Great Lakes Research Articles

Comparing Genetic Ne Reconstructions Over Time With Long-Time Wolf Monitoring Data in Two Populations.

Many methods are now available to calculate N e , but their performance varies depending on assumptions. Although simulated data are useful to discover certain types of bias, real empirical data supported by detailed known population histories allow us to discern how well methods perform with actual messy and complex data. Here, we focus on two genomic data sets of grey wolf populations for which population size changes of the past 40-120 years are well documented. We use this background to explore in what detail we can retrieve the known population history from these populations, in the light of pitfalls relating to population history, sampling design and the change in the spatial scale at which N e is estimated as we go further back in time. The Scandinavian wolf population was founded in the early 1980s from a few individuals and has gradually expanded up to 510 wolves. Although the founder event of the Scandinavian population was detected by GONE, the founding effective population size was strongly overestimated when the most recent samples were used, but less so when older samples were considered. Nevertheless, the present-day N e corresponds to theoretical expectations. The western Great Lakes wolf population of Minnesota is the only population in the contiguous United States that persisted throughout the 20th century, surviving intense persecution. We found a good concordance between the estimated N e and trends in census size data, but the reconstruction of N e clearly highlights the difficulty of interpreting results in spatially structured populations that underwent demographic fluctuations.

Tracking Chlamydia and Syphilis in the Detroit Metro Area by Molecular Analysis of Environmental Samples.

This paper describes one of the first studies applying wastewater surveillance to monitor Chlamydia and Syphilis and back-estimate infections in the community, based on bacterial shedding and wastewater surveillance data. Molecular biology laboratory methods were optimized, and a workflow was designed to implement wastewater surveillance tracking Chlamydia and Syphilis in the Detroit metro area (DMA), one of the most populous metropolitan areas in the U.S. Untreated composite wastewater samples were collected weekly from the three main interceptors that service DMA, which collect wastewater and discharge it to the Great Lakes Water Authority Water Resource Recovery Facility. Additionally, untreated wastewater was also collected from street manholes in three neighborhood sewersheds in Wayne, Macomb, and Oakland counties. Centrifugation, DNA extraction, and ddPCR methods were optimized and performed, targeting Chlamydia trachomatis and Treponema pallidum, the causative agents of Chlamydia and Syphilis, respectively. The limit of blank and limit of detection methods were determined experimentally for both targets. Both targets were detected and monitored in wastewater between December 25th, 2023, and April 22nd, 2024. The magnitudes of C. trachomatis and T. pallidum concentrations observed in neighborhood sewersheds were higher as compared to the concentrations observed in the interceptors. Infections of Chlamydia and Syphilis were back-estimated through an optimized formula based on shedding dynamics and wastewater surveillance data, which indicated potentially underreported conditions relative to publicly available clinical data.

A machine learning approach to nearshore wave modeling in large lakes using land-based wind observations

This study presents a novel machine learning-based (ML) framework that utilizes the ConvLSTM-1D model to simulate wave heights at a nearshore location in Lake Michigan using a nonuniform land-based array of wind observations from a broad geographic region as an input. This approach was applied to Lake Michigan to perform a 70-year ice-free hindcast of waves near Chicago, IL (USA). Because of annual winter gaps in Great Lakes buoy observations, output from the Wave Information System model (WIS) was used for the training, validation, and testing of the ML model. Models with different numbers of wind stations were tested, showing that a single wind station as an input feature produced a reasonably accurate wave height. However, the wave height model accuracy increased as more wind input data was included from around the lake, largely plateauing beyond the inclusion of four stations that spanned Lake Michigan’s southern basin. The optimized model lookback period was found to be 10 h for all models, suggestive of a fetch-limited temporal coupling between the wind observations and nearshore waves. The extended time series showed a statistically significant increase in the interannual standard deviation of the storm wave height and the storm height over the mean wave height while no correlation was found with the annual water level time series. The ML framework offers a promising avenue for utilizing historical wind records to extend wave height time series for nearshore locations, particularly in enclosed and semi-enclosed basins where waves are strongly linked to local winds.

