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The importance of landscape composition for pest control and crop yield: A global quantitative synthesis

dataset
posted on 2025-10-23, 01:30 authored by Katja Poveda, Heather Grab
<p>Using a global structural equation model of 116 studies from 28 countries, we tested three hypotheses: The ‘natural enemy hypothesis’, that natural areas increase natural enemies and suppress pests; the ‘resource concentration hypothesis’, that simplified agriculture increases pests;  and the ‘agronomic quality hypothesis’ with a structural equation model. This repository contains the dataset and R script for the analysis that examines how landscape composition directly and indirectly affects crop yield, mediated through natural enemies, biological control, and pests, across multiple studies using a structural equation model.</p>

Funding

NSF: DBI-1052875

USDA: 2020-67021-32477

History

Data contact name

Poveda, Katja

Data contact email

kap235@cornell.edu

Publisher

Dryad

Theme

  • Not specified

ISO Topic Category

  • biota

National Agricultural Library Thesaurus terms

pest control; landscapes; structural equation modeling; natural enemies; biological control; equations; data collection; crop yield

Pending citation

  • No

Public Access Level

  • Public

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