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- Benzylbenzofuran (1)
- Chalcone (1)
- Cytotoxicity (1)
- Dorstenia kameruniana (1)
- Eurasian Dry Grassland Group (EDGG) (1)
- European Vegetation Archive (EVA) (1)
- Furanocoumarin (1)
- GrassPlot (1)
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- animal movement (1)
GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001;... 1,000 m(2)) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database " sPlot". Its main aim is to facilitate studies on the scale-and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board.
Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area
) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.
Moving in the Anthropocene
(2018)
Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.
We present a catalogue of white dwarf candidates selected from the second data release of Gaia (DR2). We used a sample of spectroscopically confirmed white dwarfs from the Sloan Digital Sky Survey (SDSS) to map the entire space spanned by these objects in the Gaia Hertzsprung–Russell diagram. We then defined a set of cuts in absolute magnitude, colour, and a number of Gaia quality flags to remove the majority of contaminating objects. Finally, we adopt a method analogous to the one presented in our earlier SDSS photometric catalogues to calculate a probability of being a white dwarf (PWD) for all Gaia sources that passed the initial selection. The final catalogue is composed of 486641 stars with calculated PWD from which it is possible to select a sample of ≃260000 high-confidence white dwarf candidates in the magnitude range 8 < G < 21. By comparing this catalogue with a sample of SDSS white dwarf candidates, we estimate an upper limit in completeness of 85 per cent for white dwarfs with G ≤ 20 mag and Teff >7000 K, at high Galactic latitudes (|b| > 20°). However, the completeness drops at low Galactic latitudes, and the magnitude limit of the catalogue varies significantly across the sky as a function of Gaia’s scanning law. We also provide the list of objects within our sample with available SDSS spectroscopy. We use this spectroscopic sample to characterize the observed structure of the white dwarf distribution in the H–R diagram.
Chromatographic separation of the extract of the roots of Dorstenia kameruniana (family Moraceae) led to the isolation of three new benzylbenzofuran derivatives, 2-(p-hydroxybenzyl)benzofuran-6-ol (1), 2-(p-hydroxybenzyl)-7-methoxybenzofuran-6-ol (2) and 2-(p-hydroxy)-3-(3-methylbut-2-en-1-yl)benzyl)benzofuran-6-ol (3) (named dorsmerunin A, B and C, respectively), along with the known furanocoumarin, bergapten (4). The twigs of Dorstenia kameruniana also produced compounds 1-4 as well as the known chalcone licoagrochalcone A (5). The structures were elucidated by NMR spectroscopy and mass spectrometry. The isolated compounds displayed cytotoxicity against the sensitive CCRF-CEM and multidrug-resistant CEM/ADR5000 leukemia cells, where compounds 4 and 5 had the highest activities (IC50 values of 7.17 mu M and 5.16 mu M, respectively) against CCRF-CEM leukemia cells. Compound 5 also showed cytotoxicity against 7 sensitive or drug-resistant solid tumor cell lines (breast carcinoma, colon carcinoma, glioblastoma), with IC50 below 50 mu M, whilst 4 showed selective activity.