Throughout my masters in Quantitative Biology I studied modelling from writing basic functions to complex interacting models. I worked with models in Matlab then progressed to R which I am most confident with modelling has I have completed a C to R complex model conversion for my thesis. I am currently completing my second complex code conversion from matlab to R for ZSL cheetahs.

If someone had told me I would love modelling and writing code I would have laughed at them but I love it because I can do something especially code conversion that no one else wants to do, its a challenge and you need alot of determination. Code converting is like running into a wall until finally it breaks down its well worth the wait.

Why modelling is Awesome?

I’m talking about code modeling not catwalk modeling. As much as the field are dissimilar, both require innovation, individual modeling flare and determination to examine detail down to a single string.

The statistician George Box: ‘All models are wrong, but some models are useful’

Advantages of modelling

  1. Predict accurately possible scenarios of the future for many disciplines from weather and climate to future species presence.
  2. With combined pass data and experience with a current model you can examine how well they match to optimize decisions with the model which you would otherwise be blind just using intuition and personal judgement however well grounded.
  3. Manipulation of circumstances within the model to examine potential projections to allow for preparation.


  1. The simpler the model the easier it is to understand in application to the real world but the more complex a model the more accurate the results may be but therefore the results and drivers harder to understand.
  2. You have to try to grasp the understanding of complex systems that are often impossible to factor everything in. You as the modeller have to make the decision what elements are and aren’t important.
This is my favourite ways models can be explained by Hanna Kokko paper

“Maps are models that are designed to help us grasp certain features of the landscape. For example, a map might
consist of contour lines which help us predict which way a river will flow once we stumble across it. But a map
would become completely useless if it had every tuft of grass marked on it. Including every detail would mean
that we ended up carrying a paper or plastic version of the whole landscape with us on a hiking trip. In other
words, staring at a too detailed model teaches us nothing more than staring at the original ecosystem, with its
complete mess of evolutionary and ecological detail.”

“So, we must simplify, to make the essentials of the process understandable to our poorly equipped brains.
The rule: Boil the system down to the essential features – the equivalent of contour lines and location of rivers and
roads; this is the level where true understanding can be gained. But which features are essential, and which ones
can be ignored, in a natural population where everything interacts with everything?”

Its a big map to try and study!