The roles of dissolved organic matter (DOM) in microbial processes and nutrient cycles depend on its composition, which requires detailed measurements and analyses. We introduce a package for R, called staRdom (“spectroscopic analysis of DOM in R”), to analyze DOM spectroscopic data (absorbance and fluorescence), which is key to deliver fast insight into DOM composition of many samples. staRdom provides functions that standardize data preparation and analysis of spectroscopic data and are inspired by practical work. The user can perform blank subtraction, dilution correction, Raman normalization, scatter removal and interpolation, and fluorescence normalization. The software performs parallel factor analysis (PARAFAC) of excitation–emission matrices (EEMs), including peak picking of EEMs, and calculates fluorescence indices, absorbance indices, and absorbance slope indices from EEMs and absorbance spectra. A comparison between PARAFAC solutions by staRdom in R compared with drEEM in MATLAB showed nearly identical solutions for most datasets, although different convergence criteria are needed to obtain similar results and interpolation of missing data is important when working with staRdom. In conclusion, staRdom offers the opportunity for standardized multivariate decomposition of spectroscopic data without requiring software licensing fees and presuming only basic R knowledge.

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This work addresses multiple human stressors and their impacts on fish assemblages of the Drava and Mura rivers in southern Austria. The impacts of single and multiple human stressors on riverine fish assemblages in these basins were disentangled, based on an extensive dataset. Stressor configuration, i.e. various metrics of multiple stressors belonging to stressor groups hydrology, morphology, connectivity and water quality were investigated for the first time at river basin scale in Austria. As biological response variables, the Fish Index Austria (FIA) and its related single as well as the WFD biological- and total state were investigated. Stressor-response analysis shows divergent results, but a general trend of decreasing ecological integrity with increasing number of stressors and maximum stressor is observed. Fish metrics based on age structure, fish region index and biological status responded best to single stressors and/or their combinations. The knowledge gained in this work provides a basis for advanced investigations in Alpine river basins and beyond, supports WFD implementation and helps prioritizing further actions towards multi-stressor restoration- and management.