Using DNA metabarcoding to characterize national scale diatom-environment relationships and to develop indicators in streams and rivers of the United States.

Recent advancements in DNA techniques, metabarcoding, and bioinformatics could help expand the use of benthic diatoms in monitoring and assessment programs by providing relatively quick and increasingly cost-effective ways to quantify diatom diversity in environmental samples. However, such applications of DNA-based approaches are relatively new, and in the United States, unknowns regarding their applications at large scales exist because only a few small-scale studies have been done. Here, we present results from the first nationwide survey to use DNA metabarcoding (rbcL) of benthic diatoms, which were collected from 1788 streams and rivers across nine ecoregions spanning the conterminous USA. At the national scale, we found that diatom assemblage structure (1) was strongly associated with total phosphorus and total nitrogen concentrations, conductivity, and pH and (2) had clear patterns that corresponded with differences in these variables among the nine ecoregions. These four variables were strong predictors of diatom assemblage structure in ecoregion-specific analyses, but our results also showed that diatom-environment relationships, the importance of environmental variables, and the ranges of these variables within which assemblage changes occurred differed among ecoregions. To further examine how assemblage data could be used for biomonitoring purposes, we used indicator species analysis to identify ecoregion-specific taxa that decreased or increased along each environmental gradient, and we used their relative abundances of gene reads in samples as metrics. These metrics were strongly correlated with their corresponding variable of interest (e.g., low phosphorus diatoms with total phosphorus concentrations), and generalized additive models showed how their relationships compared among ecoregions. These large-scale national patterns and nine sets of ecoregional results demonstrated that diatom DNA metabarcoding is a robust approach that could be useful to monitoring and assessment programs spanning the variety of conditions that exist throughout the conterminous United States.

Understanding the effects of phosphorus on diatom richness in rivers and streams using taxon-environment relationships.

Changes in phosphorus concentrations affect periphytic diatom composition in streams, yet we rarely observe strong relationships between diatom richness and phosphorus. In contrast, changes in conductivity are strongly associated with differences in both diatom composition and richness. We hypothesised that we could better understand the mechanisms that control the phosphorus-richness relationship by examining relationships between phosphorus and the occurrence of individual diatom taxa, comparing these with relationships between conductivity and taxon occurrence, and documenting how niche breadths of taxa affect richness patterns. We estimated relationships between phosphorus and taxon occurrence using DNA metabarcoding data of diatoms collected from 1,811 sites distributed across the conterminous U.S.A. and contrasted patterns in these relationships with those between conductivity and taxon occurrence. The distribution of taxon optima for phosphorus was bimodal, with most optima located at either the maximum or minimum observed phosphorus concentration. The distribution of taxon optima for conductivity was unimodal. Niche breadths of taxa for phosphorus and for conductivity both generally increased with optimum values. The distribution of conductivity optima gave rise to a prominent hump-shaped relationship between richness and conductivity. The relationship between richness and phosphorus was also slightly hump-shaped, but this relationship would not be expected from the bimodal distribution of optima. Instead, we determined that broad niche breadths caused the hump-shaped relationship between richness and phosphorus. Our results highlight the nuanced effects that increased P loadings exert on diatom assemblages in rivers and streams and identify reasons that weak relationships between taxon richness and increased phosphorus have been observed. These findings allow us to better describe how excess phosphorus and subsets of taxa and their niche breadths contribute to patterns of taxa richness in diatom assemblages, and to improve the tools used to manage phosphorus pollution.

Quantifying spatial and temporal relationships between diatoms and nutrients in streams strengthens evidence of nutrient effects from monitoring data.

