This course gives an introductory overview of mathematical models used to describe fish population dynamics and will discuss how these models are applied in modelling fish stocks. We will start with an exploration of some of the key fish population dynamics models and show how these are translated into real-world problems. We then consider estimation methods used to fit the models and illustrate these models through application to example datasets.
This course assumes a third-year undergraduate level understanding of the principles of statistical modelling and inference (including likelihood functions). Some knowledge of mixed effects models would be an advantage but is not required.
All statistical computing will be carried out in R, and thus the course requires basic knowledge of R and working software. A package list of the programs that will be needed to complete the labs will be sent out before the course begins.
The course will be relevant to anyone with an interest in mathematical modelling of natural processes, particularly in ecology.