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Reflectance spectra provide integrative measures of plant phenotypes by capturing chemical, morphological, anatomical and architectural trait information. Here, we investigate the linkages between plant spectral variation, and spectral and resource-use complementarity that contribute to ecosystem productivity. In both a forest and prairie grassland diversity experiment, we delineated -dimensional hypervolumes using wavelength bands of reflectance spectra to test the association between the spectral space occupied by individual plants and their growth, as well as between the spectral space occupied by plant communities and ecosystem productivity. We show that the spectral space occupied by individuals increased with their growth, and the spectral space occupied by plant communities increased with ecosystem productivity. Furthermore, ecosystem productivity was better explained by inter-individual spectral complementarity than by the large spectral space occupied by productive individuals. Our results indicate that spectral hypervolumes of plants can reflect ecological strategies that shape community composition and ecosystem function, and that spectral complementarity can reveal resource-use complementarity.
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http://dx.doi.org/10.1098/rspb.2021.1290 | DOI Listing |
Spectrochim Acta A Mol Biomol Spectrosc
September 2025
Department of Chemistry, University of Copenhagen, Universitetsparken 5, Copenhagen-Ø, DK-2100, Denmark. Electronic address:
Absorption spectra of neopentyl alcohol and pinacolyl alcohol are recorded in the gas phase at room temperature and equilibrium conditions. A combination of conventional Fourier transform spectroscopy and cavity ringdown spectroscopy is used to cover the spectral OH-stretching regions, Δv=1-5. The conformer distributions of the alcohols are determined from the recorded spectra combined with transition intensities calculated with a reduced dimensional local mode model.
View Article and Find Full Text PDFNat Commun
September 2025
Institute for Theoretical Physics, University of Regensburg, Regensburg, Germany.
The nature of the dominant pairing mechanism in some two-dimensional transition metal dichalcogenides is still debated. Focusing on monolayer 1H-NbSe, we show that superconductivity can be induced by the Coulomb interaction when accounting for screening effects on the trigonal lattice with multiple orbitals. Using ab initio based tight-binding parametrizations for the relevant low-energy d-bands, we evaluate the screened interaction microscopically.
View Article and Find Full Text PDFNeural Netw
August 2025
Division of Applied Mathematics, Brown University, Providence, RI, 02912, USA; Pacific Northwest National Laboratory, Richland, WA, 99354, USA. Electronic address:
Neural operators have emerged as powerful surrogates for modeling complex physical problems. However, they suffer from spectral bias making them oblivious to high-frequency modes, which are present in multiscale physical systems. Therefore, they tend to produce over-smoothed solutions, which is particularly problematic in modeling turbulence and for systems with intricate patterns and sharp gradients such as multi-phase flow systems.
View Article and Find Full Text PDFJ Chem Phys
September 2025
MOE Key Laboratory of Laser Life Science & Institute of Laser Life Science, Guangdong Provincial Key Laboratory of Laser Life Science, Guangzhou Key Laboratory of Spectral Analysis and Functional Probes, College of Biophotonics, School of Optoelectronic Science and Engineering, South China Normal Un
Propargyl radical (•C3H3) and butadienyl radical (•i-C4H5) are two crucial intermediates in combustion and astrochemistry, particularly in the formation of C7H8 aromatics such as toluene. However, the precise formation mechanisms of the first-ring aromatics through C3 + C4 reactions have remained ambiguous. This study explores the detailed potential energy surface (PES) of C7H8 at the •C3H3 + •i-C4H5 entrance reaction channel, alongside conducting kinetic calculations and modeling.
View Article and Find Full Text PDFZhongguo Zhong Yao Za Zhi
July 2025
Engineering Center of State Ministry of Education for Standardization of Chinese Medicine Processing,College of Pharmacy, Nanjing University of Chinese Medicine Nanjing 210023, China.
Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation.
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