Wetlands Ecol Manage (2012) 20:137–150
DOI 10.1007/s11273-012-9250-x
ORIGINAL PAPER
Chemical and physical factors associated with yellow perch
abundance in Great Lakes coastal wetlands: patterns
within and among wetland types
Aaron D. Parker • Matthew J. Cooper
Carl R. Ruetz III • David P. Coulter •
Donald G. Uzarski
•
Received: 3 March 2011 / Accepted: 23 January 2012 / Published online: 19 February 2012
Ó Springer Science+Business Media B.V. 2012
Abstract Great Lakes coastal wetlands provide
important spawning and nursery habitat as well as
abundant food resources for yellow perch (Perca
flavescens). We examined multiple years of fyke-net
data from wetlands along Lakes Huron and Michigan
to describe yellow perch distribution in drowned river
mouth (DRM) and coastal fringing systems. Principal
components analysis and multi-response permutation
A. D. Parker (&) M. J. Cooper C. R. Ruetz III
Annis Water Resources Institute, Grand Valley State
University, 740 West Shoreline Drive, Muskegon,
MI 49441, USA
e-mail: [email protected]
Present Address:
A. D. Parker
Carterville Fishery Resources Office, U.S. Fish
and Wildlife Service, 9053 Route 148, Marion,
IL 62959, USA
M. J. Cooper
Department of Biological Sciences, University of Notre
Dame, 107 Galvin Life Sciences, Notre Dame,
IN 46556, USA
procedures indicated that DRM wetlands (yellow
perch CPUE = 0.2) were eutrophic systems that often
exhibit high temperatures and periods of hypoxia,
whereas coastal fringing wetlands (yellow perch
CPUE = 32.1) were less productive. Among the
coastal fringing systems, Saginaw Bay (Lake Huron),
displayed characteristics of being more productive and
had more yellow perch. Most yellow perch captured in
Saginaw Bay were age-0, suggesting that it was an
important nursery habitat. Among DRM ecosystems,
we found that the downstream lake macrohabitats
contained more yellow perch than upstream wetlands;
however, there was no significant difference in abiotic
characteristics to explain the higher catches in lakes.
We hypothesize that yellow perch were more
prevalent in wetlands with intermediate productivity
during summer because these systems provide abundant food resources without the harsh conditions
associated with highly eutrophic wetlands.
Keywords Coastal fringing Drowned river mouth Great Lakes Perca flavescens Wetlands Yellow
perch
D. P. Coulter D. G. Uzarski
Department of Biology, Institute for Great Lakes
Research, CMU Biological Station, Central Michigan
University, 156 Brooks Hall, Mount Pleasant,
MI 48859, USA
Introduction
D. P. Coulter
Department of Forestry and Natural Resources, Purdue
University, 195 Marsteller Rd, West Lafayette,
IN 47907, USA
Coastal wetlands occupy a relatively small portion of
the Laurentian Great Lakes shoreline, yet many
different fish species use these systems as spawning,
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138
feeding, and resting areas (Jude and Pappas 1992;
Albert 2003; Uzarski et al. 2005). Over the last
100 years, about 50% of the historic Great Lakes
coastal wetlands have been lost to agricultural conversion or drainage (Krieger et al. 1992). The
remaining wetlands face anthropogenic disturbances
mainly in the form of nutrient pollution (Uzarski et al.
2005; Cooper et al. 2006) and fragmentation (Gyekis
2006; Uzarski et al. 2009).
Coastal wetlands typically form along the shorelines of the Great Lakes where some protection from
wind and wave activity is present. Areas of the Great
Lakes shoreline that are exposed to the full force of
wind, waves, heavy ice formation, and the associated
erosive forces do not develop wetlands. Because much
of the Great Lakes shoreline is continuously exposed
to one or a combination of those erosive forces, coastal
wetlands only make up a small percentage of the
overall shoreline and have a clumped distribution on
the landscape. Nearshore barriers (such as shoals or
sand spits) and/or gently sloping, shallow bathymetry
that attenuate wave energy typically provide enough
protection to facilitate wetland formation (Albert
2005). Numerous hydrogeomorphic wetland types
exist along the Great Lakes shoreline.
Three broad coastal wetland classes are lacustrine,
riverine, and barrier-enclosed (Albert et al. 2005).
Within these groups, finer classifications also were
devised yielding a total of 17 unique hydrogeomorphic
wetland types (Albert et al. 2005). Yellow perch
(Perca flavescens) have been documented in many
wetland types throughout the Great Lakes, including
open and protected embayments (lacustrine; Brazner
1997; Uzarski et al. 2005), barrier-beach lagoons
(barrier-enclosed; Brazner et al. 1998, 2001; Tanner
et al. 2004), and both open and barred drowned river
mouth (DRM) wetlands (riverine; Chubb and Liston
1986; Stephenson 1990).
Open embayment wetlands maintain direct surfacewater connection to nearshore waters and are strongly
influenced by both short- and long-term fluctuations in
lake-water level (Keough et al. 1999). Open embayments exposed to high wave energy generally contain
little detrital material, whereas protected embayments
contain more organic matter (Burton et al. 2004;
Albert et al. 2005; Cooper et al. 2009). Barrier beach
lagoons form behind sand barriers which may or may
not obstruct pelagic surface water connections to the
wetlands (Keough et al. 1999; Albert et al. 2005). Most
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Wetlands Ecol Manage (2012) 20:137–150
rivers discharging into eastern Lake Michigan have
flooded mouths, forming coastal lakes with wetlands
in their upper reaches, which are described as barred
DRM systems (Wilcox et al. 2002; Albert et al. 2005).
These are the only wetlands that form along the eastern
side of Lake Michigan.
