The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit quality
- Autores
- Sáez, Agustín; Morales, Juan Manuel; Morales, Carolina Laura; Harder, Lawrence D.; Aizen, Marcelo Adrian
- Año de publicación
- 2018
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Globally, agriculture increasingly depends on pollinators to produce many seed and fruit crops. However, what constitutes optimal pollination service for pollinator-dependent crops remains unanswered. We developed a simulation model to identify the optimal pollination service that maximizes fruit quality in crops. The model depicts the pollination (i.e., autonomous self-fertilization, pollen deposition) and post-pollination (i.e., pollen germination, and time from germination to ovule fertilization) processes leading to fruit and seed set and allows for negative flower–pollinator interactions, specifically pistil damage. We parameterized and validated the model based on empirical observations of commercial raspberry in western Argentina. To assess the effects of pollination intensity for fruit production, we conducted simulations over a range of visit number per flower by the two primary managed pollinators worldwide, Apis mellifera and Bombus terrestris. Simulations identified that ~15–35 visits per flower by A. mellifera or ~10–20 visits by B. terrestris provide adequate pollination and maximize raspberry fruit quality (i.e., estimated as the proportion of ovules that develop into drupelets). Visits in excess of these optima reduce simulated fruit quality, and flowers receiving >670 honey bee visits or >470 bumble bee visits would produce fruits of poorer quality than those receiving no bee visits. The simulations generated consistent, unbiased predictions of fruit quality for 12 raspberry fields. This model could be adapted easily to other animal-pollinated crops and used to guide efficient pollinator management in any agro-ecosystem.
Fil: Sáez, Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina
Fil: Morales, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina
Fil: Morales, Carolina Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina
Fil: Harder, Lawrence D.. University of Calgary. Departament of Biological Sciences; Canadá
Fil: Aizen, Marcelo Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina - Materia
-
BUMBLE BEES
CROP POLLINATION
FRUIT QUALITY
HONEY BEES
RASPBERRY
SIMULATION MODEL - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/87007
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The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit qualitySáez, AgustínMorales, Juan ManuelMorales, Carolina LauraHarder, Lawrence D.Aizen, Marcelo AdrianBUMBLE BEESCROP POLLINATIONFRUIT QUALITYHONEY BEESRASPBERRYSIMULATION MODELhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Globally, agriculture increasingly depends on pollinators to produce many seed and fruit crops. However, what constitutes optimal pollination service for pollinator-dependent crops remains unanswered. We developed a simulation model to identify the optimal pollination service that maximizes fruit quality in crops. The model depicts the pollination (i.e., autonomous self-fertilization, pollen deposition) and post-pollination (i.e., pollen germination, and time from germination to ovule fertilization) processes leading to fruit and seed set and allows for negative flower–pollinator interactions, specifically pistil damage. We parameterized and validated the model based on empirical observations of commercial raspberry in western Argentina. To assess the effects of pollination intensity for fruit production, we conducted simulations over a range of visit number per flower by the two primary managed pollinators worldwide, Apis mellifera and Bombus terrestris. Simulations identified that ~15–35 visits per flower by A. mellifera or ~10–20 visits by B. terrestris provide adequate pollination and maximize raspberry fruit quality (i.e., estimated as the proportion of ovules that develop into drupelets). Visits in excess of these optima reduce simulated fruit quality, and flowers receiving >670 honey bee visits or >470 bumble bee visits would produce fruits of poorer quality than those receiving no bee visits. The simulations generated consistent, unbiased predictions of fruit quality for 12 raspberry fields. This model could be adapted easily to other animal-pollinated crops and used to guide efficient pollinator management in any agro-ecosystem.Fil: Sáez, Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Morales, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Morales, Carolina Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Harder, Lawrence D.. University of Calgary. Departament of Biological Sciences; CanadáFil: Aizen, Marcelo Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaEcological Society of America2018-07-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/87007Sáez, Agustín; Morales, Juan Manuel; Morales, Carolina Laura; Harder, Lawrence D.; Aizen, Marcelo Adrian; The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit quality; Ecological Society of America; Ecological Applications; 28; 5; 24-7-2018; 1215-12221939-5582CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1002/eap.1720info:eu-repo/semantics/altIdentifier/url/https://esajournals.onlinelibrary.wiley.com/doi/abs/10.1002/eap.1720info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:52:34Zoai:ri.conicet.gov.ar:11336/87007instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:52:34.93CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit quality |
title |
The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit quality |
spellingShingle |
The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit quality Sáez, Agustín BUMBLE BEES CROP POLLINATION FRUIT QUALITY HONEY BEES RASPBERRY SIMULATION MODEL |
title_short |
The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit quality |
title_full |
The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit quality |
