Contribution of temperature and nutrient loading to growth rate variation of three cyprinid fishes in a lowland river

Abstract

Scales collected during a maximum of seven fish population surveys over a 25-year period (1983-2008) in the River Wensum, a lowland river in Eastern England, enabled temporal analysis of the growth rates of roach Rutilus rutilus, dace Leuciscus leuciscus and chub Leuciscus cephalus. Across the study period, all species showed temporal variability in their growth patterns. Roach showed a significant temporal decrease in their growth, where rates recorded in surveys in 2005 and 2008 were significantly slower those recorded in surveys between 1983 and 1994. This change in growth rate was significantly associated with the implementation of phosphate stripping in the catchment's sewage treatment works that reduced nutrient inputs (specifically orthophosphate). Prior to the implementation, temperature patterns explained most of the annual growth variability; following implementation and a consequent shift to the less eutrophic conditions, this relationship was lost, with changes in annual phosphate loadings now explaining most of the annual growth variation. This suggests that the changes in roach growth rates were related to shifts in river productivity resulting from water quality improvements.

Disruption of the stress response in wastewater treatment works effluent-exposed three-spined sticklebacks persists after translocation to an unpolluted environment

“…This finding differs from previous studies which have reported a positive trend between WWTW effluent concentration and the size of resident fish (Pottinger et al 2013;Tetreault et al 2012) but is consistent with the results of a study in which the growth of sticklebacks downstream of a WWTW was improved following remediation of the effluent (Pottinger et al 2011). WWTW effluent contains nutrients likely to improve productivity of the downstream aquatic ecosystem and WWTW effluent discharges also tend to raise the water temperature in receiving waters (Brooks et al 2006;Gücker et al 2006), both of which are factors that have a positive effect on the growth of fish (Beardsley and Britton, 2012;Graham and Harrod 2009). However, WWTW effluent also contains chemicals with the potential to exert a negative effect on the growth of fish via direct effects on physiological or endocrine processes, or because the fish need to divert resources to coping with a toxicological challenge (Forbes and Calow 1998).…”

Spatial variability in the growth of invasive European barbel Barbus barbus in the River Severn basin, revealed using anglers as citizen scientists

“…Scales were measured for scale radius, distance to last annulus and distance between annulus 1 and 2, with these converted to length at the last annulus and length increment between age 1 and 2 years old by back-calculation (Dahl Lea method; Francis, 1990). Length at the last annulus enabled growth rates over the life time of the fish to be assessed, whilst the increment between age 1 and 2 years enabled assessment of juvenile growth rates (Beardsley and Britton, 2012). Differences in the lengths of the fish sampled by angling and electric fishing were tested using a generalised linear model (GLM), as these data were not normally distributed, with the significance of differences assessed by linearly independent pairwise comparisons with Bonferroni adjustment for multiple comparisons.…”

“…Firstly, analyses determined the mean standardized growth residuals for each reach according to lengths at the last annulus and length increment between age 1 and 2 years (Beardsley and Britton, 2012). Only one growth metric value per fish was used in each test to avoid pseudo-replication (Beardsley and Britton, 2012).…”

“…Firstly, analyses determined the mean standardized growth residuals for each reach according to lengths at the last annulus and length increment between age 1 and 2 years (Beardsley and Britton, 2012). Only one growth metric value per fish was used in each test to avoid pseudo-replication (Beardsley and Britton, 2012). For length at the last annulus, length at age data for all reaches and fish (age 1-15 only) were used in the log-log quadratic function of Vilizzi and Walker (1999) to determine the mean length at each age.…”

“…For length at the last annulus, length at age data for all reaches and fish (age 1-15 only) were used in the log-log quadratic function of Vilizzi and Walker (1999) to determine the mean length at each age. This enabled the standardized residual of each individual fish to be calculated (Beardsley and Britton, 2012), with these then tested between the four reaches using a generalized linear model. Outputs were the mean standardized residuals per reach and the significance of the difference between them according to linearly independent pairwise comparisons with Bonferroni adjustment for multiple comparisons.…”