Plant-flower-visiting insect interactions of semiarid arborescent scrublands with Ziziphus lotus (Habitat 5220*, EU) in the southeast of Iberian Peninsula

[Methodology] We sampled the insect assemblage visiting flowers in the arborescent scrublands with Ziziphus lotus (Habitat 5520*, Habitat Directive EU) to characterize the plant-floral visitor networks of these threatened habitats in the semiarid southeast of the Iberian Peninsula, mainly in Almería province (Andalucia, Spain). We selected 6 localities with the presence of this Ziziphus lotus habitat: i) 2 localities in habitat dominated by Ziziphus lotus individuals (ZIZ); ii) 2 localities in habitat dominated by Maytenus senegalensis with Ziziphus lotus (ZIZMAY); iii) 2 localities in habitat dominated by Chamaerops humilis with Ziziphus lotus (ZIZCHA). To study the community of insect floral visitors and the flowering plant species community (floral resources) in these habitats, 6-7 transects of [50 m x 2 m] were defined in each population, which were sampled by 50 min-censuses from February-July at 3 different times (pre-spring + spring + summer; total transects sampled = 39 transects x 3 censuses = 117 transects). The sampled transects were randomly distributed, trying to cover the largest possible area within each population to avoid sampling bias. We recorded the insect community visiting flowers (plant-floral visitor interactions) in terms of richness and abundance per transect and population. We only recorded xenogamic plant-insect interactions (as a proxy for pollen movements between different plant individuals) since they are related to more effective pollination events than geitonogamic interactions. The censuses were carried out on sunny days with low winds (<12Km/h), between 9:00-17:00, during the period of maximum insect activity. The richness and abundance of plant-floral visitor interactions by transect were pooled by population ('Interaction_data_pop.csv' file). R software (R Core, 2021) was used to calculate the summaries showed in .csv files. References: - R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: https://www.R-project.org/