Long-term dynamics of Lake Erie benthos: One lake, three distinct communities

Karatayev, Alexander Y.; Burlakova, Lyubov E.; Hrycik, Allison R.; Daniel, Susan E.; Mehler, Knut; Hinchey, Elizabeth K.; Dermott, R.; Griffiths, Ronald W.

doi:10.1016/j.jglr.2022.09.006

Cited by 12 publications

(7 citation statements)

References 98 publications

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“…In the deep areas of Lake Erie's central basin, hypoxia separates zooplankton and benthos prey from their predators, while in the nearshore or marginal areas of hypoxic waters hypoxia may increase consumption of zooplankton and benthos (Roberts et al, 2009; Pothoven et al, 2009; Vanderploeg et al, 2009). In addition, recent reports of Dreissena biomass suggest we have overestimated biomass of Dreissena (Karateyev et al, 2021), and thus may have underestimated response of the planktonic foodweb to hypoxia. In addition, hypoxia causes changes in physiology, behavior and distribution of mobile organisms and increases energy costs in adapting to suboptimal habitats (Randall, 1982, Herbert and Steffensen, 2005, Craig and Crowder, 2005, Petersen and Pihl, 1995), which are affected by other environmental factors as well (e.g.…”

Section: Discussionmentioning

confidence: 79%

Modelling effects of nutrients and hypoxia on Lake Erie's central basin foodweb

Zhang,

Mason,

Rutherford

et al. 2023

Aquatic Ecosystem Health &Amp; Management

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Hypoxia (dissolved oxygen <2 mg l-1) has long been a prevalent feature of the central basin of Lake Erie. Studies of the sublethal impacts of hypoxia on fishes have focused on individual species feeding rates, behavior and spatial distributions over short time periods, but the long-term effects on the fish community and its foodweb are poorly known. Sublethal effects of hypoxia on fish include: interrupting their vertical migration, displacing them from bottom habitats either up into the water column or away from the hypoxic zones, altering predator-prey relationships by segregation or aggregation of predators and their prey, and increasing fishing mortality by concentrating fish at the edge of hypoxic zones. We used the Ecopath with Ecosim foodweb model to investigate the singular and combined effects of nutrient concentration and hypoxia on the foodweb structure in Lake Erie's central basin. Our model tracked predator-prey interactions and population biomass of 33 model groups. We balanced the model in Ecopath and calibrated it against biomass time series data from 1996 up to 2020. Model simulations were run with varied nutrients (from 20 to 220% of the previous nutrient loading target level) and hypoxia (none, average summer value from 1996 to 2017, historical high) as forcing variables on the foodweb. Model results suggested that nutrients had positive, non-linear effects on foodweb biomass, while hypoxia decreased biomass of benthos, benthivorous fishes, and some omnivores, but increased biomass of plankton and planktivorous fishes. Nutrient effects were greater than hypoxia effects on the foodweb. Results of the foodweb model analysis may inform water quality and fisheries management strategies for Lake Erie's central basin.

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Section: Discussionmentioning

confidence: 79%

Modelling effects of nutrients and hypoxia on Lake Erie's central basin foodweb

Zhang,

Mason,

Rutherford

et al. 2023

Aquatic Ecosystem Health &Amp; Management

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“…measured in this study were similar to those measured in 2000 (Patterson et al 2005), 2004, and 2010 (J. Ciborowski et al, University of Windsor, unpubl. ), and 2019 (Karatayev et al 2022). Patterson et al (2005) reported that lakewide average densities were around 600 individuals m −2 .…”

Section: Discussionmentioning

confidence: 99%

“…Oligochaete densities are also similar to past reports in 2004 (J. Ciborowski et al, University of Windsor, unpubl. ), and 2019 (Karatayev et al 2022).…”

Section: Discussionmentioning

confidence: 99%

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The influence of environmental parameters on spatial variation in zoobenthic density and stable isotopes (δ¹³C, δ¹⁵N, and δ³⁴S) within a large lake

