Revisiting the influence of learning in predator functional response, how it can lead to shapes different from type III

Autores
Bruzzone, Octavio Augusto; Aguirre, María Belén; Hill, Jorge Guillermo; Virla, Eduardo Gabriel; Logarzo, Guillermo Alejandro
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Predator/parasitoid functional response is one of the main tools used to study predation behavior, and in assessing the potential of biological control candidates. It is generally accepted that predator learning in prey searching and manipulation can produce the appearance of a type III functional response. Holling proposed that in the presence of alternative prey, at some point the predator would shift the preferred prey, leading to the appearance of a sigmoid function that characterized that functional response. This is supported by the analogy between enzyme kinetics and functional response that Holling used as the basis for developing this theory. However, after several decades, sigmoidal functional responses appear in the absence of alternative prey in most of the biological taxa studied. Here, we propose modeling the effect of learning on the functional response by using the explicit incorporation of learning curves in the parameters of the Holling functional response, the attack rate (a), and the manipulation time (h). We then study how the variation in the parameters of the learning curves causes variations in the shape of the functional response curve. We found that the functional response product of learning can be either type I, II, or III, depending on what parameters act on the organism, and how much it can learn throughout the length of the study. Therefore, the presence of other types of curves should not be automatically associated with the absence of learning. These results are important from an ecological point of view because when type III functional response is associated with learning, it is generally accepted that it can operate as a stabilizing factor in population dynamics. Our results, to the contrary, suggest that depending on how it acts, it may even be destabilizing by generating the appearance of functional responses close to type I.
EEA Bariloche
Fil: Bruzzone, Octavio Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina
Fil: Bruzzone, Octavio Augusto. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina
Fil: Aguirre, María Belén. Fundación para el Estudio de Especies Invasivas; Argentina
Fil: Aguirre, María Belén. Consejo Nacional de Investigaciones Científicas y Tecnológicas. Fundación para el Estudio de Especies Invasivas; Argentina
Fil: Hill, Jorge Guillermo. Universidad Nacional de Tucumán. Facultad de Agronomía y Zootecnia; Argentina
Fil: Virla, Eduardo G. Fundación Miguel Lillo. Instituto de Entomología; Argentina
Fil: Virla, Eduardo G. Consejo Nacional de Investigaciones Científicas y Técnicas. Planta Piloto de Pocesos Industriales Microbiológicos (PROIMI-Biotecnología); Argentina
Fil: Logarzo, Guillermo Alejandro. Fundación para el Estudio de Especies Invasivas; Argentina
Fuente
Ecology and Evolution 2 (2) : e8593. (February 2022)
Materia
Depredadores
Control Biológico
Relaciones Predador Presa
Parasitoides
Predators
Biological Control
Predator Prey Relations
Parasitoids
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
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oai_identifier_str oai:localhost:20.500.12123/14891
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spelling Revisiting the influence of learning in predator functional response, how it can lead to shapes different from type IIIBruzzone, Octavio AugustoAguirre, María BelénHill, Jorge GuillermoVirla, Eduardo GabrielLogarzo, Guillermo AlejandroDepredadoresControl BiológicoRelaciones Predador PresaParasitoidesPredatorsBiological ControlPredator Prey RelationsParasitoidsPredator/parasitoid functional response is one of the main tools used to study predation behavior, and in assessing the potential of biological control candidates. It is generally accepted that predator learning in prey searching and manipulation can produce the appearance of a type III functional response. Holling proposed that in the presence of alternative prey, at some point the predator would shift the preferred prey, leading to the appearance of a sigmoid function that characterized that functional response. This is supported by the analogy between enzyme kinetics and functional response that Holling used as the basis for developing this theory. However, after several decades, sigmoidal functional responses appear in the absence of alternative prey in most of the biological taxa studied. Here, we propose modeling the effect of learning on the functional response by using the explicit incorporation of learning curves in the parameters of the Holling functional response, the attack rate (a), and the manipulation time (h). We then study how the variation in the parameters of the learning curves causes variations in the shape of the functional response curve. We found that the functional response product of learning can be either type I, II, or III, depending on what parameters act on the organism, and how much it can learn throughout the length of the study. Therefore, the presence of other types of curves should not be automatically associated with the absence of learning. These results are important from an ecological point of view because when type III functional response is associated with learning, it is generally accepted that it can operate as a stabilizing factor in population dynamics. Our results, to the contrary, suggest that depending on how it acts, it may even be destabilizing by generating the appearance of functional responses close to type I.EEA BarilocheFil: Bruzzone, Octavio Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; ArgentinaFil: Bruzzone, Octavio Augusto. