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32 results for “wind dispersal”
Quantifying wind-driven dispersal of zooplankton in a Mediterranean pond
<p>Dispersal is an essential component in the life history of organisms and has strong ecological implications. Although it has been assumed that small organisms have very high dispersal rates, quantitative data supporting this claim remains scarce. In the context of zooplankton, wind stands out as a primary vector facilitating passive dispersal. We quantified short-distance wind-driven dispersal of propagules across various zooplankton taxa in a Spanish Mediterranean coastal temporary pond. We have also studied dispersal patterns in relation to the wind regime (intensity, steadiness and gust direction), source pond status (volume of water) and demographic dynamics (the abundance of individuals in water column populations). Further, we related propagules size merurements (surface, L2 and volume, L3) with dispersal distances. Additionally, we have performed measurements of the dispersed propagules and investigated the relationship between their dimensions and the dispersive distance on a local scale. Here, we present the raw data gathered during research.</p>
Dataset and R-script for simple mechanistic model of Heracleum sosnowskyi seed dispersal by wind
<p>The dataset contains:</p> <p>- primary data about Heracleum sosnowskyi seeds traits (terminal velocity, mass, area, wing loading) and release heights for <em>H. sosnowskyi</em> populations from two geographically distant Russia regions;</p> <p>- results of experiments of model seeds launches under different wind speeds;</p> <p>- R script for exploratory statistical analysis, linear regressions and mechanistc models testing.</p> <p>The anemochorous seed dispersal was generalized with a number of empirical and mechanistic models of varying complexity. The aim of this work was to develop the simplest possible mechanistic model of <em>Heracleum sosnowskyi</em> that allows to determine the distance of seed dispersal by wind with an accuracy comparable to that of empirical measurements. We measured and compared the characteristics of the seeds (terminal velocity, mass, area, wing loading) as well as the release height for <em>H. sosnowskyi</em> populations from two geographically distant Russia regions. We tested two simplest mechanistic models: a ballistic model and a wind gradient model using identical artificial seeds with characteristics similar to those of real <em>H. sosnowskyi</em> seeds. The wind gradient model gave the best results, despite the fact that uniform in shape, weight and size artificial <em>H. sosnowskyi</em> seeds, when dropped simultaneously from the same height, fly off at different distances. This model provides an estimate of dispersal distances with an accuracy comparable to that of empirical measurements. We plan to use the presented model to develop an individual-based model that will allow us to calculate the flight distances of <em>H. sosnowskyi</em> propagules, taking into account real weather conditions in different years and in different parts of its invasion range. All primary data and R-scripts used are freely available at the Zenodo repository (https://doi.org/10.5281/zenodo.3766035).</p> <p> </p>
Blowin' in the wind: Mapping the dispersion of Metal(loid)s from Atacama Mining
<p><strong>Raw data from elemental and mineralogical analyses of surface sediments from Alto El Loa, Antofagasta Region, Chile.</strong></p> <p><strong>Blowin' in the wind: Mapping the dispersion of Metal(loid)s from Atacama Mining</strong></p> <p><strong>Authors: Nicolás C. Zanetta-Colombo<sup>1,2</sup> *, Carlos A. Manzano<sup>3,4 </sup>, Dagmar Brombierstäudl<sup>1</sup>, Zoë L. Fleming<sup>5,6</sup>, Eugenia M. Gayo<sup>6,7</sup>, David A. Rubinos<sup>8</sup>, Óscar Jerez<sup>9</sup>, Jorge Valdés<sup>10</sup>, Manuel Prieto<sup>11,12</sup>, Marcus Nüsser<sup>1,2</sup></strong></p> <p><strong><sup>1</sup></strong><sup> </sup>Department of Geography, South Asia Institute, Heidelberg University, Heidelberg, Germany.</p> <p><strong><sup>2</sup></strong><sup> </sup>Heidelberg Center for the Environment (HCE), Heidelberg University, Heidelberg, Germany.</p> <p><strong><sup>3</sup></strong><sup> </sup>Departamento de Química, Facultad de Ciencias, Universidad de Chile, Santiago, Chile.</p> <p><strong><sup>4</sup></strong><sup> </sup>School of Public Health, San Diego State University, San Diego, CA, USA</p> <p><strong><sup>5</sup></strong><sup> </sup>Centro de Investigación en Tecnologías para la Sociedad, Universidad Del Desarrollo, Santiago, Chile.</p> <p><strong><sup>6</sup></strong><sup> </sup>Center for Climate and Resilience Research (CR)2, Chile.</p> <p><strong><sup>7</sup></strong><sup> </sup>Departamento de Geografía, Universidad de Chile, Santiago, Chile.</p> <p><strong><sup>8</sup></strong><sup> </sup>Sustainable Minerals Institute–International Centre of Excellence Chile (SMI-ICE-Chile), The University of Queensland, Australia, Las Condes, Santiago, Chile.</p> <p><strong><sup>9</sup></strong><sup> </sup>Instituto de Geología Económica Aplicada (GEA), University of Concepción, Chile. Barrio Universitario S/N, Concepción, Chile.