Quantifying passive and driven large-scale evolutionary trends.
I introduce a new statistical method, analysis of skewness, for quantifying large-scale evolutionary trends as a combination of both passive and driven trends. My approach is based on the skewness of subclades within a parent clade. I partition the total skewness of the parent clade into three components: (1) skewness between subclades; (2) skewness within subclades; and (3) skewness due to changes in variance among subclades. The third component corresponds to a new type of passive trend, in which overall skewness of a parent clade is due to greater variability in subclades to the right of the mean. Using this partitioning, I decompose an observed trend into two components: a driven portion and a passive portion. thus quantifying the effect of small-scale dynamics on large-scale behavior of clades. Applications are given to Miocene-Pliocene rodent size and Ordovician brachiopod muscle geometry.
Wang
S C
SC
Department of Statistics, Harvard University, Cambridge, Massachusetts 02138, USA. scwang@stat.harvard.edu
D000818:Animals; D005075:Biological Evolution; D001699:Biometry; D007448:Invertebrates / Q000033:anatomy & histology; D008954:Models, Biological; D008963:Molar / Q000033:anatomy & histology; D009132:Muscles / Q000033:anatomy & histology; D010802:Phylogeny; D012377:Rodentia / Q000033:anatomy & histology; D012641:Selection, Genetic