Towards more predictive and interdisciplinary climate change ecosystem experiments
F. Rineau, R. Malina, N. Beenaerts, N. Arnauts, R.D. Bardgett, M.P. Berg, A. Boerema, L. Bruckers, J. Clerinx, E.L. Davin, H.J. De Boeck, T. De Dobbelaer, M. Dondini, F. De Laender, J. Ellers, O. Franken, L. Gilbert, L. Gudmundsson, I.A. Janssens, D. Johnson, S. Lizin, B. Longdoz, P. Meire, D. Meremans, A. Milbau, M. Moretti, I. Nijs, A. Nobel, I.S. Pop, T. Puetz, W. Reyns, J. Roy, J. Schuetz, S.I. Seneviratne, P. Smith, F. Solmi, J. Staes, W. Thiery, S. Thijs, I. Vanderkelen, W. Van Landuyt, E. Verbruggen, N. Witters, J. Zscheischler, J. VangronsveldJanuary, 2019
© 2019, Springer Nature Limited. Despite great advances, experiments concerning the response of ecosystems to climate change still face considerable challenges, including the high complexity of climate change in terms of environmental variables, constraints in the number and amplitude of climate treatment levels, and the limited scope of responses and interactions covered. Drawing on the expertise of researchers from a variety of disciplines, this Perspective outlines how computational and technological advances can help in designing experiments that can contribute to overcoming these challenges, and also outlines a first application of such an experimental design.
Nature Climate Change