Dissolved organic matter transformations in a freshwater rivermouth.

River-to-lake transitional areas are biogeochemically active ecosystems that can alter the amount and composition of dissolved organic matter (DOM) as it moves through the aquatic continuum. However, few studies have directly measured carbon processing and assessed the carbon budget of freshwater rivermouths. We compiled measurements of dissolved organic carbon (DOC) and DOM in several water column (light and dark) and sediment incubation experiments conducted in the mouth of the Fox river (Fox rivermouth) upstream from Green Bay, Lake Michigan. Despite variation in the direction of DOC fluxes from sediments, we found that the Fox rivermouth was a net sink of DOC where water column DOC mineralization outweighed the release of DOC from sediments at the rivermouth scale. Although we found DOM composition also changed during our experiments, alterations in DOM optical properties were largely independent of the direction of sediment DOC fluxes. We found a consistent decrease in humic-like and fulvic-like terrestrial DOM and a consistent increase in the overall microbial composition of rivermouth DOM during our incubations. Moreover, greater ambient total dissolved phosphorus concentrations were positively associated with the consumption of terrestrial humic-like, microbial protein-like, and more recently derived DOM but had no effect on bulk DOC in the water column. Unexplained variation indicates that other environmental controls and water column processes affect the processing of DOM in this rivermouth. Nonetheless, the Fox rivermouth appears capable of substantial DOM transformation with implications for the composition of DOM entering Lake Michigan. Supplementary Information: The online version contains supplementary material available at 10.1007/s10533-022-01000-z.

Biofouling of a unionid mussel by dreissenid mussels in nearshore zones of the Great Lakes.

In North America, native unionid mussels are imperiled due to factors such as habitat degradation, pollution, and invasive species. One of the most substantial threats is that posed by dreissenid mussels, which are invasive mussels that attach to hard substrates including unionid shells and can restrict movement and feeding of unionids. This dreissenid mussel biofouling of unionids varies spatially in large ecosystems, such as the Great Lakes, with some areas having low enough biofouling to form effective refugia where unionid mussels might persist. Here, we measured biofouling on mussels suspended in cages over the growing season (generally first week in June to last week of August) over 3 years in nearshore areas in Lake Erie (2014-2016), Lake Michigan (Grand Traverse Bay, 2015 and Green Bay, 2016), and Lake Huron (2015). Biofouling varied substantially by years within Lake Erie, with increasingly higher biofouling rates each year. Although dreissenid mussels are present throughout these lakes, we observed very low biofouling in Grand Traverse Bay (Lake Michigan) and Saginaw Bay (Lake Huron), with no dreissenid mussels in 8 of 9 sites across these two bays. Sampling in the rivermouth of the Fox River (Wisconsin) and the Maumee River (Ohio) both showed very high biofouling in areas adjacent to the outlet of these tributaries into Green Bay and Maumee Bay (Lake Erie), respectively. These watersheds are dominated by agriculture, and we would expect high growth of primary producers (i.e., mussel food) and primary consumers (unionids and zebra mussels) in these areas compared to the other sampled bays or the open waters of the Great Lakes.

Sequestration of microfibers and other microplastics by green algae, Cladophora, in the US Great Lakes.

