**The title, authors, and abstract for this completion report are provided below. For a copy of the completion report, please contact the GLFC via e-mail or via telephone at 734-662-3209**

Cisco Recruitment Dynamics in Lake Superior during 1978–2007

Benjamin J. Rook², Michael J. Hansen³, Owen T. Gorman⁴

² Cramer Fish Sciences

636 Hedburg Way #22

Oakdale, CA 95361

(209)847-7786

rook@fishsciences.net

³ University of Wisconsin – Stevens Point

College of Natural Resources

800 Reserve Street

Stevens Point, WI 54481

(715)346-3420

mhansen@uwsp.edu

⁴ U.S. Geological Survey

Great Lakes Science Center

Lake Superior Biological Station

2800 Lake Shore Drive East

Ashland, WI 54806

(715)682-6163

owen_gorman@usgs.gov

December 2010

ABSTRACT:

The cisco (Coregonus artedi) was once the most abundant fish species in the Great Lakes, but currently, cisco populations are greatly reduced, and management agencies are attempting to restore the species throughout the basin. First, to increase understanding of the spatial scale at which density-independent and density-dependent factors regulate cisco recruitment dynamics in the Great Lakes, we used a Ricker stock recruitment model to identify and quantify the appropriate spatial scale for modeling age-1 cisco recruitment dynamics in Lake Superior. We found that recruitment variation of cisco in Lake Superior was best described by an 8-parameter regional model with separate stock-recruitment relationships for western, southern, eastern, and northern stocks. The special scale for modeling was ~260 km (range = 230–290 km). We also found that the density-independent recruitment rate and the rate of compensatory density-dependence varied among regions at different rates. The density-independent recruitment rate varied 2-fold among regions (range = 2.4–4.9 age-1 recruits/spawner) and the rate of compensatory density-dependence varied 21-fold among regions (range = -0.2 to -3.4 spawners^-1). Finally, we found that peak recruitment and the spawning stock size that produced peak recruitment varied among regions. Peak recruitment varied 10-fold among regions (range = 0.5–5.4 age-1 recruits/ha) and the spawning stock size that produced peak recruitment varied 21-fold among regions (range = 0.3–6.1 spawners/ha). Second, to increase understanding of biotic and abiotic factors regulating cisco recruitment dynamics in the Great Lakes, we used a generalized version of the Ricker stock-recruitment model to identify and quantify the effects of biotic and abiotic factors on age-1 cisco recruitment dynamics within four different regions of Lake Superior. We found that recruitment variation of cisco in Lake Superior was correlated to adult spawning stock size in all four regions, the density of juvenile cisco during the year prior to cisco hatching in three of four regions, average April air temperature during spring when ciscoes were 11–12 months of age in three of four regions, average April wind speed during spring when ciscoes were hatching in two of four regions, and the biomass of rainbow smelt (Osmerus mordax) during the year of cisco hatching in one of four regions. Our findings support the hypothesis that different biotic and abiotic factors regulate cisco recruitment dynamics in Lake Superior on a regional scale, and suggest that fishery managers throughout Lake Superior and the entire Great Lakes basin should address cisco restoration and management efforts on a regional scale in each lake.