This week has been all about biogeography for me. While I wouldn’t call myself a ‘biogeographer’, I certainly do apply a lot of the discipline’s techniques.
This week I’m attending the 2013 Association of Ecology’s (INTECOL) and British Ecological Society’s joint Congress of Ecology in London, and I have purposefully sought out more of the biogeographical talks than pretty much anything else because the speakers were engaging and the topics fascinating. As it happens, even my own presentation had a strong biogeographical flavour this year.
Although the species-area relationship (SAR) is only one small aspect of biogeography, I’ve been slightly amazed that after more than 50 years since MacArthur & Wilson’s famous book, our discipline is still obsessed with SAR.
I’ve blogged about SAR issues before – what makes it so engaging and controversial is that SAR is the principal tool to estimate overall extinction rates, even though it is perhaps one of the bluntest tools in the ecological toolbox. I suppose its popularity stems from its superficial simplicity – as the area of an (classically oceanic) island increases, so too does the total number of species it can hold. The controversies surrounding such as basic relationship centre on describing the rate of that species richness increase with area – in other words, just how nonlinear the SAR itself is.
Even a cursory understanding of maths reveals the importance of estimating this curve correctly. As the area of an ‘island’ (habitat fragment) decreases due to human disturbance, estimating how many species end up going extinct as a result depends entirely on the shape of the SAR. Get the SAR wrong, and you can over- or under-estimate the extinction rate. This was the crux of the palaver over Fangliang He (not attending INTECOL) & Stephen Hubbell’s (attending INTECOL) paper in Nature in 2011.
The first real engagement of SAR happened with John Harte’s maximum entropy talk in the process macroecology session on Tuesday. What was notable to me was his adamant claim that the power-law form of SAR should never be used, despite its commonness in the literature. I took this with a grain of salt because I know all about how messy area-richness data can be, and why one needs to consider alternate models (see an example here). But then yesterday I listened to one of the greats of biogeography – Robert Whittaker – who said pretty much the complete opposite of Harte’s contention. Whittaker showed results from one of his papers last year that the power law was in fact the most commonly supported SAR among many datasets (granted, there was substantial variability in overall model performance). My conclusion remains firm – make sure you use multiple models for each individual dataset and try to infer the SAR from model-averaging. Read the rest of this entry »