Meiofauna are a diverse group of invertebrate organisms that live in aquatic sediments. Their community composition is a valuable tool for ecosystem assessment because they exhibit rapid population turnover and variable sensitivity to local conditions. Despite their growing use in ecosystem monitoring programs, little is known about their community along Long Island Sound, nor are any researchers maintaining long-term datasets to observe changes in their community. Our proposed research program is the first step in addressing this gap, as its primary goal is to investigate the use of meiofauna in monitoring programs, and to develop long-term datasets for Long Island Sound. Here, we plan to establish methodologies for meiofauna assessment along a disturbed shoreline (i.e., Seaside Park; Bridgeport, CT). We aim to determine if visual identifications to the level of phyla are sufficient to investigate community composition, or if genetic identifications to lower taxonomic levels are necessary. Visual identifications are inexpensive, but laborious; whereas genetic identifications are expensive, but less laborious and better able to identify organisms. We will use both identification methods to calculate community metrics (e.g., diversity) and comparisons will be submitted to an international peer-reviewed journal. These results will help to generate an analysis pipeline that will answer questions associated with long term goals and provide opportunity for undergraduate engagement. Thus, this project is tantamount to developing a meiofauna research program that integrates ecology and genetics, and which will create a springboard for our future investigations as tenure-track faculty and for our undergraduate students.