Fish community structure in relation to environmental variables has been assessed across Great Lakes
coastal wetlands (Brazner and Beals 1997; Uzarski
et al. 2005). However, much remains to be learned
about the distributional patterns for yellow perch in
wetlands related to chemical/physical variables. Single-species assessments, especially of game fish, have
the potential to complement community studies and
aid in conservation by highlighting the importance of
wetlands to individual fish species (Casselman and
Lewis 1996).
Yellow perch are a native fish to the Great Lakes
region where they are both ecologically and economically important. Yellow perch occupy a wide variety
of habitats where they play an important role in food
webs (Becker 1983) and energy cycling (e.g. Brazner
et al. 2001). Yellow perch can be one of the most
prevalent fishes inhabiting Great Lakes coastal wetlands (Stephenson 1990; Jude and Pappas 1992;
Brazner et al. 2001). The majority of yellow perch
found in these systems are larvae (Chubb and Liston
1986; Höök et al. 2001; Tanner et al. 2004; Gyekis
2006), age-0 (Brazner 1997; Brazner et al. 1998;
2001), or spawning adults (Stephenson 1990). The
prevalence of these particular life stages in coastal
wetlands suggests that these habitats are important for
yellow perch reproduction and recruitment. Furthermore, some yellow perch that spawn in Great Lakes
coastal wetlands have been shown to eventually
emigrate to adjacent nearshore habitats where
they are commercially and recreationally exploited
(Brazner et al. 2001; 2004; Parker et al. 2009a). Parker
et al. (2009b) found that the wetlands of Saginaw Bay,
Lake Huron provided abundant food resources and
that yellow perch in those areas made the ontogenetic
niche shift to piscivory by age 1, which is earlier than
reported by others (e.g. Keast 1985). Great Lakes
coastal wetlands are typically warmer than the deeper,
adjacent waterbodies, which leads to earlier hatch
dates and thus, longer growing seasons in these
systems for yellow perch (Jude and Pappas 1992).
Longer growing seasons can lead to larger sizes
entering winter and are important for preventing
Wetlands Ecol Manage (2012) 20:137–150
overwinter mortality from starvation, intolerance to
environmental extremes, and predation (Sogard 1997).
Previous studies have indicated the importance of
multiple types of coastal wetlands for yellow perch
throughout the Great Lakes by documenting their
abundance, however, none explored the distribution of
the species across wetland types or regions along with
abiotic variables. Therefore, given that (1) yellow
perch is an ecologically and economically important
species in the Great Lakes, (2) coastal wetlands appear
to be a critical habitat for yellow perch in many areas
throughout the Great Lakes, and (3) few studies have
explained yellow perch distributions across wetland
139
types or within coastal wetlands across regions, we
describe the distribution of yellow perch and associated abiotic variables using a multi-year sampling
record of wetland fish that included 62 unique sites
along Lake Michigan and Lake Huron (Fig. 1). This
makes up the majority of the wetlands along the
Michigan shoreline of these Lakes.
Yellow perch have been documented in Muskegon
Lake, a DRM lake, during all life stages from larval
(personal observation) to adult (Ruetz et al. 2007;
Bhagat and Ruetz 2011). Chubb and Liston (1986)
documented larval yellow perch in a DRM wetland;
however, yellow perch from age-0 to the adult stage
Fig. 1 Locations of fish
sampling sites in drowned
river mouth (triangles) and
coastal fringing (circles)
wetlands along Lakes
Michigan and Huron. Sixtytwo unique sites were
sampled in total however,
some individual points on
the map represent several
different sites located in
close proximity to each
other
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140
have not been documented in high numbers in these
wetlands. Because of this apparent disparity between
DRM wetlands and lakes, we compared yellow perch
catches between the two habitat types for a subset of
sites that were sampled simultaneously.
Our objectives were to describe yellow perch
abundances throughout wetlands along Lakes Michigan and Huron related to chemical/physical properties. Specifically, our goals were to: (1) describe
yellow perch abundances in DRM and fringing Great
Lakes coastal wetlands, (2) describe yellow perch
abundances in fringing wetlands across four regions,
and (3) directly compare yellow perch abundances in
DRM coupled lake and wetland systems of eastern
Lake Michigan. We also describe chemical and
physical variables collected at the same time that fish
were sampled. The purpose of describing abiotic
variables along with yellow perch abundances
throughout the Great Lakes, particularly the coastal
fringing systems, is to generate hypotheses. Although
our spatial distribution of wetland sites is clustered by
the nature of wetland formation, we sampled a large
array of wetlands that effectively covered a large
gradient of anthropogenic disturbance. Because of the
wide array of wetlands that we sampled, we feel that
reasonable conclusions about yellow perch abundances in wetland types and regions can be made.
Methods
Study sites
We described yellow perch abundances in Lake
Michigan barred DRM wetlands as well as open and
protected embayment wetlands of northern Lakes
Michigan and Huron, and Saginaw Bay, Lake Huron
(hereafter combined and referred to as ‘coastal fringing wetlands’; Fig. 1). Yellow perch abundances are
described amongst coastal fringing wetlands but not
directly compared because of population genetic
differences that exist throughout the Great Lakes that
may confound direct comparisons over large spatial
scales (Miller 2003; Parker et al. 2009a; SepulvedaVillet et al. 2009). We did, however, directly compare
yellow perch abundances between neighboring DRM
lake and wetland habitats for 3 years when both
habitats were sampled simultaneously. Parker et al.
(2009a) found that yellow perch populations appear to
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Wetlands Ecol Manage (2012) 20:137–150
be homogenous within DRM systems, therefore, there
should be no concern about genetic differences
confounding adjacent lake-wetland comparisons.
