Data on long-term monitoring programs to assess environmental pressures on coastal area.
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ABSTRACT:
SUBMITTER: Mali M
PROVIDER: S-EPMC6441757 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Aims and hypothesisThe optimal duration and frequency of short-term continuous glucose monitoring (CGM) to reflect long-term glycemia have not been determined. The Juvenile Diabetes Research Foundation CGM randomized trials provided a large dataset of longitudinal CGM data for this type of analysis.MethodsThe analysis included 185 subjects who had 334 3-month intervals of CGM data meeting specific criteria. For various glucose indices, correlations (r²) were computed for the entire 3-month interval versus selected sampling periods ranging from 3 to 15 days. Other computed agreement measures included median relative absolute difference, values within ± 10% and ± 20% of full value, and median absolute difference.ResultsAs would be expected, the more days of glucose data that were sampled, the higher the correlation with the full 3 months of data. For 3 days of sampling, the r² value ranged from 0.32 to 0.47, evaluating mean glucose, percentage of values 71-180 mg/dL, percentage of values > 180 mg/dL, percentage of values ≤ 70 mg/dL, and coefficient of variation; in contrast, for 15 days of sampling, the r² values ranged from 0.66 to 0.75. The results were similar when the analysis intervals were stratified by age group (8-14, 15-24, and ≥ 25 years), by baseline hemoglobin A1c level (< 7.0% and ≥ 7.0%), and by CGM device type.Conclusions and interpretationOur data suggest that a 12-15-day period of monitoring every 3 months may be needed to optimally assess overall glucose control. Shorter periods of sampling can be useful, but the correlation with 3-month measures of glycemic control is lower.
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Project description:This study reports the consumption data for 132 anticancer drugs in Catalonia (NE Spain) during the period of 2013-2017 and calculates the predicted environmental concentrations (PECs) in wastewater effluents and rivers. This long-term analysis can determine the evolution of drugs present in the environment according to prescriptions and serve as an adequate tool to determine their presence and impact. Data showed that out of 132 compounds prescribed, 77 reached wastewater effluents, which accounted for the most consumed, those excreted in the highest doses, and the least biodegradable. Once diluted in receiving river waters, only mycophenolic acid and hydroxycarbamide had PEC values higher than 10 ng L-1, which is the value set by the European Medicines Agency (EMA) to carry out further risk assessment. It was also observed that compounds present in river water are those that can pose a high risk, given their persistence and capability to bioaccumulate. Therefore, this study shows that the estimation of PEC, together with physico-chemical properties of detected compounds, is a useful tool to determine the long-term presence and fate of this new class of emerging contaminants.
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Project description:Aquatic pesticide pollution from both agricultural and urban pest control is a concern in many parts of the world. Making an accurate assessment of pesticide exposure is the starting point to protecting aquatic ecosystems. This in turn requires the design of an effective monitoring program. Monitoring is also essential to evaluate the efficacy of mitigation measures aimed to curb pesticide pollution. However, empirical evidence for their efficacy can be confounded by additional influencing factors, most prominently variable weather conditions. This review summarizes the experiences gained from long-term (>5 years) pesticide monitoring studies for detecting trends and provides recommendations for their improvement. We reviewed articles published in the scientific literature, with a few complements from selected grey literature, for a total of 20 studies which fulfill our search criteria. Overall, temporal trends of pesticide use and hydrological conditions were the two most common factors influencing aquatic pesticide pollution. Eighteen studies demonstrated observable effects to surface water concentrations from changes in pesticide application rates (e.g., use restriction) and sixteen studies from interannual variability in hydrological conditions during the application period. Accounting for seasonal- and streamflow-related variability in trend analysis is important because the two factors can obscure trends caused by changes in pesticide use or management practices. Other mitigation measures (e.g., buffer strips) were only detectable in four studies where concentrations or loads were reduced by > 45%. Collecting additional agricultural (e.g., pesticide use, mitigation measures) and environmental (e.g., precipitation, stream flow) data, as well as establishing a baseline before the implementation of mitigation measures have been consistently reported as prerequisites to interpret water quality trends from long-term monitoring studies, but have rarely been implemented in the past.
