Evidence map›Paper›PMID 33406141›Full record

ArticlePloS one2021

An assessment of temporal, spatial and taxonomic trends in harmful algal toxin exposure in stranded marine mammals from the U.S. New England coast.

Spencer E Fire, Andrea Bogomolni, Robert A DiGiovanni, Greg Early, Tod A Leighfield, Keith Matassa, Glenn A Miller, Kathleen M T Moore, Michael Moore, Misty Niemeyer and 3 more

Open access · goldAbstract 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
1.2field-weighted citation impact, top 24% 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

2 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
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

13 authors at 10 institutions in 1 country.

Spencer E FireFlorida Institute of Technology, Melbourne, FL, United States of America.ORCID 0000-0002-1657-790X
Andrea BogomolniMassachusetts Maritime Academy, Buzzards Bay, Massachusetts, United States of America.
Robert A DiGiovanniAtlantic Marine Conservation Society, Hampton Bays, New York, United States of America.
Greg EarlyIntegrated Statistics, Woods Hole, Massachusetts, United States of America.
Tod A LeighfieldNational Oceanic and Atmospheric Administration, National Ocean Service, Charleston, South Carolina, United States of America.
Keith MatassaOcean Animal Response and Research Alliance, Laguna Niguel, California, United States of America.
Glenn A MillerFlorida Institute of Technology, Melbourne, FL, United States of America.
Kathleen M T MooreInternational Fund for Animal Welfare, Yarmouth Port, Massachusetts, United States of America.
Michael MooreBiology Department, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts, United States of America.
Misty NiemeyerInternational Fund for Animal Welfare, Yarmouth Port, Massachusetts, United States of America.
Katie PugliaresNew England Aquarium, Boston, Massachusetts, United States of America.
Zhihong WangCSS Corporation, Fairfax, VA, United States of America.
Frederick W WenzelNational Oceanic and Atmospheric Administration, National Marine Fisheries Service, Woods Hole, Massachusetts, United States of America.
Florida Institute of Technology · USInternational Fund for Animal Welfare · USIntegrated Statistics (United States) · USMarine Conservation Institute · USMassachusetts Maritime Academy · USNational Oceanic and Atmospheric Administration · USNew England Aquarium · USNOAA National Marine Fisheries Service · USNOAA National Ocean Service · USWoods Hole Oceanographic Institution · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite a long-documented history of severe harmful algal blooms (HABs) in New England coastal waters, corresponding HAB-associated marine mammal mortality events in this region are far less frequent or severe relative to other regions where HABs are common. This long-term survey of the HAB toxins saxitoxin (STX) and domoic acid (DA) demonstrates significant and widespread exposure of these toxins in New England marine mammals, across multiple geographic, temporal and taxonomic groups. Overall, 19% of the 458 animals tested positive for one or more toxins, with 15% and 7% testing positive for STX and DA, respectively. 74% of the 23 different species analyzed demonstrated evidence of toxin exposure. STX was most prevalent in Maine coastal waters, most frequently detected in common dolphins (Delphinus delphis), and most often detected during July and October. DA was most prevalent in animals sampled in offshore locations and in bycaught animals, and most frequently detected in mysticetes, with humpback whales (Megaptera novaeangliae) testing positive at the highest rates. Feces and urine appeared to be the sample matrices most useful for determining the presence of toxins in an exposed animal, with feces samples having the highest concentrations of STX or DA. No relationship was found between the bloom season of toxin-producing phytoplankton and toxin detection rates, however STX was more likely to be present in July and October. No relationship between marine mammal dietary preference and frequency of toxin detection was observed. These findings are an important part of a framework for assessing future marine mammal morbidity and mortality events, as well as monitoring ecosystem health using marine mammals as sentinel organisms for predicting coastal ocean changes.

Indexed as

EcosystemHarmful Algal BloomAnimalsEnvironmental ExposureFecesGeographyKainic AcidMammalsNew EnglandSaxitoxinTime Factorsdomoic acidKainic AcidSaxitoxin

Identifiers

PMID33406141
PMCPMC7787384
OpenAlexW3120152396

What OpenQuestion holds

Textmetadata
LicenceCC0
Read underepoch 390

Registered trials

None linked

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.