Integrating distributed experimental and observational data to outline future experimental approaches: Experiences from CLIMMANI
Climate change involves changes in all key drivers for ecosystem functioning in terrestrial ecosystems, but the changes in atmospheric CO2, temperature and water availability exhibit very different patterns of change. These differences in driver patterns should ideally be reflected in the scenarios applied in climate change experiments. However, this is most often not the case, and the general approach to field scale experimentation may therefore not provide the complete picture of ecosystem responses to climate change and models therefore not being well informed. In particular the consistent finding among climate predictions of an increase in the variability of precipitation patterns with intensified extremity has not been well covered by the treatments applied in the precipitation experiments carried out globally (Beier et al., 2011). Many experimental studies have for example addressed the effects of intensified and elongated droughts by application of “extreme” scenarios, but most often only as a “conservative extreme”, while rarely experimental droughts have been so severe that they exceeded thresholds, even if this would be relevant for the long term ecosystem responses. This is because application of very severe treatments leading to threshold exceedance and severe disturbances are typically unwanted in experiments and/or may be deliberately avoided, as they will compromise the original experimental set-up and the long term perspective of the experiment. Consequently, our understanding of the ecological impacts of very extreme future events is often limited (Kreyling and Beier, 2013).
There is a need for a new generation of ecosystem experiments, which addresses exceedance of ecological thresholds to improve our understanding and inform models for better future predictions of the potential impacts. At the same time the complexity and likely appearance of these scenarios makes it impossible and possibly even irrelevant to aim for “likely” or realistic scenarios, and experiments therefore need to be designed in a new way involving gradiental approaches and combined with field scale observations. CLIMMANI is a European network of climate change experiments, data and models bringing experiences in this field together and outlining novel approaches.