009
5-Jun-15
0.072

Crooked

5-May-11
16-May-11
6-Jun-11
13-Apr-12
14-May-12
22-May-12
30-May-12
7-May-13
14-May-13
21-May-13
28-May-13
27-May-15

0.196
0.075
0.218
0.206
0.074
0.121
0.020
0.112
0.206
0.148
0.490
0.102

0.032
0.007
0.046
0.022
0.000
0.037
0.091
0.064
0.047
0.061
0.139
0.058

0.399
0.228
0.437
0.552
0.000
0.199
0.352
0.130
0.361
0.257
0.183
0.136

Grand

23-May-14
5-Jun-14
11-Jun-15

0.020
0.169
0.694

0.044
0.012
0.041

Lansing

30-Apr-14
6-May-14
16-May-14
27-May-14
7-May-15
13-May-15
19-May-15

0.188
0.188
0.278
0.415
0.407
0.520
0.606

Long

24-May-14
5-Jun-14
28-May-15

Park

25-Apr-14
5-May-14
8-May-14
12-May-14
28-May-14
28-Apr-15
13-May-15
19-May-15
1-Jun-15

Calanoid Cyclopoid Daphnia
0.217
0.146
0.006
0.155
0.143
0.024
0.236
0.233
0.008
0.001
0.014
0.001
0.006
0.062
0.002

Nauplii
0.617
0.567
0.459
0.975
0.857

Othe r
0.001
0.105
0.003
0.000
0.000

0.002
0.002
0.011
0.000
0.000
0.000
0.003
0.002
0.004
0.017
0.024
0.001

0.371
0.591
0.287
0.220
0.556
0.094
0.123
0.666
0.144
0.504
0.159
0.704

0.000
0.096
0.000
0.000
0.370
0.550
0.410
0.026
0.238
0.013
0.005
0.000

0.442
0.040
0.105

0.019
0.011
0.004

0.461
0.520
0.155

0.014
0.248
0.000

0.122
0.100
0.174
0.064
0.156
0.134
0.148

0.217
0.165
0.133
0.112
0.170
0.112
0.139

0.046
0.008
0.025
0.030
0.011
0.036
0.054

0.427
0.540
0.360
0.341
0.256
0.197
0.051

0.000
0.000
0.029
0.039
0.001
0.000
0.001

0.061
0.090
0.139

0.117
0.219
0.136

0.241
0.096
0.156

0.007
0.006
0.000

0.572
0.289
0.567

0.001
0.300
0.001

0.075
0.052
0.248
0.326
0.284
0.185
0.422
0.674
0.419

0.000
0.003
0.002
0.002
0.003
0.013
0.029
0.051
0.099

0.174
0.347
0.283
0.236
0.212
0.234
0.154
0.122
0.114

0.003
0.003
0.009
0.003
0.041
0.007
0.067
0.072
0.243

0.748
0.595
0.452
0.416
0.444
0.560
0.328
0.080
0.125

0.000
0.000
0.007
0.017
0.016
0.000
0.000
0.001
0.000

Mean Proportion

0.298

0.049

0.191

0.032

0.414

0.017

Min

0.006

0.000

0.000

0.000

0.051

0.000

Max

0.694

0.236

0.552

0.243

0.975

0.550

77

Table A4. Proportions of available zooplankton prey (Pi) by taxa for oligotrophic systems with
the mean, minimum (Min), and maximum (Max) proportion.
Lake
Burt

Date
21-May-11
4-Jun-11
10-Jun-11
8-May-12
18-May-12
31-May-12
6-Jun-12
8-May-13
22-May-13
31-May-13
28-May-15
6-Jun-15

Bosmina
0.006
0.949
0.105
0.292
0.228
0.075
0.100
0.121
0.101
0.255
0.386
0.074

Calanoid
0.014
0.005
0.113
0.086
0.142
0.471
0.156
0.034
0.041
0.027
0.132
0.058

Cyclopoid
0.023
0.008
0.052
0.242
0.172
0.107
0.064
0.155
0.135
0.191
0.112
0.033

Daphnia
0.000
0.012
0.115
0.049
0.007
0.031
0.317
0.028
0.020
0.055
0.015
0.022

Nauplii
0.957
0.025
0.461
0.331
0.446
0.261
0.310
0.459
0.662
0.373
0.355
0.804

Other
0.000
0.001
0.153
0.000
0.007
0.054
0.053
0.203
0.041
0.100
0.000
0.009

Higgins

9-Jun-15

0.262

0.065

0.272

0.023

0.378

0.000

Hubbard

6-Jun-14
19-Jun-14

0.026
0.010

0.056
0.295

0.006
0.054

0.144
0.162

0.764
0.453

0.003
0.027

Mullett

2-Jun-11
12-Jun-11
19-May-12
31-May-12
5-Jun-12
15-May-13
24-May-13

0.686
0.433
0.865
0.185
0.244
0.105
0.146

0.006
0.000
0.006
0.020
0.026
0.070
0.044

0.080
0.100
0.061
0.145
0.208
0.316
0.320

0.000
0.004
0.000
0.009
0.006
0.018
0.011

0.205
0.405
0.066
0.267
0.313
0.421
0.445

0.022
0.059
0.003
0.375
0.203
0.070
0.033

Pickerel

7-May-11
17-May-11
3-Jun-11
9-May-12
21-May-12
3-Jun-12
6-May-13
13-May-13
20-May-13
27-May-13
27-May-15

0.095
0.069
0.125
0.089
0.470
0.172
0.078
0.093
0.054
0.097
0.363

0.036
0.009
0.035
0.081
0.044
0.420
0.000
0.017
0.014
0.006
0.023

0.360
0.358
0.269
0.599
0.314
0.151
0.203
0.517
0.441
0.291
0.171

0.000
0.000
0.000
0.000
0.000
0.000
0.013
0.000
0.000
0.000
0.002

0.505
0.548
0.561
0.229
0.144
0.197
0.634
0.373
0.486
0.600
0.441

0.004
0.016
0.010
0.002
0.029
0.061
0.072
0.000
0.005
0.006
0.000

Mean proportion

0.325

0.092

0.153

0.085

0.294

0.052

Min

0.006

0.000

0.006

0.000

0.025

0.000

Max

0.949

0.471

0.599

0.317

0.957

0.375

78

Table A5. Proportions of available zooplankton prey (Pi) by size for eutrophic systems with
mean, minimum (Min), and maximum (Max) proportion.
Lake
Houghton

Date
20-May-15
21-May-15
27-May-15

<0.2
0.128
0.149
0.056

0.2 to <0.4
0.335
0.453
0.392

0.4 to < 0.6
0.212
0.204
0.231

Lobdell

11-May-14

0.186

0.443

0.250

0.050

0.021

0.050

Ovid

6-May-14
17-May-14
30-Apr-15
12-May-15
14-May-15

0.112
0.174
0.145
0.108
0.073

0.438
0.467
0.297
0.314
0.462

0.225
0.217
0.203
0.265
0.251

0.101
0.069
0.192
0.196
0.120

0.047
0.051
0.070
0.049
0.047

0.078
0.022
0.093
0.069
0.047

Mean Proportion

0.119

0.404

0.230

0.130

0.053

0.065

Min

0.056

0.297

0.203

0.050

0.021

0.022

Max

0.186

0.467

0.265

0.196

0.089

0.168

79

0.6 to <0.8 0.8 to < 1.0
0.133
0.089
0.104
0.040
0.091
0.035

> 1.0
0.103
0.050
0.168

Table A6. Proportions of available zooplankton prey (Pi) by size for mesotrophic systems with
mean, minimum (Min), and maximum
Lake
Black

Date
4-Jun-14
18-Jun-14
28-May-15
4-Jun-15
5-Jun-15

<0.2
0.131
0.236
0.108
0.108
0.106

0.2 to <0.4
0.407
0.297
0.309
0.477
0.532

0.4 to < 0.6
0.312
0.241
0.223
0.215
0.206

0.6 to <0.8
0.090
0.130
0.165
0.092
0.078

0.8 to < 1.0
0.045
0.061
0.094
0.062
0.043

> 1.0
0.015
0.034
0.094
0.046
0.035

Crooked

5-May-11
16-May-11
6-Jun-11
13-Apr-12
14-May-12
22-May-12
30-May-12
7-May-13
14-May-13
21-May-13
28-May-13
27-May-15

