January 2019 - Present
ALSIP, P.J., H. ZHANG, M.D. ROWE, D.M. MASON, E.S. RUTHERFORD, C.M. Riseng, and Z. Su. Lake Michigan's suitability for bigheaded carp: The importance of diet flexibility and subsurface habitat. Freshwater Biology (DOI:doi.org/10.1111/fwb.13382) (2019).
As bighead (Hypophthalmichthys nobilis) and silver carp (Hypophthalmichthys molitrix)—collectively bigheaded carp (BHC)—arrive at Lake Michigan's doorstep, questions remain as to whether there is sufficient food to support these invasive filter‐feeding fishes in the upper Laurentian Great Lakes. Previous studies suggest that suitable BHC habitat is limited to a few productive, nearshore areas. However, those studies did not consider the influence of BHC's diet plasticity or the presence of spatially‐discrete subsurface prey resources. This study aimed to characterise Lake Michigan's suitability for BHC and evaluate the importance of these considerations in habitat suitability assessments.
We used simulated outputs of prey biomass (phytoplankton, zooplankton, and detritus) and water temperature from a three‐dimensional biophysical model of Lake Michigan to evaluate growth rate potential (GRP, quantitative index of habitat suitability) of adult BHC throughout the entire volume of the lake. Our GRP model applied a foraging model and a bioenergetics model to translate prey concentrations and water temperatures into habitat quality indexed by individual fish growth rate. We defined suitable habitat as habitats that can support GRP ≥ 0 g g−1 day−1. We developed six feeding scenarios to evaluate the impact of diet flexibility and subsurface prey resources on suitable habitat quantity. Scenarios were defined by the number of prey types the fish could consume and the depths at which they could feed (surface or whole water column).
Consistent with previous studies, we found that habitats with the highest quality were concentrated near river mouths and in eutrophic areas of Green Bay. However, in contrast to previous studies, we found suitable offshore habitat for bighead carp owing to our added considerations of diet plasticity and subsurface prey resources. For silver carp, these considerations extended suitable habitat within Green Bay and in some tributary‐influenced nearshore areas, but offshore areas remained predominantly unsuitable in all feeding scenarios. Differences in simulated habitat suitability between these two species probably reflect differences in energy density and mass of the specific fishes we used in our model. However, reports of these two species in environments where they coexist indicate that bighead carp grow at faster rates than silver carp, as our model simulated.
Our vertical analysis at Muskegon, MI, U.S.A. indicates that subsurface temperature and prey biomass are not only sufficient to support bighead carp growth but provide maximum habitat quality during late summer stratification.
Overall, our study demonstrates that BHC are capable of surviving and growing in much larger areas of Lake Michigan than predicted by previous studies, and thus suggests that the risk of establishment is not sufficiently reduced by low plankton concentrations. Maps generated by our model identified the potential for cross‐lake migration corridors that may facilitate and accelerate lake‐wide movements. We believe these maps could be used to prioritise surveillance protocols by identifying areas to which BHC might spread upon entering the lake. More broadly, this research demonstrates how the physiology and trophic ecology of BHC contributes to their high invasive capacity and can permit their survival in novel environments.
Bosse, K.R., M.J. Sayers, R.A. Shuchman, G.L. Fahnenstiel, S.A. RUBERG, D.L. FANSLOW, D.G. STUART, T.H. JOHENGEN, and A.M. BURTNER. Spatial-temporal variability of in situ cyanobacteria vertical structure in Western Lake Erie: Implications for remote sensing observations. Journal of Great Lakes Research 45(3):480-489 (DOI:10.1016/j.jglr.2019.02.003) (2019).
Remote sensing has provided expanded temporal and spatial range to the study of harmful algal blooms (cyanoHABs) in western Lake Erie, allowing for a greater understanding of bloom dynamics than is possible through in situ sampling. However, satellites are limited in their ability to specifically target cyanobacteria and can only observe the water within the first optical depth. This limits the ability of remote sensing to make conclusions about full water column cyanoHAB biomass if cyanobacteria are vertically stratified. FluoroProbe data were collected at nine stations across western Lake Erie in 2015 and 2016 and analyzed to characterize spatio-temporal variability in cyanobacteria vertical structure. Cyanobacteria were generally homogenously distributed during the growing season except under certain conditions. As water depth increased and high surface layer concentrations were observed, cyanobacteria were found to be more vertically stratified and the assumption of homogeneity was less supported. Cyanobacteria vertical distribution was related to wind speed and wave height, with increased stratification at low wind speeds (<4.9 m/s) and wave heights (<0.27 m). Once wind speed and wave height exceeded these thresholds the assumption of vertically uniform cyanobacteria populations was justified. These findings suggest that remote sensing can provide adequate estimates of water column cyanoHAB biomass in most conditions; however, the incorporation of bathymetry and environmental conditions could lead to improved biomass estimates. Additionally, cyanobacteria contributions to total chlorophyll-a were shown to change throughout the season and across depth, suggesting the need for remote sensing algorithms to specifically identify cyanobacteria.
