Evidence map›Paper›PMID 35735258›Full record

ArticleEcological applications : a publication of the Ecological Society of America2022

Archetype models upscale understanding of natural pest control response to land-use change.

Nikolaos Alexandridis, Glenn Marion, Rebecca Chaplin-Kramer, Matteo Dainese, Johan Ekroos, Heather Grab, Mattias Jonsson, Daniel S Karp, Carsten Meyer, Megan E O'Rourke and 7 more

Abstract read
In one paragraph

Article in Ecological applications : a publication of the Ecological Society of America, 2022. 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
–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

2 citing papers in PubMed.

  1. Article
  2. Archetype models upscale understanding of natural pest control response to land-use change.Ecological applications : a publication of the Ecological Society of America · 2022
    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

17 authors.

Nikolaos AlexandridisLund University, Centre for Environmental and Climate Science (CEC), Lund, Sweden.
Glenn MarionBiomathematics and Statistics Scotland, Edinburgh, UK.
Rebecca Chaplin-KramerStanford University, Woods Institute for the Environment, Natural Capital Project, Stanford, California, USA.
Matteo DaineseEurac Research, Institute for Alpine Environment, Bozen/Bolzano, Italy.ORCID 0000-0001-7052-5572
Johan EkroosLund University, Centre for Environmental and Climate Science (CEC), Lund, Sweden.
Heather GrabDepartment of Entomology, Cornell University, Ithaca, New York, USA.
Mattias JonssonDepartment of Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Daniel S KarpDepartment of Wildlife, Fish, and Conservation Biology, University of California - Davis, Davis, California, USA.
Carsten MeyerGerman Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
Megan E O'RourkeDepartment of Horticulture, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA.
Mikael PontarpDepartment of Biology, Lund University, Lund, Sweden.
Katja PovedaDepartment of Entomology, Cornell University, Ithaca, New York, USA.
Ralf SeppeltMartin Luther University Halle-Wittenberg, Institute of Geoscience & Geography, Halle (Saale), Germany.
Henrik G SmithLund University, Centre for Environmental and Climate Science (CEC), Lund, Sweden.
Richard J WaltersLund University, Centre for Environmental and Climate Science (CEC), Lund, Sweden.
Yann CloughLund University, Centre for Environmental and Climate Science (CEC), Lund, Sweden.
Emily A MartinLeibniz University Hannover, Institute of Geobotany, Zoological Biodiversity, Hannover, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Control of crop pests by shifting host plant availability and natural enemy activity at landscape scales has great potential to enhance the sustainability of agriculture. However, mainstreaming natural pest control requires improved understanding of how its benefits can be realized across a variety of agroecological contexts. Empirical studies suggest significant but highly variable responses of natural pest control to land-use change. Current ecological models are either too specific to provide insight across agroecosystems or too generic to guide management with actionable predictions. We suggest obtaining the full benefit of available empirical, theoretical, and methodological knowledge by combining trait-mediated understanding from correlative studies with the explicit representation of causal relationships achieved by mechanistic modeling. To link these frameworks, we adapt the concept of archetypes, or context-specific generalizations, from sustainability science. Similar responses of natural pest control to land-use gradients across cases that share key attributes, such as functional traits of focal organisms, indicate general processes that drive system behavior in a context-sensitive manner. Based on such observations of natural pest control, a systematic definition of archetypes can provide the basis for mechanistic models of intermediate generality that cover all major agroecosystems worldwide. Example applications demonstrate the potential for upscaling understanding and improving predictions of natural pest control, based on knowledge transfer and scientific synthesis. A broader application of this mechanistic archetype approach promises to enhance ecology's contribution to natural resource management across diverse regions and social-ecological contexts.

Indexed as

EcosystemPest Control, BiologicalAgricultureCrops, AgriculturalNatural ResourcesPest Controlarchetypeconservation biological controlcropecological modellandscapeland usenatural enemynatural pest controlpestupscale

Identifiers

PMID35735258
PMCPMC10078142

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.