Daunting amounts of microplastics are present in surface waters worldwide. A main category of microplastics is synthetic microfibers, which originate from textiles. These microplastics are generated and released in laundering and are discharged by wastewater treatment plants or enter surface waters from other sources. The polymers that constitute many common synthetic microfibers are mostly denser than water, and eventually settle out in aquatic environments. The interaction of these microfibers with submerged aquatic vegetation has not been thoroughly investigated but is potentially an important aquatic sink in surface waters. In the Laurentian Great Lakes, prolific growth of macrophytic Cladophora creates submerged biomass with a large amount of surface area and the potential to collect and concentrate microplastics. To determine the number of synthetic microfibers in Great Lakes Cladophora, samples were collected from Lakes Erie and Michigan at multiple depths in the spring and summer of 2018. After rinsing and processing the algae, associated synthetic microfibers were quantified. The average loads of synthetic microfibers determined from the Lake Erie and Lake Michigan samples were 32,000 per kg (dry weight (dw)) and 34,000 per kg (dw), respectively, 2-4 orders of magnitude greater than loads previously reported in water and sediment. To further explore this sequestration of microplastics, fresh and aged Cladophora were mixed with aqueous mixtures of microfibers or microplastic in the laboratory to simulate pollution events. Microscopic analyses indicated that fresh Cladophora algae readily interacted with microplastics via adsorptive forces and physical entanglement. These interactions mostly cease upon algal senescence, with an expected release of microplastics in benthic sediments. Collectively, these findings suggest that synthetic microfibers are widespread in Cladophora algae and the affinity between microplastics and Cladophora may offer insights for removing microplastic pollution. Macroalgae in the Laurentian Great Lakes contain high loads of synthetic microfibers, both entangled and adsorbed, which likely account for an important fraction of microplastics in these surface waters.

Elucidating controls on cyanobacteria bloom timing and intensity via Bayesian mechanistic modeling.

The adverse impacts of harmful algal blooms (HABs) are increasing worldwide. Lake Erie is a North American Great Lake highly affected by cultural eutrophication and summer cyanobacterial HABs. While phosphorus loading is a known driver of bloom size, more nuanced yet crucial questions remain. For example, it is unclear what mechanisms are primarily responsible for initiating cyanobacterial dominance and subsequent biomass accumulation. To address these questions, we develop a mechanistic model describing June-October dynamics of chlorophyll a, nitrogen, and phosphorus near the Maumee River outlet, where blooms typically initiate and are most severe. We calibrate the model to a new, geostatistically-derived dataset of daily water quality spanning 2008-2017. A Bayesian framework enables us to embed prior knowledge on system characteristics and test alternative model formulations. Overall, the best model formulation explains 42% of the variability in chlorophyll a and 83% of nitrogen, and better captures bloom timing than previous models. Our results, supported by cross validation, show that onset of the major midsummer bloom is associated with about a month of water temperatures above 20 °C (occurring 19 July to 6 August), consistent with when cyanobacteria dominance is usually reported. Decreased phytoplankton loss rate is the main factor enabling biomass accumulation, consistent with reduced zooplankton grazing on cyanobacteria. The model also shows that phosphorus limitation is most severe in August, and nitrogen limitation tends to occur in early autumn. Our results highlight the role of temperature in regulating bloom initiation and subsequent loss rates, and suggest that a 2 °C increase could lead to blooms that start about 10 days earlier and grow 23% more intense.

Preliminary analysis to estimate the spatial distribution of benefits of P load reduction: Identifying the spatial influence of phosphorus loading from the Maumee River (USA) in western Lake Erie.

Since the early 2000s, Lake Erie has been experiencing annual cyanobacterial blooms that often cover large portions of the western basin and even reach into the central basin. These blooms have affected several ecosystem services provided by Lake Erie to surrounding communities (notably drinking water quality). Several modeling efforts have identified the springtime total bioavailable phosphorus (TBP) load as a major driver of maximum cyanobacterial biomass in western Lake Erie, and on this basis, international water management bodies have set a phosphorus (P) reduction goal. This P reduction goal is intended to reduce maximum cyanobacterial biomass, but there has been very limited effort to identify the specific locations within the western basin of Lake Erie that will likely experience the most benefits. Here, we used pixel-specific linear regression to identify where annual variation in spring TBP loads is most strongly associated with cyanobacterial abundance, as inferred from satellite imagery. Using this approach, we find that annual TBP loads are most strongly associated with cyanobacterial abundance in the central and southern areas of the western basin. At the location of the Toledo water intake, the association between TBP load and cyanobacterial abundance is moderate, and in Maumee Bay (near Toledo, Ohio), the association between TBP and cyanobacterial abundance is no better than a null model. Both of these locations are important for the delivery of specific ecosystem services, but this analysis indicates that P load reductions would not be expected to substantially improve maximum annual cyanobacterial abundance in these locations. These results are preliminary in the sense that only a limited set of models were tested in this analysis, but these results illustrate the importance of identifying whether the spatial distribution of management benefits (in this case P load reduction) matches the spatial distribution of management goals (reducing the effects of cyanobacteria on important ecosystem services).

