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At least 37 records · Page 2

Functional but not taxonomic diversity increases productivity of Populus in the southeastern United States

Plant interactions like competition and facilitation impact ecosystem function and resilience. Improving our understanding of the relationships between these interactions and community productivity has important implications for managers of production systems in forestry and agriculture as well as conservation science. Populus spp. are an excellent model system for exploring how inter‐ and intraspecific interactions impact ecosystem functions, such as productivity, in forest plantations. In this study, we compared aboveground productivity of six Populus clones from three different taxa grown in monoclonal and mixed‐clonal plots. The different mixture treatments were intended to experimentally test aboveground biomass response to contrasting levels of taxonomic diversity and functional diversity based on nitrogen use characteristics of Populus clones. We hypothesize that functional diversity would be more important than taxonomic diversity in increasing aboveground productivity of mixed‐clonal plantings compared to monocultures. In addition, a subset of treatments was carried out on additional sites representing a productivity gradient in order to determine if the relationship between biodiversity and productivity in these systems diminished at more productive sites as suggested by the stress‐gradient hypothesis. We found that functionally diverse mixtures of clones had greater yield of aboveground biomass than the average of their constituent monocultures, while more taxonomically diverse mixes of clones did not differ from the average of their constituent monocultures. However, when reestablished on sites with extremely high or low productivity, the best performing clone mixture also did not differ from the average of its constituent monocultures. Our results suggest that intimate clone mixtures of Populus have the potential to significantly increase productivity, but results vary by mixture and by site. To capitalize on positive biodiversity effects on yield in production systems, targeted mixtures based on divergent functional traits linked to different use and acquisition strategies for site‐specific limiting resources are most likely to be successful.

BEF↗

Ecological connectivity and habitat loss shape patterns of genetic diversity in a threatened salamander

Context The maintenance of genetic diversity is essential for preserving adaptive potential in populations, yet it is increasingly threatened by landscape alteration. The field of landscape genetics offers a framework for assessing how patch-level landscape conditions, modeled at multiple scales, influence genetic diversity. Objectives We sought to assess how local environmental features and connectivity influence genetic diversity across 74 four-toed salamander (Hemidactylium scutatum) breeding wetlands in the southeastern United States. Methods Using next-generation sequencing data and hierarchical Bayesian models, we examined genome-wide heterozygosity in relation to local landscape features and ecological connectivity. We also assessed the scale of effect of landscape features and tested for temporal lag effects. Results Genetic diversity was lower in wetlands with higher levels of historic deforestation and lower connectivity. An interaction between deforestation and connectivity indicated that deforestation had stronger negative effects in isolated wetlands but weaker effects in well-connected wetlands. Accounting for scale of effect and temporal lags was critical for detecting these relationships. Conclusions Our analyses highlight the importance of assessing the spatial scale (scale of effect) and temporal lag of landscape features to detect key drivers of genetic diversity. In line with population genetic theory, our results indicate that the genetic consequences of habitat loss do not affect populations uniformly and are most severe in isolated populations where gene flow cannot buffer against loss of diversity. Altogether, we highlight the importance of considering the interaction of habitat loss and connectivity in conservation genetic management.

Hemidactylium scutatum↗

Exploring genetic diversity, population structure, and subgenome differences in the allopolyploid Camelina sativa : implications for future breeding and research studies

Abstract Camelina (Camelina sativa), an allohexaploid species, is an emerging aviation biofuel crop that has been the focus of resurgent interest in recent decades. To guide future breeding and crop improvement efforts, the community requires a deeper comprehension of subgenome dominance, often noted in allopolyploid species, “alongside an understanding of the genetic diversity” and population structure of material present within breeding programs. We conducted population genetic analyses of a C. sativa diversity panel, leveraging a new genome, to estimate nucleotide diversity and population structure, and analyzed for patterns of subgenome expression dominance among different organs. Our analyses confirm that C. sativa has relatively low genetic diversity and show that the SG3 subgenome has substantially lower genetic diversity compared to the other two subgenomes. Despite the low genetic diversity, our analyses identified 13 distinct subpopulations including two distinct wild populations and others putatively representing founders in existing breeding populations. When analyzing for subgenome composition of long non-coding RNAs, which are known to play important roles in (a)biotic stress tolerance, we found that the SG3 subgenome contained significantly more lincRNAs compared to other subgenomes. Similarly, transcriptome analyses revealed that expression dominance of SG3 is not as strong as previously reported and may not be universal across all organ types. From a global analysis, SG3 “was only significant higher expressed” in flower, flower bud, and fruit organs, which is an important discovery given that the crop yield is associated with these organs. Collectively, these results will be valuable for guiding future breeding efforts in camelina.

