10.5281/zenodo.3549869
https://zenodo.org/records/3549869
oai:zenodo.org:3549869
de Manincor, Natasha
Natasha
de Manincor
0000-0001-9696-125X
Université de Lille, CNRS, UMR 8198 - Evo-Eco-Paleo, 59000 Lille, France
Hautekeete, Nina
Nina
Hautekeete
0000-0002-6071-5601
Université de Lille, CNRS, UMR 8198 - Evo-Eco-Paleo, 59000 Lille, France
Piquot, Yves
Yves
Piquot
0000-0001-9977-8936
Université de Lille, CNRS, UMR 8198 - Evo-Eco-Paleo, 59000 Lille, France
Schatz, Bertrand
Bertrand
Schatz
0000-0003-0135-8154
CEFE, EPHE-PSL, CNRS, University of Montpellier, University of Paul Valéry Montpellier 3, IRD, Montpellier, France
Vanappelghem, Cédric
Cédric
Vanappelghem
Conservatoire d'espaces naturels Nord et du Pas-de-Calais, 160 rue Achille Fanien - ZA de la Haye, 62190 LILLERS
Massol, François
François
Massol
0000-0002-4098-955X
Université de Lille, CNRS, UMR 8198 - Evo-Eco-Paleo, 59000 Lille, France
Does phenology explain plant-pollinator interactions at different latitudes? An assessment of its explanatory power in plant-hoverfly networks in French calcareous grasslands
Zenodo
2019
Bayesian model
interaction probability
latent block model
latitudinal gradient
mutualistic network
phenology overlap
species abundance
structural equation model
2019-11-22
10.5281/zenodo.2543768
Creative Commons Attribution 4.0 International
Title: Does phenology explain plant-pollinator interactions at different latitudes? An assessment of its explanatory power in plant-hoverfly networks in French calcareous grasslands
Authors: Natasha de Manincor¹*, Nina Hautekeete¹, Yves Piquot¹, Bertrand Schatz², Cédric Vanappelghem³, François Massol¹,4
Abstract
For plant-pollinator interactions to occur, the flowering of plants and the flying period of pollinators (i.e. their phenologies) have to overlap. Yet, few models make use of this principle to predict interactions and fewer still are able to compare interaction networks of different sizes. Here, we tackled both challenges using Bayesian Structural Equation Models (SEM), incorporating the effect of phenological overlap in six plant-hoverfly networks. Insect and plant abundances were strong determinants of the number of visits, while phenology overlap alone was not sufficient, but significantly improved model fit. Phenology overlap was a stronger determinant of plant-pollinator interactions in sites where the average overlap was longer and network compartmentalization was weaker, i.e. at higher latitudes. Our approach highlights the advantages of using Bayesian SEMs to compare interaction networks of different sizes along environmental gradients and articulates the various steps needed to do so.