Integrated modelling driven fusion research - Coupling of plasma and neutron transport codes

Funding Information: This work has been carried out within the framework of the EUROfusionConsortium and has received funding from the Euratom research and training programme 2014-2018 and 2019-2020 under grant agreement No 633053. The viewsand opinions expressed herein do not necessarily reflect those of the European Commission. The authors acknowledgethe funding received from the Slovenian Research Agency in the scope of the projects: Trainingof young researchers – 1000-14-0106, Reactor Physics – P2-0073-0106-019, Development of methodology for calibration of neutron detectors with a 14.1 MeV neutron generator - JET fusion reactor case – J2-6752. References [1] O. N. Jarvis, Plasma Phys. Control. Fusion 36, 2 (1994) [2] O. Meneghini et al, Nucl. Fusion, 55, 8 (2015) [3] Ž. Štancar et al, Nucl. Fusion 59, 9 (2019) [4] P. Sirén et al, Nucl. Fusion 58, 1 (2018)Non peer reviewe

Identification and Density Estimation of American Martens (Martes americana) Using a Novel Camera-Trap Method

Camera-traps are increasingly used to estimate wildlife abundance, yet few studies exist for small-sized carnivores or comparing efficacy against traditional methods. We developed a camera-trap to identify the unique ventral patches of American martens (Martes americana). Our method was designed to: (1) determine the optimal trap configuration to photograph ventral patches; (2) evaluate the use of temporally clustered photographs to determine independence and improve identification; and (3) determine factors that influence identification probability. We tested our method by comparing camera- and live-trap density estimates using spatial capture–recapture (SCR) models. The ventral patches of radio-collared martens were most visible when traps were placed 15–20 cm above a feeding platform. Radio-collared martens (n = 14) visited camera-traps for long periods (median = 7 min) with long intervals between visits (median = 419 min), and visits by different martens at the same trap \u3c15 min apart was infrequent (n = 3) during both years. Similarly, there was complete agreement among observers that clustered photos of un-collared martens were always of the same individual. Pairwise agreement was high between observers; eight un-collared martens were identifiable by consensus on 90% (54 of 60) of recorded visits. Factors influencing identification probability were directly related to the time martens spent feeding at traps (β = 0.143, P = 0.01) and inversely proportional to the time that elapsed since traps were baited (β = −0.344, P = 0.006). Density estimates were higher and more precise for camera-trapping (0.60, 0.35–1.01 martens/km2) than live-trapping (0.45, 0.16–1.22 martens/km2), providing evidence that SCR density estimates may be biased when capture heterogeneity is present, yet cannot be accounted for due to small sample size. Our camera-trap method provides a minimally invasive and accurate tool for monitoring marten populations

Low Space External Memory Construction of the Succinct Permuted Longest Common Prefix Array

The longest common prefix (LCP) array is a versatile auxiliary data structure in indexed string matching. It can be used to speed up searching using the suffix array (SA) and provides an implicit representation of the topology of an underlying suffix tree. The LCP array of a string of length $n$ can be represented as an array of length $n$ words, or, in the presence of the SA, as a bit vector of $2n$ bits plus asymptotically negligible support data structures. External memory construction algorithms for the LCP array have been proposed, but those proposed so far have a space requirement of $O(n)$ words (i.e. $O(n \log n)$ bits) in external memory. This space requirement is in some practical cases prohibitively expensive. We present an external memory algorithm for constructing the $2n$ bit version of the LCP array which uses $O(n \log \sigma)$ bits of additional space in external memory when given a (compressed) BWT with alphabet size $\sigma$ and a sampled inverse suffix array at sampling rate $O(\log n)$. This is often a significant space gain in practice where $\sigma$ is usually much smaller than $n$ or even constant. We also consider the case of computing succinct LCP arrays for circular strings

Effect of inclusion of pitch-angle dependence on a simplified model of RF deposition in tokamak plasma

Using the PION ICRH modelling code and comparisons against JET tokamak experiments, the effect of including pitch angle dependence within the RF diffusion operator on the fast ion particle distribution functions is quantified. It is found to be of greatest importance in cases of higher harmonic heating and lower heating ion mass, resulting in faster drop-off of the distribution's high energy tail. We see differences of several orders of magnitude in the high-energy range and significant non-linear alterations by several tens of percent to ion species power partition. ITER scenario operational parameters are also considered, and this improved treatment is shown to benefit anticipated ITER scenarios with second harmonic hydrogen heating, according to our predictions. PION's combination of benchmarked simplified wave physics and Fokker-Planck treatment offers modelling advantages. Since including the pitch angle dependence in the RF diffusion operator has not led to a significant increase in the required computing time when modelling different ICRF schemes in JET discharges, it has been made available within the production code.The CCFE part of this work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014–2018 and 2019–2020 under Grant Agreement No. 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission. The BSC part of this project is co-financed by the European Union Regional Development Fund within the framework of the ERDF Operational Program of Catalonia 2014–2020 with a grant of 50% of total cost eligible. The authors are grateful to Jacob Eriksson for assistance with experimental data, to Lars-Göran Eriksson for discussions on the implementation of the new features, and to Colin Roach and Michael Fitzgerald for valuable comments on the manuscript.Peer ReviewedPostprint (published version

