Determining remote sensing spatial resolution requirements for the monitoring of harmful algal blooms in the Great Lakes

Harmful algal blooms (HABs) have become a major health and environmental concern in the Great Lakes. In 2014, severe HABs prompted the State of Ohio to request NASA Glenn Research Center (GRC) to assist with monitoring algal blooms in Lake Erie. The most notable species of HAB is Microcystis aeruginosa, a hepatotoxin producing cyanobacteria that is responsible for liver complications for humans and other fauna that come in contact with these blooms. NASA GRC conducts semiweekly flights in order to gather up-to-date imagery regarding the blooms' spatial extents and concentrations. Airborne hyperspectral imagery is collected using two hyperspectral imagers, HSI-2 and HSI-3. Hyperspectral imagery is necessary in order to conduct experiments on differentiation of algal bloom types based on their spectral reflectance. In this analysis, imagery from September 19, 2016 was utilized to study the subpixel variability within the footprint of arbitrary sized pixels using several analysis techniques. This particular data set is utilized because it represents a worst case scenario where there is significant potential for public health concern due to high concentrations of microcystin toxin found in the water on this day and the concurrent observational challenges to accurately measure the algal bloom concentration variability with a remote sensing system due to the blooms high spatial variability. It has been determined that the optimal spatial resolution to monitor algal blooms in the Great Lakes is at most 50 m, and for much lower error 25 m, thus allowing for greater ease in identifying high concentration blooms near the surface. This resolution provides the best sensitivity to high concentration areas that are of significant importance in regard to human health and ecological damage.     

SeaPRISM observations in the western basin of Lake Erie in the summer of 2016

In the summer of 2016, a robotic sun photometer called the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) Photometer Revision for Incident Surface Measurements (SeaPRISM), was deployed at a Coast Guard channel marker in western Lake Erie, measuring atmospheric properties and spectral water-leaving radiance. The instrument was deployed by the National Oceanic and Atmospheric Administration (NOAA) to support remote sensing validation and harmful algal bloom (HAB) satellite products. The Lake Erie SeaPRISM is also part of the international federated AERONET program maintained by the National Aeronautics and Space Administration (NASA), and more specifically is part of the AERONET Ocean Color (AERNOET-OC) network. The main purpose of this component of AERONET is specific to calibration/validation efforts for ocean color. The AERONET-OC network currently consists of 23 field radiometers at aquatic sites around the world. The Lake Erie site is the second freshwater lake location world-wide after the Palgrunden site in Sweden. During its operating period from mid-July to early September 2016, various environmental conditions were observed including a cyanobacteria bloom. Water-leaving radiance observations were generated on 43 out of 51 days, and varied by a factor of five. The variability in the above-water radiometry tracked that of in-water measurements made by a nearby buoy. During this brief operating window, satellite matchups were generated for several satellites. We highlight the first year's observations in relation to remote sensing validation and report on observations of cyanobacteria blooms from hourly to weekly time scales.     

Satellite monitoring of harmful algal blooms in the Western Basin of Lake Erie: A 20-year time-series

Blooms of harmful cyanobacteria (cyanoHABs) have occurred on an annual basis in western Lake Erie for more than a decade. Previously, we developed and validated an algorithm to map the extent of the submerged and surface scum components of cyanoHABs using MODIS ocean-color satellite data. The algorithm maps submerged cyanoHABs by identifying high chlorophyll concentrations (>18 mg/m³) combined with water temperature >20 °C, while cyanoHABs surface scums are mapped using near-infrared reflectance values. Here, we adapted this algorithm for the SeaWiFS sensor to map the annual areal extents of cyanoHABs in the Western Basin of Lake Erie for the 20-year period from 1998 to 2017. The resulting classified maps were validated by comparison with historical in situ measurements, exhibiting good agreement (81% accuracy). Trends in the annual mean and maximum total submerged and surface scum extents demonstrated significant positive increases from 1998 to 2017. There was also an apparent 76% increase in year-to-year variability of mean annual extent between the 1998–2010 and 2011–2017 periods. The 1998–2017 time-series was also compared with several different river discharge nutrient loading metrics to assess the ability to predict annual cyanoHAB extents. The prediction models displayed significant relationships between spring discharge and cyanoHAB area; however, substantial variance remained unexplained due in part to the presence of very large blooms occurring in 2013 and 2015. This new multi-sensor time-series and associated statistics extend the current understanding of the extent, location, duration, and temporal patterns of cyanoHABs in western Lake Erie.     