Dai, Q., D.B. Bunnell, J.S. Diana, S.A. POTHOVEN, L. Eaton, T.P. O’Brien, and R.T. Kraus. Spatial patterns of rainbow smelt energetic condition in Lakes Huron and Erie in 2017: Evidence for Lake Huron resource limitation. Journal of Great Lakes Research 45(4)(DOI:10.1016/j.jglr.2019.06.001) (2019). IN PRESS
Rainbow smelt (Osmerus mordax) is a key planktivore and prey fish in Lake Huron. Given the declining offshore productivity in the lake since the early 2000s, we described the energy content of rainbow smelt in 2017 across five different regions (North Channel, Georgian Bay, Saginaw Bay, northern main basin, southern main basin) where phytoplankton and zooplankton productivity likely varied. To increase contrast across the productivity gradient, rainbow smelt energy content was also estimated from western Lake Erie. Within the North Channel where large fish (≥90 mm, total length) were sampled most frequently, mean energy density (kJ/g wet weight) varied seasonally: 4.29 in April (month of spawning), 3.86 in June, 3.99 in July, and up to 4.35 in September. Energy density of rainbow smelt from higher productivity western Lake Erie was 37% (large fish ≥90 mm) to 60% higher (small fish <90 mm) than that of fish from Lake Huron. Within Lake Huron, energy density of rainbow smelt from North Channel was slightly higher than those from other regions; rainbow smelt from Georgian Bay generally had the lowest energy density. Across regions, including western Lake Erie, energy density increased with chlorophyll a concentration. Compared with Lake Huron studies prior to 2004, when oligotrophication had not yet accelerated, energy density of rainbow smelt in 2017 was up to 31% lower. The decline in rainbow smelt energy density is likely the result of declining primary and secondary pelagic production and increased resource limitation for planktivorous fish.
GRONEWOLD, A.D., and R.B. Rood. Recent water level changes across Earth's largest lake system and implications for future variability. Journal of Great Lakes Research 45(1):1-3 (DOI:10.1016/j.jglr.2018.10.012) (2019).
Water levels on Lake Ontario, the most downstream of the Laurentian Great Lakes, reached a record high in the spring of 2017. This event was accompanied by widespread flooding and displacement of families. Water levels across all of the Great Lakes have risen over the past several years following a period of record low levels. When levels were low, public and expert discussion focused on the possibility that low levels would continue into the future due to climate change, diversions of water from the lakes, and dredging. During the current high water period, variability is being attributed to water management, despite evidence of unusually high precipitation and river flows across the region. Understanding and communicating the drivers behind water level variability, particularly in light of recent extremes, is a fundamental step towards improving regional water resources management and policy.
GRONEWOLD, A.D., E.J. ANDERSON, and J.P. SMITH. Evaluating Operational Hydrodynamic Models for Real‐time Simulation of Evaporation From Large Lakes. Geophysical Research Letters 46(6):3263-3269 (DOI:10.1029/2019GL082289) (2019).
Methods for simulating evaporative water loss from Earth's large lakes have lagged behind advances in hydrodynamic modeling. Here we explore use of oceanographic models to simulate lake evaporation from a long‐term water balance perspective. More specifically, we compare long‐term monthly simulations of latent heat flux from two configurations of a current operational hydrodynamic forecasting system (based on the Finite Volume Community Ocean Model, or FVCOM) for the Laurentian Great Lakes. We then compare these simulations to comparable simulations from a legacy conventional lake thermodynamics model, and from a recently developed statistical water balance model. We find that one of the FVCOM configurations that is currently used in operations for short‐term hydrodynamic forecast guidance is also suitable for real‐time simulation of evaporation from very large lakes. The operational versions of FVCOM should therefore be considered a readily available tool for supporting regional water supply management and, pending further research, extended water supply forecasting.
Ji, X., A.D. GRONEWOLD, H. Dahar, and R.B. Rood. Modeling seasonal onset of coastal ice. Climatic Change 154(1-2):125-141 (DOI:10.1007/s10584-019-02400-1) (2019). https://www.glerl.noaa.gov/pubs/fulltext/2019/20190016.pdf
To support regional management planning decisions, and to protect human health and safety, we developed a new statistical model that simulates the onset of seasonal ice cover along the shoreline of a US National Park (the Apostle Islands National Lakeshore, or APIS). Our model encodes relationships between different modes of climate variability and regional ice cover from 1972 to 2015, and successfully simulates both the timing of ice onset and the probability that ice cover might form at all in a particular winter season. We simulate both of these endpoints using a novel combination of statistical hazard (or survival) and beta regression models. Our analysis of coastal ice cover along the APIS reinforces findings from previous research suggesting that the late 1990s signified a regime shift in climate conditions across North America. Before this period, coastal ice cover conditions at the APIS were often suitable for pedestrian access, while after this period coastal ice cover at the APIS has been highly variable. Our new model accommodates this regime shift, and provides a stepping stone towards a broad range of applications of similar models for supporting regional management decisions in light of evolving climate conditions.
Kharbush, J.J., D.J. Smith, M. Powers, H.A. VANDERPLOEG, D.L. FANSLOW, R.S. ROBINSON, G.J. Dick, and A. Pearson. Chlorophyll nitrogen isotope values track shifts between cyanobacteria and eukaryotic algae in a natural phytoplankton community in Lake Erie. Organic Geochemistry 128:71-77 (DOI:10.1016/j.orggeochem.2018.12.006) (2019).