Because Great Lakes coastal wetland formation is
limited to areas where adequate protection from
wind, wave, and ice erosion is provided, our sites
were unevenly distributed throughout our sampling
region. The margins of Saginaw Bay and portions of
Grand Traverse Bay are gently sloping and contain
numerous lacustrine, open-embayment wetlands
(Albert 2005; Albert et al. 2005). The substrate of
Saginaw Bay and Grand Traverse Bay wetlands
generally consists of a combination of sand, silt,
clay, and some gravel, with relatively little organic
sediment compared to other types of Great Lakes
coastal wetlands (Albert 2005; Albert et al. 2005;
Nelson et al. 2009). Emergent vegetation at our
study areas in Saginaw Bay and Grand Traverse Bay
was dominated by bulrushes (Schoenoplectus spp.),
which formed nearly monodominant stands at most
sites.
Coastal fringing wetlands along the northern shore
of Lakes Michigan and Huron and along the islands of
the Beaver Archipelago consist of both open and
protected embayments, many of which are distributed
among rock till/island complexes (Burton et al. 2004;
Uzarski et al. 2004; Albert et al. 2005). Like Saginaw
Bay and Grand Traverse Bay, emergent vegetation at
our study sites in northern Lakes Michigan and Huron
and the Beaver Archipelago was dominated by
bulrushes. The areas that we sampled contain the
majority of the fringing wetlands on the Michigan
shoreline of Lakes Huron and Michigan.
The DRM systems along the eastern shore of Lake
Michigan have direct surface water connections to
Lake Michigan via channels, are hydrologically
influenced by Lake Michigan, and receive riverine
inputs (Keough et al. 1999; Wilcox et al. 2002; Jude
et al. 2005). Some DRM systems, such as Muskegon
Lake, receive large riverine inflows based on
watershed area. These systems accumulate thick
organic sediments, often [2 m deep (Albert 2003;
Albert et al. 2005). Emergent vegetation within the
Lake Michigan DRM wetlands that we sampled was
heterogeneous and contained intermixed stands of
yellow pond lily (Nuphar advena), arrow arum
(Peltandra virginica), arrowhead (Sagittaria spp.),
bur reed (Sparganium spp.), water lily (Nymphaea
odorata), and cattail (Typha spp.).
Wetlands Ecol Manage (2012) 20:137–150
141
For the direct comparisons of yellow perch between
adjacent DRM lake and wetland habitats, the two
systems were delineated by identifying the confluence
of the main tributary river with the lake. Upstream
areas from the confluence were considered ‘‘wetland’’
and downstream areas considered ‘‘lake’’ macrohabitat (Cooper et al. 2007a, 2009). Within the lake and
wetland macrohabitats, we sampled three microhabitats: monodominant stands of emergent lily vegetation (‘‘lily,’’ either N. advena or Nympheae odorata),
submerged aquatic vegetation (‘‘SAV’’, usually dense
beds of Myriophyllum spicatum, which also contained
intermixed Ceratophyllum demersum, Potomogeton
crispus, and other Potomogeton spp.), and bare
sediment (‘‘bare’’). Microhabitats were randomly
chosen within each macrohabitat based on availability.
Three replicate nets were fished in each microhabitat
(18 nets total per system).
Fish sampling
Fish were sampled for multiple years in DRM and
coastal fringing wetlands (Table 1). The sampling
protocol used was the same among all sites and years
and took place from June to September (Uzarski et al.
2005; Cooper et al. 2007a, 2009). At each site, a
minimum of three fyke nets were set with the net lead
bisecting a stand of emergent vegetation. Small fyke
nets (mouth opening: 0.5-m 9 1.0-m) were fished in
water depths of 0.2–0.5 m and large fyke nets (mouth
opening: 1.0-m 9 1.0-m) were fished in water depths
of 0.5–1.0 m. Both sizes of fyke nets had 7.3-m leads,
1.8-m wings (set at a 45° angle from the lead), and
4.8-mm mesh. Since net height was the only difference
between the two net sizes, data from both net sizes
were pooled (Uzarski et al. 2005). All nets were
soaked for one net-night (usually 24 h, see Uzarski
et al. 2005 for complete description of sampling
methods). All fish captured were identified, enumerated, and released. Size measurements were made on a
subset of fish collected because only fish abundances
were a question of concern for the initial studies from
which these data originated. Therefore, all size classes
of yellow perch captured, ranging from young-of-theyear (YOY) to adult were pooled. No larval fish were
targeted or collected.
From 2004 to 2006, DRM lakes and their associated
wetlands were sampled simultaneously (Cooper et al.
2007a, 2009), allowing us to test whether yellow perch
were more abundant in lakes or adjacent wetland
habitats. Four DRM complexes were sampled in 2004:
Pentwater, White, Muskegon, and Kalamazoo. In
2005 and 2006, two additional systems were sampled:
Lincoln and Pigeon. To control for habitat within the
lake and wetland systems, we sampled the same
microhabitats (lily, SAV, and bare) within each lake
and wetland macrohabitat to avoid confounding
(Cooper et al. 2007a, 2009).
Chemical/physical measurements
Twelve chemical/physical variables were measured at
each site. Sulfate, chloride, ammonium, nitrate, soluble reactive phosphorus, and alkalinity were measured
from samples collected with 1-L acid-washed polyethylene bottles following standard methods (American Public Health Association 1998). Dissolved
oxygen, percent dissolved oxygen saturation, pH,
temperature, specific conductance, and turbidity were
measured in situ using a HydroLab DataSonde 4a
Table 1 Yellow perch total catch and catch per unit effort (CPUE) in coastal fringing and drowned river mouth wetlands
Years sampled
Yellow perch catch
Nets fished
CPUE
Coastal fringing
2001–04, 06, 08, 09
18,801
585
32.1
Drowned river mouth
2000–06
81
494
0.2
Beaver Archipeligo
2008–09
0
42
Grand Traverse Bay
2004
2
18
0.1
Northern Lakes Huron and Michigan
2001–04, 06, 08, 09
2,188
320
6.8
Saginaw Bay
2002–04, 06–09
16,611
205
81.0
All wetlands
Coastal fringing by regions
0
Yellow perch total CPUE in coastal fringing wetlands is further divided into descriptions by regions
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142
(Hach Corporation, Loveland, CO, USA). All chemical/physical measurements were taken during daylight hours at mid-depth from a boat before fish
sampling began.
