Euan D. Reavie

Are harmful algal blooms becoming the greatest inland water quality threat to public health and aquatic ecosystems

In this Focus article, the authors ask a seemingly simple question: Are harmful algal blooms (HABs) becoming the greatest inland water quality threat to public health and aquatic ecosystems? When HAB events require restrictions on fisheries, recreation, and drinking water uses of inland water bodies significant economic consequences result. Unfortunately, the magnitude, frequency, and duration of HABs in inland waters are poorly understood across spatiotemporal scales and differentially engaged among states, tribes, and territories. Harmful algal bloom impacts are not as predictable as those from conventional chemical contaminants, for which water quality assessment and management programs were primarily developed, because interactions among multiple natural and anthropogenic factors determine the likelihood and severity to which a HAB will occur in a specific water body. These forcing factors can also affect toxin production. Beyond site-specific water quality degradation caused directly by HABs, the presence of HAB toxins can negatively influence routine surface water quality monitoring, assessment, and management practices. Harmful algal blooms present significant challenges for achieving water quality protection and restoration goals when these toxins confound interpretation of monitoring results and environmental quality standards implementation efforts for other chemicals and stressors. Whether HABs presently represent the greatest threat to inland water quality is debatable, though in inland waters of developed countries they typically cause more severe acute impacts to environmental quality than conventional chemical contamination events. The authors identify several timely research needs. Environmental toxicology, environmental chemistry, and risk-assessment expertise must interface with ecologists, engineers, and public health practitioners to engage the complexities of HAB assessment and management, to address the forcing factors for HAB formation, and to reduce the threats posed to inland surface water quality.

Responsiveness of Great Lakes Wetland Indicators to Human Disturbances at Multiple Spatial Scales: A Multi-Assemblage Assessment

ABSTRACT Developing indicators of ecosystem condition is a priority in the Great Lakes, but little is known about appropriate spatial scales to characterize disturbance or response for most indicators. We surveyed birds, fish, amphibians, aquatic macroinvertebrates, wetland vegetation, and diatoms at 276 coastal wetland locations throughout the U.S. Great Lakes coastal region during 2002–2004. We assessed the responsiveness of 66 candidate indicators to human disturbance (agriculture, urban development, and point source contaminants) characterized at multiple spatial scales (100, 500, 1,000, and 5,000 m buffers and whole watersheds) using classification and regression tree analysis (CART). Non-stressor covariables (lake, ecosection, watershed, and wetland area) accounted for a greater proportion of variance than disturbance variables. Row-crop agriculture and urban development, especially at larger spatial scales, were about equally influential and were more explanatory than a contaminant stress index (CSI). The CSI was an important predictor for diatom indicators only. Stephanodiscoid diatoms and nest-guarding fish were identified as two of the most promising indicators of row-crop agriculture, while Ambloplites rupestris (fish) and Aeshna (dragonflies) were two of the strongest indicators of urban development. Across all groups of taxa and spatial scales, fish indicators were most responsive to the combined influence of row-crop and urban development. Our results suggest it will be critical to account for the influence of potentially important non-stressor covariables before assessing the strength of indicator responses to disturbance. Moreover, identifying the appropriate scale to characterize disturbance will be necessary for many indicators, especially when urban development is the primary disturbance.

Diatom-based Weighted-averaging Transfer Functions for Great Lakes Coastal Water Quality: Relationships to Watershed Characteristics

ABSTRACT In an effort to develop indicators for Great Lakes near-shore conditions, diatom-based transfer functions to infer water quality variables were developed from 155 samples collected from coastal Great Lakes wetlands, embayments and high-energy shoreline sites. Over 2,000 diatom taxa were identified, and 352 taxa were sufficiently abundant to include in transfer function development. Multivariate data exploration revealed strong responses of the diatom assemblages to stressor variables, including total phosphorus (TP). Spatial variables such as lake, latitude and longitude also had notable relationships with assemblage characteristics. A diatom inference transfer function for TP provided a robust reconstructive relationship (r2 = 0.67; RMSE = 0.28 log(μg/L); r2jackknife = 0.55; RMSEP = 0.33 log (μg/L)) that improved following the removal of 13 samples that had poor observed-inferred TP relationships (r2 = 0.75; RMSE = 0.22 log(μg/L); r2jackknife = 0.65; RMSEP = 0.26 log (μg/L)). Diatom-based transfer functions for other water quality variables, such as total nitrogen, chloride, and chlorophyll α also performed well. Measured and diatom-inferred water quality data were regressed against watershed characteristics (including gradients of agriculture, atmospheric deposition, and industrial facilities) to determine the relative strength of measured and diatom-inferred data to identify watershed stressor influences. With the exception of pH, diatom-inferred water quality variables were better predicted by watershed characteristics than were measured water quality variables. Because diatom communities are subject to the prevailing water quality in the Great Lakes coastal environment, it appears they can better integrate water quality information than snapshot measurements. These results strongly support the use of diatoms in Great Lakes coastal monitoring programs.

