Remote sensing reflectance in the Great Lakes: In situ measurements,closure analyses,and a forward model

Observations of remote sensing reflectance (R_rs), the signal available to support remote sensing of optically active constituents (OACs) of water quality interest, are presented for multiple sites within each of the Laurentian Great Lakes based on in situ measurements made with a hyperspectral radiometer. R_rs(λ) spectra are contrasted among these lakes and in time and space within selected systems. Qualitative analyses of spectra are provided that identify the inherent optical property (IOP) and coupled OAC conditions responsible for the differences in R_rs(λ). The much higher R_rs peaks observed in the green wavelengths for the lower Great Lakes (Erie and Ontario) are attributed to elevated backscattering levels caused by higher concentrations of minerogenic particles. The credibility of the R_rs(λ) spectra is established through successful closure analyses that demonstrate good matches with IOP-based predictions and consistency of coefficient values for radiative transfer expressions with related literature and theory. A mechanistic forward model of R_rs(λ) is developed that accommodates the effects of three OACs, including metrics of phytoplankton biomass, minerogenic particles and colored dissolved organic material. This includes the development of the critical cross-section relationships that quantify the couplings between the OACs and IOPs, and in turn the IOPs and the R_rs(λ) signal. The model is demonstrated to perform well in matching observations in Lake Erie, and to be sensitive to the representation of the spectral dependency of backscattering and likely variations in the dependence of phytoplankton absorption on chlorophyll. The modeled predicted responses of Lake Erie to different OAC levels are presented.     

Optical characterizations and pursuit of optical closure for the western basin of Lake Erie through in situ measurements

In situ measurements of inherent (IOPs) and apparent optical properties (AOPs), along with laboratory measurements of optically active constituents, were made at sites (n = 14) in western Lake Erie following a wind event to advance the characterization of the underwater and emergent light fields of these waters and to support related IOP-based model development and testing. Modern instrumentation was used to make spectral (wavelength, λ) measurements of the IOPs of absorption [a(λ)], particulate scattering [b_p(λ)], and particulate backscattering [b_bp(λ)] coefficients, and the AOPs of remote sensing reflectance [R_rs(λ)], and the diffuse attenuation coefficient for downwelling irradiance [K_d(λ)]. Optical closure analyses were conducted to demonstrate the credibility of the measurements, by comparing AOP observations to predictions based on radiative transfer expressions that utilized IOP measurements as inputs. Substantial spectral variations in a and its contributing components, and more modest wavelength dependencies for b_p and b_bp, were documented that are consistent with observations reported for marine case 2 systems. The backscattering ratio, b_bp:b_p, was strongly positively related to the contribution of minerogenic particles to the overall concentration of suspended particulate material. Major spatial differences in both IOPs and AOPs were observed that were driven by the attendant differences in the concentrations and composition of the optically active constituents, but particularly minerogenic particles, mediated in part by sediment resuspension. Good optical closure between the independently measured IOPs and AOPs was achieved. Direct measurement of b_bp(λ) was found to be critical to pursue closure for R_rs(λ) and thereby support related remote sensing initiatives.     

Optical characterization of Lake Champlain: Spatial heterogeneity and closure

A robust optical characterization of the underwater and emergent light fields of Lake Champlain was conducted for sites (n = 11) throughout the lake in August 2011, based on in situ measurements with modern instrumentation and laboratory measurements of optically active constituents (OACs) and components (a_x) of the absorption coefficient (a). Inherent optical property (IOP) measurements included a, a_x, and the particulate scattering and backscattering coefficients. Metrics of apparent optical properties (AOPs) included Secchi depth, the diffuse attenuation coefficients for downwelling [K_d(λ)] and scalar (K₀) irradiance and remote sensing reflectance [R_rs(λ)]. The credibility of the measurements is demonstrated through: (1) consistency of relationships between OACs and IOPs and AOPs, (2) the approach toward equivalence of laboratory and field measurements, and (3) the extent of closure of predictions of K_d(λ) and R_rs(λ), based on IOP measurements and radiative transfer expressions, with paired observations of these AOPs (average differences of 9.4 and 19.3%). Wide spatial differences in OACs, and the resulting IOPs and AOPs, are documented throughout the bounds of the lake and are the result of its morphologic complexity and differing external loading. The lake is a complex case 2 system, with uncoupled variations in OACs and a_x over the bounds of the lake. Both empirical and radiative transfer expressions are used to predict changes in AOPs in response to hypothetical changes in OACs.     

