Differential impacts of land use change on multiple components of common Milkweed (Asclepias syriaca) pollination success
Data files
May 20, 2024 version files 23.80 KB
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Pollen_deposition.txt
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Pollen_removal.txt
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Pollinator_species_composition.txt
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pollinator_visitation.txt
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README.md
Abstract
Land-use change is one the greatest threats to biodiversity and is projected to increase in magnitude in the coming years, stressing the importance of better understanding how land-use change may affect vital ecosystem services, such as pollination. Past studies on the impact of land-use change have largely focused on only one aspect of the pollination process (e.g. pollinator composition, pollinator visitation, pollen transfer), potentially misrepresenting the full complexity of land-use effects on pollination services. Evaluating the impacts across multiple components of the pollination process can also help pinpoint the underlying mechanisms driving land-use change effects. This study evaluates how land-use change affects multiple aspects of the pollination process in common milkweed populations, including pollinator community composition, pollinator visitation rate, pollen removal, and pollen deposition. Overall, land-use change altered floral visitor composition, with small bees having a larger presence in developed areas. Insect visitation rate and pollen removal were also higher in more developed areas, perhaps suggesting a positive impact of land-use change. However, pollen deposition did not differ between developed and undeveloped sites. Our findings highlight the complexity evaluating land-use change effects on pollination, as these likely depend on the specific aspect of pollination evaluated and on the of the intensity of disturbance. Our study stresses the importance of evaluating multiple components of the pollination process in order to fully understand overall effects and mechanisms underlying land-use change effects on this vital ecosystem service.
README: Differential impacts of urbanization on multiple components of common Milkweed (Asclepias syriaca) pollination success
https://doi.org/10.5061/dryad.n5tb2rc3c
Description of the data and file structure
The data presented in the paper by Rocokow et al. Impacts of Urbanization on Pollination Success for Common Milkweed. The data is divided into four txt files each containg data for a specifc analysis outlined in the paper.
The data in the files is as follows:
File 1 pollinator visistation
Description: The visitation rate from every insect survey conducted (total # of insects observed divided by time surveyed in minutes divided by the number of inflorescences present).
Data in each column:
Type: Habitat type, either natural (A) or developed (B).
visit: The calculated insect visitation rate from every survey conducted.
site: The site in which the survey was conducted. The site numbers correspond to the following site codes: WL=1, WP=2, LR=3, JN=4, RM=5, RF=6, GC=7, RH=8, JA=9, SS=10, SW=12, and CG=13.
year: Year in which the data was collected, either 2021 (A) or 2022 (B).
day: Order in which each survey was conducted at each site, with one being the first survey.
Data was analyzed using a mixed effect model with visit as the response variable, Type as the explanatory variable, and other variables as random factors (Figure 4).
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File 2 pollen removal
Description: The number of pollinaria removed per flower for each plant surveyed. For each plant the number of pollinaria removed from all flowers on that plant was summed and then divided by the number of flowers surveyed (typically five).
Data in each column:
Type: Habitat type, either natural (A) or developed (B).
removal: Number of pollinia removed per flower on each plant surveyed.
site: The site in which the plants were surveyed. The numbers correspond to the following site codes: WL=1, WP=2, LR=3, JN=4, RM=5, RF=6, GC=7, RH=8, JA=9, SS=10, SW=12, and CG=13.
year: Year in which the data was collected, either 2021 (A) or 2022 (B).
Data was analyzed using a mixed effect model with remove as the response variable, Type as the explanatory variable, and other variables as random factors (Figure 5).
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File 3 pollen deposition
Description:The number of pollinia deposited per flower for each plant surveyed. For each plant the number of pollinia deposited from all flowers on that plant was summed and then divided by the number of flowers surveyed (typically five).
Data in each column:
Type: Habitat type, either natural (A) or developed (B).
deposit: Number of pollinia deposited per flower on each plant surveyed.
site: The site in which the plants were surveyed. The site numbers correspond to the following site codes: WL=1, WP=2, LR=3, JN=4, RM=5, RF=6, GC=7, RH=8, JA=9, SS=10, SW=12, and CG=13.
year: Year in which the data was collected, either 2021 (A) or 2022 (B).
Data was analyzed using a mixed effect model with deposit as the response variable, Type as the explanatory variable, and other variables as random factors (Figure 5).
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File 4 pollinator species composition
Description: The individual visitation rates (# of given morphogroup observed divided by minutes surveyed divided by the number of inflorescences) of each insect morpohgroup for each survey conducted.
Data in each column:
land_use: Habitat type, either natural (A) or developed (B).
BB: Visitation rate of bumblebees
LB: Visitation rate of large bees
MB: Visitation rate of medium bees
SB: Visitation rate of small bees
HB: Visitation rate of honeybees
L: Visitation rate of lepidopterans
F: Visitation rate of flies
B: Visitation rate of bugs and beetles
W: Visitation rate of wasps
A: Visitation rate of ants
Similarities between individual morphogroup visitation rates at natural and developed sites were visualized using NMDS and analyzed statistically using PERMANOVA (Figure 3).
Code/Software
All data analyses were run in R.