Agriculture↗

Genetic diversity loss in the Anthropocene

Anthropogenic habitat loss and climate change are reducing species’ geographic ranges, increasing extinction risk and losses of species’ genetic diversity. Although preserving genetic diversity is key to maintaining species’ adaptability, we lack predictive tools and global estimates of genetic diversity loss across ecosystems. We introduce a mathematical framework that bridges biodiversity theory and population genetics to understand the loss of naturally occurring DNA mutations with decreasing habitat. By analyzing genomic variation of 10,095 georeferenced individuals from 20 plant and animal species, we show that genome-wide diversity follows a mutations-area relationship power law with geographic area, which can predict genetic diversity loss from local population extinctions. We estimate that more than 10% of genetic diversity may already be lost for many threatened and nonthreatened species, surpassing the United Nations’ post-2020 targets for genetic preservation.

Science & Technology - Other Topics↗

The Brazilian Amazonian rainforest harbors a high diversity of yeasts associated with rotting wood, including many candidates for new yeast species

This study investigated the diversity of yeast species associated with rotting wood in Brazilian Amazonian rainforests. Herein, a total of 569 yeast strains were isolated from rotting wood samples collected in three Amazonian areas (Universidade Federal do Amazonas-Universidade Federal do Amazonas [UFAM], Piquiá, and Carú) in the municipality of Itacoatiara, Amazon state. The samples were cultured in yeast nitrogen base (YNB)-d-xylose, YNB-xylan, and sugarcane bagasse and corncob hemicellulosic hydrolysates (undiluted and diluted 1:2 and 1:5). Sugiyamaella was the most prevalent genus identified in this work, followed by Kazachstania. The most frequently isolated yeast species were Schwanniomyces polymorphus, Scheffersomyces amazonensis, and Wickerhamomyces sp., respectively. The alpha diversity analyses showed that the dryland forest of UFAM was the most diverse area, while the floodplain forest of Carú was the least. Additionally, the difference in diversity between UFAM and Carú was the highest among the comparisons. Thirty candidates for new yeast species were obtained, representing 36% of the species identified and totaling 101 isolates. Among them were species belonging to the clades Spathaspora, Scheffersomyces, and Sugiyamaella, which are recognized as genera with natural xylose-fermenting yeasts that are often studied for biotechnological and ecological purposes. The results of this work showed that rotting wood collected from the Amazonian rainforest is a tremendous source of diverse yeasts, including candidates for new species.

59 BASIC BIOLOGICAL SCIENCES↗

Diverging drivers of fungal diversity: seasonal effects shape aboveground communities, while geographical patterns govern belowground communities in rubber tree ecosystems

Understanding the spatiotemporal dynamics of microbial communities is essential for predicting their ecological roles and interactions with host plants. In a recent study, Wei and colleagues (Microbiol Spectr 13:e02097-24, 2024) investigated fungal diversity across multiple plant and soil compartments in rubber trees over two seasons and two geographically distinct regions in China. Their findings revealed that alpha diversity was primarily influenced by seasonal changes and physicochemical factors, while beta diversity exhibited a strong geographical pattern, shaped by leaf phosphorus and soil available potassium. These results highlight the role of environmental drivers in shaping within-community diversity, while other factors contribute to the differences between fungal communities across the soil–plant continuum. By distinguishing the effects of temporal and spatial factors, this study provides detailed insights into plant-associated microbiomes and emphasizes the need for further research on the functional implications of microbial diversity in the context of changing environmental and agricultural conditions.

fungal diversity↗

Rare species do not disproportionately contribute to phylogenetic diversity in a subalpine plant community

