For these forests with k = 10“, there were two distinct parameter sets that match the characteristics of the empirical data.

Pasoh is not included because no parameter sets consistent with the empirical data were found with k 2 10—4.

While there were two discrete parameter sets each that matched the richness and evenness of Pasoh and Lambir (one where 6 was low and m high, and one where 6 was higher and m lower), the power of the test with these parameters was always low.

Here, we choose parameter sets such that the model best describes a set of summary statistics of empirical data sets, specifically: species richness and Shannon index.

There will therefore be a discrete set of parameter values where the mean species richness and mean Shannon index of samples from the model match the empirical data sets; in most cases we found only one such parameter set , though in some cases there were two and in others there were none because the model produced a Shannon index that was always higher than, or always lower than, the empirical data.

We performed this procedure, for a set of candidate values of the non-neutral parameter, to generate parameter sets resembling three tropical forest data sets belonging to the CTFS network to which neutral theory has successfully been fitted in the past [46]: Barro Colorado Island, Pasoh Forest Reserve, and Lambir Hills National Park [37—39].

For the i’th sample neutral data set, compute the corresponding maximum likelihood estimate parameter set ijN) and maximum likelihood L(X | mm, 03%,) using the same procedure as used for XT.