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

Refined physical parameters for Chariklo's body and rings from stellar occultations observed between 2013 and 2020

Context. The Centaur (10199) Chariklo has the first ring system discovered around a small object. It was first observed using stellar occultation in 2013. Stellar occultations allow sizes and shapes to be determined with kilometre accuracy, and provide the characteristics of the occulting object and its vicinity. Aims. Using stellar occultations observed between 2017 and 2020, our aim is to constrain the physical parameters of Chariklo and its rings. We also determine the structure of the rings, and obtain precise astrometrical positions of Chariklo. Methods. We predicted and organised several observational campaigns of stellar occultations by Chariklo. Occultation light curves were measured from the datasets, from which ingress and egress times, and the ring widths and opacity values were obtained. These measurements, combined with results from previous works, allow us to obtain significant constraints on Chariklo's shape and ring structure. Results. We characterise Chariklo's ring system (C1R and C2R), and obtain radii and pole orientations that are consistent with, but more accurate than, results from previous occultations. We confirm the detection of W-shaped structures within C1R and an evident variation in radial width. The observed width ranges between 4.8 and 9.1 km with a mean value of 6.5 km. One dual observation (visible and red) does not reveal any differences in the C1R opacity profiles, indicating a ring particle size larger than a few microns. The C1R ring eccentricity is found to be smaller than 0.022 (3σ), and its width variations may indicate an eccentricity higher than ~0.005. We fit a tri-axial shape to Chariklo's detections over 11 occultations, and determine that Chariklo is consistent with an ellipsoid with semi-axes of 143.8-1.5+1.4, 135.2-2.8+1.4, and 99.1-2.7+5.4 km. Ultimately, we provided seven astrometric positions at a milliarcsecond accuracy level, based on Gaia EDR3, and use it to improve Chariklo's ephemeris.Fil: Morgado, B.E.. Centre National de la Recherche Scientifique. Observatoire de Paris; Francia. Ministério de Ciencia, Tecnologia e Innovacao. Observatorio Nacional; BrasilFil: Sicardy, Bruno. Centre National de la Recherche Scientifique. Observatoire de Paris; FranciaFil: Braga Ribas, Felipe. Ministério de Ciencia, Tecnologia e Innovacao. Observatorio Nacional; Brasil. Centre National de la Recherche Scientifique. Observatoire de Paris; Francia. Universidade Tecnologia Federal do Parana; BrasilFil: Desmars, Josselin. Centre National de la Recherche Scientifique. Observatoire de Paris; FranciaFil: Gomes Júnior, Altair Ramos. Universidade de Sao Paulo; BrasilFil: Bérard, D.. Centre National de la Recherche Scientifique. Observatoire de Paris; FranciaFil: Leiva, Rodrigo. Universidad de Chile; Chile. Centre National de la Recherche Scientifique. Observatoire de Paris; FranciaFil: Vieira Martins, Roberto. Ministério de Ciencia, Tecnologia e Innovacao. Observatorio Nacional; Brasil. Universidade Federal do Rio de Janeiro; BrasilFil: Benedetti Rossi, G.. Centre National de la Recherche Scientifique. Observatoire de Paris; Francia. Universidade Federal de Sao Paulo; BrasilFil: Santos Sanz, Pablo. Ministério de Ciencia, Tecnologia e Innovacao. Observatorio Nacional; BrasilFil: Camargo, Julio Ignacio Bueno. Ministério de Ciencia, Tecnologia e Innovacao. Observatorio Nacional; BrasilFil: Duffard, R.. Universidade Federal do Rio de Janeiro; BrasilFil: Rommel, F.L.. Ministério de Ciencia, Tecnologia e Innovacao. Observatorio Nacional; BrasilFil: Assafin, M.. Centre National de la Recherche Scientifique. Observatoire de Paris; FranciaFil: Boufleur, R.C.. Universidad Nacional de Córdoba; ArgentinaFil: Colas, F.. Ministério de Ciencia, Tecnologia e Innovacao. Observatorio Nacional; BrasilFil: Kretlow, Mike. Ministério de Ciencia, Tecnologia e Innovacao. Observatorio Nacional; BrasilFil: Beisker, W.. University of North Carolina; Estados UnidosFil: Sfair, Rafael. Centre National de la Recherche Scientifique. Observatoire de Paris; FranciaFil: Snodgrass, Colin. University of Edinburgh; Reino UnidoFil: Morales, N.. Pontificia Universidad Católica de Chile; Chile. Universidad Católica de Chile; ChileFil: Fernández Valenzuela, E.. Pontificia Universidad Católica de Chile; Chile. Universidad Católica de Chile; ChileFil: Amaral, L.S.. Massachusetts Institute of Technology; Estados UnidosFil: Amarante, A.. Ministério de Ciencia, Tecnologia e Innovacao. Observatorio Nacional; BrasilFil: Artola, R.A.. Centre National de la Recherche Scientifique. Observatoire de Paris; FranciaFil: Backes, M.. Universidad Nacional de Córdoba; ArgentinaFil: Bath, K. L.. University of North Carolina; Estados UnidosFil: Bouley, S.. University of St. Andrews; Reino UnidoFil: Garcia Lambas, Diego Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; ArgentinaFil: Schneiter, Ernesto Matías. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Departamento de Ingeniería Económica y Legal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; Argentin

