WS-01 Characterization of natural DOM-techniques and solutions
Processing and analyzing ultrahigh-resolution mass spectrometry data of dissolved organic matter: Statistical challenges and solutions  (Invited)
Julian Merder* , Carnegie Institution for Science

Dissolved organic matter (DOM) represents one of the largest active carbon pools on Earth, which is comparable to all the atmospheric CO2. DOM is a mixture of thousands of different substances, which makes its characterization challenging. Ultrahigh-resolution mass spectrometry is one of the most powerful tools in this context and has established itself as the state-of-the-art analytical method in geochemistry. Due to these improvements the follow up data processing and statistical analysis represent now a new bottlenecks for the interpretation of DOM molecular data sets. A proper and unified statistical analysis becomes even more important in times of the ever growing number of DOM data sets and to allow proper ways to compare those. Here, I give an overview about the special statistical properties of DOM data and the statistical challenges arising from it. I present an open access tool to process mass spectrometry data and show some classical but also novel ways to analyse and compare DOM samples over space and time and to link them to environmental and microbial data.