ReviewEvolutionary applications2022
Biological control needs evolutionary perspectives of ecological interactions.
Review in Evolutionary applications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Insect pests in Brassica napus crops: toward ecologically optimized integrated pest management.Pest management science · 2026Review
- Potential of bacteria isolated from chitin-enriched soil against Euschistus heros (Hemiptera: Pentatomidae).Pest management science · 2026Article
- Anthropogenic Pressures, Rather Than Plant Vigour, Promote Insect Herbivory Rates onEcology and evolution · 2026Article
- Artificial intelligence in the mass production of natural enemies for biological control in modern agriculture.Pest management science · 2025Review
- Genomic structure and life history variation of isofemale lineages of Myzus persicae with different levels of parasitization by Diaeretiella rapae.Scientific reports · 2025Article
- Genomic characterization and pathogenic mechanisms ofNew microbes and new infections · 2025Article
- Could hybridization increase the establishment success of the biological control agentEcology and evolution · 2024Article
- Go west: Population genomics reveals unexpected population fluctuations and little gene flow in Western hemisphere populations of the predatory lady beetle,Evolutionary applications · 2024Article
- Kill rate as a tool in efficiency evaluation of Neoseiulus californicus (Acari: Phytoseiidae) mass reared on factitious food.Journal of insect science (Online) · 2023Article
- The Fight against Plant-Parasitic Nematodes: Current Status of Bacterial and Fungal Biocontrol Agents.Pathogens (Basel, Switzerland) · 2022Review
- Evolution in agricultural systems: Moving toward the understanding of complexity.Evolutionary applications · 2022Review
- Biological control needs evolutionary perspectives of ecological interactions.Evolutionary applications · 2022Review
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Authors and funding
4 authors.
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Abstract
While ecological interactions have been identified as determinant for biological control efficiency, the role of evolution remains largely underestimated in biological control programs. With the restrictions on the use of both pesticides and exotic biological control agents (BCAs), the evolutionary optimization of local BCAs becomes central for improving the efficiency and the resilience of biological control. In particular, we need to better account for the natural processes of evolution to fully understand the interactions of pests and BCAs, including in biocontrol strategies integrating human manipulations of evolution (i.e., artificial selection and genetic engineering). In agroecosystems, the evolution of BCAs traits and performance depends on heritable phenotypic variation, trait genetic architecture, selection strength, stochastic processes, and other selective forces. Humans can manipulate these natural processes to increase the likelihood of evolutionary trait improvement, by artificially increasing heritable phenotypic variation, strengthening selection, controlling stochastic processes, or overpassing evolution through genetic engineering. We highlight these facets by reviewing recent studies addressing the importance of natural processes of evolution and human manipulations of these processes in biological control. We then discuss the interactions between the natural processes of evolution occurring in agroecosystems and affecting the artificially improved BCAs after their release. We emphasize that biological control cannot be summarized by interactions between species pairs because pests and biological control agents are entangled in diverse communities and are exposed to a multitude of deterministic and stochastic selective forces that can change rapidly in direction and intensity. We conclude that the combination of different evolutionary approaches can help optimize BCAs to remain efficient under changing environmental conditions and, ultimately, favor agroecosystem sustainability.
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