Observational data are frequently used to better understand the effects of changes in P and N on stream biota, but nutrient gradients in streams are usually associated with gradients in other environmental factors, a phenomenon that complicates efforts to accurately estimate the effects of nutrients. Here, we propose a new approach for analyzing observational data in which we compare the effects of changes in nutrient concentrations in time within individual sites and in space among many sites. Covarying relationships between other, potentially confounding environmental factors and nutrient concentrations are unlikely to be the same in both time and space, and, therefore, estimated effects of nutrients that are similar in time and space are more likely to be accurate. We applied this approach to diatom rbcL metabarcoding data collected from streams in the East Fork of the Little Miami River watershed, Ohio, USA. Changes in diatom assemblage composition were consistently associated with changes in the concentration of total reactive P in both time and space. In contrast, despite being associated with spatial differences in ammonia and urea concentrations, diatom assemblage composition was not associated with temporal changes in these nitrogen species. We suggest that the results of this analysis provide evidence of a causal effect of increased P on diatom assemblage composition. We further analyzed the effects of temporal variability in measurements of total reactive P and found that averaging periods greater than ~1 wk prior to sampling best represented the effects of P on the diatom assemblage. Comparisons of biological responses in space and time can sharpen insights beyond those that are based on analyses conducted on only 1 of the 2 dimensions.

Characterizing temporal variability in streams supports nutrient indicator development using diatom and bacterial DNA metabarcoding.

Interest in developing periphytic diatom and bacterial indicators of nutrient effects continues to grow in support of the assessment and management of stream ecosystems and their watersheds. However, temporal variability could confound relationships between indicators and nutrients, subsequently affecting assessment outcomes. To document how temporal variability affects measures of diatom and bacterial assemblages obtained from DNA metabarcoding, we conducted weekly periphyton and nutrient sampling from July to October 2016 in 25 streams in a 1293 km2 mixed land use watershed. Measures of both diatom and bacterial assemblages were strongly associated with the percent agriculture in upstream watersheds and total phosphorus (TP) and total nitrogen (TN) concentrations. Temporal variability in TP and TN concentrations increased with greater amounts of agriculture in watersheds, but overall diatom and bacterial assemblage variability within sites-measured as mean distance among samples to corresponding site centroids in ordination space-remained consistent. This consistency was due in part to offsets between decreasing variability in relative abundances of taxa typical of low nutrient conditions and increasing variability in those typical of high nutrient conditions as mean concentrations of TP and TN increased within sites. Weekly low and high nutrient diatom and bacterial metrics were more strongly correlated with site mean nutrient concentrations over the sampling period than with same day measurements and more strongly correlated with TP than with TN. Correlations with TP concentrations were consistently strong throughout the study except briefly following two major precipitation events. Following these events, biotic relationships with TP reestablished within one to three weeks. Collectively, these results can strengthen interpretations of survey results and inform monitoring strategies and decision making. These findings have direct applications for improving the use of diatoms and bacteria, and the use of DNA metabarcoding, in monitoring programs and stream site assessments.

Western Australian adolescent emotional wellbeing during the COVID-19 pandemic in 2020.

BACKGROUND: The impacts of the COVID-19 pandemic have been vast and are not limited to physical health. Many adolescents have experienced disruptions to daily life, including changes in their school routine and family's financial or emotional security, potentially impacting their emotional wellbeing. In low COVID-19 prevalence settings, the impact of isolation has been mitigated for most young people through continued face-to-face schooling, yet there may still be significant impacts on their wellbeing that could be attributed to the pandemic. METHODS: We report on data from 32,849 surveys from Year 7-12 students in 40 schools over two 2020 survey cycles (June/July: 19,240; October: 13,609), drawn from a study of 79 primary and secondary schools across Western Australia, Australia. The Child Health Utility Index (CHU9D) was used to measure difficulties and distress in responding secondary school students only. Using comparable Australian data collected six years prior to the pandemic, the CHU9D was calibrated against the Kessler-10 to establish a reliable threshold for CHU9D-rated distress. RESULTS: Compared to 14% of responding 12-18-year-olds in 2013/2014, in both 2020 survey cycles almost 40% of secondary students returned a CHU9D score above a threshold indicative of elevated difficulties and distress. Student distress increased significantly between June and October 2020. Female students, those in older Grades, those with few friendships or perceived poor quality friendships, and those with poor connectedness to school were more likely to score above the threshold. CONCLUSIONS: In a large dataset collected during the first year of the COVID-19 pandemic, the proportion of secondary school students with scores indicative of difficulties and distress was substantially higher than a 2013/2014 benchmark, and distress increased as the pandemic progressed, despite the low local prevalence of COVID-19. This may indicate a general decline in social and emotional wellbeing exacerbated by the events of the pandemic. TRIAL REGISTRATION: ANZCTRN (ACTRN12620000922976). Retrospectively registered 17/08/2020. https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380429&isReview=true .

