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      When conifers took flight: a biomechanical evaluation of an imperfect evolutionary takeoff

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      Paleobiology
      Cambridge University Press (CUP)

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          Abstract

          Manifera talaris, a voltzian conifer from the late early to middle Permian (ca. 270 Ma) of Texas, is the earliest known conifer to produce winged seeds indicative of autorotating flight. In contrast to autorotating seeds and fruits of extant plants, the ones of M. talaris are exceptional in that they have variable morphology. They bore two wings that produced a range of wing configurations, from seeds with two equal-sized wings to single-winged specimens, via various stages of underdevelopment of one of the wings. To examine the effects of various seed morphologies on aerodynamics and dispersal potential, we studied the flight performance of paper models of three morphotypes: symmetric double-winged, asymmetric double-winged, and single-winged. Using a high-speed camera we identified the mode of descent (plummeting, gliding, autorotation) and quantified descent speed, autorotation frequency, and other flight characteristics. To validate such modeling as an inferential tool, we compared descent of extant analogues (kauri; Agathis australis) with descent of similarly constructed seed models. All three seed morphotypes exhibited autorotating flight behavior. However, double-winged seeds, especially symmetric ones, failed to initiate slow autorotative descent more frequently than single-winged seeds. Even when autorotating, symmetric double-winged seeds descend faster than asymmetric double-winged ones, and descent is roughly twice as fast compared to single-winged seeds. Moreover, the relative advantage that (effectively) single-winged seeds have in slowing descent during autorotation becomes larger as seed weight increases. Hence, the range in seed wing configurations in M. talaris produced a wide variation in potential dispersal capacity. Overall, our results indicate that the evolutionarily novel autorotating winged seeds must have improved conifer seed dispersal, in a time when animal vectors for dispersion were virtually absent. Because of the range in wing configuration, the early evolution of autorotative flight in conifers was a functionally imperfect one, which provides us insight into the evolutionary developmental biology of autorotative seeds in conifers.

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          Spatial patterns of seed dispersal, their determinants and consequences for recruitment.

          Growing interest in spatial ecology is promoting new approaches to the study of seed dispersal, one of the key processes determining the spatial structure of plant populations. Seed-dispersion patterns vary among plant species, populations and individuals, at different distances from parents, different microsites and different times. Recent field studies have made progress in elucidating the mechanisms behind these patterns and the implications of these patterns for recruitment success. Together with the development and refinement of mathematical models, this promises a deeper, more mechanistic understanding of dispersal processes and their consequences.
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            Mechanisms of long-distance seed dispersal.

            Growing recognition of the importance of long-distance dispersal (LDD) of plant seeds for various ecological and evolutionary processes has led to an upsurge of research into the mechanisms underlying LDD. We summarize these findings by formulating six generalizations stating that LDD is generally more common in open terrestrial landscapes, and is typically driven by large and migratory animals, extreme meteorological phenomena, ocean currents and human transportation, each transporting a variety of seed morphologies. LDD is often associated with unusual behavior of the standard vector inferred from plant dispersal morphology, or mediated by nonstandard vectors. To advance our understanding of LDD, we advocate a vector-based research approach that identifies the significant LDD vectors and quantifies how environmental conditions modify their actions.
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              Why trees migrate so fast: confronting theory with dispersal biology and the paleorecord.

              Reid's paradox describes the fact that classical models cannot account for the rapid (10(2)-10(3) m yr-1) spread of trees at the end of the Pleistocene. I use field estimates of seed dispersal with an integrodifference equation and simulation models of population growth to show that dispersal data are compatible with rapid spread. Dispersal estimates lay to rest the possibility that rapid spread occurred by diffusion. The integrodifference model predicts that, if the seed shadow has a long 'fat' tail, then rapid spread is possible, despite short average dispersal distances. It further predicts that velocity is more sensitive to life history than is classical diffusion. Application of such models is frustrated because the tail of the seed shadow cannot be fitted to data. However, the data can be used to test a 'long-distance' hypothesis against alternative ('local') models of dispersal using Akaike's Information Criterion and likelihood ratio tests. Tests show that data are consistent with >10% of seed dispersed as a long (10(2) m) fat-tailed kernel. Models based on such kernels predict spread as rapid as that inferred from the pollen record. If fat-tailed dispersal explains these rapid rates, then it is surprising not to see large differences in velocities among taxa with contrasting life histories. The inference of rapid spread, together with lack of obvious life-history effects, suggests velocities may have not reached their potentials, being stalled by rates of climate change, geography, or both.
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                Author and article information

                Journal
                applab
                Paleobiology
                Paleobiology
                Cambridge University Press (CUP)
                0094-8373
                1938-5331
                March 2015
                March 12 2015
                March 2015
                : 41
                : 02
                : 205-225
                Article
                10.1017/pab.2014.18
                38de9c98-0ec4-4738-b420-7076ec28f216
                © 2015
                History

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