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.     

Relative importance of macrophyte community versus water quality variables for predicting fish assemblages in coastal wetlands of the Laurentian Great Lakes

Fish have been shown to be sensitive indicators of environmental quality in Great Lakes coastal wetlands. Fish composition also reflects aquatic macrophyte communities, which provide them with critical habitat. Although investigators have shown that the relationship between water quality and fish community structure can be used to indicate wetland health, we speculate that this relationship is a result of the stronger, more direct relationship between water quality and macrophytes, together with the ensuing interconnection between macrophyte and fish assemblages. In this study, we use data collected from 115 Great Lakes coastal marshes to test the hypothesis that plants are better predictors of fish species composition than is water quality. First we use canonical correspondence analysis (CCA) to conduct an ordination of the fish community constrained by water quality parameters. We then use co-correspondence analysis (COCA) to conduct a direct ordination of the fish community with the plant community data. By comparing the statistic ‘percent fit,’ which refers to the cumulative percentage variance of the species data, we show that plants are consistently better predictors of the fish community than are water quality variables in three separate trials: all wetlands in the Great Lakes basin (whole: 21.2% vs 14.0%; n = 60), all wetlands in Lakes Huron and Superior (Upper: 20.3% vs 18.8%; n =  32), and all wetlands in Georgian Bay and the North Channel (Georgian Bay: 18% vs 17%; n =  70). This is the largest study to directly examine plant–fish interactions in wetlands of the Great Lakes basin.     

An assessment of water quality in two Great Lakes connecting channels

Compared to the Great Lakes, their connecting channels are relatively understudied and infrequently assessed. To address this gap, we conducted a spatially-explicit water quality assessment of two connecting channels, the St. Marys River and the Lake Huron-Lake Erie Corridor (HEC) in 2014–2016. We compared the condition of the channels to each other and to the up- and downriver Great Lakes with data from an assessment of the Great Lakes nearshore. In the absence of channel-specific thresholds, we assessed the condition of the area of each channel as good, fair, or poor by applying the most protective water quality thresholds for the downriver lake. Condition of the St. Marys River was rated mostly fair for total phosphorus (TP, 56% of the area) and mostly good (61% of the area) for chlorophyll a. Area-weighted mean concentrations of these parameters were intermediate to Lake Superior and Lake Huron. Unlike Lake Superior and Lake Huron, a large proportion (97%) of the area of the St. Marys River was in poor condition for water clarity based on Secchi depth. Area-weighted mean concentrations of TP and chlorophyll a in the HEC were more like Lake Huron than Lake Erie. For these indicators, most of the area of the HEC was rated good (81% and 86%, respectively). Interpretation of assessment results is complicated by variation in thresholds among and within lakes. Appropriate thresholds should align with assessment objectives and in the case of connecting channels be at least as protective as thresholds for the downriver lake.     

Landscape-scale modeling of water quality in Lake Superior and Lake Michigan watersheds: How useful are forest-based indicators?

The Great Lakes watersheds have an important influence on the water quality of the nearshore environment, therefore, watershed characteristics can be used to predict what will be observed in the streams. We used novel landscape information describing the forest cover change, along with forest census data and established land cover data to predict total phosphorus and turbidity in Great Lakes streams. In Lake Superior, we modeled increased phosphorus as a function of the increase in the proportion of persisting forest, forest disturbed during 2000–2009, and agricultural land, and we modeled increased turbidity as a function of the increase in the proportion of persisting forest, forest disturbed during 2000–2009, agricultural land, and urban land. In Lake Michigan, we modeled increased phosphorus as a function of ecoregion, decrease in the proportion of forest disturbed during 1984–1999 and watershed storage, and increase in the proportion of urban land, and we modeled increased turbidity as a function of ecoregion, increase in the proportion of forest disturbed during 2000–2009, and decrease in the proportion softwood forest. We used these relationships to identify priority areas for restoration in the Lake Superior basin in the southwestern watersheds, and in west central and southwest watersheds of the Lake Michigan basin. We then used the models to estimate water quality in watersheds without observed instream data to prioritize those areas for management. Prioritizing watersheds will aid effective management of the Great Lakes watershed and result in efficient use of restoration funds, which will lead to improved nearshore water quality.     

