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Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie
JGLR-01100; No. of pages: 10; 4C: Journal of Great Lakes Research xxx (2016) xxx–xxx
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Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie Robin T.J. Churchill a,b,⁎, Michael L. Schummer b,c, Scott A. Petrie a,d, Hugh A.L. Henry a a
Department of Biology, Western University, London, Ontario N6A 5B7, Canada Long Point Waterfowl, P.O. Box 160, Port Rowan, Ontario N0E 1M0, Canada Department of Biological Sciences, SUNY Oswego, Oswego, NY 13126, USA d Delta Waterfowl Foundation, 1312 Basin Ave., Bismarck, ND 58504, USA b c
a r t i c l e
i n f o
Article history: Received 23 February 2016 Accepted 29 June 2016 Available online xxxx Communicated by Lee Grapentine Index words: Abundance Dreissenid mussels Lake Erie Long Point Submerged aquatic vegetation Waterfowl
a b s t r a c t Submerged aquatic vegetation (SAV) in Inner Long Point Bay (LPB), Lake Erie provides food and habitat for a diversity of fish and wildlife. The abundance and community structure of SAV often are used as bioindicators of ecosystem health. Colonization and increases in abundance of zebra mussels (Dreissena polymorpha) at LPB in the early 1990s increased water clarity which changed the SAV community. We used data from studies in 1976, 1991, and 1992 and sampled LPB in 2009 to quantify changes in abundance and occurrence of SAV, determine densities of zebra mussels, and model influences of year, water depth and substrate type on the probability of detection of SAV. We detected 96% decrease in mean (± SE) mussels/m2 between 1992 (457 ± 86) and 2009 (19 ± 2). With the exception of slender pondweed (Potamogeton pusillus), the five most abundant SAV species in 1992 had decreased by 2009. Water depth and substrate type influenced probability of detection of all SAV species, excluding Najas spp., suggesting that changes in Lake Erie water levels and sediment loading may influence future SAV communities. Decreased abundance of filter feeding mussels is consistent with increased eutrophication and changes in SAV in LPB. Carrying capacity of LPB for waterfowl and other fish and wildlife that use and eat SAV and mussels increased during the mid-1990s, but has since decreased. © 2016 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved.
Introduction Coastal wetlands of the lower Great Lakes (LGL) are critically important to a diverse array of wetland-dependent organisms. Submerged aquatic vegetation (SAV) occurring in LGL coastal wetlands provides food for migrating waterfowl and habitat for fish (Richardson et al., 1998; Knapton and Petrie, 1999; Badzinski and Petrie, 2006). In addition, SAV quantity and species composition are indicators of local water conditions, affect biogeochemical and sedimentological processes, and protect shorelines from erosion by decreasing nearshore wave action (Moore et al., 1996). Despite their importance to fish, wildlife and humans, a substantial number of LGL coastal wetlands have been drained for agriculture and other development (e.g., b5% of western Lake Erie coastal wetlands remain intact), thereby increasing the importance of remaining coastal wetland habitat for wetlanddependent organisms. Inner Long Point Bay, Lake Erie (LPB) is an important wetland complex with limited anthropogenic impacts. LPB is
⁎ Corresponding author at: Department of Biology, Western University, London, Ontario N6A 5B7, Canada. Tel.: +1 519 619 3225. E-mail address: [email protected] (R.T.J. Churchill).
important as fish and wildlife habitat because it has an extensive SAV community covering N 99% of the bay (Knapton and Petrie, 1999). Many of the remaining wetlands in the LGL region have been altered by various stressors, including the introduction of exotic plants and invertebrates (Petrie, 1998; Knapton and Petrie, 1999; Petrie and Knapton, 1999). Invasive species can affect carrying capacity for waterfowl and other animals by altering total biomass of SAV or changing species composition within wetlands (Crowder and Bristow, 1988). For instance, introduction and proliferation of zebra mussels (Dreissena polymorpha) and quagga mussels (D. burgensis) (hereafter combined as dreissenid mussels) has been associated with changes in abundance, distribution, and community composition of SAV within the LGL (Blindlow, 1992; Knapton and Petrie, 1999; Petrie and Knapton, 1999). Filtering activities of dreissenid mussels reduce suspended particles in the water column, thereby increasing water clarity and decreasing light attenuation (Knapton and Petrie, 1999). Decreased light attenuation enhances benthic photosynthesis and influences the distribution and abundance of SAV (Wetzel, 1983). In addition, dreissenid mussels can alter microbially-mediated nutrient cycling and the nearshore phosphorus cycle, further decreasing phytoplankton levels (Wilson et al., 2006). Filtering by dreissenid mussels has decreased phytoplankton levels which in turn likely has led to increased water clarity
http://dx.doi.org/10.1016/j.jglr.2016.07.012 0380-1330/© 2016 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved.
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
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and increased SAV abundance that was observed at Lake St. Clair during the mid-1990s (Schloesser and Manny, 2007). Diving ducks (e.g., Aythya spp. and Bucephala spp.) feed exclusively in aquatic habitats, and thus, the shallow, productive waters of LPB provide foraging habitat necessary for these ducks to complete migration (Petrie, 1998). Expansion of introduced dreissenid mussels to Lake Erie in the early-1990s led to an initial increase in use of LPB by molluscivorous ducks (Petrie and Knapton, 1999). Lesser scaup (Aythya affinis), greater scaup (A. marila), bufflehead (Bucephala albeola) and common goldeneye (B. clangula), in particular, have altered traditional migration patterns to take advantage of this novel food source in LPB (Hamilton et al., 1994; Petrie, 1998; Petrie and Knapton, 1999). However, since 2000, diving duck use has decreased at LPB, particularly in species that eat dreissenid mussels (Badzinski, 2007). In addition, the abundance of economically important fish species, such as yellow perch (Perca flavescens), largemouth bass (Micropterus salmoideus), and smallmouth bass (Micropterus dolomieu), have also decreased within LPB since the late-1990s (Ontario Ministry of Natural Resources, 2007). Causes of fish and diving duck declines remain unclear, but it is plausible that a decline in abundance or distribution of dreissenid mussels and SAV may be direct or indirect contributing factors. Following introduction to a suitable, new locale, exotic species often occur in greater abundance than observed in their native range. Often, initial increases in abundance of invasive species are followed by decline until a new regional carrying capacity is reached (McKillup et al., 1988). Dreissenid mussels prefer to anchor to hard substrate, but those types of substrates are not found extensively throughout LPB so mussels primarily anchor to SAV (Knapton and Petrie, 1999). Thus, in LPB, abundance of dreissenid mussels may be influenced by abundance and species distribution of SAV. Because LPB provides food and habitat for a diversity of fish and wildlife, researchers have previously quantified the distribution, abundance and long-term temporal dynamics of the SAV community (Knapton and Petrie, 1999; Petrie and Knapton, 1999). Smith (1979) mapped the distribution of SAV in LPB during the 1970s. Knapton and Petrie (1999) and Petrie and Knapton (1999) assessed the distribution and abundance of SAV and dreissenid mussel density in the mid1990s and compared their findings with those of Smith (1979). In this study, we quantified distributions and abundance of SAV and dreissenid mussel density (mussels/m2) to evaluate if changes have occurred since the 1990s when dreissenid mussels first colonized LPB. Our objectives were to: 1) determine if species percent abundance and occurrence of SAV changed in LPB between 1976 and 2009, 2) determine if the density of dreissenid mussels in LPB differed between 1991, 1992, and 2009, and 3) determine factors influencing the occurrence of SAV in LPB that may aid in our understanding of past and future changes in SAV in LPB.
a
b
c
Material and methods Study area Our study was conducted at Long Point, Ontario (80° 30′ W, 42° 35′ N to 80° 03′ W, 42° 33′ N; Fig. 1.). Long Point is a sand-spit extending 35 km south-east into Lake Erie that has facilitated the formation of the Inner and Outer Long Point Bays and associated freshwater marsh complexes (Petrie, 1998). The Inner Bay at Long Point has an area of 78 km2 and mean depth (1 to 2 m) varies depending upon annual and periodic changes in regional water budgets (Berst and McCrimmon, 1966). Coverage of the Inner Bay by SAV is N90% in most locales (Pauls and Knapton, 1993; Petrie, 1998; Smith, 1979). The mean summer temperature of Inner Bay (22 °C; Pauls and Knapton, 1993; Smith, 1979) provides favorable growing conditions for macrophytic SAV including: muskgrass (Chara vulgaris), wild celery (Vallisneria americana), Eurasian milfoil (Myriophyllum spicatum), naiad (Najas spp.), pondweeds (Potamogeton spp.), Canada water weed (Elodea canadensis), and coontail (Ceratophyllum demersum; Petrie, 1998). Big Creek is the
Fig. 1. Distribution and density (mussels/m2) of dreissenid mussels in Long Point Bay – Lake Erie a) 1991 b) 1992 and c) 2009.
