Flower-power: Flower diversity is a stronger predictor of network structure than insect diversity in an Arctic plant–pollinator network

Both plant and insect communities undergo phenological changes across the season, leading to seasonal changes in species diversity and interactions. Network theory offers important tools for understanding how groups of flowering plants and insects interact. However, most studies of plant pollinator...

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Bibliographic Details
Published in:Ecological Complexity
Main Authors: Robinson SVJ, LOSAPIO G, Henry Gregory HR
Other Authors: S. Robinson, G. Losapio, H. Henry Gregory
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2018
Subjects:
Biotic interaction
Complexity
Path analysi
Phenology
Seasonality
Settore BIO/03 - Botanica Ambientale e Applicata
Settore BIO/07 - Ecologia
Settore AGR/11 - Entomologia Generale e Applicata
Arctic
Online Access:http://hdl.handle.net/2434/899386
https://doi.org/10.1016/j.ecocom.2018.04.005
Description
Summary:Both plant and insect communities undergo phenological changes across the season, leading to seasonal changes in species diversity and interactions. Network theory offers important tools for understanding how groups of flowering plants and insects interact. However, most studies of plant pollinator networks aggregate samples over time, masking phenological changes in the network over the growing season. Furthermore, estimates of biodiversity are derived from network observations, meaning that the ecological community is not assessed independently from the structure of the network. Understanding how biodiversity influences network structure over time is important for predicting how global change will affect the ecological processes shaping networks. In this study, we sampled the flower community, insect community, and the pollination network of a high Arctic dwarf-shrub ecosystem over the course of an entire growing season. We found that the flower community was a stronger predictor of network complexity and interaction diversity than the insect community. We suggest that studying networks at scales relevant to both plants and pollinators can provide insight into the mechanisms underlying network formation. This improved knowledge could help to better understand and predict the ongoing phenological changes in Arctic and alpine ecosystems.

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