A user-friendly forest model with a multiplicative mathematical structure: a Bayesian approach to calibration

Forest models are being increasingly used to study ecosystem functioning, through the reproduction of carbon fluxes and productivity in very different forests all over the world. Over the last two decades, the need for simple and “easy to use” models for practical applications, characterized by few parameters and equations, has become clear, and some have been developed for this purpose. These models aim to represent the main drivers underlying forest ecosystem processes while being applicable to the widest possible range of forest ecosystems. Recently, it has also become clear that model performance should not be assessed only in terms of accuracy of estimations and predictions, but also in terms of estimates of model uncertainties. Therefore, the Bayesian approach has increasingly been applied to calibrate forest models, with the aim of estimating the uncertainty of their results, and of comparing their performances. Some forest models, considered to be user-friendly, rely on a multiplicative or quasimultiplicative mathematical structure, which is known to cause problems during the calibration process, mainly due to high correlations between parameters. In a Bayesian framework using a Markov Chain Monte Carlo sampling this is likely to impair the reaching of a proper convergence of the chains and the sampling from the correct posterior distribution. Here we show two methods to reach proper convergence when using a forest model with a multiplicative structure, applying different algorithms with different number of iterations during the Markov Chain Monte Carlo or a two-steps calibration. The results showed that recently proposed algorithms for adaptive calibration do not confer a clear advantage over the Metropolis–Hastings Random Walk algorithm for the forest model used here. Moreover, the calibration remains time consuming and mathematically difficult, so advantages of using a fast and user-friendly model can be lost due to the calibration process that is needed to obtain reliable results

Many-core applications to online track reconstruction in HEP experiments

Interest in parallel architectures applied to real time selections is growing in High Energy Physics (HEP) experiments. In this paper we describe performance measurements of Graphic Processing Units (GPUs) and Intel Many Integrated Core architecture (MIC) when applied to a typical HEP online task: the selection of events based on the trajectories of charged particles. We use as benchmark a scaled-up version of the algorithm used at CDF experiment at Tevatron for online track reconstruction - the SVT algorithm - as a realistic test-case for low-latency trigger systems using new computing architectures for LHC experiment. We examine the complexity/performance trade-off in porting existing serial algorithms to many-core devices. Measurements of both data processing and data transfer latency are shown, considering different I/O strategies to/from the parallel devices.Comment: Proceedings for the 20th International Conference on Computing in High Energy and Nuclear Physics (CHEP); missing acks adde

Arachidonic Acid/ppara Enhancement of Ca2+-Regulated Exocytosis in Antral Mucous Cells of Guinea Pig

N is known to be the most limiting element for vegetation growth in temperate and boreal forests. The expected increases in global temperature are predicted to accelerate N mineralization, therefore incrementing N availability in the soil and affecting the soil C cycle as well. While there is an abundance of C data collected to fulfill the requirements for national GHG accounting, more limited information is available for soil N accumulation and storage in relation to forest categories and altitudinal gradients. The data collected by the second Italian National Forest Inventory, spanning a wide range of temperature and precipitation values (10° latitudinal range), represented a unique opportunity to calculate N content and C/N ratio of the different soil layers to a depth of 30 cm. Boosted Regression Tree (BRT) models were applied to investigate the main determinants of soil N distribution and C/N ratio. Forest category was shown to be the main explanatory factor of soil N variability in seven out of eight models, both for forest floor and mineral soil layers. Moreover latitude explained a larger share of variability than single climate variables. BRT models explained, on average, the 49% of the data variability, with the remaining fraction likely due to soil-related variables that were unaccounted for. Accurate estimations of N pools and their determinants in a climate change perspective are consequently required to predict the potential impact of their degradation on forest soil N pools

Montane ecosystem productivity responds more to global circulation patterns than climatic trends

Ajuts: we thank the support of KIT IMK-IFU, the University of Wisconsin sabbatical leave program, and the Helmholtz Society/MICMOR fellowship program. We also thank the DWD for German weather data. Phenology data were provided by the members of the PEP725 project. We are indebted to the providers and funders of the eddy covariance flux tower observations, the FLUXNET program, and its database. The sites in Graswang, Rottenbuch and Fendt belong to the TERENO and ICOS-ecosystems networks, funded by Bundesministerium für Bildung und Forschung(BMBF)and the Helmholtz Association. The modeling study of SOLVEG was partially supported by Grant-in-Aid for Scientific Research, no. 21120512, provided by the Japan Society for the Promotion of Science(JSPS). This study was financially supported by the Austrian National Science Fund(FWF) under contract P26425 to GW.Regional ecosystem productivity is highly sensitive to inter-annual climate variability, both within and outside the primary carbon uptake period. However, Earth system models lack sufficient spatial scales and ecosystem processes to resolve how these processes may change in a warming climate. Here, we show, how for the European Alps, mid-latitude Atlantic ocean winter circulation anomalies drive high-altitude summer forest and grassland productivity, through feedbacks among orographic wind circulation patterns, snowfall, winter and spring temperatures, and vegetation activity. Therefore, to understand future global climate change influence to regional ecosystem productivity, Earth systems models need to focus on improvements towards topographic downscaling of changes in regional atmospheric circulation patterns and to lagged responses in vegetation dynamics to non-growing season climate anomalies