Abstract Premise Within plant communities, few species are abundant, and most are locally rare. Worldwide, 36% of plant species are exceedingly rare and often face high extinction risk. However, the community phylogenetic impact of the loss of rare plants is largely unknown in many systems. We address this gap by investigating how rare species contribute to phylogenetic diversity, considering multiple metrics of rarity and multiple elevations in a subalpine plant community. Methods We collected abundance data at three sites near the Rocky Mountain Biological Laboratory (Colorado, USA). We calculated each species' range size from public occurrence data. We calculated phylogenetic signal for abundance and range size, compared community phylogenetic metrics weighted by range size and abundance to unweighted metrics, and quantified the change in phylogenetic diversity when removing single species and groups of species ranked by rarity. Results We found phylogenetic signal for abundance, but not range size. There was no difference between rarity‐weighted and ‐unweighted phylogenetic diversity metrics. Finally, phylogenetic diversity did not decline more when we removed single rare species or groups of rare species than when we removed single common species and groups of common species. Conclusions We found that rare species, whether at low abundance or with a small range, do not disproportionately contribute to phylogenetic diversity in our subalpine plant community. These results were consistent across elevations. Instead, rare species might provide phylogenetic redundancy with common species. Deeper understanding of functional differentiation is needed to understand contributions of rare species to this system.

Plant Sciences↗

Sensor Reduction for Diversion Detection in a Realistic Heat Pipe Microreactor Using Supervised Machine Learning

Microreactors are designed as a smaller, cheaper, and safer alternative to traditional nuclear power plants. Their non-traditional characteristics and prospect of mass production and deployment will likely require new approaches to nuclear safeguards. The primary proliferation concern with microreactors is the diversion of fuel material. Such diversion may produce measurable defects in key physical attributes like neutron flux, which may in turn be detectable using machine learning models. Preliminary work has demonstrated this ability for modeled nominal and diversion scenarios using large quantities of energy integrated neutron flux data. In practice, the number of available sensors for such measurements will be limited and energy integrated flux information will not be available. This work explores the ability of tree-based gradient boosted ensemble models to classify a given microreactor core is nominal or diversion, and determine the number of fuel pins diverted in the case of diversion with reduced numbers of sensors and more realistic detector responses. Classification accuracy of greater than 98% and regression errors as low as 5% of the total number of fuel pins were achieved with as few as 15 sensors, compared to 99% and 4.1% with a maximum of 240 sensors.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Meta-virus resource (MetaVR): expanding the frontiers of viral diversity with 24 million uncultivated virus genomes

Viruses are ubiquitous in all environments and impact host metabolism, evolution, and ecology, although our knowledge of their biodiversity is still extremely limited. Viral diversity from genomic and metagenomic datasets has led to an explosion of uncultivated virus genomes (UViGs) and the development of specialized databases to catalog this viral diversity, though many lack comprehensive integration. Here, we introduce meta-virus resource (MetaVR), the successor of the IMG/VR database, designed to overcome previous limitations such as large-scale querying and programmatic access. Drawing on the increase of publicly available genomes and metagenomes, MetaVR significantly expands viral diversity, now comprising 24,435,662 UViGs, a 57.6% increase from its predecessor, organized into over 12 million viral operational taxonomic units. Key enhancements include the integration of curated eukaryotic host information, the integration of protein clusters and predicted structures for comparative studies, and an API for programmatic data access. Furthermore, MetaVR features an updated taxonomic framework based on ICTV release 39, assignment to Baltimore classes, and enhanced host assignment through novel computational tools like iPHoP. These advancements position MetaVR as a unique resource for exploring viral diversity, evolution, and host interactions across diverse environments. MetaVR can be freely accessed at https://www.meta-virome.org/.

Fiamenghi, Mateus B↗

Prevalence and diversity of TAL effector-like proteins in fungal endosymbiotic Mycetohabitans spp.

