Aim To introduce and describe the functioning of a new algorithm, phylogenetic analysis for comparing trees (PACT), for generating area cladograms that provide accurate representation of information contained in taxon–area cladograms. Methods PACT operates in the following steps. Convert all phylogenies to taxon–area cladograms. Convert all taxon–area cladograms to Venn diagrams. Choose any taxon–area cladogram from the set of taxon–area cladograms to be analysed and determine its elements. This will be the template area cladogram. Select a second taxon–area cladogram. Determine its elements. Document which elements in the second tree occur in the template tree (denoted by ‘Y’) and which do not (denoted by ‘N’). Each ‘Y’ indicates a match with previous pattern and these are combined. Each ‘N’ is a new element and is attached to the template area cladogram at the node where it is linked with a Y. This requires two rules: (1) ‘Y + Y = Y’ (combine common elements) as long as they are connected at the same node; and (2) ‘Y + N = YN’ (add novel elements to the template area cladogram at the node where they first appear). Once the novel elements in the second taxon–area cladogram have been added to the template area cladogram, see if any of them can be further combined. This requires three additional rules: (1) ‘Y(Y− = Y(Y−’ (do not combine Y's if they are attached at different nodes on the template area cladogram); (2) ‘Y + YN = YN’ (Y is part of group YN); and (3) ‘YN + YN = YNN’ (Y is the same for each, but each N is different). Repeat for all available taxon–area cladograms. Results Three exemplars demonstrate that PACT provides the most accurate area cladograms for vicariance‐driven biotic diversification, dispersal‐driven biotic diversification and taxon pulse‐driven biotic diversification. PACT can also be used as an a priori method of biogeographical analysis. Main conclusions PACT embodies all the strong points and none of the weaknesses of previously proposed methods of historical biogeography. It is most useful as an a posteriori method, but it is also superior to all previous a priori methods because it does not specify costs, or weights or probabilities, or likelihoods of particular biogeographical processes a priori and is thus sensitive to clade‐specific historical contingencies.
An algorithm for generating host cladograms from parasite-host cladograms derived from parasite phylogenies, Phylogenetic Analysis for Comparing Trees (PACT), is described. PACT satisfies Assumption 0, that all the information in each parasite-host cladogram must be used in a co-evolutionary analysis, and that the host relationships depicted in the final host cladogram must be logically consistent with the phylogenetic relationships depicted in every part of every parasite-host cladogram used to construct the host cladogram. It accounts for cases of speciation by host switching and expansion of host range, and reticulated host relationships, in addition to co-speciation, sympatric speciation, and extinction in all input parasite-host cladograms, and does so without a priori weighting schemes and without a posteriori manipulation of the data. Ó The Willi Hennig Society 2004.Brooks Parsimony Analysis (BPA), a method for comparative phylogenetic analysis of co-evolutionary patterns (Brooks and McLennan, 2002;Dowling et al., 2003;Brooks et al., 2004), can be implemented using standard methods in phylogenetic analysis (either Hennigian argumentation or maximum parsimony analysis: Brooks and McLennan, 2003), but only with laborious manipulations of the data. All parasite phylogenies must be converted into parasite-host cladograms by replacing the name of each parasite species with its hosts. For Hennigian argumentation, each parasite-host cladogram is treated as a completely polarized and ordered multistate transformation series, and all parasite-host cladograms are combined using the inclusion ⁄ exclusion rule, with homoplasious occurrences of parasites denoted by duplicating the hosts in which they occur. For maximum parsimony analysis, parasite-host cladograms are converted into binary matrices, from which the analysis produces a host cladogram in which each host species occurs only once (primary BPA). Homoplasy in that host cladogram indicates departures from co-speciation, resulting in reticulated host relationships; these events are represented by duplicating each host for each case of homoplasy (secondary BPA). This requires that the matrix be re-formulated, which in turn produces large numbers of pseudo-missing data codes representing the hosts not affected by the events requiring the duplications (Brooks and McLennan, 2002). Performing such an analysis for complex data sets is thus time-consuming. In addition, because one cannot specify the number and types of host duplications that will be needed a priori, some believe that the duplication convention in BPA is simply enumerative (or even idiosyncratic) rather than algorithmic (e.g., Ronquist, 2002).In this contribution, we present an algorithm for deriving host cladograms from parasite phylogenies which, like BPA: (1) satisfies Assumption 0 (all information in all parasite-host cladograms must be used, and the final host cladogram must be logically consistent with all input parasite-host cladograms: see Brooks et al., 2004 for a discussion of Assumption 0), (...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.