The past is a key to the future: Lessons paleoecological data can provide for management of the African Great Lakes

Rapid ecological changes in the African Great Lakes (AGL) present lake managers with extraordinary challenges to understand the changes' underlying causes and forecast what they portend for the future. Monitoring and experimental data from the AGL are essential but are limited in duration and continuity. The magnitude of change suggests that a centennial-millennial timescale perspective is needed to identify drivers of change and prepare for changes yet to come. In this review I propose that paleoecological and paleolimnological approaches can provide this perspective.AGL paleorecords have documented the impacts of excess sedimentation, external nutrient loading, and climate change, and can demonstrate the specific ecosystem responses associated with these various drivers. Paleorecords can help us understand how multiple stressors interact and in some cases can falsify specific cause-and-effect hypotheses when the putative causes can be shown to have occurred after the effect started.The number of useful AGL paleorecords is still quite small. Replication is needed to test if patterns seen and hypotheses inferred from single localities are robust for an entire lake, and to understand regional variability within and between lakes. Because many paleorecord methods are quite inexpensive it would be highly desirable if these approaches were incorporated into the routine tool kit of local AGL scientists working in tandem with fisheries and water-quality scientists. Training African lake scientists and conservation biologists to analyze paleorecords should be a high priority for AGL stakeholders interested in the long-term prognoses for the economic and biodiversity resources that they oversee.     

Forecasting impacts of climate change on Great Lakes surface water temperatures

Temperature influences the rates of many ecosystem processes. A number of recent studies have found evidence of systematic increases in Great Lakes surface water temperatures. Our study aims to construct empirical relationships between surface water temperatures and local air temperatures that can be used to estimate future water temperatures using future air temperatures generated by global climate models. Remotely sensed data were used to model lake-wide average surface water temperature patterns during the open-water period in Lakes Superior, Huron, Erie, and Ontario. Surface water temperatures typically exhibit linear warming through the spring, form a plateau in mid-summer and then exhibit linear cooling in fall. Lake-specific warming and cooling rates vary little from year to year while plateau values vary substantially across years. These findings were used to construct a set of lake-specific empirical models linking surface water temperatures to local air temperatures for the period 1995–2006. Hindcasted whole-lake water temperatures from these models compare favourably to independently collected offshore water temperatures for the period 1968–2002. Relationships linking offshore water temperatures to inshore water temperatures at specific sites are also described. Predictions of future climates generated by the Canadian Global Climate Model Version 2 (CGCM2) under two future greenhouse gas emission scenarios are used to scope future Great Lakes surface water temperatures: substantial increases are expected, along with increases in the duration of summer stratification.     

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.     

Building a research network to better understand climate governance in the Great Lakes

Climate-driven disturbances threaten the sustainability of coastal communities in the Great Lakes Basin. Because such disturbances are unpredictable, their magnitude, number and intensity are changing, and they occur at varying temporal and spatial scales. Consequently, communities struggle to respond in effective ways. The expected intensification of climate-driven disturbances will require that community capacity and governance structures match the spatial and temporal scales of these disturbances, as the most sustainable social and economic systems will be those that can respond at similar frequencies to key natural system drivers. The Climate Governance Variability in the Great Lakes Research Coordination Network (CGVG-RCN) was recently established to address questions about the relationship between climate-driven disturbances and community response. The objective of this short communication is to introduce the ideas behind the CGVG-RCN, outline its goals, and facilitate engagements and collaboration with social and natural scientists interested in social-ecological systems in the Great Lakes Basin.     

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.     

Cold and wet: Diatoms dominate the phytoplankton community during a year of anomalous weather in a Great Lakes estuary

As sentinels of climate change and other anthropogenic forces, freshwater lakes are experiencing ecosystem disruptions at every level of the food web, beginning with the phytoplankton, a highly responsive group of organisms. Most studies regarding the effects of climate change on phytoplankton focus on a potential scenario in which temperatures continuously increase and droughts intersperse heavy precipitation events. Like much of the conterminous United States in 2019, the Muskegon River watershed (Michigan, USA) experienced record-breaking rainfall accompanied by unusually cool temperatures, affording an opportunity to explore how an alternate potential climate scenario may affect phytoplankton. We conducted biweekly sampling of environmental variables and phytoplankton in Muskegon Lake, a Great Lakes Area of Concern that connects to Lake Michigan. We compared environmental variables in 2019 to the previous eight years using long-term data from the Muskegon Lake Observatory buoy, and annual monitoring excursions provided historical phytoplankton data. Under cold and wet conditions, diatoms were the single dominant division throughout the entire growth season – an unprecedented scenario in Muskegon Lake. In 10 of the 13 biweekly sampling days in 2019, diatoms comprised over 75% of the phytoplankton community in the lake by count, indicating that the spring diatom bloom persisted through the fall. Additionally, phytoplankton seasonal succession and abundance patterns typically seen in this lake were absent. In a world experiencing reduced predictability, increased variability, and regional climate anomalies, studying periods of extreme weather events may offer insight into how natural systems will be affected and respond under future climate scenarios.     

