Dataset Information

Indicators of nutrient pollution in Long Island, New York, estuarine environments.

ABSTRACT: Roughly eight million people live on Long Island, including Brooklyn and Queens, and despite improvements in wastewater treatment, nearly all its coastal waterbodies are impaired by excessive nitrogen. We used nutrient stoichiometry and stable isotope ratios in estuarine biota and soils to identify water pollution hot spots and compare among potential indicators. We found strong gradients in ?15N values, which were correlated with watershed land cover, population density, and wastewater discharges. Weaker correlations were found for ?13C values and nutrient stoichiometric ratios. Structural equation modeling identified contrasts between western Long Island, where ?15N values depended on watershed population density, and eastern Long Island where ?15N values reflected agriculture and sewage discharges. These results illustrate the use of stable isotopes as water quality indicators, and establish a baseline against which the efficacy of strategies to reduce nutrients can be measured.

SUBMITTER: Watson EB

PROVIDER: S-EPMC5937021 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Indicators of nutrient pollution in Long Island, New York, estuarine environments.

Watson Elizabeth Burke EB Powell Elisabeth E Maher Nicole P NP Oczkowski Autumn J AJ Paudel Bhanu B Starke Adam A Szura Katelyn K Wigand Cathleen C

Marine environmental research 20180108

Roughly eight million people live on Long Island, including Brooklyn and Queens, and despite improvements in wastewater treatment, nearly all its coastal waterbodies are impaired by excessive nitrogen. We used nutrient stoichiometry and stable isotope ratios in estuarine biota and soils to identify water pollution hot spots and compare among potential indicators. We found strong gradients in δ<sup>15</sup>N values, which were correlated with watershed land cover, population density, and wastewat ...[more]

PMID: 29373137

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Project description:Indicators based on nutrient-biota relationships in streams can inform water quality restoration and protection programs. Bacterial assemblages could be particularly useful indicators of nutrient effects because they are species-rich, important contributors to ecosystem processes in streams, and responsive to rapidly changing conditions. Here, we sampled 25 streams weekly (12-14 times each) and used 16S rRNA gene metabarcoding of periphyton-associated bacteria to quantify the effects of total phosphorus (TP) and total nitrogen (TN). Threshold indicator taxa analysis identified assemblage-level changes and amplicon sequence variants (ASVs) that increased or decreased with increasing TP and TN concentrations (i.e., low P, high P, low N, and high N ASVs). Boosted regression trees confirmed that relative abundances of gene sequence reads for these four indicator groups were associated with nutrient concentrations. Gradient forest analysis complemented these results by using multiple predictors and random forest models for each ASV to identify portions of TP and TN gradients at which the greatest changes in assemblage structure occurred. Synthesized statistical results showed bacterial assemblage structure began changing at 24 μg TP/L with the greatest changes occurring from 110 to 195 μg/L. Changes in the bacterial assemblages associated with TN gradually occurred from 275 to 855 μg/L. Taxonomic and phylogenetic analyses showed that low nutrient ASVs were commonly Firmicutes, Verrucomicrobiota, Flavobacteriales, and Caulobacterales, Pseudomonadales, and Rhodobacterales of Proteobacteria, whereas other groups, such as Chitinophagales of Bacteroidota, and Burkholderiales, Rhizobiales, Sphingomonadales, and Steroidobacterales of Proteobacteria comprised the high nutrient ASVs. Overall, the responses of bacterial ASV indicators in this study highlight the utility of metabarcoding periphyton-associated bacteria for quantifying biotic responses to nutrient inputs in streams.

Project description:Estuaries provide critical habitat for food webs supporting fish and shellfish consumed by humans, but estuarine ecosystem health has been threatened by increases in nitrogen loading as well as inputs of the neurotoxin, mercury (Hg), which biomagnifies in food webs and poses risk to humans and wildlife. In this study, the effects of nutrient loading on the fate of Hg in shallow coastal estuaries were examined to evaluate if their interaction enhances or reduces Hg bioavailability in sediments, the water column, and concentrations in lower trophic level fish (Fundulus heteroclitus and Menidia menidia). Multiple sites were sampled within two human impacted coastal lagoons, Great South Bay (GSB) and Jamaica Bay (JB), on the southern coast of Long Island, NY, United States of America (U.S.A.). Carbon (C), nitrogen (N), sulfur (S), Hg, and methylmercury (MeHg) were measured in surface sediments and the water column, and total Hg (THg) was measured in two species of forage fish. Minimal differences were found in dissolved and particulate Hg, dissolved organic carbon (DOC), and salinity between the two bays. Across lagoons, concentrations of chlorophyll-a were correlated with total suspended solids (TSS), and water column THg and MeHg was largely associated with the particulate fraction. Methylmercury concentrations in particulates decreased with increasing TSS and chlorophyll-a, evidence of biomass dilution of MeHg with increasing productivity at the base of the food chain. Water column Hg was associated with THg concentrations in Atlantic silversides, while mummichog THg concentrations were related to sediment concentrations, reflecting their different feeding strategies. Finally, higher nutrient loading (lower C:N in sediments) while related to lower particulate concentrations coincided with higher bioaccumulation factors (BAF) for Hg in both fish species. Thus, in shallow coastal lagoons, increased nutrient loading resulted in decreased Hg concentrations at the base of the food web but resulted in greater bioaccumulation of Hg to fish relative to its availability in algal food.

Project description:BackgroundEmerging evidence suggests a potential association between ambient air pollution and risk of gestational diabetes mellitus (GDM), but results have been inconsistent. Accordingly, we assessed the associations between ambient fine particulate matter (PM2.5) and nitrogen dioxide (NO2) levels with risk of GDM.MethodsUsing linked data from birth certificates, hospital discharge diagnoses, and air pollution estimates informed by the New York City Community Air Survey, we fit conditional logistic regression models to evaluate the association between residential levels of PM2.5 and NO2 with risk of GDM among 256,372 singleton live births of non-smoking mothers in New York City born 2008-2010, adjusting for sociodemographic factors and stratified on zip code of maternal address.ResultsGDM was identified in 17,065 women, yielding a risk of GDM in the study sample of 67 per 1000 deliveries. In single pollutant models, 1st and 2nd trimester PM2.5 was associated with a lower and higher risk of GDM, respectively. In models mutually adjusting for PM2.5 levels in both trimesters, GDM was associated with PM2.5 levels in the 2nd trimester (OR: 1.06, 95% CI: 1.02, 1.10 per interquartile range increase in PM2.5), but not the 1st trimester (OR: 0.99, 95% CI: 0.96, 1.02). Conversely, GDM was associated with NO2 during the 1st trimester (OR: 1.05, 95% CI: 1.01, 1.09), but not the 2nd trimester (OR: 1.02, 95% CI: 0.98, 1.06). The positive associations between pollutants and GDM were robust to different model specifications. PM2.5 in the 2nd trimester was more strongly associated with GDM among mothers who were aged <35 years and not Medicaid recipients. NO2 in the 1st trimester was more strongly associated with GDM among overweight and parous women.ConclusionsIn this large cohort of singleton births in New York City, NO2 in the 1st trimester and PM2.5 in the 2nd trimester were associated with higher odds of GDM, while 1st trimester PM2.5 was weakly and inconsistently associated with lower odds of GDM.

Dataset Information

Indicators of nutrient pollution in Long Island, New York, estuarine environments.

Publications

Indicators of nutrient pollution in Long Island, New York, estuarine environments.

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