427 research outputs found
Biome Q10 and Dryness
Temperature sensitivity of soil respiration (Q10) is a critical parameter in carbon cycle models with important implications for climate-carbon feedbacks in the 21st century. The common assumption of a constant Q10, usually with a value of 2.0, was shown to be invalid by a previous model-data fusion study that reported biome-specific values of this parameter. We extend the previous analysis by demonstrating that these biome-level values of Q10 also are a function of dryness (R2 = 0.54). When tundra and cultivated lands are excluded, the correlation is much stronger (R2 = 0.92). Therefore dryness is the primary driver for variability in respiration-temperature sensitivity in forest and grassland ecosystems. This finding has important implications for the response of the terrestrial carbon cycle to climate change, as it implies that the increasing dryness would potentially accelerate the respiration temperature sensitivity feedback
La tutela dell'investitore finanziario. Prime riflessioni su contratto, vigilanza e regolazione del mercato nella c.d. MI-FID2
Primary sclerosing cholangitis and overlap features of autoimmune hepatitis:A coming of age or an age-ist problem?
Efficient surrogate modeling methods for large-scale Earth system models based on machine-learning techniques
Improving predictive understanding of Earth system variability and change
requires data–model integration. Efficient data–model integration for
complex models requires surrogate modeling to reduce model evaluation time.
However, building a surrogate of a large-scale Earth system model (ESM) with
many output variables is computationally intensive because it involves a
large number of expensive ESM simulations. In this effort, we propose an
efficient surrogate method capable of using a few ESM runs to build an
accurate and fast-to-evaluate surrogate system of model outputs over large
spatial and temporal domains. We first use singular value decomposition to
reduce the output dimensions and then use Bayesian optimization techniques to
generate an accurate neural network surrogate model based on limited ESM
simulation samples. Our machine-learning-based surrogate methods can build
and evaluate a large surrogate system of many variables quickly. Thus,
whenever the quantities of interest change, such as a different objective
function, a new site, and a longer simulation time, we can simply extract the
information of interest from the surrogate system without rebuilding new
surrogates, which significantly reduces computational efforts. We apply the
proposed method to a regional ecosystem model to approximate the relationship
between eight model parameters and 42 660 carbon flux outputs. Results
indicate that using only 20 model simulations, we can build an accurate
surrogate system of the 42 660 variables, wherein the consistency between
the surrogate prediction and actual model simulation is 0.93 and the mean
squared error is 0.02. This highly accurate and fast-to-evaluate surrogate
system will greatly enhance the computational efficiency of data–model
integration to improve predictions and advance our understanding of the Earth
system.</p
Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM-Microbe Model
Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM-Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low-centered polygon (LCP) center, LCP transition, LCP rim, high-centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM-Microbe model against static-chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low-elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high-elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2 + H2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area-weighted approach before validation against EC-measured CH4 fluxes. The model underestimated the EC-measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model-data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape
Seeing the canopy for the branches: Improved within canopy scaling of leaf nitrogen
Abstract Transitioning across biological scales is a central challenge in land surface models. Processes that operate at the scale of individual leaves must be scaled to canopies, and this is done using dedicated submodels. Here, we focus on a submodel that prescribes how light and nitrogen are distributed through plant canopies. We found a mathematical inconsistency in a submodel implemented in the Community and Energy Land Models (CLM and ELM), which incorporates twigs, branches, stems, and dead leaves in nitrogen scaling from leaf to canopy. The inconsistency leads to unrealistic (physically impossible) values of the nitrogen scaling coefficient. The mathematical inconsistency is a general mistake, that is, would occur in any model adopting this particular submodel. We resolve the inconsistency by allowing distinct profiles of stems and branches versus living leaves. We implemented the updated scheme in the ELM and find that the correction reduces global mean gross primary production (GPP) by 3.9 Pg C (3%). Further, when stems and branches are removed from the canopy in the updated model (akin to models that ignore shading from stems), global GPP increases by 4.1 Pg C (3.2%), because of reduced shading. Hence, models that entirely ignore stem shading also introduce errors in the global spatial distribution of GPP estimates, with a strong signal in the tropics, increasing GPP there by over 200 g C m−2 yr−1. Appropriately incorporating stems and other nonphotosynthesizing material into the light and nitrogen scaling routines of global land models, will improve their biological realism and accuracy
Emergency Department as an epidemiological observatory of Human Mobility: the experience of the Moroccan population
We conducted a retrospective study of the accesses to the Emergency Department registered from January 2000 to December 2014 in 5 major hospitals in the Metropolitan Area of Rome. We extrapolated data relating to patients of Moroccan origin from about 5 million total accesses, so we compared with Italians data which, in the same period, came to ED.
The Moroccan population is distinguished by a larger number of diagnoses belonging to the ICD-9 code of Infectious Diseases and, more precisely, to Respiratory Infectious Diseases. There are also no differences in the assignment of such diagnoses to Moroccans with Italian citizenship, and this led to think that this could play an important role in the use of the ED and moreover that enrollment to the National Health Service may reduce its inappropriate use.
Regarding to Degenerative Disorders, the result of our analysis is quite emblematic, showing that the accesses to the ED is due to Cardiovascular Diseases: 6.33% of Italians' accesses against 1.81% of Moroccans and 2.36% of Moroccans with Italian citizenship. The main explanation for this difference is, obviously, due to the age of the population: about 60% of Moroccans who accessed to ED was less than 40 years old.
It is interesting how, in the field of ​​Cardiovascular Diseases, Moroccans have a lower percentage of diagnosis compared to Italians for acute diseases and a greater percentage of diagnoses for chronic diseases, suggesting once again that accesses to ED for migrants often is due to the inability to use the general services of the National Health Service.
In conclusion, from the point of view of the Emergency Department, Migration Medicine still has Infectious Diseases as the main reason for access. Degenerative Disorders remain a prerogative of the Italians, but we could certainly assume that the Moroccan population would develop at some point with the aging
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