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Project description:Loss of biodiversity from lower to upper trophic levels reduces overall productivity and stability of coastal ecosystems in our oceans, but rarely are these changes documented across both time and space. The characterisation of environmental DNA (eDNA) from sediment and seawater using metabarcoding offers a powerful molecular lens to observe marine biota and provides a series of 'snapshots' across a broad spectrum of eukaryotic organisms. Using these next-generation tools and downstream analytical innovations including machine learning sequence assignment algorithms and co-occurrence network analyses, we examined how anthropogenic pressures may have impacted marine biodiversity on subtropical coral reefs in Okinawa, Japan. Based on 18 S ribosomal RNA, but not ITS2 sequence data due to inconsistent amplification for this marker, as well as proxies for anthropogenic disturbance, we show that eukaryotic richness at the family level significantly increases with medium and high levels of disturbance. This change in richness coincides with compositional changes, a decrease in connectedness among taxa, an increase in fragmentation of taxon co-occurrence networks, and a shift in indicator taxa. Taken together, these findings demonstrate the ability of eDNA to act as a barometer of disturbance and provide an exemplar of how biotic networks and coral reefs may be impacted by anthropogenic activities.
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Project description:Beached bird surveys have been widely used to monitor the impact of oil pollution in the oceans. However, separating the combined effects of oil pollution, environmental variables and methodological aspects of beach monitoring on seabird stranding patterns is a challenging task. The effects of a comprehensive set of oceanographic and climatic variables and oil pollution on seabird strandings in a tropical area of Brazil were investigated herein, using two robust and innovative methods: Generalized Linear Mixed Models and Structural Equation Modeling. We assessed strandings of four resident seabird species along 480 km of beaches divided into 11 sampling areas, between November 2010 and September 2013. We found that increasing the distance from the nearest breeding island reduce the seabird stranding events. Storm activity and biological productivity were the most important factors affecting the stranding events of brown boobies Sula leucogaster, Cabot's terns Thalasseus acuflavidus and kelp gulls Larus dominicanus. These species are also indirectly affected by warm tropical waters, which reduce chlorophyll-a concentrations. Beach surveys are, thus, useful to investigate the mortality rates of resident species near breeding sites, where individuals are more abundant and exposed to local factors associated with at-sea mortality. In contrast, conservation actions and monitoring programs for far-ranging seabird species are needed in more distant foraging areas. Furthermore, beach monitoring programs investigating the impact of oil pollution on seabirds need to account for the effects of environmental factors on stranding patterns. The present study also demonstrated that seabirds inhabiting tropical coastal waters are sensitive to climate conditions such as adverse weather, which are expected to increase in frequency and intensity in next decades.
| S-EPMC5161483 | biostudies-literature
Project description:Data was collected in the field, from an office building located in Frankfurt, Germany, over the period of 4 years. The building was designed as a low-energy building and featured natural ventilation for individual control of air quality as well as buoyancy-driven night ventilation in combination with a central atrium as a passive cooling strategy. The monitored data include in total 116 data points related to outdoor and indoor environmental data, energy related data, and data related to occupancy and occupant behaviour. Data points representing a state were logged with the real timestamp of the event taking place, all other data points were recorded in 10?minute intervals. Data were collected in 17 cell offices with a size of ~20?m2, facing either east or west). Each office has one fixed and two operable windows, internal top light windows between office and corridor (to allow for night ventilation into the atrium) and sun protection elements (operated both manually and automatically). Each office is occupied by one or two persons.
| S-EPMC6879735 | biostudies-literature
Project description:Both metagenomic data and metatranscriptomic data were collected from surface water (0-2m) of the L4 sampling station (50.2518 N, 4.2089 W), which is part of the Western Channel Observatory long-term coastal-marine monitoring station. We previously generated from this area a six-year time series of 16S rRNA V6 data, which demonstrated robust seasonal structure for the bacterial community, with diversity correlated with day length. Here we describe the features of these metagenomes and metatranscriptomes. We generated 8 metagenomes (4.5 million sequences, 1.9 Gbp, average read-length 350 bp) and 7 metatranscriptomes (392,632 putative mRNA-derived sequences, 159 Mbp, average read-length 272 bp) for eight time-points sampled in 2008. These time points represent three seasons (winter, spring, and summer) and include both day and night samples. These data demonstrate the major differences between genetic potential and actuality, whereby genomes follow general seasonal trends yet with surprisingly little change in the functional potential over time; transcripts tended to be far more structured by changes occurring between day and night.