Mean Circulation in the Great Lakes

In this paper new maps are presented of mean circulation in the Great Lakes, employing long-term current observations from about 100 Great Lakes moorings during the 1960s to 1980s. Knowledge of the mean circulation in the Great Lakes is important for ecological and management issues because it provides an indication of transport pathways of nutrients and contaminants on longer time scales. Based on the availability of data, summer circulation patterns in all of the Great Lakes, winter circulation patterns in all of the Great Lakes except Lake Superior, and annual circulation patterns in Lakes Erie, Michigan, and Ontario were derived. Winter currents are generally stronger than summer currents, and, therefore, annual circulation closely resembles winter circulation. Circulation patterns tend to be cyclonic (counterclockwise) in the larger lakes (Lake Huron, Lake Michigan, and Lake Superior) with increased cyclonic circulation in winter. In the smaller lakes (Lake Erie and Lake Ontario), winter circulation is characterized by a two-gyre circulation pattern. Summer circulation in the smaller lakes is different; predominantly cyclonic in Lake Ontario and anticyclonic in Lake Erie.     

Quantification of the Lake Trophic Typologies of Naumann (Surface Quality) and Thienemann (Oxygen) with Special Reference to the Great Lakes

Separate trophic scales and indices are developed for two of the most significant symptoms of eutrophication: surface water quality and hypolimnetic dissolved oxygen depletion. The scales are made comparable by expressing them in dimensionless form with a lower bound of zero and a mesotrophic range from 5 to 10. In this way, the two symptoms can be compared and their relative importance judged. This is done for the Great Lakes with the result that for both scales Lakes Superior, Huron, and Michigan are classified as oligotrophic. However, while central and eastern Lake Erie and Lake Ontario are classified as mesotrophic in terms of surface water quality, they range from eutrophic (central Lake Erie) to oligotrophic (Lake Ontario) on the oxygen scale. This is because, although these lakes are similar in surface water quality, their hypolimnion thicknesses range from approximately 4 m for central Erie to 70 m for Lake Ontario. Because of its shallowness, western Lake Erie does not have a persistent oxygen problem. In terms of surface quality it is classified as eutrophic.We have attempted to relate the two scales by correlating surface primary production and areal depletion rate. The results indicate that for lakes of similar primary production, areal oxygen depletion is directly proportional to hypolimnion thickness.     

Unmanned aerial system based spectroradiometer for monitoring harmful algal blooms: A new paradigm in water quality monitoring

Water quality issues continue to impact recreational and resource use of waterways in the Great Lakes and across smaller inland water bodies in their watersheds. With the advancements in small unmanned aerial systems (sUAS) and in small sensor production, sUAS offer flexibility to overcome several of the shortcomings of satellite and airborne systems, and complement their measurements in this environment. In this study, we deployed two different low-cost, boat launchable sUAS configurations instrumented with Ocean Optics STS hyperspectral Vis-NIR spectroradiometers capable of making measurements over an approximately 2.5 km² area, below the cloud deck in the nearshore and open lake environment. Flights of these systems were conducted at ten locations over Lake Erie and the Maumee River. Measured spectra compared well with at-surface based Analytical Spectral Devices (ASD) Fieldspec measured spectra, and derived parameters were consistent with in-water FluoroProbe measured water quality parameters and field observations. Using flight data, we constructed transect maps of derived CI products which show the variability in algae abundance in open water. These systems provide high quality, low cost, very high spatial resolution (cm to m scale measurements) hyperspectral data in the nearshore environment, can be consistently flown at low altitude (minimizing atmospheric effects) below cloud cover and can be deployed on extremely short notice. With the continued advancement in sensor development, automated flight capabilities, and increased flight duration from vertical take off and landing (VTOL) platforms, water quality observation platforms such as these will soon be a common tool in resource manager's toolboxes.     

