This R Package implements a model from Stephen R. Carpenter’s 1992 [1] paper on predicting lake algal blooms using plankton dynamics and other variables, and was developed specifically for use in Sam Fey’s Ecology class at Reed College.
The developmental version of this package can be installed with the following code:
# install the remotes package (if you haven't yet)
# install.packages("remotes")
# install the carpentR package!
remotes::install_github("simonpcouch/carpentR")
library(carpentR)Each of the functions exported by this package begin with the prefix
carpenter_*–typing the first few letters will show all of the
different functions available in {carpentR}!
The primary function from this package is called carpenter_model,
which runs the simulations detailed in the paper based on the parameters
given. An example is shown below!
model_data <- carpenter_model(nanoplankter_diameter = 5.0,
alga_diameter = 40,
length_herbivore = 1,
death_rate_herbivore = .1,
p_influx_rate = 0.7,
p_outflow_rate = 0.0003,
mixed_layer_depth = 2.5)
head(model_data)## day phosphorus algal_chlorophyll blue_green_chlorophyll zooplankton_biomass
## 1 1 0.200000 5.000000 3.500000 111.1111
## 2 2 1.012104 4.114608 3.107484 133.2836
## 3 3 1.546669 3.469708 2.753363 154.5941
## 4 4 1.990276 2.920184 2.421692 174.1663
## 5 5 2.405145 2.434516 2.112013 190.9055
## 6 6 2.814555 2.012060 1.828556 203.8984
{carpentR} also provides several functions to interface with this data.
You might be interested in using any of the carpenter_viz_* functions:
carpenter_viz_phosphorus(model_data)
carpenter_viz_chlorophyll(model_data)
carpenter_viz_zooplankton(model_data)
The carpenter_visualize() function will call each of the three
visualization functions (in the above order), and you can add aesthetic
layers to these plots as you would with any other ggplot:
carpenter_viz_phosphorus(model_data) + ggplot2::theme_minimal()
Finally, the package supplies a function called carpenter_pivot() that
allows you to pivot between wide and long data. Here’s an example:
model_data_long <- carpenter_pivot(model_data)
head(model_data_long)## # A tibble: 6 x 3
## day type concentration
## <int> <chr> <dbl>
## 1 1 phosphorus 0.2
## 2 1 algal_chlorophyll 5
## 3 1 blue_green_chlorophyll 3.5
## 4 1 zooplankton_biomass 111.
## 5 2 phosphorus 1.01
## 6 2 algal_chlorophyll 4.11
Depending on what you want to visualize, either of the default output
structure or the “longer” data will be properly tidy (and thus easier to
use with ggplot2 and other packages from the tidyverse.)
Happy modeling!
Note that “original source code” is mentioned throughout this package’s source—this is in reference to an original implementation of the model in Pascal. Please contact the maintainer for inquiries about this implementation.
We welcome and encourage others to help us make this package as user
friendly, flexible, and efficient as possible through filing issues and
pull requests! Please note that the carpentR R package is released
with a Contributor Code of Conduct. By contributing
to this project, you agree to abide by its terms.
[1] Carpenter S.R. (1992) Destabilization of Planktonic Ecosystems and Blooms of Blue-Green Algae. In: Kitchell J.F. (eds) Food Web Management. Springer Series on Environmental Management. Springer, New York, NY