Modelling biogeochemical cycles in forest ecosystems: a Bayesian approach

Forest models are tools for explaining and predicting the dynamics of forest ecosystems. They simulate forest behavior by integrating information on the underlying processes in trees, soil and atmosphere. Bayesian calibration is the application of probability theory to parameter estimation. It is a method, applicable to all models, that quantifies output uncertainty and identifies key parameters and variables. This study aims at testing the Bayesian procedure for calibration to different types of forest models, to evaluate their performances and the uncertainties associated with them. In particular,we aimed at 1) applying a Bayesian framework to calibrate forest models and test their performances in different biomes and different environmental conditions, 2) identifying and solve structure-related issues in simple models, and 3) identifying the advantages of additional information made available when calibrating forest models with a Bayesian approach. We applied the Bayesian framework to calibrate the Prelued model on eight Italian eddy-covariance sites in Chapter 2. The ability of Prelued to reproduce the estimated Gross Primary Productivity (GPP) was tested over contrasting natural vegetation types that represented a wide range of climatic and environmental conditions. The issues related to Prelued's multiplicative structure were the main topic of Chapter 3: several different MCMC-based procedures were applied within a Bayesian framework to calibrate the model, and their performances were compared. A more complex model was applied in Chapter 4, focusing on the application of the physiology-based model HYDRALL to the forest ecosystem of Lavarone (IT) to evaluate the importance of additional information in the calibration procedure and their impact on model performances, model uncertainties, and parameter estimation. Overall, the Bayesian technique proved to be an excellent and versatile tool to successfully calibrate forest models of different structure and complexity, on different kind and number of variables and with a different number of parameters involved.

Online Stream Processing di Big Data su Apache Storm per Applicazioni di Instant Coupon

Big data è il termine usato per descrivere una raccolta di dati così estesa in termini di volume,velocità e varietà da richiedere tecnologie e metodi analitici specifici per l'estrazione di valori significativi. Molti sistemi sono sempre più costituiti e caratterizzati da enormi moli di dati da gestire,originati da sorgenti altamente eterogenee e con formati altamente differenziati,oltre a qualità dei dati estremamente eterogenei. Un altro requisito in questi sistemi potrebbe essere il fattore temporale: sempre più sistemi hanno bisogno di ricevere dati significativi dai Big Data il prima possibile,e sempre più spesso l’input da gestire è rappresentato da uno stream di informazioni continuo. In questo campo si inseriscono delle soluzioni specifiche per questi casi chiamati Online Stream Processing. L’obiettivo di questa tesi è di proporre un prototipo funzionante che elabori dati di Instant Coupon provenienti da diverse fonti con diversi formati e protocolli di informazioni e trasmissione e che memorizzi i dati elaborati in maniera efficiente per avere delle risposte in tempo reale. Le fonti di informazione possono essere di due tipologie: XMPP e Eddystone. Il sistema una volta ricevute le informazioni in ingresso, estrapola ed elabora codeste fino ad avere dati significativi che possono essere utilizzati da terze parti. Lo storage di questi dati è fatto su Apache Cassandra. Il problema più grosso che si è dovuto risolvere riguarda il fatto che Apache Storm non prevede il ribilanciamento delle risorse in maniera automatica, in questo caso specifico però la distribuzione dei clienti durante la giornata è molto varia e ricca di picchi. Il sistema interno di ribilanciamento sfrutta tecnologie innovative come le metriche e sulla base del throughput e della latenza esecutiva decide se aumentare/diminuire il numero di risorse o semplicemente non fare niente se le statistiche sono all’interno dei valori di soglia voluti.

Improved detection of blood stream pathogens by real-time PCR in severe sepsis

Evaluation of the technical and diagnostic feasibility of commercial multiplex real-time polymerase chain reaction (PCR) for detection of blood stream infections in a cohort of intensive care unit (ICU) patients with severe sepsis, performed in addition to conventional blood cultures.

The Small Project Observatory: Visualizing Software Ecosystems

Software evolution research has focused mostly on analyzing the evolution of single software systems. However, it is rarely the case that a project exists as standalone, independent of others. Rather, projects exist in parallel within larger contexts in companies, research groups or even the open-source communities. We call these contexts software ecosystems, and on this paper we present The Small Project Observatory, a prototype tool which aims to support the analysis of project ecosystems through interactive visualization and exploration. We present a case-study of exploring an ecosystem using our tool, we describe about the architecture of the tool, and we distill the lessons learned during the tool-building experience.