0.122
0.250
0.273
0.242
0.682
0.380
0.340
0.314
0.250
0.213
0.196
0.207

0.341
0.227
0.455
0.273
0.227
0.180
0.255
0.294
0.269
0.468
0.478
0.428

0.268
0.295
0.212
0.364
0.091
0.220
0.170
0.255
0.154
0.234
0.196
0.192

0.122
0.205

0.122
0.023
0.030
0.061

0.024

0.100
0.170
0.078
0.231
0.064
0.022
0.087

0.100
0.043
0.020
0.038
0.021

0.020
0.021
0.039
0.038

0.072

0.109
0.014

Grand

23-May-14
5-Jun-14
11-Jun-15

0.196
0.263
0.117

0.375
0.462
0.425

0.313
0.155
0.142

0.065
0.064
0.175

0.034
0.036
0.075

0.017
0.020
0.067

Lansing

30-Apr-14
6-May-14
16-May-14
27-May-14
7-May-15
13-May-15
19-May-15

0.071
0.171
0.158
0.223
0.128
0.107
0.152

0.331
0.343
0.357
0.372
0.378
0.390
0.331

0.233
0.217
0.194
0.215
0.243
0.181
0.232

0.184
0.144
0.122
0.102
0.128
0.160
0.126

0.083
0.080
0.102
0.045
0.068
0.088
0.106

0.098
0.046
0.066
0.045
0.054
0.074
0.053

Long

24-May-14
5-Jun-14
28-May-15

0.087
0.240
0.092

0.377
0.434
0.447

0.290
0.181
0.296

0.126
0.073
0.092

0.048
0.024
0.013

0.072
0.049
0.059

Park

25-Apr-14
5-May-14
8-May-14
12-May-14
28-May-14
28-Apr-15
13-May-15
19-May-15
1-Jun-15

0.350
0.230
0.154
0.180
0.149
0.092
0.140
0.157
0.130

0.273
0.358
0.521
0.438
0.521
0.517
0.379
0.255
0.460

0.203
0.236
0.183
0.230
0.260
0.254
0.228
0.216
0.170

0.147
0.109
0.089
0.124
0.058
0.095
0.148
0.167
0.050

0.021
0.058
0.041
0.017
0.012
0.025
0.068
0.059
0.060

0.007
0.010
0.012
0.011

Mean Proportion

0.168

0.405

0.223

0.115

0.049

0.039

Min

0.071

0.180

0.091

0.022

0.012

0.007

Max

0.682

0.532

0.364

0.231

0.122

0.147

(Max) proportion.

80

0.030

0.030
0.030

0.016
0.037
0.147
0.130

Table A7. Proportions of available zooplankton prey (Pi) by size for oligotrophic systems with
mean, minimum (Min), and maximum (Max) proportion.
Lake
Burt

Date
21-May-11
4-Jun-11
10-Jun-11
8-May-12
18-May-12
31-May-12
6-Jun-12
8-May-13
22-May-13
31-May-13
28-May-15
6-Jun-15

<0.2
0.077
0.067
0.217
0.120
0.159
0.291
0.194
0.283
0.178
0.245
0.236
0.109

Higgins

9-Jun-15

0.147

0.420

0.156

0.183

0.054

0.040

Hubbard

6-Jun-14
19-Jun-14

0.030
0.080

0.418
0.463

0.149
0.220

0.097
0.036

0.030
0.034

0.276
0.168

Mullett

2-Jun-11
12-Jun-11
19-May-12
31-May-12
5-Jun-12
15-May-13
24-May-13

0.189
0.395
0.121
0.275
0.254
0.257
0.320

0.378
0.372
0.515
0.431
0.377
0.457
0.267

0.270
0.070
0.152
0.118
0.217
0.114
0.133

0.108
0.070
0.061
0.059
0.058
0.114
0.160

0.027
0.023
0.091
0.078
0.051

0.027
0.070
0.061
0.039
0.043
0.057
0.040

7-May-11
17-May-11
3-Jun-11
9-May-12
21-May-12
3-Jun-12
6-May-13
13-May-13
20-May-13
27-May-13
27-May-15

0.077
0.180
0.116
0.227
0.200
0.240
0.186
0.219
0.189
0.250
0.123

0.436
0.311
0.419
0.341
0.387
0.520
0.419
0.406
0.486
0.438
0.548

0.282
0.197
0.256
0.227
0.253
0.120
0.233
0.125
0.243
0.281
0.274

0.154
0.230
0.163
0.023
0.080
0.020
0.163
0.125
0.054
0.031
0.014

0.051
0.049
0.047
0.068

Mean proportion

0.181

0.395

0.189

0.109

0.065

0.059

Min

0.030

0.250

0.070

0.014

0.023

0.000

Max

0.395

0.548

0.282

0.317

0.180

0.276

Pickerel

0.2 to <0.4 0.4 to < 0.6 0.6 to <0.8 0.8 to < 1.0
0.423
0.269
0.038
0.350
0.217
0.317
0.050
0.300
0.150
0.150
0.117
0.280
0.220
0.180
0.180
0.295
0.273
0.159
0.114
0.255
0.255
0.200
0.339
0.185
0.169
0.065
0.250
0.233
0.150
0.050
0.289
0.267
0.178
0.067
0.347
0.122
0.163
0.041
0.382
0.163
0.098
0.065
0.327
0.178
0.178
0.129

81

0.080

> 1.0
0.192
0.067
0.020

0.048
0.033
0.022
0.082
0.057
0.079

0.033
0.000
0.114
0.080

0.100
0.063

0.063
0.027

0.041

Table A8. Number of fish processed (N) per lake-day sampling event with number of empty
larval stomachs, mean total length (TL), standard error (SE) of total length, minimum size of
larvae (Min), and maximum length of larvae (Max).

82

Table A8 cont.

83

Table A8 cont.

84

Table A8 cont.

85

Table A9. Mean number of major zooplankton taxa groups per larval gut by date with Standard
Error (SE) of the mean, and number of samples collected and analyzed (N) for each lake-day
sampling event.
Lake