Periphytic algal biomass as a bioindicator of phosphorus concentrations in agricultural headwater streams of southern Ontario

Algal blooms in Lake Erie have worsened in recent decades and are driven by diffuse export of phosphorus (P) from a large stream network that drains predominately agricultural land. Given the diffuse nature of nonpoint source pollution, best management practices (BMPs) must target areas where P levels are high. This requires long-term watershed-wide monitoring programs that do not currently exist in many jurisdictions. Instead of conventional nutrient analyses that can be costly and time-consuming, we propose the use of periphyton biomass as a bioindicator of trophic status in low-order streams, where agricultural runoff first enters watercourses. We carried out 2-week in-stream bioassays to measure periphytic algal biomass (CHL_peri) in 19 low-order streams in southern Ontario across an agricultural gradient (8 % to 89 %). CHL_peri was significantly related to total P (TP) concentration (r² = 0.46; p = 0.0015) but was not significantly related to soluble reactive P (SRP). A relationship between TP and turbidity (r² = 0.52; p = 0.0007) is consistent with previous observations of increasing SRP uptake in streams draining agriculturally-dominated landscapes. Stream temperature (°C) was correlated with the proportion of agricultural land (R = 0.55; p = 0.019) and may reflect the warming effects of the sun in unshaded agricultural streams. This method involving substrate rods (Peristix) is cost-effective, requires very little training, and yielded data that were significantly related to TP concentrations in agricultural streams. We recommend that environmental agencies and landowners use this bioassay to identify areas for implementing BMPs to reduce P export from the Lake Erie watershed.     

Light-absorbing components in the Great Lakes

Features of light absorption are critical in regulating the optical signal available for remote sensing. The magnitudes, spectral characteristics, spatial patterns, and, to a lesser extent, dynamics of light-absorbing components are documented for the Laurentian Great Lakes. This includes the open waters of each of the five lakes, and selected rivers, embayments and near-shore areas. The absorption coefficient, a(m^? 1), is partitioned according to the additive components (a_x) of colored dissolved organic matter (a_CDOM), non-algal particles (a_NAP), phytoplankton (a_φ), and water itself (a_w; known). Dependencies of a_x on various metrics of optically active constituents (OACs), cross-sections, are evaluated. A wide range of magnitudes of a_x and a, and contributions of a_x to a are documented. For example, the magnitude of a at a wavelength of 440 nm was nearly 10-fold greater in the western basin of Lake Erie than in the open waters of Lake Huron. Rivers, embayments, and near-shore areas generally had higher levels than the open waters. The largest a_x throughout the system was a_CDOM, originating mostly from terrestrial sources. Most of a_NAP was associated with clay mineral particles. The distribution of a_φ was highly correlated to chlorophyll concentration. The collected data set is appropriate to support initiatives to develop and preliminarily test mechanistic retrieval algorithms for OACs in the Great Lakes.     

Surface Corrections for Remote Sensing Reflectance in Case 2 Waters of Lake Superior

We establish the average wavelength dependence for rough-surface reflectance S_rs(λ) in Lake Superior and determine its magnitude at any individual site by extrapolating the total reflectance or raw remote sensing reflectance R_rsT(λ) measured at the surface to the asymptotic limit of zero scattering where S_rs(λ) ≅ R_rsT(λ). The results show that S_rs(λ) differs from the flat-surface Fresnel reflectance of sky radiance used in standard determination of the remote sensing reflectance R_rs(λ) attributed to the scattering of light by particles and molecules in bulk water. In waters containing colored dissolved organic matter (CDOM), R_rs(λ) can be very low and radiometric measurements at ground level can often lead to negative estimates of R_rs(λ) if we assume simple mirror-like reflectance of the sky radiance as the basis for correcting radiometric data for surface reflectance. We examine the differences between Fresnel reflectance and S_rs(λ) and estimate the ratio of the concentrations of CDOM versus suspended particles that could produce negative values of R_rs(λ) if assume Fresnel reflectance in calculation of R_rs(λ).     