Active remote sensing data and dispersal processes improve predictions for an invasive aquatic plant during a climatic extreme in Great Lakes coastal wetlands

Invasive aquatic plants pose a significant threat to coastal wetlands. Predicting suitable habitat for invasive aquatic plants in uninvaded yet vulnerable wetlands remains a critical task to prevent further harm to these ecosystems. The integration of remote sensing and geospatial data into species distribution models (SDMs) can help predict where new invasions are likely to occur by generating spatial outputs of habitat suitability. The objective of this study was to assess the efficacy of utilizing active remote sensing datasets (synthetic aperture radar (SAR) and light detection and ranging (LiDAR) with multispectral imagery and other geospatial data in predicting the potential distribution of an invasive aquatic plant based on its biophysical habitat requirements and dispersal dynamics. We also considered a climatic extreme (lake water levels) during the study period to investigate how these predictions may change between years. We compiled a time series of 1628 field records on the occurrence of Hydrocharis morsus-ranae (European frogbit; EFB) with nine remote sensing and geospatial layers as predictors to train and assess the predictive capacity of random forest models to generate habitat suitability in Great Lakes coastal wetlands in northern Michigan, USA. We found that SAR and LiDAR data were useful as proxies for key biophysical characteristics of EFB habitat (emergent vegetation and water depth), and that a vegetation index calculated from spectral imagery was one of the most important predictors of EFB occurrence. Our SDM using all predictors yielded the highest mean overall accuracy of 88.3% and a true skill statistic of 75.7%. Two of the most important predictors of EFB occurrence were dispersal-related: 1) distance to the nearest known EFB population (m), and 2) distance to nearest public boat launch (m). The area of highly suitable habitat (pixels assigned ≥0.8 probability) was 74% larger during a climatically extreme high water-level year compared to an average year. Our findings demonstrate that active remote sensing can be integrated into SDM workflows as proxies for important drivers of invasive species expansion that are difficult to measure in other ways. Moreover, the importance of a proxy variable for endogenous dispersal (distance to nearest known population) in these SDMs indicates that EFB is currently spreading, and thereby less influenced by within-site dynamics such as interspecific competition. Lastly, we found that extreme climatic conditions can dramatically change this species’ niche, and therefore we recommend that future studies include dynamic climate conditions in SDMs to more accurately forecast the spread during early invasion stages.

Strategic Water Management in the Great Lakes: Integrating Network Models and Optimization

Strategic Water Management in the Great Lakes: Integrating Network Models and Optimization

Spring Water Quality in a Flood-Prone Area of Kampala City, Uganda: Insights Furnished by Sanitary and Limnochemical Data

For millennia, springs have provided water for drinking, domestic use, balneological treatment, liminality rites as well as tourist attractions. Amidst these uses, anthropogenic activities, especially urbanization and agriculture, continue to impair the functionality of springs. With the looming decadal climate change, freshwater springs could be a sustainable source of clean water for the realisation of Sustainable Development Goal 6. This paper presents the results of the sanitary inspection and assessment of limnochemical characteristics and quality of water samples (n = 64) from four freshwater springs (coded SPR1, SPR2, SPR3, and SPR4) in Kansanga, a flash flood-prone area in the African Great Lakes region of Uganda. Each sample was analysed for 17 parameters (temperature, pH, electrical conductivity, turbidity, fluorides, sulphates, chlorides, nitrates, orthophosphates, total dissolved solids, dissolved oxygen, total alkalinity, potassium, sodium, total, magnesium and calcium hardness) following the standard methods. Water quality index (WQI) was calculated to establish the quality of the water samples based on the physicochemical parameters measured. Based on the sanitary risk assessment results, the springs had medium- to high-risk scores, but most water parameters were within the WHO guidelines for potable water, except for nitrates (in SPR1 and SPR2), hardness levels (in SPR2), and dissolved oxygen (in all the samples). Sampling season and location had significant effects on the limnochemistry of the freshwater springs (p < 0.05). The water quality indices calculated indicated that the water from the springs was of good quality (WQI = 50–57), but there was a reduction in water quality during the wet season. The best water quality was recorded in samples from SPR4, followed by those for SPR3, SPR1, and SPR2. These results provide insights into the contribution of floods and poor sanitation facilities to the deterioration of spring water quality in Kansanga, and the need to leverage additional conservation strategies to support vulnerable communities in the area. Further studies are required to establish the risk posed by trace metals and microbes that may contaminate freshwater in the studied springs, especially following flood events.