Date

N

Bosmina

Calanoid

Cyclopoid

Daphnia

Nauplii

Other

Mean SE Mean SE Mean SE Mean SE Mean SE Mean SE
Black

4-Jun-14 13
18-Jun-14 15

0.0
0.0

0.0
0.0

0.0
0.0

0.0
0.0

0.5
0.1

0.5
0.1

0.1
0.0

0.1
0.0

0.2
1.0

0.0
3.3

0.0
1.8

28-May-15 28
4-Jun-15 4
5-Jun-15 9

0.0
0.3
1.0

0.0
0.3
0.5

3.2
0.0
0.1

0.5
0.0
0.1

3.8
1.0
1.9

0.8
1.0
0.8

0.1
0.0
0.0

0.1 2.3 0.6
0.0 132.8 33.8
0.0 14.7 6.0

0.1
0.0
0.1

0.1
0.0
0.1

21-May-11 5
4-Jun-11 5
10-Jun-11 5

0.0
2.2
19.2

0.0
1.5
4.8

0.0
2.8
3.0

0.0
1.0
0.7

0.2
37.0
2.8

0.2
8.3
1.7

0.0
0.0
2.6

0.0
0.0
1.1

0.8
0.4
0.0

0.2
0.4
0.0

0.0
0.0
0.0

0.0
0.0
0.0

8-May-12
18-May-12
31-May-12
6-Jun-12

5
5
5
9

0.0
0.0
0.4
7.8

0.0
0.0
0.2
2.1

0.2 0.2 6.2
0.8 0.5 7.6
63.8 22.4 31.6
13.6 4.0 12.4

2.0
2.2
8.4
3.0

0.0
0.0
1.8
7.4

0.0
0.0
0.9
1.6

4.6
0.8
5.8
0.0

1.5
0.8
0.6
0.0

0.0
0.0
0.0
1.3

0.0
0.0
0.0
0.8

8-May-13 3
22-May-13 5
31-May-13 5

0.0
0.0
3.2

0.0
0.0
1.8

0.0
0.4
0.2

0.0
0.4
0.2

0.3
3.4
11.8

0.3
2.9
5.2

0.0
0.0
0.0

0.0
0.0
0.0

0.3
4.6
2.8

0.3
3.6
1.5

0.0
0.0
0.0

0.0
0.0
0.0

28-May-15 21
6-Jun-15 4

0.0
2.3

0.0
1.1

0.2
3.5

0.1
2.1

1.1
5.8

0.3
2.4

0.0
0.0

0.0
0.0

0.5
2.5

0.1
1.7

0.1
0.3

0.1
0.3

Crooked 5-May-11 5
16-May-11 5
6-Jun-11 5

0.0
0.0
0.0

0.0
0.0
0.0

0.0
0.0
0.0

0.0
0.0
0.0

0.0 0.0
9.4 3.2
32.6 12.3

0.0
0.0
0.0

0.0
0.0
0.0

0.0
2.8
10.2

0.0
1.2
3.1

0.0
0.0
0.0

0.0
0.0
0.0

0.0
0.6
9.3
2.3

0.0
0.4
4.6
1.4

0.0
1.6
5.8
0.5

0.0
0.8
2.2
0.5

0.0
12.4
25.0
1.5

0.0
0.2
0.0
4.3

0.0
0.2
0.0
3.0

0.4
1.2
0.0
0.0

0.2
0.5
0.0
0.0

0.0
0.6
0.0
0.0

0.0
0.6
0.0
0.0

Burt

13-Apr-12
14-May-12
22-May-12
30-May-12

5
5
4
4

86

0.0
3.1
8.8
1.0

0.4
5.1

Table A9 cont.
Lake

Date

N

Bosmina

Calanoid

Cyclopoid

Daphnia

Nauplii

Other

Mean SE Mean SE Mean SE Mean SE Mean SE Mean SE
Crooked 7-May-13
14-May-13
21-May-13
28-May-13

5
5
5
5

0.0
0.0
0.4
14.0

0.0
0.0
0.4
3.9

0.0
0.0
0.2
3.0

0.0
0.0
0.2
1.1

0.2
2.0
2.6
10.0

0.2
0.6
0.5
6.1

0.0
0.0
0.2
0.0

0.0
0.0
0.2
0.0

4.6
2.4
0.8
3.2

1.5
0.8
0.4
2.7

0.0
0.0
0.0
0.2

0.0
0.0
0.0
0.2

27-May-15 20

0.1

0.1

0.0

0.0

0.0

0.0

0.0

0.0

0.5

0.1

0.2

0.1

Grand 23-May-14 31
5-Jun-14 22

0.0
2.5

0.0
1.1

0.1
0.0

0.1
0.0

8.7
1.2

0.9
0.5

0.0
0.1

0.0
0.1

6.9
1.1

1.0
0.3

0.1
1.8

0.0
0.8

11-Jun-15 27

0.7

0.2

0.2

0.1

2.4

0.3

0.0

0.0

1.4

0.4

0.2

0.1

9-Jun-15

40

0.0

0.0

0.5

0.1

14.7

1.4

0.0

0.0

0.8

0.2

0.0

0.0

Houghton 20-May-15 10
21-May-15 17
27-May-15 31

0.7
9.7
4.4

0.5
4.6
1.4

0.3
0.9
5.9

0.3
0.5
1.1

7.1
9.4
23.0

3.0
3.4
3.0

0.2
0.3
0.5

0.2
0.2
0.2

1.4
1.4
0.0

0.8
0.4
0.0

0.1
9.5
0.4

0.1
5.1
0.2

Hubbard 6-Jun-14
19-Jun-14

7
4

0.0
0.3

0.0
0.3

0.4
0.3

0.3
0.3

0.7
0.0

0.4
0.0

0.0
2.5

0.0
0.9

0.0
0.0

0.0
0.0

0.0
0.0

0.0
0.0

Lansing 30-Apr-14
6-May-14
16-May-14
27-May-14

21
20
13
18

0.0
0.0
0.1
1.4

0.0
0.0
0.1
0.8

0.0
0.2
0.0
0.4

0.0
0.1
0.0
0.3

0.1
0.7
1.0
2.4

0.1
0.2
0.4
1.0

0.0
0.0
0.0
0.1

0.0
0.0
0.0
0.1

0.9
2.5
2.3
4.6

0.6
0.5
0.8
1.1

0.0
0.0
0.0
0.3

0.0
0.0
0.0
0.3

7-May-15 18
13-May-15 28
19-May-15 17

0.0
0.1
1.2

0.0
0.1
0.5

0.0
0.1
0.9

0.0
0.1
0.3

0.6
0.6
6.7

0.3
0.2
1.0

0.0
0.0
0.2

0.0
0.0
0.1

1.6
3.0
1.8

0.4
0.6
0.5

0.0
0.0
0.2

0.0
0.0
0.1

Lobdell 11-May-14 6

0.0

0.0

0.0

0.0

0.3

0.3

0.0

0.0

2.7

1.4

0.2

0.2

24-May-14 18
5-Jun-14 30

0.1
4.5

0.1
1.0

0.0
2.7

0.0
0.9

1.6
2.4

0.4
0.5

0.0
0.0

0.0
0.0

0.7
3.9

0.2
1.1

0.0
3.6

0.0
1.3

28-May-15 24

1.7

0.5

1.4

0.4

4.7

0.7

0.0

0.0

18.1

3.0

0.0

0.0

Higgins

Long

87

Table A9 cont.
Lake

Date

N

Bosmina

Calanoid

Cyclopoid

Daphnia

Nauplii

Other

Mean SE Mean SE Mean SE Mean SE Mean SE Mean SE
Mullett

5
5

2.8
0.4

1.9
0.2

0.0
6.0

0.0
3.7

25.8
18.0

9.0
5.9

0.0
0.0

0.0
0.0

0.8
0.0

0.5
0.0

0.0
0.0

0.0
0.0

19-May-12 5
31-May-12 5
5-Jun-12 10

0.2
4.6
4.7

0.2
1.8
1.5

0.0
1.0
2.5

0.0
0.3
1.2

14.0
3.2
11.0

3.8
2.7
3.2

0.0
0.0
0.3

0.0
0.0
0.2

6.0
0.0
0.8

2.1
0.0
0.4

0.0
0.0
0.2

0.0
0.0
0.2

15-May-13 1
24-May-13 9

0.0
0.0

.
0.0

0.0
0.1

.
0.1

1.0
1.9

.
1.1

0.0
0.0

.
0.0

3.0
1.7

.
1.3

0.0
0.0

0.0
0.0

6-May-14 21
17-May-14 3

0.2
0.0

0.1
0.0

1.1
0.0

0.3
0.0

4.4
0.3

0.7
0.3

0.0
0.0

0.0
0.0

4.9
3.3

1.1
1.5

0.0
0.3

0.0
0.3

30-Apr-15 18
12-May-15 11
14-May-15 28

0.0
0.0
0.2

0.0
0.0
0.1

0.0
0.0
0.0

0.0
0.0
0.0

1.3
1.0
0.1

0.3
0.2
0.1

0.0
0.0
0.0

0.0
0.0
0.0

5.4
1.2
2.8

0.8
0.4
0.4

0.0
0.0
0.0

0.0
0.0
0.0

25-Apr-14
5-May-14
8-May-14
12-May-14
28-May-14

8
13
25
25
26

0.0
0.0
0.0
0.0
0.5

0.0
0.0
0.0
0.0
0.2

0.0
0.0
0.2
0.0
0.1

0.0
0.0
0.2
0.0
0.1

0.4
0.6
2.8
0.8
5.0

0.2
0.3
0.9
0.2
1.2

0.0
0.0
0.0
0.0
0.3

0.0
0.0
0.0
0.0
0.2

4.9
2.3
3.1
5.4
1.6

1.5
0.9
0.5
0.8
0.5

0.3
0.0
0.0
0.0
0.0

0.3
0.0
0.0
0.0
0.0

28-Apr-15
13-May-15
19-May-15
1-Jun-15

30
30
20
20

0.0
0.0
2.6
3.1

0.0
0.0
0.9
0.8

0.0
0.0
0.2
0.8

0.0
0.0
0.1
0.2

0.7
1.2
2.8
1.0

0.2
0.3
0.7
0.3

0.0
0.2
0.3
1.9

0.0
0.1
0.1
0.5

10.5
8.7
4.0
2.3

1.3
1.1
1.1
0.9

0.0
0.1
0.6
0.7

0.0
0.1
0.4
0.4

Pickerel 7-May-11 5
17-May-11 5
3-Jun-11 5

0.0
0.0
34.2

0.0
0.0
7.6

0.0
0.0
15.6

0.0
0.0
1.3

0.0
9.2
69.0

0.0
1.9
9.0

0.0
0.0
0.0

0.0
0.0
0.0

1.2
8.2
6.6

0.6
3.5
4.9

0.0
0.2
1.2

0.0
0.2
1.2

9-May-12 5
21-May-12 5
3-Jun-12 1

0.4
10.6
64.0

0.4
7.1
.