Forecasting species distributions : correlation does not equal causation

This research was funded by the U.S. Department of the Interior Northeast Climate Adaptation Science Center, which is managed by the U.S. Geological Survey National Climate Adaptation Science Center. Additional funding was provided by T-2- 3R grants for Nongame Species Monitoring and Management through the New Hampshire Fish and Game Department and E-1- 25 grants for Investigations and Population Recovery through the Vermont Fish and Wildlife Department.Aim Identifying the mechanisms influencing species' distributions is critical for accurate climate change forecasts. However, current approaches are limited by correlative models that cannot distinguish between direct and indirect effects. Location New Hampshire and Vermont, USA. Methods Using causal and correlational models and new theory on range limits, we compared current (2014?2019) and future (2080s) distributions of ecologically important mammalian carnivores and competitors along range limits in the northeastern US under two global climate models (GCMs) and a high-emission scenario (RCP8.5) of projected snow and forest biomass change. Results Our hypothesis that causal models of climate-mediated competition would result in different distribution predictions than correlational models, both in the current and future periods, was well-supported by our results; however, these patterns were prominent only for species pairs that exhibited strong interactions. The causal model predicted the current distribution of Canada lynx (Lynx canadensis) more accurately, likely because it incorporated the influence of competitive interactions mediated by snow with the closely related bobcat (Lynx rufus). Both modeling frameworks predicted an overall decline in lynx occurrence in the central high-elevation regions and increased occurrence in the northeastern region in the 2080s due to changes in land use that provided optimal habitat. However, these losses and gains were less substantial in the causal model due to the inclusion of an indirect buffering effect of snow on lynx. Main conclusions Our comparative analysis indicates that a causal framework, steeped in ecological theory, can be used to generate spatially explicit predictions of species distributions. This approach can be used to disentangle correlated predictors that have previously hampered understanding of range limits and species' response to climate change.Publisher PDFPeer reviewe

Composite repetition-aware data structures

In highly repetitive strings, like collections of genomes from the same species, distinct measures of repetition all grow sublinearly in the length of the text, and indexes targeted to such strings typically depend only on one of these measures. We describe two data structures whose size depends on multiple measures of repetition at once, and that provide competitive tradeoffs between the time for counting and reporting all the exact occurrences of a pattern, and the space taken by the structure. The key component of our constructions is the run-length encoded BWT (RLBWT), which takes space proportional to the number of BWT runs: rather than augmenting RLBWT with suffix array samples, we combine it with data structures from LZ77 indexes, which take space proportional to the number of LZ77 factors, and with the compact directed acyclic word graph (CDAWG), which takes space proportional to the number of extensions of maximal repeats. The combination of CDAWG and RLBWT enables also a new representation of the suffix tree, whose size depends again on the number of extensions of maximal repeats, and that is powerful enough to support matching statistics and constant-space traversal.Comment: (the name of the third co-author was inadvertently omitted from previous version

Lightweight BWT and LCP merging via the gap algorithm

Recently, Holt and McMillan [Bioinformatics 2014, ACM-BCB 2014] have proposed a simple and elegant algorithm to merge the Burrows-Wheeler transforms of a collection of strings. In this paper we show that their algorithm can be improved so that, in addition to the BWTs, it also merges the Longest Common Prefix (LCP) arrays. Because of its small memory footprint this new algorithm can be used for the final merge of BWT and LCP arrays computed by a faster but memory intensive construction algorithm

Taxonomic and Functional Characterization of the Microbial Community During Spontaneous in vitro Fermentation of Riesling Must

