How to make a directed tripartite network from two bipartite networks?

Question

Excuse me because I feel like this doubt should be simpler, but I can't find a satisfactory answer.

I have two quantitative bipartite networks (that show the ecological relationships among A-B, and B-C). My problem is that I do not know how join both in order to make a directed quantitative tripartite network (like a typical food web). The B level of each bipartite network have the same vertex composition (in quantitie and vertex names). In addition, the levels A and C can not interact among them. For this reason, the order and direction of the final tripartite network it should be C->B->A

Any suggestions?

Thanks for your attention!

Answer 1

How about this:

Cook-up some data (i was hoping you would cook it for me :) )

library(igraph)
set.seed(666)
# herbivore-plant
m_hp <- matrix( rbinom(12, 10, p=0.2), 4, 3)
dimnames(m_hp) <- list(
  consuming=paste0("h", seq(1, nrow(m_hp))),
  consumed=paste0("p", seq(1, ncol(m_hp)))
)
# carnivore-herbivore
m_ch <- matrix( rbinom(20, 10, p=0.2), 5, 4)
dimnames(m_ch) <- list(
  consuming=paste0("c", seq(1, nrow(m_ch))),
  consumed=paste0("h", seq(1, ncol(m_ch)))
)

... so it looks like yours (I presume):

m_hp

##          consumed
## consuming p1 p2 p3
##        h1  3  1  0
##        h2  1  3  1
##        h3  5  5  3
##        h4  1  2  0

m_ch

##          consumed
## consuming h1 h2 h3 h4
##        c1  0  4  0  2
##        c2  1  2  1  2
##        c3  1  2  3  3
##        c4  3  5  1  2
##        c5  0  2  0  2

Now turn them into igraph objects via edgelists

el_hp <- as.data.frame(as.table(m_hp), stringsAsFactors = FALSE)
el_ch <- as.data.frame(as.table(m_ch), stringsAsFactors = FALSE)
el <- rbind(el_hp, el_ch)
g <- graph.data.frame( el[el$Freq != 0 , ]  )
V(g)$type <- substr(V(g)$name, 1, 1)

Adjacency matrix of joint network:

get.adjacency(g, sparse=FALSE, attr="Freq")

##    h1 h2 h3 h4 c2 c3 c4 c1 c5 p1 p2 p3
## h1  0  0  0  0  0  0  0  0  0  3  1  0
## h2  0  0  0  0  0  0  0  0  0  1  3  1
## h3  0  0  0  0  0  0  0  0  0  5  5  3
## h4  0  0  0  0  0  0  0  0  0  1  2  0
## c2  1  2  1  2  0  0  0  0  0  0  0  0
## c3  1  2  3  3  0  0  0  0  0  0  0  0
## c4  3  5  1  2  0  0  0  0  0  0  0  0
## c1  0  4  0  2  0  0  0  0  0  0  0  0
## c5  0  2  0  2  0  0  0  0  0  0  0  0
## p1  0  0  0  0  0  0  0  0  0  0  0  0
## p2  0  0  0  0  0  0  0  0  0  0  0  0
## p3  0  0  0  0  0  0  0  0  0  0  0  0

Graphically

t <- match(V(g)$type, c("p", "h", "c") )
plot(g, vertex.color=t )

or even

l <- layout_with_fr(g, miny=t, maxy=t  )
plot(g, vertex.color=t, layout=l, edge.width=E(g)$Freq)