Estimating phytoplankton stoichiometry from routinely collected monitoring data.

Accurately estimating the elemental stoichiometry of phytoplankton is critical for understanding biogeochemical cycles. In laboratory experiments, stoichiometric ratios vary among species and with changes in environmental conditions. Field observations of total phosphorus (P) and total nitrogen (N) collected at regional and national scales can supplement and expand insights into factors influencing phytoplankton stoichiometry, but analyses applied to these data can introduce biases that affect interpretations of the observed patterns. We introduce an analytical approach for estimating the ratio between phytoplankton N and P from the particulate fraction of nutrient pools in lake samples. We use Bayesian models to represent observations of particulate P and N as the sum of contributions from nutrients bound within phytoplankton and nutrients associated with non-phytoplankton suspended sediment. Application of this approach to particulate nutrient data collected in Missouri impoundments yields estimates of the mass ratio of N:P in phytoplankton ranging from 8-10 across a variety of lakes and seasons. N:P in particulate matter ranged from 6 to 70, a variability driven by differences in nutrients bound to non-phytoplankton suspended sediment. We adapted the Bayesian models to estimate N:P using more commonly available measurements of total P and total N and applied this model to a continental-scale monitoring data set. We compared phytoplankton nutrient content estimated from the two analyses and found that when datasets lack direct measurements of particulate nutrient concentrations, the model estimate of phytoplankton nutrient content includes contributions from nutrients within phytoplankton and dissolved nutrients that are associated with changes in phytoplankton biomass.

Continental-scale effects of phytoplankton and non-phytoplankton turbidity on macrophyte occurrence in shallow lakes.

Submerged macrophytes are key components of shallow lake biological communities, and their presence has been associated with a predominantly clear-water state. Conversely, lakes lacking macrophytes are often turbid with elevated phytoplankton abundance. One main mechanism that influences the presence or absence of submerged macrophytes is turbidity that reduces the light available to macrophytes. Increases in turbidity can be caused by increased phytoplankton abundance and by increased concentrations of suspended inorganic sediment and understanding the relative contributions of these two factors can inform efforts to manage the effects of increased turbidity on macrophyte occurrence. Here, a continental scale data set is analyzed to quantify the effects of macrophytes on turbidity that originates from phytoplankton and from non-phytoplankton sources (e.g., inorganic sediment). Effects of phytoplankton assemblage composition on turbidity are also estimated. Based on this model, illustrative examples of chlorophyll concentrations needed to maintain or restore macrophytes to shallow lakes are calculated, and the difference in the magnitude of these concentrations illustrates the stabilizing effect of macrophytes on lake condition.

Asthma and high-intensity interval training have no effect on clustered cardiometabolic risk or arterial stiffness in adolescents.

PURPOSE: Cardiometabolic risk, including arterial stiffness, is increasing in youth. Those with asthma are suggested to be particularly at risk of cardiovascular disease. Efficient and effective strategies are required to prevent the atherosclerotic process in youth. The purpose of this study was to investigate the effect of 6 months high-intensity interval training (HIIT) on cardiometabolic risk in youth with and without asthma. METHODS: 65 adolescents (31 mild asthma; 34 non-asthma) were recruited, 32 (16 asthma) of whom were randomly allocated to receive HIIT three times per week for 6 months. At baseline, mid-intervention, post-intervention and at a 3-month follow-up, anthropometric, metabolic and vascular determinants of cardiometabolic risk were assessed. Following principal component analysis (PCA), linear mixed models were used to assess the influence of asthma, HIIT and their interaction. RESULTS: Seven factors were identified which explained 88% of the common variance shared among the parameters. Those with asthma demonstrated lower arterial stiffness factor scores mid-intervention (P = 0.047) and lower cholesterol factor scores post-intervention (P = 0.022) but there was no effect of the intervention, or interaction effects, on any PCA-identified factor, at any time-point. HIIT was associated with a lower low-density lipoprotein and diastolic blood pressure at mid-intervention. DISCUSSION: Neither arterial stiffness nor clustered cardiometabolic risk are influenced by HIIT in adolescents with or without asthma, despite important changes in blood lipid and pressure profiles. Blood pressure, augmentation and pulse wave velocity should be considered physiologically distinct constructs and as potential markers of cardiovascular health.

