Modelling dynamic relationships between marine animal species and their local environment is integral to evaluating the past and current state of any ecosystem. With significant changes in both climate and biodiversity occurring in recent decades, and with fluctuations expected to increase in frequency and severity, ecosystem models employed need to show high fidelity to recorded data to allow for accurate future predictions in response to long-term environmental instability. Holistic Dynamic Bayesian Network ecosystem models can identify the key relationships between environmental and species/biological variables, but do not necessarily capture crucial life-history characteristics relating to individual species population dynamics. In this study, we attempt to incorporate Leslie Matrix modelling of population dynamics into H-DBN models. Two ‘testing’ methods were investigated for our models, with the aim of applying realistic bounding to the rate of population increase for two contrasting species of seabird, measured through their breeding success. The first method used all available variables to both train and test the DBN model, while the second method used a reduced number of variables as ‘evidence’ to test the model. In early results, significant improvements in predictive accuracy of the models for both species was observed when population dynamics data was included. Specifically, after the addition of the Leslie Matrix output to the DBN ecosystem model, we were able to capture with high accuracy the inter-annual variability of the breeding success.