define_species.BipartiteEvol: Build the phylogenies for BipartiteEvol

In RPANDA: Phylogenetic ANalyses of DiversificAtion

Build the phylogenies for BipartiteEvol

Description

Build the phylogenies from the output of BipartiteEvol and the corresponding genealogies

Usage

define_species.BipartiteEvol(genealogy, threshold = 1, 
      distanceH = NULL, distanceP = NULL, verbose = T,
      monophyly = TRUE, seed = NULL)

Arguments

genealogy	The output of a run of make_gen.BipartiteEvol
threshold	The species definition ratchet (s)
distanceH	Distance (ie nb of mutations) matrix between the individual of clade H
distanceP	Distance (ie nb of mutations) matrix between the individual of clade P
verbose	Should the progression of the computation be printed?
monophyly	Should the species delineations be strictly monophyletic species (TRUE - default) or not (FALSE)? If not, the threshold must be equal to 1.
seed	If monophyly==FALSE, the seed is used to pick one representative individual per (potentially non-monophyletic) species.

Details

If monophyly==TRUE, species delineation is performed using the model of Speciation by Genetic Differentiation (Manceau et al., 2015) where the 'threshold' (the number of mutations needed to belong to different species) can vary. It results in monophyletic species. If monophyly==FALSE, we consider that each new mutation (i.e. each new combination of traits) gives rise to a new species (Perez-Lamarque et al., 2021). As a result, species are not necessarily formed by a monophyletic group of individuals.

Value

a list with

P	The species identity of each individual in guild P
H	The species identity of each individual in guild H
Pphylo	The phylogeny for guild P
Hphylo	The phylogeny for guild H

Author(s)

O. Maliet & B. Perez-Lamarque

References

Manceau, M., A. Lambert, and H. Morlon. (2015). Phylogenies support out-of-equilibrium models of biodiversity. Ecology letters 18:347–356.

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

Perez‐Lamarque, B., Maliet, O., Pichon B., Selosse, M-A., Martos, F., Morlon H. (2021). Do closely related species interact with similar partners? Testing for phylogenetic signal in bipartite interaction networks. bioRxiv. doi: https://doi.org/10.1101/2021.08.30.458192

See Also

sim.BipartiteEvol

Examples

# run the model
set.seed(1)


if(test){

mod = sim.BipartiteEvol(nx = 8,ny = 4,NG = 800,
                        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)

#build the network
net = build_network.BipartiteEvol(gen, phy1)

trait.id = 1
plot_net.BipartiteEvol(gen,phy1,trait.id, net,mod, nx = nx, spatial = FALSE)


## add time steps to a former run
seed=as.integer(10)
set.seed(seed)

mod = sim.BipartiteEvol(nx = 8,ny = 4,NG = 200,
                        D = 3, muP = 0.1 , muH = 0.1,
                        alphaP = 0.12,alphaH = 0.12,
                        rP = 10, rH = 10,
                        verbose = 100, thin = 5,
                        P=mod$P,H=mod$H)  # former run output

# update the genealogy
gen = make_gen.BipartiteEvol(mod,
                             treeP=gen$P, treeH=gen$H)

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

#... and the network
net = build_network.BipartiteEvol(gen, phy1)

trait.id = 1
plot_net.BipartiteEvol(gen,phy1,trait.id, net,mod, nx = 10, spatial = FALSE)

}

RPANDA documentation built on Oct. 24, 2022, 5:06 p.m.