We estimated temporal beta diversity in plant communities and partitioned it into its two dissimilarity resultant components, accounting for replacement of species (i.e. turnover) and for the nested gain or loss of species (i.e. nestedness).
In particular we used the two "dissimilarity metrics" introduced in Ref. [8].
If D β j β k F ≤ γ is lower than a predefined threshold γ, then the transform leading to the larger of the two dissimilarity scores d is removed from the target list.
Thus we calculated, for each individual, a root mean square of the acoustic parameters in component 1, and a second root mean square of the acoustic parameters in component 2. Fourth, we used these two dissimilarity indexes to calculate Euclidian distances between all possible dyads, producing a matrix of acoustic dissimilarity.
The above two dissimilarity measures are related, since the Pearson's correlation is essentially equivalent to a centered cosine similarity measure: As above, all the unique pairwise distances within a set of profiles are computed and the distribution of pairwise distances is summarized by its mean or its median.
For dissimilarities involving position in frame and frame time, we define four dissimilarities: two for the motion (based on tracklets or optical-flows), one for the speed (in pixel per frame time), and one for the time.
Then, these five dissimilarity measures are defined as follows.
Three dissimilarity matrices were generated, pocket vs. pocket using all binding site atoms (of every amino acid within a 5 Å distance from the ligand), pocket vs. pocket using binding site atoms only within 6.5 Å of the ligand, and inversely, ligand vs. ligand using the ligand atoms only.
We consider three dissimilarity metrics that can be computed easily over a large number of k-mers in sequential manner, i.e. one k-mer at a time, and without storing all the k-mer frequencies explicitly.
We studied three d 2 −type dissimilarity measures, as defined in [ 34], based on k-tuple count vectors and three dissimilarity measures defined on the basis of comparing the actual k-tuple frequency vectors to evaluate the beta-diversity between different samples.
