Tools for Modeling Bumblebee Colony Growth and Decline

Bumblebee colonies grow during worker production, then decline after switching to production of reproductive individuals (drones and gynes). This package provides tools for modeling and visualizing this pattern by identifying a switchpoint with a growth rate before and a decline rate after the switchpoint. The mathematical models fit by bumbl are described in Crone and Williams (2016) .

Tools for modeling bumblebee colony growth

bumbl implements a model for bumblebee colony growth described in Crone and Williams 2016¹. It models colony growth as having a switchpoint at some time, tau, where the colony switches from growth and worker production to gyne production and decline. Currently bumbl() works by fitting a separate switchpoint model to each colony, optimizing the switchpoint, tau. It returns the optimal switchpoint, growth, and decline rates for each colony. Because the current version of bumbl() works by fitting a separate GLM to each colony, if covariates are included, their estimates could vary significantly among colonies. Stay tuned for future developments that may allow estimating a single value of a covariate but different values of growth and decline rates and tau for each colony.

Contributing

I’m looking for collaborators who know (or are willing to let me teach them) how to use git and GitHub and who have an interest in taking over as maintainer of this package. I’m not a bumblebee biologist, so I would especially love a collaborator who works on bumblebees or other organisms with a similar growth, switch, decline lifecycle.

I also welcome contributions including bug-fixes, improvement of documentation, additional features, or new functions relating to bumblebee ecology and demography from anyone!

Roadmap

[x] Write bumbl() function to model colony growth with switchpoint
[x] Finish documentation and vignette(s)
[x] rOpenSci review
[x] Regroup with Elizabeth Crone to discuss current behavior of bumbl()
[x] Release v0.1.0 and archive on Zenodo
[x] Bug fixes
[x] Submit v1.0.0 of package to CRAN
[x] Write a manuscript for JOSS (desk-reject, out of scope)
[x] Release minor version to CRAN to update citation
[ ] Possibly re-work internals of bumbl()? (see #58 and notes)
[ ] Submit v2.0.0 of package to CRAN

Other possible areas of improvement:

Extend bumbl() to work with GLMMs
Test significance of switchpoint (see #62)
Extend bumbl() to work with dates, datetimes, or other timeseries classes (see #46)

Installation

You can install bumbl with:

install.packages("bumbl")

Or install the development version with:

devtools::install_github("Aariq/bumbl", build_vignettes = TRUE)

Getting started

View the package vignette with:

library(bumbl)
vignette("bumbl")

View the bomubs dataset

head(bombus)
#> # A tibble: 6 × 10
#>   site  colony  wild habitat date        week  mass d.mass floral_resources
#>   <fct> <fct>  <dbl> <fct>   <date>     <int> <dbl>  <dbl>            <dbl>
#> 1 PUT2  9       0.98 W       2003-04-03     0 1910.    0.1            27.8 
#> 2 PUT2  9       0.98 W       2003-04-09     1 1940    30.6            27.8 
#> 3 PUT2  9       0.98 W       2003-04-15     2 1938    28.6            27.8 
#> 4 PUT2  9       0.98 W       2003-04-22     3 1976.   67.1            27.8 
#> 5 PUT2  9       0.98 W       2003-05-01     4 2010.  101.              7.96
#> 6 PUT2  9       0.98 W       2003-05-07     5 2143   234.              7.96
#> # ℹ 1 more variable: cum_floral <dbl>

Example use

Using a subset of the bombus dataframe to estimate the week (tau) that colonies switch to reproduction

bombus2 <- bombus[bombus$colony %in% c(9, 82, 98, 35), ]
results <- bumbl(bombus2, colonyID = colony, t = week, formula = d.mass ~ week)
results
#> # A tibble: 4 × 7
#>   colony converged   tau logN0 logLam  decay logNmax
#>   <chr>  <lgl>     <dbl> <dbl>  <dbl>  <dbl>   <dbl>
#> 1 35     TRUE       9.37  3.65  0.214 -0.296    5.60
#> 2 82     TRUE       7.34  2.91  0.407 -0.512    5.82
#> 3 9      TRUE       6.52  2.45  0.579 -0.660    6.19
#> 4 98     TRUE       6.37  1.27  0.570 -0.578    4.90

Plot the results

par(mfrow = c(2, 2))
plot(results)
#> Creating plots for 4 colonies...

par(mfrow = c(1, 1))

References

¹Crone, E. E., and Williams, N. M. (2016). Bumble bee colony dynamics: quantifying the importance of land use and floral resources for colony growth and queen production. Ecol. Lett. 19, 460–468. https://doi.org/10.1111/ele.12581

Please note that the bumbl project is released with a Contributor Code of Conduct. By contributing to this project you agree to abide by its terms.