12 research outputs found
Consistent patterns of common species across tropical tree communities
Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees
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MULPEX: A compact multi-layered polymer foil collector for micrometeoroids and orbital debris
Detailed studies of preserved hypervelocity impact residues on spacecraft multi-layer insulation foils have yielded important information about the flux of small particles from different sources in low-Earth orbit (LEO). We have extended our earlier research on impacts occurring in LEO to design and testing of a compact capture device. MUlti-Layer Polymer EXperiment (MULPEX) is simple, cheap to build, lightweight, of no power demand, easy to deploy, and optimised for the efficient collection of impact residue for analysis on return to Earth. The capture medium is a stack of very thin (8 and 40 mu m) polyimide foils, supported on polytetrafluoroethylene sheet frames, surrounded by a protective aluminium casing. The uppermost foil has a very thin metallic coating for thermal protection and resistance to atomic oxygen and ultra-violet exposure. The casing provides a simple detachable interface for deployment on the spacecraft, facing into the desired direction for particle collection. On return to the laboratory, the stacked foils are separated for examination in a variable pressure scanning electron microscope, without need for surface coating. Analysis of impact residue is performed using energy dispersive X-ray spectrometers. Our laboratory experiments, utilising buck-shot firings of analogues to micrometeoroids (35-38 mu m olivine) and space debris (4 mu m alumina and 1 mm stainless steel) in a light gas gun, have shown that impact residue is abundant within the foil layers, and preserves a record of the impacting particle, whether of micrometer or millimetre dimensions. Penetrations of the top foil are easily recognised, and act as a proxy for dimensions of the penetrating particle. Impact may cause disruption and melting, but some residue retains sufficient crystallographic structure to show clear Raman lines, diagnostic of the original mineral. (c) 2005 Published by Elsevier Ltd on behalf of COSPAR
Influence of Initial Riboflavin Content on Retention in Pasta During Photodegradation and Cooking
ARE WE MAKING PROGRESS IN THE MANAGEMENT OF CYTOTOXIC DRUG–INDUCED NAUSEA AND VOMITING?
Learning the Edit Costs of Graph Edit Distance Applied to Ligand-Based Virtual Screening
sPlotOpen – An environmentally balanced, open-access, global dataset of vegetation plots
Motivation: Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained: Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain: Global, 0.01–40,000 m². Time period and grain: 1888–2015, recording dates. Major taxa and level of measurement: 42,677 vascular plant taxa, plot-level records. Software format: Three main matrices (.csv), relationally linked