Chlorophylls are produced by all photosynthetic organisms and are ideal targets for compound-specific isotopic studies of phytoplankton. In laboratory cultures, the difference between the nitrogen (N) isotope ratio (δ15N value) of chlorophyll and the δ15N value of biomass, known as εpor, varies taxonomically, yielding potential applications for studying productivity in modern and ancient environments. Here we take advantage of the annual cyanobacterial bloom in Lake Erie, USA, to demonstrate εpor patterns in a natural community. The resulting time series shows that environmental observations are similar to laboratory cultures: predicted εpor endmember values range from 4.6‰ to 7.4‰ for eukaryotic algae, and −18‰ to −21‰ for cyanobacteria. Because the range and sensitivity of εpor is similar between laboratory and natural settings, the data support the use of εpor as a reliable tracer of the relative contributions of cyanobacteria and eukaryotic algae to nutrient utilization and primary production in lacustrine environments.
Lee, C.-M., C.-Y. Kuo, J. Sun, T.-P. Tseng, K.-H. Chen, W.-H. Lan, C.K. Shum, T. Ali, P. CHU, and Y. Jia. Evaluation and improvement of coastal GNSS reflectometry sea level variations from existing GNSS stations in Taiwan. Advances in Space Research 63(3):1280-1288 (DOI:10.1016/j.asr.2018.10.039) (2019).
Global sea level rise due to an increasingly warmer climate has begun to induce hazards, adversely affecting the lives and properties of people residing in low-lying coastal regions and islands. Therefore, it is important to monitor and understand variations in coastal sea level covering offshore regions. Signal-to-noise ratio (SNR) data of Global Navigation Satellite System (GNSS) have been successfully used to robustly derive sea level heights (SLHs). In Taiwan, there are a number of continuously operating GNSS stations, not originally installed for sea level monitoring. They were established in harbors or near coastal regions for monitoring land motion. This study utilizes existing SNR data from three GNSS stations (Kaohsiung, Suao, and TaiCOAST) in Taiwan to compute SLHs with two methods, namely, Lomb–Scargle Periodogram (LSP)-only, and LSP aided with tidal harmonic analysis developed in this study. The results of both methods are compared with co-located or nearby tide gauge records. Due to the poor quality of SNR data, the worst accuracy of SLHs derived from traditional LSP-only method exceeds 1 m at the TaiCOAST station. With our procedure, the standard deviations (STDs) of difference between GNSS-derived SLHs and tide gauge records in Kaohsiung and Suao stations decreased to 10 cm and the results show excellent agreement with tide gauge derived relative sea level records, with STD of differences of 7 cm and correlation coefficient of 0.96. In addition, the absolute GNSS-R sea level trend in Kaohsiung during 2006–2011 agrees well with that derived from satellite altimetry. We conclude that the coastal GNSS stations in Taiwan have the potential of monitoring absolute coastal sea level change accurately when our proposed methodology is used.
Lei, R., J.K. Hutchings, J. WANG, and X. Pang. Backward and forward drift trajectories of sea ice in the northwestern Arctic Ocean in response to changing atmospheric circulation. International Journal of Climatology (DOI:10.1002/joc.6080) (2019). https://www.glerl.noaa.gov/pubs/fulltext/2019/20190024.pdf (IN PRESS)
To track sea ice motion, four ice-tethered buoys were deployed at 84.6_ N and 144.3_ W, 87.3_ N and 172.3_ W, 81.1_ N and 157.4_ W, and 82.8_ N and 166.5_ W in summers of 2008, 2010, 2014, and 2016, respectively. In addition, the remote sensed ice motion product provided by National Snow and Ice Data Center was used to reconstruct backward and forward ice drifting trajectories from the buoy deployment sites during 1979– 2016. Sea ice in the central Arctic Ocean in late summer is trending to have travelled from lower latitudes, and to be advected to the region more involved in the Transpolar Drift Stream (TDS) during 1979– 2016. The strengthened TDS has played a crucial role in Arctic sea ice loss from a dynamic perspective. The trajectory of ice is found to be significantly related to atmosphere circulation indices. The Central Arctic Index (CAI), defined as the difference in sea level pressure between 84_ N,90_ W and 84_ N, 90_ E, can explain 34– 40% of the meridional displacement along the backward trajectories, and it can explain 27– 40% of the zonal displacement along the forward trajectories. The winter Beaufort High (BH) anomaly can explain 18– 27% of the zonal displacement. Under high positive CAI values or high negative winter BH anomalies, floes from the central Arctic tended to be advected out of the Arctic Ocean through Fram Strait or other marginal gateways. Conversely, under high negative CAI values or high positive winter BH anomalies, ice tended to become trapped within a region close to the North Pole or it drifted into the Beaufort Gyre region. The longterm trend and spatial change in Arctic surface air temperature were more remarkable during the freezing season than the melt season because most energy from the lower troposphere is used to melt sea ice and warm the upper ocean during summer.
