Landscape composition and pollinator traits interact to influence pollination success in an individual-based model
- Autores
- Kortsch, Susanne; Saravia, Leonardo Ariel; Cirtwill, Alyssa R.; Timberlake, Thomas; Memmott, Jane; Kendall, Liam; Roslin, Tomas; Strona, Giovanni
- Año de publicación
- 2023
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- The arrangement of plant species within a landscape influences pollination via changes in pollinator movement trajectories and plant–pollinator encounter rates. Yet the combined effects of landscape composition and pollinator traits (especially specialisation) on pollination success remain hard to quantify empirically. We used an individual-based model to explore how landscape and pollinator specialisation (degree) interact to influence pollination. We modelled variation in the landscape by generating gradients of plant species intermixing—from no mixing to complete intermixing. Furthermore, we varied the level of pollinator specialisation by simulating plant–pollinator (six to eight species) networks of different connectance. We then compared the impacts of these drivers on three proxies for pollination: visitation rate, number of consecutive visits to the focal plant species and expected number of plants pollinated. We found that the spatial arrangements of plants and pollinator degree interact to determine pollination success, and that the influence of these drivers on pollination depends on how pollination is estimated. For most pollinators, visitation rate increases in more plant mixed landscapes. Compared to the two more functional measures of pollination, visitation rate overestimates pollination service. This is particularly severe in landscapes with high plant intermixing and for generalist pollinators. Interestingly, visitation rate is less influenced by pollinator traits (pollinator degree and body size) than are the two functional metrics, likely because ‘visitation rate’ ignores the order in which pollinators visit plants. However, the visitation sequence order is crucial for the expected number of plants pollinated, since only prior visits to conspecific individuals can contribute to pollination. We show here that this order strongly depends on the spatial arrangements of plants, on pollinator traits and on the interaction between them. Taken together, our findings suggest that visitation rate, the most commonly used proxy for pollination in network studies, should be complemented with more functional metrics which reflect the frequency with which individual pollinators revisit the same plant species. Our findings also suggest that measures of landscape structure such as plant intermixing and density—in combination with pollinators' level of specialism—can improve estimates of the probability of pollination. Read the free Plain Language Summary for this article on the Journal blog.
Fil: Kortsch, Susanne. University of Helsinki; Finlandia
Fil: Saravia, Leonardo Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; Argentina
Fil: Cirtwill, Alyssa R.. University of Helsinki; Finlandia
Fil: Timberlake, Thomas. University of Bristol; Reino Unido
Fil: Memmott, Jane. University of Bristol; Reino Unido
Fil: Kendall, Liam. Lund University; Suecia
Fil: Roslin, Tomas. University of Helsinki; Finlandia. Swedish Agricultural University; Suecia
Fil: Strona, Giovanni. Joint Research Centre; Italia. University of Helsinki; Finlandia - Materia
-
AGENT-BASED MODEL
HABITAT HETEROGENEITY
MOVEMENT ECOLOGY
NETLOGO
PATCH SIZE
VISITATION RATE - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/223820
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oai:ri.conicet.gov.ar:11336/223820 |
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CONICET Digital (CONICET) |
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Landscape composition and pollinator traits interact to influence pollination success in an individual-based modelKortsch, SusanneSaravia, Leonardo ArielCirtwill, Alyssa R.Timberlake, ThomasMemmott, JaneKendall, LiamRoslin, TomasStrona, GiovanniAGENT-BASED MODELHABITAT HETEROGENEITYMOVEMENT ECOLOGYNETLOGOPATCH SIZEVISITATION RATEhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1The arrangement of plant species within a landscape influences pollination via changes in pollinator movement trajectories and plant–pollinator encounter rates. Yet the combined effects of landscape composition and pollinator traits (especially specialisation) on pollination success remain hard to quantify empirically. We used an individual-based model to explore how landscape and pollinator specialisation (degree) interact to influence pollination. We modelled variation in the landscape by generating gradients of plant species intermixing—from no mixing to complete intermixing. Furthermore, we varied the level of pollinator specialisation by simulating plant–pollinator (six to eight species) networks of different connectance. We then compared the impacts of these drivers on three proxies for pollination: visitation rate, number of consecutive visits to the focal plant species and expected number of plants pollinated. We found that the spatial arrangements of plants and pollinator degree interact to determine pollination success, and that the influence of these drivers on pollination depends on how pollination is estimated. For most pollinators, visitation rate increases in more plant mixed landscapes. Compared to the two more functional measures of pollination, visitation rate overestimates pollination service. This is particularly severe in landscapes with high plant intermixing and for generalist pollinators. Interestingly, visitation rate is less