Linking multi-media modeling with machine learning to assess and predict lake chlorophyll a concentrations

Eutrophication and excessive algal growth pose a threat on aquatic organisms and the health of the public, environment, and the economy. Understanding what drives excessive algal growth can inform mitigation measures and aid in advance planning to minimize impacts. We demonstrate how simulated data from weather, hydrological, and agroecosystem numerical prediction models can be combined with machine learning (ML) to assess and predict chlorophyll a (chl a) concentrations, a proxy for lake eutrophication and algal biomass. The study area is Lake Erie for a 16-year period, 2002–2017. A total of 20 environmental variables from linked and coupled physical models are used as input features to train the ML model with chl a observations from 16 measuring stations. Included are meteorological variables from the Weather Research and Forecasting (WRF) model, hydrological variables from the Variable Infiltration Capacity (VIC) model, and agricultural management practice variables from the Environmental Policy Integrated Climate (EPIC) agroecosystem model. The consolidation of these variables is conducive to a successful prediction of chl a. Aside from the synergistic effects that weather, hydrology, and fertilizers have on eutrophication and excessive algal growth, we found that the application of different forms of both P and N fertilizers are highly ranked for the prediction of chl a concentration. The developed ML model successfully predicts chl a with a coefficient of determination of 0.81, bias of −0.12 μg/l and RMSE of 4.97 μg/l. The developed ML-based modeling approach can be used for impact assessment of agriculture practices in a changing climate that affect chl a concentrations in Lake Erie.     

Assessment of nitrogen fixation rates in the Laurentian Great Lakes

Nitrogen fixation (N_Fix) is an important, yet understudied, microbial process in aquatic ecosystems, especially in the Laurentian Great Lakes (LGL). To date, a dearth of nitrogen fixation rate measurements exists in the LGL, are from temporally isolated studies, and were collected primarily from near-shore and surface water environments. Evidence of nitrogen accumulation across the Laurentian Great Lakes suggest that we do not have a firm grasp on nitrogen cycling in large lakes. Thus, we sought to quantify the spatial variability of N_Fix in the LGL. We found lakes are significantly different in N_Fix rates from one another and that rates are depth dependent. Overall mean surface N_Fix rates of Lakes Superior, Michigan, Huron, Erie and Ontario were 0.024, 0.020, 0.069, 0.145, and 0.078 (nmol N₂/L/hr), respectively. Likewise, we found the Western, Central and Eastern basins of Lake Erie are significantly different in N_Fix rates (0.1540, 0.1032, 0.0738 nmol N₂/L/hr). However, we found no significant difference in N_Fix rates between near and offshore sites in Lake Erie, which may have been biased due to a cyanobacterial bloom containing a nitrogen-fixing Dolichospermum sp. Linear regression models indicate N_Fix is generally positively correlated with chlorophyll-a concentration and negatively correlated with oxidized nitrogen species concentrations. However, Lakes Erie and Huron exhibited a positive linear relationship with oxidized nitrogen, suggesting that N_Fix may persist to meet cellular and community nitrogen demands. Together, our data highlight N_Fix is important despite the presence of abundant nitrogen in all LGL.     

Variability of light absorption properties in optically complex inland waters of Lake Chaohu,China

Absorption coefficients of phytoplankton, colored detrital matter (CDM), non-algal particles (NAP), colored dissolved organic matter (CDOM), and their relative contributions to total non-water absorption (a_t ? w) are essential variables for bio-optical and radiative transfer models. Light absorption properties showed large range and variability sampled at 194 stations throughout Lake Chaohu between May 2013 and April 2015. The a_t ? w was dominated by phytoplankton absorption (a_ph) and NAP absorption (a_d). The contribution of CDOM absorption to a_t ? w was lower than 30%. Phytoplankton and NAP were the primary sources of spatial and vertical variability in absorption properties. Light absorption by CDOM, though significant in magnitude, was relatively constant. CDM absorption (a_dg) was dominated by NAP. The spatial variation of the absorption coefficients from each of the optically active constituents were driven by several main inflow rivers in the western and middle part of Lake Chaohu. Algal blooms and bottom resuspension contributed to vertical variability as observed by phytoplankton and NAP profiles. Specific absorption of phytoplankton had significant spatial and seasonal variations without vertical variation. The spectral slope of absorption showed no significant spatial variability (p > 0.05). Variations of absorption affected different ranges of remote sensing reflectance (R_rs) spectrum, thereby increasing the difficulty of applying the remote sensing algorithm in optically complex waters. Parameters and relationships presented in this study provide useful information for bio-optical models and remote sensing of lakes similar to Lake Chaohu in terms of optical properties.     