Modeling the Great Lakes Basin based on dynamic network flows

Modeling the Great Lakes Basin based on dynamic network flows

Integrated Management of Sclerotinia Stem Rot of Soybean Including Organically-Allowed Fungicides in the Midwest United States

Sclerotinia stem rot (SSR) is an economically important disease of soybean, especially in the Great Lakes region of the United States. Few studies on SSR have considered organic management practices and how integrated management techniques best apply in these systems. Trials in Wisconsin and Indiana aimed to evaluate management techniques available to organic farmers for their efficacy in SSR control while preserving yield. The practices evaluated included genetically resistant cultivars, tillage techniques, and the application of Organic Materials Review Institute (OMRI) listed foliar fungicides. The resistant cultivar had significantly lower SSR than the susceptible cultivar in three site-years (P < 0.01). The resistant cultivar also had significantly greater yield than the susceptible cultivar in two site-years (P < 0.05). Using a roller-crimped rye cover crop resulted in mixed results on SSR and yield. No effect on SSR or yield by OMRI listed foliar fungicides was observed (P > 0.05). Overall, the results emphasize the importance of planting a resistant soybean cultivar to manage SSR in organic farming systems in the Midwestern United States.

Invasive mussels reduce community bioturbation but do not affect oxygen penetration or nutrient fluxes in organic‐poor Great Lakes sediments

Abstract Invasive zebra and quagga (dreissenid) mussels have disrupted nutrient cycling and benthic macrofauna communities in the Laurentian Great Lakes and other invaded ecosystems. Dreissenids are now the dominant benthic macroinvertebrate in the Great Lakes, replacing the formerly dominant native bioturbating amphipod Diporeia spp. Dreissenids and Diporeia interact with their environment in fundamentally different ways, and the consequences of this functional shift in benthic community structure on benthic–pelagic coupling are not well understood, particularly in unproductive offshore lake regions. To determine how functional biology and benthic community structure impact sediment mixing and biogeochemistry in low particulate organic matter (POM) lake regions, we conducted a 6‐week sediment microcosm experiment with dreissenids, Diporeia and oligochaete worms—the second most common Great Lakes benthic macroinvertebrate. We found that sediment mixing rate and depth varied significantly among the taxa. Diporeia mixed sediment the deepest and strongest, followed by oligochaetes, while dreissenids did not appreciably mix sediment. Despite these differences, we found no significant variations among treatments in sediment oxygen penetration depth, sediment respiration (oxygen uptake) or nutrient dynamics. Our results suggest that dreissenids mix sediment less than native Great Lakes taxa, but that differential mixing rates may not measurably affect nutrient and oxygen dynamics in low‐POM sediments. Therefore, mussel effects in these areas may be manifested more through direct mechanisms rather than via altered sediment geochemistry.

Land Use Simulation and Ecological Network Construction around Poyang Lake Area in China under the Goal of Sustainable Development

The pivotal aspects of enhancing regional ecosystem services and augmenting socioeconomic growth lie in optimizing the land-space development and protection strategies, coupled with the establishment of a robust ecological network (EN). This article examines the Poyang Lake area and employs the MOP model, NSGA-II, and PLUS model to determine the best sustainable land use strategy. Subsequently, the MSPA, InVEST model, circuit theory, complex network, and others are employed to construct and analyze the land-space EN across three time periods. Ultimately, the EN is optimized based on spatial protection priority, ecological obstacle areas, and ecological nodes. The results show the following: (1) From 2005 to 2035, more construction land will be developed around the Greater Nanchang area and other urban centers. In the BAU scenario, construction land will expand faster, while cultivated land, forest, grassland, and bare land will continue to decline. In the SD scenario, the alteration to comparable land is minimal, the growth rate of construction land will slow, cultivated land, forest, grassland, and bare land will all decline little, and the water area will increase slightly; (2) While the area of ecological sources is decreased and ecological corridors become longer and narrower in the BAU scenario, the spatial distribution of ENs in different periods is small, and the quantitative structure and spatial distribution of ecological sources and corridors are essentially unchanged in the SD scenario; (3) Based on the topological structure of ENs, it is found that the clustering of nodes in the SD scenario is more obvious, the importance of ecological sources is enhanced, the efficiency of information transmission is improved, and the radiation range is wider and more stable; (4) The greatest priority ecological sources in each period are concentrated around Poyang Lake. In the SD scenario, the priority of ecological sources improves, and 7025 km2 of ecological obstacle restoration area is identified, with 41, 31, and 36 ecological breakpoints in the first, second, and third levels. The study’s findings can assist and shape theoretical and practical approaches to land governance and sustainable development in great lake areas.