0.0
2.4
3.0

0.0
0.8
.

13.0
28.4
8.0

0.5
7.6
.

0.0
0.0
4.0

0.0
0.0
.

7.0
4.4
0.0

2.1
2.9
.

0.2
0.0
0.0

0.2
0.0
0.0

Ovid

Park

2-Jun-11
12-Jun-11

88

Table A9 cont.
Lake

Date

N

Bosmina

Calanoid

Cyclopoid

Daphnia

Nauplii

Other

Mean SE Mean SE Mean SE Mean SE Mean SE Mean SE
Pickerel 6-May-13
13-May-13
20-May-13
27-May-13

5
5
5
5

0.0
0.0
0.2
5.0

0.0
0.0
0.2
1.8

0.0
0.0
0.4
0.2

0.0
0.0
0.4
0.2

0.0
1.6
6.8
4.8

0.0
0.6
1.4
1.2

0.0
0.0
0.0
0.0

0.0
0.0
0.0
0.0

0.4
0.4
0.2
0.4

0.2
0.4
0.2
0.2

0.0
0.0
0.0
1.2

0.0
0.0
0.0
0.7

27-May-15 17

0.0

0.0

0.0

0.0

0.2

0.2

0.0

0.0

3.2

0.8

0.1

0.1

Table A10. Average proportion of zooplankton prey (Pi) taxa per larval gut by lake-day combo
for eutrophic systems with the mean, minimum (Min), and maximum (Max) proportion.
Lake
Houghton

Date
Bosmina Calanoid Cyclopoid
20-May-15
0.072
0.031
0.732
21-May-15
0.311
0.030
0.302
27-May-15
0.129
0.172
0.672

Lobdell

11-May-14

0.000

0.000

0.105

0.000

0.842

0.053

Ovid

6-May-14
17-May-14
30-Apr-15
12-May-15
14-May-15

0.018
0.000
0.000
0.000
0.057

0.104
0.000
0.000
0.000
0.000

0.416
0.083
0.198
0.458
0.034

0.000
0.000
0.000
0.000
0.011

0.462
0.833
0.802
0.542
0.898

0.000
0.083
0.000
0.000
0.000

0.065
0.000
0.311

0.037
0.000
0.172

0.333
0.034
0.732

0.006
0.000
0.021

0.507
0.000
0.898

0.050
0.000
0.304

Mean proportion
Min
Max

89

Daphnia
0.021
0.009
0.014

Nauplii
Other
0.144
0.000
0.043
0.304
0.000
0.012

Table A11. Average proportion of zooplankton prey (Pi) taxa per larval gut by lake-day combo
for mesotrophic systems with the mean, minimum (Min), and maximum (Max) proportion.
Lake
Black

Crooked

Grand

Lansing

Long

Park

Mean proportion
Min
Max

Date
Bosmina Calanoid Cyclopoid
4-Jun-14
0.000
0.000
0.538
18-Jun-14
0.000
0.000
0.008
28-May-15
0.000
0.336
0.399
4-Jun-15
0.002
0.000
0.007
5-Jun-15
0.057
0.006
0.107
16-May-11
0.000
0.000
0.770
6-Jun-11
0.000
0.000
0.762
13-Apr-12
0.000
0.000
0.000
14-May-12
0.036
0.096
0.747
22-May-12
0.231
0.144
0.625
30-May-12
0.265
0.059
0.176
7-May-13
0.000
0.000
0.042
14-May-13
0.000
0.000
0.455
21-May-13
0.095
0.048
0.619
28-May-13
0.464
0.099
0.331
27-May-15
0.100
0.000
0.000
23-May-14
0.000
0.006
0.552
5-Jun-14
0.382
0.000
0.181
11-Jun-15
0.143
0.032
0.524
30-Apr-14
0.000
0.000
0.053
6-May-14
0.000
0.045
0.197
16-May-14
0.023
0.000
0.295
27-May-14
0.157
0.048
0.265
7-May-15
0.000
0.000
0.263
13-May-15
0.029
0.019
0.152
19-May-15
0.112
0.085
0.606
24-May-14
0.047
0.000
0.674
5-Jun-14
0.261
0.158
0.138
28-May-15
0.065
0.053
0.182
25-Apr-14
0.000
0.000
0.070
5-May-14
0.000
0.000
0.211
8-May-14
0.000
0.039
0.454
12-May-14
0.000
0.000
0.130
28-May-14
0.071
0.015
0.663
28-Apr-15
0.000
0.000
0.065
13-May-15
0.003
0.000
0.116
19-May-15
0.267
0.015
0.287
1-Jun-15
0.341
0.089
0.106
0.083
0.000
0.464

0.037
0.000
0.336

90

0.310
0.000
0.770

Daphnia
0.077
0.000
0.015
0.000
0.000
0.000
0.000
0.000
0.012
0.000
0.500
0.000
0.000
0.048
0.000
0.000
0.000
0.007
0.000
0.000
0.000
0.000
0.006
0.000
0.010
0.016
0.000
0.002
0.000
0.000
0.000
0.000
0.000
0.036
0.000
0.020
0.026
0.212
0.026
0.000
0.500

Nauplii
Other
0.385
0.000
0.602
0.391
0.243
0.007
0.991
0.000
0.830
0.000
0.230
0.000
0.238
0.000
1.000
0.000
0.072
0.036
0.000
0.000
0.000
0.000
0.958
0.000
0.545
0.000
0.190
0.000
0.106
0.000
0.900
0.000
0.437
0.004
0.160
0.270
0.302
0.000
0.947
0.000
0.758
0.000
0.682
0.000
0.500
0.024
0.737
0.000
0.790
0.000
0.165
0.016
0.279
0.000
0.230
0.211
0.700
0.000
0.907
0.023
0.789
0.000
0.507
0.000
0.870
0.000
0.214
0.000
0.935
0.000
0.861
0.000
0.405
0.000
0.251
0.000
0.519
0.000
1.000

0.026
0.000
0.391

Table A12. Average proportion of zooplankton prey (Pi) taxa per larval gut by lake-day combo
for oligotrophic systems with the mean, minimum (Min), and maximum (Max) proportion.
Lake
Burt

Date
Bosmina Calanoid Cyclopoid
21-May-11
0.000
0.000
0.200
4-Jun-11
0.052
0.066
0.873
10-Jun-11
0.696
0.109
0.101
8-May-12
0.000
0.018
0.564
18-May-12
0.000
0.087
0.826
31-May-12
0.004
0.617
0.306
6-Jun-12
0.183
0.319
0.292
8-May-13
0.000
0.000
0.500
22-May-13
0.000
0.048
0.405
31-May-13
0.178
0.011
0.656
28-May-15
0.000
0.128
0.615
6-Jun-15
0.158
0.246
0.404

Daphnia
0.000
0.000
0.094
0.000
0.000
0.017
0.175
0.000
0.000
0.000
0.000
0.000

Nauplii
Other
0.800
0.000
0.009
0.000
0.000
0.000
0.418
0.000
0.087
0.000
0.056
0.000
0.000
0.031
0.500
0.000
0.548
0.000
0.156
0.000
0.256
0.000
0.175
0.018

