Daniel Rafael Miranda-Esquivel

A Phylogenetic Approach to Conserving Amazonian Biodiversity

Amazonia is a highly threatened rainforest that encompasses a major proportion of Earths biological diversity. Our main goal was to establish conservation priorities for Amazonias areas of endemism on the basis of measures of evolutionary distinctiveness. We considered two previously identified sets of areas of endemism. The first set consisted of eight large areas used traditionally in biogeographical studies: Belém, Tapajós, Xingu, Guiana, Rondônia, Imeri, Inambari, and Napo. The second set consisted of 16 smaller areas that were subdivisions of the larger areas. We assembled a data set of 50 phylogenies that represented 16 orders and 1715 distributional records. We identified priority conservation areas for the areas of endemism according to node-based metrics of evolutionary distinctiveness. We contrasted these results with priority areas identified on the basis of raw species richness and species endemicity. For the larger areas, we identified Guiana and Inambari as the first- and second-most important areas for conservation. The remaining areas in this first group scored half (e.g., Napo) or less than Guiana and Inambari on all indices. For the smaller areas, a subdivision of Guiana (i.e., Guyana and the Brazilian states of Roraima and Amazonas) was at the top of the ranking and was followed by a subdivision of Inambari (i.e., northwestern portion of Amazonas) and then another subdivision of Guiana (i.e., Suriname, French Guiana, and the Brazilian state of Amapá). The distinctiveness-based rankings of the priority of areas correlated directly with those derived from species richness and species endemicity. Current conservation strategies in Amazonia, although they rely on many other criteria apart from phylogeny, are focusing on the most important areas for conservation we identified here.

MartiTracks: A Geometrical Approach for Identifying Geographical Patterns of Distribution

Panbiogeography represents an evolutionary approach to biogeography, using rational cost-efficient methods to reduce initial complexity to locality data, and depict general distribution patterns. However, few quantitative, and automated panbiogeographic methods exist. In this study, we propose a new algorithm, within a quantitative, geometrical framework, to perform panbiogeographical analyses as an alternative to more traditional methods. The algorithm first calculates a minimum spanning tree, an individual track for each species in a panbiogeographic context. Then the spatial congruence among segments of the minimum spanning trees is calculated using five congruence parameters, producing a general distribution pattern. In addition, the algorithm removes the ambiguity, and subjectivity often present in a manual panbiogeographic analysis. Results from two empirical examples using 61 species of the genus Bomarea (2340 records), and 1031 genera of both plants and animals (100118 records) distributed across the Northern Andes, demonstrated that a geometrical approach to panbiogeography is a feasible quantitative method to determine general distribution patterns for taxa, reducing complexity, and the time needed for managing large data sets.

Profile Parsimony (PP): an analysis under Implied Weights (IW)

Faith and Trueman [Syst. Biol. (2001) 331] recently proposed “Profile Parsimony” (PP) as a new form of phylogenetic analysis, but it is equivalent to the Implied Weights (IW) method when certain functions are used. The PP method cannot accommodate missing/inapplicable cells and/or multistate characters. Finally we demonstrate that, as defined, PP scores are not random, and there is no need to generate random trees as proposed by Faith and Trueman.

Weighted compromise trees: a method to summarize competing phylogenetic hypotheses

A new consensus method for summarizing competing phylogenetic hypotheses, weighted compromise, is described. The method corrects for a bias inherent in majority‐rule consensus/compromise trees when the source trees exhibit non‐independence due to ambiguity in terminal clades. Suggestions are given for its employment in parsimony analyses and tree resampling strategies such as bootstrapping and jackknifing. An R function is described that can be used with the programming language R to produce the consensus.

What is PACT really

“Phylogenetic Analysis for Comparing Trees” (PACT) has been presented as a “new algorithm” for the study of biogeography and coevolution. However, an exploration of this algorithm revealed some important problems missed in the original description. First, PACT is not new, rather it is an extension of Tree Mapping under Maximum Codivergence (TM‐MC). Second, as was described, PACT lacks an optimality criterion, and like secondary BPA, it does not offer a solution for handling incongruent elements. We found that PACT and TM‐MC differ only in the way the final answer is presented, and in the absence of an explicit algorithm of historical reconstruction under PACT. Given the equivalence between TM‐MC and PACT in their aims and assumptions, the criticism to TM‐MC as “orthogenetic” is not well founded.