Cargando…
Predicting direct and indirect non-target impacts of biocontrol agents using machine-learning approaches
Biological pest control (i.e. ‘biocontrol’) agents can have direct and indirect non-target impacts, and predicting these effects (especially indirect impacts) remains a central challenge in biocontrol risk assessment. The analysis of ecological networks offers a promising approach to understanding t...
Autores principales: | Kotula, Hannah J., Peralta, Guadalupe, Frost, Carol M., Todd, Jacqui H., Tylianakis, Jason M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8168882/ https://www.ncbi.nlm.nih.gov/pubmed/34061885 http://dx.doi.org/10.1371/journal.pone.0252448 |
Ejemplares similares
-
Correction: Predicting direct and indirect non-target impacts of biocontrol agents using machine-learning approaches
por: Kotula, Hannah J., et al.
Publicado: (2021) -
Apparent competition drives community-wide parasitism rates and changes in host abundance across ecosystem boundaries
por: Frost, Carol M., et al.
Publicado: (2016) -
Nematodes as biocontrol agents /
Publicado: (2005) -
A machine‐learning approach to predict success of a biocontrol for invasive Eurasian watermilfoil reduction
por: White, Diana T., et al.
Publicado: (2022) -
Utilizing associational resistance for biocontrol: impacted by temperature, supported by indirect defence
por: Himanen, Sari J, et al.
Publicado: (2015)