The application of metacommunity theory to the management of riverine ecosystems.

River managers strive to use the best available science to sustain biodiversity and ecosystem function. To achieve this goal requires consideration of processes at different scales. Metacommunity theory describes how multiple species from different communities potentially interact with local-scale environmental drivers to influence population dynamics and community structure. However, this body of knowledge has only rarely been used to inform management practices for river ecosystems. In this paper, we present a conceptual model outlining how the metacommunity processes of local niche sorting and dispersal can influence the outcomes of management interventions and provide a series of specific recommendations for applying these ideas as well as research needs. In all cases, we identify situations where traditional approaches to riverine management could be enhanced by incorporating an understanding of metacommunity dynamics. A common theme is developing guidelines for assessing the metacommunity context of a site or region, evaluating how that context may affect the desired outcome, and incorporating that understanding into the planning process and methods used. To maximize the effectiveness of management activities, scientists and resource managers should update the toolbox of approaches to riverine management to reflect theoretical advances in metacommunity ecology.

Rethinking phosphorus-chlorophyll relationships in lakes.

The empirical relationship between total phosphorus and chlorophyll has guided lake management decisions for decades, but imprecision in this relationship in individual lakes limits the utility of these models. Many environmental factors that potentially affect the total phosphorus-chlorophyll relationship have been studied, but here we hypothesize that imprecision can be reduced by considering differences in the proportions of phosphorus bound to three different "compartments" in the water column: phosphorus bound in phytoplankton, phosphorus bound to suspended sediment that is not associated with phytoplankton, and dissolved phosphorus. We specify a hierarchical Bayesian network model that estimates phosphorus associated with each compartment using field measurements of chlorophyll, total suspended solids, and total phosphorus collected from reservoirs in Missouri, USA. We then demonstrate that accounting for these different compartments yields accurate predictions of total phosphorus in individual lakes. Results from this model also yield insights into the mechanisms by which lake morphometric and watershed characteristics affect observed relationships between total phosphorus and chlorophyll.

Modeling hypolimnetic dissolved oxygen depletion using monitoring data.

Eutrophication increases hypoxia in lakes and reservoirs, causing deleterious effects on biological communities. Quantitative models would help managers develop effective strategies to address hypoxia issues, but most existing models are limited in their applicability to lakes with temporally resolved dissolved oxygen data. We describe a hierarchical Bayesian model that predicts dissolved oxygen in lakes based on a mechanistic understanding of the factors that influence the development of hypoxia during summer stratification. These factors include the days elapsed since stratification, dissolved organic carbon concentration, lake depth, and chlorophyll concentration. We demonstrate that the model can be fit to two datasets: one in which temporally resolved dissolved oxygen profiles were collected from 20 lakes in a single state and one in which single profiles were collected from 381 lakes across the United States. Analyses of these two datasets yielded similar relationships between volumetric oxygen demand and chlorophyll concentration, suggesting that the model structure appropriately represented the effects of eutrophication on oxygen depletion. Combining both datasets in a single model further improved the precision of predictions.

The value of sponsor fit and sincerity when promoting health messages at sport and art events.

Commercial companies invest in sport and arts sponsorship to align their brand with highly engaged spectators. Competing for spectator attention are government and non-government organizations promoting healthy lifestyles. This study investigated spectator engagement on the effectiveness of health messages promoted at sponsored events. Surveys from 2165 adults attending 28 sponsored events collected data on event engagement, health message awareness, behavioral intention, and perceptions of sponsor fit and sincerity. Spectators who were more highly engaged in the event showed significantly greater levels of awareness and acceptance of the health message (all P < 0.01). Path analysis showed that product and event interest were significantly related to both fit and sincerity, and perceived sponsorship fit was significantly associated with greater behavioral intention (all P < 0.01). Product, category and event interest, fit and sincerity were significantly greater for positive advocacy messages than neutral or negative advocacy messages (all P < 0.05). Health message sponsorship is assisted by spectator engagement and perceived fit of sponsored health messages. There exists greater potential to actively leverage spectator engagement to build or reinforce the perceived fit and sincerity of health messages to strengthen existing awareness and behavioral intention.

