Evidence map›Paper›PMID 35478314›Full record

ArticleEcology letters2022

Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude.

Mischa P Turschwell, Sean R Connolly, Ralf B Schäfer, Frederik De Laender, Max D Campbell, Chrystal Mantyka-Pringle, Michelle C Jackson, Mira Kattwinkel, Michael Sievers, Roman Ashauer and 4 more

Abstract readLetter
In one paragraph

Article in Ecology letters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
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

21 citing papers in PubMed.

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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

14 authors.

Mischa P TurschwellCoastal and Marine Research Centre, School of Environment and Science, Australian Rivers Institute, Griffith University, Gold Coast, Queensland, Australia.ORCID https://orcid.org/0000-0002-6307-9604
Sean R ConnollyNaos Marine Laboratories, Smithsonian Tropical Research Institute, Balboa Ancón, Republic of Panama.ORCID https://orcid.org/0000-0003-1537-0859
Ralf B SchäferQuantitative Landscape Ecology, iES-Institute for Environmental Sciences, University Koblenz-Landau, Landau in der Pfalz, Germany.
Frederik De LaenderResearch Unit of Environmental and Evolutionary Biology, Namur Institute of Complex Systems and Institute of Life, Earth, and the Environment, University of Namur, Namur, Belgium.ORCID https://orcid.org/0000-0002-4060-973X
Max D CampbellCoastal and Marine Research Centre, School of Environment and Science, Australian Rivers Institute, Griffith University, Gold Coast, Queensland, Australia.ORCID https://orcid.org/0000-0003-2860-1580
Chrystal Mantyka-PringleWildlife Conservation Society Canada, Whitehorse, Yukon Territory, Canada.
Michelle C JacksonDepartment of Zoology, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0003-2227-1111
Mira KattwinkelQuantitative Landscape Ecology, iES-Institute for Environmental Sciences, University Koblenz-Landau, Landau in der Pfalz, Germany.
Michael SieversCoastal and Marine Research Centre, School of Environment and Science, Australian Rivers Institute, Griffith University, Gold Coast, Queensland, Australia.ORCID https://orcid.org/0000-0001-7162-1830
Roman AshauerEnvironment Department, University of York, York, UK.
Isabelle M CôtéEarth to Ocean Research Group, Department of Biological Sciences, Simon Fraser University, Burnaby, British Columbia, Canada.
Rod M ConnollyCoastal and Marine Research Centre, School of Environment and Science, Australian Rivers Institute, Griffith University, Gold Coast, Queensland, Australia.ORCID https://orcid.org/0000-0001-6223-1291
Paul J van den BrinkAquatic Ecology and Water Quality Management Group, Wageningen University, Wageningen, The Netherlands.
Christopher J BrownCoastal and Marine Research Centre, School of Environment and Science, Australian Rivers Institute, Griffith University, Gold Coast, Queensland, Australia.ORCID https://orcid.org/0000-0002-7271-4091

Funding

Australian Research Council DP180103124Australian Research Council FT210100792Griffith University
6 · The paper itself

Abstract

Predicting the impacts of multiple stressors is important for informing ecosystem management but is impeded by a lack of a general framework for predicting whether stressors interact synergistically, additively or antagonistically. Here, we use process-based models to study how interactions generalise across three levels of biological organisation (physiological, population and consumer-resource) for a two-stressor experiment on a seagrass model system. We found that the same underlying processes could result in synergistic, additive or antagonistic interactions, with interaction type depending on initial conditions, experiment duration, stressor dynamics and consumer presence. Our results help explain why meta-analyses of multiple stressor experimental results have struggled to identify predictors of consistently non-additive interactions in the natural environment. Experiments run over extended temporal scales, with treatments across gradients of stressor magnitude, are needed to identify the processes that underpin how stressors interact and provide useful predictions to management.

Indexed as

EcosystemEnvironmentantagonismconsumer-resourceseagrassstressor interactionssynergy

Identifiers

PMID35478314
PMCPMC9320941

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.