Lekki, J., S.A. RUBERG, C. Binding, R. Anderson, and A. VANDER WOUDE. Airborne hyperspectral and satellite imaging of harmful algal blooms in the Great Lakes Region: Successes in sensing algal blooms. Journal of Great Lakes Research 45(3):405-412 (DOI:10.1016/j.jglr.2019.03.014) (2019).
Harmful algal blooms have become a more significant issue in recent years in many lakes and rivers, and it is a particularly significant issue in the western basin of Lake Erie. In response, several research organizations in the United States and Canada have increased their efforts to improve capabilities for the remote sensing of harmful algal blooms. Efforts are underway to improve the ability to monitor, assess and study harmful algal blooms using various remote sensing platforms. Research into improvements in remote sensing platforms and algorithms provide powerful new tools to study and understand spatial and temporal aspects of harmful algal blooms. These developing tools will also help stakeholders to assess the efficacy of harmful algal bloom mitigation efforts into the future. In this commentary we describe selected NASA, NOAA, and ECCC's ongoing research projects as well as brief descriptions on the overall goal and specific objectives of the programs. Specific results from these three agencies' investigations, including modeling efforts, are discussed in a number of papers found within a special section of this issue.
Linares, A., C.H. Wu, A. Bechle, E.J. ANDERSON, and D.A.R. Kristovich. Unexpected rip currents induced by a meteotsunami. Scientific Reports 9(Article number: 2105)(DOI:10.1038/s41598-019-38716-2) (2019). https://www.glerl.noaa.gov/pubs/fulltext/2019/20190013.pdf
A tragic drowning event occurred along southeastern beaches of Lake Michigan on a sunny and calm July 4, 2003, hours after a fast-moving convective storm had crossed the lake. Data forensics indicates that a moderate-height (~0.3 m) meteotsunami was generated by the fast-moving storm impacting the eastern coast of the lake. Detailed Nearshore Area (DNA) modeling forensics on a high-resolution spatial O(1 m) grid reveals that the meteotsunami wave generated unexpected rip currents, changing the nearshore condition from calm to hazardous in just a few minutes and lasting for several hours after the storm. Cross-comparison of rip current incidents and meteotsunami occurrence databases suggests that meteotsunamis present severe water safety hazards and high risks, more frequently than previously recognized. Overall, meteorological tsunamis are revealed as a new generation mechanism of rip currents, thus posing an unexpected beach hazard that, to date, has been ignored.
Marino, J.A., S.D. Peacor, D.B. Bunnell, H.A. VANDERPLOEG, S.A. POTHOVEN, A.K. ELGIN, J.R. Bence, J. Jiao, and E.L. Ionides. Evaluating consumptive and nonconsumptive predator effects on prey density using field times series data. Ecology 100(3)(DOI:10.1002/ecy.2583) (2019). https://www.glerl.noaa.gov/pubs/fulltext/2019/20190015.pdf
Determining the degree to which predation affects prey abundance in natural communities constitutes a key goal of ecological research. Predators can affect prey through both consumptive effects (CEs) and nonconsumptive effects (NCEs), although the contributions of each mechanism to the density of prey populations remain largely hypothetical in most systems. Common statistical methods applied to time series data cannot elucidate the mechanisms responsible for hypothesized predator effects on prey density (e.g., differentiate CEs from NCEs), nor provide parameters for predictive models. State space models (SSMs) applied to time series data offer a way to meet these goals. Here, we employ SSMs to assess effects of an invasive predatory zooplankter, Bythotrephes longimanus, on an important prey species, Daphnia mendotae, in Lake Michigan. We fit mechanistic models in a SSM framework to seasonal time series (1994‐2012) using a recently developed, maximum likelihood‐based optimization method, iterated filtering, which can overcome challenges in ecological data (e.g. nonlinearities, measurement error, and irregular sampling intervals). Our results indicate that B. longimanus strongly influences D. mendotae dynamics, with mean annual peak densities of B. longimanus observed in Lake Michigan estimated to cause a 61% reduction in D. mendotae population growth rate and a 59% reduction in peak biomass density. Further, the observed B. longimanus effect is most consistent with an NCE via reduced birth rates. The SSM approach also provided estimates for key biological parameters (e.g., demographic rates) and the contribution of dynamic stochasticity and measurement error. Our study therefore provides evidence derived directly from survey data that the invasive zooplankter B. longimanus is affecting zooplankton demographics and offer parameter estimates needed to inform predictive models that explore the effect of B. longimanus under different scenarios such as climate change.
MASON, L.A., A.D. GRONEWOLD, M. Laitta, D. Gochis, K. Sampson, L. Read, E. Klyszejko, J. Kwan, L.M. Fry, K. Jones, P. Steeves, A. Pietroniro, and M. Major. A new transboundary hydrographic dataset for advancing regional hydrological modeling and water resources management. Journal of Water Resources Planning and Management 145(6)(DOI:10.1061/(ASCE)WR.1943-5452.0001073) (2019).
