%0 Journal Article
%A Poisot, T.
%A Cirtwill, A.R.
%A Cazelles, K.
%A Gravel, D.
%A Fortin, M.-J.
%A Stouffer, D.B.
%T The structure of probabilistic networks
%B Methods in Ecology and Evolution
%D 2016
%V 7
%P 303-312
%N 3
%X * There is a growing realization among community ecologists that interactions
between species vary across space and time and that this variation
needs to be quantified. Our current numerical framework to analyse
the structure of species interactions, based on graph-theoretical
approaches, usually do not consider the variability of interactions.
As this variability has been show to hold valuable ecological information,
there is a need to adapt the current measures of network structure
so that they can exploit it.
* We present analytical expressions of key measures of network structured,
adapted so that they account for the variability of ecological interactions.
We do so by modelling each interaction as a Bernoulli event; using
basic calculus allows expressing the expected value, and when mathematically
tractable, its variance. When applied to non-probabilistic data,
the measures we present give the same results as their non-probabilistic
formulations, meaning that they can be generally applied.
* We present three case studies that highlight how these measures
can be used, in re-analysing data that experimentally measured the
variability of interactions, to alleviate the computational demands
of permutation-based approaches, and to use the frequency at which
interactions are observed over several locations to infer the structure
of local networks. We provide a free and open-source implementation
of these measures.
* We discuss how both sampling and data representation of ecological
networks can be adapted to allow the application of a fully probabilistic
numerical network approach.
%Z doi=(10.1111/2041-210X.12468)
%( 2041-210X
%K connectance, degree distribution, ecological networks, modularity,
nestedness, species interactions
%U http://dx.doi.org/10.1111/2041-210X.12468
%F PoisotCirtwillCazellesEtAl2016
%3 BibTeX type = ARTICLE