Evidence map›Paper›PMID 37604831›Full record

ArticleScientific reports2023

Increasing landscape heterogeneity as a win-win solution to manage trade-offs in biological control of crop and woodland pests.

Axelle Tortosa, Brice Giffard, Clélia Sirami, Laurent Larrieu, Sylvie Ladet, Aude Vialatte

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Axelle TortosaUniversité de Toulouse, INRAE, DYNAFOR, Castanet-Tolosan, France. axelle.tortosa@inrae.fr.ORCID http://orcid.org/0000-0002-8668-4559
Brice GiffardBordeaux Sciences Agro, INRAE, ISVV, SAVE, 33140, Villenave d'Ornon, France.
Clélia SiramiUniversité de Toulouse, INRAE, DYNAFOR, Castanet-Tolosan, France.
Laurent LarrieuUniversité de Toulouse, INRAE, DYNAFOR, Castanet-Tolosan, France.
Sylvie LadetUniversité de Toulouse, INRAE, DYNAFOR, Castanet-Tolosan, France.
Aude VialatteUniversité de Toulouse, INRAE, DYNAFOR, Castanet-Tolosan, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Agriculture and forestry cover more than 75% of Europe, and invertebrate pests are a costly challenge for these two economic sectors. Landscape management is increasingly promoted as a solution to enhance biological pest control, but little is known on its effects on adjacent crop fields and woodlands. This study aims to explore the effect of the proportion of woodlands and permanent grasslands as well as crop diversity on biological pest control simultaneously in cereals fields and woodland patches, in south-western France. We used different types of sentinel prey as well as bird and carabid community metrics to assess biological pest control potential in these two ecosystems. We first show that land cover variables influence biological pest control both in cereal fields and woodland patches, but have antagonistic effects in the two ecosystems. Although results vary according to the biological control indicator considered, we show that increasing landscape heterogeneity represents a valuable solution to manage trade-offs and promote higher average predation rates across forests and cereal fields. Our study therefore calls for more integrative studies to identify landscape management strategies that enable nature-based solutions across ecosystems.

Indexed as

EcosystemForestsAgricultureEdible GrainEnvironmental BiomarkersEnvironmental Biomarkers

Identifiers

PMID37604831
PMCPMC10442452

What OpenQuestion holds

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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.