Orchard layout and plant traits influence fruit yield more strongly than pollinator behaviour and density in a dioecious crop.

Mutualistic plant-pollinator interactions are critical for the functioning of both non-managed and agricultural systems. Mathematical models of plant-pollinator interactions can help understand key determinants in pollination success. However, most previous models have not addressed pollinator behav...

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Main Authors: Angela Peace, David Pattemore, Melissa Broussard, Dilini Fonseka, Nathan Tomer, Nilsa A Bosque-Pérez, David Crowder, Allison K Shaw, Linley Jesson, Brad G Howlett, Mateusz Jochym, Jing Li
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0231120
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spelling doaj-087edf98502243da8a9253161203a0572021-03-03T22:07:01ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-011510e023112010.1371/journal.pone.0231120Orchard layout and plant traits influence fruit yield more strongly than pollinator behaviour and density in a dioecious crop.Angela PeaceDavid PattemoreMelissa BroussardDilini FonsekaNathan TomerNilsa A Bosque-PérezDavid CrowderAllison K ShawLinley JessonBrad G HowlettMateusz JochymJing LiMutualistic plant-pollinator interactions are critical for the functioning of both non-managed and agricultural systems. Mathematical models of plant-pollinator interactions can help understand key determinants in pollination success. However, most previous models have not addressed pollinator behavior and plant biology combined. Information generated from such a model can inform optimal design of crop orchards and effective utilization of managed pollinators like western honey bees (Apis mellifera), and help generate hypotheses about the effects of management practices and cultivar selection. We expect that the number of honey bees per flower and male to female flower ratio will influence fruit yield. To test the relative importance of these effects, both singly and simultaneously, we utilized a delay differential equation model combined with Latin hypercube sampling for sensitivity analysis. Empirical data obtained from historical records and collected in kiwifruit (Actinidia chinensis) orchards in New Zealand were used to parameterize the model. We found that, at realistic bee densities, the optimal orchard had 65-75% female flowers, and the most benefit was gained from the first 6-8 bees/1000 flowers, with diminishing returns thereafter. While bee density significantly impacted fruit production, plant-based parameters-flower density and male:female flower ratio-were the most influential. The predictive model provides strategies for improving crop management, such as choosing cultivars which have their peak bloom on the same day, increasing the number of flowers with approximately 70% female flowers in the orchard, and placing enough hives to maintain more than 6 bees per 1000 flowers to optimize yield.https://doi.org/10.1371/journal.pone.0231120
collection DOAJ
language English
format Article
sources DOAJ
author Angela Peace
David Pattemore
Melissa Broussard
Dilini Fonseka
Nathan Tomer
Nilsa A Bosque-Pérez
David Crowder
Allison K Shaw
Linley Jesson
Brad G Howlett
Mateusz Jochym
Jing Li
spellingShingle Angela Peace
David Pattemore
Melissa Broussard
Dilini Fonseka
Nathan Tomer
Nilsa A Bosque-Pérez
David Crowder
Allison K Shaw
Linley Jesson
Brad G Howlett
Mateusz Jochym
Jing Li
Orchard layout and plant traits influence fruit yield more strongly than pollinator behaviour and density in a dioecious crop.
PLoS ONE
author_facet Angela Peace
David Pattemore
Melissa Broussard
Dilini Fonseka
Nathan Tomer
Nilsa A Bosque-Pérez
David Crowder
Allison K Shaw
Linley Jesson
Brad G Howlett
Mateusz Jochym
Jing Li
author_sort Angela Peace
title Orchard layout and plant traits influence fruit yield more strongly than pollinator behaviour and density in a dioecious crop.
title_short Orchard layout and plant traits influence fruit yield more strongly than pollinator behaviour and density in a dioecious crop.
title_full Orchard layout and plant traits influence fruit yield more strongly than pollinator behaviour and density in a dioecious crop.
title_fullStr Orchard layout and plant traits influence fruit yield more strongly than pollinator behaviour and density in a dioecious crop.
title_full_unstemmed Orchard layout and plant traits influence fruit yield more strongly than pollinator behaviour and density in a dioecious crop.
title_sort orchard layout and plant traits influence fruit yield more strongly than pollinator behaviour and density in a dioecious crop.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2020-01-01
description Mutualistic plant-pollinator interactions are critical for the functioning of both non-managed and agricultural systems. Mathematical models of plant-pollinator interactions can help understand key determinants in pollination success. However, most previous models have not addressed pollinator behavior and plant biology combined. Information generated from such a model can inform optimal design of crop orchards and effective utilization of managed pollinators like western honey bees (Apis mellifera), and help generate hypotheses about the effects of management practices and cultivar selection. We expect that the number of honey bees per flower and male to female flower ratio will influence fruit yield. To test the relative importance of these effects, both singly and simultaneously, we utilized a delay differential equation model combined with Latin hypercube sampling for sensitivity analysis. Empirical data obtained from historical records and collected in kiwifruit (Actinidia chinensis) orchards in New Zealand were used to parameterize the model. We found that, at realistic bee densities, the optimal orchard had 65-75% female flowers, and the most benefit was gained from the first 6-8 bees/1000 flowers, with diminishing returns thereafter. While bee density significantly impacted fruit production, plant-based parameters-flower density and male:female flower ratio-were the most influential. The predictive model provides strategies for improving crop management, such as choosing cultivars which have their peak bloom on the same day, increasing the number of flowers with approximately 70% female flowers in the orchard, and placing enough hives to maintain more than 6 bees per 1000 flowers to optimize yield.
url https://doi.org/10.1371/journal.pone.0231120
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