The impact of phytoplankton community composition on optical properties and satellite observations of the 2017 western Lake Erie algal bloom

Since the early 2000s Lake Erie has seen a dramatic increase in phytoplankton biomass, manifested in particular by the rise in the severity of cyanobacteria blooms and the prevalence of potentially toxic taxa such as Microcystis. Satellite remote sensing has provided a unique capacity for the synoptic detection of these blooms, enabling spatial and temporal trends in their extent and severity to be documented. Algorithms for satellite detection of Lake Erie algal blooms often rely on a single consistent relationship between algal or cyanobacterial biomass and spectral indices such as the Maximum Chlorophyll Index (MCI) or Cyanobacteria Index (CI). Blooms, however, are known to vary significantly in community composition over space and time. A suite of phytoplankton and optical property measurements during the western Lake Erie algal bloom of 2017 showed highly diverse bloom composition with variable absorption and backscatter properties. Elevated backscattering coefficients were observed in the Maumee Bay, likely due to phytoplankton cell morphology and buoyancy regulating gas vacuoles, compared with typically Planktothrix dominated blooms in Sandusky Bay. MCI and CI calibrated to historical chlorophyll observations and applied to Sentinel 3's OLCI sensor accurately captured the 2017 bloom in Maumee Bay but underestimated the Sandusky Bay bloom by nearly 80%. The phycoerythrin-rich picocyanobacteria Aphanothece and Synechococcus were found in abundance throughout the western and central basins, resulting in substantial biomass underestimations using blue to green ratio-based algorithms. Potential misrepresentation of bloom severity resulting from phytoplankton optical properties should be considered in assessments of bloom conditions on Lake Erie.     

Empirical modeling of chlorophyll a from MODIS satellite imagery for trophic status monitoring of Lake Victoria in East Africa

We detail our attempts at empirical modeling of MODIS derived Chlorophyll a (Chl a) distribution on Lake Victoria in East Africa and consequently its trophic status. This was motivated by the need for Lake Victoria specific algorithms, as the current satellite based standard algorithms overestimate derived Chl a. In situ Chl a data was hence collected in three field campaigns in November 2014, March 2015 and July 2015. In situ reflectances were collected during the July campaign only. We first developed models from in situ reflectances and in situ Chl a, which when applied to MODIS bands performed dismally (R² = 0.03). We then proceeded to derive empirical models by directly comparing MODIS bands with in situ Chl a based on data collected in November 2014 and July 2015. The March 2015 dataset couldn’t be used due to cloud cover hence no matchups could be obtained. The best model derived (R² = 0.88) was based on the ratio 488 nm/645 nm, and was then used to determine the trophic status of Lake Victoria using Carlson’s Chl a Trophic State Index (TSI). The results show that large areas of the lake are mesotrophic with eutrophic displays closer to the shores. The modeled TSI was then validated against in situ TSI derived from the March dataset and posted an 80% matchup. One of the main challenges, however is the prevalence of cloud cover, which hinders synoptic mapping of the lake. That notwithstanding, the study demonstrates the potential of earth observation in providing accurate TSI information for improved management of Lake Victoria.     

