Ecology of Lake Erie – Chemistry, plankton & planktivory: A synthesis
Bibliographic record
Abstract
As with other large lake ecosystems worldwide, Lake Erie can be considered a moving target for management, owing to physicochemical and biological changes brought on by anthropogenic change, both planned (e.g. nutrient and fisheries management) and unplanned (e.g. climate change, invasive species, modified land-use activities). These changes have challenged efforts to conserve biodiversity, sustain exploitable resources, and maintain the integrity of services valued by society both within the Lake Erie basin and (Fraker et al., 2022; Fussell et al., 2016; Sinclair et al., 2021; Sinclair et al., 2023) and outside of it (Allan et al., 2013; Jenny et al., 2020; Sterner et al., 2017). Some of these changes and their ramifications for management were documented in the first of four AEHM special issues devoted to the Lake Erie ecosystem (the fourth issue of 2023, volume 26, issue 4; see overview by Ludsin et al., 2023). That special issue focused explicitly on nutrient inputs and availability in Lake Erie and the lower food web, including planktonic and benthic microbial (including cyanobacteria), algal, and invasive dreissenid mussel communities.Similar to the previous Lake Erie special issue, this second one has focused on documenting the state of the lake, providing ecological understanding that could potentially benefit management. While some overlap in topics exists between issues, the studies conducted herein were completely independent of those previous investigations and offer unique insights. Specifically, the contributions to this current issue center on: 1) dynamics of water chemistry in Lake Erie's central basin (i.e. bottom hypoxia; Ackerman et al., 2024) and western basin (i.e. mercury; Starr et al., 2024); 2) changes in primary producer biomass (Lesht et al., 2024), cyanotoxins (i.e. microcystin; Zastepa et al., 2024), and water quality (e.g. water clarity and dissolved nutrients; Howell et al., 2024); and 3) larval fish foraging (i.e. Lake Whitefish; Coregonus clupeaformis; Amidon et al., 2024) and community structure and phenology (DeBruyne et al., 2024). Below we summarize the major findings of these papers and offer a synthetic perspective on the value of this research for understanding the state of Lake Erie and enhancing management.Lake Erie has a long history of pollution, including from nutrients (Kane et al., 2014; Sinclair et al., 2023; Vollenweider et al., 1974), organochlorine contaminants (e.g. PCBs; Frank et al., 1997; Marvin et al., 2004; Salamova et al., 2013), and heavy metals (e.g. mercury; Bhavsar et al., 2010; Pillay et al., 1972). While legislation and abatement programs enacted as part of the Great Lakes Water Quality Agreement have at least partially mitigated these forms of pollution, each remains a concern to management agencies and is routinely monitored. Most conspicuously, non-point source nutrient pollution has re-emerged as a major problem since the early 2000s, which has caused the magnitude, duration, and extant of both harmful cyanobacteria blooms (cyanoHABs) and bottom hypoxia to increase in the western and central basins of Lake Erie, respectively (Scavia et al., 2014; Watson et al., 2016). In turn, effort has continued to understand the causes of Lake Erie's most recent bout with eutrophication (e.g. Bocaniov et al., 2023; Hounshell et al., 2023; Johnson et al., 2023; Scavia et al., 2023), as well as its consequences for the lake's food webs and the fisheries that they support (Briland et al., 2020; Scavia et al., 2014; Watson et al., 2016; Zhang et al., 2023). Similar to Lake Erie's first battle with eutrophication during the 1960s – 1970s, management efforts aimed at reducing organic and trace-metal pollution proved successful, at least through the end of the 20th Century (Marvin et al., 2004; Painter et al., 2001). However, methyl mercury concentrations have increased at least through the early part of the 21st Century (Bhavsar et al., 2010; Zhou et al., 2017). The status of mercury contamination since this time remains uncertain, however, which is an important information gap, given that mercury can biomagnify in aquatic organisms that might be consumed by humans (e.g. fish; Azim et al., 2011; Zhou et al., 2017). The first two papers of this special issue provide an update on the pollution-induced water chemistry in Lake Erie, including dissolved oxygen (Ackerman et al., 2024) and mercury (Starr et al., 2024) fluxes.Ackerman et al. (2024) examined the seasonal chronology of hypoxia in central Lake Erie during 2008 and 2009. Specifically, these authors deployed instruments on the lakebed along a 26-km east-west transect that spanned the hypoxic edge. By taking dissolved oxygen, temperature, and lakebed turbidity measurements along this transect, Ackerman et al. could evaluate how dissolved oxygen concentrations varied across timescales ranging from minutes to seasons, as well as explore how intra- and inter-basin sources of oxygen demand contribute to hypoxia. Using spectral analysis to analyze their data, Ackerman et al. learned that dissolved oxygen levels varied most due to variation in seasonal stratification, with it varying next most at a periodicity of several days owing to episodic strong wind events. Spikes in turbidity at the lakebed, also stemming from episodic winds, were positively correlated with falling dissolved