Higgins

9-Jun-15

0.000

0.030

0.919

0.000

0.052

0.000

Hubbard

6-Jun-14
19-Jun-14

0.000
0.083

0.375
0.083

0.625
0.000

0.000
0.833

0.000
0.000

0.000
0.000

Mullett

2-Jun-11
12-Jun-11
19-May-12
31-May-12
5-Jun-12
15-May-13
24-May-13

0.095
0.016
0.010
0.523
0.241
0.000
0.000

0.000
0.246
0.000
0.114
0.128
0.000
0.030

0.878
0.738
0.693
0.364
0.564
0.250
0.515

0.000
0.000
0.000
0.000
0.015
0.000
0.000

0.027
0.000
0.297
0.000
0.041
0.750
0.455

0.000
0.000
0.000
0.000
0.010
0.000
0.000

Pickerel

7-May-11
17-May-11
3-Jun-11
9-May-12
21-May-12
3-Jun-12
6-May-13
13-May-13
20-May-13
27-May-13
27-May-15

0.000
0.000
0.270
0.019
0.231
0.810
0.000
0.000
0.026
0.481
0.000

0.000
0.000
0.123
0.000
0.052
0.038
0.000
0.000
0.053
0.019
0.000

0.000
0.529
0.545
0.631
0.620
0.101
0.000
0.800
0.895
0.462
0.069

0.000
0.000
0.000
0.000
0.000
0.051
0.000
0.000
0.000
0.000
0.000

1.000
0.471
0.052
0.340
0.096
0.000
1.000
0.200
0.026
0.038
0.931

0.000
0.000
0.009
0.010
0.000
0.000
0.000
0.000
0.000
0.000
0.000

0.124
0.000
0.810

0.089
0.000
0.617

0.483
0.000
0.919

0.036
0.000
0.833

0.266
0.000
1.000

0.002
0.000
0.031

Mean proportion
Min
Max

91

Table A13. Mean number of major zooplankton size groups per larval gut by date with Standard
Error (SE) of the mean, and number of samples collected and analyzed (N) for each lake-day
sampling event.
Lake

Date

N

<0.2

0.2 to <0.4 0.4 to < 0.6 0.6 to <0.8 0.8 to < 1.0

> 1.0

Mean

SE

Mean

SE

Mean

SE

4-Jun-14 13
.
18-Jun-14 15 51.8

.
18.2

1.5
81.5

0.5
17.1

4
3.0

.
.

1.5
.

0.5
.

.
.

.
.

.
.

.
.

28-May-15 28
4-Jun-15 4
5-Jun-15 9

8.9
7.0
3.1

3.4
1.8
0.7

10.8
2.9
3.3

3.7
0.8
0.5

3.7
1.0
4.0

1.5
.
0.7

.
.
2.2

.
.
0.3

1.0
.
2.1

.
.
0.3

.
.
1.5

.
.
0.3

21-May-11 5
4-Jun-11 5
10-Jun-11 5

2.0
.
2.0

.
.
1.0

4.0
6.8
5.3

2.0
1.7
3.4

17.2
10.6
3.3

3.6
1.5
1.9

20.2
12.7
2.7

4.6
4.6
0.9

1.7
9.9
5.0

0.3
2.9
2.0

1.7
2.3
2.5

0.3
0.6
0.5

8-May-12
18-May-12
31-May-12
6-Jun-12

5
5
5
9

4.7
.
.
4.0

1.3
.
.
.

7.0
2.0
16.0
2.5

1.7
.
4.1
0.5

3.0
.
5.0
7.8

1.0
.
1.6
1.6

1.5
.
4.6
2.0

0.5
.
1.2
.

1.0
.
2.0
1.5

.
.
0.0
0.5

.
.
2.0
1.0

.
.
1.0
.

8-May-13 3
22-May-13 5
31-May-13 5

1.0
2.0
1.3

0.0
1.0
0.2

1.0
7.7
1.0

0.0
4.2
0.0

.
3.3
1.6

.
2.3
0.2

.
5.0
1.6

.
.
0.2

.
.
.

.
.
.

.
.
1.0

.
.
.

28-May-15 21
6-Jun-15 4

1.3
1.0

0.3
0.0

11.2
5.6

2.4
0.9

34.6
9.0

5.9
4.4

48.0 23.6
3.0 0.0

8.6
2.0

5.2
1.0

1.0
.

.
.

Crooked 5-May-11 5
16-May-11 5
6-Jun-11 5

5.5
4.8
1.0

1.2
1.4
0.0

7.3
1.3
.

2.3
0.3
.

36.0
1.0
.

10.9
.
.

19.0
.
.

.
.
.

.
.
.

.
.
.

.
.
.

.
.
.

1.0
2.3
2.0
1.0

0.0
1.0
0.0
0.0

3.6
1.8
7.7
2.7

0.4
0.5
0.3
1.2

5.4
1.5
8.0
1.3

1.9
0.3
2.1
0.3

5.2
.
.
2.0

1.7
.
.
1.0

2.0
.
.
1.0

0.6
.
.
.

1.0
.
.
.

0.0
.
.
.

Black

Burt

13-Apr-12
14-May-12
22-May-12
30-May-12

5
5
4
4

92

Mean SE Mean SE Mean SE

Table A13 cont.
Lake

Date

N

<0.2

0.2 to <0.4 0.4 to < 0.6 0.6 to <0.8 0.8 to < 1.0

> 1.0

Mean

SE

Mean

SE

Mean

SE

1.0
.
1.2
5.0

0.0
.
0.1
4.0

2.7
13.0
1.0
15.2

1.2
6.4
0.0
3.1

1.3
26.3
.
9.3

0.3
6.4
.
3.2

2.0
4.3
.
8.3

1.0
0.9
.
5.3

1.0
4.3
.
1.3

.
0.9
.
0.3

.
1.5
.
.

.
0.5
.
.

.

.

4.5

1.5

1.5

0.5

2.0

1.0

4.5

1.5

3.0

.

Grand 23-May-14 31
5-Jun-14 22

4.5
1.8

1.5
0.5

5.5
2.6

1.7
0.3

3.0
1.9

0.7
0.3

3.5
1.7

1.5
0.4

.
.

.
.

.
.

.
.

11-Jun-15 27

2.1

0.5

10.1

1.4

5.2

0.8

3.0

0.6

.

.

.

.

9-Jun-15

1.0

0.0

2.7

0.4

7.6

0.8

6.7

0.7

1.8

0.2

1.0

0.0

Houghton 20-May-15 10 3.5
21-May-15 17 19.2
27-May-15 31
.

1.2
8.7
.

3.7
13.3
9.1

1.3
5.0
2.1

12.8
8.3
17.3

1.3
2.6
2.5

2.8
5.3
8.0

0.5
1.8
1.5

3.7
2.8
5.2

0.9
1.0
1.0

.
1.6
3.8

.
0.4
0.9

Crooked 7-May-13
14-May-13
21-May-13
28-May-13

5
5
5
5

27-May-15 20

Higgins

40

Mean SE Mean SE Mean SE

Hubbard 6-Jun-14
19-Jun-14

7
4

.
.

.
.

1.0
1.0

.
.

.
.

.
.

.
1.0

.
.

2.0
1.0

.
.

2.5
.

0.5
.

Lansing 30-Apr-14
6-May-14
16-May-14
27-May-14

21
20
13
18

2.1
2.0
3.3
2.0

0.4
0.8
0.7
0.5

1.9
3.1
2.5
3.1

0.3
0.7
0.4
1.0

1.8
.
1.8
1.6

0.6
.
0.5
0.4

.
.
1.0
.

.
.
0.0
.

1.0
.
.
.

.
.
.
.

.
.
.
.

.
.
.
.

7-May-15 18
13-May-15 28
19-May-15 17

2.0
4.1
3.0

0.3
0.7
2.0

5.1
6.4
3.3

0.6
1.4
1.3

4.9
4.1
.

0.9
1.2
.

2.7
.
.

1.0
.
.

1.3
.
.

0.3
.
.

1.0
.
.

.
.
.

Lobdell 11-May-14 6

4.3

1.7

.

.

.

.

2.0

.

.

.

.

.

7.4
1.2

2.2
0.2

9.0
1.5

1.4
0.4

4.2
2.2

1.2
0.4

3.4
1.0

1.0
0.0

5.3
1.0

2.2
.

2.0
.

0.4
.

28-May-15 24 11.6

1.7

15.6

2.6

4.1

0.8

2.5

0.3

3.5

0.5

1.0

0.0

Long

24-May-14 18
5-Jun-14 30

93

Table A13 cont.

