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FWebs (v. 0.1.1) - Downloading and processing food web datasets

Download food web datasets from online databases, process, compute structural metrics and evaluate robustness.

DISCLAIMER: This is development version. The code is continuously being subjected to improvements. Any suggestions are welcomed!

In the blog Geekcologist I provided an example of the use of some of these functions: https://geekcologist.wordpress.com/2020/02/06/function-to-download-biotic-interaction-datasets/

1. Install the package

library(devtools) 
install_github("FMestre1/fw_package")
library(FWebs)

2. Create food web list (from the mangal database as an example)

mg1 <- create.fw.list(db="mg", ref=TRUE, spatial = TRUE)

3. Which are adjacency matrices (0 and 1 matrices)?

is.adjacency.matrix(mg1)

3.1.Need to convert to adjacency (not needed here)?

mg2 <- convert2adjacency(mg1)
is.adjacency.matrix(mg2)

4. Which are square matrices (same number of columns and rows)?

is.sq.matrix(mg1) 

4.1. Need to convert to square matrix (not needed here)?

mg3 <- rec2square(mg2)
is.sq.matrix(mg3)

5. Deriving Food Web metrics

metrics <- fw.metrics(mg1)

metrics

6. Plot the degree distribution of all food webs in the dataset

dd.fw(mg1, log=TRUE, cumulative=TRUE)

7. Evaluate the robustness of a food web to disturbance

#Convert to list a list of ghraph objects
graph_list1 <- convert.to.graph.list(mg1)

#Create a vector with the values for the Intentionality Index (I)
i_index <- seq(from = 0, to = 1, by =0.01)
i_index <- head(i_index,-1)

#Extract one food web as example
fw1 <- graph_list1[[40]]

#Compute the probability to remove each species 
prob_exp <- exponent.removal(fw1, i_index)

#Simulate the extraction of species to evaluate how many primary extinctions are required to have 50% of the total species extinguished
it1 <- iterate(fw_to_attack=fw1, prob_exp, alpha1=50, iter=10, i_index, plot = TRUE)

Robustness (50%) across levels of intentionality of the attack to the food web. As we move along the x axis the probability of removing hubs increases.