Production properties of K*(892) vector mesons and their spin alignment as measured in the NOMAD experiment

First measurements of K*(892) mesons production properties and their spin alignment in nu_mu charged current (CC) and neutral current (NC) interactions are presented. The analysis of the full data sample of the NOMAD experiment is performed in different kinematic regions. For K*+ and K*- mesons produced in nu_mu CC interactions and decaying into K0 pi+/- we have found the following yields per event: (2.6 +/- 0.2 (stat.) +/- 0.2 (syst.))% and (1.6 +/- 0.1 (stat.) +/- 0.1 (syst.))% respectively, while for the K*+ and K*- mesons produced in nu NC interactions the corresponding yields per event are: (2.5 +/- 0.3 (stat.) +/- 0.3 (syst.))% and (1.0 +/- 0.3 (stat.) +/- 0.2 (syst.))%. The results obtained for the rho00 parameter, 0.40 +/- 0.06 (stat) +/- 0.03 (syst) and 0.28 +/- 0.07 (stat) +/- 0.03 (syst) for K*+ and K*- produced in nu_mu CC interactions, are compared to theoretical predictions tuned on LEP measurements in e+e- annihilation at the Z0 pole. For K*+ mesons produced in nu NC interactions the measured rho00 parameter is 0.66 +/- 0.10 (stat) +/- 0.05 (syst).Comment: 20 p

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+. Though broad scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8–50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass (AGB) at spatial grains ranging from 5 to 250m (0.025–6.25 ha), and we evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that the spatial sampling error in AGB is large for standard plot sizes, averaging 46.3% for 0.1 ha subplots and 16.6% for 1 ha subplots. Topographically heterogeneous sites showed positive spatial autocorrelation in AGB at scales of 100m and above; at smaller scales, most study sites showed negative or nonexistent spatial autocorrelation in AGB. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGB leads to a substantial “dilution” bias in calibration parameters, a bias that cannot be removed with current statistical methods. Overall, our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise

A study of strange particle production in νμ\nu_\mu charged current interactions in the NOMAD experiment

NeutrinosA study of strange particle production in $\nu_\mu$ charged current interactions has been performed using the data from the NOMAD experiment. Yields of neutral strange particles (\ko, \lam, \alam) have been measured. Mean multiplicities are reported as a function of the event kinematic variables $E_\nu$, $W^2$ and $Q^2$ as well as of the variables describing particle behaviour within a hadronic jet: $x_F$, $z$ and $p_T^2$. Decays of resonances and heavy hyperons with identified \ko and \lam in the final state have been analyzed. Clear signals corresponding to $\rm {K^\star}^\pm$ $\rm {\Sigma^\star}^\pm$, $\rm \Xi^-$ and $\rm \Sigma^0$ have been observed

Search for a new gauge boson in π0\pi^{0} decays

A search was made for a new light gauge boson $X$ which might be produced in $\pi^{0}\to\gamma + X$ decay from neutral pions generated by 450-GeV protons in the CERN SPS neutrino target. The X's would penetrate the downstream shielding and be observed in the NOMAD detector via the Primakoff effect, in the process of $X \to\pi^{0}$ conversion in the external Coulomb field of a nucleus. With $1.45\times10^{18}$ protons on target, 20 candidate events with energy between 8 and 140 GeV were found from the analysis of neutrino data. This number is in agreement with the expectation of 18.1$\pm$2.8 background events from standard neutrino processes. A new 90% C.L. upper limit on the branching ratio $Br(\pi^{0}\to\gamma + X)< (3.3 to 1.9) \times10^{-5}$ for $X$ masses ranging from 0 to 120 MeV/c^2 is obtained.Comment: 15 pages, LaTex, 6 eps figures included, submitted to Physics Letters

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Gender differences in the use of cardiovascular interventions in HIV-positive persons; the D:A:D Study

Peer reviewe

Hyperdominance in Amazonian Forest Carbon Cycling

While Amazonian forests are extraordinarily diverse, the abundance of trees is skewed strongly towards relatively few ‘hyperdominant’ species. In addition to their diversity, Amazonian trees are a key component of the global carbon cycle, assimilating and storing more carbon than any other ecosystem on Earth. Here we ask, using a unique data set of 530 forest plots, if the functions of storing and producing woody carbon are concentrated in a small number of tree species, whether the most abundant species also dominate carbon cycling, and whether dominant species are characterized by specific functional traits. We find that dominance of forest function is even more concentrated in a few species than is dominance of tree abundance, with only ≈1% of Amazon tree species responsible for 50% of carbon storage and productivity. Although those species that contribute most to biomass and productivity are often abundant, species maximum size is also influential, while the identity and ranking of dominant species varies by function and by region