Heuvel,

Zhao,

Ciborowski

et al. 2023

Limnology & Oceanography

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The use of baselines in stable isotope studies to interpret food web structure is essential, but baseline isotope values are often assumed to be spatially homogeneous, even in large aquatic ecosystems. To test this assumption in large lakes, we quantified spatial variation in δ13C, δ15N (deposit‐feeding Oligochaeta and filter‐feeding Dreissena spp.), and δ34S (Dreissena spp. only) and density in Lake Erie between 2014 and 2016. Lake Erie's three distinct basins differ in size, bathymetry, and nutrient loading, making it an excellent system for exploring spatial variation in stable isotopes of baseline organisms. Dreissena spp. densities were highest in the western and lowest in the seasonally hypoxic central basin, while Oligochaeta densities were relatively consistent throughout Lake Erie. Values of δ13C, δ15N, and δ34S exhibited distinct spatial trends that were not related to population densities but followed the west to east direction of water flow within the lake. For both taxa, δ13C was lower in the deeper, oligotrophic east basin than the shallow, mesotrophic west basin, and δ15N and δ34S increased from west to east. Spatial patterns of low δ34S in Dreissena spp. in the western and central basins were likely related to hypoxia, whereas patterns of δ15N in both taxa were probably related to the greater influence of agricultural land uses in the western basin. Spatial trends of stable isotopes in large lake zoobenthos are driven by complex interactions of environmental gradients, which could introduce bias in evaluations of trophic structures within aquatic ecosystems that use stable isotopes.

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“…Historical eutrophication from runoff and pollution led to detrimental algal blooms, affecting water quality and oxygen levels. Recent studies on Lake Erie have shown the prominent role that DO plays in the dynamics of Lake Erie's benthic community [1,8,9]. These studies identify hypoxia, or low levels of DO, as a major factor influencing the composition and health of benthic communities, especially in the central basin of Lake Erie [1,9].…”

Section: Introductionmentioning

confidence: 99%

Dissolved Oxygen Forecasting for Lake Erie’s Central Basin Using Hybrid Long Short-Term Memory and Gated Recurrent Unit Networks

Pan,

Zhang,

Deng

et al. 2024

Water

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Dissolved oxygen (DO) concentration is a pivotal determinant of water quality in freshwater lake ecosystems. However, rapid population growth and discharge of polluted wastewater, urban stormwater runoff, and agricultural non-point source pollution runoff have triggered a significant decline in DO levels in Lake Erie and other freshwater lakes located in populated temperate regions of the globe. Over eleven million people rely on Lake Erie, which has been adversely impacted by anthropogenic stressors resulting in deficient DO concentrations near the bottom of Lake Erie’s Central Basin for extended periods. In the past, hybrid long short-term memory (LSTM) models have been successfully used for the time-series forecasting of water quality in rivers and ponds. However, the prediction errors tend to grow significantly with the forecasting period. Therefore, this research aimed to improve the accuracy of DO forecasting models by taking advantage of Lake Erie’s real-time water quality (water temperature and DO concentration) monitoring network to establish temporal and spatial links between adjacent monitoring stations. We developed hybrid LSTM models that combine LSTM, convolutional neuron network LSTM (CNN-LSTM), hybrid CNN with gated recurrent unit (CNN-GRU) models, and convolutional LSTM (ConvLSTM) to forecast near-bottom DO concentrations in Lake Erie’s Central Basin. These hybrid LSTM models improve their capacity to handle complicated datasets with spatial and temporal variability. These models can serve as accurate and reliable tools for forecasting DO concentrations in freshwater lakes to help environmental protection agencies better access and manage the health of these vital ecosystems. Following analysis of a 21-site Lake Erie dataset for 2020 and 2021, the ConvLSTM model emerged as the most accurate and reliable, boasting an MSE of 0.51 mg/L, MAE of 0.42 mg/L, and an R-squared of 0.95 over the 12 h prediction range. The model foresees future hypoxia in Lake Erie. Notably, the temperature near site 713 holds significance for Central Basin DO forecasting in Lake Erie, as indicated by outcomes derived from the Shapley additive explanations (SHAP).

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Long-term dynamics of Lake Erie benthos: One lake, three distinct communities

Cited by 12 publications

References 98 publications

Modelling effects of nutrients and hypoxia on Lake Erie's central basin foodweb

Modelling effects of nutrients and hypoxia on Lake Erie's central basin foodweb

The influence of environmental parameters on spatial variation in zoobenthic density and stable isotopes (δ¹³C, δ¹⁵N, and δ³⁴S) within a large lake

Dissolved Oxygen Forecasting for Lake Erie’s Central Basin Using Hybrid Long Short-Term Memory and Gated Recurrent Unit Networks

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Long-term dynamics of Lake Erie benthos: One lake, three distinct communities

Cited by 12 publications

References 98 publications

Modelling effects of nutrients and hypoxia on Lake Erie's central basin foodweb

Modelling effects of nutrients and hypoxia on Lake Erie's central basin foodweb

The influence of environmental parameters on spatial variation in zoobenthic density and stable isotopes (δ13C, δ15N, and δ34S) within a large lake

Dissolved Oxygen Forecasting for Lake Erie’s Central Basin Using Hybrid Long Short-Term Memory and Gated Recurrent Unit Networks

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The influence of environmental parameters on spatial variation in zoobenthic density and stable isotopes (δ¹³C, δ¹⁵N, and δ³⁴S) within a large lake