EndofungalMycetohabitans(formerlyBurkholderia) spp. rely on a type III secretion system to deliver mostly unidentified effector proteins when colonizing their host fungus,Rhizopus microsporus. The one known secreted effector family fromMycetohabitansconsists of homologues of transcription activator-like (TAL) effectors, which are used by plant pathogenicXanthomonasandRalstoniaspp. to activate host genes that promote disease. These ‘BurkholderiaTAL-like (Btl)’ proteins bind corresponding specific DNA sequences in a predictable manner, but their genomic target(s) and impact on transcription in the fungus are unknown. Recent phenotyping of Btl mutants of twoMycetohabitansstrains revealed that the single Btl in oneMycetohabitans endofungorumstrain enhances fungal membrane stress tolerance, while others in aMycetohabitans rhizoxinicastrain promote bacterial colonization of the fungus. The phenotypic diversity underscores the need to assess the sequence diversity and, given that sequence diversity translates to DNA targeting specificity, the functional diversity of Btl proteins. Using a dual approach to maximize capture of Btl protein sequences for our analysis, we sequenced and assembled nineMycetohabitansspp. genomes using long-read PacBio technology and also mined available short-read Illumina fungal–bacterial metagenomes. We show thatbtlgenes are present across diverseMycetohabitansstrains from Mucoromycota fungal hosts yet vary in sequences and predicted DNA binding specificity. Phylogenetic analysis revealed distinct clades of Btl proteins and suggested thatMycetohabitansmight contain more species than previously recognized. Within our data set, Btl proteins were more conserved acrossM. rhizoxinicastrains than acrossM. endofungorum, but there was also evidence of greater overall strain diversity within the latter clade. Overall, the results suggest that Btl proteins contribute to bacterial–fungal symbioses in myriad ways.

Genetics & Heredity↗

When more data hurts: Optimizing data coverage while mitigating diversity-induced underfitting in an ultrafast machine-learned potential

Machine-learned interatomic potentials (MLIPs) are becoming an essential tool in materials modeling. However, optimizing the generation of training data used to parametrize the MLIPs remains a significant challenge. This is because MLIPs can fail when encountering local environments too different from those present in the training data. The difficulty of determining a priori the environments that will be encountered during molecular dynamics simulation necessitates diverse, high-quality training data. Here, this study investigates how training data diversity affects the performance of MLIPs using the Ultra-Fast force field (UF 3 ) to model amorphous silicon nitride. We employ expert and autonomously generated data to create the training data and fit four force field variants to subsets of the data. Our findings reveal a critical balance in training data diversity: insufficient diversity hinders generalization, while excessive diversity can exceed the MLIP's learning capacity, reducing simulation accuracy. Specifically, we found that the UF 3 variant trained on a subset of the training data, in which nitrogen-rich structures were removed, offered vastly better prediction and simulation accuracy than any other variant. By comparing these UF 3 variants, we highlight the nuanced requirements for creating accurate MLIPs, emphasizing the importance of application-specific training data to achieve optimal performance in modeling complex material behaviors.

ab initio molecular dynamics↗

Disturbance–diversity relationships of microbial communities change based on growth substrate

Disturbance events can impact ecological community dynamics. Understanding how communities respond to disturbances and how those responses can vary is a challenge in microbial ecology. In this study, we grew a previously enriched specialized microbial community on either cellulose or glucose as a sole carbon source and subjected them to one of five different disturbance regimes of varying frequencies ranging from low to high. Using 16S rRNA gene amplicon sequencing, we show that the community structure is largely driven by substrate, but disturbance frequency affects community composition and successional dynamics. When grown on cellulose, bacteria in the genera Cellvibrio, Lacunisphaera, and Asticcacaulis are the most abundant microbes. However, Lacunisphaera is only abundant in the lower disturbance frequency treatments, while Asticcacaulis is more abundant in the highest disturbance frequency treatment. When grown on glucose, the most abundant microbes are two Pseudomonas sequence variants and a Cohnella sequence variant that is only abundant in the highest disturbance frequency treatment. Communities grown on cellulose exhibited a greater range of diversity (1.95–7.33 Hill 1 diversity) that peaks at the intermediate disturbance frequency treatment or one disturbance every 3 days. Communities grown on glucose, however, ranged from 1.63 to 5.19 Hill 1 diversity with peak diversity at the greatest disturbance frequency treatment. These results demonstrate that the dynamics of a microbial community can vary depending on substrate and the disturbance frequency and may potentially explain the variety of diversity–disturbance relationships observed in microbial systems.

