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 under...
Guardado en:
Autores principales: | Hannah J Kotula, Guadalupe Peralta, Carol M Frost, Jacqui H Todd, Jason M Tylianakis |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Public Library of Science (PLoS)
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/58b5f1ba8bfc4ec4930378af99d9e11b |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Correction: Predicting direct and indirect non-target impacts of biocontrol agents using machine-learning approaches.
por: Hannah J Kotula, et al.
Publicado: (2021) -
Apparent competition drives community-wide parasitism rates and changes in host abundance across ecosystem boundaries
por: Carol M. Frost, et al.
Publicado: (2016) -
Compatibility of Biocontrol Agent Trichoderma viride with Various Pesticides
por: G Bindu Madhavi, et al.
Publicado: (2011) -
Endophytic fungi as potential biocontrol agents of Phytophthora palmivora in the cocoa plant
por: AGNES VIRGINIA SIMAMORA, et al.
Publicado: (2021) -
Disease severity enhancement by an esterase from non-phytopathogenic yeast Pseudozyma antarctica and its potential as adjuvant for biocontrol agents
por: Hirokazu Ueda, et al.
Publicado: (2018)