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An extraordinary strong wind‐driven upwelling event occurred in Lake Superior in summer of 2010 when the lake was strongly stratified. In this paper, a detailed three‐dimensional (3‐D) investigation of the current and thermal structures during the upwelling event was conducted using in situ observations, remote sensing products, and the results of a long‐term numerical simulation. A 3‐D finite‐volume coupled ice–ocean model tailored for the Laurentian Great Lakes was employed for this purpose. The model was validated with temperature observations at National Oceanic and Atmospheric Administration buoys and mooring data from 2010. The upwelling event observed in satellite imagery and at a mooring station was reproduced by the model, showing a cooling of as much as 10°C in August 2010 along the northwestern coast. The relationship between the alongshore wind and the offshore thermocline displacement (upwelling front) derived in theoretical work (Csanady, 1977, https://doi.org/10.1029/JC082i003p00397) was used to calculate upwelling front movement offshore and found to be in in close agreement with model prediction. A significant correlation between alongshore wind stress and lake temperature change in the upwelling zone was found with a correlation coefficient of −0.87. A simple linear heat balance model explained most of variability in temperature. Plain Language Summary: An extraordinary strong upwelling event observed during summer 2010 in Lake Superior was reproduced by a numerical ocean model. A detailed three‐dimensional (3‐D) investigation of the current and thermal structures during the upwelling event was conducted using in situ observations, remote sensing products, and the results of a long‐term numerical simulation. A 4‐day long strong, persistent alongshore wind was the major driving force of this event. A significant correlation between alongshore wind stress and lake temperature change in the upwelling zone was found. A simple linear heat balance model explained most of variability in temperature measurements. The relationship between the alongshore wind and the offshore displacement of the upwelling front derived in theoretical work was used to calculate upwelling front movement offshore and found to be in in close agreement with model prediction. Key Points: An extraordinarily strong upwelling event observed during summer 2010 in Lake Superior was reproduced by a coupled ice–ocean modelStrong correlation between lake surface temperature change in the upwelling zone and alongshore wind stress was found (with a correlation coefficient of −0.87); a simple linear heat balance model explained most of time rate of change in temperatureOffshore thermocline displacement (upwelling front) in the model was in good agreement with predictions of an analytical model that employed alongshore wind and initial thermal structure [ABSTRACT FROM AUTHOR]

Efficient management and prevention of species invasions requires accurate prediction of where species of concern can arrive and persist. Species distribution models provide one way to identify potentially suitable habitat by developing the relationship between climate variables and species occurrence data. However, these models when applied to freshwater invasions are complicated by two factors. The first is that the range expansions that typically occur as part of the invasion process violate standard species distribution model assumptions of data stationarity. Second, predicting potential range of freshwater aquatic species is complicated by the reliance on terrestrial climate measurements to develop occurrence relationships for species that occur in aquatic environments. To overcome these obstacles, we combined a recently developed algorithm for species distribution modeling—range bagging—with newly available aquatic habitat-specific information from the North American Great Lakes region to predict suitable habitat for three potential invasive species: golden mussel, killer shrimp, and northern snakehead. Range bagging may more accurately predict relative suitability than other methods because it focuses on the limits of the species environmental tolerances rather than central tendency or “typical” cases. Overlaying the species distribution model output with aquatic habitat-specific data then allowed for more specific predictions of areas with high suitability. Our results indicate there is suitable habitat for northern snakehead in the Great Lakes, particularly shallow coastal habitats in the lower four Great Lakes where literature suggests they will favor areas of wetland and submerged aquatic vegetation. These coastal areas also offer the highest suitability for golden mussel, but our models suggest they are marginal habitats. Globally, the Great Lakes provide the closest match to the currently invaded range of killer shrimp, but they appear to pose an intermediate risk to the region. Range bagging provided reliable predictions when assessed either by a standard test set or by tests for spatial transferability, with golden mussel being the most difficult to accurately predict. Our approach illustrates the strength of combining multiple sources of data, while reiterating the need for increased measurement of freshwater habitat at high spatial resolutions to improve the ability to predict potential invasive species. [ABSTRACT FROM AUTHOR]