Life after Dreissena: The decline of exotic suspension feeder may have significant impacts on lake ecosystems

It is well documented that the introduction of dreissenid bivalves in eutrophic lakes is usually associated with decreases in turbidity and total phosphorus concentrations in the water column, concomitant increases in water clarity, as well as other physical changes to habitat that may have cascading effects on other species in the invaded waterbody. In contrast, there is a paucity of data on the ecological ramifications of the elimination or decline of dreissenids due to pollution, bottom hypoxia, or other mechanisms. Using data collected by the U.S. Environmental Protection Agency Great Lakes National Program Office's Long-Term Biology and Water Quality Monitoring Programs, we analyzed the impacts of the hypoxia-induced declines in Dreissena densities in the central basin of Lake Erie on major water chemistry and physical parameters. Our analysis revealed that the decline in Dreissena density in the central basin was concomitant with a decrease in spring dissolved silica concentrations and an increase in total phosphorus and near bottom turbidity not seen in the western or eastern basins. In contrast, opposite patterns in water quality were observed in the eastern basin which was characterized by a high and relatively stable Dreissena population. We are the first to report on observations suggesting that dreissenid-related shifts in water quality may be reversible by documenting that the sharp decline of Dreissena in the central basin of Lake Erie was concomitant with a shift from clear to turbid water.     

Using machine learning to model and predict water clarity in the Great Lakes

Over the last several decades, multiple environmental issues have led to dramatic changes in the water clarity of the Great Lakes. While many of the key factors are well-known and have direct anthropogenic origins, climatic variability and change can also impact water clarity at various temporal scales, but their influence is less often studied. Building upon a recent examination of the univariate relationships between synoptic-scale weather patterns and water clarity, this research utilizes nonlinear autoregressive models with exogenous input (NARX models) to explore the multivariate climate-to-water clarity relationship. Models trained on the observation period (1997–2016) are extrapolated back to 1979 to reconstruct a daily-scale historical water clarity dataset, and used in a reforecast mode to estimate real-time forecast skill. Of the 20 regions examined, models perform best in Lakes Michigan and Huron, especially in spring and summer. The NARX models perform better than a simple persistence model and a seasonal-trend model in nearly all regions, indicating that climate variability is a contributing factor to fluctuations in water clarity. Further, six of the 20 regions also show promise of useful forecasts to at least 1 week of lead-time, with three of those regions showing skill out to two months of lead time.     

Great Lakes coastal fish habitat classification and assessment

Basin-scale assessment of fish habitat in Great Lakes coastal ecosystems would increase our ability to prioritize fish habitat management and restoration actions. As a first step in this direction, we identified key habitat factors associated with highest probability of occurrence for several societally and ecologically important coastal fish species as well as community metrics, using data from the Great Lakes Aquatic Habitat Framework (GLAHF), Great Lakes Environmental Indicators (GLEI) and Coastal Wetland Monitoring Program (CWMP). Secondly, we assessed whether species-specific habitat was threatened by watershed-level anthropogenic stressors. In the southern Great Lakes, key habitat factors for determining presence/absence of several species of coastal fish were chlorophyll concentrations, turbidity, and wave height, whereas in the northern ecoprovince temperature was the major habitat driver for most of the species modeled. Habitat factors best explaining fish richness and diversity were bottom slope and chlorophyll a. These models could likely be further improved with addition of high-resolution submerged macrophyte complexity data which are currently unavailable at the basin-wide scale. Proportion of invasive species was correlated primarily with increasing maximum observed inorganic turbidity and chlorophyll a. We also demonstrate that preferred habitat for several coastal species and high-diversity areas overlap with areas of high watershed stress. Great Lakes coastal wetland fish are a large contributor to ecosystem services as well as commercial and recreational fishery harvest, and scalable basin-wide habitat models developed in this study may be useful for informing management actions targeting specific species or overall coastal fish biodiversity.     