Estimation of Zooplankton Mean Length for Use in an Index of Fish Community Structure and its Application to Lake Erie

Mills et al. (1987) developed an index of zooplankton mean size to assess the state of fish communities. The use of this index was evaluated in an assessment of the fish community structure in 1993 at nearshore and offshore sites in the three Lake Erie basins. Mills et al.’s index was developed using a 153-μm mesh net, while the samples in this study have been collected with 64-μm and 110-μm mesh size nets. Two methods were used to convert the data to 153-μm equivalent collections: (a) regression relationships based on simultaneous collections with three mesh sizes, and (b) elimination of smaller organisms that would have passed through the 153-μm mesh by determining the minimum length of inclusion (MLI). The regressions employed for the conversion of zooplankton mean length (ZML) between the nets were: ZML₁₅₃ = 0.137 + 0.988 ZML₁₁₀ (mm) (r²= 0.804) (n = 10) and ZML₁₅₃ = 0.042 + 1.330 ZML₆₄ (mm) (r² = 0.931) (n = 9). The MLI that resulted in the same mean length as the 153-μm sample averaged (± 1 SE) 0.267 ± 0.016 mm (n =19).The comparison between zooplankton mean length and fish community structure in the western basin of Lake Erie in 1993 showed good agreement with Mills et al.’s index. However, the same was not true for the 1988 to 1990 data. Reasons for this discrepancy are discussed.     

Trends in Lake Erie phytoplankton biomass and community structure during a 20-year period of rapid environmental change

Since the 1990s, Lake Erie has experienced resurgent eutrophication due in part to climate change-driven increases in precipitation, which have combined with increasingly intensive agricultural practices in the region to produce excessive nutrient runoff into the lake. Harmful blooms of the cyanobacterium Microcystis aeruginosa (“Microcystis”) in Lake Erie’s western and central basins (WB and CB, respectively) have been a highly visible consequence of this eutrophication, however few studies have characterized intra- or interannual trends in less abundant, though likely more edible, phytoplankton taxa over the last 25 years. Here, we used the 20-year Lake Erie Plankton Abundance Study (LEPAS) dataset to quantify intra- and interannual trends in the dynamics of six major phytoplankton groups in the WB and CB during 1995–2015. Cyanobacteria biomass in the WB increased >1000-fold during this period, while biomass of all other major taxa groups increased between 10- and 100-fold. Early summer (June–July) and spring (May) communities saw more modest directional change in the biomass of both edible and less-edible taxa as well as community structure. Around 2008, the CB also began to experience Microcystis blooms concurrent with those in the WB, with similar, though less dramatic consequences for phytoplankton community structure and edible biomass. The biomass of several phytoplankton groups exhibited intra-annual oscillations with a ∼5-year period. The mechanisms underlying changes in the phytoplankton community structure and their consequences for higher trophic levels are not well understood, however increases in edible phytoplankton may be sustaining long-term upward trends in many zooplankton taxa.     

Methane and nitrous oxide measured throughout Lake Erie over all seasons indicate highest emissions from the eutrophic Western Basin

Eutrophication has been linked to increased greenhouse gas emissions from inland waters. Phytoplankton blooms in Lake Erie have increased since the 1990s, although its greenhouse gas emissions are not well characterized. We measured CH₄ and N₂O concentrations and diffusive fluxes in four seasons around the entire lake, and CO₂ fluxes in one summer season. Lake Erie is a source of CH₄ all year across the lake, concentrated in spring and summer in the Western Basin. Methane emissions ranged from 0.03 to 14.87 mg C m⁻² d^-1. Methane is predominantly biogenic, and natural gas leaks are an insignificant source. While Lake Erie is an overall N₂O source, it is an N₂O sink in winter and occasionally during summer. Emissions of N₂O ranged from −0.08 to 1.22 mg N m⁻² d^-1. We also measured CO₂ fluxes in summer only, when Lake Erie is a small atmospheric CO₂ sink. While areal fluxes of CH₄ and N₂O are similar to those observed elsewhere, total fluxes from Lake Erie are higher due to its surface area. Lake Erie emits ~ 6300 (±19%) metric tons of CH₄-C yr⁻¹ and ~600 (±37%) metric tons N₂O-N yr⁻¹: almost 500,000 metric tons CO₂-eq yr⁻¹ total. This is the first comprehensive dataset of CH₄ and N₂O concentrations and diffusive emissions in a very large lake. More measurements and monitoring are needed to determine whether increased eutrophication in the Great Lakes is tied to increased emissions of these powerful climate forcers in a possible positive feedback to climate warming.     

