21 research outputs found
Effects of temporal floral resource availability and non-crop habitats on broad bean pollination
Context
Flowering plants can enhance wild insect populations and their pollination services to crops in agricultural landscapes, especially when they flower before the focal crop. However, characterizing the temporal availability of specific floral resources is a challenge.
Objectives
Developing an index for the availability of floral resources at the landscape scale according to the specific use by a pollinator. Investigating whether detailed and temporally-resolved floral resource maps predict pollination success of broad bean better than land cover maps.
Methods
We mapped plant species used as pollen source by bumblebees in 24 agricultural landscapes and developed an index of floral resource availability for different times of the flowering season. To measure pollination success, patches of broad bean (Vicia faba), a plant typically pollinated by bumblebees, were exposed in the center of selected landscapes.
Results
Higher floral resource availability before bean flowering led to enhanced seed set. Floral resource availability synchronous to broad bean flowering had no effect. Seed set was somewhat better explained by land cover maps than by floral resource availability, increasing with urban area and declining with the cover of arable land.
Conclusions
The timing of alternative floral resource availability is important for crop pollination. The higher explanation of pollination success by land cover maps than by floral resource availability indicates that additional factors such as habitat disturbance and nesting sites play a role in pollination. Enhancing non-crop woody plants in agricultural landscapes as pollen sources may ensure higher levels of crop pollination by wild pollinators such as bumblebees
Comparing floral resource maps and land cover maps to predict predators and aphid suppression on field bean
Context
Predatory insects contribute to the natural control of agricultural pests, but also use plant pollen or nectar as supplementary food resources. Resource maps have been proposed as an alternative to land cover maps for prediction of beneficial insects.
Objectives
We aimed at predicting the abundance of crop pest predating insects and the pest control service they provide with both, detailed flower resource maps and land cover maps.
Methods
We selected 19 landscapes of 500 m radius and mapped them with both approaches. In the centres of the landscapes, aphid predators – hoverflies (Diptera: Syrphidae), ladybeetles (Coleoptera: Coccinellidae) and lacewings (Neuroptera: Chrysopidae) – were surveyed in experimentally established faba bean phytometers (Vicia faba L. Var. Sutton Dwarf) and their control of introduced black bean aphids (Aphis fabae Scop.) was recorded.
Results
Landscapes with higher proportions of forest edge as derived from land cover maps supported higher abundance of aphid predators, and high densities of aphid predators reduced aphid infestation on faba bean. Floral resource maps did not significantly predict predator abundance or aphid control services.
Conclusions
Land cover maps allowed to relate landscape composition with predator abundance, showing positive effects of forest edges. Floral resource maps may have failed to better predict predators because other resources such as overwintering sites or alternative prey potentially play a more important role than floral resources. More research is needed to further improve our understanding of resource requirements beyond floral resource estimations and our understanding of their role for aphid predators at the landscape scale
Comparing floral resource maps and land cover maps to predict predators and aphid suppression on field bean
Context
Predatory insects contribute to the natural control of agricultural pests, but also use plant pollen or nectar as supplementary food resources. Resource maps have been proposed as an alternative to land cover maps for prediction of beneficial insects.
Objectives
We aimed at predicting the abundance of crop pest predating insects and the pest control service they provide with both, detailed flower resource maps and land cover maps.
Methods
We selected 19 landscapes of 500 m radius and mapped them with both approaches. In the centres of the landscapes, aphid predators – hoverflies (Diptera: Syrphidae), ladybeetles (Coleoptera: Coccinellidae) and lacewings (Neuroptera: Chrysopidae) – were surveyed in experimentally established faba bean phytometers (Vicia faba L. Var. Sutton Dwarf) and their control of introduced black bean aphids (Aphis fabae Scop.) was recorded.
Results
Landscapes with higher proportions of forest edge as derived from land cover maps supported higher abundance of aphid predators, and high densities of aphid predators reduced aphid infestation on faba bean. Floral resource maps did not significantly predict predator abundance or aphid control services.
Conclusions
Land cover maps allowed to relate landscape composition with predator abundance, showing positive effects of forest edges. Floral resource maps may have failed to better predict predators because other resources such as overwintering sites or alternative prey potentially play a more important role than floral resources. More research is needed to further improve our understanding of resource requirements beyond floral resource estimations and our understanding of their role for aphid predators at the landscape scale
R script analysing pollen at the anther data
Data file used for the analysis "pollen.anther.csv", software R 3.2.2 (2015) used to create the file
R script analysing video data
Data files analysed "vis.rate_video2014.csv" and "handling.time_video2014". Software R 3.2.2 (2015) was used
Pollen-yield experiment data from 2014 and 2015
Data from hand-pollination experiments in fields with different levels of pollen deposition in 2014 (5 levels) and in 2015 (7 levels). Details see manuscript and Table S1 in the supplementary material. Open Office Calc used to create this file. Abbreviations: "harvestable" = 1, if pumpkin fruits could be harvested, "marketable" = 1, if pumpkin fruits weigh more than 800 g
Calculated pollen deposition per bee species group
Formulas used for the calculation from "R_script_SVD". Data used in the formulas from field data "handling.time_video2014.csv", "vis.rate_video2014.csv", "SVD.bee-species_pumpkin_2015.csv", one sheet per bee species group (d.bumble, d.honey, d.halictid). Microsoft Excel used to create the file
R script modelling the contribution of bee groups to pumpkin yield
Single visit pollen deposition data is the calculated data from the file "calculated deposition.model.xls". Data file used "mean_hpa.csv". Software R 3.2.2 used
R script for the analysis of the single visit deposition data
Data analysed "SVD.bee-species_pumpkin_2015.csv"; software R 3.2.2 (2015) use
Visitation rates of bee groups in videos in 2014
Visitation rates collected by in total 54 hours of video recording in 18 fields in 2014. Open Office Org Calc was used to create this data file. "no.visits" = number of visits by the corresponding species groups, "species" = species group {"bumble" = Bombus terrestris, B. lucorum, B. lapidarium; "halictid" = several Halictidae, mainly Lasioglossum species; "honey" = Apis mellifera}, "start.time" = starting time of the video at three different time periods (7:00 am, 8:30 am, 10:00 am)