59 BASIC BIOLOGICAL SCIENCES↗

Microbes display broad diversity in cobamide preferences

ABSTRACT Cobamides, the vitamin B 12 (cobalamin) family of cofactors, are used by most organisms but produced by only a fraction of prokaryotes, and are thus considered key shared nutrients among microbes. Cobamides are structurally diverse, with multiple different cobamides found in most microbial communities. The ability to use different cobamides has been tested for several bacteria and microalgae, and nearly all show preferences for certain cobamides. This approach is limited by the commercial unavailability of cobamides other than cobalamin. Here, we have extracted and purified seven commercially unavailable cobamides to characterize bacterial cobamide preferences based on growth in specific cobamide-dependent conditions. The tested bacteria include engineered strains of Escherichia coli , Sinorhizobium meliloti , and Bacillus subtilis expressing native or heterologous cobamide-dependent enzymes, cultured under conditions that functionally isolate specific cobamide-dependent processes such as methionine synthesis. Comparison of these results to those of previous studies of diverse bacteria and microalgae revealed that a broad diversity of cobamide preferences exists not only across different organisms but also between different cobamide-dependent metabolic pathways within the same organism. The microbes differed in the cobamides that support growth most efficiently, cobamides that do not support growth, and the minimum cobamide concentrations required for growth. The latter differ by up to four orders of magnitude across organisms from different environments and by up to 20-fold between cobamide-dependent enzymes within the same organism. Given that cobamides are shared, required for use of specific growth substrates, and essential for central metabolism in certain organisms, cobamide preferences likely impact community structure and function. IMPORTANCE Nearly all bacteria are found in microbial communities with tens to thousands of other species. Molecular interactions such as metabolic cooperation and competition are key factors underlying community assembly and structure. Cobamides, the vitamin B 12 family of enzyme cofactors, are one such class of nutrients, produced by only a minority of prokaryotes but required by most microbes. A unique aspect of cobamides is their broad diversity, with nearly 20 structural forms identified in nature. Importantly, this structural diversity impacts growth as most bacteria that have been tested show preferences for specific cobamide forms. We measured cobamide-dependent growth in several model bacteria and compared the results to those of previous analyses of cobamide preference. We found that cobamide preferences vary widely across bacteria, showing the importance of characterizing these aspects of cobamide biology to understand the impact of cobamides on microbial communities.

Mok, Kenny C. (ORCID:0000000252276987)↗

Insights into ENSO Diversity from an Intermediate Coupled Model. Part I: Uniqueness and Sensitivity of the ENSO Mode

Abstract The basic dynamics of the spatiotemporal diversity for El Niño–Southern Oscillation (ENSO) has been the subject of extensive research and, while several hypotheses have been proposed, remains elusive. One promising line of studies suggests that the observed eastern Pacific (EP) and central Pacific (CP) ENSO may originate from two coexisting leading ENSO modes. We show that the coexistence of unstable EP-like and CP-like modes in these studies arises from contaminated linear stability analysis due to unnoticed numerical scheme caveats. In this two-part study, we further investigate the dynamics of ENSO diversity within a Cane–Zebiak-type model. We first revisit the linear stability issue to demonstrate that only one ENSO-like linear leading mode exists under realistic climate conditions. This single leading ENSO mode can be linked to either a coupled recharge-oscillator (RO) mode favored by the thermocline feedback or a wave-oscillator (WO) mode favored by the zonal advective feedback at the weak air–sea coupling end. Strong competition between the RO and WO modes for their prominence in shaping this ENSO mode into a generalized RO mode makes it sensitive to moderate changes in these two key feedbacks. Modulations of climate conditions yield corresponding modulations in spatial pattern, amplitude, and period associated with this ENSO mode. However, the ENSO behavior undergoing this linear climate condition modulations alone does not seem consistent with the observed ENSO diversity, suggesting the inadequacy of linear dynamics in explaining ENSO diversity. A nonlinear mechanism for ENSO diversity will be proposed and discussed in Part II.

Geng, Licheng↗

Insights into ENSO Diversity from an Intermediate Coupled Model. Part II: Role of Nonlinear Dynamics and Stochastic Forcing

