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      Evolution of the army ant syndrome: The origin and long-term evolutionary stasis of a complex of behavioral and reproductive adaptations

      Proceedings of the National Academy of Sciences
      Proceedings of the National Academy of Sciences

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          Abstract

          The army ant syndrome of behavioral and reproductive traits (obligate collective foraging, nomadism, and highly specialized queens) has allowed these organisms to become the premiere social hunters of the tropics, yet we know little about how or why these strategies evolved. The currently accepted view holds that army ants evolved multiple times on separate continents. I generated data from three nuclear genes, a mitochondrial gene, and morphology to test this hypothesis. Results strongly indicate that the suite of behavioral and reproductive adaptations found in army ants throughout the world is inherited from a unique common ancestor, and did not evolve convergently in the New World and Old World as previously thought. New Bayesian methodology for dating the antiquity of lineages by using a combination of fossil and molecular information places the origin of army ants in the mid-Cretaceous, consistent with a Gondwanan origin. Because no known army ant species lacks any component of the army ant syndrome, this group represents an extraordinary case of long-term evolutionary stasis in these adaptations.

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          Most cited references37

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          Estimating Absolute Rates of Molecular Evolution and Divergence Times: A Penalized Likelihood Approach

          Rates of molecular evolution vary widely between lineages, but quantification of how rates change has proven difficult. Recently proposed estimation procedures have mainly adopted highly parametric approaches that model rate evolution explicitly. In this study, a semiparametric smoothing method is developed using penalized likelihood. A saturated model in which every lineage has a separate rate is combined with a roughness penalty that discourages rates from varying too much across a phylogeny. A data-driven cross-validation criterion is then used to determine an optimal level of smoothing. This criterion is based on an estimate of the average prediction error associated with pruning lineages from the tree. The methods are applied to three data sets of six genes across a sample of land plants. Optimally smoothed estimates of absolute rates entailed 2- to 10-fold variation across lineages.
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            Estimating the rate of evolution of the rate of molecular evolution.

            A simple model for the evolution of the rate of molecular evolution is presented. With a Bayesian approach, this model can serve as the basis for estimating dates of important evolutionary events even in the absence of the assumption of constant rates among evolutionary lineages. The method can be used in conjunction with any of the widely used models for nucleotide substitution or amino acid replacement. It is illustrated by analyzing a data set of rbcL protein sequences.
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              Divergence time and evolutionary rate estimation with multilocus data.

              Bayesian methods for estimating evolutionary divergence times are extended to multigene data sets, and a technique is described for detecting correlated changes in evolutionary rates among genes. Simulations are employed to explore the effect of multigene data on divergence time estimation, and the methodology is illustrated with a previously published data set representing diverse plant taxa. The fact that evolutionary rates and times are confounded when sequence data are compared is emphasized and the importance of fossil information for disentangling rates and times is stressed.
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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proceedings of the National Academy of Sciences
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                May 27 2003
                May 15 2003
                May 27 2003
                : 100
                : 11
                : 6575-6579
                Article
                10.1073/pnas.1137809100
                164488
                12750466
                ec03682d-99e4-42fc-b2bb-78768c00a508
                © 2003
                History

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