Statistical analyses
Separate principal components analyses (PCAs) were
used to explore variation in the 12 chemical/physical
variables between DRM and coastal fringing wetlands, among coastal fringing systems based on
region, and between DRM lake and wetland habitats.
The DRM lake chemical/physical data were excluded
when comparing wetland types. Chemical/physical
variables were averaged over all years that a site was
sampled. To interpret PCAs, we labeled component
scores in the PCA bi-plots by wetland type (coastal
fringing (n = 47), DRM (n = 15)), and by region in
coastal fringing wetlands (Beaver Archipelago
(n = 5), Grand Traverse Bay (n = 3), northern Lake
Michigan-Huron (n = 18), and Saginaw Bay
(n = 21)), or microhabitat type in DRM systems (lake
lily, SAV, bare, wetland lily, SAV, bare). Principal
components were calculated using a correlation
matrix, which gives equal weighting to all variables
and was preferable over a covariance matrix in our
study because the units of measurement differed
among the variables used (Noy-Meir et al. 1975;
McGarigal et al. 2000). To generate hypotheses as to
whether yellow perch abundances were related to
abiotic conditions, linear and quadratic regression
models were run on transformed [loge(n ? 1)] yellow
perch CPUE versus PC (principal component)-1
scores for the coastal fringing wetlands.
We tested for statistical differences between coastal
fringing and DRM wetlands with a multi-response
permutation procedure (MRPP; Mielke 1984; Zimmerman et al. 1985). Euclidean distance measures and
a natural weighting (n/sum[n]), recommended by
Mielke (1984), were used in the MRPP, and we
defined significance as a = 0.05. Since six comparisons were made within the coastal fringing systems
based on region (Beaver Archipelago, Grand Traverse
Bay, northern Lake Huron-Michigan, and Saginaw
Bay), we Bonferroni-corrected for multiple comparisons, in order to guard against a Type I error, and
significance was defined as a = 0.008. Chemical/
physical variables were also compared using MRPP
between DRM (n = 15) and coastal fringing wetlands
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Wetlands Ecol Manage (2012) 20:137–150
(n = 37) on a subset of data for years (2001–04, 2006)
when both system types were sampled. Among coastal
fringing wetlands, we also compared chemical/physical variables between northern Lake Michigan-Huron
(n = 20) and Saginaw Bay (n = 17) and Saginaw Bay
(n = 8) and Beaver Archipelago (n = 5) on a subset
of data for years (northern Lake Michigan-Huron and
Saginaw Bay: 2002–04, 2008; Saginaw Bay and
Beaver Archipelago: 2008–09) when both regions
were sampled. These comparisons were made to guard
against confounding temporal and spatial variation in
the previous comparisons because not all wetland
types or regions were sampled in all years (Table 1).
To compare yellow perch catch per unit effort
(CPUE; defined as catch per net night) in DRM lakes
and wetlands from 2004 to 2006, we used a three-way
split-plot analysis of variance (ANOVA) to test
whether catches differed between macrohabitats (lake
and wetland), microhabitats (lily, SAV, and bare), and
their interaction (Montgomery 1991). System served
as the blocking variable, macrohabitat was the whole
plot, and microhabitat was the subplot (Cooper et al.
2007a). We used the system–macrohabitat interaction
as the whole plot error term and the system–macrohabitat–microhabitat interaction as the subplot error
term. Yellow perch CPUE was averaged over the years
sampled for the analysis: 3 years for Pentwater,
White, Muskegon, and Kalamazoo and 2 years for
Lincoln and Pigeon. Yellow perch CPUE was transformed [loge(n ? 1)] prior to analysis to homogenize
variance based on residual plots. When significant
interactions were found, Tukey’s HSD tests were
performed post hoc to identify differences.
Results
We captured a total of 81 yellow perch in 7 years of
sampling (0.2 fish net-night-1) in DRM wetlands,
whereas we captured 18,801 yellow perch in 7 years of
sampling (32.1 fish net-night-1) in coastal fringing
wetlands. Among the coastal fringing wetlands, most
yellow perch were captured in Saginaw Bay (Table 1).
Coastal fringing wetlands were sampled in 2008 and
2009, whereas DRM wetlands were not. In 2008 and
2009, 12,438 yellow perch were captured (129.6 fish
net-night-1) in coastal fringing wetlands. If the 2008
and 2009 sampling years are excluded, yellow perch
catch in coastal fringing wetlands was still
Wetlands Ecol Manage (2012) 20:137–150
143
6
A
A
8
- Coastal fringing
- DRM
6
% D.O.
D.O.
pH
4
SO4
TEMP
CL
COND
2
NO3
TURB
ALK
NH4
0
-2
PO4
-4
-4
between DRM and coastal fringing wetlands when a
subset of the entire analysis was done that only
compared years in which both wetland types were
sampled (t = -5.035, p = 0.003).
The PCA bi-plot representing the 47 coastal
fringing sites showed a clear distinction between
northern Lakes Michigan and Huron sites (including
Grand Traverse Bay and the Beaver Archipelago) and
Saginaw Bay sites in PC-1, which explained 27% of
the variability in the correlation matrix (Fig. 2b). The
MRPP confirmed our visual interpretation of differences in chemical and physical conditions between
regions (t = -11.439, p \ 0.001). Subsequent MRPP
pairwise comparisons revealed significant differences
(after Bonferroni-correction for multiple comparisons) between Saginaw Bay and northern Lakes
Huron and Michigan, Beaver Archipelago and Saginaw Bay, and Beaver Archipelago and Grand Traverse
Bay (Table 2). Similarly, when comparisons were
made on a subset of data from regions that were
sampled at the same time, we found that chemical/
physical conditions in northern Lakes Michigan and
-2
0
2
4
6
8
Principal Component 2 19%
Principal Component 2 19%
considerably higher than DRM wetlands with 6,363
(13.01 fish net-night-1) caught in coastal fringing
wetlands compared to 81 (0.2 fish net-night-1) caught
in DRM wetlands at the same time.