Spatial and temporal variability of inherent and apparent optical properties in western Lake Erie: Implications for water quality remote sensing

Lake Erie has experienced dramatic changes in water quality over the past several decades requiring extensive monitoring to assess effectiveness of adaptive management strategies. Remote sensing offers a unique potential to provide synoptic monitoring at daily time scales complementing in-situ sampling activities occurring in Lake Erie. Bio-optical remote sensing algorithms require knowledge about the inherent optical properties (IOPs) of the water for parameterization to produce robust water quality products. This study reports new IOP and apparent optical property (AOP) datasets for western Lake Erie that encapsulate the May–October period for 2015 and 2016 at weekly sampling intervals. Previously reported IOP and AOP observations have been temporally limited and have not assessed statistical differences between IOPs over spatial and temporal gradients. The objective of this study is to assess trends in IOPs over variable spatial and temporal scales. Large spatio-temporal variability in IOPs was observed between 2015 and 2016 likely due to the difference in the extent and duration of mid-summer cyanobacteria blooms. Differences in the seasonal trends of the specific phytoplankton absorption coefficient between 2015 and 2016 suggest differing algal assemblages between the years. Other IOP variables, including chromophoric, dissolved organic matter (CDOM) and beam attenuation spectral slopes, suggest variability is influenced by river discharge and sediment re-suspension. The datasets presented in this study show how these IOPs and AOPs change over a season and between years, and are useful in advancing the applicability and robustness of remote sensing methods to retrieve water quality information in western Lake Erie.     

The effect of Lake Erie water level variations on sediment resuspension

Variability in Lake Erie water levels results in variations of the fluid forces applied to the lake bed by free-surface gravity wind-waves. An increase in the bed stress may re-suspend sediment deposited years earlier. This study identifies areas of possible non-cohesive sediment mobilization in response to the forcing conditions and water levels present in Lake Erie. Observations from NOAA buoy 45005 were used to identify wave events generated by a variety of atmospheric forcing conditions. For each event, numerical predictions of significant wave height, wave period, and water level from the Great Lakes Forecasting System (GLFS) were used to characterize the wave event variability over the lake. The Shields parameter was estimated at each 2 km × 2 km grid cell with the local wave forcing as predicted by GLFS assuming an estimate of the wave-induced friction factor. In the Cleveland harbor region of the central basin, the Shields parameter was also estimated by assuming uniform wave conditions as observed by NOAA buoy 45005. The “contour of incipient motion” for both variable and uniform wave events was defined as the offshore contour where the Shields parameter exceeds the critical limit for motion. Comparisons with a radiometrically corrected image from Landsat-7 showed that the spatially varying wave events from GLFS were in qualitative agreement with the satellite observations. A sensitivity analysis of wave height, wave period, and grain size showed the contour of incipient motion to be the most sensitive to wave period. Calculations performed for record high and low water levels showed that the incipient motion of non-cohesive sediments in the relatively flat central basin to be the most sensitive to the historic hydrologic variability present in Lake Erie.     

Fungal community dynamics associated with harmful cyanobacterial blooms in two Great Lakes

Harmful algal blooms (HABs) impose major costs on aquatic ecosystems worldwide, including the Laurentian Great Lakes. Microbial consumers, including fungi, can have important interactions with bloom-forming algae and cyanobacteria, although relatively few studies have investigated the relationship between fungi and HABs. We examined changes in the aquatic fungal community coincident with the occurrence of large cyanobacterial blooms in two areas of the Great Lakes (western Lake Erie and Saginaw Bay, Lake Huron). We collected water samples over the course of bloom development, peak, and decline from 3 sites in western Lake Erie on 11 dates and 2 sites in Saginaw Bay on 4 dates. Single molecule sequencing (PacBio RS II) with two molecular markers (the internal transcribed spacer (ITS) of the rRNA locus using fungal-specific primers and the 18S rRNA with primers targeting early-diverging lineages of fungi) was used to estimate fungal community composition. Results indicate a diverse fungal community within the lakes, including several major fungal phyla. The Chytridiomycota were particularly well-represented (54.8% and 45.4% of ITS and 18S sequences, respectively), and we also found representation from both Cryptomycota and Aphelidiomycota, which are putatively obligate intracellular parasites. Further, we found associations between the fungal community (alpha diversity; community composition) and measures of bloom magnitude (chlorophyll a, phycocyanin, and microcystin concentrations) in western Lake Erie. Our results suggest potentially important spatial and temporal heterogeneity in the fungal community that motivates further research on functional importance of fungi in the Great Lakes and consequences for HABs and freshwater ecosystems more broadly.     