</p> <p><strong><sup>10</sup></strong><sup> </sup>Laboratorio de Sedimentología y Paleoambientes (LASPAL), Instituto de Ciencias Naturales Alexander von Humboldt, Facultad de Ciencias del Mar y de Recursos Biológicos, Universidad de Antofagasta, Antofagasta, Chile.</p> <p><strong><sup>11 </sup></strong>Millenium Nucleus in Andean Peatlands (AndesPeat), Chile</p> <p><strong><sup>12 </sup></strong>Departamento de Ciencias Históricas y Geográficas, Universidad de Tarapacá, 18 de Septiembre 2222, Arica, Chile</p> <p> </p> <p><strong><span>Data Set 1 (ds1): </span></strong><span>Elemental concentrations (mg/kg) of metal(loid)s in surface sediment samples. The dataset also includes geographic coordinates (LONG, LAT), distance to the nearest mines (Dist_mines), distance to tailings (Dist_tailing), and buffer zone classifications for tailings (Buffer_T) and mines (Buffer_M).</span></p> <p><strong>Data set 2 (ds2)</strong>: Mineralogical composition of selected surface sediment samples. </p>
Data from: Mechanisms of dispersal and colonisation in a wind-borne cereal pest, the haplodiploid wheat curl mite
<p><strong>Filename: </strong>1_Allele_freq</p> <p>Variables:</p> <p>1. marker_id - Name of the microsatellite marker analysed<br> 2. regime - Experimental regime (low heterozygosity - LH; medium heterozygosity - MH; high heterozygosity - HH)<br> 3. allele frequency - The frequency of alleles occurrence in the tested populations</p> <p><strong>Filename: </strong>2_Pattern_of_plants_infestation</p> <p>Variables:</p> <p>1. regime - Experimental regime (low heterozygosity - LH; medium heterozygosity - MH; high heterozygosity - HH)<br> 2. rep.id - Repetition ID<br> 3. mites.no - Number of mites found on one plant<br> 4. plant.no - Number of plant examinated<br> </p> <p><strong>Filename: </strong>3_Dispersal_colonisation_data</p> <p>Variables:</p> <p>1. regime - Experimental regime (low heterozygosity - LH; medium heterozygosity - MH; high heterozygosity - HH)<br> 2. rep.no - Number of repetition within regime<br> 3. rep.id - Repetition ID<br> 4. mite.id - Individual mite ID<br> 5. plant.no - Number of plant examinated<br> 6. dds - Developmental stage of dispersing individual<br> 7. egg.no - Number of eggs laid<br> 8. F1_f.sex - Number of individuals developing into females<br> 9. F1_m.sex - Number of individuals developing into males</p> <p> </p> <p><strong>Filename: </strong>4_Sex_ratio</p> <p>Variables:</p> <p>1. regime - Experimental regime (low heterozygosity - LH; medium heterozygosity - MH; high heterozygosity - HH)<br> 2. source - The source of the tested population (predisperal or postdispersal)<br> 3. rep.id - Repetition ID<br> 4. females.no - Number of females found in a population<br> 5. males.no - Number of males found in a population</p>
Data for: The influence of vegetation structure on secondary diaspore dispersal by wind
<p><span>The role of vegetation structure in relation to wind speed and diaspore attributes on secondary diaspore dispersal by wind has not </span><span>been empirically studied</span><span>. </span><span>Here, we investigated secondary dispersal by wind of diaspores placed in </span><span>12</span><span> different kinds of vegetation</span><span> and bare land</span><span>. The experiments were conducted in a wind tunnel using a range of wind speeds and diaspores that differed in mass and kind of appendages. </span><span>The explanations of wind speed, diaspore attribute</span><span>s</span><span>, vegetation coverage, life-form, vertical </span><span>pattern </span><span>and horizontal pattern for diaspore dispersal capacity were 6.67~10.40%, 16.13~20.53%, </span><span>6.227~</span><span>24.64%, 0.10%, 0.74%, and 0.10%, respectively. </span><span>Compared with wind speed and diaspore attributes, vegetation coverage contributed the most to diaspore dispersal capacity when vegetation coverage was low (</span><span><10% in our study). However</span><span>, but with a high (10-30%) coverage, vegetation coverage was the least influential factor in secondary diaspore dispersal by wind. V</span><span>egetation coverage </span><span>significantly </span><span>interact</span><span>ed with</span> <span>vegetation life-form, horizontal pattern and vertical pattern </span><span>on affecting</span><span> diaspore dispersal capacity. </span><span>Thus,</span><span> the most influential factor determining secondary diaspore dispersal by wind is vegetation coverage.</span></p>
Data for: The influence of vegetation structure on secondary diaspore dispersal by wind
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Data from: Covariation in abscission force and terminal velocity of wind-borne sibling seeds alters long distance dispersal projections