The PCA bi-plot representing all 62 sites showed a
clear distinction between DRM and coastal fringing
wetlands in PC-1, which explained 29% of the
variability in the chemical/physical correlation matrix
(Fig. 2a). Principal component-1 was best explained as
a gradient of anthropogenic disturbance (i.e. increasing
chloride, conductivity, and turbidity along PC-1) and
heterotrophic productivity/organic sediment accumulation (i.e. decreasing dissolved oxygen and pH along
PC-1). DRM wetlands received higher PC-1 scores and
were associated with higher chloride, conductivity,
alkalinity, and turbidity, while coastal fringing wetlands received lower PC-1 scores and were associated
with higher dissolved oxygen and pH. The MRPP
revealed a significant difference in conditions between
DRM and coastal fringing wetlands confirming our
interpretation of the PCA bi-plot (t = -3.809,
p = 0.010). We also found the same general pattern
B
B
4
2
SO4
Principal Component 2 (19%)
COND
CL
TEMP
PO4
NO3
NH4
0
ALK
TURB
-2
-4
-4
-2
0
2
4
6
Principal Component 1 27%
- Lake bare
- Lake lily
- Lake SAV
- Wetland bare
- Wetland lily
- Wetland SAV
%D.O.
CC
- Saginaw Bay
- N Lakes Huron-Michigan
- Grand Traverse Bay
- Beaver Archipelago
pH
Principal Component 1 29%
4
D.O. % D.O.
D.O.
pH
2
SRP
TEMP
NH 4
0
CL
SO 4
-2
SPC
NO 3
ALKTURB
-4
-4
-2
0
2
4
Principal Component 1 (38%)
Fig. 2 Principal components analyses of 12 chemical/physical
variables for a all wetlands b coastal fringing wetlands, and
c drowned river mouth lake and wetlands. Arrows eigenvectors
multiplied by 10 to scale to the bi-plot area (TEMP temperature,
DO dissolved oxygen, %DO percent dissolved oxygen saturation, COND specific conductance, pH, TURB, turbidity, ALK
alkalinity, NH4 ammonium, NO3 nitrate, SRP soluble reactive
phosphate, SO4 sulfate, CL chloride)
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Wetlands Ecol Manage (2012) 20:137–150
Table 2 MRPP test statistics (t) and p values for pair-wise comparisons of chemical/physical variables between different coastal
fringing wetland regions
Beaver Archipelago
Grand Traverse Bay
Northern Lakes Huron and Michigan
-4.10, 0.004
-2.91, 0.018
Grand Traverse Bay
Saginaw Bay
-8.99, <0.001
-2.64, 0.025
-1.13, 0.125
Northern Lakes Huron and Michigan
-16.41, <0.001
p values in bold indicate significance at a = 0.008
Huron differed from Saginaw Bay (t = -9.828,
p \ 0.001) and Beaver Archipelago differed from
Saginaw Bay (t = -2.646, p = 0.02).
Similar to the PCA of all 62 sites, PC-1 of the coastal
fringing analysis was best explained as a gradient of
anthropogenic disturbance (i.e. increasing chloride,
conductivity, and turbidity along PC-1) and heterotrophic productivity/organic sediment accumulation (i.e.
decreasing dissolved oxygen and pH along PC-1).
Saginaw Bay wetlands received higher PC-1 scores
and were associated with higher chloride, conductivity, and turbidity, while northern Lakes Michigan and
Huron wetlands received lower PC-1 scores and were
associated with higher pH and dissolved oxygen.
Both the linear (r2 = 0.18) and quadratic regression
models (r2 = 0.26) of yellow perch CPUE versus PC-1
scores for coastal fringing wetlands were significant
(p \ 0.001; Fig. 3), although the quadratic regression
model provided a better fit.
DRM lakes versus wetlands
Yellow perch were captured in all DRM lake and
wetland microhabitats over the 3 years they were
simultaneously sampled (Fig. 4). Overall, DRM lake
macrohabitats tended to have higher yellow perch
CPUE than their associated wetlands (Table 3).
Within the lake macrohabitats, yellow perch were
most abundant in the SAV microhabitats. Only two
yellow perch were caught in the four systems sampled
in 2004. In 2005 yellow perch were collected in all
microhabitats except wetland bare substrate and
wetland SAV and in 2006, yellow perch were
collected in all microhabitats. The interaction between
microhabitat and macrohabitat was marginally significant; macrohabitat explained most variability in
yellow perch catch (Table 3). Yellow perch CPUE at
lake-SAV sites was significantly greater than at all
other microhabitats (Table 4).
