Julia in ecology: why multiple dispatch is good

In what is going to be the most technical note so far, I will try to reflect on a few years of using the Julia programming language for computational ecology projects. In particular, I will discuss how multiple dispatch changed my life (for the better), and how it can be used to make ecological analyses streamlined. I will most likely add a few entries to this series during the fall, leading up to a class I will give in the winter.

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What is computational ecology?

What is computational ecology? I am working on a manuscript to discuss this topic in the context of ecological synthesis. Since it is almost ready, I would love to get some feedback. And so I have pasted below a part of the introduction. If this little experiment goes well, I will add another section next week, before making it public as a preprint. Think of this as a trailer. To an academic article. Because these, I guess, are the times we live in.

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Approximate Bayesian Computation and tiny data in ecology

Every time I hear about Big Data in ecology, I cringe a little bit. Some of us may be lucky enough to have genuinely big data, but I believe this is the exception rather than the norm. And this is a good thing, because tiny data are extremely exciting – in short, they offer the challenge of isolating a little bit of signal in a lot of noise, and this is a perfect excuse to apply some really fun tools. And one of my favorite approaches for really small data is ABC, Approximate Bayesian Computation. Let’s dig in!

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