Stellar occultations enable milliarcsecond astrometry for Trans-Neptunian objects and Centaurs

Trans-Neptunian objects (TNOs) and Centaurs are remnants of our planetary system formation, and their physical properties have invaluable information for evolutionary theories. Stellar occultation is a ground-based method for studying these small bodies and has presented exciting results. These observations can provide precise profiles of the involved body, allowing an accurate determination of its size and shape. The goal is to show that even single-chord detections of TNOs allow us to measure their milliarcsecond astrometric positions in the reference frame of the Gaia second data release (DR2). Accurated ephemerides can then be generated, allowing predictions of stellar occultations with much higher reliability. We analyzed data from stellar occultations to obtain astrometric positions of the involved bodies. The events published before the Gaia era were updated so that the Gaia DR2 catalog is the reference. Previously determined sizes were used to calculate the position of the object center and its corresponding error with respect to the detected chord and the International Celestial Reference System (ICRS) propagated Gaia DR2 star position. We derive 37 precise astrometric positions for 19 TNOs and 4 Centaurs. Twenty-one of these events are presented here for the first time. Although about 68\% of our results are based on single-chord detection, most have intrinsic precision at the submilliarcsecond level. Lower limits on the diameter and shape constraints for a few bodies are also presented as valuable byproducts. Using the Gaia DR2 catalog, we show that even a single detection of a stellar occultation allows improving the object ephemeris significantly, which in turn enables predicting a future stellar occultation with high accuracy. Observational campaigns can be efficiently organized with this help, and may provide a full physical characterization of the involved object.Comment: 16 pages, 28 figures. The manuscript was accepted and is to be publishe

A large topographic feature on the surface of the trans-Neptunian object (307261) 2002 MS4_4 measured from stellar occultations

This work aims at constraining the size, shape, and geometric albedo of the dwarf planet candidate 2002 MS4 through the analysis of nine stellar occultation events. Using multichord detection, we also studied the object's topography by analyzing the obtained limb and the residuals between observed chords and the best-fitted ellipse. We predicted and organized the observational campaigns of nine stellar occultations by 2002 MS4 between 2019 and 2022, resulting in two single-chord events, four double-chord detections, and three events with three to up to sixty-one positive chords. Using 13 selected chords from the 8 August 2020 event, we determined the global elliptical limb of 2002 MS4. The best-fitted ellipse, combined with the object's rotational information from the literature, constrains the object's size, shape, and albedo. Additionally, we developed a new method to characterize topography features on the object's limb. The global limb has a semi-major axis of 412 $\pm$ 10 km, a semi-minor axis of 385 $\pm$ 17 km, and the position angle of the minor axis is 121 $^\circ$ $\pm$ 16$^\circ$. From this instantaneous limb, we obtained 2002 MS4's geometric albedo and the projected area-equivalent diameter. Significant deviations from the fitted ellipse in the northernmost limb are detected from multiple sites highlighting three distinct topographic features: one 11 km depth depression followed by a 25$^{+4}_{-5}$ km height elevation next to a crater-like depression with an extension of 322 $\pm$ 39 km and 45.1 $\pm$ 1.5 km deep. Our results present an object that is $\approx$138 km smaller in diameter than derived from thermal data, possibly indicating the presence of a so-far unknown satellite. However, within the error bars, the geometric albedo in the V-band agrees with the results published in the literature, even with the radiometric-derived albedo

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