oxygen concentration, supporting the view that oxygen demand associated with suspended organic-rich sediment contributes to hypoxia. Ultimately, this study provides insights into the dynamic nature of dissolved oxygen in the hypolimnion, making the case that hypoxia is not a static event but instead is comprised of multiple events of varying duration and intensity over a season. These findings mesh with recent hypoxia research in Lake Erie (Kraus et al., 2015; Rowe et al., 2019), and support the notion that quantifying the causes of hypoxia and its consequences for biota is complex.While Ackerman et al. (2024) centered on factors that influence dissolved oxygen levels in central Lake Erie, Starr et al. (2024) measured multiple mercury metrics in the water column at numerous sites in the western basin of Lake Erie during 2018-2021. Their approach was unique for Lake Erie, given that most recent studies have measured mercury and methyl mercury concentrations in the sediments and or biota (e.g. Zhou et al., 2017). Similar to Ackerman et al.’s (2024) study of dissolved oxygen, Starr et al. (2024) found that water-column concentrations of total mercury and methyl mercury varied spatially, with their levels being highest near the Maumee River relative to the Detroit River and Sandusky Bay inlets. Starr et al.’s investigation also revealed that methyl mercury was released from sediments into the water column near the Maumee River, whereas an opposite pattern in net fluxes (into the sediments) was observed near the Detroit River and Sandusky Bay, indicating heterogeneity in the drivers of methyl mercury availability. Finally, while methyl mercury concentrations in the water column were shown to increase during the beginning of the 20th Century, possibly due to legacy sediment contaminants in western basin tributaries (Bhavsar et al., 2010), Starr et al. (2014) found a reduction in total mercury concentrations in the water column of approximately 3.3% per year. The authors attributed this decrease to state, provincial, and federal water and environmental regulations.Owing to its small size, shallowness, southern location, and vast agricultural watershed, Lake Erie has historically been more biologically productive across all trophic levels relative to the other Laurentian Great Lakes (Barbiero et al., 2019; Bunnell et al., 2014; Makarewicz and Bertram, 1991). In turn, Lake Erie has been more prone to water quality impairments such as hypoxia and cyanoHABs than the other lakes. For this reason, much effort has been spent on understanding primary producer dynamics (e.g. Conroy et al., 2005; Fitzpatrick et al., 2007; Reavie et al., 2014), as well as trying to delineate how invasive filter feeds like the Zebra Mussel (Dreissena polymorpha) and the Quagga Mussel (D. bugensis) influence the dynamics of nutrients, primary producers, and water clarity (Barbiero and Tuchman, 2004; Carter et al., 2023; North et al., 2012; Vanderploeg et al., 2023). Despite a wealth of research on these topics, information gaps abound. The next three papers in this special fill some of these gaps by quantifying primary production across the lake (Lesht et al., 2024), by describing spatial variation in cyanotoxins in western Lake Erie (Zastepa et al., 2024), and by monitoring the impacts of dreissenid mussels on water quality in the eastern basin (Howell et al., 2024). Below, we report on some key findings from these three studies.As with other north-temperature ecosystems, primary producers in Lake Erie show predictable seasonality (e.g. dense blooms of diatoms in spring followed by thick cyanobacteria blooms in summer; Barbiero et al., 2019; O'Donnell et al., 2023a), which can drive spatiotemporal variability in physicochemical conditions (e.g. bottom hypoxia; Carrick et al., 2005; Watson et al., 2016) and consumer biomass (e.g. Kovalenko et al., 2023). Although existing monitoring programs have successfully captured fluctuations in phytoplankton biomass, tracking rates of overall carbon fixation (i.e. photosynthesis) has fallen short due to methodological limitations. Absence of this crucial measurement has in turn limited our ability to quantify the relative importance each lake basin to lakewide primary production, and how such production has varied through time. During 2019, Lesht et al. (2024) used 13C uptake methods to compare seasonal estimates of primary production within each of Lake Erie's three lake basins (western, central, and eastern) to levels last made using radiocarbon 14C methods during the late 1990s. Lesht et al. found that areal primary production was highest in the central basin relative to the shallower western and deeper eastern basins. By contrast, the western basin had higher volumetric estimates of production and a shallower photic depth. While some evidence of photoinhibition existed across the lake, no indication of light or nutrient limitation was found, which seems plausible given that lake has become more eutrophic due to non-point source nutrient runoff (Kane et al., 2014; Scavia et al., 2014; Watson et al., 2016). Surprisingly, however, lakewide primary production estimates during 2019 were nearly half that of estimates during the 1990s. As such, these authors suggested the need for further comparisons of the two methods. Even so, this work represents an important baseline for future monitoring and a calibration for remote-sensing approaches.Similar to Lesht et al. (2024), Zastepa