Lake

Date

N

<0.2

0.2 to <0.4 0.4 to < 0.6 0.6 to <0.8 0.8 to < 1.0

> 1.0

Mean

SE

Mean

SE

Mean

SE

5
5

1.5
.

0.5
.

4.5
4.0

2.0
0.9

17.2
5.7

6.5
1.3

8.3
9.7

1.6
3.8

3.5
4.3

1.5
1.5

.
2.0

.
0.8

19-May-12 5
31-May-12 5
5-Jun-12 10

.
1.0
5.0

.
.
1.0

1.0
3.0
11.2

0.0
.
2.0

9.5
.
7.0

2.4
.
2.9

10.8
.
.

4.7
.
.

4.0
.
.

1.5
.
.

4.0
.
.

1.0
.
.

15-May-13 1
24-May-13 9

5.0
1.0

1.0
.

3.8
3.0

1.9
1.4

3.0
3.8

1.0
1.0

1.0
1.5

0.0
0.5

.
2.5

.
1.5

.
1.5

.
0.5

6-May-14 21
17-May-14 3

1.9
2.3

0.3
0.8

5.9
1.6

1.1
0.4

4.2
1.0

0.7
0.0

1.8
1.0

0.4
.

1.0
.

0.0
.

.
.

.
.

30-Apr-15 18
12-May-15 11
14-May-15 28

1.7
2.7
3.1

0.2
1.2
1.0

3.0
1.3
5.0

0.4
0.3
0.5

1.0
.
1.9

.
.
0.3

.
.
.

.
.
.

.
.
.

.
.
.

.
.
.

.
.
.

25-Apr-14
5-May-14
8-May-14
12-May-14
28-May-14

8
13
25
25
26

5.4
1.7
3.2
4.6
4.9

1.4
0.3
0.5
0.6
0.5

4.6
3.1
5.1
3.0
5.5

0.8
1.2
1.0
0.4
0.8

2.4
1.0
1.4
1.0
1.3

0.6
.
0.2
0.0
0.1

2.6
.
1.0
.
2.5

0.7
.
0.0
.
0.7

1.6
.
.
.
1.0

0.3
.
.
.
.

1.0
.
.
.
.

0.0
.
.
.
.

28-Apr-15
13-May-15
19-May-15
1-Jun-15

30
30
20
20

4.1
4.0
3.5
8.8

0.6
1.5
0.7
1.1

4.8
5.0
3.1
4.0

1.1
1.3
0.6
0.7

1.4
1.0
3.5
1.1

0.2
0.0
1.9
0.1

4.5
.
7.1
.

1.5
.
1.8
.

1.0
.
1.4
.

0.0
.
0.2
.

1.0
.
1.0
.

.
.
0.0
.

Pickerel 7-May-11 5
17-May-11 5
3-Jun-11 5

8.0
.
1.0

3.1
.
0.0

39.2
61.0
.

3.2
.
.

56.8
9.0
.

7.1
.
.

9.8
5.0
.

3.2
.
.

10.0
4.0
.

1.1
.
.

5.0
.
.

1.7
.
.

9-May-12 5
21-May-12 5
3-Jun-12 1

2.0
7.5
2.0

0.6
2.3
.

.
2.0
1.0

.
0.4
.

.
11.2
2.3

.
0.9
0.7

.
3.0
.

.
0.0
.

.
.
.

.
.
.

.
.
.

.
.
.

Mullett

Ovid

Park

2-Jun-11
12-Jun-11

94

Mean SE Mean SE Mean SE

Table A13 cont.

Lake

Date

N

<0.2

0.2 to <0.4 0.4 to < 0.6 0.6 to <0.8 0.8 to < 1.0

> 1.0

Mean

SE

Mean

SE

Mean

SE

5
5
5
5

5.2
.
10.0
2.3

1.3
.
.
1.3

8.2
2.4
17.3
7.0

4.7
0.9
12.2
1.4

6.3
6.3
21.6
3.0

1.2
1.9
8.0
0.6

2.0
2.3
9.0
2.0

.
1.3
3.5
1.0

.
.
1.0
.

.
.
0.0
.

.
.
1.0
.

.
.
.
.

27-May-15 17

3.4

0.7

2.0

0.5

.

.

.

.

.

.

.

.

Pickerel 6-May-13
13-May-13
20-May-13
27-May-13

Mean SE Mean SE Mean SE

Table A14. Average proportion of zooplankton prey (Pi) size group per larval gut by lake-day
combo for eutrophic systems with the mean, minimum (Min), and maximum (Max) proportion.
Lake
Houghton

Date
20-May-15
21-May-15
27-May-15

<0.2
0.143
0.326
0.000

0.2 to <0.4
0.112
0.377
0.200

0.4 to < 0.6
0.520
0.189
0.497

Lobdell

11-May-14

0.895

0.000

0.000

0.105

0.000

0.000

Ovid

6-May-14
17-May-14
30-Apr-15
12-May-15
14-May-15

0.086
0.667
0.231
0.375
0.193

0.484
0.333
0.661
0.458
0.795

0.357
0.000
0.107
0.125
0.011

0.063
0.000
0.000
0.042
0.000

0.009
0.000
0.000
0.000
0.000

0.000
0.000
0.000
0.000
0.000

Mean Proportion

0.324

0.380

0.201

0.060

0.025

0.010

Min

0.000

0.000

0.000

0.000

0.000

0.000

Max

0.895

0.795

0.520

0.145

0.112

0.074

95

0.6 to <0.8 0.8 to < 1.0
0.112
0.112
0.070
0.021
0.145
0.084

> 1.0
0.000
0.017
0.074

Table A15. Average proportion of zooplankton prey (Pi) size group per larval gut by lake-day
combo for mesotrophic systems with the mean, minimum (Min), and maximum (Max)
proportion.
Lake
Black

Date
4-Jun-14
18-Jun-14
28-May-15
4-Jun-15
5-Jun-15

<0.2
0.000
0.766
0.105
0.386
0.388

0.2 to <0.4
0.462
0.227
0.263
0.608
0.538

0.4 to < 0.6
0.308
0.008
0.312
0.006
0.069

0.6 to <0.8
0.231
0.000
0.192
0.000
0.000

0.8 to < 1.0
0.000
0.000
0.102
0.000
0.006

> 1.0
0.000
0.000
0.026
0.000
0.000

Crooked

16-May-11
6-Jun-11
13-Apr-12
14-May-12
22-May-12
30-May-12
7-May-13
14-May-13
21-May-13
28-May-13
27-May-15

0.098
0.113
1.000
0.063
0.000
0.000
0.792
0.409
0.100
0.068
0.857

0.377
0.149
0.000
0.375
0.325
0.333
0.167
0.318
0.400
0.514
0.143

0.525
0.738
0.000
0.563
0.494
0.111
0.042
0.273
0.250
0.250
0.000

0.000
0.000
0.000
0.000
0.081
0.148
0.000
0.000
0.200
0.169
0.000

0.000
0.000
0.000
0.000
0.081
0.333
0.000
0.000
0.050
0.000
0.000

0.000
0.000
0.000
0.000
0.019
0.074
0.000
0.000
0.000
0.000
0.000

Grand

23-May-14
5-Jun-14
11-Jun-15

0.039
0.267
0.138

0.622
0.570
0.462

0.308
0.111
0.254

0.031
0.052
0.146

0.000
0.000
0.000

0.000
0.000
0.000

Lansing

30-Apr-14
6-May-14
16-May-14
27-May-14
7-May-15
13-May-15
19-May-15

0.316
0.409
0.286
0.268
0.263
0.472
0.085

0.684
0.439
0.524
0.536
0.737
0.443
0.410

0.000
0.136
0.190
0.196
0.000
0.066
0.388

0.000
0.000
0.000
0.000
0.000
0.019
0.085

0.000
0.015
0.000
0.000
0.000
0.000
0.021

0.000
0.000
0.000
0.000
0.000
0.000
0.011

Long

24-May-14
5-Jun-14
28-May-15

0.140
0.249
0.298

0.279
0.503
0.577

0.465
0.117
0.085

0.093
0.048
0.016

0.023
0.042
0.011

0.000
0.042
0.011

Park

25-Apr-14
5-May-14
8-May-14
12-May-14
28-May-14
28-Apr-15
13-May-15
19-May-15
1-Jun-15