6
40
Yellow perch catch
Yellow Perch CPUE (ln + 1 transformed)
50
5
4
3
30
20
2
10
1
0
BARE LILY
Lake
0
-4
-2
0
2
4
BARE LILY
SAV
Wetland
6
Principal Component 1 Scores
Fig. 3 Regression of coastal fringing wetland yellow perch
catch and principal component 1 scores fitted with linear and
quadratic regression lines
123
SAV
Fig. 4 Yellow perch catch (±1 standard error) showing
differences between macrohabitats (lake, wetland) and among
microhabitats (bare bare sediment, lily lily habitat, SAV
submerged aquatic vegetation habitat) in Lake Michigan
drowned river mouth systems
Wetlands Ecol Manage (2012) 20:137–150
145
Table 3 Split-plot analysis of variance results for the effect of
macrohabitat (lake and wetland), microhabitat (lily, bare, and
SAV), and the interaction of macrohabitat and microhabitat on
Source of variation
average yellow perch catch in drowned river mouth systems
from 2004 to 2006
df
MS
F
p
10.30
0.024
System
5
0.71
Macrohabitat
1
2.17
Whole plot errora
5
0.21
Microhabitat
2
0.61
1.67
0.213
Microhabitat 9 Macrohabitat
2
1.11
3.07
0.069
20
0.36
Subplot error
b
System was used as the blocking variable
a
Whole plot error term was the system 9 macrohabitat effect
b
Subplot error term was the system 9 macrohabitat 9 microhabitat effect
p values in bold indicate significance at a = 0.05
Table 4 Tukey’s HSD p values for pair-wise comparisons of average yellow perch catch per net-night per microhabitat in drowned
river mouth systems from 2004 to 2006
Lake bare
Lake lily
Lake lily
Lake SAV
Wetland bare
Wetland lily
Wetland SAV
0.410
0.047
0.357
0.441
0.230
0.008
0.920
0.956
0.696
0.006
0.009
0.003
0.877
0.771
Lake SAV
Wetland bare
Wetland lily
0.656
p values in bold indicate significance at a = 0.05
When comparing the chemical/physical properties
of DRM wetlands and lakes using PCA, conditions at
some lake sites appeared more similar to wetlands and
received PC-1 and PC-2 scores that were within the
range of wetland sites (Fig. 2c). Accordingly, the
MRPP comparing lake and wetland chemical/physical
characteristics was not significant (t = -1.3,
p = 0.10).
Discussion
All wetlands
We found that yellow perch were much more abundant
in coastal fringing wetlands than DRM wetlands.
When 2008 and 2009 catches in coastal fringing
wetlands were removed so that timing was consistent
between both wetland types, there was a large
reduction in the total number of yellow perch caught.
However, the CPUE for yellow perch in coastal
fringing wetlands was still 65 times higher than in
DRM wetlands when keeping sampling years consistent. Although we did not measure all of the yellow
perch that we sampled, the vast majority that we
caught in the coastal fringing wetlands were less than
6 cm standard length (SL), which would be age-0 (e.g.
Fitzgerald et al. 2001). Thus, given our observations
on the size of yellow perch captured, and large
difference in yellow perch CPUE in DRM versus
coastal fringing wetlands, we strongly suspect that
even if we had measured a different metric such as
yellow perch biomass, we would still find the same
general distribution pattern throughout Great Lakes
coastal wetlands. For instance, Parker et al. (2009b)
captured 1,092 yellow perch throughout the Saginaw
Bay wetlands in July–August, 2004 and retained all
fish greater than 6 cm SL for diet analysis. Only 43
(3.9%) of the 1,092 yellow perch captured were
greater than 6 cm SL, and age analysis revealed that
42 were age-1 and one was age-2 (Parker et al. 2009b).
Because of the dominance of age-0 fish sampled, we
propose that coastal fringing wetlands serve as
important nursery habitat for young yellow perch.
123
146
However, the role of DRM wetlands as nursery
habitats is less clear because so few yellow perch
were captured in those habitats.
We propose that the difference in yellow perch
CPUE between DRM and coastal fringing wetlands is
likely a real phenomenon resulting from different
habitat characteristics rather than differences in fyke
net capture efficiencies between the coastal fringing
and DRM wetlands. Fyke nets have been used
successfully to capture fish in a variety of littoral
habitats (Wilcox et al. 2002; Uzarski et al. 2005; Ruetz
et al. 2007). Moreover, the fyke nets were soaked in
the same depths at both habitats (0.5–1 m), which
adequately sampled all wetland areas characterized by
emergent vegetation. Most adjacent deep-water areas
([1 m) were devoid of emergent vegetation and were
not sampled because we were interested in sampling
fish that were in the wetland habitats. Yellow perch in
DRM systems most likely inhabit deeper areas ([1 m)
adjacent to the wetlands.
Overall, DRM wetlands were more eutrophic than
coastal fringing wetlands and had lower dissolved
oxygen concentrations and pH. Our PCA results were
similar to Uzarski et al. (2005). Uzarski et al. (2005),
found three groupings using consistent sites and
parameters: sites with low PC-1 and PC-2 scores tend
to be the least disturbed, and those with high PC-1
scores and either high or low PC-2 scores, tend to be
more disturbed areas. When DRM and coastal fringing
wetland comparisons were made to only include years
when both types were sampled, DRM wetlands were
still more productive/eutrophic than coastal fringing
wetlands. DRM wetlands have a tendency to be
eutrophic because of sediment and detritus from the
rivers that is deposited in these delta-like systems
(Albert 2003; Albert et al. 2005; Jude et al. 2005).
DRM wetlands also are not subject to waves or pelagic
mixing from Lake Michigan, thus minimizing the
flushing of organic material from the wetland (Jude
et al. 2005; Nelson et al. 2009). Interestingly, and
consistent with Cooper et al. (2007b), we found that
DRM wetlands with the highest conductivity, turbidity, and chloride did not have the highest dissolved
nutrient concentrations, which contribute to eutrophication. This may be due to different sources of solutes
(e.g. urban versus agricultural land uses) or because
we measured only dissolved forms of nutrients. In the
most eutrophic and impacted systems, a large proportion of nutrients were likely sequestered in biomass
123
Wetlands Ecol Manage (2012) 20:137–150
during the summer when we sampled (Uzarski et al.
2004, 2005). Eutrophication of DRM wetlands and the
periods of low dissolved oxygen concentrations that
are associated with it, especially at night, may repel
yellow perch, which others have found as well (Coble
1982; Suthers and Gee 1986). In contrast, Cooper
(2009) found that night-time dissolved oxygen measurements in Saginaw Bay and northern Lakes Huron
and Michigan coastal fringing wetlands were rarely
hypoxic (\30% saturation), which is preferred by
yellow perch (Coble 1982; Suthers and Gee 1986) and
noon temperatures never exceeded 29°C, which are
lethal to yellow perch (Hokanson 1977).
