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Sökning: WFRF:(Rosell J)

  • Resultat 1-10 av 71
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  • Thomas, H. J. D., et al. (författare)
  • Global plant trait relationships extend to the climatic extremes of the tundra biome
  • 2020
  • Ingår i: Nature Communications. - : Nature Publishing Group. - 2041-1723 .- 2041-1723. ; 11:1
  • Tidskriftsartikel (refereegranskat)abstract
    • The majority of variation in six traits critical to the growth, survival and reproduction of plant species is thought to be organised along just two dimensions, corresponding to strategies of plant size and resource acquisition. However, it is unknown whether global plant trait relationships extend to climatic extremes, and if these interspecific relationships are confounded by trait variation within species. We test whether trait relationships extend to the cold extremes of life on Earth using the largest database of tundra plant traits yet compiled. We show that tundra plants demonstrate remarkably similar resource economic traits, but not size traits, compared to global distributions, and exhibit the same two dimensions of trait variation. Three quarters of trait variation occurs among species, mirroring global estimates of interspecific trait variation. Plant trait relationships are thus generalizable to the edge of global trait-space, informing prediction of plant community change in a warming world.
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  • Thomas, H. J.D., et al. (författare)
  • Traditional plant functional groups explain variation in economic but not size-related traits across the tundra biome
  • 2019
  • Ingår i: Global Ecology and Biogeography. - : Wiley-Blackwell. - 1466-822X .- 1466-8238. ; 28:2, s. 78-95
  • Tidskriftsartikel (refereegranskat)abstract
    • Aim: Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits. Location: Tundra biome. Time period: Data collected between 1964 and 2016. Major taxa studied: 295 tundra vascular plant species. Methods: We compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species-level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post hoc clustering of species-level traits. Results: Traditional functional groups explained significant differences in trait expression, particularly amongst traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species-level trait expression. Main conclusions: Traditional functional groups only coarsely represent variation in well-measured traits within tundra plant communities, and better explain resource economic traits than size-related traits. We recommend caution when using functional group approaches to predict tundra ecosystem change, or ecosystem functions relating to plant size, such as albedo or carbon storage. We argue that alternative classifications or direct use of specific plant traits could provide new insight into ecological prediction and modelling.
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  • Farahi, A., et al. (författare)
  • Mass variance from archival X-ray properties of Dark Energy Survey Year-1 galaxy clusters
  • 2019
  • Ingår i: Monthly notices of the Royal Astronomical Society. - : OXFORD UNIV PRESS. - 0035-8711 .- 1365-2966. ; 490:3, s. 3341-3354
  • Tidskriftsartikel (refereegranskat)abstract
    • Using archival X-ray observations and a lognormal population model, we estimate constraints on the intrinsic scatter in halo mass at fixed optical richness for a galaxy cluster sample identified in Dark Energy Survey Year-One (DES-Y1) data with the redMaPPer algorithm. We examine the scaling behaviour of X-ray temperatures, T-X, with optical richness, lambda(RM), for clusters in the redshift range 0.2 < z < 0.7. X-ray temperatures are obtained from Chandra and XMM observations for 58 and 110 redMaPPer systems, respectively. Despite non-uniform sky coverage, the T-X measurements are > 50 per cent complete for clusters with lambda(RM) > 130. Regression analysis on the two samples produces consistent posterior scaling parameters, from which we derive a combined constraint on the residual scatter, sigma(ln) (T) (vertical bar) (lambda) = 0.275 +/- 0.019. Joined with constraints for T-X scaling with halo mass from the Weighing the Giants program and richness-temperature covariance estimates from the LoCuSS sample, we derive the richness-conditioned scatter in mass, sigma(ln) (M) (vertical bar) (lambda) = 0.30 +/- 0.04((stat)) +/- 0.09((sys)), at an optical richness of approximately 100. Uncertainties in external parameters, particularly the slope and variance of the T-X-mass relation and the covariance of T-X and lambda(RM) at fixed mass, dominate the systematic error. The 95 per cent confidence region from joint sample analysis is relatively broad, sigma(ln) (M) (vertical bar) (lambda) is an element of [0.14, 0.55], or a factor 10 in variance.