Geostatistically Derived Great Lakes USLE Monthly Rainfall Erosivity Factors

The R factor, an index of rainfall erosivity in the universal soil loss equation (USLE), fundamentally governs water related soil loss from agricultural plots and is based on well studied empirical relations. Soil particles and adsorbed contaminants from agricultural runoff inevitably end up in water-courses and ultimately the Great Lakes system, disturbing natural habitat, reducing water clarity and quality. We here use over 22 years of records containing hourly precipitation recordings for 453 meteorological-recording sites in Ontario, southwestern Quebec, Michigan, Ohio, Pennsylvania, and New York to estimate the R factor surrounding the lower Laurentian Great Lakes. We generate annual and monthly R factor maps for the major growing season months using geostatistical interpolation. Our annual and seasonal maps can help in land use planning within the regions of intense agriculture surrounding Lakes Huron, Erie, and Ontario. Moving north of the Great Lakes, we find greater proportional errors on estimated R values because of low meteorological-recording site density. We find a strong northeast trend in decreasing erosivity of rainfall in the study area. The mean R value for 453 sites was 1,599.13 MJ mm⁻¹ ha⁻¹ yr⁻¹, with a standard deviation of 591.74 MJ mm⁻¹ ha⁻¹ yr⁻¹. Results are in general agreement with other published work but show some spatial differences due to climatic and physiographic variations across our study area.     

Trace element loads in the Great Lakes Basin: A reconnaissance

Water quality data for trace elements in the Great Lakes are relatively scarce, complicating the assessment of current trace element baselines and their distribution patterns. Here, we present concentration data for >40 major and trace elements in >100 samples from the Great Lakes connecting channels, surface waters, precipitation and select Canadian tributaries, to establish a high-level assessment of loading rates across the basin. Contrasting upstream-to-downstream trends were observed for the investigated trace elements, ranging from net-decreasing (>5-fold for e.g., Co, Tl, Y) to net-increasing surface water concentrations (>2-fold for e.g., Sb, U, As). Calculated loading rates reveal different, element-specific controls of runoff, connecting channel loads or precipitation on trace element occurrence. Lake-wide elemental mass-balances could be reasonably closed for conservative trace elements (e.g., Li, <53% residual) but not for others (e.g., rare earth elements with up to 5-fold discrepancies), reflective of general data scarcity and uncertainty in loading rates. In line with major water quality trends, spatial distribution patterns in Lakes Erie and Ontario display subtle near-shore to off-shore heterogeneity for a few trace elements (<1 order-of-magnitude for V or Se), but higher variability for trace elements with significant inputs derived from tributaries. This work provides important quantitative baseline data for trace elements in the Great Lakes that may help optimize surveillance and management strategies for the preservation of Great Lakes water quality.     

U.S. EPA Great Lakes National Program Office monitoring of the Laurentian Great Lakes: Insights from 40 years of data collection

The U.S. EPA Great Lakes National Program Office (GLNPO) implements long-term monitoring programs to assess Great Lakes ecosystem status and trends for many interrelated ecosystem components, including offshore water quality as well as offshore phytoplankton, zooplankton and benthos; chemical contaminants in air, sediments, and predator fish; hypoxia in Lake Erie's central basin; and coastal wetland health. These programs are conducted in fulfillment of Clean Water Act mandates and Great Lakes Water Quality Agreement commitments. This special issue presents findings from GLNPO's Great Lakes Biology Monitoring Program, Great Lakes Water Quality Monitoring Program, Lake Erie Dissolved Oxygen Monitoring Program, Integrated Atmospheric Deposition Network, Great Lakes Fish Monitoring and Surveillance Program, and Great Lakes Sediment Surveillance Program. These GLNPO programs have generated temporal and spatial datasets for all five Great Lakes that form the basis for assessment of the state of these lakes, including trends in nutrients, key biological indicators, and contaminants in air, sediments and fish. These datasets are used by researchers and managers across the Great Lakes basin for investigating physical, chemical and biological drivers of ongoing ecosystem changes; some of these analyses are presented in this special issue, along with discussion of new methods and approaches for monitoring.     