et al. (2024) sought to increase knowledge about the dynamics of primary producers. These authors, however, focused on the dynamics of cyanotoxins, reporting on findings from binational “HAB Grab” sampling that occurred in western Lake Erie during in 2017 and 2019. While most of the focus of cyanotoxins in Lake Erie has been on microcystins (e.g. Qian et al., 2021; Rinta-Kanto et al., 2009), Zastepa et al. (2024) measured not only microcystin but other cyanopeptides, including nodularin and a selection of anabaenopeptins, both of which can negatively impact the health of biota (Chen et al., 2021; Lenz et al., 2019). As might be expected given the heterogeneous nature of cyanoHABs in Lake Erie (Wynne and Stumpf, 2015), cyanotoxins were widely distributed in a spatially varied manner. Specifically, microcystin concentrations were highest on the south shore of the basin, with microcystin-RR, -LR, -YR being in the highest concentration of the 12 microcystins quantified. Anabaenopeptins were broadly detected with anabaenopeptin-F being the most widespread and in the highest concentration, followed by anabaenopeptin-B and -A. Anabaenopeptins were similarly distributed to microcystins with the exception that the highest concentrations of anabaenopeptins were found along the north shore of western Lake Erie. Given the prevalence of anabaenopeptins, which at times surpassed microcystin concentrations, Zastepa et al. (2024) point to the need expand cyanotoxin research to assess potential negative human and animal health effects.Phytoplankton also is a focus of the last paper of this grouping; however, in this paper, Howell et al. (2024) also explore the dynamics of nutrients and water clarity, centering on the role that dreissenid mussels have played in driving their dynamics in Lake Erie's oligotrophic eastern basin. Howell et al. took advantage of a long-term monitoring dataset from a nearshore site on Waverly Shoal, which began in 1988, early enough to track the effects of the dreissenid mussel introduction. Specifically, these authors report the dynamics of water clarity, chlorophyll a, and sediment quality at this location, which were last reported in Howell et al. (1996). In that study, water clarity increased, chlorophyll a decreased, and the organic content of sediments increased following the rapid expansion of the Zebra Mussel. However, in this more recent study, Howell et al. (2024) learned that the impact of dreissenid mussels has lessened following the establishment of the Quagga Mussel, which was lower in abundance relative to that of the Zebra Mussel during the early 1990s. Specifically, water clarity has decreased, chlorophyll a has increased, and phosphorus levels have returned to historical levels, suggesting a reduction in dreissenid-induced oligotrophication. Surprisingly, however, Howell et al. also found that their study site is now characterized by high variability, seemingly due to wind-driven resuspension of materials initially trapped by mussel beds. This periodic resuspension of sediments appears to be moderating many of the perceived impacts of mussels. In addition to discussing the high unpredictability of water quality locally, Howell et al. discuss implications for nutrient loading into downstream Lake Ontario.To this point, the papers published as part of this special issue series, including the previous volume (AEHM volume 26, issue 4), have focused on physicochemical attributes and/or the lower food web, discussing the drivers of the planktonic organisms (e.g. cyanobacteria, algae, and zooplankton), as well as the distribution and impact of invasive dreissenid mussels. Thus, insights into how higher consumers such as fish have yet to be discussed as part of this special issue series. Because Lake Erie's most abundant fish species are obligate planktivores during the larval stage (Ludsin et al., 2014), recent changes in zooplankton availability in Lake Erie (O'Donnell et al., 2023b) hold the potential to drive larval fish foraging and subsequent survival to the adult population and the fisheries that they support. Currently, however, our understanding of the interactions between zooplankton and larval fish communities in Lake Erie has primarily been limited to percids like Walleye Sander vitreus and Yellow Perch Perca flavescens (e.g. Marin Jarrin et al., 2015; May et al., 2021), given their economic, ecological, and cultural importance in the lake. Likewise, while climate change is expected to drive shifts in the spawning phenology of Lake Erie fishes, which could create mismatches between larval fish and their zooplankton prey (Farmer et al., 2015), a lakewide, synoptic study of fish spawning has yet to be conducted in the lake. The final two papers of this special issue address these knowledge gaps.In the first of these two papers, Amidon et al. (2024) characterize the distribution of larval Lake Whitefish across a spatial gradient in western Lake Erie (i.e. nearshore to offshore) and explore the degree to which zooplankton availability might impact survival of larval Lake Whitefish to the new year-class. Collections made during 2017-2021 showed that larval Lake Whitefish densities were generally higher in nearshore areas, as compared to mid- and offshore areas. This spatial distribution matched trends in crustacean zooplankton biomass, with Lake Whitefish diets from 2018, 2019, and 2021 showing that larvae preferentially fed upon copepods