Turning the tables or business as usual? COVID-19 as a catalyst in North–South research collaborations

Since February 2020, we have witnessed COVID-19 profoundly disturb ongoing research dynamics – including research collaborations between the Global North and the Global South. Reduced international and regional mobility obliged research collaborations to reinvent their modalities. The role of field-based researchers (those physically ‘there’) has never been more crucial. This article draws on the testimonies of researchers from the African Great Lakes region to reflect on the positionality of field-based researchers in North–South research collaborations throughout the COVID-19 pandemic. Their embeddedness in the field foregrounded their complementary strengths in interactions with scholars from the Global North. We also illustrate how vulnerabilities – both unstable employment and field-related risks – were unevenly shared by partners in the Global South and the Global North. In conclusion, the COVID-19 experience inspired us to adhere to new collaboration modalities that move beyond post-colonial dynamics in North–South research collaborations.

Finding the Holy Grail of Library Value: Characteristics of Academic Libraries at Universities with High Retention Rates

Objective – What are the characteristics of academic libraries at schools with high retention rates? To help libraries tell the story of their impact, we sought to determine which academic library practices were linked to high retention rates. Methods – The investigators created a survey for the United States Great Lakes region library deans and directors in the Spring of 2022 with 19 questions about their library services and staffing. The survey was sent to 226 schools and had a response rate of 31%. We compared the resulting information to publicly available data on student retention from ACRL Metrics and IPEDS to look for correlations and associations. Results – Statistical analysis used the Chi-squared test and the Pearson correlation to calculate association and correlation. This found six attributes of student connections with library staff and with unique local collections that were associated with statistically significant differences in retention rates and institutions. These attributes were institutions who: used students as archives student workers, used students to staff reference desks, conducted multiple library instruction sessions with the same class, had a staffed archive or special collection space, had an institutional repository that included student work, or had an Instagram account. Conclusion – The survey results gave a clear profile of academic libraries with above average retention, particularly in terms of student focused initiatives and the curation of unique collections. Additionally, the survey gave a foundation, with recommendations, for future researchers to build upon.

Range maps and waterbody occupancy data for 1158 freshwater macroinvertebrate genera in the contiguous USA

Range maps are used to estimate the geographic extent of taxa, providing valuable information for biodiversity and conservation research and management. Freshwater macroinvertebrates are not well-represented in the range map literature relative to freshwater vertebrates. To address this knowledge gap, we provide range maps for 1158 freshwater macroinvertebrate genera based on two decades of publicly available occurrence data from the USEPA National Aquatic Resource Surveys, which included 11,628 sites and 6,906,990 organisms across the contiguous USA. Maps were created by applying unweighted and weighted pair group method with arithmetic mean clustering and single-linkage clustering algorithms to the occurrence data and creating three layers of polygons from the minimum convex hulls of clusters. A total of 25 freshwater macroinvertebrate classes are represented in the range map dataset. Most mapped genera were insects (394/1158), followed by malacostracans (242/1158), polychaetes (182/1158), and bivalves (121/1158). Additionally, we provide waterbody type percent occupancy data for all genera, detailing how genera are partitioned between boatable streams, wadeable streams, inland lakes, Laurentian Great Lakes, and coastal estuaries.

