Table 1.
Glossary of main network terms and key references
Metric | Definition |
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Asymmetry | Measures the imbalance in the interaction strength of two interacting species (Bascompte et al, 2006). It is defined as ASij=(bij-bji)/(bij+bji), where bji is the reciprocal dependence of species j on species i (bij see interaction strength, Bascompte et al, 2006; Blüthgen et al, 2007). |
Binary network | In binary network matrix, the value is 0 or 1, if the interaction occurs, the value is 1, otherwise 0 (Jordano, 1987). |
Connectance | Proportion of the realized interactions in all possible interactions (Yodzism 1980). In mutualistic networks, connectance (C) is: C=L/(IJ). L describes the number of realized links; I and J are the number of species of each bipartite network (Blüthgen et al, 2008). |
Degree | Number of interactions a species has (Jordano et al, 2003). |
Interaction strength | Interaction strength of species j on species i (bij) can be defined by the proportion of interactions between i and j (aij) of the total interactions recorded for i; thus ![]() |
Modularity | Measures the degree to which the network is organized into clearly delimited modules (Olesen et al, 2007). Modularity (M):![]() |
Module | A set of weakly interlinked subsets of species that consist of strongly connected species (Olesen et al, 2007). |
Nestedness | A nonrandom pattern of the network structure, which entails the tendency of specialized species to interact with a subset of the interaction partners of more generalized species. The nestedness temperature (T) measures the departure from a perfectly nested interaction matrix, ranging from 0 to 100, which indicates the degree of disorder. T=0 is defined for maximum nestedness: when rows and columns are ordered by decreasing number of links, links of each row and column exactly represent a subset of the previous ones. Nestedness can be defined as N=(100°-T)/100° (Bascompte et al, 2003). |
Weighted network | Networks that include information on the intensity or weight of the interactions among nodes (Bascompte & Jordano, 2007). |