Synergistic and antagonistic interactions between plant defences and biological pest control
Plants have evolved various defence mechanisms against herbivorous pests, ranging from physical barriers (constitutive defences) to the release of toxins (induced defences) in response to an attack. Plant defences are not always target-specific and can also act against natural enemies of these pests...
| Autores: | , , , , |
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| Formato: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2024 |
| País: | España |
| Recursos: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/370085 |
| Acesso em linha: | http://hdl.handle.net/10261/370085 https://api.elsevier.com/content/abstract/scopus_id/85198599616 |
| Access Level: | acceso abierto |
| Palavra-chave: | Integrated pest management | Modelling | Multi-trophic interactions | Predatory bugs | Predatory mites | Thrips | Tomato | Whiteflies |
| Resumo: | Plants have evolved various defence mechanisms against herbivorous pests, ranging from physical barriers (constitutive defences) to the release of toxins (induced defences) in response to an attack. Plant defences are not always target-specific and can also act against natural enemies of these pests. This could potentially become problematic when considering both plant defences and predators as part of an Integrated Pest Management (IPM) scheme. Here we used a predator-prey model to capture the population dynamics of a biological control system to investigate the conditions where both plant defences and biological control act synergistically, leading to better pest control, and under what condition antagonistic outcomes could be expected. Our results demonstrate that both antagonistic and synergistic interactions are observable under small changes in key parameters, such as predation and growth rates. We then compared the qualitative model predictions against a set of population dynamic experiments using the |
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