Evaluation of regional climate simulations over the Great Lakes region driven by three global data sets

The performance of regional climate simulations is evaluated for the Great Lakes region. Three 10-year (1990–1999) current-climate simulations are performed using the MM5 regional climate model (RCM) with 36-km horizontal resolution. The simulations employed identical configuration and physical parameterizations, but different lateral boundary conditions and sea-surface temperatures derived from the NCEP Global Reanalysis and output from the CCSM3 and GISS general circulation models (GCMs). The simulation results are compared to the North American Regional Reanalysis (NARR). The three RCM simulations appeared to be more accurate in winter and least accurate in summer, and more accurate aloft than near the surface. The reanalysis-constrained simulation adequately captured the spatial distribution and seasonal cycle of the observed surface-air temperature and precipitation, but it produced consistently across all seasons a cold bias that is generally larger over the lakes than over land and a wet bias due to an overestimation of non-convective precipitation. The simulated seasonal cycle of moisture–flux convergence over the region was in very good agreement with NARR. The two GCM-driven runs adequately simulated the spatial and seasonal variation of temperature, but overestimated cold-season precipitation and underestimated summer precipitation, reversing the observed annual precipitation cycle. The GISS-driven run failed to simulate the prevailing low-level flow and moisture convergence patterns. All three RCM simulations successfully captured the impact of the Great Lakes on the region's climate, especially on winter precipitation, a significant improvement over coarse-resolution GCM simulations over the region.     

Extreme water level rise across the upper Laurentian Great Lakes region: Citizen science documentation 2010–2020

As the global water balance accelerates in a warming climate, extreme fluctuations in the water levels of lakes and aquifers are anticipated, with biogeochemical, ecological and water supply consequences. However, it is unclear how site-specific factors, such as location, morphometry and hydrology, will modulate these impacts on regional spatial scales. Here, we report water level time series collected by citizen scientists for 15 diverse inland lakes in the upper Laurentian Great Lakes region from 2010 to 2020, and we compare these time series with those for the two largest Great Lakes, Lake Superior and Lake Michigan-Huron. Combined with historical data (1942–2010), the findings indicate that lakes spanning seven orders of magnitude in size (10^?2 to 10⁵ km²) all rebounded from record low to record high water levels during the recent decade. They suggest coherent water level oscillations among regional lakes (large and small) implying a common, near-decadal, climatic driver that may be changing.     

Reducing current and future risks: Using climate change scenarios to test an agricultural conservation framework

Evaluating the potential effects of changes in climate on conservation practices can help inform strategies to protect freshwater biodiversity that are robust, even as conditions change. Here we apply a climate change “test” to a framework for estimating the amount of agricultural conservation practices needed to achieve desired fish conservation outcomes for four watersheds in the Saginaw Bay region of Michigan, USA. We developed three climate scenarios from global climate model outputs (high emissions scenario, “2080s” timeframe) to provide insight on potential impacts of a climate driver that represents a key uncertainty for this management system, the amount and timing of spring and summer precipitation. These scenarios were used as inputs to agricultural watershed models, which produced water quality outputs that we compared to thresholds in fish biodiversity metrics at the subwatershed scale. Our results suggest that impacts of climate change on evaporation rates and other aspects of hydrology will shift the relative importance of key stressors for fish (i.e., sediment loadings vs. nutrient concentrations) across these different watersheds, highlighting the need to design resilient implementation plans and policies. Overall, we found that changes in climate are likely to increase the need for agricultural conservation practices, but that increasing the implementation rate above current levels will likely remain a good investment under current and future climate conditions.     

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.     

Impacts on biodiversity and species changes in the lower Great Lakes

The Great Lakes basin ecosystem evolved after the retreat of the last ice sheet, about 10 000 years ago. Today, the complex of species present in the Great Lakes and much of the visible landscape bears little resemblance to that found some 400 years ago. Rather, the effects of various aspects of human development have caused major changes in the natural biodiversity. Lessons learned in the lower Great Lakes are applicable to many lakes around the world that have undergone agricultural, industrial and urban development in their drainage basins and have become managed, artificial ecosystems.     