and cladocerans while selecting against rotifers and nauplii. Interestingly, Amidon et al. found that, while zooplankton densities were highest in the nearshore, larval Lake Whitefish fed at similar levels at all locations (nearshore, mid-, and offshore). Amidon et al. concluded form these results that western Lake Erie, even during low productivity spring periods, provides sufficient preferred zooplankton prey to support larval Lake Whitefish survival such that starvation during this stage is to Amidon et al. (2024), et al. (2024) results from a lakewide of larval to their distribution and phenology along the southern shore of Lake Erie. This was conducted in 2019 as a part of and with sampling during late through late in all three lake basins. from were across the lake, with total larval fish densities being higher in the western basin relative to the central and eastern basins. Their also showed 1) that and of larval were nearshore than offshore in all three lake basins the sampling and 2) that while larval fish occurred in more sites than the phenology of species was across Erie has a dynamic ecosystem during the owing in large part that have its physicochemical (Fraker et al., and its phytoplankton (O'Donnell et al., 2023a), zooplankton (Barbiero et al., 2019; O'Donnell et al., and fish communities et al., 2021; Sinclair et al., 2023). In addition to being Lake Erie has a heterogeneous with its and biological attributes and varying both within and its three major lake basins. This and associated heterogeneity were captured both in the previous AEHM special issue on Lake Erie (Ludsin et al., 2023), as well as as by investigations into 1) dissolved oxygen (Ackerman et al., 2024) and mercury (Starr et al., 2024) 2) primary producer (Lesht et al., 2024), cyanotoxin (Zastepa et al., 2024), and water quality (Howell et al., 2024) and 3) the distribution of Lake Whitefish et al., 2024) and the larval fish including the phenology (DeBruyne et al., 2024). Below we expand on these findings and their importance to agencies Lake Erie and its valued and services both now and into the papers in this special issue the dynamic nature of Lake Erie, the role that episodic events can in driving spatial or heterogeneity in water While Ackerman et al. (2024) the role of in driving seasonal dissolved oxygen these authors also that hypoxia is not a static and that events can dissolved oxygen This of hypoxia being a at its is by other recent studies of central Lake Erie (e.g. et al., 2015; Rowe et al., 2019). Howell et al. (2024) show similar in water quality conditions in eastern Lake Erie, the importance of episodic wind events in driving sediment and nutrient which in turn could potentially downstream (i.e. Lake water Finally, being synoptic Lesht et al. (2024), Starr et al. (2024), and Zastepa et al. (2024) point to the important role that such as loading and water can in driving the distribution of primary production, methyl mercury from and cyanotoxin in the water In addition to the continued of water quality impairments in Lake Erie, these studies of water it be dissolved oxygen, mercury or nutrient has been in Lake Erie. these studies show how synoptic and long-term monitoring investigations can provide ecological understanding and benefit not focused on water the of and heterogeneity were in the final two papers of this special issue, which focused on larval in distribution were for Lake Whitefish et al. 2024), as well as the fish community as a (DeBruyne et al., 2024). In both of these studies into driving variability in larval fish with Amidon et al. (2024) the role of crustacean zooplankton variability and et al. (2024) suggesting the importance of ecosystem productivity in driving larval fish and Lake Erie's three of these papers in this special issue that could be used to management, the first Lake Erie special issue (e.g. Bocaniov et al., 2023; Johnson et al., 2023; et al., 2023), each insights that could future and/or understand how the Lake Erie ecosystem has during the The lakewide of primary production (Lesht et al., 2024), for can the of primary production relative to the the lake a (Scavia et al., 2014; Watson et al., 2016). By contrast, Ackerman et al. (2024), Starr et al. (2024), and Howell et al. (2024) have to understand the need episodic events (e.g. winds, the dynamics of dissolved oxygen, and nutrient resuspension in Lake Erie. Likewise, the independent of cyanotoxins (Zastepa et al., 2024) and Lake Whitefish distribution and foraging et al., 2024) in the western basin, as well as the lakewide of larval fish and phenology (DeBruyne et al., 2024), have that can be used to assess the continued impact of unplanned anthropogenic change (e.g. climate change, invasive and planned management (e.g. phosphorus et al., on the Lake Erie need for these of is given the by the research and management communities to to management, a that has been long been on the of many in the Great Lakes et al., et al., and to is to management by providing a to assess the current state of the management and management and the of management et al., et al., et al., For this reason, we are by the new information in these first two AEHM special issues focused on Lake Erie and to the as we to to provide data, and that can efforts to and sustain the health of the Lake Erie ecosystem and the valued services it for providing on a previous of this
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".