Abstract
Species abundance distributions (SAD) are probably ecology’s most well-known empirical pattern, and over the last decades many models have been proposed to explain their shape. There is no consensus over which model is correct, because the degree to which different processes can be discerned from SAD patterns has not yet been rigorously quantified. We present a power calculation to quantify our ability to detect deviations from neutrality using species abundance data. We study non-neutral stochastic community models, and show that the presence of non-neutral processes is detectable if sample size is large enough and/or the amplitude of the effect is strong enough. Our framework can be used for any candidate community model that can be simulated on a computer, and determines both the sampling effort required to distinguish between alternative processes, and a range for the strength of non-neutral processes in communities whose patterns are statistically consistent with neutral theory. We find that even data sets of the scale of the 50 Ha forest plot on Barro Colorado Island, Panama, are unlikely to be large enough to detect deviations from neutrality caused by competitive interactions alone, though the presence of multiple non-neutral processes with contrasting effects on abundance distributions may be detectable.
Highlights
The extent to which ecological processes can be inferred from macroecological patterns has long been debated [1,2,3,4]
A classic idea in Ecology is that species coexist because they occupy different “niches”
“Neutral” models embody this idea, omitting niche differentiation and assuming all species are identical. Such models are mostly statistically consistent with the relative abundances of tree species in tropical forests, but statistical procedures always contain an element of uncertainty and many other models could be consistent with a particular data set
Summary
The extent to which ecological processes can be inferred from macroecological patterns has long been debated [1,2,3,4]. Empirical SADs are in many cases found to be statistically consistent with Hubbell’s neutral theory [12,13,14,15,16,17], but this does not mean that communities are truly neutral because non-neutral models can predict similar [8,9,10, 18, 19] or even identical [4] patterns. This raises the question of whether anything can be inferred from fitting it to SAD data [3, 4, 20]. More realistic models will include non-neutral processes, such as interactions that depend on species identity [32, 33], but neutral theory can act as a null model for assessing the weight of evidence for such processes
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