Just published: An empirical attack tolerance test alters the structure and species richness of plant–pollinator networks

The latest paper from Paolo Biella‘s PhD work, on which I collaborated and that I’ve discussed before on the blog, has just been published in the journal Functional Ecology. It’s entitled “An empirical attack tolerance test alters the structure and species richness of plant–pollinator networks“. The paper presents more of Paolo’s work showing how the experimental removal of the floral resources provided by the more generalised plants in a community can significantly (and negatively) affect the patterns of interaction between flowers and pollinators that we observe. It’s another piece of evidence that demonstrates how important it is to not neglect the common plants that attract a lot of flower visitors when considering how to manage a habitat.

If anyone has trouble accessing the PDF, drop me a line and I will send it to you.

Here’s the reference:

Biella, P., Akter, A., Ollerton, J., Nielsen, A. & Klecka, J. (2020) An empirical attack tolerance test alters the structure and species richness of plant-pollinator networks. Functional Ecology DOI: 10.1111/1365-2435.13642

Here’s the abstract:

Ecological network theory hypothesizes that the structuring of species interactions can convey stability to the system. Investigating how these structures react to species loss is fundamental for understanding network disassembly or their robustness. However, this topic has mainly been studied in‐silico so far.

Here, in an experimental manipulation, we sequentially removed four generalist plants from real plant–pollinator networks. We explored the effects on, and drivers of, species and interaction disappearance, network structure and interaction rewiring. First, we compared both the local extinctions of species and interactions and the observed network indices with those expected from three co‐extinction models. Second, we investigated the trends in network indices and rewiring rate after plant removal and the pollinator tendency at establishing novel links in relation to their proportional visitation to the removed plants. Furthermore, we explored the underlying drivers of network assembly with probability matrices based on ecological traits.

Our results indicate that the cumulative local extinctions of species and interactions increased faster with generalist plant loss than what was expected by co‐extinction models, which predicted the survival or disappearance of many species incorrectly, and the observed network indices were lowly correlated to those predicted by co‐extinction models. Furthermore, the real networks reacted in complex ways to plant removal. First, network nestedness decreased and modularity increased. Second, although species abundance was a main assembly rule, opportunistic random interactions and structural unpredictability emerged as plants were removed. Both these reactions could indicate network instability and fragility. Other results showed network reorganization, as rewiring rate was high and asymmetries between network levels emerged as plants increased their centrality. Moreover, the generalist pollinators that had frequently visited both the plants targeted of removal and the non‐target plants tended to establish novel links more than who either had only visited the removal plants or avoided to do so.

With the experimental manipulation of real networks, our study shows that despite their reorganizational ability, plant–pollinator networks changed towards a more fragile state when generalist plants are lost.

4 Comments

Filed under Bees, Biodiversity, Pollination

4 responses to “Just published: An empirical attack tolerance test alters the structure and species richness of plant–pollinator networks

  1. Dr P A Azeez

    Thank you for that update; It is very interesting. If you can share a PDF of the full paper that would be great.
    Regards
    P A Azeez

    Liked by 1 person

  2. Hi thats really interesting I would also like to read the PDF if possible.

    Liked by 1 person

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