Evidence map›Paper›PMID 34428262›Full record

ArticlePloS one2021

Large spatiotemporal variability in metabolic regimes for an urban stream draining four wastewater treatment plants with implications for dissolved oxygen monitoring.

Sarah H Ledford, Jacob S Diamond, Laura Toran

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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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

3 authors.

Sarah H LedfordDepartment of Geosciences, Georgia State University, Atlanta, Georgia, United States of America.ORCID 0000-0003-1802-1961
Jacob S DiamondEnvironnement, Ville & Société (EVS UMR5600), Centre National de la Recherche Scientifique (CNRS), Lyon, France.
Laura ToranDepartment of Earth and Environmental Science, Temple University, Philadelphia, Pennsylvania, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Urbanization and subsequent expansion of wastewater treatment plant (WWTP) capacity has the potential to alter stream metabolic regimes, but the magnitude of this change remains unknown. Indeed, our understanding of downstream WWTP effects on stream metabolism is spatially and temporally limited, and monitoring designs with upstream-downstream comparison sites are rare. Despite this, and despite observed spatiotemporal variability in stream metabolic regimes, regulators typically use snapshot monitoring to assess ecosystem function in receiving streams, potentially leading to biased conclusions about stream health. To address these important practical issues, we assessed the spatiotemporal variability in stream metabolism at nine sites upstream and downstream of four WWTPs in a suburban stream. We used one year (2017-2018) of high-frequency dissolved oxygen (DO) data to model daily gross primary productivity (GPP) and ecosystem respiration (ER). We found that GPP was 1.7-4.0 times higher and ER was 1.2-7.2 times higher downstream of the WWTPs, especially in spring when light was not limited by canopy shading. Critically, we observed that these effects were spatially limited to the kilometer or so just downstream of the plant. These effects were also temporally limited, and metabolic rates upstream of WWTPs were not different from sites downstream of the plant after leaf-out at some sites. Across sites, regardless of their relation to WWTPs, GPP was positively correlated with potential incident light suggesting that light is the dominant control on GPP in this system. Temporal windowing of DO to proposed regulatory monitoring lengths revealed that the violation frequency of water quality criteria depended on both the monitoring interval and start date. We conclude that spatiotemporal variability in metabolism and DO are crucial considerations when developing monitoring programs to assess ecosystem function, and that evidence of WWTP effects may only arise during high light conditions and at limited scales.

Indexed as

Environmental MonitoringWater PurificationEcosystemHumansOxygenSeasonsUrbanizationWater Pollutants, ChemicalWater QualityOxygenWater Pollutants, Chemical

Identifiers

PMID34428262
PMCPMC8384190

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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.