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Phenological shifts alter the seasonal structure of pollinator assemblages in Europe

Nature Ecology & Evolution volume 4, pages 115–121 (2020)Cite this article

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An Author Correction to this article was published on 13 January 2020

This article has been updated

Abstract

Pollinators play an important role in terrestrial ecosystems by providing key ecosystem functions and services to wild plants and crops, respectively. The sustainable provision of such ecosystem functions and services requires diverse pollinator communities over the seasons. Despite evidence that climate warming shifts pollinator phenology, a general assessment of these shifts and their consequences on pollinator assemblages is still lacking. By analysing phenological shifts of over 2,000 species, we show that, on average, the mean flight date of European pollinators shifted to be 6 d earlier over the last 60 yr, while their flight period length decreased by 2 d. Our analysis further reveals that these shifts have probably altered the seasonal distribution of pollination function and services by decreasing the overlap among pollinators’ phenologies within European assemblages, except in the most northeastern part of Europe. Such changes are expected to decrease the functional redundancy and complementarity of pollinator assemblages and, therefore, might alter the performance of pollination function and services and their robustness to ongoing pollinator extinctions.

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Fig. 1: MFD shifts of European flower visitors between 1960 and 2016.
Fig. 2: Spatial and seasonal heterogeneity in phenological shifts among species.
Fig. 3: Changes in within- and among-orders average overlaps in phenology between 1980 and 2016 across Europe.

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Data availability

The final dataset analysed in this paper is available at https://zenodo.org/record/3480120.

Code availability

The codes used to extract data from the GBIF, to separate modes of multimodal phenologies and to estimate phenological shifts are available at https://github.com/f-duchenne/Flower-visitors-phenology.

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Acknowledgements

We especially thank N. Loeuille and T. Van Dooren for their comments on this work, and E. Porcher, A. Perrard, E. Teulière, E. Faure, E. Kerdoncuff, B. Perez and T. Olivier for fruitful discussions. We also thank all naturalists who provided data to complete our database, especially L. Casset, F. Chevaillot, L. Guilbaud (INRA), J.-L. Hentz (Nature du Gard) and G. Lemoine, as well as C. Daugeron, R. Rougerie, C. Villemant, E. Delfosse, J. Barbut and O. Montreuil who helped us to access insect collections of the French National Natural History Museum. This project was funded by the Ministère de la Transition Ecologique et Solidaire as part of the project ‘What is the sensitivity of pollinators to global warming in France?’ (convention no. SJ 3–17) led by C. Daugeron and C. Fontaine, and by the Institut de la Transition Ecologique, Sorbonne Université, as part of the project Yapludsaison.

Author information

Authors and Affiliations

  1. Institute of Ecology and Environmental Sciences of Paris, Sorbonne Université, CNRS, Université Paris-Est Créteil, INRA, IRD, Paris, France

    F. Duchenne & E. Thébault

  2. Centre d’Ecologie et des Sciences de la Conservation, CNRS, MNHN, Sorbonne Université, Paris, France

    F. Duchenne & C. Fontaine

  3. Laboratory of Zoology, Research Institute of Biosciences, University of Mons, Mons, Belgium

    D. Michez

  4. Institut de Systématique, Evolution, Biodiversité, MNHN, CNRS, Sorbonne Université, EPHE, Université des Antilles, Paris, France

    M. Elias

  5. Orchid House, Axminster, UK

    M. Drake

  6. Department of Water Resources Engineering, Lund University, Lund, Sweden

    M. Persson

  7. Natagora, Brussels, Belgium

    J. S. Rousseau-Piot

  8. Research Group Species Diversity (SPECDIV), Research Institute for Nature and Forest (INBO), Brussels, Belgium

    M. Pollet

  9. Natuurpunt Studie, Mechelen, Belgium

    P. Vanormelingen

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  1. F. Duchenne
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Contributions

F.D., C.F. and E.T. conceived the project. F.D. assembled the dataset and performed the statistical analysis. F.D., C.F., E.T., D.M. and M.E. interpreted the results. M.D., M.Persson, J.S.R.-P., M.Pollet and P.V. provided data and biological expertise on the studied species. F.D. wrote the paper with contributions from all authors.