major tributary of the Inner Bay that drains a 730 km2 watershed comprised primarily of agricultural land northwest of Long Point (Berst and McCrimmon, 1966; Leach, 1981). Big Creek influences the SAV communities in LPB because it is the primary source of nutrients and sediments in the bay (Leach, 1981). LPB substrate is predominantly mud at the mouth of Big Creek, sandy loam over most of the central portion, and sand bordering the eastern and south-eastern portions (Churchill, 2015). Study design and sample collection We used a grid generated with geographic information system software (GIS) to uniformly distribute 321 sampling stations throughout
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
R.T.J. Churchill et al. / Journal of Great Lakes Research xxx (2016) xxx–xxx
LPB (ArcMAP10, Release 10. Redlands, CA: Environmental Systems Research Institute). We used a Global Positioning System (GPS) with ± 3 m accuracy (Garmin 76C x) to navigate to sampling stations a using a 7 m pontoon boat. We collected SAV, dreissenid mussels, and environmental variables at the 321 stations 5–29 August 2009 according to the methodology used in the previous studies. At each sampling station, we recorded water and Secchi depth using a Secchi disk with a lowering line marked at 5 cm intervals. We measured water temperature using a digital thermometer (± 0.001 °C; Fisher Scientific 0666426). We dove to the substrate using SCUBA to collect SAV, dreissenid mussels, and benthic substrate samples. We estimated SAV percentage cover using a modified Braun-Blanquet scale of abundance and ascended to the surface to record values. We modified the BraunBlanquet scale using categories 0–4 (category mid-points at 12.5%, 37.5%, 62.5%, and 87.5% cover) instead of 0–5 to create continuous values for multivariate analysis. We used scissors to clip all aboveground SAV in a 0.5 m2 quadrat at substrate level. We used a mesh bag with 1 mm netting to capture and strain samples. We sampled substrate by collecting three horizontal scoops of substrate with a perforated metal can (total combined sample volume = 0.03 m3; Badzinski, 2003). Dreissenid mussels were removed from SAV samples on the deck of the boat, where we bottled and labelled each of the mussel samples separately. Finally, we differentiated between above and belowground (i.e., roots, turions/tubers, and rhizomes) SAV samples, and froze samples until further processing.
Laboratory procedures All species-specific aboveground vegetation samples were blotted dry using paper towel. We weighed each sample using a digital balance (± 0.001 g; A&D Company Ltd. FX3000i) and recorded values as wet mass. Belowground plant parts were separated from benthic substrate using a fine mesh sieve (2 mm × 2 mm; Fisher Scientific U.S. standard brass). Substrate type was classified into one of three groups (mud, sandy loam, or sand) using the modified Wentworth scale (Wentworth, 1922). Three substrate classifications were selected based on previously reported substrate types within LPB (Smith, 1979). Dry mass of subsamples was obtained to allow for estimation of dry mass for aboveground samples (by species). We selected sub-samples from aboveground samples for each species and oven-dried them separately at 80 °C to constant mass (±0.001 g). We ensured that sub-samples represented the range of wet masses observed in samples of each species. Thereafter, we used linear regression to estimate dry mass using wet mass measurements (Table 1). The only species we detected in belowground sampling was wild celery tubers and occurrence was negligible, accounting for 0.05% and 0.58% in autumn and spring respectively, of the total SAV biomass and were included with the aboveground parts of wild celery in our analysis. Dreissenid mussels were counted at each sample site.
3
Data mapping and analysis We obtained SAV abundance and distribution data in LPB from previous studies (1976, 1991, and 1992) from Bird Studies Canada archives (Port Rowan, Ontario). In 1976, only cover (using the Braun-Blanquet scale) for each plant species was available. In 1991 and 1992, cover data for each plant species as well as water depth, Secchi depth, and dreissenid mussel abundance were available. We used inverse distance-weighted (IDW) spatial interpolation to estimate speciesspecific distributions and changes in SAV and dreissenid mussel distribution in LPB (Spatial Analyst tool, ArcGIS Desktop: Release 10. Redlands, CA: Environmental Systems Research Institute; Watson and Philip, 1985; Neckles et al., 2012). We mapped the abundances of dreissenid mussels and the six most abundant SAV species (see Fig. 2) for 1976, 1991, 1992, and 2009 to provide a graphical representation of community changes in LPB. We used the modified Braun-Blanquet scale described above to map our ordinal SAV data. We used dreissenid mussel density (mussels/m2) to develop maps to show changes in density among years. To test for temporal variation in mussel abundance, we used repeated measures analysis of variance (ANOVA). Spatial interpolation provides a visual representation of SAV coverage in LPB but does not provide statistical comparisons of abundances among years. We used multivariate analysis of variance (MANOVA) to test for changes in plant community (e.g., percent cover of SAV) among years using SAV abundance data. We included muskgrass, wild celery, Eurasian milfoil, naiad, slender pondweed (Potamogeton pusillus) and Richardson's pondweed (Potamogeton richardsonii) cover using the modified BraunBlanquet values as response variables and year as a repeated measure to account for sampling the same points through time. We included latitude and longitude as covariates to control for spatial autocorrelation and substrate as a categorical fixed variable to assess potential changes to growing conditions among sampling points. We inspected studentized residual plots from all models for normal distribution. We log-transformed SAV data to normalize residual distribution (Littell et al., 2007). We selected a α = 0.10 level of significance a priori because it is appropriate for observational data (Tacha et al., 1982). We used Wilks' lambda to evaluate statistical significance of year effects within multivariate analysis (MANOVA) and when MANOVA was significant, used F-tests (type III sum of squares) produced from univariate analyses. We used logistic regression to determine factors influencing detection probability of a species at a sampling station for the 6 most common species of SAV by biomass (Churchill, 2015; Fig. 2). We initially included dreissenid mussel abundance, substrate type, year, water
Table 1 Linear regressions for conversion of wet weights to dry weights for species of SAV sampled at Long Point Bay, Lake Erie, autumn 2009 and spring 2010. Species
n
Intercept
slope
r2
Chara vulgaris Myriophyllum spicatum Najas spp. Najas flexilis Najas guadalupensis Potamogeton richardsonii Potamogeton pusillus Vallisneria americana
23 32
2.5306 0.2487
0.2544 0.1524
0.99 0.98
29 14 19 25 26
0.6847 0.1009 0.0341 0.6916 0.3649
0.1218 0.1557 0.1309 0.1141 0.1003
0.99 0.98 0.95 0.99 0.97
Fig. 2. Percent composition (dry wt.) of submerged aquatic vegetation within Long Point Bay, Lake Erie, Ontario, August 2009.
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
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R.T.J. Churchill et al. / Journal of Great Lakes Research xxx (2016) xxx–xxx
a
b
c
d
Fig. 3. Distribution and abundance (percent cover) of muskgrass (Chara vulgaris) in Long Point Bay – Lake Erie a) 1976 b) 1991 c) 1992 and d) 2009.
depth, depth × depth, and substrate × year as fixed effects and latitude and longitude as covariates to control for spatial effects. We included depth × depth to test for quadratic relationships typical of SAV occurrence as depth increases, whereby likelihood of occurrence can decrease or increase beyond a threshold depth (Blindlow, 1992). We included substrate × year to determine whether detection probability of SAV changed through time within substrate types and within years among substrate types. We did not include 1976 data in our model because data were lacking. We removed variables not significant at α = 0.10. We did not include Secchi disk reading because it was strongly
correlated with water depth (P b 0.01; r = 0.90), but subject to greater error than water depth because of daily difference in turbidity. We compared means of reduced models using post-hoc Tukey's adjustment and produced plots using model predicted values. Results We detected that density of dreissenid mussels (mussels/m2) increased by 2110% between 1991 (20.6 mussels/m2) and 1992 (456.8), decreased 96% between 1992 and 2009 (18.9), and did not differ
a
b
c
d
Fig. 4. Distribution and abundance (percent cover) of wild celery (Vallisnaria americana) in Long Point Bay – Lake Erie a) 1976 b) 1991 c) 1992 and d) 2009.
