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The Seventeenth Data Release of the Sloan Digital Sky Surveys : Complete Release of MaNGA, MaStar, and APOGEE-2 Data
- 2022
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Ingår i: Astrophysical Journal Supplement Series. - : Institute of Physics (IOP). - 0067-0049 .- 1538-4365. ; 259:2
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Tidskriftsartikel (refereegranskat)abstract
- This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 survey that publicly releases infrared spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the subsurvey Time Domain Spectroscopic Survey data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey subsurvey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated value-added catalogs. This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper, Local Volume Mapper, and Black Hole Mapper surveys.
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| 2. |
- Alonso-Rosa, Manuel, et al.
(författare)
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An IoT based mobile augmented reality application for energy visualization in buildings environments
- 2020
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Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 10:2
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Tidskriftsartikel (refereegranskat)abstract
- Augmented reality (AR) improves how we acquire, understand, and display information without distracting us from the real world. These technologies can be used in different applications and industries as they can incorporate domain-specific visualizations on a real-world screen. Mobile augmented reality (MAR) essentially consists of superimposing virtual elements over real objects on the screen, to give added value and enrich the interaction with reality. In numerous plants, it is being used for maintenance and repair tasks, as well as training. The Internet of Things (IoT) is increasingly pervading every aspect of our lives, including the power infrastructure of our buildings. IoT-enabled devices offer many connectivity options for helping supervise all-important energy assets. Aggregating data to cloud-based platforms enables operations teams to have on-time information access to make fast decisions and have a fast response regarding energy use, while maintenance teams keep on top of the appliance power quality and reliability needed by using MAR. This paper presents a novel approximation for visualizing appliance-related power quality to enhance awareness about the consumed electricity. A combined solution of MAR with IoT technologies is employed. Engineered solutions’ hands-free way to get data about surrounding appliances reduces the complexity, saves energy, and speeds up the operations. An innovative way to measure things at the right time leads to a competitive advantage.
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| 3. |
- Ballesteros-Cánovas, Juan Antonio, et al.
(författare)
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Estimation of recent peat accumulation with tree saplings
- 2022
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Ingår i: Progress in Physical Geography. - : SAGE Publications. - 0309-1333. ; 46:4, s. 515-529
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Tidskriftsartikel (refereegranskat)abstract
- The purpose of this paper is to develop an approach to estimate peat accumulation rates (PAR) over recent decades based on the age and burial depths of roots from pine sapling and to use the newly developed approach to estimate spatial variations of PAR. To this end, we sampled 120 pine saplings growing in three plots at Rėkyva peatland in Lithuania and accounted for the microtopography around each specimen. In the lab, all saplings were cut into 1-cm segments, sanded and analysed. The counting of annual rings allowed dating the germination of each sapling with a yearly resolution and thus also enabled estimation of peat accumulation. The latter was derived by measuring the distance from the original root collar at germination to the ground level (or peat surface) at the time of sampling. The large number of samples selected from three plots also enabled determination of spatial variations in PAR. We obtain averaged PAR values of 1.6 ± 0.72 cm yr−1 across the three plots and over the last decades, but also observe strong spatial heterogeneity in PAR resulting from differences in local hydrology and vegetation. To validate the results, we compared tree-ring derived PAR with radiocarbon-based (14C) estimates at one of the plots. The results are consistent between the two approaches with PAR estimated to 0.8 and 0.79 cm yr−1, respectively, over the last 20 years. We conclude that PAR can be assessed accurately with tree-ring approaches and that they have clear advantages over radiocarbon dating for shorter timescales as they can be replicated more easily. For longer timescales and larger depths (> 15 cm), however, 14C dating remains the preferred approach.
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| 4. |
- Benavides, Raquel, et al.
(författare)
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The GenTree Leaf Collection : Inter- and intraspecific leaf variation in seven forest tree species in Europe
- 2021
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Ingår i: Global Ecology and Biogeography. - : John Wiley & Sons. - 1466-822X .- 1466-8238. ; 30:3, s. 590-597
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Tidskriftsartikel (refereegranskat)abstract
- Motivation Trait variation within species can reveal plastic and/or genetic responses to environmental gradients, and may indicate where local adaptation has occurred. Here, we present a dataset of rangewide variation in leaf traits from seven of the most ecologically and economically important tree species in Europe. Sample collection and trait assessment are embedded in the GenTree project (EU-Horizon 2020), which aims at characterizing the genetic and phenotypic variability of forest tree species to optimize the management and sustainable use of forest genetic resources. Our dataset captures substantial intra- and interspecific leaf phenotypic variability, and provides valuable information for studying the relationship between ecosystem functioning and trait variability of individuals, and the response and resilience of species to environmental changes. Main types of variable contained We chose morphological and chemical characters linked to trade-offs between acquisition and conservation of resources and water use, namely specific leaf area, leaf size, carbon and nitrogen content and their ratio, and the isotopic signature of stable isotope C-13 and N-15 in leaves. Spatial location and grain We surveyed between 18 and 22 populations per species, 141 in total, across Europe. Time period Leaf sampling took place between 2016 and 2017. Major taxa and level of measurement We sampled at least 25 individuals in each population, 3,569 trees in total, and measured traits in 35,755 leaves from seven European tree species, i.e. the conifers Picea abies, Pinus pinaster and Pinus sylvestris, and the broadleaves Betula pendula, Fagus sylvatica, Populus nigra and Quercus petraea. Software format The data files are in ASCII text, tab delimited, not compressed.
