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    Let's "bee" friendly!

    Introduction

    In an era marked by environmental challenges and the alarming decline of pollinator populations, the significance of creating pollinator bee-friendly spaces has never been more critical. This project endeavors to design and establish spaces that provide a haven for pollinators, particularly bees, by optimizing their natural environment with a thoughtful selection of both native and non-native plants. By embracing a holistic approach that combines the benefits of indigenous flora and complementary non-native species, we aim to foster biodiversity and ecological harmony. Through this initiative, we strive to enhance pollinator populations, promote sustainable ecosystems, and cultivate a shared sense of responsibility towards safeguarding the delicate tapestry of life upon which we all depend. This report outlines our methodology, plant selection strategies, and the expected ecological outcomes, providing insights for broader implementation and conservation efforts. Together, let us sow the seeds of change and cultivate a future where pollinators thrive amidst the splendor of well-crafted and nurturing habitats.

    Summary

    This report presents a comprehensive analysis of the data collected on native and non-native plants and their impact on pollinator bees. The primary objectives of this study were twofold:

    • To discern the preferences of native and non-native bee species for specific plant types and
    • to identify the most effective plant species that optimize the environment for pollinator bees. Through rigorous data analysis and visualization, we sought to uncover patterns of plant-bee interactions, offering valuable insights to guide the creation of pollinator bee-friendly spaces. By understanding the distinct preferences of native and non-native bees, we can formulate targeted strategies to support their populations. Moreover, the recommended top three plant species will serve as a foundational framework for environmental agencies to foster biodiversity, restore ecological balance, and nurture pollinator communities. Ultimately, our findings aim to empower conservation efforts and inspire a collective commitment towards safeguarding these essential contributors to our natural ecosystems.

    Which plants are preferred by native vs non-native bee species?

    The first thing we notice is that native bees are clearly fewer than non native bees, which makes evident the need to take measures to increase the population of the local bee.

    After filtering out observations involving air-collected bees (we cannot know if they have a plant preference), the data analysis reveals intriguing insights into the plant preferences of native and non-native bees. Among the non-native bee species, "Leucanthemum vulgare," "Rudbeckia hirta," "Cichorium intybus," "Daucus carota," and "Chamaecrista fasciculata" emerge as their top favored plant species. On the other hand, the native bee species show a distinct preference for "Rudbeckia hirta," "Melilotus officinalis," "Asclepias tuberosa," "Leucanthemum vulgare," and "Coronilla varia."

    One interesting observation is the overlap in the preferences for "Rudbeckia hirta" and "Leucanthemum vulgare" among both native and non-native bee species. These plant species seem to be universally appealing and could play a pivotal role in attracting and supporting a diverse array of pollinator bees.

    Another noteworthy point is that while some plant species are preferred by both native and non-native bees, there are also specific plant preferences unique to each group. Understanding these distinctions can be crucial for designing pollinator bee-friendly spaces that cater to the needs and preferences of diverse bee populations, contributing to increased biodiversity and pollination efficiency.

    Additionally, the prevalence of "Melilotus officinalis" and "Asclepias tuberosa" among the preferred plants for native bees suggests the importance of incorporating native flowering species that provide essential resources and habitats for local bee communities.

    In conclusion, this data-driven analysis equips us with valuable information to create optimized environments for pollinator bees. By strategically incorporating a mix of plant species, including both universally favored options like "Rudbeckia hirta" and "Leucanthemum vulgare," and native-specific choices such as "Melilotus officinalis" and "Asclepias tuberosa," we can bolster pollinator populations and foster thriving bee-friendly spaces that benefit both the native ecosystem and non-native species.

    The distribution of bee and plant species across sample "17454"

    • Abundance of Non-Native Bees: Non-native bee species, including Nomada texana, Halictus poeyi/ligatus, Halictus confusus, Augochlorella aurata, and Augochlora pura, collectively account for 532 bees out of the total 632 bees observed. This highlights the dominance of non-native bee populations in the area.

    • Prevalence of Halictus poeyi/ligatus: Among the non-native bees, the species Halictus poeyi/ligatus is the most abundant, with 456 individuals recorded. This significant presence suggests that this particular non-native species has successfully established itself in the local ecosystem.

    • Native Bee Diversity: The sample also reveals the presence of native bee species, including Melissodes subillatus, which accounted for 100 individuals. This demonstrates that despite the dominance of non-native bees, native bee populations are still present in the area.

    • Plant Preference: The data indicates a strong preference for the Rudbeckia hirta plant among the observed bees, with 625 bees found over this plant. This preference aligns with its attractiveness to both native and non-native bee species, as observed in the previous insights.

    • Increased percentage of native bees: The percentage of native bees in the entire sample (100 out of 632) is relatively high, at approximately 15.82% compared to the overall percentage of 8.26%.

    • High Non-Native Bee Percentage: Conversely, the percentage of non-native bees in the entire sample (532 out of 632) is considerably higher, at approximately 84.18%. This highlights the need for monitoring and managing non-native bee populations to mitigate potential ecological impacts and protect local biodiversity.

    Overall, this data underscores the significance of creating pollinator bee-friendly spaces that not only attract and support native bee populations but also carefully manage and control the presence of non-native bees. By understanding the dynamics of bee-plant interactions and promoting the use of native plants, we can foster a more balanced and resilient ecosystem that benefits both pollinators and the broader biodiversity.