Coastal fringing wetlands
We found that among coastal fringing wetlands,
yellow perch were more prevalent in Saginaw Bay.
Saginaw Bay had more eutrophic/productive characteristics (higher conductivity, chloride, turbidity) and
warmer temperatures than wetlands in northern Lakes
Michigan and Huron and Beaver Archipelago. Furthermore, Saginaw Bay was more eutrophic/productive than northern Lakes Huron and Michigan and
Beaver Archipelago when both systems were sampled
in the same year. Although we did not directly
measure ecosystem productivity, others have established that Saginaw Bay is a very productive ecosystem (e.g. Sprules and Munawar 1986). Saginaw Bay
had lower dissolved oxygen concentrations than the
other coastal fringing wetlands, which is characteristic
of heterotrophically-productive systems (Wetzel and
Likens 2000). Brazner (1997) found high numbers of
yellow perch in the coastal fringing wetlands of Green
Bay, which is a shallow, productive embayment
(albeit mostly at the southern end of the bay) of Lake
Michigan, located at similar latitude to Saginaw Bay.
According to Eshenroder (1977), despite Saginaw
Bay’s eutrophic status, frequent wind-mixing of the
water column maintains adequate oxygen concentrations for fish.
Yellow perch in higher latitudes generally have
shorter growing seasons than those in the lower
latitudes, which is primarily due to differences in
water temperature (Power and Van Den Heuvel 1999).
Warmer temperatures lead to early hatch dates for
yellow perch before the initial spring zooplankton
bloom (Fitzgerald et al. 2001), which are important
prey during larval (Bremigan et al. 2003) and juvenile
Wetlands Ecol Manage (2012) 20:137–150
stages (Parker et al. 2009b). Zooplankton were not
regularly sampled at the same time as yellow perch;
however, Gyekis (2006) collected zooplankton from
coastal fringing wetlands in Grand Traverse Bay,
Saginaw Bay, and northern Lakes Huron and Michigan during the summer of 2004. Similar amounts of
zooplankton biomass were sampled in northern Lakes
Huron and Michigan and Saginaw Bay, but Grand
Traverse Bay had very low biomass (Gyekis 2006).
Gyekis (2006) did not sample zooplankton until July
2004, so while the amounts of zooplankton in Saginaw
Bay and northern Lakes Huron and Michigan were
similar by July, early peak zooplankton levels may be
different across systems.
Yellow perch in Saginaw Bay wetlands consumed
zooplankton until they were about 3.5 cm SL, fed
mainly on macroinvertebrates at 5–6 cm SL, and
became primarily piscivorous by age 1 (Parker et al.
2009b), which is earlier than typically reported (e.g.
Keast 1985), suggesting that these wetlands may
provide abundant invertebrate and small fish prey.
Thus, hatching during the spring zooplankton bloom
in regions with a relatively long-growing season, such
as Saginaw Bay, could benefit yellow perch because
attaining a large size is important for preventing
overwinter mortality from starvation, intolerance to
environmental extremes, and predation (Sogard 1997).
However, Fitzgerald et al. (2004) proposed that
overwinter mortality was not a significant source of
yellow perch loss in southeastern Lake Michigan. We
hypothesize that water temperature and productivity
are important factors that explain the high abundance
of juvenile yellow perch in Saginaw Bay wetlands.
We found that yellow perch CPUE peaked in the
moderately-productive coastal fringing wetlands
along a disturbance gradient and decreased in the
more-impacted systems. A quadratic relationship
along a disturbance gradient seems most appropriate,
rather than yellow perch abundance continuing to
increase as disturbance increases. This is also evidenced by the lack of yellow perch in the more
disturbed/eutrophic DRM wetlands. Increased nutrient
concentrations result in increased algal and zooplankton biomass (e.g. Vanni 1987). However, excess
eutrophication has been shown to be detrimental to
yellow perch (Schaeffer et al. 2000; Tyson and Knight
2001). We propose that moderately-productive coastal
fringing wetlands are most strongly preferred by
yellow perch.
147
DRM systems
Catch per unit effort was variable from 2004 to 2006
when directly comparing yellow perch CPUE in
connected DRM lakes and wetlands. Despite the
variability among years, yellow perch CPUE tended
to be lower in the wetland macrohabitat as well as lakelily and lake-bare microhabitats relative to the lakeSAV microhabitat in DRM systems. In 2005, the
Muskegon and White lake-SAV microhabitats had
high yellow perch CPUEs (81 and 53.67 fish netnight-1, respectively), followed by Pigeon (8 fish netnight-1), and then Pentwater (0.33 fish net-night-1),
Lincoln (0 fish net-night-1), and Kalamazoo (0 fish
net-night-1). While yellow perch were completely
absent from some lakes, there also was not just one high
CPUE at one lake that singly increased the average
CPUE. This coupled with the fact that we sampled the
same microhabitats in both the wetland and lake
macrohabitats, so as not to confound comparisons,
leads us to conclude that yellow perch are more
abundant in DRM lakes than wetlands. Our conclusion
that yellow perch are more abundant in DRM lake
macrohabitats is further supported by observations in
the littoral zone of Muskegon Lake (a DRM lake)
where high numbers of age-0 and adult yellow perch
have been captured using boat electrofishing and fyke
netting (Ruetz et al. 2007; Bhagat and Ruetz 2011). By
comparing microhabitats within both lake and wetland
macrohabitats, we were able to provide further insight
into yellow perch habitat use within DRM systems. We
propose that yellow perch prefer lake-SAV because
lake-lily sites most likely become hypoxic at night due
to organic matter accumulation while the SAV sites
offer more protection from predation than the bare sites
(e.g. Rozas and Odum 1988).