Trends in Water Clarity of the Lower Great Lakes from Remotely Sensed Aquatic Color

Satellite observations of aquatic colour enable environmental monitoring of the Great Lakes at spatial and temporal scales not obtainable through ground-based monitoring. By merging data from the Coastal Zone Color Scanner (CZCS) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), monthly binned images of water-leaving radiance over the Great Lakes have been produced for the periods 1979–1985 and 1998–2006. This time-series can be interpreted in terms of changes in water clarity, showing seasonal and inter-annual variability of bright-water episodes such as phytoplankton blooms, re-suspension of bottom sediments, and whiting events. Variations in Secchi disk depth over Lakes Erie and Ontario are predicted using empirical relationships from coincident measurements of water transparency and remotely-sensed water-leaving radiance. Satellite observations document the extent to which the water clarity of the lower Great Lakes has changed over the last three decades in response to significant events including the invasion of zebra mussels. Results confirm dramatic reductions in Lake Ontario turbidity in the years following mussel colonization, with a doubling of estimated Secchi depths. Evidence confirms a reduction in the frequency/intensity of whiting events in agreement with suggestions of the role of calcium uptake by mussels on lake water clarity. Increased spring-time water clarity in the eastern basin of Lake Erie also corroborates previous observations in the region. Despite historical reports of localised increases in transparency in the western basin immediately following the mussel invasion, image analysis shows a significant increase in turbidity between the two study periods, in agreement with more recent reports of longer term trends in water clarity. Through its capacity to provide regular and readily interpretable synoptic views of regions undergoing significant environmental change, this work illustrates the value of remotely sensing water colour to water clarity monitoring in the lower Great Lakes.     

Widespread prevalence of hypoxia and the classification of hypoxic conditions in the Laurentian Great Lakes

Aquatic hypoxia within the Laurentian Great Lakes has contributed to various adverse ecological consequences and stimulated research interest in recent decades. An analysis of published peer-reviewed journal articles from 2000 to 2020 demonstrates an increasing trend of studies related to hypoxia in the Laurentian Great Lakes. However, the majority of these studies (78%) focus on Lake Erie and in particular the well-documented hypolimnetic hypoxic conditions that develop in the central basin of Lake Erie. This hypoxic zone is relatively large (up to 1.5 million ha), has substantial ecological effects, and motivates monitoring programs and water quality improvement initiatives. Nonetheless, the hypoxic zone in the central basin of Lake Erie is only one of over twenty documented hypoxic zones in the Laurentian Great Lakes. Moreover, hypoxic conditions in the Great Lakes are quite diverse. Here, we define and characterize a four-fold classification of Great Lakes hypoxic conditions: 1) hypolimnetic hypoxia, 2) over-winter hypoxia, 3) diel hypoxia, and 4) episodic hypoxia. We suggest that Great Lakes research and monitoring programs should seek to more broadly document hypoxic conditions and develop models to predict the temporal and spatial occurrence of hypoxia. Such efforts are particularly timely as future climatic conditions contributing to warmer temperatures, longer and more intense stratified periods, increased spring nutrient loading and more variable allocthonous inputs are expected to exacerbate three of the four hypoxic conditions described for the Great Lakes (hypolimnetic, diel, and episodic hypoxia).     

Status of the major aquaculture carps of China in the Laurentian Great Lakes Basin

There is concern of economic and environmental damage occuring if any of the four major aquacultured carp species of China, black carp Mylopharyngodon piceus, bighead carp Hypophthalmichthys nobilis, silver carp H. molitrix, or grass carp Ctenopharyngodon idella, were to establish in the Laurentian Great Lakes. All four are reproducing in the Mississippi River Basin. We review the status of these fishes in relation to the Great Lakes and their proximity to pathways into the Great Lakes, based on captures and collections of eggs and larvae. No black carp have been captured in the Great Lakes Basin. One silver carp and one bighead carp were captured within the Chicago Area Waterway System, on the Great Lakes side of electric barriers designed to keep carp from entering the Great Lakes from the greater Mississippi River Basin. Three bighead carp were captured in Lake Erie, none later than the year 2000. By December 2019, at least 650 grass carps had been captured in the Great Lakes Basin, most in western Lake Erie, but none in Lake Superior. Grass carp reproduction has been documented in the Sandusky and Maumee rivers in Ohio, tributaries of Lake Erie. We also discuss environmental DNA (eDNA) results as an early detection and monitoring tool for bighead and silver carps. Detection of eDNA does not necessarily indicate presence of live fish, but bigheaded carp eDNA has been detected on the Great Lakes side of the barriers and in a small proportion of samples from the western basin of Lake Erie.     