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; ArgentinaFil: Aguirre, María Belén. Fundación para el Estudio de Especies Invasivas; ArgentinaFil: Aguirre, María Belén. Consejo Nacional de Investigaciones Científicas y Tecnológicas. Fundación para el Estudio de Especies Invasivas; ArgentinaFil: Hill, Jorge Guillermo. Universidad Nacional de Tucumán. Facultad de Agronomía y Zootecnia; ArgentinaFil: Virla, Eduardo G. Fundación Miguel Lillo. Instituto de Entomología; ArgentinaFil: Virla, Eduardo G. Consejo Nacional de Investigaciones Científicas y Técnicas. Planta Piloto de Pocesos Industriales Microbiológicos (PROIMI-Biotecnología); ArgentinaFil: Logarzo, Guillermo Alejandro. Fundación para el Estudio de Especies Invasivas; ArgentinaWiley2023-08-09T13:54:53Z2023-08-09T13:54:53Z2022-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/14891https://onlinelibrary.wiley.com/doi/10.1002/ece3.85932045-7758https://doi.org/10.1002/ece3.8593Ecology and Evolution 2 (2) : e8593. (February 2022)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-10-16T09:31:13Zoai:localhost:20.500.12123/14891instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-10-16 09:31:13.603INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Revisiting the influence of learning in predator functional response, how it can lead to shapes different from type III
title Revisiting the influence of learning in predator functional response, how it can lead to shapes different from type III
spellingShingle Revisiting the influence of learning in predator functional response, how it can lead to shapes different from type III
Bruzzone, Octavio Augusto
Depredadores
Control Biológico
Relaciones Predador Presa
Parasitoides
Predators
Biological Control
Predator Prey Relations
Parasitoids
title_short Revisiting the influence of learning in predator functional response, how it can lead to shapes different from type III
title_full Revisiting the influence of learning in predator functional response, how it can lead to shapes different from type III
title_fullStr Revisiting the influence of learning in predator functional response, how it can lead to shapes different from type III
title_full_unstemmed Revisiting the influence of learning in predator functional response, how it can lead to shapes different from type III
title_sort Revisiting the influence of learning in predator functional response, how it can lead to shapes different from type III
dc.creator.none.fl_str_mv Bruzzone, Octavio Augusto
Aguirre, María Belén
Hill, Jorge Guillermo
Virla, Eduardo Gabriel
Logarzo, Guillermo Alejandro
author Bruzzone, Octavio Augusto
author_facet Bruzzone, Octavio Augusto
Aguirre, María Belén
Hill, Jorge Guillermo
Virla, Eduardo Gabriel
Logarzo, Guillermo Alejandro
author_role author
author2 Aguirre, María Belén
Hill, Jorge Guillermo
Virla, Eduardo Gabriel
Logarzo, Guillermo Alejandro
author2_role author
author
author
author
dc.subject.none.fl_str_mv Depredadores
Control Biológico
Relaciones Predador Presa
Parasitoides
Predators
Biological Control
Predator Prey Relations
Parasitoids
topic Depredadores
Control Biológico
Relaciones Predador Presa
Parasitoides
Predators
Biological Control
Predator Prey Relations
Parasitoids
dc.description.none.fl_txt_mv Predator/parasitoid functional response is one of the main tools used to study predation behavior, and in assessing the potential of biological control candidates. It is generally accepted that predator learning in prey searching and manipulation can produce the appearance of a type III functional response. Holling proposed that in the presence of alternative prey, at some point the predator would shift the preferred prey, leading to the appearance of a sigmoid function that characterized that functional response. This is supported by the analogy between enzyme kinetics and functional response that Holling used as the basis for developing this theory. However, after several decades, sigmoidal functional responses appear in the absence of alternative prey in most of the biological taxa studied. Here, we propose modeling the effect of learning on the functional response by using the explicit incorporation of learning curves in the parameters of the Holling functional response, the attack rate (a), and the manipulation time (h). We then study how the variation in the parameters of the learning curves causes variations in the shape of the functional response curve. We found that the functional response product of learning can be either type I, II, or III, depending on what parameters act on the organism, and how much it can learn throughout the length of the study. Therefore, the presence of other types of curves should not be automatically associated with the absence of learning. These results are important from an ecological point of view because when type III functional response is associated with learning, it is generally accepted that it can operate as a stabilizing factor in population dynamics. Our results, to the contrary, suggest that depending on how it acts, it may even be destabilizing by generating the appearance of functional responses close to type I.
