Evidence map›Paper›PMID 35769867›Full record

ArticleEcological modelling2020

Quantitative food web modeling unravels the importance of the microphytobenthos-meiofauna pathway for a high trophic transfer by meiofauna in soft-bottom intertidal food webs.

L H van der Heijden, N Niquil, M Haraldsson, R M Asmus, S R Pacella, M Graeve, J Rzeznik-Orignac, H Asmus, B Saint-Béat, B Lebreton

Open access · greenAbstract read
In one paragraph

Article in Ecological modelling, 2020. 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
2.2field-weighted citation impact, top 14% 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, 26 citations in OpenAlex.

  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

10 authors at 4 institutions in 7 countries.

L H van der HeijdenUMR 7266 Littoral, Environnement et Sociétés (CNRS - University of La Rochelle), Institut du littoral et de l'environnement, 2 rue Olympe de Gouges, 17000 La Rochelle, France.
N NiquilCentre National de la Recherche Scientifique (CNRS)/University of Caen Normandy, BOREA (MNHN, IRD, UA, SU), 14032 Caen, France.
M HaraldssonCentre National de la Recherche Scientifique (CNRS)/University of Caen Normandy, BOREA (MNHN, IRD, UA, SU), 14032 Caen, France.
R M AsmusAlfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Wattenmeerstation Sylt, Hafenstrasse 43, 25992 List/Sylt, Germany.
S R PacellaPacific Ecological Systems Division, Center for Public Health and Environmental Assessment, Office of Research and Development, United States Environmental Protection Agency, Newport, OR 97365, USA.
M GraeveAlfred Wegener Institut Helmholtz Centre for Polar- and Marine Research, Bremerhaven, Germany.
J Rzeznik-OrignacSorbonne Université, UPMC Univ Paris 06, CNRS, Laboratoire d'Ecogéochimie des Environnements Benthiques (LECOB UMR 8222), Observatoire Océanologique, 66650 Banyuls/Mer, France.
H AsmusAlfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Wattenmeerstation Sylt, Hafenstrasse 43, 25992 List/Sylt, Germany.
B Saint-BéatQuébec-Océan and Takuvik, Département de Biologie, Université Laval, Québec City, QC, Canada.
B LebretonUMR 7266 Littoral, Environnement et Sociétés (CNRS - University of La Rochelle), Institut du littoral et de l'environnement, 2 rue Olympe de Gouges, 17000 La Rochelle, France.
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung · DECentre National de la Recherche Scientifique · FREnvironmental Protection Agency · USUniversité Laval · CA

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

Meiofauna are known to have an important role on many ecological processes, although, their role in food web dynamics is often poorly understood, partially as they have been an overlooked and under sampled organism group. Here, we used quantitative food web modeling to evaluate the trophic relationship between meiofauna and their food sources and how meiofauna can mediate the carbon flow to higher trophic levels in five contrasting soft-bottom intertidal habitats (including seagrass beds, mudflats and sandflats). Carbon flow networks were constructed using the linear inverse model-Markov chain Monte Carlo technique, with increased resolution of the meiofauna compartments (i.e. biomass and feeding ecology of the different trophic groups of meiofauna) compared to most previous modeling studies. These models highlighted that the flows between the highly productive microphytobenthos and the meiofauna compartments play an important role in transferring carbon to the higher trophic levels, typically more efficiently so than macrofauna. The pathway from microphytobenthos to meiofauna represented the largest flow in all habitats and resulted in high production of meiofauna independent of habitat. All trophic groups of meiofauna, except for selective deposit feeders, had a very high dependency on microphytobenthos. Selective deposit feeders relied instead on a wider range of food sources, with varying contributions of bacteria, microphytobenthos and sediment organic matter. Ecological network analyses (e.g. cycling, throughput and ascendency) of the modeled systems highlighted the close positive relationship between the food web efficiency and the assimilation of high-quality food sources by primary consumers, e.g. meiofauna and macrofauna. Large proportions of these flows can be attributed to trophic groups of meiofauna. The sensitivity of the network properties to the representation of meiofauna in the models leads to recommending a greater attention in ecological data monitoring and integrating meiofauna into food web models.

Indexed as

food web modelintertidal habitatslinear inverse modelmeiofaunamicrophytobenthosstable isotope mixing models

Identifiers

PMID35769867
PMCPMC9238397
OpenAlexW3030961278

What OpenQuestion holds

Textmetadata
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.