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Animals visit flowers to access resources and by moving pollen to conspecific individuals act as pollinators. While biotic pollinators can increase the seed set of plants, other flower visitors can reduce seed set directly by damaging vital reproductive organs and indirectly by affecting the way the plant interacts with subsequent flower visitors. It is, therefore, vital to understand the varied effects of all visitors and not only pollinators on plant fitness, including those visitors that are temporally or spatially rare. We document the first known case of flower visitation by small mammals to C rotalaria cunninghamii ( Fabaceae), a plant species morphologically suited to bird pollination. During a rain-driven resource pulse in the Simpson Desert in 2011, the rodents M us musculus ( Muridae) and P seudomys hermannsburgensis ( Muridae) visited flowers to remove nectar by puncturing the calyx. We investigated the effects of this novel interaction on the reproductive output of C . cunninghamii. Compared with another recent resource pulse in 2007, plants flowering during mammal visitation had five times as many inflorescences per plant, 90% more flowers per inflorescence, and two to three times more nectar per flower, but this nectar was 30% less sugar rich. Concurrently, rodent plagues were up to three times larger during this rain-driven resource pulse than during a previous pulse in 2007. Up to 75% of flowers had evidence of small mammal florivory, but this was not necessarily destructive, as up to 90% of fruit had the remains of florivory. Through a series of exclusion experiments, we found that small mammal florivory did not directly reduce seed set. We conclude that rain-driven resource pulses led to a unique combination of events that facilitated the novel florivory interaction. Our findings emphasize the dynamic nature of biotic interactions and the importance of testing the role of all visitors to pollination services. [ABSTRACT FROM AUTHOR]

Mutualistic networks display distinct structural and organizational features such as nestedness, power-law degree distribution and asymmetric dependencies. Attention is now focused on how these structural properties influence network function. Most plant-pollinator networks are constructed using records of animals contacting flowers, which is based on the assumption that all visitors to flowers are pollinators; however, animals may visit flowers as nectar robbers, florivores, or to prey upon other visitors. To differentiate potential pollinator interactions from other interaction types, we examined individual bees that had visited flowers to detect if they carried pollen. Using these data, we constructed visitation and pollen-transport networks for a spinifex-dominated arid zone grassland. To determine how the structure of the visitation network reflects pollen transport, we compared the two networks using a null model approach to account for differences in network size. Differences in number of species, nestedness and connectance observed between the visitation and pollen-transport networks were within expected ranges generated under the null model. The pollen-transport network was more specialized, had lower interaction evenness, and fewer links compared to the visitation network. Almost half the number of species of the visitation network participated in the pollen-transport network, and one-third of unique visitation interactions resulted in pollen transport, highlighting that visitation does not always result in pollination. Floral visitor data indicate potential pollen transporters, but inferring pollination function from visitation networks needs to be performed cautiously as pollen transport resulted from both common and rare interactions, and depended on visitor identity. Although visitation and pollen-transport networks are structurally similar, the function of all species cannot be predicted from the visitation network alone. Considering pollen transport in visitation networks is a simple first step towards determining pollinators from non-pollinators. This is fundamental for understanding how network structure relates to network function. [ABSTRACT FROM AUTHOR]