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Fraser B. Neave

Publications and source records attributed to Fraser B. Neave.

2 recordsLinked to original sources

The offshore benthic fish community

Lake Ontario’s offshore benthic fish community includes primarily slimy sculpin, lake whitefish, rainbow smelt, lake trout, burbot, and sea lamprey. Of these, lake trout have been the focus of an international restoration effort for more than three decades (Elrod et al. 1995; Lantry and Lantry 2008). The deepwater sculpin and three species of deepwater ciscoes (Coregonus spp.) that were historically important in the offshore benthic zone became rare or were extirpated by the 1960s (Christie 1973; Owens et al. 2003; Lantry et al. 2007b; Roth et al. 2013). Ecosystem changes continue to influence the offshore benthic fish community, including the effects of dreissenid mussels, the near disappearance of burrowing amphipods (Diporeia spp.) (Dermott et al. 2005; Watkins et al. 2007), and the increased abundance and expanded geographic distribution of round goby (see Nearshore Fish Community chapter) (Lantry et al. 2007b). The fish-community objectives for the offshore benthic fish community, as described by Stewart et al. (1999), are: The offshore benthic fish community will be composed of self-sustaining native fishes characterized by lake trout as the top predator, a population expansion of lake whitefish from northeastern waters to other areas of the lake, and rehabilitated native prey fishes.

New York

Relative contributions of sampling effort, measuring, and weighing to precision of larval sea lamprey biomass estimates

We developed two weight-length models from 231 populations of larval sea lampreys (Petromyzon marinus) collected from tributaries of the Great Lakes: Lake Ontario (21), Lake Erie (6), Lake Huron (67), Lake Michigan (76), and Lake Superior (61). Both models were mixed models, which used population as a random effect and additional environmental factors as fixed effects. We resampled weights and lengths 1,000 times from data collected in each of 14 other populations not used to develop the models, obtaining a weight and length distribution from reach resampling. To test model performance, we applied the two weight-length models to the resampled length distributions and calculated the predicted mean weights. We also calculated the observed mean weight for each resampling and for each of the original 14 data sets. When the average of predicted means was compared to means from the original data in each stream, inclusion of environmental factors did not consistently improve the performance of the weight-length model. We estimated the variance associated with measures of abundance and mean weight for each of the 14 selected populations and determined that a conservative estimate of the proportional contribution to variance associated with estimating abundance accounted for 32% to 95% of the variance (mean = 66%). Variability in the biomass estimate appears more affected by variability in estimating abundance than in converting length to weight. Hence, efforts to improve the precision of biomass estimates would be aided most by reducing the variability associated with estimating abundance.

Journal of Great Lakes Research