Predicted Atrazine Concentrations in the Great Lakes: Implications for Biological Effects

Atrazine is an herbicide used extensively throughout the Midwest corn belt, including the agricultural regions within the Great Lakes basin watershed. Measurements of atrazine concentrations in the Great Lakes are few, however, so knowledge of its current concentrations, persistence, and trends in this ecosystem is limited. A dynamic annual time step model was used to predict atrazine concentrations over time in the Great Lakes based on varied atrazine loading rates to the lakes (“most-likely” and “high” loading conditions). Four degradation scenarios were evaluated: no degradation, and atrazine degradation with half-lives of 2 years, 5 years, and 10 years. Predicted steady-state concentrations for all of the scenarios and all the Great Lakes ranged from 0.0024 to 0.88 μg/L. The number of years until steady-state conditions were achieved ranged from 4 to over 400 years. The most-likely loading rate and two-year half-life scenario had the lowest concentrations (0.0024 to 0.13 μg/L) and the fewest years (4 to 13 years) to achieve steady-state conditions. Available monitored atrazine concentrations in the Great Lakes are very similar to the most-likely loading rate and 2-year half-life scenario predicted values. Monitored and predicted concentrations in the Great Lakes indicate atrazine does not currently pose a toxicological risk to humans or aquatic organisms, and under current and expected lower loading rates should remain well below criteria values.     

Climate change projections of temperature and precipitation for the great lakes basin using the PRECIS regional climate model

The Great Lakes Basin plays an important role in the economy and society of the United States and Canada, and climate change in this region may affect many sectors. In this study, six GCM simulations were downscaled to resolve the Great Lakes using a regional climate model (RCM) with 25 km × 25 km resolution. This model was used to project changes in temperature and precipitation during the mid-century (2040–2069) and late-century (2070–2099) over the Great Lakes basin region with reference to a baseline of 1980–2009. The whole-basin annual mean temperature is projected to increase 2.1 °C to 4.0 °C above the baseline during the mid-century, and 3.3 °C to 6.0 °C during the late-century. Summer temperatures in the southern portion of the basin are projected to increase more than the temperatures in the northern portion of the basin; whereas winter temperatures are projected to increase more in the north than in the south. Estimates of the whole-basin annual precipitation with respect to the baseline vary from −3.0% to 16.5% during the mid-century and −2.9% to 21.6% during the late-century, respectively. Future summer precipitation in southwestern areas of this region is expected to decrease by 20%–30% compared to the baseline, but winter precipitation (mostly snow) is expected to increase by 11.6% and 15.4% during the mid-century and late-century. This study highlights the effects of the large expanses of water (such as the Great Lakes) on regional climate projections and the associated uncertainties of climate change.     

Analysis of changes in the Great Lakes hydro-climatic variables

A study of changes in hydro-climatology of the Great Lakes was performed incorporating the nonparametric Mann–Kendall trend detection test and a recently developed Bayesian multiple change point detection model. The Component Net Basin Supply (C-NBS) and its components (runoff, precipitation, evaporation) as well as water levels of Great Lakes were analyzed for gradual (i.e. trend type) and abrupt (i.e. shift type) nonstationary behaviors at seasonal and annual scales. It was found that the C-NBS experienced significant upward trends only in the lower Great Lakes (Erie, Ontario) during the summer portion of the year. At an annual scale upward trends were observed only in Lake Ontario. Change point analysis suggested an upward shift in Great Lakes C-NBS in the late 1960s and early 1970s. A combination of gradual and abrupt change analysis of Great Lakes water levels indicated a common upward shift along with a change in trend direction around the early 1970s. It was also found that precipitation and runoff are on a plateau and in some cases on a decreasing course following an increasing trend in the early twentieth century. Results obtained from this study show that the hydro-climatology of Great Lakes is characterized by nonstationary behavior. Changes in this behavior have caused the Great Lakes water levels to decrease during the last few decades. This study provides valuable insights into the nature of the nonstationary behavior of hydro-climatic variables of Great Lakes and contributes useful information to the future water management planning.     

