AUTHORS: Evan Spencer, GRA South Dakota State University, Dr. Christopher Cheek, Assistant Professor South Dakota State University
ABSTRACT: Stream channel fragmentation constrains the movement of stream fishes, thereby reducing access to critical habitats. Stream-road crossings are prevalent throughout the United States and have the potential to fragment aquatic ecosystems. Tube culverts, where streams pass under the road through metal pipes, are particularly concerning for stream connectivity. Undersized, aging, or inappropriately installed culverts can develop vertical drops at the outflow due to high velocities and stream bed scouring. This condition, known as perching, can function as a barrier preventing the upstream movement of fishes. Due to the prevalence of culverts in stream networks, novel solutions are needed that rapidly address fish passage at perched culverts. In this study, we assessed a low-cost Denil-type fish ladder designed to integrate with tube culverts and mitigate stream fragmentation caused by tube culverts. Specific objectives are to (1) quantify the impact road crossings have on the movement of small-bodied fishes, (2) demonstrate the long-term and short-term efficacy of experimental fish ladders in facilitating fish passage through tube culverts, (3) determine passage rates among different swimming guilds of stream fishes in Eastern South Dakota. For this, eight stream road crossings we selected in the Big Sioux, Vermillion, and Minnesota River watersheds. A before-after-control impact design was adopted to evaluate the effectiveness of fish ladders on the movement of fishes through tube culverts. In the summer of 2023-2024, over 6000 small-bodied stream fishes comprised of 22 species were captured and implanted with Biomark 8mm PIT (passive integrated transponder) tags. Capture-recapture data was collected using PIT telemetry. In the Spring-Summer 2024, experimental fish ladders were installed at perched tube culverts and fish passage was evaluated using capture-recapture methodologies to model multi-state detection, survival, and transition probability.
