James E McKenna, Jr. is a Research Ecologist based in Cortland, NY.
Dr. McKenna is a Research Ecologist with the Tunison Laboratory of Aquatic Science in Cortland, NY. For the past 28 years, he has conducted research on Great Lakes ecosystems, including tributary watersheds and the St. Lawrence River. His research topics range from native fish population restoration to ecosystem function and threats evaluation. Much of his work focuses on applied ecology of fish communities in the Great Lakes Region to support natural resource manager decision-making. His work often involves development of new analytical tools and methods to address complex ecological questions about how biodiversity and ecosystem function and adaptability is maintained (or repairable) in the face of continuing human activities. The methods have been applied to simplify the complex relationships among more than 100 fish species and their habitats into salient interpretations of fish communities that managers may use to address conservation and restoration objectives for Great Lakes ecosystems. This includes characterization of the best potential of any aquatic habitat to support the various fish species and associated biodiversity. Recent research has revealed habitat conditions (both locally and globally) most influential to fish communities in the Great Lakes proper and identified the inherent suitability (or unsuitability) of each of the millions of 30-m habitat units within a Great Lake. The research demonstrates how the natural suitability of habitat conditions varies by species and is affected by anthropogenic disturbances, including climate change. One research project, supporting native American tribal interests, provides managers and scientists with a detailed understanding of biodiversity and fish communities in rivers and streams throughout a large region of the St. Lawrence River valley, highlighting the abundance and distributions of threatened and endangered species, and characterizing their habitats. Restoration research has included work with the thousands of Atlantic Salmon, Ciscos, and Bloaters raised at the Tunison laboratory to support reintroduction of these native species to historically occupied habitats, and has shown how native prey fish (e.g., Cisco and other Coregonine species) can be raised in hatcheries in large numbers, transported to a Great Lake, and released successfully. The work also demonstrates how to mark the fish and their tolerance for use of advance technology, like acoustic telemetry, to track their movement and survival after release into the wild. This research advances our ability to understand threats to fish populations and aquatic communities at scales from stream reaches and small open lake locations to entire watersheds and whole Great Lake basins, and supports cost-effective management decisions about Great Lakes fishes and restoration or conservation of their habitats.
Science and Products
Science pages by this scientist
Aquatic Native Species and Habitat Restoration: Restoring native freshwater fish populations
NorEaST: A Tool to Understand the Responses of Fish to Changes in Stream Temperature
Science and Products
- Science
Science pages by this scientist
Aquatic Native Species and Habitat Restoration: Restoring native freshwater fish populations
USGS is working to help restore Atlantic salmon, bloater and cisco populations in Lake Ontario and the St. Lawrence River as part of the Coregonid Restoration effort. These three key species of the native Lake Ontario fish community are extirpated (Atlantic salmon and bloater) or are at low levels of former abundance (cisco).NorEaST: A Tool to Understand the Responses of Fish to Changes in Stream Temperature
Climate change is expected to alter stream temperature and flow regimes over the coming decades, and in turn influence distributions of aquatic species in those freshwater ecosystems. To better anticipate these changes, there is a need to compile both short- and long-term stream temperature data for managers to gain an understanding of baseline conditions, historic trends, and future projections. - Data
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