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Projected decline in European bumblebee populations in the twenty-first century

Nature volume 628, pages 337–341 (2024)Cite this article

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Abstract

Habitat degradation and climate change are globally acting as pivotal drivers of wildlife collapse, with mounting evidence that this erosion of biodiversity will accelerate in the following decades1,2,3. Here, we quantify the past, present and future ecological suitability of Europe for bumblebees, a threatened group of pollinators ranked among the highest contributors to crop production value in the northern hemisphere4,5,6,7,8. We demonstrate coherent declines of bumblebee populations since 1900 over most of Europe and identify future large-scale range contractions and species extirpations under all future climate and land use change scenarios. Around 38–76% of studied European bumblebee species currently classified as ‘Least Concern’ are projected to undergo losses of at least 30% of ecologically suitable territory by 2061–2080 compared to 2000–2014. All scenarios highlight that parts of Scandinavia will become potential refugia for European bumblebees; it is however uncertain whether these areas will remain clear of additional anthropogenic stressors not accounted for in present models. Our results underline the critical role of global change mitigation policies as effective levers to protect bumblebees from manmade transformation of the biosphere.

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Fig. 1: Changes in ecological suitability for 46 European bumblebee species based on an observational dataset of 401,046 unique georeferenced occurrence records.
Fig. 2: Analysis of the loss of areas ecologically suitable for bumblebee species.

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Data availability

Bombus occurrence data are available on Atlas Hymenoptera: http://www.atlashymenoptera.net/page.aspx?id=169). All ISIMIP2b data used are publicly available on https://www.isimip.org/protocol/2b/.

Code availability

R scripts related to the ecological niche modelling and projections are all available at https://github.com/sdellicour/projections_bombus.

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Acknowledgements

We are grateful to A. Dejins for his useful comments on the analytical approach. G.G., F.M. and S.D. acknowledge support from the Fonds National de la Recherche Scientifique (FNRS, Belgium). G.G. and D.M. acknowledge support from the European DG ENV projects ORBIT (contract no. 09.029901/2021/848268/SER/ENV.D.2), PULSE (contract no. 07.027755/2020/840209/SER/ENV.D.2), SPRING (contract no. 09.02001/2021/847887/SER/ENV.D.2) and the H2020 project SAFEGUARD (grant agreement no. 101003476). S.D. acknowledges support from the FNRS (grant no. F.4515.22), the Research Foundation—Flanders (Fonds voor Wetenschappelijk Onderzoek—Vlaanderen, grant no. G098321N) and from the European Union Horizon 2020 project MOOD (grant agreement no. 874850). For the production and coordination of the input data and impact model output of ISIMIP (www.isimip.org), we are grateful to the modelling groups, the ISIMIP sector coordinators and the ISIMIP cross-sectoral science team.

Author information

Authors and Affiliations

  1. Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium

    Guillaume Ghisbain, Diana Erazo & Simon Dellicour

  2. Laboratory of Zoology, Research Institute for Biosciences, Université de Mons, Mons, Belgium

    Guillaume Ghisbain, Pierre Rasmont & Denis Michez

  3. Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel, Brussels, Belgium

    Wim Thiery

  4. Earth and Climate Research Center, Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium

    François Massonnet

  5. Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium

    Simon Dellicour

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  1. Guillaume Ghisbain
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Contributions

G.G. and S.D. designed the research and wrote the manuscript. S.D. conducted the analyses with the assistance of W.T., F.M. and D.E. P.R. and D.M. managed the database. All authors contributed to editing the manuscript.

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Correspondence to Guillaume Ghisbain or Simon Dellicour.

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Extended data figures and tables

Extended Data Fig. 1 Assessment of the predictive performance of species-specific ecological niche models trained on past (1901–1970) and present-day (2000–2014) occurrence and environmental data.

Specifically, we computed the prevalence-pseudoabsence-calibrated Sørensen index (SIppc) while performing an optimization of the ecological suitability threshold in the range [0, 1] with a 0.01 step increment. This threshold value was used to generate binary versions of the ecological suitability maps necessary for the computation of this index and we eventually selected the threshold value maximizing the SIppc (see Extended Data Table 1 for the optimized SIppc values and associated threshold). We here report the evolution of the SIppc according to the considered ecological suitability threshold value. We report this relationship for each species and for each ecological niche model trained on past (light grey curves) and present-day (dark grey curves) data.

Extended Data Fig. 2 Evolution of the ecological suitability map of European bumblebees as measured by the species richness index (SRI).

The SRI is here defined as the local number of species associated with an ecological suitability higher than the median threshold value retrieved from the optimization step of the prevalence-pseudoabsence-calibrated Sørensen index (SIppc) computed for each of ten ecological niche models trained on present-day data (see the Methods for further detail). We here report the SRI estimates for the past, present (‘t0’) and future projections, as well as the differences between past, present (‘t0’) and future projections.

Extended Data Fig. 3 Occurrence data available for the 46 selected European bumblebee species for the first time period (1901–1974).

Duplicate records were removed to reflect species presence rather than species density and to further decrease potential sampling biases. All species distributions are represented by at least 30 unique data records. A total of 125,283 unique records were retained for this time period.

Extended Data Fig. 4 Occurrence data available for the 46 selected European bumblebee species for the second time period (2000–2014).

Duplicate records were removed to reflect species presence rather than species density and to further decrease potential sampling biases. All species distributions are represented by at least 30 unique data records. A total of 275,763 unique records were retained for this time period.

Extended Data Fig. 5 Response curves associated with the different environmental variables included in the ecological niche models.

Each curve was retrieved from a boosted regression tree (BRT) model trained for a distinct species on present-day (2000–2014) occurrence data.

Extended Data Table 1 Assessment of the predictive performance of species-specific ecological niche models trained on past (1901–1970) and present-day (2000–2014) occurrence and environmental data
Full size table
Extended Data Table 2 Assessment of the predictive performance of ecological niche models to predict present and past ecological suitability maps
Full size table
Extended Data Table 3 Projection of the ecological suitability change between the present time and 2061–2080
Full size table
Extended Data Table 4 Relative importance (RI) of the different environmental factors in the ecological niche models either trained on past (1901–1970) or present-day (2000–2014) occurrence and environmental data
Full size table

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Ghisbain, G., Thiery, W., Massonnet, F. et al. Projected decline in European bumblebee populations in the twenty-first century. Nature 628, 337–341 (2024). https://doi.org/10.1038/s41586-023-06471-0

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