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Agricultural intensification without biodiversity loss is possible in grassland landscapes

Nature Ecology & Evolution volume 1, pages 1136–1145 (2017)Cite this article

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Abstract

Grassland biodiversity in managed landscapes is threatened by land-use intensification, but is also dependent on low-intensity management. Solutions that allow for both agricultural production and species conservation may be realized either on individual grasslands, by adjusting management intensity, or at the landscape level, when grasslands are managed at different intensities. Here we use a dataset of more than 1,000 arthropod species collected in more than 100 grasslands along gradients of productivity, to assess the reaction of individual species to changes in productivity. We defined a range of land-use strategies and evaluated their effects on overall production and on species abundances. We show that conservation of arthropods can be improved without reducing overall production. We also find that production can be increased without jeopardizing conservation. Conservation and production could, however, not be maximized simultaneously at the landscape level, emphasizing that management goals need to be clearly defined.

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Figure 1: Selection of optimal land-use strategies based on abundance–productivity curves.
Figure 2: Optimal strategies across the range of possible landscape-level production targets.
Figure 3: Productivity in grassland biomass on each grassland assigned by the optimization algorithms.
Figure 4: Rare species that reach their critical productivity for vulnerability or extinction at different levels of productivity.

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Acknowledgements

We thank T. Lewinsohn for his comments on an earlier draft of this publication. We thank S. Boch, J. Müller, E. Pašalić and S. A. Socher for conducting the plant biomass sampling and for providing the data online. We thank T. Husen for helpful comments on the implementation of the optimization algorithms. We also thank the managers of the three exploratories, K. Wels, S. Renner, S. Gockel, K. Wiesner, A. Hemp and M. Gorke for their work in maintaining the plot and project infrastructure; S. Pfeiffer, M. Gleisberg and C. Fischer for giving support through the central office, as well as J. Nieschulze and M. Owonibi for managing the central database. We also thank M. Fischer, E. Linsenmair, D. Hessenmöller, D. Prati, I. Schöning, F. Buscot, E.-D. Schulze and the late E. Kalko for their role in setting up the Biodiversity Exploratories project. The work was funded by the DFG Priority Program 1374 ‘Infrastructure-Biodiversity-Exploratories’ (DFG-WE 3081/21-1.). Fieldwork permits were issued by the responsible state environmental offices of Baden-Württemberg, Thüringen and Brandenburg (according to § 72 BbgNatSchG).

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Authors and Affiliations

  1. Terrestrial Ecology Research Group, Department for Ecology and Ecosystem Management, School of Life Sciences Weihenstephan, Technical University of Munich, Hans-Carl-von-Carlowitz-Platz 2, 85354, Freising, Germany

    Nadja K. Simons & Wolfgang W. Weisser

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Contributions

N.K.S. and W.W.W. conceived the idea for the manuscript and defined the final outline. N.K.S. analysed the data and wrote the first manuscript draft. W.W.W. commented on all manuscript versions.

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Correspondence to Nadja K. Simons.

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The authors declare no competing financial interests.

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Supplementary Information

One Supplementary Table, 12 Supplementary Figures, 3 Supplementary Methods and three sets of additional Supplementary Figures

Supplementary Data 1

Average productivity on the sampled grasslands over the years 2006–2012. Grasslands are located in three regions in Germany, indicated by the first three letters of the PlotID: AEG indicates grasslands located in the Schwäbische Alb, HEG indicates grasslands located in the Hainich-Dün, SEG indicates grasslands located in the Schorfheide Chorin. The PlotIDs correspond to the PlotIDs given in the other data files used in the current study (see ‘Data availability’). Further publicly available data from the study regions and grasslands can be found in the data repository of the Biodiversity Exploratories (https://www.bexis.uni-jena.de/PublicData/PublicData.aspx).

Supplementary Data 2

Results from the selected best model for abundance-productivity curves of each common arthropod species sampled in the Schwäbische Alb. SpeciesID indicates scientific species name, Best_model indicates selected best model based on the residual deviances of all tested models. Res_Dev gives the residual deviance. _Est indicates the parameter estimate, _SE indicates the parameters’ standard error: _z indicates the value of the z-statistic for each parameter and _p indicates the probability level from the z-statistic for each parameter. Missing values (because a parameter is not used in the respective model or because statistical tests could not be performed) are indicated by NA.

Supplementary Data 3

Results from the selected best model for abundance-productivity curves of each common arthropod species sampled in Hainich-Dün. SpeciesID indicates scientific species name, Best_model indicates selected best model based on the residual deviances of all tested models. Res_Dev gives the residual deviance. _Est indicates the parameter estimate, _SE indicates the parameters’ standard error: _z indicates the value of the z-statistic for each parameter and _p indicates the probability level from the z-statistic for each parameter. Missing values (because a parameter is not used in the respective model or because statistical tests could not be performed) are indicated by NA.

Supplementary Data 4

Results from the selected best model for abundance-productivity curves of each common arthropod species sampled in Schorfheide-Chorin. SpeciesID indicates scientific species name, Best_model indicates selected best model based on the residual deviances of all tested models. Res_Dev gives the residual deviance. _Est indicates the parameter estimate, _SE indicates the parameters’ standard error: _z indicates the value of the z-statistic for each parameter and _p indicates the probability level from the z-statistic for each parameter. Missing values (because a parameter is not used in the respective model or because statistical tests could not be performed) are indicated by NA.

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Simons, N.K., Weisser, W.W. Agricultural intensification without biodiversity loss is possible in grassland landscapes. Nat Ecol Evol 1, 1136–1145 (2017). https://doi.org/10.1038/s41559-017-0227-2

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