A space-time geostatistical model for probabilistic estimation of harmful algal bloom biomass and areal extent.

Harmful algal blooms (HABs) have been increasing in intensity worldwide, including the western basin of Lake Erie. Substantial efforts have been made to track these blooms using in situ sampling and remote sensing. However, such measurements do not fully capture HAB spatial and temporal dynamics due to the limitations of discrete shipboard sampling over large areas and the effects of clouds and winds on remote sensing estimates. To address these limitations, we develop a space-time geostatistical modeling framework for estimating HAB intensity and extent using chlorophyll a data sampled during the HAB season (June-October) from 2008 to 2017 by five independent monitoring programs. Based on the Bayesian information criterion for model selection, trend variables explain bloom northerly and easterly expansion from Maumee Bay, wind effects over depth, and variability among sampling methods. Cross validation results demonstrate that space-time kriging explains over half of the variability in daily, location-specific chlorophyll observations, on average. Conditional simulations provide, for the first time, comprehensive estimates of overall bloom biomass (based on depth-integrated concentrations) and surface areal extent with quantified uncertainties. These new estimates are contrasted with previous Lake Erie HAB monitoring studies, and deviations among estimates are explored and discussed. Overall, results highlight the importance of maintaining sufficient monitoring coverage to capture bloom dynamics, as well as the benefits of the proposed approach for synthesizing data from multiple monitoring programs to improve estimation accuracy while reducing uncertainty.

Measuring spatial variation in secondary production and food quality using a common consumer approach in Lake Erie.

Lake Erie is a large lake straddling the border of the USA and Canada that has become increasingly eutrophic in recent years. Eutrophication is particularly focused in the shallow western basin. The western basin of Lake Erie is hydrodynamically similar to a large estuary, with riverine inputs from the Detroit and Maumee Rivers mixing together and creating gradients in chemical and physical conditions. This study was driven by two questions: (1) How does secondary production and food quality for consumers vary across this large mixing zone? and (2) Are there correlations between cyanobacterial abundance and secondary production or food quality for consumers? Measuring spatial and temporal variation in secondary production and food quality is difficult for a variety of logistical reasons, so here a common consumer approach was used. In a common consumer approach, individuals of a single species are raised under similar conditions until placed in the field across environmental gradients of interest. After some period of exposure, the response of that common consumer is measured to provide an index of spatial variation in conditions. Here, a freshwater mussel (Lampsilis siliquoidea) was deployed at 32 locations that spanned habitat types and a gradient in cyanobacterial abundance in the western basin of Lake Erie to measure spatial variation in growth (an index of secondary production) and fatty acid (FA) content (an index of food quality). We found secondary production was highest within the Maumee river mouth and lowest in the open waters of the lake. Mussel tissues in the Maumee river mouth also included more eicosapentaenoic and docosapentaenoic fatty acids (EPA and DPA, respectively), but fewer bacterial FAs, suggesting more algae at the base of the food web in the Maumee river mouth compared to open lake sites. The satellite-derived estimate of cyanobacterial abundance was not correlated to secondary production, but was positively related to EPA and DPA content in the mussels, suggesting more of these important FAs in locations with more cyanobacteria. These results suggest that growth of secondary consumers and the availability of important fatty acids in the western basin are centered on the Maumee river mouth.

A scenario and forecast model for Gulf of Mexico hypoxic area and volume.