Spatial-temporal variability of in situ cyanobacteria vertical structure in Western Lake Erie: Implications for remote sensing observations

Remote sensing has provided expanded temporal and spatial range to the study of harmful algal blooms (cyanoHABs) in western Lake Erie, allowing for a greater understanding of bloom dynamics than is possible through in situ sampling. However, satellites are limited in their ability to specifically target cyanobacteria and can only observe the water within the first optical depth. This limits the ability of remote sensing to make conclusions about full water column cyanoHAB biomass if cyanobacteria are vertically stratified. FluoroProbe data were collected at nine stations across western Lake Erie in 2015 and 2016 and analyzed to characterize spatio-temporal variability in cyanobacteria vertical structure. Cyanobacteria were generally homogenously distributed during the growing season except under certain conditions. As water depth increased and high surface layer concentrations were observed, cyanobacteria were found to be more vertically stratified and the assumption of homogeneity was less supported. Cyanobacteria vertical distribution was related to wind speed and wave height, with increased stratification at low wind speeds (<4.9 m/s) and wave heights (<0.27 m). Once wind speed and wave height exceeded these thresholds the assumption of vertically uniform cyanobacteria populations was justified. These findings suggest that remote sensing can provide adequate estimates of water column cyanoHAB biomass in most conditions; however, the incorporation of bathymetry and environmental conditions could lead to improved biomass estimates. Additionally, cyanobacteria contributions to total chlorophyll-a were shown to change throughout the season and across depth, suggesting the need for remote sensing algorithms to specifically identify cyanobacteria.     

Associations between Breeding Marsh Bird Abundances and Great Lakes Hydrology

We used Great Lakes hydrologic data and bird monitoring data from the Great Lakes Marsh Monitoring Program from 1995–2002 to: 1) evaluate trends and patterns of annual change in May-July water levels for Lakes Ontario, Erie, and Huron-Michigan, 2) report on trends of relative abundance for birds breeding in Great Lakes coastal marshes, and 3) correlate basin-wide and lake-specific annual indices of bird abundance with Great Lakes water levels. From 1995–2002, average May, June, and July water levels in all lake basins showed some annual variation, but Lakes Erie and Huron-Michigan had identical annual fluctuation patterns and general water level declines. No trend was observed in Lake Ontario water levels over this period. Abundance for five of seven marsh birds in Lake Ontario wetlands showed no temporal trends, whereas abundance of black tern (Chlidonias niger) declined and that of swamp sparrow (Melospiza georgiana) increased from 1995–2002. In contrast, abundances of American coot (Fulica americana), black tern, common moorhen (Gallinula chloropus), least bittern (Ixobrychus exilis), marsh wren (Cistorthorus palustris), pied-billed grebe (Podilymbus podiceps), sora (Porzana carolina), swamp sparrow, and Virginia rail (Rallus limicola) declined within marshes at Lakes Erie and Huron/Michigan from 1995–2002. Annual abundances of several birds we examined showed positive correlations with annual lake level changes in non-regulated Lakes Erie and Huron/Michigan, whereas most birds we examined in Lake Ontario coastal wetlands were not correlated with suppressed water level changes of this lake. Overall, our results suggest that long-term changes and annual water level fluctuations are important abiotic factors affecting abundance of some marsh-dependent birds in Great Lakes coastal marshes. For this reason, wetland bird population monitoring initiatives should consider using methods in sampling protocols, or during data analyses, to account for temporal and spatial components of hydrologic variability that affect wetlands and their avifauna.     

Trends in Total Phosphorus in Canadian Near–Shore Waters of the Laurentian Great Lakes: 1976–1999

Beginning as early as 1976 at many locations, total phosphorus concentrations (TP) were measured weekly in samples collected year-round in the intake water of 18 municipal water treatment plants in Canadian (Ontario) waters of the Laurentian Great Lakes. No consistent long-term trends were evident at two north-shore Lake Superior sampling locations, but there were significant long-term declines in TP measured at all three Lake Huron locations; however, concentrations there have remained relatively constant during the past decade. Declines in TP averaging about 1 μg/L/yr during 1976 to 1990 were prevalent at lower Great Lakes sampling locations and by the early 1990s TP had declined to 15–25 μg/L in Lake Erie and 10–20 μg/L in Lake Ontario. Declines generally levelled out in Lake Ontario after 1990, but TP increased substantially at some Lake Erie locations in the late 1990s. Recent (1996 to 1999) total phosphorus concentrations in north-shore Lake Erie locations in the range of 20 to 30 μg/L were 2 to 3 times higher than at Lake Ontario near-shore locations in the 8 to 11 μg/L range. Rates of decline of TP were generally highest for the March–April period (−1.88, −1.61, and −1.34 μg/L/yr in Lakes Ontario, Erie, and Huron, respectively for 1976 to 1990). The March–April Lake Ontario near-shore rate of TP decline was nearly twice as high as that reported previously for off-shore Lake Ontario (attributed to proximity to P loading sources and to lower net sedimentation losses of P in the near-shore environment). There were substantial declines in chlorophyll-to-TP ratios and in the slopes and Y-intercepts of chlorophyll-TP regressions for both Lake Erie and Lake Ontario following the establishment of dreissenid mussels.     