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
R.T.J. Churchill et al. / Journal of Great Lakes Research xxx (2016) xxx–xxx
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a
b
c
d
Fig. 5. Distribution and abundance (percent cover) of naiad (Najas spp.) in Long Point Bay – Lake Erie a) 1976 b) 1991 c) 1992 and d) 2009.
between 1991 and 2009 (P = 0.999) (year effect, F2,960 = 25.72, P b 0.001) (Fig. 1). We also detected an influence of sampling year on percent cover of the six most abundant SAV species in LPB between 1976 and 2009 (MANOVA: Wilks' λ = 0.90, F3, 316 = 11.76, P b 0.001) (Figs. 3–8). Percent cover of wild celery (P b 0.001; Fig. 9a), Richardson's pondweed (P b 0.001; Fig. 9d) and Eurasian milfoil (P b 0.001; Fig. 9f) were greatest in 1991 and 1992, whereas Najas spp. (P b 0.001; Fig. 9b) and muskgrass (P b 0.001; Fig. 9e) cover was greater in 1992, and slender pondweed (P b 0.001; Fig. 9c) was the only species with greater percent cover in 2009.
Probability of detecting wild celery and muskgrass varied negatively with depth as quadratic and linear functions, respectively (P b 0.001; Table 2; Fig. 10a–b), whereas Eurasian milfoil (P b 0.001; Table 2; Fig. 10c) and Richardson's pondweed (P = 0.002; Table 2; Fig. 10d) varied positively and negatively, respectively, with depth as quadratic functions. Slender pondweed (P = 0.054; Table 2; Fig. 10e) varied positively with water depth. Detection of Najas spp. did not differ among water depths (P = 0.641; Table 2). Species responses to substrate type varied; detection probability of muskgrass (P ≤ 0.006; Table 2; Fig. 11a) was greater on sand and
a
b
c
d
Fig. 6. Distribution and abundance (percent cover) of Eurasian milfoil (Myriophyllum spicatum) in Long Point Bay – Lake Erie a) 1976 b) 1991 c) 1992 and d) 2009.
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
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R.T.J. Churchill et al. / Journal of Great Lakes Research xxx (2016) xxx–xxx
a
b
c
d
Fig. 7. Distribution and abundance (percent cover) of Richardson's pondweed (Potamogeton richardsonii) in Long Point Bay – Lake Erie a) 1976 b) 1991 c) 1992 and d) 2009.
sandy loam substrate, whereas slender pondweed (P = 0.018; Table 2; Fig. 11c) and Eurasian milfoil (P b 0.001; Table 2; Fig. 11b) were more likely to be detected on mud substrate. Effects of substrate and sampling year interacted to influence detection probability of wild celery, Najas spp., and Richardson's pondweed (Table 2; Fig. 12). Detection probability was greater for Richardson's pondweed (P = 0.019; Fig. 12c) across all sampling years in mud substrate. Najas spp. (P b 0.001; Table 2; Fig. 12b) was more likely to be detected on sandy loam during 1991, though this changed to mud in 1992 and 2009.
Discussion A diversity of fish and wildlife rely on SAV for food and cover in the Great Lakes region and beyond. The distribution and abundance of SAV, and consequently their availability to fish and wildlife is a function of several environmental factors including light quantity, interspecific competition, nutrient availability, herbivory, ice and storm damage, fluctuating water levels, temperature, pH, and presence of invasive species (Knapton and Petrie, 1999; Petrie and Knapton, 1999). Expansion of
a
b
c
d
Fig. 8. Distribution and abundance (percent cover) of slender pondweed (Potamogeton pusilus) in Long Point Bay – Lakie Erie a) 1976 b) 1991 c) 1992 and d) 2009.
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
R.T.J. Churchill et al. / Journal of Great Lakes Research xxx (2016) xxx–xxx
7
b
c
d
e
f
Log LS Means
a
Year Fig. 9. Least-squared means (log transformed) of cover (±90% CI; using the Braun-Blanquet values) for the most abundant species of SAV in LPB: a) Wild celery b) Najas spp. c) Slender pondweed d) Richardson's pondweed e) Muskgrass and f) Eurasian milfoil. Years with the same letter are not significantly different (P N 0.10).
dreissenid mussels into LPB in the early 1990s had been the most pronounced recent influence on SAV within the bay (Petrie and Knapton, 1999). We initiated this study to determine if the abundance and distribution of dreissenid mussels and SAV had changed since previous studies in the early 1990s. Although the distribution of dreissenid mussels in LPB has not changed substantially since 1992, the total abundance of these mussels has decreased substantially. The increase in dreissenid mussel abundance in the early-1990s resulted in increased water transparency and declines in all phytoplankton taxa and chlorophyll concentrations in Lake Erie (Holland, 1993). The decline in suspended particulate matter could have contributed to the overall decline in dreissenid mussels since 1992 because of a reduced food source. Furthermore, predation by both fish and waterfowl also likely contributed to the decline in abundance of dreissenid mussels (Mitchell, 1995; Petrie and Knapton, 1999). The resulting change in water clarity in LPB also may have influenced the SAV community within LPB. With the exception of slender pondweed, the 5 most abundant SAV species in LPB experienced declines in abundance since 1992 (Figs. 3–8). Because nutrient enrichment and light availability are interrelated, it is possible that synergistic effects explain SAV growth within LPB. Angiosperm SAV species are known to proliferate in eutrophic
water (Smith, 1979), but it is possible that there is a point at which there is not enough light available to stimulate growth, regardless of nutrient availability. Inputs of nitrogen and phosphorus from fertilizer applications can result in declines of SAV and enhancement of phytoplankton (Twilley et al., 1985). Increased abundance of suspended particles in the water column decrease light availability for SAV and can cause reductions in plant growth. At inner Saginaw Bay, where inputs from agriculture are substantial, colonization by dreissenid mussels caused decreases in phosphorus and phytoplankton and increases in water clarity (Fahnenstiel et al., 1995a, 1995b). As such, declines in dreissenid mussels in LPB and an associated increase in phytoplankton growth since 1992 may have reduced light availability for SAV below a threshold that retards growth of these plants. We suggest that further investigation of types and locations of nutrient inputs into LPB influencing water quality and clarity are needed to determine specific mechanisms for changes in SAV. Water depth and substrate type greatly influenced probability of detection for most species of SAV we observed in LPB. Our models could be used to predict future changes in SAV communities in LPB with decreasing water depth resulting from changes in climate and changes in sediment loading from Big Creek. Winter precipitation and run-off are
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
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Table 2 Reduced multiple logistic regression models of the SAV distribution data (n = 321). Specific SAV species' presence or absence was the response variable and the 11 site characteristics were the explanatory variables. X2
Species
Effect
Estimate
Error
DF
P
Wild Celery
Intercept Substrate Mud Sandy loam Depth Year 1991 1992 Depth × depth Substrate × year Intercept Substrate Mud Sandy loam Depth Year 1991 1992 Depth × depth Intercept Substrate Mud Sandy loam Year 1991 1992 Depth × depth Intercept Substrate Sandy loam Year 1991 1992 Substrate × year Intercept Substrate Mud Sandy loam Depth Year 1991 1992 Depth × depth Substrate × year Intercept Substrate Mud Sandy loam Depth Year 1991 1992
−1243.2
213.6
b0.001 0.034
33.884 6.788
−0.319 −0.142 −0.018
0.251 0.153 0.007
0.011 0.067
6.521 5.489
0.179 0.162 b0.001
0.157 0.162 b0.001
1567.5
237.3
−0.56 0.671 0.013
0.208 0.144 0.007
−0.6 0.828 b−0.001 −927.3
0.134 0.141 b0.001 299.2
0.419 −0.649
0.213 0.152
0.874 0.625 b0.001 −220.3
0.141 0.139 b0.001 196.6
0.603
0.135
0.357 0.859
0.117 0.123
−618.4
240.1
1 2 1 1 1 2 1 1 1 4 1 2 1 1 1 2 1 1 1 1 2 1 1 2 1 1 1 1 2 1 2 1 1 4 1
0.027 0.035 b0.001 b0.001 0.007 b0.001 0.047 b0.001 b0.001 b0.001 b0.001 b0.001 0.001 0.049 b0.001 b0.001 b0.001 b0.001 b0.001 0.262 b0.001 b0.001 b0.001 0.002 b0.001 b0.001 0.01
4.885 10.354 43.636 22.056 7.214 21.734 3.941 36.341 19.923 34.592 13.872 16.367 17.731 3.854 17.723 90.513 38.624 20.301 11.556 1.256 44.131 20.047 104.433 9.262 49.022 33.341 6.636
0.9420 0.1756 −0.020
0.734 0.798 0.007
0.002 b0.001
9.325 23.652
2.787 2.115 b0.001
0.635 0.647 b0.001
−1243.2
213.6
0.002 0.047 b0.001 0.024
9.853 9.650 33.884 7.491
1.245 −0.512 −0.018
0.755 0.572 0.007
0.054 b0.001
3.710 5.489
−13.720 −2.056
153.7 0.483
Muskgrass
Eurasian Milfoil
Najas
Richardson's pondweed
Slender pondweed
predicted to decrease in the Great Lakes region, which would reduce spring run-off into LPB from Big Creek and water coming from other areas of the Great Lakes watershed (Steen et al., 2006; Notaro et al., 2014). Soil conservation practices aimed at reducing siltation in the Big Creek watershed coupled with decreased flood intensity and duration from spring snow melt may reduce development of mud substrate in LPB (Petrie, 1998). Our models predict that decreasing water levels would favor wild celery and possibly muskgrass, whereas Eurasian milfoil would decrease in LPB. Shifts in substrate type are difficult to predict, but our models suggest that decreases in mud substrate would favor muskgrass relative to other SAV in LPB. Decreased water levels and decreased mud substrate combined would favor muskgrass over other SAV in LPB. Muskgrass, while eaten by waterfowl, is less preferred relative to pondweeds and wild celery (Bellrose, 1980; Petrie, 1998). Considering that 83% of the SAV community was musk grass in 2009, a scenario of increasing musk grass would decrease plant diversity and quality of foods available to waterfowl in LPB.