0.273
0.316
0.336
0.623
0.145
0.652
0.405
0.314
0.255

0.682
0.658
0.605
0.364
0.306
0.321
0.510
0.440
0.406

0.045
0.026
0.046
0.013
0.145
0.027
0.049
0.082
0.151

0.000
0.000
0.013
0.000
0.368
0.000
0.033
0.130
0.094

0.000
0.000
0.000
0.000
0.036
0.000
0.003
0.024
0.073

0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.010
0.021

Mean Proportion

0.308

0.428

0.180

0.057

0.022

0.006

Min

0.000

0.000

0.000

0.000

0.000

0.000

Max

1.000

0.737

0.738

0.368

0.333

0.074

96

Table A16. Average proportion of zooplankton prey (Pi) size group per larval gut by lake-day
combo for oligotrophic systems with the mean, minimum (Min), and maximum (Max)
proportion.
Lake
Burt

Date
21-May-11
4-Jun-11
10-Jun-11
8-May-12
18-May-12
31-May-12
6-Jun-12
8-May-13
22-May-13
31-May-13
28-May-15
6-Jun-15

<0.2
0.400
0.010
0.000
0.255
0.089
0.008
0.000
0.000
0.095
0.022
0.200
0.071

0.2 to <0.4 0.4 to < 0.6 0.6 to <0.8 0.8 to < 1.0
0.600
0.000
0.000
0.000
0.058
0.417
0.490
0.024
0.580
0.181
0.167
0.043
0.509
0.164
0.055
0.018
0.111
0.689
0.044
0.067
0.118
0.366
0.507
0.000
0.164
0.256
0.307
0.240
1.000
0.000
0.000
0.000
0.548
0.238
0.119
0.000
0.311
0.500
0.100
0.067
0.100
0.475
0.200
0.000
0.286
0.179
0.143
0.179

Higgins

9-Jun-15

0.003

0.097

0.453

0.378

0.059

0.009

Hubbard

6-Jun-14
19-Jun-14

0.000
0.000

0.125
0.083

0.000
0.000

0.000
0.083

0.250
0.083

0.625
0.750

Mullett

2-Jun-11
12-Jun-11
19-May-12
31-May-12
5-Jun-12
15-May-13
24-May-13

0.020
0.000
0.099
0.025
0.000
0.250
0.303

0.122
0.017
0.554
0.300
0.186
0.750
0.455

0.585
0.322
0.347
0.475
0.294
0.000
0.182

0.224
0.458
0.000
0.075
0.299
0.000
0.061

0.048
0.136
0.000
0.125
0.155
0.000
0.000

0.000
0.068
0.000
0.000
0.067
0.000
0.000

Pickerel 7-May-11
17-May-11
3-Jun-11
9-May-12
21-May-12
3-Jun-12
6-May-13
13-May-13
20-May-13
27-May-13
27-May-15

1.000
0.295
0.040
0.291
0.044
0.000
1.000
0.200
0.000
0.121
0.733

0.000
0.466
0.325
0.078
0.307
0.772
0.000
0.100
0.316
0.603
0.267

0.000
0.216
0.471
0.544
0.480
0.114
0.000
0.700
0.500
0.207
0.000

0.000
0.023
0.081
0.087
0.160
0.063
0.000
0.000
0.184
0.069
0.000

0.000
0.000
0.083
0.000
0.000
0.051
0.000
0.000
0.000
0.000
0.000

0.000
0.000
0.000
0.000
0.009
0.000
0.000
0.000
0.000
0.000
0.000

Mean proportion

0.169

0.395

0.189

0.109

0.065

0.059

Min

0.000

0.000

0.000

0.000

0.000

0.000

Max

1.000

1.000

0.700

0.507

0.250

0.750

97

> 1.0
0.000
0.000
0.029
0.000
0.000
0.000
0.032
0.000
0.000
0.000
0.025
0.143

BIBLIOGRAPHY

98

BIBLIOGRAPHY

Auer, N. A., and Great Lakes Fishery Commission. 1982. Identification of larval fishes of the
Great Lakes basin with emphasis on the Lake Michigan drainage. Great Lakes Fishery
Commission, Ann Arbor, Mich.
Balcer, M. D., N. L. Korda, and S. I. Dodson. 1984. Zooplankton of the Great Lakes: a guide to
the identification and ecology of the common crustacean species. Univ of Wisconsin
Press.
Barbiero, R. P., D. B. Bunnell, D. C. Rockwell, and M. L. Tuchman. 2009. Recent Increases in
the Large Glacial-Relict Calanoid Limnocalanus macrurus in Lake Michigan. Journal of
Great Lakes Research 35(2):285–292.
Barbiero, R. P., and M. L. Tuchman. 2004. Changes in the crustacean communities of Lakes
Michigan, Huron, and Erie following the invasion of the predatory cladoceran
Bythotrephes longimanus. Canadian Journal of Fisheries and Aquatic Sciences
61(11):2111–2125.
Bremigan, M. T., J. M. Dettmers, and A. L. Mahan. 2003. Zooplankton Selectivity by Larval
Yellow Perch in Green Bay, Lake Michigan. Journal of Great Lakes Research 29(3):501–
510.
Bremigan, M. T., and R. A. Stein. 1994. Gape-dependent larval foraging and zooplankton size:
implications for fish recruitment across systems. Canadian Journal of Fisheries and
Aquatic Sciences 51(4):913–922.
Bunnell, D. B., B. M. Davis, D. M. Warner, M. A. Chriscinske, and E. F. Roseman. 2011.
Planktivory in the changing Lake Huron zooplankton community: Bythotrephes
consumption exceeds that of Mysis and fish. Freshwater Biology 56(7):1281–1296.
Chesson, J. 1978. Measuring preference in selective predation. Ecology:211–215.
Chesson, J. 1983. The estimation and analysis of preference and its relatioship to foraging
models. Ecology:1297–1304.
Clady, M. D. 1976. Influence of temperature and wind on the survival of early stages of yellow
perch, Perca flavescens. Journal of the Fisheries Board of Canada 33(9):1887–1893.
Cleveland, W. S. 1979. Robust locally weighted regression and smoothing scatterplots. Journal
of the American statistical association 74(368):829–836.

99

Cleveland, W. S., and S. J. Devlin. 1988. Locally weighted regression: an approach to regression
analysis by local fitting. Journal of the American Statistical Association 83(403):596–
610.
Craig, J. F. 2008. Percid fishes: systematics, ecology and exploitation. John Wiley & Sons.
Cushing, D. H. 1990. Plankton production and year-class strength in fish populations: an update
of the match/mismatch hypothesis. Advances in marine biology 26:249–293.
Dettmers, J. M., M. J. Raffenberg, and A. K. Weis. 2003. Exploring zooplankton changes in
southern Lake Michigan: implications for yellow perch recruitment. Journal of Great
Lakes Research 29(2):355–364.
Farmer, T. M., E. A. Marschall, K. Dabrowski, and S. A. Ludsin. 2015. Short winters threaten
temperate fish populations. Nature communications 6.
Fielder, D. G., and M. V. Thomas. 2006. Fish Population Dynamics of Saginaw Bay, Lake
Huron, 1998-2004. Michigan Department of Natural Resources, Fisheries Division.
Fulford, R. S., J. A. Rice, T. J. Miller, and F. P. Binkowski. 2006a. Elucidating patterns of sizedependent predation on larval yellow perch (Perca flavescens) in Lake Michigan: an
experimental and modeling approach. Canadian journal of fisheries and aquatic sciences
63(1):11–27.
Fulford, R. S., J. A. Rice, T. J. Miller, F. P. Binkowski, J. M. Dettmers, and B. Belonger. 2006b.
Foraging selectivity by larval yellow perch (Perca flavescens): implications for
understanding recruitment in small and large lakes. Canadian Journal of Fisheries and
Aquatic Sciences 63(1):28–42.
Graeb, B. D., J. M. Dettmers, D. H. Wahl, and C. E. CĂĄceres. 2004a. Fish size and prey
availability affect growth, survival, prey selection, and foraging behavior of larval yellow
perch. Transactions of the American Fisheries Society 133(3):504–514.
Graeb, B. D., J. M. Dettmers, D. H. Wahl, and C. E. CĂĄceres. 2004b. Fish size and prey
availability affect growth, survival, prey selection, and foraging behavior of larval yellow
perch. Transactions of the American fisheries Society 133(3):504–514.
Graeb, B. D., M. T. Mangan, J. C. Jolley, D. H. Wahl, and J. M. Dettmers. 2006. Ontogenetic
changes in prey preference and foraging ability of yellow perch: insights based on
relative energetic return of prey. Transactions of the American Fisheries Society
135(6):1493–1498.
Hayes, D. B., and W. W. Taylor. 1990. Reproductive strategy in yellow perch (Perca flavescens):
effects of diet ontogeny, mortality, and survival costs. Canadian Journal of Fisheries and
Aquatic Sciences 47(5):921–927.