Linking boundary organizations to co-produce actionable knowledge: A case study of ice forecasting for Great Lakes navigation

Abstract Navigating the Great Lakes during icy conditions poses significant safety challenges for the shipping sector. Available ice information is uncertain and fragmented, and navigators must seek out multiple sources for information at the spatial and temporal scales they require, if the information is available at all. Navigators have expressed that they require more highly localized and easily usable information for current and predicted ice conditions to support decision-making. In this study, we seek to meet this information need by applying a boundary organizations chain (BOC) approach to facilitate the co-production of an actionable short-term Great Lakes ice forecast. We focus on two main aspects of this research: 1) producing an actionable decision-support product that meets the needs of Great Lakes ice navigators, and 2) contributing to the knowledge co-production scholarship on BOCs by providing a detailed account of our methods to create a BOC and co-produce an actionable ice forecast. Our results support incorporating existing communities of practice (COPs) into BOCs to enhance the co-production of actionable knowledge, specifically through increasing their complementarity and embeddedness. COPs are informal networks of users that meet voluntarily to share knowledge and develop professional skills, which we found naturally builds the co-production capacities of participants (e.g. embeddedness and complementarity). We also find that COP members are well positioned to disseminate co-produced knowledge across wider user groups.

Turbidity assessment in coastal regions combining machine learning, numerical modeling, and remote sensing

ABSTRACT Machine learning models for water quality prediction often face challenges due to insufficient data and uneven spatial-temporal distributions. To address these issues, we introduce a framework combining machine learning, numerical modeling, and remote sensing imagery to predict coastal water turbidity, a key water quality proxy. This approach was tested in the Great Lakes region, specifically Cleveland Harbor, Lake Erie. We trained models using observed and synthetic data from 3D numerical models and tested them against in situ and remote sensing data from PlanetLabs' Dove satellites. High-resolution (HR) data improved prediction accuracy, with RMSE values of 0.154 and 0.146 log10(FNU) and R2 values of 0.92 and 0.93 for validation and test datasets, respectively. Our study highlights the importance of unified turbidity measures for data comparability. The machine learning model demonstrated skill in predicting turbidity through transfer learning, indicating applicability in diverse, data-scarce regions. This approach can enhance decision support systems for coastal environments by providing accurate, timely predictions of water quality variables. Our methodology offers robust strategies for turbidity and water quality monitoring and holds significant potential for improving input data quality for numerical models and developing predictive models from remote sensing data.

Quantifying the effects of carborundum rock surface smoothing for Schmidt hammer R‐value metrics measured on glacial erratics in the North American Great Lakes region

AbstractSchmidt hammer R‐values, which reflect the degree of rock surface weathering, can be paired with independent rock surface exposure ages to produce Schmidt hammer exposure‐age dating (SHD) calibration curves that are used to provide rapid estimations of exposure ages for undated rock surfaces. In this Letter, we lay the groundwork for later establishing a SHD calibration curve based on glacial erratics deposited by the Laurentide Ice Sheet in the North American Great Lakes region. First, we establish a reference R‐value for a calibration boulder, which may be used to facilitate direct comparison of R‐values collected by different individuals using mechanical N‐type Schmidt hammers, specifically. We then assess how no, light or heavy use of a carborundum puck to smooth rock surfaces affects resulting R‐value data. Lastly, we compare two different R‐value metrics on the same rock surface: Rmean (n = 30) versus ΔR (Rmax − Rmin of five consecutive R‐values on the same spot). In all assessments, Rmean is similar for erratic surfaces with no and light surface treatment, and both are significantly lower than Rmean of surfaces with heavy treatment. Thus, we advise against the use of heavy surface treatment in SHD applications. We observe no relationship between inferred erratic age and either Rmean or ΔR, which could arise from inferred ages of erratics being inaccurate, from inferred ages of erratics being too similar or from measuring too few erratics from each landform.

Watershed inputs of suspended sediment drive patterns of total phosphorus in Chequamegon Bay, Lake Superior

