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Knowledge about the biogeographic affinities of the world’s tropical forests helps to better understand regional differences in forest structure, diversity, composition, and dynamics. Such understanding will enable anticipation of region-specific responses to global environmental change. Modern phylogenies, in combination with broad coverage of species inventory data, now allow for global biogeographic analyses that take species evolutionary distance into account. Here we present a classification of the world’s tropical forests based on their phylogenetic similarity. We identify five principal floristic regions and their floristic relationships: (i) Indo-Pacific, (ii) Subtropical, (iii) African, (iv) American, and (v) Dry forests. Our results do not support the traditional neo- versus paleotropical forest division but instead separate the combined American and African forests from their Indo-Pacific counterparts. We also find indications for the existence of a global dry forest region, with representatives in America, Africa, Madagascar, and India. Additionally, a northern-hemisphere Subtropical forest region was identified with representatives in Asia and America, providing support for a link between Asian and American northern-hemisphere forests.
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.
A data-driven method was applied to Au+Au collisions at √sNN = 200 GeV made with the STAR detector at RHIC to isolate pseudorapidity distance η-dependent and η-independent correlations by using two- and four-particle azimuthal cumulant measurements. We identified a η-independent component of the correlation, which is dominated by anisotropic flow and flow fluctuations. It was also found to be independent of η within the measured range of pseudorapidity |η| < 1. In 20–30% central Au+Au collisions, the relative flow fluctuation was found to be 34%±2%(stat.)±3%(sys.) for particles with transverse momentum pT less than 2 GeV/c. The η-dependent part, attributed to nonflow correlations, is found to be 5% ± 2%(sys.) relative to the flow of the measured second harmonic cumulant at |η| > 0.7.
We report results on the ratio of midrapidity antiproton-to-proton yields in Au+Au collisions at sqrt[sNN] = 130 GeV per nucleon pair as measured by the STAR experiment at RHIC. Within the rapidity and transverse momentum range of | y|<0.5 and 0.4<pt<1.0 GeV/c, the ratio is essentially independent of either transverse momentum or rapidity, with an average of 0.65±0.01(stat)±0.07(syst) for minimum bias collisions. Within errors, no strong centrality dependence is observed. The results indicate that at this RHIC energy, although the p-p-bar pair production becomes important at midrapidity, a significant excess of baryons over antibaryons is still present.
The first measurements of light antinucleus production in Au+Au collisions at the Relativistic Heavy-Ion Collider are reported. The observed production rates for d-bar and 3He-bar are much larger than in lower energy nucleus-nucleus collisions. A coalescence model analysis of the yields indicates that there is little or no increase in the antinucleon freeze-out volume compared to collisions at CERN SPS energy. These analyses also indicate that the 3He-bar freeze-out volume is smaller than the d-bar freeze-out volume.
We present the first measurement of midrapidity vector meson phi production in Au+Au collisions at RHIC (sqrt[sNN]=130 GeV) from the STAR detector. For the 11% highest multiplicity collisions, the slope parameter from an exponential fit to the transverse mass distribution is T=379±50(stat)±45(syst) MeV, the yield dN/dy=5.73±0.37(stat)±0.69(syst) per event, and the ratio N phi /Nh- is found to be 0.021±0.001(stat)±0.004(syst). The measured ratio N phi /Nh- and T for the phi meson at midrapidity do not change for the selected multiplicity bins.
We report the first measurement of inclusive antiproton production at midrapidity in Au+Au collisions at sqrt[sNN] = 130 GeV by the STAR experiment at RHIC. The antiproton transverse mass distributions in the measured transverse momentum range of 0.25<pperp<0.95 GeV/c are found to fall less steeply for more central collisions. The extrapolated antiproton rapidity density is found to scale approximately with the negative hadron multiplicity density.
The STAR Collaboration reports the first observation of exclusive rho 0 photoproduction, AuAu-->AuAu rho 0, and rho 0 production accompanied by mutual nuclear Coulomb excitation, AuAu-->Au [star] Au [star] rho 0, in ultraperipheral heavy-ion collisions. The rho 0 have low transverse momenta, consistent with coherent coupling to both nuclei. The cross sections at sqrt[sNN]=130 GeV agree with theoretical predictions treating rho 0 production and Coulomb excitation as independent processes.