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| 5. |
- Calatayud, Joaquín, et al.
(författare)
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Positive associations among rare species and their persistence in ecological assemblages
- 2020
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Ingår i: Nature Ecology & Evolution. - : Nature Publishing Group. - 2397-334X. ; 4:1, s. 40-45
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Tidskriftsartikel (refereegranskat)abstract
- According to the competitive exclusion principle, species with low competitive abilities should be excluded by more efficient competitors; yet, they generally remain as rare species. Here, we describe the positive and negative spatial association networks of 326 disparate assemblages, showing a general organization pattern that simultaneously supports the primacy of competition and the persistence of rare species. Abundant species monopolize negative associations in about 90% of the assemblages. On the other hand, rare species are mostly involved in positive associations, forming small network modules. Simulations suggest that positive interactions among rare species and microhabitat preferences are the most probable mechanisms underpinning this pattern and rare species persistence. The consistent results across taxa and geography suggest a general explanation for the maintenance of biodiversity in competitive environments. Analysing spatial association networks among >300 terrestrial and aquatic assemblages, the authors find that the majority of negative associations involve abundant species. In contrast, rare species form mostly positive associations, potentially explaining their persistence in natural communities.
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| 6. |
- Merbold, Lutz, et al.
(författare)
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Opportunities for an African greenhouse gas observation system
- 2021
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Ingår i: Regional Environmental Change. - : Springer Science and Business Media LLC. - 1436-3798 .- 1436-378X. ; 21:4
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Tidskriftsartikel (refereegranskat)abstract
- Global population projections foresee the biggest increase to occur in Africa with most of the available uncultivated land to ensure food security remaining on the continent. Simultaneously, greenhouse gas emissions are expected to rise due to ongoing land use change, industrialisation, and transport amongst other reasons with Africa becoming a major emitter of greenhouse gases globally. However, distinct knowledge on greenhouse gas emissions sources and sinks as well as their variability remains largely unknown caused by its vast size and diversity and an according lack of observations across the continent. Thus, an environmental research infrastructure—as being setup in other regions—is more needed than ever. Here, we present the results of a design study that developed a blueprint for establishing such an environmental research infrastructure in Africa. The blueprint comprises an inventory of already existing observations, the spatial disaggregation of locations that will enable to reduce the uncertainty in climate forcing’s in Africa and globally as well as an overall estimated cost for such an endeavour of about 550 M€ over the next 30 years. We further highlight the importance of the development of an e-infrastructure, the necessity for capacity development and the inclusion of all stakeholders to ensure African ownership.
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| 7. |
- Opgenoorth, Lars, et al.
(författare)
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The GenTree Platform : growth traits and tree-level environmental data in 12 European forest tree species
- 2021
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Ingår i: GigaScience. - : Oxford University Press. - 2047-217X. ; 10:3
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Tidskriftsartikel (refereegranskat)abstract
- Background: Progress in the field of evolutionary forest ecology has been hampered by the huge challenge of phenotyping trees across their ranges in their natural environments, and the limitation in high-resolution environmental information.Findings: The GenTree Platform contains phenotypic and environmental data from 4,959 trees from 12 ecologically and economically important European forest tree species: Abies alba Mill. (silver fir), Betula pendula Roth. (silver birch), Fagus sylvatica L. (European beech), Picea abies (L.) H. Karst (Norway spruce), Pinus cembra L. (Swiss stone pine), Pinus halepensis Mill. (Aleppo pine), Pinus nigra Arnold (European black pine), Pinus pinaster Aiton (maritime pine), Pinus sylvestris L. (Scots pine), Populus nigra L. (European black poplar), Taxus baccata L. (English yew), and Quercus petraea (Matt.) Liebl. (sessile oak). Phenotypic (height, diameter at breast height, crown size, bark thickness, biomass, straightness, forking, branch angle, fructification), regeneration, environmental in situ measurements (soil depth, vegetation cover, competition indices), and environmental modeling data extracted by using bilinear interpolation accounting for surrounding conditions of each tree (precipitation, temperature, insolation, drought indices) were obtained from trees in 194 sites covering the species' geographic ranges and reflecting local environmental gradients.Conclusion: The GenTree Platform is a new resource for investigating ecological and evolutionary processes in forest trees. The coherent phenotyping and environmental characterization across 12 species in their European ranges allow for a wide range of analyses from forest ecologists, conservationists, and macro-ecologists. Also, the data here presented can be linked to the GenTree Dendroecological collection, the GenTree Leaf Trait collection, and the GenTree Genomic collection presented elsewhere, which together build the largest evolutionary forest ecology data collection available.
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