STRESSFLEA develops and uses genomics tools to unravel patterns and mechanisms of adaptation to anthropogenic and natural stressors in natural populations, using the water flea Daphnia magna as a model system. Daphnia is a key model organism in ecology, evolutionary biology and ecotoxicology, and rapidly develops to become a leading model invertebrate in ecological genomics. Daphnia has clear assets as an ecogenomic model because of its ecological importance and life cycle features (short generation time, clonal lineages, layered dormant egg banks). STRESSFLEA aims to (1) obtain insight into the genomic underpinning of genetic adaptation to specific stressors (predation, parasitism, habitat unpredictability); (2) identify gene function by linking gene expression to trait values; (3) obtain insight into the genomics of adaptation to multiple stressors; and (4) reconstruct evolutionary processes over an extended time axis through the use of genomic markers and candidate genes in layered egg banks. STRESSFLEA brings together the key European research groups developing genomic resources for studying responses to stressors in natural Daphnia populations (supplemented with a pivotal research group from the USA), and combines transcriptome analysis, targeted genome scans, QTL analysis and gene mapping, microarrays, proteomics and methylome analysis to identify candidate loci and associated SNP markers, analyse gene function, and apply this knowledge to reconstruct evolutionary dynamics in a paleogenomics approach and analyse the dynamics and signature of local adaptation. The legacy of STRESSFLEA will include firm insight into the genomic underpinning of local adaptation to single and multiple stressors, insight into the dynamics of micro-evolutionary adaptation over extended timescales, a strongly elaborated genomics and transcriptomics toolbox for ecologic genomics using the model system Daphnia, and a firmly established network of European research groups that collaborate on ecological and functional genomics of natural populations, using Daphnia as a model.