Brachionus leydigii (Monogononta: Ploima) reported from the western basin of Lake Erie

Several species of non-indigenous planktonic invertebrates have historically been introduced to the Laurentian Great Lakes. Previous introductions of non-indigenous planktonic invertebrates to the Great Lakes have been crustacean zooplankton, specifically Cladocera and Copepoda. This report documents the first known occurrence of Brachionus leydigii var. tridentatus (Zernov, 1901) in Lake Erie and possibly the first detection of a non-indigenous rotifer species in the Laurentian Great Lakes. The specimen was collected from a U.S. EPA monitoring station in the western basin of Lake Erie on April 4, 2016.     

Retrieval of ice/water observations from synthetic aperture radar imagery for use in lake ice data assimilation

High-resolution lake ice/water observations retrieved from satellite imagery through efficient, automated methods can provide critical information to lake ice forecasting systems. Synthetic aperture radar (SAR) data is well-suited to this purpose due to its high spatial resolution (approximately 50 m). With recent increases in the volume of SAR data available, the development of automated retrieval methods for these data is a priority for operational centres. However, automated retrieval of ice/water data from SAR imagery is difficult, due to ambiguity in ice and open water signatures, both in terms of image tone and in terms of parameterized texture features extracted from these images. Convolutional neural networks (CNNs) can learn features from imagery in an automated manner, and have been found effective in previous studies on sea ice concentration estimation from SAR. In this study the use of CNNs to retrieve ice/water observations from dual-polarized SAR imagery of two of the Laurentian Great Lakes, Lake Erie and Lake Ontario, is investigated. For data assimilation, it is crucial that the retrieved observations are of high quality. To this end, quality control measures based on the uncertainty of the CNN output to eliminate incorrect retrievals are discussed and demonstrated. The quality control measures are found to be effective in both dual-polarized and single-polarized retrievals. The ability of the CNN to downscale the coarse resolution training labels is demonstrated qualitatively.     

Origins of Rainbow Smelt in Lake Ontario

The first rainbow smelt (Osmerus mordax) to enter Lake Ontario were probably migrants from an anadromous strain introduced into New York's Finger Lakes. Since the upper Great Lakes were originally stocked with a landlocked strain from Green Lake, Maine, subsequent migration to Lake Ontario from Lake Erie makes Lake Ontario unique among the Great Lakes in probably having received introductions from two distinct populations.     

Spatial Structure and the Estimation of Zooplankton Biomass in Lake Erie

Data collected by an optical plankton counter were analyzed to quantify the horizontal spatial patterns of zooplankton biomass in Lake Erie during 1994. During spring and late summer, an optical plankton counter was towed along a total of 11 transects, ranging from 26 to 67 km in length, distributed among the three major basins of the lake. A general model of spatial variation was used to identify large-scale trends, cyclic components at intermediate scales, and small-scale autocorrelation. Significant trends in biomass were found along all transects, while significant spatial autocorrelation underlying these trends was present in all but one case. The observed spatial autocorrelation was then removed, and standard statistical methods were used to estimate mean biomass and confidence limits. In most cases, the larger-scale spatial trends remained after removing autocorrelation. Regression methods were therefore used to estimate mean biomass in the presence of these trends. Relatively little overlap in confidence bands of the regression estimates were found from different regions of the lake. Mean biomass estimates for the entire lake from two seasons, when spatial trends and autocorrelation were ignored, fell outside the 95% confidence limits of estimates that did account for these spatial structures more than 50% of time. The relatively large change in biomass within and among many transects show that spatial variability of zooplankton biomass should be incorporated in future zooplankton studies in Lake Erie and the other Great Lakes.