1 1 1 2 1 1 1 4 1 2 1 1 1 2 1 1
Further monitoring of SAV and dreissenid mussels within LPB is important given its importance to migrating waterfowl, especially diving ducks and dabbling ducks that require an abundance of these plants to fuel migration (Petrie, 1998; Baldassarre and Bolen, 2006). Additionally, it would be beneficial for future studies to assess nutrient inputs and levels in LPB because they influence SAV growth and were not analyzed as part of this study. Nutrient inputs also are important when considering substrate types in LPB. Big Creek flows into northwest LPB, an area that is covered with dense, diverse stands of SAV. The Big Creek delta has a mud substrate, and this study shows the importance of this substrate type to a variety of plants. Sediment from Big Creek watershed deposited in LPB as mud substrate likely contributes substantially to turbidity, light attenuation, and nutrient loading. Further research on landscape change and inputs from Big Creek into LPB are necessary to increase our ability to predict future changes to SAV in LPB. This study establishes a new baseline for SAV and mussel distribution and abundance which can be used to detect the ecological impacts of future invasive species introductions.
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
Predicted Probability
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9
a
b
c
d
e
Depth (cm) Fig. 10. Relationship between the predicted probability of SAV presence (a) wild celery b) muskgrass c) Eurasian milfoil d) Richardson's pondweed e) slender pondweed) and water depth (±90% CI) in Long Point Bay – Lake Erie in 1991, 1992, and 2009.
Predicted Probability
a
b
c
Mud
Sandy Loam Substrate
Sand
1991
1992
2009
Year
Fig. 11. Relationship between the predicted probability (±90% CI) of SAV presence (a) muskgrass b) Eurasian milfoil c) slender pondweed and the effects of substrate and year in Long Point Bay – Lake Erie in 1991, 1992, and 2009. Substrate and year interactions were not significant. Substrate and year were not significant for plant species not shown.
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
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a
Predicted Probability
b
c
1991
1992 Year
2009
Fig. 12. Relationship between the predicted probability (± 90% CI) of SAV presence (a) wild celery b) Najas spp. c) Richardson's pondweed and the interactive effects of substrate and year in Long Point Bay – Lake Erie in 1991, 1992, and 2009. Substrate and year were not significant for plant species not shown.
Acknowledgements Funding for this project was provided by Long Point Waterfowl, The Bluff's Hunt Club, S.C. Johnson & Son, Ltd., Ontario Ministry of Natural Resources and Forestry, Ontario Federation of Anglers and Hunters, Ducks Unlimited Canada, Long Point Waterfowler's Association and The Order of Good Cheer. We thank J. Cook, J. Gilbert, T. Barney, A. Dhamorikar, J. Palframan, D. Messmer, M. Bossyut, S. Bossyut, S. Hockley, C. Walker, R. Watt, M. Morse, A. Winstanley-Hayes, and A. Good for technical, field, and lab assistance. We also thank T. Barney, E. Hanna, R. Brook, K. Abraham and S. Badzinski for helpful comments in development of this manuscript. References Badzinski, S.S., 2003. Influence of tundra swans on aquatic vegetation and staging waterfowl at Long Point, Ontario (Unpublished Ph.D. dissertation) University of Western Ontario, London. Badzinski, S.S., 2007. Toward rehabilitation of the Crown Marsh – Long Point, Lake Erie, Ontario (Unpublished report to the Long Point Crown Marsh Rehabilitation Steering Committee) p. 16. Badzinski, S.S., Petrie, S.A., 2006. Lesser scaup spring nutrient reserve dynamics on the lower Great Lakes. Wildl. Soc. Bull. 34, 395–407. Baldassarre, G.A., Bolen, E.G., 2006. Waterfowl Ecology and Management. Kreiger, Malabar, Fl. Berst, A.H., McCrimmon, H.R., 1966. Comparative summer limnology of Inner Long Point Bay, Lake Erie, and its major tributary. Can. J. Fish. Aquat. Sci. 23, 275–291. Bellrose, F.C., 1980. Ducks, geese and swans of North America. Mechanicsburg, Stackpole.
Blindlow, I., 1992. Long- and short term dynamics of submerged macrophytes in two shallow eutrophic lakes. Freshw. Biol. 28, 15–27. Churchill, R. T. J., 2015. Seasonal and long-term changes in the distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Inner Long Point Bay, Lake Erie. unpublished MSc thesis, University of Western Ontario, London, Ontario. Crowder, A.A., Bristow, J.M., 1988. The future of waterfowl habitats in the Canadian lower Great Lakes wetlands. J. Great Lakes Res. 14, 115–127. Fahnenstiel, G.L., Bridgeman, T.B., Lang, G.A., McCormick, M.J., Nalepa, T.F., 1995a. Phytoplankton productivity in Saginaw Bay, Lake Huron: effects of zebra mussel (Dreissena polymorpha) colonization. J. Great Lakes Res. 21, 464–475. Fahnenstiel, G.L., Lang, G.A., Nalepa, T.F., Johengen, T.H., 1995b. Effects of zebra mussel (Dreissena polymorpha) colonization on water quality parameters in Saginaw Bay, Lake Huron. J. Great Lakes Res. 21, 435–448. Hamilton, D.J., Ankney, C.D., Bailey, R.C., 1994. Predation of Zebra mussels by diving ducks: an exclosure study. Ecology 75, 521–531. Holland, R.E., 1993. Changes in planktonic diatoms and water transparency in Hatchery Bay, Bass Island area, western Lake Erie since the establishment of the zebra mussel. J. Great Lakes Res. 19, 617–624. Knapton, R.W., Petrie, S.A., 1999. Changes in distribution and abundance of submerged macrophytes in the Inner Bay at Long Point, Lake Erie: implications for foraging waterfowl. J. Great Lakes Res. 25, 783–798. Leach, J.H., 1981. Comparative limnology on inner Long Point Bay, Lake Erie, and adjacent waters of the outer bay. J. Great Lakes Res. 7, 123–129. Littell, R.C., Milliken, G.A., Stroup, W.W., Wolfinger, R.D., Schabenberger, O., 2007. SAS formixed models. 2nd ed. SAS Institute Inc., Cary. McKillup, S.C., Allen, P.G., Skewes, M.A., 1988. The natural decline of an introduced species following its initial increase in abundance; and explanation for Ommatoiulus moreletii in Australia. Oecologia 77, 339–342. Mitchell, J.S., 1995. The Effects of Waterfowl and Fish Predation on Dreissenid Mussels at Nanticoke, Lake Erie M.Sc. thesis University of Western Ontario, London, Ontario. Moore, K.A., Neckles, H.A., Orth., R.J., 1996. Zostera marina (eelgrass) growth and survival along a gradient of nutrients and turbidity in the lower Chesapeake Bay. Mar. Ecol. Prog. Ser. 142, 247–259. Neckles, H.A., Kopp, B.S., Peterson, B.J., Pooler, P.S., 2012. Integrating scares of seagrass monitoring to meet conservation needs. Estuar. Coasts 35, 23–46. Notaro, M., Lorenz, D., Hoving, C., Schummer, M., 2014. Twenty-first century projections of snowfall and winter severity across central-eastern North America. J. Clim. 27, 6526–6550. Ontario Ministry of Natural Resources, 2007. Status of Major Stocks. Lake Erie Management Unit, Port Dover, Ontario. Pauls, K., Knapton, R.W., 1993. Submerged macrophytes of Long Point’s Inner Bay: their distribution and value for waterfowl. Long Point Environmental Folio Publication Series., Technical Paper 1. University of Waterloo, Waterloo, Ontario. Petrie, S.A., 