146 research outputs found

    Lianas have a greater competitive effect than trees of similar biomass on tropical canopy trees

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    Lianas (woody vines) reduce growth and survival of host trees in both temperate and tropical forests; however, the relative strength of liana‐tree competition in comparison to tree‐tree competition remains unexplored. When controlling for biomass, lianas may have greater competitive effects than trees because the unique morphology of lianas allows them to reach the forest canopy at relatively small stem diameters and deploy a substantial crown above their host. We tested the hypothesis that lianas have a greater negative effect on canopy trees than do trees of similar biomass with a liana‐ and tree sapling‐cutting experiment in a seasonal tropical moist forest in Panama. The response of canopy trees to the cutting treatments was characterized as the change in their daily water use by measuring their sap velocity before and after cutting. We compared the responses of canopy trees around which a similar biomass of either lianas or tree saplings had been cut to control trees with no cutting. Liana cutting increased canopy‐tree sap velocity by ∼8% from before to after cutting relative to control trees during the dry season. In contrast, canopy‐tree sap velocity did not respond to tree cutting, probably because trees with biomass similar to lianas were confined to the forest understory. We observed a similar pattern of sap velocity changes during the wet season, but treatment differences were not significant. Our results demonstrate that release from liana competition, but not tree competition, resulted in increased water transport in canopy trees, and suggests that relative to their biomass, lianas have greater competitive effects on canopy tree performance than do competing trees

    Unique Competitive Effects of Lianas and Trees in a Tropical Forest Understory

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    Lianas are an important component of tropical forests, contributing up to 25 % of the woody stems and 35 % of woody species diversity. Lianas invest less in structural support but more in leaves compared to trees of similar biomass. These physiological and morphological differences suggest that lianas may interact with neighboring plants in ways that are different from similarly sized trees. However, the vast majority of past liana competition studies have failed to identify the unique competitive effects of lianas by controlling for the amount of biomass removed. We assessed liana competition in the forest understory over the course of 3 years by removing liana biomass and an equal amount of tree biomass in 40 plots at 10 sites in a secondary tropical moist forest in central Panama. We found that growth of understory trees and lianas, as well as planted seedlings, was limited due to competitive effects from both lianas and trees, though the competitive impacts varied by species, season, and size of neighbors. The removal of trees resulted in greater survival of planted seedlings compared to the removal of lianas, apparently related to a greater release from competition for light. In contrast, lianas had a species-specific negative effect on drought-tolerant Dipteryx oleifera seedlings during the dry season, potentially due to competition for water. We conclude that, at local scales, lianas and trees have unique and differential effects on understory dynamics, with lianas potentially competing more strongly during the dry season, and trees competing more strongly for light

    How variation in head pitch could affect image matching algorithms for ant navigation

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    Desert ants are a model system for animal navigation, using visual memory to follow long routes across both sparse and cluttered environments. Most accounts of this behaviour assume retinotopic image matching, e.g. recovering heading direction by finding a minimum in the image difference function as the viewpoint rotates. But most models neglect the potential image distortion that could result from unstable head motion. We report that for ants running across a short section of natural substrate, the head pitch varies substantially: by over 20 degrees with no load; and 60 degrees when carrying a large food item. There is no evidence of head stabilisation. Using a realistic simulation of the ant’s visual world, we demonstrate that this range of head pitch significantly degrades image matching. The effect of pitch variation can be ameliorated by a memory bank of densely sampled along a route so that an image sufficiently similar in pitch and location is available for comparison. However, with large pitch disturbance, inappropriate memories sampled at distant locations are often recalled and navigation along a route can be adversely affected. Ignoring images obtained at extreme pitches, or averaging images over several pitches, does not significantly improve performance

    Liana Abundance, Diversity, and Distribution on Barro Colorado Island, Panama

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    Lianas are a key component of tropical forests; however, most surveys are too small to accurately quantify liana community composition, diversity, abundance, and spatial distribution – critical components for measuring the contribution of lianas to forest processes. In 2007, we tagged, mapped, measured the diameter, and identified all lianas ≥1 cm rooted in a 50-ha plot on Barro Colorado Island, Panama (BCI). We calculated liana density, basal area, and species richness for both independently rooted lianas and all rooted liana stems (genets plus clones). We compared spatial aggregation patterns of liana and tree species, and among liana species that varied in the amount of clonal reproduction. We also tested whether liana and tree densities have increased on BCI compared to surveys conducted 30-years earlier. This study represents the most comprehensive spatially contiguous sampling of lianas ever conducted and, over the 50 ha area, we found 67,447 rooted liana stems comprising 162 species. Rooted lianas composed nearly 25% of the woody stems (trees and lianas), 35% of woody species richness, and 3% of woody basal area. Lianas were spatially aggregated within the 50-ha plot and the liana species with the highest proportion of clonal stems more spatially aggregated than the least clonal species, possibly indicating clonal stem recruitment following canopy disturbance. Over the past 30 years, liana density increased by 75% for stems ≥1 cm diameter and nearly 140% for stems ≥5 cm diameter, while tree density on BCI decreased 11.5%; a finding consistent with other neotropical forests. Our data confirm that lianas contribute substantially to tropical forest stem density and diversity, they have highly clumped distributions that appear to be driven by clonal stem recruitment into treefall gaps, and they are increasing relative to trees, thus indicating that lianas will play a greater role in the future dynamics of BCI and other neotropical forests

    Probing host pathogen cross-talk by transcriptional profiling of both Mycobacterium tuberculosis and infected human dendritic cells and macrophages

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    This study provides the proof of principle that probing the host and the microbe transcriptomes simultaneously is a valuable means to accessing unique information on host pathogen interactions. Our results also underline the extraordinary plasticity of host cell and pathogen responses to infection, and provide a solid framework to further understand the complex mechanisms involved in immunity to M. tuberculosis and in mycobacterial adaptation to different intracellular environments

    Evolving a Neural Model of Insect Path Integration

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    Path integration is an important navigation strategy in many animal species. We use a genetic algorithm to evolve a novel neural model of path integration, based on input from cells that encode the heading of the agent in a manner comparable to the polarization-sensitive interneurons found in insects. The home vector is encoded as a population code across a circular array of cells that integrate this input. This code can be used to control return to the home position. We demonstrate the capabilities of the network under noisy conditions in simulation and on a robot
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