Risk analysis of species invasions links biology and economics, is increasingly mandated by international and national policies, and enables improved management of invasive species. Biological invasions proceed through a series of transition probabilities (i.e., introduction, establishment, spread, and impact), and each of these presents opportunities for management. Recent research advances have improved estimates of probability and associated uncertainty. Improvements have come from species-specific trait-based risk assessments (of estimates of introduction, establishment, spread, and impact probabilities, especially from pathways of commerce in living organisms), spatially explicit dispersal models (introduction and spread, especially from transportation pathways), and species distribution models (establishment, spread, and impact). Results of these forecasting models combined with improved and cheaper surveillance technologies and practices [e.g., environmental DNA (eDNA), drones, citizen science] enable more efficient management by focusing surveillance, prevention, eradication, and control efforts on the highest-risk species and locations. Bioeconomic models account for the interacting dynamics within and between ecological and economic systems, and allow decision makers to better understand the financial consequences of alternative management strategies. In general, recent research advances demonstrate that prevention is the policy with the greatest long-term net benefit. [ABSTRACT FROM AUTHOR]

1. Hypoxia occurs seasonally in many stratified coastal marine and freshwater ecosystems when bottom dissolved oxygen (DO) concentrations are depleted below 2-3 mg O L. 2. We evaluated the effects of hypoxia on fish habitat quality in the central basin of Lake Erie from 1987 to 2005, using bioenergetic growth rate potential (GRP) as a proxy for habitat quality. We compared the effect of hypoxia on habitat quality of (i) rainbow smelt, Osmerus mordax mordax Mitchill (young-of-year, YOY, and adult), a cold-water planktivore, (ii) emerald shiner, Notropis atherinoides Rafinesque (adult), a warm-water planktivore, (iii) yellow perch, Perca flavescens Mitchill (YOY and adult), a cool-water benthopelagic omnivore and (iv) round goby Neogobius melanostomus Pallas (adult) a eurythermal benthivore. Annual thermal and DO profiles were generated from 1D thermal and DO hydrodynamics models developed for Lake Erie's central basin. 3. Hypoxia occurred annually, typically from mid-July to mid-October, which spatially and temporally overlaps with otherwise high benthic habitat quality. Hypoxia reduced the habitat quality across fish species and life stages, but the magnitude of the reduction varied both among and within species because of the differences in tolerance to low DO levels and warm-water temperatures. 4. Across years, trends in habitat quality mirrored trends in phosphorus concentration and water column oxygen demand in central Lake Erie. The per cent reduction in habitat quality owing to hypoxia was greatest for adult rainbow smelt and round goby (mean: −35%), followed by adult emerald shiner (mean: −12%), YOY rainbow smelt (mean: −10%) and YOY and adult yellow perch (mean: −8.5%). 5. Our results highlight the importance of differential spatiotemporally interactive effects of DO and temperature on relative fish habitat quality and quantity. These effects have the potential to influence the performance of individual fish species as well as population dynamics, trophic interactions and fish community structure. [ABSTRACT FROM AUTHOR]

In this paper we develop and examine several schemes for combining daily images obtained from the Sea-viewing Wide Field Spectrometer (SeaWiFS) with a two-dimensional sediment transport model of Lake Michigan. We consider two data assimilation methods, direct insertion and a kriging-based approach, and perform a forecasting study focused on a 2-month period in spring 1998 when a large storm caused substantial amounts of sediment resuspension and horizontal sediment transport in the lake. By beginning with the simplest possible forecast method and sequentially adding complexity we are able to assess the improvements offered by combining the satellite data with the numerical model. In our application, we find that data assimilation schemes that include both the data and the lake dynamics improve forecast root mean square error by 40% over purely model-based approaches and by 20% over purely data-based approaches. [ABSTRACT FROM AUTHOR]

We present a method for assimilating current observations into a two-dimensional circulation model of Lake Michigan, based on the Princeton Ocean Model (POM) and driven by observed winds. Because measurements of surface level are not available, we require that the point-wise update to the forecast horizontal current does not change the forecast surface level. This requirement makes it possible to represent the current updates by a stream function. Given an appropriate covariance model of this stream function, the current updates are calculated by kriging interpolation using the observations and the corresponding model forecast. It is further required that the current updates do not create cross-shore flows; this is represented by the stream function being constant along the coastline and is enforced by incorporating pseudo coastal data into the interpolation. This eliminates the need to construct complex spatial covariance models for the stream function. The method also accommodates observational errors. Results show that the method successfully melds observations into the model, and the influence of data assimilation propagates in space and time. [ABSTRACT FROM AUTHOR]

