Specialization on traits as basis for the niche-breadth of flower visitors and as structuring mechanism of ecological networks

• Published in: Functional ecology Vol. 27; no. 2; pp. 329 - 341
• Main Authors: Junker, Robert R., Blüthgen, Nico, Brehm, Tanja, Binkenstein, Julia, Paulus, Justina, Schaefer, H. Martin, Stang, Martina
• Format: Journal Article
• Language: English
• Published: Oxford Blackwell Publishing 01.04.2013; Wiley-Blackwell; Wiley Subscription Services, Inc
• Subjects: Animal and plant ecology; Animal, plant and microbial ecology; Animals; Arthropoda; Autoecology; Biological and medical sciences; Ecology; Evolutionary ecology; floral filters; floral resources; flower colour; Flowers; Fundamental and applied biological sciences. Psychology; General aspects; hierarchy of traits; Human ecology; morphology; niche; n‐dimensional hypervolume; Phenotypic traits; Plant ecology; Plant taxonomy; Plants; pollination; Species; Taxa; floral resources; Flower; floral filters; Visitor; Color; Ecology; flower colour; Pollination; n-dimensional hypervolume; Hierarchy; Specialization; Filter; Morphology; Ecological niche; niche; hierarchy of traits
• DOI: 10.1111/1365-2435.12005
• ISSN: 0269-8463

1. Biotic interactions do not occur in isolation but are imbedded in a network of species interactions. Network analysis facilitates the compilation and understanding of the complexity found in natural ecosystems and is a powerful tool to reveal information on the degree of specialization of the interacting partners and their niches. The indices measuring these properties are based on qualitative or quantitative observations of interactions between partners from different trophic levels, which informs about the structure of network patterns, but not about the underlying mechanisms. Functional traits may control the interaction strength between partners and also the (micro-) structure of networks. Here, we ask whether flower visitors specialize on certain plant traits and how this trait specialization contributes to niche partitioning and interaction partner diversity. 2. We introduce two novel statistical approaches suited to evaluate the dimension of the realized niche and to analyse which traits determine niches. As basis for our analysis, we measured 10 quantitative flower traits and evaluated whether 31 arthropod taxa i visited flowers displaying only subsets of the available trait characteristics, indicating a specialization on these traits by narrow trait-widths 〈S i 〉. The product of 10 trait- and species-specific trait-widths 〈S i 〉 was defined as trait-volume V i (expansion of a n-dimensional hypervolume) occupied by each taxon i. These indices are applicable beyond flower—visitor interactions to quantify realized niches based on various biotic and abiotic factors. 3. Each flower visitor species showed some degree of specialization to a unique set of flower traits (realized niche). Overall, our data suggested a hierarchical sequence of flower traits influencing the flower visitors' behaviour and thus network structure: flowering phenology was found to have the strongest effect, followed by flower height, nectar-tube depth and floral reflectance. Less important were pollen-mass/flower, sugar/flower, anther position, phylogeny, display size and abundance. 4. The species-specific specialization on traits suggests that plant communities with more diverse floral niches may sustain a larger number of flower visitors with non-redundant fundamental niches. Our study and statistical approach provide a basis for a better understanding of how plant traits shape interactions between flowers and their visitors and thus network structure.