title_fullStr |
The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit quality |
title_full_unstemmed |
The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit quality |
title_sort |
The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit quality |
dc.creator.none.fl_str_mv |
Sáez, Agustín Morales, Juan Manuel Morales, Carolina Laura Harder, Lawrence D. Aizen, Marcelo Adrian |
author |
Sáez, Agustín |
author_facet |
Sáez, Agustín Morales, Juan Manuel Morales, Carolina Laura Harder, Lawrence D. Aizen, Marcelo Adrian |
author_role |
author |
author2 |
Morales, Juan Manuel Morales, Carolina Laura Harder, Lawrence D. Aizen, Marcelo Adrian |
author2_role |
author author author author |
dc.subject.none.fl_str_mv |
BUMBLE BEES CROP POLLINATION FRUIT QUALITY HONEY BEES RASPBERRY SIMULATION MODEL |
topic |
BUMBLE BEES CROP POLLINATION FRUIT QUALITY HONEY BEES RASPBERRY SIMULATION MODEL |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.6 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
Globally, agriculture increasingly depends on pollinators to produce many seed and fruit crops. However, what constitutes optimal pollination service for pollinator-dependent crops remains unanswered. We developed a simulation model to identify the optimal pollination service that maximizes fruit quality in crops. The model depicts the pollination (i.e., autonomous self-fertilization, pollen deposition) and post-pollination (i.e., pollen germination, and time from germination to ovule fertilization) processes leading to fruit and seed set and allows for negative flower–pollinator interactions, specifically pistil damage. We parameterized and validated the model based on empirical observations of commercial raspberry in western Argentina. To assess the effects of pollination intensity for fruit production, we conducted simulations over a range of visit number per flower by the two primary managed pollinators worldwide, Apis mellifera and Bombus terrestris. Simulations identified that ~15–35 visits per flower by A. mellifera or ~10–20 visits by B. terrestris provide adequate pollination and maximize raspberry fruit quality (i.e., estimated as the proportion of ovules that develop into drupelets). Visits in excess of these optima reduce simulated fruit quality, and flowers receiving >670 honey bee visits or >470 bumble bee visits would produce fruits of poorer quality than those receiving no bee visits. The simulations generated consistent, unbiased predictions of fruit quality for 12 raspberry fields. This model could be adapted easily to other animal-pollinated crops and used to guide efficient pollinator management in any agro-ecosystem. Fil: Sáez, Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina Fil: Morales, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina Fil: Morales, Carolina Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina Fil: Harder, Lawrence D.. University of Calgary. Departament of Biological Sciences; Canadá Fil: Aizen, Marcelo Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina |
description |
Globally, agriculture increasingly depends on pollinators to produce many seed and fruit crops. However, what constitutes optimal pollination service for pollinator-dependent crops remains unanswered. We developed a simulation model to identify the optimal pollination service that maximizes fruit quality in crops. The model depicts the pollination (i.e., autonomous self-fertilization, pollen deposition) and post-pollination (i.e., pollen germination, and time from germination to ovule fertilization) processes leading to fruit and seed set and allows for negative flower–pollinator interactions, specifically pistil damage. We parameterized and validated the model based on empirical observations of commercial raspberry in western Argentina. To assess the effects of pollination intensity for fruit production, we conducted simulations over a range of visit number per flower by the two primary managed pollinators worldwide, Apis mellifera and Bombus terrestris. Simulations identified that ~15–35 visits per flower by A. mellifera or ~10–20 visits by B. terrestris provide adequate pollination and maximize raspberry fruit quality (i.e., estimated as the proportion of ovules that develop into drupelets). Visits in excess of these optima reduce simulated fruit quality, and flowers receiving >670 honey bee visits or >470 bumble bee visits would produce fruits of poorer quality than those receiving no bee visits. The simulations generated consistent, unbiased predictions of fruit quality for 12 raspberry fields. This model could be adapted easily to other animal-pollinated crops and used to guide efficient pollinator management in any agro-ecosystem. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-07-24 |
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/11336/87007 Sáez, Agustín; Morales, Juan Manuel; Morales, Carolina Laura; Harder, Lawrence D.; Aizen, Marcelo Adrian; The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit quality; Ecological Society of America; Ecological Applications; 28; 5; 24-7-2018; 1215-1222 1939-5582 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/87007 |
identifier_str_mv |
Sáez, Agustín; Morales, Juan Manuel; Morales, Carolina Laura; Harder, Lawrence D.; Aizen, Marcelo Adrian; The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit quality; Ecological Society of America; Ecological Applications; 28; 5; 24-7-2018; 1215-1222 1939-5582 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1002/eap.1720 info:eu-repo/semantics/altIdentifier/url/https://esajournals.onlinelibrary.wiley.com/doi/abs/10.1002/eap.1720 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-nd/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Ecological Society of America |
publisher.none.fl_str_mv |
Ecological Society of America |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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1842269167909076992 |
score |
13.13397 |