Measurements of salmonid population performance in relation to habitat in eastern Newfoundland streams

Abstract

The density, biomass and estimated production of brook trout Salvelinus fontinalis and Atlantic salmon Salmo salar were related to habitat factors in streams of Terra Nova National Park, Newfoundland, Canada. Fish communities at 29 sites (18 brooks; 15 watersheds) were sampled in the summer of 2002, 2003 and 2005. Salmonid density, biomass per unit area and production (derived from biomass and fish size using allometric P:B relationships) were compared with site habitat characteristics (wetted width, lactustrine habitat, per cent riffle habitat, canopy coverage and stream gradient), using an interactive stepwise multiple linear regression. Salmonid biomass (mean: 2Á87 g m À2 ; range: 0Á33-10Á88 g m À2 ) and estimated production (mean: 3Á05 g m À2 year À1 ; range: 0Á32-10Á98 g m À2 year À1 ) within the study area varied by an order of magnitude, however, habitat variables accounted for much of this variation. Specifically, wetted width and lacustrine area of the tributary played important roles in explaining density, biomass and production. Wetted width was important for all measurements of brook trout and total salmonids while lacustrine area was important for all measurements of Atlantic salmon and played a lesser role in total salmonid biomass. Other factors such as the percentage of riffle habitat, site gradient and canopy coverage provided modest improvements to the fit of some relationships. When models using the same environmental factors were compared, those using production estimates derived from allometric P:B equations in the literature provided improved predictive capability than did those from direct density and biomass estimates. It is proposed that allometric P:B relationships have utility in improving comparisons of stream fish communities, particularly in studies with insufficient resources to measure production directly.

Barriers to fish passage and barriers to fish passage assessments: the impact of assessment methods and assumptions on barrier identification and quantification of watershed connectivity

“…The diadromous length-frequency distribution and relative species abundance were derived from two fish counting fences of similar size to Big Brook (Minchins Brook, Cote (2005); Wings Brook, Potter (1989)) during the migration period. Potamodromous fish communities were characterized based on electrofishing in streams (Cote 2007) and fyke netting in lakes (Cote 2005;Cote et al 2011) throughout TNNP. Population abundance for brook trout and Atlantic salmon was calculated using available habitat in the Big Brook system and existing habitat models (Cote 2007;Cote et al 2011).…”

“…Potamodromous fish communities were characterized based on electrofishing in streams (Cote 2007) and fyke netting in lakes (Cote 2005;Cote et al 2011) throughout TNNP. Population abundance for brook trout and Atlantic salmon was calculated using available habitat in the Big Brook system and existing habitat models (Cote 2007;Cote et al 2011). Finally, the integrated abundance-weighted watershed connectivity value for Big Brook was calculated using Eq.…”

Production of juvenile salmonids in small Norwegian streams is affected by agricultural land use

“…The success of organisms depends on their ability to gain and retain energy (Lindeman, 1942). Consequently, production represents the quantitative performance of a population, a proxy for its ability to withstand exploitation and environmental disturbance (Cote, 2007) and an indicator of its role in energy flow in the ecosystem (Benke & Huryn, 2010). These are the reasons why production estimates are important in the management of aquatic resources (e.g.…”

Monitoring and estimating scale-dependent hierarchical relationships between Sicyopterus japonicus density and stream habitat features in different seasons in northern Taiwan

“…Above observations suggest that large-scale fluvial dynamics could benefit determination the brook trout density at the reach scale. Moreover, it has been found that stream width is the most accurate predictor or most influential variable of stream fish abundance (Kozel et al 1989;Knapp et al 1998;Dunham and Rieman 1999;Rosenfeld et al 2000;Inoue and Nunokawa 2002;Inoue and Miyayoshi 2006;Mesquita et al 2006;Cote 2007). Kozel et al (1989) and Knapp et al (1998) also found that stream fish habitat factors are related to stream width, including correlations with width-depth ratios.…”