Combining national and state data improves predictions of microcystin concentration.

Data collected from lakes at national (regional) scales and state (local) scales can provide different insights regarding relationships between environmental factors and biological responses, and combining these two types of data can potentially yield more precise and accurate understanding of ecological phenomena. National data can include many measures, cover large spatial areas, and span broad environmental gradients. Because of these characteristics, analyses of these data can yield accurate estimates of relationships among different lake characteristics. However, the number of samples in a national data set that is available for estimating a relationship specific to waterbodies within a smaller region, like a single state, is limited. Conversely, state monitoring data provide intensive sampling of lakes within a smaller area, but these data span a narrower range of conditions and may only include a subset of relevant measurements. Here, a Bayesian network model is described that represents the causal linkages between observations of chlorophyll a concentration, cyanobacterial biovolume, and microcystin concentration. This network model was fit to national data and provided a context for modeling observations of chlorophyll a and microcystin collected from lakes in Iowa. Using the knowledge inherent in the national network model improved the accuracy of predictions of microcystin concentrations in Iowa compared to a model based only on Iowa data.

A Bayesian network model for estimating stoichiometric ratios of lake seston components.

The elemental composition of seston provide insights into the functioning of lake food webs and how nutrients cycle through the environment. Here, we describe a Bayesian network model that simultaneously estimates relationships between dissolved and particulate nutrients, suspended volatile and non-volatile sediments, and algal chlorophyll. The model provides direct estimates of the phosphorus and nitrogen content of phytoplankton, suspended non-living organic matter, and suspended inorganic sediment. We apply this model to data collected from reservoirs in Missouri, USA to test the validity of our assumed relationships. The results indicate that, on average among all samples, the ratio of nitrogen to phosphorus (N:P) in phytoplankton and non-living organic matter in these reservoirs were similar, although under nutrient replete conditions, N:P in phytoplankton decreased. Phosphorus content of inorganic sediment was lower than in phytoplankton and non-living organic matter. The analysis also provided a means of tracking changes in the composition of whole seston over time. In addition to informing questions regarding seston stoichiometry, this modeling approach may inform efforts to manage lake eutrophication because it can improve traditional models of relationships between nutrients and chlorophyll in lakes.

Taxonomic harmonization may reveal a stronger association between diatom assemblages and total phosphorus in large datasets.

Diatom data have been collected in large-scale biological assessments in the United States, such as the U.S. Environmental Protection Agency's National Rivers and Streams Assessment (NRSA). However, the effectiveness of diatoms as indicators may suffer if inconsistent taxon identifications across different analysts obscure the relationships between assemblage composition and environmental variables. To reduce these inconsistencies, we harmonized the 2008-2009 NRSA data from nine analysts by updating names to current synonyms and by statistically identifying taxa with high analyst signal (taxa with more variation in relative abundance explained by the analyst factor, relative to environmental variables). We then screened a subset of samples with QA/QC data and combined taxa with mismatching identifications by the primary and secondary analysts. When these combined "slash groups" did not reduce analyst signal, we elevated taxa to the genus level or omitted taxa in difficult species complexes. We examined the variation explained by analyst in the original and revised datasets. Further, we examined how revising the datasets to reduce analyst signal can reduce inconsistency, thereby uncovering the variation in assemblage composition explained by total phosphorus (TP), an environmental variable of high priority for water managers. To produce a revised dataset with the greatest taxonomic consistency, we ultimately made 124 slash groups, omitted 7 taxa in the small naviculoid (e.g., Sellaphora atomoides) species complex, and elevated Nitzschia, Diploneis, and Tryblionella taxa to the genus level. Relative to the original dataset, the revised dataset had more overlap among samples grouped by analyst in ordination space, less variation explained by the analyst factor, and more than double the variation in assemblage composition explained by TP. Elevating all taxa to the genus level did not eliminate analyst signal completely, and analyst remained the most important predictor for the genera Sellaphora, Mayamaea, and Psammodictyon, indicating that these taxa present the greatest obstacle to consistent identification in this dataset. Although our process did not completely remove analyst signal, this work provides a method to minimize analyst signal and improve detection of diatom association with TP in large datasets involving multiple analysts. Examination of variation in assemblage data explained by analyst and taxonomic harmonization may be necessary steps for improving data quality and the utility of diatoms as indicators of environmental variables.

