plot_div.BipartiteEvol: Plot the output of BipartiteEvol

Description Usage Arguments Details Author(s) References See Also Examples

View source: R/plot_BipartiteEvol.R

Description

Plot the genealogies and phylogenies simulated with BipartiteEvol

Usage

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plot_div.BipartiteEvol(gen, spec, trait.id, lwdgen = 1, 
    lwdsp = lwdgen, scale = NULL)

Arguments

gen

The output of a run of make_gen.BipartiteEvol

spec

The output of a run of define_species.BipartiteEvol

trait.id

The trait dimension used to color the genealogies, phylogenies an network with trait values

lwdgen

Width of the branches of the genealogies, default to 1

lwdsp

Width of the branches of the phylogenies, default to 1

scale

Optional, used to force the trait scale

Details

The upper line shows the genealogies colored with trait values for both guilds (the number above shows the depth of the respective genealogy).

The second line shows the phylogenies colored with trait values for both guilds (the number above shows the tip number of the respective phylogeny).

On the third line there is, from left to right, the trait distribution within individuals in guild P, trait of the individual in H as a function of the trait of the interacting individual in P, and the trait distribution within individuals in guild H (for the dimension trait.id).

The lower line shows the quantitative interaction network, with species colored according to their mean trait value (for the dimension trait.id).

Author(s)

O. Maliet

References

Maliet, O., Loeuille, N. and Morlon, H. (2020), An individual-based model for the eco-evolutionary emergence of bipartite interaction networks. Ecol Lett. doi:10.1111/ele.13592

See Also

sim.BipartiteEvol

Examples

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# run the model
set.seed(1)
mod = sim.BipartiteEvol(nx = 8,ny = 4,NG = 1000,
                        D = 3, muP = 0.1 , muH = 0.1,
                        alphaP = 0.12,alphaH = 0.12,
                        rP = 10, rH = 10,
                        verbose = 100, thin = 5)

#build the genealogies
gen = make_gen.BipartiteEvol(mod)
plot(gen$H)

#compute the phylogenies
phy1 = define_species.BipartiteEvol(gen,threshold=1)

#plot the result
plot_div.BipartiteEvol(gen,phy1, 1)

RPANDA documentation built on Nov. 10, 2021, 9:08 a.m.