In many life situations, we base our decisions and actions on their predicted
consequences. Yet, predictions are also indispensable in fundamental sciences
where interests center on understanding how our universe works, rather than
assisting with practical life problems. We recently asked some colleagues why we want to predict things in
science and often heard something like "because this will tell us whether
we got it right or not". – This made us think. If true, what does this
mean for a field of research still struggling with making accurate predictions?
(And now for some shameless self-promotion!...)
This question marked the starting point for our essay3, which now appeared online and will be part of a special volume on "Speciation" in CSH Perspectives in Biology. To start, it seems essential to distinguish between two types of scientific predictions because they fundamentally differ in their function and value: in fundamental research, we are mainly interested in "causal predictions", not "correlational predictions". We then identify the three fundamental challenges for making accurate causal predictions in speciation research and discuss which of them are theoretically surmountable. Don't despair, there is hope! We also outline how these and further insights (more in the paper!) could shape future speciation research – namely toward a Standard Model – as well as related research in ecology and evolution.
Indeed, although tailored to speciation research, our essay connects with and easily translates to scientific disciplines beyond this field. We believe there are benefits for many of us in a deep consideration of scientific predictability, whether empiricists, theoreticians, or folks drawn to the philosophy of science. Perhaps even Nostradamus would have found interest in this read. While the fundamental topics we discuss in the essay are not new, we use an integrative and somewhat unorthodox approach – including a thought experiment with an Orrery and a Speciation Machine (see figure below) – to hopefully stimulate not only vivid and fun but also fruitful discussions. In fact, our (many) discussions on predictability have led us to organize a symposium on this topic at this year's joint ESEB/Evolution conference in Montreal (stay tuned for it!).
And folks in North America, don't forget to mark 8 April in your
calendars for an astronomical spectacle because it won’t happen there again for
the next 9 years (3278 days, to be precise)!
References
1. Nostradamus, M. Les Prophéties. Lyon, 1555.
2. From https://science.nasa.gov/eclipses/future-eclipses/eclipse-2024/where-when/ (accessed 28 January 2024)
3. Roesti M, Roesti H, Satokangas I, Boughman J, Chaturvedi S, Wolf JBW, Langerhans RB. Predictability, an Orrery, and a Speciation Machine: Quest for a Standard Model of Speciation. Cold Spring Harbor Perspectives in Biology 2024 Feb 12:a041456. doi: 10.1101/cshperspect.a041456. Epub ahead of print. PMID: 38346860.
4. Hendry A. Prediction in ecology and evolution, BioScience, Volume 73, Issue 11, November 2023, Pages 785–799, https://doi.org/10.1093/biosci/biad083