1. Despite the fact that seeds are unlikely to be identical—even among siblings within a maternal individual—dispersal models typically use one mean trait value to represent the ability of an entire species to disperse. Previous work has shown that the environmental conditions under which individuals leave the maternal site strongly affect how far seeds will travel. However, less is known about how trait variation within individuals contributes to dispersal or how such variation might interact with abiotic factors. 2. Here, we develop the use of an ergometer in a novel application to investigate variation in seed traits, specifically the force required for seed abscission and seed terminal velocity, exhibited by seeds from different locations within maternal capitula of the invasive species Carduus nutans (Asteraceae). 3. We find that seeds from the center of capitula are significantly easier to liberate and have slower falling velocities than siblings found near the edge of capitula. When abscission force is positively correlated with terminal velocity, slowly falling, easily abscised seeds are projected to travel much further than the average seed on slow winds. 4. Our experimental and theoretical results, which together show that within-individual variation can strongly affect model projections of species dispersal, have important implications for our broader understanding of population spread rates, the spatial structure of populations, metapopulation connectivity, and gene flow in the landscape.
Data from: Wind dispersal is predicted by tree, not diaspore, traits in comparisons of neotropical species
1. The seed shadow created by wind dispersal around parent trees may be affected by functional traits, as well as wind conditions and surrounding vegetation. 2. This study of one mature tree each of 12 Neotropical species determined the extent to which species variation in diaspore traits vs. tree height and crop size explains (1) rate of diaspore descent in still air, (2) distributions of diaspores dispersed from a 40-m tower in the forest, and (3) natural seed shadows around the parent tree. 3. A model of diaspore wing-loading to a fitted power explained 66.9% of the variation among species in the geometric mean rate of descent in still air. For a subset of four species, expected dispersal distance was not correlated with actual dispersal distance from the forest tower. For a subset of seven species, variation in wing-loading1/2 of individual diaspores explained ≤4.3% of the dispersal distance from the parent tree. 4. Measured seed shadows, particularly their distribution edges and area, differed significantly among the 12 species (range in maximum tree height 19–42 m), and were best fit by 12 separate anisotropic dispersal kernels and surveyed fecundities. Measured mean distance was highly correlated with simulated distances from the kernels. 5. The best models, explaining 57.6% of the variation among species in shadow area, and 59.6, 61.6, and 61.7% of variation in mean, median and maximum distances, included maximum tree height, either alone or in combination with crop size, and not diaspore rate of descent. 6. Among 10 species, seed shadow area was not related to rank of seedling shade tolerance. In their highly skewed distributions, most seeds were much closer than the distance of greatest seedling recruitment and in very high density, thus enhancing later density- and/or distance-related seedling mortality. 7. Tree functional traits, rather than the historically emphasized diaspore traits, explain distance distributions of these wind-dispersed species. Additional exploration of diaspore abscission in relation to wind and the influence of wind patterns after release are needed.
Data from: Pollen dispersal in fragmented populations of the dioecious wind-pollinated tree, Allocasuarina verticillata (drooping sheoak, drooping she-oak; Allocasuarinaceae)
Vegetation clearing, land modification and agricultural intensification have impacted on many ecological communities around the world. Understanding how species respond to fragmentation and the scales over which functionality is retained, can be critical for managing biodiversity in agricultural landscapes. Allocasuarina verticillata (drooping sheoak, drooping she-oak) is a dioecious, wind-pollinated and -dispersed species with key conservation values across southeastern Australia. But vegetation clearing associated with agricultural expansion has reduced the abundance and spatial distribution of this species in many regions. Spatial genetic structure, relatedness among trees, pollen dispersal and mating patterns were examined in fragmented A. verticillata populations selected to represent the types of remnants that now characterise this species. Short scale spatial genetic structure (5–25 m) and relatedness among trees were observed in most populations. Unexpectedly, the two male trees closest to each female did not have a reproductive advantage accounting for only 4–15% of the seed produced in larger populations. Biparental inbreeding was also generally low (<4%) with limited evidence of seed crop domination by some male trees. More male trees contributed to seed crops in linear remnants (mean 17) compared to those from patch remnants (mean 11.3) which may reflect differences in pollen dispersal within the two remnant types. On average, pollen travels ~100 m irrespective of remnant type but was also detected to have dispersed as far as 1 km in open landscapes. Low biparental inbreeding, limited reproductive assurance for near-neighbour and probably related males and variability in the distances over which females sample pollen pools suggest that some mechanism to prevent matings between relatives exists in this species.