The authors document the development and testing of a new suite of hydrologic and hydraulic data for the customization of the new National Water Model (NWM) to the Great Lakes basin. The NWM was recently (August 2016) deployed operationally across the United States, including extensions across the international basins of the Columbia and Rio Grande Rivers. In its current configuration the NWM does not extend across the entire Great Lakes basin due to the challenges of reconciling data discontinuities along the United States–Canada border. The new hydrographic data set was developed by harmonizing data from existing sources across the Great Lakes basin, and by leveraging a strong binational partnership between US and Canadian federal agencies and research institutions. The completed hydrographic data set allows the NWM to be customized to the Great Lakes basin, and to be applied to water resources management problems including differentiating drivers behind long-term changes in Great Lakes water levels, forecasting water supplies for regional hydropower management, and understanding the physical processes along the Great Lakes coastline that govern the fate and transport of waterborne pollutants.
Merzel, R.L., L. Purser, T.L. Soucy, M. Olszewski, I. Colon-Bernal, M.B. Duhaime, A.K. ELGIN, and M.M. Banaszak Holl. Uptake and Retention of Nanoplastics in Quagga Mussels. Global Challenges (DOI:10.1002/gch2.201800104) (2019). https://www.glerl.noaa.gov/pubs/fulltext/2019/20190026.pdf (IN PRESS)
Here, a set of experiments to assess the feasibility of using an invasive and widespread freshwater mussel (Dreissena rostrformis bugensis) as a sentinel species for nanoplastic detection is reported. Under laboratory experimental conditions, mussels ingest and retain fluorescent polystyrene (PS) beads with carboxylic acid (COOH) termination over a size range of 200–2000 nm. The number of beads the mussels ingested is quantified using fluorescence spectroscopy and the location of the beads in the mussels is imaged using fluorescence microscopy. PS beads of similar size (1000–2000 nm) to mussels' preferred food are trafficked in the ciliated food grooves of the gills. Beads of all sizes are observed in the mussels' digestive tracts, indicating that the mussels do not efficiently reject the beads as unwanted foreign material, regardless of size. Fluorescence microscopy shows all sizes of beads are concentrated in the siphons and are retained there for longer than one month postexposure. Combined atomic force microscopy–infrared spectroscopy and photothermal infrared spectroscopy are used to locate, image, and chemically identify the beads in the mussel siphons. In sum, these experiments demonstrate the potential for using mussels, specifically their siphons, to monitor environmental accumulation of aquatic nanoplastics.
Moore, T.S., J.H. Churnside, J.M. Sullivan, M.S. Twardowski, A.R. Nayak, M.N. McFarland, N.D. Stockley, R.W. Gould, T.H. JOHENGEN, and S.A. RUBERG. Vertical distributions of blooming cyanobacteria populations in a freshwater lake from LIDAR observations. Remote Sensing of Environment 225:347-367 (DOI:10.1016/j.rse.2019.02.025) (2019).
The vertical distributions of freshwater cyanobacteria populations are important to plankton community structure, ecology and for influencing water column optical properties relevant to remote sensing. In August of 2014, we examined the vertical structure of a cyanobacteria bloom across the western basin of Lake Erie with new technologies, including LIDAR and a digital holographic system. In addition, vertical profiles of environmental and optical properties were made. The active LIDAR penetrated the water column, and provided a detailed picture of the particle distribution for the whole water column. The holographic system provided digital images processed for particle size, count and identification of Microcystis and Planktothrix - the two main cyanobacteria genera that were present. The correlations between the LIDAR backscatter intensity and the cyanobacteria cell counts from holography averaged to 0.53 and ranged from −0.13 to 0.96 based on nearest matchups. The vertical structure of the overall cyanobacteria population was influenced by wind speed, and to a lesser degree the solar heating of surface waters. On a more detailed level, Microcystis populations were consistently nearer to the surface relative to Planktothrix. Pigments from surface samples revealed a higher degree of photoprotection for Planktothrix-dominated communities. The vertical distributions of the cyanobacteria genera were related to light intensity in the water column and known tolerances and/or preferences for each genus. Vertical profiles of optical properties supported the patterns seen in the LIDAR and holographic data, and had direct implications on the exiting light field. These combined data provide a unique view into the natural variations in spatial (vertical and horizontal) distribution patterns of cyanobacteria and resulting impacts on remote sensing detection and associated interpretations, and demonstrate the potential for these technologies to observe cyanobacteria in lake environments.
Moore, T.C., H. Feng, S.A. RUBERG, K.S. BEADLE, S.A. CONSTANT, R. MILLER, R.W. MUZZI, T.H. JOHENGEN, P.M. DiGiacomo, V.P. Lance, B.N. Holben, and M. Wang. SeaPRISM observations in the western basin of Lake Erie in the summer of 2016. Journal of Great Lakes Research 45(3):547-555 (DOI:10.1016/j.jglr.2018.10.008) (2019).
