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Climate and land-use changes drive biodiversity turnover in arthropod assemblages over 150 years

Nature Ecology & Evolution volume 5, pages 1291–1300 (2021)Cite this article

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Abstract

Long-term studies are essential to understand the impacts of global changes on the multiple facets of biological diversity. Here, we use distribution data for over 600 species of arthropods collected over 150 years from locations across Italy and test how multiple environmental stressors (climate, land use and human population density) influenced assemblage composition and functionality. By carefully reconstructing the temporal changes in these stressors, we explicitly tested how environmental changes can determine the observed changes in taxonomic and functional diversity. We found that rapid changes in precipitation destabilize the assemblages and maximize colonization and extinction rates, especially when coupled with changes in human population density (for taxonomy) or temperature (for functionality). Higher microclimatic heterogeneity increases the stability of biodiversity by reducing taxonomic and functional loss. Finally, changes in natural habitats increased colonization, influencing taxonomic nestedness and functional replacement. The integration of long-term datasets combining distributions, climate and traits may deepen our understanding of the processes underlying biodiversity responses to global-scale drivers.

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Fig. 1: Potential effects of environmental changes on the α- and β-diversity of assemblages.
Fig. 2: Temporal changes in climate, land use and human population density over the entire time series (1859–2003 ce).
Fig. 3: Density plots of the posterior distributions for the relationships between the rates of change of β-diversity, turnover and nestedness and the candidate environmental drivers.
Fig. 4: Relationships between β-diversity and the environmental drivers returning significant interactions.
Fig. 5: Density plots of the posterior distributions for the relationships between the rates of change in Dgain and Dloss and candidate environmental drivers.

Data availability

The data used to run the analyses are available at https://doi.org/10.6084/m9.figshare.14748057. Source data are provided with this paper.

Code availability

The R codes used to run the analyses are available at https://doi.org/10.6084/m9.figshare.14748057.

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Acknowledgements

We thank D. O’Brien for the revision of an early version of the manuscript. S.M. and G.F.F. are funded by the European Research Council under the European Community’s Horizon 2020 Programme, grant agreement no. 772284 (‘IceCommunities—Reconstructing community dynamics and ecosystem functioning after glacial retreat’).

Author information

Authors and Affiliations

  1. Department of Environmental Science and Policy, University of Milan, Milan, Italy

    Silvio Marta, Raoul Manenti & Gentile Francesco Ficetola

  2. Institute of Atmospheric Sciences and Climate, ISAC-CNR, Italian National Research Council, Bologna, Italy

    Michele Brunetti

  3. Institute of Geosciences and Earth Resources, IGG-CNR, Italian National Research Council, Pisa, Italy

    Antonello Provenzale

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  1. Silvio Marta
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Contributions

S.M., G.F.F. and R.M. designed the study. M.B. and A.P. associated climatic information to each distribution record, while S.M. retrieved the distribution and trait data and performed the analyses. S.M. and G.F.F. led the writing with substantial contributions from all the other authors.

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Correspondence to Silvio Marta.

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Peer review information Nature Ecology & Evolution thanks Alistair Auffret and Marta Jarzyna for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Relationships between the rate of change of precipitation at slower, medium and faster changes of the human population density and taxonomic indices (βsim, βsne, Dgain, Dloss).

Relationships between taxonomic indices and the rate of change of precipitation (mm/year) at slower (−0.45), medium (0.72) and faster (1.82) changes of the human population density (cube-root transformed; (inhabitants/km2/year)1/3). In each plot, the thick red line represents the average predicted relationship on the link scale, while the grey lines represent 500 samples of the posterior distribution. a–c, turnover (βsim). d–f, nestedness (βsne). g–i, standardized gain (Dgain). j–l, standardized loss (Dloss).

Source data

Extended Data Fig. 2 Relationships between the rate of change of temperature with negative, stable and positive rate of changes of precipitation and functional indices (βsim, βsne, Dgain, Dloss).

Relationships between functional indices and the rate of change of temperature (°C/year) with negative (−10.06), stable (−1.96) and positive (5.4) rates of change in precipitation (mm/year). In each plot, the thick red line represents the average predicted relationship on the link scale, while the grey lines represent 500 samples of the posterior distribution. a–c, turnover (βsim). d–f, nestedness (βsne). g–i, standardized gain (Dgain). j–l, standardized loss (Dloss).

Source data

Supplementary information

Supplementary Information

Supplementary Table 1 and Note 1.

Reporting Summary

Supplementary Data 1

Trait dataset.

Source data

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Extended Data Fig. 1

Statistical source data.

Source Data Extended Data Fig. 2

Statistical source data.

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Marta, S., Brunetti, M., Manenti, R. et al. Climate and land-use changes drive biodiversity turnover in arthropod assemblages over 150 years. Nat Ecol Evol 5, 1291–1300 (2021). https://doi.org/10.1038/s41559-021-01513-0

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