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6.
  • Kattge, Jens, et al. (författare)
  • TRY plant trait database - enhanced coverage and open access
  • 2020
  • Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
  • Tidskriftsartikel (refereegranskat)abstract
    • 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.
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7.
  • Grandis, S., et al. (författare)
  • Validation of selection function, sample contamination and mass calibration in galaxy cluster samples
  • 2020
  • Ingår i: Monthly notices of the Royal Astronomical Society. - 0035-8711 .- 1365-2966. ; 498:1, s. 771-798
  • Tidskriftsartikel (refereegranskat)abstract
    • We construct and validate the selection function of the MARD-Y3 galaxy cluster sample. This sample was selected through optical follow-up of the 2nd ROSAT faint source catalogue with Dark Energy Survey year 3 data. The selection function is modelled by combining an empirically constructed X-ray selection function with an incompleteness model for the optical follow-up. We validate the joint selection function by testing the consistency of the constraints on the X-ray flux–mass and richness–mass scaling relation parameters derived from different sources of mass information: (1) cross-calibration using South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) clusters, (2) calibration using number counts in X-ray, in optical and in both X-ray and optical while marginalizing over cosmological parameters, and (3) other published analyses. We find that the constraints on the scaling relation from the number counts and SPT-SZ cross-calibration agree, indicating that our modelling of the selection function is adequate. Furthermore, we apply a largely cosmology independent method to validate selection functions via the computation of the probability of finding each cluster in the SPT-SZ sample in the MARD-Y3 sample and vice versa. This test reveals no clear evidence for MARD-Y3 contamination, SPT-SZ incompleteness or outlier fraction. Finally, we discuss the prospects of the techniques presented here to limit systematic selection effects in future cluster cosmological studies.
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8.
  • Drlica-Wagner, A., et al. (författare)
  • SEARCH FOR GAMMA-RAY EMISSION FROM DES DWARF SPHEROIDAL GALAXY CANDIDATES WITH FERMI-LAT DATA
  • 2015
  • Ingår i: Astrophysical Journal Letters. - 2041-8205 .- 2041-8213. ; 809:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Due to their proximity, high dark-matter (DM) content, and apparent absence of non-thermal processes, Milky Way dwarf spheroidal satellite galaxies (dSphs) are excellent targets for the indirect detection of DM. Recently, eight new dSph candidates were discovered using the first year of data from the Dark Energy Survey (DES). We searched for gamma-ray emission coincident with the positions of these new objects in six years of Fermi Large Area Telescope data. We found no significant excesses of gamma-ray emission. Under the assumption that the DES candidates are dSphs with DM halo properties similar to the known dSphs, we computed individual and combined limits on the velocity-averaged DM annihilation cross section for these new targets. If the estimated DM content of these dSph candidates is confirmed, they will constrain the annihilation cross section to lie below the thermal relic cross section for DM particles with masses less than or similar to 20 GeV annihilating via the b (b) over bar or pi(+)pi(-) channels.
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9.
  • Fresard, Laure, et al. (författare)
  • Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts
  • 2019
  • Ingår i: Nature Medicine. - : NATURE PUBLISHING GROUP. - 1078-8956 .- 1546-170X. ; 25:6, s. 911-919
  • Tidskriftsartikel (refereegranskat)abstract
    • It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene(1). The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches(2-5). For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases(6-8). This includes muscle biopsies from patients with undiagnosed rare muscle disorders(6,9), and cultured fibroblasts from patients with mitochondrial disorders(7). However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We developed a robust approach to compare data from these individuals with large sets of RNA-seq data for controls (n = 1,594 unrelated controls and n = 49 family members) and demonstrated the impacts of expression, splicing, gene and variant filtering strategies on disease gene identification. Across our cohort, we observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution.
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