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Correspondence to F. Duchenne.

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Extended data

Extended Data Fig. 1 Spatial and temporal distribution of records by order.

a, Number of phenologies (light colors, left) and species (dark colors, right) for each insect order. b-e, Spatial and f, temporal distribution of records for Coleoptera (b, red), Diptera (c, blue), Hymenoptera (d, light green) and Lepidoptera (e, magenta). Y-axis of (f) is on a log10 scale.

Extended Data Fig. 2 Average MFD shifts before and after the temperature increase.

a, Temperatures anomalies on the first 150 days of each year against years. The orange curve represents the result of a LOESS fit. Vertical lines show the position of the 3 breakpoints chosen to define periods used in (b). b, Mean flight date shifts for the whole pollinator assemblage by period, before the breakpoints (Slope1) and after the breakpoints (Slope 2).

Extended Data Fig. 3 Flight period length (FPL) changes of European flower visitors between 1960 and 2016.

a, Phylogeny of studied species showing FPL shifts. The bars around the phylogeny tips are proportional to the FPL shifts and colored in blue and red for shortening and lengthening, respectively. Values are truncated to −0.6 and to 0.6 days/year to preserve readability. Histograms show FPL shifts for all studied species of b, Coleoptera (red), c, Diptera (blue), d, Hymenoptera (light green) and e, Lepidoptera (magenta). Full bars represent species with values significantly distinct from zero whereas open bars are species with a value non-significantly distinct from zero. FPL shifts shown here are predicted for the averaged latitude and longitude of each species’ records.

Extended Data Fig. 4 MFD shifts of the second mode against MFD shifts of the first mode for multimodal phenologies.

Mean flight date (MFD) shifts of the second mode against MFD shifts of the first mode for all 190 species presenting a multimodal phenologies with enough data in 2 modes to study both (cf. Methods). Color indicates p-value (red: <0.05 and blue >0.05) of the Z test comparing both shifts. The black line is the first bisector. Red points above the first bisector show species with a first mode advancing significantly more than the second one, while red points under the first bisector show the opposite pattern and blue points do not show any significant differences between two mode shifts.

Extended Data Fig. 5 Seasonal changes in the overlap among phenologies between 1980 and 2016.

Changes in the overlap among orders (blue) and within orders (yellow) between 1980 and 2016 along the season, considering only grid cells with enough data (see Supplementary Fig. 6). Cells are sorted by latitude then longitude (Lat,Long).

Extended Data Fig. 6 Spatial distribution of phenologies in grid cells.

Number of phenologies by order in 5° × 5° grid cells, considering only grid cells with enough data, that is with at least 3 insect orders including at least 20 species with at least 30 records each.

Extended Data Fig. 7 Examples of multimodal phenologies split into distinct modes.

The example of Epirrhoe tristate (Lepidoptera) shows how our method distributes records in function of a, Julian days, b, space and especially c, latitude. Other examples for Bombus lapidarius (d, Hymenoptera), Melitaea phoebe (e, Lepidoptera) and Pararge aegeria (f, Lepidoptera). For the Bombus, we can see that our method is able to separate emerging queens (light blue) and workers/males (dark blue) phenology, whereas we also detect 3 modes for Pararge aegeria and 2 for Melitaea phoebe in agreement with what we know about the voltinism of these species.

Supplementary information

Supplementary Information

Supplementary Tables 1, 3 and 4 and Supplementary Methods.

Reporting Summary

Supplementary Table 2

Estimates of MFD shifts, FPL changes, interaction effects among the year and the spatial variables on the MFD for each phenology mode of each species. The interaction coefficient shows the spatial intraspecific variation in MFD shifts.

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Duchenne, F., Thébault, E., Michez, D. et al. Phenological shifts alter the seasonal structure of pollinator assemblages in Europe. Nat Ecol Evol 4, 115–121 (2020). https://doi.org/10.1038/s41559-019-1062-4

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