In the summer of 2016, a robotic sun photometer called the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) Photometer Revision for Incident Surface Measurements (SeaPRISM), was deployed at a Coast Guard channel marker in western Lake Erie, measuring atmospheric properties and spectral water-leaving radiance. The instrument was deployed by the National Oceanic and Atmospheric Administration (NOAA) to support remote sensing validation and harmful algal bloom (HAB) satellite products. The Lake Erie SeaPRISM is also part of the international federated AERONET program maintained by the National Aeronautics and Space Administration (NASA), and more specifically is part of the AERONET Ocean Color (AERNOET-OC) network. The main purpose of this component of AERONET is specific to calibration/validation efforts for ocean color. The AERONET-OC network currently consists of 23 field radiometers at aquatic sites around the world. The Lake Erie site is the second freshwater lake location world-wide after the Palgrunden site in Sweden. During its operating period from mid-July to early September 2016, various environmental conditions were observed including a cyanobacteria bloom. Water-leaving radiance observations were generated on 43 out of 51 days, and varied by a factor of five. The variability in the above-water radiometry tracked that of in-water measurements made by a nearby buoy. During this brief operating window, satellite matchups were generated for several satellites. We highlight the first year's observations in relation to remote sensing validation and report on observations of cyanobacteria blooms from hourly to weekly time scales.
Newell, S.E., T.W. Davis, T.H. JOHENGEN, D.C. GOSSIAUX, A. BURTNER, D. PALLADINO, and M.J. McCarthy. Reduced forms of nitrogen are a driver of non-nitrogen-fixing harmful cyanobacterial blooms and toxicity in Lake Erie. Harmful Algae 81:86-93 (DOI:10.1016/j.hal.2018.11.003) (2019). https://www.glerl.noaa.gov/pubs/fulltext/2019/20190010.pdf
Western Lake Erie (WLE) experiences anthropogenic eutrophication and annual, toxic cyanobacterial blooms of non-nitrogen (N) fixing Microcystis. Numerous studies have shown that bloom biomass is correlated with an increased proportion of soluble reactive phosphorus loading from the Maumee River. Long term monitoring shows that the proportion of the annual Maumee River N load of non-nitrate N, or total Kjeldahl nitrogen (TKN), has also increased significantly (Spearman's ρ = 0.68, p = 0.001) over the last few decades and is also significantly correlated to cyanobacterial bloom biomass (Spearman's ρ = 0.64, p = 0.003). The ratio of chemically reduced N to oxidized N (TKN:NO3) concentrations was also compared to extracted chlorophyll and phycocyanin concentrations from all weekly sampling stations within WLE from 2009 to 2015. Both chlorophyll (Spearman's ρ = 0.657, p < 0.0001) and phycocyanin (Spearman's ρ = 0.714, p < 0.0001) were significantly correlated with TKN:NO3. This correlation between the increasing fraction of chemically reduced N from the Maumee River and increasing bloom biomass demonstrates the urgent need to control N loading, in addition to current P load reductions, to WLE and similar systems impacted by non-N-fixing, toxin-producing cyanobacteria.
POTHOVEN, S.A., and H.A. VANDERPLOEG. Variable demographics and consumption requirements of Bythotrephes longimanus (Crustacea, Cercopagididae) along a nearshore to offshore gradient in Lake Michigan. Hydrobiologia 830(1):63-75 (DOI:10.1007/s10750-018-3850-2) (2019).
Demographic differences in Bythotrephes longimanus populations are often used to infer the prevalence of different environmental conditions that regulate their population. We collected seasonal data on Bythotrephes abundance and life history at a nearshore (15 m), transitional (45 m) and offshore site (110 m) in Lake Michigan during 2007–2016. Due to higher fish predation requirements and the small size of zooplankton prey at the nearshore site, we expected life-history attributes of Bythotrephes would differ compared to the deeper sites, but body and spine length, percent of growth allocated to the spine, and brood size were similar among depths. Owing to higher abundances in the offshore, the ratio of consumption requirements: prey production (C:P) was relatively high throughout the growing season at the deepest site compared to the two shallower sites, where C:P was generally only high in the fall. However, reproductive characteristics of Bythotrephes at the offshore site did not reflect a food-limited population compared to the other two sites. Rather the proportion of barren females was higher at the nearshore site than those at the deeper sites, leading to much lower birth rates and abundance of Bythotrephes at the shallow site compared to the deeper sites.
POTHOVEN, S.A., and A.K. ELGIN. Dreissenid veliger dynamics along a nearshore to offshore transect in Lake Michigan. Journal of Great Lakes Research 45(2):300-306 (DOI:10.1016/j.jglr.2019.01.001) (2019).
Dreissenid mussel veligers compose a substantial component of pelagic biomass in the Great Lakes, yet their dynamics are poorly understood. To evaluate seasonal, spatial, and inter-annual variation in veliger density, we used a 64-μm mesh plankton net (2008, 2013–2016) and a 153-μm mesh plankton net (2007–2016) to collect dreissenid veligers at nearshore (15–25 m depth), transitional (45 m) and offshore (93–110 m) sites in southeast Lake Michigan during March–December. We also evaluated trends in density of recently settled mussels relative to veliger abundance and the density of the standing stock of adult mussels. Veliger density peaked during both summer and fall at all sites, but peak densities in summer were generally higher nearshore, whereas peak densities in the fall were generally higher offshore. The density of veligers in the 153-μm net was overall 28% of that in the 64-μm net, but there was high variability in this comparison among months. Smaller veligers were much more abundant in the 64-μm net, but there was little difference in the size distribution and abundance between nets for the 210–300 μm size classes. Thus, the 153-μm net could still be a useful tool for assessing density trends of larger veligers just prior to their settlement. Newly settled mussels (≤2 mm) were most abundant in summer or fall at the nearshore and offshore sites but were nearly absent at the transitional site despite the high density of veligers there. Factors other than veliger density must play an important role in mussel recruitment.
