<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<ArticleSet>
<Article>
<Journal>
<PublisherName>International Academy of Ecology and Environmental Sciences</PublisherName>
<JournalTitle>Arthropods</JournalTitle>
<eissn>2224-4255</eissn>
<Volume>15</Volume>
<Issue>4</Issue>
<PubDate PubStatus="ppublish">
<Year>2026</Year>
<Month>12</Month>
<Day>1</Day>
</PubDate>
</Journal>
<ArticleTitle>Reflecting Integrated Pest Management and constructing a Dynamic Resilience-based IPM framework</ArticleTitle>
<Pages>183-206</Pages>
<Language>EN</Language>
<AuthorList>
<Author>WenJun Zhang</Author>
</AuthorList>
<ArticleList>
<ArticleId IdType="url">http://www.iaees.org/publications/journals/arthropods/articles/2026-15(4)/Dynamic-Resilience-based-IPM-framework.pdf</ArticleId>>
</ArticleList>
<Abstract>
Integrated Pest Management has been championed for more than half a century as the rational middle ground between chemical-dependent crop protection and ecologically benign but knowledge-intensive alternatives. A vast body of evidence confirms that well-implemented IPM delivers measurable economic, ecological, and social benefits, yet its global adoption remains patchy and often symbolic, while reliance on broad-spectrum synthetic insecticides is stubbornly high. This paper conducts a critical multidisciplinary review to diagnose why a conceptually robust and evidence-rich paradigm persistently underperforms. We identify the root cause as a deep-seated mismatch between the static, optimization-oriented engineering logic embedded in conventional IPM thinking and the dynamic, nonlinear, self-organizing nature of agroecosystems. Drawing on resilience theory, adaptive co-management, and complex adaptive system perspectives, we articulate an original framework termed Dynamic Resilience-based Integrated Pest Management. DR-IPM replaces fixed economic thresholds with dynamic adaptive thresholds that couple real-time population signals, predator-prey ratios, crop compensatory capacity, weather forecasts, and market prices. It organizes responses across nested spatial scales from the field to the landscape, mandates strategic redundancy in control tactics, institutionalizes participatory adaptive learning loops, and valorizes ecosystem services through smart contracts and verified green credits. The framework is operationalized through an agricultural digital twin platform powered by multi-agent simulation and continuous stakeholder sensing. DR-IPM constitutes a shift from managing pest populations to stewarding the self-regenerative capacity of social-ecological systems, turning IPM from a prescriptive toolkit into an adaptive governance philosophy. We outline its implementation pathway, discuss differentiated trajectories for smallholder and large-scale agriculture, and propose a research agenda to empirically test the core hypotheses.
</Abstract>
</Article>
</ArticleSet>