FIGURES 18–23 in Gone with the wind: westward dispersal across the Indian Ocean and island speciation in Hemicordulia dragonflies (Odonata: Corduliidae)
FIGURES 18–23. Distribution of discussed genera. The courses of storms from May to November in the northern hemisphere and November to May in the southern hemisphere are indicated by arrows (after Times Books 1997). (18) Hemicordulia and Procordulia dragonflies, pale shading: main range in Australasia and Pacific; dark shading: H. africana n. sp.; crosses and pale shading: H. similis; square: H. virens; circle: H. atrovirens n. sp.; (19) Teinobasis damselflies, pale shading: main range in Australasia and Pacific; dark shading: T. alluaudi; (20) Collocalia swiftlets; (21) Copsychus magpie robins; (22) Hypsipetes bulbuls; (23) Pteropus flying foxes.
FIGURES 2–11. 2–6 in Gone with the wind: westward dispersal across the Indian Ocean and island speciation in Hemicordulia dragonflies (Odonata: Corduliidae)
FIGURES 2–11. 2–6, Male appendages of Hemicordulia species in dorsal view. (2) H. asiatica; (3) H. virens; (4) H. atrovirens n. sp.; (5) H. similis; (6) H. africana n. sp.; 7–11, Male appendages of Hemicordulia species in lateral view. (7) H. asiatica; (8) H. virens; (9) H. atrovirens n. sp.; (10) H. similis; (11) H. africana n. sp.
FIGURES 12–17. Vulvar scale and S9 in Gone with the wind: westward dispersal across the Indian Ocean and island speciation in Hemicordulia dragonflies (Odonata: Corduliidae)
FIGURES 12–17. Vulvar scale and S9 of Hemicordulia species in ventral view. (12) H. asiatica; (13) H. virens; (14) H. atrovirens n. sp.; (15) aberrant H. similis (cf. Fraser 1949); (16) typical H. similis; (17) H. africana n. sp.
FIGURES 24–25 in Gone with the wind: westward dispersal across the Indian Ocean and island speciation in Hemicordulia dragonflies (Odonata: Corduliidae)
FIGURES 24–25. Geographic (24) and altitudinal (25) distribution of H. africana n. sp. relative to large water bodies. Filled circles are known records (present paper), open circles forested localities near large waterbodies that have recently been intensively surveyed by V. Clausnitzer (pers. comm.), except Mbala by Pinhey (1984). Many sites in the region away from large water bodies have also been researched. A line connects each site to the altitude of the nearest large water body.
Data associated with studies on wind and phoretic dispersal of crapemyrtle bark scale
<p>These are data associated with studies on the wind-mediated and phoretic dispersal of crapemyrtle bark scale.</p>
Wind dispersal and 1-year survival of Vataireopsis iglesiasii (Fabaceae) seedlings in a Neotropical lowland rain forest
<p>Populations of many tropical tree species are regulated by negative distance- and density-dependent processes (NDD), yet most studies on the effects of conspecific seedling and adult neighbours on seedling survival have focused on animal-dispersed species. Species with seeds dispersed by wind may not be moved as far on average as seeds dispersed by animals, but some seeds may be dispersed a lot further, suggesting that knowledge of dispersal mechanism may help in our understanding of NDD. In this study, we took advantage of a high-fecundity reproductive event that occurred for an individual isolated canopy tree of Vataireopsis iglesiasii in a tropical lowland rain forest site in Amazonian Ecuador to document seed dispersal and seedling survival to 1-year post-dispersal. Most seeds did not disperse far: 86% of germinated seedlings were found within 100 m. Mortality was high: only 49 of the 1732 monitored seedlings survived one year and only five survived a further four years. We found a significant negative effect of conspecific seedling density (but no effect of distance from the parent tree) on 1-year survival. Rare long-distance dispersal events may increase the probability of a seed reaching specific habitats, such as high-light patches, and surviving beyond one year, thereby shifting the population recruitment curve outwards away from adult trees and maintaining diversity in species-rich forests.</p>
Apendices(Effect of Vegetation Structure on Secondary Wind Dispersal Distance of Diaspores)
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Data from: Wind dispersal is predicted by tree, not diaspore, traits in comparisons of neotropical species
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Data from: Covariation in abscission force and terminal velocity of wind-borne sibling seeds alters long distance dispersal projections
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Wind dispersal and 1-year survival of Vataireopsis iglesiasii (Fabaceae) seedlings in a Neotropical lowland rain forest
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Data from: Pollen dispersal in fragmented populations of the dioecious wind-pollinated tree, Allocasuarina verticillata (drooping sheoak, drooping she-oak; Allocasuarinaceae)
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