Chubb and Liston (1986) found most larval yellow
perch in wetlands associated with the Pentwater DRM
system during April and May, suggesting that reproduction occurs in DRM wetlands. Moreover, larval
yellow perch were absent from the bayou portions of
this wetland complex by July, but they were present in
the main channels, which were cooler and more
oxygenated (Chubb and Liston 1986). We observed
that conditions did not become hypoxic (lowest
dissolved oxygen concentration over a 24-hour period
was 5.91 mg L-1 (51.8% saturation) at 9.0°C) in a
DRM wetland associated with the Muskegon River
during April, 2005 (DGU ‘‘unpublished data’’).
123
148
Furthermore, yellow perch egg skeins tend to become
entangled on the upper portions of macrophytes, logs,
and other substrates when spawning (Scott and
Crossman 1973), which keeps the eggs of percids
suspended above the hypoxic sediment (Regier et al.
1969). There is also evidence that Perca species may
intentionally wrap their egg skeins around plant stems
(Treasurer 1981; Patrick Hudson, USGS ‘‘personal
communication’’). Most of our sampling in DRM
wetlands occurred in July and yielded few yellow
perch. We hypothesize that soon after yellow perch
larvae hatch in DRM wetlands they disperse downstream to the lake ecosystems.
No differences were found between DRM lake and
wetland macrohabitats when comparing chemical/
physical variables, despite an apparent dissolved
oxygen gradient (Snodgrass et al. 1996) along PC-2.
This is probably because some of the lily habitats
within the lakes shared the same characteristics as
wetlands. Nelson et al. (2009) did not find significant
differences between DRM lakes and wetlands when
comparing dissolved oxygen, total dissolved solids,
turbidity, pH, and chlorophyll a (all measured during
daytime). However, Nelson et al. (2009) did find that
DRM wetlands had greater organic sediment depth,
less water movement, and more hypoxic conditions
(measured at nighttime) than adjacent lake habitats.
Organic sediment depth and water movement in
wetland habitats, which we did not measure, most
likely affect yellow perch distribution among certain
habitats (discussed below) and may be the principal
reasons why we found low numbers of yellow perch in
DRM wetlands.
Low to hypoxic nighttime dissolved oxygen concentrations have been observed in DRM wetlands
(Chubb and Liston 1986; Nelson et al. 2009). Additionally, we observed dissolved oxygen concentrations fluctuate, in a 24-hour period, from 1.1 mg L-1
(13.1% saturation) at 14.3°C in the early morning to
9.5 mg L-1 (121.6% saturation) at 27.0°C in the
afternoon in the DRM wetland associated with the
Muskegon River during August 2005 (DGU ‘‘unpublished data’’). The optimal temperature for adult
yellow perch is 24.7°C with lethal temperatures
ranging from 29 to 34°C (Hokanson 1977). Coble
(1982) found more yellow perch in areas of a large
river where dissolved oxygen was C5 mg L-1, and
Suthers and Gee (1986) found that juveniles completely avoided sections of a prairie marsh that had
123
Wetlands Ecol Manage (2012) 20:137–150
mean dissolved oxygen concentrations B1.5 mg L-1.
During summer, hypoxia most likely repels yellow
perch from DRM wetlands at night, and they may
avoid those habitats during the day because of high
temperatures. We hypothesize that nighttime hypoxia,
caused by a combination of low water movement and
deep organic sediment, and high daily water temperatures limit the use of some DRM-wetland habitats by
juvenile yellow perch during summer.
Conclusions
We observed that Great Lakes yellow perch are
substantially more abundant in coastal fringing wetlands than DRM wetlands. Among the coastal fringing
wetlands that we sampled, Saginaw Bay had the
highest CPUE of yellow perch. The yellow perch that
we captured in Saginaw Bay were mostly age-0,
indicating that these wetlands serve as important
nursery areas. The population genetic structure of
yellow perch in the Great Lakes suggest distinct
populations in southern Lake Michigan, northern
Lakes Michigan and Huron, and Saginaw Bay (Miller
2003; Parker et al. 2009a). Thus, inferring differences
among wetland types or regions based on chemical/
physical characteristics may be confounded with local
population dynamics (e.g. low or high recruitment) of
yellow perch in the adjacent Great Lake. We suspect
that laboratory studies and field investigations conducted at appropriate spatial scales could provide
useful approaches for testing our hypotheses related to
age-0 yellow perch distribution in wetlands and
chemical/physical variables. Among Lake Michigan
DRM systems, we found that yellow perch tended to
be more prevalent in the downstream lake macrohabitats relative to upstream wetlands. No differences
were found between the chemical/physical characteristics of the lakes and wetlands, which may mean that
other variables, not measured in this study (such as
organic sediment depth and water movement), may
govern yellow perch distribution in DRM systems.
Our results show that some wetlands, such as those in
Saginaw Bay, provide important nursery habitats
during summer for juvenile yellow perch and should
be recognized as such when drafting and implementing fisheries management plans.
Acknowledgments Funding for the various studies that
generated this dataset came from the Great Lakes
Wetlands Ecol Manage (2012) 20:137–150
Commission, Great Lakes Protection Fund, Michigan
Department of Environmental Quality, Michigan Department
of Natural Resources, U.S. Environmental Protection Agency,
and U.S. Fish and Wildlife Service. ADP was funded by a
research assistantship from Grand Valley State University’s
Annis Water Resources Institute. Dr. Thomas Burton provided
valuable guidance and insight on this research. We thank
members of the Burton, Ruetz, and Uzarski labs for assistance
with fish sampling and chemical analysis. Kevin Wyatt and two
anonymous reviewers offered valuable comments on an earlier
draft of this manuscript.
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