1. |
- Kattge, Jens, et al.
(author)
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TRY plant trait database - enhanced coverage and open access
- 2020
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In: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Journal article (peer-reviewed)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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2. |
- Zakhozhay, Olga, et al.
(author)
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Radial Velocity Survey for Planets around Young stars (RVSPY) Target characterisation and high-cadence survey
- 2022
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 667
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Journal article (peer-reviewed)abstract
- Context. The occurrence rate and period distribution of (giant) planets around young stars is still not as well constrained as for older main-sequence stars. This is mostly due to the intrinsic activity-related complications and the avoidance of young stars in many large planet search programmes. Yet, dynamical restructuring processes in planetary systems may last significantly longer than the actual planet formation phase and may well extend long into the debris disc phase, such that the planet populations around young stars may differ from those observed around main-sequence stars.Aims. We introduce our Radial Velocity Survey for Planets around Young stars (RVSPY), which is closely related to the NaCo-ISPY direct imaging survey, characterise our target stars, and search for substellar companions at orbital separations smaller than a few au from the host star.Methods. We used the FEROS spectrograph, mounted to the MPG/ESO 2.2 m telescope in Chile, to obtain high signal-to-noise spectra and time series of precise radial velocities (RVs) of 111 stars, most of which are surrounded by debris discs. Our target stars have spectral types between early F and late K, a median age of 400 Myr, and a median distance of 45 pc. During the initial reconnaissance phase of our survey, we determined stellar parameters and used high-cadence observations to characterise the intrinsic stellar activity, searched for hot companions with orbital periods of up to 10 days, and derived the detection thresholds for longer-period companions. In our analysis we, have included archival spectroscopic data, spectral energy distribution, and data for photometric time series from the TESS mission.Results. For all target stars we determined their basic stellar parameters and present the results of the high-cadence RV survey and activity characterisation. We have achieved a median single-measurement RV precision of 6 m s−1 and derived the short-term intrinsic RV scatter of our targets (median 23 m s−1), which is mostly caused by stellar activity and decays with an age from >100 m s−1 at <20 Myr to <20 m s−1 at >500 Myr. We analysed time series periodograms of the high-cadence RV data and the shape of the individual cross-correlation functions. We discovered six previously unknown close companions with orbital periods between 10 and 100 days, three of which are low-mass stars, and three are in the brown dwarf mass regime. We detected no hot companion with an orbital period <10 days down to a median mass limit of ~1 MJup for stars younger than 500 Myr, which is still compatible with the established occurrence rate of such companions around main-sequence stars. We found significant RV periodicities between 1.3 and 4.5 days for 14 stars, which are, however, all caused by rotational modulation due to starspots. We also analysed the data for TESS photometric time series and found significant periodicities for most of the stars. For 11 stars, the photometric periods are also clearly detected in the RV data. We also derived stellar rotation periods ranging from 1 to 10 days for 91 stars, mostly from the TESS data. From the intrinsic activity-related short-term RV jitter, we derived the expected mass-detection thresholds for longer-period companions, and selected 84 targets for the longer-term RV monitoring.
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3. |
- Ried, Janina S., et al.
(author)
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A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape
- 2016
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
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Journal article (peer-reviewed)abstract
- Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.
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