A two-dimensional circulation model has been used to test the hypothesis of whether the observed low-frequency current variations in the central Gulf of Riga, Baltic Sea, can be explained by basin-scale topographic wave response. A comparison of two-dimensional model results with measurements from a single current meter in the gulf showed good correlation. More sophisticated three-dimensional barotropic and baroclinic models provided only marginal improvement over the two-dimensional model. The model results indicate that wind-driven flow over variable bottom topography is the dominant process during moderate and strong winds. The double-gyre circulation pattern resembles the gravest basin-scale topographic wave. The free topographic wave propagates cyclonically around the basin, but does not complete a full cycle because of the shallowness of the Gulf of Riga. The evolution of the topographic wave under realistic wind conditions is analyzed using vorticity dynamics in a basin-scale sense. The topographic wave is reinforced by cyclonically rotating wind and can be destroyed most effectively by anticyclonically rotating wind. The topographic wave signature is more apparent in deep water and almost absent in shallow areas of the basin. During calm periods or under the influence of weak winds, the double-gyre circulation will evolve into predominantly cyclonic circulation. [ABSTRACT FROM AUTHOR]

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 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 bya two-gyre circulation pattern. Summer circulation in the smaller lakes is different; predominantly cyclonic in Lake Ontario and anticyclonic in Lake Erie. [ABSTRACT FROM AUTHOR]

A coupled physical and biological model was developed for Lake Michigan. The physical model was the Princeton ocean model (POM) driven directly by observed winds and net surface heat flux. The biological model was an eight-component, phosphorus-limited, lower trophic level food web model, which included phosphate and silicate for nutrients, diatoms and non-diatoms for dominant phytoplankton species, copepods and protozoa for dominant zooplankton species, bacteria and detritus. Driven by observed meteorological forcings, a 1-D modeling experiment showed a controlling of physical processes on the seasonal variation of biological variables in Lake Michigan: diatoms grew significantly in the subsurface region in early summer as stratification developed and then decayed rapidly in the surface mixed layer when silicate supplied from the deep stratified region was reduced as a result of the formation of the thermocline. The non-diatoms subsequently grew in mid and late summer under a limited-phosphate environment and then declined in the fall and winter as a result of the nutrient consumption in the upper eutrophic layer, limitation of nutrients supplied from the deep region and meteorological cooling and wind mixing. The flux estimates suggested that the microbial loop had a significant contribution in the growth of microzooplankton and hence, to the lower-trophic level food web system. The model results agreed with observations, suggesting that the model was robust to capture the basic seasonal variation of the ecosystem in Lake Michigan. [Copyright &y& Elsevier]

The influence of suspended sediments on the Lake Michigan ecosystem was examined using a 3-dimensional (3-D) coupled biological and physical model developed by Chen et al. (part I). The model was driven by the realistic meteorological forces observed in March 1998, with daily inputs of suspended sediment concentration that were derived from temporally and spatially interpolated satellite imagery. The model results show the significant impact of a seasonally recurring coastal resuspension plume on the spatial and temporal variation of the nutrients and plankton in southern Lake Michigan. The plume-released nutrients played an essential role in maintaining the nutrient level in the lake. Although the growth of phytoplankton in the plume depended on the availability of nutrients and light, the offshore decrease in phytoplankton biomass still satisfied the Sverdrup''s relationship. Cross-shore fluxes of nutrients and phytoplankton were controlled by episodic wind events with a period of ≈5–7 days: offshore during southward winds and onshore during northward winds. The flux estimates for biological variables suggest that the microbial food web is a key contributor to secondary production in southern Lake Michigan and the lower trophic level food web system could be dynamically divided into two decoupled loops: (1) detritus–bacteria–microzooplankton–large zooplankton; and (2) nutrient–phytoplankton–detritus. The model-predicted spatial distributions of nutrients and phytoplankton were in reasonable agreement with observations taken during the 1998 EEGLE interdisciplinary cruises, suggesting that the model was sufficiently robust to capture the basic characteristics of the Lake Michigan ecosystem during the plume event. [Copyright &y& Elsevier]