A novel method for tracking western Lake Erie Microcystis blooms, 2002–2011

After a period of improvement from the late 1970s through the mid 1990s, western Lake Erie has returned to eutrophic conditions and harmful algal blooms now dominated by the cyanobacterium Microcystis aeruginosa. The detection of long-term trends in Microcystis blooms would benefit from a convenient method for quantifying Microcystis using archived plankton tows. From 2002 to 2011, summer Microcystis blooms in western Lake Erie were quantified using plankton tows (N = 649). A flotation separation method was devised to quantify Microcystis biovolume in the tows, and the method was tested against whole water cell counts. Floating Microcystis biovolume (mL) in preserved tows was highly correlated with total Microcystis cells (R² = 0.84) and biomass (R² = 0.95) in whole water samples. We found that Microcystis annual biovolume was highly variable among years; the 2011 bloom was 2.4 times greater than the second largest bloom (2008) and 29.0 times greater than the smallest bloom (2002). Advantages of the method include use of archived samples, high sampling volume, and low effort and expense. Limitations include specificity for cyanobacterial blooms dominated by large Microcystis colonies and the need for site-specific validation. This study indicates that the flotation method can be used to rapidly assess past and present Microcystis in western Lake Erie and that there was high variability in the timing, duration, and intensity of the annual Microcystis blooms over a 10-year period. The data made possible by this method will aid further investigations into the underlying causal factors of blooms.     

Algal bloom transport in Lake Erie using remote sensing and hydrodynamic modelling: Sensitivity to buoyancy velocity and initial vertical distribution

In this study, we simulate three-dimensional transport of algal blooms in Lake Erie using a combination of remote sensing and hydrodynamic modelling. The remote sensing algorithms use data from the Sentinel-3 OLCI satellite sensor to derive chlorophyll-a concentration from cyanobacteria blooms in Lake Erie. The derived chlorophyll-a concentration initializes an algal bloom transport model driven by the lake component of the Water Cycle Prediction System for the Great Lakes, a system of coupled atmosphere-lake-hydrological models operated out of Environment and Climate Change Canada. The bloom is modelled as Microcystis aeruginosa, a buoyant species that is often dominant in harmful algal blooms in western Lake Erie. Short-term (a few days) predictions of algal bloom transport from July 27 to October 8, 2017 are modelled in both Eulerian and Lagrangian frameworks. The Eulerian framework is used to evaluate the sensitivity of model results to the initial vertical distribution of the bloom. In this work, the Lagrangian framework is limited to two-dimensional surface confined particles. We use several error metrics to evaluate model predictions. We find that results are sensitive to the buoyancy velocity for cases where the bloom was initially distributed over a large portion of the water column. An initial vertical distribution selected from modelled chlorophyll-a half depth shows the highest accuracy for the entire range of buoyancy velocities tested. We also find that the Pierce skill score is difficult to interpret, particularly in cases where bloom intensity is greatly overpredicted by the model.     

Twenty five years of changes in Dreissena spp. populations in Lake Erie

Lake Erie has the longest history of colonization by both Dreissena polymorpha and Dreissena rostriformis bugensis in North America and is therefore optimal for the study of long-term dynamics of dreissenid species. In addition, the morphometry of Lake Erie basins varies dramatically from the shallow western to the deep eastern basin, making this waterbody a convenient model to investigate patterns of Dreissena distribution, as well as interspecies interactions among dreissenids. We compare our data on the distribution, density and wet biomass of both dreissenid species in Lake Erie collected in 2009 and 2011–2012 with previous data. We found that Dreissena spp. distribution in Lake Erie varied depending on the time since the initial invasion, collection depth, and lake basin. In 2009–2012, zebra mussels were smaller than in 1992 and were consistently smaller than quagga mussels. During 2009–2012, quagga mussels were found at all depths and in all basins, while zebra mussels were common in the western basin only, and in the central and eastern basins were limited to shallow depths, resulting in an almost complete replacement of D. polymorpha with D. rostriformis bugensis. In the shallowest western basin of Lake Erie, zebra mussels represented > 30% of the combined dreissenid density even after more than 20 years of coexistence, providing strong evidence that, even in lakes as large as Lake Erie (or at least its western basin), D. polymorpha may sustain a significant presence for decades without being displaced by quagga mussels.     