Qian, S.S., C.A. STOW, F.A. Nojavan, J. Stachelek, Y.K. Cha, I.M. Alameddine, and P.A. Soranno. The implications of Simpson's paradox for cross-scale inference among lakes. Water Research 163(DOI:10.1016/j.watres.2019.114855) (2019). (IN PRESS)
Using cross-sectional data for making ecological inference started as a practical means of pooling data to enable meaningful empirical model development. For example, limnologists routinely use sample averages from numerous individual lakes to examine patterns across lakes. The basic assumption behind the use of cross-lake data is often that responses within and across lakes are identical. As data from multiple study units across a wide spatiotemporal scale are increasingly accessible for researchers, an assessment of this assumption is now feasible. In this study, we demonstrate that this assumption is usually unjustified, due largely to a statistical phenomenon known as the Simpson's paradox. Through comparisons of a commonly used empirical model of the effect of nutrients on algal growth developed using several data sets, we discuss the cognitive importance of distinguishing factors affecting lake eutrophication operating at different spatial and temporal scales. Our study proposes the use of the Bayesian hierarchical modeling approach to properly structure the data analysis when data from multiple lakes are employed.
Sayers, M.J., A.G. Grimm, R.A. Shuchman, K.R. Bosse, G.L. Fahnenstiel, S.A. RUBERG, and G.A. LESHKEVICH. Satellite monitoring of harmful algal blooms in the Western Basin of Lake Erie: A 20-year time-series. Journal of Great Lakes Research 45(3):508-521 (DOI:10.1016/j.jglr.2019.01.005) (2019).
Blooms of harmful cyanobacteria (cyanoHABs) have occurred on an annual basis in western Lake Erie for more than a decade. Previously, we developed and validated an algorithm to map the extent of the submerged and surface scum components of cyanoHABs using MODIS ocean-color satellite data. The algorithm maps submerged cyanoHABs by identifying high chlorophyll concentrations (>18 mg/m3) combined with water temperature >20 °C, while cyanoHABs surface scums are mapped using near-infrared reflectance values. Here, we adapted this algorithm for the SeaWiFS sensor to map the annual areal extents of cyanoHABs in the Western Basin of Lake Erie for the 20-year period from 1998 to 2017. The resulting classified maps were validated by comparison with historical in situ measurements, exhibiting good agreement (81% accuracy). Trends in the annual mean and maximum total submerged and surface scum extents demonstrated significant positive increases from 1998 to 2017. There was also an apparent 76% increase in year-to-year variability of mean annual extent between the 1998–2010 and 2011–2017 periods. The 1998–2017 time-series was also compared with several different river discharge nutrient loading metrics to assess the ability to predict annual cyanoHAB extents. The prediction models displayed significant relationships between spring discharge and cyanoHAB area; however, substantial variance remained unexplained due in part to the presence of very large blooms occurring in 2013 and 2015. This new multi-sensor time-series and associated statistics extend the current understanding of the extent, location, duration, and temporal patterns of cyanoHABs in western Lake Erie.
Sayers, M.J., K.R. Bosse, R.A. Schuchman, S.A. RUBERG, G.L. Fahnenstiel, G.A. LESHKEVICH, D.G. STUART, T.H. JOHENGEN, A.M. BURTNER, and D. PALLADINO. Spatial and temporal variability of inherent and apparent optical properties in western Lake Erie: Implications for water quality remote sensing. Journal of Great Lakes Research 45(3):490-507 (DOI:10.1016/j.jglr.2019.03.011) (2019). https://www.glerl.noaa.gov/pubs/fulltext/2019/20190019.pdf
Lake Erie has experienced dramatic changes in water quality over the past several decades requiring extensive monitoring to assess effectiveness of adaptive management strategies. Remote sensing offers a unique potential to provide synoptic monitoring at daily time scales complementing in-situ sampling activities occurring in Lake Erie. Bio-optical remote sensing algorithms require knowledge about the inherent optical properties (IOPs) of the water for parameterization to produce robust water quality products. This study reports new IOP and apparent optical property (AOP) datasets for western Lake Erie that encapsulate the May–October period for 2015 and 2016 at weekly sampling intervals. Previously reported IOP and AOP observations have been temporally limited and have not assessed statistical differences between IOPs over spatial and temporal gradients. The objective of this study is to assess trends in IOPs over variable spatial and temporal scales. Large spatio-temporal variability in IOPs was observed between 2015 and 2016 likely due to the difference in the extent and duration of mid-summer cyanobacteria blooms. Differences in the seasonal trends of the specific phytoplankton absorption coefficient between 2015 and 2016 suggest differing algal assemblages between the years. Other IOP variables, including chromophoric, dissolved organic matter (CDOM) and beam attenuation spectral slopes, suggest variability is influenced by river discharge and sediment re-suspension. The datasets presented in this study show how these IOPs and AOPs change over a season and between years, and are useful in advancing the applicability and robustness of remote sensing methods to retrieve water quality information in western Lake Erie.
