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Factors Influencing Daily Growth in Young-of-the-Year Winter Flounder along an Urban Gradient Revealed Using Hierarchical Linear Models

Abstract Growth during early life history plays a key role in the recruitment dynamics of marine fishes; however, the effects of environmental stressors on growth are often difficult to quantify. In this study, increment widths from sagittal otoliths were used as a proxy for daily growth in 102 young-of-the-year Winter Flounder Pseudopleuronectes americanus collected over a 2-year period from three sites in Long Island, New York. We hypothesized that we would observe different growth patterns among bays due to an environmental gradient driven primarily by contaminant loadings and environmental stressors in our study sites. Hierarchical linear models were utilized to associate individual attributes (ontogeny, condition, and gene expression) to daily growth patterns during each year. As expected, daily growth generally displayed a negative relationship with age and daily average temperature, although the effect of temperature was much more variable. Out of 14 individual attributes, the settlement date, the age at capture, the condition indices Fulton's K and hepatosomatic index, and the expression of genes associated with immune response (pleurocidin), contaminant exposure (cytochrome P5401A), and glucose and glycogen metabolism (glycerol-3-phosphate dehydrogenase) were observed to significantly and consistently affect growth. The results provide evidence of differential growth based on the date of settlement and condition, and the molecular indicators of stress suggest that growth is also influenced by habitat quality. There were significantly different relationships between individual attributes and growth among bays, but these did not always reflect the proposed environmental gradient. Together, the results suggest that anthropogenic stressors likely play a role in growth and recruitment processes in Long Island bays and indicate that growth is both spatially and temporally dynamic at multiple scales. Furthermore, this study highlights the utility of hierarchical linear models in analyzing complex daily growth data in juvenile fish, which may be applicable to other species.