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Project description:Understanding trends in the diverse resources provided by large rivers will help balance tradeoffs among stakeholders and inform strategies to mitigate the effects of landscape scale stressors such as climate change and invasive species. Absent a cohesive coordinated effort to assess trends in important large river resources, a logical starting point is to assess our ability to draw inferences from existing efforts. In this paper, we use a common analytical framework to analyze data from five disparate fish monitoring programs to better understand the nature of spatial and temporal trends in large river fish assemblages. We evaluated data from programs that monitor fishes in the Colorado, Columbia, Illinois, Mississippi, and Tallapoosa rivers using non-metric dimensional scaling ordinations and associated tests to evaluate trends in fish assemblage structure and native fish biodiversity. Our results indicate that fish assemblages exhibited significant spatial and temporal trends in all five of the rivers. We also document native species diversity trends that were variable within and between rivers and generally more evident in rivers with higher species richness and programs of longer duration. We discuss shared and basin-specific landscape level stressors. Having a basic understanding of the nature and extent of trends in fish assemblages is a necessary first step towards understanding factors affecting biodiversity and fisheries in large rivers.
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Project description:The active collection of wildlife sighting data by trained observers is expensive, restricted to small geographical areas and conducted infrequently. Reporting of wildlife sightings by members of the public provides an opportunity to collect wildlife data continuously over wider geographical areas, at lower cost. We used individual koala sightings reported by members of the public between 1997 and 2013 in South-East Queensland, Australia (n = 14,076 koala sightings) to describe spatial and temporal trends in koala presence, to estimate koala sighting density and to identify biases associated with sightings. Temporal trends in sightings mirrored the breeding season of koalas. Sightings were high in residential areas (63%), followed by agricultural (15%), and parkland (12%). The study area was divided into 57,780 one-square kilometer grid cells and grid cells with no sightings of koalas decreased over time (from 35% to 21%) indicative of a greater level of spatial overlap of koala home ranges and human activity areas over time. The density of reported koala sightings decreased as distance from primary and secondary roads increased, indicative of a higher search effort near roads. Our results show that koala sighting data can be used to refine koala distribution and population estimates derived from active surveying, on the condition that appropriate bias correction techniques are applied. Collecting koala absence and search effort information and conducting repeated searches for koalas in the same areas are useful approaches to improve the quality of sighting data in citizen science programs.
| S-EPMC6624211 | biostudies-literature
Project description:BackgroundThe development and management of shelf-sea ecosystems require a holistic understanding of the factors that influence the zooplankton structure and ecosystem functions. The Black Sea is an example of such areas influenced by eutrophication, overfishing, climate variability, invasions of the ctenophores Mnemiopsis leidyi followed by Beroe ovata. Thus, there is a set of principal factors which may influence and explain periodicities in the Black Sea ecosystem.MethodsWe analysed a total of 918 samples taken from 1991 to 2017 with intervals of 10 days. Taxa were identified to species, their abundance and biomass were calculated. We tested 12 environmental factors, which may explain zooplankton distribution: temperature, productivity-linked factors (surface chlorophyll as a proxi), wind, turbidity, lowest winter temperature, and concentration of the ctenophore M. leidyi. We used canonical correspondence analyses to find the dominant environmental factors and further regression analyses to retrieve dependences of plankton biomass on the major factors. Periodicities were assessed with the use of the Continuous wavelet transform and tested with use of One-way ANOSIM and PERMANOVA. The distances between ecosystem states in different years were assessed using non-metric multidimensional scaling.ResultsCurrently, temperature and productivity are the major environmental factors driving zooplankton dynamics. Not long ago, before 1999, abundance of M. leidyi was one of the major factors explaining the zooplankton variance. Spectral analysis of species abundances revealed a 4-year transitional period in 1999-2002 (not reported before) when ecosystem adapted to a new invader B. ovata. Statistically robust 2- and 3-year periodicities were retrieved for most plankton taxa and some benthic larvae. We found robust correlations between temperature and surface chlorophyll concentration on one side and plankton abundances and biomass on the other, and retrieved multivariate regressions, which may have a prognostic value.
| S-EPMC6768059 | biostudies-literature