Landscape composition and pollinator traits interact to influence pollination success in an individual-based model

Susanne Kortsch*, Leonardo Saravia, Alyssa R. Cirtwill, Thomas Timberlake, Jane Memmott, Liam Kendall, Tomas Roslin, Giovanni Strona

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)2056-2071
Number of pages16
JournalFunctional Ecology
Volume37
Issue number7
Early online date14 May 2023
DOIs
Publication statusPublished - 4 Jul 2023

Bibliographical note

Funding Information:
This work was supported by the Natural Environment Research Council (NERC) (NE/T013621/1), the National Science Foundation (NSF) and the Academy of Finland (AKA) (grant 334787), coordinated through the Belmont Forum Climate, Environment and Health Collaborative Research Action (proposal 1550). Further support was provided by the Bristol Centre for Agricultural Innovation. T.R. was funded by the European Research Council Synergy Grant 856506 (LIFEPLAN), by the Academy of Finland (grant 322266), and by a Career Support grant from the Swedish University of Agricultural Sciences. A.C. was supported by a postdoctoral fellowship from the Academy of Finland (1332999). L.K. was supported by the Strategic Research Environment BECC (Biodiversity and Ecosystem Services in a Changing Climate). The authors are greatly indebted to Adrian Newton, Mário Santos and Matthias Becher for advice on individual‐based modelling in the initial phase of this project, Lai Zhang for reviewing equation specifications and the ‘IT for Science’ support team at Helsinki University, in particular Juhana Kammonen, for help with cluster computing.

Funding Information:
This work was supported by the Natural Environment Research Council (NERC) (NE/T013621/1), the National Science Foundation (NSF) and the Academy of Finland (AKA) (grant 334787), coordinated through the Belmont Forum Climate, Environment and Health Collaborative Research Action (proposal 1550). Further support was provided by the Bristol Centre for Agricultural Innovation. T.R. was funded by the European Research Council Synergy Grant 856506 (LIFEPLAN), by the Academy of Finland (grant 322266), and by a Career Support grant from the Swedish University of Agricultural Sciences. A.C. was supported by a postdoctoral fellowship from the Academy of Finland (1332999). L.K. was supported by the Strategic Research Environment BECC (Biodiversity and Ecosystem Services in a Changing Climate). The authors are greatly indebted to Adrian Newton, Mário Santos and Matthias Becher for advice on individual-based modelling in the initial phase of this project, Lai Zhang for reviewing equation specifications and the ‘IT for Science’ support team at Helsinki University, in particular Juhana Kammonen, for help with cluster computing.

Publisher Copyright:
© 2023 The Authors. Functional Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

Keywords

  • agent-based model
  • habitat heterogeneity
  • movement ecology
  • Netlogo
  • patch size
  • visitation rate

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