1998. Waterfowl and Wetlands of Long Point Bay and Old Norfolk County: Present Conditions and Future Options for Conservation. Norfolk Land Stewardship Council and Long Point. Waterfowl & Wetlands Research Fund Report, Port Rowan, Ontario, Canada. Petrie, S.A., Knapton, R.W., 1999. Rapid increase and subsequent decline of Zebra and Quagga mussels in Long Point Bay, Lake Erie: possible influence of waterfowl predation. J. Great Lakes Res. 25, 772–782. Richardson, W.B., Zigler, S.J., Dewey, M.R., 1998. Bioenergetic relations in submerged aquatic vegetation: an experimental test of prey use by juvenile bluegills. Ecol. Freshw. Fish 7, 1–12. Schloesser, D.W., Manny, B.A., 2007. Restoration of wild celery, Vallisneria americana Michx., in the lower Detroit River of the Lake Huron- Lake Erie corridor. J. Great Lakes Res. 33, 8–19. Smith, D., 1979. Ecological Isolation Between Aythya Species at Long Point Bay, Ontario M.A. Thesis University of Western Ontario, London, Ontario. Steen, D.A., Gibbs, J.P., Timmermans, S.T.A., 2006. Assessing the sensitivity of wetland bird communities to hydrologic change in the eastern Great Lakes region. Wetlands 26, 605–611. Tacha, T.C., Warde, W.D., Burnham, K.P., 1982. Use and interpretation of statistics in wildlife journals. Wildl. Soc. Bull. 10, 355–362. Twilley, R.R., Kemp, W.M., Staver, K.W., Stevenson, J.C., Boynton, W.R., 1985. Nutrient enrichment of estuarine submersed vascular plant communities. 1. Algal growth and effects on production of plants and associated communities. Mar. Ecol. Prog. Ser. 23, 179–191. Watson, D.F., Philip, G.M., 1985. A refinement of inverse distance weighted interpolation. Geo-Process. 2, 315–327. Wentworth, C.K., 1922. A scale of grade and class terms for clastic sediments. J. Geol. 30, 377–392. Wetzel, R.G., 1983. Limnology. second ed. Saunders, Philadelphia. Wilson, K.A., Howell, E.T., Jackson, D.A., 2006. Replacement of zebra mussels by quagga mussels in the Canadian nearshore Lake Ontario: the importance of substrate, round goby abundance, and upwelling frequency. J. Great Lakes Res. 32, 11–28.
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
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Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie Robin T.J. Churchill a,b,⁎, Michael L. Schummer b,c, Scott A. Petrie a,d, Hugh A.L. Henry a a
Department of Biology, Western University, London, Ontario N6A 5B7, Canada Long Point Waterfowl, P.O. Box 160, Port Rowan, Ontario N0E 1M0, Canada Department of Biological Sciences, SUNY Oswego, Oswego, NY 13126, USA d Delta Waterfowl Foundation, 1312 Basin Ave., Bismarck, ND 58504, USA b c
a r t i c l e
i n f o
Article history: Received 23 February 2016 Accepted 29 June 2016 Available online xxxx Communicated by Lee Grapentine Index words: Abundance Dreissenid mussels Lake Erie Long Point Submerged aquatic vegetation Waterfowl
a b s t r a c t Submerged aquatic vegetation (SAV) in Inner Long Point Bay (LPB), Lake Erie provides food and habitat for a diversity of fish and wildlife. The abundance and community structure of SAV often are used as bioindicators of ecosystem health. Colonization and increases in abundance of zebra mussels (Dreissena polymorpha) at LPB in the early 1990s increased water clarity which changed the SAV community. We used data from studies in 1976, 1991, and 1992 and sampled LPB in 2009 to quantify changes in abundance and occurrence of SAV, determine densities of zebra mussels, and model influences of year, water depth and substrate type on the probability of detection of SAV. We detected 96% decrease in mean (± SE) mussels/m2 between 1992 (457 ± 86) and 2009 (19 ± 2). With the exception of slender pondweed (Potamogeton pusillus), the five most abundant SAV species in 1992 had decreased by 2009. Water depth and substrate type influenced probability of detection of all SAV species, excluding Najas spp., suggesting that changes in Lake Erie water levels and sediment loading may influence future SAV communities. Decreased abundance of filter feeding mussels is consistent with increased eutrophication and changes in SAV in LPB. Carrying capacity of LPB for waterfowl and other fish and wildlife that use and eat SAV and mussels increased during the mid-1990s, but has since decreased. © 2016 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved.
Introduction Coastal wetlands of the lower Great Lakes (LGL) are critically important to a diverse array of wetland-dependent organisms. Submerged aquatic vegetation (SAV) occurring in LGL coastal wetlands provides food for migrating waterfowl and habitat for fish (Richardson et al., 1998; Knapton and Petrie, 1999; Badzinski and Petrie, 2006). In addition, SAV quantity and species composition are indicators of local water conditions, affect biogeochemical and sedimentological processes, and protect shorelines from erosion by decreasing nearshore wave action (Moore et al., 1996). Despite their importance to fish, wildlife and humans, a substantial number of LGL coastal wetlands have been drained for agriculture and other development (e.g., b5% of western Lake Erie coastal wetlands remain intact), thereby increasing the importance of remaining coastal wetland habitat for wetlanddependent organisms. Inner Long Point Bay, Lake Erie (LPB) is an important wetland complex with limited anthropogenic impacts. LPB is
⁎ Corresponding author at: Department of Biology, Western University, London, Ontario N6A 5B7, Canada. Tel.: +1 519 619 3225. E-mail address: [email protected] (R.T.J. Churchill).
important as fish and wildlife habitat because it has an extensive SAV community covering N 99% of the bay (Knapton and Petrie, 1999). Many of the remaining wetlands in the LGL region have been altered by various stressors, including the introduction of exotic plants and invertebrates (Petrie, 1998; Knapton and Petrie, 1999; Petrie and Knapton, 1999). Invasive species can affect carrying capacity for waterfowl and other animals by altering total biomass of SAV or changing species composition within wetlands (Crowder and Bristow, 1988). For instance, introduction and proliferation of zebra mussels (Dreissena polymorpha) and quagga mussels (D. burgensis) (hereafter combined as dreissenid mussels) has been associated with changes in abundance, distribution, and community composition of SAV within the LGL (Blindlow, 1992; Knapton and Petrie, 1999; Petrie and Knapton, 1999). Filtering activities of dreissenid mussels reduce suspended particles in the water column, thereby increasing water clarity and decreasing light attenuation (Knapton and Petrie, 1999). Decreased light attenuation enhances benthic photosynthesis and influences the distribution and abundance of SAV (Wetzel, 1983). In addition, dreissenid mussels can alter microbially-mediated nutrient cycling and the nearshore phosphorus cycle, further decreasing phytoplankton levels (Wilson et al., 2006). Filtering by dreissenid mussels has decreased phytoplankton levels which in turn likely has led to increased water clarity
http://dx.doi.org/10.1016/j.jglr.2016.07.012 0380-1330/© 2016 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved.