Environmental control of diatom community size structure varies across aquatic ecosystems

Changes in the size structure of photoautotrophs influence food web structure and the biogeochemical cycling of carbon. Decreases in the median size of diatoms within communities, in concert with climate warming and water column stratification, have been observed over the Cenozoic in the ocean and over the last 50 years in Lake Tahoe. Decreases in the proportion of larger plankton are frequently observed in response to reduced concentrations of limiting nutrients in marine systems and large stratified lakes. By contrast, we show a decrease in the median size of planktonic diatoms in response to higher nutrient concentrations in a set of intermediate-sized alkaline lakes. Climate-induced increases in the frequency, duration and strength of water column stratification may select smaller planktonic species in the ocean and larger lakes owing to a reduction in nutrient availability and sinking rates, while light limitation, stimulated by nutrient eutrophication and high chlorophyll concentrations, may select smaller species within a community owing to their high light absorption efficiencies and lower sinking rates. The relative importance of different physiological and ecological rates and processes on the size structure of communities varies in different aquatic systems owing to varying combinations of abiotic and biotic constraints.

Exploration of sample size and diatom-based indicator performance in three North American phosphorus training sets

Three large training sets were investigated to determine optimal sample sizes for diatom-based inference models. The sample sets represented (1) assemblages from Great Lakes coastlines, (2) phytoplankton from the pelagic Great Lakes and (3) surface sediment assemblages from Minnesota lakes. Diatom-based weighted average models to infer nutrient concentrations were developed for each training set. Training set sample sizes ranging from 10 to the maximum number of samples were created through random sample selection, and performance of each model was evaluated. For each model iteration, diatom-inferred (DI) nutrient data were related to stressor data (e.g., adjacent agricultural or urban development) to characterize the ability of each model to track human activities. The relationships between model performance parameters (DI-stressor correlations and model r2, error and bias) and sample size were used to determine the minimum sample size needed to optimize models for each region. Depending on the training set, at least 40–70 samples were needed to capture the variation in diatom assemblages and environmental conditions to such a degree that non-analog situations should be rare and so should provide an unambiguous result if the model was applied to any sample assemblage from the region. It is recommended that one exercises caution when dealing with smaller training sets unless there is certainty that the selected samples reflect the regional variability in diatom assemblages and environmental conditions.

Ice cover extent drives phytoplankton and bacterial community structure in a large north‐temperate lake: implications for a warming climate

Mid-winter limnological surveys of Lake Erie captured extremes in ice extent ranging from expansive ice cover in 2010 and 2011 to nearly ice-free waters in 2012. Consistent with a warming climate, ice cover on the Great Lakes is in decline, thus the ice-free condition encountered may foreshadow the lakes future winter state. Here, we show that pronounced changes in annual ice cover are accompanied by equally important shifts in phytoplankton and bacterial community structure. Expansive ice cover supported phytoplankton blooms of filamentous diatoms. By comparison, ice free conditions promoted the growth of smaller sized cells that attained lower total biomass. We propose that isothermal mixing and elevated turbidity in the absence of ice cover resulted in light limitation of the phytoplankton during winter. Additional insights into microbial community dynamics were gleaned from short 16S rRNA tag (Itag) Illumina sequencing. UniFrac analysis of Itag sequences showed clear separation of microbial communities related to presence or absence of ice cover. Whereas the ecological implications of the changing bacterial community are unclear at this time, it is likely that the observed shift from a phytoplankton community dominated by filamentous diatoms to smaller cells will have far reaching ecosystem effects including food web disruptions.

Laurentian Great Lakes Phytoplankton and Their Water Quality Characteristics, Including a Diatom-Based Model for Paleoreconstruction of Phosphorus

Recent shifts in water quality and food web characteristics driven by anthropogenic impacts on the Laurentian Great Lakes warranted an examination of pelagic primary producers as tracers of environmental change. The distributions of the 263 common phytoplankton taxa were related to water quality variables to determine taxon-specific responses that may be useful in indicator models. A detailed checklist of taxa and their environmental optima are provided. Multivariate analyses indicated a strong relationship between total phosphorus (TP) and patterns in the diatom assemblages across the Great Lakes. Of the 118 common diatom taxa, 90 (76%) had a directional response along the TP gradient. We further evaluated a diatom-based transfer function for TP based on the weighted-average abundance of taxa, assuming unimodal distributions along the TP gradient. The r2 between observed and inferred TP in the training dataset was 0.79. Substantial spatial and environmental autocorrelation within the training set of samples justified the need for further model validation. A randomization procedure indicated that the actual transfer function consistently performed better than functions based on reshuffled environmental data. Further, TP was minimally confounded by other environmental variables, as indicated by the relatively large amount of unique variance in the diatoms explained by TP. We demonstrated the effectiveness of the transfer function by hindcasting TP concentrations using fossil diatom assemblages in a Lake Superior sediment core. Passive, multivariate analysis of the fossil samples against the training set indicated that phosphorus was a strong determinant of historical diatom assemblages, verifying that the transfer function was suited to reconstruct past TP in Lake Superior. Collectively, these results showed that phytoplankton coefficients for water quality can be robust indicators of Great Lakes pelagic condition. The diatom-based transfer function can be used in lake management when retrospective data are needed for tracking long-term degradation, remediation and trajectories.