influenced by pollinator traits (pollinator degree and body size) than are the two functional metrics, likely because ‘visitation rate’ ignores the order in which pollinators visit plants. However, the visitation sequence order is crucial for the expected number of plants pollinated, since only prior visits to conspecific individuals can contribute to pollination. We show here that this order strongly depends on the spatial arrangements of plants, on pollinator traits and on the interaction between them. Taken together, our findings suggest that visitation rate, the most commonly used proxy for pollination in network studies, should be complemented with more functional metrics which reflect the frequency with which individual pollinators revisit the same plant species. Our findings also suggest that measures of landscape structure such as plant intermixing and density—in combination with pollinators' level of specialism—can improve estimates of the probability of pollination. Read the free Plain Language Summary for this article on the Journal blog.Fil: Kortsch, Susanne. University of Helsinki; FinlandiaFil: Saravia, Leonardo Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; ArgentinaFil: Cirtwill, Alyssa R.. University of Helsinki; FinlandiaFil: Timberlake, Thomas. University of Bristol; Reino UnidoFil: Memmott, Jane. University of Bristol; Reino UnidoFil: Kendall, Liam. Lund University; SueciaFil: Roslin, Tomas. University of Helsinki; Finlandia. Swedish Agricultural University; SueciaFil: Strona, Giovanni. Joint Research Centre; Italia. University of Helsinki; FinlandiaWiley Blackwell Publishing, Inc2023-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/223820Kortsch, Susanne; Saravia, Leonardo Ariel; Cirtwill, Alyssa R.; Timberlake, Thomas; Memmott, Jane; et al.; Landscape composition and pollinator traits interact to influence pollination success in an individual-based model; Wiley Blackwell Publishing, Inc; Functional Ecology; 37; 7; 7-2023; 2056-20710269-8463CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1111/1365-2435.14353info:eu-repo/semantics/altIdentifier/doi/10.1111/1365-2435.14353info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:32:17Zoai:ri.conicet.gov.ar:11336/223820instacron: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:34982025-09-29 10:32:17.663CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Landscape composition and pollinator traits interact to influence pollination success in an individual-based model |
title |
Landscape composition and pollinator traits interact to influence pollination success in an individual-based model |
spellingShingle |
Landscape composition and pollinator traits interact to influence pollination success in an individual-based model Kortsch, Susanne AGENT-BASED MODEL HABITAT HETEROGENEITY MOVEMENT ECOLOGY NETLOGO PATCH SIZE VISITATION RATE |
title_short |
Landscape composition and pollinator traits interact to influence pollination success in an individual-based model |
title_full |
Landscape composition and pollinator traits interact to influence pollination success in an individual-based model |
title_fullStr |
Landscape composition and pollinator traits interact to influence pollination success in an individual-based model |
title_full_unstemmed |
Landscape composition and pollinator traits interact to influence pollination success in an individual-based model |
title_sort |
Landscape composition and pollinator traits interact to influence pollination success in an individual-based model |
dc.creator.none.fl_str_mv |
Kortsch, Susanne Saravia, Leonardo Ariel Cirtwill, Alyssa R. Timberlake, Thomas Memmott, Jane Kendall, Liam Roslin, Tomas Strona, Giovanni |
author |
Kortsch, Susanne |
author_facet |
Kortsch, Susanne Saravia, Leonardo Ariel Cirtwill, Alyssa R. Timberlake, Thomas Memmott, Jane Kendall, Liam Roslin, Tomas Strona, Giovanni |
author_role |
author |
author2 |
Saravia, Leonardo Ariel Cirtwill, Alyssa R. Timberlake, Thomas Memmott, Jane Kendall, Liam Roslin, Tomas Strona, Giovanni |
author2_role |
author author author author author author author |
dc.subject.none.fl_str_mv |
AGENT-BASED MODEL HABITAT HETEROGENEITY MOVEMENT ECOLOGY NETLOGO PATCH SIZE VISITATION RATE |
topic |
AGENT-BASED MODEL HABITAT HETEROGENEITY MOVEMENT ECOLOGY NETLOGO PATCH SIZE VISITATION RATE |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.6 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
The arrangement of plant species within a landscape influences pollination via changes in pollinator movement trajectories and plant–pollinator encounter rates. Yet the combined effects of landscape composition and pollinator traits (especially specialisation) on pollination success remain hard to quantify empirically. We used an individual-based model to explore how landscape and pollinator specialisation (degree) interact to influence pollination. We modelled variation in the landscape by generating gradients of plant species intermixing—from no mixing to complete intermixing. Furthermore, we varied the level of pollinator specialisation by simulating plant–pollinator (six to eight species) networks of different connectance. We then compared the impacts of these drivers on three proxies for pollination: visitation rate, number of consecutive visits to the focal plant species and expected number of plants pollinated. We found that the spatial arrangements of plants and pollinator degree interact to determine pollination success, and that the influence of these drivers on pollination depends on how pollination is estimated. For most pollinators, visitation rate increases in more plant mixed landscapes. Compared to the two more functional