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
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and increased SAV abundance that was observed at Lake St. Clair during the mid-1990s (Schloesser and Manny, 2007). Diving ducks (e.g., Aythya spp. and Bucephala spp.) feed exclusively in aquatic habitats, and thus, the shallow, productive waters of LPB provide foraging habitat necessary for these ducks to complete migration (Petrie, 1998). Expansion of introduced dreissenid mussels to Lake Erie in the early-1990s led to an initial increase in use of LPB by molluscivorous ducks (Petrie and Knapton, 1999). Lesser scaup (Aythya affinis), greater scaup (A. marila), bufflehead (Bucephala albeola) and common goldeneye (B. clangula), in particular, have altered traditional migration patterns to take advantage of this novel food source in LPB (Hamilton et al., 1994; Petrie, 1998; Petrie and Knapton, 1999). However, since 2000, diving duck use has decreased at LPB, particularly in species that eat dreissenid mussels (Badzinski, 2007). In addition, the abundance of economically important fish species, such as yellow perch (Perca flavescens), largemouth bass (Micropterus salmoideus), and smallmouth bass (Micropterus dolomieu), have also decreased within LPB since the late-1990s (Ontario Ministry of Natural Resources, 2007). Causes of fish and diving duck declines remain unclear, but it is plausible that a decline in abundance or distribution of dreissenid mussels and SAV may be direct or indirect contributing factors. Following introduction to a suitable, new locale, exotic species often occur in greater abundance than observed in their native range. Often, initial increases in abundance of invasive species are followed by decline until a new regional carrying capacity is reached (McKillup et al., 1988). Dreissenid mussels prefer to anchor to hard substrate, but those types of substrates are not found extensively throughout LPB so mussels primarily anchor to SAV (Knapton and Petrie, 1999). Thus, in LPB, abundance of dreissenid mussels may be influenced by abundance and species distribution of SAV. Because LPB provides food and habitat for a diversity of fish and wildlife, researchers have previously quantified the distribution, abundance and long-term temporal dynamics of the SAV community (Knapton and Petrie, 1999; Petrie and Knapton, 1999). Smith (1979) mapped the distribution of SAV in LPB during the 1970s. Knapton and Petrie (1999) and Petrie and Knapton (1999) assessed the distribution and abundance of SAV and dreissenid mussel density in the mid1990s and compared their findings with those of Smith (1979). In this study, we quantified distributions and abundance of SAV and dreissenid mussel density (mussels/m2) to evaluate if changes have occurred since the 1990s when dreissenid mussels first colonized LPB. Our objectives were to: 1) determine if species percent abundance and occurrence of SAV changed in LPB between 1976 and 2009, 2) determine if the density of dreissenid mussels in LPB differed between 1991, 1992, and 2009, and 3) determine factors influencing the occurrence of SAV in LPB that may aid in our understanding of past and future changes in SAV in LPB.
a
b
c
Material and methods Study area Our study was conducted at Long Point, Ontario (80° 30′ W, 42° 35′ N to 80° 03′ W, 42° 33′ N; Fig. 1.). Long Point is a sand-spit extending 35 km south-east into Lake Erie that has facilitated the formation of the Inner and Outer Long Point Bays and associated freshwater marsh complexes (Petrie, 1998). The Inner Bay at Long Point has an area of 78 km2 and mean depth (1 to 2 m) varies depending upon annual and periodic changes in regional water budgets (Berst and McCrimmon, 1966). Coverage of the Inner Bay by SAV is N90% in most locales (Pauls and Knapton, 1993; Petrie, 1998; Smith, 1979). The mean summer temperature of Inner Bay (22 °C; Pauls and Knapton, 1993; Smith, 1979) provides favorable growing conditions for macrophytic SAV including: muskgrass (Chara vulgaris), wild celery (Vallisneria americana), Eurasian milfoil (Myriophyllum spicatum), naiad (Najas spp.), pondweeds (Potamogeton spp.), Canada water weed (Elodea canadensis), and coontail (Ceratophyllum demersum; Petrie, 1998). Big Creek is the
Fig. 1. Distribution and density (mussels/m2) of dreissenid mussels in Long Point Bay – Lake Erie a) 1991 b) 1992 and c) 2009.
major tributary of the Inner Bay that drains a 730 km2 watershed comprised primarily of agricultural land northwest of Long Point (Berst and McCrimmon, 1966; Leach, 1981). Big Creek influences the SAV communities in LPB because it is the primary source of nutrients and sediments in the bay (Leach, 1981). LPB substrate is predominantly mud at the mouth of Big Creek, sandy loam over most of the central portion, and sand bordering the eastern and south-eastern portions (Churchill, 2015). Study design and sample collection We used a grid generated with geographic information system software (GIS) to uniformly distribute 321 sampling stations throughout
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
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LPB (ArcMAP10, Release 10. Redlands, CA: Environmental Systems Research Institute). We used a Global Positioning System (GPS) with ± 3 m accuracy (Garmin 76C x) to navigate to sampling stations a using a 7 m pontoon boat. We collected SAV, dreissenid mussels, and environmental variables at the 321 stations 5–29 August 2009 according to the methodology used in the previous studies. At each sampling station, we recorded water and Secchi depth using a Secchi disk with a lowering line marked at 5 cm intervals. We measured water temperature using a digital thermometer (± 0.001 °C; Fisher Scientific 0666426). We dove to the substrate using SCUBA to collect SAV, dreissenid mussels, and benthic substrate samples. We estimated SAV percentage cover using a modified Braun-Blanquet scale of abundance and ascended to the surface to record values. We modified the BraunBlanquet scale using categories 0–4 (category mid-points at 12.5%, 37.5%, 62.5%, and 87.5% cover) instead of 0–5 to create continuous values for multivariate analysis. We used scissors to clip all aboveground SAV in a 0.5 m2 quadrat at substrate level. We used a mesh bag with 1 mm netting to capture and strain samples. We sampled substrate by collecting three horizontal scoops of substrate with a perforated metal can (total combined sample volume = 0.03 m3; Badzinski, 2003). Dreissenid mussels were removed from SAV samples on the deck of the boat, where we bottled and labelled each of the mussel samples separately. Finally, we differentiated between above and belowground (i.e., roots, turions/tubers, and rhizomes) SAV samples, and froze samples until further processing.
Laboratory procedures All species-specific aboveground vegetation samples were blotted dry using paper towel. We weighed each sample using a digital balance (± 0.001 g; A&D Company Ltd. FX3000i) and recorded values as wet mass. Belowground plant parts were separated from benthic substrate using a fine mesh sieve (2 mm × 2 mm; Fisher Scientific U.S. standard brass). Substrate type was classified into one of three groups (mud, sandy loam, or sand) using the modified Wentworth scale (Wentworth, 1922). Three substrate classifications were selected based on previously reported substrate types within LPB (Smith, 1979). Dry mass of subsamples was obtained to allow for estimation of dry mass for aboveground samples (by species). We selected sub-samples from aboveground samples for each species and oven-dried them separately at 80 °C to constant mass (±0.001 g). We ensured that sub-samples represented the range of wet masses observed in samples of each species. Thereafter, we used linear regression to estimate dry mass using wet mass measurements (Table 1). The only species we detected in belowground sampling was wild celery tubers and occurrence was negligible, accounting for 0.05% and 0.58% in autumn and spring respectively, of the total SAV biomass and were included with the aboveground parts of wild celery in our analysis. Dreissenid mussels were counted at each sample site.
3
Data mapping and analysis We obtained SAV abundance and distribution data in LPB from previous studies (1976, 1991, and 1992) from Bird Studies Canada archives (Port Rowan, Ontario). In 1976, only cover (using the Braun-Blanquet scale) for each plant species was available. In 1991 and 1992, cover data for each plant species as well as water depth, Secchi depth, and dreissenid mussel abundance were available. We used inverse distance-weighted (IDW) spatial interpolation to estimate speciesspecific distributions and changes in SAV and dreissenid mussel distribution in LPB (Spatial Analyst tool, ArcGIS Desktop: Release 10. Redlands, CA: Environmental Systems Research Institute; Watson and Philip, 1985; Neckles et al., 2012). We mapped the abundances of dreissenid mussels and the six most abundant SAV species (see Fig. 2) for 1976, 1991, 1992, and 2009 to provide a graphical representation of community changes in LPB. We used the modified Braun-Blanquet scale described above to map our ordinal SAV data. We used dreissenid mussel density (mussels/m2) to develop maps to show changes in density among years. To test for temporal variation in mussel abundance, we used repeated measures analysis of variance (ANOVA). Spatial interpolation provides a visual representation of SAV coverage in LPB but does not provide statistical comparisons of abundances among years. We used multivariate analysis of variance (MANOVA) to test for changes in plant community (e.g., percent cover of SAV) among years using SAV abundance data. We included muskgrass, wild celery, Eurasian milfoil, naiad, slender pondweed (Potamogeton pusillus) and Richardson's pondweed (Potamogeton richardsonii) cover using the modified BraunBlanquet values as response variables and year as a repeated measure to account for sampling the same points through time. We included latitude and longitude as covariates to control for spatial autocorrelation and substrate as a categorical fixed variable to assess potential changes to growing conditions among sampling points. We inspected studentized residual plots from all models for normal distribution. We log-transformed SAV data to normalize residual distribution (Littell et al., 2007). We selected a α = 0.10 level of significance a priori because it is appropriate for observational data (Tacha et al., 1982). We used Wilks' lambda to evaluate statistical significance of year effects within multivariate analysis (MANOVA) and when MANOVA was significant, used F-tests (type III sum of squares) produced from univariate analyses. We used logistic regression to determine factors influencing detection probability of a species at a sampling station for the 6 most common species of SAV by biomass (Churchill, 2015; Fig. 2). We initially included dreissenid mussel abundance, substrate type, year, water
Table 1 Linear regressions for conversion of wet weights to dry weights for species of SAV sampled at Long Point Bay, Lake Erie, autumn 2009 and spring 2010. Species
n
Intercept
slope
r2
Chara vulgaris Myriophyllum spicatum Najas spp. Najas flexilis Najas guadalupensis Potamogeton richardsonii Potamogeton pusillus Vallisneria americana
23 32
2.5306 0.2487
0.2544 0.1524
0.99 0.98
29 14 19 25 26
0.6847 0.1009 0.0341 0.6916 0.3649
0.1218 0.1557 0.1309 0.1141 0.1003
0.99 0.98 0.95 0.99 0.97
Fig. 2. Percent composition (dry wt.) of submerged aquatic vegetation within Long Point Bay, Lake Erie, Ontario, August 2009.
