Testing the accuracy of methods for reconstructing ancestral states of continuous characters.

Many methods are available for estimating ancestral values of continuous characteristics, but little is known about how well these methods perform. Here we compare six methods: linear parsimony, squared-change parsimony, one-parameter maximum likelihood (Brownian motion), two-parameter maximum likelihood (Ornstein-Uhlenbeck process), and independent comparisons with and without branch-length information. We apply these methods to data from 20 morphospecies of Pleistocene planktic Foraminifera in order to estimate ancestral size and shape variables, and compare these estimates with measurements on fossils close to the phylogenetic position of 13 ancestors. No method produced accurate estimates for any variable: estimates were consistently less good as predictors of the observed values than were the averages of the observed values. The two-parameter maximum-likelihood model consistently produces the most accurate size estimates overall. Estimation of ancestral sizes is confounded by an evolutionary trend towards increasing size. Shape showed no trend but was still estimated very poorly: we consider possible reasons. We discuss the implications of our results for the use of estimates of ancestral characteristics.     

Atlas versus range maps: robustness of chorological relationships to distribution data types in European mammals

Aim Chorological relationships describe the patterns of distributional overlap among species. In addition to revealing biogeographical structure, the resulting clusters of species with similar geographical distributions can serve as natural units in conservation planning. Here, we assess the extent to which temporal, methodological and taxonomical differences in the source of species’ distribution data can affect the relationships that are found. Location Western Europe. Methods We used two data sets – the Atlas of European mammals and polygon range maps from the IUCN Global Mammal Assessment – both as presence–absence data for UTM 50 km × 50 km squares. We performed pairwise comparisons among 156 species for each data set to build matrices of the similarity in distribution across species, using both Jaccard’s and Baroni‐Urbani & Buser’s indices. We then compared these similarity matrices (chorological relationships), as well as the species richness and occurrence patterns from the two data sets. Results As expected, range maps increased both the mean prevalence per species and mean species richness per grid cell in comparison to atlas data, reflecting the general view that these data types respectively over‐ and underestimate species occurrence. However, species richness and occurrence patterns in atlas and range map data were positively associated and, most importantly, the chorological relationships underlying the two data sets were highly similar. Main conclusions Despite many methodological, temporal and taxonomical differences between atlas data and range maps, the chorological relationships encountered between species were similar for both data sets. Chorological analyses can thus be robust to the data source used and provide a solid basis for analytical biogeographical studies, even over broad spatial scales.