Diverging phenology change in the European mountains in a warming world

Global warming lengthens the potential thermal growing season, strongly influencing vegetation phenology in temperature constrained ecosystems. The spatial resolution of phenological studies usually ranges from 1 km to 50 km and may hinder elevation patter ns in areas with complex topography and the response of different vegetation types in fragmented landscapes, which are therefore still poorly understood. To fill this gap, we investigated phenological trends in broadleaved forests and natural grasslands in the Alps, in the Carpathians, and in the Pyrenees from 2001 to 2021 using MODIS satellite imagery at 500 m resolution. We observed a more evident change in autumn rather than in spring phenology, with different patterns along elevation gradients, mountain regions, and vegetation types. Moreover, we assessed the existence of a general uniformization of phenology across elevations, and we explored changes in the sensitivity of spring phenology to temperatur

A hierarchical dataset of vegetative and reproductive growth in apple tree organs under conventional and non-limited carbon resources

A monitoring of apple fruit, shoot and trunk growth was performed on 15 trees, equally split according to three treatments, which determined heavily contrasting carbon assimilate availability: unmanipulated trees (FRU), thinned trees (THI) and defruited trees (DEF). Several variables describe the vegetative growth on FRU and DEF trees (shoot length, base diameter, number of fruits on shoot, and height, diameter, pruning intensity and number of fruits of the branch carrying the shoot; trunk circumference), as well as the fruit growth on FRU and THI trees (3 fruit diameters). Additional measurements from ancillary shoots (apical diameter, number of leaves, leaf dry weight, stem dry weight, fresh mass, volume) and fruits (3 diameters, dry weight) from trees undergoing the same treatments, provide a more complete (destructive) characterization of organs growth, thanks to several measurements performed across the growing season. Organs are provided with categorical variables indicating the treatment, tree, canopy height, orientation (for both shoots and fruit), as well as branch and shoot identifiers, so that hierarchical modeling of the dataset can be performed. The dataset is completed with dates and day of the year of the measurements and the accumulated growing degree days from full bloom. Data can be used to calculate apple tree absolute and relative growth rates, maximum potential growth rates, as well as shoot growth responses to thinning and pruning. The dataset can also be used to calibrate allometric relationships, estimate structural apple tree growth parameters and their variabilit

Влияние облучения и отжига на термическую стабильность радиационных дефектов в кремнии

Описан отжиг А-центров, дивакансий, А-центров, модифицированных водородом, в n-Si (P ≈ 10^14 см^-3), в отсутствие и при наличии примеси платины, после облучения протонами с энергией 1,8 МэВ. Показано, что энергия активации отжига радиационных дефектов при взаимодействии с водородно-вакансионными дефектами уменьшается с 1,1 до 0,8 эВ при увеличении концентрации платины в кремнии, так как деформационные поля, создаваемые атомами платины, уменьшают энергию переориентации дефектов. Уточнено энергетическое положение в запрещенной зоне кремния донорного уровня А-центра (ЕV + 0,415 эВ) на основании известных данных о положении А-центра, модифицированного атомом углерода (ЕV + 0,38 эВ) или водорода (ЕV + 0,28 эВ).Описано відпал А-центрів, дивакансій, А-центрів, модифікованих воднем, у n-Si (P ≈ 10^14 см^-3), за відсутності та при наявності домішки платини, після опромінення протонами з енергією 1,8 МеВ. Показано, що енергія активації відпалу радіаційних дефектів при взаємодії з воднево-вакансійними дефектами зменшується від 1,1 до 0,8 еВ зі збільшенням концентрації платини в кремнії, оскільки деформаційні поля, які створюються атомами платини, зменшують енергію переорієнтації дефектів. Уточнено енергетичне положення у забороненій зоні кремнію донорного рівня А-центра (ЕV + 0,415 еВ), виходячи із відомих даних щодо положення А-центра, модифікованого атомом вуглецю (ЕV + 0,38 еВ) або водню (ЕV + 0,28 еВ).The annealing of A-centers, divacancies, A-centers modified by hydrogen was described for n-Si (P ≈ 10^14 cm^-3), with and without platinum dopants, after the irradiation by protons with energy 1.8 MeV. It was shown that the activation energy of annealing for radiation defects under their interaction with hydrogen-vacancy defects is decreased from 1.1 to 0.8 eV with the increasing of platinum concentration in silicon, because the deformation fields, creating by platinum atoms, decrease the energy of the defect re-orientation. In the forbidden zone of silicon the energy state for the donor level of A-center (ЕV + 0.415 eV) was specified based on the data about the position of A-center modified by the carbon atom (ЕV + 0.38 eV) or the hydrogen atom (ЕV + 0.28 eV)

Monitoring of GHGs flux dynamics at the "Viote" mountain peatland (Eastern Alps, Italy) under climate change pressure

This presentation focuses on the alpine peatland "le Viote" (46.01 N, 11.04 E, 1560 m asl), located at the centre of a plateau in the Mt. Bondone area, in the eastern Italian Alps (Figure), where the fluxes of methane (CH4) and carbon dioxide (CO2) between the peatland ecosystem and the atmosphere have been measured by chamber technique since summer 2024. The objectives of the current research activities are to analyse the spatial and temporal variability of both GHGs with special attention to CH4 fluxes, considering the response to climatic drivers, the influence of peatland vegetation community types, hydrology and natural and anthropogenic disturbances history. These activities build on 10+ years of CO2 fluxes monitoring by eddy covariance and a more limited dataset of CH4 fluxes, providing a temporal background for detecting flux magnitude changes