# calc_QSS: Calc the Quasi Sign Stability measure for antagonistic... In lsaravia/EcoNetwork: Ecological network analysis includind multiplex networks

## Description

The proportion of matrices that are locally stable, these matrices are created by sampling the values of the community matrix (the Jacobian) from a uniform distribution, preserving the sign structure 1. If the 'ig' parameter is an `mgraph` network it needs to have been built with the order `c("Competitive", "Mutualistic", "Trophic")` It also calculates the mean of the real part of the maximum eingenvalue, which is also a measure of stability 2. It uses a uniform distribution between 0 and maximum values given by the parameters `negative`, `positive` and `selfDamping`, corresponding to the sign of interactions and self-limitation effect 3,4. If the edges of the networks have a weigth attribute and `istrength` parameter is true, weigth will be used as interaction strength, then the limits of the uniform distribution will be `negative*-x`, `positive*x` where x is the value of the weigth for the edge. If the values of these parameters are 0 then there is no interaction of that kind.

## Usage

 ```1 2 3 4 5 6 7 8 9``` ```calc_QSS( ig, nsim = 1000, ncores = 0, negative = -10, positive = 0.1, selfDamping = -1, istrength = FALSE ) ```

## Arguments

 `ig` igraph or a list of igraph networks or mgraph network `nsim` number of simulations to calculate QSS `ncores` number of cores to use in parallel comutation if 0 it uses sequential processing `negative` the maximum magnitude of the negative interaction (the effect of the predator on the prey) must be <= 0 `positive` the maximum magnitude of the positive interaction (the effect of the prey on the predator) must be >= 0 `selfDamping` the maximum magnitude of the self-limitation (the effect of the species on itself) must be <= 0 `istrength` If TRUE takes the weigth attribute of the network as interaction strength.

## Value

a data.frame with the QSS, and MEing, the mean of the real part of the maximum eingenvalue

## References

1. Allesina, S. & Pascual, M. (2008). Network structure, predator - Prey modules, and stability in large food webs. Theor. Ecol., 1, 55–64.

2. Grilli, J., Rogers, T. & Allesina, S. (2016). Modularity and stability in ecological communities. Nat. Commun., 7, 12031

3. Monteiro, A.B. & Del Bianco Faria, L. (2017). Causal relationships between population stability and food-web topology. Functional Ecology, 31, 1294–1300.

4. Borrelli, J. J. 2015. Selection against instability: stable subgraphs are most frequent in empirical food webs. - Oikos 124: 1583–1588.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```## Not run: g <- netData[] tp <- calc_QSS(g) # Read Multiplex network and calculate QSS fileName <- c(system.file("extdata", package = "multiweb")) dn <- list.files(fileName,pattern = "^Kefi2015.*\\.txt\$") gt <- readMultiplex(dn,types,"inst/extdata", skipColumn = 2) calc_QSS(gt) ## End(Not run) ```

lsaravia/EcoNetwork documentation built on Feb. 11, 2022, 6:37 a.m.