The 2017 African Great Lakes Conference: Conservation and development in a changing climate

In May 2017, the African Great Lakes community convened for a region-wide conference in Entebbe, Uganda. The African Great Lakes Conference (AGLC) focused on 6 regionally-important themes, and 300+ attendees presented over 100 talks and posters. The AGLC culminated in the adoption of a set of Conference Resolutions designed to direct the future of African Great Lakes conservation and management. As an Introduction to this Journal of Great Lakes Research special section on African Great Lakes, we report on the impetus for the African Great Lakes Conference as well as discuss three major advances and investments that were a direct result of conference resolutions adopted at the meeting. First, we present the AGLC Resolutions, a set of management issues and solutions developed at the conference. Second, we discuss the African Great Lakes Conference Fund, a conservation fund that has awarded $500,000 USD to launch four new initiatives. Finally, we describe African Great Lakes Inform, a knowledge management platform designed to promote collaboration in the region. The AGLC in general, and these three major conference outcomes specifically, provide a set of basic building blocks to advance partnerships, research and capacity in the African Great Lakes region.     

A brief history of the U.S. EPA Great Lakes National Program Office's water quality survey

The U.S. Environmental Protection Agency Great Lakes National Program Office (GLNPO) water quality survey (WQS) constitutes the longest-running, most extensive monitoring of water quality and the lower trophic level biota of the Laurentian Great Lakes, and has been instrumental in tracking shifts in nutrients and the lower food web over the past several decades. The initial impetus for regular monitoring of the Great Lakes was provided by the 1972 Great Lakes Water Quality Agreement (GLWQA) which asked the parties to develop monitoring and surveillance programs to ensure compliance with the goals of the agreement. The resulting monitoring plan, eventually known as the Great Lakes International Surveillance Plan (GLISP), envisioned a nine-year rotation of intensive surveys of the five lakes. A broadening of the scope of the GLWQA in 1978 and the completion of the first nine-year cycle of sampling, prompted reappraisals of the GLISP. During this pause, and using knowledge gained from GLISP, GLNPO initiated an annual WQS with the narrower focus of tracking water quality changes and plankton communities in the offshore waters of the lakes. Beginning in 1983 with lakes Erie, Huron, and Michigan, the WQS added Lake Ontario in 1986 and Lake Superior in 1992, evolving into its current form in which all five lakes are sampled twice a year. The WQS is unique in that all five lakes are sampled by one agency, using one vessel and one principal laboratory for each parameter group, and represents an invaluable resource for managing and understanding the 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).     

A systematic review of the literature on plastic pollution in the Laurentian Great Lakes and its effects on freshwater biota

Plastic pollution is ubiquitous in freshwater systems worldwide, and the Laurentian Great Lakes are no exception. We conducted a systematic review to synthesize the current state of the literature on plastic pollution, including macroplastics (>5 mm) and microplastics (<5 mm), in the Great Lakes. Thirty-four publications were used in our systematic review. We found ubiquitous contamination of microplastics in surface water, with maximum abundances exceeding those in ocean gyres. There are also high levels of plastic contamination reported across benthic sediments and shorelines of the Great Lakes. Citizen science data reveals macroplastic across Great Lakes shorelines, with more than three million pieces of plastic litter recorded over a span of three years. We completed a second systematic review of plastic pollution and its impact on freshwater ecosystems in general to inform how plastic in the Great Lakes may impact wildlife. Among studies published in the literature, we found 390 tested effects, 234 (60%) of which were detected and 156 (40%) of which were not; almost all of the freshwater effects (>98%) were tested on microplastics. Based on a subset of these papers, we found that the shape and size of a particle likely affects whether an effect is detected, e.g., more effects are detected for smaller particles. Finally, we identify gaps in scientific knowledge that need to be addressed and discuss how the state of the science can inform management strategies.     

