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 helping to develop and maintain this package long-term. 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

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_reso…¹ cum_f…²
#>   <fct> <fct>  <dbl> <fct>   <date>     <int> <dbl>  <dbl>         <dbl>   <dbl>
#> 1 PUT2  9       0.98 W       2003-04-03     0 1910.    0.1         27.8     27.8
#> 2 PUT2  9       0.98 W       2003-04-09     1 1940    30.6         27.8     55.5
#> 3 PUT2  9       0.98 W       2003-04-15     2 1938    28.6         27.8     83.3
#> 4 PUT2  9       0.98 W       2003-04-22     3 1976.   67.1         27.8    111. 
#> 5 PUT2  9       0.98 W       2003-05-01     4 2010.  101.           7.96   119. 
#> 6 PUT2  9       0.98 W       2003-05-07     5 2143   234.           7.96   127. 
#> # … with abbreviated variable names ¹floral_resources, ²cum_floral

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.