The biological characteristics of fisheries stocks that are assessed for management considerations are rarely homogeneous over time or space. However, stock assessment scientists largely ignore this heterogeneity in their models. This thesis addresses the effects of spatial and temporal heterogeneity on stock assessment models using Atlantic Weakfish (Cynoscion regalis) as a case study. First, spatial and temporal variation was incorporated into length-, weight-, and maturity-at-age estimates using mixed-effects models (Chapter Two). The resulting heterogeneous weight and maturity parameters then were applied to per-recruit analyses to examine the sensitivity of biological reference points to spatial and temporal variation in life history attributes (Chapter Three). Mixed-effects life history models incorporating spatial and temporal variation revealed distinct regional and annual trends that were not visible from standard homogeneous models. In several instances, the homogeneous modelling approach produced life history estimates that varied significantly from the spatial and temporal means produced by the heterogeneous models. In some cases, this difference was so great that the homogeneous means were much higher or lower than the heterogeneous means for all regions or years. Minimized AIC statistics revealed that spatially and temporally integrated mixed-effects models were more robust and descriptive of Atlantic Weakfish life history than the standard homogeneous models. Per-recruit and biological reference points derived from these life history estimates in Chapter Three were found to be highly sensitive to spatial and temporal variations in weight parameters. In several cases, reference points used as management targets were so significantly different that ignoring spatial and temporal heterogeneity in Atlantic Weakfish life history would likely cause overfishing and decline of Weakfish in certain regions and years. / Master of Science / Many stocks of commercially and recreationally harvested marine fish have displayed a declining trend in recent years. Marine fisheries are a vital component of the global economy, and, as such, sophisticated management measures have been developed to reduce and reverse this trend. These management strategies are based on regular reports from fisheries stock assessment scientists, who evaluate the status of fish stocks by modelling life history and productivity trends. One of the greatest challenges to stock assessments is the identification and incorporation of variability in fish populations. There is an inherent variation in fish growth, maturity, and productivity among geographical locations and over time. To produce the most effective management strategies, stock assessments must incorporate this spatial (regional) and temporal (annual) variation. In this thesis, I used mixed effects models to integrate spatial and temporal variation in life history and productivity using Atlantic Weakfish (Cynoscion regalis) as a case study. Distinct trends were observed in fishery-independent data for this species that were reflected in spatially and temporally incorporated models. However, these trends were masked in the standard models which incorporated neither spatial nor temporal variation. This oversight could cause weakfish to be overfished in certain regions and years and underfished in others. To maximize the effectiveness of management and the sustainable fisheries yield in all regions and years for Atlantic Weakfish and other harvested species, I highly recommend using spatially and temporally incorporated life history and productivity models such as the ones developed in this thesis.