Rapid monitoring of aquatic organisms, particularly endangered and invasive species, is essential for preserving the biodiversity in Earth’s water. Management and conservation of fish species, such as Salmo salar, Salmo trutta and Salvelinus alpinus, within these environments requires knowledge of distribution, traditionally gained through visual detection. These methods are expensive, labour intensive and can lead to habitat disruption and harm to the target species. Environmental DNA (eDNA) offers a solution to this, using non-invasive molecular techniques to detect DNA shed into the environment. Conventional eDNA approaches use PCR-based methodology for single-species detection. In this thesis, a qPCR assay was developed for S. salar detection. However, although sensitive and specific, PCR-based methods pose a logistical challenge for on-site monitoring due to the need for high temperatures and thermal cycling. To circumvent this, we developed an isothermal approach that couples Recombinase Polymerase Amplification to CRISPR-Cas12a detection as a route to a cost-effective biosensor device. This system harnesses the collateral cleavage activity of Cas12a, a ribonuclease guided by a specific CRISPR RNA. We show the applicability of this technique to three salmonid species, with the S. salar assay compared to qPCR as a detection/non-detection assay in samples from Ireland and Canada. To facilitate this RPA-CRISPR-Cas assay as an on-site detection tool, the method was adapted for visualisation on a custom portable fluorometer and via lateral flow. Both systems maintain the specificity and sensitivity of the original assay but enable simplified readouts without complex instrumentation. The assays and visualisation methods developed in this thesis were applied to samples from the Burrishoole Catchment, Co. Mayo, demonstrating their applicability to environmental monitoring. In summary, this thesis provides the first application of CRISPR-Cas diagnostics to eDNA monitoring, and further progresses the field towards field-based applications, by removing the need for complex instrumentation and allowing rapid species detection.