Abandoned Coal Mine Drainage and Its Remediation: Impacts on Stream Ecosystem Structure and Function

The effects of abandoned mine drainage (AMD) on streams and responses to remediation efforts were studied using three streams (AMD-impacted, remediated, reference) in both the anthracite and the bituminous coal mining regions of Pennsylvania (USA). Response variables included ecosystem function as well as water chemistry and macroinvertebrate community composition. The bituminous AMD stream was extremely acidic with high dissolved metals concentrations, a prolific mid-summer growth of the filamentous alga, Mougeotia, and .10-fold more chlorophyll than the reference stream. The anthracite AMD stream had a higher pH, substrata coated with iron hydroxide(s), and negligible chlorophyll. Macroinvertebrate communities in the AMD streams were different from the reference streams, the remediated streams, and each other. Relative to the reference stream, the AMD stream(s) had (1) greater gross primary productivity (GPP) in the bituminous region and undetectable GPP in the anthracite region, (2) greater ecosystem respiration in both regions, (3) greatly reduced ammonium uptake and nitrification in both regions, (4) lower nitrate uptake in the bituminous (but not the anthracite) region, (5) more rapid phosphorus removal from the water column in both regions, (6) activities of phosphorus-acquiring, nitrogenacquiring, and hydrolytic-carbon-acquiring enzymes that indicated extreme phosphorus limitation in both regions, and (7) slower oak and maple leaf decomposition in the bituminous region and slower oak decomposition in the anthracite region. Remediation brought chlorophyll concentrations and GPP nearer to values for respective reference streams, depressed ecosystem respiration, restored ammonium uptake, and partially restored nitrification in the bituminous (but not the anthracite) region, reduced nitrate uptake to an undetectable level, restored phosphorus uptake to near normal rates, and brought enzyme activities more in line with the reference stream in the bituminous (but not the anthracite) region. Denitrification was not detected in any stream. Water chemistry and macroinvertebrate community structure analyses capture the impact of AMD at the local reach scale, but functional measures revealed that AMD has ramifications that can cascade to downstream reaches and perhaps to receiving estuaries.

Use and Performance of In-Stream Structures for River Restoration: a Case Study from North Carolina

In-stream structures including cross-vanes, J-hooks, rock vanes, and W-weirs are widely used in river restoration to limit bank erosion, prevent changes in channel gradient, and improve aquatic habitat. During this investigation, a rapid assessment protocol was combined with post-project monitoring data to assess factors influencing the performance of more than 558 in-stream structures and rootwads in North Carolina. Cross-sectional survey data examined for 221 cross sections from 26 sites showed that channel adjustments were highly variable from site to site, but approximately 60 % of the sites underwent at least a 20 % net change in channel capacity. Evaluation of in-stream structures ranging from 1 to 8 years in age showed that about half of the structures were impaired at 10 of the 26 sites. Major structural damage was often associated with floods of low to moderate frequency and magnitude. Failure mechanisms varied between sites and structure types, but included: (1) erosion of the channel bed and banks (outflanking); (2) movement of rock materials during floods; and (3) burial of the structures in the channel bed. Sites with reconstructed channels that exhibited large changes in channel capacity possessed the highest rates of structural impairment, suggesting that channel adjustments between structures led to their degradation of function. The data question whether currently used in-stream structures are capable of stabilizing reconfigured channels for even short periods when applied to dynamic rivers.

Constraining global methane emissions and uptake by ecosystems

Natural methane (CH4) emissions from wet ecosystems are an important part of today's global CH4 budget. Climate affects the exchange of CH4 between ecosystems and the atmosphere by influencing CH4 production, oxidation, and transport in the soil. The net CH4 exchange depends on ecosystem hydrology, soil and vegetation characteristics. Here, the LPJ-WHyMe global dynamical vegetation model is used to simulate global net CH4 emissions for different ecosystems: northern peatlands (45°–90° N), naturally inundated wetlands (60° S–45° N), rice agriculture and wet mineral soils. Mineral soils are a potential CH4 sink, but can also be a source with the direction of the net exchange depending on soil moisture content. The geographical and seasonal distributions are evaluated against multi-dimensional atmospheric inversions for 2003–2005, using two independent four-dimensional variational assimilation systems. The atmospheric inversions are constrained by the atmospheric CH4 observations of the SCIAMACHY satellite instrument and global surface networks. Compared to LPJ-WHyMe the inversions result in a~significant reduction in the emissions from northern peatlands and suggest that LPJ-WHyMe maximum annual emissions peak about one month late. The inversions do not put strong constraints on the division of sources between inundated wetlands and wet mineral soils in the tropics. Based on the inversion results we diagnose model parameters in LPJ-WHyMe and simulate the surface exchange of CH4 over the period 1990–2008. Over the whole period we infer an increase of global ecosystem CH4 emissions of +1.11 Tg CH4 yr−1, not considering potential additional changes in wetland extent. The increase in simulated CH4 emissions is attributed to enhanced soil respiration resulting from the observed rise in land temperature and in atmospheric carbon dioxide that were used as input. The long-term decline of the atmospheric CH4 growth rate from 1990 to 2006 cannot be fully explained with the simulated ecosystem emissions. However, these emissions show an increasing trend of +3.62 Tg CH4 yr−1 over 2005–2008 which can partly explain the renewed increase in atmospheric CH4 concentration during recent years.