Evidence map›Paper›PMID 19813039›Full record

ArticleEnvironmental science and pollution research international2010

A novel method using sedimentary metals and GIS for measuring anthropogenic change in coastal lake environments.

Marco Antonio Olmos, Gavin F Birch

Abstract read
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In one paragraph

Article in Environmental science and pollution research international, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 22 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Marco Antonio OlmosEnvironmental Geology Group, School of Geosciences, The University of Sydney, Sydney, NSW, 2006, Australia. marco@geosci.usyd.edu.au
Gavin F Birch
University of Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND, AIM AND SCOPE: A new method using sedimentary metals and geographic information system as indicators for assessing temporal and spatial anthropogenic change in estuaries has been applied to a large coastal lake (Lake Macquarie) in New South Wales, Australia. MATERIALS, METHODS AND

resultsTwo vintages of data (1975 and 2003) on surficial sediment metal (Cd, Cu, Pb and Zn) concentrations combined with (210)Pb core profiles were used to determine past changes in sediment quality and to predict possible future relaxation rates for the entire lake area in response to change in anthropogenic pressure. Sediment cores showed distinct vertical profiles; sedimentation rates in the northern part of the lake were consistent (14 mm year(-1)) over the 55-year period investigated. DISCUSSION AND

conclusionsSurficial metal concentrations were highest in the 1975 sediment than in the 2003 samples, with the northern part of Lake Macquarie having much greater metal concentrations than the rest of the lake. Past and future declining sedimentary metal concentrations in the northern part of the lake were expected due to the closure of a nearby Pb-Zn smelter; however, possible increases in Cu in the south of the lake to the year 2020 were surprising. The new method presented in this study can assist estuary managers by providing data on past, present and future conditions, which are essential in making informed decisions for the improvement of estuarine systems.

Indexed as

Environmental MonitoringFresh WaterGeographic Information SystemsGeographyGeologic SedimentsKineticsMetals, HeavyRadiometric DatingWater Pollutants, ChemicalMetals, HeavyWater Pollutants, Chemical

Identifiers

PMID19813039
OpenAlexW2000563945

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.