For almost three decades, the relative size of the hypoxic region on the Louisiana-Texas continental shelf has drawn scientific and policy attention. During that time, both simple and complex models have been used to explore hypoxia dynamics and to provide management guidance relating the size of the hypoxic zone to key drivers. Throughout much of that development, analyses had to accommodate an apparent change in hypoxic sensitivity to loads and often cull observations due to anomalous meteorological conditions. Here, we describe an adaptation of our earlier, simple biophysical model, calibrated to revised hypoxic area estimates and new hypoxic volume estimates through Bayesian estimation. This application eliminates the need to cull observations and provides revised hypoxic extent estimates with uncertainties corresponding to different nutrient loading reduction scenarios. We compare guidance from this model application, suggesting an approximately 62% nutrient loading reduction is required to reduce Gulf hypoxia to the Action Plan goal of 5000 km(2), to that of previous applications. In addition, we describe for the first time, the corresponding response of hypoxic volume. We also analyze model results to test for increasing system sensitivity to hypoxia formation, but find no strong evidence of such change.

Record-setting algal bloom in Lake Erie caused by agricultural and meteorological trends consistent with expected future conditions.

In 2011, Lake Erie experienced the largest harmful algal bloom in its recorded history, with a peak intensity over three times greater than any previously observed bloom. Here we show that long-term trends in agricultural practices are consistent with increasing phosphorus loading to the western basin of the lake, and that these trends, coupled with meteorological conditions in spring 2011, produced record-breaking nutrient loads. An extended period of weak lake circulation then led to abnormally long residence times that incubated the bloom, and warm and quiescent conditions after bloom onset allowed algae to remain near the top of the water column and prevented flushing of nutrients from the system. We further find that all of these factors are consistent with expected future conditions. If a scientifically guided management plan to mitigate these impacts is not implemented, we can therefore expect this bloom to be a harbinger of future blooms in Lake Erie.

Incidental oligotrophication of North American Great Lakes.

Phytoplankton production is an important factor in determining both ecosystem stability and the provision of ecosystem goods and services. The expansive and economically important North American Great Lakes are subjected to multiple stressors and understanding their responses to those stresses is important for understanding system-wide ecological controls. Here we show gradual increases in spring silica concentration (an indicator of decreasing growth of the dominant diatoms) in all basins of Lakes Michigan and Huron (USA and Canadian waters) between 1983 and 2008. These changes indicate the lakes have undergone gradual oligotrophication coincident with and anticipated by nutrient management implementation. Slow declines in seasonal drawdown of silica (proxy for seasonal phytoplankton production) also occurred, until recent years, when lake-wide responses were punctuated by abrupt decreases, putting them in the range of oligotrophic Lake Superior. The timing of these dramatic production drops is coincident with expansion of populations of invasive dreissenid mussels, particularly quagga mussels, in each basin. The combined effect of nutrient mitigation and invasive species expansion demonstrates the challenges facing large-scale ecosystems and suggest the need for new management regimes for large ecosystems.

Gulf of Mexico hypoxia: exploring increasing sensitivity to nitrogen loads.

Hypoxia is a critical issue in the Gulf of Mexico that has challenged management efforts in recent years by an increase in hypoxia sensitivity to nitrogen loads. Several mechanisms have been proposed to explain the recent increase in sensitivity. Two commonly cited mechanisms are bottom-water reducing conditions preventing nitrification and thus denitrification, leading to more N recycling and production of oxygen-consuming organic matter, and carryover of organic matter from previous years increasing oxygen demand, making the system more sensitive. We use models informed by these mechanisms and fit with Bayesian inference to explore changes in Gulf of Mexico hypoxia sensitivity. We show that a model including an annually fit parameter representing variation in the fraction of nutrient loading and recycling contributing to bottom water oxygen demand provides a good fit to observations and is not improved by explicit inclusion of organic matter carryover to subsequent years. Both models support two stepwise increases in system sensitivity during the period of record. This change in sensitivity has greatly increased the nutrient reduction needed to achieve the established hypoxia goal. If the Gulf remains at the current state of sensitivity, our analysis suggests a roughly 70% reduction of spring TN loads from the 1988-1996 average of 6083 ton/day may be required.