Effective fisheries management requires reliable tools for assessing both population structure and abundance while reducing disturbance to fish and their habitats. Environmental DNA (eDNA) offers a non-invasive approach for aquatic monitoring and enables the detection of intraspecific genetic differentiation and abundance-related patterns. This thesis assessed whether genetic methods suitable for eDNA-based monitoring can support the study of population structure and abundance-related patterns in brown trout (Salmo trutta) in southern Swedish rivers. Tissue-derived mitochondrial DNA markers were used to evaluate genetic differentiation between brown trout from Rönne å and Mörrumsån, while eDNA samples from Nybroån collected at 8 sampling time points were used for a preliminary comparison between species-specific PCR amplification and cumulative fish-counter records from upstream migration during autumn. Four mitochondrial markers, ATP6, ND4, CYTB, and D-loop, were amplified, sequenced, edited, and analyzed using haplotype networks, haplotype and nucleotide diversity, pairwise FST, and AMOVA. As a result, the markers differed strongly in their resolution. ND4 provided the highest resolution for population structure and showed significant differentiation between Rönne å and Mörrumsån (FST = 0.361, P < 0.001), whereas ATP6 and D-loop showed low-frequency haplotypes and no significant differentiation. CYTB was monomorphic and therefore not informative for population structure. In the qualitative analysis of eDNA components, species-specific PCR amplification showed stronger and more consistent bands in December, especially on 04.12.2025 (time point 7) and 18.12.2025 (time point 8), which corresponded to the highest cumulative fish count from upstream. However, the bands at time point 8 were slightly less intense than those at time point 7, despite the higher cumulative fish count. This may be due to higher water velocity at time point 8, which could have transported or diluted upstream eDNA away from the sampling locations. These results suggest that species-specific eDNA signals may provide a useful basis for future quantitative monitoring of brown trout abundance and population-level differentiation, but further validation using qPCR or ddPCR is needed.