EEA Bariloche
Fil: Bruzzone, Octavio Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina
Fil: Bruzzone, Octavio Augusto. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina
Fil: Aguirre, María Belén. Fundación para el Estudio de Especies Invasivas; Argentina
Fil: Aguirre, María Belén. Consejo Nacional de Investigaciones Científicas y Tecnológicas. Fundación para el Estudio de Especies Invasivas; Argentina
Fil: Hill, Jorge Guillermo. Universidad Nacional de Tucumán. Facultad de Agronomía y Zootecnia; Argentina
Fil: Virla, Eduardo G. Fundación Miguel Lillo. Instituto de Entomología; Argentina
Fil: Virla, Eduardo G. Consejo Nacional de Investigaciones Científicas y Técnicas. Planta Piloto de Pocesos Industriales Microbiológicos (PROIMI-Biotecnología); Argentina
Fil: Logarzo, Guillermo Alejandro. Fundación para el Estudio de Especies Invasivas; Argentina
description Predator/parasitoid functional response is one of the main tools used to study predation behavior, and in assessing the potential of biological control candidates. It is generally accepted that predator learning in prey searching and manipulation can produce the appearance of a type III functional response. Holling proposed that in the presence of alternative prey, at some point the predator would shift the preferred prey, leading to the appearance of a sigmoid function that characterized that functional response. This is supported by the analogy between enzyme kinetics and functional response that Holling used as the basis for developing this theory. However, after several decades, sigmoidal functional responses appear in the absence of alternative prey in most of the biological taxa studied. Here, we propose modeling the effect of learning on the functional response by using the explicit incorporation of learning curves in the parameters of the Holling functional response, the attack rate (a), and the manipulation time (h). We then study how the variation in the parameters of the learning curves causes variations in the shape of the functional response curve. We found that the functional response product of learning can be either type I, II, or III, depending on what parameters act on the organism, and how much it can learn throughout the length of the study. Therefore, the presence of other types of curves should not be automatically associated with the absence of learning. These results are important from an ecological point of view because when type III functional response is associated with learning, it is generally accepted that it can operate as a stabilizing factor in population dynamics. Our results, to the contrary, suggest that depending on how it acts, it may even be destabilizing by generating the appearance of functional responses close to type I.
publishDate 2022
dc.date.none.fl_str_mv 2022-02
2023-08-09T13:54:53Z
2023-08-09T13:54:53Z
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12123/14891
https://onlinelibrary.wiley.com/doi/10.1002/ece3.8593
2045-7758
https://doi.org/10.1002/ece3.8593
url http://hdl.handle.net/20.500.12123/14891
https://onlinelibrary.wiley.com/doi/10.1002/ece3.8593
https://doi.org/10.1002/ece3.8593
identifier_str_mv 2045-7758
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv Ecology and Evolution 2 (2) : e8593. (February 2022)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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