Changes in mid-summer water temperature and clarity across the Great Lakes between 1968 and 2002

In recent decades, three important events have likely played a role in changing the water temperature and clarity of the Laurentian Great Lakes: 1) warmer climate, 2) reduced phosphorus loading, and 3) invasion by European Dreissenid mussels. This paper compiled environmental data from government agencies monitoring the middle and lower portions of the Great Lakes basin (lakes Huron, Erie and Ontario) to document changes in aquatic environments between 1968 and 2002. Over this 34-year period, mean annual air temperature increased at an average rate of 0.037 °C/y, resulting in a 1.3 °C increase. Surface water temperature during August has been rising at annual rates of 0.084 °C (Lake Huron) and 0.048 °C (Lake Ontario) resulting in increases of 2.9 °C and 1.6 °C, respectively. In Lake Erie, the trend was also positive, but it was smaller and not significant. Water clarity, measured here by August Secchi depth, increased in all lakes. Secchi depth increased 1.7 m in Lake Huron, 3.1 m in Lake Ontario and 2.4 m in Lake Erie. Prior to the invasion of Dreissenid mussels, increases in Secchi depth were significant (p < 0.05) in lakes Erie and Ontario, suggesting that phosphorus abatement aided water clarity. After Dreissenid mussel invasion, significant increases in Secchi depth were detected in lakes Ontario and Huron.     

Otolith microchemistry shows natal philopatry of walleye in western Lake Erie

Natal philopatry is important to the structure of fish populations because it can lead to local adaptations among component stocks of a mixed population, reducing the risk of recruitment failure. By contrast, straying between component stocks may bolster declining populations or allow for colonization of new habitat. To examine rates of natal philopatry and straying among western Lake Erie walleye (Sander vitreus) stocks, we used the concentration of strontium [Sr] in otolith cores to determine the natal origin of adults captured at three major spawning sites: the Sandusky (n = 62) and Maumee (n = 55) rivers and the Ohio reef complex (n = 50) during the 2012–2013 spawning seasons. Mean otolith core [Sr] was consistently and significantly higher for individuals captured in the Sandusky River than for those captured in the Maumee River or Ohio reef complex. Although logistic regression indicates that no individuals with a Maumee River or Ohio reef complex origin were captured in the Sandusky River, quadratic discriminant analysis suggests low rates of straying of fish between the Maumee and Sandusky rivers. Our results suggest little straying and high rates of natal philopatry in the Sandusky River walleye stock. Similar rates of natal philopatry may also exist across western Lake Erie walleye stocks, demonstrating a need for stock-specific management.     

The effect of mayfly (Hexagenia spp.) burrowing activity on sediment oxygen demand in western Lake Erie

Previous studies support the hypothesis that large numbers of infaunal burrow-irrigating organisms in the western basin of Lake Erie may increase significantly the sediment oxygen demand, thus enhancing the rate of hypolimnetic oxygen depletion. We conducted laboratory experiments to quantify burrow oxygen dynamics and increased oxygen demand resulting from burrow irrigation using two different year classes of Hexagenia spp. nymphs from western Lake Erie during summer, 2006. Using oxygen microelectrodes and hot film anemometry, we simultaneously determined oxygen concentrations and burrow water flow velocities. Burrow oxygen depletion rates ranged from 21.7 mg/nymph/mo for 15 mm nymphs at 23 °C to 240.7 mg/nymph/mo for 23 mm nymphs at 13 °C. Sealed microcosm experiments demonstrated that mayflies increase the rate of oxygen depletion by 2–5 times that of controls, depending on size of nymph and water temperature, with colder waters having greater impact. At natural population densities, nymph pumping activity increased total sediment oxygen demand 0.3–2.5 times compared to sediments with no mayflies and accounted for 22–71% of the total sediment oxygen demand. Extrapolating laboratory results to the natural system suggest that Hexagenia spp. populations may exert a significant control on oxygen depletion during intermittent stratification. This finding may help explain some of the fluctuations in Hexagenia spp. population densities in western Lake Erie and suggests that mayflies, by causing their own population collapse irrespective of other environmental conditions, may need longer term averages when used as a bio-indicator of the success of pollution-abatement programs in western Lake Erie and possibly throughout the Great Lakes.