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Abstract

BackgroundNetwork analyses of plant-animal interactions hold valuable biological information. They are often used to quantify the degree of specialization between partners, but usually based on qualitative indices such as 'connectance' or number of links. These measures ignore interaction frequencies or sampling intensity, and strongly depend on network size.ResultsHere we introduce two quantitative indices using interaction frequencies to describe the degree of specialization, based on information theory. The first measure (d') describes the degree of interaction specialization at the species level, while the second measure (H2') characterizes the degree of specialization or partitioning among two parties in the entire network. Both indices are mathematically related and derived from Shannon entropy. The species-level index d' can be used to analyze variation within networks, while H2' as a network-level index is useful for comparisons across different interaction webs. Analyses of two published pollinator networks identified differences and features that have not been detected with previous approaches. For instance, plants and pollinators within a network differed in their average degree of specialization (weighted mean d'), and the correlation between specialization of pollinators and their relative abundance also differed between the webs. Rarefied sampling effort in both networks and null model simulations suggest that H2' is not affected by network size or sampling intensity.ConclusionQuantitative analyses reflect properties of interaction networks more appropriately than previous qualitative attempts, and are robust against variation in sampling intensity, network size and symmetry. These measures will improve our understanding of patterns of specialization within and across networks from a broad spectrum of biological interactions.

Changes in phytophagous insect host ranges following the invasion of their community: Long‐term data for fruit flies

“…Fruits are thought to vary in terms of their biotic capacity. Thus, insects using all plants at rates proportional to their biotic capacity in the environment should be considered more generalist than species using resources with a low biotic capacity (Blüthgen, Menzel, & Blüthgen, 2006). We took this variation between fruit species into account by normalizing each row of the 10,000 matrices.…”

Partitioning of seed dispersal services between birds and bats in a fragment of the Brazilian Atlantic Forest

“…There are several ecological concepts of specialization, which take into account not only the number of interactions made by a species, but also different aspects of the phylogenetic signal in those interactions (DEVICTOR et al 2010). However, in the network literature, specialization is in most cases referred to as simply the number or strength of the interactions made by a species or the uniqueness of those interactions when compared to the patterns observed in other species in the same network (BLÜTHGEN et al 2006). We propose that, in network studies, specialization should be defined on biological grounds, while centrality metrics should be used as surrogates for relative importance in the community as a network.…”

Trophic level, successional age and trait matching determine specialization of deadwood-based interaction networks of saproxylic beetles

“…Logs with samples lost during the investigation period due to storm or mice damage were excluded from all analyses. The calculation of specialization may be highly confounded for species representing just one individual in all samples or in a single network [7]. Therefore, we excluded 116 singletons: 51 xylophages, 26 fungivores and 39 predatory saproxylic beetle species.…”

“…For both levels, we choose indices that are robust against variation in matrix size, shape and sampling effort [7,34].…”

“…An often-used tool for this purpose was to examine structural differences between network types, such as specialization, nestedness, compartmentalization, robustness and generality. For example, mutualistic plantpollinator networks are more specialized than seed-disperser networks [7], and show a higher degree of nestedness, while antagonistic networks are more compartmentalized [8]. A new approach to explain the structure and dynamics of mutualistic networks incorporates traits of interaction partners [9].…”