Evidence map›Paper›PMID 39605380›Full record

ArticlebioRxiv : the preprint server for biology2024

How population control of pests is modulated by density dependence: The perspective of genetic biocontrol.

C D Butler, A L Lloyd

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

C D ButlerBiomathematics Graduate Program and Department of Mathematics, North Carolina State University, Raleigh, NC 27606.ORCID 0000-0001-8557-1344
A L LloydBiomathematics Graduate Program and Department of Mathematics, North Carolina State University, Raleigh, NC 27606.ORCID 0000-0002-6389-6321

Funding

Combining Aedes aegypti genomics and modeling to improve gene drive strategies and our understanding of resistance evolutionR01AI139085 · NIAID · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI GOULD, FRED · 2018 to 2022
$1.9M
NIAID NIH HHS R01 AI139085
6 · The paper itself

Abstract

Managing pest species relies critically on mechanisms that regulate population dynamics, particularly those factors that change with population size. These density-dependent factors can help or hinder control efforts and are especially relevant considering recent advances in genetic techniques that allow for precise manipulation of the timing and sex-specificity of a control. Despite this importance, density dependence is often poorly characterized owing to limited data and an incomplete understanding of developmental ecology. To address this issue, we construct and analyze a mathematical model of a pest population with a general control under a wide range of density dependence scenarios. Using this model, we investigate how control performance is affected by the strength of density dependence. By modifying the timing and sex-specificity of the control, we tailor our analysis to simulate different pest control strategies, including conventional and genetic biocontrol methods. We pay particular attention to the latter as case studies by extending the baseline model to include genetic dynamics. Finally, we clarify past work on the dynamics of mechanistic models with density dependence. As expected, we find substantial differences in control performance for differing strengths of density dependence, with populations exhibiting strong density dependence being most resilient to suppression. However, these results change with the size and timing of the control load, as well as the target sex. Interestingly, we also find that population invasion by certain genetic biocontrol strategies is affected by the strength of density dependence. While the model is parameterized using the life history traits of the yellow fever mosquito,

Identifiers

PMID39605380
PMCPMC11601221

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.