Evidence map›Paper›PMID 33247223›Full record

ArticleScientific reports2020

Population viability in a host-parasitoid system is mediated by interactions between population stage structure and life stage differential susceptibility to toxicants.

John D Stark, Jenifer K McIntyre, John E Banks

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

John D StarkEcotoxicology Program, Department of Entomology, Research and Extension Center, Washington State University, Puyallup, WA, 98371, USA. starkj@wsu.edu.
Jenifer K McIntyreResearch and Extension Center, School of the Environment, Washington State University, Puyallup, WA, 98371, USA.
John E BanksUndergraduate Research Opportunities Center, California State University, 100 Campus Center Seaside, Monterey Bay, CA, 93955, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The effects of toxicants, such as pesticides, may be more severe for some life stages of an organism than others. However, in most toxicity studies, data is developed for only one life stage, which may lead to misleading interpretations. Furthermore, population stage-structure may interact with differential susceptibility, especially when populations consist of higher proportions of individuals in more susceptible stages at the time of toxicant exposure. We explore the interaction of differential stage susceptibility and stage distribution using a stage-structured Lefkovitch matrix model. We incorporate lab-derived toxicity data for a common parasitoid, the braconid Diaeretiella rapae (M'Intosh), a common natural enemy of the cabbage aphid (Brevicoryne brassicae L.), exposed to the pesticide imidacloprid. We compare population outcomes of simulations in which we vary both the population stage structure along with the susceptibility of each stage to toxicants. Our results illustrate an interaction between differential susceptibility and initial stage distribution, highlighting the fact that both of these demographic features should be considered in interpreting toxicity data and the development of ecological risk assessments.

Indexed as

Host-Parasite InteractionsAnimalsBrassicaInsecticidesLarvaNeonicotinoidsNitro CompoundsPolydnaviridaePopulation DynamicsimidaclopridInsecticidesNeonicotinoidsNitro Compounds

Identifiers

PMID33247223
PMCPMC7699617

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.