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
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a
b
c
d
Fig. 3. Distribution and abundance (percent cover) of muskgrass (Chara vulgaris) in Long Point Bay – Lake Erie a) 1976 b) 1991 c) 1992 and d) 2009.
depth, depth × depth, and substrate × year as fixed effects and latitude and longitude as covariates to control for spatial effects. We included depth × depth to test for quadratic relationships typical of SAV occurrence as depth increases, whereby likelihood of occurrence can decrease or increase beyond a threshold depth (Blindlow, 1992). We included substrate × year to determine whether detection probability of SAV changed through time within substrate types and within years among substrate types. We did not include 1976 data in our model because data were lacking. We removed variables not significant at α = 0.10. We did not include Secchi disk reading because it was strongly
correlated with water depth (P b 0.01; r = 0.90), but subject to greater error than water depth because of daily difference in turbidity. We compared means of reduced models using post-hoc Tukey's adjustment and produced plots using model predicted values. Results We detected that density of dreissenid mussels (mussels/m2) increased by 2110% between 1991 (20.6 mussels/m2) and 1992 (456.8), decreased 96% between 1992 and 2009 (18.9), and did not differ
a
b
c
d
Fig. 4. Distribution and abundance (percent cover) of wild celery (Vallisnaria americana) in Long Point Bay – Lake Erie a) 1976 b) 1991 c) 1992 and d) 2009.
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
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5
a
b
c
d
Fig. 5. Distribution and abundance (percent cover) of naiad (Najas spp.) in Long Point Bay – Lake Erie a) 1976 b) 1991 c) 1992 and d) 2009.
between 1991 and 2009 (P = 0.999) (year effect, F2,960 = 25.72, P b 0.001) (Fig. 1). We also detected an influence of sampling year on percent cover of the six most abundant SAV species in LPB between 1976 and 2009 (MANOVA: Wilks' λ = 0.90, F3, 316 = 11.76, P b 0.001) (Figs. 3–8). Percent cover of wild celery (P b 0.001; Fig. 9a), Richardson's pondweed (P b 0.001; Fig. 9d) and Eurasian milfoil (P b 0.001; Fig. 9f) were greatest in 1991 and 1992, whereas Najas spp. (P b 0.001; Fig. 9b) and muskgrass (P b 0.001; Fig. 9e) cover was greater in 1992, and slender pondweed (P b 0.001; Fig. 9c) was the only species with greater percent cover in 2009.
Probability of detecting wild celery and muskgrass varied negatively with depth as quadratic and linear functions, respectively (P b 0.001; Table 2; Fig. 10a–b), whereas Eurasian milfoil (P b 0.001; Table 2; Fig. 10c) and Richardson's pondweed (P = 0.002; Table 2; Fig. 10d) varied positively and negatively, respectively, with depth as quadratic functions. Slender pondweed (P = 0.054; Table 2; Fig. 10e) varied positively with water depth. Detection of Najas spp. did not differ among water depths (P = 0.641; Table 2). Species responses to substrate type varied; detection probability of muskgrass (P ≤ 0.006; Table 2; Fig. 11a) was greater on sand and
a
b
c
d
Fig. 6. Distribution and abundance (percent cover) of Eurasian milfoil (Myriophyllum spicatum) in Long Point Bay – Lake Erie a) 1976 b) 1991 c) 1992 and d) 2009.
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
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a
b
c
d
Fig. 7. Distribution and abundance (percent cover) of Richardson's pondweed (Potamogeton richardsonii) in Long Point Bay – Lake Erie a) 1976 b) 1991 c) 1992 and d) 2009.
sandy loam substrate, whereas slender pondweed (P = 0.018; Table 2; Fig. 11c) and Eurasian milfoil (P b 0.001; Table 2; Fig. 11b) were more likely to be detected on mud substrate. Effects of substrate and sampling year interacted to influence detection probability of wild celery, Najas spp., and Richardson's pondweed (Table 2; Fig. 12). Detection probability was greater for Richardson's pondweed (P = 0.019; Fig. 12c) across all sampling years in mud substrate. Najas spp. (P b 0.001; Table 2; Fig. 12b) was more likely to be detected on sandy loam during 1991, though this changed to mud in 1992 and 2009.
Discussion A diversity of fish and wildlife rely on SAV for food and cover in the Great Lakes region and beyond. The distribution and abundance of SAV, and consequently their availability to fish and wildlife is a function of several environmental factors including light quantity, interspecific competition, nutrient availability, herbivory, ice and storm damage, fluctuating water levels, temperature, pH, and presence of invasive species (Knapton and Petrie, 1999; Petrie and Knapton, 1999). Expansion of
a
b
c
d
Fig. 8. Distribution and abundance (percent cover) of slender pondweed (Potamogeton pusilus) in Long Point Bay – Lakie Erie a) 1976 b) 1991 c) 1992 and d) 2009.
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
R.T.J. Churchill et al. / Journal of Great Lakes Research xxx (2016) xxx–xxx
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b
c
d
e
f
Log LS Means
a
Year Fig. 9. Least-squared means (log transformed) of cover (±90% CI; using the Braun-Blanquet values) for the most abundant species of SAV in LPB: a) Wild celery b) Najas spp. c) Slender pondweed d) Richardson's pondweed e) Muskgrass and f) Eurasian milfoil. Years with the same letter are not significantly different (P N 0.10).