Initial insights into the development and implementation of a citizen-science drone-based coastal change monitoring program in the Great Lakes region

High-resolution spatio-temporal data are needed to improve coastal management programs, particularly along the Great Lakes where lake level fluctuations pose challenges to coastal decision-making and planning. Unfortunately, there is a paucity of coastal change monitoring datasets, particularly those that document event-scale changes over a large spatial scale. This paucity of data is compounded by the large size and range of shore types throughout the region.Unoccupied aerial vehicle (UAV) or drone data collected by citizen scientists are a potential solution to this challenge. However, no citizen science coastal change monitoring program exists in the Great Lakes region, nor does a comprehensive drone-based coastal change monitoring programs exist anywhere in the United States. To inform the development of drone-based citizen science programs, the goal of this paper is to describe the development and implementation of a citizen science coastal change monitoring program along the Great Lakes shores of Michigan. The citizens participating in this project generate imagery in two ways: (1) the submission of photos of coastal changes or hazards via a web app developed for the project called PicShores and (2) drone collection of survey-quality aerial imagery for use in the generation of orthomosaic images and digital elevation models (DEMs). This paper presents the methods utilized to develop the citizen science monitoring program, some initial findings from the citizen science monitoring, and explores some challenges and next steps for the program.     

Dissolved and Total Thallium in Great Lakes Waters

While being a highly toxic element, thallium (Tl) has been studied to a much lesser degree than other toxic elements such as lead, cadmium or mercury. This is mainly because Tl is often undetected by classical analytical methods which tend to have poorer sensitivity for Tl than for other elements. This is clearly evidenced by our findings that Tl is more concentrated than Cd in Great Lakes waters, yet there have been no published Tl data compared to a good amount of published Cd data for this ecosystem. Recently, we have developed an ultrasensitive Laser-Excited Atomic Fluorescence Spectrometric (LEAFS) method which made possible the direct determination of thallium in lake waters. This paper reports for the first time the concentration and the distribution of dissolved and total Tl in the waters of three Great Lakes and some point sources. The median dissolved concentration of Tl are 1.2, 5.7, 9.4, and 25.7 ng/L (6, 27, 45, and 124 × 10⁻¹² M) in Lakes Superior, Ontario, Erie, and Hamilton Harbor, respectively. A range of sub-ng/L to 50 ng/L of Tl was found. The overall average ratio of dissolved over total Tl is 87% with a standard deviation of 8%. To our knowledge these Tl data are the first ones ever reported for this important ecosystem.     

Great Lakes Fish Finder App; a tool for biologists,managers and education practitioners

As technology advances and smartphone use continues to rise, so do the opportunities for community members to collect valuable scientific data via their smart phones. While the iNaturalist project and phone application (app) are widely known and used, only a fraction (<1.5%) of the >26 million observations logged to date represent fishes. To increase georeferenced observational data on fishes, the John G. Shedd Aquarium announces the Great Lakes Fish Finder (GLFF) phone application and iNaturalist project. The GLFF app contains helpful identification tips in its field guide and allows community-sourced species identification through iNaturalist.org. The georeferenced observations are open-source data allowing anyone to employ GLFF as a data collection tool and repository for their projects. We see the GLFF app as a mechanism for public engagement (anglers and the general community), that contributes useful data for researchers and resources managers, as well as a tool for educators. Ultimately, we envision the GLFF app as a tool for freshwater biodiversity conservation via public engagement.     

Dissolved Organic Matter in the Great Lakes: Role and Nature of Allochthonous Material

Dissolved organic matter (DOM) quality and the modifying influence of light on DOM bioavailability were investigated along a natural gradient of allochthonous influence in the lower Great Lakes. Using parallel factor analysis (PARAFAC), three DOM fluorophores were identified. One fluorophore, previously identified as peak C, was of allochthonous (component 1) origin and two previously uncharacterized fluorophores were identified as autochthonous (components 2 and 3). Component 1 was photoreactive and the dominant form in creek water samples while components 2 and 3 were dominant in Hamilton Harbour and lake water samples. Components 2 and 3 showed limited photoreactivity. Exposure to full spectrum irradiance decreased the average molecular weight of DOM (i.e., increased the absorbance ratio (a254:a365)) for all water samples. DOM bioavailability was lowest in creek and highest in lake water samples and was inversely related to DOM average molecular weight. Photomodification of DOM resulted in higher bacterial activity although these differences were not significantly different. This suggests that light plays a significant role in the cycling of terrestrially-derived DOM and to a certain extent autochthonous DOM, potentially increasing metabolism of both terrestrially and microbially derived DOM in the Great Lakes aquatic ecosystems.