Measuring specialization in species interaction networks

By Nico Blüthgen, Florian Menzel, Nils Blüthgen. BMC Ecology, 2006

1,386 citations recorded by the source corpus.

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.

Subfields: Ecology, Evolution, Behavior and Systematics, Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/f57ea409c997ffc9d8a2b8203a0311b70397ac0f

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Citations in the corpus

Plant-hummingbird interaction networks in urban areas: Generalization and the importance of trees with specialized flowers as a nectar resource for pollinator conservation (2019, background): “Complementary specialization, H 2 ’ , is an index designed to measure network-wide specialization for quantitative interaction matrices and describes how species restrict their interactions from those randomly expected based on partner availability (Blüthgen et al., 2006).”
The same, but different: pollen foraging in honeybee and bumblebee colonies (2011, methodology): “To further describe the overall degree of chemical partitioning of amino acids across bee species or colonies, we used the quantitative network-level specialization index H2′ (Blüthgen et al. 2006) modified for the analysis of chemical data as described in Leonhardt et al.”
Weed-insect pollinator networks as bio-indicators of ecological sustainability in agriculture. A review (2016, background): “Specialization can be measured as the specific or network level (Blüthgen et al. 2006).”
Network properties of an epiphyte metacommunity (2007, background): “Bluthgen et al. (2006) documented that pollination networks aren’t always predicted by the relative abundances of mutualists, while Santamaria & Rodriguez-Girones (2007) found that ‘mixed-models’, which incorporated the effects of both relative abundances and forbidden links, provide the best fit t”
Patterns of pollinator turnover and increasing diversity associated with urban habitats (2017, background): “ciations (while fixing row and column totals), thereby simulating completely opportunistic associations (Blüthgen et al. 2006).”