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Thousand Islands Biological Station
Northern Pike

Population genetics

A microsatellite genomic DNA analysis, a tagging study, and angler recapture information were used to assess the level of reproductive isolation and test the hypothesis of natal-site fidelity as a northern pike (Esox lucius) spawning strategy in the Thousand Islands Region of the St. Lawrence River (Bosworth and Farrell 2006). A genetic analysis using six polymorphic microsatellite loci resolved significant differences (P < 0.05) in allelic frequency among spawning populations separated by less than five river kilometers. Angler recaptures of tagged fish indicated that northern pike did not disperse widely, as 72% were recaptured less than 2.5 km from their natal site. Results support the idea that natal fidelity is operating in certain sites and has important implications for management of stocks.

Northern pike and muskellunge spawning ecology

Reproductive success of two sympatric esocids in a shared spawning and nursery bay was compared based on naturally spawned egg (embryo) and age-0 abundance estimates and distribution (Farrell 2001).  Northern pike have declined dramatically over the 20th century.  Historically, northern pike were noted to commence spawning runs soon after ice-out in shallow flooded areas.  In the present study more than 87% of estimated northern pike spawning in 1994, and 97% in 1995, occurred in offshore, deep-water habitats (2-5 m), while muskellunge (Esox masquinongy)  spawned primarily in shallow habitats.  The deepwater spawning trend resulted in a temporal delay in spawning that is hypothesized to be related to habitat loss in shallow nearshore and tributary areas due to water level regulation.  A detailed simulation model of the process indicated poor survival among deep and late spawned fish, and suggested this pattern represents an ecological sink for recruitment (Farrell et al. 2006).

Factors affecting year class formation

Variables associated with year-class formation in upper St. Lawrence River northern pike were examined to better understand recent declines in populations (Smith et al. 2007).  A 21-year (1977-1997) year-class strength index (YCSI) was related to environmental variables with three complementary statistical approaches. Year class strength exceeded the 21-year mean in only two of the last ten years.  Late summer water levels, mid summer water temperatures, duration of ice cover over the previous winter, and adult yellow perch abundance explained 84% of the variation associated with YCSI using multiple regression.  Year class formation processes had mixed responses to spring water levels supporting recent evidence indicating loss and reduced access to emergent marsh spawning habitat.  Sensitivity of northern pike to water levels highlights the strong influence hydrologic regulation has on their population health.

Predicting effects of water level regulation plans on northern pike recruitment

A spatially-explicit model of young-of-the-year northern pike production was used to provide a water levels performance indicator for proposed IJC regulation plans.  The model was developed from extensive TIBS data collection in the St. Lawrence River as well as experiment trials for bioenergetics and egg larval development completed in the wet lab.  Because the early life history of northern pike is wetland dependent, the simulations provided a sensitive process based indicator for IJC to judge water level plan effects on this important species.  Digital elevation models (DEMs) were developed for many of our study sites including the water controlled treatment and reference sites used by spawning northern pike.  The DEMs coupled with predictions of vegetation change depict how water level fluctuations interacted with habitat characteristics (e.g., vegetation and water temperature) based on field data derived logistic models of the probability of egg deposition.  The model was validated using long-term index data and provides simulation over 101 years for ten proposed regulation plans.  IJC is using the model along with other TIBS data in an Integration Ecosystem Response Model as part of a Shared Vision model that predicts water level regulation impacts for Lake Ontario and the St. Lawrence River downstream to Quebec City, Canada.