    The best choice of plant species to support native bees.

    Based on the data provided, we recommend the folownig species to support native bees:

    • Rudbeckia hirta: This plant species is highly favored by both native and non-native bees, with 143 native bees and 804 non-native bees observed over it. Its attractiveness to both groups makes it a crucial plant to include in pollinator-friendly spaces to support a diverse bee population.

    • Melilotus officinalis: As a native plant, Melilotus officinalis attracted 96 native bees in the data. Including this species in pollinator-friendly areas can provide specific resources and habitat for the native bee communities.

    • Asclepias tuberosa: While not as highly preferred as Rudbeckia hirta, Asclepias tuberosa still attracted 39 native bees. Asclepias species, or milkweed, are essential for supporting native bee populations and are particularly beneficial for monarch butterflies.

    By incorporating these top three native plant species into the pollinator-friendly spaces, the agency can enhance the habitat for native bee species, bolster pollinator populations, and contribute to overall biodiversity conservation. Additionally, planting a diverse array of native flowering plants will provide a continuous supply of nectar and pollen throughout the seasons, ensuring a sustained and thriving environment for native bees.



    Under the hood...

    The Data

    We assembled information on the plants and bees research. Each row represents a sample that was taken from a patch of land where the plant species were being studied.

    ColumnDescription
    sample_idThe ID number of the sample taken.
    bees_numThe total number of bee individuals in the sample.
    dateDate the sample was taken.
    seasonSeason during sample collection ("early.season" or "late.season").
    siteName of collection site.
    native_or_nonWhether the sample was from a native or non-native plot.
    samplingThe sampling method.
    plant_speciesThe name of the plant species the sample was taken from. None indicates the sample was taken from the air.
    timeThe time the sample was taken.
    bee_speciesThe bee species in the sample.
    sexThe gender of the bee species.
    specialized_onThe plant genus the bee species preferred.
    parasiticWhether or not the bee is parasitic (0:no, 1:yes).
    nestingThe bees nesting method.
    statusThe status of the bee species.
    nonnative_beeWhether the bee species is native or not (0:no, 1:yes).

    Source (data has been modified)

    # loadind the data
    suppressPackageStartupMessages(library(tidyverse))
    data <- readr::read_csv("data/plants_and_bees.csv", show_col_types = FALSE)
    # acquire packages
    if(!require(ggpubr)){
        install.packages("ggpubr")}
    library(ggpubr)
    library(png)
    library(lubridate)
    if(!require(ggraph)){
        install.packages("ggraph")}
    suppressPackageStartupMessages(library(ggraph))
    suppressPackageStartupMessages(library(igraph))
    img <- readPNG("bees5opc.png")

    Data cleaning and wrangling

    While processing the data, we initially found that columns sex,sampling,specialized_on,nesting and status do not contain important information for the specific project and proceeded to delete them. More specifically, we removed the variable sex, since male and female bees contribute equally to pollination. The method of collecting the bees (sampling) and the nesting method (nesting) does not concern us in the present analysis. Finaly, the vast majority of plant genus (specialized_on) observations and status were null, as shown in the tables below.

    # Cleaning the data
    ## Sample_id
    data$sample_id<-as.factor(data$sample_id)
    ##date & time
    data<-data%>%
    	mutate(datetime=paste(date,time%/%100,":",time%%100))%>%
    	mutate(datetime=as.POSIXct(datetime, format = "%m/%d/%Y %H : %M"))%>%
    	select(-date,-time)
    ## season
    data<-data%>%
    	mutate(season=if_else(season=='early.season',"early season","late season"))%>%
    	mutate(season=as.factor(season))
    ## site
    data$site<-as.factor(data$site)
    ## native_or_non
    data$native_or_non<-as.factor(data$native_or_non)
    ## sampling
    data$sampling<-as.factor(data$sampling)
    ## plant_species
    data$plant_species<-as.factor(data$plant_species)
    ## bee_species
    data$bee_species<-as.factor(data$bee_species)
    ## sex
    data<-data%>%
    	mutate(sex=if_else(sex=='f',"female","male"))%>%
    	mutate(sex=as.factor(sex))
    ## specialized_on
    data$specialized_on<-as.factor(data$specialized_on)
    ## parasitic
    data<-data%>%
    	mutate(parasitic=if_else(parasitic==0,"non parasitic","parasitic"))%>%
    	mutate(parasitic=as.factor(parasitic))
    ## nesting
    data$nesting<-as.factor(data$nesting)
    ##status
    data$status<-as.factor(data$status)
    ## nonnative_bee
    data<-data%>%
    	mutate(nonnative_bee=if_else(nonnative_bee==0,"non native","native"))%>%
    	mutate(nonnative_bee=as.factor(nonnative_bee))
    #Count the observations of each level of the plant genus the bee species preferred
    specialized_on_count<-data%>%
    	group_by(specialized_on)%>%
    	count()
    names(specialized_on_count)<-c("Plant genus","count")
    specialized_on_count
    
    #Count the observations of each level of the status of the bee species
    status_count<-data%>%
    	group_by(status)%>%
    	count()
    names(status_count)<-c("Status","count")
    status_count
    ## Select the columns to use in analysis
    data<-data%>%
    	select(-sex,-native_or_non,-sampling,-specialized_on,-nesting,-status)