Although there is an extensive tradition of research into the microbes that underlie the winemaking process, much remains to be learnt. We combined the high-throughput sequencing (HTS) tools of metabarcoding and metagenomics, to characterize how microbial communities of Riesling musts sampled at four different vineyards, and their subsequent spontaneously fermented derivatives, vary. We specifically explored community variation relating to three points: (i) how microbial communities vary by vineyard; (ii) how community biodiversity changes during alcoholic fermentation; and (iii) how microbial community varies between musts that successfully complete alcoholic fermentation and those that become ‘stuck’ in the process. Our metabarcoding data showed a general influence of microbial composition at the vineyard level. Two of the vineyards (4 and 5) had strikingly a change in the differential abundance of Metschnikowia. We therefore additionally performed shotgun metagenomic sequencing on a subset of the samples to provide preliminary insights into the potential relevance of this observation, and used the data to both investigate functional potential and reconstruct draft genomes (bins). At these two vineyards, we also observed an increase in non-Saccharomycetaceae fungal functions, and a decrease in bacterial functions during the early fermentation stage. The binning results yielded 11 coherent bins, with both vineyards sharing the yeast bins Hanseniaspora and Saccharomyces. Read recruitment and functional analysis of this data revealed that during fermentation, a high abundance of Metschnikowia might serve as a biocontrol agent against bacteria, via a putative iron depletion pathway, and this in turn could help Saccharomyces dominate the fermentation. During alcoholic fermentation, we observed a general decrease in biodiversity in both the metabarcoding and metagenomic data. Unexpected Micrococcus behavior was observed in vineyard 4 according to metagenomic analyses based on reference-based read mapping. Analysis of open reading frames using these data showed an increase of functions assigned to class Actinobacteria in the end of fermentation. Therefore, we hypothesize that bacteria might sit-and-wait until Saccharomyces activity slows down. Complementary approaches to annotation instead of relying a single database provide more coherent information true species. Lastly, our metabarcoding data enabled us to identify a relationship between stuck fermentations and Starmerella abundance. Given that robust chemical analysis indicated that although the stuck samples contained residual glucose, all fructose had been consumed, we hypothesize that this was because fructophilic Starmerella, rather than Saccharomyces, dominated these fermentations. Overall, our results showcase the different ways in which metagenomic analyses can improve our understanding of the wine alcoholic fermentation process

Local climate determines vulnerability to camouflage mismatch in snowshoe hares

AimPhenological mismatches, when life‐events become mistimed with optimal environmental conditions, have become increasingly common under climate change. Population‐level susceptibility to mismatches depends on how phenology and phenotypic plasticity vary across a species’ distributional range. Here, we quantify the environmental drivers of colour moult phenology, phenotypic plasticity, and the extent of phenological mismatch in seasonal camouflage to assess vulnerability to mismatch in a common North American mammal.LocationNorth America.Time period2010–2017.Major taxa studiedSnowshoe hare (Lepus americanus).MethodsWe used > 5,500 by‐catch photographs of snowshoe hares from 448 remote camera trap sites at three independent study areas. To quantify moult phenology and phenotypic plasticity, we used multinomial logistic regression models that incorporated geospatial and high‐resolution climate data. We estimated occurrence of camouflage mismatch between hares’ coat colour and the presence and absence of snow over 7 years of monitoring.ResultsSpatial and temporal variation in moult phenology depended on local climate conditions more so than on latitude. First, hares in colder, snowier areas moulted earlier in the fall and later in the spring. Next, hares exhibited phenotypic plasticity in moult phenology in response to annual variation in temperature and snow duration, especially in the spring. Finally, the occurrence of camouflage mismatch varied in space and time; white hares on dark, snowless background occurred primarily during low‐snow years in regions characterized by shallow, short‐lasting snowpack.Main conclusionsLong‐term climate and annual variation in snow and temperature determine coat colour moult phenology in snowshoe hares. In most areas, climate change leads to shorter snow seasons, but the occurrence of camouflage mismatch varies across the species’ range. Our results underscore the population‐specific susceptibility to climate change‐induced stressors and the necessity to understand this variation to prioritize the populations most vulnerable under global environmental change.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154444/1/geb13049.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154444/2/geb13049_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154444/3/geb13049-sup-0001-Supinfo.pd

A Cross-Site Analysis of Neotropical Bird Hunting Profiles

© The Author(s) 2017. Subsistence hunting of neotropical birds is common and widespread in the tropical forests of Latin America. Although its sustainability under different scenarios is subject to debate, hunting has already contributed to the decline and local extirpation of several taxa and is considered to be a significant threat to a range of large-bodied species. Gaining a better understanding of the variability of hunting patterns, as well as the factors that can potentially be used to predict them, is important if we are to develop conservation strategies that target the species most likely to be experiencing declines. In this article, we examine the avian hunting profiles of 65 communities in the neotropics. We describe their variability and look at the relationship between a hunting profile and (a) its geographical location, (b) the community’s age, (c) the community’s population size, and (d) the year in which the survey was carried out. We find that there is a significant but weak relationship between a community’s geographic location and the composition of its bird hunting profile, and that prey profiles can be considerably different even among close neighbors. We found no relationship between a community’s age or size and the mean biomass of bird prey hunted. Our results challenge the assumption that older and larger settlements have a predictable impact upon avian prey communities and suggest that cultural preferences or the starting availability of prey species can change rapidly over short distances