100

Hayes, D. B., W. W. Taylor, and J. C. Schneider. 1992. Response of yellow perch and the
benthic invertebrate community to a reduction in the abundance of white suckers.
Transactions of the American Fisheries Society 121(1):36–53.
Holling, C. S. 1959a. The components of predation as revealed by a study of small-mammal
predation of the European pine sawfly. The Canadian Entomologist 91(05):293–320.
Holling, C. S. 1959b. Some characteristics of simple types of predation and parasitism. The
Canadian Entomologist 91(07):385–398.
Holling, C. S. 1965. The functional response of predators to prey density and its role in mimicry
and population regulation. Memoirs of the Entomological Society of Canada 97(S45):5–
60.
Houde, E. D. 1989. Subtleties and episodes in the early life of fishes. Journal of Fish Biology
35:29–38.
Houde, E. D., and R. D. Hoyt. 1987. Fish early life dynamics and recruitment variability. Page
Am. Fish. Soc. Symposium
Ivlev, V. S. 1961. Experimental ecology of the feeding of fishes. Yale University Press 1:961.
Jenkins, R. E., and N. M. Burkhead. 1994. Freshwater fishes of Virginia.
Kerfoot, W. C., M. M. Hobmeier, F. Yousef, B. M. Lafrancois, R. P. Maki, and J. K. Hirsch.
2016. A plague of waterfleas (Bythotrephes): impacts on microcrustacean community
structure, seasonal biomass, and secondary production in a large inland-lake complex.
Biological Invasions 18(4):1121–1145.
Krebs, C. J. 1989. Ecological methodology. Harper & Row New York.
Leclerc, V., P. Sirois, D. Planas, and P. BĂŠrubĂŠ. 2011. Diet and feeding success of fast-growing
yellow perch larvae and juveniles in perturbed boreal lakes. Transactions of the American
Fisheries Society 140(5):1193–1205.
Letcher, B. H., J. A. Rice, L. B. Crowder, and K. A. Rose. 1996. Variability in survival of larval
fish: disentangling components with a generalized individual-based model. Canadian
Journal of Fisheries and Aquatic Sciences 53(4):787–801.
Manly, B. F. J., P. Miller, and L. M. Cook. 1972. Analysis of a selective predation experiment.
American Naturalist:719–736.
Manning, N. F., J. M. Bossenbroek, C. M. Mayer, D. B. Bunnell, J. T. Tyson, L. G. Rudstam, J.
R. Jackson, and D. Brickman. 2014. Modeling turbidity type and intensity effects on the
growth and starvation mortality of age-0 yellow perch. Canadian Journal of Fisheries and
Aquatic Sciences 71(10):1544–1553.

101

Massicotte, P., A. Bertolo, P. Brodeur, C. Hudon, M. Mingelbier, and P. Magnan. 2015.
Influence of the aquatic vegetation landscape on larval fish abundance. Journal of Great
Lakes Research 41(3):873–880.
McCullough, D. E., E. F. Roseman, K. M. Keeler, R. L. DeBruyne, J. J. Pritt, P. A. Thompson,
S. Ireland, J. E. Ross, D. Bowser, and R. D. Hunter. 2015. Evidence of the St. ClairDetroit River System as a dispersal corridor and nursery habitat for transient larval
burbot. Hydrobiologia:1–14.
McDonald, E. A., A. S. McNaught, and E. F. Roseman. 2013. Use of main channel and two
backwater habitats by larval fishes in the Detroit River. Journal Of Great Lakes Research.
McDonnell, K. N., B. M. Roth, and J. Post. 2014. Evaluating the effect of pelagic zooplankton
community composition and density on larval walleye (Sander vitreus) growth with a
bioenergetic-based foraging model. Canadian Journal of Fisheries and Aquatic Sciences
71(7):1039–1049.
Michigan Department of Natural Resources. 2013. State Licensed Commercial Fishing Data for
Michigan.
Mills, E. L., R. Sherman, and D. S. Robson. 1989. Effect of zooplankton abundance and body
size on growth of age-0 yellow perch (Perca flavescens) in Oneida Lake, New York,
1975-86. Canadian Journal of Fisheries and Aquatic Sciences 46(5):880–886.
Nalepa, T. F., D. L. Fanslow, S. A. Pothoven, A. J. Foley, and G. A. Lang. 2007. Long-term
Trends in Benthic Macroinvertebrate Populations in Lake Huron over the Past Four
Decades. Journal of Great Lakes Research 33(2):421–436.
Patalas, K. 1972. Crustacean plankton and the eutrophication of St. Lawrence Great Lakes.
Journal of the Fisheries Board of Canada 29(10):1451–1462.
Pennak, R. W. 1953. Fresh-water invertebrates of the United States. Page Fresh-water
invertebrates of the United States. Ronald Press.
Poe, T. P. 1983. Food Habits of Larval Yellow Perch as a Potential Indicator of Water and
Habitat Quality.
Post, J. R., and D. J. McQueen. 1988. Ontogenetic changes in the distribution of larval and
juvenile yellow perch (Perca flavescens): a response to prey or predators? Canadian
Journal of Fisheries and Aquatic Sciences 45(10):1820–1826.
Roswell, C. R., S. A. Pothoven, and T. O. HÜÜk. 2013. Spatio-temporal, ontogenetic and
interindividual variation of age-0 diets in a population of yellow perch. Ecology of
Freshwater Fish 22(3):479–493.

102

Roswell, C. R., S. A. Pothoven, and T. O. HÜÜk. 2014. Patterns of age-0 yellow perch growth,
diets, and mortality in Saginaw Bay, Lake Huron. Journal of Great Lakes Research
40:123–132.
Schael, D. M., L. G. Rudstam, and J. R. Post. 1991. Gape limitation and prey selection in larval
yellow perch (Perca flavescens), freshwater drum (Aplodinotus grunniens), and black
crappie (Pomoxis nigromaculatus). Canadian Journal of Fisheries and Aquatic Sciences
48(10):1919–1925.
Sharp, G. D. 1987. Averaging the way to inadequate information in a varying world.
Siefert, R. E. 1972. First food of larval yellow perch, white sucker, bluegill, emerald shiner, and
rainbow smelt. Transactions of the American Fisheries Society 101(2):219–225.
Strauss, R. E. 1979. Reliability estimates for Ivlev’s electivity index, the forage ratio, and a
proposed linear index of food selection. Transactions of the American Fisheries Society
108(4):344–352.
Sullivan, T. J., and C. A. Stepien. 2014. Genetic diversity and divergence of yellow perch
spawning populations across the Huron–Erie Corridor, from Lake Huron through western
Lake Erie. Journal of Great Lakes Research 40:101–109.
U.S. Environmental Protection Agency (USEPA). 2003. Standard Operative Procedure for
Zooplankton Analysis. Great Lakes National Program Office Report LG403.
Vanderploeg, H. A., D. B. Bunnell, H. J. Carrick, and T. O. HÜÜk. 2015. Complex interactions in
Lake Michigan’s rapidly changing ecosystem. Elsevier.
Whiteside, M. C., C. M. Swindoll, and W. L. Doolittle. 1985. Factors affecting the early life
history of yellow perch, Perca flavescens. Environmental Biology of Fishes 12(1):47–56.
Wu, L., and D. A. Culver. 1992. Ontogenetic diet shift in Lake Erie age-0 yellow perch (Perca
flavescens): a size-related response to zooplankton density. Canadian Journal of Fisheries
and Aquatic Sciences 49(9):1932–1937.

103