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
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/223820

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network_name_str CONICET Digital (CONICET)
spelling 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)
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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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