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1. Verification of trophic interactions Individually collected insects with chewing mouth parts were tested in no-choice feedingassays to verify active herbivory. Insects were kept in an arena (50 ml PP tubes) with 10 – 20 mm² pieces of leaf material conspecific to the sampled host plant on the bottom and 2 cm² of moistened paper clips on the top to provide humidity. Leaf pieces were screened for chewing traces (positive interaction) 24 – 48 h after start. Insects with negative no-choice assays were excluded. As insects with sucking mouth parts (e.g. cicadas) usually don’t show clear feeding traces in plant material, they were identified to species level and checked if their published records of host plants included the sampled plant species (Tables S1 and S2). Wingless insects that belonged to exclusively herbivorous taxa (e.g. cicada nymphs) were not submitted to no-choice feeding-assays but instead assigned to morphospecies levels and kept in the analysis, as they were most probably no tourists on the particular host plant. Caterpillars were reared to adults (in 50 ml PP tubes with moisture paper clips and plenty of source plant material), if possible, and then identified. Where final identification was impossible, morphospecies were assigned. Voucher specimens of all herbivores were deposited at the Natural Museum of Basel (Psylloidea) and at the department of Plant Ecology and Systematics at the University of Kaiserslautern (all other taxa). Reared butterflies were conserved by pinning, about half of the caterpillars frozen, all other insects stored in 70% Ethanol. Using published host plant ranges, herbivores were classified into two levels of trophic specialization: Specialists (not feeding on more than one plant family) and generalists (feeding on several plant families or being zoophytophagous) (Table S1). Voucher Bähner K, Zweig KA, Leal IR, Wirth R. Robustness of plant-insect herbivore interaction networks to climate change in a fragmented temperate forest landscape. [email protected] specimens were deposited at the Natural Museum of Basel (Psylloidea) and at the department of Plant Ecology and Systematics at the University of Kaiserslautern (all other taxa). 2. Analysis of effects of forest fragmentation on plant-herbivore interaction networks (PHNs) via rarefaction curves For network-related definitions and terminology we followed Dormann et al. (2009). To quantify topological network properties related to network robustness (complexity, cohesiveness and trophic niche redundancy) we used quantitative indices, i.e. Shannon diversity of interactions (H2, Rzanny & Voigt, 2012), nestedness (Bascompte et al., 2003) and the complementary specialization at network level (H2’, Blüthgen et al., 2008). Shannon diversity of interactions simply is the two-dimensional equivalent of the Shannon index (Rzanny & Voigt, 2012) and is positively affected by the number of links and their evenness (Blüthgen et al., 2008). In nested bipartite networks few species from both trophic levels form a core or hub of many strong links that also connects to all other species as succeeding subsets. Nestedness therefore also is a measure for trophic redundancy (Bascompte & Jordano, 2007). Consequently, nested PHNs are highly resistant to extinctions, in which least abundant species die off first, because a large core of interactions remains relatively unchanged until the very end of an extinction series (Bascompte & Jordano, 2007), yet they are highly fragile if strongly connected species are eliminated first (Memmott et al., 2004). Nestedness is affected by, and must Bähner K, Zweig KA, Leal IR, Wirth R. Robustness of plant-insect herbivore interaction networks to climate change in a fragmented temperate forest landscape. [email protected] hence be controlled for, sampling effort, since nested interaction patterns can be the result of abundance-based interactions (Blüthgen, 2010) under interaction neutrality (Vázquez et al., 2009). From the various available metrics that measure nestedness, we chose the BINMATNEST algorithm (Rodríguez-Gironés & Santamaría, 2006) that gives values between 0 (perfect nestedness) and 100 (maximal matrix entropy). The complementary specialization on network level (H2’, Blüthgen et al., 2006) measures niche-based trophic complementarity in a network. It is a normalized derivative from the Shannon diversity of interactions (H2, see above) based on constant matrix row- and column sums. An H2’ score of 0 represents maximal redundancy, i.e. each trophic niche is nested within another (Blüthgen & Klein, 2011), while values close to 1 indicate high niche complementarity (Blüthgen et al., 2006), i.e. the full range of host plants is needed to sustain the herbivore community. Note that the metric measures the topology of realized, rather than fundamental niches (Blüthgen & Klein, 2011), as it is applied to empirical data under field conditions. Supporting references Bascompte, J. & Jordano, P. (2007) Plant-animal mutualistic networks: the architecture of biodiversity. Annual Review of Ecology, Evolution, and Systematics 38, 567–593. Bascompte, J., Jordano, P., Melián, C. J., & Olesen, J. M. (2003). The nested assembly of plant-animal mutualistic networks. Proceedings of the National Academy of Sciences of the United States of America 100, 9383–9387. Bähner K, Zweig KA, Leal IR, Wirth R. Robustness of plant-insect herbivore interaction networks to climate change in a fragmented temperate forest landscape. [email protected] Blüthgen, N. (2010) Why network analysis is often disconnected from community ecology: a critique and an ecologist’s guide. Basic and Applied Ecology 11, 185– 195. Blüthgen, N., Menzel & F., Blüthgen, N. (2006) Measuring specialization in species interaction networks. BMC Ecology 6, 1–12. Blüthgen, N., Fründ, J., Vázquez, D.P. & Menzel, F. (2008) What do interaction network metrics tell us about specialization and biological traits? Ecology 89, 3387– 3399. Blüthgen, N., Klein & A.-M. (2011) Functional complementarity and specialisation: the role of biodiversity in plant–pollinator interactions. Basic and Applied Ecology 12, 282–291. Dormann, C. F., Fründ, J., Blüthgen, N., & Gruber, B. (2009). Indices, graphs and null models: analyzing bipartite ecological networks. The Open Ecology Journal 2, 7–24. Memmott, J., Waser, N.M. & Price, M.V. (2004) Tolerance of pollination networks to species extinctions. Proceedings of the Royal Society B: Biological Sciences 271, 2605–2611. Rodríguez-Gironés, M.A. & Santamaría, L. (2006) A new algorithm to calculate the nestedness temperature of presence-absence matrices. Journal of Biogeography 33, 924–935. Rzanny, M., & Voigt, W. (2012). Complexity of multitrophic interactions in a grassland ecosystem depends on plant species diversity. Journal of Animal Ecology 81, 614– 627. Bähner K, Zweig KA, Leal IR, Wirth R. Robustness of plant-insect herbivore interaction networks to climate change in a fragmented temperate forest landscape. [email protected] Vázquez, D.P., Blüthgen, N., Cagnolo, L. &Chacoff, N.P. (2009) Uniting pattern and process in plant-animal mutualistic networks: a review. Annals of Botany 103, 1445–1457. Bähner K, Zweig KA, Leal IR, Wirth R. Robustness of plant-insect herbivore interaction networks to climate change in a fragmented temperate forest landscape. [email protected]