Location of capture sufficiently characterises lifetime growth trajectories in a highly mobile fish

Abstract

Variation in somatic growth plays a critical role in determining an individual’s body size and the expression of its life history. Understanding the environmental drivers of growth variation in mobile organisms such as fishes can be challenging because an individual’s growth expression integrates processes operating at different spatial and temporal scales. Traditionally, otolith (ear stone) based growth analyses have focussed on temporal environmental variation by assuming an individual spends its whole life at its capture location. This approach ignores the movement potential of individuals and thus the role of spatio-temporal variation in conditions experienced. Here, we develop a modelling framework that incorporates individual movement information reconstructed via the analysis of chemical tracers in otoliths. We assess whether consideration of movement histories is important to estimating growth of a mobile freshwater fish, golden perch (Macquaria ambigua) at three spatial resolutions: basin-scale, reach-scale (movement-exclusive), and reach-scale (movement-inclusive). The predictive capacity of annual growth models slightly improved from the basin to the reach spatial scales (inclusive or exclusive of movement histories). Contrary to expectations, incorporating individual movement information, did not improve our ability to describe growth patterns. Golden perch growth was linked to the magnitude of and variation in spring, summer, and previous-year (antecedent) discharge, and spring temperature. The direction and magnitude of these effects was, however, dependent on life stage. Adults benefitted strongly from any increase in discharge or temperature, whereas juveniles benefitted only from increased summer discharge and grew slower in years characterised by wetter and warmer springs. We suggest that, for highly mobile fish like golden perch and in the absence of fine, ‘within reach’ scale biological data, coarser ‘reach-scale’ environmental variation may adequately describe individual growth trajectories.