dreissenid mussels into LPB in the early 1990s had been the most pronounced recent influence on SAV within the bay (Petrie and Knapton, 1999). We initiated this study to determine if the abundance and distribution of dreissenid mussels and SAV had changed since previous studies in the early 1990s. Although the distribution of dreissenid mussels in LPB has not changed substantially since 1992, the total abundance of these mussels has decreased substantially. The increase in dreissenid mussel abundance in the early-1990s resulted in increased water transparency and declines in all phytoplankton taxa and chlorophyll concentrations in Lake Erie (Holland, 1993). The decline in suspended particulate matter could have contributed to the overall decline in dreissenid mussels since 1992 because of a reduced food source. Furthermore, predation by both fish and waterfowl also likely contributed to the decline in abundance of dreissenid mussels (Mitchell, 1995; Petrie and Knapton, 1999). The resulting change in water clarity in LPB also may have influenced the SAV community within LPB. With the exception of slender pondweed, the 5 most abundant SAV species in LPB experienced declines in abundance since 1992 (Figs. 3–8). Because nutrient enrichment and light availability are interrelated, it is possible that synergistic effects explain SAV growth within LPB. Angiosperm SAV species are known to proliferate in eutrophic
water (Smith, 1979), but it is possible that there is a point at which there is not enough light available to stimulate growth, regardless of nutrient availability. Inputs of nitrogen and phosphorus from fertilizer applications can result in declines of SAV and enhancement of phytoplankton (Twilley et al., 1985). Increased abundance of suspended particles in the water column decrease light availability for SAV and can cause reductions in plant growth. At inner Saginaw Bay, where inputs from agriculture are substantial, colonization by dreissenid mussels caused decreases in phosphorus and phytoplankton and increases in water clarity (Fahnenstiel et al., 1995a, 1995b). As such, declines in dreissenid mussels in LPB and an associated increase in phytoplankton growth since 1992 may have reduced light availability for SAV below a threshold that retards growth of these plants. We suggest that further investigation of types and locations of nutrient inputs into LPB influencing water quality and clarity are needed to determine specific mechanisms for changes in SAV. Water depth and substrate type greatly influenced probability of detection for most species of SAV we observed in LPB. Our models could be used to predict future changes in SAV communities in LPB with decreasing water depth resulting from changes in climate and changes in sediment loading from Big Creek. Winter precipitation and run-off are
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
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Table 2 Reduced multiple logistic regression models of the SAV distribution data (n = 321). Specific SAV species' presence or absence was the response variable and the 11 site characteristics were the explanatory variables. X2
Species
Effect
Estimate
Error
DF
P
Wild Celery
Intercept Substrate Mud Sandy loam Depth Year 1991 1992 Depth × depth Substrate × year Intercept Substrate Mud Sandy loam Depth Year 1991 1992 Depth × depth Intercept Substrate Mud Sandy loam Year 1991 1992 Depth × depth Intercept Substrate Sandy loam Year 1991 1992 Substrate × year Intercept Substrate Mud Sandy loam Depth Year 1991 1992 Depth × depth Substrate × year Intercept Substrate Mud Sandy loam Depth Year 1991 1992
−1243.2
213.6
b0.001 0.034
33.884 6.788
−0.319 −0.142 −0.018
0.251 0.153 0.007
0.011 0.067
6.521 5.489
0.179 0.162 b0.001
0.157 0.162 b0.001
1567.5
237.3
−0.56 0.671 0.013
0.208 0.144 0.007
−0.6 0.828 b−0.001 −927.3
0.134 0.141 b0.001 299.2
0.419 −0.649
0.213 0.152
0.874 0.625 b0.001 −220.3
0.141 0.139 b0.001 196.6
0.603
0.135
0.357 0.859
0.117 0.123
−618.4
240.1
1 2 1 1 1 2 1 1 1 4 1 2 1 1 1 2 1 1 1 1 2 1 1 2 1 1 1 1 2 1 2 1 1 4 1
0.027 0.035 b0.001 b0.001 0.007 b0.001 0.047 b0.001 b0.001 b0.001 b0.001 b0.001 0.001 0.049 b0.001 b0.001 b0.001 b0.001 b0.001 0.262 b0.001 b0.001 b0.001 0.002 b0.001 b0.001 0.01
4.885 10.354 43.636 22.056 7.214 21.734 3.941 36.341 19.923 34.592 13.872 16.367 17.731 3.854 17.723 90.513 38.624 20.301 11.556 1.256 44.131 20.047 104.433 9.262 49.022 33.341 6.636
0.9420 0.1756 −0.020
0.734 0.798 0.007
0.002 b0.001
9.325 23.652
2.787 2.115 b0.001
0.635 0.647 b0.001
−1243.2
213.6
0.002 0.047 b0.001 0.024
9.853 9.650 33.884 7.491
1.245 −0.512 −0.018
0.755 0.572 0.007
0.054 b0.001
3.710 5.489
−13.720 −2.056
153.7 0.483
Muskgrass
Eurasian Milfoil
Najas
Richardson's pondweed
Slender pondweed
predicted to decrease in the Great Lakes region, which would reduce spring run-off into LPB from Big Creek and water coming from other areas of the Great Lakes watershed (Steen et al., 2006; Notaro et al., 2014). Soil conservation practices aimed at reducing siltation in the Big Creek watershed coupled with decreased flood intensity and duration from spring snow melt may reduce development of mud substrate in LPB (Petrie, 1998). Our models predict that decreasing water levels would favor wild celery and possibly muskgrass, whereas Eurasian milfoil would decrease in LPB. Shifts in substrate type are difficult to predict, but our models suggest that decreases in mud substrate would favor muskgrass relative to other SAV in LPB. Decreased water levels and decreased mud substrate combined would favor muskgrass over other SAV in LPB. Muskgrass, while eaten by waterfowl, is less preferred relative to pondweeds and wild celery (Bellrose, 1980; Petrie, 1998). Considering that 83% of the SAV community was musk grass in 2009, a scenario of increasing musk grass would decrease plant diversity and quality of foods available to waterfowl in LPB.
1 1 1 2 1 1 1 4 1 2 1 1 1 2 1 1
Further monitoring of SAV and dreissenid mussels within LPB is important given its importance to migrating waterfowl, especially diving ducks and dabbling ducks that require an abundance of these plants to fuel migration (Petrie, 1998; Baldassarre and Bolen, 2006). Additionally, it would be beneficial for future studies to assess nutrient inputs and levels in LPB because they influence SAV growth and were not analyzed as part of this study. Nutrient inputs also are important when considering substrate types in LPB. Big Creek flows into northwest LPB, an area that is covered with dense, diverse stands of SAV. The Big Creek delta has a mud substrate, and this study shows the importance of this substrate type to a variety of plants. Sediment from Big Creek watershed deposited in LPB as mud substrate likely contributes substantially to turbidity, light attenuation, and nutrient loading. Further research on landscape change and inputs from Big Creek into LPB are necessary to increase our ability to predict future changes to SAV in LPB. This study establishes a new baseline for SAV and mussel distribution and abundance which can be used to detect the ecological impacts of future invasive species introductions.
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
Predicted Probability
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a
b
c
d
e
Depth (cm) Fig. 10. Relationship between the predicted probability of SAV presence (a) wild celery b) muskgrass c) Eurasian milfoil d) Richardson's pondweed e) slender pondweed) and water depth (±90% CI) in Long Point Bay – Lake Erie in 1991, 1992, and 2009.
Predicted Probability
a
b
c
Mud
Sandy Loam Substrate
Sand
1991
1992
2009
Year
Fig. 11. Relationship between the predicted probability (±90% CI) of SAV presence (a) muskgrass b) Eurasian milfoil c) slender pondweed and the effects of substrate and year in Long Point Bay – Lake Erie in 1991, 1992, and 2009. Substrate and year interactions were not significant. Substrate and year were not significant for plant species not shown.
Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012
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a
Predicted Probability
b
c
1991
1992 Year
2009
Fig. 12. Relationship between the predicted probability (± 90% CI) of SAV presence (a) wild celery b) Najas spp. c) Richardson's pondweed and the interactive effects of substrate and year in Long Point Bay – Lake Erie in 1991, 1992, and 2009. Substrate and year were not significant for plant species not shown.
Acknowledgements Funding for this project was provided by Long Point Waterfowl, The Bluff's Hunt Club, S.C. Johnson & Son, Ltd., Ontario Ministry of Natural Resources and Forestry, Ontario Federation of Anglers and Hunters, Ducks Unlimited Canada, Long Point Waterfowler's Association and The Order of Good Cheer. We thank J. Cook, J. Gilbert, T. Barney, A. Dhamorikar, J. Palframan, D. Messmer, M. Bossyut, S. Bossyut, S. Hockley, C. Walker, R. Watt, M. Morse, A. Winstanley-Hayes, and A. Good for technical, field, and lab assistance. We also thank T. Barney, E. Hanna, R. Brook, K. Abraham and S. Badzinski for helpful comments in development of this manuscript. References Badzinski, S.S., 2003. Influence of tundra swans on aquatic vegetation and staging waterfowl at Long Point, Ontario (Unpublished Ph.D. dissertation) University of Western Ontario, London. Badzinski, S.S., 2007. Toward rehabilitation of the Crown Marsh – Long Point, Lake Erie, Ontario (Unpublished report to the Long Point Crown Marsh Rehabilitation Steering Committee) p. 16. Badzinski, S.S., Petrie, S.A., 2006. Lesser scaup spring nutrient reserve dynamics on the lower Great Lakes. Wildl. Soc. Bull. 34, 395–407. Baldassarre, G.A., Bolen, E.G., 2006. Waterfowl Ecology and Management. Kreiger, Malabar, Fl. Berst, A.H., McCrimmon, H.R., 1966. Comparative summer limnology of Inner Long Point Bay, Lake Erie, and its major tributary. Can. J. Fish. Aquat. Sci. 23, 275–291. Bellrose, F.C., 1980. Ducks, geese and swans of North America. Mechanicsburg, Stackpole.
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Please cite this article as: Churchill, R.T.J., et al., Long-term changes in distribution and abundance of submerged aquatic vegetation and dreissenid mussels in Long Point Bay, Lake Erie, J. Great Lakes Res. (2016), http://dx.doi.org/10.1016/j.jglr.2016.07.012