The challenges that spatial context present for synthesizing community ecology across scales.

Accurately characterizing spatial patterns on landscapes is necessary to understand the processes that generate biodiversity, a problem that has applications in ecological theory, conservation planning, ecosystem restoration, and ecosystem management. However, the measurement of biodiversity patterns and the ecological and evolutionary processes that underlie those patterns is highly dependent on the study unit size, boundary placement, and number of observations. These issues, together known as the modifiable areal unit problem, are well known in geography. These factors limit the degree to which results from different metacommunity and macro-ecological studies can be compared to draw new inferences, and yet these types of comparisons are widespread in community ecology. Using aquatic community datasets, we demonstrate that spatial context drives analytical results when landscapes are sub-divided. Next, we present a framework for using resampling and neighborhood smoothing to standardize datasets to allow for inferential comparisons. We then provide examples for how addressing these issues enhances our ability to understand the processes shaping ecological communities at landscape scales and allows for informative meta-analytical synthesis. We conclude by calling for greater recognition of issues derived from the modifiable areal unit problem in community ecology, discuss implications of the problem for interpreting the existing literature, and identify tools and approaches for future research.

Changes in the relationship between zooplankton and phytoplankton biomasses across a eutrophication gradient.

The relationship between zooplankton biomass and phytoplankton biomass can provide insight into the structure and function of lake biological communities. We used a Bayesian network model to analyze a continental-scale data dataset to estimate changes in the relationship between zooplankton (Z) and phytoplankton (P) biomasses along a eutrophication gradient. The Bayesian network model allowed us to combine two different measurements of phytoplankton biomass (chlorophyll a concentration and directly observed biovolume) to improve the precision of estimates of true biomass within each sample. The model also allowed us to estimate separate relationships between P and zooplankton abundance and between P and mean individual zooplankton biomass and then to combine these two relationships into an estimate of seasonal mean zooplankton biomass. The resulting analysis indicated that seasonal mean zooplankton biomass increased proportionally with phytoplankton biomass in oligotrophic lakes, yielding a constant ratio between Z and P and suggested that bottom-up forces determined zooplankton biomass in these systems. In eutrophic lakes, seasonal mean zooplankton biomass was nearly constant with increases in phytoplankton biomass, yielding a decrease in the ratio between Z and P with increasing eutrophication. Bottom-up forces, as quantified by an increase in the proportion of cyanobacteria, accounted for approximately one fifth of the residual variance in the model as the relationship between Z and P changed from direct proportionality in oligotrophic lakes to the nearly constant value of Z observed in eutrophic lakes, suggesting that a combination of both top-down and bottom-up forces likely determined zooplankton biomass in eutrophic lakes.

Hospital Acquired Thrombosis (HAT) Prevention in an Acute Hospital; A Single Centre Cross-Sectional Study.

Evidence based guidelines are effective in reducing incidence of venous thromboembolism (VTE) which is associated with morbidly, mortality and economic burden. This study aimed to identify the proportion of inpatients who had a VTE risk assessment (RA) performed and who received thromboprophylaxis (TP), in Cork University Hospital. There was no structured RA tool at the time; information was obtained from medical and drug charts to ascertain if a RA was performed. Patients were then RA by researchers and stratified as per NICE guidelines and the proportion who received TP was calculated. One thousand and nineteen inpatients were screened. Risk was documented in 24% of cases. TP was prescribed in 43.2% of inpatients. Following application of a RA tool >80% were at high risk of VTE with low risk of bleeding with TP prescription in 46.3% of inpatients. A national collaborative effort should be encouraged to develop a standardized approach for safe RA of inpatients and prescription of TP for prevention of HAT.