ScaleX is a collaborative measurement campaign, collocated with a long-term environmental observatory of the German Terrestrial Environmental Observatories (TERENO) network in the mountainous terrain of the Bavarian Prealps, Germany. The aims of both TERENO and ScaleX include the measurement and modeling of land surface–atmosphere interactions of energy, water, and greenhouse gases. ScaleX is motivated by the recognition that long-term intensive observational research over years or decades must be based on well-proven, mostly automated measurement systems, concentrated in a small number of locations. In contrast, short-term intensive campaigns offer the opportunity to assess spatial distributions and gradients by concentrated instrument deployments, and by mobile sensors (ground and/or airborne) to obtain transects and three-dimensional patterns of atmospheric, surface, or soil variables and processes. Moreover, intensive campaigns are ideal proving grounds for innovative instruments, methods, and techniques to measure quantities that cannot (yet) be automated or deployed over long time periods. ScaleX is distinctive in its design, which combines the benefits of a long-term environmental-monitoring approach (TERENO) with the versatility and innovative power of a series of intensive campaigns, to bridge across a wide span of spatial and temporal scales. This contribution presents the concept and first data products of ScaleX-2015, which occurred in June–July 2015. The second installment of ScaleX took place in summer 2016 and periodic further ScaleX campaigns are planned throughout the lifetime of TERENO. This paper calls for collaboration in future ScaleX campaigns or to use our data in modelling studies. It is also an invitation to emulate the ScaleX concept at other long-term observatories.

An improved regional assessment of the productivity of grasslands depends on comprehensive knowledge of the interactions between climatic drivers, vegetation properties and human activity. Managed grasslands in Europe display highly dynamic responses, which contribute to the challenge in making representative model simulations. considered individually, the relationship between GEP and above-ground biomass, leaf area and vegetation height appeared to follow unified patterns for all sites. In addition, our study highlights a substantial potential for systematic error based on the techniques used to quantify vegetation properties and a mitigating approach was evaluated that includes continuous automated observations of vegetation height. These outcomes can serve as a reference for modelling studies on the seasonal allocation of carbon and vegetation properties in managed humid temperate grassland systems.

Hardwood floodplain (HF) forests can store a considerable amount of carbon (C), and floodplains may be good candidates for reforestation to provide natural C sinks. In this study, we use nondestructive inventory methods to estimate the C stocks of different tree species and C pools within HF forests of varying age and structure and located at sites differing in hydrological conditions (low and high active floodplain, seepage water zone, tributaries). The study was carried out along the Elbe river (Germany). Average C stocks for young plantations in the active floodplain were significantly lower (50.2 ± 10.8 SE Mg ha−1) than those of old dense (140.6 ± 11.6 SE Mg ha−1) and old sparse forests (180.4 ± 26.6 SE Mg ha−1) with comparable hydrological conditions. C stocks of old dense forests did not significantly vary from old sparse forests. Additionally, C stocks of old forests did not significantly vary according to hydrological conditions. The highest amount of C was stored in Quercus robur for all hydrological conditions. Ulmus laevis stored the second-highest amount of C on the active floodplain. We conclude that sparse and dense forests as well as forests under different hydrological conditions provide the same C storage function.

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