Engineering topics

Normand, S.

Publications and source records attributed to Normand, S..

4 records

DOE OSTI2020

Global plant trait relationships extend to the climatic extremes of the tundra biome

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.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Traditional plant functional groups explain variation in economic but not size-related traits across the tundra biome

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 among 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 conclusion: 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 for ecological prediction and modelling.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Qualitative and quantitative validation of the SINBAD code on complex HPGe gamma-ray spectra

Radionuclides identification and quantification is a serious concern for many applications as safety or security of nuclear power plant or fuel cycle facility, CBRN risk identification, environmental radioprotection and waste measurements. High resolution gamma-ray spectrometry based on HPGe detectors is a performing solution for all these topics. During last decades, a great number of software has been developed to improve gamma spectra analysis. However, some difficulties remain in the analysis when photoelectric peaks are folded together with a high ratio between theirs amplitudes, when the Compton background is much larger compared to the signal of a single peak and when spectra are composed of a great number of peaks. This study deals with the comparison between conventional methods in radionuclides identification and quantification and the code called SINBAD ('Spectrometrie par Inference Non parametrique Bayesienne Deconvolutive'). For many years, SINBAD has been developed by CEA LIST for unfolding complex spectra from HPGe detectors. Contrary to conventional methods using fitting procedures, SINBAD uses a probabilistic approach with Bayesian inference to describe spectrum data. This conventional fitting method founded for example in Genie 2000 is compared with the nonparametric SINBAD approach regarding some key figures of merit as the peak centroid evaluation (identification) and peak surface evaluation (quantification). Unfriendly cases are studied for nuclides detection with closed gamma-rays energies and high photoelectric peak intensity differences. Tests are performed with spectra from the International Atomic Energy Agency (IAEA) for gamma spectra analysis software benchmark and with spectra acquired at the laboratory. Results show that SINBAD and Genie 2000 performances are quite similar with sometimes best results for SINBAD with the important difference that to achieve same performances the nonparametric method is user-friendly compared to the conventional method which need an expert parameters adjustment. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2015

Maximum Likelihood Expectation-Maximization Algorithms Applied to Localization and Identification of Radioactive Sources with Recent Coded Mask Gamma Cameras

In this work, we tested Maximum likelihood expectation-maximization (MLEM) algorithms optimized for gamma imaging applications on two recent coded mask gamma cameras. We respectively took advantage of the characteristics of the GAMPIX and Caliste HD-based gamma cameras: noise reduction thanks to mask/anti-mask procedure but limited energy resolution for GAMPIX, high energy resolution for Caliste HD. One of our short-term perspectives is the test of MAPEM algorithms integrating specific prior values for the data to reconstruct adapted to the gamma imaging topic. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