measures of pollination, visitation rate overestimates pollination service. This is particularly severe in landscapes with high plant intermixing and for generalist pollinators. Interestingly, visitation rate is less influenced by pollinator traits (pollinator degree and body size) than are the two functional metrics, likely because ‘visitation rate’ ignores the order in which pollinators visit plants. However, the visitation sequence order is crucial for the expected number of plants pollinated, since only prior visits to conspecific individuals can contribute to pollination. We show here that this order strongly depends on the spatial arrangements of plants, on pollinator traits and on the interaction between them. Taken together, our findings suggest that visitation rate, the most commonly used proxy for pollination in network studies, should be complemented with more functional metrics which reflect the frequency with which individual pollinators revisit the same plant species. Our findings also suggest that measures of landscape structure such as plant intermixing and density—in combination with pollinators' level of specialism—can improve estimates of the probability of pollination. Read the free Plain Language Summary for this article on the Journal blog. Fil: Kortsch, Susanne. University of Helsinki; Finlandia Fil: Saravia, Leonardo Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; Argentina Fil: Cirtwill, Alyssa R.. University of Helsinki; Finlandia Fil: Timberlake, Thomas. University of Bristol; Reino Unido Fil: Memmott, Jane. University of Bristol; Reino Unido Fil: Kendall, Liam. Lund University; Suecia Fil: Roslin, Tomas. University of Helsinki; Finlandia. Swedish Agricultural University; Suecia Fil: Strona, Giovanni. Joint Research Centre; Italia. University of Helsinki; Finlandia |
description |
The arrangement of plant species within a landscape influences pollination via changes in pollinator movement trajectories and plant–pollinator encounter rates. Yet the combined effects of landscape composition and pollinator traits (especially specialisation) on pollination success remain hard to quantify empirically. We used an individual-based model to explore how landscape and pollinator specialisation (degree) interact to influence pollination. We modelled variation in the landscape by generating gradients of plant species intermixing—from no mixing to complete intermixing. Furthermore, we varied the level of pollinator specialisation by simulating plant–pollinator (six to eight species) networks of different connectance. We then compared the impacts of these drivers on three proxies for pollination: visitation rate, number of consecutive visits to the focal plant species and expected number of plants pollinated. We found that the spatial arrangements of plants and pollinator degree interact to determine pollination success, and that the influence of these drivers on pollination depends on how pollination is estimated. For most pollinators, visitation rate increases in more plant mixed landscapes. Compared to the two more functional measures of pollination, visitation rate overestimates pollination service. This is particularly severe in landscapes with high plant intermixing and for generalist pollinators. Interestingly, visitation rate is less influenced by pollinator traits (pollinator degree and body size) than are the two functional metrics, likely because ‘visitation rate’ ignores the order in which pollinators visit plants. However, the visitation sequence order is crucial for the expected number of plants pollinated, since only prior visits to conspecific individuals can contribute to pollination. We show here that this order strongly depends on the spatial arrangements of plants, on pollinator traits and on the interaction between them. Taken together, our findings suggest that visitation rate, the most commonly used proxy for pollination in network studies, should be complemented with more functional metrics which reflect the frequency with which individual pollinators revisit the same plant species. Our findings also suggest that measures of landscape structure such as plant intermixing and density—in combination with pollinators' level of specialism—can improve estimates of the probability of pollination. Read the free Plain Language Summary for this article on the Journal blog. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-07 |
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/11336/223820 Kortsch, Susanne; Saravia, Leonardo Ariel; Cirtwill, Alyssa R.; Timberlake, Thomas; Memmott, Jane; et al.; Landscape composition and pollinator traits interact to influence pollination success in an individual-based model; Wiley Blackwell Publishing, Inc; Functional Ecology; 37; 7; 7-2023; 2056-2071 0269-8463 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/223820 |
identifier_str_mv |
Kortsch, Susanne; Saravia, Leonardo Ariel; Cirtwill, Alyssa R.; Timberlake, Thomas; Memmott, Jane; et al.; Landscape composition and pollinator traits interact to influence pollination success in an individual-based model; Wiley Blackwell Publishing, Inc; Functional Ecology; 37; 7; 7-2023; 2056-2071 0269-8463 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1111/1365-2435.14353 info:eu-repo/semantics/altIdentifier/doi/10.1111/1365-2435.14353 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Wiley Blackwell Publishing, Inc |
publisher.none.fl_str_mv |
Wiley Blackwell Publishing, Inc |
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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1844614336086016000 |
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13.070432 |