Abstract In this study, we investigate how a single leading linear El Niño–Southern Oscillation (ENSO) mode, as studied in Part I, leads to the irregular coexistence of central Pacific (CP) and eastern Pacific (EP) ENSO, a phenomenon known as ENSO spatiotemporal diversity. This diversity is fundamentally generated by deterministic nonlinear pathways to chaos via the period-doubling route and, more prevailingly, the subharmonic resonance route with the presence of a seasonally varying basic state. When residing in the weakly nonlinear regime, the coupled system sustains a weak periodic oscillation with a mixed CP/EP pattern as captured by the linear ENSO mode. With a stronger nonlinearity effect, the ENSO behavior experiences a period-doubling bifurcation. The single ENSO orbit splits into coexisting CP-like and EP-like ENSO orbits. A sequence of period-doubling bifurcation results in an aperiodic oscillation featuring irregular CP and EP ENSO occurrences. The overlapping of subharmonic resonances between ENSO and the seasonal cycle allows this ENSO irregularity and diversity to be more readily excited. In the strongly nonlinear regime, the coupled system is dominated by regular EP ENSO. The deterministic ENSO spatiotemporal diversity is thus confined to a relatively narrow range corresponding to a moderately unstable ENSO mode. Stochastic forcing broadens this range and allows ENSO diversity to occur when the ENSO mode is weakly subcritical. A close relationship among a weakened mean zonal temperature gradient, stronger ENSO activity, and more (fewer) occurrences of EP (CP) ENSO is noted, indicating that ENSO–mean state interaction may yield ENSO regime modulations on the multidecadal time scale.

Geng, Licheng↗

Demographic drivers of gut microbiome diversity

Abstract The gut microbiome plays a central role in orchestrating metabolic, immune, and neurological functions essential for human health. While extensive research has explored the effects of diseases and pathological conditions on gut microbiome composition, the influence of demographic factors remains underexplored, limiting our understanding of microbiome variations in disease states. This study addresses this gap by investigating the impact of demographic variables, including age, sex, and geography, on gut microbiome diversity in healthy individuals. Using the American Gut Project’s extensive dataset and the QIIME2 bioinformatics pipeline, we conducted a comprehensive analysis of microbial profiles across diverse demographic groups. Our results revealed significant age-related shifts in microbial richness and composition, and geographic location strongly influenced phylogenetic diversity. In contrast, sex exhibited limited impact on microbial diversity within healthy BMI ranges. These findings highlight the critical role of demographic factors in shaping gut microbiome diversity, providing a foundational framework to better contextualize disease-related microbiome variations and advance personalized healthcare approaches.

Biotechnology & Applied Microbiology↗

Diversity and Distribution of Hydrocarbon-Degrading Genes in the Cold Seeps from the Mediterranean and Caspian Seas

Marine cold seeps are unique ecological niches characterized by the emergence of hydrocarbons, including methane, which fosters diverse microbial communities. This study investigates the diversity and distribution of hydrocarbon-degrading genes and organisms in sediments from the Caspian and Mediterranean Seas, utilizing 16S rRNA and metagenomic sequencing to elucidate microbial community structure and functional potential. Our findings reveal distinct differences in hydrocarbon degrading gene profiles between the two seas, with pathways for aerobic and anaerobic hydrocarbon degradation co-existing in sediments from both basins. Aerobic pathways predominate in the surface sediments of the Mediterranean Sea, while anaerobic pathways are favored in the surface sediments of the anoxic Caspian Sea. Additionally, sediment depths significantly influence microbial diversity, with variations in gene abundance and community composition observed at different depths. Aerobic hydrocarbon-degrading genes decrease in diversity with depth in the Mediterranean Sea, whereas the diversity of aerobic hydrocarbon-degrading genes increases with depth in the Caspian Sea. These results enhance our understanding of microbial ecology in cold seep environments and have implications for bioremediation practices targeting hydrocarbon pollutants in marine ecosystems.

Microbiology↗

Exploring diversion-pathway analysis of a generic molten-salt fast reactor using multiphysics informed signatures

Molten salt reactors are being explored by multiple commercial ventures due to their inherent safety features, flexibility in fuel sources, and high fuel utilization and thermal efficiency. The continual flow of fuel salt, large fissile quantities present, and ability to add or divert material due to the liquid nature introduces new challenges for international safeguards. To understand how international safeguards should be applied, it is important to capture the inherent multi-physics nature of a molten salt reactor. This work examines a generic molten salt fast reactor to understand how potential diversion scenarios would affect the concentration of radionuclides in the primary and auxiliary systems. Three types of diversion were examined: a slow drip of fuel salt, gaseous plutonium extraction, and uranium metal plating. The analysis determined that several key isotopes become statistically significant once diversion begins, indicating that detection of such diversion cases would be possible through measuring specific signatures such as gamma spectra.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