Lake Superior is considered the least anthropogenically stressed and has the lowest offshore phosphorus (P) concentrations of the five Laurentian Great Lakes. However, nearshore habitats in Lake Superior are showing evidence of nutrient related stress. We examined drivers of total P dynamics in Chequamegon Bay, a shallow embayment in southwestern Lake Superior located in a region of the Laurentian Great Lakes that is primarily forested with low human development. Over a nine-year period (2014–2022) we measured total and soluble reactive phosphorus (TP and SRP, respectively), total suspended solids (TSS), and chlorophyll-a (Chl-a) at 12 locations distributed across Chequamegon Bay. Path analysis revealed that TP in this region of Lake Superior is largely sediment bound and driven by watershed inputs of suspended sediment. SRP and Chl-a make up only a small portion of TP. TP and TSS were highly correlated, with a stronger correlation at the most nearshore locations and following extreme precipitation events in 2016 and 2018. TP and Chl-a had a weak positive correlation at low TP concentrations, and lack of correlation at high TP concentrations. This suggests that despite high TP inputs from runoff events, Chl-a response was minimal, likely due to low light availability and limited bioavailability of sediment-bound P. Understanding conditions where episodic inputs of TP could contribute to the reactive P pool and how hydrodynamics affect biogeochemical processes and algal response to nutrient inputs are critical to understanding how an expected increase in extreme events will influence nearshore water quality in large lakes.

칼 사우어(Carl O. Sauer)의 문화·역사지리학에 투영된 환경관

Despite Sauer set out his coursework in 1909 in the midst of Davisian physiography and environmentalism, Salisbury at Chicago assisted him to avoid the causative man-nature relation by laying emphasis on field observations. Having witnessed the widespread soil exhaustion in Illinois and Missouri, Sauer now at Ann Arbor had to redress economic and ecological problems from the deforestration of white pines on the Great Lakes. Advising on the issues of land utilization and soil erosion for the New Deal Government, Sauer in Berlekey shaped up the landscape morphology in which culture was conceived as an agent, natural landscape a medium and cultural landscape an outcome. The intellectual encounter with Boasian anthropology resulted in cultural and historical geography or culture history of seeking out the origin, diffusion and transformation of culture and cultural landscape, bearing the brunt of environmentalism. To be noted is that Sauer resurrected Marsh’s Man and Nature by organizing the 1955 international symposium on ‘Man’s Role in Changing the Face of the Earth’. Sauer’s environmental ethics urges us to do our moral and ecological duties for the coming generation.

“Sweet Like Honey”: Twa Photographers Reframing the Past, Present and Future in a Remote Rwandan Marginalised Community

ABSTRACT Nyabageni, a small village in north-west Rwanda, is home to a remote rural community of historically marginalised people, formerly known as Twa. Today the village is made up of both those who grew up in the forest and those born in the new settlement into a very different Rwanda. This article examines the artistic work of 12 members of the community who took part in a participatory photography workshop in May 2022. It discusses what the Nyabageni artists’ striking images tell us about conceptions of the past, present and future, and how their self-narratives contest and reframe ongoing prejudice. Close readings of individual photographs show how they: re-animate the past; place members of the community in roles they have previously been excluded from; mobilise visual imagery to activate social change; and stress reparative internal perspectives on a close-knit community. Focusing on the aesthetic and strategic choices made by the photographers, we discuss the complexity and sophistication of their vision, which expands existing literature on Twa identities in the Great Lakes. We also reflect on the role of photography in foregrounding the complex memories, dreams and aspirations of marginalised indigenous people.

Aeolian sediments in western Mongolia: Distribution and (paleo)climatic implications

The largest dune fields in Mongolia are mainly restricted to the Basin of Great Lakes in western Mongolia. These dune fields extend from 800 m a.s.l. in the basins for 200 to 300 km into the mountains up to about 2100 m a.s.l. Analyses of these dune fields, using an integrative mapping approach, provide evidence for different wind regimes. The dune fields result from a long-term Quaternary sediment cycle. Rivers transported the sand into the basins from where the wind carried the sand eastwards along the dune fields with a concurrent loss of silt-sized particles. Different paleolake levels and sandy plains with mobilized sand at their western ends exist in the lake basins. The largest masses of dune sand are found in the central parts of the dune fields. Towards their eastern ends, lower and more vegetated dunes and sand sheets result from both the decrease in sediment supply and increased vegetation at higher elevations. Three climatic and paleoclimatic implications are derived from the mapping approach. A: Under the modern semi-arid to semi-humid climate, wind systems from north to the north-west prevail, whereas in the southern Mongolian Els also wind from the south-east occurs. B: The highest lake levels occurred during pluvial phases in the basins, caused by increased moisture supply, also due to water supply from glacier- and permafrost retreat. C: The fundamental west-east orientation of the dune fields is a result of westerly winds which were prevalent during arid periods.