The FLUFLUX team has achieved empirical data collections in 5 different river networks: The Ybbs and Kamp in Austria, the Mara in Kenya, the Vjosa in Albania and the Thur in Switzerland. The Vjosa was sampled three times, once in spring at high flow and twice in fall at baseflow conditions. Work in the Ybbs also included two field campaigns. In all cases we either established new collaborations with local researchers or strengthened existing ones. The focus of data collection shifted slightly between river networks. Notably, we included biodiversity of primary producers and measures of functional diversity of this important functional group. One campaign in the Ybbs focused on primary producers exclusively. The decision to include primary producers within the context of FLUFLUX was prompted by (i) its importance for riverine carbon cycling, and (ii) the perceived better chance for testing a core hypothesis of FLUFLUX: the translation of network-scale patterns of biodiversity and resources to ecosystem functioning. The team collected data on dissolved organic matter (OM) diversity and microbial biodiversity on at least 50 sites in all rivers. Further data collected include: OM-related extracellular enzyme activities, ecosystem-scale metabolism, carbon dioxide and methane concentrations and emissions. In the rivers Mara and Vjosa, we further collected data on invertebrate communities and food webs with the help of collaboration partners. In the rivers Thur, Ybbs and Kamp we ran river network-scale leaf litter degradation experiments, including investigation of invertebrate biodiversity colonizing the leaf litter bags. In concert with these measurements, we also progressed on GIS-based descriptions of the various river networks, including analyses of geology and landcover.
In parallel to this observational work, we developed a meta-ecosystem model for river networks. This model has meanwhile been made available as a R-package and is capable of modelling network-scale biodiversity, resource distribution and ecosystem functioning as the result of the interaction between biodiversity and available resources. The model is in fact blending a metacommunity model with a biogeochemical transport-reaction model. As such it allows simulation of river meta-ecosystem functioning based on mechanistic principles involving species and resources with particular traits. Besides this mechanistic model, we also advanced on the network-scale statistical analysis of empirical data. Mostly using a Bayesian framework we build models explaining the distribution of microbes, invertebrates and fish, and further develop those to analyze ecosystem functions. In addition to this modelling work, we developed a prototype for a laboratory meta-ecosystem. Work on this experimental approach has been slower than anticipated and could not be brought to the intended level that could support the planned series of hypothesis tests about meta-ecosystem functioning.
