No abstract

No abstract

Abstract. The gynogenetic Amazon molly (Poecilia formosa) is a clonal, all-female lineage of livebearing fish that faces an unusual obstacle to evolutionary persistence. Sperm from heterospecific males (either sailfin, P. latipinna, or Atlantic, P. mexicana, mollies) is necessary to trigger embryogenesis. However, none of the male's genes are incorporated into the genome of the gynogenetic offspring. Some investigators have proposed that the evolution of male mate discrimination is a result of this cost, leading to a coevolutionary arms race between male avoidance of P. formosa and P. formosa attractiveness. Given that P. formosa successfully reproduces and has not yet gone extinct, it is clear there are mechanisms by which they attract the sexual attention of males. Although a Red Queen coevolutionary process in typical host/parasite systems has been shown to favor the persistence of sexual species, in this system an arms race has been invoked to explain the reverse. Here I present behavioral data supporting a more parsimonious scenario: that mechanisms of attraction in P. formosa are simply a consequence of its hybrid origin. Poecilia latipinna and P. mexicana males do not discriminate between gynogenetic P. formosa females and first generation sexual hybrid females, and females do not differ in agonistic behaviors associated with competition for mates. Both results contradict predictions from the Red Queen hypothesis. Therefore, coevolution is not necessary to explain the apparent evolutionary persistence of P. formosa. Evolutionary theory predicts that clonal or asexual lineages will suffer a loss in average fitness over time due to a range of

We investigated the usefulness of a parallel genetic algorithm for phylogenetic inference under the maximum-likelihood (ML) optimality criterion. Parallelization was accomplished by assigning each "individual" in the genetic algorithm "population" to a separate processor so that the number of processors used was equal to the size of the evolving population (plus one additional processor for the control of operations). The genetic algorithm incorporated branch-length and topological mutation, recombination, selection on the ML score, and (in some cases) migration and recombination among subpopulations. We tested this parallel genetic algorithm with large (228 taxa) data sets of both empirically observed DNA sequence data (for angiosperms) as well as simulated DNA sequence data. For both observed and simulated data, search-time improvement was nearly linear with respect to the number of processors, so the parallelization strategy appears to be highly effective at improving computation time for large phylogenetic problems using the genetic algorithm. We also explored various ways of optimizing and tuning the parameters of the genetic algorithm. Under the conditions of our analyses, we did not find the best-known solution using the genetic algorithm approach before terminating each run. We discuss some possible limitations of the current implementation of this genetic algorithm as well as of avenues for its future improvement.

Understanding population change is essential for conservation of imperiled species, such as amphibians. Worldwide amphibian declines have provided an impetus for investigating their population dynamics, which can involve both extrinsic (density‐independent) and intrinsic (density‐dependent) drivers acting differentially across multiple life stages or age classes. In this study, we examined the population dynamics of the endangered Barton Springs Salamander (Eurycea sosorum) using data from a long‐term monitoring program. We were interested in understanding both the potential environmental drivers (density‐independent factors) and demographic factors (interactions among size classes, negative density dependence) to better inform conservation and management activities. We used data from three different monitoring regimes and multivariate autoregressive state‐space models to quantify environmental effects (seasonality, discharge, algae, and sediment cover), intraspecific interactions among three size classes, and intra‐class density dependence. Results from our primary data set revealed similar patterns among sites and size classes and were corroborated by our out‐of‐sample data. Cross‐correlation analysis showed juvenile abundance was most strongly correlated with a 9‐month lag in aquifer discharge, which we suspect is related to inputs of organic carbon into the aquifer. However, sedimentation limited juvenile abundance at the surface, emphasizing the importance of continued sediment management. Recruitment from juveniles to the sub‐adult size class was evident, but negative density‐dependent feedback ultimately regulated each size class. Negative density dependence may be an encouraging sign for the conservation of E. sosorum because populations that can reach carrying capacity are less likely to go extinct compared to unregulated populations far below their carrying capacity. However, periodic population declines coupled with apparent migration into the aquifer complicate assessments of species status. Although both density‐dependent and density‐independent drivers of population change are not always apparent in time series of animal populations, both have important implications for conservation and management of E. sosorum.