Application of continuous turbidity sensors to supplement estimates of total phosphorus concentrations in the Grand River,Ontario, Canada

Accurate estimates of total phosphorus (TP) loadings to eastern Lake Erie are critical for developing load reduction targets and for determining if commitments are being met under the Great Lakes Water Quality Agreement, 2012 (GLWQA). Currently, loading calculations from Canadian priority tributaries are supported by year-round event-focused water quality sampling using automated samplers and laboratory water quality measurements. Here we evaluate the suitability of continuously-measured parameters, namely turbidity and flow, to supplement or enhance knowledge about TP concentrations in the Grand River, ON, by providing continuous data alongside event-focused sample measurements. A series of simple and multiple linear regression models were evaluated and compared with respect to their ability to predict TP water concentrations as a function of different combinations of explanatory variables. Explanatory variables included turbidity, flow, season and flow condition (i.e. hysteresis). The models that performed best explained 63–65% of the variation of TP which is comparable to surrogate model applications in the U. S and elsewhere. Additional model calibration work is needed due to gaps in turbidity data particularly during high flow events. We emphasize the need for continued automated, event-focused water quality sampling. However, provided that operational challenges are overcome, our results indicate that sensor-derived water quality parameters to predict TP concentrations is a promising technique that may supplement and improve nutrient loading estimates in the Grand River into the future and provides guidance for the utilization of this method in other tributaries.     

Large Lake Models—Uses,Abuses, and Future

Mathematical modeling has played and should continue to play an important role in Great Lakes management and scientific development. Great Lakes modeling is entering a phase of relative maturity in which expectations are more realistic than in the past. For example, it is now realized that the modeling process itself is valuable even if the resulting models are not immediately useful for management. The major thrust in the past has been water quality (eutrophication) modeling, but there has been a recent shift toward developing toxic substances models. Modelers and model users have been limited by a lack of knowledge of Great Lakes processes, limited data availability, and incomplete or improper validation. In the future, greater emphasis is needed on specifying prediction uncertainty and conducting proper model validation — including calibration, verification, and post-audits. Among the Great Lakes modeling activities likely to have the greatest payoff in the near future are (1) the development and refinement of toxic substances models, (2) post-auditing and improvement of eutrophication models, and (3) the adaption of models for use on personal computers to allow greater model utilization.     

Impacts of climate change on groundwater in the Great Lakes Basin: A review

Climate change has the potential to alter the physical and chemical properties of water in the Great Lakes Basin, in turn impacting ecological function. This study synthesizes existing research associated with the potential effects of a changing climate on the quality and quantity of groundwater in the Great Lakes Basin. It includes analyses of impacts on (1) recharge, (2) groundwater storage, (3) discharge and groundwater-surface water (GW-SW) interactions, (4) exacerbating future urban development impacts on groundwater, (5) groundwater quality, and (6) ecohydrology.Large spatial and temporal (i.e., seasonal) variability in groundwater response to climate change between regions is anticipated. Most studies combine field observations with modelling, but many have focused only on small/medium basins. At these small scales, groundwater systems are generally projected to be fairly resilient to climate change impacts. However, modelling studies of larger basins (e.g., Grand River, Saginaw Bay, Maumee River) predict an increase in groundwater storage. Uncertainty in model simulations, particularly from climate models that are used to force hydrological models, is a major challenge. There have been too few studies to date that investigate the interplay of climate change and groundwater quality in the Great Lakes Basin to draw conclusions about future groundwater quality and ecohydrology.A summary of methods, models, and technology is provided. Model uncertainty has become an increasingly important topic and is also discussed. The study concludes with a synthesis of the main science needs to understand groundwater impacts in order to adapt to a changing climate in the Great Lakes Basin.     