Congruence of community thresholds in response to anthropogenic stress in Great Lakes coastal wetlands

Abstract: Biological attributes of ecosystems often change nonlinearly as a function of anthropogenic and natural stress. Plant and animal communities may exhibit zones of change along a stressor gradient that are disproportionate relative to the incremental change in the stressor. The ability to predict such transitions is essential for effective management intervention because they may indicate irreversible changes in ecological processes. Despite the importance of recognizing transition zones along a stressor gradient, few, if any, investigators have examined these responses across multiple taxa, and no community threshold studies have been reported at large geographic scales. We surveyed benthic macroinvertebrate, fish, bird, diatom, and plant communities in coastal wetlands across a geospatially referenced gradient of anthropogenic stress in the Laurentian Great Lakes. We used Threshold Indicator Taxon Analysis (Baker and King 2010) to analyze each communitys response to identify potential zones of disproportionate change in community structure along gradients of major watershed-scale stress: agriculture and urban/suburban development. Our results show surprising congruence in community thresholds among different taxonomic groups, particularly with respect to % developed land in the watershed. We also analyzed uncertainty associated with the community-specific thresholds to understand the ability of different assemblages to predict stress. The high and congruent sensitivity of assemblages to development demonstrates that watershed-scale stress has discernible effects on all biological communities, with increasing potential for ecosystem-scale functional changes. These findings have important implications for identifying reference-condition boundaries and for informing management and policy decisions, in particular, for selecting freshwater protected areas.

A Diatom Quality Index from a Diatom-Based Total Phosphorus Inference Model

A diatom quality index to assess diatom community impairment in the nearshore wetlands of the Laurentian Great Lakes was developed from a diatom-based total phosphorus (TP) weighted average inference model. The index is calculated with a weighted average equation using species optima standardized to a 1–10 scale and species tolerance standardized to a 1–3 scale. Multiple regression analysis revealed a moderate fit (R 2 = 0.63) between site scores of the selected index and GIS derived watershed characteristics (agriculture, soils, and industrial facilities). These index scores more closely fit watershed characteristics than the diatom inferred TP (R 2 = 0.59). In a regression tree analysis, soil permeability separated higher index scores from lower scores identifying this variable as an important interaction factor in the analysis. The diatom quality index can be a powerful tool for analyzing habitat quality in the Great Lakes and can communicate the link between quantifiable diatom assemblage response with watershed-level disturbance.

An integrated approach to assessing multiple stressors for coastal Lake Superior

Biological indicators can be used both to estimate ecological condition and to suggest plausible causes of ecosystem degradation across the U.S. Great Lakes coastal region. Here we use data on breeding bird, diatom, fish, invertebrate, and wetland plant communities to develop robust indicators of ecological condition of the U.S. Lake Superior coastal zone. Sites were selected as part of a larger, stratified random design for the entire U.S. Great Lakes coastal region, covering gradients of anthropogenic stress defined by over 200 stressor variables (e.g. agriculture, altered land cover, human populations, and point source pollution). A total of 89 locations in Lake Superior were sampled between 2001 and 2004 including 31 sites for stable isotope analysis of benthic macroinvertebrates, 62 sites for birds, 35 for diatoms, 32 for fish and macroinvertebrates, and 26 for wetland vegetation. A relationship between watershed disturbance metrics and 15N levels in coastal macroinvertebrates confirmed that watershed-based stressor gradients are expressed across Lake Superiors coastal ecosystems, increasing confidence in ascribing causes of biological responses to some landscape activities. Several landscape metrics in particular—agriculture, urbanization, human population density, and road density—strongly influenced the responses of indicator species assemblages. Conditions were generally good in Lake Superior, but in some areas watershed stressors produced degraded conditions that were similar to those in the southern and eastern U.S. Great Lakes. The following indicators were developed based on biotic responses to stress in Lake Superior in the context of all the Great Lakes: (1) an index of ecological condition for breeding bird communities, (2) diatom-based nutrient and solids indicators, (3) fish and macroinvertebrate indicators for coastal wetlands, and (4) a non-metric multidimensional scaling for wetland plants corresponding to a cumulative stress index. These biotic measures serve as useful indicators of the ecological condition of the Lake Superior coast; collectively, they provide a baseline assessment of selected biological conditions for the U.S. Lake Superior coastal region and prescribe a means to detect change over time.