Shuchman, R.A., C. Binding, G.A. LESHKEVICH, and J.D. Ortiz. Remote sensing of harmful algal blooms (HABs) in Lake Erie and other surrounding inland waters: Foreword to special section. Journal of Great Lakes Research 45(3):403-404 (DOI:10.1016/j.jglr.2019.03.015) (2019).
SMITH, J.P., E.K. LOWER, F.A. MARTINEZ, C.M. Riseng, L.A. Mason, E.S. RUTHERFORD, M. Neilson, P. Fuller, K.E. Wehrly, and R.A. STURTEVANT. Interactive mapping of nonindigenous species in the Laurentian Great Lakes. Management of Biological Invasions 10(1):192-199 (DOI:10.3391/mbi.2019.10.1.12 ) (2019). https://www.glerl.noaa.gov/pubs/fulltext/2019/20190014.pdf
Nonindigenous species pose significant risks to the health and integrity of ecosystems around the world. Tracking and communicating the spread of these species has been of interest to ecologists and environmental managers for many years, particularly in the bi-national Laurentian Great Lakes of North America. In this paper, we introduce the Great Lakes Aquatic Nonindigenous Species Information System (GLANSIS) Map Explorer. The Map Explorer provides access to records of documented nonindigenous species and their spatial distributions. Users may view the distributions of well-known nonindigenous species (such as zebra mussels) as well as perform custom queries. Additional map layers allow users to compare the distribution of nonindigenous species to environmental conditions. This tool serves to communicate knowledge to diverse stakeholder groups and to enable further in-depth research on nonindigenous species.
VANDER WOUDE, A., S.A. RUBERG, T.H. JOHENGEN, R. MILLER, and D. STUART. Spatial and temporal scales of variability of cyanobacteria harmful algal blooms from NOAA GLERL airborne hyperspectral imagery. Journal of Great Lakes Research 45(3):536-546 (DOI:10.1016/j.jglr.2019.02.006) (2019). https://www.glerl.noaa.gov/pubs/fulltext/2019/20190020.pdf
NOAA GLERL has routinely flown a hyperspectral imager to detect cyanobacteria harmful algal blooms (cyanoHABs) over the Great Lakes since 2015. Three consecutive years of hyperspectral imagery over the Great Lakes warn drinking water intake managers of the presence of cyanoHABs. Western basin imagery of Lake Erie contributes to a weekly report to the Ohio Environmental Protection Agency using the cyanobacteria index (CI) as an indicator of the presence of cyanoHABs. The CI is also used for the weekly NOAA NCCOS cyanoHAB Lake Erie bulletin applied to satellite data. To date, there has not been a sensor comparison to look at the variability between the satellite and hyperspectral imagery on a pixel-by-pixel basis, as well as a time scale comparison between measurements from buoys and shipboard surveys. The spatial scale is a measure of size of a cyanobacteria bloom on a scale of meters to kilometers. The change in the spatial scale or spatial variability has been quantified from satellite and airborne imagery using a decorrelation scale analysis to find the point at which the values are not changing or are not correlated with each other. The decorrelation scales were also applied to the buoy and shipboard survey data to look at temporal scales or changes in time on hourly to daytime scales for blue-green algae, chlorophyll and temperature. These scales are valuable for ecosystem modelers and for those initiating sampling efforts to optimize sampling plans and to infer a potential mechanism in an observational study from a synoptic viewpoint.
ZHANG, H., E.S. RUTHERFORD, D.M. MASON, M.E. Wittman, D.M. Lodge, X. Zhu, T.B. Johnson, and A. Tucker. Modeling potential impacts of three benthic invasive species on the Lake Erie food web. Biological Invasions 21(5):1697-1719 (DOI:10.1007/s10530-019-01929-7) (2019). https://www.glerl.noaa.gov/pubs/fulltext/2019/20190012.pdf
Assessing the potential for aquatic invasive species (AIS) to impact ecosystem function and services is an important component of ecological risk assessment. This study focuses on quantifying changes in biomass of food web groups in response to changes in AIS biomass as a function of variable AIS prey vulnerabilities (i.e. food availability) and AIS vulnerabilities to predators (i.e. predation pressure). We modified an existing Lake Erie food web model to assess the potential food web impacts of three benthic AIS (Eurasian ruffe Gymnocephalus cernua, killer shrimp Dikerogammarus villosus, and golden mussel Limnoperna fortunei) that may invade Lake Erie in the near future. Simulated biomass of golden mussels was most affected by bottom-up control, while killer shrimp and ruffe were affected by both top-down and bottom-up controls. AIS food web impacts showed both monotonic and non-monotonic responses to AIS biomass. Impacts from ruffe were highest when their biomass was high, while killer shrimp and golden mussels had maximal impacts at intermediate biomass levels on some food web groups. Our results suggest that golden mussels, which can feed at a lower trophic level and have fewer predators than ruffe or killer shrimp, may reach much higher equilibrium biomass under some scenarios and affect a broader range of food web groups. While all three species may induce negative effects if introduced to Lake Erie, golden mussels may pose the highest risk of impact for Lake Erie’s food web.
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