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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Hejcman, M., Hejcmanová, P., Pavlů, V. & Beneš, J. Origin and history of grasslands in central Europe - a review. Grass Forage Sci. 68, 345–363 (2013).
Greening (European Commission, 2016); http://ec.europa.eu/agriculture/direct-support/greening/index_en.htm
Gossner, M. M. et al. Land-use intensification causes multitrophic homogenization of grassland communities. Nature 540, 266–269 (2016).
Allan, E. et al. Interannual variation in land-use intensity enhances grassland multidiversity. Proc. Natl Acad. Sci. USA 111, 308–313 (2014).
Hopkins, A. & Wilkins, R. J. Temperate grassland: key developments in the last century and future perspectives. J. Agr. Sci. 144, 503–523 (2006).
Kleijn, D. & Sutherland, W. J. How effective are European agri-environment schemes in conserving and promoting biodiversity? J. Appl. Ecol. 40, 947–969 (2003).
Veen, P., Jefferson, R., de Smidt, J. & van derStraaten, J. (eds) Grasslands in Europe of High Nature Value 320 (KNNV, 2009).
Phalan, B., Onial, M., Balmford, A. & Green, R. E. Reconciling food production and biodiversity conservation: land sharing and land sparing compared. Science 333, 1289–1291 (2011).
Hulme, M. F. et al. Conserving the birds of Uganda’s banana-coffee arc: land sparing and land sharing compared. PLoS ONE 8, e54597 (2013).
Kamp, J. et al. Agricultural development and the conservation of avian biodiversity on the Eurasian steppes: a comparison of land-sparing and land-sharing approaches. J. Appl. Ecol. 52, 1578–1587 (2015).
Green, R. E., Cornell, S. J., Scharlemann, J. P. & Balmford, A. Farming and the fate of wild nature. Science 307, 550–555 (2005).
Gabriel, D., Sait, S. M., Kunin, W. E., Benton, T. G. & Steffan-Dewenter, I. Food production vs. biodiversity: comparing organic and conventional agriculture. J. Appl. Ecol. 50, 355–364 (2013).
Lamb, A., Balmford, A., Green, R. E. & Phalan, B. To what extent could edge effects and habitat fragmentation diminish the potential benefits of land sparing? Biol. Conserv. 195, 264–271 (2016).
Butsic, V. & Kuemmerle, T. Using optimization methods to align food production and biodiversity conservation beyond land sharing and land sparing. Ecol. Appl. 25, 589–595 (2015).
Miettinen, K. Nonlinear Multiobjective Optimization (Springer, 1998).
Edwards, D. P. et al. Land-sharing versus land-sparing logging: reconciling timber extraction with biodiversity conservation. Glob. Change Biol. 20, 183–191 (2014).
Tscharntke, T. et al. Global food security, biodiversity conservation and the future of agricultural intensification. Biol. Conserv. 151, 53–59 (2012).
Fischer, J. et al. Land sparing versus land sharing: moving forward. Conserv. Lett. 7, 149–157 (2014).
Tilman, D., Cassman, K. G., Matson, P. A., Naylor, R. & Polasky, S. Agricultural sustainability and intensive production practices. Nature 418, 671–677 (2002).
Bennett, E. M. Changing the agriculture and environment conversation. Nat. Ecol. Evol. 1, 0018 (2017).
Dotta, G., Phalan, B., Silva, T. W., Green, R. & Balmford, A. Assessing strategies to reconcile agriculture and bird conservation in the temperate grasslands of South America. Conserv. Biol. 30, 618–627 (2016).
Bennett, J. R. et al. Balancing phylogenetic diversity and species numbers in conservation prioritization, using a case study of threatened species in New Zealand. Biol. Conserv. 174, 47–54 (2014).
Cadotte, M. W. & Jonathan Davies, T. Rarest of the rare: advances in combining evolutionary distinctiveness and scarcity to inform conservation at biogeographical scales. Divers. Distrib. 16, 376–385 (2010).
Simons, N. K. et al. Contrasting effects of grassland management modes on species-abundance distributions of multiple groups. Agr. Ecosyst. Environ. 237, 143–153 (2017).
Simons, N. K., Weisser, W. W. & Gossner, M. M. Multi-taxa approach shows consistent shifts in arthropod functional traits along grassland land-use intensity gradient. Ecology 97, 754–764 (2016).
Allan, E. et al. Land use intensification alters ecosystem multifunctionality via loss of biodiversity and changes to functional composition. Ecol. Lett. 18, 834–843 (2015).
Batáry, P. et al. Responses of grassland specialist and generalist beetles to management and landscape complexity. Divers. Distrib. 13, 196–202 (2007).
Ball, I. R., Possingham, H. P. & Watts, M. in Spatial Conservation Prioritisation: Quantitative Methods and Computational Tools (eds Moilanen, A., Wilson, K. A. & Possingham, H. P.) Ch. 14, 185–195 (Oxford Univ. Press, 2009).
Tscharntke, T., Klein, A. M., Kruess, A., Steffan-Dewenter, I. & Thies, C. Landscape perspectives on agricultural intensification and biodiversity - ecosystem service management. Ecol. Lett. 8, 857–874 (2005).
Fischer, M. et al. Implementing large-scale and long-term functional biodiversity research: the biodiversity exploratories. Basic Appl. Ecol. 11, 473–485 (2010).
Blüthgen, N. et al. A quantitative index of land-use intensity in grasslands: integrating mowing, grazing and fertilization. Basic Appl. Ecol. 13, 207–220 (2012).
Simons, N. K. et al. Resource-mediated indirect effects of grassland management on arthropod diversity. PLoS ONE 9, e107033 (2014).
Socher, S. A. et al. Direct and productivity-mediated indirect effects of fertilization, mowing and grazing on grassland species richness. J. Ecol. 100, 1391–1399 (2012).
Riehl, G. Ermittlung von Erträgen auf dem Grünland (Sächsisches Landesamt für Umwelt, Landwirtschaft und Geologie, 2001).
Mewes, M. Agrarökonomische Kostenberechnungen für Biodiversitätsschutzmaßnahmen Report No. 1436-140X (Helmholtz-Zentrum für Umweltforschung GmbH - UFZ, 2010).
R Core Team R: A Language and Environment for Statistical Computing v3.3.0 (R Foundation for Statistical Computing, 2016).
Bolker, B. & R Core Team Tools for General Maximum Likelihood Estimation Version 1.0.18 (2016).
Marler, R. T. & Arora, J. S. Survey of multi-objective optimization methods for engineering. Struct. Multidiscip. O. 26, 369–395 (2004).
Mersmann, O. mco: Multiple Criteria Optimization Algorithms and Related Functions (2014).
Deb, K., Pratap, A. & Agarwal, S. A fast and elitist multiobjective genetic algorithm: NSGAII. IEEE T. Evolut. Comput. 6, 182–197 (2002).
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).
The authors declare no competing financial interests.
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Electronic supplementary material
One Supplementary Table, 12 Supplementary Figures, 3 Supplementary Methods and three sets of additional Supplementary Figures
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).
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.
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.
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