The Great Lakes Region and Bulk Water Exports

Abstract

The article provides an overview of the latest developments in the debate concerning the bulk water export of Great Lakes water. It examines the policy and legal dimensions of this new debate. The policy dimension focuses on the public attention and concern, in Canada, regarding bulk water removals from the Great Lakes basin. This concern has triggered the new Canadian federal legislation banning water exports from the region (Bill C-15). Is this a sign that the Canadian government now embraces a water conservation ethic? Is its position in line with the recent recommendations on the issue of the International Joint Commission (IJC), the joint body created by the United States and Canada to manage its shared waters? The attempt by investors to export water from the Great Lakes basin raises issues regarding Canada's obligations under international and regional trade agreements, most notably the General Agreement on Tariffs and Trade (GATT) and the North American Free Trade Agreement (NAFTA). The article examines the provisions of those two trade agreements in the context of the water export debate in Canada and concludes that increased clarity on Canada/US transboundary water issues is required.     

Great Lakes Cladophora in the 21st century: same algae—different ecosystem

Nuisance growth of the attached, green alga Cladophora was considered to have been abated by phosphorus management programs mandated under the Great Lakes Water Quality Agreement. The apparent resurgence of nuisance growth in Lakes Erie, Michigan and Ontario has been linked conceptually to ecosystem alterations engineered by invasive dreissenid mussels (Dreissena polymorpha and Dreissenabugensis). Here, we apply contemporary modeling tools and historical water quality data sets in quantifying the impact of long-term changes in phosphorus loading and dreissenid-mediated changes in water clarity on the distribution and production of Cladophora. It is concluded that reductions in phosphorus loading in the pre-dreissenid period achieved the desired effect, as model simulations were consistent with the biomass declines reported from the early 1970s to the early 1980s. These declines were, however, largely offset by dreissenid-driven changes in water clarity that extended the depth of colonization by Cladophora, increasing total production. We were not able to isolate and quantify the significance of dreissenid mediation of phosphorus cycling using the historical database. Phosphorus management remains the appropriate mechanism for reducing nuisance levels of Cladophora growth. The development of action plans will require an improved understanding of nearshore phosphorus dynamics such as might be obtained through regular monitoring of soluble reactive phosphorus levels, internal phosphorus content and Cladophora biomass in impacted nearshore regions of the Great Lakes.     

Requirements for Autonomous Underwater Vehicles (AUVs) for scientific data collection in the Laurentian Great Lakes: A questionnaire survey

Using mobile environmental monitoring can aid in gathering ecological data to meet fish community goals in the Great Lakes. One such approach is the use of large Autonomous Underwater Vehicles (AUVs) to gather data, or the potential use of AUV swarms, where multiple small AUVs work together with each having different data-gathering capabilities. To understand data needs that could be collected by mobile sensor networks to inform decision making, we surveyed Great Lakes professionals involved directly and indirectly in such decision making. Basic data that respondents chose as most important to collect were water temperature, dissolved oxygen, chlorophyll a, turbidity, and blue-green “algae”, which seems to align with variables affecting fish directly or indirectly (through identification of harmful algal blooms). Specialized data chosen as most important were mapping of habitat characteristics, sonar of groupings of fish, and images/video. The time of year to collect all data was chosen as all seasons by the majority of respondents, the frequency most chosen was once a season for mapping of habitat characteristics, once a week for sonar detection of groupings of fish, and once per day for images/video and water temperature. Results were very similar when respondents were asked where data should be collected in the Great Lakes (i.e., tributaries, nearshore areas, etc.) except respondents indicated that images/video should be collected most in fish spawning habitats. Understanding data important to inform decisions of resource professionals will help guide the design of mobile and stationary sensor networks in the Great Lakes.